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.
Highlights
Entrepreneurial development studies are rapidly gathering momentum in the 21st century, due to the growing recognition of its potential in wealth creation and general economic development (Robson et al 2009)
This study proposes that entrepreneurial decisionmaking is enriched in an environment of Artificial intelligence systems, which is complemented by customer preference, industry benchmark, and employee involvement
Social Implications: The introduction of artificial intelligence (AI) in the business decision-making process comes with many social issues in relation to the impact machines have on humans and society
Summary
Entrepreneurial development studies are rapidly gathering momentum in the 21st century, due to the growing recognition of its potential in wealth creation and general economic development (Robson et al 2009). Global economies have evolved from brick and mortar to convenience at the click of buttons This modernization influences business functions and transforms enterprises and societies (Wirtz and Zeithaml 2018). Accurate data are not obtained solely for the creation of practical insight, and for their implementation in strategic business decision-making. This is expected of entrepreneurs due to the significance of making precise decisions under unpredictable conditions, in order to discover business opportunities (Shane and Venkataraman 2000). Artificial intelligence (AI) systems comprising advanced data analysis, data mining, cloud computing, and machine learning technologies are discussed and posited to influence better entrepreneurial decision-making through customer preference and industry benchmark mediation. Employee involvement, encapsulated in the circular economy theory, is considered fundamental to the value delivery process and has consequences for firm performance (Payne et al 2009; Prahalad and Ramaswamy 2004)
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