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Prior research from transaction costs economics argued that central firms perform better because they have superior access to information to discipline their alliance partners. Central firms may also, however, face higher costs and risks of unintentional learning and weaken their competence through structural inertia. We propose that these costs and risks are influenced by the learning capacities of the firms in the network and can explain different outcomes for focal firm performance.

To test our predictions, we use instrumental variable–generalized method of moments estimation techniques on 15,517 firm-year observations from equity alliance portfolios in the global food industry across a 21-year window.

We find support for our predictions and show that the relationship between network degree centrality and firm performance is negatively influenced by partners’ learning capacity and positively influenced by focal firms’ learning capacity, while firms with low network degree centrality benefit less from their learning capacity.

Future developments in transaction cost economics may consider partner and focal firms’ learning capacity as moderators of the network degree centrality – firm performance relationship.

In alliance decisions, managers must consider that the combination of high network degree centrality and partners’ learning capacity can lead to high costs, risks of unintentional learning, and structural inertia, all of which have negative consequences for performance. In concentrated industries where network positions are controlled by a few large firms, policymakers must acknowledge that firms may face substantial barriers to collaboration with learning-intensive firms.

This study is the first to develop and test a comprehensive transaction cost analysis of the central firm’s unintended knowledge flows and structural inertia in alliance networks. It is also the first to incorporate theoretically and empirically the hazards of complex and unintended information flows on the relationship of network degree centrality to performance in equity alliance portfolios.

This paper aims to investigate whether executive compensation, corporate social responsibility (CSR)-based incentives, environmental social and governance (ESG) performance and firm performance are the significant predictors of CSR committees, in addition to CEO, firm and corporate governance characteristics, from the tenet of stakeholder and managerial power theories.

Switzerland is an exemplary country from the perspective of corporate governance and executive compensation. This empirical study includes a panel data set of listed Swiss companies, so fixed-effect logistic regression has been used.

It has been found that the companies that offer CSR-based incentives and higher compensation to their CEOs and have better ESG performance are more likely to have CSR committees.

This empirical paper fills the gap in the literature, guides practitioners about the factors that influence the creation and efficiency of CSR committees, and inspires regulatory bodies to ponder on a mandatory CSR committee to form resilient and sustainable organizations worldwide.

COVID-19 has re-emphasized the prominence of sustainability and the stakeholder approach. Thus, this paper indicates that CSR committees require the adaption and implementation of a holistic sustainability policy that integrates both external and internal factors and thereby provides a whole process for sustainability issues.

The impact of CSR committees on corporate social performance (CSP) has already been investigated. However, the predictors of CSR committees have been less scrutinized in the literature.

While different attempts have been made to use artificial intelligence (AI) to codify communicative behaviors and analyze startups’ video presentations in relation to crowdfunding projects, less is known about other forms of access to entrepreneurial finance, such as video pitches for candidacies into startup accelerators and incubators. This research seeks to demonstrate how AI can enable the startup selection process for both entrepreneurs and investors in terms of video pitch evaluation.

An AI startup (Speechannel) was used to predict the outcomes of startup video presentations by analyzing text, audio, and video data from 294 video pitches sent to a leading European startup accelerator (LUISS EnLabs). 7 investors were also interviewed in Silicon Valley to establish the differences between humans and machines.

This research proves that AI has profound implications with regards to the decision-making process related to fundraising and, in particular, the video pitches of startup accelerators and incubators. Successful entrepreneurs are confident (but not overconfident), engaging in terms of speaking quickly (but also clearly), and emotional (but not overemotional).

This study not only fills the existing research gap but also provides a practical guide on AI-driven video pitch evaluation for entrepreneurs and investors, reshaping the landscape of entrepreneurial finance thanks to AI. On the one hand, entrepreneurs could use this knowledge to modify their behaviors, enabling them to increase their likelihood of being financially backed. On the other hand, investors could use these insights to better rationalize their funding decisions, enabling them to select the most promising startups.

This paper makes a significant contribution by bridging the gap between theoretical research and the practical application of AI in entrepreneurial finance, marking a notable advancement in this field. At a theoretical level, it contributes to research on managerial decision-making processes – particularly those related to the analysis of video presentations in a fundraising context. At a practical level, it offers a model that we called the “AI-enabled video pitch evaluation”, which is used to extract features from the video pitches of startup accelerators and incubators and predict an entrepreneurial project’s success.

This paper investigated the relationship between intellectual capital (IC)/its components, and the business performance of Vietnamese small and medium enterprises (SMEs).

The panel data set was obtained from the Vietnam SME database. Using the value-added intellectual coefficient (VAIC) approach for IC measurement, this paper employs various panel data estimation approaches, including fixed effects (FE) and the generalized method of moments (GMM), to examine the relationship between IC and the financial performance of SMEs in Vietnam.

The result suggests that the value creation activities of SMEs in Vietnam mainly occur on the basis of physical and financial capital. In other words, the findings indicate that Vietnamese SMEs mainly depend on physical and financial capital to profit: they have not fully utilized their human capital and structural capital, two main components of IC for value creation.

The results underline the urgency of effective management of tangible and IC to boost the utilization of human and structural capital to increase the profitability of Vietnamese SMEs. The results lead to suggesting a series of policy recommendations to achieve the objective.

This paper is the first to examine the relationship between IC and the financial performance of SMEs in Vietnam, contributing to the literature on IC in emerging countries.

This study assesses the SDG-related well-being of indigenous communities in India using bibliometric analysis and the ADO-TCM framework. It provides insights into their alignment with sustainable development objectives.

This study analysed 74 high-impact journals using bibliometric analysis to evaluate the well-being of India’s indigenous peoples about the SDGs.

This study analyses the well-being of tribal communities in India using existing scholarly articles and the ADO-TCM framework. It emphasises the importance of implementing Sustainable Development Goals (SDGs) to promote the well-being of indigenous populations.

This study uses bibliometric analysis and the ADO-TCM framework to investigate factors impacting tribal community welfare. It proposes theoretical frameworks, contextual considerations and research methodologies to achieve objectives.

The purpose of this global study is to investigate the critical failure factors (CFFs) in the deployment of operational excellence (OPEX) programs as well as the key performance indicators (KPIs) that can be used to measure OPEX failures. The study also empirically analyzes various OPEX methodologies adopted by various organizations at a global level.

This global study utilized an online survey to collect data. The questionnaire was sent to 800 senior managers, resulting in 249 useful responses.

The study results suggest that Six Sigma is the most widely utilized across the OPEX methodologies, followed by Lean Six Sigma and Lean. Agile manufacturing is the least utilized OPEX methodology. The top four CFFs were poor project selection and prioritization, poor leadership, a lack of proper communication and resistance to change issues.

This study extends the current body of knowledge on OPEX by first delineating the CFFs for OPEX and identifying the differing effects of these CFFs across various organizational settings. Senior managers and OPEX professionals can use the findings to take remedial actions and improve the sustainability of OPEX initiatives in their respective organizations.

This study uniquely identifies critical factors leading to OPEX initiative failures, providing practical insights for industry professionals and academia and fostering a deeper understanding of potential pitfalls. The research highlights a distinctive focus on social and environmental performance metrics, urging a paradigm shift for sustained OPEX success and differentiating itself in addressing broader sustainability concerns. By recognizing the interconnectedness of 12 CFFs, the study offers a pioneering foundation for future research and the development of a comprehensive management theory on OPEX failures.

This study aims to investigate the factors contributing to the low adoption rate of mobile money services (MMS) in the Middle East and North Africa (MENA) region compared to other regions. The study focussed on socio-demographic factors and macro-level determinants in several selected MENA and Sub-Saharan African (SSA) regions where MMS have been successful.

This study analysed 23 countries across MENA and SSA to establish the correlation between socio and macroeconomic factors and MMS adoption using a quantitative approach. The analysis used the generalized least square (GLS) method.

The study revealed that gender and income are factors that positively influence the adoption of MMS in MENA and SSA regions. Additionally, the study found that the affordability index, which measures macroeconomic indicators, correlates with MMS adoption in both regions but in an inversed way. On the other hand, political stability appears to have a positive correlation with MMS adoption in the MENA region. The correlation between the regulatory index and MMS adoption positively impacts the entire study group, although it is insignificant in the SSA region.

Future studies should assess market competition among MMS providers and the psychological aspect of user adoption behaviour. Additionally, conducting a focus group discussion with stakeholders in the MMS industry can assist in uncovering potential factors contributing to low MMS adoption in the MENA region.

This study contributes to understanding the role of the socio-demographic and macroeconomic determinants in promoting digital transformation through adopting MMS.

The aim of this paper is to evaluate the impact of the sustainable financial disclosure regulation (SFDR) on the environmental, social and governance (ESG) performance and risk scores of sustainable funds (SFs) from a multi-regional perspective.

This research involves conducting a comparative study between self-labeled SFs and conventional funds of the same mutual fund company matched using a five-step process. Using the SFDR publication as a natural study, this study uses panel data methodology on a portfolio ESG score database before SFDR implementation and three to six months post-SFDR Level 1 requirement to measure the impact.

The findings provide evidence of a clear reduction in ESG risk and an improvement in ESG performance across all samples and ESG dimensions following the SFDR regulation. In addition, the results reveal a positive spillover effect of the regulation on conventional funds following its implementation.

The study can be helpful for fund managers, investors and regulators as it provides insights into the impact of mandatory ESG disclosure regulation on the global fund investment market. The study is limited by data availability due to the restrictive matching approach used, which starts with fund pairs from the same fund management company.

The study can be helpful for fund managers, investors and regulators as it provides insights into the impact of mandatory ESG disclosure regulation on the global fund investment market.

To the best of the authors’ knowledge, there is a lack of research papers that analyze the impact of the SFDR mandatory regulation as a driving force on the ESG scores of the fund market using the same fund management matched pair approach. This paper tests the importance of the investment area through a multi-regional approach to study potential “spillover” effects.

Against social cognitive and social exchange theories, this research paper aims to investigate the significance and interaction between perceived knowledge, involvement, trust and brand community engagement in brand communities (BC).

BC participants (n = 503) completed a cross-sectional survey for this research. Analysis was performed using PLS-SEM via SmartPLS (v. 4.1.0.2) and the novel Necessary Condition Analysis (NCA).

An integrative KITE model with positive and significant relationships of key BC constructs was established. The perceived BC knowledge influenced involvement and engagement. Furthermore, the constructs of involvement and trust were discovered to have a positive and significant impact on engagement, with trust having a substantial effect on BC engagement. The indirect effects of the trust construct via the BC knowledge and BC involvement constructs were also significant.

This research advances the existing conceptual approaches by introducing knowledge as the key BC constructs. The study illustrates that members’ knowledge about a BC facilitates their involvement in the BCs. The vital role of trust is revealed in the KITE model, as it is significantly related to BC knowledge, BC involvement and BC engagement with at least medium to large effect sizes. Notably, the role of trust is enhanced as it is the only necessary must-have (instead of “should-have”) condition to achieve high levels of BC engagement. Furthermore, the KITE model provides insights for marketers to develop a valuable BC.

Against the backdrop of dynamic capabilities theory, this research examines the relationship between knowledge and marketing agility in the context of big data marketing analytics (BDMA). The relevant knowledge constructs under investigation are business/marketing, relational, technological and technology management. The level of BDMA deployment is also examined to determine its impact on these relationships.

A survey was used to gather data from marketing professionals working in firms with at least limited experience in big data (BD) deployment in the United States and Canada. The results were analyzed using partial least squares structural equation modeling (PLS-SEM) with a sample of 236 responses.

The results indicate that marketing professionals perceived the knowledge and marketing agility constructs differently than the previous research on IT professionals. The knowledge construct was perceived as a two-dimensional construct consisting of broad knowledge skills and specific technical knowledge skills. Only the broad knowledge skills construct was significantly related to the marketing agility construct, with progressively high predictive validity and relevance when the deployment of BDMA progresses.

The paper's originality stems from the different conceptualizations of the knowledge and marketing agility constructs due to the use of a novel sample of marketing professionals in this study. The research also contributes to the dynamic capabilities theory by emphasizing the critical role of vital knowledge when aiming to enhance marketing agility.