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Consumers are increasingly choosing social media over other channels and mechanisms for grievance redressal. However, not all social media grievances elicit a response from businesses. Hence, in this research the authors aim to explore the effect of the complainant's social characteristics and the complaint's social and content characteristics on the likelihood of receiving a response to a grievance from the business on social media.

The authors build a conceptual model and then empirically test it to explore the effect of the complainant's characteristics and the complaint's characteristics on the likelihood of response from a business on social media. The authors use data of consumer grievances received by an Indian airline operator on Twitter during two time periods – the first corresponding to lockdown during Covid-19 pandemic, and the second corresponding to the resumption of business as usual following these lockdowns. The authors use logistic regression and the hazard rate model to model the likelihood of response and the response delay, respectively, for social media customer grievances.

Complainants with high social influence are not more likely to get a response for their grievances on social media. While tagging other individuals and business accounts in a social media complaint has negative effect on the likelihood of business response in both the time periods, the effect of tagging regulatory bodies on the likelihood of response was negative only in the Covid-19 lockdown period. The readability and valence of a complaint were found to positively affect the likelihood of response to a social media grievance. However, the effect of valence was significant only in lockdown period.

This research offers insights on what elicits responses from a service provider to consumers' grievances on social media platforms. The extant literature is a plenty on how firms should be engaging consumers on online media and how online communities should be built, but scanty on grievance redressal on social media. This research is, therefore, likely to be useful to service providers who are inclined to improve their grievance handling mechanisms, as well as, to regulatory authorities and ombudsmen.

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 present work has proposed and employed an innovative hybrid method based on the combination of factor analysis and an artificial neural network (ANN) model to forecast customer satisfaction from the identified dimensions of service quality in India, a developing country.

The qualitative study is conducted with Internet banking users to understand e-banking clients' perceptions. The data is collected with the help of a questionnaire from randomly selected 208 customers in India. Firstly, factor analysis was performed to determine the influential factors of customer satisfaction, and four factors i.e. efficiency, reliability, security and privacy, and issue and problem handling were extracted accordingly. The neural network model is then applied to the factor scores to validate the key elements. Lastly, the comparative analysis of the actual ANN and the regression predicted result is done.

The success ability of the linear regression model is challenged when approximated to nonlinear problems such as customer satisfaction. It is concluded that the ANN model is a better fit than the linear regression model, and it can recognise the complex connections between the exogenous and endogenous variables. The results also show that reliability, security and privacy are the most influencing factors; however, problem handling and efficiency have the slightest effect on bank client satisfaction.

This research is conducted in India, and the sample is chosen from the urban area. The limitation of the purposeful sampling technique and the cross-sectional nature of the data may hamper the generalisation of the results.

The conclusions from the study will be helpful for policymakers, bankers and academicians. To our knowledge, few studies used ANN modelling to predict customer satisfaction in the service sector

The present world is captivated by the global challenges of climate change, environmental and ecological degradation, challenges related to migration, inequality, conflict and unrest. The development process failed to appreciate and signify the role of non-value, non-materialistic and altruistic value of both living and non-living natural entities. Thus, a significant disconnect or gap between public policy and human well-being has been observed. The departure of human beings from their true self has also distanced humans from the rest of the species and ecosystem. The essence of altruistic value and its recognition is plausible only through the upliftment and evolution of the inner self. The interconnectivity of the inner and outer world can be perceived through self-evolution. A public policy that is driven by the force of self-enhancement and realization, connecting and synthesizing human and non-human interactions selflessly, is required for revolutionizing the development paradigm. Against this backdrop, Gandhian philosophy that values the individual and his relationship with his true self becomes instrumental in ethical transformation. The self-transformation, manifestation and realization of truth and love are deeply embedded in Gandhian Revolution. Gandhian philosophy is a phenomenal illustration of self-transformation based on self–realization and soul force (Satyagraha) that acts as a driving force for a paradigm shift. Gandhian thoughts recognize the otherness of others (either human beings or nature), embedded in the notion of ‘Sarvodaya’. Based on spiritual inquiry and ethical value judgement, and cosmic interdependence, the Gandhian notion constitutes a building block for a non-violent socioeconomic system guided by empathy and the law of non-possession. The twin models, ‘The trusteeship model’ and ‘Economy of Permanence’, advocate a spiritual inquiry and ethical value judgement in economics and governance. Addressing the economic problem of scarcity and choice, the attributes of decentralization, self-sufficiency and self-reliance envisage that individuals are satisfied with minimum consumption. In addition, non-violence, truth and love create a subsequent balance in ecology and the environment. Ethical responsibility is not just limited to socio-economic and political systems but also integrates environmental and ecological sustainability.

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.