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The study aims to explore digital transformation from the viewpoint of human resource management to uncover possible threads of relationship using bibliometric analysis. It also aims to identify the trending research themes within the domains of digital transformation (DT) and human resource management (HRM) collectively.

The research employs a mix of quantitative bibliometric techniques and qualitative content analysis. A corpus of 227 articles retrieved from the Scopus database was analyzed using the R-based Biblioshiny and VOS viewer.

The study shows publication trends, influential authors, leading journals, highly productive institutions, and, countries in the domain of DT and HRM. Co-citation and co-occurrence analysis was undertaken to identify the research clusters, depicting trending research themes that extensively dominate the research under this domain.

This study will serve as a ready reckoner for academicians and business leaders, giving them useful insights to make their road towards digital transformation less challenging with the assistance of human capital.

This study is one of the initial efforts to quantitatively synthesize the results of earlier publications using bibliometric techniques in the domain of DT and HRM together. It will aid researchers in locating research gaps and filling those gaps in the future.

The purpose of this paper is to understand the dark side of blockchain technology (BCT) adoption in small and mid-size enterprises. The focus of the authors is to decode the intricate relationship among the selected variables missing in the existing literature.

A focused group approach is initiated by the authors to identify the barriers. Total interpretive structural modeling, Matrice d'impacts croisés multiplication appliquée á un classment, that is, matrix multiplication applied to classification and decision-making trial and evaluation laboratory are used to analyze the complex relationships among identified barriers.

This study finds that implementation of BCT reduces maintenance cost by withdrawing manual effort, as BCT has better capability to quantify the internal status of the system (observability characteristic). The observability characteristic of BCT provides high compatibility to the system. This study also finds that the compatibility of BCT with the organization reduces implementation cost and facilitates project management. The findings of this study recommend analyzing maintenance cost and compatibility of BCT before implementing it. Small and mid-size enterprises can select complex BCT depending on the sophistication level of IT usage and IT project management capabilities.

This study comes with various limitations, where the model developed by the authors may not be conclusive, as it is based exclusively on expert opinion. The samples collected may not help in validating the model statistically. Though the model has its limitations, it can still be considered as a nascent initiative for further investigation using structural equation modeling.

The outcomes of the theoretical and managerial contributions of the study can be categorized into three levels. This study can be used both by the industrialists and researchers to understand the barriers and the recovery methods thereafter. Suggestions that serve as future directives are also discussed by the authors.

The present study aims to examine whether leisure time posts shared on WhatsApp status drive to travel and tourism consumption among users.

In this study, discriminant analysis was employed to test hypotheses and identify essential factors.

The study indicated that the eight most contributing factors are expressing happiness, planning leisure time, views and comments, attractiveness, inquiring about places, preferring to post, nice way of expression and relax. These factors came from the latent variables of attitude, motivation and self-expression. Overall, the main influencing factors are internal (attitude and motivation), followed by an external factor i.e. self-expression. Additionally, the findings indicated that these significantly and positively impact travel and tourism consumption.

The discriminators identified in the study would guide tour and travel agencies and the agencies' managers on how best to adopt WhatsApp and WhatsApp's status application to influence aspiring travelers.

This study enlarges the existing literature by integrating three factors, attitude, motivation and self-expression, into a model to influence the behavioral outcomes of aspirational travelers using WhatsApp status.

During the COVID-19 pandemic, organizations undertook initiatives such as safety coaching to ensure the safety of their employees and to prevent the spread of the disease. However, the question arises if such measures can have a spill-over effect on other important work-related outcomes. Hence, the objective of the current study is to uncover the impact of safety coaching on one such outcome, i.e. work engagement.

In this study, the authors developed a quantitative model with the help of the social exchange theory. The responses of 250 working professionals captured using a three-wave study were analyzed using the SPSS PROCESS macro.

The authors found that safety coaching does not directly affect work engagement. It is only when safety coaching is perceived to be effective or appropriate and/or invokes organizational trust that it significantly affects organizational members' work engagement.

This study motivates practitioners to adopt safety coaching by highlighting the benefits that it has to offer beyond safety-related behavior. Moreover, this study discusses mechanisms that can aid organizations in facilitating organizational trust and satisfaction with corporate philanthropic COVID-19 response among employees.

This is one of the first studies that examines the spillover effect of safety coaching on other work-related outcomes. It also uncovers novel antecedents of satisfaction with corporate philanthropic COVID-19 response and organizational trust.

Nowadays, the competition is not only emerging from within the banking sector, but nonbanking companies like nonbanking financial companies (NBFCs) and FinTech are also growing in size and numbers, offering innovative financial products and services, giving a stiff competition to Indian banks. Thus, this study aims to investigate whether competition from within and outside the banking sector enhances or reduces the financial stability of the banking industry.

The study uses Herfindahl–Hirschman index to measure market share and Z score to measure financial stability. The study further examines the role of NBFCs and FinTech companies in impacting the financial stability by introducing variables like innovation, cybercrimes, systemically important institutions, etc. Thereafter, panel regression has been applied.

Empirical results show a positive relation of market share with financial stability, implying that increased competition in the Indian banking industry erodes the market power, adversely affecting the profit margins which encourages banks to take more risk and which may impact financial stability. The study shows a positive impact of innovation on financial stability which implies that the competition is acting as an enabler for banks. The authors find a negative relation of systemic important NBFCs with financial stability. The authors observe a negative association of cybercrimes with financial stability, reflecting that competition emerging from FinTech sector has exposed banks to new risks.

The policymakers should make sure that the competition of banks with other financial institutions, such as FinTech sector, remains healthy; otherwise, it can jeopardize the entire financial system. It is for the policymakers to define a boundary for FinTech sector, as the development of this sector has exposed the banking industry to new kinds of risks potential to create financial instability. The banks should do a comprehensive check on the company to which it is granting loans, and the government should amend laws. Though big banks have huge potential, consolidations can pose challenges at a macroeconomic level.

FinTech firms are a new entrant in the financial world which are providing immense competition to the banking sector, and thus radically changing the entire financial system. Therefore, it is extremely vital to study and explore the role of NBFCs and the FinTech industry as the main variable to analyze bank competition, which to the best of the authors’ knowledge is completely missing in the previous studies.

Nature’s evolution has shaped intelligent behaviors in creatures like insects and birds, inspiring the field of Swarm Intelligence. Researchers have developed bio-inspired algorithms to address complex optimization problems efficiently. These algorithms strike a balance between computational efficiency and solution optimality, attracting significant attention across domains.

Bio-inspired optimization techniques for feature engineering and its applications are systematically reviewed with chief objective of assessing statistical influence and significance of “Bio-inspired optimization”-based computational models by referring to vast research literature published between year 2015 and 2022.

The Scopus and Web of Science databases were explored for review with focus on parameters such as country-wise publications, keyword occurrences and citations per year. Springer and IEEE emerge as the most creative publishers, with indicative prominent and superior journals, namely, PLoS ONE, Neural Computing and Applications, Lecture Notes in Computer Science and IEEE Transactions. The “National Natural Science Foundation” of China and the “Ministry of Electronics and Information Technology” of India lead in funding projects in this area. China, India and Germany stand out as leaders in publications related to bio-inspired algorithms for feature engineering research.

The review findings integrate various bio-inspired algorithm selection techniques over a diverse spectrum of optimization techniques. Anti colony optimization contributes to decentralized and cooperative search strategies, bee colony optimization (BCO) improves collaborative decision-making, particle swarm optimization leads to exploration-exploitation balance and bio-inspired algorithms offer a range of nature-inspired heuristics.

A large number of organisations are moving towards adopting Industry 4.0 (I4.0), and simultaneously, the emphasis on attaining sustainability development goals is also increasing. Hence, it is imperative to understand the interplay between I4.0 and sustainability. However, the literature addressing the same is still in infancy. Accordingly, the purpose of this study is to fill this gap in the literature by exploring the potential sustainability impacts of I4.0 on the organisations and society in terms of sustainability risks.

To gain an understanding of sustainability aspects in the I4.0 context, relevant literature is gathered using Scopus and Web-of-Science database. An in-depth review of 51 research papers is performed to determine the sustainability risks associated with I4.0.

From the study, a total of 16 sustainability risks are identified, and I4.0 sustainability risk taxonomy is developed. The proposed taxonomy extends the sustainability implications of I4.0 beyond the triple bottom line umbrella and includes the organisational perspective as well. Furthermore, the study provides future research avenues to scholars by positing five potential research questions under different risk management stages.

The study provides an understanding of sustainability risks associated with the adoption of I4.0. The findings will help practitioners streamline their production and operation processes by finding out possible solution to the sustainability risks of their smart factories in advance. The present research will act as a stepping stone towards I4.0 sustainability. The proposed research questions will assist the future researchers in extending the field of I4.0.

To the best of the authors’ knowledge, this is one of the first studies to address the topic of sustainability risks in the context of I4.0.

This research integrates maintenance planning and production scheduling from a green perspective to reduce the carbon footprint.

A mixed-integer nonlinear programming (MINLP) model is developed to study the relation between production makespan, energy consumption, maintenance actions and footprint, i.e. service level and sustainability measures. The speed scaling technique is used to control energy consumption, the capping policy is used to control CO2 footprint and preventive maintenance (PM) is used to keep the machine working in healthy conditions.

It was found that ignoring maintenance activities increases the schedule makespan by more than 21.80%, the total maintenance time required to keep the machine healthy by up to 75.33% and the CO2 footprint by 15%.

The proposed optimization model can simultaneously be used for maintenance planning, job scheduling and footprint minimization. Furthermore, it can be extended to consider other maintenance activities and production configurations, e.g. flow shop or job shop scheduling.

Maintenance planning, production scheduling and greenhouse gas (GHG) emissions are intertwined in the industry. The proposed model enhances the performance of the maintenance and production systems. Furthermore, it shows the value of conducting maintenance activities on the machine's availability and CO2 footprint.

This work contributes to the literature by combining maintenance planning, single-machine scheduling and environmental aspects in an integrated MINLP model. In addition, the model considers several practical features, such as machine-aging rate, speed scaling technique to control emissions, minimal repair (MR) and PM.

The surge in coronavirus disease (COVID-19) cases in India raises the need to study the variables that affect product and category choices, consumer buying preferences and consumrs' future spending. The purpose of the research is to analyse the purchasing behaviour of Indian consumers with regard to health and hygiene products, taking into consideration the impact of the current pandemic crisis.

Using purposive sampling criteria, a web-based questionnaire was circulated and a total of 411 responses were received.

The results assert that variables such as awareness of social distancing, brand-cause fit, word-of-mouth (WOM) publicity, altruist attribution, perceived usefulness and social norms have significant impact on trust and perceived values, which ultimately leads to consumer's purchase intention towards health and hygiene products. In addition, the model detects the moderating role of health consciousness.

The empirical findings will help marketers in designing their strategies to enhance consumer purchase intention with regard to health and hygiene products in the current pandemic situation.

The study enriches the emerging literature with regard to the impact of COVID-19 on health and hygiene products retailing.

The major objective of this research work was to evaluate various physico-chemical characteristics, such as, chemical composition, antioxidant capacity, objective color and texture profile analysis (TPA) of the wheat flour/chickpea flour (CF) blends, so that nutritious baked products could be consumed by the type-2 diabetic persons.

Wholegrain wheat flour (WGF) and white wheat flour (WWF) were substituted with CF at 0 to 40% levels. These wheat flour/CF blends were analyzed for proximate composition, the prepared dough and baked breads were tested for objective color, antioxidant capacity as trolox equivalent antioxidant capacity (TEAC), malondialdehyde (MDA) and total phenolic content (TPC) and TPA.

WGF had the highest TEAC (117.42 mM/100g) value, followed by WWF (73.98 mM/100g) and CF (60.67 mM/100g). TEAC, MDA and TPC values varied significantly among all the three flour samples.

Inclusion of whole chickpea (without dehulling) flour in such type of blends would be another interesting investigation during the future research studies.

These research findings have a great potential for the production of these baked products for human consumption on an industrial scale.

Production of breads using wheat flour and CF blends would benefits the consumers.

Production of Arabic and pan breads using wheat flour and CF blends would, therefore, combine the benefits of both the needed proteins of plant origin and the health-promoting bioactive compounds, in a most sustainable way for the consumers.