Automated chatbots powered by artificial intelligence (AI) can act as a ubiquitous point of contact, improving access to healthcare and empowering users to make effective decisions. However, despite the potential benefits, emerging literature suggests that apprehensions linked to the distinctive features of AI technology and the specific context of use (healthcare) could undermine consumer trust and hinder widespread adoption. Although the role of trust is considered pivotal to the acceptance of healthcare technologies, a dearth of research exists that focuses on the contextual factors that drive trust in such AI-based Chatbots for SelfDiagnosis (AICSD). Accordingly, a contextual model based on the trust-in-technology framework was developed to understand the determinants of consumers' trust in AICSD and its behavioral consequences. It was validated using a free simulation experiment study in India (N = 202). Perceived anthropomorphism, perceived information quality, perceived explainability, disposition to trust technology, and perceived service quality influence consumers' trust in AICSD. In turn, trust, privacy risk, health risk, and gender determine the intention to use. The research contributes by developing and validating a context-specific model for explaining trust in AICSD that could aid developers and marketers in enhancing consumers' trust in and adoption of AICSD.

Automated chatbots powered by artificial intelligence (AI) can act as a ubiquitous point of contact, improving access to healthcare and empowering users to make effective decisions. However, despite the potential benefits, emerging literature suggests that apprehensions linked to the distinctive features of AI technology and the specific context of use (healthcare) could undermine consumer trust and hinder widespread adoption. Although the role of trust is considered pivotal to the acceptance of healthcare technologies, a dearth of research exists that focuses on the contextual factors that drive trust in such AI-based Chatbots for SelfDiagnosis (AICSD). Accordingly, a contextual model based on the trust-in-technology framework was developed to understand the determinants of consumers' trust in AICSD and its behavioral consequences. It was validated using a free simulation experiment study in India (N = 202). Perceived anthropomorphism, perceived information quality, perceived explainability, disposition to trust technology, and perceived service quality influence consumers' trust in AICSD. In turn, trust, privacy risk, health risk, and gender determine the intention to use. The research contributes by developing and validating a context-specific model for explaining trust in AICSD that could aid developers and marketers in enhancing consumers' trust in and adoption of AICSD.

This study deals with airlines' handling of customer complaints pre- and post-Covid 19. Authors extracted airlines' responses regarding redress, timeliness, apology, credibility, facilitation, and attentiveness and analyzed them pre- and post-pandemic. The results indicate the differential impacts of organizational responses on recovery satisfaction pre- and post-pandemic. Attentiveness (timeliness) had a significant role only pre- (post-) pandemic. Redress, credibility and facilitation remained crucial in both scenarios. Further, pre-pandemic results showed that the impact of organizational responses (credibility, timeliness, and facilitation) on recovery satisfaction was greater for failures associated with core rather than augmented elements of airline service. In the post-pandemic scenario, the impact of organizational responses on consumers' recovery satisfaction was the same for both categories of service failures. Thus, post-pandemic, airlines may emphasize redress, credibility, timeliness, and facilitation responses in their social media posts for both service failure types.

We attempt to study the psycho -social conditions of people during the COVID-19 and observe the conditions of distress, which are closely associated to each other. Using incidence analysis and grey theory, we examined uncertainty with various psycho -social conditions, indicating stress, anxiety, depression, sleep impairment, stigma issues, other psychiatric issues, and social needs reported across the 14 districts of Kerala, as a case. On critical analysis of the results, we have observed that different psycho -social conditions of distress are mostly closely associated. Anxiety appears as the psycho -social condition, which is observed to having the highest degree of incidences to other conditions. And, stigma issues show second highest degree of incidences, as observed from the study. Observing from the results, anxiety, at a higher level can be a reason for various other psycho -social conditions and is needed to have urgent attention, if not can lead to several conditions of phobia, panic disorder, social anxiety disorder, and obsessive -compulsive disorder during the time of the COVID-19 pandemic. Based on the proposed six incidence sequences, we measure the geometric pattern of their developmental tendencies and propose suggestions for doctors and health practitioners.

Research Question/IssueThis paper primarily explores the relationship between busy boards and firm performance. Additionally, we have performed a quasi-natural experiment to evaluate the impact of SEBI regulatory restrictions on multiple directorships on the firm performance.Research Findings/InsightsThe study sample includes all firms listed on the National Stock Exchange (NSE) and Bombay Stock Exchange (BSE). Our primary findings indicate a nonlinear relationship between busy boards and firm performance. These results are more pronounced for the non-business group firms and firms with high promoter ownership. Our quasi-natural experiment results indicates that the treatment firms had a significant improvement in firm performance. The results of event study analysis and difference-in-difference analysis are robust for both short- and long-term measures of firm performance. Furthermore, we observe an increase in the board meeting attendance of independent directors in the post-mandate period.Theoretical/Academic ImplicationsTwo competing views prevalent in busy board literature are reputational effect hypothesis and distraction effect hypothesis. Our findings support the limit on number of outside directorships; if this number exceeds a certain threshold, the directors become less effective monitors and exacerbate the firm performance.Practitioner/Policy ImplicationsThe results are in favor of restriction on multiple directorship positions of independent directors by the regulators in emerging markets. Further, the study demonstrates that firms that adhere to good governance practices protect the investors' interests and improve the firm's performance.

We connect business group research with literature on competitive repertoire-a firm's portfolio of actions that characterize its strategy-to examine the influence of business group affiliation on firm strategy. We theorize that access to a larger stock and a broad range of resources, both within the firm and through the business group network, enables affiliate firms to execute a higher number (competitive repertoire intensity) and a wider variety (competitive repertoire complexity) of competitive actions. Our analysis of a sample of Indian firms during 2009-2017 supports our hypotheses. In supplementary analyses, we find that business group characteristics-size and affiliate intra-group position-positively influence competitive repertoire. We also find that competitive repertoire intensity mediates affiliation-firm performance relationship. Our findings enhance our understanding of business groups by establishing the link between affiliation-firm strategy-performance. Our work also extends research on network-based and ownership-based antecedents of competitive repertoire. We discuss these implications in detail.

To combat emissions from transportation sector, India is transitioning to a zero or low carbon emission transportation paradigm by encouraging the use of hydrogen fuel cars and electric vehicles (EVs). The study aims to investigate the challenges impeding the adoption of electric vehicles and to understand the causal relations among them. The novel Grey Influence Analysis (GINA) methodology has been utilised to study the causal relations among the challenges and managers and practitioners are benefitted as they are able to identify the most important challenges in the adoption of EVs in India and act accordingly. The findings of a survey-based study show that lack of charging infrastructure comes in second place and the reliability and lifespan of EV components come in first place, when evaluating the overall or total influence scores. The third place among the most important drivers is occupied by lack of servicing/workshops, low awareness of battery characteristics, high upfront cost, and fear of battery explosions. On detailed analysis of the driving forces for adoption, it is apparent that the reliability and lifespan of EV components is the most important driving factor for adoption; hence, policy makers and practitioners can focus on this for augmenting the adoption rates.

PurposeThis study aims to investigate the co-volatility patterns between cryptocurrencies and conventional asset classes across global markets, encompassing 26 global indices ranging from equities, commodities, real estate, currencies and bonds.Design/methodology/approachIt used a multivariate factor stochastic volatility model to capture the dynamic changes in covariance and volatility correlation, thus offering empirical insights into the co-volatility dynamics. Unlike conventional research on price or return transmission, this study directly models the time-varying covariance and volatility correlation.FindingsThe study uncovers pronounced co-volatility movements between cryptocurrencies and specific indices such as GSCI Energy, GSCI Commodity, Dow Jones 1 month forward and U.S. 10-year TIPS. Notably, these movements surpass those observed with precious metals, industrial metals and global equity indices across various regions. Interestingly, except for Japan, equity indices in the USA, Canada, Australia, France, Germany, India and China exhibit a co-volatility movement. These findings challenge the existing literature on cryptocurrencies and provide intriguing evidence regarding their co-volatility dynamics.OriginalityThis study significantly contributes to applying asset pricing models in cryptocurrency markets by explicitly addressing price and volatility dynamics aspects. Using the stochastic volatility model, the research adding methodological contribution effectively captures cryptocurrency volatility's inherent fluctuations and time-varying nature. While previous literature has primarily focused on bitcoin and a few other cryptocurrencies, this study examines the stochastic volatility properties of a wide range of cryptocurrency indices. Furthermore, the study expands its scope by examining global asset markets, allowing for a comprehensive analysis considering the broader context in which cryptocurrencies operate. It bridges the gap between traditional asset pricing models and the unique characteristics of cryptocurrencies.

Prior research has primarily concentrated on non-digital and process-oriented methods for achieving carbon neutrality (CN) in the context of mitigating climate change (CC), while the potential of digital technology (DT) has hardly been investigated. This study addresses this gap by answering four research questions: How are firms utilizing DT to achieve CN? What drives the adoption of DT for achieving CN? What are the barriers that prevent the adoption of DT for achieving CN? What risk mitigation strategies can be adopted by firms to overcome these barriers? An inductive method using open-ended essays has been adopted to gather data from firms that have already implemented DT for CN. The findings revealed four distinct dimensions. Utilization of DT for CN includes enhancing business value, managing one's carbon footprint, enabling smart solutions, and enhancing efficiency. The drivers for adopting DT for CN included driving business growth, external pressures, competitive advantage, and environmental consciousness. Key barriers included financial barriers, technological barriers, human resource barriers, and external barriers. Risk mitigation strategies included pre-implementation strategies, detailed planning and evaluation, ensuring employees' buy-in and readiness, and external stakeholder engagement. This study offers a broad-based foundation for designing DT strategies for achieving CN.

PurposeThis study investigates the impact of pre-IPO earnings management on investor demand in the Indian IPO market. It also examines whether earnings management by issuer firms affects IPO valuation, a topic that is underexplored in accounting research.Design/methodology/approachThe study uses the data of 310 IPOs from India during the period 2000-2021. The association between pre-IPO earnings management with investor demand and valuation is tested using cross-sectional ordinary least squares regression models with heteroscedasticity-robust standard errors.FindingsThe study finds that the degree of pre-IPO earnings management impacts retail investor demand, measured as their over-subscription multiple. Pre-IPO earnings management is unrelated to institutional investor bidding. Further, this paper suggests no relation between pre-IPO earnings management and IPO valuation.Research limitations/implicationsFuture studies could explore various other forms of earnings management and their impact on investor demand and valuation.Practical implicationsThe findings of this study will help the investors and regulators to understand the practice of earnings management among IPO firms and how it is related to IPO demand and valuation.Originality/valueThis study contributes to the existing literature on IPO-earnings management and investor demand by documenting that issuer firms engage in earnings management to influence investor demand, particularly retail investor demand. Analysis of IPO valuation reveals that earnings management is mostly unrelated to IPO valuation, contrary to the general perception in the literature.

PurposeThis paper aims to examine the relationship between earnings quality and corporate cash holdings in an emerging economy. Existing literature posits that earnings quality is a result of information asymmetry and firms with lower earnings quality increases cash holdings, to shield the firm from future uncertainties. In this paper, the authors propose a 'private benefits hypothesis', which suggests that lower earnings quality is an indicator of opportunism and expropriation of resources in the firm, through tunneling or excessive executive compensations. As a result, firms with lower earnings quality increase cash holdings in their control, to increase their private benefits and to avoid the scrutiny of the external stakeholders. The authors further examine the monitoring role played by institutional investors on cash holdings, with varying degrees of earnings quality.Design/methodology/approachThis study uses an unbalanced panel data sourced from Prowessdx, from 2000 to 2019. The analysis employs 20,231 firm-year observations from 2,421 firms. Earnings quality is calculated following Dechow and Dichev (2002).FindingsEmpirical analysis confirms that the firms with higher earnings quality reduce cash. Further, institutional investors reduce the cash holdings in firms with higher earnings quality. Institutional investors effectively reduce the cash only in firms with at least 10% of equity shareholding. The results are robust to alternative measures of earnings quality and endogeneity concerns.Originality/valueThis study diverges from the information asymmetry hypothesis in the existing literature on earnings quality and cash holdings and highlights the underlying private benefits hypothesis, that will impact cash holdings. Next, the 10% institutional shareholding is important in the Indian context as it represents the minimum threshold at which block holders can request extraordinary general meetings (Section 100 of the Companies Act 2013) or the involvement of the National Company Law Tribunal (NCLT) (Section 213 of the Companies Act 2013). This study highlights that unlike in Anglo-Saxon economies, institutional investors or other minority shareholders are empowered by the Companies Act 2013 to play a vital role in corporate governance with a mere 10% equity.

The micro-entrepreneurship sector, as the second-largest employment generator in rural areas, plays a crucial role in alleviating poverty. This study explores how social enterprises can assist rural micro-entrepreneurs in mobilizing and leveraging indigenous knowledge to align production with demand. We propose technoficing as a strategic approach to rural microentrepreneurship. We conducted a case study of CommunityLink, a social enterprise implementing ICT-enabled practices to facilitate the growth of rural micro-entrepreneurship in India. Our findings reveal knowledge disconnections impeding the development of rural microentrepreneurship. Importantly, we propose a four-phase approach of technoficing - basic, internal, external, and offline-online - that can effectively mobilize and leverage indigenous knowledge for rural micro-entrepreneurs with minimal resource investment. We synthesize our findings into a comprehensive process model. Our research contributes to the discourse on ICT for development and the emerging academic dialogue on decoloniality by highlighting the significance of empowering local institutions and practices through the strategic use of off-the-shelf technologies. Practitioners and policymakers can leverage our findings to propel indigenous efforts toward rural development and improve rural livelihoods.

PurposeThe main purpose of this paper is to determine the bias-corrected efficiencies and rankings of the selected hotels and restaurants (H&Rs) in India.Design/methodology/approachThe data for the Indian H&R sector are collected from the Prowess database. The bootstrap data envelopment analysis (DEA) based on a constant return to scale (CRS), variable return to scale-input oriented (VRS-IP) and variable return to scale-output oriented (VRS-OP) are applied on H&Rs to obtain the bias-corrected efficiencies.FindingsIt is found that relative efficiencies using basic DEA methods of all the 45 H&Rs of India are overestimated. These efficiencies are corrected using bias correction through bootstrap DEA methods. The bounds for the efficiencies of each H&R are computed using all the adopted methods. All H&Rs are ranked using bias-corrected efficiencies, and the linear trend between ranks suggests that the H&Rs are ranked almost similarly by all the adopted methods.Practical implicationsTo improve efficiency, Indian H&R companies must rethink their personnel needs by enhancing their workforce management capabilities. The government needs to extend more support to this sector by introducing a liberal legislation framework and supporting infrastructure policies.Originality/valueThere is a paucity of studies on H&Rs in India. The current study focused on measuring bias-corrected efficiencies of the selected H&Rs of India. This study is one of the few initiatives to explore bias-corrected efficiencies extensively using the bootstrap DEA method.

Despite crises being a dominant theme in organizational research, little inquiry has been conducted into how small firms built resilience and coped with uncertainties created by the COVID-19 pandemic. In this study, we explore the challenges faced by small firms during this crisis and how they handled it and built resilience. We collected qualitative data using the open-ended essay method to answer our research questions. Findings reveal that small firms encountered challenges that were predominantly related to employees, technology, and liquidity. Three key paradoxes also emerged during the crisis: short-term and long-term performance, efficiency and adaptability, and safety and profit. The findings further revealed that small firms employed digitalization, prior and new knowledge, and leadership to cope with these challenges. By elucidating these challenges and coping strategies, the research contributes to the existing literature on resilience in small firms. Our findings emphasize that the survival prospects of small firms during the COVID-19 crisis depended on understanding potential paradoxes that needed to be resolved and utilizing the coping mechanisms developed to build resilience.

Retailers often sell their own store brands that compete with the national brands. Store brand competition induces the supplier to quote lower wholesale prices for national brands. In multi-period selling environments, retailers may complement this wholesale price reduction by carrying strategic inventories. Hence, store brand carrying retailers face the following dilemma. On the one hand, strong store brand competition might be sufficient to lower the national brand's wholesale price substantially. In this case, the retailer need not carry any strategic inventory. On the other hand, the wholesale price reduction induced solely by store brand competition might not be substantial. In this case, the retailer might want to carry either national brand or store brand strategic inventory to complement the wholesale price reduction. We address the above dilemma by investigating the effect of store brand competition on the strategic inventory decision using a two-period game-theoretic framework. We enhance the current understanding of the retailer's strategic inventory by incorporating the impact of store brand competition. Our analysis reveals that it is never optimal for the retailer to carry store brand as strategic inventory even when the store brand and the national brand are close substitutes. We also find that a store brand selling retailer may become worse off when being endowed with the option of carrying strategic inventory. However, when the holding cost is sufficiently low, we show that the strategic inventory and store brand competition complement each other and benefit the retailer.

PurposeThe objective of this paper is to investigate the effect of working capital efficiency (WCE) and its components on the composite financial performance of a sample of Indian firms.Design/methodology/approachOur sample includes 796 non-financial listed firms from 2015-16 to 2021-22. Sample firms' profitability, liquidity, solvency, cash flow management, and financial and operational leverage have been used to classify them into companies with high composite financial performance (HCFP) and with low composite financial performance (LCFP) by using K-Means Clustering technique. A composite financial performance score (CFPS) of 1 has been assigned to HCFP and 0 to LCFP. We have used logistic regression models with fixed effect to estimate the effect of cash conversion cycle (CCC) and its components, i.e. inventory days, accounts receivable days and accounts payable days on CFPS in the presence of control variables such as growth, leverage, firm size, and age.FindingsThe study finds that CCC and inventory days are inversely associated with CFPS. This finding shows that the firms' WCE leads to superior financial performance on a composite basis.Research limitations/implicationsThe research findings are based on samples drawn from the population of the listed Indian non-financial companies. Since the operation, financial practices, working capital policies, and management styles of firms vary greatly among nations, the results of this study should be extended to firms in other countries after taking into account the degree of resemblance to the sample firms.Practical implicationsThe findings of this study hold significant value for industry practitioners, as they provide guidance in determining the optimal allocation of funds for working capital and devising strategies for effectively managing inventory levels, credit sales, and vendor payments in order to increase the overall value of the company. This study aims to help investors in building their investment portfolios by identifying companies with superior composite financial performance. Investors can enhance the construction of their investment portfolios by strategically selecting companies that demonstrate superior overall performance.Social implicationsThe results of our study will help companies improve their WCM strategies to enhance their overall value, and their significance increases manifold during economic downturns. Business firms that perform well by efficiently managing their working capital have a multiplier effect on the economy and society at large in the form of GDP contribution, labor income, taxes to the government, investment in capital assets, and payments to suppliers.Originality/valueTo understand the impact of WCE on firms' performance, the extant working capital literature focuses on some specific characteristics such as profitability, valuation, solvency, and liquidity. The limitation of employing a single parameter is its inability to present the comprehensive performance evaluation of firms. This study is among the earliest studies that focus on the holistic evaluation of WCE's impact on the composite performance of a company.

This paper aims to conceptualize whether revenge tourism is an apt description of travel in the post global health emergency period from the perspective of travelers. Furthermore, it examines the outcomes of post global health emergency travel. The multiphase work included screening and three phases of qualitative study. Participants perceived the term revenge with skepticism, although the nature of travel and activities and consumption in the post global health emergency have changed for them. In this period, the need for introspection was greater, and travel was a way of rediscovering oneself. Furthermore, participants were negotiating new, different boundaries again after a tumultuous period, which indicated tourism travel was inextricably intertwined with several important aspects of their lives. The most important implication of the study is that it enables us to understand the connectedness between the process by which the post global health emergency phenomenon influences travel and its outcomes.

We observe and analyze the causal relations among risk factors in a system, considering the manufacturing supply chains. Seven major categories of risks were identified and scrutinized and the detailed analysis of causal relations using the grey influence analysis (GINA) methodology is outlined. With expert response based survey, we conduct an initial analysis of the risks using risk matrix analysis (RMA) and the risks under high priority are identified. Later, the GINA is implemented to understand the causal relations among various categories of risks, which is particularly useful in group decision-making environments. The results from RMA concludes that the capacity risks (CR) and delays (DL) are in the category of very high priority risks. GINA results also ratify the conclusions from RMA and observes that managers need to control and manage capacity risks (CR) and delays (DL) with high priorities. Additionally from the results of GINA, the causal factors disruptions (DS) and forecast risks (FR) appear to be primary importance and if unattended can lead to the initiation of several other risks in supply chains. Managers are recommended to identify disruptions at an early stage in supply chains and reduce the forecast errors to avoid bullwhips in supply chains.

PurposeThis study attempts to quantify the degree of independence of Central Bank of India from both legal and behavioural contexts over the period 1990-1991 to 2018-2019, a period encompassing major developments in the operation and regulation of Reserve Bank of India (RBI).Design/methodology/approachWe followed Jasmine et al. (2019) to calculate the magnitude of de jure independence of RBI and for de facto independence, turnover rate (TOR) of CB governor as proposed by Cukierman et al. (1992) is applied.FindingsThe results report that the legal autonomy of RBI increased specifically after the reforms and post formulation of Monetary Policy Committee (MPC). However, the actual independence of RBI remains more or less in line within the critical threshold limit of 0.2.Practical implicationsThe study proposes effective implementation of laws and procedures designed to promote the independence of Central Bank of India imperative for an effective monetary operation along with a coordinated fiscal policy.Originality/valueTargeted study of a particular central bank on its independence aspect in general and of the Reserve Bank of India in particular has not been attempted as on date. It is to this end that the present study contributes.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-02-2023-0098.

PurposeThe author identifies the traits of consumer resilience in emerging markets, classifies these major traits into five categories and analyses the influence relationships among them with distinctive focus on the psychological and personal resilience aspects.Design/methodology/approachThe influence relations among the traits of consumer resilience from an expert perspective were identified with typical focus on electronic supply chains, and later the same was analysed through an intelligent influence modelling method, the grey causal modelling (GCM).FindingsThe major traits were analysed using the GCM, where the cause-consequence relations were observed for various objectives and the situational effects are noted. By constructing a magnitude plot and further a causal magnitude table, the important influence traits of consumer resilience for the considered case were observed and the same were auxiliary validated using an interpretive structural modelling (ISM) based approach.Research limitations/implicationsAs perceived from the results, it is evident that social support and recommendations from customers emerge as the principal influence traits of consumer resilience from an expert perspective, considering the case. The study can be further extended empirically to validate the findings.Practical implicationsAltogether, the author can recommend for practitioners that the influence of family, society, friends, peers as well as ratings from the customers can determine the level of consumer resilience. Hence, practitioners of customer relationship management can focus on improving the product and brand awareness among customers, so that more customers may recommend for typical products.Originality/valueConsumer resilience depend on several factors, where the author has identified 25 major traits of the same and classified them into five major categories, including individual psychological factors, individual attitudes, individual socio demographic factors, micro environmental factors and macro environmental factors and the influence relations among them were studied from an expert perspective.