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The goal of this paper is to use the stimulus-organism-response (S-O-R) paradigm to understand how ineffective marketplace stimuli affect perceptions related to online travel package booking, which in turn cultivate various types of confusion, and how these confusions are channelled into behavioural dispositions of consumers, such as negative electronic word-of-mouth (eWOM). It also aims to investigate the moderating effects of gender and technology self-efficacy for the suggested framework.

A sample of 437 participants who had recently booked an online travel package, underwent an analysis using a survey study design. Structural equation modelling with multigroup analysis was used to evaluate the hypotheses and the moderation effect.

The findings suggest that inefficient market stimulus results in various forms of confusion, further contributing to negative eWOM. The results also imply that technology self-efficacy lessens the effect of various confusions on adverse eWOM, and gender is found to have a moderating effect on the relationships between ineffective marketplace stimuli, confusion and negative eWOM.

The research offers tourism and hospitality management advice on how to deal with inefficient marketplace stimulation to lessen confusion, which then reduces unfavourable eWOM. Additionally, the moderate impact of technology self-efficacy and gender established through the current study has important ramifications from a tourism managers' perspective.

This study develops and validates an empirical model, which will be utilised as a framework to fully understand consumer confusion brought on by ineffective marketplace stimulation, which causes adverse eWOM. The study also gives new perspectives on the moderating roles of gender and technology self-efficacy, which have received little attention in earlier studies.

The authors' research examines how negative electronic word-of-mouth (e-WOM) alters focal customers' post-recovery justice perceptions and attitudes to determine their future behavior with the service provider. Specifically, this paper develops and tests a conceptual model to investigate how negative e-WOM alters focal customers' perceptual and attitudinal outcomes after the service recovery experience. It also examines the post-recovery effect of negative e-WOM on focal customers’ willingness to patronize the service after their recovery experience.

To test the hypotheses, two pretests and two experimental studies with created scenarios in the retail context were conducted.

The authors' findings reveal that services are judged during and well beyond failure and recovery occurrences. To maintain a loyal customer base, service managers should develop processes that address service complaints both within and beyond the service consumption stage. The authors also find that despite a favorable recovery, focal customers gravitate toward the failure experience and develop unfavorable attitudes toward the service provider, leading to likely defections.

The authors' research demonstrates the persuasive power of negative e-WOM at the post-service recovery stage, making a unique contribution to the service recovery literature. This research also contributes to the persuasive effect of negative e-WOM, demonstrating message context as a boundary condition of negative e-WOM effects. In general, the authors' work highlights the importance of understanding the psychological processes involved in eliciting the persuasive influence of negative e-WOM in the post-service recovery stage that may lead to the defection of “so-called” successfully recovered customers.

This study aims to address the adoption issues of green and sustainable practices in the hotel industry. The study identifies critical performance indicators (CPIs) and utilizes Hotel Carbon Management Initiative (HCMI) framework to prioritize CPIs for achieving a robust adoption framework for green and sustainable practices.

The hotel industry is driven by changing ecological degradation, and it is necessary to achieve feasible development goals. This research article formulates the CPIs derived from HCMI and decision-making model is created using the Analytic Hierarchy Process (AHP).

In this research, CPIs of HCMI are considered and aim to formulate five major CPIs of HCMI, namely air pollution, energy efficiency, water conservation, noise pollution and waste management. The study identifies the need for better control and sustainable growth in the Indian hotel industry with minimum carbon emissions coupled with the green approach adoption.

The CPIs work on minimization of risks and maximizing optimality of return on investment. The development of the hotel industry will be improved and immensely welcomed by capping the carbon emission with the green initiatives. This research is limited as urban hotels are surveyed in this study.

This work makes a valid argument to establish HCMI as a model initiative for environment quality improvement and further extension of other activities in the hospitality sector and scale-up sustainable practices for future-ready circular economies.

Purpose: The study aims to explore the wider acceptance of blockchain technology and growing faith in this technology among all business domains to mitigate the chances of fraud in various sectors.

Design/Methodology/Approach: The authors focus on studies conducted during 2015–2022 using keywords such as blockchain, fraud detection and financial domain for Systematic Literature Review (SLR). The SLR approach entails two databases, namely, Scopus and IEEE Xplore, to seek relevant articles covering the effectiveness of blockchain technology in controlling financial fraud.

Findings: The findings of the research explored different types of business domains using blockchains in detecting fraud. They examined their effectiveness in other sectors such as insurance, banks, online transactions, real estate, credit card usage, etc.

Practical Implications: The results of this research highlight (1) the real-life applications of blockchain technology to secure the gateway for online transactions; (2) people from diverse backgrounds with different business objectives can strongly rely on blockchains to prevent fraud.

Originality/Value: The SLR conducted in this study assists in the identification of future avenues with practical implications, making researchers aware of the work so far carried out for checking the effectiveness of blockchain; however, it does not ignore the possibility of zero to less effectiveness in some businesses which is yet to be explored.

This paper aims to investigate the short- and long-run influence of core banking solutions (CBSs) on productive efficiency and identify the presence of potential network externalities arising from CBS adoption. This paper further examines the differential behaviour of long-term effects across the banking structure.

This study uses a panel data set of Indian commercial banks from 2005 to 2021. Economic efficiency is quantified using VRS-based DEA programming algorithms. Productivity changes are measured through an input-oriented, DEA-based Malmquist productivity index. Short- and long-run effects are examined through a finite autoregressive distributed lag model, estimated through a pooled mean-group estimator.

Findings suggest that CBS adoption negatively correlates with cost structure until the first year of adoption. Nevertheless, significant benefits are visible from the third year. Furthermore, such associations are highly susceptible to the industry structure. CBS results in higher incremental benefits for private banks vis-à-vis state-owned banks. Large banks receive significant and quicker productivity improvements from CBS vis-à-vis small banks. Bank age guides CBS–performance associations, highlighting that mature banks may face the issue of legacy infrastructure in CBS adoption. The resultant networking externalities are significant as they enhance the attractiveness of the network, which subsequently augments inter-branch and inter-bank communications.

To the best of the authors’ knowledge, this study is the first to recognise the stickiness of one of the most homogeneously adopted technological innovations in the Indian banking sector. The presence of a conjoint technological network has the potential to enhance the service delivery process and ensure superior returns for Indian banks.

This paper investigates how the channel leadership strategies develop a post-coronavirus disease (COVID-19) resilient agri-supply chain, which reduces supplier and retailer's price loss and enhances the logistics service quality level considering logistics outsourcing of agri-product especially for the rapidly changing market condition.

Based on the classical leadership theory, two channel leadership strategies, i.e. LPL and SL, are considered. The proposed framework first derives the equilibrium price and service quality level decision among the supplier, the logistics provider and the retailer. Then it compares both leadership strategies in terms of the equilibrium prices and service quality theoretically. This article also presents a case study of Arabian dates pricing and supply chain to test the theoretically derived propositions.

Selection of suitable leadership strategy is a critical factor for profit maximization of the supply chain drivers and proper optimization of equilibrium price and service quality. Here, the product's quality and the market's socio-economic condition play an important role in selecting a suitable leadership strategy. A random transformation of the physical market to an e-commerce portal creates a wide variation of the market's socio-economic parameters, affecting the equilibrium pricing and the logistics provider's service quality.

This study proposes a post-COVID-19 resilient agri-supply chain framework considering price and quality-dependent stochastic market demand, incorporating a wide range of socio-economic factors in the model to counteract the effect of rapid behavior change of agri-market due to COVID-19 norms. This research examines the effect of different channel leadership strategies to facilitate suitable decisions on prices and service quality and retrieve the profit of the supplier, retailer and logistics provider. The future models can incorporate competitiveness in logistics outsourcing, fourth-party logistics (4PL) and contract farming in the agri-supply chain. Each of the extensions can open avenues in different directions.

As the post-COVID-19 market and the customer behavior is randomly changing, and the traditional market is rapidly converting into supermarkets and e-commerce portals, this paper examines the model with a wide variety of e-commerce portals with multi-variation of product. It is conclusive that the product's quality and the market's socio-economic behavior significantly impact the equilibrium decision. The drivers of the supply chain must take them into account before choosing a particular channel leadership strategy.

This study considers a multi-product and multi-market (e-commerce) model by integrating a wide variety of products and the market's socio-economic parameters. The model is tested in a price and quality-dependent stochastic market condition, contributing to the literature by reconciling two different channel leadership strategies into the global logistics of fresh agri-product.

The present study assesses the commercial bank profit efficiency and its relationship to banking sector competition in a rapidly growing emerging economy, India from 2009 to 2019 using stochastic frontier analysis (SFA).

Lerner indices, conventional and efficiency-adjusted, quantify competition. Two SFA models are employed to calculate alternative profit efficiency (inefficiency) scores: the two-step time-decay approach proposed by Battese and Coelli (1992) and the recently developed single-step pairwise difference estimator (PDE) by Belotti and Ilardi (2018). In the first step of the BC92 framework, profit inefficiency is calculated, and in the second step, Tobit and Fractional Regression Model (FRM) are utilized to evaluate profit inefficiency correlates. PDE concurrently solves the frontier and inefficiency equations using the maximum likelihood process.

The results suggest that foreign banks are less profit efficient than domestic equivalents, supporting the “home-field advantage” hypothesis in India. Further, increasing competition drives bank managers to make riskier lending and investment choices, decreasing bank profit efficiency. However, this effect varies depending on bank ownership and size.

Literature on the competition bank efficiency link is conspicuously scant, with a focus on technical and cost efficiency. Less is known regarding the influence of competition on bank profit efficiency. The article is one of the first to examine commercial bank profit efficiency and its relationship to banking sector competition. Additionally, the study work represents one of the first applications of the FRM presented by Papke and Wooldridge (1996) and the PDE provided by Belotti and Ilardi (2018).

Amidst the backdrop of a wide array of structural developments that have revolutionized the competitive landscape of Indian commercial banking, this paper aims to empirically examine the role of two external monitoring mechanisms – competition and concentration on financial stability and further highlights the significance of bank-level heterogeneity in the nexus.

The study uses the Lerner index, defined through a translog specification, as a measure of market power. A system generalized method of moments technique accounts for the dynamic associations among the competition-concentration-stability nexus. The study further examines the moderating effect of ownership, size and capitalization on the nexus. The study also uses the Boone indicator and comments on the competition-bank stability relationship after controlling for bank governance.

The findings indicate that banks are less stable in a more competitive and higher concentrated environment. Exploring bank-level heterogeneity, first, the authors report that as competition increases, state-owned banks have greater incentives to undertake risky activities than private and foreign banks, which point to implicit sovereign guarantees that characterize the former. Second, the authors document an adverse influence of competition on the soundness of larger banks consistent with the “too-big-to-fail” assertion. Third, results corroborate the disciplinary role of regulatory capital and lend support to stricter capital norms under Basel III in a more competitive environment.

This paper is perhaps the first to capture competition and concentration in a single model; to reconcile conflicting evidence on competition-risk nexus; to shed light on the joint effect of competition and Basel accords for Indian banks.

The global non-attainment of the Sustainable Development Goal (SDG) 5 indicates the issue of rising gender inequality. Educated women shying away from the labor force is worsening it. The labor market dynamics might shape the female labor force participation (FLFP). The present study recommends a policy framework by analyzing this dynamism across 125 countries over 1990–2020.

The Two-step System Generalized Method of Moments is used to address endogeneity bias. Dynamism in policy environment is captured by relaxing the Ceteris Paribus condition in the empirical model.

Results show that the moderation of labor market factors has increased with the attainment of Secondary and Tertiary Education. Results also highlight that these factors promote FLFP through prospective opportunities but also hinder female participation through employer’s discrimination despite educational attainment.

Studies have examined the role of education on FLFP. However, prior research has not investigated the role of labor market factors in influencing the impact of education on FLFP. The consideration of these factors will help in addressing the global policy lacuna by recommending a policy framework for enhancing FLFP through internalization of the externalities exerted by the labor market factors, and thereby, help the countries attaining the SDG 5 objectives.

This study aims to analyze the existing literature in human resource analytics and highlights the future research agenda and trends in the same context. It deals with evaluating regional distribution, identifying key authors, publications, journals and keyword occurrences while examining current literature.

A total of 127 articles exported from the Scopus database were systematically analyzed using bibliometric analysis through VOSviewer, including performance analysis and science mapping of the literature studied.

This research postulates the inconsistency between the number of publications and citations received by an author. There was an increase in collaborative research over the years. Human Resource Management Review was regarded as the most influential journal with maximum citation. Maximum publications came from Asian countries. The study revealed that the author with maximum citation were mostly the first authors of the most cited documents.

This research may be beneficial for both researchers and human resource (HR) practitioners because it identifies the research gaps and research needs in the HR analytics domain. Besides, this study recognizes the patterns in HR analytics literature that helps researchers better understand the subject area.

This research incorporates bibliometric analysis for analyzing HR analytics literature to establish a more exhaustive and systematic understanding of the research area. This research contributes to the existing body of literature and assists fellow researchers in future studies.