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This paper investigates gender disparity in investment decisions within the popular American TV show Shark Tank.

The research uses a comprehensive dataset of 925 pitches from 14 seasons and 316 episodes, covering August 2009 to May 2023.

Contrary to previous studies, the findings indicate that female entrepreneurs do n'ot face discrimination in terms of their pitching success rates, regardless of their industry affiliation. However, the authors did observe that female entrepreneurs tend to receive lower valuations, both self-assessed and in final deals. This suggests a self-imposed gender gap in venture capital and angel investing, likely stemming from lower entrepreneurial aspirations among women.

To tackle this issue, the authors propose promoting female venture capital by increasing the representation of female entrepreneurs and business angels on Shark Tank. Such role models can inspire aspiring women in these fields. Additionally, the authors believe that mixed-gender founder teams, comprising both men and women, can play a significant role in developing promising startups with viable business models.

This research paper aims to explore the link between financial innovation (FINV), green finance (GRF) and sustainability performance (SUSP) with the overarching objective of driving sustainable growth. The purpose is to understand how the integration of FINV and GRF can contribute to improved SUSP for businesses and organizations.

The study adopts a survey-based approach, synthesizing existing scholarly works, empirical studies and industry reports. It examines the theoretical foundations and empirical evidence to understand the relationship between FINV, GRF and SUSP.

The findings highlight a positive relationship between GRF and SUSP. GRF acts as a catalyst for FINV by providing the necessary financial resources and incentives for organizations to invest in sustainable technologies and practices. It enables businesses to enhance their SUSP by adopting environmentally friendly processes, reducing carbon emissions and promoting resource efficiency. The integration of FINV and GRF fosters sustainable growth by aligning economic, environmental and social objectives.

This research paper contributes to the existing literature by offering a comprehensive examination of the link between FINV, GRF and SUSP. It consolidates and synthesizes previous studies, providing a holistic view of the topic. The paper also presents practical implications for businesses and policymakers, emphasizing the need for strategic integration of GRF and FINV to drive sustainable growth. The identification of future research directions adds originality to the study, guiding scholars and practitioners toward areas of further investigation.

Supply chain risks and disruptions pose a significant threat to the healthcare industry. This paper aims to synthesize the research streams in the intersection of healthcare supply chain management and risk management to identify the research gaps and future research directions.

We collected 205 papers published between 2006 and 2023 for the bibliometric analysis for the keyword co-occurrence and co-citation analysis, generating backward- and forward-looking perspectives on the scholarship in healthcare supply chain risk management (HSCRM).

This study finds a growing scholarly interest in HSCRM. Using bibliometric tools and mapping, this study presents the overall research trends in HSCRM literature and identifies seven research, namely, clusters, cost analysis, allocation, performance management, patient safety, quality, risk assessment and logistics and four research themes, namely, resilience, risk management strategy, healthcare supply chain disruption and data analytics, through the keyword co-occurrence and co-citation analyses. A future research agenda is provided based on these clusters for further investigation in this field.

This study conducted bibliometric analysis to identify clusters and associated themes for insights for further research. This approach helps advance the scholarship and proactively apply the implications in practice beyond the reactive strategy to risk management in healthcare supply chain management.

The present study uses a meta-analysis technique to explore the association between corporate governance and dividend policy. The extant literature delivers inconclusive findings on the relationship between corporate governance and dividend policy. Therefore, this study aims to resolve the issues and deliver comprehensive results.

The study involves a meta-analysis of 53 research studies using preferred reporting items for systematic reviews and meta-analyses and population, intervention, comparison, outcome and study design approaches. The paper examines the impact of moderators: corporate governance structure (Anglo-American, communitarian or emerging system) and dividend distribution metrics (dividend over net income, dividend over total assets and absolute amount of dividend/dividend per share). The study involves subgroup analysis and meta-regression analysis to examine the impact of moderators.

The study’s results specify that board size and percentage of female directors significantly impact the dividend decisions of the company. In addition, subgroup analysis and meta-regression results demonstrate that dividend measurement proxy moderates the association between corporate governance and dividend policy.

Based on the existing literature surveyed, to the best of the authors’ knowledge, the current study is the first to conduct a meta-analysis on the relationship between corporate governance and dividend policy. This paper is unique and the first one of its kind (to the best of the authors’ knowledge) to cover all these moderating variables under an umbrella and consolidate the results to understand the existing knowledge and direct future research in the area of corporate governance and dividend decisions.

This study aims to examine the role of big data analytics (BDA) powered by artificial intelligence (AI) in improving sustainable performance (SP) through green supply chain collaboration (GSCC), sustainable manufacturing (SM) and environmental process integration (EPI).

Data was collected from 249 supply chain professionals working at various manufacturing firms, and hypotheses were tested through a quantitative method using PLS-SEM with the help of SmartPLS version 4 to validate the measurement model.

This study identified that BDA-AI significantly and positively affects GSCC, SM and EPI. Similarly, the results showed that GSCC significantly and positively affects SP. At the same time, SM and EPI have an insignificant effect on SP. The GSCC found a significant relationship between BDA-AI and SP for mediation. However, SM and environmental performance integration did not mediate the relationship between BDA and AI and SP.

This research evaluated a second-order model and tested SP in conjunction with the dynamic capability theory in the manufacturing industry of Pakistan. Therefore, this research could be beneficial for researchers, manufacturers and policymakers to attain sustainable goals by implementing the BDA-AI in the supply chain.

Recent disruptions have sparked concern about building a resilient and sustainable manufacturing supply chain. While artificial intelligence (AI) strengthens resilience, research is needed to understand how cloud adoption can foster integration, collaboration, adaptation and sustainable manufacturing. Therefore, this study aimed to unleash the power of cloud adoption and AI in optimizing resilience and sustainable performance through collaboration and adaptive capabilities at manufacturing firms.

This research followed a deductive approach and employed a quantitative method with a survey technique to collect data from its target population. The study used stratified random sampling with a sample size of 1,279 participants working in diverse manufacturing industries across California, Texas and New York.

This research investigated how companies can make their manufacturing supply chains more resilient and sustainable. The findings revealed that integrating the manufacturing supply chains can foster collaboration and enhance adaptability, leading to better performance (hypotheses H1-H7, except H5). Additionally, utilizing artificial intelligence helps improve adaptability, further strengthening resilience and sustainability (H8-H11). Interestingly, the study found that internal integration alone does not significantly impact collaboration (H5). This suggests that external factors are more critical in fostering collaboration within the manufacturing supply chain during disruptions.

This study dives into the complex world of interconnected factors (formative constructs in higher order) influencing manufacturing supply chains. Using advanced modeling techniques, it highlights the powerful impact of cloud-based integration. Cloud-based integration and artificial intelligence unlock significant improvements for manufacturers and decision-makers by enabling information processes and dynamic capability theory.

Muslim engagement with cryptocurrencies (CC) raises fundamental questions rooted in religious faith: How should Muslims integrate Islamic Accounting principles like zakat into this new and rapidly evolving financial paradigm? Thus, it is essential to understand CC holders’ perceptions thoroughly and whether they are willing to pay zakat using crypto assets. This research aims to explore factors influencing Muslim CC holders’ intention to pay zakat on CC, emphasizing financial risk, theory of planned behavior (TPB) constructs and Shariah compliance’s moderating role.

This attempt uses a quantitative approach through a cross-sectional research design, using purposive sampling to gather data from Muslim CC holders. An extended theory of planned behavior (ETPB) model is applied to comprehensively analyze the key factors influencing intentions to pay zakat on CC. SmartPLS software is used to generate meaningful findings.

The study finds that financial risk associated with CC exerted a negative influence on TPB constructs, attitude (ATT), social norms (SN) and perceived behavioral control regarding zakat on CC (PBC). However, ATT and PBC positively shaped holders’ intention to pay zakat on CC. Interestingly, Shariah compliance-moderated interactions of TPB constructs on payment intentions were statistically significant.

With the rise of CC, a profound transformation is underway in the financial landscape. As this evolution unfolds, it becomes increasingly essential for stakeholders to understand how zakat could fit into such a new and rapidly evolving paradigm. A pioneering effort was made in this study by exploring Muslim CC holders’ intentions to fulfill zakat obligations, bridging a significant gap in the literature.

The purpose of this study is to investigate the reasons (for and against) affecting owners' attitudes and intentions to use digital marketing (DM) strategies in tourism and hospitality (T&H) small and medium enterprises (SMEs), by employing the behavioral reasoning theory (BRT).

A survey method was used to collect data from 306 T&H (SMEs) owners and analyze the data through partial least square structural equation modelling (PLS-SEM).

The study results indicate that reasons significantly affect owners' attitudes and intentions to use DM in T&H (SMEs). The “RF” was as follows: perceived ease of use (PEU), perceived usefulness (PU), and trust in DM professionals” and the “RA” technological anxiety, usage barriers (UB), and perceived complexity (PC) effect on owners’ attitudes and intentions to use DM. Also, it indicates that openness to change value significantly affects the “RF” insignificant with “RA” and attitude.

The findings of this study emphasize that if owners/managers, governments, and policymakers overcome the “RA” that discourages and raises the knowledge about the “RF” in the adoption of DM, then the usage intention of DM strategies can rise in T&H (SMEs).

This study is the first to investigate the reasons (for and against) the owner’s attitude and intention to use DM in T&H (SMEs) by utilizing behavioral reasoning theory (BRT), technology acceptance model (TAM), and innovation resistance theory (IRT).

In this research, we seek to understand the effects of artificial intelligence (AI) and knowledge management (KM) processes in enhancing proactive green innovation (PGI) within oil and gas organizations. It also aims to investigate the moderator role of trust and sustainability in these relationships.

This paper employs a quantitative analysis. Surveys have been gathered from the middle-line managers of twenty-four oil and gas government organizations to evaluate the perceptions of the managers towards AI, KM processes, trust, sustainability measures and proactive measures toward green innovation. Analytical and statistical tools that were employed in this study, including structural equation modeling with SmartPLSv3.9, have been used to analyze the data and to examine the measurement and structural models of this study.

The study results reveal a significant and positive impact of AI utilization, KM processes and PGI within oil and gas organizations. Furthermore, trust and sustainability turn out to be viable moderators affecting, and influencing the strength and direction of AI, KM and PGI relationships. In particular, higher levels of trust and more substantial sustainability commitments enhance the positive impact of AI and KM on green innovation outcomes.

Understanding the impact of AI, KM, trust and sustainability offers valuable insights for organizational leaders and policymakers seeking to promote proactive green innovation within the oil and gas industry. Thus, organizations can increase the efficiency of sustainable product development, process improvement and environmental management by using robust AI technologies and effective KM systems. Furthermore, fostering trust among stakeholders and embedding sustainability principles into organizational culture can amplify the effectiveness of AI and KM initiatives in driving green innovation outcomes.

This study extends the current knowledge by assessing the effect of AI and KM on proactive green innovation while accounting for trust and sustainability as moderators. Utilizing quantitative methods offers a nuanced understanding of the complex interactions between these variables, thereby advancing theoretical knowledge in the fields of innovation management, sustainability and organizational behavior. Additionally, the identification of specific mechanisms and contextual factors enriches practical insights for organizational practitioners striving for a practical understanding of the dynamics of the complexities of sustainable innovation in an AI-driven era.

This study seeks to: (1) examine the extent of interconnectedness prevailing between the cryptocurrency market, the stock market and the precious metals market. (2) Conduct thorough assessment of hedge and safe-haven qualities of broad range of precious metals and cryptocurrencies against returns on the African stock market.

This study applied two novel approaches that is Cross-quantilogram, an advanced statistical technique used to examine the relationship between quantiles of response variable and the quantiles of predictor variables, and TVP-VAR, a technique that captures the dynamic connectedness of variables under consideration.

It was found that the three markets are highly interconnected, particularly among assets under the respective financial markets. It was further revealed that the Johannesburg Stock Exchange (JSE) was the most resilient stock market, whereas Bitcoin, BNB, Silver (XAG) and Platinum (XPT) also exhibited notable resistance to shocks. Finally, the study found that cryptocurrencies and precious metals portrayed varying hedge and safe haven qualities under the various stock markets.

The high interdependency between the African stock market, cryptocurrencies and precious metals suggests that none of the markets is immune to shocks form the other market. The finding that cryptocurrencies and precious metals exhibit some degree of safe-haven and hedge potentials, albeit limited in certain stock markets, provides investors with alternative investment options during market downturns. Since most African stock markets, except the JSE, are net receivers of shocks, investors in these markets should exercise caution during periods of global financial uncertainty.

To the best of our knowledge, this study is the first to explore the dynamic interconnectedness between seven carefully selected African stock markets, three distinct cryptocurrencies and four precious metals, while also assessing the hedge and safe-haven potential of the cryptocurrencies and precious metals against stock market returns. Additionally, the study stands out in recent literature by employing two novel approaches: the TVP-VAR model, which captures the dynamic connectedness among variables, and the Cross-Quantilogram, an advanced statistical method that analyzes the relationship between the quantiles of the response and predictor variables, all within a single study.