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This paper aims to reveal the interdisciplinarity of information science (IS) from the perspective of the evolution of theory application.

Select eight representative IS journals as data sources, extract the theories mentioned in the full texts of the research papers and then measure annual interdisciplinarity of IS by conducting theory co-occurrence network analysis, diversity measure and evolution analysis.

As a young and vibrant discipline, IS has been continuously absorbing and internalizing external theoretical knowledge and thus formed a high degree of interdisciplinarity. With the continuous application of some kernel theories, the interdisciplinarity of IS appears to be decreasing and gradually converging into a few neighboring disciplines. Influenced by big data and artificial intelligence, the research paradigm of IS is shifting from a theory centered one to a technology centered one.

This study helps to understand the evolution of the interdisciplinarity of IS in the past 21 years. The main limitation is that the data were collected from eight journals indexed by the Social Sciences Citation Index and a small amount of theories might have been omitted.

This study identifies the kernel theories in IS research, measures the interdisciplinarity of IS based on the evolution of the co-occurrence network of theory source disciplines and reveals the paradigm shift being happening in IS.

The purpose of this paper is to review the utilization of game theory in the entrepreneurship literature. Game theory can potentially be employed to assess strategies incentivizing productive entrepreneurial activities and subsequent economic development. Therefore, the author reviews entrepreneurship articles and explores the application of game-theoretic models and concepts in the literature.

First, the author provides an overview of the entrepreneurship ecosystem concept, highlighting key challenges in its study. The author also briefly highlights successful applications of game theory in the innovation literature. Second, the author systematically reviews and synthesizes entrepreneurship research employing game-theoretic models and concepts. The author's objective is to provide a state-of-the-art overview of the use of game theory in entrepreneurship.

Broadly, the author categorizes entrepreneurship-game theory articles into three groups based on their scope and purpose: entrepreneurial policy applications, inter-firm applications and entrepreneurship theory applications. Entrepreneurial policy applications include entrepreneurs and the government or policy as the main players in a game. Inter-firm applications encompass games between entrepreneurs and other private entities. Entrepreneurship theory applications include articles that utilize game theory to advance the author's understanding of entrepreneurial behavior and/or mechanisms in the market.

To the best of the author's knowledge, no previous paper has reviewed the use of game-theoretic approaches and models in entrepreneurship literature. This study addresses this research gap.

This study aims to develop the first Theory of Technological Response and Progress in Chaos (TRPC) and examine the case of technological development during the COVID-19 pandemic. The research objectives of this study were to: identify the key technologies that act as a response mechanism during the chaos event, specifically in the case of COVID-19; examine how technologies evolve, develop and diffuse in an immediate crisis and a chaotic environment; theorise various types and periods of technological response and progress during the emergence of chaos and the stages that unfold; and develop policy-oriented recommendations and establish technological foundations to address subsequent chaos events.

This study used the grounded theory as a methodology with a mixed-method approach that included quantitative and qualitative methods. The authors used the quantitative method to assist with the qualitative step to build the TRPC theory. Accordingly, this study integrated machine learning and text mining approaches to the qualitative data analysis following the steps of the grounded theory approach.

As a result of the TRPC theory development process, the authors identified three types of technologies (survival, essential and enhancement technologies) and five types of periods (stable, initial, survival-dominant, essential-dominant and enhancement-dominant periods) that are specific to chaos-technology interactions. The policy implications of this study demonstrate that a required technological base and know-how must be established before a chaotic event emerges.

Concerning the limitations of this study, social media data has advantages over other data sources, such as the examination of dynamic areas and analyses of immediate responses to chaos. However, other researchers can examine publications and patent sources to augment the findings concerning scientific approaches and new inventions in relation to COVID-19 and other chaos-specific developments. The authors developed the TRPC theory by studying the COVID-19 pandemic, however, other researchers can utilise it to study other chaos-related conditions, such as chaotic events that are caused by natural disasters. Other scholars can investigate the technological response and progress pattern in other rapidly emerging chaotic events of an uncertain and complex nature to augment these findings.

Following the indications of the OECD (2021a) and considering the study conducted by the European Parliamentary Research Service (Kritikos, 2020), the authors identified the key technologies that are significant for chaos and COVID-19 response using machine learning and text intelligence approach. Accordingly, the authors mapped all technological developments using clustering approaches, and examined the technological progress within the immediate chaos period using social media data.

The key policy implication of this study concerns the need for policymakers to develop policies that will help to establish the required technological base and know-how before chaos emerges. As a result, a rapid response can be implemented to mitigate the chaos and transform it into a competitive advantage. The authors also revealed that this recommendation overlaps with the model of dynamic capabilities in the literature (Teece and Pisano, 2003). Furthermore, this study recommends that nations and organisations establish a technological base that specifically includes technologies that bear 3A characteristics. These are the most crucial technologies for the survival- and essential-dominant stages. Moreover, the results of this study demonstrate that chaos accelerates technological progress through the rapid adoption and diffusion of technologies into different fields. Hence, nations and organisations should regard this rapid progress as an opportunity and establish the prior knowledge base and technologies before chaos emerges.

The authors have contributed to the chaos studies and the relationship between chaos and technological development by establishing the first theoretical foundation using the grounded theory approach, hereafter referred to as the TRPC theory. As part of the TRPC theory, the authors present three periods of technological response in the following sequence: survival technology, essential technology and enhancement technology. Moreover, this study illustrates the evolving technological importance and priorities as the periods of technological progress proceed under rapidly developing chaos.

Digital transformation using Industry 4.0 technologies can address various challenges in food supply chains (FSCs). However, the integration of emerging technologies to achieve digital transformation in FSCs is unclear. This study aims to establish how the digital transformation of FSCs can be achieved by adopting key technologies such as the Internet of Things (IoTs), cloud computing (CC) and big data analytics (BDA).

A systematic literature review (SLR) resulted in 57 articles from 2008 to 2022. Following descriptive and thematic analysis, a conceptual framework based on the diffusion of innovation (DOI) theory and the context-intervention-mechanism-outcome (CIMO) logic is established, along with avenues for future research.

The combination of DOI theory and CIMO logic provides the theoretical foundation for linking the general innovation process to the digital transformation process. A novel conceptual framework for achieving digital transformation in FSCs is developed from the initiation to implementation phases. Objectives and principles for digitally transforming FSCs are identified for the initiation phase. A four-layer technology implementation architecture is developed for the implementation phase, facilitating multiple applications for FSC digital transformation.

The study contributes to the development of theory on digital transformation in FSCs and offers managerial guidelines for accelerating the growth of the food industry using key Industry 4.0 emerging technologies. The proposed framework brings clarity into the “neglected” intermediate stage of data management between data collection and analysis. The study highlights the need for a balanced integration of IoT, CC and BDA as key Industry 4.0 technologies to achieve digital transformation successfully.

The Grey System Theory (GST) is an emerging area of research within artificial intelligence. Since its founding in 1982, it has seen a lot of multidisciplinary applications. In just a short period, it has garnered some considerable strengths. Based on the 1987–2021 data collected from the Web of Science (WoS), the current study reports the advancement of the GST.

Research papers utilizing the GST in the fields of economics and education were retrieved from the Web of Science (WoS) platform using a set of predetermined keywords. In the final stage of the process, the papers that underwent analysis were manually chosen, with selection criteria based on the information presented in the titles and abstracts.

The study identifies prominent authors, institutions, publications and journals closely associated with the subject. In terms of authors, two major clusters are identified around Liu SF and Wang ZX, while the institution with the highest number of publications is Nanjing University of Aeronautics and Astronautics. Moreover, significant keywords, trends and research directions have been extracted and analyzed. Additionally, the study highlights the regions where the theory holds substantial influence.

The study is subject to certain limitations stemming from factors such as the language employed in the chosen literature, the papers included within the Web of Science (WoS) database, the designation of works categorized as “articles” in the database, the specific selection of keywords and keyword combinations, and the meticulous manual process employed for paper selection. While the manual selection process itself is not inherently limiting, it demands a greater investment of time and meticulous attention, contributing to the overall limitations of the study.

The significance of the study extends not only to scholars and practitioners but also to readers who observe the development of emerging scientific disciplines.

The analysis of trends revealed a growing emphasis on the application of GST in diverse domains, including supply chain management, manufacturing and economic development. Notably, the emergence of COVID-19 as a new research focal point among GST scholars is evident. The heightened interest in COVID-19 can be attributed to its global impact across various academic disciplines. However, it is improbable that this interest will persist in the long term, as the pandemic is gradually brought under control.

This paper aims to map the antecedents and precursory contexts regarding the four principles of management. Moreover, a description of its codification and coalescence as a unified teaching framework is provided, critically reviewing key theoretical underpinnings of management principles in academic research and management textbooks.

A historiographic approach reviewed seminal works for theory origins of the four principles of management, by analyzing 260 management textbooks from 1935 to 2013 to document their adoption in management education. This study used critical hermeneutics (Prasad, 2002) to explore the framework’s progression by providing the context of cultural, political and economic influences.

This research study tracked and mapped the creation of the four principles of management, as it became the commonly accepted teaching framework in management education. Today, every predominant management principles textbook uses the four principles of management – plan, lead, organize and control – as the basis for teaching students.

There is limited research on the application of the four principles of management in contemporary management, despite its ubiquity in management education. The study’s historical account of its formation provides insights into its adoption and utilization in modern education context. The study’s primary limitation stems from the generalization of the representative sample of textbooks used in the study (1917–2013). However, data saturation was achieved for the scale of textbooks and writings which was reviewed.

Through a critical analysis into the formation of the four principles of management, this research not only provides a historical account of its construction but, as importantly, the influencing factors that led to its development. This research fills a gap in critical literature, as a post mortem exegesis has never been conducted on the four principles of management in the afteryears of its amalgamation.

The purpose of this research is to provide a theoretical and practical theory and application that provides understanding and means to manage complex infrastructures.

In this research, complexity, nonlinear, noncontinuous effects and aleatoric and data unknowns are bypassed by directly addressing systems' responses. Graph theory, statistics and digital signal processing (DSP) tools are applied within a theoretical framework of the theory of faults (ToF). Motivational complex infrastructure systems (CISs) are difficult to model. Data are often missing or erroneous, changes are not well documented and processes are not well understood. On top of it, under complexity, stalwart analytical tools have limited predictive power. The aleatoric risk, such as rain and risk cascading from interconnected infrastructures, is unpredictable. Mitigation, response and recovery efforts are adversely affected.

The theory and application are presented and demonstrated by a step-by-step development of an application to a municipal drainage system. A database of faults is analyzed to produce system statistics, spatio-temporal morphology, behavior and traits. The gained understanding is compared to the physical system's design and to its modus operandi. Implications for design and maintenance are inferred; DSP tools to manage the system in real time are developed.

Sociological systems are interest driven. Some events are intentionally created and directed to the benefit and detriment of the opposing parties in a project. Those events may be explained and possibly predicted by understanding power plays, not power functions. For those events, sociological game theories provide better explanatory value than mathematical gain theories.

The theory provides a thematic network for modeling and resolving aleatoric uncertainty in engineering and sociological systems. The framework may be elaborated to fields such as energy, healthcare and critical infrastructure.

ToF provides a framework for the modeling and prediction of faults generated by inherent aleatoric uncertainties in social and technological systems. Therefore, the framework and theory lay the basis for automated monitoring and control of aleatoric uncertainties such as mechanical failures and human errors and the development of mitigation systems.

The contribution of this research is in the provision of an explicatory theory and a management paradigm for complex systems. This theory is applicable to a wide variety of fields from facilities and construction project management to maintenance and from academic studies to commercial use.

The main purpose of this study is to provide a comprehensive review and critical insights of the application of fuzzy methods in modeling, assessing and understanding the various aspects of green and sustainable supply chains (SSCs).

The present study conducts a systematic literature review (SLR) and bibliometric analysis of 252 research articles. This study employs various tools such as VOSviewer version 1.6.10, Publish or Perish, Mendeley and Excel that aid in descriptive analysis, bibliometric analysis and network visualization. These tools have been used for performing citation analysis, top authors' analysis, co-occurrence of keywords, cluster and content analysis.

The authors have divided the literature into seven application areas and discussed detailed insights. This study has observed that research in the social sustainability area, including various issues like health and safety, labor rights, discrimination, etc. is scarce. Integration of the Industry 4.0 technologies like blockchain, big data analytics, Internet of Things (IoT) with the sustainable and green supply chain (GSC) is a promising field for future research.

The authors' contribution primarily lies in providing the integrated framework which shows the changing trends in the use of fuzzy methods in the sustainability area classifying and consolidating green and sustainable supply chain management (SSCM) literature in seven major areas where fuzzy methods are predominantly applied. These areas have been obtained after the analysis of clusters and content analysis of the literature presenting key insights from the past and developing the conceptual framework for future research studies.

Site supervision features largely influence the productivity status of construction operational processes. This study aims to use a case study containing mixed methods to test the site supervisory traits in applying mathematical theories to construction operations for directing supervisory capabilities under various operational characteristics.

A total of 62 construction site supervisors were trained as part of a new apprenticeship programme. Through literature reviews and expert consultations, grading criteria were designed with various degrees of descriptions and score ratings. The supervisory attributes were evaluated under seven competency element characteristics mapped with the relevant learning domains.

The results demonstrate a detailed sectional view of performance ratings of supervisors under different characteristics of competency factors with the validity, reliability, applicability and generalisability assurance of the research findings using relevant statistical tests and expert evaluations.

Though the research applications were engaged directly with the construction industry in the Sri Lankan setting, other developing countries and emerging industries can also employ equivalent tactics to attain similar outcomes in their industry-based operations.

The research findings have led to producing a new guide that makes significant impacts on deciding the capability levels in construction supervisory attributes while executing problem-solving applications in construction planning and operational processes. Accordingly, the findings push to open a gate to intake advanced cognitive attributes towards addressing the industry's knowledge gap on how the problem-solving-based apprenticeship protocols need to be linked with the supervision features.

This paper lays the groundwork for future research in supply chain transparency in two ways. First, the authors delineate the construct and explore how it is shifting the business landscape. Second, the authors connect nine theories to the construct to guide future scholars in this growing research area.

The authors explore the practical implications for the future of supply chain transparency research through the application of nine theories: stakeholder theory; the technology acceptance model; transaction cost theory; commodity theory; competing values theory; ambidexterity; the natural-resource-based view of the firm; actor-network theory and neo-institutional theory. The authors also consider the blending of theories to provide further insights into the ways firms engage in supply chain transparency.

This analysis relates theories from several disciplines (i.e. marketing, supply chain management, economics, information systems and organizational behavior) to add theoretical insights to the concept of supply chain transparency, with suggestions for using these theories in conjunction to address complex emerging issues. The authors offer guidance and direction for cross-disciplinary research to help supply chain and logistics influence other fields.

Supply chain transparency is a boundary-spanning phenomenon swiftly proliferating multiple aspects of business. This research applies nine theoretical perspectives to guide future researchers and lays the foundation for managers looking to adopt transparency into their supply chains.