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Digital Transformation in the Era of Technological Disruption: The Reshaping...
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Digital Transformation in the Era of Technological Disruption: The Reshaping and Application of Emerging Technologies on Management Models

A special issue of Systems (ISSN 2079-8954). This special issue belongs to the section "Systems Practice in Social Science".

Deadline for manuscript submissions: 20 August 2025 | Viewed by 1862

Special Issue Editors

Dr. Jianhua Zhu

E-Mail Website
Guest Editor
School of Economics and Management, Harbin Institute of Technology (Weihai), Weihai, China
Interests: complex supply chain management; green innovation; digital transformation of manufacturing enterprises
Special Issues, Collections and Topics in MDPI journals
Dr. Qingsong He

E-Mail Website
Guest Editor
School of Economics and Management, Harbin Institute of Technology (Weihai), Weihai, China
Interests: enterprise intelligent transformation; employee green involvement; sustainable development; stakeholder engagement
Dr. Jianmin Sun

E-Mail Website
Guest Editor
School of Management, Nanjing University of Posts and Telecommunications, Nanjing, China
Interests: consumer psychology; behavior and decision making; digital and intelligent transformation of enterprises
Dr. Ming Chen

E-Mail Website
Guest Editor
School of Economics and Management, Qingdao University of Science and Technology, Qingdao, China
Interests: intelligent algorithm application; production operation management; ecological economy; green finance

Special Issue Information

Dear Colleagues,

This Special Issue explores the profound impact of emerging technologies such as Artificial Intelligence (AI), Big Data, Blockchain, and the Internet of Things (IoT) on modern management practices. In today’s rapidly evolving business landscape, these technologies not only enable operational efficiencies, but also drive strategic innovations, transforming business models, and reshaping the way organizations make decisions. By focusing on how these technologies are integrated into various business functions—ranging from strategic planning and customer relationship management to supply chain optimization and financial operations—this Special Issue highlights both the opportunities and challenges presented by the digital transformation process. It aims to provide comprehensive insights into how companies leverage these technologies to enhance their competitiveness, sustainability, and agility in an increasingly complex environment.

This Special Issue is highly relevant to the Systems journal’s scope, as it addresses the integration of emerging technologies within complex organizational systems. It explores the intersection between technology and management, analyzing how systems thinking can optimize the implementation and impact of digital transformation strategies in organizations. Through research, case studies, and theoretical frameworks, this Special Issue will contribute to a deeper understanding of how organizations can successfully navigate the evolving technological landscape.

Dr. Jianhua Zhu
Dr. Qingsong He
Dr. Jianmin Sun
Dr. Ming Chen
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. Systems 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 2400 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

  • digital transformation
  • management models
  • organizational systems
  • strategic innovation
  • technology integration
  • emerging technologies

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Published Papers (2 papers)

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Research

24 pages, 555 KiB  
Article
Artificial Intelligence Symbolic Leadership in Small and Medium-Sized Enterprises: Enhancing Employee Flexibility and Technology Adoption
by Chunjia Hu, Qaiser Mohi Ud Din and Aqsa Tahir
Systems 2025, 13(4), 216; https://doi.org/10.3390/systems13040216 - 21 Mar 2025
Viewed by 434
Abstract
This study examines the influence of leaders’ artificial intelligence symbolization on job-crafting behaviors, highlighting both positive and negative consequences in Chinese small and medium-sized firms. This research utilizes signaling theory to investigate the impact of leaders’ visible adoption of AI on employees’ readiness [...] Read more.
This study examines the influence of leaders’ artificial intelligence symbolization on job-crafting behaviors, highlighting both positive and negative consequences in Chinese small and medium-sized firms. This research utilizes signaling theory to investigate the impact of leaders’ visible adoption of AI on employees’ readiness for change, perceived threats, and job-crafting behaviors. This study examines the moderating influence of organizational support to understand its amplifying and decreasing effects. This work utilizes Python-based statistical tools to provide a novel approach for evaluating behavioral data in social science research. The results reveal that leaders’ AI symbolization significantly improves employees’ readiness for change and promotes proactive job crafting. Conversely, symbolic actions may exacerbate perceived risks, adversely affecting job-crafting behaviors. Organizational support is essential to enhancing the beneficial impacts of AI symbolization on change readiness while alleviating its adverse consequences on perceived threats. These results show how crucial symbolic leadership is for getting people to use new technology and making staff more flexible in SMEs that use AI. By offering organizational training and resources, leaders may optimize favorable results and mitigate adverse effects. This study highlights its significance regarding change readiness, perceived threats, and job crafting. Furthermore, it underscores Python’s (3.9) potential as a groundbreaking tool for enhancing behavioral research in the age of AI. Full article
(This article belongs to the Special Issue Digital Transformation in the Era of Technological Disruption: The Reshaping and Application of Emerging Technologies on Management Models)
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37 pages, 8149 KiB  
Article
Dynamic Evolution and Chaos Management in the Integration of Informatization and Industrialization
by Jianhua Zhu, Bo Sun and Fang Zhang
Systems 2025, 13(3), 148; https://doi.org/10.3390/systems13030148 - 21 Feb 2025
Viewed by 464
Abstract
The accelerating digital transformation necessitates a paradigm shift in manufacturing, requiring a structured transition from traditional to smart manufacturing. To address the challenges of fragmented integration, this study proposes an evolutionary model known as the integration of informatization and industrialization (TIOII) that systematically [...] Read more.
The accelerating digital transformation necessitates a paradigm shift in manufacturing, requiring a structured transition from traditional to smart manufacturing. To address the challenges of fragmented integration, this study proposes an evolutionary model known as the integration of informatization and industrialization (TIOII) that systematically analyzes the dynamic interactions among product, technique, and business integration using a back-propagation neural network approach. A significant research gap exists in understanding how the chaotic and nonlinear interactions between these dimensions influence enterprise stability and adaptability. Prior studies have primarily focused on static models, failing to capture the evolutionary and dynamic nature of TIOII. To address this gap, this study employs stability theory and chaos theory to uncover the mechanisms through which TIOII disrupts pre-existing equilibrium states, leading to chaotic fluctuations before stabilizing into new structural configurations. This research also incorporates robust control theory to formulate strategies for enterprises to effectively manage instability and uncertainty throughout this transformation process. The findings reveal that TIOII is not a linear progression but an iterative process marked by instability and self-organized restructuring. The proposed model successfully explains the intricate, nonlinear interactions and evolutionary trajectories of TIOII dimensions, demonstrating that enterprise transformation follows a chaotic yet structured pattern. Moreover, the robust control methodology proves effective in mitigating uncontrolled instability, offering enterprises practical guidelines for refining investment strategies and adapting business operations amidst disruptive changes. This study enhances the theoretical understanding of industrial transformation by revealing the pivotal role of chaos in transitioning from stability to new stability, contributing to research on complex adaptive systems in enterprise management. The findings highlight the necessity of proactive strategic reconfiguration in technology, management, and product development, enabling enterprises to restructure investment strategies, refine business models, and achieve resilient, innovation-driven growth. Full article
(This article belongs to the Special Issue Digital Transformation in the Era of Technological Disruption: The Reshaping and Application of Emerging Technologies on Management Models)
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