PurposeThis study aims to empirically investigate the factors that impact housing prices in the National Capital Region (NCR), India, using ordinary least squares (OLS) and quantile regression estimation approaches.Design/methodology/approachThe data for the study were collected from various websites of various real estate intermediaries and through discussions with apartment owners' associations in NCR. Quantile regression was used along with OLS to understand the impact of various factors on housing prices using a dataset of 529 residential properties.FindingsThe study findings establish that size, age, number of bathrooms, floor level, security, parking, lift, power backup, waste disposal system and distances from hospital and shopping complexes have a positive impact on housing prices, while the number of rooms, number of balconies, distances from school, metro station and employment zone are established as negative factors for housing prices. The impact is not uniform across all quantiles for some factors. The impact of amenities was established to be the highest in deciding the housing prices in NCR, India.Research limitations/implicationsThe research extends the ongoing empirical research on understanding what impacts the housing prices? by providing empirical evidence on the factors impacting housing prices in an emerging market (India) and a buoyant residential market (NCR). This study will help future researchers explore the other factors impacting housing prices in diverse residential settings in India and globally.Practical implicationsThe study findings provide significant insights to various stakeholders in housing development ecosystems like regulatory bodies, policymakers, builders, designers and homebuyers. The rising demand for houses driven by rural migration towards urban locations is a positive factor for real estate developers. Still, the increased competitive scenario makes it difficult to achieve competitive pricing to attract home buyers. The findings will help the real estate developers understand the factors impacting the housing prices and help them design and structure their house offerings accordingly. Governments also increasingly use public-private partnerships in the affordable housing segment. The study findings will help the planning bodies achieve the right design, amenities and pricing to attract buyers and make their housing societies citizen-friendly.Originality/valueAs per the authors' knowledge, this is the first comprehensive research endeavour to empirically investigate the major factors influencing housing prices in NCR, India.

This paper aims to identify the important risk factors considered by Small and Medium Enterprises (SMEs) in lucrative investment options and also prioritizes and ranks risk factors based on their respective impacts on investment. In addition, we propose a level-wise hierarchical structure model and its interrelationships based on driving power and dependence. A hybrid four-phase methodology was used to address the research objectives. In the initial phase of the literature review, expert opinions and Delphi techniques were used to identify and finalize critical risk factors that impact SMEs' investment opportunities. The Best Worst Method (BWM) was applied to rank to prioritize, and study the relationship with the help of the Interpretive Structural Modelling (ISM), and the MICMAC was used to cluster the critical issues based on their driving power and dependence. Furthermore, a more exhaustive analysis can be conducted on the earnings and disposition of SMEs' income in lucrative investment options. The study finds that financial uncertainty, security in investment, and earnings are the most critical risk factors influencing SMEs' investment decisions in the IT sector, with high return expectations and fear acting as key driving forces shaping these decisions.

Military institutionalization involves internalizing military values, norms and structured behaviours that differ significantly from civilian life, leading to culture shock during the transition. Career experiences in the military imprint behaviours and identities that shape subsequent roles and how retired officers transition to the civilian world. The present study explored how military culture and identity influence military-to-civilian transition difficulty among retired army officers. Fourteen semi-structured interviews were conducted and analysed using interpretative phenomenological analysis, resulting in three overarching themes: Transition and Contrasting Cultures, Transition and the Role of Military Imprinting and Relearning-Connecting Disparate Cultures. The themes are divided into subthemes that shed light on how veterans navigate cultural disparities, experience identity and ego conflict tribulation and highlight factors that facilitate bridging the military-civilian cultural gap. The study's findings underscore the pivotal influence of military culture and the identity forged within military organizations on veterans' transition experiences. These insights carry significant implications for veterans and reintegration programs. It further offers possible suggestions to enhance transition interventions by addressing psychological distress related to reculturation and identity transition to facilitate smoother integration.

Purpose - This study aims to provide a comprehensive bibliometric analysis of cyberloafing by identifying key trends, distinctive works and prominent contributors in the area. Design/methodology/approach - The authors conducted a bibliometric analysis of 398 documents (between 2001 and 2024) indexed in Scopus. The Biblioshiny through R studio and VOS Viewer was used to aid the investigation. Findings - The study used bibliometric techniques like citation and keyword analysis to analyse existing literature, identify influential publications, key terms and emerging research trends. Additionally, bibliographic coupling enabled the classification of learning outcomes (LO) into five clusters, and Theory-Context-Characteristics-Methodology (TCCM) provides a structured approach to identifying future research directions by categorising them into Theory, Context, Characteristics and Methodology to ensure comprehensive and systematic academic exploration. Practical implications - The research seeks to identify gaps, emerging themes, and the intellectual trajectory of cyberloafing, offering a valuable resource for researchers and policymakers to understand its antecedents, attitudes and implications for organisations. Originality/value - This study provides a comprehensive novel bibliometric analysis of cyberloafing research from 2001 to 2024, highlighting thematic mapping and cluster analysis and using TCCM for knowledge advancement and future research pathways.

While the pursuit of green growth in tandem with environmental sustainability has captured academic interest globally, the empirical investigation of its determinants remains inconsistent. Although the unidirectional nexus between green finance and green technology in relation to economic growth has been studied, there is a dearth of comprehensive, cross-country evaluations that examine the interplay between green finance, green technology, and green energy in relation to green growth. This study fills that gap by establishing a multifaceted mediation framework in the case of 29 countries using data from 2014 to 2021. To do so, this study uses the well-known Sobel approach. The results reveal that green technology significantly mediates both the green finance-green growth and green energy-green growth nexuses, with 0.019 % and 0.004 % for every 1 % increase in green technology, respectively. Further, results from this study indicate that green finance mediates the green technology-green growth nexus with 0.99 % for every 1 % increase in green finance. Several robustness tests were also conducted as part of this study, which supported the original findings. These findings offer fresh insights by highlighting the critical role of green technology and green finance in facilitating environmentally sustainable (green) economic growth.

Despite significant improvements in enrolment rates in developing countries over recent decades, global disparities in human capital persist. This study re-examines whether human capital levels are converging globally or if countries tend to cluster around multiple steady-state equilibria. The empirical exercise identifies two distinct steady states: one with higher levels of human capital and another with lower levels. This study finds that a country's initial human capital level is crucial in determining which steady state it converges to. Countries with extremely low initial human capital tend to converge to the lower steady state. Additionally, this study highlights public spending on education, economic growth, population growth, access to bank credit, and openness as key factors influencing human capital disparities across countries.

In recent times, green supply chain practices have garnered significant attention from researchers and academia. Owing to the ever-pressing environmental issues faced by today's businesses, the need for sustainable development has become more critical than ever. The effective implementation of green practices enables firms to enhance their sustainable performances. This study provides a comprehensive literature review of green supply chain management (GSCM), drawing insights from 377 peer-reviewed papers. These papers were carefully sorted after a detailed study of 2945 articles collected through the Web of Science database. The 7G's of GSCM are defined and discussed in detail. Special focus is given to the methods and approaches of operations research that are readily adopted in GSCM practices. Furthermore, various industries that have implemented GSCM practices are examined. The findings and observations offer state-of-the-art insights for scientists and business professionals. The study covers a timeframe of over a decade, from 2010 to 2024* (20 December 2024).

The study aims to contribute to the field of credit ratings, by presenting models grounded on new variants of neighbourhood linkage method (NLM), an agglomerative hierarchical clustering technique. These models have been applied so as to analyse and predict the long-term bank credit ratings provided by an international rating agency. For this cause, the long-term ratings provided by an Indian arm of international rating agency have been considered. The dataset consists of 35 banks operating in India; this consists of 21 rated banks and 14 unrated banks. In order to validate the optimal number of cluster formations, the study uses a novel performance measure called 'modified structure strength'. Ultimately, based on the best performing NLM variant's cluster formations (of rated banks), unrated banks' potential ratings have been predicted. This model is agnostic to country or region and can be employed to forecast credit ratings of any bank across geography.

PurposeRising greenhouse gas emissions significantly drive global climate change, highlighting the need for sustainable energy solutions. This study explores performance barriers affecting the large-scale adoption of green hydrogen as a clean energy source in India. It presents a managerial framework that assesses these barriers' severity, aiding strategic planning by revealing their interconnections.Design/methodology/approachAn extensive literature review identifies 22 barriers to green hydrogen adoption. Using best-worst method (BWM), these are categorised into six groups. The decision-making trial and evaluation laboratory (DEMATEL) then analyses the 16 most critical performance barriers through a cause-and-effect approach to identify influential factors. The sensitivity analysis is performed to ensure the robustness of the results.FindingsFindings show that infrastructure challenges, lack of materials availability and clean water and financial barriers, like high production and maintenance costs, significantly hinder green hydrogen initiatives in India. The analysis reveals that raw material availability and electrolyser capacity are the most impactful barriers affecting the performance of the green hydrogen value chain.Practical implicationsWith global demand for sustainable energy surging amid rising emissions and ecological concerns, green hydrogen is becoming a viable source for sustainable energy production, especially in developing nations like India. This framework helps organisations and policymakers systematically evaluate and prioritise barriers to green hydrogen adoption, providing actionable insights for strategic interventions.Originality/valueThis study presents a structured framework employing BWM and DEMATEL to categorise and analyse green hydrogen adoption barriers. It equips practitioners and policymakers with a practical tool to assess and prioritise performance barriers, offering insights into their hierarchical and causal relationships.

Health-care apps have become a boon for individuals, offering easy access to doctors, record maintenance, and health tracking. However, the research on healthcare apps among the rural population is scarce. The present research comprehends the motivators and barriers associated with healthcare app adoption among the rural population. Using a generic qualitative research design with roots in an interpretivist paradigm, the study was conducted with the help of semi-structured interviews collected from the rural population and analyzed using thematic analysis. A total of 21 responses were collected using a semi-structured interview. The findings reported perceived usefulness, ease of access, and trust in these apps as the motivation for adoption of health-care apps. In contrast, aversion to change, lack of awareness, and complexity of healthcare apps were identified as barriers. The insights provide several implications for policymakers seeking to expand the reach of health-care apps among rural populations.

PurposeThe present study develops a theoretical framework based on the institutional theory and practice-based view. This study analyzes the role of top management commitment (TMC) in explaining the impact of institutional pressures (IP) on sustainable manufacturing practices (SMP). It also aims to explain the impact of Industry 4.0 technologies (I4T) and SMP on sustainable organizational performance (SOP).Design/methodology/approachThis paper develops and evaluates the theoretical framework using covariance-based structural equation modeling (SEM) based on the data collected from 291 respondents representing 234 manufacturing companies.FindingsThe findings reveal the mediating effect of TMC between IP and SMP, and the mediating effect of SMP between I4T and SOP. TMC positively impacts the adoption of both I4T and SMP. Findings also discovered that there is a serial mediation of TMC and I4T between IP and SMP. Further, results show that I4T-enabled SMP positively affects SOP.Originality/valueThe current study highlights the importance of looking beyond mere compliance with external forces. It posits that sustainability concerns can be addressed proactively through top management's strategic adoption of Industry 4.0 technologies and SMP. Further, this study demonstrates how companies can achieve better sustainable performance by adopting imitable, transferable and commonly available practices.

PurposeRecent trends in business-to-consumer (B2C) e-commerce indicate rising consumer demand for efficient, rapid and sustainable deliveries, making last mile delivery (LMD) increasingly vital. This study investigates the previously underexplored dimensions of sustainability in LMD within the Indian B2C e-commerce context by examining the associated risks and their corresponding mitigation strategies.Design/methodology/approachA three-round Delphi study was conducted with 33 experts to establish a comprehensive and consensus-based understanding of sustainability risks and mitigation strategies in the LMD of B2C e-commerce.FindingsThis study identified several novel types of sustainability risks and corresponding mitigation strategies. It develops a theoretical framework that categorizes these risks and strategies using diverse theoretical lenses. Additionally, eight key propositions are formulated as major contributions.Research limitations/implicationsThis study addresses the gaps in LMD research by linking risks with sustainability using the TBL, STM, SCOR, stakeholder and institutional perspectives. It identifies and maps new sustainability risks and strategies and develops a holistic sustainability risk and mitigation framework for decision-making. This study's outcomes provide actionable insights for e-commerce policymakers and practitioners to enhance the efficiency, sustainability and resilience of LMD operations.Originality/valueThis study explores sustainability risks in B2C e-commerce LMD through the theoretical lenses of the triple bottom line (TBL) and systems theory of management (STM), with particular attention to product returns as a major sustainability concern. It further leverages the supply chain operations reference (SCOR) model to formulate actionable strategies.

The present work investigates the previous research on cryptocurrency since its inception and provides an overview of its journey as a discipline. The study utilizes the Scopus database to collect the documents, resulting in 2,533 research papers published between 2008 and 2021. A bibliometric analysis is conducted, followed by the network analysis using VOSviewer. The study provides a more comprehensive overview of cryptocurrency research and its significant growth since its inception. It also gives us an understanding of how cryptocurrency research emerged as a domain across various dimensions. Further, it also provides an understanding of the possible future research areas for cryptocurrency research. It will provide a base for scholars and researchers to identify the current gaps in cryptocurrency research across various domains within business, management, and accounting and select the most appropriate field for their study.

PurposeThe study aims to theorize and empirically test the direct and indirect mechanisms through which distributors' stewardship orientation (DSO) could increase manufacturer relationship performance (RP). We unveil the mechanisms through the impact of DSO on distributor opportunism and distributor compliance behaviors, which serve as two mediating variables between DSO and RP.Design/methodology/approachA matched cross-sectional survey involving 237 manufacturer-distributor dyads within the Indian fast-moving consumer goods (FMCG) and pharmaceutical sectors was used to empirically test how a stewardship approach through DSO improves manufacturer firm RP.FindingsFindings show that distributor opportunism and distributor compliance mediate the positive impact of DSO on manufacturer firm RP.Originality/valueThis study represents one of the initial investigations emphasizing the importance of DSO in curtailing distributor opportunism and enhancing distributor compliance. The study thus lays the groundwork for future research on stewardship in interfirm contexts.

The second-hand market (SM) trades used products from the reverse channel. In practice, manufacturers such as Apple Inc. collect used products and sell refurbished products in the SM. However, third-party firms (TPFs) such as Gazelle independently manage the SM. Alternatively, the manufacturer may delegate the responsibility of managing the SM to a TPF under a contract or choose to operate in the SM with a TPF serving as a competitor. The optimal strategy to manage the SM is an important operations issue for the manufacturer as well as the TPF. This decision becomes even more critical when the manufacturer plans to sell the upgraded version, markdown version, and remanufactured version of the product concurrently. In the presence of product competition, SM selling can affect the prices and sales of the markdown product as well as the upgraded product. Therefore, in this study, we analyze impacts of the manufacturer's choice of delegation. Our analytical findings reveal that the SM selling strongly influences the equilibrium price and the demand for the markdown product offered by the manufacturer under all the mechanisms. However, demand cannibalization of the markdown product is most severe under the delegation mechanism. Additionally, we counter-intuitively reveal that the manufacturer is better-off under the delegation mechanism when the sales commission is low and remanufacturing cost is high. In fact, the delegation mechanism is found to be the most profitable arrangement for the manufacturer as well as the TPF. Interestingly, demand for the upgraded version product remains unaffected by SM sales under the independent TPF mechanism, allowing the manufacturer to launch the upgraded version product without any fear of demand cannibalization. Furthermore, we discover that consumers secure the maximum surplus under the competitive scenario owing to intense price competitiveness. For robustness checking, we further extend our model to consider the cases with variable remanufacturing cost, differential emission cost, environmental cost, and collection rate of used product.

Healthcare disparity is a major issue for Universal Health Coverage (UHC) faced by countries across the globe. It results in hardship for people living in rural areas who need healthcare services, ultimately impeding their right to health. A key digital transformation component, 'Telemedicine,' has the potential to reduce this healthcare disparity by offering virtual consultation, diagnosis, and treatment, thus leading to better healthcare access. However, research and practice on telemedicine adoption in rural healthcare systems (RHS) is nascent. The present study addresses this issue by examining the barriers to telemedicine adoption and mitigation strategies through a mixed-method study of India's RHS. In the first phase, the Grey Decision Making Trial and Evaluation Laboratory (Grey-DEMATEL) method is used, which identifies seventeen barriers that impede telemedicine adoption in RHS and unearths the causal relationship between them. In the second phase, a qualitative approach is used, which helps propose barrier mitigation strategies under three heads: Patient Acceptance, Physician Buy-in, and Policy Support, referred to as the 3P framework. A total of 10 strategies are proposed under this 3P framework to strengthen the RHS. The study results provide valuable insights to policymakers and decisionmakers working towards healthcare digital transformation, UHC, and improving RHS.

Properties of the Shannon entropy vectors are instrumental for analyzing the limits of reliable communication for various communication models. However, the set of all Shannon entropy vectors is not yet known even for three random variables. Often, there are constraints on the entropy vectors of random variables due to the underlying communication model, e.g., functional dependence, independence, and Markov chain constraints. Moreover, the entropy vectors may be constrained to belong to a specific class for a given model, e.g., belonging to the class of quasi-uniform entropy vectors due to code design constraints. This paper presents distribution construction approaches and converse results for such constrained entropy vectors. We present three approaches for constructing distributions such that corresponding entropy vectors satisfy given constraints: 1) by exploiting functional dependence constraints, 2) by quasi-uniform constructions, and 3) by using independent random vectors. In particular, these approaches are utilized to show the looseness of the known inner bounds for constrained entropy vectors for three random variables. We also present converse results for entropy vectors constrained by basic equalities and quasi-uniformity.

PurposeThis article aims to shed light on the nexus between artificial intelligence (AI) and financial inclusion in 13 developing countries from 2017 to 2023.Design/methodology/approachThe analysis employs panel data techniques, including pooled ordinary least squares, cross-section weighted POLS, robust least squares and feasible generalised least squares, to examine the impact of AI on financial inclusion.FindingsEmpirical results demonstrate that AI significantly enhances financial inclusion in the selected economies. The findings are robust across the alternative panel estimation techniques.Practical implicationsFrom the policy viewpoint, these findings imply that the widespread adoption of AI in the financial sector is vital to enhance financial inclusion and address current financial exclusion issues, especially in developing countries.Originality/valueThe rapid digital transformation in recent years has reshaped financial service access, with digitalisation's role in financial inclusion well investigated. However, the role of AI remains underexplored, especially in developing nations. This study addresses the geographic gap by providing new empirical evidence on the relationship between AI and financial inclusion in developing economies, enriching existing literature.

Study explores CEO duality's impact on ESG-EM relationship in six emerging markets. Findings reveal that ESG disclosures constraints accrual earnings management; however, high ESG scores lead to higher real earnings management, indicating possible greenwashing behavior. For three pillars of ESG, we find that firms with environmental disclosures constrain EM, while social disclosures tend to enhance EM practices. Study reveals that ESG and its sub-pillars have a curvilinear relationship with EM. CEO duality moderates ESG-EM to provide a cushion for potential greenwashing. ESG impact is not limited to EM; consequently, it affects the firms' market performance by mediating real earnings management.

India currently reports one of the lowest robot densities worldwide. Nevertheless, the country's industrial robot stock is consistently increasing, although adoption rates vary across different industries. We analyse the impact of industrial robots on wage employment in manufacturing in India from 2017 to 2022, particularly focusing on the plant and machinery labour force. Our study utilises data from the International Federation of Robotics (IFR)and various Periodic Labour Force Survey (PLFS) rounds to investigate employment dynamics based on application types, industries, and occupations. Among the occupational streams, robots directly impact plant and machine operators, especially in the automotive industry. The recent arc elasticity of employment to robots is negative for this occupational segment, implying that robots substitute specific segments of industrial labour. We examine two labour market outcomes: wage levels and formal employment. Using classification trees, we assess the influence of human capital and experience on wages and the implications for the substitution and complementarity of labour factors. Our findings reveal that the growth of industrial robots coexists with a stagnant low-skilled labour force while high-skilled labour expands, especially in larger firms. The development of the high human capital segment coexists with a visible drop in nominal and real wages and required experience. It indicates that in India, industrial robots tend to substitute routine labour, such as in material handling operations. However, further disruptions may affect the skilled workforce if the focus of robot manufacturing shifts from mechatronics to artificial intelligence-based technologies.