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This study aims to answer two significant questions: What are the relative consumer and firm-level effects of marketing through metaverse compared to conventional marketing endeavours? What are the current trends in utilizing the metaverse as reported in the recent literature?

This study uses a systematic literature review methodology, using a Preferred Reporting Items for Systematic Reviews and Meta-Analyses flowchart to synthesize existing research. A total of 35 articles written in English were selected and analysed from two databases, Web of Science and EBSCO Host.

The findings indicate that consumer-level effects of the metaverse include consumer loyalty and brand attachment. The firm-level benefits are decentralization and cost reductions. The paper proposes a framework indicating variables that could attenuate or enhance the association between immersive components of the metaverse and their resultant effects.

This study contributes to understanding the role of metaverse in marketing practices related to the marketing mix components. The study conceptualizes a novel framework for the metaverse and its resultant effects.

The purpose of this paper is to integrate academic research on hubristic organizational leaders by proposing a comprehensive conceptual framework and research directions on the hubristic literature.

The paper systematically reviewed 25 years of literature on hubristic organizational leaders based on the PRISMA methodology.

The literature on hubristic leaders is analyzed, and a conceptual framework is presented that highlights the antecedent, consequence, mediators and moderators. Literature has primarily focused on the negative impact of hubris leadership concerning firm performance and destructive behaviors. Few scholars have explored the positive side of hubris leadership, relating it to innovation and product success.

This paper presents the first systematic review of hubristic organizational leaders, to the best of the authors’ knowledge. The review provides an improved grasp of the current status of research, trends and potential future research directions.

Organizations widely adopt knowledge management (KM) to develop and promote technologies and improve business effectiveness. Analytics can aid in KM, further augmenting company performance and decision-making. There has been significant research in the domain of analytics in KM in the past decade. Therefore, this paper aims to examine the current body of literature on the adoption of analytics in KM by offering prominent themes and laying out a research path for future research endeavors in the field of KM analytics.

A comprehensive analysis was conducted on a collection of 123 articles sourced from the Scopus database. The research has used a Latent Dirichlet Allocation methodology for topic modeling and content analysis to discover prominent themes in the literature.

The KM analytics literature is categorized into three clusters of research – KM analytics for optimizing business processes, KM analytics in the industrial context and KM analytics and social media.

Systematizing the literature on KM and analytics has received very minimal attention. The KM analytics view has been examined using complementary topic modeling techniques, including machine-based algorithms, to enable a more reliable, systematic, thorough and objective mapping of this developing field of research.

This paper introduces “virtual fun at the virtual workplace” and conceptualizes its impact on virtual socialization and the formation of virtual professional ties. The conceptual model also recognizes the moderation of a few variables: “awareness of being observed,” “diversity in the virtual workplace” and “virtual impression management.”

The paper takes a theoretical approach to develop a conceptual framework of virtual fun in the virtual workplace, drawing on social exchange theory (SET) and social network theory (SNT).

The study extends the tenets of the SET and extends the applicability of SNT to a virtual workplace. The study suggests that managers should introduce semi-organized virtual fun during scheduled breaks within work hours to aid in virtual socialization, which further aids in the formation and strengthening of “professional ties” in the virtual workplace.

This study is the first of its kind to conceptualize a model for virtual fun in the virtual workplace.

This study aims to intend and implement the optimal power flow, where tuning the production cost is done with the inclusion of stochastic wind power and different kinds of flexible AC transmission systems (FACTS) devices. Here, the speed with fitness-based krill herd algorithm (SF-KHA) is adopted for deciding the FACTS devices’ optimal sizing and placement integrated with wind power. Here, the modified SF-KHA optimizes the sizing and location of FACTS devices for attaining the minimum average production cost and real power depletions of the system. Especially, the objective includes reserve cost for overestimation, cost of thermal generation of the wind power, direct cost of scheduled wind power and penalty cost for underestimation. The efficiency of the offered method over several popular optimization algorithms has been done, and the comparison over different algorithms establishes proposed KHA algorithm attains the accurate optimal efficiency for all other algorithms.

The proposed FACTS devices-based power system with the integration of wind generators is based on the accurate placement and sizing of FACTS devices for decreasing the actual power loss and total production cost of the power system.

Through the cost function evaluation of the offered SF-KHA, it was noted that the proposed SF-KHA-based power system had secured 13.04% superior to success history-based adaptive differential evolution, 9.09% enhanced than differential evolution, 11.5% better than artificial bee colony algorithm, 15.2% superior to particle swarm optimization and 9.09% improved than flower pollination algorithm.

The proposed power system with the accurate placement and sizing of FACTS devices and wind generator using the suggested SF-KHA was effective when compared with the conventional algorithm-based power systems.