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Behavioral Sciences
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Leadership in the New Era of Technology
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Leadership in the New Era of Technology

A special issue of Behavioral Sciences (ISSN 2076-328X). This special issue belongs to the section "Organizational Behaviors".

Deadline for manuscript submissions: 20 December 2025 | Viewed by 4826

Special Issue Editors

Prof. Dr. Xin-An Zhang

E-Mail Website
Guest Editor
Antai College of Economics and Management, Shanghai Jiao Tong University, Shanghai 200030, China
Interests: artificial intelligence and leadership
Prof. Dr. Lin Lu

E-Mail Website
Guest Editor
Antai College of Economics and Management, Shanghai Jiao Tong University, Shanghai 200030, China
Interests: knowledge sharing; teamwork, human resource management
Dr. Ming Kong

E-Mail Website
Guest Editor
School of Education, Shanghai Jiao Tong University, Shanghai 200030, China
Interests: strategic leadership; managerial psychology and behavior; human resource management

Special Issue Information

Dear Colleagues,

The rapid advancement of technology has reshaped the business landscape and the role of leadership within it. Leaders are facing unprecedented challenges. For instance, in businesses like food delivery platforms, gig workers complete tasks under the guidance of algorithms, which are increasingly substituting human roles in leadership positions. Moreover, the extensive application of big data in business operations demands new capabilities from leaders, necessitating a greater emphasis on data-driven decision making. Artificial intelligence, by enabling employees to transcend the limitations of work experience and clearly defined skill levels, has gradually diminished the traditional advantages of appointing leaders based on their experience and asymmetrical information. These shifts suggest that leaders need to adjust their behavior patterns to respond effectively. Against this backdrop, this Special Issue aims to encourage organizational scholars to delve deeper into industries to discover and investigate effective leadership strategies in the era of new technology.  We are particularly interested in topics that include, but are not limited to, the role of artificial intelligence in leader judgment, effective leadership styles for digitized subordinates, how subordinates respond to leaders' use of technology, and the new dynamics between leaders and subordinates brought about by technological advancements.

Prof. Dr. Xin-An Zhang
Prof. Dr. Lin Lu
Dr. Ming Kong
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Behavioral Sciences is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • leadership
  • technology
  • artificial intelligence
  • big data
  • algorithm
  • platform gig workers
  • leader substitution
  • leader judgment

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Published Papers (2 papers)

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Research

27 pages, 1240 KiB  
Article
Impact of Ethical Leadership on Autonomy and Self-Efficacy in Virtual Work Environments: The Disintegrating Effect of an Egoistic Climate
by Carlos Santiago-Torner, José-Antonio Corral-Marfil, Yirsa Jiménez-Pérez and Elisenda Tarrats-Pons
Behav. Sci. 2025, 15(1), 95; https://doi.org/10.3390/bs15010095 - 20 Jan 2025
Cited by 1 | Viewed by 2315
Abstract
Ethical management is key to ensuring organizational sustainability, through resources such as autonomy or self-efficacy. However, economic and social uncertainty occasionally leads to adaptive responses that prioritize profit as the primary interest, blurring the integrating role of ethical leadership. There are a number [...] Read more.
Ethical management is key to ensuring organizational sustainability, through resources such as autonomy or self-efficacy. However, economic and social uncertainty occasionally leads to adaptive responses that prioritize profit as the primary interest, blurring the integrating role of ethical leadership. There are a number of studies that support this reality in a virtual work environment. This sector-specific and cross-sectional research explores how ethical leadership influences self-efficacy among teleworkers, through active commitment to job autonomy, and how an egoistic climate hinders this influence. The analysis is quantitative and correlational, and the sample includes 448 teleworkers. A model of conditional indirect effects, including both a mediation process and a moderation process, is used. The results support that ethical leadership enhances followers’ self-efficacy through a redistribution of responsibilities, which increases the perception of autonomy. However, when ethical leadership coincides with a climate that has opposing interests, such as an egoistic climate, ethical leadership is unable to counteract it, and its effect on self-efficacy gradually diminishes. The benefits of this management style are widely known, but it is crucial to understand under what circumstances it loses efficacy. This research presents a new theoretical model that contributes to the existing literature on ethical leadership. Lastly, organizations that embrace ethical leadership can avoid the emergence of ethical climates disconnected from collective benefit, such as those characterized by selfishness, which hinder prosocial motivation. In this context, ethical leadership fosters the development of high-quality interpersonal relationships with followers, which are considered essential for creating an environment conducive to group learning. Consequently, change management in organizations necessitates the adoption of an ethical system that enhances self-efficacy through moral principles, rather than relying solely on individualistic aspects. Full article
(This article belongs to the Special Issue Leadership in the New Era of Technology)
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26 pages, 1789 KiB  
Article
How Do Algorithmic Management Practices Affect Workforce Well-Being? A Parallel Moderated Mediation Model
by Husam Zayid, Ahmad Alzubi, Ayşen Berberoğlu and Amir Khadem
Behav. Sci. 2024, 14(12), 1123; https://doi.org/10.3390/bs14121123 - 23 Nov 2024
Viewed by 1795
Abstract
Modern workplaces increasingly use algorithmic management practices (AMPs), which shape task assignment, monitoring, and evaluation. Despite the potential benefits these practices offer, like increased efficiency and objectivity, their impact on workforce well-being (WFW) has raised concerns. Drawing on self-determination theory (SDT) and conservation [...] Read more.
Modern workplaces increasingly use algorithmic management practices (AMPs), which shape task assignment, monitoring, and evaluation. Despite the potential benefits these practices offer, like increased efficiency and objectivity, their impact on workforce well-being (WFW) has raised concerns. Drawing on self-determination theory (SDT) and conservation of resources theory (COR), this study examines the relationship between algorithmic management practices and workforce well-being, incorporating job burnout (JBO) and perceived threat (PT) as parallel mediators and person–job fit (PJF) as a moderator. The research employed a cross-sectional survey design targeting 2450 KOSGEB-registered manufacturing SMEs in Istanbul, Turkey. A sample of 666 respondents participated, and the data were analyzed using Smart PLS 4, employing structural equation modeling to test the proposed model. The results indicated that algorithmic management practices significantly increased job burnout and perceived threat, both of which negatively impacted workforce well-being. However, the direct effect of algorithmic management practices on workforce well-being was non-significant. Person–job fit moderated the relationships between algorithmic management practices and both job burnout and perceived threat, further influencing workforce well-being. The findings underscore the critical need for organizations to balance algorithmic efficiency with human-centric practices. Prioritizing person–job fit and fostering transparency in algorithmic processes can mitigate negative impacts, enhance employee well-being, and drive sustainable organizational success in the digital age. Full article
(This article belongs to the Special Issue Leadership in the New Era of Technology)
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