JMO Special Issue Call for Papers
Artificial Intelligence and Corporate Social Responsibility
Special Issue Editors:
Yang Liu, PhD, Zhejiang University, yangliu@zju.edu.cn
Shenjiang Mo, PhD, Zhejiang University, mosj@zju.edu.cn
Ying Ying, PhD, Zhejiang University of Finance and Economics, yingying@zufe.edu.cn
Jason Jin Lu, PhD, The City University of Hong Kong, jason.jin@cityu.edu.cn
Jiang Wei, PhD, Zhejiang University, weijiang@zju.du.cn
Deadline for Submissions: 30th Mach 2024
Significant advancements in Artificial Intelligence (AI), defined as 'the frontier of computational advancements that references human intelligence in addressing ever more complex decision-making problems' (Berente, Gu, Recker, & Santhanam, 2021: 1435), have a profound effect on business and society (Chalmers, MacKenzie, & Carter, 2020; Davenport, Guha, Grewal, & Bressgott, 2020; Huang & Rust, 2018; Tóth, Caruana, Gruber, & Loebbecke, 2022). Incorporating AI technologies, such as robots, facial recognition, algorithms, and natural language processing into business, not only provides corporate benefits (e.g., helping employees make better decisions, providing novel offerings to customers), but also yields potential challenges to the different stakeholders in terms of privacy, discrimination, bias, surveillance, etc. (e.g., Davenport et al., 2020; Du & Xie, 2021; Martin, 2019b; Russell, Hauert, altman, & Velsoso, 2015).
'How to do business responsibility in the era of AI' is a timely and important research question. The literature on corporate social responsibility (CSR), defined as context-specific organizational actions and policies that take into account stakeholders' expectations and the triple bottom line of economic, social, and environmental performance (Aguinis, 2011; Liu, Dai, Liao, & Wei, 2021), has long focused on the factors affecting corporate decisionmakers to act in socially responsible ways towards various stakeholders such as customers, employees, suppliers, communities, and the environment (Dmytriyev, Freeman, & Hörisch, 2021; Wang, 2016). Adoption of AI technologies in business is changing almost all aspects of doing business in socially responsible ways, since AI technologies have three distinct and interrelated facets namely autonomy, learning, and inscrutability (Berente et al., 2021). For example, Ai technologies themselves have no moral standards, the unexplainable 'black box' of algorithmic decision making process is scrutinized as being unfair and causing harm (Martin, 2019a; Du & Xie, 2021). The extant literature on AI mainly focuses on how AI development influences firms' market-based strategies and decisions (e.g., Berente, Gu, Recker, & Santhanam, 2021; Wielgos, Homburg, & Christina Kuehnl, 2021). AI adoption may lead to many potential unethical behaviors. Recent studies began to examine relevant concerns, such as information privacy threat, security and ethical concerns (Quach et al., 2022). Further, Ai development makes firms re-engineer their internal processes and blur organizational boundaries, which significantly changes the relationships between the firm and various stakeholders. AI technologies can also five rise to novel ways of engaging in CSR. In this circumstance, effectively managing firms' stakeholder relationships and CSR behaviors becomes critical for their sustained competitive advantage in the digital era.
However, despite the heavy call for attention to be paid to responsible AI in business1, relatively little theoretical and empirical studies have examined how technologies affect CSR (e.g., Tóth, Caruana, Gruber, & Loebbecke, 2022; Sullivan & Fosso Wamba, 2022). Therefore, this Special Issue aims to focus on AI and CSR. Investigating the relationships between AI and CSR could not only advance our understanding of the role of AI in organizations, but also provide opportunities to advance the literature on CSR. The aim of the Special Issue is to assemble high quality papers that contribute towards both theoretical and practical development in the context of AI and CSR. Submissions with a strong connection between theory and practice are particularly welcome.
Possible Research Topics
We invite works on the following topics, but are not limited to:
‑ What is the evolving role of AI in framing and driving CSR?
‑ How does AI change the nature of stakeholder engagement in CSR?
‑ How does the interaction of institutions and AI development shape the nature of CSR?
‑ How to alleviate the irresponsible business decisions and behaviors caused by AI adoption?
‑ How can employees push back against ethical issues that they encounter with AI management?
‑ How can firms balance the need for increased AI based data collection with consumers’ right to
privacy?
More generally, we welcome contributions investigating issues related to the sustainable behaviors with Ai. The editors are keen to bring significant value to the fields of CSR, AI, organizational behaviors and IS management. We are seeking high-quality empirical and conceptual papers, and welcome diverse methods, including qualitative, field, survey, archival, and laboratory.
Submission Details
Completed papers must comply with the Journal of Management & Organization (JMO) paper guidelines, and they must be submitted through the JMO Manuscript Central system (https://mc.manuscriptcentral.com/jmo).
• 30 March 2024: Paper submission deadline
• 30 August 2024: Completion of first-round review
• 29 February 2025: Completion of second-round review
• 30 Mat 2025: Final manuscripts due
• 30 January 2026: Tentative publication date
About the guest editors
Yang Liu ZJU 100 Young Professor at Zhejiang University. His research interests include innovation management and CSR in digital economy. His research works have appeared in Journal of Management & Organization, Technovation, Technological Forecasting and Social Change, Computers in Human Behavior and Journal of Business Ethics.
Shenjiang Mo Associate Professor in the Department of Leadership and Organizational Management at Zhejiang University. His main expertise is on leadership and team management in the digital economy, unethical behavior and CSR in China. His works have appeared in Journal of Management & Organization, Journal of Business Ethics, Organizational Behavior and Human Decision Processes.
Ying Ying Associate Professor in the School of Business Administration, Zhejiang University of Finance and Economics. Her research interests include digital innovation and transformation. She has published works in Journal of Business Research, Technovation, Technological Forecasting and Social Change.
Jason Lu Jin Research Fellow at The City University of Hong Kong Dongguan Research Institute. His research interests include innovation, inter-organizational relationship, and marketing strategy. His work has appeared in International Journal of Operations & Production Management, Journal of Business Research, Industrial Marketing Management, Journal of International Marketing.
Jiang Wei Professor of Innovation and Strategic Management and the Dean of School of Management, Zhejiang University. His research focuses on innovation and strategic management. He has published more than 200 papers in peer-reviewed journals such as Journal of Business Ethics, Journal of International Business Studies, Asia Pacific Journal of Management, Management and Organization Review, Technovation.
1OECD has set standards for using AI in responsible ways. See: Principles on Artificial Intelligence, https://www.oecd.org/digital/artificial-intelligence/, accessed on March 16, 2022.
References
Aguinis, H. (2011). Organizational responsibility: Doing good and doing well. In S. Zedeck (Ed.), APA handbook of industrial and organizational psychology (pp. 855–879). Washington, DC: American Psychological Association.
Berente, N., Gu, B., Recker, J., & Santhanam, R. (2021). Managing artificial intelligence. MIS Quarterly, 45(3), 1433-1450.
Chalmers, D., MacKenzie, N. G., & Carter, S. (2021). Artificial intelligence and entrepreneurship: implications for venture creation in the fourth industrial revolution. Entrepreneurship Theory and Practice, 45(5), 1028-1053.
Davenport, T., Guha, A., Grewal, D., & Bressgott, T. (2020). How artificial intelligence will change the future of marketing. Journal of the Academy of Marketing Science, 48(1), 24-42.
Dmytriyev, S. D., Freeman, R. E., & Hörisch, J. (2021). The relationship between stakeholder theory and corporate social responsibility: Differences, similarities, and implications for social issues in management. Journal of Management Studies, 58(6), 1441-1470.
Du, S., & Xie, C. (2021). Paradoxes of artificial intelligence in consumer markets: Ethical challenges and opportunities. Journal of Business Research, 129, 961-974.
Huang, M. H., & Rust, R. T. (2018). Artificial intelligence in service. Journal of Service Research, 21(2), 155-172.
Krkac, K. (2019). Corporate social irresponsibility: humans vs artificial intelligence. Social Responsibility Journal, 15(6), 786-802.
Liu, Y., Dai, W., Liao, M., & Wei, J. (2021). Social status and corporate social responsibility: Evidence from Chinese privately owned firms. Journal of Business Ethics, 169, 651-672.
Russell, S., Hauert, S., Altman, R., & Veloso, M. (2015). Ethics of artificial intelligence. Nature, 521(7553), 415–416.
Martin, K. (2019a). Designing ethical algorithms. MIS Quarterly Executive, 18(2), 129-142.
Martin, K. (2019b). Ethical implications and accountability of algorithms. Journal of Business Ethics, 160(4), 835-850.
Quach, S., Thaichon, P., Martin, K. D., Weaven, S., & Palmatier, R. W. (2022). Digital technologies: tensions in privacy and data. Journal of the Academy of Marketing Science, forthcoming.
Sullivan, Y. W., & Fosso Wamba, S. (2022). Moral judgments in the age of artificial intelligence. Journal of Business Ethics, Doi: doi.org/10.1007/s10551-022-05053-w
Tong, S., Jia, N., Luo, X., & Fang, Z. (2021). The Janus face of artificial intelligence feedback: Deployment versus disclosure effects on employee performance. Strategic Management Journal, 42(9), 1600-1631.
Tóth, Z., Caruana, R., Gruber, T., & Loebbecke, C. (2022). The dawn of the AI robots: Towards a new framework of AI robot accountability. Journal of Business Ethics, Doi: doi.org/10.1007/s10551-022-05050-z
Wang, H., Tong, L., Takeuchi, R., & George, G. (2016). Corporate social responsibility: An overview and new research directions: Thematic issue on corporate social responsibility. Academy of Management Journal, 59(2), 534-544.
Wielgos, D. M., Homburg, C., & Kuehnl, C. (2021). Digital business capability: its impact on firm and customer performance. Journal of the Academy of Marketing Science, 49(4), 762-78