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At the beginning of the 21st century, multiple and diverse social entities, including the public (consumers), private and nonprofit healthcare institutions, government (public health) and other industry sectors, began to recognize the limitations of the current fragmented healthcare system paradigm. Primary stakeholders, including employers, insurance companies, and healthcare professional organizations, also voiced dissatisfaction with unacceptable health outcomes and rising costs. Grand challenges and wicked problems threatened the viability of the health sector. American health systems responded with innovations and advances in healthcare delivery frameworks that encouraged shifts from intra- and inter-sector arrangements to multi-sector, lasting relationships that emphasized patient centrality along with long-term commitments to sustainability and accountability. This pathway, leading to a population health approach, also generated the need for transformative business models. The coproduction of health framework, with its emphasis on cross-sector alignments, nontraditional partner relationships, sustainable missions, and accountability capable of yielding return on investments, has emerged as a unique strategy for facing disruptive threats and challenges from nonhealth sector corporations. This chapter presents a coproduction of health framework, goals and criteria, examples of boundary spanning network alliance models, and operational (integrator, convener, aggregator) strategies. A comparison of important organizational science theories, including institutional theory, network/network analysis theory, and resource dependency theory, provides suggestions for future research directions necessary to validate the utility of the coproduction of health framework as a precursor for paradigm change.

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.

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.

Literature on strategic alliances (SAs) is large, diverse and growing. It needs synthesis and analysis for application and further research. Authors have also underlined the need for studies covering differences in structuring, situational application and management of alliances. This systematic literature review aims to cover dyadic, network and ecosystem (DNE) alliances with theory, context, characteristics and methodology (TCCM) methodology covering the life cycle stages of an alliance (pre-formation, formation and management) to uncover insights which inform practice and guide further research on this important subject.

This paper follows systematic literature review (SLR) methodology for research design and article selection and TCCM methodology for analysis. It also analyses the literature on DNE alliances using a nine-box matrix with DNE alliance forming one axis and three alliance lifecycle stages of pre-formation (alliance objectives), formation (alliance design and operationalisation) and post formation (alliance management) stages along the other axis.

Analysis indicates focus on individual firms and their own customer value proposition (CVP) in the dyadic and network alliances. Industries with fast-paced technological change benefit from loosely coupled alliances. Social context and social exchanges leading to collaboration and collective strengths mark network alliances, with a focus on knowledge creation and dissemination. Ecosystems focus on a collective CVP, which guides alliance behaviour. Ecosystem leadership guides this purpose through governance for sustained competitiveness. Negative consequences (dark side) of alliances can be mitigated by careful design, formation and management of DNE alliances.

While literature has focussed on static view of alliances in their industry or social context, this literature review analyses alliances along the dyadic, network and ecosystem typology, thus providing a new lens to study alliances. The review also recognises that alliances evolve over their life-cycle stages and observes their progression through their lifecycle stages aids for fuller comprehension of their behaviour. Areas for future research in structuring, leadership, value co-creation and technological change set an agenda for future research.

Dynamic managerial capabilities are drivers of alliance performance. The analysis using the nine-box matrix allows managers to better appreciate the options that exist and the consequences of their actions. Situating their alliance in the appropriate box can allow managers better plan, operationalise and manage their own alliances.

This systematic review compares and contrasts DNE alliances in extant literature and through their lifecycle stages. Insights from TCCM analysis and the nine-box matrix provide unique contribution to both theory and practice in this large and growing domain.

The role of chief executive officer (CEO) personal characteristics in shaping corporate policies has attracted increasing academic attention in the past two decades. In this review, the authors synthesize extant research on CEO attributes by reviewing 232 articles published in 29 journals from the accounting, finance and management literature. This review provides an overview of existing findings, highlights current trends and interdisciplinary differences in research approaches and identifies potential avenues for future research.

To review the literature on CEO attributes, the authors manually collected peer-reviewed articles in accounting, finance and management journals from 2000 to 2021. The authors conducted in-depth analysis of each paper and manually recorded the theories, data sources, country of study, study period, measures of CEO attributes and dependent variables. This procedure helped the authors group the selected articles into themes and sub-themes. The authors compared the findings in various disciplines and provided direction for future research.

The authors highlight the role of CEO personal attributes in influencing corporate decision-making and firm outcomes. The authors categorize studies of CEO traits into three main research themes: (1) demographic attributes and experience (including age, gender, culture, experience, education); (2) CEO interactions with others (social and political networks) and (3) underlying attributes (including personality, values and ideology). The evidence shows that CEO characteristics significantly affect a wide range of specific corporate policies that serve as mechanisms through which individual CEOs determine firm success and performance.

CEO selection is one of the most crucial decisions made by corporations. The study findings provide valuable insights to corporate executives, boards, investors and practitioners into how CEOs’ personal characteristics can impact future firm decisions and outcomes that can, in turn, inform the high-stake process of CEO recruitment and selection. The study findings have significant practical implications for corporations, such as contributing to executive training programs, to assist executives and directors attain a greater level of self-awareness.

Building on the theoretical foundation of upper echelons theory, the authors offer an integrated theoretical framework to consolidate existing empirical research on the impacts of CEO personal attributes on firm outcomes across accounting and finance (A&F) and management literature. The study findings provide a roadmap for scholars to bridge the interdisciplinary divide between A&F and management research. The authors advocate a more holistic and multifaceted approach to examining CEOs, each of whom embodies a myriad of personal characteristics that comprise their unique identity. The study findings encourage future researchers to expand the investigation of the boundary conditions that magnify or moderate the impacts of CEO idiosyncrasies.

This study aims to systematically review papers on women’s entrepreneurship in the internationalization of small and medium enterprises (SMEs) by examining the research profile (i.e. publication trends, publishers, domain and quality of journals, methodologies and units of analysis and regional classifications), internationalization entry modes and the theories underpinning, key variables using AMO framework (i.e. antecedents, mediators, moderators and outcomes) and suggestions for potential future studies.

This study used bibliometric analysis by selecting 62 relevant papers from 3,016 papers collected from the Web of Science, Scopus, Google Scholar and EBSCO databases. Content analysis was conducted to identify key research issues and gaps, which were then mapped on an AMO framework to address potential future research.

This study found that the number of papers published during the period 1994–September 2022 fluctuated, indicating an increasing trend of women’s entrepreneurship research in the internationalization of SMEs being published in various reputable journals by well-known publishers. This study also found several alternatives of internationalization entry modes, although export is still the most widely used alternative. Various theories that underlie this research include internationalization theory, resource-based theory, feminist theory and international entrepreneurship. This study proposes a future research framework on women’s entrepreneurship in the internationalization of SMEs: AMO.

This study contributes to the intersection of gender-focused international business and entrepreneurship domains. This study proposes a conceptual model of women’s entrepreneurship in internationalization of SMEs by mapping the antecedents, mediators/moderators and outcomes and offers promising opportunities for future research directions.

Employees play an essential role in interactive innovation activities in Open Innovation Communities (OICs). Nevertheless, the factors influencing employees' innovation behavior in OICs have not been studied in depth. This study selects personality traits and social network characteristics to explain why and how these two factors affect employees' innovation behavior in OICs.

Three regression models were constructed to test the relationship between personality traits, social network characteristics, and interactive innovation behaviors. The authors examined how employees' personality traits (Big Five personality traits) influence employees' innovative behavior (initiating and supporting innovation) directly in OICs and explored whether social network characteristics (social group) mediate the relationship between employees' personality traits and employees' innovation behavior.

Using empirical data on 162 employees from Salesforce's IdeaExchange, the authors found that extraversion and openness to experience have significant positive effects on employees' interactive innovation behaviors, while conscientiousness has a significant negative effect on employees' interactive innovation behaviors in OICs. Furthermore, the mediation effect test results indicated that social network characteristics have a mediating effect on the relationship between extraversion and innovative behavior, and between openness and innovative behavior.

This study analyzes how personality traits influence innovation behavior in an open innovation environment, thus enriching research related to the factors influencing interactive innovation behavior. Meanwhile, the study integrates personality, social network, and innovative behavior research streams and clearly explains the relationship between the three variables. The research findings assist firms in selecting suitable employees to participate in interactive innovation behaviors in OICs.

The purpose of this paper is to present a practical data-based framework for the prioritization of investment in manufacturing technologies, methods and tools, and to demonstrate its applicability and practical relevance through two case studies of manufacturing firms of different industrial segments.

The proposed framework is based on network theory applied on technology adoption. For this, the database of Industry 4.0 maturity assessments of SENAI was used to develop data visualization tools named “Technology Networks”. Thus, this study is descriptive research with correlational design. Besides, the framework was applied in two companies and semi-structured interviews were carried out with domain experts.

The technology networks highlight the technological adoption patterns of six industrial segments, by considering the answers of 863 Brazilian companies. In general, less sophisticated technologies were positioned in the center of the networks, which facilitates the visualization of adoption paths. Moreover, the networks presented a well-balanced adoption scenario of Industry 4.0 related technologies and lean manufacturing methods and tools.

Since the database was not built under an experimental design, it is not expected to make statistical inferences about the variables. Furthermore, the decision to use an available database prevented the editing or inclusion of technologies. Besides, it is estimated that the technology networks given have few years for obsolescence due to the fast pace of technological development.

The framework is a tool that may be used by practicing manufacturing managers and entrepreneurs for taking assertive decisions regarding the adoption of manufacturing technologies, methods and tools. The proposition of using network theory to support decision making on this topic may lead to further studies, developments and adaptations of the framework.

This paper addresses the topics of lean manufacturing and Industry 4.0 in an unprecedented way, by quantifying the adoption of its technologies, methods and tools and presenting it in network visualizations. The main value of this paper is the comprehensive framework that applies the technology networks for supporting decision making regarding technology adoption.

This study explores how factors arising from supply chain (SC) network and complexity work together in supply chain learning (SCL) behavior.

Fuzzy set qualitative comparative analysis, which is an emerging configurational analysis method, was adopted to examine the complex combination of five influencing factors. The data were collected using a two-stage survey. First, the authors selected seven typical firms with an awareness of SCL. Second, questionnaires were sent to the partners of the seven selected firms, and 156 valid questionnaires were obtained from 76 firms.

Drawing on emergent insights from the initiative, the authors find that multiple configurations of SC network and complexity lead to high SCL. Specifically, weak ties are necessary conditions of such learning, while strong ties are also conducive to this. Moreover, a moderate SC complexity is conducive to SCL.

This study enriches the understanding of SCL and provides new insights for SC management practitioners to take measures to improve it.

This study addresses the lack of in-depth understanding of the antecedent conditions of SCL in the literature. It establishes an integrated and comprehensive theoretical framework of such learning based on contingency theory. Additionally, this study incorporates ambidextrous SCL (i.e. creation capability and dispersion capacity). An overall prototype of SCL capability is proposed on SC network and complexity theory.

Research suggests that engaging in networking behaviors can affect individual work outcomes. However, relatively less is known about how internal versus external networking behaviors influence work outcomes, and whether gender moderates these relationships. Drawing on social capital theory and social role theory, the authors propose a positive relationship between employees' internal and external networking behaviors and their work outcomes (job commitment and career success), and the moderating effect of gender. The authors also explore employee preference in networking.

Based on a sequential mixed-method research design with a four-month time lag, Study 1 data on networking behaviors and employee outcomes were collected via a survey of middle managers and their supervisors from 10 private sector organizations in Sri Lanka. Study 2 data were collected via interviews from a sample of those middle managers and their supervisors.

Study 1 findings indicate a positive relationship between internal networking behaviors and job commitment, and external networking behaviors and career success. The authors also found that internal networking behaviors enhance job commitment. Study 2 findings indicate men and women network differently and benefit differently from that networking but achieve equitable workplace benefits.

This study provides pioneering evidence that internal networking behaviors enhance job commitment among women. It appears that past research did not test the moderating effect of gender for internal versus external networking behaviors separately. Moreover, this study refines the evidence that internal and external networking behaviors differentially impact employee outcomes and explains the processes through a qualitative inquiry.