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This paper aims to introduce two draft concepts, spiritual self-managed teams and holacracy, as solutions for reducing the friction within neo-enterprises and the issues of hierarchical leadership dynamics and mindset present within orthodox organizations’ structures and communications and they help businesses to grow further, achieve their goals, and become self-sustainable.

To counter the popular maxim, “management and leadership are what cause many problems for organizations and its people,” the authors argue for six novel propositions constructed around the two draft concepts following a critical review and meta-analysis of notable business/leadership cases, presented in a narrative-based descriptive style.

This article presents a list of novel propositions for entrepreneurs, managers and researchers who may investigate further and possibly test it in organizations. The findings merit opening new frontiers for perceiving leadership, group dynamics and decision-making in organizations using spiritual ideas.

Adopting the paper’s content can benefit organizations’ management, efficiency and sustainability. Implementation of the two novel concepts – spiritual self-managed teams and holacracy – and their combination can significantly reduce friction within organizations’ structures and communications.

This case studies the growth of OYO Hotels (OYO) to illustrate the operational processes necessary to succeed in the service sector. The case allows for a discussion of employee- and customer-management systems, tech-driven solutions, and profit drivers. The material unfolds OYO's growth and its solution for making economy hotels discoverable and bookable online.

The case raises a series of questions around OYO's business model, its ability to translate across global markets, and growth potential. It has been successfully taught in a second-year MBA class on the management of service operations.

The importance of workplace inclusion continues to gain scholarly acclaim. However, in reality, many employees choose to ostracize their colleagues post workplace relationship strife. With this notion the present study aims to delve into the intricate linkages between workplace relationship conflict (WRC) and employee ostracism behavior (EOB), exploring the serial mediating roles of relational identification (RI) and emotional energy (EE). Additionally, the study examines the potential moderating effect of perceived forgiveness climate (PFC) to understand how forgiveness climate may serve as a boundary condition in shaping these crucial relationships.

The analysis utilized five-wave time-tagged data collected from 228 employees through scenario and survey methods. The Hayes PROCESS Macro was employed to examine the proposed hypotheses.

The results indicate a positive influence of WRC on EOB. Additionally, RI and EE sequentially mediate the relationship between WRC and EOB. Furthermore, PFC moderates the serial mediation process (RI and EE) between WRC and EOB as well as the adverse effects of WRC on RI.

Grounded in the theoretical framework of conservation of resource (COR) theory and cognitive-affective personality system (CAPS) theory, the present study offers new insights. By establishing the complicated interplay of RI and EE between WRC and EOB along with the moderating role of PFC, the study extends the understanding of the mechanisms involved, providing a more comprehensive perspective. By shedding light on these complicated interconnected links, the study paved the way for positive social dynamics at work.

The purpose of this study is twofold. Firstly, the authors have conducted a systematic investigation considering the historical pandemic periods (1991–2021) over 30 years to identify critical factors and business failure phenomenon during pandemics to explore “what”, “why” and “how” factors contributing to business failure during the COVID-19 pandemic and secondly identified interlinks of these factors to explain the phenomenon of business failure strategically through various quantitative models.

Firstly, the critical factors were identified through previous literature and systematically reported in accordance with the PRISMA guidelines. To remove any bias in critical factor selection, Delphi method was employed. In the second phase, m-TISM approach was adopted to understand the interrelationships of the factors to develop the hierarchy levels. Lastly, MICMAC analysis was also done to evaluate the driving and dependence powers of the critical factors. For implementation of the stated methodology, expert opinion was collected to assess the critical factors based on their knowledge and experience. A total of seven experts were involved in this study.

Two major takeaways from the results of phase one were that “external environmental changes” was at the highest level and had the highest driving power as well as the lowest dependence power, while “inappropriate marketing techniques” was at the lowest level and had the highest dependence and lowest driving powers.

The ever-developing digital technologies act as a synonym to innovation and are shaping up to be the key to future-proofing any industry. However, before one can move towards developing effective strategies to mitigate any business disruptions, there is a need to assess the causes of business failures in the first place which is a major managerial implication identified through this study.

This paper can be considered as the first few studies to conduct a systematic investigation considering the historical pandemic periods (1991–2021) over 30 years to identify critical factors and business failure phenomenon during pandemics to explore “what”, “why” and “how” factors contributing to business failure during the COVID-19 pandemic and secondly identified interlinks of these factors to explain the phenomenon of business failure strategically through various quantitative models.

This chapter takes on the role of the metaverse in skill development, such as skilling, reskilling, and upskilling in the digital age. Metaverse is instrumental in revolutionizing skill development in the digital age and bringing the paradigm shift in learning. This chapter will cover the capability of the metaverse to transform the ways of learning and developing skills in the evolving digital landscape. Individuals can be part of tailor-made solutions for their needs through innovative methodologies and interactive experiences. This chapter takes through real cases to get deeper insights about conventional methods that transform how an individual experiences learning to acquire skills to get exposed to the rapidly changing digital world, allowing people to customize their learning experiences to adapt their unique requirements through cutting-edge methodologies and digitally responsive encounters. It then deliberates the importance of the metaverse in the individual-led industry in a manner that allows people to reach their potential. Individuals succeed in the evolution of the metaverse dynamic by continually upskilling granted to them.

Purpose: This study investigates the influence of inflation and oil price fluctuations on stock prices and returns. A thorough bibliometric analysis of research articles published in the last 22 years has been conducted to achieve this objective.

Need for the Study: Inflation and oil prices are critical macroeconomic variables that significantly impact the economy, including the stock market. It is crucial for investors and policymakers to understand the complex relationship between these economic variables and the stock market.

Methodology: The study employed a bibliometric analysis to identify the most influential authors, institutions, and research themes related to the impact of inflation and oil prices on stock prices.

Findings: The study identified that the fluctuations of the stock market are significantly influenced by both inflation and oil prices. This relationship has been extensively studied in the literature, with several key research themes identified. These themes include the effects of inflation and oil prices on various sectors and industries, the role played by monetary and fiscal policy, and the impact of international trade and global economic conditions.

Practical Implications: The insights that have emerged have significant implications for investors and policymakers. It highlights the need for risk management strategies and mitigation of macroeconomic factors’ impact on stock prices.

One of the most marginalized communities in India is the Lesbian, Gay, Bisexual and Transgender (LGBT) community which commonly experiences discrimination. Many studies have countered that the LGBT community faces high discrimination in the banking and financing industry. As a result, this study concentrates on this marginalized community and its acceptance and continuation habit regarding mobile wallets. Consequently, this study has considered continuance intentions as a response to confirm the progress of the mobile-wallet industry. Also, this study tried to study the relationship between behavioral intention (BI) and continuous intention (CI) which is seriously lacks in the library of literature. The research operationalized the stimulus–organism–response (SOR) framework for the conceptual model and surveyed 100 self-proclaimed members of the LGBT community in India. The analysis has been done using the partial least structure (PLS). The findings demonstrate that variables like perceived trust (PT) directly influence the BI. On the other hand, variables like perceived ease of use (PEoU), social influence (SI), and satisfaction (S) doesn’t influence BI of the LGBT Community. The main outcome was a favorable association between BI and CI. It will help the stakeholders to understand how important this new market avenue is and how it can be explored. To ensure safe and secure transactions, a group think tank composed of important parties (financial institutions, mobile-wallet providers, the government, security specialists, etc.) should make recommendations. Mobile-wallet providers will attain benefit from this study’s understanding of user categories and ability to tailor their service offers as per the community.

This research explores the application of machine learning to optimize pricing strategies in the aftermarket sector, particularly focusing on parts with no assigned values and the detection of outliers. The study emphasizes the need to incorporate technical features to improve pricing accuracy and decision-making.

The methodology involves data collection from web scraping and backend sources, followed by data preprocessing, feature engineering and model selection to capture the technical attributes of parts. A Random Forest Regressor model is chosen and trained to predict prices, achieving a 76.14% accuracy rate.

The model demonstrates accurate price prediction for parts with no assigned values while remaining within an acceptable price range. Additionally, outliers representing extreme pricing scenarios are successfully identified and predicted within the acceptable range.

This research bridges the gap between industry practice and academic research by demonstrating the effectiveness of machine learning for aftermarket pricing optimization. It offers an approach to address the challenges of pricing parts without assigned values and identifying outliers, potentially leading to increased revenue, sharper pricing tactics and a competitive advantage for aftermarket companies.

As the Metaverse emerges as a prominent paradigm, Artificial Intelligence (AI) plays a pivotal role in shaping its landscape. This chapter explores the convergence of AI and the Metaverse, exploring the symbiotic relationship between these two transformative technologies. From virtual assistants to immersive experiences, AI-driven innovations are redefining how individuals interact and navigate within the Metaverse. This chapter also assesses the challenges and prospects brought about by AI in the Metaverse which is impacting both businesses and society on a broader scale.