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FINANCIAL VIABILITY AND ADOPTION 
 OF THE ZECC TECHNOLOGY FOR TOMATO STORAGE IN 
SAVELUGU AND SAGNARIGU MUNICIPALITIES IN THE 
NORTHERN REGION OF GHANA 
 
 
BY 
EUNICE AMA ESSEL 
10598470 
 
 
 
 
THIS THESIS IS SUBMITTED TO THE UNIVERSITY OF GHANA, LEGON IN 
PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE AWARD OF 
MASTER OF PHILOSOPHY DEGREE IN AGRIBUSINESS 
 
 
DEPARTMENT OF AGRICULTURAL ECONOMICS AND AGRIBUSINESS, 
SCHOOL OF AGRICULTURE, COLLEGE OF BASIC AND APPLIED 
SCIENCES, UNIVERSITY OF GHANA, LEGON 
 
 
                                                                                                                            
                                                                                                                           JULY, 2018
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DECLARATION 
I, Eunice Ama Essel, the author of this thesis titled, “Financial Viability and Adoption of 
the ZECC Technology for Tomato Storage in Savelugu and Sagnarigu Municipalities in 
the Northern Region of Ghana” do hereby declare that, except for the references which 
have been duly acknowledged, this thesis was done entirely by me in the Department of 
Agricultural Economics and Agribusiness, University of Ghana, Legon from August 
2017 to July 2018.  This work has never been presented either in whole or in part for any 
other degree of this University or elsewhere.  
 
………………………….………     ……………………… 
Eunice Ama Essel        Date 
    (10598470) 
 
This thesis has been presented for examination with our approval as supervisors. 
 
………………………….………     ……………………… 
Mr. Ditchfield P. K. Amegashie        Date 
          (Major Supervisor) 
 
…………………………….…               ……….……………… 
Dr. Henry Anim-Somuah        Date 
       (Co-supervisor)  
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DEDICATION 
I dedicate this work to God Almighty for His guidance and protection; my beloved 
husband (Mr. Reuben Nartey), my lovely Essel family, and my special friends (David and 
Elsie Adomako-Kotei) for the love and support given throughout the period of my study.  
  
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ACKNOWLEDGEMENTS 
I thank the Almighty God for successfully seeing me through this piece of work. My first 
gratitude goes to my supervisors, Mr. Ditchfield P. K. Amegashie and Dr. Henry Anim-
Somuah, for their insightful contributions, constructive criticisms, suggestions and 
directives.  
I also wish to express my profound gratitude to Dr. Mrs Irene Egyir for her inspiration 
and motherly love shown throughout my studies, Dr. Akwasi Mensah-Bonsu and all the 
senior and junior members of the Department of Agricultural Economics and 
Agribusiness for their immense contributions towards the completion of this work.  
My indebtedness also extends to Leventis Foundation for funding my research. Tomato 
farmers and traders in the Savelugu and Sagnarigu Municipalities for their time during 
my data collection. Finally, I am grateful to Dr. Daniel Boamah, Mr. Vincent Yeboah-
Asuamah, Mr. Fustus Kwofie, Mr. Jacob Ankamah, Patience Bruku and all those who 
contributed in diverse ways to the success of this work.  
May the Good Lord enrich you all abundantly. 
 
 
 
 
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ABSTRACT 
Zero Energy Cool Chamber (ZECC) storage technology is the use of an evaporative cool 
chamber for maintaining low temperature of fruits and vegetables compared to field, shed 
and room temperature. In order to help farmers and traders, the ZECC technology was 
introduced in the Savelugu and Sagnarigu municipalities. However, only a few of the 
farmers and traders have adopted it in these municipalities. Although the ZECC seems to 
be a means to help solve storage challenges, the validity of the farmers’ and traders’ 
perception of high cost relative to returns in the usage of the ZECC cannot be ascertained. 
This study, therefore, sought to examine the levels of awareness and usage of the ZECC, 
compare the net benefits of the ZECC with the existing storage method, the factors that 
would influence them in adoption of the ZECC, and finally identify constraints that affect 
farmers and traders in using the ZECC. A multistage sampling method was employed to 
select 210 farmers and traders in the municipalities. The study used descriptive statistics 
such as frequencies, percentages, likert scale, the benefit-cost analysis, probit, and the 
Kendall’s coefficient of concordance (W) to address the objectives. Findings indicated 
that 83.33% of the respondents were aware of the ZECC technology but 26.19% have 
adopted the ZECC. The study revealed an NPV of GHS6, 436.15 and BCR of 1.52 for 
ZECC; and an NPV of GHS2, 699.41 and BCR of 1.09 for the existing method at 21% 
discount rate. With the exception of location, marital status and age, remaining factors 
were statistically significant to influence adoption of the ZECC. Among the constraints 
identified, access to credit and animal disturbances were ranked as the first and second 
most pressing constraints, respectively for farmers. High cost of transportation and high 
cost of storage were the first two most pressing constraints, in order of priority for 
traders. In conclusion, most of the respondents were aware of the ZECC but do not see 
the need for its usage, even though the ZECC proves to be more cost effective.  It is, 
therefore, recommended, among others, that agricultural training institution and NGOs 
should organize sensitization programmes and training sessions for farmers and traders 
on the ZECC. Additionally, developmental agencies should tailor their development 
plans and projects towards addressing these challenges that hinder the ZECC usage in the 
Northern Region of Ghana. 
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TABLE OF CONTENTS 
 
DECLARATION ................................................................................................................. i 
DEDICATION .................................................................................................................... ii 
ACKNOWLEDGEMENTS ............................................................................................... iii 
ABSTRACT ....................................................................................................................... iv 
TABLE OF CONTENTS .................................................................................................... v 
LIST OF TABLES ........................................................................................................... viii 
LIST OF FIGURES ........................................................................................................... ix 
LIST OF ACRONYMS ...................................................................................................... x 
CHAPTER ONE ............................................................................................................... 1 
INTRODUCTION............................................................................................................. 1 
1.1 Background ............................................................................................................... 1 
1.2 Problem Statement .................................................................................................... 3 
1.3 Objectives of the Study ............................................................................................. 7 
1.4 Relevance of the Study .............................................................................................. 8 
1.5 Organization of the Thesis ........................................................................................ 8 
CHAPTER TWO ............................................................................................................ 10 
LITERATURE REVIEW .............................................................................................. 10 
2.1 Introduction ............................................................................................................. 10 
2.2 Characteristics of Tomato ....................................................................................... 10 
2.3 Tomato Production and Marketing in Ghana .......................................................... 12 
2.4 Tomato Storage Systems ......................................................................................... 16 
2.4.1 Refrigeration: .................................................................................................... 16 
2.4.2 Freezing tomatoes: ............................................................................................ 17 
2.4.3 Canning Tomatoes: ........................................................................................... 18 
2.4.4 Drying Tomatoes: ............................................................................................. 18 
2.4.5 Zero-energy storage technology ....................................................................... 19 
     2.5 Tomato behaviour in the ZECC and other storage technologies ........................... 20 
 2.6 Studies on viability of the ZECC and other Storage Technologies........................ 22 
     2.7 Factors that Influence Adoption of Agricultural Technologies ............................. 23 
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2.8 Constraints Faced in Adopting Storage Technology …...………………………...30 
2.9 Summary of Literature Reviewed…………………………………………………36 
CHAPTER THREE ........................................................................................................ 35 
METHODOLOGY ......................................................................................................... 35 
3.1 Introduction ............................................................................................................. 35 
3.2 Research Design ...................................................................................................... 35 
3.3 Study Area ............................................................................................................... 35 
3.4 Conceptual Framework of the Study ....................................................................... 37 
3.5 Theoretical Framework ........................................................................................... 38 
3.6 Methods of Analysis................................................................................................ 40 
3.6.1 Determining the Level of Awareness and Usage of ZECC Technology .......... 41 
3.6.2 Comparing net benefits of ZECC storage technology and the TMS ................ 42 
Assumptions .......................................................................................................... 42 
‘With’ and ‘Without’ project cash flow analysis .................................................. 43 
Sensitivity Analysis .............................................................................................. 44 
3.7 Examining the Factors That Influence Tomato Farmers’ and Traders’ Adoption of 
Storage Technology....................................................................................................... 45 
3.8 Identification and ranking of constraints faced by farmers and traders in adopting 
ZECC technology .......................................................................................................... 51 
3.9. Methods of Data Collection ................................................................................... 53 
3.9.1 Types and sources of data ................................................................................. 53 
3.9.2 Sample size and sampling technique ................................................................ 53 
3.9.3 Survey Instrument............................................................................................. 54 
CHAPTER FOUR ........................................................................................................... 56 
RESULTS AND DISCUSSION ..................................................................................... 56 
4.1 Introduction ............................................................................................................. 56 
4.2 Socio-Economic Characteristics of Respondents .................................................... 56 
4.3 Level of Awareness and Usage of the ZECC Technology...................................... 58 
4.4 Comparing Cost and Benefits of the ZECC Tomato Storage Technology ............. 61 
4.4.1 Capital costs estimation .................................................................................... 61 
4.4.2 Average operating budget estimation ............................................................... 61 
4.4.3 Cash Flow Projections ...................................................................................... 63 
4.5 Factors Influencing Adoption of the ZECC by Farmers and Traders ..................... 66 
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4.6 Identification and Ranking of Constraints Faced by Farmers and Traders ............. 70 
4.6.1 Constraints faced by farmers ............................................................................ 70 
4.6.2 Constraints Faced By Traders ........................................................................... 71 
CHAPTER FIVE ............................................................................................................ 73 
SUMMARY, CONCLUSIONS AND RECOMMENDATIONS ................................ 73 
5.1 Introduction ............................................................................................................. 73 
5.2 Summary ................................................................................................................. 73 
5.3 Conclusions ............................................................................................................. 75 
5.4 Recommendations ................................................................................................... 76 
REFERENCES ................................................................................................................ 78 
APPENDICES ................................................................................................................. 86 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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LIST OF TABLES 
Table 3.1: Variables and a Priori Expectation of the Probit Model .................................. 47 
Table 3.2 Sample Size Distribution .................................................................................. 54 
Table 4. 1: Characteristics of Respondents ....................................................................... 57 
Table 4. 2: Level of Awareness and Usage of ZECC Technology ................................... 59 
Table 4.3 Reasons for ZECC storage Technology Usage................................................. 60 
Table 4.4 Reasons for TMS storage Usage ....................................................................... 61 
Table 4. 5: Average Capital Cost for a 50 Kilogram Capacity ZECC Facility ................ 61 
Table 4. 6: Average Operating Budget for a 50 Kilogram Capacity ZECC Facility ........ 63 
Table 4.7: Net Cash Flows for ZECC and TMS (in Ghana Cedis) ................................... 64 
Table 4.8: Annual Nominal Weighted Average Rural Wholesale Tomato Prices(GHS/Mt)
........................................................................................................................................... 65 
Table 4. 9: Results of Probit Model .................................................................................. 67 
Table 4. 10: Ranked Constraints of Farmers .................................................................... 71 
Table 4.11 Ranked Constraints of Traders ....................................................................... 72 
 
 
 
 
 
 
 
 
 
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LIST OF FIGURES 
Figure 2.1: Structure of the ZECC .................................................................................... 20 
Figure 3. 1: Map of Savelugu and Sagnarigu Municipalities in the Northern Region of 
Ghana ................................................................................................................................ 36 
Figure 3.2 Conceptual Framework ................................................................................... 37 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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LIST OF ACRONYMS 
BCA   Benefit-Cost Analysis 
BCR   Benefit-Cost Ratio 
CBR    Cost Benefit Ratio 
FAO   Food and Agricultural Organization 
FOASTAT  Food and Agriculture Organization Corporate Statistical Database 
GBO   Group Based Organization 
GLSS   Ghana Living Standards Survey 
GSS   Ghana Statistical Service 
Hort (CRSP)  Horticulture Collaborative Research Support Program 
MoFA   Ministry of Food and Agriculture 
NGO   Non-Governmental Organization 
NPV   Net Present Value 
SSA   Sub-Saharan African 
TMS   Traditional Method of Storage 
USAID  United States Agency of International Development 
ZECC   Zero-Energy Cool Chamber 
 
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CHAPTER ONE 
INTRODUCTION 
 
1.1 Background  
In the quest to reduce post-harvest losses, solve problems with food quality, safety and 
nutrition, and improve the livelihood of farmers and traders in the agricultural sector at 
the global level, Roy and Khurdiya (1983) invented the Zero-Energy Cool Chamber 
(ZECC) storage technology at New Delhi, India in the 1980s. They indicated that it has a 
potential of reducing the level of fruits and vegetable losses. The ZECC is an evaporative 
cool chamber which maintains considerably and relatively low temperature of fruits and 
vegetables compared to field, shed and room temperature, that will prolong the shelf life 
of the fruits and vegetables (Dubey, Roy, Saran & Raman 2013). The ZECC storage 
technology has been tested and proven to be safe and of good quality over the years 
(Kirk, 2014).  
In view of the ZECC storage technology quality, a pilot program was introduced in 2012 
by the USAID in collaboration with the Horticulture Collaborative Research Support 
Program Hort (CRSP) to help solve issues related to physical losses of horticultural crops 
after harvesting, which continues to range from 30-80% in the Sub Saharan Africa (SSA). 
The Hort (CRSP), MoFA and other stakeholders have contributed tremendously towards 
the implementation of the ZECC in the Northern region of Ghana during the major 
training on the ZECC storage in Tanzania (Kitinoja & Barrett, 2015). This was with the 
aim of sustaining fruits and vegetables production and storage system in the rural 
communities in the Sub Saharan African countries.  
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The implementation of Hort (CRSP)’s objectives led to the construction of about five(5) 
demonstration sites of the ZECC storage technology to enhance farmers’ and traders’ 
training on the usage of the ZECC for storage of their produce (tomato most especially) 
in the Northern region.  Over the years, smallholder tomato farmers and petty traders rely 
on the traditional method of storage (TMS) at the Savelugu and Sagnarigu municipalities. 
However, challenges associated with the off-farm storage and high post-harvest losses, 
boosted the Hort (CRSP) to promote the use of the ZECC storage technology. The ZECC 
storage technologies together with other cooling evaporative systems are appropriate for 
the storage of high value crops such as vegetables and/or fruits (Roy and Pal, 1988). 
ZECC has a better evaporative cooling system for prolonging shelf-life of the produce 
after harvest. According to Singh, Singhrot, Sharma and Sadooja (1987), using the ZECC 
storage technology could reduce water loss of fruits and/or vegetables and retain the 
fruits and or vegetables freshness during storage. ZECC system has several justifications 
in relation to its benefits and usage in the Sub-Saharan African countries. 
The need for the usage of the ZECC was identified when the Ghana Statistical Survey 
(GSS) (2014), rendered the northern part of Ghana as the poorest in the country during 
their survey on poverty profiling in Ghana. It has, therefore, become necessary to 
promote the adoption of the ZECC storage technology in this part of the country. 
Furthermore, the high records on post-harvest losses of fruits and vegetables increases the 
level of diversity into other businesses by farmers and traders in the area.  
Therefore, the need for appropriate, reliable, eco-friendly and low-cost storage 
technology coupled with increasing diversity of the tomatoes business in the Northern 
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region calls for the development and adoption of improved agricultural storage 
technologies. ZECC storage technology promises a substantial increase in agricultural 
processing and storage especially for high water content fruits and vegetables like tomato 
and an increase in household income. The high temperatures and lack of access to cold 
storage facilities in West Africa contribute largely to the high perishability of fresh 
tomatoes (Robinson, Kolavalli, & Diao 2012). 
Moreover, Robinson et al. (2012) reported that the shelf life of tomato is often less than a 
week due to the methods used in cultivating the tomato and the varieties grown. Small-
scale farmers and petty traders using the ZECC are able to prolong the life span of fruits 
and vegetables for up to nine days by storing their produce in simple non-energy reliant 
cool chambers like the ZECC. According to Singh et al., (1987), the Zero Energy Cool 
Chamber storage technology does not require any form of power to run. This makes it 
convenient for off-the grid farmers and traders. It is in this light that USAID in 
collaboration with Hort (CRSP) came up with the pilot program in the municipalities to 
help train more facilitators that would impact on farmers and traders on the benefits of 
adopting the ZECC. Pal & Roy (1988) concluded that, a major key element to reduce 
poverty in our rural areas and enhance the agricultural sector especially hot climate areas 
is the adoption of the ZECC and other modernized technologies. This study, therefore, 
focuses on the adoption and test of viability for the ZECC storage technology in the 
Savelugu and Sagnarigu municipalities of the Northern region of Ghana. 
1.2 Problem Statement 
According to Sibomana, Workneh and Audain, (2016) the Sub-Saharan African (SSA) 
countries face a lot of post-harvest losses in the supply of freshly harvested tomato. These 
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challenges are as a result of poor storage, handling, lack of cold storage facilities, and 
inadequate monitoring, among others, in the SSA countries. In most tropical countries, 
quality deterioration of horticultural produce including tomato occurs immediately after 
harvest due to lack of on-farm storage facilities and maintenance of low temperatures in 
fruits and vegetables including tomatoes (Sharma, Pal, Singh, Kar & Asrey, 2004) 
 Food and Agriculture Organization estimated that about 40% of farm fresh produce goes 
bad after harvesting and results in its perishability due to issues related to postharvest 
losses (MoFA, 2012). According to Kearney (2010), although farmers have increased 
tomato production levels over the past decade, proper technologies needed to avoid or 
reduce post-harvest losses particularly the rate at which tomatoes rot or perish has not 
been keenly given attention. This is evidenced by food losses occurring due to post-
harvest losses and inadequate storage and marketing system (MoFA, 2012). 
 Current studies on tomato production and marketing of tomato in Ghana by Robinson & 
Kolavalli (2010) showed that, most of the vegetables and fruit farmers in the rural areas 
sell their produce to middle market woman just after the harvest. In some cases, the 
middle marketers come to harvest themselves after the price has been bargained between 
the farmers and traders. 
 Lack of good transportation systems or poor roads, inadequate energy supply, lack of 
investment in storage mostly results in lower price of vegetables and fruits during the 
peak harvesting season.  Farmers in the remote areas mostly sell their produce in the local 
market at low prices to petty traders (Yeboah, 2011).  Most farmers are unable to get 
the return of invested money of cultivating their vegetables or fruits. As a result, a high 
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percentage of poverty level still remains in such rural areas.  Additionally, traders in these 
areas are unable to sell all their tomatoes among other vegetables and fruits during market 
days. Storage of these left overs becomes a headache to the traders due to the high cost 
involved in cold chain storage. Inability to store leftovers also results in early 
deterioration of the leftover tomatoes causing losses to the traders. 
 
Considering acute energy crisis, high costs involved in the usage of refrigerators and lack 
of cold storage facilities in remote areas like the northern regions of Ghana, the adoption 
of new technologies become crucial. In most cases, whenever there is the introduction of 
new technologies in rural areas, smallholder farmers and traders are unwilling to adopt 
that particular technology, but continue to apply their old methods (Kitinoja & Barrett, 
2015).  The unwillingness of farmers and traders to adopt new technologies has been 
observed in the Savelugu and Sagnarigu municipalities. Very few farmers and traders in 
these municipalities have adopted the ZECC storage ever since its introduction. This is as 
a result of their perception of high costs involved in the adoption of the ZECC storage 
technology. 
Although studies consider the ZECC storage technology as a low cost storage system 
which does not require electricity for operating (Islam et al., 2014); there is no 
documentation on the financial viability of the technology in the Savelugu and Sagnarigu 
municipalities to substantiate or otherwise the perception of the farmers and traders on 
the costs and returns involved in the usage of the ZECC. Sufficient information on 
farmers’ and traders’ unwillingness to adopt the ZECC and cost-benefit analysis is 
necessary for the formulation in tomato storage. In order to ascertain or otherwise the 
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perceived high cost involved in adopting the ZECC storage technology. It is appropriate 
to know whether it is viable to use the ZECC for storage. This would inform farmers’ and 
traders’ decision to either adopt or continue to use the existing method of storage. 
Knowledge on the viability of the ZECC will enable the few adopters (early adopters) to 
back up on the maximum and proper usage of the technology adopted, so that the rest 
(late adopters) will follow suite. Nzomoi, Byaruhanga, Maritim and Omboto (2007) 
indicated that it is apparent that potential and/or early adopters of every new technology 
always consider the financial implications of the technology.   
To ensure full adoption of the ZECC, the early adopters would have to be updated on the 
amount of money needed for their technology, cost involved towards the operations and 
maintenance of the ZECC, and most importantly know whether they are making profit or 
not. This will help decrease the uncertainties about the ZECC storage.   
Empirical information on the validity of the farmers’ and traders’ perception of high costs 
relative to returns in the usage of the ZECC technology cannot be ascertained and 
majority of farmers and traders continue to use the traditional method of tomato storage. 
Even though there are some studies conducted in other countries in relation to the ZECC 
adoption, there is no study specifically addressing the storage technology adoption in 
Ghana. 
Factors that will compel them to adopt the ZECC still remain unknown. It is also 
observed that, all technologies come with impediments and/or constraints hindering their 
smooth adoption and ZECC cannot be an exception. It is, therefore, imperative to identify 
the constraints faced in the usage of the ZECC for tomato storage for policy direction. 
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This study is ultimately designed to provide empirical answers to the under listed 
research questions: 
1. What is the level of awareness and usage of the ZECC storage technology among 
tomato farmers and traders in the Savelugu and Sagnarigu municipalities? 
2. How do the net benefits of ZECC technology compare with the net benefits of the 
traditional method of storage in the study area? 
3. What are the factors that influence the adoption of ZECC storage technology in 
the study area? 
4. What constraints do farmers and traders face in using the ZECC technology in the 
study area? 
1.3 Objectives of the Study 
The general objective of the study is to assess the financial viability and adoption of the 
ZECC storage technology in the Savelugu and Sagnarigu municipalities in the Northern 
region. This was achieved through the following specific objectives: 
1. To determine the level of awareness and usage of the ZECC storage 
technology in the Savelugu and Sagnarigu municipalities. 
2. To compare the net benefits of using the ZECC storage technology with the 
net benefits of the traditional method of storage in the study area. 
3.  To examine factors influencing tomato farmers’ and traders’ adoption of the 
ZECC storage technology in the study area. 
4. To identify and rank the constraints faced by the farmers and traders in using 
the ZECC technology in the study area. 
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1.4 Relevance of the Study 
Having had ample literature on high rates of postharvest losses in tomato, it would be 
relevant to conduct studies that would suggest policy implications on how to improve on 
tomato storage and assess the overall financial viability of the tomato storage in Ghana. 
Although studies have been conducted on the economics of the ZECC storage technology 
elsewhere, the financial viability and factors that would influence its adoption has not 
been done in Ghana.  
 
This study, therefore, seeks to create awareness on costs and benefits of using the ZECC 
storage technology in the Northern Region of Ghana, and provide stakeholders with 
relevant information on whether to invest in the technology or not. The findings in this 
study would also be a guide to facilitate future technological interventions by 
government, NGOs, and other stakeholders in making smallholder agriculture more 
efficient and attractive.  
Also, this study would be of great significance since it would be added to existing 
literature and those in academia for future research. Finally, it will be of relevance to 
government in policy formulations, especially on the aspect of government investments 
and spending in tomato storage. 
 
1.5 Organization of the Study 
This study is organized into five chapters. Chapter One gives the background of the study 
with emphasis on the specific problems leading to the study. Chapter Two presents 
review of literature related to the study. Chapter Three provides the methodology for the 
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study, including methods employed to analyse the set objectives, description of the study 
area, and data collection. Chapter Four presents the empirical results with discussion. 
Chapter Five, is the final chapter which presents the summary of the study, conclusions 
and recommendations based on the findings.  
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CHAPTER TWO 
LITERATURE REVIEW 
 
2.1 Introduction 
This chapter presents review of relevant literature on the study. It highlights the 
characteristics of tomato, tomato production and marketing, the benefits of tomatoes 
storage systems, viability of the ZECC storage together with other storage technologies, 
types of storage and its process for usage, examination of the determinants of farmers’ 
and traders’ decision to adopt a storage technology, and other studies on adoption in 
relation to agricultural technology usage. And finally, literature on the various constraints 
farmers and traders face in adopting storage technologies as a whole.  
 
2.2 Characteristics of Tomato 
Tomato (Lycopersicum esculentum Mill) belongs to the Solanaceae family, which also 
includes other well-known species such as potato, tobacco, pepper and eggplant. Tomato 
has its origin in the South American Andes (Van, Goffau, Van Lidt de Jeude, & Naika, 
2005). As per Anang et al., (2013), the extremely different and extensive Solanaceae 
family is accepted to comprise 96 genera and more than 2,800 species conveyed in three 
sub-families: Solanoideae (in which Solanum has a place), Cestroideae, and Solanineae. 
According to Tambo & Gbemu, (2010), tomato is scientifically known to be a fruit but in 
trade is it categorised among vegetables. 
Tomato is known to be a moderately brief span crop and gives a high return; it is 
monetarily profitable. It needs a moderately cool, dry atmosphere for high returns and 
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better quality (Arah, Kumah, Anku & Amaglo, 2015). However, it can adjust to an 
extensive variety of climatic conditions of varied temperatures. In the Tropics, tomato is 
severely constrained by insects and mite pests (Ntow, Gijzen, Kelderman & Drechsel, 
2006). Tomatoes are perishables which could decay easily if not properly handled and 
these affect their taste, flavour and nutritional value (Van et al., 2005). 
Tomato is one of the important crops recently cultivated in both rainy and dry seasons in 
Northern Ghana and Southern Volta (Ntow et al., 2006). It provides important nutrients 
to food consumed at the household level, and many Ghanaian meals have tomatoes as an 
ingredient (Tambo & Gbemu, 2010). The high rainfall and humidity in Ghana breed pests 
and diseases, which adversely affect tomato production as reported by Anang, Zulkarnain 
and Yusif (2013). When tomato is harvested, environmental conditions considered as 
latent energy is removed from the canopy through evapo-transpiration mechanism, and 
make the tomato become more vulnerable to direct solar radiation. This is a major 
problem when tomato is transported in vehicles that are not climate controlled (FAO, 
2003). 
The features of tomato that are most desirable and appreciated by consumers are with its 
texture (firmness), size, shape, and colour. A variety of quality attributes of fresh produce 
can be considered in terms of colour as studied by Hossain, Strezov, Chan, & Nelson, 
(2010). Firmness is a widely accepted indicator of quality which can be measured easily 
and which has direct economic consequences. In addition, firmness is highly sensitive to 
external environmental conditions such as temperature and relative humidity. 
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Tomato is rich in folate, phytonutrients, carotenoids, lycopene, gamma-carotene and 
photogene, and in addition a few minor carotenoids (Anang et al., 2013). It is also rich in 
minerals, vitamins, fundamental amino acids, sugars and dietary filaments. Tomato 
contains vitamins B and C, iron and phosphorus. The crop is easily prepared into purees, 
juice, ketchup, and other forms which are used in different meals.  
 
2.3 Tomato Production and Marketing in Ghana 
Production  
Tomato production plays an essential role in the economic activities in Ghana, especially 
in the Northern, Upper East and around southern Volta regions of Ghana (Gould, 2013). 
Major production areas includes Akumadan and the Wenchi districts. Commercial 
production, according to Norman (1992), is centered on Mankessim, Swedru, Agogo, 
Nsawam, Amasaman, Sege and Dodowa. Tomato production in Ghana is intensive, even 
though the methods of production are relatively old. The soil is usually prepared by 
crating hoes. The plants are grown in raised beds where watering is done by hand. The 
plants are grown in mounds, and seedlings are grown in nursery beds and transplanted to 
the field. In the field, the plants are staked and usually pruned to single stem. 
 The plants are uncertain, so flowering and fruit set occur over a considerable period of 
time. The commonly produced varieties are Roma, Pectomech, Burkina and Power (Khor 
& Hormeku 2006). According to Robinson & Kolavalli (2010), Ghana’s tomato sector 
has been unsuccessful in attaining its potential in terms of yields comparable to other 
countries, in terms of the ability to sustain processing plants, and in terms of improving 
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the livelihoods of households involved in tomato production and the tomato commodity 
chain. 
With different government interventions such as the establishment of tomato processing 
factories, the favourable quality and quantity of tomatoes for commercial agro- 
processing are not being produced (Norman, 1992). Many farmers still prefer to plant 
local varieties, typically with a high water content, many seeds, poor colour, and low 
brix. Land husbandry practices are often suboptimal. Average yields remain low, 
typically under ten tons per hectare (Robinson & Kolavalli, 2010).  
Because of production seasonality, high perishability, poor market access, and 
competition from imports, some farmers are unable to sell their tomatoes, which are left 
to rot in their fields. Yet other farmers in Ghana have achieved higher tomato yields, 
production is profitable, and many farmers in Ghana continue to choose to grow tomatoes 
over other crops (Yeboah 2011). One of the key issues for tomato farmers in Ghana is 
high per-unit input cost. The cost of production and the returns attained after sales of the 
tomatoes mostly results in low income.  
When farm gate prices are low and variable, as is mostly the case for rained farmers who 
plant according to the rains. These farmers are used to harvesting their produce at a 
similar time, which in turn reduce the per unit input costs. Further, for tomato processing 
to be competitive in Ghana, average per unit production cost needs to be considerably 
lower so that farmers can sell their tomatoes profitably at the low but guaranteed prices 
offered by the processors (Aidoo et al., 2014). 
 
 
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Marketing of Tomatoes 
Tomato is one of the commonly demanding vegetables in Ghana. The in-take estimates 
from the 2012-2013 Ghana Living Standards Survey (GLSS) show that households spend 
about 12.8 % of total food expenditure on vegetables, of which the highest was  tomatoes, 
an expenditure of (35.2 %). In spite of tomatoes demand and its necessity in the country, 
the demand for it is largely supplied by imports. Most especially from Burkina Faso. 
Ghanaian farmers are mostly unable to meet the productivity levels needed for the tomato 
to compete in the regional market, which according to the traders it is a mere perception 
or a myth. 
The ability to bargain on a fair price mostly depends on whether a farmer will choose to 
produce the crop in the next season or whether the farmer will make investments to 
increase his or her income (Harriss, 1979). Trader decision to continue buying and selling 
tomatoes is equally based on these pricing effects.  In Ghana, most of the vegetables 
marketed are affected by the associations of traders in a particular market. These 
associations are largely made up of wholesalers and retailers. These wholesalers and 
retailers are also controlled by female leaders called ‘Queen Mothers’ or ‘Market 
Queens’ (Robinson & Kolavalli 2010).  
Peppenelen (2005) reported that these market based associations have the monopoly-like 
power in the vegetable sector in Ghana, especially when it comes to tomato marketing. 
These associations restrict mostly, the vegetable supply in the market system. First, in 
some markets, the wholesalers and retailers are forced to be registered members of the 
market before they can sell out their tomatoes. Traders who fail to do so are either not 
allowed selling in those markets or buying from the registered wholesaler. Secondly, 
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because these associations have the power to control the market; they determine the 
quantity of supplies that enters the market. This is done by limiting the total number of 
trucks that comes to their market to offload the tomatoes (Robinson & Kolavalli 2010). 
Due to these reasons, farmers are not allowed to have access to this market when they 
harvest. 
Tomato traders mostly travel to vegetable farms to purchase their produce. They mostly 
bargain with the farmers on the quantity and price at which they wish to buy the tomatoes 
and other vegetables available. Upon reaching a reasonable price, the farmers give the 
traders the produce. Even in some cases of the tomatoes in the major production areas, 
the traders harvest the tomatoes themselves, or hire labourers to do the harvesting. The 
major problem with this system of marketing vegetables is that, farmers are unable to 
have the bargaining right. The perishable nature of vegetables subjects the produce to 
early deterioration: and when sales are delayed, results in rotting and loss to the farmer or 
producer. This makes about 60% of the farmers’ sales at the farm gate stage (Robinson et 
al., 2012). 
The farm gate sales involves two types of buyers; thus, local buyers who sell to nearby 
markets, and traders or middlemen who buy and transport the produce to major markets 
at the capital cities. Farmers who sell their tomatoes themselves mostly are registered 
members of that particular market (Harriss, 1979).  Recently, it was reported by Robinson 
& Kolavalli (2010) that, educated farmers now sell their tomatoes to one known buyer 
per season. This helps the farmers increase their profit and reduces the losses they were 
making previously. It is quite interesting to know that, most of the farmers who sell at 
farm gate received higher prices on average than farmers who sell their produce in the 
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market. Although this may not be economically sound, it is the situation involved in the 
marketing of tomatoes in Ghana. Tomato prices averaged almost GHS 80 per crate if 
farm sales took place as opposed to off-farm. The production of tomatoes in the Upper 
East overlaps peak production in Burkina Faso. Ghanaian traders, who control access to 
important markets, prefer to buy Burkina Faso tomatoes (Robinson et al., 2012).  
Trader’s claim that the Burkina Faso tomatoes are of better quality than those from the 
Upper East, especially because they last longer and travel better, reducing the risk of loss 
to wholesalers. The association of tomato traders who import from Burkina Faso also 
claimed that locally produced tomatoes no longer stay on the same day as the tomatoes 
they import (Yeboah, 2011). In a survey done by Robinson et al. (2012), they found that 
tomato farmers do not store their crops for long. Especially tomato, irrespective of where 
ever their farms may be located, implying that  most farmers would prefer to sell out their 
tomatoes instead of  processing them to be sold later or storing them to meet the lean 
season where prices of tomatoes are higher. 
 
2.4 Tomato Storage Systems  
There are several storage systems for preserving fruits and vegetables particularly fresh 
tomatoes. Some of the systems have been highlighted and discussed as follows: 
Refrigeration: 
Fresh tomatoes purchased from a retail outlet or at a farm gate, usually ripe can best be 
eaten within 2 to 3 days if stored under room temperature. Within these days, the quality 
of the tomatoes is retained and hardly deteriorates (Parnell, Harris, & Suslow 2005). 
However, the unripe tomatoes can be held from a retail outlet for quite a longer time as 
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compared to the ripe tomatoes. Refrigeration is not generally prescribed for freshly 
harvested tomatoes as it can cause season misfortune and also result in reduction of the 
tomato during sales. Softening of "simply ready" tomatoes can be postponed by holding 
them for a brief time frame in refrigerated capacity. Flavour misfortune will be 
insignificant if icy stockpiling keeps going under three days. 
In the event that fresh tomatoes have to be refrigerated, they must be in the crisper area in 
their plastic clamshell compartment (if that is the means by which they were pack-
matured in the store). A paper sack or a plastic sack should be used with a couple of 
openings, to help diminish water misfortune. It is best to expel the tomato from the fridge 
one hour before eating to enable it recovers a portion of its unique flavour. 
Freezing tomatoes: 
According to Parnell et al., (2004), tomatoes might be solidified to save life expectancy 
for a little while. In the process of freezing the tomatoes, they should be whitened before 
solidifying. Once solidified, the tomatoes are exchanged from the treat sheets into cooler 
packs or different compartments and sealed firmly. To utilize the solidified tomatoes, it is 
expelled from the cooler almost immediately or late. Frozen tomatoes can be used by 
peeling, and simply running a solidified tomato under warm water in the kitchen sink. 
The tomato skin slips off effortlessly. On the other hand, processing the tomato into other 
forms like blending or chopping into smaller pieces can be done and the freezing system 
can be applied after the processing. 
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Canning tomatoes: 
Tomato canning is done by selecting healthy matured tomatoes; while sorting all spoilt 
and overly ripped tomato. The selected tomatoes are then washed in clean water and 
boiled. Boiling is prolonged enough to ensure that the tomato skin is cracked. They are 
then transferred into cold water for the skin to come off easily, after which the boiled 
tomato is stored in a sealed container (Parnell et al., 2004). 
Drying tomatoes: 
Drying tomatoes may be in the form of dehydration, oven drying or microwave drying. 
Dehydration drying reduces dampness of tomatoes to prolong their time of perishability. 
The amount of time it takes to dry tomatoes to some extent depends on the tomato 
assortment, the dampness amid the drying procedure, the thickness of the tomato cuts or 
pieces, and the proficiency of the dehydrator (Parnell et al., 2004). 
Oven drying of tomatoes is possible, but because tomatoes takes a longer time to dry 
well, it is not advised most of the time. The method of drying sometime makes the 
kitchen hot. The heat formed during the drying sometimes can cause the skin of the 
person drying to burn. Where microwave drying is done, it needs enough attention, and 
frequently opening the microwave door to allow moisture to escape. Microwave-dried 
tomatoes do not dry evenly, and can easily scorch or burn. 
Clay pot storage: 
This storage is done by inserting a constructed clay pot in another clay pot (pot-in-pot). In 
India, this type of storage is also referred to as Zeer. The space between the two pots is 
filled with sand and wetted some few minutes before the harvested tomatoes or left over 
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tomato are stored. Pal et al., 2004) reported that the wet surface around the pot makes the 
inside of the inner pot cool. The tomato is then sorted, cleaned and placed in the pot.  
 
Ash storage:  
Ash storage is done by burning dry banana leaves with other crop debris. The ashes are 
then collected, seized and placed in boxes. Matured tomatoes are kept in the ash for 5 to 6 
days and sold out or used (Anaisk, 2017).  Although this storage does not store for long, 
the quality of the tomato remains unchanged.  
 
2.4.5 Zero-energy storage technology 
According to Sturm et al., (2012), a zero energy cool chamber does not need any type of 
energy to run. The structure which is constructed with locally accessible materials, 
depends on the evaporative cooling system. Materials required include blocks, stream bed 
sand, bamboo and water. Two parallel block dividers are built into a type of rectangle 
over the ground, and the space between the dividers filled with sand. The structure is 
illustrated in Figure 2.1. 
A standard scale unit of about 165 cm by 115 cm floor is built, with a cavity of 67.5 cm 
high, leaving a space of about 7.5cm. The sand-filled space is soaked with water, and a 
shed made of bamboo and straws of grass is constructed over the chamber. Evaporative 
cooling happens when air, escapes from a wet place (Pal & Roy, 1988). This cools the 
sand-bed of the cool chamber. As water dissipates from the bed, it causes a cool impact 
and speedier rates of dissipation prompt more noteworthy coolness. 
 
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2.5 Tomato behaviour in the ZECC and other storage technologies 
In a test on how tomato behaves in the ZECC storage technology, Islam et al., (2013) 
reported that harvested tomato at maturity has a shelf-life of only about seven (7) days at 
ambient temperature. Storing tomato inside the ZECC could extend storage life up to 
fifteen (15) days by reducing the rate of its degradation due to reduced weight loss. Loss 
in weight (PLW) was faster for fruits held at ambient temperature. Weight loss during 
storage at ambient temperature was 5.4%, but using ZECC storage over the same period 
showed a weight loss of 2.6%. 
 
Figure 2.1: Structure of the ZECC 
 
Source: Anais (2017) 
The effect of hot water treatment (60℃ for 3 minutes) on quality of tomatoes was found 
to increase storage life up to twenty-nine (29) days. It reduced weight loss and decay, 
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inhibited colour development and maintained firmness of tomatoes. Hot water treatment 
slightly reduced the mould growth of tomatoes stored inside ZECC.  According to Islam, 
et al. (2013), the ZECC storage technology is considered a very low cost technology 
structure, with the following advantages during its usage:  
1. The nutritive value of fruits and vegetables stored under the ZECC is always 
retained and is very environmentally friendly. 
2. The ZECC does not only reduce the air temperature around the produce, but also 
raises the moisture content of the air. This helps to prevent the drying out of the 
produce and, therefore, extends its shelf life. 
3. It is inexpensive to install, and can be easily made, operated and maintained. 
4. It is basically constructed using unskilled labour, without the application of 
machines or electricity, and  
5.  It is economical and can store ripe fruits and vegetables for 3 to 5 days without 
any significant loss (Pal & Roy, 1988). 
Although the ZECC has several advantages, it also has a number of disadvantages. 
Notable among them are the following: 
1. Evaporative cooling system requires a constant water supply to wet the pads, and 
therefore, needs to be watered daily (Ambuko, Wanjiru,  Chemining’wa, Owino, 
& Mwachoni, 2017). 
2. Enough space is required outside the home; therefore in locations where there is 
limited space, it makes the effective use of the ZECC difficult. 
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3.  ZECC requires a lot of water, and therefore, when water which is high in 
minerals is used, it leaves mineral deposits on the pads (bricks) and damage the 
interior of the cooler.  
4. A high humidity situation reduces the cooling ability of the chamber (Ambuko et 
al., 2017). 
5. Evaporative cooling adds moisture; and in dry climates, dryness may not improve 
thermal comfort at higher temperatures. 
 
2.6 Studies on Viability of the ZECC and Other Storage Technologies 
The ZECC and other storage technologies for storing fruits and vegetables over the past 
decade have been of keen importance (Singh et al., 2007). Some studies have been 
conducted to ascertain the profitability of some of these storage technologies.  Among 
others, Pal & Roy (1988) in assessing the economics of the ZECC and the Clay Pot 
storage technologies in India used the Cost-Benefit technique in their analysis and 
reported positive Net Present Values (NPVs) for both selected storage technologies. This 
suggested that storage under these storage technologies would be financially viable. They 
recommended improvement on these structures and the promotion of education to ensure 
sustainability and profitability of these technologies. 
Equally, in Sierra Leone, Jenny, Anakus, & Nwimana (2013) confirmed a positive Net 
Present Value for the usage of the Ash storage technology (a new technology introduced) 
and the traditional storage system for tomato. Although their analysis of the viability had 
a limitation, the Net Present Value and the Benefit-Cost Ratio of the Ash storage were 
greater than those of the alternative traditional storage system. Based on these results, 
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they concluded that investment in the Ash storage was more viable and should be adopted 
by the native farmers in the study area. 
Drew and Rhee (1980) on the other hand used the profit and loss analysis in determining 
the cost and benefit of using freezer and other energy demanding storage  and revealed 
that energy demanding forms of storage are cost effective. 
 
2.7 Factors that Influence Adoption of Agricultural Technologies 
 Technology adoption has not achieved a standard definition by many researchers. Most 
current amongst the new definitions have been that of Loevinsohn, Sumberg, and Diagne  
(2012). They defined technology adoption as the processing and acquiring of a systematic 
ease device which results in an easier and accurate work done as compared to the non-
existence of that device. As per these writers, the technology adopted is mostly new in 
the areas where they have been introduced , and hence, how the technology is used, or 
about to be used at a specific place depends on the culture and level of knowledge of the 
people in that location. According to Lavison (2013), adopting technologies are the 
learning or data that makes a few assignments to be finished more effectively. This helps 
the users of the technology to work less than they would have without that technology. 
Thus it enables spare time and work (Bonabana-Wabbi 2002). 
Quite a lot of literature has been reviewed when it comes to technology adoption and the 
determinants of its usage. According to Loevinsohn et al. (2012), the decisions taken 
when a person wants to use a new technology is dependent on the nature of the 
technology itself and situations around the surroundings (place) of that technology. A 
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comprehension of the components affecting this decision relies both on the financial 
analysis and the dissemination of such technology (Pavao, 2005). 
Generally, financial investigation on innovation appropriateness clarifies selection 
conduct in connection with individual attributes and enrichments, defective data, hazards, 
vulnerability, institutional requirements, input accessibility, and framework (Feder et al., 
1985; Koppel 1994; Foster & Rosenzweig 1996; Kohli & Singh, 1997; Rogers, 2003 and 
Uaiene, 2009). A few examinations group these variables into various classifications. For 
instance Akudugu et al., (2012) assembled the determinants of technology adoption into 
three classes: financial, social and institutional components. Lavison (2013) extensively 
arranged the components that impact selection of advances into social, economic and 
physical classifications, while McNamara, Wetzstein and Douce (1991) sorted the 
variables into users attributes institutional qualities and administrative structure. 
Technology factors: 
The nature of a technology introduced can determine whether or not people will adopt it 
or not. The extent to which a potential adopter would try a technology depends on the 
results observed or seen by previous users of that technology (Arah et al., 2016). In 
considering the determinants of a new technology in Western Kenya, farmers who saw 
the benefit of using the Imazapyr-Resistant maize (IRM) adopted it earlier. When they 
discovered that, the use of the newly introduced maize crop resulted in high yield, 
reduces the level of damage, and had a positive venture; their adoption rate increased 
(Mignouna, Manyong, Rusike, Mutabazi, and Senkondo, 2011).  
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A comparative outcome was accounted for by Doss (2003) when contemplating on the 
understanding of farmers’ level when it comes to technology adoption in the Eastern 
Africa reported that, the perception towards the adoption of a technology was based on 
the fact that, it was appropriate to use and the conditions around its adoption was based 
on the fact that, an NGO was given subsidies to the adopters. 
Institutional factors: 
Having a social gathering improves social capital, permitting trust, thought and data trade 
(Mignouna et al., 2011).  As indicated by Mwangi and Kariuki (2015), farmers and 
traders belonging to a social gathering gain from each other and the advantages of the use 
of another innovation. Uaiene et al.,(2009) proposes that interpersonal organization 
impacts are essential for singular choices, and that, in the specific setting of agrarian 
developments, ranchers share data and gain from each other centering on the impact of 
group based association in selection of the innovated technology in Uganda, Katungi and 
Akankwasa (2010) found that ranchers (managers of larger farms) who partook more in 
group-based associations were probably going to show more interest in trying to know 
more about the innovation, consequently raising their probability to receive the 
advancements. Numerous analysts have revealed a positive impact of social gathering on 
technology adoption or an innovation selection. 
Foster and Rosenzweig (1995) when considering reception of Green Revolution 
innovations in India found that learning externalities inside informal communities 
expanded the productivity of selection, yet additionally agriculturists gave off an 
impression of being free-riding on their neighbours’ experimentation with the new 
innovation. Bandiera and Rasul (2002) in Hogset (2005) revealed that learning 
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externalities produce inverse impacts to such an extent that, the more other individuals 
take part in experimentation with another innovation, the more useful it is to participate, 
and the more helpful it is to free-ride on the experimentation of others. In addition to 
factors that aid adoption of new innovations, access to extension service and access to 
credit were also reviewed.  
Access to extension services:  
Agriculturists are educated on the viable utilization and advantages of new innovations 
through extension officers. Extension officers serve as specialists between the trend-
setters of the innovation and clients of a given innovation. This lessens exchange costs 
incurred when passing on the new innovation to an expansive heterogeneous populace of 
ranchers (Genius et al., 2010). Extension specialists, more often than not, target particular 
agriculturists who are perceived as educators, as the major source of influence to farmers 
in terms of innovation adoption (Genius et al., 2010). 
There have been numerous creators who have reported positive relationship between an 
innovation selection and technology adoption. An example of this relationship is an 
adoption study on the maize resistant crop by Mignouna et al. (2011); factors influencing 
the decision to select the innovation reception among Nepalese (Karki & Bauer, 2004; 
Uaiene et al., 2009); adoption of enhanced maize and land administration in Uganda by 
Sserunkuuma (2005); and selection of current farming advances in Ghana by Akudugu et 
al., (2012). 
 
 
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Access to credit: 
Having access to credit mostly influence an individual to either adopt the technology or 
otherwise, (Mohamed & Temu, 2008). It is observed that, having access to credit 
advances the reception of hazardous innovations through the boosting of household's risk 
bearing capacity (Simtowe & Zeller, 2006). Access to credit has also been observed to be 
sexually oriented in a few nations. In families where females are the head or bread 
winner, they are oppressed by acknowledged foundations, resulting in not been able to 
fund yield-raising innovations, and prompting low selection rates (Muzari et al., 2013).  
Despite this report in other countries, the vice is said of most female-heads in other 
countries (Muzari et al., 2013). In a recent report by FOASTAT (2014) there has been a 
program that offers free advances to the young women in Kenya by their legislation, 
known as the UWEZO support. The support program is empowering these young people 
and enabling this to acquire the new horticultural innovations introduced, which in return 
boosting the development of their financial instability. 
Household factors: 
Most adoption studies revealed that, assessing human capital through the farmer’s age, 
sex, level of education, and household size (Atibioke et al., 2012; Mignouna et al, 2011; 
Keelan et al., 2014; Arah et al., 2016) is essential when it comes to technology adoption 
and innovation selections. 
Age: 
Age is usually expected to have influence on adoption of an agricultural technology. 
There is that believe that, matured and older farmers have the experience and skills 
needed unlike the young and immature youth growing up. The assumption is that, firstly 
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they have the required assets to adopt when it comes to financial assets.  Secondly older 
farmers have gained enough skills and experience and are in the best position than 
younger farmers (Kariyasa & Dewi., 2011 and Mignouna et al., 2011). 
Also, most adoption studies report that age most have a negative relationship when it 
comes to adoption. Mauceri et al., (2005) & Adesina and Zinnah (1993) explains that, 
this results is negative because, when older farmers are aging, they see adoption of a 
particular technology to have a high risk. What they might have achieved at that level is 
what they live on till they pass away. This deters them from adopting and investing in a 
newly introduced technology. But unlike younger farmers, they are typically the less risk-
averse. They are eager to make a lot of money, and explore new technologies. Especially 
in cases where the technology has been proven to ease the effort toward their work done, 
and assures them of higher income. This study was backed by a research done by 
Alexander & Van in 2005. They found that, younger farmers had a positive relationship 
on adopting of genetically modified maize when it was introduced, as compared to older 
farmers.  
Gender: 
Gender issues in agricultural technology adoption have been studied regarding the 
different roles men and women play in technology adoption (Bonabana-Wabbi, 2002). 
The impact of sex on technology adoption, as detailed by Arah et al., (2016) had 
discovered no noteworthy relationship amongst sexual orientation and likelihood to 
receive enhanced maize in Ghana. 
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They inferred that, technology appropriation choices depend principally on access to 
assets, instead of on sex; and if selection of enhanced maize relies upon access to land, 
work, or different assets, and if in a specific setting males have a tendency to have 
preferable access to these assets over females, at that point in that setting the 
advancements will not profit people similarly. In any case, Atibioke et al., (2012) found 
that male ranchers swing to embrace new agrarian innovations more than female 
agriculturists. 
Furthermore, sexual orientation may affect a few innovations. Sex influences innovation 
selection since the leader of the family unit is the essential chief and male have full 
access to and control over creation assets than female due to socio-social qualities and 
standards  (Mesfin, 2005; Omonona et al., 2006; Mignouna et al., 2011). For example, an 
examination by Obisesan (2014) on appropriation of innovation found that, sexual 
orientation impacted selection of enhanced cassava creation in Nigeria. His outcome 
vanquished with that of Lavison (2013) which showed that male ranchers will probably 
embrace natural manure not at all like their female partners. Family unit estimate is 
essentially utilized as a measure of work accessibility. It decides selection process in that, 
a bigger family has the ability to unwind the work limitations required amid presentation 
of new innovation (Mignouna et al., 2011; Bonabana-Wabbi 2002).  
Education: 
Education of the farmers and traders has been assumed to have a positive influence on 
their decision to adopt new technologies. Educational level of a farmer or trader increases 
his ability to obtain process and use information relevant to adoption of a new technology 
(Mignouna et al., 2011; Lavison 2013; Namara et al., 2013). For instance a study by 
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Okunlola et al., (2011) on adoption of new technologies by fish farmers on organic 
fertilizers found out that the level of education had a positive impact and significant 
influence on adoption of the technology. This is because higher education influences 
respondents’ attitudes and thoughts; it makes them more open, rational and able to 
analyse the benefits of the new technologies introduced (Waller et al., 1998). This eases 
the introduction of a new technology which ultimately affects the adoption process 
(Adebiyi & Okunlola, 2010). 
Other studies that have reported a positive relationship between education and adoption 
as cited by Uematsu and Mishra (2010) include: Goodwin and Schroeder (1994) on 
forward pricing methods, Huffman and Mercier (1991); and Putler and Zilberman (1988) 
on adoption of microcomputers in agriculture, Mishra and Park (2005); and Mishra et al., 
(2009) on use of internet, Rahm and Huffman (1984) on reduced tillage, Roberts et al. 
(2004) on precision farming and Traore, et al. (1998) on an on-farm adoption of 
conservation tillage. On the other hand, some authors have reported insignificant or 
negative effects of education on the rate of technology adoption (Grieshop et al., 1988; 
Khanna, 2001; Banerjee, et al., 2008; Samiee et al., 2009). Studying the effect of 
education on technology adoption, Uematsu and Mishra (2010) reported a negative 
influence of formal education towards adopting genetically modified crops. The fore 
going empirical evidence have shown mixed results on the influence of education and 
adoption of new technology. 
2.8 Constraints Faced in Adopting Storage Technology  
Constraints to tomato production and storage have been empirically presented as 
problems associated with land rents, water charges and costs of tractor services, 
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pesticides, seed and fertilizer (Clottey, Karbo & Gyasi, 2009). According to Clottey et al. 
(2009), constraints tomato farmers face were: inadequate number of tractors and land for 
expansion, no places to locate nurseries, poor seed quality, high incidence of diseases, no 
storage facilities, difficulties in accessing credit, and no ready markets. All these 
constraints were summed up as lack of capital to invest in tomato production and storage. 
Aside the biological and environmental factors that contribute to post-harvest losses, 
Kader (2004) reported that some socioeconomic factors such as marketing systems and 
transport systems can be attributed to the incidence of post-harvest losses. 
Firstly, the challenge of inadequate marketing systems exists in many developing 
countries like Ghana where producers of fresh vegetables and fruits produce large 
quantities of their commodities which results in post-harvest losses. However, there is 
also no dependable and fast means of getting such commodities to the consumer hence 
losses become extensive. These come about as a result of lack of communication among 
the actors. Kader (2004), therefore, suggested marketing cooperatives should be 
encouraged among producers of major commodities that are exportable.  
Also, alternative distribution systems such as direct selling to the consumer (road side 
sales, produce market in cities and local farmer's market) should be encouraged. This is 
evident and is usually practiced in Ghana especially in production areas. An inadequate 
transport facility to properly transport the horticultural crops to the markets is also 
another constraint. Even if there are some vehicles, they are mostly not in good 
conditions to cart produce from the production sites. Finally, local farmers and traders 
may not be able to afford their own transport vehicles hence the produce tends to keep 
long before it reaches its destination. 
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Furthermore, Kader (2004) included lack of post-harvest information as another 
socioeconomic factor leading to losses in horticultural crops. He indicated that good post-
harvest handling activities are not properly disseminated to the farmers and traders 
consequently, information on how to handle crops are limited to those who perform or 
are directly involved in harvesting, packaging, transporting, and marketing of the 
produce. Hence he suggested that farmers and traders need the requisite knowledge about 
postharvest handling practices to enhance reduction or minimize losses. Diiro, (2013) 
indicated that, the absence of farm storage facilities and proper pack house or packing 
station results in the perishability of the produce hence it is sold immediately after 
harvesting without primary processing or adequate packaging. Tomato yields are 
influenced by seed variety. 
However, tomato cultivators in Ghana are compelled by the nonattendance of national 
seed procedure that furnishes agriculturists with a dependable wellspring of fitting seeds 
and specialized help (Robinson & Kolavalli, 2010). Consequently, Ouma et al., 2002) 
recommended that there was the need to concoct assortments that could withstand the 
transportation harms or enhance the dealing with capacity of assortments developed. A 
study by MoFA (2012) additionally showed that absence of store rooms, inconsistent 
transport and absence of information on post-gather procedures were not requirements 
that tomato farmers and traders in Ghana were confronted with. Adarkwa (2011) detailed 
that uncalled for collect and post-reap rehearsals bring about misfortunes because of 
deterioration of the item before achieving the market and misfortunes of value traits, such 
as, appearance, solidness, taste and nourishing quality. 
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Adu-Dapaah and Oppong-Konadu (2002) concentrated on cultivation practices and 
creation imperatives. As indicated in their paper, the elements in charge of low yields of 
tomato incorporate poor adjustment of enhanced assortments, wasteful seed conveyance 
framework, and poor administration of water system water frameworks, mistaken 
planning of the use of information sources and absence of powerful sensitivity analysis 
and malady control instruments. The paper presumed that the components that cut off the 
size of tomato generation were high cost of creation and absence of access to credit. 
Issahaku (2012), however, focused on constraints across the whole tomato industry and 
that includes several actors in the production and marketing chain. These include farmers, 
wholesalers, retailers and processors. Hence this survey analysed the challenges 
confronting the whole industry by seeking views from not only some but all the 
stakeholders involved. The major problems that confronted the tomato value chain were 
found to be low prices, price volatility, lack of access to credit, poor quality of tomatoes, 
inadequate storage and warehousing facilities, inadequate transportation facilities, 
dispersed nature of source of supply, high interest rate and lack of adequate information.  
Low price was ranked as the most worrying constraint of farmers while poor quality of 
tomatoes produced in Ghana was ranked as the most pressing constraint of wholesalers 
and retailers. Aidoo et al.(2014) in a survey reported and emphasized that there were 
other things that contributed to post–harvest losses and these included time of harvest, 
type of variety grown and technology adopted in handling the produce. These constraints 
were ranked least whiles lack of market avenues, unreliable transport and longer distance 
to market were considered the three most critical constraints causing secondary losses. 
 
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2.9 Summary of Literature Reviewed 
The above reviewed literature helps understand the gaps in the study. Reviews on other 
tomato storage technologies provide a clear understanding on why the ZECC should be 
adopted due to its advantage over the others. It identifies economic, institutional, 
technological and family characteristics as the primary factors influencing the choice of 
the ZECC and highlights the fact that the studies cut across countries and regions around 
the globe and that it is applicable everywhere.   
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CHAPTER THREE 
METHODOLOGY 
 
3.1 Introduction 
This chapter describes the study area with brief discussions on data collection method. 
This chapter highlights information on types and sources of data, the appropriate 
sampling technology, sample size, and the instrument used for the data collection. This 
chapter further presents the conceptual and theoretical frameworks used for the study. 
This chapter indicates the method of analysis used to achieve the various objectives set 
for the study. 
 
3.2 Research Design 
This study employed an exploratory research design, a mixed method approach which 
considered both qualitative and quantitative data. This design was deemed appropriate for 
this study since it provides understanding and empirical evidence on the factors that 
influence the adoption of tomato storage technology among farmers and traders in the 
Northern Region of Ghana.  
 
3.3 Study Area 
The study area is located at the Savelugu and Sagnarigu municipalities. The Savelugu 
municipality is located  at  the  northern  part  of  the  Northern  Region  of  Ghana.  It 
shares boundaries with West Mamprusi to the North, Karaga to the East, Kumbungu to 
the West and Tamale Metropolitan Assembly to the South. The altitude of the 
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municipalities ranges between 400 and 800 feet above sea level. The population of the 
municipality according to 2010 population and housing census stands at 139,283 with 
67,531 males and 71,752 females. The municipality is located in longitude and latitude 
9°24′N and 0°28′W, respectively. Also, the Sagnarigu municipality lies between latitudes 
9º16’ and 9º 34’ North and longitudes 0º 36’ and 0º 57’ West. The municipality covers a 
total land size of 200.4km² and shares boundaries with the Savelugu municipal to the 
north, Tamale metropolis to the south and east, Tolon District to the west and Kumbungu 
District to the north-west. The population of the municipality according to 2010 
population and housing census stands at 148,099 with 74,886 males and 73,213 females 
(GSS, 2014).  
Figure 3. 1: Map of Savelugu and Sagnarigu Municipalities in the Northern Region      
                     of Ghana 
 
Source: University of Ghana, Geography Department (2018) 
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3.4 Conceptual Framework of the Study 
This study conceptualizes the interrelationships among variables as illustrated by the 
framework in Figure 3.2. The smooth running and sustainability of all businesses requires 
enhanced output which results in profits (Baba, 2017). A new technology may either be 
financial viable or otherwise, and offers opportunities for adoption. Where the technology 
is viable and has been adopted, it results in an enhanced output subject to the influence of 
factors which may be socio-economic, institutional or managerial. Likely constraints in 
the use of new technology are also important to help the sustainability of the technology. 
 
Figure 3.2 Conceptual Framework 
 
 New technology (ZECC) 
 
 
Financial viability of the technology 
                                 
 
Viable Not viable 
 
 Adopt technology Reject technology 
                      Affected by                                                 Leads to 
Socio-economic 
 Low output 
Institutional and managerial factors 
                and                             Results in                                          
 
Constraints in using  Improved Output 
 new technology  
  
Source: Author’s Construction (2018) 
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3.5 Theoretical Framework 
The theoretical framework underlying adoption is based on individual investment, 
behaviour and profit maximisation. A farmer or trader maximizes profit by producing, 
storing or distributing a quantity of goods that indicate the level of combination of inputs 
(technology adoption). Farmers and traders derive satisfaction from the utilization of 
inputs (example storage technologies) they use in storage or marketing to maximize 
output or profit margins. Assuming a farmer has access to a storage technology (an 
intermediate good), then the farmer’s expected production output or profit margin, 
according to Greene (2012) is represented mathematically as shown in equation 3.1. 
𝑸𝒊 = 𝒒𝒊(𝒀𝒋, 𝑿𝒋, 𝒆𝒊𝒋)                    (3.1) 
Where 
Qi = the Output/Profit level of farmer/ trader i by good/ input  
Yj = the household income for farmer/trader j 
Xj = the vector of the observed characteristics of the farmer/trader and       
  of the given choice of the farmer/ trader   
𝑒𝑖𝑗 = the unobserved error term of the indirect production (profit) 
  function. 
The farmer or trader will agree to adopt an input (tomato storage technology) if and only 
if the output (profit) derived from the new technology is greater than the profit derived 
from the traditional methods.   That is, if  
𝑸𝒊 (𝒀𝒋 −  𝒀
∗
𝒊 , 𝑿𝒋, 𝒆𝒊𝒋) > 𝑸𝒋(𝒀𝒋, 𝑿𝒋, 𝒆𝒊𝒋)     (3.2) 
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Where 
𝑌∗𝑖  denotes the farmer’s or trader’s income (profit margin). The probability that the jth 
farmer or trader responds ‘yes’ is an indication that he or she has access to credit is given 
by: 
Pr (yes) = 𝑸𝒊 (𝒀𝒋 −  𝒀
∗
𝒊 , 𝑿𝒋, 𝒆𝒊𝒋) > 𝑸𝒊𝒋(𝒀𝒋, 𝑿𝒋, 𝒆𝒊𝒋)    (3.3) 
A common formulation of the profit maximization model is the additive profit model 
(Cameron and Trivedi, 2005). Thus the Additive Profit Model assumes that the storage 
(profit) function is additively separable into deterministic and stochastic preferences. 
 This is given as: 
𝑸𝒊𝒋 = 𝑸𝒊(𝒀𝒋, 𝑿𝒋) + 𝒆𝒊𝒋       (3.4) 
Hence, the probability statement that a respondent answers ‘yes’ to an adoption of ZECC 
technology is, therefore, illustrated as: 
Pr (yes) = 𝑸𝒊𝒋 (𝒀𝒋 −  𝒀
∗
𝒊 , 𝑿𝒋 ) +  𝒆𝒊𝒋 > 𝑸𝒊𝒋(𝒀𝒋, 𝑿𝒋) + 𝒆𝒊𝒋   (3.5) 
According to Greene (2012), 𝑃𝑟 is hypothesized to be a function of household’s 
socioeconomic characteristics such as age, sex, education, household size, access to 
credit, access to storage technologies, etc. These exogenous variables were employed to 
examine socioeconomic characteristics of tomato farmers and traders that will influence 
the intention to adopt new technologies. 
The theory underlying the financial analysis is based on Cost-Benefit Analysis technique 
which used the discounted measures of project worth such as NPV and BCR. According 
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to Gittinger (1982), Cost-Benefit Analysis shows the worth of an investment by 
comparing the costs involved with the benefits. This is used for financial analysis of 
projects in order to assess the financial viability of the project. Financial analysis was 
used because it takes into account both costs and benefits. The total cost involved in the 
storage of tomato is the sum of fixed or capital costs and recurrent or operating costs. 
These costs are inherently different both with respect to the cost structure itself and to the 
timing of accruals. 
According to Gittinger (1982), the total costs are compared with the benefits to see 
whether the investment is financially justifiable. This is done taking into account the 
different times at which costs and benefits are realized over the life of the investment 
through the use of discounting which reduces all the future values to their present worth. 
The present worth of the cost is compared with that of the benefit in which the discounted 
measure of project worth such as Net Present Value (NPV), Benefit-Cost Ratio (BCR) at 
a given discount rate. The decision rule is that an investment is financially viable if NPV 
is greater than or equal to zero, and BCR is greater than or equal to one. For policy 
makers, sensitivity analysis is conducted to test the sensitivity to changes in assumptions 
about prices, delay in implementation, cost overrun and yield. That is, the NPV and BCR 
are tested to see whether the investment will be viable under these changes underlying the 
Cost-Benefit analysis. 
 
3.6 Methods of Analysis 
This part of the study illustrates the various methods employed in addressing the specific 
objectives of this study. 
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3.6.1 Determining the Level of Awareness and Usage of ZECC Technology 
Descriptive statistics such as percentages and frequencies were used to determine the 
level of awareness of the ZECC storage technology among the tomato farmers and 
traders. A three point Likert scale was applied in the case of their various reasons for the 
usage of the ZECC and the traditional methods of storage. The scale was constructed as 
1= disagree, 2 = indifferent, 3 = agree. The number of farmers and traders according to 
their reasons was determined, and the weighted mean index calculated to reflect their 
priority reasons for using the ZECC storage technology and the traditional method. The 
weighted mean index (WMI) is mathematically given by: 
Wi 𝑥 Fi
         (3.6) 
𝑁
Where  
th
Wi is the weight of the i  reason 
th
Fi is the response rate of the i  reason; and  
N is the total number of respondents 
The decision rule for degree of agreement on the reasons for using the ZECC and TMS 
variables are: 
1. A bench mark of 2.5 would be used. 
2. Agree if weighted mean index is greater than or equal to 2.5(WMI ≥ 2.5) 
3. Indifferent if weighted mean index is greater than 1.5 but less than 2.5 
(1.5<WMI<2.5), and 
4. Disagree if weighted mean index is less than or equal to 1.5 (WMI ≤ 1.5) 
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This allowed for the calculation of general or overall reasons for using either of the two 
storage methods.  
3.6.2 Comparing Net Benefits of ZECC Storage and the Traditional Method of  
           Storage Technologies 
Assumptions 
Comparing net benefits requires the generation of cash flows for both technologies under 
the following assumptions: 
The cash flow was generated over a period of fifteen (15) years; this is based on the fact 
that, the main capital item of the initial investment has a useful life of fifteen years. This 
number of years was assumed to have given enough room to make up for the cost and 
benefit from the investment (Kuwornu et al., 2013). The ZECC facility has a 50-kilogram 
storage capacity with a floor space of about three (3) square-meters. Costs were entered 
in the year in which they were incurred and benefits as and when they were realized, 
using constant average prices (Gittinger, 1982). The residual value was computed as the 
proportion of the capital cost left at the end of the useful life of the project, including the 
salvage value. It is assumed that no repairs and maintenance was done in year one due to 
the fact that, the items were new and no repairs or maintenance would be needed. 
Notwithstanding, repairs and maintenance is assumed to increase by 5% in years 3 to 7, 
and remain constant in the subsequent year; because most of the items had been expected 
to be replaced at some point over the 15 years. Therefore, reducing the cost of repairs and 
maintenance. 
Items were valued at constant prices to eliminate the influence of inflation. The cash 
flows were discounted at 21 percent discount rate, which represents the lending rate of 
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rural banks in Ghana for agricultural investments at the time of the study. All other costs, 
except casual labour were assumed to be directly proportional to revenue. Operating cost 
was allocated a 5 percent contingency cost, which would be used should there be an 
adverse change in the prices of inputs. 
‘With’ and ‘Without’ Project Cash Flow Analysis 
The with’ and ‘without’ project cash flow analysis was employed  to ascertain whether 
the net benefits from the use of the ZECC storage technology is higher than the net 
benefits of the existing method  of  storage. Cash flows were generated for the ZECC 
storage technology and the TMS. Then the incremental cash flow was obtained as the 
difference between the two cash flows. Discounted measures of project worth such as the 
Benefit-Cost Ratio (BCR) and the Net Present Value (NPV) were used to determine the 
financial viability of each form of storage, and the incremental NVP for comparing the 
ZECC storage technology with the existing method. A positive incremental NPV 
indicates that the ZECC storage technology is more financially viable. 
According to Gittinger (1982), the Benefit-Cost Ratio is defined as the value today of all 
benefits divided by the value today of all costs. The equation is given as:  
T
Bt
BCR  0          (3.7) 
T
Ct
0
 
Where  
Bt = benefits in a time t 
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Ct = costs incurred in time t 
The Net Present Value (NPV) is defined by Gittinger (1982) as the difference between 
the value today of all benefits and the value today of all costs. The equation is stated as:  
tT 1
NPV   (Bt Ct )        (3.8) t
t0 (1 r )
Where Bt and Ct are as earlier defined and r = discount rate. 
 The decision rule states that if NPV is greater than zero, then the project is said to be 
financially viable; hence it can be accepted. 
Sensitivity Analysis 
A sensitivity analysis was conducted using switching values. It takes into account the 
extent parameter’s value would change for a project that is acceptable to become 
unacceptable, or a project that is unacceptable to become acceptable. For example, 
investors would like to have knowledge on how much cost would increase and/or how 
much benefit would reduce before the Net Present Value (NPV) of a project falls to zero. 
Switching values are determined by examining the Benefit-Cost Ratio (BCR) and Cost- 
Benefit Ratio (CBR) for changes in cost and benefits, respectively.  
That is, BCR minus 1 gives the percentage by which costs would increase to make the 
project break-even, while 1 minus CBR gives the percentage by which benefits fall to 
make the project break-even. 
An increase in cost beyond the break-even point or fall in benefit below the breakeven 
point will render the project unacceptable.  
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3.7 Examining the Factors that Influence Tomato Farmers’ and Traders’ Adoption  
       of Storage Technology 
To analyse the factors that statistically influence tomato farmers’ and traders’ decision to 
adopt a particular technology, the probit regression model was used. The method of 
estimation of the probit model was by maximum likelihood. The interpretation of probit 
results is based on marginal effects treated as probabilities. The marginal effect explains 
the slope of the probability curve relating one explanatory variable to a prob (y=1|x), 
holding all other variables constant. 
The observable dependent variable is defined by: 
1 Adopt technology if y*  0
y     
0 no adoption if y* 0 
The Probit model Y  follows the Bernoulli distribution with probability 
 i  proby  1ΦX 
         (3.9) 
Where i  is the probability that tomato farmers and traders would either adopt the ZECC 
'
storage technology or remain as non-adopters.  X i is the explanatory variables, i is the 
regression parameters to be estimated. 
In the Probit model the functional distribution of the error term is very important to 
constrain the values of the latent variable into desirable properties of probability values of 
between 0 and 1. The Probit model assumes a cumulative distribution function of 
standard normal distribution represented byΦ . 
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proby 1  proby*i  0 probX  e  0
 probe  X 
    (3.10) 
 probe  X 
 ΦX 
In the case of a normal distribution function, the model to estimate the probability of 
observing respondent’s choice to adopting a technology can be represented as: 
X 1  z 2 
Pr obyi 1/XΦX   exp-  z     (3.11) 2  2 
Where 
yi is the Probability (dependent variable) that a respondent would chose adopt the ZECC 
technology or not, X is a vector of the explanatory variables, z is the standard normal 
variable ( z ~N (0, 2 ) and  is a k by 1 vector of the coefficients estimated.  The 
empirical probit model is specified as: 
Y = β0 + β1X1 + β2X2 + β3X3+ ......... + βnXn + Ui      (3.12) 
 
Variable Definition and Justification  
The variables included in the model, with their units of measurement and a-priori 
expectations, are described in Table 3.1. 
X1: Gender  
 In the northern regions of Ghana, women have less access to land and other assets 
needed for investment, and most decisions in their homes are taken by either their 
husbands or fathers who often influence the way household resources are allocated. 
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Gender in this study is expected to have a positive influence on the adoption of the ZECC 
storage technology, given that males are assigned 1 and females 0. 
 
Table 3.1: Variables and a Priori Expectation of the Probit Model 
Variables Description Measurement A-priori 
expectations 
Gender Gender of respondent    1 = male,  + 
  0 = female 
Age Age (in years)   Number + 
Household Size Number of persons in   Number of persons + 
household of respondent 
Education   Years of education    Number of years + 
Marital status Marital status   1 = married, +/- 
  0 = otherwise 
GBO Membership of group-   1 = member, +/- 
based organisation    0 = otherwise 
Extension Number of extension     
visits   Number + 
Location Location of respondent   1 = Savelugu, +/- 
   0 = Sagnarigu 
Perceived Cost Perception of high cost   1 = high,  +/- 
of ZECC  of ZECC   0 = otherwise 
Monthly Average monthly tomato      
Tomato income income    Ghana cedis +/- 
Savings Average income saved      
per month    Ghana cedis + 
Type of person Type of person aware of     1 = trader  
aware the ZECC     0 = farmer +/- 
User of TMS Traditional method of     1 = yes            
storage user     0 = no           + 
Source: Author’s construct (2018)  
 
X2: Age  
It is also expected that, age would have a positive influence on the adoption of the ZECC 
storage technology up to a certain age threshold with on-farm or off-farm income. 
Younger farmers and traders are often more dynamic, agile and adventurous, and require 
of more formal education. The older farmers and traders often have greater access to land 
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than the youth; hence the younger ones have a tendency to rely on some other business as 
their source of livelihood (Woldenhanna and Oskam, 2001). 
 
X3: Household size 
Household size is measured in number of people in the home. The larger the household 
size, the greater the household demand, compelling the bread winner to find alternative 
ways of increasing the household income.  It is, therefore, postulated that, the larger the 
family size the more likely that, respondent will adopt the ZECC storage technology. 
This was justified by Agyekum (2014), that the correlation between household size and 
technology adoption would have a significant influence on adoption of the ZECC storage 
technology. Therefore with this understanding one can expect a positive relationship 
between household and their influence on adoption of the ZECC.  
 
X4: Years of education 
The number of years of education of a farmers or traders increases their general 
knowledge level; education makes one well informed and sharpens the way people think. 
People with high level of education are able to make good of the information attained 
during the learning process (Mignouna et al., 2011; Lavison 2013; Namara et al., 2013). 
The information increases framers and traders’ knowledge on the importance of adopting 
a new technology like the ZECC storage technology and therefore, it is expected to have 
a positive influence on adopting the ZECC.  
 
 
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X5: Marital status 
Marital status of farmers and traders was expected to have either a positive or negative 
influence on adoption. It is assumed that, there is increase in financial responsibility for 
the married. Therefore, there would be a negative influence on adoption of the ZECC 
storage technology. On the other hand, married women in the study area confirmed that 
most of their assets were only obtained as a result of their husband’s hard work. Meaning 
that marital status can also give room to a positive influence on adoption should a 
respondent be a female. 
 
X6: Membership of Group-Based Organization (GBO) 
Being a member of a GBO or association related to one’s career exposes the respondent 
to information that enables him/her to reduce uncertainty, and have access to financial 
support. It was expected that, membership of GBO would have a positive influence on 
adoption. However, rules and regulations involved of being a member in the GBO also 
deter some farmers and traders from having full participation of the organization. 
X7: Extension Service Received by Respondents 
Extension services give respondents access to vital information and impart knowledge to 
respondent. Access to extension service was measured as contact with respond during 
farming or trading and also the frequency of visits. Extension officers are able to monitor 
respondents’ activities and grant support through their various ministries or 
organizations. It is expected to have a positive influence on respondents’ adoption of the 
ZECC storage technology. 
 
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X8: Location 
Although both study areas were in the northern region, it was chosen to help understand 
if their adoption rates would be different based on the fact that, they are at different 
geographical areas, and also, an individual’s behaviour is also dependent on the 
environment in which they stay, location is expected to have either a positive or negative 
influence of the ZECC storage technology. 
X9: Perceived Cost of ZECC  
Since the validity of the farmers’ and traders’ perception of high cost relative to returns in 
the usage of the ZECC technology cannot be ascertained, it is expected that, when the 
perception of farmers and traders on high cost of technology is high, there would be a 
negative influence on adoption of the technology and when low too the otherwise would 
influence adoption positively. 
X10: Monthly Tomato Income 
With the economic theory that, the higher the income levels of respondents, the higher 
their purchasing power of ability to go for an extra service.(Asare,2016). Hence the a-
priori expectation may either be positive and negative influence on adoption.  
X11: Monthly Savings 
Savings helps respondents to become financially secured. It was, therefore, expected that 
the more savings made by respondents the higher their likelihood to use their savings for 
investment in the ZECC.  
 
 
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X12: Type of Person Aware (ZECC) 
In ascertaining some of the factors that would influence adoption of the ZECC, farmers 
and traders, whom the technology has been introduced to, were needed in assessing this 
objective, this was to help know which of these two respondents stands a chance of 
adopting. Taking into consideration the different nature of their occupation, traders are 
expected to have a higher adoption influence as compared to farmers. 
 
X13:  Users of TMS 
Users of existing technologies can influence the farmers or traders decision to adopt the 
ZECC storage technology since they have knowledge of the importance of technology 
user and its benefits. It is expected that, individuals who are using an existing technology 
would have a positive influence on the ZECC storage technology. 
 
3.8 Identification and Ranking of Constraints Faced by Respondents in Adopting 
ZECC Technology     
Constraints were identified through pre testing on adoption of new technology (ZECC). 
The Kendall’s Coefficient of Concordance (W) was used in ranking the constraints 
tomato farmers and traders face in the usage of the ZECC storage technology in the study 
area. Respondents were asked to rank the identified constraints in order of most pressing 
to the least pressing constraint. As posited by Legendre (2005), the Kendall’s Coefficient 
of Concordance (W) is a suitable estimator in an attempt to examine the degree to which 
a group of variables provide a common ranking for a set of objects.  
 
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The Kendall’s Coefficient of Concordance (W) was represented as: 
𝟏𝟐𝑺
W = 𝟐 𝟑               (3.13)  𝒎 (𝒏 −𝒏)−𝒎𝑻
Where  
S = ∑𝒏𝒊=𝟏(𝑹𝒊 −  ?̅? )
𝟐        (3.14) 
S = the sum of squared deviation, n = the number of constraints identified, m = the 
number of respondents or judges and T = the correction factor for tied ranked T = 0 if 
there is no ties in the rankings. The Kendall’s Coefficient of Concordance (W) is a 
statistic of the variance of the rows sum of ranks Ri divided by the highest possible value 
the variance can take. This happens when all the variables are in total agreement.  
The estimate for the agreement lies between 0≤W≤1 where, W = 0 means exactly no 
agreement between respondents and W = 1 indicates a perfect or total agreement between 
respondents. 
Hypotheses testing for the constraints for farmers and traders 
The null hypothesis (H0) was tested against the alternative hypothesis (H1) as follows:  
H0: There is no agreement among tomato farmers and traders in their ranking of 
constraints.    
H1: There is an agreement among tomato farmers and traders in their ranking of 
constraints. 
 
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3.9. Methods of Data Collection  
3.9.1 Types and sources of data  
Data were obtained from both primary and secondary sources. This study involved 
largely the use of primary data for the purpose of empirical analysis. The primary data 
were obtained through face-to-face interview, where a structured questionnaire was used 
to elicit information from farmers and traders. The primary data collected reflected the 
background information of the respondents such as age, educational qualification of 
respondents, gender, household size of respondents, farming and trading experience in 
terms of years, respondents’ average annual income from tomatoes, the quantities of 
tomatoes harvested and stored within each cropping year, and the sale prices of tomatoes 
that were kept under the ZECC storage technology. Secondary data reflected on previous 
studies in relation to the study especially on the financial discounting rate and price 
forecasting estimations. 
 
3.9.2 Sample size and sampling technique 
The study employed a multi-stage sampling technique for the selection of hundred (100) 
farmers and one hundred and ten (110) traders. The Savelugu and Sagnarigu 
municipalities were purposively selected due to the fact that introduction of the ZECC in 
Ghana has been done in these two (2) municipalities. This was followed by a purposive 
selection of tomato farmers and traders in these municipalities due to the fact that they 
were the target for this study. Tomato traders were selected based on the decision to pick 
every other tomato seller starting from the first respondent who was picked at random. 
The numbers 1 and 2 were written on pieces of paper, folded and spread on the table. The 
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number picked represented the first respondent. Thus the first tomato trader located 
became number 1, the second was skipped and the third chosen. This pattern was 
followed till the last trader in each municipality was reached. 
 
Table 3.2 Sample Size Distribution 
Municipality Farmers Traders Total 
Savelugu 36 54 90 
Sagnarigu 64 56 120 
Grand total 100 110 210 
Source: Author’s computation (2018)  
 
This technique resulted in selecting 54 and 56 traders in the Savelugu and Sagnarigu 
municipalities, respectively. Tomato farmers were selected using the snow ball method 
since the total number of tomato farmers in the municipalities was unknown. A total of 
36 and 64 farmers were obtained in the Savelugu and Sagnarigu municipalities 
respectively.  A total of two hundred and ten (210) tomato farmers and traders were 
interviewed in these municipalities. Sample size distribution is illustrated in Table 3.2 
 
3.9.3 Survey Instrument 
The study employed a well-structured questionnaire administered to tomato farmers and 
traders in both closed and opened format. A preliminary questionnaire was developed and 
sent to three (3) research analysts for their comments. Their comments were addressed in 
the questionnaire for pretesting. The questionnaire was pretested specifically at Savegulu 
because most of the farmers and traders there were assumed to be aware of the ZECC 
storage technology. The pre-test was carried out in early December, 2017 to ascertain the 
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reliability of the questionnaire in terms of clarity of the questions, avoidance of 
omissions, and timeliness of the questionnaire administration. The completeness and 
appropriateness was tested based on how respondents understood the questions asked. 
Observations and experience from pre-testing helped in updating and improving the final 
questionnaire. The questionnaire used for the primary data collection is attached as 
Appendix 3.1. 
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CHAPTER FOUR 
RESULTS AND DISCUSSION 
 
4.1 Introduction 
This chapter presents and describes the socio-economic characteristics of the 
respondents. It also presents the cost-benefit analysis of using the ZECC tomato storage 
technology, the factors that influence tomato farmers’ and traders’ adoption of the ZECC 
storage technology, and finally, the constraints that affect farmers’ and traders’ decision 
to adopt the ZECC storage technology. 
 
4.2 Socio-Economic Characteristics of Respondents  
The socio-economic characteristics of the respondents are presented in Table 4.1. The 
characteristics include: gender, age, household size, level of education, and the average 
monthly income generated from tomato. Gender of respondents showed that 46.19% 
were males made up of 40.00% farmers and 6.19% traders. Accordingly, 53.81% were 
females made up of 7.62% farmers and 46.19 % traders. This indicates that there are 
more males involved when it comes to tomato farming and more female in tomato trading 
in the study area. Considering the ages of the respondents, majority (58.10%) for both 
farmers (30.00%) and traders (28.10 %) was within the age group of 36 - 60 years. This 
group is classified in Ghana as the ‘vibrant group’ whereas those who fall below 36 were 
29.04%. The remaining respondents (12.86%) of both farmers (3.81%) and traders 
(9.05%) were over 60 years. 
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The household size of respondents ranges from 1 to 12. Majority (51.43%) of the 
households for both farmers (27.14 %) and traders (24.29%) had household size above 
nine (9) members. This result gives a true picture of why the Ghana Statistical census 
survey reports on high household numbers in the Northern region of Ghana. There are a 
lot of mouths to be fed and catered for in terms of their health, education, and other bills 
one can think of, hence the northern sector being classified as poor as stated by the 
GLSS, 2010.  
 
Table 4.1: Characteristics of Respondents 
Socio-Economic     Farmer Trader Total 
Variables 
 Frequency  Percent Frequency   Percent     Frequency    Percent 
Gender 
Male 84 40.00 13 6.19 97 46.19 
Female 16 7.62 97 46.19 113 53.81 
Age  
≤ 35 29 13.81 32 15.24 61 29.05 
36-60 63 30.00 59 28.10 122 58.10 
60+ 8 3.81 19 9.05 27 12.86 
Household Size 
1-3 3 1.43 5 2.38 8 3.81 
4-6 21 10.00 24 11.43 45 21.43 
7-9 19 9.05 30 14.29 49 23.33 
9+ 57 27.14 51 24.29 108 51.43 
Level of Education 
No Education 35 16.67 67 31.90 102 48.57 
Basic 59 28.10 38 18.10 97 46.19 
Secondary 4 1.90 5 2.38 9 4.29 
Tertiary 2 0.95 0 0.00 2 0.95 
Average Monthly Tomato Income 
≤ 200       67 31.90 41 19.52 108 51.43 
201-400      24 11.43 53 25.24 77 36.67 
401-600       9 4.29 14 6.67 23 10.95 
601-800        0 0.00 2 0.95 2 0.95 
Source: Field Data (2018) 
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Education in agriculture cannot be overemphasized given the role it plays in one’s 
productivity. As indicated from Table 4.1, 48.57% of the respondents have had no formal 
education, but of others 31.9% are tomato traders.  This implies that majority of 
respondents mainly farmers had formal education.  The data implies that the level of 
education attained by the respondents is quite average and this is expected to influence 
adoption of the ZECC storage technology. 
The average monthly income from tomatoes indicated that 51.43% of the respondents of 
which 31.9% were farmers have an average income of GHS 200 or less from their 
tomatoes. This indicates that most of the respondents (especially) farmers do not generate 
much of income from tomatoes, and can be said that, if the poorly resourced farmer or 
trader could adopt the ZECC storage technology their income would rise above GHS 200. 
Respondents generating GHS 201-400 monthly from their tomato were 36.67% of which 
25.24% are trader.  Very few respondents, of less than 12% (mainly tomato traders have 
had their monthly incomes higher than GHS 400. 
 
4.3 Level of Awareness and Usage of the ZECC Technology  
The study assessed the proportion of respondents who were aware and were using the 
ZECC storage technology for tomato storage. The results presented in Table 4.2, indicate 
that most (83.33%) of the sampled tomato farmers and traders were aware of the ZECC 
technology whiles a few 16.67% of them indicated that they were not aware of the ZECC 
tomato storage technology.  
 
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However, small proportions of the sampled respondents 26.19% (55) have adopted and 
have been using the ZECC storage technology for tomato storage. The majority (53.81%) 
of the respondents indicated that they do not use the ZECC storage technology, but the 
traditional method of storage such as using the jute to cover the tomatoes, and spreading 
the tomatoes on bare cement floor. Also, a proportion (20%) of the 210 total sampled 
respondents indicated that, they do not use any form of storage for their tomatoes.  
Table 4. 2: Level of Awareness and Usage of ZECC Technology 
 Technology Usage 
ZECC TMS None Pooled 
Awareness No. of % No. of % No. of % No. of % 
Status Resp. Resp Resp Resp 
Aware:         
 Farmers 10 4.76 45 21.43 24 11.43 79 37.62 
 Traders 45 21.23 33 15.71 18 8.57 96 45.64 
 Total 55 26.19 78 37.14 42 12.57 175 83.33 
 
Unaware:         
  Farmers 0 0 21 10.00 0 0 21 10.00 
  Traders 0 0 14   6.67 0 0 14     6.67 
  Total 0 0 35 16.67 0 0 35 16.67 
         
Pooled:         
  Farmers 10 4.76 66 31.43 24 11.43 100 47.62 
  Traders 45 21.43 47 22.38 18 8.57 110 52.38 
         
Overall  55 26.19 113 53.81 42 20.00 210 100.00 
Source: Field data (2018) 
 
Those respondents who do not store their produce, thus the 20% of the total respondent, 
made it clear that, after major market days, they just leave their tomatoes at the market 
square for the next day’s sales. They do not make any effort in storing or keeping the 
tomatoes in a form that will reduce deterioration.  Such respondents explained that, they 
grade the tomatoes and price them for next day’s sales according to the level of 
deterioration. 
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Out of the five reasons given for the usage of the ZECC, three of the reasons had their 
weighted mean index greater than 2.5(WMI> 2.5), while the other 2 reasons had an index 
less than 2.5 (WMI < 2.5). Table 4.3 shows that, the respondents were positive on three 
reasons for using the ZECC. Specifically, it ensures quality of produce; it serves as 
employment and increases income. 
Table 4.3 Reasons for ZECC storage Technology Usage 
  Disagree Indifferent Agree Total WMI Remark 
Reasons 1 2 3       
It ensures quality of 
produce 0 14 144 158 2.9 Agree 
 
It serves as 
employment 1 24 126 151 2.7 Agree 
It increases shelf life 2 62 66 130 2.4 Indifferent 
It increases income 0 32 117 149 2.7 Agree 
Because others are 
using it 22 46 30 98 1.8 Indifferent 
Source: Computed from field data (2018) 
 
The reasons why some of the respondents were not using the ZECC even though they 
were aware of it were three fold. All of the three reasons given for continuing with the 
existing method (TMS) had the weighted mean index greater than 2.5 (WMI> 2.5). This 
is presented in Table 4.4 revealing that, all the respondents were positive on the three 
reasons for using the TMS. Specifically, they claimed that the TMS is less costly, reduces 
spoilage and that because others are using it. 
 
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Table 4.4 Reasons for TMS storage Usage 
  Disagree Indifferent Agree Total WMI Remark 
Reasons 1 2 3       
It is less costly 1 22 303 326 2.9 Agree 
It reduces spoilage 3 56 246 305 2.7 Agree 
Because others are using it 2 36 279 317 2.8 Agree 
Source: computed from field data 
 
 
 
4.4 Comparing Cost and Benefits of the ZECC Tomato Storage Technology 
4.4.1 Capital costs estimation 
The average capital cost items are presented in Table 4.5.  These items include bricks, 
bamboo sticks, and sand among others. Quantities of items and unit prices were averages 
estimated based on information from the field.  
Table 4. 5: Average Capital Cost for a 50-Kilogram Capacity ZECC Facility 
Capital Cost Quantity Unit Value Useful 
Price  (GHS) Life 
(GHS) 
Bricks 400 pieces 0.80 320.00 15 
Bamboo 10 sticks 2.00 20.00 2 
Sand 80 kg 0.025 2.00 - 
Watering can 1 unit 6.00 6.00 3 
Crates (35kg) 3 units 4.17 12.51 3 
Shovel 1 unit 25.00 25.00 3 
Knapsack sprayer 1 unit 90.00 90.00 5 
Bucket 1 unit 2.00 4.00 2 
Pipe hole 722 metres 0.17 122.74 3 
Labour cost for building 2 man-days 45.00 90.00  
Total Capital Cost   692.24  
Source: Compiled from field data (2018) 
 
 
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For a 50-kg capacity ZECC storage technology, it was estimated that a total of six 
hundred and ninety-two Ghana cedis, twenty- four pesewas (GHS692.24) was needed at 
the study area. 
 
4.4.2 Average operating budget estimation 
Table 4.6 presents the average annual estimates for a 50kg capacity for the ZECC storage 
technology. Quantities of items and unit prices were averages estimated based on 
information from the field. It was found that, an average total revenue of GHS 3,588.34 
was attained annually in using the ZECC for storing tomatoes. This includes revenues 
obtained when the ZECC storage facility owners render service to non-facility owners in 
storing their produce at a charge. The total operating cost for the year amounted to GHS 
2,505.19. 
Average Operating Budget 
The average operating budget for the 50-kilogram capacity ZECC facility is illustrated in 
Table 4.6. This includes items like tomatoes, dry palm fronds, napkins, and insecticides 
among others. The main type of labour in the storage consists of loading and off-loading 
the tomatoes, watering of bricks, sorting, and cleaning of the ZECC storage technology. 
Regular wetting of the laid bricks results in wearing off and requires occasional repairs 
and maintenance. 
Additionally, services are provided in the replacement of palm fronds as and when they 
are out of use. In all, maintenance is done averagely five times a year at an average cost 
of GHS60.00 each. Average net cash flow was GHS 1,083.15 and it shows higher 
benefits than costs. 
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Table 4. 6: Average Operating Budget for a 50-Kilogram Capacity ZECC Facility 
 Quantity/Year Unit Price  Value 
(GHS) (GHS) 
Revenue    
Sales 432.6 kg 1.36 588.34  
Services 50 requests 60.00  3,000.00  
Total Cash Inflow   3,588.34 
Operating Costs     
Materials:    
   Tomatoes 525 kg 0.86  452 .00 
   Dry palm fronds 24 bundles 2.00  48.00  
   Napkin 10 pieces 2.00  20.00  
   Insecticides 96 kg 5.00  480.00  
   Dust Bin 1 unit 5.00  5.00  
   Broom 4 units 1.00  4.00  
   Water 11,232 litres       0.006  67.39  
Labour 120 man-days 10.00  1,200  
Transport 50 kg-metres 1.00  50.00  
Repairs & Maintenance 5 times 12.00  60.00  
Sub-Total    2,385.89 
Contingencies 5% of operating cost  119.29  
Total Operating Cost   2,505.19  
Total Cash Outflows   2,505.19  
Net Cash Flow   1,083.15  
Source: Compiled from field data (2018) 
 
 
 
4.4.3 Cash Flow Projections 
Net Cash Flows   
On the basis of the assumptions stated in the methodology, the net cash flow projections 
for the ZECC, TMS and the incremental were generated as in Table 4.7. Discounting the 
cash flows for the ZECC storage technology at 21% discount rate yielded a Net Present 
Value (NPV) of GHS 6, 436.15 whiles discounting the cash flow projection for tomato 
storage under the TMS at 21% yielded a Net Present Value (NPV) of GHS 2, 699.41. 
Similarly, the ZECC and the TMS yielded Benefit-Cost Ratios of 1.52 and 1.09, 
respectively which are both greater than 1.00. These indicate that both ZECC storage 
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technology and the existing TMS are both financially viable in the Savelugu and 
Sagnarigu municipalities, although the ZECC storage technology had a higher NPV. 
 
Table 4.7: Net Cash Flows for ZECC and TMS (in Ghana Cedis) 
Years         ZECC  TMS Incremental  
0 (755.11) (50.27) (704.84) 
1 372.77 81.30  291.47  
2 1,063.15 528.42  534.73  
3 2,093.77 781.48  1,312.29  
4 2,059.71 776.71  1,283.00  
5 2,029.46 796.38  1,233.08  
6 2,067.83 755.19 1,308.65 
7 2,086.13 792.82 1,293.32 
8 2,049.27 771.49 1,277.79 
9 2,080.19 774.69  1,305.50  
10 2,002.33 771.49  1,230.85  
11 2,086.14 792.82  1,293.32  
12 2,059.91 761.65  1,298.26  
13 2,102.72 777.11  1,325.61  
14 2,082.72 803.78  1,278.94  
15 2,197.67 813.98  1,383.69  
NPV@ 21% DR 6,436.15 2,699.41 3,739.32  
BCR @ 21%DR 1.52 1.09  
CBR@21%DR 0.66 0.92  
Source: Computed from field data, as in Appendices 4.4, 4.5, & 4.6 (2018) 
 
 
The results from the table revealed that discounting the incremental net cash flow gave an 
incremental Net Present Value of GHS3, 739.32. The positive incremental NPV indicates 
that the ZECC storage technology is more profitable than the Traditional Method of 
storage in the study area. 
Sensitivity Analysis Using Switching Values 
The switching values computed in determining the sensitivity analysis were derived from 
the Benefit-Cost Ratio (BCR) of 1.52 and Cost-Benefit Ratio (CBR) of 0.66 for the 
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ZECC. By examination, BCR minus 1 gave 0.52, while 1 minus CBR gave 0.34. This 
implies that cost would have to increase by 52 percent or benefits to fall by 34 percent for 
the investment to break-even.  In either case, the percentage value implies that an 
increase in cost beyond 52 percent or decrease in benefit beyond 34 percent would give a 
negative NPV or a BCR of less than one, and the investment would no longer be 
financially viable.  
The cost driver in this study is labor cost of the tomatoes, followed by insecticide cost 
and then the cost of tomatoes. A report by the Statistics, Research and Information 
Directorate in 2015 on nominal weighted average rural wholesale prices of tomato over 
the period 2006 to the year 2015 gives an average annual increase of 26.18% which is far 
less than the 52 percent cost increase that would  make the investment break-even.  
 
Table 4.8: Annual Nominal Weighted Average Rural Wholesale  
                  Tomato Prices (GHS/Mt) 
Years Prices (GHS) Growth rate 
2006 575.48 - 
2007 649.44 12.86 
2008 899.83 38.55 
2009 1503.30 67.00 
2010 1449.23 -3.60 
2011 1962.97 35.45 
2012 2573.74 31.11 
2013 3305.37 28.43 
2014 4253.09 28.67 
2015 5246.83 23.37 
Mean Growth Rate             2  6  . 1  8                                  
Source: Statistics, Research and Information Directorate, MoFA (2015) 
 
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This gives an indication that NPV will never get to zero or less over the investment 
period. Table 4.8 gives the annual nominal weighted average rural wholesale prices and 
growth rate of tomato from the year 2006 to 2015. 
 
              
4.5 Factors Influencing Adoption of the ZECC by Farmers and Traders 
Table 4.9 presents the results of the probit regression model on factors that influence 
adoption of the ZECC storage technology. Results of the Probit model (ZECC) showed a 
2
pseudo R  of 0.903 which indicates that about 90% of the variation in the farmers’ and 
traders’ adoption of the ZECC is jointly influenced by the independent variables. The 
probability value of 0.000 of the Wald chi-square statistics suggests that the independent 
variables explained the farmers’ and traders’ adoption of the ZECC storage technology. 
Results of the probit regression presented in Table 4.9 revealed that, age, marital status 
and location (community) of respondent were not statistically significant to influence 
adoption of the ZECC technology among tomato farmers and traders in the selected 
municipalities. However, some explanatory variables were found to be statistically 
significant. 
Gender of the respondents was positive and statistically significant at 1% level. Given 
that a respondent is a male, then the probability of him to adopt a ZECC technology 
increases by 0.03 percent than a female respondent. This results satisfies the expected a-
priori based on the fact that, the women in this study area have lesser access to properties 
needed for investment.  Also, findings from this study is in line with the study done by 
Obisesan (2014) on gender differences and technology adoption in Nigeria. 
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Table 4.9: Results of Probit Model 
Variables  Coefficients Standard errors P-Value Marginal 
effects 
Gender  1.6340 0.6426 0.011  0.0315** 
Age -0.0347 0.0281 0.216 -0.0004 
Household Size -0.3264 0.1310 0.013 -0.0039** 
Years of Education  1.4648 0.3676 0.000  0.0175** 
Marital status -0.3864 0.4027 0.337 -0.0046 
GBO  1.6561 0.7600 0.029  0.0382** 
Extension  1.3391 0.6845 0.050  0.0427** 
Location  0.1874 0.9438 0.843  0.0019 
Perceived Cost of -2.9363 1.0654 0.006 -0.1876*** 
ZECC  
Monthly Tomato  0.0040 0.0020 0.051  0.00005*** 
Income 
Savings -1.3161 0.5556 0.018 -0.0145** 
Type of Person Aware  1.1514 0.5338 0.031  0.02687** 
of ZECC 
User of TMS  -3.5968 1.4800 0.015 -0.0406** 
Constant  1.6469 2.2445 0.463  0.0000 
Model Diagnostics      
Number of observations = 175    
Wald Chi2(13) = 62.07    
Prob. > Chi2 = 0.000    
2
Pseudo R  = 0.903    
Variables with *, ** and *** are statistically significant at 10%, 5% and 1% 
respectively  
Source: Author’s Computation from field data (2018) 
 
 
Household size of the respondent significantly influences ZECC technology. Results as 
presented in Table 4.9 show that, an increase in the size of the household by one person 
would decrease the probability of adopting by 0.0004 percent. This result however does 
not satisfy the a-priori expected .it further disagrees with the study by (Mignouna et al., 
2011 and Bonabana- Wabbi 2002). Their report revealed that, household size is simply 
used as a measure of labor availability. It determines adoption process in that, a larger 
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household have the capacity to relax the labor constraints required during introduction of 
a new technology.  
Years of Education of the respondent was also positive and significant as indicated in 
Table 4.9. The results indicated that a one year increase in the years of a tomato farmer’s 
or trader’s education (schooling) increases the probability of adopting the ZECC 
technology by 0.02 percent. This study result on education is similar to the findings of 
Uematsu & Mishra (2010). 
Membership of GBO (Group-Based Organization) was positive and statistically 
significant. Given that a tomato farmer or trader is a member of a Group-Based 
Organization, then his or her probability of adopting the ZECC storage technology 
increases by 0.0382%.  
Extension visits in terms of the number of times a tomato farmer or trader had contacts 
to an extension officer per year was positive and significant to influence a tomato farmer 
and trader to adopt the ZECC technology. A one unit increase in the number of extension 
visits received by a tomato farmer or trader increases his or her probability of adopting a 
ZECC by 0.0427%. It can be established that, where extension visits serves its main 
purpose; thus providing knowledgeable information to a farmer or trader, it helps in a 
faster rate of adoption. This results meets the expected a-priori. The positive relationship 
between extension and the factors that would influence adoption of the ZECC storage 
technology is similar to that of Uaiene et al., (2009). They reported in their study that, 
whenever farmers are exposed to needed and essential information concerning an 
innovated technology, it influences their decision to adopt such a technology.  
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Perceived Cost of ZECC technology negatively influences respondents to adopt the 
Zero Energy Cool Chamber storage technology. As presented in Table 4.9, a one Ghana 
cedi increase in the perceived cost of ZECC decreases adoption of ZECC technology by 
0.2 percent. This gives a true reflection of the fact that, farmers and traders who perceive 
higher cost of adopting the ZECC storage technology would either choose to use the 
traditional storage method or decide not to store their produce at all. The result obtained 
in this study is in line with what was reported by Kinyangi (2014) on determinants of 
technology adoption by rural farmers and traders. It also, gives a true reflection of why 
most of the respondents are aware of the ZECC storage technology but do not use it in 
the first objective. 
Monthly Tomato Income received per season was also positive and statistically 
significant at 1% level. Results presented in Table 4.9 indicated that a one Ghana cedi 
increase in the incomes generated from tomato farming and trading increases the 
probability of adopting the ZECC storage technology by 0.00005%. This result is also in 
line with the economic theory that, the higher the income of an individual, the higher the 
individual’s ability to purchase, ceteris paribus. 
Monthly Savings was significant and had a negative influence. The results indicate that, 
when savings increases by one Ghana Cedis, the probability of adopting the ZECC 
storage decreases by 0.02 percent. Savings gives the opportunity to have access to 
money. It is obvious that, when an individual have money, that is when that individual 
can decide to invest into a particular investment, and the vice versa holds for it. Most 
banks in Ghana normally give our loans based on your saving ability, amount saved and 
your frequency of depositing. This is the baseline most rural banks use. 
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Type of person aware of ZECC storage technology was significant. Results of the table 
4.9 revealed that, a trader’s probability increase by 0.03 percent when the person who 
wants to adopt is a trader. This result is also in connection with the reasons why most of 
the respondents using the ZECC storage technology are traders as analysed and revealed 
by the objective one. 
User of TMS as a factor had a negative influence on the adoption of the ZECC storage 
technology. The results on this factor showed that, being a user of the traditional storage 
method decreases the probability of adopting the ZECC by 0.04 percent. This result 
shows that the farmers and traders are conservative, and gives a clear explanation on why 
most of the farmers and traders are still using the existing method of storage although 
they are aware of the ZECC storage technology. Although it was expected that, a user of 
an existing technology is likely to adopt a new technology, this result showed the 
otherwise of the a-priori expectation. 
 
4.6 Identification and Ranking of Constraints Faced by Farmers and Traders  
4.6.1 Constraints faced by farmers 
As presented in Table 4.10, the computed Kendall’s Coefficient of Concordance (W) 
statistics was 0.91 which is significant at 5%. This means that there is 91% agreement 
among the tomato farmers (who are using the ZECC) in rankings of the constraints faced 
in adopting and or using the ZECC storage technology. This means that, the null 
hypothesis which specifies that there is no agreement among the farmers in rankings of 
constraints is rejected. Since then PValue   0.000  0.05 , it shows that there is an 
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agreement among the farmers in ranking of constraints faced in adopting the ZECC 
storage technology.  
Results presented in Table 4.10 indicate the mean scores with the least scores showing 
the major constraints. Sampled tomato farmers identified and ranked access to credit’’ as 
the first most pressing constraint to adopting the ZECC storage technology. It was 
followed by animal disturbances and scarcity of water as third ranked constraint.  
Table 4. 10: Ranked Constraints of Farmers  
Constraint Mean Score Rank 
st
Access to Credit 1.186 1  
nd
Animal Disturbances  2.138 2  
rd
Scarcity of Water  3.024 3  
th
High Cost of Storage Inputs 4.052 4  
th
High cost of maintenance 5.000 5  
th 
Time demanding 6.000 6
N = 10 Degrees of Freedom = 5 Chi-Square = 154.189 
Kendall’s (W) = 0.91 Asymptotically Significant: P – Value = 0.00 < 0.05 
Source: Field data (2018) 
 
th th
High cost of storage inputs, high cost of maintenance and time demanding ranked 4 , 5 , 
th
and 6  constraints faced by farmers in using the ZECC storage technology respectively.  
The results of this study on the constraints or challenges faced by rural households in 
technology adoption confirms what was reported by Robinson et al., (2012) and Muzari 
(2012) in their studies. 
 
4.6.2 Constraints Faced by Traders 
Results presented in Table 4.11 indicated the ranked constraints faced by tomato traders. 
Tomato traders (who are using the ZECC) identified and ranked high cost of 
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transportation (mean score = 1.189) as the first most pressing constraint in adopting the 
ZECC storage technology followed by high cost of storage (mean score = 2.132) as 
second. Limited storage facilities as third constraint and time demanding (mean score = 
4.052) as the last but not the least constraint faced in adopting the ZECC storage 
technology. The result of the constraints or challenges faced by farmers and traders in the 
study area is not different from that of those reported by Robinson et al., (2012) in the 
study of technology adoption by rural household at India and Tanzania, respectively. 
Table 4.11 Ranked Constraints of Traders 
Constraint Mean Score Rank 
st
High Cost of Transportation 1.189 1  
nd
High Cost of Storage 2.132 2  
rd
Limited Storage Facilities 3.014 3  
th
Time Demanding 4.052 4  
N = 45 Degrees of Freedom = 3 Chi-Square = 630.77 
Kendall’s (W) = 0.89 Asymptotically Significant: P – Value = 0.00 < 0.05 
Source: Field data (2018) 
   
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CHAPTER FIVE 
SUMMARY, CONCLUSIONS AND RECOMMENDATIONS 
 
5.1 Introduction 
This chapter of the study presents the summary of main findings, conclusions, and 
suggested recommendations from the study for policy implications. 
 
5.2 Summary 
The study described the level of awareness and adoption of the ZECC storage technology 
among tomato farmers and traders in the Northern Region of Ghana. It further evaluated 
Cost-Benefit analysis of using the ZECC tomato storage technology. Also, the study 
examined the factors that influence tomato farmers and traders to adopt the ZECC storage 
technology. Finally, the study identified constraints that affect farmers and traders in the 
usage of the ZECC tomato storage technology. 
The study was conducted on a 210 sampled tomato farmers and traders in the Savelugu 
and Sagnarigu municipalities. The study used a well-structured questionnaire designed in 
closed and open format. Pretesting was done to examine the validity and reliability of the 
data collection instrument. The study used descriptive statistics such as frequencies, 
percentages, and means. The Benefit-Cost analysis, the probit regression model, and the 
Kendall’s Coefficient of concordance (W) to address the set objectives.  
The results show that the majority of respondents (53.80%) were females. The household 
size of respondents ranges from 1 to 12. Majority (51.40%) of the households had 
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household size above ten (10) members. Findings indicated that most (83.33%) of the 
sampled tomato farmers and traders were aware of the ZECC storage technology.  
On the other hand, a small proportion of the respondents (26%) (less than one-third of 
those who were aware) have adopted the ZECC technology whiles a larger proportion of 
about 74% of the respondents indicated that, they do not use the ZECC technology but 
either use the traditional methods of tomato storage (53.81%) or do not use any form of 
storage. Reasons given for using the ZECC storage technology included its ability to 
ensure quality of the tomato, serving as a source of employment, and increasing the shelf 
life of the tomato among others. On the other hand, farmers and traders who were aware 
of the ZECC storage technology but prefer to continue with the traditional method of 
storage also gave reasons being that, it is less costly, reduces spoilage of their tomatoes 
and lastly simply because other people are using it. 
The results of the Benefit-Cost analysis indicated a BCR of 1.52 and an NPV of GHS6, 
436.15 for ZECC and an NPV of GHS2, 699.41 and BCR of 1.09 for the traditional 
method of storage at 21% discount rate. The NPVs of both technologies gave an 
incremental NPV of GHS3, 739.32.  This implies that both the ZECC and the TMS are 
financially viable but the ZECC is more profitable. 
2
The probit model for the ZECC technology showed a pseudo R  of 0.903 which indicates 
that, about 90% of the variation in the farmers’ and traders’ adoption of the ZECC 
storage technology is influenced by the independent variables. Results of the probit 
regression revealed that gender, household size, marital status, years of education, GBOs, 
extension visits, tomato income, savings, types of persons aware of the ZECC, perceived 
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cost of the ZECC storage technology and users of the TMS were statistically significant 
in influencing the adoption of the ZECC storage technology among tomato farmers and 
traders in the study area. 
Also, Kendall’s Coefficient of Concordance (W) statistics was 0.91 and significant at 5%. 
This showed that there was 91% agreement among the tomato farmers and traders in the 
rankings of the constraints faced in adopting the ZECC storage technology. For farmers, 
‘access to credit’, ‘animal disturbances’, and ‘scarcity of water’ were ranked as first, 
second and third most pressing constraints, among others. Traders, also ranked ‘high cost 
of transportation’, ‘high storage charges’, and ‘limited storage facilities’ as their most 
pressing constraints, among others. 
 
5.3 Conclusions 
The study concluded, based on the findings that although most of the sampled 
respondents were aware of the ZECC storage technology the majority do not see the need 
for using it. The Benefit-Cost ratios (BCRs) and Net Present Values (NPVs) showed that 
the ZECC technology is more financially viable than the existing method of storage. 
Factors that significantly influenced the ZECC storage technology adoption were: gender, 
years of education, GBOs, extension visits, tomato income, and perceived cost of the 
ZECC storage technology. Based on these findings, improvements targeted at male 
farmers and traders on factors identified would increase the probability of adopting the 
ZECC storage technology. Both farmers and traders face a number of peculiar constraints 
which need to be addressed, notable among them being ‘‘access to credit’’ and ‘‘high 
cost of transportation’’ respectively. 
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5.4 Recommendations 
The following recommendations have been suggested based on the findings of the study:  
1. There is a need to increase smallholder farmers’ and traders’ education on the 
significance of adopting modernized technologies like the Zero Energy Cool 
Chamber storage technology (ZECC). Currently, modern storage technologies 
improve the life span of perishable commodities like tomatoes, and other fruits and 
vegetables. Therefore, there would be a great farming and agribusiness success if 
farmers and traders are educated to adopt new technologies that would assist them in 
their farming businesses rather than the continued reliance on the traditional storage 
methods. The agriculture training institutions like the Agricultural training colleges 
in the country should channel their students to places like Savelugu and Sagnarigu 
during internship to help sensitize the key importance of adopting the ZECC storage 
technology to farmers and traders. Agribusiness related NGOs like Alliance for the 
Green Revolution in Africa (AGRA) should place keen attention on farmers’ and 
traders’ education and training programmes on modern technology adoption since 
their major policy is to help millions of small-scale farmers and traders lift 
themselves out of poverty and hunger. 
2. Zero Energy Cool Chamber (ZECC) storage technology proves to be a financially 
viable technology for tomato storage in the Northern Region. It is recommended that 
the Ministry of Food and Agriculture and NGOs like GIZ should subsidize the cost 
of providing facilities like the ZECC storage technology for the rural or remote 
farming communities in order to prevent and/or reduce the frequent tomato post-
harvest losses as a result of lack of cold storage technology or poor storage systems 
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in such areas in the country.  Also Rural and Agricultural financial institutions like 
Agricultural Development Bank (ADB) should assist farmers and traders (by 
granting them loans applied for) to build storage facilities like the ZECC.   
3. Socio-economic factors including gender (particularly males), years of education, 
membership of group-based organizations, extension visits, tomato income and 
perceived cost of ZECC technology should be given close attention by agricultural 
agents, especially extension officers, in the course of providing their services to the 
rural tomato farmers and traders. It is recommended that the extension-to-farmer 
ratio be improved upon to enable extension officers pay frequent visits to farmers 
and traders to educate them on modern storage culture of raw farm produce.  
4. Since the major constraints faced by tomato farmers in adopting the ZECC tomato 
storage technology were: access to credit, animal disturbances, and scarcity of water; 
and ‘high cost of transportation’, ‘high cost of storage’, and ‘limited storage 
facilities’ for traders in the Northern Region, It is therefore, recommended that, 
development agencies tailor their development plans and projects towards provision 
of subsidized credit, reduced cost of building storage facilities, and addressing other 
challenges that hinder the ZECC usage in the Northern Region of Ghana.  
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APPENDICES 
APPENDIX 3.1: QUESTIONNAIRE FOR THE STUDY 
 
UNIVERSITY OF GHANA, LEGON 
DEPARTMENT OF AGRICULTURAL ECONOMICS AND AGRIBUSINESS 
This questionnaire is to gather data on the topic: Financial Viability and Adoption of the 
ZECC Storage Technology for Tomato storage in the Savelugu and Sagnarigu 
municipalities in the Northern Region of Ghana. Please this is for an academic purpose 
only therefore information provided will be treated with confidentiality.  
Questionnaire Number: …………  Name of Enumerator ……………………. 
Date of interview: ……………  Please kindly tick where necessary. 
Location…………………. 
A. Socio – Economic characteristics of farmers and traders 
1. Gender 1 = Male [ ] 0 = Female [ ] 
2. Household size ………………………………………… 
3. Age of respondent …………………………………………. 
4. What are your years of formal education? ………………………. 
5. Highest Educational Qualification obtained?   0 = None [ ] 1 = Primary [ ]    2= JHS []    
3 = SHS/Vocational/Technical   4 = Tertiary [ ] 5 = Other (    ) ……                        
6. What is your marital status? 1=Single [ ] 2=Married [ ] 3=Divorce/separated [ ] 4=   
widowed [ ] 
7. What is your major occupation?........................................................... 
8. What are the other occupation(s) in other of priority? ......................................... 
9. Do you belong to any Farmer Based or Market Organization (GBO)? 1=Yes [ ] 0=No[]  
10. If yes what is the name of that Organization? ………………………………….  
11. Do you have contact with extension/market officer(s)? 1= Yes [ ] 0= No [ ]  
12. If yes, how often do they contact you? 1= Weekly [ ] 2. Monthly [ ] 3. Others 
(specify)…... 
13. What is the ownership of the Land you use for storing? 1= Own 2 = Relatives 3 = 
Renting 4 = Not Applicable 
14. If renting, how much do you pay a month?..................... 
15. Please which of these communities is your tomato storage located? 1= Savelugu, 2= 
Sagnarigu  
16. What are your source of financing your tomato business? 1= self 2= relatives 3= 
Bank 
17. How much income do you get monthly in the tomato cultivation?............................. 
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18. Do you cultivate/sell other crops aside tomatoes? 1= Yes [ ] 0= No [ ]  
19. How much money do you get from the other crops each month? …………………  
20. How much income do you get from other occupation(s) month?.................................. 
21. What is your total average monthly income?..................................... 
22. Do you save? 1=yes 0=no 
23. On average, how much do you save monthly? GH¢………………… 
24. Do you store your tomatoes? 1= yes 0= No 
25. What is your minimum quantity stored at a time for the market? .........................  
26. What is your maximum quantity stored at a time for the market? .................................  
27. Please since when have you been storing your tomatoes?…………………… 
28. For how long do you store your tomatoes? Less than 7 days [  ] One week [  ] About 
Two weeks [ ] 
29. Do you get any financial assistance in your storage business? 1= Yes [ ]  0 = No [ ] 
30. If yes, from where? 1= relatives 2= Bank 3= other (specify)………………………… 
 
Awareness of ZECC Method and other Tomato Storage Techniques 
 
(ZECC is a brick layered rectangular shaped structures that requires zero energy to 
operate, it provides cooling environment that prolongs the shelf life of produce. These 
produce are mainly fruits and vegetables.) 
31. Are you aware of the Zero Energy Cool Chamber (ZECC) used for tomato storage?  
1= Yes 0=No 
32. If yes do you use it? 1= Yes 0=No 
33. If you use it, how much does it cost on the average... 
 34. If you don’t use it why don’t you...  
35. Are you aware of any other storage technique used for tomato storage? 1= Yes 0=No 
36. If yes what is it? …………………………………………………………. 
37. If you are aware do you use it? 1= Yes 0=No 
38.  If you use it, how much does it cost... 
39. If you are aware but you do not use it, why don’t you? ……… 
40. Which of the following would be your reason for using the Zero Energy Cool 
Chamber? 
 Please tick where appropriate.  
Reasons for adopting Zero 1= 2= 3=  agreed 
Energy Cool Chamber  disagree Indifferent 
It ensures quality of produce    
It serves as employment    
It increases shelf life    
It increases income    
Because others are using it    
 
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41. Which of the following would be your reason for using the Other Storage Technique? 
Please tick where appropriate 
Reasons for adopting other Storage 1= disagree 2= Indifferent 3=  agreed 
It is less costly    
It reduces spoilage    
Because others are using it    
 
 
Assessing the costs and benefits of using the Zero Energy Cooling Chamber 
42. Please indicate the quantities and unit prices of the materials used for your tomato  
       storage.    
 
Capital cost 
ITEMS SIZE QUANTITY COST 
Land    
Pipe holes    
Tomato crates    
Jute cloth    
Bricks    
Bamboo    
Reefs    
Shovel    
Knapsack sprayer    
Sand    
Watering can    
Bucket    
Others (specify)    
    
 
Material Input 
Items Quantity Unit price 
Tomatoes   
Insecticide   
Dry grass   
Broom   
Water   
Napkin   
Dust collector   
Others(specify)   
 
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Labour Input 
Activity Tech. Capacity No. of No. of No. of No. of Wages 
of storage Males Females Chn Days 
facility Worked 
Debris collection        
and burning 
Sorting        
Watering        
Cleaning        
Loading and off        
loading 
Others(specify)        
 
Services 
Activity Cost 
Transportation  
Repairs & Maintenance  
Hiring other than transport  
Utilities  
Others(specify)  
 
 
Revenue from Tomato Storage (ZECC) 
Type of  Frequency Quantity No. of Total Total Quantity  Unit 
Tomatoes of storage  of storage sales per quantity sold after storage Price  
stored batch of sales 
       
       
 
Revenue from Other Tomato Storage 
Type Frequency Quantity No. of Total Total Unit Price  
of  of storage  of sales per quantity of Quantity  
Tomat storage batch sales sold after 
oes storage 
stored 
       
       
 
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44. Constraints Faced in Adopting the ZECC Tomato Storage Technology 
Please kindly rank the constraints faced in order of 1 = most pressing constraint to least 
constraint. 
Constraints Rankings  
Inadequate storage facilities  
High cost of maintenance  
High cost of Transportation in going to store  
High cost storage charges  
Access to credit  
Animal Disturbances  
Scarcity of water  
Time demanding  
Limited storage facilities  
Others(specify)  
 
 
 
Thank you for your time 
 
 
 
 
 
 
 
 
 
 
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APPENDIX 4.1 AVERAGE CAPITAL COST ESTIMATION FOR   
TRADITIONAL METHOD STORAGE METHOD (TMS) 
CAPITAL UNIT QUANTITY UNIT VALUE USEFUL 
ITEMS PRICE LIFE 
COST 
Jute Sack Pieces 4 pieces 6.00 24.00 2 years 
Bucket Litre 5616 litres 0.006 33.696 2 years 
Crates(35kg) Kg 3units 5.00 15.00 3 years 
TOTAL    72.696  
COST 
 
 
 
APPENDIX 4.2 AVERAGE ANNUAL OPERATING BUDGET FOR 
TRADITIONAL METHOD OF STORAGE (TMS) 
  QUANTITY UNIT PRICE             VALUE  
(GHS)        (GHS) 
     
Revenue     
Sales  4495.4 1.36 6113.744 
Total Cash inflow    6113.744 
Operating Costs     
(Recurrent Costs) 
Materials     
Tomatoes  5460kg 0.86 4695.60 
Dust Bin  1unit 5.00 5.00 
Broom  4units 1.00 4.00 
Water  5616liters 0.006 33.696 
Labour  60man-days 10.00 600.00 
Transport  50kg-metre 1.00 50.00 
 Maintenance  5 times 6.00 30.00 
Contingencies  5%  145.6988 
Total Operating    5563.9948 
Cost 
Total Cash Outflow    5636.6908 
Net Cash Flow    549.7492 
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APPENDIX 4.7: STATA RESULTS FOR PROBIT REGRESSION OUTPUTS 
 
Probit regression                               Number of obs     =        175
                                                Wald chi2(13)     =      62.07
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -11.249184               Pseudo R2         =     0.9030
                                                                                    
                                   Robust
         AdoptZECC        Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
                                                                                    
            Gender     1.634345   .6426167     2.54   0.011     .3748394     2.89385
               Age    -.0347962   .0281066    -1.24   0.216    -.0898842    .0202917
            HHSize     -.326414   .1310144    -2.49   0.013    -.5831975   -.0696306
           YrsEdu2     1.464869   .3676174     3.98   0.000     .7443524    2.185386
           Marital    -.3864575   .4027139    -0.96   0.337    -1.175762    .4028473
               GBO     1.656085   .7600316     2.18   0.029       .16645    3.145719
         Extension     1.339175     .68459     1.96   0.050    -.0025973    2.680946
          Location     .1874261   .9438962     0.20   0.843    -1.662576    2.037429
 PerceivedCostZECC    -2.936343    1.06542    -2.76   0.006    -5.024528    -.848158
MonthlyIncomTomato     .0040041   .0020487     1.95   0.051    -.0000114    .0080195
              Save    -1.316072   .5556276    -2.37   0.018    -2.405082   -.2270615
   TypePersonAware     1.151424   .5338167     2.16   0.031     .1051626    2.197686
          UsersTMS    -3.596869   1.480074    -2.43   0.015    -6.497761    -.695976
             _cons     1.646924   2.244501     0.73   0.463    -2.752216    6.046064
                                                                                    
 
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APPENDIX 4.8  MARGINAL EFFECTS OUTPUTS 
 
. mfx
Marginal effects after probit
      y  = Pr(AdoptZECC) (predict)
         =  .99595546
                                                                              
variable        dy/dx    Std. Err.     z    P>|z|  [    95% C.I.   ]      X
                                                                              
  Gender*     .031591      .04499    0.70   0.483  -.056595  .119777   .485714
     Age    -.0004163      .00066   -0.63   0.531  -.001719  .000886   43.1886
  HHSize    -.0039056      .00671   -0.58   0.561  -.017057  .009245   9.89143
 YrsEdu2     .0175273      .02991    0.59   0.558    -.0411  .076155   4.74857
 Marital     -.004624      .00991   -0.47   0.641  -.024044  .014796   2.08571
     GBO*    .0382024      .04571    0.84   0.403  -.051383  .127788   .531429
Extens~n*     .042745      .08937    0.48   0.632  -.132425  .217915   .702857
Location*    .0019081      .01042    0.18   0.855  -.018514   .02233       .16
Percei~C*   -.1876019      .13851   -1.35   0.176  -.459069  .083865        .4
Monthl~o     .0000479      .00008    0.62   0.537  -.000104    .0002   227.314
    Save*   -.0145912      .02435   -0.60   0.549  -.062323  .033141       .64
TypePe~e*    .0268793       .0435    0.62   0.537  -.058387  .112145       .64
UsersTMS*   -.0405818       .0417   -0.97   0.330  -.122312  .041149   .748571
                                                                              
(*) dy/dx is for discrete change of dummy variable from 0 to 1
 
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