University of Ghana http://ugspace.ug.edu.gh UNIVERSITY OF GHANA CHOICE AS A CONSTRAINT TO DECISION EFFICIENCY: THE SOCIAL MEDIA PERSPECTIVE JUDITH AKU MASOPE-CRABBE (10599569) THIS THESIS IS SUBMITTED TO THE UNIVERSITY OF GHANA, LEGON IN PARTIAL FULFILMENT OF THE REQUIREMENT FOR THE AWARD OF MPHIL MARKETING DEGREE. JULY 2018 University of Ghana http://ugspace.ug.edu.gh DECLARATION I do hereby declare that this long essay is the result of my own research and has not been replicated by anyone for any academic award in any institution. All references used in the work have been fully acknowledged. I hereby bear sole responsibility for any shortcomings. ………………………….. ….……….……… JUDITH AKU MASOPE- CRABBE DATE (10599569) i University of Ghana http://ugspace.ug.edu.gh CERTIFICATION I hereby certify that this thesis was supervised in accordance with procedures laid down by University of Ghana, Legon. .………………………………… …………………………….. DR. KOBBY MENSAH DATE (PRINCIPAL SUPERVISOR) ………………………………….. ……………………………….. DR. PRINCE KODUA DATE (CO-SUPERVISOR) ii University of Ghana http://ugspace.ug.edu.gh DEDICATION I dedicate this thesis to the Almighty God for His mercies and my beloved husband who made several sacrifices to enable me complete this work successfully. iii University of Ghana http://ugspace.ug.edu.gh ACKNOWLEDGEMENT In preparing this research work, many people were of immense assistance. I wish to acknowledge my indebtedness to the Almighty God who strengthened me throughout the period. I would like to thank my supervisor, Dr. Kobby Mensah, for his guidance, patience and advice even during times I experienced difficulties. I also would like to thank my co-supervisor Dr. Prince Kodua who dedicated his time and effort by way of suggestions and support throughout the project. Their suggestions and remarks have been very useful. Not forgetting innovative suggestions from faculty members and classmates, especially Priscilla, and Gertrude, who out of their busy schedule were still able to assist me. Finally, I wish to acknowledge my family, especially, my mother-in-law. To all of you – a heartfelt thank you. iv University of Ghana http://ugspace.ug.edu.gh ABSTRACT Social media tools such as Facebook, Twitter, Instagram and YouTube have become important sources of information. However, the dynamics between the volume of information on social media and the quality of choices consumers make remain unclear in literature. While some social media users complain of choice overload affecting the quality of choices and post purchase dissonance, others believe that information on social media is of quality and sufficient for effective decision making. Therefore, this study formulated four objectives to investigate and understand this phenomenon. The first objective sought to explore how consumers use social media tools in decision making. Objective two seek to explain whether there is information overload on social media. Objective three sought to assess whether social media information support consumers in decision making. The last objective investigated the impact of choice overload on quality of choice leading to post purchase dissonance. The study employed interpretivist research paradigm and exploratory design to understand how and why consumers employ social media tools and information in decision making. Six (6) respondents were sampled for qualitative interview and two hundred and forty-nine respondents for quantitative analysis using structural equation modelling. After analysis of field data, the result showed that social media tools are used to create content to help consumer decision. The study also found that there is no information overload on social media and the content is based on what the user wants. Based on the third objective the result showed that social media information is very supportive in decision making even though some users post information that are irrelevant. The last objective found that information (choice) overload influence quality of choice, thus affecting post purchase dissonance. The study therefore concludes that social media tools such as Twitter and Facebook are used to create quality information to support consumer decision making. The study recommends that social media users explore social media tools as alternative source for quality information and also provide quality and relevant information on social media platforms to help other users. Again, marketing managers must ensure that they create quality content about their brand and also protect their brand content on social media. Sales and marketing managers must improve their client interactivity and engagement on Twitter and Facebook in order to help consumers make quality choice. v University of Ghana http://ugspace.ug.edu.gh TABLE OF CONTENT Item Page DECLARATION ............................................................................................................................. i CERTIFICATION .......................................................................................................................... ii DEDICATION ............................................................................................................................... iii ACKNOWLEDGEMENT ............................................................................................................. iv ABSTRACT .................................................................................................................................... v TABLE OF CONTENT ................................................................................................................. vi LIST OF TABLES .......................................................................................................................... x LIST OF FIGURES ....................................................................................................................... xi LIST OF ABREVIATIONS ......................................................................................................... xii 1.1 Problem Statement ................................................................................................................ 5 1.2 Research Purpose .................................................................................................................. 7 1.3 Research Objectives .............................................................................................................. 7 1.4 Research Questions ............................................................................................................... 8 1.5 Significance of the Study ...................................................................................................... 8 1.6 Scope of the Study ................................................................................................................. 9 1.7 Chapter Disposition ............................................................................................................... 9 CHAPTER TWO .......................................................................................................................... 10 CONTEXT OF STUDY ............................................................................................................... 10 2.0 Introduction ......................................................................................................................... 10 2.1 Overview of the Internet ..................................................................................................... 10 2.2 Internet in Ghana ................................................................................................................. 11 2.3 Social Media Usage in Ghana ............................................................................................. 14 CHAPTER THREE ...................................................................................................................... 17 LITERATURE REVIEW ............................................................................................................. 17 3.0 Introduction .................................................................................................................... 17 3.1 Concept of Social Media ................................................................................................ 17 3.2 Benefits and Challenges of Social Media ...................................................................... 19 3.3 Social Media Platforms .................................................................................................. 20 vi University of Ghana http://ugspace.ug.edu.gh 3.3.1 Facebook ................................................................................................................. 21 3.3.2 Twitter ..................................................................................................................... 22 3.3.3 Instagram................................................................................................................. 23 3.3.4 YouTube ................................................................................................................. 24 3.4 Consumer Behaviour and Consumer Decision-Making................................................. 25 3.4.1 Problem Recognition .............................................................................................. 26 3.4.2 Information Search.................................................................................................. 27 3.4.3 Evaluation of Alternatives ...................................................................................... 28 3.4.4 Purchase Decision ................................................................................................... 28 3.4.5 Post-Purchase Behaviour ........................................................................................ 29 3.5 Concept of Choice Overload .......................................................................................... 29 3.6 Information Quality in Social Media Platform .............................................................. 30 3.7 Conceptual Framework .................................................................................................. 36 CHAPTER FOUR ......................................................................................................................... 38 METHODOLOGY ....................................................................................................................... 38 4.0 Introduction .................................................................................................................... 38 4.1 Research Paradigm ......................................................................................................... 38 4.2 Research Approach ........................................................................................................ 41 4.3 Research Design ............................................................................................................. 43 4.4 Research Strategy ........................................................................................................... 46 4.4.1 Ethnography ............................................................................................................ 47 4.4.2 Archival Research ................................................................................................... 47 4.4.3 Grounded Theory .................................................................................................... 48 4.4.4 Case Study .............................................................................................................. 48 4.5 Justification for Research Strategy ................................................................................. 49 4.6 Choice of Research Method ........................................................................................... 50 4.7 Quantitative vs. Qualitative ............................................................................................ 50 4.8 Types of Data ................................................................................................................. 53 4.9 Population and Sampling ............................................................................................... 54 4.10 Sampling Techniques ........................................................................................................ 55 4.10.1 Probability Sampling .................................................................................................. 55 vii University of Ghana http://ugspace.ug.edu.gh 4.10.2 Non-Probability Sampling .......................................................................................... 56 4.11 Sampling Size .................................................................................................................... 57 4.12 Data Collection Instrument ............................................................................................... 57 4.12.1 Justification of Qualitative Instrument (Interview) .................................................... 58 4.13 Data Analysis .................................................................................................................... 61 4.13.1 Qualitative Data .......................................................................................................... 61 4.13.2 Quantitative Data ........................................................................................................ 62 4.14 Pre-Testing Quantitative Instrument ................................................................................. 63 4.15 Validity and Argument Reliability of Qualitative Study................................................... 63 4.16 Ethical Considerations ....................................................................................................... 64 CHAPTER FIVE .......................................................................................................................... 65 DATA ANALYSES AND DISCUSSION OF RESULT ............................................................. 65 5.0 Introduction .................................................................................................................... 65 5.1 Analysis of Objectives ................................................................................................... 65 5.1.1 Analysis of Qualitative Data....................................................................................... 66 Objective 1: How consumers use social media tools in decision making ............................ 67 Objective 2: To examine whether there is information overload on social media ................ 68 Objective 3: To investigate whether social media information support consumer decision making ................................................................................................................................... 70 5.2 Discussion of Findings ................................................................................................... 71 How consumers use social media tools in decision making.................................................. 71 Investigate whether social media information support consumer decision making .............. 74 5.3 Analysis of Quantitative Data ........................................................................................ 74 5.3.1 Data Screening ........................................................................................................ 75 5.3.2 Profile of Respondents ............................................................................................ 75 5.4 Confirmatory Factor Analysis (CFA) ......................................................................... 78 5.5 Analysis of Study Objectives Using Structural Equation Model ............................... 82 Analysis of Hypothesis One (H1): Choice Overload and Quality Choice ............................ 84 Analysis of Hypothesis Two (H2): Choice Quality and Post Purchase Dissonance ............. 85 CHAPTER SIX ............................................................................................................................. 87 SUMMARY, CONCLUSIONS AND RECOMMENDATIONS................................................. 87 viii University of Ghana http://ugspace.ug.edu.gh 6.0 Summary ........................................................................................................................ 87 6.1 Conclusions .................................................................................................................... 89 6.2 Recommendations .......................................................................................................... 89 6.3 Future Research Direction .............................................................................................. 90 REFERENCES ............................................................................................................................. 92 APPENDIX A ............................................................................................................................. 117 APPENDIX B ............................................................................................................................. 119 ix University of Ghana http://ugspace.ug.edu.gh LIST OF TABLES Table 2.1: Internet Usage in Ghana and Population Growth ........................................................ 14 Table 2.2: Ratings of Social Media Use in Ghana ........................................................................ 16 Table 3.1: Analysis of IQ in Different SM Applications .............................................................. 35 Table 5.1: Profile of Respondents ................................................................................................. 66 Table 5.2: Descriptive Statistics of Respondents .......................................................................... 76 Table 5.3: KMO and Bartlett’s Test Results ................................................................................. 79 Table 5.4: Validity and Reliability Test ........................................................................................ 79 Table 5.5: Discriminant Validity .................................................................................................. 80 Table 5.6: Table Model Fit Measures ........................................................................................... 82 Table 5.7: Cut-off Criteria ............................................................................................................ 82 Table 5.8: Summary of Structural Equation Modeling Result ..................................................... 84 x University of Ghana http://ugspace.ug.edu.gh LIST OF FIGURES Figure 3.1: The Consumer Purchasing Process ............................................................................ 26 Figure 5.1: Final Measurement Model .......................................................................................... 81 Figure 5.2: Structural Equation Model for Choice overload, Quality of Choice and Post-Purchase Dissonance ............................................................................................................ 82 xi University of Ghana http://ugspace.ug.edu.gh LIST OF ABREVIATIONS ARPANET - Advanced Research Projects Agency Network AVE - Average Variance Extracted CFA - Confirmatory Factor Analysis CO - Choice Overload CR - Construct Reliability IQ - Information Quality LAN - Local Area Network PDD - Post Purchase Dissonance Qoc - Quality of Choice SEM - Structural Equation Modelling SM s - Social Media SPSS - Statistical Package for Social Science UGC - User Generated Content URL - Uniform Resource Locator WAN - Wide Area Network WTO - World Trade Organisation WWW - World Wide Web xii University of Ghana http://ugspace.ug.edu.gh CHAPTER ONE INTRODUCTION 1.0 Background of the Study The last decade has witnessed a revolution in technology and internet accessibility that has transformed the traditional communication channels of many organisations (Karanatsiou, Misirlis & Vlachopoulou, 2017; Lingelbach, Patino & Pitta, 2012). The revolution in technology has created multiple high speed online communication and information sources for consumers to use in their purchase decisions. Today, many organisations have to rely on IT to gather, share and exchange product information with current and potential consumers in various forms such as online reviews and content. The strategic role of technology communication means that the traditional forms of communication such as print and radio are no longer effective to reach target audiences with the content and quality of information (Duffet, 2015). The inefficiencies in the traditional communication media means that contemporary businesses require information communication (IT) tools with wide accessibility, quality of content, global reach, modernity, permanence, and user friendly features (Agarwal & Yiliyasi, 2010; Baeza-Yates, 2009). Recent trends have exposed that, commercial and non-commercial organisations have responded to the new digital revolution by investing in digital communication media such as social media (SM) (Waters, Canfield, Foster & Hardy, 2011). Social media has been regarded as one of the topmost online applications used by many organisations to create content (information), attract customers, engage them and meet their information needs in a more convenient and efficient manner (Sinclaire & Vogus, 2011). 1 University of Ghana http://ugspace.ug.edu.gh According to Liang and Lai (2002), the success of the SM platforms depends on various factors such as the quality and depth of its content that provides support for user choices and purchase decisions. Generally, rational consumers go through a series of steps that include “identifying the problem, searching for information, evaluating alternatives, purchase, and post purchase behaviour” (Darley, Blankson & Luethge, 2010). There are instances where consumers may not go through the entire stages but the quality of social media (SM) content remain a critical factor in the consumer decision making process (Brady, Goodman Hansen, Keller & Kotler 2009). Quite profoundly, social media plays an important role in the ability of a firm to create content and communicate it to the consumer. For instance, retail stores continuously advertise new goods and services, provide discounts, engage with customers and seek feedback via social media (Oh, Roumani, Nwankpa & Hu, 2017). There are several and multiple social media applications and tools that organisations use to provide content about their brand (Hsu & Lawrence, 2016). Both the consumer and the supplier are always beholding SM applications such as Facebook, Twitter and Instagram to disseminate, create and share information because they provide instant information (Xu, 2017). Consumers have seen social media as a central component of their daily lives because they “feed” on the content to make product choices and a final decision (Xu, 2017). Organisations are also loading brand content to social media platforms such as Instagram, LinkedIn, Facebook and Twitter (Alalwan, Rana, Dwivedi & Algharabat, 2017). According to Yee Cheung, Ling and Kuan (2012), these social media platforms have dramatically altered the social and commercial interaction by creating a database platform for communication and information exchange. 2 University of Ghana http://ugspace.ug.edu.gh According to Alalwan et al. (2017), consumers and social media users of social media create content. This content (information) is mostly promotional campaign messages that are used by the audience and organisations to influence decisions (Alalwan et al., 2017; Duffett, 2015). For instance, Barger et al. (2016) conceptualized that consumers take some actions on SM in response to brand-related content that organisations put on the SM platform. These actions include: responding to content (e.g. likes, hearts, _1s, 1 to 5 star ratings), commenting on content posted (e.g. Facebook comments, Twitter retweets), sharing content with other users (e.g. sharing of content on Facebook shares, and retweeting on Twitter) as well as posting User-Generated Content (UGC) (e.g. product reviews, Facebook posts about brands). According to Barger, these actions and responses create content that might be destructive or informative, hence affecting quality of choice and post purchase perception. When consumers are exposed to so much of information on Social Media, also termed as “information overload”, it is expected that the quality of choice will be affected (Gensler et al., 2013). According to Sinclaire and Vogus (2011) consumers rely on the quality of content posted on SM to make choices about the brands. Further evidence has shown that; quality of information, the relevance of the information, consumer’s environment, options that a consumer are willing to trade off, and effort they may be required to exert in order to come up with these final decisions that influence the quality of choice and post purchase perception (Lye et al., 2005). Filo, Lock and Karg (2015) further note that social media technologies such as Twitter and Facebook help organisations to relate and engage well and conveniently with their clients through brand stories, which becomes information that influences consumer purchase decisions (Kuksov, 3 University of Ghana http://ugspace.ug.edu.gh Schachar & Wang, 2013; Singh & Sonneburg, 2012). For instance, social media applications such as Facebook and Instagram allow organisations to create, share and exchange relevant product information (content) widely, which positively influence a user’s perception and actual purchase of the brand (Gensler et al., 2013). Gensler et al. (2013) further noted that this information and brand stories may not be necessary in the purchase decision of the consumer, thus creating overload of information. Bianchi and Andrews (2015) and De Vries, Gensler and Leeflang (2014) further noted that organisations use social media to share information about their brand, which helps build awareness of the brand, and creates a strong sense of recognition, recall, and meaning in the minds of customers (Singh & Sonnenburg, 2012). The depth and quality of information on SM affects the choice of the consumer, and this is partly blamed on the nature of content posted on the platform (Chen & Hsieh, 2012; Hsu & Lawrence, 2016; Singh & Sonnenburg, 2012; Qualman, 2013). In this study, the researcher sought to investigate how Ghanaian consumers employ social media in their purchase decisions. The study also sought to examine whether there is information overload on social media. The study also investigates how social media content influence consumer purchase decision. Lastly, this current study sought to examine the influence of social media information overload on choice quality leading to post purchase dissonance. 4 University of Ghana http://ugspace.ug.edu.gh 1.1 Problem Statement Organisations create and share product information with current and potential consumers in extremely large audience who are mostly consumers of the product (Nasiruddin and Hashim, 2015; Lu, Ba, Huang & Feng, 2013). Likewise, consumers rely on this information to make brand choices and final purchase decisions (Ludwig, de Ruyter, Friedman, Brüggen, Wetzels & Pfann, 2013; Lepkowska-White, 2013; Kurz-Milcke & Gigerenzer, 2007). However, literature reports inconclusive result whether volume of information influence consumer choices and decision making on social media (Beniot & Miller, 2017). For instance, studies show that information quality, large volume of content, convincing power and usefulness of social media information influences consumer final decision (Hong, Huang, Burtch & Li, 2016; Jiménez & Mendoza 2013; Felbermayr & Nanopoulos, 2016). Further studies such as Grabner-Kräuter and Kaluscha (2003); Nasiruddin and Hashim (2015); Lu, Ba, Huang and Feng (2013) posited that, the absence of direct contact in social media environment creates doubts/uncertainty and consumers require large volume of information to make purchase decision. However, literature report contrary evidence that social media provide too much information which causes consumers to decide wrongly and have the quality choice marred (Barger et al., 2016; McCarthy, Rowley, Jane & Pioch, 2014; Zhang & Vos, 2014). Significant trends in these studies show that too much information impact quality of choice and decision making. Many researchers have even questioned the quality of the large volumes of content generated by social media users (Baeza-Yates, 2009; Yee Cheung, Ling & Kuan, 2012). Consumers find very difficult to translate data received into actionable visions and plans (Rowley, Jane & Pioch, 2014; Kleinrichert, Ergul, Johnson & Uydaci, 2012; Tsimonis & Dimitriadis, 2014). 5 University of Ghana http://ugspace.ug.edu.gh Similarly, about 91 per cent of corporate bodies do not possess sufficient skills to swiftly turn these large chunks of data they receive to help consumers make informed decisions at the strategic levels of various work places (https://www.entrepreneur.com/article/309104). There is lack of clarity whether there is information overload on social media and whether information overloads lead consumers to make wrong online purchase decision (Guesalaga, 2015; Hsu & Lawrence, 2016; Kaltcheva & Milne, 2013). Lack of clarity on the extent of influence of choice overload requires further investigation (Jacoby, 1984; Beniot & Miller, 2017). Importantly, Guesalaga, (2015) and Paquette (2013) advocated for further studies to examine whether there is information overload on social media and whether information overload positive or negatively affect consumer decision making (Guesalaga, 2015; Paquette, 2013; Barger et al., 2016). Studies conducted in the area of information overload and quality of consumer decision making use quantitative experimental design and found information overload as antecedent of consumer choice and decision making (Chang, Yu & Lu, 2015; Christou, 2015; Enginkaya & Yilmaz, 2014; Hudson, Huang, Roth & Madden, 2015; Salvolainen, 2007; Meyer, 2017). However, few studies that used qualitative approach to investigate the effect of social media however found contrary evidence to the effect that content on social media does not strongly influence the choices consumers make and the quality of their choices (Abreza, O’Reilly & Reid, 2013; Moore, et al., 2013; Sanderson et al, 2012). The inconsistency in the findings may be blamed on the methodological inconsistency, hence limits the generalisation of key finding in wider context. While Powers et al. (2012) called for mixed methodological approach, Hudson et al. (2015), 6 University of Ghana http://ugspace.ug.edu.gh recommended that studies must use proper methodology to improve the level of generalisations of research findings. This study seeks to bring clarity to the inconsistent findings – whether or not consumers actually use social media tools in their decision and whether they actually use social media information in purchase decisions (Beldad, Jong & Steehouder, 2010). This study also responds to the call for further investigation into whether consumers actually use social media tools in decision making and also the features of social media information that may influence consumer decision (Cyr, 2013). 1.2 Research Purpose This study investigates how social media users make use of social media platforms such as Facebook, Twitter and Instagram in their purchase decisions. Again, this current study examines whether online users consider there is information overload on social media. The study also examines how consumers use social media information in their purchase decision. Lastly, the study examines how social media information impact on consumers purchase decision. 1.3 Research Objectives Therefore, the following research objectives were investigated: 1. To investigate how consumers, use social media tools in decision making 2. To examine whether there is information overload on social media. 3. To investigate whether social media information support consumer decision making. 4. To assess the effect of social media content on consumers purchase choice leading to post purchase dissonance. 7 University of Ghana http://ugspace.ug.edu.gh 1.4 Research Questions The following research questions were asked: 1) Do consumers use social media tools in decision making? 2) Is there information overload on social media? 3) To what extent is consumer decision influenced by social media? 4) What is the effect of social media content on consumer choice leading to post purchase dissonance? 1.5 Significance of the Study Given that this is an era where consumers have so much information available to them from marketers, this study sought to address the issue of consumers being bound to make inefficient choices as to what they actually need. Hence, this research will assist consumers on how to effectively make good decisions in the midst of so much information. This research intends to ultimately help consumers make better decisions, since they will be able to filter information in a way that will best suit their needs and preferences at every given time. Furthermore, as marketers gradually become aware of the above facts, and taking cognisance of intense competition currently on-going among various industries, this study will assist them to effectively manage marketing communication activities on social media platforms. Lastly, this inquiry will add to available literature and the knowledge base in the field of consumer behaviour for the benefits of both students and future researchers. 8 University of Ghana http://ugspace.ug.edu.gh 1.6 Scope of the Study The focus of this current study is on online (social media) users in Accra Metropolis. The research project consists of the social media consumers who have used information on social media as a basis to make purchase decision. Only respondents in Accra Metropolis were considered for the study. 1.7 Chapter Disposition The study is structured into six chapters. Chapter one of this research work discussed the introduction and research problem under investigation. Chapter Two looked at the context of the study, where issues relating to the internet and social media were addressed. Chapter Three discussed relevant literature on the topic. Chapter Four highlights the research methods used for the study. Chapter Five presents and discusses the results from the analysis of the data. In chapter six, the work presented the key and major findings, summary and conclusions, and furthermore presents the recommendations for practical and policy inferences as well as some suggestions for further research work. 9 University of Ghana http://ugspace.ug.edu.gh CHAPTER TWO CONTEXT OF STUDY 2.0 Introduction This second chapter provides insights into the contextual background information of the study, providing an overview of the internet, social media in Ghana, and social media use in decision making. 2.1 Overview of the Internet The internet is not only a tool for communication or undertaking commercial activities but is also a tool for creating social relationships where individuals have interactions in a virtual world, with social media sites acknowledged to be one of the social tools that is mostly used (Amichai- Hamburger, Wainapel & Fox, 2002). Leiner, Cerf, Clark, Kahn, Kleinrock, Lynch, Postel, Roberts and Wolff (2000) assert that the internet, which is a channel of spreading information and facilitating interaction between persons and their computers irrespective of geographical boundaries, is seen as arguably the most important technological development discovered in the late 20th century. According to Dawson (1995), the internet as an innovation originated from a United States Department Defence Project’s narrow base. There was a concern that the United States’ communication system could be destroyed due to the impact of missiles on the main communication centres during the cold war era. The need to create a distribution system that can overcome such attacks led to the development of the original ‘internet’. The internet, which was originally called ARPANET (Advanced Research Projects Agency Network) in the late 1960s, was purposely created to be used only by the military, but it evolved 10 University of Ghana http://ugspace.ug.edu.gh to meet sophisticated standards as a result of interest exhibited by a lot of institutions in networking their computer systems. The internet is now commonly used by civilians to communicate worldwide and has presented many opportunities for academia as well. Experts use the internet to support networking services among themselves across various geographical boundaries. The internet consists of Local Area Network (LAN) and Wide Area Networks (WAN), which are linked to provide very quick and efficient communication (Krol, 1992). According to Sheldon (1996), the internet presents a system of communication that ensures the occurrence of various communications simultaneously with the use of the same network. Sheldon’s (1996) research revealed an increase of the number of pages from 320 to 380 million. It also indicated that a lot of new databases have been created (Kassel, 1999). As a result, the greatest challenging issue facing individuals who use the internet is how to browse through the various pages in order to identify important information from the databases in existence. Most internet services have been structured in a way that will help to easily locate a file, transfer and retrieve information. The services for retrieving information are search engines, information gateways, directories and metasearch engines (Hinson & Amidu, 2006). 2.2 Internet in Ghana According to Falch (2004), in Ghana, tele-centres provided inexpensive accessibility to internet connection. The study found that the tele-centres in the capital city, Accra, were more advanced than those found outside Accra. The tele-centres were about 150, out of this number, 90% of the tele-centres that had internet connectivity were located within Accra. Entrepreneurs who engaged in small business created these tele-centres. The tele-centres were characterised by intense 11 University of Ghana http://ugspace.ug.edu.gh competition and were not highly profitable and, as a result, those who managed these tele-centres sometimes could not afford to pay for the services of Capital Telecom. The presence of tele-centres in the business centre of Accra was less than the surrounding areas because people largely used fixed and mobile lines. The low income level in Ghana prevented large scale patronage of the services of tele-centres and telecommunications services. In 1997, some African countries became signatories to the World Trade Organisation (WTO) Telecommunications Agreement. These countries, which were seven in number, included Ghana, Morocco, Senegal, Cote d’Ivoire, Mauritius, South Africa and Tunisia. The WTO Telecommunications Agreement aimed at the liberation of markets for foreign investment (Fuchs & Horak, 2008). Ghana is one of the countries in Africa that is highly liberalised in the telecommunications industry. This liberalisation started with 30% privatisation of Ghana Telecom in 1996. In 1997, Westel and Capital Telecoms became operational in Ghana. Four additional mobile service providers were licensed between 1992 and 2000 (Sciadas, 2005, p. 67). Ghana was the first developing country to fully embrace privatisation and service competition nationwide (World Bank, 1999, p. 68). Liberalisation in the telecommunications sector in Ghana did not significantly lead to a rise in the usage of phones and internet connectivity although there was an increase in the number of fixed lines from 0.4 per 100 inhabitants in 1995 to 1.35 in 2003 (Sciadas, 2005, p. 68). This, therefore, indicates that there is no automatic link between opening markets and attracting foreign investment to a rise in internet usage (Fuchs & Horak, 2008). 12 University of Ghana http://ugspace.ug.edu.gh In addition, Fuchs and Horak (2008) argued that poverty reduction will not automatically bridge the gap unless technological infrastructure, applications and digital literacy are provided. Wilson (2006) asserted that “progressive and visionary leaders” aided internet expansion by being against “conservative” strategies and persistently called for the liberalisation and deregulation of the telecommunications market in Ghana. Wilson argued that Ghana’s economic and social problems are not as a result of lack of equal distribution of global wealth and colonialism by the West, but are due to self-centred and corrupt governments. The visionaries’ goal was to ensure that Ghana’s telecommunications market could attract direct foreign investment. Due to that, Malaysia Telecom purchased a 30% share of Ghana Telecom, which led to a rise in direct foreign in Ghana. With respect to the internet usage in academia Ghana, Hinson and Amidu (2006) indicated that most final year students in the University of Ghana Business School are aware of the existence of the internet through sources such as family, friends and self-tuition. Despite the awareness of the of the internet, the students did not fully utilise the internet as a resource and a learning aid due to their limitation in the use of e-mail and the WWW. The table below provides some statistical data on the internet usage in Ghana and the penetration rate based on Ghana’s population growth. 13 University of Ghana http://ugspace.ug.edu.gh Table 2.1: Internet Usage in Ghana and Population Growth Year Users Population %Percentage Usage Source 2000 30,000 18,881,600 0.02% ITU 2005 368,000 21,029,850 1.60% ITU 2006 401,300 21,801,662 1.80% ITU 2007 609,800 21,801,662 2.80% ITU 2008 880,000 23,382,848 3.80% ITU 2009 997,000 23,887,812 4.20% ITU 2010 1,297,000 24,339,838 5.30% ITU 2011 2,085,501 24,791,073 8.40% ITU 2015 5,171,993 26,327,649 19.60% IWS 2016 7,958,675 26,908,262 29.6 % IWS Source: (Internet World Stats, 2016) 2.3 Social Media Usage in Ghana The concept “Social media” has been described as an “interrelated group of internet-based technologies and applications which allow users to create content, share and exchange the content on a platform” (Wu, 2016; Kaplan & Haenlein, 2010). It has become an informative platform that has generated global attention with over 2.0 billion active members on Facebook alone (Facebook, June 2017). eMarketer (2014) reported that businesses have increased their budget allocations to social media and digital technologies with record high of $138 billion in 2014. In Ghana, for instance, Internet World Stats (2017) reported that social media users increased from 2,900,000 in 2015 to 3,500,000 in 2016 on Facebook alone. The surge in patronage of SM shows the significance of the platform as an important tool for informative content. 14 University of Ghana http://ugspace.ug.edu.gh Social media has attracted the attention of scholars in Ghana even though it is a new media platform. According to Boateng (2016), telecommunications companies in Ghana use social media platforms to manage customer knowledge about their brand. Boateng and Okoe’s (2015) findings also revealed a positive relationship between social media advertising and perception of consumers about the reputation of the company. Scholarly work of Ahenkorah-Marfo and Akussah (2016) further indicated that many of the top libraries in Ghanaian universities possess the knowledge of social media but the integration of social media in the libraries has been militated by several challenges such as inadequate skills. Additional research findings by Stats Monkey (2015) revealed that Facebook was the most used social media tool in Ghana. Top three social media platforms include Facebook (94.89%), Twitter (3.97%), and Pinterest (0.62%). Furthermore, Internet World Stat (2016) research revealed that there are 3,500,000 users of Facebook in Ghana. In addition, research findings by Stats Monkey (2015) revealed that Facebook was the most used social media tool in Ghana. Below is the table that presents the research findings. 15 University of Ghana http://ugspace.ug.edu.gh Table 2.2: Ratings of Social Media Use in Ghana Rank Ghana Social Media Usage % Social Media Usage 1 Facebook 94.89 94.89 2 Twitter 3.97 3.97 3 Pinterest 0.62 0.62 4 Google+ 0.18 0.18 5 Tumblr 0.16 0.16 6 YouTube 0.08 0.08 7 StumbleUpon 0.07 0.07 8 Reddit 0.02 0.02 9 Others 0.01 0.01 Total Usage 100 Source: (Stats Monkey, 2015) Furthermore, Internet World Stat (2016) research revealed that there are 3,500,000 users of Facebook in Ghana. These statistics depict the relevance of SM as an information tool for decision making. 16 University of Ghana http://ugspace.ug.edu.gh CHAPTER THREE LITERATURE REVIEW 3.0 Introduction Chapter Three of this research report presents the literature review of the study. The chapter reviewed literature on the concepts of social media, brand equity and the relationship between social media and brand equity. In this chapter, an empirical review was similarly presented. The chapter also presented a theoretical review that discussed the underlying theories in this study. The final section of this study report pesents the conceptual framework relating to social media and brand equity and finally the hypotheses for the study was formulated. 3.1 Concept of Social Media Historically, “Usenet” was invented in 1979 by two individuals at Duke University, namely Jim Ellis and Tom Truscott. These individuals’ invention gave an opportunity for users to have global interaction through the posting of messages publicly. But before then, social media was perhaps invented earlier by Bruce and Susan Abelson who developed an online network that helped to assemble online diary writers. The increased accessibility of the internet served as a major boost to the concept of social media. As a result, sites such as Facebook and Myspace were created in 2004 and 2003 respectively and this led to the creation of “social media” as we have in contemporary times (Laroche., Habibi., Richard & Sankaranarayanan, 2012). Interestingly, the definition of “social media” has not achieved consensus over the last decades (Van & Coursaris, 2013). Ala-Mutka, Broster, Cachia, Centeno…and Pascu (2009) described social media as tools used by organisations to engage in socially-based activities such as sharing 17 University of Ghana http://ugspace.ug.edu.gh of pictures and videos, networking within the social context and engaging in both blogging and micro-blogging. It moreover represents a number of technological innovations that help users of the applications to generate social media’s inexpensive content, and interact with and among themselves on the platform (Berthon, Pitt, Plangger & Shapiro, 2012). Social media applications have also been described as one of the common, influential and efficient implications that has received progressive engagement in various aspects of people’s lives (social life, educations, political, commercial life among others) (Algharabat et al., 2017; Alalwan et al., 2017). Different kinds of social media technologies have emerged over the last years, and they are based on the user and functions, and they all play a significant role in accessing public opinion in real time (Kietzmann, Hermken, McCarth & Silvestre, 2011). Businesses mostly advertise on social media through platforms such as Youtube, Facebook, Twitter and LinkedIn and others which have also become of great importance to organizations (Saxena & Khanna, 2013). Many consumers have transformed their channels of interaction with firms and other customers based on the fastest growing nature of social media platforms. As a result, firms have similarly transformed their ways of attracting and maintaining current and prospective consumers (Leung, Bai & Stahura, 2015). According to Chandra, Goswami and Chouhan (2013), Patino, Pitta and Quinones (2012) and He and Zha (2014), marketers previously would design attractive advertising messages and buy mass media space and hope that it would create brand awareness and preference for consumers. The birth of social media has resulted in the loss of viewership and readership in television. In every market, consumer and the suppliers alike are beholding social media tools as central component in their businesses (Xu, 2017). Social media tools such as Instagram, LinkedIn, 18 University of Ghana http://ugspace.ug.edu.gh Facebook and Twitter are used predominantly (Alalwan, Rana, Dwivedi & Algharabat, 2017) to create content, share and exchange the content “message” on the platform (Wu, 2016; Kaplan & Haenlein, 2010). Investigations such as Alalwan et al. (2017) and Duffett (2015) Singh and Sonnenburg (2012) report that organisations use social media tools to share promotional campaigns, build awareness of the brand, create strong sense of recognition, recall, and meaning in the minds of customers. Contrary evidence also shows that consumers do not consider social media messages that organisations put on their social media platform (Wu, 2016; Yelba, 2010). As a result, marketers have improved their budget and investment in interactive social media technologies (eMarketer, 2014). Interactive platforms such as WhatsApp, Facebook, Twitter, Instagram, and YouTube have all emerged. 3.2 Benefits and Challenges of Social Media Organisations have changed their marketing communication media and tools due to the emergence of social media (Hassan, Nadzim & Shiratuddin, 2015). Large sums of organisations’ budgets, time, and scarce resources have been invested in social media infrastructure to attract large numbers of customers through involvement and interaction in their online activities (Filo et al., 2015). Reports have emerged to the effect that about 93 percent of businesses worldwide have employed and constantly engaged clients on innovative platforms as a process to communicate their brand values (Alalwan et al., 2017). A survey of student use of social media in the United Kingdom (UK) by Reyneke, Pitt and Berthon (2011) reported that suppliers and consumers are able to monitor the brands that they prefer on social media technologies such as Twitter, Facebook and Instagram and even questions about the products. 19 University of Ghana http://ugspace.ug.edu.gh According to Kaplan and Haenlein (2010), there are no differences in the various social media applications but the distinction is clear among sites that engage in social networking such as LinkedIn that is designed for professionals to interact; those that are crafted for the dissemination of videos such as YouTube; sites for the sharing of pictures such as Flickr; social bookmarking sites like Delicious and Digg; and those that are invented for the purpose of disseminating knowledge online such as Wikipedia. Usually, the characteristic of social media technologies is to present an opportunity for individuals to have social interactions in a manner that did not previously exist (Fischer & Reuber, 2011). On the contrary, social media, when not properly used, could have a negative impact on a firm’s brand image and the value as well (Alalwan et al., 2017). The negative consequences of social media technologies could emanate from negative comments from current or potential customers and the subsequent sharing of these negative stories with all users on the platform (Hennig-Thurau, Hofacker & Bloching, 2013). 3.3 Social Media Platforms According to Kaplan and Haenlein (2010), there are social media platforms that are designed for different purposes. Smith and Gallicano (2015), in their content analysis of social media platforms research, found that Twitter, Facebook and Youtube remain the most operative social media technologies that most organisations use to connect with customers, create and share content and stories. In this study, the researcher focused on Facebook, Twitter, Instagram and YouTube as the four social technologies. 20 University of Ghana http://ugspace.ug.edu.gh 3.3.1 Facebook Facebook has become the common technology examined in literature (Chang et al., 2015), which makes it possible for users to share information and pictures in a framework that is structured (Gamboa & Gonçalves, 2014; Eskisu, Hosoglu & Rasmussen, 2017). Facebook is globally known and has over 1.09 billion members who actively use the social networking site (Facebook, 2013). Facebook presents users with the right environment where predictions of social behaviour can be tested. Extant literature has revealed that factors such as enjoyment ease of use and identification influences the behaviour of the consumer to share the stories online (Pereira et al., 2014; Kang & Schuett, 2013). Further investigations have found that Facebook uses features that have proven to be useful for interactions and creation of friendship. These are the frequency of use of members on Facebook (Leung et al., 2015), total friends made on the platform (Lee et al., 2012), settings that provide privacy (Smith, Mendez & White, 2014), and nature of posts (He & Zha, 2014; Patino et al., 2012). According to Karal, Kokoç and Ayyıldız (2010), individuals use Facebook for acquaintance reasons (knowing people and people knowing you), social engagement and interaction (e.g. staying in touch with friends) and education (acquiring up-dated idea that are of a different nature). In 2015, Leung et al. (2015) conducted a study in the hotel industry in the USA and found that social media experience has a significant influence on consumer attitudes towards Facebook that is predicted by their role of user’s involvement in the experience on the platform. In effect, Wang et al. (2012) indicated that client’s intention to use Facebook is predicted by the nature of his/her involvement that constantly creates a reminder in the minds of the clients. 21 University of Ghana http://ugspace.ug.edu.gh 3.3.2 Twitter Twitter is observed as the second most visited social media platform examined in literature as a social media tool used to communicate brand information (Coulter & Roggeveen, 2012; Kim et al., 2014). Twitter has globally been established as a public communication platform as well as a micro-blogging service instrument (Java et al., 2007). Twitter is regarded as an online platform that allows users to share real time information on a wide range of issues. The application has increased the number of opportunities available for undertaking scholarly research and, as a result, has become a source of increased attention. Twitter presently experiences 500 million tweets in a day, which makes it the largest micro-blogging service since its commercialization in October 2006 (Twitter, 2015). Recent global statistics have indicated that about 22 percent active internet users frequently use Twitter (Globalwebindex, 2014). Twitter has five functions, namely tweets, retweets, hashtags, @-messages and follower relations. A Tweeter subscriber can tweet information and follow tweets of other users as well. This establishes a social sites and a network of twitters where follower relationships and direct friendships exist (Marwick & Boyd, 2011). This system varies from other social media sites like Facebook, which are undirected models. Tweet users can forward tweets in the form known as retweeting to other users, or annotated by a #hashtag. Tweets can also provide information to web links where press releases, news articles or reports, for instance, can be accessed. The main types of interaction available to Tweeters are engaging in conversations, reporting news as well as sharing relevant information (Java, Song, Finin & Tseng, 2007). Twitter has transformed from mostly sharing of personal information to the sharing of various information (Risse, Peters, Senellart & Maynard, 2014). 22 University of Ghana http://ugspace.ug.edu.gh 3.3.3 Instagram Instagram is a mobile device application structured and developed in a way that allows the sharing of lifetime events through pictures in real time (Instagram, 2015). It is the growing social online platform in the United States with over 400 million active users and almost 80 million pictures shared on a daily basis (Pew, 2015). Instagram allow the users on the platform to snap pictures and upload them for public viewing. Instagram users can make comments or ‘like’ the pictures of other users. Instagram possess a rare characteristic that allows users to create high-quality pictures (Lee, Lee, Moon & Sung, 2015). The reason behind the creation of Instagram is to provide users the opportunity to share their life stories through pictures. Previous studies have suggested that interaction between individuals is one of the main motivations for using the Instagram platform (Geurin-Eagleman & Burch, 2016; Pittman & Reich, 2016; Ridgway & Clayton, 2016). For example, Pittman and Reich (2016) indicated that a more positive attitude towards Instagram will lessen the possibility of the user feeling lonely. Just like Facebook and Twitter, social interaction also plays a significant role for the use of Instagram (Lee et al., 2015). In other words, Lee et al. (2015) posited that the major motivation for using Instagram is that users are able to create and maintain their relationships. Another important motivation for using Instagram is the ability for self-expression and social interaction. The application has multiple opportunities for users on the platform to express themselves more using pictorial features (Marwick, 2015). Ridgway and Clayton (2016) further noted that Instagram users have stronger motivations because of self-presentation and the desire to see and be seen by others through pictures. Users on Instagram are able to manipulate of pictures 23 University of Ghana http://ugspace.ug.edu.gh with filters and the use of “selfies” to take picture shots of themselves. The satisfaction of the image of an individual is positively related to the posting of selfies on Instagram. 3.3.4 YouTube According to Siamagka et al. (2015), YouTube has become an important social media application but has received less significant interest (Marwick, 2015). YouTube is an applications that represents a community that allows users to create content using videos and helps viewers to rate and comment on videos (Kaplan & Haenlein, 2010). Kaplan and Haenlein (2010) added that the viewing and rating increase the popularity of the video and the content in the video. In this 21st century, YouTube has become a medium that impacts on how users interact and influence other users on social media. YouTube provides an opportunity for subscribers to generate and disseminate content created by them in order to strengthen business opportunities (Filo et al., 2015; Zeng & Gerritsen, 2014; Gensler et al., 2013) and it allows for the creation of strategies that will aid marketing activities as well as branding (Filo et al., 2015). Filo et al. (2015) stipulated that the contents on YouTube make it possible for users to inform, entertain and engage moods. The platform also allows users to express themselves and feel self-actualised. YouTube presents many characteristics that strengthen social interaction (Benevenuto, Duarte, Rodrigues, Almeida & Ross, 2008) and users are able to make comments on videos, like or dislike videos, or share videos on other social network platforms like Facebook or Twitter (Kaplan & 24 University of Ghana http://ugspace.ug.edu.gh Haenlein, 2010). The feedback to the videos on YouTube specifically plays a critical role in users’ interaction and network relationships within the society. 3.4 Consumer Behaviour and Consumer Decision-Making Behaviour of rational consumers has become very difficult to predict. The behaviour of consumers comprises of the various steps that individuals or groups go through in the identification, purchase, utilisation and disposal of products with the overall intention of satisfying needs (Solomon, 1995; Schiffman, Hansen & Kanuk, 2007). According to Ramachander (1988), the field of consumer behaviour combines three social science fields: individual psychology, cultural anthropology and societal psychology. The study of consumer behaviour helps firms to know and better understand the consumer because it provides answers to very pertinent questions. The study provides answers to questions such as what product a customer purchases, why consumers purchase a product, where and when a consumer buys (Green, 1992). Studying consumer behaviour provides immense benefits to various firms because it helps them to develop proper plans and superior strategies (Khaniwale, 2015). Consumers have to cope with information overload as a result of many daily decisions (Scammon, 1977; Jacoby, 1984). Marketers are interested in obtaining insights in the manner in which consumers buy. This is a complicated process since the decisions that consumers make over a period of time need to be understood (Hoyer & Macinnis, 2001). Olshavsky and Granbois (1979) argue that consumers go through various processes when making a buying decision. Extant literature indicated the five steps that consumers go through in making decisions as identifying problem, searching for information, evaluating alternatives, purchase, and post purchase behaviour 25 University of Ghana http://ugspace.ug.edu.gh (Liang & Lai, 2002; Darley et al., 2010). The figure below presents the processes that consumers go through before making the final decision. Figure .1: The Consumer Purchasing Process Source: David (2001) 3.4.1 Problem Recognition The consumer purchasing process begins with the recognition of a need (Kardes, Cline & Cronley, 2011). According to Kotler et al. (2009), a consumer can identify a need due to the presence of either some internal or external stimuli. The internal stimuli are within the physiological make-up of the consumer whereas the external stimuli are due to the environment of the consumer. 26 University of Ghana http://ugspace.ug.edu.gh Consumers therefore identify the existence of a problem or problems. The problems or needs may be simple such as the need for food or a much more complex one such as the purchase of a vehicle. Consumers are shaped by various factors such as social, cultural, reference groups and the environment in recognising their needs (Hawkins & Mothersbaugh, 2010). 3.4.2 Information Search After the recognition of a problem, the consumer searches for information through various sources. The sources for information are internal and external. The internal source refers to the recall of a product from memory by consumers. This is what is referred to as an internal search. Hawkins and Mothersbaugh (2010) and Agresta and Bough (2010) argue that the use of the internet has become an important external source that consumers use to search for information in contemporary times. Bhatnagar and Ghose (2004) assert that, the higher the frequency of information search by consumers on the internet, the more information they get, which affects decision-making. Kotler et al. (2009) argue that close associates, peers and neighbours constitute personal sources of consumer information gathering. Exhibition of products, marketing intermediaries, salespersons, product packages, advertising content and business websites represent the commercial sources of consumer information. There is also another source of consumer information that is referred to as an experiential source. This includes the handling, scrutinising and use of a product by consumers. Commercial sources present most product information to consumers but the most effective sources are public or personal sources, which are independent sources. 27 University of Ghana http://ugspace.ug.edu.gh 3.4.3 Evaluation of Alternatives At this stage, consumers compare and assess several options in terms of products’ characteristics and needs. Consumers’ choices could be based on a simple decision such as ‘buy the cheapest products’ but there are complex decisions. Consumers at this stage consider which alternative would be the best to satisfy needs (Blythe, 2008). According to Campbell and Goodstein (2001), a consumer’s decision can be associated with perceived risk, which may make a consumer modify, postpone or avoid a purchase. Kotler et al. (2009) have identified five risks that the consumer takes into consideration at this stage. There is the risk that the product will not perform as expected and this is called functional risk. Physical risk is the danger that the product may hurt the user or others. Consumers also fear that they will not receive value from the product purchased; thus, the product will not reflect value for money. This is called financial risk. In evaluating a product, there is also the risk that the product might embarrass the consumer or others and this is called the social risk. Consumers similarly have the risk of purchasing products that do not suit the image that they perceive about themselves. This also called psychological risk. Finally, consumers consider time risk, which is the period that has been wasted in buying an unsatisfactory product. 3.4.4 Purchase Decision Once consumers have found their relevant alternatives and assessed them, they make their choice among the alternatives. Consumers choose particular products because the product appeals to them. The choice can be impacted by the gathered information from various sources (Hawkins & Mothersbaugh, 2010). According to Kotler et al. (2009), consumers can lessen the doubt and adverse effects of risk by compiling information from friends and preferences for national brand, 28 University of Ghana http://ugspace.ug.edu.gh which then calls for marketers to thoroughly understand the factors that account for consumer risks and provide information to minimise perceive risk. 3.4.5 Post-Purchase Behaviour Consumers have expectations of how well the product purchased will perform. When a product performs based on the expectation of the consumer, such an individual becomes satisfied. Consumers become dissatisfied when the product falls short of providing the required satisfaction. This implies that what the consumer expects from a product was not achieved. A consumer becomes delighted if the product performance exceeds expectation (Mitchell & Boustani, 1994). A customer is likely to repeat the purchases if expectations are met or exceeded. In situations where the performance of a product falls short of expectation, the customer will experience psychological discomfort (Kardes et al., 2011). 3.5 Concept of Choice Overload Consumers on SM are exposed to a large array of information. Several scholars have attempted to conceptualise this phenomenon since Alvin Toffler popularized the term “information overload” in 1970 (Toffler, 1984). Since the popularization of the term scholars have used it predominantly in academic research. According to Beniot and Miller (2017), information overload occurs when the amount of input to a system exceeds its processing capacity. Quite importantly, the advent of SM and other online networking sites has led to a dramatic increase in the amount of information a user is exposed to, thereby greatly increasing the chances of the user experiencing an information overload. 29 University of Ghana http://ugspace.ug.edu.gh The depth of information on social media presents a system where consumers complain of information overload, especially micro-bloggers. Evidence has shown that two thirds of Twitter users felt that they receive too many posts or information, and over half of Twitter users felt the need for a tool to filter out the irrelevant posts to allow for more important and informative ones (Bontcheva, Gorrell, & Wessels 2013). Humans have limited cognitive processing capacities, and consequently, when they are overloaded with information, their quality of decision making suffers (Gross, 1964). Empirical investigations have shown that when users experience too much information “information overload” has a major impact on users, which include work productivity (Dean & Webb, 2011), recommendation systems (Borchers et al., 1998), and information systems (Bawden & Robinson, 2009). These prior works have all typically relied on qualitative analysis, surveys or small-scale experiments. This study therefore attempts to: (i) understand how social media information assists in decision making; (ii) explore whether there is too much information on social media; (iii) whether the information is destructive or informative, and (iv) ultimately infer how information overload influences quality of choice and post purchase dissonance. 3.6 Information Quality in Social Media Platform Over the past years, SM sites such as LinkedIn, Facebook and Twitter have considerably changed the phase of social interaction by building new platforms for communicating and exchanging information. Organizations are endeavouring to properly integrate information from various SM platforms into their daily business activities by, for example, recruiting, sales and marketing 30 University of Ghana http://ugspace.ug.edu.gh (Sinclaire & Vogus, 2011). However, if organisations are to depend on data collected through SM sites, they need to comprehend the quality of information from these sites. Although there are some concerns raised as to the quality of these information, understanding significant quality attributes and having an effective means to assess them is limited. This has raised, for several researchers, a question as to the quality of user generated content in SM (Baeza-Yates, 2009). Social media content can either be quality or not quality (Baeza-Yates, 2009). Ideally, consumers prefer quality information on SM to enhance the quality of their decision making. Unfortunately, social media has extended knowledge creation borders across organizational boundaries, therefore the organisation has no control or influence on the quality of the information that users post on the SM platform (Kane & Ransbotham, 2012). Information quality (IQ) in the context of SM in information systems (IS) comprises unique attributes such as wide accessibility, permanence, global reach, modernity and user friendliness (Agarwal & Yiliyasi, 2010). Literature further explains that the quality of SM information is determined from both the user (subjective) and data (objective) perspectives. From the users’ perspective, IQ is described as the extent to which SM information fits for the intended use of the consumer (Chai et al., 2009; Strong, Lee, & Wang, 1997; Ge & Helfert, 2007). On the other hand, data quality refers to meeting pre- defined and well-established requirements and specifications that ensures that information on SM is free from deficiencies that may interfere with its use (Kahn, Strong, & Wang, 2002; Madnick, Wang, Lee, & Zhu, 2009). 31 University of Ghana http://ugspace.ug.edu.gh Furthermore, various businesses do not effectively handle negative information contents on SM in order to translate the negativity into opportunities that will be beneficial to business communications strategies (Dekay, 2012). Negative word of mouth is the resultant effect of poor means of dealing with negative statements that have been posted by consumers of a brand on social media. Businesses are confronted with the challenge of effective management of negative consumer statements (Hennig-Thurau et al., 2010; Roehm & Tybout, 2006) since, according to Schlosser (2005), the attitude of consumers can be substantially affected by a few negative comments of a brand on social media pages. Corstjens and Umblijs (2012) asserted that brand image and sales would be negatively affected if firms do not put in place mechanisms to deal with negative consumer comments. The literature therefore reveals that social media has many benefits compared to the few risks but it is important for businesses to manage the risks in order to enjoy the full benefits of social media. Barger, Peltier and Schultz (2016) focused on the response of customers to brand related content in a social media environment. According to Angella and Eunju (2012), Kim and Ko (2012) and Bebac (2011) social media use (such as online communities, interaction, content sharing, accessibility and credibility) influences the quality of choice the consumer make as well as the decision of the consumer. Alalwan et al. (2017), in a review of 144 articles on social media, indicated that 89 percent of studies supported the crucial roles of social media. The review revealed that using social media platform messages enhances customer’s perception of the brand and the level of awareness of the brand. Similarly, Duffett (2015) indicated that the efficiency and effectiveness of social media content significantly drives how customers perceive the brand, either positively or negatively and likewise how they formulate their attitudes. 32 University of Ghana http://ugspace.ug.edu.gh Rotzoll, Haefner and Sandage (1990) defined informativeness as the “ability to inform users about product alternatives that enable them to make choices yielding the highest value”. This construct is developed based on how individuals perceive content and this is measured based on their feedback (Palvo, Liang & Xue, 2007). Informativeness embodies an appeal to individuals to take decisions rationally. It is therefore distinct from emotional appeal (Lee & Hong, 2016). Resnik and Bruce (1977) identified that the presence of information in advertising material on television aids consumers in decision making that is more intelligent and serves their interest when buying. According to Andrews (1989) and Taylor, Lewin and Strutton (2011), an advertisement would be found valuable by consumers if it is consistent with the product that it displays. Gao and Koufaris (2006) argue that businesses that engage in transactions electronically through the use of websites have identified the provision of essential information for the formation of the attitudes of consumers. This assertion is likewise shared by Resnik and Bruce (1977) who studied television advertising. Taylor et al. (2011) argued that, within the social networking environment, informative advertising eventually leads to the development of word-of-mouth comments by consumers. Literature generally agrees that informative content of advertisements that are placed on social media sites play a very significant role because customers base their future decisions on it (Lee & Hong, 2016). Empirical evidence investigates the impact that the amount of social ties of a social media user has on the way she interacts or exchanges information with her friends, followees or contacts (Backstrom et al., 2011; Hodas & Lerman, 2012; Miritello et al., 2013). For instance, Backstrom et al. measured the way in which an individual divides his or her attention across contacts by 33 University of Ghana http://ugspace.ug.edu.gh analysing Facebook data. Their analysis suggests that some people focus most of their attention on a small circle of close friends, while others disperse their attention more broadly over a large set. Hodas et al. (2013) quantify how a user’s limited attention is divided among information sources (or followees) by tracking URLs as markers of information on Twitter. They provide empirical evidence that highly connected individuals are less likely to propagate an arbitrary tweet. Miritello et al. analyze mobile phone call data and note that individuals exhibit a finite communication capacity, which limits the number of ties they can maintain actively. In the SM context, Chai, Potdar and Dillon (2009) described information quality as Content Quality (CQ) that permits for the identification and distinction of high quality content over poor quality content. Table 3.1 categorizes IQ studies according to their goals to investigate to what extent these studies cover various applications of SM information. The table presents a brief synthesis of IQ in SM research, categorised around four main goals distinguished from the set of studies, and compared across study goals, contexts, dimensions and methods. 34 University of Ghana http://ugspace.ug.edu.gh Table 3.1: Analysis of IQ in Different SM Applications Goal Contex Dimension Methods Adopted From t Learning Q&A Informativeness, Politeness, User survey, experts, (Kim, Shaw, and website Completeness, Readability, developing automated Feng, Beal, & education s, Relevance, Conciseness, NLP, automated text Hovy, 2006; Lui, forum Truthfulness Level of Detail, categorisation, neural Li, & Choy, Originality, Objectivity, networks, text mining, 2007; McKlin, Novelty, Usefulness, information retrieval, Harmon, Evans, expertise, semantic content, natural language & Jones, 2002; Z. amount of data processing Zhu, Bernhard, & Gurevych, 2009) Information Q&A Amount of data, description, Using web crawlers to (Agarwal & retrieval website discrimination, information analyse data, Yiliyasi, 2010; services and s, diversity, semantic content , stochastic gradient Agichtein, search forum, user relationships, usage boosted trees Total Castillo, Donato, engines media statistic Accuracy, data quality Gionis, & sharing, Believability, Objectivity, management Mishne, 2008; Social Reputation, Value-added, methodology Figueiredo et al., media Relevancy, Timeliness, 2013),(Chen & website Completeness, Amount of Tseng, 2011) s data, Interpretability, Ease of understanding, Manipulability, Conciseness, Accessibility, Security Evaluating Q&A Accuracy, completeness, Content analysis, (Fichman, 2011; the website verifiability, content distortion analysis Olsina, Sassano, knowledge s, accuracy, suitability, (Wu, Greene, Smyth, & Mich, 2008; custom accessibility, legal & Cunningham, 2010), Yee Cheung, et er compliance, argument survey analysis al., 2012) review quality, source credibility, website review consistency, review sidedness User Forum User feedback, amount of Quality ratings by (Chai, et al., contribution data other users, developing 2009; Klamma et and ranking prototype al., 2007) From Table 3.1, it can be inferred that the scope, perspectives and approach to determining information quality in the SM environment and through academic studies have been varied over the period. While previous literature offers several avenues to SM information quality, it is 35 University of Ghana http://ugspace.ug.edu.gh observed from the table that the scope, perspectives and tactic of these works is disparate, largely incomparable and lacking any common theoretical basis. For instance, Wang and Strong (1997; 1996), discussed information quality in terms of usefulness and usability for consumers. They further proposed that SM information quality should consist of four additional dimensions that include intrinsic, accessibility, contextual and representational. These dimensions have been used widely in information quality research and they are the most cited dimensions in content/information quality literature (Agarwal & Yiliyasi, 2010; Alkhattabi, Neagu, & Cullen, 2011; Chen & Tseng, 2011). 3.7 Conceptual Framework Studies have examined the relationship between choice overload and purchase decisions. Scholars such as Beniot and Miller (2017), found that information overload occurs when the amount of input to a system exceeds its processing capacity. Further empirical investigations reveals that when consumers experience too much information it has a major impact on their pre and post purchase decisions, recommendations (Borchers et al., 1998), and information systems (Bawden & Robinson, 2009). Quite profoundly, the advent of SM and other online networking sites has led to a dramatic increase in the amount of information a user is exposed to, thereby greatly increasing the chances of the user experiencing an information overload leading to post-purchase dissonance (Kane & Ransbotham, 2012; Agarwal & Yiliyasi, 2010). Based on the trend in literature, the study proposes that choice overload leads to low quality decisions as a result of consumers being confused, having difficulty in processing alternatives and short cues. In effect, low quality decisions may result in consumer experiencing post purchase 36 University of Ghana http://ugspace.ug.edu.gh dissonance. Fig 3.2 explains the structural relationship between choice overload and post purchase dissonance. Confused Post Choice Use of Short Poor Purchase Overload Cues Quality Dissonance Difficulty in of processing Choice choice alternatives Source: Author’s Construct 37 University of Ghana http://ugspace.ug.edu.gh CHAPTER FOUR METHODOLOGY 4.0 Introduction This chapter provides an overview of the methods that the researcher selected in carrying out the research so as to address the research problem and achieve the purpose of the study. The general approach for executing a research project is also known as ‘Research Methodology’ (Leedy & Ormrod, 2001). Potter (1996) once said that “Methods are the tools used in a study while methodology is the blueprint of the study.” Saunders, Lewis and Thornhill (2009) also defined research methodology as “the procedural framework within which a research is conducted.” According to Taylor and Bogdan (1984), the manner in which the researcher examines and looks for solutions to pre-defined/already existing research problems constitutes research methodology. Also, serves as a set of guidelines for analysis, where the assessment of data can be used to elicit conclusions (Eldabi, Irani, Paul, & Love, 2002). 4.1 Research Paradigm It is essential that in all research projects, there should be a relationship between the researcher’s own values, worldview about knowledge, theory underpinning the study, research methods and the aims of the research (Buame, 1996; Taylor & Bogdan, 1984). For that reason, it is imperative to discuss the research philosophy and paradigm underlying the research before embarking on a study of this nature. In this study the researcher employed the interpretivist paradigm to interpret the findings. 38 University of Ghana http://ugspace.ug.edu.gh Gummesson (2000) observes that the concept of paradigms was proposed by Thomas Kuhn (in the early 1960s) to stand for “people’s value, standards, frames of reference, perspectives, ideologies, myths, theories, and approved procedures that govern their thinking and action”. Kuhn (1962) defined paradigms as the “entire constellation of beliefs, values, techniques, and theories shared by members of a scientific community”. The concept of a paradigm can moreover refer to “a set of assumptions about the social world, and about what constitutes proper techniques and topics for inquiry” (Punch, 2013). After reviewing extant literature, Boateng concluded in 2014 that there are numerous and different paradigms with several taxonomies to distinguish between them. The most dominant paradigms commonly referred to in social science research include positivism, interpretivism, realism, relativism and critical realism (ibid). Creswell (2007) noted that each paradigm has a structure that differentiates itself from other paradigms though its own set of epistemological, ontological and methodological assumptions. According to Boateng (2014), researchers in support of the positivist paradigm are of the view that there is a reality that is single, objective and tangible. On the contrary, the interpretivist ontology believes there are several truths that are reliant on human experiences and interpretation. The realist viewpoint believes that a triangulation from many sources is required to try to know “reality” because, although it is real, it is improperly understood (ibid). Saunders et al. (2009) simply explains the theory of realism as there exists a reality that is, to a certain extent, independent of the mind. Furthermore, the critical realist paradigm argues that experiencing the world is a two- step process: first of all, there is the thing itself and the sensations it conveys (Saunders et al., 2009; the transitive world, see Boateng (2014)); and secondly, there is the psychological processing that goes on sometime after that sensation meets our senses (the intransitive world, see Boateng 39 University of Ghana http://ugspace.ug.edu.gh (2014)). The relativism theory perceives that multiple realities exist. Thus, reality as truth is not “absolute,” it is dependent on ‘something’ and it does exist (Boateng, 2014). Considering the research objectives outlined in Chapter One of this study, the researcher deems it appropriate to follow the interpretivist approach or view. This stance was enlightened by Bhattacherjee (2012), who postulates that the social scientist needs to understand the social actions of their research subjects through interpretive means - considering the meaning and purpose they place on their actions. The interpretivist view has a concern to understand the world as it is - see the world as an emergent social process and seek to understand at the level of subjective experience. According to Whitley (1984), interpretivists try to find the implications and rationale behind people’s actions, like how they behave and interact with others in the society and culture. Another reason for using the interpretivist approach is that Elster (2007) and Walsham (1995b) explain interpretivism as the approach that highlights the expressive nature of people’s character and involvement in both social and cultural life. Saunders et al. (2009) explain that interpretivism is an epistemology that differentiates conducting research among people rather than objects (such as trucks and computers), because it advocates that the researcher needs to understand variances between people in our role as societal beings. Hence, the researcher has to take it upon him/herself to enter the social world of the research subjects and understand their world from their perspective because Schwandt (2000, p. 191) opines that “what an action means can be grasped only in terms of the system of meanings to which it belongs”. Interpretivism provides an understanding of differences between the human actors. Conversely, Lin (1998) explained that interpretivist researchers look for specific ways in which a 40 University of Ghana http://ugspace.ug.edu.gh relationship is established and the setting within which it occurs. As a result, these scholars are able to understand how relationship occurs (Chowdhury, 2014; Kelliher, 2005; Lin, 1998). The interpretivist is fundamentally not interested in generalizing his/her findings because life is dynamic (Saunders et al., 2009) and how every research subject reacts to a particular issue is dependent on their viewpoint and environment. Therefore, as researchers try to interpret what they see, hear and understand (Creswell, 2009), they work towards theory building through interpretive methods such as action research and ethnography (Bhattacherjee, 2012). On the basis of the above justifications, this study used the interpretivist paradigm. 4.2 Research Approach Generally research approach can be categorised into deductive and inductive research approaches (Saunders et al., 2009). The approach a researcher adopts should be influenced by the paradigm that s/he belongs to. This is because the research approach will also influence the research design and strategy that will be adopted. In this study, the researcher employed an inductive research approach, which explains research reasoning that draws from an instance or repeated combination of events in order to conclude or maybe make generalizations. According to Malhotra (2007), the deductive research approach refers to a form of thinking in which a conclusion is validly inferred from some premises as deduction; and these conclusions are true only if those premises are true. Understanding data in the deductive approach makes use of existing knowledge, since it serves as a guide. The premise for deductive arguments is formed from the building and establishment of ‘facts’. This reasoning begins from general principles from which the deduction is to be made, and proceeds to a conclusion by way of some statement relating 41 University of Ghana http://ugspace.ug.edu.gh to the particular case in question. Ali and Birley (1999) further posit that well-established existing theory underpins a deductive research, which informs the development of hypotheses, the choice of variables and the resultant measures. The deductive approach therefore commences with theory articulated in the form of hypotheses, which are then tested (Malhotra & Birks, 2006). Induction, as explained by Malhotra and Birks (2006), is a form of reasoning that draws from an instance or repeated combination of events in order to conclude or maybe make universally accepted generalizations. In Saunders et al.’s (2009) view, the induction approach allows the researcher to appreciate the way in which humans interpret their social world; unlike the deduction approach, which enables a cause–effect link to be made between certain variables without understanding humans and the context within which they find themselves. The strength of the inductive approach therefore lies on the development of understanding humans and how they interpret their social world. Furthermore, unlike the deductive approach, the inductive approach provides a less structured/flexible methodology that is likely to reveal some additional explanations to the phenomenon under study. Moreover, the context in which events take place is of great importance to the inductive approach (Saunders et al., 2009). It is therefore more appropriate to use a small number of respondents in an inductive approach as against a large number in the deductive approach. Thus, researchers inclined towards the inductive approach should work with both qualitative and quantitative data collection methods in order to establish different views of the phenomena (Easterby-Smith, Thorpe, & Lowe, 2002). For these reasons, the researcher adopts an inductive approach to better understand the role of choice as a constraint to efficient decision making among social media users. 42 University of Ghana http://ugspace.ug.edu.gh 4.3 Research Design Malhotra and Birks (2006) defined research design as “a framework or blueprint for conducting the marketing research project. It also specifies the details of the procedures necessary for obtaining the information needed to structure or solve marketing research problems”. However, research design is not only limited to the field of marketing but can be used in any field of research. In order to structure or solve research problems, the research design specifies the necessary process that the researcher needs to go through to obtain the information needed. It similarly provides both the framework and road map for the research (Kuada, 2015). Thus, Teyi (2014) concludes that the research design sets the basis for conducting the project. McGivern (2006) notes that the research design’s purpose is to organize the research such that it provides evidence necessary to answer the research problem as “accurately, clearly and unequivocally” as possible. A research design furthermore ensures that the researcher strives toward objectivity (Allen, Arafat, Edgley, & Guy, 1987). The process of turning a research question into a research project can be referred to as the research design (Robson, 2002). Notably, research design is different from research tactics (Saunders et al., 2009). The overall plan for the research is the research design, and the finer details of data collection and analysis are the tactics. Other scholars likewise postulate that the choice of a research design shapes the subsequent research activities; for instance, what data to collect and how it should be collected (Ghauri & Grønhaug, 2005; Kornhauser & Lazarsfeld, 1955). The research design invariably exposes the type of research (whether exploratory, descriptive or casual) and the researcher’s priorities (Ghauri & Grønhaug, 2005). These priorities are reflected in the purpose of the study, which then seeps into the research questions asked. 43 University of Ghana http://ugspace.ug.edu.gh In general, literature pertaining to research methods classifies research purpose into three, namely: exploratory, descriptive and explanatory (Saunders et al., 2009). They, however, noted that the research project may have more than one purpose, just as a research question can be both descriptive and explanatory. Descriptive research, as the name suggests, “portrays an accurate profile of persons, events or situations” (Robson, 2002, p.59). In addition, Malhotra and Birks (2006) postulate that the major goal of descriptive research is to describe something, such as market characteristics or functions. In conducting this kind of research, Saunders et al. (2009) are of the view that the formulation of specific research questions and hypotheses precedes data collection; therefore, the researcher needs to understand the phenomena on which s/he wishes to collect data before collecting it. As a result, descriptive research is pre-planned and structured, as the information needed is clearly defined. It is most appropriate for surveys, because it is based on large representative samples. Again, Malhotra and Birks (2006) are of the view that descriptive research design lays down the methods for selecting data sources and how to collect data from those sources. According to Saunders et al. (2009), explanatory studies are studies that prove the existence of causal relationships between variables. In order to explain the relationships between variables in explanatory studies, the emphasis is on studying a situation or a problem giving a researcher two options: either collect qualitative data to explain, in order to get a clearer view of the relationship or subject the data to statistical tests such as correlation (ibid). In view of the above, the current study employs this research design for the quantitative element of the study. 44 University of Ghana http://ugspace.ug.edu.gh An exploratory research refers to a research design that is characterized by a flexible and evolving approach to understanding events that are inherently difficult to measure (Malhotra & Birks, 2006). Robson (2002, p.59) highlights the fact that a study, exploratory in nature, is a constructive way of finding out “what is happening; to seek new insights; to ask questions and to assess phenomena in a new light”. In cases where the exact nature of the problem is uncertain, yet the researcher wishes to explain the problem, exploratory research is most appropriate (Saunders et al., 2009). A search of the literature; interviewing ‘experts’ in the subject; and conducting focus group interviews are the three main ways of conducting exploratory research (ibid). They further postulate that exploratory research’s advantage over both descriptive and explanatory is its flexible nature and the fact that it is adaptable to change. Thus, when conducting the exploratory study, a pollster must be willing to make adjustments where necessary, due to new data that appear and new insights that may occur. Metaphorically, Adams and Schvaneveldt (1991) compared exploratory research with the activities of a traveller or explorer because of the flexible nature of their expedition. They however emphasize that the flexibility in this context does not mean there is no direction to the investigation. Instead, it means the researcher initially has a broad focus and as the research progresses, the broad picture becomes progressively narrower. Thus, this research is exploratory in nature as it tries to explore how social media content supports choices of consumers. The researcher believes that exploratory design helps to seek new insights, ask questions and also assess the dynamism of choice overload in decision efficiency. 45 University of Ghana http://ugspace.ug.edu.gh 4.4 Research Strategy Research strategy is the roadmap for undertaking a systematic research of a phenomenon of interest (Marshall & Rossman, 1999). Similarly, Saunders et al. (2009) refers to research strategy as the general plan regarding the answering of research questions that have been set. Remenyi, Williams, Money and Swartz (1998) proffer that every research is guided by a strategy, and that strategy gives a general guideline for the research, which includes the manner in which the research is to be conducted. A researcher has the opportunity to choose from a variety of research strategies due to the mixed methodological approach. Yin (2013; 2003) posits that, irrespective of whether the study is exploratory, descriptive or explanatory, these strategies can be used; although, some of these strategies are deductively inclined while others are biased towards the inductive approach. It is important to note that none of the research strategies is inherently superior or inferior to any other (Saunders et al., 2009); however, a researcher’s choice of strategy is directed by the research question(s) and objectives, the extent of existing knowledge, the amount of time and other resources that he/she may have available, as well as the researcher’s own philosophical viewpoints. Thus, Saunders et al. (2009) postulate that the most important thing is not the label that is attached to a particular strategy, but that the chosen strategy should help the researcher solve the research question(s) and meet the research objectives. In view of that, Saunders et al. (2009) outline seven research strategies that any researcher can select from: experiment, ethnography, action research, archival research, grounded theory, survey and case study. Some of the strategies are discussed below followed by a justification for using the case study approach. 46 University of Ghana http://ugspace.ug.edu.gh 4.4.1 Ethnography Ethnography is a typical inductive approach believed to explain the social world at first hand (Saunders et al., 2009). This strategy is a qualitative design that, according to Creswell (2007), includes studying how people of the same culture behave, relate to one another and their language. The researcher adopting this strategy should describe and interpret the shared and learned patterns of values, behaviours, beliefs, and language of a cultural-sharing group (Harris, 1968, cited in Creswell, 2007). Saunders et al. (2009) opine that the researcher ought to immerse him/herself in the daily lives of the people sharing the same culture, with the intention of observing and interviewing them. The research process has to be flexible and responsive to change since the researcher will constantly be developing new patterns of thought about what is being observed. Ethnography research strategy is timewasting; yet, the researcher’s purpose for choosing this strategy is to describe and explain the social world in which the research subjects live just as they would describe and explain it (Saunders et al., 2009). 4.4.2 Archival Research As the name suggests, archival research strategy makes use of documents in the archives. Saunders et al. (2009) explain that, in archival research, the researcher relies on administrative records and documents as the primary source of data. In addition, Bryman (1993) noted that archival research can refer to both recent and historical documents, although the term has historical connotations. As a result, this strategy allows researchers to ask questions related to past events and changes that have occurred over time, irrespective of whether exploratory, descriptive or explanatory in nature (Saunders et al., 2009). However, the ability to answer such questions is limited by the kind of administrative records and documents available. Thus, Saunders et al. (2009) suggest that the 47 University of Ghana http://ugspace.ug.edu.gh researcher using this strategy needs to establish what data are available and design the research to make the most of it. 4.4.3 Grounded Theory According to Saunders et al. (2009), grounded theory is developed from data generated by a chain of observations. Collis and Hussey, in 2003, referred to this strategy as an inductive/deductive approach: why, because researchers continually refer to the data to develop and test theory. This strategy, according to Goulding (2002), helps in predicting and explaining behaviours and is geared towards developing and building theory. The strength of grounded theory lies in the generation of theories regarding social phenomena: that is, to develop higher level understanding that is “grounded in, or derived from a systematic analysis of data” (Lingard, Albert & Levinson, 2008). The aim of this strategy is to describe processes rather than test or verify existing theories. Grounded theory is therefore suitable for studies concerning social to social relations or experiences (Saunders et al., 2009). 4.4.4 Case Study Case study is a "systematic inquiry into an event or a set of related events that aims to describe and explain the phenomenon of interest. A case study is “a strategy for doing research which involves an empirical investigation of a particular contemporary phenomenon within its real-life context using multiple sources of evidence” (Robson, 2002; p. 178). Saunders et al. (2009) also describes case studies as a study of a phenomenon in its real context. Yin (2003) defines case study as an empirical inquiry that investigates a contemporary phenomenon within its real-life context, especially when the boundaries between phenomenon and context are not clearly evident. He 48 University of Ghana http://ugspace.ug.edu.gh further adds that a case study allows the researcher to explore individuals or organizations simply through complex interventions, relationships, communities or programs (Yin, 2011). Case study approach is most appropriate for researchers in search of a rich understanding of a phenomenon in a given context and the processes being enacted (Morris & Wood, 1991). Most often than not, a case study is used in explanatory and exploratory research, and it has a substantial capability to generate answers to ‘why’, ‘how’ and ‘what’ questions although what and how questions tend to be more associated with the survey strategy (Saunders et al., 2009). The aforementioned paragraphs highlight the various research strategies that can be espoused in this study. Guy et al. (1987), however, warns that the researcher must be cautious when selecting a research strategy. They suggest that the researcher must consider the unit of analysis, research period, research setting and research purpose before deciding which research strategy will be most appropriate for the research. 4.5 Justification for Research Strategy Drawing from the above discussions, this research adopts the case study strategy and it is inductive. This is because Morris and Wood (1991) postulated that case study approach is most appropriate for researchers in search of a rich understanding of a phenomenon in a given context and the processes being enacted. Thus, since the researcher’s main aim is to gain an in-depth qualitative and quantitative understanding of choice in decision making, the case study strategy is the most appropriate. Creswell (2007) likewise argues that a case study is a good approach when the enquirer has clearly identifiable cases with boundaries and seeks to provide an in-depth understanding of the cases or a comparison of several cases. This is evident in the cases the 49 University of Ghana http://ugspace.ug.edu.gh researcher used as all the respondents are individuals who have used social media to make purchase decisions. As posited by Yin (2011), the case study strategy provides the researcher the liberty to explore and explain a number of respondents through complex interventions, relationships, communities or programs. Last, but not the least, one of the objectives of this study is to understand ‘how’ information overload on social media affect quality of consumer choices, and Saunders et al. (2009) opines that the most appropriate strategy that answers ‘why’, ‘how’ and ‘what’ questions is the case study strategy; hence the choice of the case study strategy. 4.6 Choice of Research Method In any research, the researcher is normally confronted with the choice of method to employ in data collection and analysis. A researcher may choose either a qualitative method or a quantitative method or a blend of both methods (normally referred to as mixed methods). 4.7 Quantitative vs. Qualitative This study is exploratory and explanatory; and in design research, there are two kinds of approaches - the quantitative approach or qualitative approach. Quantitative research refers to the research techniques that seek to measure data and apply some form of statistical analysis. They are mostly explanatory or descriptive. On the contrary, qualitative research is mainly an exploratory design that is unstructured and based on small samples, with the aim of providing insight and understanding. 50 University of Ghana http://ugspace.ug.edu.gh When it comes to making a choice, Malhotra and Birks (2006) point out that assertive positions (i.e., which approach is perceived to give the most accurate understanding of the phenomenon (or phenomena)) are often taken in favour of either qualitative or quantitative research by both researchers and decision-makers alike. Many quantitative researchers are quick to dismiss qualitative studies completely because they believe it provides no valid findings – indeed as being little better than journalistic accounts (ibid). They further assert that qualitative researchers ignore representative sampling, with their findings based on a single case or only a few cases (Malhotra & Birks, 2006). Some qualitative researchers, on the other hand, firmly reject statistical and other quantitative methods as yielding shallow or completely misleading information. They believe that to understand some phenomenon such as cultural values and consumer behaviour, involves interviewing or intensive field observation. Strauss and Corbin (1998) posit that qualitative researchers see qualitative techniques as the only method of data collection sensitive enough to capture the differences in consumer attitudes, motives and behaviour. According to Wilson and Hutchinson (1996), there is a close parallel in the distinctions between exploratory and conclusive research and qualitative and quantitative research. Quantitative research involves the use of structured questions where the response options have been predetermined and a large number of respondents is involved; that is, a large sample and structured questionnaire make up quantitative research. A researcher is able to measure and analyse data as well as establish a detailed relationship between independent and dependent variables using the quantitative approach. This is possible because quantitative research gives room for more objectivity about the findings of the research. It is most appropriate for testing hypotheses in experiments because of its ability to measure data using statistics. However, Burns and Bush 51 University of Ghana http://ugspace.ug.edu.gh (2000) point out that, in quantitative research, the context of the study is ignored. Unlike qualitative research, quantitative research does not study things in a natural setting. Moreover, large samples are always preferred in quantitative research. This is because the larger the sample, the more statistically correct the results will be. On the other hand, qualitative research involves an explanatory and realistic approach to the world. According to Denzin and Lincoln (2005), qualitative researchers study things in their natural settings, attempting to make sense of, or interpret phenomena in terms of the meaning people give them. As a result, qualitative research provides an in-depth examination of the phenomenon in question. It, as well, examines complex questions that cannot be possible with quantitative research. In addition, it is not limited to rigidly definable variables. However, it is very expensive and labour-intensive as well as time consuming to use qualitative research. As a result of its subjectivity, there are procedural problems associated with qualitative approach. This likewise makes replicability very difficult for researchers, not to mention that the qualitative approach is riddled with researcher bias as result of its subjective nature. In spite of all these complexities, this study adopted the mixed method research approach because, according to Creswell (2007), it gives a holistic account from exploratory and explanatory perspectives. In other words, it develops a complex picture of the phenomenon under study. Hence, the qualitative research approach in this study provides a complete account of social media use in decision making, whether information on social media is too much, destructive or information and, lastly, provides an understanding as to whether information characteristics makes a consumer satisfied or not. From the quantitative perspective, the study examines a statistical view of whether 52 University of Ghana http://ugspace.ug.edu.gh choice overload affects quality of choice and whether quality of choice likewise affects decision efficiency. 4.8 Types of Data As identified by Ghauri and Gronhaug (2005), the two sources used in collecting data are primary and secondary sources. Hence, the origin of the data is the main difference between primary data and secondary data (Patzer, 1995). Both can be of extreme importance to a researcher. Malhotra (2007) labelled the type of data invented by the researcher to specifically address the research problem as primary data. It is custom-made just for the imminent problem. Secondary data, conversely, are data collected for some goal other than the problem at hand, but has some significance to the current research (Hair, Wolfinbarger, Ortinau, & Bush, 2008; Malhotra, 2007). Some examples of secondary data include data generated within an organization, information made available by business and government sources, commercial marketing research firms, and computerized databases. Using secondary data is cost-effective and provides a quick source of background information. In contrast, primary data is regarded as more authentic and reliable as well as objective since it has not been published yet (Patzer, 1995). Primary data has a higher validity than secondary data because it has not been altered by anybody. Among the numerous advantages of primary data are greater control of data, address of specific issues, and more efficient budget spending. However, primary data is very expensive and time consuming to collect. Secondary data, on the contrary, is relatively cheaper and easier to obtain but it is prone to distortion and therefore has less reliability and validity value. 53 University of Ghana http://ugspace.ug.edu.gh Thus, the researcher chooses to use primary data in order to avoid distortion and inconsistencies that come with secondary data. Furthermore, although secondary data is cheap, there is no readily available data on how social media user conceives online information in their purchase decisions in the Greater Accra Region of Ghana, hence the researcher’s choice of primary data. 4.9 Population and Sampling Population is the target group the researcher is interested in gaining information from upon which to draw conclusions (Leedy & Ormrod, 2010). The study population serves as a focus of a researcher’s effort (Baumgartner, Strong, & Hensley, 2002). A sample is a subgroup of the elements of the population selected for participation in the study; and a sample frame consists of a list or set of directions for identifying the target population (Malhotra & Birks, 2006; 2007). In this research, the population includes social media users in Ghana, and the sampling frame is individuals who have employed social media as information search tools in their purchase decisions in the Greater Accra Region. The sample therefore refers to the people the researcher selected for the study. As noted by Malhotra and Birks (2006), a number of qualitative elements such as: (1) the importance of the decision; (2) the nature of the research; (3) the number of variables; (4) the nature of the analysis; (5) sample sizes used in similar studies; (6) incidence rates; (7) completion rates; and (8) resource constraints were taken into consideration when determining the sample size; thus, the sample size for this research is four (4). The researcher chose four respondents because, according to Baker, Edwards and Doidge (2012), one respondent is enough provided that that respondent provides the needed information. According to Creswell (2007), between four and five 54 University of Ghana http://ugspace.ug.edu.gh respondents is appropriate for a single case study. On the other hand, the research sampled 249 respondents for the quantitative analysis of the study. 4.10 Sampling Techniques There are the two main types of sampling techniques: probability sampling and non-probability sampling (Malhotra & Birks, 2006). 4.10.1 Probability Sampling Saunders et al. (2009) explain that with probability sampling each member of the population has an equal chance or probability of being selected. In other words, every individual in the population has the same opportunity of being selected. Malhotra and Birks (2006) refer to probability sampling as the sampling procedure in which each element of the population has a fixed probabilistic chance of being selected for the sample. Consequently, probability sampling is often associated with survey and experimental research strategies (Saunders et al., 2009). They further indicated that, across disciplines, four types of probability sampling are generally accepted as standard techniques. These include random sampling (i.e., it refers to the random choosing of an individual or sample from a sampling frame); systematic sampling (i.e., this involves selecting a sample at even intervals from the sample frame); stratified random sampling (i.e., it involves dividing the sample into two or more strata and later using either random sampling or systematic sampling to select from each strata); and cluster sampling (i.e., this involves the division of the population into discrete groups and later selecting the sample from the groups). In probability sampling, sampling units (a single element or group of elements subject to selection in the sample (Zikmund, 1994) are selected by chance. 55 University of Ghana http://ugspace.ug.edu.gh 4.10.2 Non-Probability Sampling On the other hand, non-probability sampling is a sampling technique in which the sampling units are selected based on the personal judgments of the researcher. According to Saunders et al. (2009) and Barnett (1991), there are four different categories of non-probability sampling: (1) quota sampling, which is a two-stage, restricted judgmental sampling. It ensures that the various subgroups of the population will be represented on certain key characteristics to the exact extent that the investigator desires (Zikmund, 1994). (2) Snowball sampling is the type of non-probability sampling where the first group of respondents is selected randomly, and then the second group are selected based on the recommendations of the first group. (3) Judgmental sampling (also known as purposive sampling) is a form of convenience sampling in which the population elements are selected based on the experience and beliefs (what the researcher deems as the appropriate characteristic) of the researcher. Babbie (1990) suggests that the researcher can select based on his/her own knowledge about the population, its elements, and the nature of the research aims. Lastly, convenience sampling is where the researcher obtains the sample units that are most conveniently available to him/her (Zikmund, 1994). The selection of sampling units is left primarily to the interviewer (Malhotra & Birks, 2006). Marshall (1996) explained that researchers use this technique because it is the least costly in terms of time, effort and money. Malhotra and Birks (2006) explain that, often, respondents are selected because they happen to be in the right place at the right time. In this study, the researcher used the non-probability sampling technique (convenience) to select the respondents for both the qualitative and quantitative data. This sampling technique relies on 56 University of Ghana http://ugspace.ug.edu.gh the researcher’s own judgement (Malhotra & Birks, 2007). The researcher used convenience sampling because the sample units are based in Accra and, moreover, the researcher sees some of the people very often. Due to the nature of the study, the researcher chose the respondents based on the fact that they are Ghanaian who use social media information in their purchase decisions. 4.11 Sampling Size As indicated above, the researcher interviewed four males and two females for the qualitative aspect of the study results. Creswell (2007) opined that four respondents and above is adequate for a qualitative approach. Regarding the quantitative section of this study, 249 respondents were sampled for the study. The choice of the sample size was informed by Hair et al (2017) assertion that a minimum of 150 respondents and above should be used for a quantitative approach. 4.12 Data Collection Instrument According to Malhotra and Birks (2007), there are four data collection instruments, viz.; participant observation, personal interviews, telephone interviews and self-administered questionnaires used in collecting primary data. Creswell (2009) likewise identified some common data collection instruments that are exclusive to qualitative researchers. These are interviews, observation, documents, and audio-visual materials. Other scholars add pictures, archival records, and physical artefacts (Miles, Huberman & Saldana, 2013; Saunders et al., 2009; Yin, 2015). Each of these data source brings strength to the findings as these different strands of data are joined 57 University of Ghana http://ugspace.ug.edu.gh together to enable the researcher to understand the entire phenomenon (Baxter & Jack, 2008; Teyi, 2014). 4.12.1 Justification of Qualitative Instrument (Interview) Bhattacherjee (2012) is of the view that qualitative researchers generally employ qualitative methods such as unstructured interviews and participant observation to study a social phenomenon. According to Kajornboon (2005), interviews are systematic ways of collecting information through talking and listening to individuals who may provide relevant data for a research. Interviews can be structured or unstructured and can be implemented with one or more persons. They can also be done over the phone. Creswell (2009) however cautions that the responsibility lies on the researcher to understand and report the meaning that participants give to their experiences, as well as taking measures to restrict the meaning that the researcher would have regarding the issue. Interviews are appropriate to use when you want to know the underlying reasons for respondents' standpoint. Patton (2002, p. 278) opined that the “purpose of interviewing is to find out what is in and on someone else’s mind”. Thus, the researcher used personal interviews to collect data in order to: a) To explore how consumers use social media tools in decision making by consumers b) To find whether there is information overload on social media. c) To investigate whether social media information support consumer decision making. 58 University of Ghana http://ugspace.ug.edu.gh In the qualitative data collection, since “the quality of the information obtained during an interview is largely dependent on the interviewer” (Patton, 1990, p. 279), the researcher employed the semi- structured in-depth interview, with questions drawn from the interview guide (see Appendix 1) for the study. In the process, some additional information were volunteered (Baxter & Jack, 2008). Furthermore, the interviewer started with some pep talk to break the ice, and just before the interview began, the interviewer asked permission to record the interview and assures them of utmost confidentiality. As much as possible, the interviewer used simple English that the interviewees would understand. To ensure that accurate responses were captured, the researcher periodically asked for clarification and confirmation. The interviewer ensured a cordial atmosphere by not showing disapproval nor personal opinions for any of the answers. This made the respondents feel at ease and ready to provide the information needed for the study. The researcher used a smartphone to record the interview proceedings and paused anytime there were interruptions. This is because all but one of the interviews took place in the respondents’ offices. This made the respondent feel comfortable knowing that their normal business dealings were off record. Manual records were also taken as back-up, because the second interview had to be redone because some phone calls interrupted the recordings (i.e., it automatically stopped the recording on the phone. After that experience, the phone was put on flight mode before commencing all the other interviews. After each interview session, the researcher thanked the respondent and reassured them of confidentiality after which interviewees chatted informally with the researcher on life and business issues. 59 University of Ghana http://ugspace.ug.edu.gh After the interviews, the researcher transcribed all the recordings. It was a tedious and time- consuming process; however, it was necessary as it enabled the researcher to become familiar with the scripts and made analysis more effective. On the quantitative data, the research screened the data after it was entered into SPSS where Structural Equation modelling was used to perform the statistical analysis. 4.12.2 Justification for research instrument Structured questionnaires were chosen because they are deemed suitable for gathering a large amount of accurate and reliable data (Bushiri, 2014; Saunders, et al., 2011). Similar studies on social media have depended largely on questionnaire as a reliable instrument to give accurate research data (Chang et al., 2015; Christou, 2015; Enginkaya & Yilmaz, 2014). The questionnaire instrument allows a respondent to skip some questions, reflect over questions and come back to them later to fill in the answers. In a survey research a large sample/data (Glasow, 2005) is required, “large enough to yield the desired level of precision” (Salant & Dillman, 1994). The research employed a structured questionnaire to examine objective four (4) a) To examine the impact of choice overload on the quality of choice and the extent of the effect of quality of choice on post purchase dissonance. The questionnaire was divided into four (4) distinct sections numbered (A) – (D). The first part of the questionnaire sought to ask respondents to provide demographic data such as age, gender, education, and type of social media used. Sections (B) sought to elicit information on the information choice overload. (C) elicited information on the quality of choice and Section (D) asked respondents the degree of effect of quality of choice on post purchase dissonance. 60 University of Ghana http://ugspace.ug.edu.gh The set of items were structured using the Likert-scale format with a five-point response scale ranking from the lowest 1 –Strongly disagree (SD), 2 – Disagree (D), 3 – Neutral (N), 4 – Agree (A), to the highest 5- Strongly agree (SA). Closed ended questionnaire was used because it is known to provide control over the participant’s range of responses by providing specific response alternatives (Borden & Abbott, 2002). 4.13 Data Analysis 4.13.1 Qualitative Data Creswell (2013) suggests that the type of qualitative research strategy will determine the type of analysis that will be carried out. For instance, in ethnographic studies the most appropriate form of analysis is the conversational analysis; and in grounded theory research, the most appropriate data analysis is coding. For case studies, either content analysis or thematic analysis can be used to analyse the data gathered; however, Saldana (2009) is of the view that thematic analysis is appropriate for all qualitative studies. Therefore, this study employs the case study strategy to data analysis in analysing data collected from the interviews. The qualitative analysis aims to highlight the underlying pattern and processes that exist in the data by finding the leading words explaining the content (Miles, Huberman, & Saldana, 2013). The analysis was conducted based on the thematic qualitative process; the pattern of leading key words comes from the theory and secondary data. Thus, by transcribing the interview and establishing the connection with the questions, relevant data is drawn. The following coding was therefore used for the transcription. The first respondent was coded as RA, the second respondents named as RB, the third respondent was identified as RC; the fourth respondent was coded as RD, 61 University of Ghana http://ugspace.ug.edu.gh the fifth respondent was coded RE, while the last respondent was coded RF. The interviewer was coded as I (interviewer). Data analysis is a systematic process of selecting, categorizing, comparing, synthesizing and interpreting data to provide an explanation to a single phenomenon of interest (Macmillan & Schumariacher, 1997). The responses from the questionnaires were edited, coded and entered into Statistical Package for Social Science (SPSS) version 20.0 for analysis. This statistical software was recommended for use in studies in social sciences (Zickmund, 2000). 4.13.2 Quantitative Data For the quantitative analysis, SPSS was firstly used to analyse the demographic responses of the respondents. The SPSS software has been used extensively by various researchers in quantitative study in analysing data (Banerjee, 2012). This data was analyzed and interpreted with descriptive statistics such as the use of mean, and frequency count (Guilford & Frutcher, 1996). Second, Structural Equation modelling was used to test the hypotheses/structural path relationship. SEM was adopted for the study because it analyses complex models and provides more robust results (Hair et al., 2008). Similar empirical investigations have employed Structural Equation Modelling (SEM) to analyse their empirical data (Chang et al., 2015; Enginkaya & Yilmaz, 2014; Hudson et al., 2015; Kang & Schuett, 2013) as it is considered to be a more robust tool for analysis. Before performing the actual analysis of the main data, preliminary data analysis was done. During the preliminary data analysis (PDA), datasets and variables were cleaned and cleansed (Ainim, Darani, Afshani & 62 University of Ghana http://ugspace.ug.edu.gh Amini, 2012) to eliminate unengaged responses and correct errors that could skew the research findings (Coakes, 2006). Exploratory factor analysis was done to explore the data to ensure that the data is fit and adequate for the study. Confirmatory factor analysis was then done to ensure that the data meet the reliability and validity significance. Several tests including validity, reliability, and factor loading were used under the confirmatory factor analysis. After the confirmatory factor analysis, the study moved to assess and test the hypotheses using structural equation modelling. 4.14 Pre-Testing Quantitative Instrument The research instrument was pre-tested on a small sample of students in Accra. A sample size of fifteen (15) students was used for the pre-testing. The sample size for the pre-testing was chosen based on Saunders et al. (2007) who indicated that a minimum of ten (10) respondents is adequate for pre-testing. The researcher explained the purpose of the study to each respondent before the research instruments were administered. Respondents were assured of anonymity and confidentiality of responses before they were given the questionnaire to respond to. After pre- testing, adjustments were made to obtain a more effective construct to be administered on the sample size. 4.15 Validity and Argument Reliability of Qualitative Study The appropriate steps were taken to ensure both content and construct validity. In accordance with Si and Bruton (2005), the researcher shepherded a face-to-face interview with all the respondents and furthermore transcribed exacted as recorded. In addition, a summary of the findings were given to all respondents to confirm that they had been well represented, and to invite suggestions 63 University of Ghana http://ugspace.ug.edu.gh (Goodwill, Mayo, & Hill, 1997). Therefore, the researcher can confidently defend the credibility, reliability and validity of the results. 4.16 Ethical Considerations As recommended by Miles and Huberman (1994), ethical considerations are paramount and the onus lies on the researcher to be sincere with respondents, and to treat the confidential information appropriately. These factors were adhered to during the data collection process. In accordance with this, the researcher allowed the respondents to take part in the research voluntarily (meaning, they were neither forced nor threatened to join in the research), and ensured that participants were not harmed in any way. Verbal permission was sought from each respondent before any digital recording was done. In all, participants were assured that the study is for academic purposes only. Furthermore, the privacy of all the respondents was protected as codes were given to them to conceal their identity. 64 University of Ghana http://ugspace.ug.edu.gh CHAPTER FIVE DATA ANALYSES AND DISCUSSION OF RESULT 5.0 Introduction This current chapter of the study presents both the qualitative and quantitative results that emerged from the field work. The first section of this chapter presents the result from the qualitative interview followed by discussion of the interview results. The second section of the chapter presents the quantitative results. The analysis of the quantitative results commences with the descriptive statistics of the respondents. Afterwards, confirmatory factor analysis and Structural Equation Modelling were employed to analyse the quantitative results. Reliability and validity tests were conducted in order to determine the suitability of the measurement items and constructs used in the work. The chapter concludes each section with a discussion of the quantitative and qualitative interview results and then presents a summary of the entire chapter. 5.1 Analysis of Objectives It is important to recall that this current study formulated four objectives to examine: 1) How consumers use social media tools in decision making; 2) To examine whether there is information overload on social media; 3) To investigate whether social media information support consumer decision making. Qualitative methodology was employed to achieve these research objectives. Research objective four (4) examined the effect of choice overload on quality of choice, and how quality of choice affects post purchase dissonance. Two research hypotheses were formulated from this objective of this study. 65 University of Ghana http://ugspace.ug.edu.gh 5.1.1 Analysis of Qualitative Data Table 5.1 presents the demographic information of the six respondents interviewed. These six respondents have used social media to make purchases and other useful decisions. Table 5.1: Profile of Respondents Participant Sex Age Marital Education Years on SM Status RA Female 27 Married First Degree 5 RB Female 29 Single Professional Qual. 7 RC Male 42 Single Professional Qual. 5 RD Male 27 Single Second Degree 6 RE Male 31 Married First Degree 4 RF Male 27 Single Post Graduate 8 Source: Field Survey (2018) Table 5.1 shows the demographic characteristics of the six respondents who were engaged in the study. First, it emerges from the study that the majority of the respondents have a sufficient educational background to understand the research issues, thus being able to provide an appropriate answer. Furthermore, the results elucidate that the respondents have spent a considerable number of years on social media. This characteristic was important because it provides justification that consumers understand how to search for information on social media to make purchase decisions. Additionally, even though there were four males compared with two females, the skewness of the gender did not affect the direction of the findings. 66 University of Ghana http://ugspace.ug.edu.gh Objective 1: How consumers use social media tools in decision making Objective one asked respondents to indicate how they use social media tools in their decision making. It emerged from the responses that social media is one of the common platforms used to make informed decisions. Respondents indicated that traditional modes of searching for product information are no longer relevant to them. It rather delays time, and limits the types of decisions they make. For instance, the respondents mention that relying on traditional media such as billboards, TV and radio does not give them information to make decisions at the time they want. They need to wait for these traditional media to make adverts on them before they can get the information they need. Even with the above mentioned, such information may not be very relevant to aid decision making. Actual responses from the respondents are presented below: Respondents RA: “… I needed to actually go to the hospital but did not have the money and I did not have insurance as well, and I needed to get information on what medicine I needed to by. I have this WhatsApp group with doctors and nurses. What I did was that, I sent a message to my WhatsApp group concerning my health and the information I need on the drug I have to take. I can tell you that, it did not take me a second for me to get my responses. Based on the feedback I received from the WhatsApp page, I was able to go and buy the medicine I needed and I was very much okay. So it helps me in taking my decision on what to do”- RA Respondents RB: “Since I need a second opinion, I just go and search for whatever I am looking for and then with what I have in mind and what is there I compare or I add and then I do my decision”.-RB 67 University of Ghana http://ugspace.ug.edu.gh Respondents RC: “ hmmmm.. eer, I think I would use the football. There are times, you are like ok a couple of them, there is no need to watch the whole match again. It’s a done deal, and with this course I am doing too, they are very active on twitter let’s say u’ve got four weeks to an exams. Weekly or daily updates on say, want to motivate, prepare you to whatever you are doing. So let say a day, each and every day, 2 questions, 3 questions on the platform on the handle for you to try your hands on where ever you are, like look at this, look at this”.-RC Respondents RD: “… I actually needed some information on an App to download. So I went to the reviewers comments where many people had written their views concerning the App. So based on what I saw, I used that and made my decision on whether to download the App or not. I can really say that social media helps me to take decisions”-RD Respondents RE: “I normally use social media for some staff. Whenever I want to buy something like watch or mobile phone I go to YouTube and Facebook to read some information about it. I use social media a lot and every day I read something there”. – RE Objective 2: To examine whether there is information overload on social media Objective two of this research examined whether consumers consider information on social media as too much. It appears from the responses that social media does not provide too much information 68 University of Ghana http://ugspace.ug.edu.gh to them, but rather provides information at the right time. They mention that information provided by other participants on social media platforms are not too much. They are satisfied with the information they get though some users such as “bloggers” may post something that is not reliable just to get the attention of readers. For example: Respondent RD says that: “oh I cannot quantify that information is too much or not. I rather see social media as very informative as it helps me to get all the necessary items I need concerning my studies, to the extent of getting past questions from there”. - RD Also, RA affirms that: “Information provided on social media is not too much at all. It gives me the information at the right time. For instance, during the rainy season, it gives me idea about whether it will rain or not. It just provides me with daily information. I rather say information provided by them is very adequate rather than too much”. -RA Also, RC put that: “I think it’s not being controlled, I won’t say it’s too much”- RC RF further stated that: “…I think some people put unnecessary stuff there which makes reading very difficult. I know sometimes people put some good stuff there “burr” you have to know what information you want and just read what you want to read”. - RF 69 University of Ghana http://ugspace.ug.edu.gh Objective 3: To investigate whether social media information support consumer decision making Objective three of this current study explored whether information on social media is useful (quality or not) in their decision making. Responses from the study indicate that social media is considered as more informative than distractive. Consumers mention that social media provides more information than distracting them. Respondents similarly indicated that they get information very fast and on time although they do not really rely on the information too much. Most of the respondents mention that they become very knowledgeable with the information they receive to the extent they forget if it distracts them or not. They moreover highlighted that they do not read all information they receive from social media but select the most relevant ones. This is what RB says to buttress this assertion: “ errm, using social media does not distract me at all. It rather informs me on what is trending. Though sometimes, you will be doing something different while an information pops up, to distract you from what you are reading, you come to realize that it is equally important to read that message too”. - RB Social media has become the order of the day where most people utilize it to search for information and make purchase decision. Since most of the respondents are in their youthful ages and mostly students, the probability that social media informs them to learn is higher than it being distractive. 70 University of Ghana http://ugspace.ug.edu.gh RC had this to say: “Yes, I really love using YouTube for my daily information. There has not been a day that I have complained that it is disturbing me or something” - RC Responses appear to suggest that information on social media is very help but some can be destructive. It is therefore important to note that consumers have a choice and a purchase decision to make and therefore they must search for information, which includes considering alternative sources of information. To further support the contrary findings in this objective, Respondent RF had this to say: “…some information on social media is very good and some are not relevant. But, I don’t seen information on social media as destructive but rather very helpful” - RF 5.2 Discussion of Findings How consumers use social media tools in decision making This current study found that consumers utilise social media information during decision making. From the interview results, majority of respondents reported that they have used social media extensively in various decisions that they have taken. Respondents noted that there is a social media group that comprises of medical doctors and nurses. Importantly, respondents indicated that they use social media for first aid information from this page. Other respondents indicated that they use social media platforms to search for whatever item they want. Respondents noted that, in effect, social media has become an important tool for consumer decision making. 71 University of Ghana http://ugspace.ug.edu.gh This finding from this current study support the finding of Hawkins and Mothersbaugh (2010) and Agresta and Bough (2010) who found that social media has become an important external source that consumers use to search for information in contemporary times. Similarly, the work of Chandra, Goswami and Chouhan (2013), Patino, Pitta and Quinones (2012) and He and Zha (2014) support the findings that the traditional media has become obsolete and irrelevant and therefore consumers are always exploring and utilising online information because it helps them in their decision making. The paradigm shift from traditional media to social media can partly be explained by the fact that the traditional media are not controlled, thus users cannot modify it to suit the needs of consumers. With current social media like Twitter, WhatsApp, Facebook, Yen.com, YouTube etc., you only type in the information you want and you are there. This partly explains why the majority of the responses indicated that they use social media platforms extensively in their decision making. Another reason for the high acceptance of social media is that all the respondents using social media to make decisions are in their youthful age where they resort to social media as their source of information. To examine whether there is information overload on social media Objective two investigated whether there is information overload on social media. Interview results show consistency in consumers’ views regarding the content on social media. The results showed that SM platforms such as Twitter and Facebook provide a vast amount of information for users. It has emerged from the interviews that SM provides information that helps users make informed decisions. Respondents recounted that information they receive on social media is not too much. Despite the convergent view about social media content, the interview results further 72 University of Ghana http://ugspace.ug.edu.gh noted that there are instances when some users post irrelevant content to generate attention. This presented mixed findings about the sufficiency and amount of information that consumers post on social media. The high rate of irrelevant material can partly be explained by the type of social media and the nature of information that consumers seek. Some social media platforms like LinkedIn is used for professional connection, thus users may not post irrelevant content. On the other hand, social media platform such as Facebook and WhatsApp can be an avenue for large amounts of irrelevant contents that may not be needed by the users. Consumer choice is impacted by the volume of gathered information from various sources on social media; hence, consumers require more information (Hawkins & Mothersbaugh, 2010). Literature explains that consumers have to cope with information overload as a result of multiple information sources and many daily decisions (Scammon, 1977; Jacoby, 1984). Findings from this current study is contrary to this finding to the effect that there is no information overload on social media. Even though consumers require adequate information to make choices, the study results espoused that consumers have the option to choose a particular social media platform and the tools they require and the information they wish to read or use. This, therefore, means that consumers will not be overloaded with information. The findings from this study support the work of Kotler et al. (2009), who found that consumers on social media can reduce the uncertainty and negative effects of risk by gathering enough information. In view of this, our findings support the view of Kotler that marketers must understand the factors that account for consumer risks and provide enough information to minimise perceived risks that consumers encounter in the information search and choices. 73 University of Ghana http://ugspace.ug.edu.gh Investigate whether social media information support consumer decision making Objective three of this current study examined whether social media content or information provides support for consumer decision making. This study sought to examine whether content on social media is informative or destructive in decision making. Following from the previous interview question, this current objective found that social media content is informative and helps users in their decision making. Respondents further indicated that they receive quick responses from other users whenever they want information to make a decision. Responses further noted that social media platforms such as trending YouTube provides quality information that is always helpful in daily lives. It likewise emerged from the findings that there are often “pop-ups” while reading some contents but such pop-ups are equally important. Essentially, these findings support previous studies from the literature. Our findings support the work of Bhatnagar and Ghose (2004) who concluded that the frequency and quality of SM content helps consumer information search, which affects decision- making. Their study added that, when consumers accumulate enough information during their search, they are able to gather the best and quality information, which helps consumer choice and decision-making. In effect, this finding reveals that social media content is of good quality and consumers appreciate the amount of information in the content. 5.3 Analysis of Quantitative Data It is recalled that this current study is a mixed methodology. The quantitative dimension of the study sought to investigate the effect of information overload (choice overload) on Quality of 74 University of Ghana http://ugspace.ug.edu.gh choice and the effect of quality of choice on post purchase dissonance. Two hypotheses were formulated from objective four of this study: H1: There is a positive relationship between choice overload (ChoiceOverload) in social media and choice quality (ChoiceQual). H2: There is a positive relationship between choice quality (ChoiceQual) in social media and post purchase dissonance (PPD). 5.3.1 Data Screening According to Saunders et al. (2009), there are a number of activities that must be undertaken after data has been collected before the commencement of the analysis. The data was inputted into the Statistical Package for Social Sciences (S.P.S.S.). The researcher coded and screened the data in order to correct errors and to eliminate missing values in the data. The activity was done to eliminate inputs that could skew the research findings (Coakes, Steed & Dzidic, 2006). Two hundred and forty-nine questionnaires were considered fit for imputation and subsequently used for the quantitative analysis. 5.3.2 Profile of Respondents According to Pallant (2011), one of the fundamental statistical analyses is the demographic analysis, which must be undertaken before data is subjected to further validation analysis. Descriptive statistics provide a measurement of central tendency. Table 5.2 below presents the descriptive statistics of respondents. 75 University of Ghana http://ugspace.ug.edu.gh Table 5.2: Descriptive Statistics of Respondents Profile of Respondents S t a t e m e n t Freq. % Gender Specifications Male 128 51.4 Female 121 48.6 249 100 Age categories of Respondents 18-23 193 77.5 24-28 29 11.6 29-34 23 9.2 35-39 1 0.4 40+ 3 1.2 249 100 Educational Status Senior High 6 2.4 Diploma 3 1.2 Degree 202 81.1 Post-Graduate 38 15.3 249 100 Employment Status Student 140 56.2 Employed 68 25.3 Self-employed 41 16.5 Unemployed 5 2 Retired 0 0 249 100 Social Media Platform Usage Yes 249 100 No 0 0 249 100 Social Media Platform Mostly Used Facebook 212 85.1 Twitter 27 10.8 Instagram 7 2.8 YouTube 3 1.2 249 100 Frequency of Social Media Usage Daily 217 74.8 Once a Week 7 6.2 More than Once a Week 20 13.9 Once a Month 1 3.2 More than Once a Month 6 1.9 How long have you been on social media Less than one year 146 58.6 1-5 24 9.6 6-10 30 12.0 11-15 10 4.0 15+ 39 15.7 Source: Field Survey (2018) 76 University of Ghana http://ugspace.ug.edu.gh From Table 5.2, the analysis of responses from 249 valid responses showed that there were 128 (51.4%) males and 121 (48.6%), which indicates that the majority of the respondents sampled for the study were males. The results therefore mean that the minority of clients surveyed are females. In effect the skewness of gender of respondents did not affect the direction of the responses and the outcome since the gap between male and female was just 7 respondents. Out of 249 respondents, the majority (193 representing 75%) of respondents surveyed are within the ages of 18-23, followed by 29(11.6%) who are within the ages of 24-28. The result showed that 1(0.4%) respondent was within the ages of 35-39. The implications of this demographic element is that the majority of the respondents are very youthful within the ages of 18 and 34. This shows the use of social media is mainly engaged by the youth. In terms of educational background, the majority (202 representing 81.1%) of the respondents have completed their first degree. The diploma level had the lowest level of participation with 3 respondents representing 1.2% of the sample size. This result elucidate that the majority of respondents have a sufficient educational background to answer the research questions properly. The result also showed varied employment levels as well. The findings indicated that the majority of the respondents (140 representing 56.2%) were employed while 5 (2%) were unemployed. A total of 180 respondents representing 58.1% were salaried workers. The findings also revealed that 50 respondents of the sample representing 16.1% were self-employed. There were 5 respondents who were retired workers representing 1.6% of the respondents. Four social media platforms were considered for the study based on the recommendations of scholars such as Duffet (2015) and Hennig-Thurau et al. (2010) that studies should be conducted 77 University of Ghana http://ugspace.ug.edu.gh into several social media platforms. The social media platforms were Facebook, Twitter, Instagram and YouTube. The selected platforms were based on responses from the pre-testing responses. All of the 249 respondents indicated that they use social media for various purposes: 212 respondents representing 85.1 per cent mostly used Facebook platform; Twitter was the second ranked social media platform mostly used with 27 respondents representing 10.8 per cent; Instagram had 7 respondents representing 2.8% was the third mostly used platform; and YouTube was the least used social media platform among the respondents with only 3 of the respondents representing 1.2% mostly used YouTube. Most of the respondents used social media platform daily. This is because, 217 respondents representing 74.8% used social media on a day-to-day basis. This confirms the findings of Tuurosong and Faisal (2014) that most subscribers of social media in Ghana use it daily. The implication of these demographic elements was to give a full appreciation of the respondents and to assess whether their responses has any effect on the final outcome of this study. 5.4 Confirmatory Factor Analysis (CFA) The principal component analysis was conducted based on the responses of the 21 scales on the Likert scale with the aid of SPSS version 20. Kaiser (1970) asserted that the suitable value for the Kaiser-Meyer-Olkin (KMO) should be 0.6 or above. The value for the KMO was .827. Bartlett’s Test of Sphericity (Bartlett 1954) reached statistical significance (Approx.: Chi-square= 2007.266, df. 171, sig. 0.000), which aided in the correlation matrix being factorised. 78 University of Ghana http://ugspace.ug.edu.gh Table 5.3: KMO and Bartlett’s Test Results Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .827 Approx. Chi-Square 1244.515 Bartlett's Test of Sphericity Df 91 Sig. .000 Source: Field Survey (2018) Table 5.4: Validity and Reliability Test Construct Average Reliability Variance (CR) Extracted Principal Component Loadings Internal Consistencies ( A V E ) Variance Cronbach's Items V ariables Varimax Explained Alphas Factor 3 ChoOv1 0.659 54.475 0.720 0.734 0.411 ChoOv2 0.662 ChoOv3 0.723 ChoOv4 0.717 ChoOv5 0.632 Factor 4 QoC1 0.727 64.892 0.818 0.821 0.537 QoC2 0.841 QoC3 0.723 QoC4 0.779 Factor 5 PPD1 0.749 57.846 0.813 0.819 0.532 PPD2 0.793 PPD3 0.812 PPD4 0.761 PPD5 0.600 Source: Field Survey (2018) Data dimension or reduction was done in order to drop some scales or items that were inappropriate for further analysis in the research. As a result, a rotated component matrix was undertaken and 79 University of Ghana http://ugspace.ug.edu.gh the threshold was set at 0.5. All variables loaded well and none of them fell below 0.5. Table 5.5 indicates the various constructs and the result shows that all the fourteen (14) measurement scales loaded very well. The reliability measures in this study are above the acceptable satisfactory levels (Cronbach’s alphas > .70, Average Variance Extracted > .50, composite reliability > .70) as recommended by scholars (Fornell & Larcker, 1981). Furthermore, the factor loadings (ranging from 0.61 to 0.87) showed good convergent validity. The retained scales or items met the threshold for Cronbach alpha of 7.0. According to Cronbach (1951), the Cronbach Alpha value should be 7.0 or above before a data collection instrument can be deemed reliable. Reliability is defined as the degree to which measurement duplicates outcomes that are consistent if the procedural measurement steps are repeated (Malhotra & Birks, 2007). Table 5.5: Discriminant Validity Factor CO QoC PPD CO 0.641 QC 0.328 0.730 PPD 0.353 0.198 0.733 Source: Field Survey (2018) There were no validity concerns. The table above presents the validity test results after model fit for the final measurement model. CO, QoC and PDD were the constructs used in the study with fourteen measurement scales. After the reliability and validity test, the indicators of the final three 80 University of Ghana http://ugspace.ug.edu.gh constructs with their correlations are displayed above. Thus, the three constructs were considered fit for analysis. Figure 5.1: Final Measurement Model Source: Field Survey, (2018) The final measurement model was achieved after some items were deleted. Choice Overload represent Choice Overload, ChoiceQual represents Choice Quality and Post_Pur_Disson represents post purchase dissonance. Choice Overload is the construct for the independent variable. Choice Quality is the mediating variable. Post Purchase Dissonance is the dependent variable. Table 5.7 shows the fit indices. 81 University of Ghana http://ugspace.ug.edu.gh Table 5.6: Table Model Fit Measures Measure Estimate Threshold CMIN 145.278 -- DF 73 -- CMIN/DF 1.990 Between 1 and 3 CFI 0.939 >0.95 SRMR 0.060 <0.08 RMSEA 0.063 <0.06 PClose 0.074 >0.05 Source: Field Survey (2018) Table 5.7: Cut-off Criteria Measure Terrible Acceptable CMIN/DF > 5 > 3 CFI <0.90 <0.95 SRMR >0.10 >0.08 RMSEA >0.08 >0.06 PClose <0.01 <0.05 Source: Hu and Bentler (1999) 5.5 Analysis of Study Objectives Using Structural Equation Model In this research work, four research objectives were formulated to examine the cause-effect relationship between digitalisation and performance of SMEs. Two Hypotheses (H1 and H2) were formulated to test the effect of three constructs: the relationship between choice overload and quality of choice (H1) and the effect of quality of choice on post purchase dissonance (H2). The results of the data analysis using Structural equation modelling are presented in Figure 5.2. 82 University of Ghana http://ugspace.ug.edu.gh Figure 5.2: Structural Equation Model for Choice overload, Quality of Choice and Post- Purchase Dissonance Source: Field Survey (2018) Hypotheses: Two main hypotheses were formulated as: H1: There is a positive relationship between choice overload (ChoiceOverload) in social media and choice quality (ChoiceQual). H2: There is a positive relationship between choice quality (ChoiceQual) in social media and post purchase dissonance (PPD). The final model was assessed for fit indices, which showed: CMIN=4.597, DF=4, CMIN/DF=1.149<3,CFI=0.996, SRMR=0.034<0.08, RMSEA=0.022<0.06, PClose=0.649>0.05, GFI=.995, TLI=987, IFI=.997, NFI=.975, RFI=.905. Table 5.9 below provides a summary of the results from the SEM. 83 University of Ghana http://ugspace.ug.edu.gh Table 5.8: Summary of Structural Equation Modeling Result Relationship Construct β t- p- Outco (Hypothesis) Structural SE Estimate Values Values me Relationship Effect of Choice Overload on Choice Quality Hypothesis 1: Choice_Overload---> Support 0.368 0.062 6.228 *** Post_Purchase_ Dissonance ed Choice Overload and Post Purchase Dissonance Mediated by Choice Quality Hypothesis 2: Choice_Quality--- Support Mediation 0.247 0.55 4.008 *** >Post_Purchase_Disonnance ed Effect Indirect Effect 0.091 *** Source: Field Survey (2018) Analysis of Hypothesis One (H1): Choice Overload and Quality Choice Hypothesis one of this research investigated the effect of choice overload on quality of choice. Table 5.9 shows the structural equation results of the first hypothesis. The study results elucidate a significant effect of choice overload on quality of choice (H1: t=6.228, β = 0.368, p=0***<0.05). This result therefore means that hypothesis one of research objective one is confirmed. In effect, this result suggests that using too much or less information on social media influences the quality of choice that people make. For instance, excessive information of Facebook that is generated from discussions, send quick and simultaneously shared contents (Eskisu et al., 2017) significantly influencing the user’s ability to recognise and make quality choice of information that s/he needs. 84 University of Ghana http://ugspace.ug.edu.gh This finding resonates with previous studies that have found too much information on social media such as Facebook influences the quality of choice that people make through the social media platform (Nguyen et al., 2015). The findings confirm the assertion made by Kim and Ko (2010) and Duffet (2015) that using Facebook, as a social media tool to engage clients, positively influences the credibility of information about the brand and the organisation. This finding likewise resonates with the work of Andrews (1989) and Taylor, Lewin and Strutton (2011) who found that advertisement information is valuable to consumers if it is consistent with the product that it displays. Findings of this study further confirms the work of Gao and Koufaris (2006) who argued that businesses that engage in transactions electronically through the use of websites have identified the provision of relevant information essential in the formation of the attitudes of consumers. This assertion is also shared by Taylor et al. (2011) who argued that, within the social networking environment, adverts with adequate information eventually leads to the development of word-of-mouth comments by consumers. Analysis of Hypothesis Two (H2): Choice Quality and Post Purchase Dissonance The second hypothesis investigates the extent of influence of quality of choice on post purchase decision (H2). Table 5.9 shows the structural equation results. An analysis of field data showed a significant influence of quality of choice on post purchase dissonance (H2: t= 4.008, β = 0.247, p=***<0.05). The statistics here means that hypothesis two, which sought to investigate the effect of quality of choice on social media influence on post purchase dissonance, was confirmed. The result therefore means that quality of choice on social media positively influences post purchase perception. In effect, this finding implies that, when social media information is clear and 85 University of Ghana http://ugspace.ug.edu.gh moderate, consumers are able to make a quality choice of what they want, which negatively affect their after-purchase decision. This finding supports previous works that showed that social media allows interactions about brands and helps consumers to obtain the requisite information in relation to various products, and eventually it affects their decision on whether to buy a particular brand or not (Kozinets et al., 2010). Findings from this hypothesis is consistent with earlier studies such as Duffett (2015) who found that quality information on social media platforms such as YouTube platforms significantly drive how customers perceive the brand, either positively or negatively. Literature generally agrees that that quality of information content that is placed in social media sites play a very significant role because customers base their future decisions on that (Lee & Hong, 2016). 86 University of Ghana http://ugspace.ug.edu.gh CHAPTER SIX SUMMARY, CONCLUSIONS AND RECOMMENDATIONS 6.0 Summary This thesis investigated the effect of choice overload on quality of consumer choices and post purchase dissonance. Four research objectives were formulated that involved three qualitative questions and one quantitative question. Objective one assessed how consumers use social media tools in decision making. Objective two assessed whether there is information overload on social media. The third objective examined social media information support consumer decision making. The last objective examined how social media information impact on quality of choice and post purchase dissonance. In this study, objective one, two and three were analysed using the qualitative approach, while objective four was analysed using the quantitative approach. From objective four, two hypotheses were formulated (H1: H2). From this study, the results showed that social media consumers consider social media to be a useful information platform that helps in decision making. From the qualitative result, the findings showed that social media platforms such as Facebook and WhatsApp provide quick responses, share relevant content and quick notifications help SM users to make prompt decisions. From objective two, the results showed that information or content on social media is not too much despite some cases of “irrelevant” content. It has emerged from the findings that students use SM to share and communicate information about their exams and classes, which helps them in their academic exercise. 87 University of Ghana http://ugspace.ug.edu.gh Regarding the third objective, the analysis of qualitative field data showed that there is no information overload on social media. Consumers elucidated that social media information is not quality (informative). Essentially, the result summarises that engaging other social media users’ SM platforms provides adequate and essential information for decision making. The result further espoused that users do not always read information; hence they are able to leave out irrelevant content that other users post on the platforms. On hypothesis one of objective two, the results showed that there is a significant effect of choice overload on quality of choice. The results summarise that information on social media platforms such as twitter and Facebook are moderate and clear, which helps users to make quality choices. On hypothesis two of study objective two, the results showed that moderate information on social media significantly influences the quality of choice, which significantly drives positive post purchase dissonance. This result summarises that, when information on social is moderate, it drives quality of choice in decision making, which subsequently creates positive post purchase dissonance. The study used a mixed method approach to achieve its objectives. Qualitative methods were used to analyse the qualitative data. The study employed a case study design, mixed methodological approach and convenience sampling technique to select 6 respondents for interview and 249 for quantitative Structural Equation Modelling. 88 University of Ghana http://ugspace.ug.edu.gh 6.1 Conclusions Based on the summary of the study, the following conclusions were arrived at: From objective one, the study concludes that social media platforms such as Twitter, Facebook, Instagram and WhatsApp provide useful information, relevant to social media users to make informed decision. This conclusion is reached as a result of the qualitative responses that, social media give instant responses to questions that users post on the various platforms. Based on objective two, the study concludes that social media information is not too much, nor is it too complex. Consumers consider SM information as sufficient for their information needs. Even though some users post irrelevant information, readers have the option whether or not to read the post. From objective three, the study concludes that the social media information is not distractive. The study concludes that social media provides informative content to help purchase decisions. On objective four, the study concludes that choice overload (or too less) information on social media positively and significantly influences quality of choice. Again, the study concludes quality of choice drive positive post purchase dissonance. 6.2 Recommendations Based on the findings from this project, the following recommendations are made for policy direction. Firms that use social media platforms to advertise their brand must focus on crafting content that is creative and informative in order to influence the decisions that consumers make on social 89 University of Ghana http://ugspace.ug.edu.gh media. According to Maria and Carlos (2014) advertising content on SM must be relevant and worthwhile in order to have a significant impact on consumers. Sales and marketing managers must improve their interactivity and engagement with their clients on Twitter and Facebook in order to improve them make quality choice. If no skilled personnel exist, social media engagement experts can be engaged to keep their twitter and Facebook account active in order to provide clear and simple content that will help consumers make quality choices. Studies on social media have helped firms to know and better understand the consumer because it provides answers to very pertinent questions on SM. This current study has provided some answers to questions such as why consumers use social media content, how they use information and why consumers make such decisions based on the context. These answers are important because they provide immense benefits to various firms who advertise on social media so as to develop proper plans and superior strategies to help online shoppers. In relation to the findings of the study, the researcher recommends that organisations should not only limit information about the organisation to only their corporate platforms, such as, websites. There should be extensive release of such information on social media platforms as well. 6.3 Future Research Direction It is suggested that future studies may consider employing specific social media platforms since this study used the four main SM tools (Twitter, YouTube, Facebook and Instagram). This will give specificity to the application of the findings. Additional future research can also focus on the 90 University of Ghana http://ugspace.ug.edu.gh social media content of specific organisations in order to narrow the findings to give it a more precise meaning to organisations. 91 University of Ghana http://ugspace.ug.edu.gh REFERENCES Adams, G. R., & Schvaneveldt, J. D. (1991). Understanding research methods. Addison-Wesley Longman Ltd. Agarwal, N., & Yiliyasi, Y. (2010, November). Information quality challenges in social media. In International Conference on Information Quality (ICIQ) (pp. 234-248). Agichtein, E., Castillo, C., Donato, D., Gionis, A., & Mishne, G. (2008, February). Finding high- quality content in social media. In Proceedings of the 2008 international conference on web search and data mining (pp. 183-194). ACM. Agresta, S., & Bough, B. B. (2010). Perspectives on social media marketing. Nelson Education. Ahenkorah-Marfo, M., & Akussah, H. (2016). Changing the face of reference and user services: Adoption of social media in top Ghanaian academic libraries. Reference Services Review, 44(3), 219-236. Alalwan, A. A., Rana, N. P., Dwivedi, Y. K., & Algharabat, R. (2017). Social media in marketing: A review and analysis of the existing literature. Telematics and Informatics. Ala-Mutka, K., Broster, D., Cachia, R., Centeno, C., Feijóo, C., Haché, A., ... & Pascu, C. (2009). The impact of social computing on the EU information society and economy. JRC Scientific and Technical Report EUR, 24063. Ali, H., & Birley, S. (1999). Integrating deductive and inductive approaches in a study of new ventures and customer perceived risk. Qualitative market research: an international journal, 2(2), 103-110. Alkhattabi, M., Neagu, D., & Cullen, A. (2011). Assessing information quality of e-learning systems: a web mining approach. Computers in Human Behaviour, 27(2), 862-873. 92 University of Ghana http://ugspace.ug.edu.gh Allen, D. E., Arafat, I., Edgley, C. E., & Guy, R. F. (1987). Social Research Methods–Puzzles and Solutions Allyn and Bacon. Inc. Boston, London, Sydney and Toronto. Allen, D. E., Arafat, I., Edgley, C. E., & Guy, R. F. (1987). Social Research Methods–Puzzles and Solutions Allyn and Bacon. Inc. Boston, London, Sydney and Toronto. Amichai-Hamburger, Y., Wainapel, G., & Fox, S. (2002). " On the Internet no one knows I'm an introvert": Extroversion, neuroticism, and Internet interaction. Cyberpsychology & behaviour, 5(2), 125-128. Amini, A., Darani, M., Afshani, M., & Amini, Z. (2012). Effectiveness of marketing strategies and corporate image on brand equity as a sustainable competitive advantage. Interdisciplinary Journal of Contemporary Research in Business, 4(2), 192-205. Babbie, E. R. (1990). Survey research methods Wadsworth Pub. Co Belmont, Calif, 3(9). Backstrom, L., & Leskovec, J. (2011, February). Supervised random walks: predicting and recommending links in social networks. In Proceedings of the fourth ACM international conference on Web search and data mining (pp. 635-644). ACM. Baeza-Yates, R., Junqueira, F., Plachouras, V., & Witschel, H. F. (2009). U.S. Patent Application No. 11/868,396. Baker, S. E., Edwards, R., & Doidge, M. (2012). How many qualitative interviews is enough?: Expert voices and early career reflections on sampling and cases in qualitative research. Barger, V., Peltier, J. W., & Schultz, D. E. (2016). Social media and consumer engagement: a review and research agenda. Journal of Research in Interactive Marketing, 10(4), 268-287. Barnett, L. A. (1991). The playful child: Measurement of a disposition to play. Play & Culture, 4(6), 51-74. 93 University of Ghana http://ugspace.ug.edu.gh Baumgartner, T. A., Strong, C. H., & Hensley, L. D. (2002). Measurement issues in research. Conducting and Reading Research in Health and Human Performance, McGraw- Hill, New York, NY, 329-50. Bawden, D., & Robinson, L. (2009). The dark side of information: overload, anxiety and other paradoxes and pathologies. Journal of information science, 35(2), 180-191. Baxter, P., & Jack, S. (2008). Qualitative case study methodology: Study design and implementation for novice researchers. The qualitative report, 13(4), 544-559. Beldad, A., De Jong, M., & Steehouder, M. (2010). How shall I trust the faceless and the intangible? A literature review on the antecedents of online trust. Computers in human behavior, 26(5), 857-869. Benevenuto, F., Duarte, F., Rodrigues, T., Almeida, V. A., Almeida, J. M., & Ross, K. W. (2008, October). Understanding video interactions in youtube. In Proceedings of the 16th ACM international conference on Multimedia (pp. 761-764). ACM. Benoit, S. L., Miller, E. F., & Maier, R. J. (2013). Helicobacter pylori stores nickel to aid its host colonization. Infection and immunity, 81(2), 580-584. Berthon, P. R., Pitt, L. F., Plangger, K., & Shapiro, D. (2012). Marketing meets Web 2.0, social media, and creative consumers: Implications for international marketing strategy. Business horizons, 55(3), 261-271. Bhatnagar, A., & Ghose, S. (2004). Online information search termination patterns across product categories and consumer demographics. Journal of Retailing, 80(3), 221-228. Bhattacherjee, A. (2012). Social science research: Principles, methods, and practices. Bianchi, C., & Andrews, L. (2015). Investigating marketing managers' perspectives on social media in Chile. Journal of Business Research, 68(12), 2552-2559. 94 University of Ghana http://ugspace.ug.edu.gh Blythe, J. (2008). Consumer behaviour. Cengage Learning EMEA. Boateng, H., & Okoe, A. F. (2015). Consumers’ attitude towards social media advertising and their behavioural response: The moderating role of corporate reputation. Journal of Research in Interactive Marketing, 9(4), 299-312. Boateng, R. (2016). Research made easy. CreateSpace Independent Publishing Platform. Bontcheva, K., Gorrell, G., & Wessels, B. (2013). Social media and information overload: Survey results. arXiv preprint arXiv:1306.0813. Borchers, A., Herlocker, J., Konstan, J., & Riedl, J. (1998). Ganging up on information overload. Computer, (4), 106-108. Bordens, S.K and B.B. Abbott (2002) Research Design & Methods: A Process Approach, 5th ed, Bordet, R., Lang, M., Dieu, C., Billon, N., & Duffet, J. P. (2015). Early results from a multi- component French public-private partnership initiative to improve participation in clinical research–CeNGEPS: a prospective before-after study. BMC medical research methodology, 15(1), 67. Brady, M., Goodman, M., Hansen, T., Keller, K., & Kotler, P. (2009). Marketing management. England: Pearson Education Limited. Brady, M., Goodman, M., Hansen, T., Keller, K., & Kotler, P. (2009). Marketing management. England: Pearson Education Limited. Bryman, A. (1993). Charismatic leadership in business organisations: Some neglected issues. The Leadership Quarterly, 4(3-4), 289-304. Buame, S. K. (1996). Entrepreneurship: A contextual perspective: Discourses and praxis of entrepreneurship activities within the institutional context of Ghana. Burns, A. C., & Bush, R. F. (2000). Marketing research. Globalisation, 1(7). 95 University of Ghana http://ugspace.ug.edu.gh Bushiri, C. P. (2014). The impact of working environment on employees’ performance, the case of Institute of Finance Management in Dar es Salaam (Doctoral dissertation, The Open University of Tanzania). Campbell, M. C., & Goodstein, R. C. (2001). The moderating effect of perceived risk on consumers' evaluations of product incongruity: Preference for the norm. Journal of consumer Research, 28(3), 439-449. Chai, K., Potdar, V., & Dillon, T. (2009, June). Content quality assessment related frameworks for social media. In International Conference on Computational Science and Its Applications (pp. 791-805). Springer, Berlin, Heidelberg. Chandra, B., Goswami, S., & Chouhan, V. (2013). Investigating altitude towards online advertising on social media-an empirical study. Management Insight, 8(1). Chang, C. C., Chow, C. C., Tellier, L. C., Vattikuti, S., Purcell, S. M., & Lee, J. J. (2015). Second- generation PLINK: rising to the challenge of larger and richer datasets. Gigascience, 4(1), 7. Chang, Y. T., Yu, H., & Lu, H. P. (2015). Persuasive messages, popularity cohesion, and message diffusion in social media marketing. Journal of Business Research, 68(4), 777-782. Chen, C. C., & Tseng, Y. D. (2011). Quality evaluation of product reviews using an information quality framework. Decision Support Systems, 50(4), 755-768. Cheung, C. M. Y., Sia, C. L., & Kuan, K. K. (2012). Is this review believable? A study of factors affecting the credibility of online consumer reviews from an ELM perspective. Journal of the Association for Information Systems, 13(8), 618. Coakes, S. J., Steed, L., & Dzidic, P. (2006). SPSS version 13.0 for windows. John Willey and Sons Australia Ltd., Australia. 96 University of Ghana http://ugspace.ug.edu.gh Collis, J., & Hussey, R. (2003). Business research (ed.). Corstjens, M., & Umblijs, A. (2012). The power of evil: The damage of negative social media strongly outweigh positive contributions. Journal of Advertising Research, 52(4), 433-449. Coulter, K. S., & Roggeveen, A. (2012). “Like it or not” Consumer responses to word-of-mouth communication in on-line social networks. Management Research Review, 35(9), 878-899. Creswell, J. W. (2013). Steps in conducting a scholarly mixed methods study. Creswell, J. W., & Zhang, W. (2009). The application of mixed methods designs to trauma research. Journal of Traumatic Stress: Official Publication of The International Society for Traumatic Stress Studies, 22(6), 612-621. Creswell, J. W., Hanson, W. E., Clark Plano, V. L., & Morales, A. (2007). Qualitative research designs: Selection and implementation. The counseling psychologist, 35(2), 236-264. Creswell, J. W., Hanson, W. E., Clark Plano, V. L., & Morales, A. (2007). Qualitative research designs: Selection and implementation. The counseling psychologist, 35(2), 236-264. Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. psychometrika, 16(3), 297-334. Cyr, D. (2013). Website design, trust and culture: An eight country investigation. Electronic Commerce Research and Applications, 12(6), 373-385. Darley, W. K., Blankson, C., & Luethge, D. J. (2010). Toward an integrated framework for online consumer behaviour and decision-making process: A review. Psychology & marketing, 27(2), 94-116. Dawson, G. R., & Tricklebank, M. D. (1995). Use of the elevated plus maze in the search for novel anxiolytic agents. Trends in pharmacological sciences, 16(2), 33-36. 97 University of Ghana http://ugspace.ug.edu.gh Dean, D., & Webb, C. (2011). Recovering from information overload. McKinsey Quarterly, 1(1), 80-88. Dekay, S. H. (2012). How large companies react to negative Facebook comments. Corporate Communications: An International Journal, 17(3), 289-299. Duffett, R. G. (2015). Facebook advertising’s influence on intention-to-purchase and purchase amongst Millennials. Internet Research, 25(4), 498-526. Easterby-Smith, M., Thorpe, R., & Lowe, A. (2002). Management research methods. London: Sage Publications Examinership-Friel Stafford, Available from www. liquidation. ie. Eldabi, T., Irani, Z., Paul, R. J., & Love, P. E. (2002). Quantitative and qualitative decision-making methods in simulation modelling. Management Decision, 40(1), 64-73. Elster, D. (2007). Student interests—the German and Austrian ROSE survey. Journal of Biological Education, 42(1), 5-10. Enginkaya, E., & Yılmaz, H. (2014). What drives consumers to interact with brands through social media? A motivation scale development study. Procedia-Social and Behavioural Sciences, 148, 219-226. Eşkisu, M., Hoşoğlu, R., & Rasmussen, K. (2017). An investigation of the relationship between Facebook usage, Big Five, self-esteem and narcissism. Computers in Human Behaviour, 69, 294-301. Felbermayr, A., & Nanopoulos, A. (2016). The role of emotions for the perceived usefulness in online customer reviews. Journal of Interactive Marketing, 36, 60-76. Fichman, P. (2011). A comparative assessment of answer quality on four question answering sites. Journal of Information Science, 37(5), 476-486. 98 University of Ghana http://ugspace.ug.edu.gh Filo, K., Lock, D., & Karg, A. (2015). Sport and social media research: A review. Sport management review, 18(2), 166-181. Fischer, E., & Reuber, A. R. (2011). Social interaction via new social media:(How) can interactions on Twitter affect effectual thinking and behaviour?. Journal of business venturing, 26(1), 1-18. Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 39-50. Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 39-50. Fuchs, C., & Horak, E. (2008). Africa and the digital divide. Telematics and informatics, 25(2), 99-116. Gamboa, A. M., & Gonçalves, H. M. (2014). Customer loyalty through social networks: Lessons from Zara on Facebook. Business Horizons, 57(6), 709-717. Gao, Y., & Koufaris, M. (2006). Perceptual antecedents of user attitude in electronic commerce. ACM SIGMIS Database: the DATABASE for Advances in Information Systems, 37(2-3), 42-50. Ge, M., & Helfert, M. (2013). Impact of information quality on supply chain decisions. Journal of Computer Information Systems, 53(4), 59-67. Gensler, S., Völckner, F., Liu-Thompkins, Y., & Wiertz, C. (2013). Managing brands in the social media environment. Journal of interactive marketing, 27(4), 242-256. Geurin-Eagleman, A. N., & Burch, L. M. (2016). Communicating via photographs: A gendered analysis of Olympic athletes’ visual self-presentation on Instagram. Sport management review, 19(2), 133-145. 99 University of Ghana http://ugspace.ug.edu.gh Ghauri, P. N., & Grønhaug, K. (2005). Research methods in business studies: A practical guide. Pearson Education. Glasow, P. A. (2005). Fundamentals of survey research methodology. Retrieved January, 18, 2013. Goodwin, C., Mayo, M., & Hill, R. P. (1997). Salesperson response to loss of a major account: A qualitative analysis. Journal of Business Research, 40(2), 167-180. Goulding, C. (2002). Grounded theory: A practical guide for management, business and market researchers. Sage. Goyal, S. (2015). Networks in economics: a perspective on the literature. Grabner-Kräuter, S., & Kaluscha, E. A. (2003). Empirical research in on-line trust: a review and critical assessment. International journal of human-computer studies, 58(6), 783-812. Green, A. E., & Zerna, W. (1992). Theoretical elasticity. Courier Corporation. Greenwood, R., Oliver, C., Lawrence, T. B., & Meyer, R. E. (Eds.). (2017). The Sage handbook of organisational institutionalism. Sage. Gross, B. M. (1964). The managing of organisations: The administrative struggle (Vol. 2). [New York]: Free Press of Glencoe. Guesalaga, R. (2016). The use of social media in sales: Individual and organisational antecedents, and the role of customer engagement in social media. Industrial Marketing Management, 54, 71-79. Gummesson, E. (2000). Qualitative methods in management research. Sage. Guy, B., Kieny, M. P., Riviere, Y., Le Peuch, C., Dott, K., Girard, M., ... & Lecocq, J. P. (1987). HIV F/3'orf encodes a phosphorylated GTP-binding protein resembling an oncogene product. Nature, 330(6145), 266-269. 100 University of Ghana http://ugspace.ug.edu.gh Hair, J. F., Celsi, M., Ortinau, D. J., & Bush, R. P. (2008). Essentials of marketing research. New York, NY: McGraw-Hill/Higher Education. Hair, J., Hollingsworth, C. L., Randolph, A. B., & Chong, A. Y. L. (2017). An updated and expanded assessment of PLS-SEM in information systems research. Industrial Management & Data Systems, 117(3), 442-458. Hair, J., Wolfinbarger, M., Ortinau, D., & Bush, R. (2008). In Hair JF. Essentials of marketing research. Hassan, S., Nadzim, S. Z. A., & Shiratuddin, N. (2015). Strategic use of social media for small business based on the AIDA model. Procedia-Social and Behavioural Sciences, 172, 262- 269. Hawkins, D., Mothersbaugh, D., & Best, R. L.(2010) Consumer Behaviour Building Marketing Strategy. He, W., & Zha, S. (2014). Insights into the adoption of social media mashups. Internet Research, 24(2), 160-180. He, W., Wang, F. K., & Zha, S. (2014). Enhancing social media competitiveness of small businesses: insights from small pizzerias. New Review of Hypermedia and Multimedia, 20(3), 225-250. Hennig-Thurau, T., Hofacker, C. F., & Bloching, B. (2013). Marketing the pinball way: understanding how social media change the generation of value for consumers and companies. Journal of Interactive Marketing, 27(4), 237-241. Hinson, R., & Amidu, M. (2006). Internet adoption amongst final year students in Ghana's oldest business school. Library Review, 55(5), 314-323. 101 University of Ghana http://ugspace.ug.edu.gh Hodas, N. O., & Lerman, K. (2012,). How visibility and divided attention constrain social contagion. In Privacy, Security, Risk and Trust (PASSAT), 2012 International Conference on and 2012 International Confernece on Social Computing (SocialCom) (pp. 249-257). IEEE. Hodas, N. O., Kooti, F., & Lerman, K. (2013). Friendship Paradox Redux: Your Friends Are More Interesting Than You. ICWSM, 13, 8-10. Hong, Y., Huang, N., Burtch, G., & Li, C. (2016). Culture, conformity and emotional suppression in online reviews. Journal of the Association for Information Systems, forthcoming, 16- 020. Hoyer, W. D., MacInnis, D. J., & Pieters, R. (2001). Customer behaviour. Boston, Houghton Mifflin Company. Hsu, L., & Lawrence, B. (2016). The role of social media and brand equity during a product recall crisis: A shareholder value perspective. International journal of research in Marketing, 33(1), 59-77. Hudson, N. (2015). Soil conservation: fully revised and updated (No. Ed. 3). New India Publishing Agency. Hudson, S., Huang, L., Roth, M. S., & Madden, T. J. (2016). The influence of social media interactions on consumer–brand relationships: A three-country study of brand perceptions and marketing behaviours. International Journal of Research in Marketing, 33(1), 27-41. Jacoby, J. (1984). Perspectives on information overload. Journal of consumer research, 10(4), 432-435. 102 University of Ghana http://ugspace.ug.edu.gh Java, A., Song, X., Finin, T., & Tseng, B. (2007, August). Why we twitter: understanding microblogging usage and communities. In Proceedings of the 9th WebKDD and 1st SNA- KDD 2007 workshop on Web mining and social network analysis (pp. 56-65). ACM. Jiménez, F. R., & Mendoza, N. A. (2013). Too popular to ignore: The influence of online reviews on purchase intentions of search and experience products. Journal of Interactive Marketing, 27(3), 226-235. Kahn, B. K., Strong, D. M., & Wang, R. Y. (2002). Information quality benchmarks: product and service performance. Communications of the ACM, 45(4), 184-192. Kajornboon, A. B. (2005). Using interviews as research instruments. E-journal for Research Teachers, 2(1), 1-9. Kane, G., & Ransbotham, S. (2012). Codification and collaboration: Information quality in social media. Kang, M., & Schuett, M. A. (2013). Determinants of sharing travel experiences in social media. Journal of Travel & Tourism Marketing, 30(1-2), 93-107. Kaplan, A. M., & Haenlein, M. (2010). Users of the world, unite! The challenges and opportunities of Social Media. Business horizons, 53(1), 59-68. Karal, H., Kokoç, M., & Ayyıldız, U. (2010). Educational computer games for developing psychomotor ability in children with mild mental impairment. Procedia-Social and Behavioural Sciences, 9, 996-1000. Karanatsiou, D., Misirlis, N., & Vlachopoulou, M. (2017). Bibliometrics and altmetrics literature review: Performance indicators and comparison analysis. Performance Measurement and Metrics, 18(1), 16-27 103 University of Ghana http://ugspace.ug.edu.gh Karanatsiou, D., Misirlis, N., & Vlachopoulou, M. (2017). Bibliometrics and altmetrics literature review: Performance indicators and comparison analysis. Performance Measurement and Metrics, 18(1), 16-27. Kardes, F. R., Cronley, M. L., & Cline, T. W. (2011). Consumer Behaviour, Mason, OH: South- Western, Cengage Learning, 2011. ISBN 978-0-538-74540-6. Kassel, A. (1999). How to write a marketing plan. Marketing Library Services, 13(5), 4-6. Khaniwale, M. (2015). Consumer buying behaviour. International Journal of innovation and scientific research, 14(2), 278-286. Kietzmann, J. H., Hermkens, K., McCarthy, I. P., & Silvestre, B. S. (2011). Social media? Get serious! Understanding the functional building blocks of social media. Business horizons, 54(3), 241-251. Kim, A. J., & Ko, E. (2012). Do social media marketing activities enhance customer equity? An empirical study of luxury fashion brand. Journal of Business Research, 65(10), 1480-1486. Klamma, R., Chatti, M., Duval, E., Hummel, H., Hvannberg, E. T., Kravcik, M., ... & Scott, P. (2007). Social software for life-long learning. Kleinrichert, D., Ergul, M., Johnson, C., & Uydaci, M. (2012). Boutique hotels: technology, social media and green practices. Journal of Hospitality and Tourism Technology, 3(3), 211-225. Kornhauser, A., & Lazarsfeld, P. F. (1955). The analysis of consumer actions. The language of social research, 392-404. Kotler, P., & Caslione, J. A. (2009). Chaotics: The business of managing and marketing in the age of turbulence. AMACOM Div American Mgmt Assn. 104 University of Ghana http://ugspace.ug.edu.gh Kozinets, R. V., De Valck, K., Wojnicki, A. C., & Wilner, S. J. (2010). Networked narratives: Understanding word-of-mouth marketing in online communities. Journal of marketing, 74(2), 71-89. Krol, E., & Hoffman, E. (1993). FYI on" What is the Internet?" (No. RFC 1462). Kuada, J. (2015). Entrepreneurship in Africa–a classificatory framework and a research agenda. African Journal of Economic and Management Studies, 6(2), 148-163. Kuhn, T. (1962). IX. The Nature and Necessity of Scientific Revolutions. Kuksov, D., Shachar, R., & Wang, K. (2013). Advertising and consumers' communications. Marketing Science, 32(2), 294-309. Kurz-Milcke, E., & Gigerenzer, G. (2007). Heuristic decision making. Marketing: Journal of Research and Management, 3(1), 48-56. Laroche, M., Habibi, M. R., Richard, M. O., & Sankaranarayanan, R. (2012). The effects of social media based brand communities on brand community markers, value creation practices, brand trust and brand loyalty. Computers in Human Behavior, 28(5), 1755-1767. Lee, D. A., & Blackshaw, S. (2012). Functional implications of hypothalamic neurogenesis in the adult mammalian brain. International journal of developmental neuroscience, 30(8), 615- 621. Lee, E., Lee, J. A., Moon, J. H., & Sung, Y. (2015). Pictures speak louder than words: Motivations for using Instagram. Cyberpsychology, Behaviour, and Social Networking, 18(9), 552-556. Lee, J., & Hong, I. B. (2016). Predicting positive user responses to social media advertising: The roles of emotional appeal, informativeness, and creativity. International Journal of Information Management, 36(3), 360-373. Leedy, P. D., & Ormrod, J. E. (2001). Practical research: Planning and research. Upper Saddle. 105 University of Ghana http://ugspace.ug.edu.gh Leeflang, P. S., Verhoef, P. C., Dahlström, P., & Freundt, T. (2014). Challenges and solutions for marketing in a digital era. European management journal, 32(1), 1-12. Leeflang, P. S., Verhoef, P. C., Dahlström, P., & Freundt, T. (2014). Challenges and solutions for marketing in a digital era. European management journal, 32(1), 1-12. Leiner, B. M., Cerf, V. G., Clark, D. D., Kahn, R. E., Kleinrock, L., Lynch, D. C., ... & Wolff, S. (2000). A brief history of the internet. 2000. Web Page. URL: http://info. isoc/org/internet- history/brief. html, 18. Lepkowska-White, E. (2013). Are they listening? Designing online recommendations for today's consumers. Journal of Research in Interactive Marketing, 7(3), 182-200. Leung, X. Y., Bai, B., & Stahura, K. A. (2015). The marketing effectiveness of social media in the hotel industry: A comparison of Facebook and Twitter. Journal of Hospitality & Tourism Research, 39(2), 147-169. Liang, T. P., & Lai, H. J. (2002). Effect of store design on consumer purchases: an empirical study of on-line bookstores. Information & Management, 39(6), 431-444. Liang, T. P., & Lai, H. J. (2002). Effect of store design on consumer purchases: an empirical study of on-line bookstores. Information & Management, 39(6), 431-444. Lin, D. (1998, July). An information-theoretic definition of similarity. In Icml (Vol. 98, No. 1998, pp. 296-304). Lincoln, N. K. D. Y. S., & Lincoln, Y. S. (2005). The Sage handbook of qualitative research. Sage. Lingard, L., Albert, M., & Levinson, W. (2008). Grounded theory, mixed methods, and action research. Bmj, 337, a567. Lingelbach, D., Patino, A., & Pitta, D. A. (2012). The emergence of marketing in Millennial new ventures. Journal of Consumer Marketing, 29(2), 136-145. 106 University of Ghana http://ugspace.ug.edu.gh Lu, X., Ba, S., Huang, L., & Feng, Y. (2013). Promotional marketing or word-of-mouth? Evidence from online restaurant reviews. Information Systems Research, 24(3), 596-612. Ludwig, S., De Ruyter, K., Friedman, M., Brüggen, E. C., Wetzels, M., & Pfann, G. (2013). More than words: The influence of affective content and linguistic style matches in online reviews on conversion rates. Journal of Marketing, 77(1), 87-103. Lui, A. K. F., Li, S. C., & Choy, S. O. (2007, July). An evaluation of automatic text categorization in online discussion analysis. In Seventh IEEE International Conference on Advanced Learning Technologies (ICALT 2007) (pp. 205-209). IEEE. Lye, K. W., & Wing, J. M. (2005). Game strategies in network security. International Journal of Information Security, 4(1-2), 71-86. Madnick, S. E., Wang, R. Y., Lee, Y. W., & Zhu, H. (2009). Overview and framework for data and information quality research. Journal of Data and Information Quality (JDIQ), 1(1), 2. Malhotra, N. K. (2007). Review of marketing research. In Review of Marketing Research (pp. v- v). Emerald Group Publishing Limited. Malhotra, N. K., & Birks, D. F. (2007). Marketing research: An applied approach: Pearson Education. Malhotra, N., & Birks, D. (2006). Marketing research: An applied perspective. Harlow: Prentice Hall. Marshall, C., & Rossman, G. B. (1999). The “what” of the study: Building the conceptual framework. Designing qualitative research, 3, 21-54. Marshall, C., & Rossman, G. B. (1999). The “what” of the study: Building the conceptual framework. Designing qualitative research, 3, 21-54. 107 University of Ghana http://ugspace.ug.edu.gh Marshall, M. N. (1996). Sampling for qualitative research. Family practice, 13(6), 522-526. Marwick, A. E. (2015). Instafame: Luxury selfies in the attention economy. Public culture, 27(1 (75)), 137-160. Marwick, A. E., & Boyd, D. (2011). I tweet honestly, I tweet passionately: Twitter users, context collapse, and the imagined audience. New media & society, 13(1), 114-133. McCarthy, J., Rowley, J., Jane Ashworth, C., & Pioch, E. (2014). Managing brand presence through social media: the case of UK football clubs. Internet Research, 24(2), 181-204. McKlin, T., Harmon, S. W., Evans, W., & Jones, M. G. (2002). Cognitive presence in web-based learning: A content analysis of students’ online discussions. ITForum Paper# 60. McMillan, J. H., & Schumacher, S. (1997). Research in education: A conceptual framework. New York: Longman. Miles, M. B., Huberman, A. M., & Saldana, J. (2013). Qualitative data analysis. Sage. Miles, M. B., Huberman, A. M., Huberman, M. A., & Huberman, M. (1994). Qualitative data analysis: An expanded sourcebook. sage. Miritello, G. (2013). Temporal patterns of communication in social networks. Springer Science & Business Media. Mitchell, V. W., & Boustani, P. (1994). A preliminary investigation into pre-and post-purchase risk perception and reduction. European Journal of Marketing, 28(1), 56-71. Monkey, S. (2015). Mobile Facebook, Twitter, Social Media Usage Statistics in Ghana. Retrieved 3rd March 2016. Moore, C. R., Johnson, L. S., Kwak, I. Y., Livny, M., Broman, K. W., & Spalding, E. P. (2013). High-throughput computer vision introduces the time axis to a quantitative trait map of a plant growth response. Genetics, genetics-113. 108 University of Ghana http://ugspace.ug.edu.gh Morris, T., & Wood, S. (1991). Testing the survey method: continuity and change in British industrial relations. Work, Employment and Society, 5(2), 259-282. Nasiruddin, K. B., & Hashim, H. B. (2015). Electronic Word of Mouth: Exploring Consumer Reactions and Purchase Intention. Journal of Global Business and Social Entrepreneurship, 1(1), 85-93. Nguyen, J. V. (2015). U.S. Patent No. 9,087,319. Washington, DC: U.S. Patent and Trademark Office. Oh, C., Roumani, Y., Nwankpa, J. K., & Hu, H. F. (2017). Beyond likes and tweets: Consumer engagement behaviour and movie box office in social media. Information & Management, 54(1), 25-37. Olshavsky, R. W., & Granbois, D. H. (1979). Consumer decision making—fact or fiction?. Journal of consumer research, 6(2), 93-100. Olsina, L., Sassano, R., & Mich, L. (2008). Specifying quality requirements for the web 2.0 applications. In Proc. of IWWOST (Vol. 8, pp. 56-62). Pacquette, L. H., Levenson, A. M., Thompson, J. J., & Dowell, D. (2013). Total iodine in infant formula and nutritional products by inductively coupled plasma/mass spectrometry: First Action 2012.14. Journal of AOAC International, 96(4), 798-801. Pallant, J. (2011). SPSS Survival manual: a step by step guide to data analysis using SPSS. Crows Nest. New South Wales: Allen & Unwin. Patino, A., Pitta, D. A., & Quinones, R. (2012). Social media's emerging importance in market research. Journal of Consumer Marketing, 29(3), 233-237. Patzer, G. L. (1995). Using secondary data in marketing research: United States and worldwide. Greenwood Publishing Group. 109 University of Ghana http://ugspace.ug.edu.gh Pew, J., Muir, P. H., Wang, J., & Frasier, T. R. (2015). related: an R package for analysing pairwise relatedness from codominant molecular markers. Molecular Ecology Resources, 15(3), 557-561. Pittman, M., & Reich, B. (2016). Social media and loneliness: Why an Instagram picture may be worth more than a thousand Twitter words. Computers in Human Behavior, 62, 155-167. Potter, J. (1996). Representing reality: Discourse, rhetoric and social construction. Sage. Punch, K. F. (2013). Introduction to social research: Quantitative and qualitative approaches. sage.qualitative research (2nd ed., pp. 189-214). Thousand Oaks, CA: Sage. Qualman, E. (2013). Social media video 2013. Socid-nomi. cs, http://www. socialnomics. net/2Ol3/OlO1/social media-video-2013. Qualman, E. (2013). Social media video 2013. Socid-nomi. cs, http://www. socialnomics. net/2Ol3/OlO1/social media-video-2013. Ramachander, S. (1988). Consumer Behaviour and Marketing: Towards an Indian Approach?. Economic and Political Weekly, M22-M25. Remenyi, D., Williams, B., Money, A., & Swartz, E. (1998). Research in business and management. London: Sage. Remmen, D.(2003). Performance pays off. Strategic Finance, 84(9), 24-31. Resnik, A., & Stern, B. L. (1977). An analysis of information content in television advertising. The Journal of Marketing, 50-53. Reyneke, M., Pitt, L., & Berthon, P. R. (2011). Luxury wine brand visibility in social media: An exploratory study. International Journal of Wine Business Research, 23(1), 21-35. 110 University of Ghana http://ugspace.ug.edu.gh Ridgway, J. L., & Clayton, R. B. (2016). Instagram unfiltered: Exploring associations of body image satisfaction, Instagram# selfie posting, and negative romantic relationship outcomes. Cyberpsychology, Behaviour, and Social Networking, 19(1), 2-7. Risse, T., Peters, W., Senellart, P., & Maynard, D. (2014). Documenting contemporary society by preserving relevant information from Twitter. Twitter and society, 207, 219. Robson, P. (2002). The economics of international integration. Routledge. Roehm, M. L., & Tybout, A. M. (2006). When will a brand scandal spill over, and how should competitors respond?. Journal of Marketing Research, 43(3), 366-373. Rohm, A., D. Kaltcheva, V., & R. Milne, G. (2013). A mixed-method approach to examining brand-consumer interactions driven by social media. Journal of Research in Interactive Marketing, 7(4), 295-311. Rohm, A., D. Kaltcheva, V., & R. Milne, G. (2013). A mixed-method approach to examining brand-consumer interactions driven by social media. Journal of Research in Interactive Marketing, 7(4), 295-311. Rohm, A., D. Kaltcheva, V., & R. Milne, G. (2013). A mixed-method approach to examining brand-consumer interactions driven by social media. Journal of Research in Interactive Marketing, 7(4), 295-311. Salant, P., Dillman, I., & Don, A. (1994). How to conduct your own survey (No. 300.723 S3.). Saldaña, J. (2009). An introduction to codes and coding. The coding manual for qualitative researchers, 3. Sanderson, J., & Hambrick, M. E. (2012). Covering the scandal in 140 characters: A case study of Twitter’s role in coverage of the Penn State saga. International Journal of Sport Communication, 5(3), 384-402. 111 University of Ghana http://ugspace.ug.edu.gh Sanderson, J., & Hambrick, M. E. (2012). Covering the scandal in 140 characters: A case study of Twitter’s role in coverage of the Penn State saga. International Journal of Sport Communication, 5(3), 384-402. Saunders, M., Lewis, P., & Thornhill, A. (2009). Research methods for business students. Pearson education. Savolainen, R. (2007). Information behaviour and information practice: Reviewing the “umbrella concepts” of information-seeking studies. The Library Quarterly, 77(2), 109-132. Saxena, A., & Khanna, U. (2013). Advertising on social network sites: A structural equation modelling approach. Vision, 17(1), 17-25. Scammon, D. L. (1977). “Information load” and consumers. Journal of consumer research, 4(3), 148-155. Schiffman, H. Kanuk,(2007). Consumer Behaviour: A European Outlook. Schlosser, A. E. (2005). Source perceptions and the persuasiveness of internet word-of-mouth communication. ACR North American Advances. Schwandt, T. A. (2000). Three epistemological stances for qualitative inquiry: Interpretivism, hermeneutics and social constructivism. In N. K. Denzin & Y. S. Lincoln (Eds.), Handbook of Sciadas, G. (2005). Infostates across countries and over time: Conceptualization, modeling, and measurements of the digital divide. Si, S., & Bruton, G. D. (2005). Knowledge learning, cost economizing, and competitive positioning: IJV motivation in emerging economies. Journal of Business Research, 58, 1465-1473. 112 University of Ghana http://ugspace.ug.edu.gh Siamagka, N. T., Christodoulides, G., Michaelidou, N., & Valvi, A. (2015). Determinants of social media adoption by B2B organisations. Industrial Marketing Management, 51, 89-99. Sinclaire, J. K., & Vogus, C. E. (2011). Adoption of social networking sites: an exploratory adaptive structuration perspective for global organisations. Information Technology and Management, 12(4), 293-314. Singh, S., & Sonnenburg, S. (2012). Brand performances in social media. Journal of interactive marketing, 26(4), 189-197. Smith, B. G., & Gallicano, T. D. (2015). Terms of engagement: Analyzing public engagement with organisations through social media. Computers in Human Behaviour, 53, 82-90. Smith, K., Mendez, F., & White, G. L. (2014). Narcissism as a predictor of Facebook users' privacy concern, vigilance, and exposure to risk. International Journal of Technology and Human Interaction (IJTHI), 10(2), 78-95. Smith, K., Mendez, F., & White, G. L. (2014). Narcissism as a predictor of Facebook users' privacy concern, vigilance, and exposure to risk. International Journal of Technology and Human Interaction (IJTHI), 10(2), 78-95. Solomon, R. C. (1995). A passion for justice: Emotions and the origins of the social contract. Rowman & Littlefield. Strauss, A., & Corbin, J. (1998). Basics of qualitative research: Procedures and techniques for developing grounded theory. Strong, D. M., Lee, Y. W., & Wang, R. Y. (1997). Data quality in context. Communications of the ACM, 40(5), 103-110. 113 University of Ghana http://ugspace.ug.edu.gh Taylor, D. G., Lewin, J. E., & Strutton, D. (2011). Friends, fans, and followers: do ads work on social networks?: how gender and age shape receptivity. Journal of advertising research, 51(1), 258-275. Taylor, S. J., & Bogdan, R. (1984). Introduction to qualitative research methods: The search for meaning. Teyi, S. S. (2014). Entrepreneurship education: A case study of Ghana’s premier university (Unpublished master’s thesis). University of Ghana Business School. Toffler, A. (1984). Future shock (Vol. 553). Bantam. Tsimonis, G., & Dimitriadis, S. (2014). Brand strategies in social media. Marketing Intelligence & Planning, 32(3), 328-344. Tsimonis, G., & Dimitriadis, S. (2014). Brand strategies in social media. Marketing Intelligence & Planning, 32(3), 328-344. Tuurosong, D., & Faisal, A. M. (2014). The social media scourge among university students: a study of the university for development studies, Ghana. Stud, 3(2). Van Osch, W., & Coursaris, C. K. (2013, January). Organisational social media: A comprehensive framework and research agenda. In System Sciences (HICSS), 2013 46th Hawaii International Conference on (pp. 700-707). IEEE. Walsham, G. (1995). Interpretive case studies in IS research: nature and method. European Journal of information systems, 4(2), 74-81. Wang, Z., Tchernev, J. M., & Solloway, T. (2012). A dynamic longitudinal examination of social media use, needs, and gratifications among college students. Computers in Human Behavior, 28(5), 1829-1839. 114 University of Ghana http://ugspace.ug.edu.gh Waters, R. D., Canfield, R. R., Foster, J. M., & Hardy, E. E. (2011). Applying the dialogic theory to social networking sites: Examining how university health centers convey health messages on Facebook. Journal of Social Marketing, 1(3), 211-227. Whitley, R. (1984). The scientific status of management research as a practically‐oriented social science. Journal of Management Studies, 21(4), 369-390. Wilson, H. S., & Hutchinson, S. A. (1996). Methodologic mistakes in grounded theory. Nursing research, 45(2), 122-124. Wu, J. C., & Xia, F. D. (2016). Measuring the macroeconomic impact of monetary policy at the zero lower bound. Journal of Money, Credit and Banking, 48(2-3), 253-291. Xu, Z., Liu, Y., Xuan, J., Chen, H., & Mei, L. (2017). Crowdsourcing based social media data analysis of urban emergency events. Multimedia Tools and Applications, 76(9), 11567- 11584. Yin, H., Gesbert, D., Filippou, M., & Liu, Y. (2013). A coordinated approach to channel estimation in large-scale multiple-antenna systems. IEEE Journal on Selected Areas in Communications, 31(2), 264-273. Yin, R. K. (2003). Case study research design and methods third edition. Applied social research methods series, 5. Yin, R. K. (2011). Applications of case study research. Sage. Yin, R. K. (2015). Qualitative research from start to finish. Guilford Publications. Zeng, B., & Gerritsen, R. (2014). What do we know about social media in tourism? A review. Tourism Management Perspectives, 10, 27-36. 115 University of Ghana http://ugspace.ug.edu.gh Zhang, B., & Vos, M. (2014). Social media monitoring: aims, methods, and challenges for international companies. Corporate Communications: An International Journal, 19(4), 371-383. Zhou, M. L., Zhu, X. M., Shao, J. R., Tang, Y. X., & Wu, Y. M. (2011). Production and metabolic engineering of bioactive substances in plant hairy root culture. Applied microbiology and biotechnology, 90(4), 1229-1239. Zhu, Z., Bernhard, D., & Gurevych, I. (2009). A multi-dimensional model for assessing the quality of answers in social Q&A sites (Doctoral dissertation). Ziliani, F., Velastin, S., Porikli, F., Marcenaro, L., Kelliher, T., Cavallaro, A., & Bruneaut, P. (2005, September). Performance evaluation of event detection solutions: the CREDS experience. In Advanced Video and Signal Based Surveillance, 2005. AVSS 2005. IEEE Conference on (pp. 201-206). IEEE. 116 University of Ghana http://ugspace.ug.edu.gh APPENDIX A UNIVERSITY OF GHANA BUSINESS SCHOOL DEPARTMENT OF MARKETING AND ENTREPRENEURSHIP INTERVIEW GUIDE TOPIC: “Choice as a constraint to Consumer Decision Efficiency: The Social Media Perspective” Dear Respondent: Thank you for making time to have this interview with me. This interview is designed to understand the role social media play on the behavioural patterns of consumers during their search for information and decision making. Kindly note that, this interview is purely for academic purposes and as such all information provided would be treated with utmost confidentiality. The researcher would appreciate it if all answers provided are very honest, since there are no wrong or right answers. Please note that you will be recorded so all responses and comments will be captured, therefore kindly try to speak up. Section A: General Information 1. My name is Judith Aku Masope-Crabbe. Please introduce yourself. Tell me your name, your age, your level of education, and Income range 2. Are you subscribed on any of the social media platforms? Section B: Respondents Profile a. Please tell me a little about yourself b. Which on the social network platforms are you active on? Section C: Social Media usage and decision making. a. Kindly give reasons why you are more active on the platforms just mentioned? b. Do you consider information on your SM platform in your purchase decision? c. What makes you trust social media as sources of information? d. Would you say that information on social media is too much or too less? e. Per your experience with social media, would you say the information distracts you or informs you in making good decisions? 117 University of Ghana http://ugspace.ug.edu.gh f. Do you check if information provided on social media meet certain characteristics before you read them and what are some of the characteristics? g. Can you let me know during which instances have you relied on social media to make decisions and what was the outcome? 118 University of Ghana http://ugspace.ug.edu.gh APPENDIX B UNVERSITY OF GHANA BUSINESS CHOOL RESEARCH QUESTIONNAIRE UNIVERSITY OF GHANA BUSINESS SCHOOL DEPARTMENT OF MARKETING AND ENTREPRENEURSHIP QUESTIONNAIRE Dear Respondent: The researcher is a Master of Philosophy (MPhil) Marketing student at the University of Ghana Business School, Legon-Accra. The researcher is undertaking a study on the topic “Choice as a constraint to consumer Decision Efficiency: The social media Perspective”. This is in partial fulfilment of requirement for the award of a master of philosophy degree in marketing. Kindly note that, this questionnaire is purely for academic purposes and as such all information provided would be treated with utmost confidentiality. The researcher would appreciate if all answers provided are very honest, since they are wrong or right answers. Indicate where appropriate (*) Section A: Demographic Information of Respondents 1. Sex a. Male [ ] b. Female [ ] 2. Age of Respondents a. 18-25 [ ] c. 26-35 [ ] d. 36-45 [ ] e. 46+ [ ] 3. Education Status a. JHS/SHS [ ] b. Diploma [ ] c. Degree [ ] d. Post-Graduate [ ] 4. Employment Status a. Student [ ] f. Employed [ ] g. Self-employed [ ] h. Unemployed [ ] i. Retired [ ] 5. Do you use Social media Platform a. YES [ ] b. NO [ ] 119 University of Ghana http://ugspace.ug.edu.gh 6. Which of the social media platforms are you subscribed on? Indicate as many as required. a. Facebook [ ] b. Twitter [ ] c. Instagram [ ] d. YouTube [ ] 7. How long have you been on social media? a. Less than one year [ ] b. 1-5 [ ] c. 6-10 [ ] d. 11-15 [ ] e. 15 + [ ] 8. Frequency of using social media a. Daily [ ] b. Once a Week [ ] c. More than Once a Week [ ] d. Once a Month [ ] e. More than Once a Month[ ] Kindly indicate your level of agreement or disagreement with the following statements as stated below, ranking from the lowest 1 –Strongly disagree (SD), 2 – Disagree (D), 3 – Neutral (N), 4 – Agree (A), to the highest 5- Strongly agree (SA). Section B: Choice overload SD D N A SA (1) (2) (3) (4) (5) There are so much information on social media to choose from that I feel confused The more I learn about these information on social media, the harder it seems to choose the best It is difficult to obtain an overview on products offered on social media With the many options to choose between on social media, I have a hard time identifying distinguishing product characteristics. Section C: Quality of Choice SD D N A SA (1) (2) (3) (4) (5) Social media information is of high quality to me Using social media to make decision appears reliable to me Using social media to make decisions is useful to me Social media information help me to make quality decision 120 University of Ghana http://ugspace.ug.edu.gh Kindly indicate your level of agreement or disagreement with the following statements after using social media to make a decision. Ranking from the lowest 1 –Strongly disagree (SD), 2 – Disagree (D), 3 – Neutral (N), 4 – Agree (A), to the highest 5- Strongly agree (SA). Section D: Post Purchase Dissonance SD D N A SA (1) (2) (3) (4) (5) I was in despair after using social media in making a decision I resented using social media in making decision I wonder if I really needed the product I bought using social media I wonder whether I should have bought anything at all using social media After I made a decision based on social media I wondered if I’d been fooled After I made this purchase decision using social media I wondered if there was something wrong with the deal I got 121