PurposeService encounters, involving interactions between customers, service providers and other customers within servicescapes, play a critical role in shaping perceptions of inclusion and safety. Despite growing visibility of LGBTQIA+ consumers as a valuable segment, their experiences within servicescapes remain understudied, often filtered through heteronormative assumptions.Design/methodology/approachThis study addresses this gap by examining co-consumption dynamics, the shared use of service spaces by LGBTQIA+ and heterosexual consumers, and how these interactions influence experiences of inclusion and exclusion. Two qualitative studies to explore perceptions of safe spaces and social inclusivity during service encounters from the perspectives of LGBTQIA+ individuals and heterosexual consumers in India. Building on these insights, a conceptual model was developed and empirically tested to examine the influence of heteronormativity and openness to experience on attitudes towards gender neutrality and social inclusion intentions.FindingsThe findings demonstrate that heteronormativity negatively impacts attitudes towards gender neutrality and social inclusion, while openness to experience positively fosters inclusive attitudes and behaviours within co-consumed service settings.Research limitations/implicationsThe study advances service marketing and transformative service literature by illustrating how visible signals of inclusivity, frontline interactions and consumer attitudes intersect to shape equitable and welcoming service experiences.Practical implicationsPractical implications underscore the importance of authentic inclusivity initiatives, including staff training and feedback mechanisms, to foster safe and inclusive servicescapes that enhance consumer participation and satisfaction.Originality/valueThis research contributes to the growing body of literature on inclusive service design, offering practical implications for creating welcoming and equitable service environments that meet the needs of a diverse clientele.

PurposeThis study aims to identify the themes in the existing research on the role of digital technologies in financial inclusion. This study also highlights the important journals, authors and countries leading the research on this topic and points towards the directions for future research.Design/methodology/approachThe study uses a bibliometric analysis on a dataset of 653 articles in high-impact journals collected from Scopus. Science mapping and network analysis on this data are conducted using the Bibliometrix package in R and the VOS Viewer software.FindingsThe literature on the role of digital technologies in financial inclusion has grown exponentially in the last few years, especially in the developing countries. Lack of reliable databases on financial inclusion are an impediment to research. Seven important themes in existing research are identified - antecedents of digital financial inclusion (DFI), impact of DFI on macroeconomic outcomes, consumption patterns and sustainability, banks' stability and risk-taking, environmental impacts of financial technologies, improved access to credit for small businesses and economic geography-based critiques of these technologies.Originality/valueThis is the first bibliometric study on the role of digital technologies in financial inclusion and provides a thematic understanding of existing research clusters. The research gaps on the topic of DFI identified in this study can help drive future academic research.

The study explores patient-to-patient representation of customer-to-customer (C2C) value co-creation within social media health communities. It investigates the influence of online social capital factors on C2C value co-creation behaviours via the sense of belongingness (SOB). The mediating effect of SOB explains the underlying mechanism behind the social capital-C2C value co-creation relationship, which earlier studies ignored. The study also examines the influence of value co-creation on individuals' well-being. A quantitative approach is adopted to examine the relationships, where the surveyed data are tested using structural equation modelling. The analysis shows that social capital dimensions positively influence the individuals' SOB to the community, affecting the C2C co-creation behaviours. Furthermore, among C2C value co-creation behaviours, responsible and helping behaviours positively influence subjective well-being, whereas information sharing does not. Overall, the study contributes to the customer domain of value co-creation by highlighting the antecedents and consequences of C2C co-creation.

The study investigated how environmental regulation, specifically India's National Action Plan on Climate Change (NAPCC) and the subsequent Paris Agreement, affects the environmental and financial performance of Indian manufacturing firms. Employing a quasi-natural experiment approach, the analysis evaluates how these regulations influence compliance costs, access to external financing, and market valuation for highly polluting firms. The results demonstrate that stringent environmental regulations can incentivize firms to adopt sustainable practices through efficiency-oriented compliance strategies such as process upgradation, leading to reduced abatement expenses and improved access to finance at lower costs. These outcomes provide empirical evidence supporting the weak form of the Porter Hypothesis, showing that well-designed regulations can stimulate innovation and efficiency gains, even when formal research and development (R&D)-led innovation remains limited. The findings further show that the Paris Agreement amplified these effects, facilitating long-term value creation and enhancing market legitimacy. Overall, the study contributes to environmental finance and policy discourse by highlighting how national and global environmental frameworks jointly influence firm adaptation, sustainability, and financial resilience.

The article investigates how crisis response strategy is influenced by pre-crisis reputation and country of origin during (COO) during crisis. A quasi-experimental study was undertaken to test this influence in Indian versus Non-Indian countries. Countries with positive national identity can withstand the crisis situation better than one with a negative or neutral identity. Based on the COO, companies can choose a less accommodative crisis response strategy like diminishing rather than rebuilding to quell the crisis impact. It provides an understanding of how crisis managers can select the most appropriate response strategy during crisis.

This qualitative inquiry examines the ways in which the governmentality of 'conducting the conduct' of the farming population contributes to adverse ecological outcomes, such as the widespread practice of stubble burning in neoliberal India, which exacerbates the challenges posed by climate change. The analysis suggests that governmentality, as a governing framework, distorts interactions within the marketing system, leading to misalignments in the motivations of system actors that ultimately contributes to the failure of the system. By focusing on the phenomenon of stubble burning in India, this study highlights the complex interconnections between governmental framework, market forces, and individual actors in agricultural marketing system. The misalignment of these elements is shown to result in negative system outcomes. The qualitative analysis identifies three key themes: the interplay of governmentality, hegemonic commissioning agents, and marginalization of farmers. The study proposes the development of an inclusive 'farm waste' value chain that emphasizes the circularity of agriculture, and fosters equitable sharing of benefits, thereby preserving the regenerative capacities of agricultural systems.

Drawing from institutional theory and behaviour risk agency perspective, we argue that various institutional investors' risk propensity and perception towards emerging market firms' R&D investments are contingent on the institutional context. We examine a longitudinal sample of 11,359 firm-year observations of Indian firms for a period of 20 years (2005-2024) to test the proposed hypothesis. Our findings suggest that pressure-sensitive institutional investors' (PSIIs) ownership negatively impacts R&D investment decisions. The ownership by pressure-resistant institutional investors (PRIIs - mutual funds and foreign institutional investors) positively affects the R&D investment decisions of firms. We also find that firms' export intensity negatively moderates the association between mutual funds (MFs) ownership and R&D investment. In contrast, it positively moderates the association between foreign institutional investors (FIIs) ownership and firms' R&D investment. Our findings have important implications for policymakers in strengthening the environment to protect institutional investors and encourage R&D investments.

PurposeWorkplace loneliness costs enormously to business organizations and has sparked considerable interest among researchers and practitioners in identifying the proximal factors associated with it. Drawing on the conservation of resource perspective, this study aims to examine the impact of bullying experiences through co-worker(s) and supervisor(s) on workplace loneliness. This study further examines emotional exhaustion as an underlying psychological mechanism in the aforementioned relationship.Design/methodology/approachThe multi-wave data was collected from a sample of 281 employees working in the Indian hospitality industry.FindingsThe authors found a significant positive relationship between workplace bullying through supervisor(s) and employees' experiences of loneliness. However, the association between workplace bullying experienced through co-worker(s) and employee's loneliness appeared insignificant. In case of indirect effects, it was found that emotional exhaustion mediated the relationship between workplace bullying through supervisor(s) and loneliness among employees, but demonstrated insignificant effect in case of bullying through co-worker(s) - loneliness relationship.Originality/valueThe study makes an original and meaningful contribution to overall loneliness and negative emotions literature by deepening insights around the consequences and boundary conditions of loneliness in the workplace. Theoretical contributions and managerial implications are discussed.

The article reports on pedagogical interventions designed to integrate the lived realities of impoverished consumer segments into marketing education. Drawing on teaching experiences from the Rural and Inclusive Marketing (RIM) course at an Indian business school, it describes two field-based experiential projects, Ethnographic Story and Unpacking Markets. These projects enabled students to interact directly with impoverished consumers, reducing initial disconnectedness. It also honed ethnographic research skills, cultural sensitivity, and compassion toward marginalized consumer groups. The analysis highlights the importance of sensitization, collaborative and co-creative learning, and narrative-driven outputs in equipping students to critically interpret impoverished consumers' lifeworlds. By engaging students in real-world contexts, the interventions helped cultivate contextual literacy and methodological preparedness, while also addressing gaps in conventional business curricula. More broadly, the study demonstrates how experiential learning can address blind spots in marketing education and enrich understanding of impoverished markets. It further shows how such learning can be implemented to understand other such markets globally and contribute to the development of inclusive marketing strategies aligned with broader goals of equity and social justice.

This study employs a mixed-method approach to examine how firms combine multiple real earnings management (REM) strategies under the performance pressure of meeting earnings benchmarks. Using expert-based modeling and panel data from QUAD countries (the United States, Japan, Australia, and India) between 2003 and 2022, we assess whether REM decisions follow structured, sequenced patterns. Qualitatively, we apply Fuzzy Interpretive Structural Modeling (F-ISM) and MICMAC analysis to map interdependencies among seven EM tools. The resulting framework reveals three dominant paths, shaped by implementation cost, detection risk, and urgency to meet earnings thresholds. Empirically, we estimate REM activities using established REM models (Roychowdhury, 2006; Gunny, 2010; Srivastava, 2019), confirming the prevalence of REM in the post-SOX era. We introduce a novel REM Bundling Index to capture whether firms deploy multiple REM techniques in a given year. Regression results show that firms narrowly meeting benchmarks are significantly more likely to engage in bundling behavior. This study contributes to corporate finance theory by framing REM as a structured, constraint-driven response rather than an isolated act. By linking process modeling with empirical data, we provide a forward-looking diagnostic tool for analysts and regulators monitoring sophisticated forms of financial reporting management.

The study evaluates the appropriateness and effectiveness of covariance-based, consistent and partial least squares structural equation modelling by comparing their outcomes on a proposed conceptual model while examining factors impacting customer loyalty in the Indian hotel industry. Using 382 responses collected through a structured survey, the model was evaluated using SmartPLS and AMOS software packages. The study underscores the superiority of partial least squares in handling non-normal data and small samples. At the same time, covariance-based method is more appropriate for larger samples and factor-based models. A consistent method demonstrates advantages in path coefficients and R-2 values while examining the model. Managerial implications emphasize tailoring different analytical methods to a specific research context. At the same time, researchers are advised to consider study-specific characteristics, such as sample size and model complexity, in their respective research problems. The study has limitations pertaining to the moderate sample size, the absence of control variables and dependency on a specific software. Future research could explore more complex models, incorporate formative constructs and address cross-industry applications. This study contributes to the methodological rigour of structural equation modelling approaches, providing valuable guidance to academics and practitioners in selecting the most appropriate analytical tools.

PurposeFocusing on the commercial surrogacy market in India, this paper aims to examine the symbolic processes of contestation between conflicting institutional logics reflected in surrogate mothers' lived experiences.Design/methodology/approachThe authors phenomenological ethnography that involved collecting data from multiple sources such as participant observation, in-depth interviews, follow-up interviews, personal interactions and field notes. Data analysis has been conducted using the standard procedures of thematic analysis.FindingsThe interpretation of surrogate mother experiences shows that service workers not only combat both the market logic and the stigmatizing logic through the integrative construction of the defensive logic but also weave the premises of these three logics to pursue several strategies of logic reconciliation.Originality/valueThis research sheds light onto the institutional turn in service research through extending a scholarly understanding of the mechanisms of reconciliation between conflicting institutional logics in service settings. It provides a detailed account of processes of the construction and development of institutional logics in the context of morally contentious service milieus, which is important because it enables service managers and public policymakers to gain relevant insights into institutional causes of change in service markets.

PurposeThis study aims to identify the reason for the lack of explanation in present economic theories for the presence of low household savings rates in some high-income countries and high household savings rates in some low-income countries.Design/methodology/approachWe perform a narrative review of the literature on household savings to build a conceptual framework for household savings. Then, we conducted a survey on household finances from US and Indian nationals to understand their motives for savings, their ability to maintain their finances and their present levels of household savings and debt.FindingsIt is found that the present theories and empirical evidence on household savings do not adequately explain the phenomenon of low savings rates found in some high-income countries and the high savings rates found in some low-income countries. We find that the underestimation of the impact of cultural factors on household savings is the most likely reason for the same. A comparative analysis of household finances in the USA and India using a survey provides supporting evidence for the above proposition.Originality/valueThis paper contributes a conceptual framework that shows the impact of cultural factors on the Marginal Propensity to Consume in households. It highlights the connection between cultural factors like Thrift and Long-Term Orientation and the prevailing rates of household savings and debt. The paper provides empirical evidence using primary data from a survey on household finances in the USA and India to support the above findings.

Understanding how anthropomorphic design influences user decision-making is critical as anthropomorphic technologies become more integrated into daily life and work environments. The existing literature on AI-anthropomorphism mainly focuses on physical or voice-based anthropomorphism and its impact on adoption. However, it ignores mind-based (cognitive and affective) anthropomorphism and its impact on users' decision delegation (automated or augmented) to AI-systems. This study examines how mind-based anthropomorphism influences users' decisions to delegate tasks to AI-powered agents, using a survey of 243 actual AI agent users and PLS-SEM for data analysis. Results revealed that users' choice for augmented decision delegation to AI-powered agents is significantly increased by cognitive anthropomorphism. Also, users' choice for automated decision delegation to AI-powered agents is positively influenced by affective anthropomorphism. Trust emerged as a crucial mediator between anthropomorphism and automated decision delegation, encouraging users to hand over the decision-making completely to AI-powered agents. Results also revealed decreased reliance on trust when users prefer to retain a certain level of control in the decision-making process. The study significantly contributes to the literature on human-AI interaction by enhancing the understanding of users' psychology towards anthropomorphism and their choice for decision delegation to AI-powered agents.

PurposeThis study investigates the caste-based disparities in employment probabilities and wage earnings within India's rapidly growing IT industry, using insights from the labour market segmentation theory. Our theoretical conceptualization attempts to pin down the inaccessibility of marginalised sections of the population to the high productivity job market.Design/methodology/approachWe rely on the National Sample Survey rounds of 2011-2012 and 2020-2021 to estimate employment probabilities and wage differentials using linear and logic regression models, controlling for educational attainments and other important determinants of individual's job market outcomes.FindingsThe results indicate a significant -1.24 odds differential, even after considering education and other control variables. Notably, this disparity has increased since 2011-2012, with lower caste graduate pass-outs facing a mere 13% probability of IT sector employment compared to their upper caste counterparts at 41%. Further, our findings expose gender and rural-urban differentials, highlighting the vulnerability faced by females and individuals from rural areas. The wage analysis shows a 24% and a 22% earning gap for SCs and OBCs, respectively, which remain statistically significant even after controlling for educational attainments and employment arrangements.Originality/valueThis is first micro-level study that counters Indian IT sector's claim of castelessness and pro-merit, identifying significant presence of labour market segmentation in the sector. The caste-based labour market segmentation has far-reaching consequences as it can perpetuate income inequalities and hurt industrial efficiency, stifling economic growth in the long-run. Concerted policy responses are imperative to eliminate structural barriers, ensuring equitable access to quality education and employment opportunities for marginalized sections of the society.

Whereas extant literature treats social voice, that is, complaining via brand-managed social media pages, as a mere channel for existing consumer complaining behaviours (CCBs), like voice and negative word of mouth, this research aims to assess it as a distinct CCB. We draw from CCB theory and its associated taxonomies towards this goal. To identify the unique palette of motives and antecedents of social voice, we adopt a mixed-method research design by extracting archival social voice posts and interviewing social voicers across four sub-studies. Our analysis reveals the motives, CCB process stage, antecedents and other peculiarities associated with social voice, thereby demarcating it from other CCBs. Further, social voice is identified as a predominantly secondary-stage CCB, triggered by a blend of constructive and vindictive motivations. This work is among the few examining social voice from a consumer viewpoint and attempts to place it within the overall CCB framework as divergent from its standalone assessments. We thus pave a foundation for examining behavioural changes implied by the Internet and social media within the CCB landscape and provide managerial guidelines towards reducing primary social voice while optimizing its secondary-stage incidence.

Software as-a-service (SaaS) adoption is essential in regulated industry such as capital market to bring in scalability, required to deal with the fluctuations in trading volumes, and agility, required to stay responsive to changing market conditions. In this context, the study examines the factors that the capital market organization look for in adopting SaaS. Based on the perceived risk theory and prospect theory, we propose a perceived risk based IT governance framework in SaaS adoption decision in capital market. Following a case study-based research methodology, we examined the factors that influence the risk perception of the decision makers about SaaS-based solution in a capital market industry. We found that the decision to opt for SaaS adoption in organization depends on (i) the top management's consideration for risk preference, problem framing, decision domain, and data security, and (ii) organizational processes in practice such as IT governance archetype and risk management processes. Based on this, we generate a risk score for a capital market firm to weigh potential benefits and risks in adopting SaaS. In this study, we assume that the top management provides guidance toward firm's risk appetite which is then compared to the generated risk score to decide for SaaS adoption. This study contributes to the technology adoption literature by emphasizing the role of individual risk preferences and problem framing in influencing technology adoption decisions particularly for technologies that pose certain risks. Finally, the study contributes by bringing forth the role of an IT governance framework in assessing SaaS-related risks.

This paper studies a collection centre location problem for e-waste acquisition from households. The proposed location-allocation model is a bi-objective mixed-integer non-linear model that maximises waste collection and minimises the cost of collection. The model considers that both drop-off and pick-up policies are in place, i.e., people can either drop their e-waste at a collection centre or request doorstep pick-up of their e-waste. The model considers that people ' s decision to drop off their e-waste at the collection centres depends on the financial incentive offered by the firm and the distance of the collection centre. However, in the case of pick-up, no incentive is provided, and it is considered that the households ' willingness to return depends on people's concern for environmental degradation. The proposed model decides the location of the collection centre, the assignment of customer nodes, the incentive offered, and the e-waste collected using both pick-up and drop-off methods. Instances generated using a real case of Delhi, India, demonstrate the feasibility and validity of the proposed model, and the epsilon constraint method is employed to handle its multi-objectivity. Furthermore, sensitivity analysis is used to assess the relative importance of the parameters on the model output. The study offers valuable theoretical and practical implications.

The extended and complex nature of agri-food supply chain systems results in food loss and an asymmetrical flow of information. It is vital to integrate the cultivation, harvest, processing, and distribution decisions for designing a sustainable agri-food supply chain to minimize overall cost and create employment opportunities alongside considering global concerns. A multi-objective, integrated, sustainable mathematical model is presented in this study to maximize the revenue and employment generated while reducing the environmental impacts. The criteria for the evaluation of farmlands are derived from literature, and Geographical Information System (GIS) is used to obtain geospatial data to assess the performance of diverse farmlands across various criteria. The farmlands are then assessed and prioritized using the Best Worst Method (BWM). Among all criteria for selecting the farmlands, favorable temperature and land-use have the highest and lowest impact, respectively. Furthermore, a pricing model is proposed to estimate the price in various customer zones. The robust possibilistic model is suggested to take into account weather patterns, transportation costs, and customer zone demand under uncertain situation. The proposed model is illustrated in the Stevia processing plant in Iran and the tradeoffs between different model parameters and objective functions are studied, and the validity of the model is assessed by sensitive analyses. The outcomes show that to meet robustness, the number of active farmlands and warehouses should be increased by about 11%, which imposes a 10% cost on the model. Based on sensitive analysis, increases in production capacity and demand result in a significant rise in the profit function (12% and 16%, respectively), despite the fact that improvements to farmland and warehouse capacity have little effect on profit, indicating the need for managers to prioritize production rate and advertising. Moreover, the results show the best location for planting stevia, the optimum production rate, the proper number of warehouses, and their capacities in each period.

PurposeOver the past two decades, the hub location domain has witnessed remarkable growth, yet no prior study reviewed and synthesised problem formulation and solution methodologies to address real-life challenges. Design/methodology/approachThe current study conducts a comprehensive bibliometric literature review to develop a thematic framework that describes and presents hub location problems. The work employs cluster, bibliometric, and social network analyses to delve into the essential themes. FindingsKey themes include cooperation, coopetition, sustainability, reshoring, and dynamic demand, contributing to the complex challenges in today's hub location problems. As the first work in this field, the study serves as a valuable single-source reference, providing scholars and industry practitioners with key insights into the evolution of hub location research, prominent research clusters, influential authors, leading countries, and crucial keywords. Research limitations/implicationsFindings have significant implications since they highlight the current state of hub location research and set the stage for future endeavours. Specifically, by identifying prominent research clusters, scholars can explore promising directions to push the boundaries of knowledge in this area. Originality/valueThis work is a valuable resource for scholars in this domain and offers practical insights for industry practitioners seeking to understand the hub location problems. Overall, the study's holistic approach provides a solid foundation for advancing future research work in the hub location field.