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The purpose of this study is to explore the shifting power dynamics within an inter-organizational relationship (IOR) over time through an institutional theory lens. Specifically, this manuscript explores power by acknowledging its relationality, temporality and typology through a case study focusing on an international collegiate ice hockey tournament. This study seeks to demonstrate the complexity of power as a multi-dimensional, relational, and temporal concept that can ebb and flow given actors’ positionality.

This study uses a chronological case study that is an appropriate in-depth qualitative framework to explore the how and why of a particular phenomenon. Yin (2018) describes a case study as “investigat[ing] a contemporary phenomenon (the ‘case’) in depth and within its real-world context, especially when the boundaries between phenomenon and context may not be clearly evident” (p. 45). Specifically, I used a chronological case study method as it provides the ability to document the chronology of events to determine important factors shaping the phenomenon (Yin, 2018). This includes collecting various types of data (organizational documents, news articles, interviews and observations) to create a robust understanding of a bounded chronological case over time.

Examining power dynamics is important as “power or its absence influences the mechanisms available to partners for initiating, challenging, and/or enforcing institutional change” (Gray et al., 2022, p. 3). This paper demonstrates the complexity of power as a multi-dimensional, relational and temporal concept that can ebb and flow given actors’ positionality. Further, the paper provides a case study showing how power asymmetries in an IOR can shift over time.

This study provides a case study on an IOR wherein multiple international organizations collaborated to create an ice hockey tournament. Through the case study, I demonstrate how different partners navigate power imbalances and changes over time.

This study provides a textbook case study of a successful IOR. Entrepreneurial actors capitalized on a catalyst event to leverage a boundary-spanning document and their professional networks to form a new identity and shared vision through the formation of the tournament. Further, this study provides insight into how an organization in an IOR can work to balance asymmetrical power relations.

As organizations seek to engage in collaborations, leveraging power through their contextuality can help create more equitable arrangements over time. Even when organizations may truly be at a disadvantage when entering an IOR, such as a local indigenous community partnering with an international corporation or non-profit, the status of particular locals or local organizations can be powerful in balancing an imbalanced relationship.

While a wealth of research documents the relational dynamics of IORs, there remains a significant gap in our understanding pertaining to the dynamics of power asymmetries in IOR partnerships. Existing research primarily focuses on the antecedents leading to sport organizations engaging in IORs and the various processes organizational leaders can employ to ensure an IOR’s success. However, several scholars acknowledge a profound gap in our understanding of how partners experiencing a power deficit in an IOR partnership work to balance power asymmetries.

Global businesses are witnessing a transformation in their products and services, processes and business models due to digitalisation. This trend has led to the digitalisation of innovation and entrepreneurship from the modern business perspective. The present study primarily aims to study how digital innovations shape the landscape of digital entrepreneurship and thematic perspectives.

The present research applied a systematic literature review (SLR) method based on the PRISMA 2020 guidelines, and 47 articles were selected as the final sample size related to digital innovation and digital entrepreneurship. Though the ultimate sample size is acceptable and signifies a small sample size of 40, the choice is still justifiable as it follows the rule of thumb. Hence, “the rule of thumb” empowers the study to meaningfully contribute to the arena using the SLR method, and 40 qualified papers are an adequate lowest threshold number.

This study found that there is little investigation performed from the perspective of digital innovation and digital entrepreneurship. Prior studies researched were centred on innovation and entrepreneurship. The United Kingdom was the leading country that performed research on this domain followed by other countries such as the Netherlands, Sweden and the United States of America.

The present study supports the existing body of knowledge by throwing light on the association of digital innovation and digital entrepreneurship and how it further leads to the development of the digital ecosystem. It also highlights future research opportunities in the domain of digital innovation and digital entrepreneurship.

Predicting commodity futures trading volumes represents an important matter to policymakers and a wide spectrum of market participants. The purpose of this study is to concentrate on the energy sector and explore the trading volume prediction issue for the thermal coal futures traded in Zhengzhou Commodity Exchange in China with daily data spanning January 2016–December 2020.

The nonlinear autoregressive neural network is adopted for this purpose and prediction performance is examined based upon a variety of settings over algorithms for model estimations, numbers of hidden neurons and delays and ratios for splitting the trading volume series into training, validation and testing phases.

A relatively simple model setting is arrived at that leads to predictions of good accuracy and stabilities and maintains small prediction errors up to the 99.273th quantile of the observed trading volume.

The results could, on one hand, serve as standalone technical trading volume predictions. They could, on the other hand, be combined with different (fundamental) prediction results for forming perspectives of trading trends and carrying out policy analysis.

Generative artificial intelligence (GenAI) can potentially improve supply chain management (SCM) processes across levels and verticals. However, despite its promise, the implementation of GenAI for SCM remains challenging, mainly due to the lack of knowledge regarding its key drivers. To address this gap, this study examines the factors driving GenAI implementation in an SCM environment and how these factors optimize SCM performance.

A thorough literature review was followed to identify the drivers. The resultant model from the drivers was validated using a quantitative study based on partial least squares structural equation modeling (PLS-SEM) that used responses from 315 expert respondents from the field of SCM.

The results confirmed the positive effect of performance expectancy, output quality and reliability, organizational innovativeness and management commitment to GenAI usage. Further, they showed that successful GenAI usage improved SCM performance through improved transparency, better decision-making, innovative design, robust development and responsiveness.

This study reports the potential drivers for the contemporary development of GenAI in SCM and highlights an action plan for GenAI’s optimal performance. The findings suggest that by increasing the rate of GenAI implementation, organizations can continuously improve their strategies and practices for better SCM performance.

This study establishes the first step toward empirically testing and validating a theoretical model for GenAI implementation and its effect on SCM performance.

The objective of this study is to analyse the integration of technology in Human Resources Management (HRM) with a special focus on Artificial Intelligence (AI), Machine Learning (ML), Internet of Things (IoT) and Big Data.

This study aims to contribute to the understanding of these trends by conducting a thorough bibliometric analysis using the Scopus database, encompassing research on HRM and Technology from 1991 to 2022. By employing citation analysis, co-citation analysis and co-word analysis, the study uncovers key patterns and trends in the field.

The findings indicate that AI, Big Data and ML are the focal points of research when exploring the intersection of Technology and HRM. These technologies offer promising prospects for enhancing Human Resource processes, such as Talent Acquisition, Performance Management and Employee Engagement.

In our study, we showcase the practical implications that offer guidance for HR researchers and professionals, enabling them to make informed decisions regarding the adoption and implementation of Information Technology.

This research can provide valuable insights to HR managers on the use of cutting-edge technology in HRM. It aims to enhance the manager’s awareness of how technology-enabled HRM can improve HR performance.

This study adds to the existing body of knowledge on how Modern Technology empowers HRM. It also proposes a conceptual framework for the use of Modern Technology along with Strategic Management and Knowledge Management to improve Human Resource Performance.

To advance understanding of transparency by problematising the motivations and strategies of a so far underexplored group: its users.

We explore the relationship between blindness, visibility, and transparency by drawing on our analysis of Max Frisch’s experimental novel Gantenbein (1964), in which the protagonist lives a life of feigned blindness.

The accounting scholarly debate on transparency has neglected the users of transparency. We address this through a novel theorisation of transparency as a game, highlighting some of its distinctive features and paradoxes.

By theorising the transparency game we move beyond concerns with what transparency reveals or conceals and conceptualise the motivations and strategies of the players engaged in this game. We show how different players have something to gain from the transparency game and warn of its emancipatory limits.

This study aims to examine the literature on accounting ethics education to capture and synthesise the characteristics of scholars dedicated to this area of research.

Using a combination of PRISMA systematic literature review methods and research profiling, the study collects a sample frame consisting of 278 articles published in peer-reviewed academic journals from 1970 to 2023. The articles were analysed to identify key authors of accounting ethics education research, the institutions conducting this research and the journals publishing this research.

The results indicate that research in accounting ethics education is not dominated by any single institution but is distributed across 225 institutions in 36 countries, with a significant concentration in the United States. Additionally, most articles were published in accounting or business journals, rather than in education-focused journals.

The findings provide insights into the ranking of researchers in accounting ethics education and establish benchmarks among the institutions involved in this research area. Further studies could explore the implications of these findings on future research directions.

This study offers valuable information for academics and institutions seeking to understand the landscape of accounting ethics education research and highlights areas for potential collaboration and development.

This paper addresses a gap in the literature by providing a comprehensive synthesis of the existing research on accounting ethics education and the scholarly community surrounding it.

The construction industry has been investigating “where Henry Ford is in the industry system.” Given that listed construction enterprises are the backbone of the promotion of the high-quality development of the industry, their research and innovation are of considerable importance. This study aims to comprehensively assess the research and development (R&D) status quo and trends within various types of construction enterprises in order to identify effective strategies to enhance R&D efficiency in the construction industry.

Based on the data won from annual reports and the CSMAR database for the period 2016–2020, this study examines 104 listed construction enterprises in China. By applying both the data envelopment analysis (DEA) method and the Malmquist productivity index, this research compares and analyzes the static and dynamic differences in R&D efficiency across different types of construction enterprises.

Results suggest that the magnitude of change in the Malmquist decomposition index of 104 listed construction enterprises gradually narrowed, but the comprehensive technological level remained relatively low. Although state-owned enterprises had an advantage in scale efficiency, meaning they could maximize output with given inputs, their technological progress efficiency, also known as the degree of technological innovation, was significantly lower than that of private enterprises. As one finding, state-owned enterprises in comparison with private enterprises experience significant R&D inefficiency. It represents the main cause of their low degree of technological innovation and efficiency.

This study assesses the R&D efficiency of listed construction enterprises in China from the perspective of different market segments, state-owned and private enterprises and suggests approaches to improve strategies for various corporate types. Thus, the study’s new findings contribute to addressing the challenge of low R&D levels in the construction industry in the fields of engineering, construction and architectural management.

Humans are largely influenced by the environment in which they work, and the positive environment offers positive outcomes. Building on these lines, this study aims to propose and empirically investigate the relationship of fun on employees’ knowledge sharing behavior. The study also proposes and empirically tests the mediation mechanism of psychological empowerment and boundary condition of person–environment fit.

Considering the nature of the study, the data is collected from employees working in information technology firms at two points of time. At first point of time 600 questionnaire were distributed while at the end of second point of time all in all 313 useful responses were available for data analysis purpose.

The statistical analysis reveals that fun improves the psychological state of individual and in turn they share more knowledge. The findings also highlight that person–environment fit strengthens the relationship.

Based on the findings the study highlights some important theoretical and practical implications. The future direction is also provided based on these lines.

The present paper aims to conduct a comprehensive scientific mapping of exchange rate forecasting, highlighting trends, developments, and methodological changes. This will provide research scholars, researchers, and policymakers valuable insights to facilitate predictions.

The researchers performed a bibliometric analysis of exchange rate forecasting using a scientific search method on the Scopus database from 1991 to 2022. They applied a web interface program called Biblioshiny, part of the Bibliometric package built in R by Aria and Cuccurullo (2017). VOSviewer was used to identify the most influential journals, authors, countries, articles, citations, and co-citations from 1,602 documents.

The conceptual and intellectual framework of the papers under review provided an in-depth and comprehensive analysis of the domain. The research outcomes provided essential information on the subject matter, highlighting the need for further investigation. The study’s findings demonstrate the evolution of the theory of forecasting exchange rates reflecting continuous developments in the methodologies applied to forecast the exchange rates.

The scientific mapping of the present study’s bibliometric analysis is limited to the Scopus database because of its comprehensive coverage of high-quality journals and predefined structures compatible with Bibliometrix software.

The study provides considerable insight into forecasting exchange rates and their interlinkages. By outlining the social and intellectual structure of the field, it directs upcoming scholars about the relevant topics, contexts and potential collaborations emerging in this field. The study also reveals the critical concerns in the area and leads to potential research opportunities.

The study sheds light on emerging trends and approaches to forecasting exchange rates and will provide valuable information and insights to policymakers, economists, investors and decision-makers in the financial sector. It will contribute to prioritising research in overlooked areas and support the formulation of effective policies.

This study contributes significantly by bringing together disparate literature on exchange rate forecasting, highlighting important journals, authors and documents, and examining the recent studies on the foreign exchange rate.