The evolving role of artificial intelligence in marketing: A review and research agenda

Vlačić, Božidar; Corbo, Leonardo; Silva, Susana Costa e; Dabić, Marina

doi:10.1016/j.jbusres.2021.01.055

Cited by 245 publications

(120 citation statements)

References 191 publications

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“…Further, the main reason for using SCI and SSCI databases is that web of science is "generally considered credible among the scientific community, and [are] commonly used by researchers from a wide range of fields (de Garcia et al, 2020, p. 4). Several reviews have used these databases (e.g., Bernatović et al, 2021;Vlačić et al, 2021). Retrieval conditions were "Title = knowledge hiding" or "Title = knowledge withholding, " and the time span was "All years ."…”

Section: Methodsmentioning

confidence: 99%

Knowledge Hiding: Current Research Status and Future Research Directions

Jiang

et al. 2021

Front. Psychol.

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This article provides a review of scientific articles addressing the topic of knowledge hiding in organizations. Based on a descriptive analysis, bibliometric analysis, and content analysis of a sample of 81 articles published in the academic journals in the Web of Science from 2012 to 2020, we identify the main areas and current dynamics of knowledge hiding research. Our results show that the central research themes of knowledge hiding include five clusters: concept and dimensions, antecedents, consequences, theories, and influence mechanisms. Based on our findings, we suggest future research should further develop the concept and dimensions of knowledge hiding; probe deeper into the consequences of knowledge hiding; explore multilateral, cross-level, and collective knowledge hiding; employ innovative theoretical perspectives and research methods to study knowledge hiding; and address how cultural and other contextual factors may shape the knowledge hiding behavior.

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Section: Methodsmentioning

confidence: 99%

Knowledge Hiding: Current Research Status and Future Research Directions

Jiang

et al. 2021

Front. Psychol.

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“…Next, to ensure the reliability of our research and present the progression of the research field, we focused on academic journals with a peer-review process, written in English. We excluded book chapters, book reviews, conference proceedings, and editorial notes without any time constraints (Gonzalez-Loureiro et al, 2015;Vlačić et al, 2021). This search criterion resulted in 118 articles.…”

Section: The Sample Of Articles and Data Collectionmentioning

confidence: 99%

“…In recent years, one of the most prominent phenomena is the digital revolution or 4.0 era, which has affected society and, consequently, organizations and their business models (Caputo et al, 2021;Fakhar-Manesh et al, 2021). The advent of new technologies, such as the Internet of Things and the heavy use of artificial intelligence, have substantially changed how knowledge is managed within organizations (Vlačić et al, 2021) and entrepreneurial activities (Obschonka & Audretsch, 2020). As serial entrepreneurs have higher levels of imaginativeness (McMullen & Kier, 2017), they should also be able to innovate rapidly and adapt to such futuristic paradigms.…”

Section: Future Research Avenues Regarding Technopreneurship and Innovationmentioning

confidence: 99%

Serial entrepreneurs: A review of literature and guidance for future research

Dabić

Vlačić

Kiessling

et al. 2021

Journal of Small Business Management

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Little research has been conducted regarding serial entrepreneurship compared to entrepreneurship research more broadly, despite research that suggests that as many as 50% of all entrepreneurs are serial entrepreneurs. Entrepreneurship research shows that most new ventures fail, yet serial entrepreneurs continually exit previous ventures and start new ones. Our study explores 118 scholarly articles indexed in Web of Science and Scopus databases on serial entrepreneurship through multiple correspondence analysis. Through our analysis, we identify key areas for future research, explore and consolidate the theoretical foundations used, and provide a review of academic literature for future researchers to utilize. Our perceptual map has identified four key research areas that researchers should focus upon: heuristics in entrepreneurship, entrepreneurial capabilities, the entrepreneurial ecosystem, and technological development and resources.

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“…The increasing computational power, data availability and intensity, context awareness, and emotional-sensing capabilities of AI allow to tailor customized and personalized offerings, and establish and maintain responsive customer interactions and relationships with experiential value (e.g., Grewal, Hulland, et al, 2020;Huang & Rust, 2021b;Ma & Sun, 2020;Puntoni et al, 2021). However, the substantial and growing scale and scope of consumer data feeding AI systems, the level of AI (emotional) intelligence, and AI-driven sales and consumption increases raise ethical controversies and challenges (e.g., Davenport et al, 2020;De Bruyn et al, 2020;Vlačić et al, 2021). Among other things, AI applications and systems can be discriminatory in various respects.…”

Section: Introductionmentioning

confidence: 99%

“…In the same vein, customers are concerned with the environmental and social impact of their purchases (Vadakkepatt et al, 2021) and demand sustainable products and services (Kotler, 2011). Therefore, AI in marketing that fosters environmental and social good can create win-win-win situations for companies, customers, and society at large (Vlačić et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Leveraging Artificial Intelligence in Marketing for Social Good—An Ethical Perspective

Hermann

2021

J Bus Ethics

112

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Artificial intelligence (AI) is (re)shaping strategy, activities, interactions, and relationships in business and specifically in marketing. The drawback of the substantial opportunities AI systems and applications (will) provide in marketing are ethical controversies. Building on the literature on AI ethics, the authors systematically scrutinize the ethical challenges of deploying AI in marketing from a multi-stakeholder perspective. By revealing interdependencies and tensions between ethical principles, the authors shed light on the applicability of a purely principled, deontological approach to AI ethics in marketing. To reconcile some of these tensions and account for the AI-for-social-good perspective, the authors make suggestions of how AI in marketing can be leveraged to promote societal and environmental well-being.

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The evolving role of artificial intelligence in marketing: A review and research agenda

Cited by 245 publications

References 191 publications

Knowledge Hiding: Current Research Status and Future Research Directions

Knowledge Hiding: Current Research Status and Future Research Directions

Serial entrepreneurs: A review of literature and guidance for future research

Leveraging Artificial Intelligence in Marketing for Social Good—An Ethical Perspective

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