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We conducted this study to examine the relationship between revenue concentration and a firm's financial leverage. We aimed to analyze whether revenue concentration influences a firm's capital structure decisions and whether this relationship is driven by customer-specific investments or the direct effect of revenue concentration itself. Additionally, we investigated the role of asset redeployability in mediating or moderating the relationship between revenue concentration and financial leverage.

The paper investigates the relationship between revenue concentration and a firm's financial leverage. The results indicate a negative association between revenue concentration and financial leverage. This finding holds across various regression models and is statistically significant. Furthermore, the paper explores the potential role of asset redeployability in explaining the relationship between revenue concentration and financial leverage. The results indicate that even after controlling for asset redeployability, the negative relationship between revenue concentration and leverage remains significant, suggesting that revenue concentration affects capital structure decisions independently of the risks associated with relationship-specific investments. Robustness tests are conducted using a three-stage least squares approach to account for the simultaneity between revenue concentration, asset redeployability and capital structure.

Our findings demonstrate that revenue concentration is negatively associated with financial leverage, even after accounting for asset redeployability. This suggests that revenue concentration affects capital structure decisions independently of the risks associated with customer-specific investments. Furthermore, we performed robustness tests to address potential simultaneity issues between revenue concentration, asset redeployability and capital structure.

The study relies on available data sources, which may have inherent limitations in terms of accuracy, completeness or consistency. The quality of the data used in the analysis could impact the robustness of the findings. Time Period: The study focuses on more recent years, which might limit the ability to compare the findings with studies conducted over different time periods. Historical trends or structural changes that could impact the relationship between revenue concentration and financial leverage might not be fully captured.

Firms with higher revenue concentration tend to have lower financial leverage. Recent years show a negative relationship between profitability and market leverage compared to earlier periods. Revenue concentration has a distinct effect on financial leverage, not fully explained by risks from relationship-specific investments or asset redeployability. Insights for firms in managing capital structure decisions, considering revenue concentration and its implications for leverage.

This research is one of the first papers that investigates the impact of revenue concentration on the capital structure choices of firms. By exploring the relationship between revenue concentration and financial leverage, the study contributes to the existing literature by shedding light on an underexplored area. Thus, this study adds originality to the field by addressing a research gap and contributing to the understanding of the relationship between revenue concentration and capital structure choices.

The study aims to estimate the short- and long-run effects of monetary policy on residential property prices in South Africa. Over the past decades, there has been a monetary policy shift, from targeting money supply and exchange rate to inflation. The shifts have affected residential property market dynamics.

The Johansen cointegration approach was used to estimate the effects of changes in monetary policy proxies on residential property prices using quarterly data from 1980 to 2022.

Mortgage finance and economic growth have a significant positive long-run effect on residential property prices. The consumer price index, the inflation targeting framework, interest rates and exchange rates have a significant negative long-run effect on residential property prices. The Granger causality test has depicted that exchange rate significantly influences residential property prices in the short run, and interest rates, inflation targeting framework, gross domestic product, money supply consumer price index and exchange rate can quickly return to equilibrium when they are in disequilibrium.

There are limited arguments whether the inflation targeting monetary policy framework in South Africa has prevented residential property market boom and bust scenarios. The study has found that the implementation of inflation targeting framework has successfully reduced booms in residential property prices in South Africa.

This study aims to investigate the effect of overconfident chief executive officers (CEOs) on corporate tax avoidance and whether this relationship is affected by institutional and family ownership.

Using a sample of French-listed firms from 2009 to 2021, the authors find that firms managed by overconfident CEOs engage in more tax avoidance practice.

The authors further find that institutions and families are likely to discourage tax avoidance practices, paying close attention to their long-term horizons and reputational concerns. Overall, the authors' findings shed light on the monitoring role of institutional and family shareholders in restraining the effect of CEO behavioral bias on companies' tax avoidance.

To the authors' knowledge, no study has investigated the impact of managerial overconfidence on the tax behavior of French firms. The authors also extend the growing literature regarding managerial effects by providing new evidence that French firms held by concentrated institutional and family ownership curtail CEO overconfidence behavior toward corporate tax avoidance practices.

This study aims to investigate the role of negative media coverage of environmental, social and governance (ESG) issues in deterring tax avoidance. Inspired by media agenda-setting theory and legitimacy theory, this study hypothesises that an increase in ESG negative media coverage should cause a reputational drawback, leading companies to reduce tax avoidance to regain their legitimacy. Hence, this study examines a novel channel that links ESG and taxation.

This study uses panel regression analysis to examine the relationship between negative media coverage of ESG issues and tax avoidance among the largest European entities. This study considers different measures of tax avoidance and negative media coverage.

The results show that negative media coverage of ESG issues is negatively associated with tax avoidance, suggesting that media can act as an external monitor for corporate taxation.

The findings have implications for policymakers and regulators, which should consider tax transparency when dealing with ESG disclosure requirements. Tax disclosure should be integrated into ESG reporting.

The study has social implications related to the media, which act as watchdogs for firms’ irresponsible practices. According to this study’s findings, increased media pressure has the power to induce a better alignment between declared ESG policies and tax strategies.

This study contributes to the literature on the mechanisms that discourage tax avoidance and the literature on the relationship between ESG and taxation by shedding light on the role of media coverage.

This study aims to identify the strategic leadership and change management used to obtain the Association to Advance Collegiate Schools of Business (AACSB) accreditations as well as the research development on AACSB in the past decade.

This study used a systematic literature review following Petticrew and Roberts’ study. The articles were limited to empirical studies published from 2013 to 2022, taken from the Dimensions AI database.

The findings suggested that two leadership styles were used to obtain AACSB accreditation: dominance-oriented transformational and financial leadership, alongside three traits of academic leaders: commitment, engagement and encouragement. Additionally, three change management models/processes were found in the articles: teaching evaluation framework, temporary isomorphism and authenticity. Finally, they discovered that the object of the studies on AACSB accreditation had been narrowed down from the organizational level to smaller objects consisting of schools’ identity, teaching, learning and business schools’ key players.

As this study only used Dimensions AI, potential articles related to the topic outside the database could not be obtained. Thus, it limits the scope of the findings of this paper.

This study informs academic leaders in business schools about the role of strategic leadership and change management in obtaining AACSB accreditation.

Through a systematic scoping review, this study presented a decade of research development on AACSB in addition to the strategic leadership and change management needed to obtain it.

The COVID-19 pandemic has posed many challenges in almost all sectors around the globe. Because of the pandemic, government entities responsible for managing health-care resources face challenges in managing and distributing their limited and valuable health resources. In addition, severe outbreaks may occur in a small or large geographical area. Therefore, county-level preparation is crucial for officials and organizations who manage such disease outbreaks. However, most COVID-19-related research projects have focused on either state- or country-level. Only a few studies have considered county-level preparations, such as identifying high-risk counties of a particular state to fight against the COVID-19 pandemic. Therefore, the purpose of this research is to prioritize counties in a state based on their COVID-19-related risks to manage the COVID outbreak effectively.

In this research, the authors use a systematic hybrid approach that uses a clustering technique to group counties that share similar COVID conditions and use a multi-criteria decision-making approach – the analytic hierarchy process – to rank clusters with respect to the severity of the pandemic. The clustering was performed using two methods, k-means and fuzzy c-means, but only one of them was used at a time during the experiment.

The results of this study indicate that the proposed approach can effectively identify and rank the most vulnerable counties in a particular state. Hence, state health resources managing entities can identify counties in desperate need of more attention before they allocate their resources and better prepare those counties before another surge.

To the best of the authors’ knowledge, this study is the first to use both an unsupervised learning approach and the analytic hierarchy process to identify and rank state counties in accordance with the severity of COVID-19.

This study aims to map and assess the conceptual development of the innovation ecosystem literature.

A bibliometric analysis was performed using the VOSviewer, RStudio software, Bibliometrix and Biblioshiny packages. To accomplish this, 367 publications published between 2006 and 2020 and indexed in the Web of Science and Scopus databases were assessed.

The results demonstrate a rise in research during 2016, with almost 30% of publications concentrated in only six journals. The co-citation analysis presented four clusters: case studies, business and innovation ecosystems (platform approach), open innovation and national and regional innovation systems (territorial approach). We proposed a theoretical framework based on two approaches in the innovation ecosystem literature based on co-citation analysis: platform, which has its roots in the literature on strategy, and territory, grounded in research on economic geography literature.

One of the limitations of the study is that only articles published in journals were analyzed, leaving out of the sample those published in congresses, books and other sources.

This paper contributes to the literature by presenting and clarifying the different conceptual trajectories of research in innovation ecosystems. We also proposed an analytical framework based on the two main approaches to innovation ecosystems – platform and territory. This framework presents the critical elements of managing innovation ecosystems from both perspectives.

Advanced servitization is the process that involves the combination of different services that facilitate both the use of a product and customer operations. Although servitization has emerged as a frequent strategy for manufacturers to differentiate themselves from the competition, its implementation can pose major challenges and may not always result in superior firm performance. Consequently, successful advanced servitization may require specific organizational capabilities to unleash performance-enhancing effects. To date, little is known about how to effectively configure advanced servitization to achieve such performance gains.

Adopting a fit theory perspective and using a configurational approach, we examine the interplay between servitization, organizational capabilities, contextual factors and financial performance. Specifically, we focus on advanced servitization and assess its necessity and sufficiency for achieving high financial performance. In addition, we study how the alignment of servitization approaches with organizational capabilities and contextual factors affects financial performance. We analyze data from 151 manufacturers in an emerging economy using fuzzy-set Qualitative Comparative Analysis (fsQCA).

Our findings indicate that advanced servitization is sufficient, but not necessary for high financial performance. In addition, the findings indicate that the alignment of servitization approaches with specific service-related capabilities unfolds complementarity effects that contribute to achieving high financial performance for manufacturers with different firm size and competitive intensity. The findings indicate three configurations that may serve as templates for managers to orchestrate resource allocation and successfully deploy advanced servitization.

Our study advances the servitization literature by further illuminating advanced servitization as a more complex servitization process. We show how high-performing manufacturers align servitization and organizational capabilities across different contexts, and thus provide design choices for managers in configuring servitization.

Although businesses continue to take up artificial intelligence (AI), concerns remain that companies are not realising the full value of their investments. The study aims to provide insights into how AI creates business value by investigating the mediating role of Business Process Management (BPM) capabilities.

The integrative model of IT Business Value was contextualised, and structural equation modelling was applied to validate the proposed serial multiple mediation model using a sample of 448 organisations based in the EU.

The results validate the proposed serial multiple mediation model according to which AI adoption increases organisational performance through decision-making and business process performance. Process automation, organisational learning and process innovation are significant complementary partial mediators, thereby shedding light on how AI creates business value.

In pursuing a complex nomological framework, multiple perspectives on realising business value from AI investments were incorporated. Several moderators presenting complementary organisational resources (e.g. culture, digital maturity, BPM maturity) could be included to identify behaviour in more complex relationships. The ethical and moral issues surrounding AI and its use could also be examined.

The provided insights can help guide organisations towards the most promising AI activities of process automation with AI-enabled decision-making, organisational learning and process innovation to yield business value.

While previous research assumed a moderated relationship, this study extends the growing literature on AI business value by empirically investigating a comprehensive nomological network that links AI adoption to organisational performance in a BPM setting.