Conceptual Framework—Artificial Intelligence and Better Entrepreneurial Decision-Making: The Influence of Customer Preference, Industry Benchmark, and Employee Involvement in an Emerging Market

George Amoako, Paul Omari, Desmond K. Kumi, George Cudjoe Agbemabiase and George Asamoah
Additional contact information
George Amoako: Department of Marketing, University of Professional Studies, Accra P.O. Box 149, Ghana
Paul Omari: Department of Marketing, University of Professional Studies, Accra P.O. Box 149, Ghana
Desmond K. Kumi: DAL Consultancy, Co. Ltd., Kwabenya, Accra Box KW 310, Ghana
George Cudjoe Agbemabiase: Department of Marketing, University of Professional Studies, Accra P.O. Box 149, Ghana
George Asamoah: Department of Marketing, Ghana Institute of Journalisms, Accra P.O. Box 667, Ghana

JRFM, 2021, vol. 14, issue 12, 1-20

Abstract: Purpose : Technology initiatives are now incorporated into a wide range of business domains. The objective of this paper is to explore the possible effects that Artificial intelligence systems have on entrepreneurs’ decision-making, through the mediation of customer preference and industry benchmark. Design/methodology/approach : This is a non-empirical review of the literature and the development of a conceptual model. Searches were conducted in key academic databases, such as Emerald Online Journals, Taylor and Francis Online Journals, JSTOR Online Journals, Elsevier Online Journals, IEEE Xplore, and Directory of Open Access Journals (DOAJ) for papers which focused on Artificial intelligence (AI) , Entrepreneurial decision-making , Customer preference , Industry benchmarks , and Employee involvement . In total, 25 articles met the predefined criteria and were used. Findings : The study proposes that Artificial intelligence systems can facilitate better decision-making from the entrepreneurial perspective. In addition, the study demonstrates that employees, as stakeholders, can moderate the relationship between Artificial intelligence systems and better decision-making for entrepreneurs with their involvement. Moreover, the study demonstrates that customer preference and industry benchmark can mediate the relationship between Artificial intelligence systems and better entrepreneur decision-making. Research limitations/implications : The study assumes a perfect ICT environment for the smooth operation of Artificial intelligence systems. However, this might not always be the case. The study does not consider the personal disposition of entrepreneurs in terms of ICT usage and adoption. Practical implications : This study proposes that entrepreneurial decision-making is enriched in an environment of Artificial intelligence systems, which is complemented by customer preference, industry benchmark, and employee involvement. This finding provides entrepreneurs with a possible technological tool for better decision-making, highlighting the endless options offered by Artificial intelligence systems. Social Implications : The introduction of AI in the business decision-making process comes with many social issues in relation to the impact machines have on humans and society. This paper suggests how this new technology should be used without destroying society. Originality/value : This conceptual framework serves as a valuable organizational spectrum for entrepreneurial development. In addition, this study makes a valuable contribution to entrepreneurial development through Artificial intelligence systems.

Keywords: entrepreneurship; decision-making; artificial intelligence; employee involvement; customer preference (search for similar items in EconPapers)
JEL-codes: C E F2 F3 G (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://www.mdpi.com/1911-8074/14/12/604/pdf (application/pdf)
https://www.mdpi.com/1911-8074/14/12/604/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jjrfmx:v:14:y:2021:i:12:p:604-:d:701435

Access Statistics for this article

JRFM is currently edited by Ms. Chelthy Cheng

More articles in JRFM from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().