Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

Mediating Effect of Price Value on Effort Expectancy and Behavioural Intentions to use Mobile Communication Technologies by Commercial Farmers in Uganda


Affiliations
1 Department of Management and Business Administration, Makerere University Business School, Uganda
     

   Subscribe/Renew Journal


This study examines the mediating role of Price Value on Effort Expectancy and Behavioural Intentions to Use mobile communication technologies by commercial farmers in Uganda. A cross sectional design and quantitative field survey method were adopted with 302 commercial farmers’ selected using snowball and purposive sampling techniques for the survey. Statistical mediation analysis was carried out using bootstrap mediation tool in Analysis of Moments Structures (AMOS) and Statistical Package for Social Sciences (SPSS) to test for mediation between the three variables of Price value, Effort Expectancy and Behavioural Intentions to Use. Price Value was found to mediate Effort Expectancy on Behavioural Intentions to use. From the findings, there is need for knowledge creation and market research so as to understand the unique needs of price value perceived by commercial farmers on mobile communication technologies, effort expectancy and behavioural intention on demand side. The study thus provides critical literature and evidence on the mediating role of Price value on relationship between Effort Expectancy and behavioural intention of mobile communication technologies by commercial farmers in resource constrained countries like Uganda. The study further proves that there exists a direct relationship between Price Value and Effort Expectancy; Effort Expectancy and Behavioural intentions to use of Mobile communication technologies. Policy makers need to design mobile phone policies and adopt strategies geared through Price Value, Effort Expectancy and Behavioral Intentions to use. It is also imperative that Policy frameworks support the establishment of robust, cost effective and easy to use Mobile communication technologies in ministry of agriculture to enhance service delivery.

Keywords

Mobile Communication Technologies (MCTs), Price Value (PV), Effort Expectancy (EE), UTAUT2, Behavioural Intentions to Use (BIU).
Subscription Login to verify subscription
User
Notifications
Font Size

  • F. Akbar, “What Affects Students’ Acceptance and Use of Technology?”, PhD Dissertation, Department of Information Systems, Dietrich College of Humanities and Social Sciences, 2013.
  • S.J. Alotaibi and W. Mike, “Acceptance Theories and Models for Studying the Integrating Physical and Virtual Identity Access Management Systems”, International Journal for e-Learning Security, Vol. 3, No. 1-2, pp. 1-10, 2013.
  • M. Adewumi, “Constraints to use of Mobile Telephony for Agricultural production in Ondo State, Nigeria Falola”, Journal of Research in Forestry, Wildlife and Environment, Vol. 4, No. 2, pp. 52-63, 2012.
  • A. Bhattacherjee, “Social Science Research: Principles, Methods, and Practices”, 2nd Edition, Createspace Independent Publishing, 2012.
  • P. Cisar and S.M. Cisar, “Skewness and Kurtosis in Function of Selection of Network Traffic Distribution”, Acta Polytechnica Hungarica, Vol. 7, No. 2, pp. 95-106, 2010.
  • W.G. Cochran, “Sampling Techniques”, Wiley Press, 1963.
  • L.J. Cronbach, “Coefficient Alpha and the Internal Structure of Tests”, Psychometrika, Vol. 16, No. 1, pp. 297-334, 1951.
  • A.Y.L. Chong, “A Two Staged SEM Neural Network Approach for Understanding and Predicting the Determinants of M-Commerce Adoption”, Expert Systems with Applications, Vol. 40, No. 4, pp. 1240-1247, 2013.
  • S. Datta and S. Mullainathan, “Behavioral Design: a New Approach to Development Policy”, Review of Income and Wealth, Vol. 60, No. 1, pp. 7-35, 2014.
  • S.N. Dick, “Use of Community Radio to Communicate Agricultural Information to Zimbabwe’s Peasant Farmers”, Aslib Proceedings, Vol. 64, No. 5, pp. 494-508, 2012.
  • J. Dudovskiy, “The Ultimate Guide to Writing a Dissertation in Business Studies”, Research Methodology.Net, 2014.
  • E. Duflo, M. Kremer and J. Robinson, “How high are Rates of Return to Fertilizer? Evidence from Field Experiments in Kenya”, American Economic Review, Vol. 98, No. 2, pp. 482-488, 2008.
  • B. Engotoit, G.M. Kituyi and M.B. Moya, “Influence of Performance Expectancy on Commercial Farmers’ Intention to Use Mobile-based Communication Technologies for Agricultural market Information Dissemination in Uganda”, Journal of Systems and Information Technology, Vol. 18, No. 4, pp. 551-567a, 2016.
  • T. Elly and E.E. Silayo, “Agricultural Information Needs and Sources of the Rural Farmers in Tanzania”, Library Review, Vol. 62, No. 8-9, pp. 547-566, 2013.
  • F.R.M. Lashgarara, “Challenges and Implications of ICT Application for Improving the Marketing of Agricultural Products at Garmsar City, Iran”, Agricultural Science Digest, Vol. 31, No. 3, pp. 161-166, 2011.
  • K. Ghalandari, “The effect of Performance Expectancy, Effort Expectancy, Social Influence and Facilitating Conditions on Acceptance of E-Banking Services in Iran: The Moderating Role of Age and Fender”, Middle East Journal of Scientific Research, Vol. 12, No. 6, pp. 801-807, 2012.
  • Lisa M. Given, “The Sage Encyclopedia of Qualitative Research Methods”, Sage Publications. 2008.
  • R. Hanna, S. Mullainathan and J. Schwartzstein, “Learning by Attending: Theory and Experimental Evidence in Seaweed Farming”, Available at: https://www.dartmouth.edu/~jschwartzstein/papers/noticing.pdf, Accessed on 2012.
  • J.F.J. Hair, W.C. Black, B.J. Babin and R.E. Anderson, “Multivariate Data Analysis: A Global Perspective”, Prentice Hall, 2010.
  • C.Y. Huang and Y.S. Kao, “UTAUT2 based Predictions of Factors Influencing the Technology Acceptance of Phablets by DNP”, Mathematical Problems in Engineering, Vol. 2015, pp. 1-23, 2015.
  • P. Howley, C.O. Donoghue and K. Heanue, “Factors Affecting Farmers’ Adoption of Agricultural Innovations: A Panel Data Analysis of the use of Artificial Insemination among Dairy Farmers in Ireland”, Journal of Agricultural Science, Vol. 4, No. 6, pp. 171-183, 2012.
  • M.S. Islam, “Agriculture Market Information Services (AMIS) in the Least Developed Countries (LDCs): Nature, Scopes, and Challenges”, Proceedings of International Conference on Electronic Government, pp. 109-120, 2010.
  • S.L. Jackson, “Research Methods and Statistics: A Critical Thinking Approach”, 4th Edition, Wadsworth Publishing, 2011.
  • M. Jambulingam, “Behavioral Intention to Adopt Mobile Technology among Tertiary Students”, World Applied Sciences Journal, Vol. 22, No. 9, pp. 1262-1271, 2013.
  • S.P. Katengeza, J.H. Mangisoni and J.J. Okello, “The Role of ICT-based Market Information Services in Spatial Food Market Integration: The Case of Malawi Agricultural Commodity Exchange”, Available at: http://ageconsearch.umn.edu/bitstream/96170/2/117.%20ICT%20information%20systems%20in%20Malawi.pdf, 2010.
  • C.R. Kothari, “Research Methodology: Methods and Techniques”, New Age International Ltd, 2009.
  • E. Listyo and S. Lisandy, “Factors Affecting the Use Behavior of Social Media Using UTAUT 2 Model”, Proceedings of 1st Asia Pacific Conference on Global Business, Economics, and Social Sciences, pp. 1-8, 2014.
  • N.R. Manaf and M. Ariyanti, “Exploring Key Factors on Technology Acceptance of Mobile Payment Users in Indonesia Using Modified UTAUT2 Model Use Case: ABC Easy Tap”, International Journal of Management and Applied Science, Vol. 3, No. 1, pp. 40-44, 2017.
  • Monitoring African Food and Agricultural Policies, “Review of Food and Agricultural Policies in Uganda 2005-2011”, Country Report, pp. 1-218, 2013.
  • Ministry of Agriculture, Animal Industry and Fisheries, “Agriculture Sector Development Strategy and Investment Plan”, Available at: http://www.fao.org/fileadmin/user_upload/drought/docs/Agriculture_DSIP%20Uganda1.pdf.
  • A. Miwanda, E. Kabaale and M.K. Kituyi, “Using ICTs to Disseminate Agricultural Marketing Information to Small Scale Rural Farmers in Western Uganda”, International Journal of Innovative and Applied Research, Vol. 2, No. 12, pp. 64-73, 2014.
  • G. Malima, C. Bukaza and K. Faustine, “Farmers Acceptance Behavior in Using Mobile Phones for Agricultural Marketing in Iringa Region, Tanzania”, PhD Dissertation, Department of General Management, University of Dar es Salaam Business School, 2015.
  • Z. Zaremohzzabieh, B. Abu Samah, S.O. Zobidah, J. Bolong and M.S. Azril, “Fisherman’s Acceptance of Information and Communication Technology Integration in Malaysia: Exploring the Moderating Effect of Age and Experience”, Journal of Applied Sciences, Vol. 14, No. 9, pp. 873-882, 2014.
  • M. Moya and B. Engotoit, “Behavioral Intention: Mediator of Performance Expectancy and Adoption of Commercial Farmers’ to Use Mobile-Based Communication Technologies for Agricultural Market Information Dissemination in Uganda”, Operations Research Society of Eastern Africa Journal, Vol. 7, No. 1, pp. 12-23, 2017.
  • H. Munyua and E. Adera, “Emerging ICTs and Their Potential in Revitalzing Small-Scale Agriculture”, Agricultural Information Worldwide, Vol. 2, No. 1, pp. 3-9, 2009.
  • Introduction to Research and Research Methods, Available at: https://www.unrwa.org/sites/default/files/introduction-to-research-and-research-methods.pdf
  • J. Nunnaly, “Psychometric Theory”, McGraw-Hill, 1978.
  • S.Y. Nyamba and R.S. Malongo, “Factors Influencing the Use of Mobile Phones in Communicating Agricultural Information: A Case of Kilolo District, Iringa, Tanzania”, International Journal of Information and Communication Technology Research, Vol. 2 No. 7, pp. 558-563, 2012.
  • C. Nyesiga, G.K. Mayoka, M. Musa and G. Aballo, “Effort Expectancy, Performance Expectancy, Social Influence and Facilitating Conditions as Predictors of Behavioural Intentions to use ATMs with Fingerprint Authentication in Ugandan Banks”, Global Journal of Computer Science and Technology: E Network, Web and Security, Vol. 17, No. 5, pp. 1-19, 2017.
  • Using ICT to Enhance Marketing for Small Agricultural Producers, Available at: https://www.agrilinks.org/sites/default/files/resource/files/Using_ICT_to_Enhance_Marketing_for_Small_Agricultural_Producers.pdf.
  • D.F. Polit, C.T. Beck and S.V. Owen, “Is the CVI an Acceptable Indicator of Content Validity? Appraisal and Recommendations”, Research in Nursing and Health, Vol. 30, No. 4, pp. 459-467, 2007.
  • K.J. Preacher and A.F. Hayes, “Asymptotic and Resampling Strategies for Assessing and Comparing Indirect Effects in Multiple Mediator Models”, Behaviour Research Methods, Vol. 40, No. 3, pp. 879-891, 2008.
  • K.J. Preacher, D.D. Rucker and A.F. Hayes, “Addressing moderated mediation hypotheses: Theory, methods, and prescriptions”, Multivariate Behavioral Research, Vol. 42, No. 1, pp. 185-227, 2007.
  • L.S. Prokopy, K. Floress, D. Klotthor Weinkauf and A. Baumgart Getz, “Determinants of Agricultural best Management Practice Adoption: Evidence from the Literature”, Journal of Soil and Water Conservation, Vol. 63, No. 5, pp. 300-311, 2008.
  • J.T. Roscoe, “Fundamental Research Statistics for the Behavioral Sciences”, Rinehart and Winston Publisher, 1975.
  • The Behavioral Economics Guide 2015, Available at: https://www.behavioraleconomics.com/the-behavioral-economics-guide-2015/.
  • S. Mugerwa, B.M. Musa and G.K. Mayoka, “Determinants of Behavioral Intention in Adopting Network Monitoring System”, International Journal of Computer Applications Technology and Research, Vol. 7, No. 3, pp. 139-157, 2018.
  • L.K. Soiferman, “Compare and Contrast Inductive and Deductive Research Approaches”, Available at: https://files.eric.ed.gov/fulltext/ED542066.pdf.
  • S. Sukamolson, “Fundamentals of Quantitative Research. Language Institute”, Available at: http://www.culi.chula.ac.th/Research/e-Journal/bod/Suphat%20Sukamolson.pdf.
  • F. Schrag, “In Defense of Positivist Research Paradigms”, Educational Researcher, Vol. 21, No. 5, pp. 5-8, 1992.
  • T.W. Toh, G. Marthandan, A.Y.L. Chong, K.B. Ooi and S. Arumugam, “What Drives Malaysian M-Commerce Adoption? An Empirical Analysis”, Industrial Management and Data Systems, Vol. 109, No. 3, pp. 370-388, 2009.
  • V. Venkatesh, M. Morris, G. Davis and F. Davis, “User Acceptance of Information Technology: Toward a Unified View”, MIS Quarterly, Vol. 27, No. 3, pp. 425-478, 2003.
  • V. Venkatesh, J.Y.L. Thong and X. Xu, “Consumer Acceptance and use of Information: Extending the Unified Theory of Acceptance and Use of Technology”, MIS Quarterly, Vol. 36, No. 1, pp. 157-178, 2012.
  • V. Venkatesh, J.Y.L. Thong and X. Xu, “Unified Theory of Acceptance and Use of Technology: A Synthesis and the Road Ahead”, Journal of the Association for Information Systems, Vol. 17, No. 5, pp. 328-376, 2016.
  • A. Vadivelu and B.R. Kiran, “Problems and Prospects of Agricultural Marketing in India: An Overview”, International Journal of Agricultural and Food Science, Vol. 3, No. 3, pp. 108-118, 2013.
  • Y.L. Wu, Y.H. Tao and P.C.Yang, “Using UTAUT to Explore the Behaviour of 3G Mobile Communication users”, Proceedings of IEEE International Conference on Industrial Engineering and Engineering Management, pp. 531-538, 2007.
  • K. Yang, “Determinants of US Consumer Mobile Shopping Services Adoption: Implications for Designing Mobile Shopping Services”, Journal of Consumer Marketing, Vol. 27, No. 3, pp. 262-270, 2010.

Abstract Views: 170

PDF Views: 0




  • Mediating Effect of Price Value on Effort Expectancy and Behavioural Intentions to use Mobile Communication Technologies by Commercial Farmers in Uganda

Abstract Views: 170  |  PDF Views: 0

Authors

Musa B. Moya
Department of Management and Business Administration, Makerere University Business School, Uganda
Benard Engotoit
Department of Management and Business Administration, Makerere University Business School, Uganda
Geoffrey Kituyi Mayoka
Department of Management and Business Administration, Makerere University Business School, Uganda

Abstract


This study examines the mediating role of Price Value on Effort Expectancy and Behavioural Intentions to Use mobile communication technologies by commercial farmers in Uganda. A cross sectional design and quantitative field survey method were adopted with 302 commercial farmers’ selected using snowball and purposive sampling techniques for the survey. Statistical mediation analysis was carried out using bootstrap mediation tool in Analysis of Moments Structures (AMOS) and Statistical Package for Social Sciences (SPSS) to test for mediation between the three variables of Price value, Effort Expectancy and Behavioural Intentions to Use. Price Value was found to mediate Effort Expectancy on Behavioural Intentions to use. From the findings, there is need for knowledge creation and market research so as to understand the unique needs of price value perceived by commercial farmers on mobile communication technologies, effort expectancy and behavioural intention on demand side. The study thus provides critical literature and evidence on the mediating role of Price value on relationship between Effort Expectancy and behavioural intention of mobile communication technologies by commercial farmers in resource constrained countries like Uganda. The study further proves that there exists a direct relationship between Price Value and Effort Expectancy; Effort Expectancy and Behavioural intentions to use of Mobile communication technologies. Policy makers need to design mobile phone policies and adopt strategies geared through Price Value, Effort Expectancy and Behavioral Intentions to use. It is also imperative that Policy frameworks support the establishment of robust, cost effective and easy to use Mobile communication technologies in ministry of agriculture to enhance service delivery.

Keywords


Mobile Communication Technologies (MCTs), Price Value (PV), Effort Expectancy (EE), UTAUT2, Behavioural Intentions to Use (BIU).

References