ECONOMIC GROWTH ON THE PLATE: UNVEILING DETERMINANTS OF ONLINE FOOD DELIVERY ADOPTION IN EMERGING MARKETS

https://doi.org/10.5281/zenodo.8239528

Authors

  • Delone, W. H University of Ghana Business School, Accra, Greater Accra Region, Ghana.
  • McLean, E. R. University of Ghana Business School, Accra, Greater Accra Region, Ghana.

Keywords:

hotel industry, emerging economies, COVID-19 pandemic, online food delivery systems

Abstract

The hotel industry holds a pivotal role in fostering development within emerging economies, contributing significantly to national budgets, especially in Sub-Saharan Africa (SSA). However, the global hospitality sector has encountered formidable challenges due to the unprecedented impact of the COVID-19 pandemic. In response to the high mortality risk and human-to-human transmission associated with the virus, the World Health Organization (WHO) proposed interventions including mask mandates, social distancing, self-quarantine, and movement restrictions. Consequently, the food-service sector suffered closures or limitations, significantly affecting hotels and restaurants. To counteract this decline, many restaurants turned to online food delivery systems, particularly in SSA where literacy, technology, and internet access remain barriers. Prior studies underscore the transformative potential of digitization in business enhancement, a premise amplified by the substantial surge in online food delivery during the pandemic. However, scant research has delved into the drivers of customers' motives for utilizing online food delivery systems, especially in the context of emerging economies. This study bridges this gap by examining the United Theory of Acceptance and Use of Technology (UTAUT-2) model's applicability in influencing user intentions toward online food delivery services. The research framework uniquely integrates system and user characteristics, addressing the intricate cognitive processes inherent in the purchase of perishable and heterogeneous products through online platforms. This study not only advances theoretical understanding but also provides practical insights for implementing innovative systems, particularly within the food service industry of emerging economies. The findings contribute to the comprehension of individuals' resistance or acceptance of novel systems within organizations, specifically shedding light on the dynamics of adopting online food delivery services. By adapting the UTAUT-2 model to the restaurant customers' perspective, this research elucidates the factors shaping users' intentions and choices in the domain of online food delivery. In doing so, it offers a comprehensive exploration of drivers influencing the adoption of digital food services, particularly relevant in the pandemic era, and presents implications for bolstering strategies in emerging economies' food service industry.

Published

2023-08-11

How to Cite

Delone, W. H., & McLean, E. R. (2023). ECONOMIC GROWTH ON THE PLATE: UNVEILING DETERMINANTS OF ONLINE FOOD DELIVERY ADOPTION IN EMERGING MARKETS. SADI Journal of Economics and Social Sciences (SJESS), 10(3), 1–18. https://doi.org/10.5281/zenodo.8239528

Issue

Section

Original Peer Review Articles

References

Aaltonen, T., González, B. Á., Amerio, S., Amidei, D., Anastassov, A., Annovi, A., ... & Arisawa, T. (2011). Evidence for a mass-dependent forward-backward asymmetry in top quark pair production. Physical Review.

Ahmed, I., Nawaz, M. M., Ahmad, Z., Ahmad, Z., Shaukat, M. Z., Usman, A., & Ahmed, N. (2010). Does service quality affect students' performance? Evidence from institutes of higher learning. African journal of business management, 4(12), 2527-2533.

Albion, P. R. (2001). Some factors in the development of self-efficacy beliefs for computer

Aldholay, A. H., Isaac, O., Abdullah, Z., & Ramayah, T. (2018). The role of transformational leadership as a mediating variable in DeLone and McLean information system success model: The context of online learning usage in Yemen. Telematics and Informatics.

Alnoor, A.M., Al Abrrow, H., Abdullah, H. and Abbas, S., 2020. The impact of self efficacy on employees' ability to accept new technology in an Iraqi university. Global Business and Organizational Excellence, 39(2), pp.41-50.

Asamoah, D., Annan, J., Rockson, S.B. and Effah-Baah, D., 2019. The influence of the status quo bias theory in the compliance to public procurement regulations in a Sub-Saharan economy. International Journal of Procurement Management, 12(1), pp.15-40.

Bach, B. W. (1989). The effect of multiplex relationships upon innovation adoption: A reconsideration of Rogers' model. Communications Monographs, 56(2), 133-150.

Bandura, A., & Wood, R. (1989). Effect of perceived controllability and performance standards on self-regulation of complex decision making. Journal of personality and social psychology.

Chaudhry, B., Wang, J., Wu, S., Maglione, M., Mojica, W., Roth, E., ... & Shekelle, P. G. (2006). Systematic review: impact of health information technology on quality, efficiency, and costs of medical care. Annals of internal medicine, 144(10), 742-752.

Chen, C., & Czerwinski, M. P. (2000). Empirical evaluation of information visualizations: an introduction. International journal of human-computer studies, 53(5), 631-635.

Creswell, J. W. (2003). A framework for design. Research design: Qualitative, quantitative, and mixed methods approach.

Curran, J. M., & Meuter, M. L. (2005). Self service technology adoption: comparing three technologies. Journal of services marketing.

Dabholkar, P. A., & Bagozzi, R. P. (2002). An attitudinal model of technology-based self-service: moderating effects of consumer traits and situational factors. Journal of the academy of marketing science.

Dabholkar, P. A., & Bagozzi, R. P. (2002). An attitudinal model of technology-based self-service: moderating effects of consumer traits and situational factors. Journal of the academy of marketing science, 30(3), 184-201.

Delone, W. H., & McLean, E. R. (2003). The DeLone and McLean model of information systems success: a tenyear update. Journal of management information systems, 19(4), 9-30.

Dillon, A. (Ed.) (2001). User acceptance of information technology. In W. Karwowski (Ed.),

Eastin, M. S., & LaRose, R. (2000). Internet self-efficacy and the psychology of the digital divide. Journal of computer-mediated communication.

Ellen, P. S., Wiener, J. L., & Cobb-Walgren, C. (1991). The role of perceived consumer effectiveness in motivating environmentally conscious behaviors. Journal of public policy & marketing. Encyclopedia of human factors and ergonomics, London, UK: Taylor and Francis.

Engelmann, D., & Hollard, G. (2010). Reconsidering the effect of market experience on the “endowment effect”. Econometrica.

Gao, R., Cao, B., Hu, Y., Feng, Z., Wang, D., Hu, W., ... & Xu, X. (2013). Human infection with a novel avianorigin influenza A (H7N9) virus. New England Journal of Medicine, 368(20), 1888-1897.

Gist, M. E., & Mitchell, T. R. (1992). Self-efficacy: A theoretical analysis of its determinants and malleability. Academy of Management Review, 17(2), 183-211.

Hafeez, S., & Muhammad, B. (2012). The Impact of Service Quality, Customer Satisfaction and Loyalty Programs on Customer's Loyalty: Evidence from Banking Sector of Pakistan. International Journal of Business and Social Science, 3(16).

Hershey, PA: IGI Global Publishing.

Hill, T., Smith, N. D., & Mann, M. F. (1987). Role of efficacy expectations in predicting the decision to use advanced technologies: The case of computers. Journal of applied psychology.

Hirschman, E. C. (1980). Innovativeness, novelty-seeking, and consumer creativity. Journal of consumer research, 7(3), 283-295.

Hoaglund, A., Birkenfeld, K., & Box, J. (2014). Professional learning communities: Creating a foundation for collaboration skills in pre-service teachers. Education, 134(4), 521-528.

Hoemann, C. D., Buschmann, M. D., & McKee, M. D. (2006). U.S. Patent No. 7,148,209. Washington, DC: U.S. Patent and Trademark Office

Hsieh, H. L., & Shanechi, M. M. (2018). Optimizing the learning rate for adaptive estimation of neural encoding models. PLoS computational biology

Hu, P. J., Clark, T. H., & Ma, W. W. (2003). Examining technology acceptance by school implementation: A status quo bias perspective. MIS Quarterly.Information Technology, Learning, and Performance Journal.

Jambedu, H. A. (2006). Adherence to anti-hypertensive medication regimens among patients attending the GPHA Hospital in Takoradi-Ghana (Doctoral dissertation)

Khayun, V., & Ractham, P. (2011, January). Measuring e-excise tax success factors: Applying the DeLone & McLean information systems success model. In 2011 44th Hawaii International Conference on System Sciences (pp. 1-10). IEEE.

Kim, H. W., Xu, Y., & Gupta, S. (2012). Which is more important in Internet Shopping, perceived price or trust?. Electronic Commerce Research and Applications

Kim, H.-W., & Kankanhalli, A. (2009). Investigating user resistance to information systems

Lai, M.-L. (2008). Technology readiness, Internet self-efficacy, and computing experience of

Laing, I. F. (2009). The impact of training and development on worker performance and productivity in public sector organizations: A case study of Ghana Ports and Harbours Authority (Doctoral dissertation).

Lee, D. Y., & Lehto, M. R. (2013). User acceptance of YouTube for procedural learning: An extension of the Technology Acceptance Model. Computers & Education.

Ma, Q., & Liu, L. (2007). The role of Internet self-efficacy in accepting Web-based medical

Ma, W. W.-K., Andersson, R., & Streich, K.-O. (2005). Examining user acceptance of computer technology: An empirical study of student teachers. Journal of Computer Assisted Learning

Makokha, M. W., & Ochieng, D. O. (2014). Assessing the success of ICT's from a user perspective: A case study of Coffee Research Foundation, Kenya. Journal of Management and Strategy, 5(4), 46. Management Science.

Marteau, J. F., Raballand, G., & Arvis, J. F. (2007). The cost of being landlocked: logistics costs and supply chain reliability. The World Bank.

McDonald, T. and Siegall, M., 1992. The effects of technological self-efficacy and job focus on job performance, attitudes, and withdrawal behaviors. The Journal of Psychology, 126(5), pp.465-475.

McGrath, D. G., De Castro, F., Futenma, C., de Amaral, B. D., & Calabria, J. (1993). Fisheries and the evolution of resource management on the lower Amazon floodplain. Human ecology.

Midgley, D. F., & Dowling, G. R. (1978). Innovativeness: The concept and its measurement. Journal of consumer research, 4(4), 229-242.

Mills, R. J. (2001). Analyzing instructional software using a computer-tracking system. Model: Four longitudinal field studies. Management Science.

Mohammad, O. S., Ali, W. K., & Al-Hulitan, A. M. T. (2012). The effect of infestation by the confused flour beetle (Tribolium confusum Duv.) on specifications of wheat flour. Journal of Agricultural Science and Technology.

Montesdioca, G., Hino, M., & Maçada, A. (2015). The information privacy concerns at the organizational level: An exploratory study in the bank sector.

Moore, G. C., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information systems research.

Morrison, E. W., & Vancouver, J. B. (2000). Within-person analysis of information seeking: The effects of perceived costs and benefits. Journal of Management, 26(1), 119-137.

Noe, R. A., & Wilk, S. L. (1993). Investigation of the factors that influence employees' participation in development activities. Journal of applied psychology, 78(2), 291.

Norzaidi, M. D., Chong, S. C., Murali, R., & Salwani, M. I. (2007). Intranet usage and managers' performance in the port industry. Industrial Management & Data Systems.

Osei-Owusu, J.Y. and Mahmood, R., 2020. Port paperless system in Ghana, the way forward: GCNET or UNIPASS/ICUMS. ADRRI Journal of Arts and Social Sciences, 17(6 (5)), pp.72-87. Park, S. Y. (2009). An analysis of the Technology Acceptance Model in understanding professional accounting students. Campus-Wide Information Systems.

Raghuram, S., Wiesenfeld, B. and Garud, R., 2003. Technology enabled work: The role of self-efficacy in determining telecommuter adjustment and structuring behavior. Journal of Vocational Behavior, 63(2), pp.180-198.

Rai, A. K., & Medha, S. (2013). The antecedents of customer loyalty: An empirical investigation in the life insurance context. Journal of Competitiveness, 5(2), 139-163. records. In M. Mahmood (Ed.), Contemporary issues in end-user computing.

Rey-Moreno, M., Felício, J. A., Medina-Molina, C., & Rufín, R. (2018). Facilitator and inhibitor factors: Adopting e-government in a dual model. Journal of Business Research.

Samuelson, W., & Zeckhauser, R. (1988). Status quo bias in decision making. Journal of Risk and uncertainty.

Sánchez, R. A., Cortijo, V., & Javed, U. (2014). Students' perceptions of Facebook for academic purposes. Computers & Education.

Stapel, D. A., & Blanton, H. (2004). From seeing to being: subliminal social comparisons affect implicit and explicit self-evaluations. Journal of personality and social psychology, 87(4), 468.

Strong, D. M., DiShaw, M., & Brady, D. B. (2006). Extending task technology fit with computer

Szajna, B. (1996). Empirical evaluation of the revised technology acceptance model. Teachers: A longitudinal study. Information & Management.

Timofte, R., Agustsson, E., Van Gool, L., Yang, M. H., & Zhang, L. (2017). Nature 2017 challenge on single image super-resolution: Methods and results. In Proceedings of the IEEE conference on computer vision and pattern recognition workshops

Tufour, A. K. (2015). Critical Factors that Influence the Attractiveness of Ghana’s Corridor to Stake-Holders engaged in the Transit Business of Landlocked Burkina Faso. ADRRI Journal. University students’ behavioral intention to use e-learning. Educational Technology & use among teacher education students. Journal of Technology and Teacher Education.

Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the Technology Acceptance

Wang, G., Wei, Y., Qiao, S., Lin, P., & Chen, Y. (2018). Generalized inverses: theory and computations (Vol. 53). Berlin, Germany: Springer.

Wang, Y. S., & Liao, Y. W. (2008). Assessing eGovernment systems success: A validation of the DeLone and McLean model of information systems success. Government information quarterly, 25(4), 717-733.

Wyatt, M. C. (2005). The insignificance of PR drag in detectable extrasolar planetesimal belts. Astronomy & Astrophysics.

Xie, C., Bagozzi, R. P., & Troye, S. V. (2008). Trying to presume: toward a theory of consumers as co-creators of value. Journal of the Academy of Marketing Science, 36(1), 109-122.

Yeo, G. B., & Neal, A. (2006). An examination of the dynamic relationship between self-efficacy and performance across levels of analysis and levels of specificity. Journal of Applied Psychology, 91(5), 1088.