联系我们
Isaac Scientific Publishing
Manuscript Tracking System
Journal of Advances in Economics and Finance
JAEF > Volume 4, Number 3, August 2019

Industry Performance and Digital Disruption: Unleashing Possibilities for the African Farmer
Download PDF  (452.6 KB)PP. 98-108,  Pub. Date:July 4, 2019
DOI: 10.22606/jaef.2019.43002

Author(s)
Susanna E Botwood, Richard Chinomona, Krishna K Govender
Affiliation(s)
Da Vinci Institute of Technology Management, South Africa
Da Vinci Institute of Technology Management, South Africa
Da Vinci Institute of Technology Management, South Africa
Abstract
This study investigated digital maturity elements and possible disruptive technology platforms to test whether these elements contain the “secret recipe” for African farmers to gain access to markets and unleash their performance possibilities to alleviate poverty and increase the African farmer’s income. To empirically test four research hypotheses, data was collected from a sample of registered farmers and co-ops in databases from ProAgri, PanGlobal and TLU, and analysed using SPSS and the Smart PLS statistical software. It became evident that the most important antecedents of digital maturity in the industry are cultural aspects as well as the technology capabilities and digital platform capabilities positively influenced digital organisational performance. Managerial implications of the research findings are discussed, and limitations and future research directions are indicated.
Keywords
Digitisation, digital disruption, African farmer, global markets, poverty alleviation, developing countries, organisational performance.
References
  • [1]  Anthony, S.D., Johnson, M. & Sinfield, J.V. 2007. Building an innovation dynasty: how to build an engine that makes innovation more repeatable. Infosight Whitepaper. Available at: www.innosight.com.
  • [2]  Anthony, S.D., Johnson, M. & Sinfield, J.V. 2008. Institutionalizing innovation, MIT Sloan Management Review, 49(2): 45-53.
  • [3]  Beneke, J., Blampied, S. 2012. Driving Consumer Perceptions through Facebook: An Investigation into Empowering Brands in the 21st Century. The South African Institute of Management Scientists (SAIMS) 1987- 2012.
  • [4]  Bentler, P. M., & Bonett, D. G. (1980). Significance Tests and Goodness-of-Fit in the Analysis of Covariance Structures. Psychological Bulletin, 88: 588-600.
  • [5]  Berndt, M.C. & Petzer, D. 2013. Marketing Research. Cape Town: Pearson Education South Africa
  • [6]  Bramante, R., Petrella, G., & Zappa, D. (2015). On the use of the market model R-square as a measure of stock price efficiency. Review of Quantitative Finance and Accounting, 44(2), 379-391.
  • [7]  Brennan, S. & Kreiss, D. 2014. Digitalization & Digitization. Available at: http://culturedigitally.org/ 2014/09/digitalization-and-digitization. (Accessed: 18 October 2017).
  • [8]  Byrne, B.M. 2013. Structural Equation Modeling with LISREL, PRELIS, and SIMPLIS: Basic concepts, applications and programming. Lawrence Erlbaum Associates Inc. ISBN 0-8058-2924-5.
  • [9]  Chen, Y.Q., Zhang, Y.B., Liu, J.Y. and Mo, P., 2011. Interrelationships among critical success factors of construction projects based on the structural equation model. Journal of Management in Engineering, 28(3), pp.243-251.
  • [10]  Chinomona, R., 2011. Non-mediated channel powers and relationship quality: A case of SMES in Zimbabwe channels of distribution. Unpublished PhD. National Central University, Taiwan.
  • [11]  Chin, W.W. and Newsted, P.R., 1999. Structural equation modeling analysis with small samples using partial least. squares. Statistical strategies for small sample research, 1(1), pp.307-341
  • [12]  Christensen, C.M. 2006. The ongoing process of building a theory of disruption, Journal of Product Innovation Management, 23: 39-55.
  • [13]  Dockens, W.S 1979. Induction / Catastrophe Theory: A behavioral Ecological Approach to Cognition in Human Individuals. Behavioral Science. 24(2): 94 – 111.
  • [14]  Dunn, S.C., Seaker, R.F. and Waller, M.A., 1994. Latent variables in business logistics research: scale development and validation. Journal of Business logistics, 15(2).
  • [15]  Drnevich, P.L. & Kriauciunas, A. 2011. Clarifying the conditions and limits of the contributions of ordinary and dynamic capabilities to relative firm performance, Strategic Management Journal, 32: 254-279.
  • [16]  Fagarasanu, M. & Kumar, S. 2002. Measurement instrument and data collection: a consideration of constructs and biases in ergonomics research. International Journal of industrial ergonomics. 30(6): 355-369.
  • [17]  Geigher, S., Le Roux, E. & Bothma, T. 2014. The Predictive Value of Disruptive Technology Theory for Digital Publishing in the Traditional Publishing Environment: A South African Case Study, Journal Of Scholarly Publishing, 45(3): 261-288. (Accessed: 11 June 2015).
  • [18]  Gimpel, C. & Westerman, G. 2012. Shaping the future: Seven enduring principles for fast changing industries, MIT Center for Digital Business.
  • [19]  Glendenning, C.J. & Ficarelli, P.P. 2011. Content development and management processes of ICT initiatives in Indian agriculture. Article first published online: December 9, 2011; Issue published: November 1, 2011. International Livestock Research Institute, New Delhi, India Volume: 27 issue: 4, page(s): 301-314
  • [20]  Grace, J.B., 2006. Structural equation modeling and natural systems. Cambridge University Press.
  • [21]  Hair, J.F. J., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2014). A Primer On Partial Least Squares Structure Equation Modeling (PLS-SEM). Sage Publications Inc.
  • [22]  He, Y., Gai, Y., Wu, X. and Wan, H., 2012. Quantitatively analyze composition principle of Ma Huang Tang by structural equation modeling. Journal of ethnopharmacology, 143(3), pp.851-858.
  • [23]  Hirota, N. 2016. Impact of new technologies (revolutionary change) on a firm’s existence. Explanation of Disruptive Innovation of Clayton Christensen (1997). 12 Manage.com
  • [24]  Johnson, R.B. & Onwuegbuzie, A.J. 2004. Mixed Methods Research: A Research Paradigm Whose Time Has Gone, Educational Researcher, 33(7): 14-26.
  • [25]  Johnson, R.B. & Christen, L. 2008. Educational Research Quantitative, Qualitative and Mixed Method Approaches. 3rd Ed. Thousand Oaks, CA: Sage Publications.
  • [26]  Karimi, J. & Walter, Z. 2015. The Role of Dynamic Capabilities in Responding to Digital Disruption: A Factor- Based Study of the Newspaper Industry. Journal of Management Information Systems, 32(1): 39-81. (Accessed: 17 July 2015).
  • [27]  Kichner, L. 2005. Will “digital first” bring home the bacon? Columbia Journalism Review. Available at: www.cjr.org.
  • [28]  Kim, S. & Lee, H. 2006. The impact of Organisational Context and Information Technology on Employee Knowledge – Sharing Capabilities. Wiley Online Library. Public Administration Review. Vol. 66, No.3 (May – June 2006) pp. 370-385.
  • [29]  Lakoff, J. & Johnson, M. 1987. Metaphors We Live By. Chicago, IL: The University of Chicago Press. ISBN 0- 226-46801-1.
  • [30]  Liljander, V. Polsa, P., Van Riel, A. 2009. Modelling consumer responses to an apparel store brand. Elsevier.
  • [31]  Nitzl, C., Roldan, J. L., & Cepeda, G. (2016). Mediation analysis in partial least squares path modeling: Helping researchers discuss more sophisticated models. Industrial management & data systems, 116(9), 1849-1864.
  • [32]  Nusair, K. and Hua, N., 2010. Comparative assessment of structural equation modeling and multiple regression research methodologies: E-commerce context. Tourism Management, 31(3), pp.314-324.
  • [33]  Makhaya, T. & Nhundu, N. 2015. Competition Barriers to Entry and Inclusive Growth in Retail Banking: Capitec Case Study. Centre of Competition Regulation and Economic Development (CCRED), University of Johannesburg. Cited in Bloomberg Article.
  • [34]  Mantena, R. & Saha, R. 2012. Co-opetition between differentiated platforms in two-sided markets, Journal of Management Information Systems, 29(2): 109-139.
  • [35]  McKinsey & Co. 2014. Building up your digital quotient: How to harness digital to accelerate business performance. McKinsey Digital.
  • [36]  Meyer, M.H. & Lehnerd, M.A. 1997. The Power of Product Platforms, Building value and cost leadership. New York, NY: New York Free Press.
  • [37]  Meyer, M.H. & Lehnerd, M.A. 1997. The Power of Product Platforms, Building value and cost leadership. New York, NY: New York Free Press.
  • [38]  Milliot, J. 2015. Hastings Fights Digital Disruption 2014, Publishers Weekly, 261(19): 7. (Accessed: 20 July 2015).
  • [39]  O’Reilly, C.A. & Pfeffer, J. 2000. Hidden value: How great companies achieve extra-ordinary results with ordinary people. Boston, MA: Harvard Business School Press.
  • [40]  Owusu, A., Agbemabiasie, G. C., Abdurrahaman, D. T., & Soladoye, B. A. (2017). Determinants of Business Intelligence Systems Adoption in Developing Countries: An Empirical Analysis from Ghanaian Banks. The Journal of Internet Banking and Commerce, 2017.
  • [41]  Owusu, A., Agbemabiasie, G. C., Abdurrahaman, D. T., & Soladoye, B. A. (2017). Determinants of business intelligence systems adoption in developing countries: An empirical analysis from Ghanaian Banks. The Journal of Internet Banking and Commerce, 1-25.
  • [42]  Qureshi, S.M. and Kang, C., 2015. Analysing the organizational factors of project complexity using structural equation modelling. International Journal of Project Management, 33(1), pp.165-176.
  • [43]  Ringle, C.M., Wende, S. and Will, S., 2005. SmartPLS 2.0 (M3) Beta, Hamburg 2005.
  • [44]  Sarstedt, M., Ringle, C.M., Smith, D., Reams, R. and Hair Jr, J.F., 2014. Partial least squares structural equation modeling (PLS-SEM): A useful tool for family business researchers. Journal of Family Business Strategy, 5(1), pp.105-115.
  • [45]  Schumacker, R.E. & Lomax, R.G., (2004). A beginner’s guide to structural equation modeling. Psychology Press.
  • [46]  Sekaran, U. 2003. Research Methods for Business: A Skill Building Approach. Singapore: John Wiley and Sons Inc.
  • [47]  Soat, M. 2015. Digital disruption and the death of storytelling, Marketing News, 4: 36. (Accessed: 20 July 2015).
  • [48]  Tenenhaus, M., Vinzi, V. E., Chatelin, Y. M., & Lauro, C. (2005). PLS path modeling. Computational statistics & data analysis, 48(1), 159-205.
  • [49]  Washington, S., Karlaftis, M.G. and Mannering, F.L., 2003. Statistical and econometric methods for transportation data analysis (pp. 241-255). Boca Raton, FL: Chapman & Hall/CRC.
  • [50]  Wang, N., Liang, H., Zhong, W., XueE, Y. & Xiao, J. 2012. Resource structuring or capability building? An empirical study of the business value of information technology, Journal of Management Information Systems, 29(2): 325-367.
  • [51]  Wang, C.L. & Ahmed, P. K. 2007. Dynamic Capabilities: A review and Research Agenda. Wiley Online Library.
  • [52]  Wetzels, M., Odekerken-Schröder, G., & Van Oppen, C. (2009). Using PLS path modeling for assessing hierarchical construct models: Guidelines and empirical illustration. MIS quarterly, 177-195.
  • [53]  Zaidi, M.F.A., Othman, S.N. 2011. Understanding dynamic capability as an ongoing concept for studying technological capability. Journal of Business and Social Science. Research.Net. Google Scholar.
Copyright © 2019 Isaac Scientific Publishing Co. All rights reserved.