Topic Editors

Department of Business Administration, College of Business Administration, University of Ulsan, Ulsan 44610, Republic of Korea
College of Business, Gachon University, Seongnamdaero 1342, Republic of Korea

Navigating the Crossroads of Technology and Social Responsibility of Firms

Abstract submission deadline
1 July 2024
Manuscript submission deadline
31 December 2024
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1679

Topic Information

Dear Colleagues,

With a foundation built on the recognized importance of corporate social responsibility (CSR) (Carroll and Shabana, 2010), this Special Issue aims to interrogate the evolving dynamics of CSR in the contemporary digital milieu. Inspired by Bessen's (2018) and Frank’s (2019) explorations of AI and job insecurity, we intend to delve deeper into the intricate relationship between AI, job insecurity, and CSR. By building upon the work of D'Arcy et al. (2014) and Mylonas et al. (2013), the issue further expands to investigate cyber and general security behavior in the context of technological advances. Furthermore, incorporating insights from Frank et al. (2020) and Elhai et al. (2017), we aim to present an in-depth analysis of the implications of these factors for employee mental health. Summary: In this era of digital transformation, our understanding of corporate responsibility is undergoing substantial change. Using Agrawal et al.'s (2019) work on the economics of AI as a starting point, this Special Issue will delve into the complex relationship between AI in the workplace, job insecurity, and cyber and general security behavior. By combining empirical research, case studies, and theoretical insights, we aim to present an enhanced understanding of the need to reassess CSR strategies amidst rapid technological changes. This Special Issue, therefore, is positioned to provide fresh perspectives to academics, researchers, practitioners, and policymakers interested in these intersections. Keywords: corporate social responsibility; artificial intelligence at work; job insecurity; cyber security behavior; security behavior; technological advances at work; mental health (depression and anxiety); workplace technology.

References:

Agrawal, A., Gans, J., & Goldfarb, A. (2018). Prediction machines: the simple economics of artificial intelligence. Harvard Business Press.

Bessen, J. (2018). Artificial intelligence and jobs: The role of demand. In The economics of artificial intelligence: an agenda (pp. 291–307). University of Chicago Press.

Carroll, A. B., & Shabana, K. M. (2010). The business case for corporate social responsibility: A review of concepts, research and practice. International journal of management reviews, 12(1), 85–105.

Chui, M., Manyika, J., & Miremadi, M. (2018). What AI can and can’t do (yet) for your business. McKinsey Quarterly, 1(97–108).

D'Arcy, J., Hovav, A., & Galletta, D. (2009). User awareness of security countermeasures and its impact on information systems misuse: A deterrence approach. Information systems research, 20(1), 79–98.

Elhai, J. D., Dvorak, R. D., Levine, J. C., & Hall, B. J. (2017). Problematic smartphone use: A conceptual overview and systematic review of relations with anxiety and depression psychopathology. Journal of affective disorders, 207, 251–259.

Frank, M. R., Autor, D., Bessen, J. E., Brynjolfsson, E., Cebrian, M., Deming, D. J., & Rahwan, I. (2019). Toward understanding the impact of artificial intelligence on labor. Proceedings of the National Academy of Sciences, 116(14), 6531–6539.

Mylonas, A., Kastania, A., & Gritzalis, D. (2013). Delegate the smartphone user? Security awareness in smartphone platforms. Computers & Security, 34, 47–66.

I look forward to receiving your contributions.

Prof. Dr. Kim Byung-Jik
Dr. Joong-Hak Lee
Topic Editors

Keywords

  • corporate social responsibility
  • artificial intelligence at work
  • job insecurity
  • cyber security behavior
  • security behavior
  • technological advances at work
  • mental health (depression, anxiety)
  • workplace technology

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC
Administrative Sciences
admsci
3.0 3.9 2011 20.6 Days CHF 1400 Submit
Behavioral Sciences
behavsci
2.6 3.0 2011 21.5 Days CHF 2200 Submit
Healthcare
healthcare
2.8 2.7 2013 19.5 Days CHF 2700 Submit
International Journal of Environmental Research and Public Health
ijerph
- 5.4 2004 29.6 Days CHF 2500 Submit

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Published Papers (1 paper)

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19 pages, 770 KiB  
Article
The Mental Health Implications of Corporate Social Responsibility: The Significance of the Sense-Making Process and Prosocial Motivation
Behav. Sci. 2023, 13(10), 870; https://doi.org/10.3390/bs13100870 - 23 Oct 2023
Viewed by 1251
Abstract
As corporate social responsibility (CSR) has progressively ascended to prominence among academics and industry professionals, numerous studies have embarked on examining its impact on employees’ perceptions, attitudes, and behaviors. Notwithstanding, the current body of research has predominantly overlooked the influence of CSR on [...] Read more.
As corporate social responsibility (CSR) has progressively ascended to prominence among academics and industry professionals, numerous studies have embarked on examining its impact on employees’ perceptions, attitudes, and behaviors. Notwithstanding, the current body of research has predominantly overlooked the influence of CSR on employees’ mental health, encompassing depression, anxiety, and burnout. In order to acknowledge the critical role of employee mental health within an organization, our exploration is focused on discerning the effect of CSR on depressive states. Furthermore, our paper undertakes a thorough analysis of the link between CSR and depression, probing its underlying processes and potential contingent factors. We posit that CSR can alleviate the incidence of employee depression by amplifying the sense of meaningfulness that work provides. Moreover, the element of prosocial motivation among employees may act as a positive moderating variable that intensifies the beneficial effect of CSR on the sense of meaningfulness derived from work. By relying on data obtained through a tripartite online survey involving 214 South Korean workers, this paper scrutinized the proposed hypotheses via the application of moderated mediation analysis with structural equation modeling. We contend that the insights yielded by this study bear significant theoretical and practical implications. Full article
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