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An Empirical Investigation of Factors Influencing the Adoption Decision of Mobile Agriculture in Nigeria

by Oladotun Okediran, Wajeed Wahab, Olusola Ogunjinmi
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 175 - Number 20
Year of Publication: 2020
Authors: Oladotun Okediran, Wajeed Wahab, Olusola Ogunjinmi
10.5120/ijca2020920739

Oladotun Okediran, Wajeed Wahab, Olusola Ogunjinmi . An Empirical Investigation of Factors Influencing the Adoption Decision of Mobile Agriculture in Nigeria. International Journal of Computer Applications. 175, 20 ( Sep 2020), 44-51. DOI=10.5120/ijca2020920739

@article{ 10.5120/ijca2020920739,
author = { Oladotun Okediran, Wajeed Wahab, Olusola Ogunjinmi },
title = { An Empirical Investigation of Factors Influencing the Adoption Decision of Mobile Agriculture in Nigeria },
journal = { International Journal of Computer Applications },
issue_date = { Sep 2020 },
volume = { 175 },
number = { 20 },
month = { Sep },
year = { 2020 },
issn = { 0975-8887 },
pages = { 44-51 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume175/number20/31572-2020920739/ },
doi = { 10.5120/ijca2020920739 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:25:37.125693+05:30
%A Oladotun Okediran
%A Wajeed Wahab
%A Olusola Ogunjinmi
%T An Empirical Investigation of Factors Influencing the Adoption Decision of Mobile Agriculture in Nigeria
%J International Journal of Computer Applications
%@ 0975-8887
%V 175
%N 20
%P 44-51
%D 2020
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, an extended technology acceptance model (TAM) was presented to investigate the factors that have effects on the intention to adopt and use mobile agriculture (m-Agriculture). The paper’s main objective is to survey the usage of mobile phones in agriculture and examine the prospects and intents toward m-Agriculture among smallholder famers in South-western Nigeria. A survey was conducted by administering a questionnaire containing 25 items. The data collected from the survey was used to empirically test the proposed model for the adoption and use of m-Agriculture. The model was evaluated using the partial least squares structural equation analysis. The results of the evaluation showed that all the variables have significant effect on the farmers’ behavioural intention to use m-Agriculture. In concluding the paper, the authors proposed an m-Agriculture architecture whose contents delivery channels are based on voice, short message service (SMS) and Unstructured Supplementary Service Data (USSD) of basic/feature phones with the aim of providing a digital platform for enhancing agricultural productivity, efficiency and sustainability.

References
  1. Okediran, O.O., Ganiyu, R.A. and Badmus, T.A. 2018. An m-Agriculture framework for agriculture information services delivery, LAUTECH Journal of Engineering and Technology 12(2):72-79.
  2. Okediran, O.O. 2019. An e-Agriculture framework for inclusive agricultural values chains in Nigeria, Annals. Computer Science Series, Tibiscus University of Timisoara, Romania, 17(2): 2009 – 2019.
  3. Miller, C., Saroja, V.N. and Linder C. 2013. ICT Uses for Inclusive Agricultural Value Chains. FAO, Rome.
  4. Awuor, F., Kimeli, K., Rabah, K. and Rambim, D. 2013. ICT Solution Architecture for Agriculture, IST-Africa 2013 Conference Proceedings Paul Cunningham and Miriam Cunningham (Eds) IIMC International Information Management Corporation.
  5. Namisiko, P. and Aballo, M. 2013. Current Status of e-Agriculture and Global Trends: A Survey Conducted in TransNzoia County, Kenya, International Journal of Science and Research, India, 2(7): 18-22.
  6. Meera, S., Jhamtani, A. and Rao, D.U.M. 2004. Information and communication technology in agricultural development: A comparative analysis of three projects from India, Agricultural Research and Extension Network, Network Paper No. 135, pp 1-20.
  7. ICT Updates 2013. e-Agriculture Strategies”, Issue 73, Available at https://cgspace .Cigar. org/bitstream /handle/ 10568/75314/ICT073E_PDF.pdf?sequence= 1&is Allowed=y.
  8. Mcnamara, K.., Belden, C., Kelly, T., Pehu, E. and Donovan, K. 2011. Introduction: ICT in Agricultural Development, ICT in Agriculture. The World Bank.
  9. Okediran, O.O. and Ganiyu, R.A. 2019. e-Agriculture reviewed: Theories, concepts and trends, FUOYE Journal of Engineering and Technology, 4(1):125-130.
  10. [10 Okediran, O.O., Omidiora, E.O., Olabiyisi, S.O. and Ganiyu, R.A. 2013. An M-voting System Framework for Electronic Voting, Proceedings of the Second International Conference on Engineering and Technology Research, Lautech, Ogbomoso, Nigeria.
  11. Burrell, J. 2008. Livelihoods and the Mobile Phone in Rural Uganda. Retrieved from http://www. Rameen foundation.applab.org/section/ethnographic-research
  12. Qiang, C.Z., Kuek, S.C., Dymond, A. and Esselaar, S. 2012. Mobile Applications for Agriculture and Rural Development, ICT Sector Unit World Bank, Washington D.C.
  13. Davis, F. 1989, Perceived Usefulness, Perceived ease of use and user acceptance of information technology, MIS Quarterly, 13(3): 318–339.
  14. 4Ajzen, I. and Fishbein, M., 1980. Understanding Attitudes and Predicting Social Behaviour. Prentice-Hall, Englewood Cliffs, New Jersey.
  15. Taylor, S. and Todd, P. 1995. Understanding information technology usage: A test of competing models, Information Systems Research, 6(2):143–176.
  16. Davis, F.D., Bagozzi, R.P. and Warshaw, P.R. 1989. User acceptance of computer technology: A comparison of two theoretical models, Management Science 35, 982–1003.
  17. Davis, F.D. and Cosenza, R.M. 1993. Business Research for Decision Making. Third Edition. Belmont, CA.: Wadsworth Inc.
  18. Adams, D., Nelson, R. and Todd, P. 1992. Perceived usefulness, ease of use, and usage of information technology: A replication’, MIS Quarterly, 16(2): 227–247.
  19. Fishbein, M. and Ajzen, I. 1975. Belief, Attitude, Intentions and Behaviour: An Introduction to Theory and Research. Addison-Wesley, Boston.
  20. Fishbein, M. and Ajzen, I. 1979. A Theory of Reason Action: Some Applications and Implications, in Howe H. and Page M. (Eds): Nebraska Symposium on Motivation, University of Nebraska Press, Lincoln, NB, pp.65–116.
  21. Yogesh, M. and Dennis, F. 1999. Extending the Technology Acceptance Model to Account for Social Influence: Theoretical Bases and Empirical Validation’, Thirty-Second Annual Hawaii International Conference on System Sciences, IEEE.
  22. Chen, L., Gillenson, M. and Sherrell, D. 2002. Enticing online consumers: an extended technology acceptance perspective, Information and Management,39(8):705–719.
  23. Legris, P., Ingham, J. and Collerette, P. 2003. Why Do People Use Information Technology? A Critical Review of the Technology Acceptance Model, Information & Management, 40(3):191–204.
  24. Venkatesh, V. and Davis, F. 2000. A theoretical extension of the technology acceptance model: Four longitudinal field studies, Management Science, 46(2): 186–204.
  25. Szajna, B. 1996. Empirical Evaluation of the revised technology acceptance model, Management Science, 42(1): 85–92.
  26. Lucas, H.C. and Spitler, V.K. 2000. Implementation in a world of workstations and networks, Information & Management, 38(2): 119–128.
  27. Venkatesh V. and Bala H. 2008. Technology acceptance model 3 and a research agenda on interventions”. Decision sciences, 39(2):273-315.
  28. Rogers, E.M. 1995. Diffusion of Innovations. The Free Press, New York.
  29. Cheong, J. and Park, M. 2005. Mobile Internet Acceptance in Korea, Internet Research: Electronic Networking Applications and Policy, 15:.125–140.
  30. Yin R.K. 1984. Case Study Research: Design and Methods. Sage Publications, Beverly Hills, California.
  31. DeVellis R.F. 1991. Scale Development. Newbury Park, CA: Sage Publications.
  32. Thompson. R.L., Higgins, C.A. and Howell, J.M. 1995. Influence of experience on personal computer utilization: Testing a conceptual model, Journal of Management Information Systems, 11(1): 167-187.
  33. Cheung, C. and Lee, M. 2000. Trust in Internet Shopping: A Proposed Model and Measurement Instrument”, Proceedings of the Sixth Americas Conference in Information Systems, August 10-13, 2000, Long Beach, CA.
  34. Fornell, C. and Larcker, D.F. 1981, Evaluating structural equation models with unobservable variables and measurement error, Journal of Marketing Research, 18: 39-50.
Index Terms

Computer Science
Information Sciences

Keywords

Mobile agriculture Technology acceptance model Smallholder farmers Job relevance Performance expectancy Perceived compatibility Perceived price value Social influence

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