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The purpose of this study is to present the overall trend and dynamics in global mergers and acquisitions activity while suggesting future research avenues in this domain. The analysis covers two aspects to examine the main contours of the domain, that is performance analysis followed by thematic cluster analysis.

Bibliometric analysis has been used for examining 1,433 publications extracted from the Scopus database to identify the research trend between 2000 and 2021. With the help of VosViewer (a bibliometric software), bibliographic coupling, citation, co-authorship, keyword and network analysis have been carried out.

The analysis reveals that most of the research on cross-border mergers and acquisitions (CBMA) is concentrated in the context of developed markets, USA and UK being the largest. Most of the research till date is confined to wealth effects, value creation, corporate governance, socio-cultural aspects and various determinants of CBMA, all from the standpoint of the acquirer.

The present study highlights numerous opportunities for future research based on empirical analysis. There exists a dearth of studies around CBMA in the context of emerging nations which provides a relatively unexplored field to carry out research work.

The study makes use of a comprehensive list of keywords to have an extensive analysis. This is a pioneering study that has used bibliographic coupling of documents for content analysis and to the best of authors’ knowledge, no previous works on cross-border acquisitions have performed bibliographic coupling for this.

Purpose of This Chapter: This chapter examines the gender-based skewness witnessed in terms of women-led unicorns, as well as, in the field of entrepreneurship in general in India. India has been witnessing a booming startup landscape lately, with the country producing several new unicorns. Competing internationally, India comes third in world rankings regarding the number of unicorns made.

Design / Methodology / Approach: The methodology adopted in this chapter is case-based analysis of individuals with the help of secondary data available in the public domain. The authors employ comparative analysis methodology keeping two major parameters of interest as the verticals that form the basis of the comparative analysis.

Findings: The special provisions in place that are especially meant for women entrepreneurs in order to help them scale up their business and target higher profits have loopholes in them and as a result, a very low number of women-led businesses have been able to mark their presence in the unicorn club.

Research Limitations / Implications: A lesser number of women entrepreneurs in the unicorn club, so making generalizations has not been possible.

Practical Implications: The chapter gives a better understanding of the dynamics of the entrepreneurship arena in India with respect to women entrepreneurs who are doing significant work on the basis of scale of operation and profits.

Originality: This is an original chapter which has not been presented or published before. This chapter can be of immense value to anyone interested in India’s current entrepreneurial scenario, and useful to policymakers, researchers, and academicians.

The aim of this paper states that total productive maintenance (TPM) is an improvement tool which employs the effective utilization of employees in order to enhance the reliability of the equipment in consideration.

This paper identifies and evaluates the factors accountable for the adoption of TPM methodology in manufacturing organizations. Twenty-four factors affecting the TPM implementation are explored and categorized into five significant categories. Afterwards, these identified TPM factors have been evaluated by using a most popular Multi-criteria decision-making (MCDM) approach namely fuzzy pivot pairwise relative criteria importance assessment (F-PIPRECIA).

In this paper, through application of F-PIPRECIA, “Behavioural factor” is ranked first while “Financial factor” the last. Considering the sub-factors, “Top management support and commitment” is ranked first while “Effective use of performance indices” is ranked the last. A further sensitivity analysis indicates the factors that need higher level of attention.

The result of current research work may be exploited by the top administration of manufacturing enterprises for assessing their TPM adoption status and to recognize the frail links of TPM application and improve accordingly. Moreover, significant factors of TPM can be identified and deploy them successfully in their implementation procedure.

The conclusion obtained from this research enables the management to clearly understand the significance of each considered factor on the adoption of TPM in the organization and hence, provides effective utilization of resources.

Introduction: With many new technologies requiring real-time data processing, cloud computing has become challenging to implement due to high bandwidth and high latency requirements.

Purpose: To overcome this issue, edge computing is used to process data at the network’s edge. Edge computing is a distributed computing paradigm that brings computation and data storage closer to the location where it is needed. It is used to process time-sensitive data.

Methodology: The authors implemented the model using Linux Foundation’s open-source platform EdgeX Foundry to create an edge-computing device. The model involved getting data from an on-board sensor (on-board diagnostics (OBD-II)) and the GPS sensor of a car. The data are then observed and computed to the EdgeX server. The single server will send data to serve three real-life internet of things (IoT) use cases: auto insurance, supporting a smart city, and building a personal driving record.

Findings: The main aim of this model is to illustrate how edge computing can improve both latency and bandwidth usage needed for real-world IoT applications.

This study focuses on work from home (WFH) issues faced by faculty members of higher education institutes in India during the coronavirus infection (COVID-19) pandemic. The study aims to understand the impact of these issues on faculty productivity. The study also analyzes the moderating effect of information technology (IT) training on the relationship between work- from-home issues and faculty productivity.

This study is quantitative. Data were collected from 215 faculty members working in higher education institutes in India. Correlation and hierarchical regression analysis have been used to analyze the data.

The analysis revealed that online teaching, lack of technology acceptance, poor working environment and work–life conflict negatively impacts faculty productivity. Thus, IT training work as a moderator plays an important role in reducing the WFH issues mainly Online Teaching, Lack of Technology acceptance & Poor Working Enviornment by increasing faculty productivity. IT training work does not moderate the relationship between work–life conflict and faculty productivity.

This research is limited to the higher education sector; the research limits the generalization of the higher education sector's finding to other sectors.

The findings would help policymakers and educational institutes to explore the use of digital technology to break boundaries of workplace and education institutes to disseminate knowledge to a global level. The findings also help to understand how the workplace is essential for the smooth functioning of tasks of the institute.

The study will also help management, institute, organization, society and individuals to change their mindset that education can be imparted through online mode in a better way with the help of digital technology.

There is a scarcity of research work examining WFH issues in conducting mandatory online classes due to COVID-19 pandemic and COVID-19's relation to faculty productivity in the higher education sector. This study contributes to the knowledge regarding the impact of COVID-19 on faculty productivity in the education sector.

This study aims to present a great deal of interest in researching plant-based phytopharmaceuticals and nutraceuticals as a possible alternative to synthetic medication, both to avoid their side effects and for financial reasons.

Mankind has used medicinal plants since the beginning of civilization. Nature has been explored as a source of therapeutic chemicals for thousands of years, and many modern drugs have been discovered from natural sources. The primary medical care system of resource-poor areas in India has continued to rely on traditional medicine as the most accessible and reasonably priced form of treatment.

Tinospora cordifolia is a plant that is frequently used in Ayurvedic and traditional medicine throughout India. Although almost all of its parts are used in conventional medical systems, the leaves, stems and roots are the most significant ones used medicinally. All forms of existence can benefit from the versatility of T. cordifolia. It includes a wide variety of compounds that impact the body.

The goal of this review is to provide a concise summary of the knowledge about the pharmacological, phytochemistry, botanical, ethnopharmacology, toxicity study, marketed products and patents of the T. cordifolia plant.

The increasing prevalence of mobile phones and the ease of cheaper Internet access have accelerated the growth of mobile-based payments in India. The study aims to identify must-have and should-have factors affecting consumers’ usage intention toward “Near-Field Communication (NFC)” based mobile payments.

The research integrates diffusion innovation theory and the technology acceptance model. Employing a mixed-methods approach, combining partial least square structural equation modeling and Necessary Condition Analysis (NCA). Thus, the study draws from qualitative interviews and a quantitative survey of 218 respondents.

The study results indicate that the relative advantage of NFC-based mobile payments over conventional payment modes and security concerns directly affect the intention to use it. However, complexity, transaction speed and ease of use do not affect the intention to use. Moreover, perceived usefulness mediates the relationship between complexity, relative advantage and transaction speed with the intention to use NFC-based mobile payments. Less complexity and ease of use, despite being insignificant determinants as per PLS-SEM, must be focused on as the NCA results indicate its necessity for future market growth.

This research addresses a significant gap by focusing on Indian consumers' intention to use NFC-based mobile payments, an area largely unexplored despite the global and availability of such services. The study distinguishes itself by examining factors influencing adoption within the nascent stage of mobile-based NFC payments in India, where digital growth and technology uptake are gradually unfolding.

Psychology studies have gradually evolved in the past decades from examining negative to positive states of mind. This has led to an increasing interest in understanding the well-being of individuals. Further, organizational research has demonstrated a positive impact of employee well-being on key business indicators. Drawing from positive psychology, this study examines the impact of happiness-enhancing activities and positive practices (HAPP) on employee well-being.

This study was conducted in an emerging information technology firm in India. Using validated measures, this study designed an online survey that was completed by 54 employees of the firm.

Employees largely perceived the HAPP as important but reported low levels of engagement in most activities or practices. Using hierarchical linear regression, this study found that self-concordant work significantly impacted employee’s job satisfaction and job-related affective well-being.

Leaders must harness the synergy between individual and organizational growth by providing self-concordant work contexts in which employee’s key skills, competencies and strengths are leveraged.

This study contributes to the existing scant literature on HAPP. Further, in a first, this study uses these psychological interventions in the context of workplace and assesses their impact on employee well-being which itself is an area of growing interest among academicians and practitioners.

Federation analytics approaches are a present area of study that has already progressed beyond the analysis of metrics and counts. It is possible to acquire aggregated information about on-device data by training machine learning models using federated learning techniques without any of the raw data ever having to leave the devices in the issue. Web browser forensics research has been focused on individual Web browsers or architectural analysis of specific log files rather than on broad topics. This paper aims to propose major tools used for Web browser analysis.

Each kind of Web browser has its own unique set of features. This allows the user to choose their preferred browsers or to check out many browsers at once. If a forensic examiner has access to just one Web browser's log files, he/she makes it difficult to determine which sites a person has visited. The agent must thus be capable of analyzing all currently available Web browsers on a single workstation and doing an integrated study of various Web browsers.

Federated learning has emerged as a training paradigm in such settings. Web browser forensics research in general has focused on certain browsers or the computational modeling of specific log files. Internet users engage in a wide range of activities using an internet browser, such as searching for information and sending e-mails.

It is also essential that the investigator have access to user activity when conducting an inquiry. This data, which may be used to assess information retrieval activities, is very critical. In this paper, the authors purposed a major tool used for Web browser analysis. This study's proposed algorithm is capable of protecting data privacy effectively in real-world experiments.