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Globally, the landscape of corporate carbon disclosures (CCD) is continually evolving as societal, environmental and regulatory expectations change over time. The goal of this study is to examine the challenges faced by Indian firms’ corporate carbon reporting (CCR). The literature recognized the hurdles to reaching net zero emissions and decarbonization, which are equally applicable to carbon disclosure (CD).

The scope 3 emission disclosure barriers (S3EDBs) identified from the literature were ranked, and their relationships were discovered using the “Grey-based decision-making trial and evaluation laboratory” (Grey- DEMATEL) technique.

The key findings are the S3EDBs, the most prominent barriers, their interrelationships and important insights for managers of organizations in prioritizing the action area for scope 3 CD. Eight S3EDBs were categorized in terms of cause and effect, threshold value is calculated as 0.78. “Quality, and reliability of data,” “Government policies and statutory requirement on emission disclosure” and “Traceability and managing supply chain partners” are the most prominent S3EDBs.

The results will help industry people in countries with emerging economies that have significant scope 3 carbon footprints. The managers can plan to deal with top S3EDBs as a step towards decarbonization and ultimately fighting climate change (CC).

This study is one of the first to rank these barriers to CD so that industry practitioners can prioritize their actions. The core contribution of this research is to detect the most significant S3EDBs and their interdependencies.

This study aims to understand holistic consumer perceptions of quality and their effect on re-purchase intentions by measuring the latent characteristics of online Amazon reviews.

Data was collected from entries in the Amazon customer review data set, which explicitly mentions quality, economic evaluation and future purchase intention. The analyses included natural language processing, structural topic modeling and econometric analysis. The study used real-time customer reviews to determine the overall perceived quality, the impact of perceived quality on re-purchase intention and the mediating roles of price consciousness and customer satisfaction.

Consumers’ perception of overall quality includes product- and service-related dimensions. Perceived quality influences re-purchase intentions through the mediating role of customer satisfaction. While price consciousness impacts the link between perceived quality and customer satisfaction, it does not affect re-purchase intention.

The managerial implications emphasize multiple dimensions of quality in the online environment and the role of customer satisfaction in consumers’ online re-purchase intentions. The results also illustrate that price effects are insignificant in influencing re-purchase intentions. Thus, while price cuts may encourage initial purchases, quality and customer satisfaction are vital to stimulate re-purchase.

The e-commerce literature lacks a comprehensive and rigorous understanding of the components of consumers’ perceived quality. This research develops a thorough understanding of what impacts overall e-commerce quality based on real-time customer reviews, avoiding the biases arising from traditional methods, including surveys.

This study aimed to explore the impact of Artificial Intelligence (AI) characteristics, namely Perceived Animacy (PAN), perceived intelligence (PIN), and perceived anthropomorphism (PAI), on user satisfaction (ESA) and continuous intentions (CIN) by integrating Expectation Confirmation Theory (ECT), with a particular focus on Generation Y and Z.

Using a quantitative method, the study collected 495 data from Gen Y (204) and Z (291) respondents who were users of digital banking apps through structured questionnaires that were analysed using PLS-SEM. The latter helped investigate the driving forces of AI characteristics and user behavioural intentions as well as reveal generation-specific features of digital banking engagement.

The study revealed that PAN and PIN have significant positive effects on the anthropomorphic perceptions of digital banking apps, which in turn increases perceived usefulness, satisfaction, and continuous intentions. In particular, the influence of these AI attributes varies across generations; Gen Y’s loyalty is mostly based on the benefits derived from AI features, whereas Gen Z places a greater value on the anthropomorphic factor of AI. This marked a generational shift in the demand for digital banking services.

The specificity of Indian Gen Y and Z users defines the scope of this study, suggesting that demographic and geographical boundaries can be broadened in future AI-related banking research.

The results have important implications for bank executive officers and policymakers in developing AI-supported digital banking interfaces that appeal to the unique tastes of millennial customers, thus emphasising the importance of personalising AI functionalities to enhance user participation and loyalty.

This study enriches the digital banking literature by combining AI attributes with ECT, offering a granular understanding of AI’s role in modulating young consumers' satisfaction and continuance intentions. It underscores the strategic imperative of AI in cultivating compelling and loyalty-inducing digital banking environments tailored to the evolving expectations of Generations Y and Z.

This study aims to analyse and understand customer sentiments and perceptions from neobanking mobile applications by using advanced machine learning and text mining techniques.

This study explores a substantial large data set of 330,399 user reviews available in the form of unstructured textual data from neobanking mobile applications. This study is aimed to extract meaningful patterns, topics, sentiments and themes from the data.

The results show that the success of neobanking mobile applications depends on user experience, security features, personalised services and technological innovation.

This study is limited to textual resources available in the public domain, and hence may not present the entire range of user experiences. Further studies should incorporate a wider range of data sources and investigate the impact of regional disparities on user preferences.

This study provides actionable ideas for neobanking service providers, enabling them to improve service quality and mobile application user experience by integrating customer input and the latest trends. These results can offer important inputs to the process of user interaction design, implementation of new features and customer support services.

This study uses text mining approaches to analyse neobanking mobile applications, which further contribute to the growing literature on digital banking and FinTech. This study offers a unique view of consumer behaviour and preferences in the realm of digital banking, which will add to the literature on the quality of service concerning mobile applications.

The purpose of this study is to integrate customer value theory (CVT) and protection motivation theory (PMT) to understand the factors that have an impact on customer experience, e-trust and intention to recommend, which influence the adoption behaviour of digital currency users.

A purposive sampling technique was used, and data were gathered through an online survey of 414 respondents. The measurement and structural models were tested using partial least squares structural equation modelling to establish linkages between the constructs.

Functional, emotional and social values positively impact customer experience. Furthermore, perceived severity, perceived vulnerability, response efficacy and self-efficacy had a positive impact on e-trust. E-trust positively affects customer experience and intention to use the digital currency directly. The study demonstrated that perceived value and protection motivation factors play a significant role in influencing the use of digital currency.

For managers and policymakers interested in the Indian digital currency market, it is suggested that functional utility and emotional and social benefits can enhance user satisfaction. In an e-trust model, user education to increase risk and protection awareness, effectiveness of responses and self-efficacy are critical to building e-trust.

Building on CVT and PMT’s usage in the broader financial services domain, this research empirically confirms the significance of perceived value and protection motivation factors while adopting digital currency. It provides an extensive and multifaceted approach to comprehending customer involvement and trust in digital financial services, thus enhancing the theoretical and empirical knowledge of both the fintech and blockchain industries.

The study aims to add to the existing literature on food supply chains by specifically taking into the redesigning of the alignment of storage, packaging and distribution practices in the modern complex supply chain. The redesign of the food supply chain’s storage, distribution and packaging is a transformative endeavor ultimately aimed at enhancing efficiency, sustainability and reliability.

In order to identify, classify and prioritize the main challenges, this study conducted an extensive analysis of the literature and experts’ opinions in the areas of academia, information technology and the food supply chain (FSC) using combined compromise solution method (CoCoSo) and complex proportional assessment (COPRAS).

The top three classes of key indicators revealed in this study are dynamic route optimization and on-demand delivery pods (RD4), implementation of active packaging with nanotechnology (RP3) and collaborative last-mile (RD2). The findings reveal that dynamic route optimization and on-demand delivery pods (RD4) and collaborative last-mile (RD2) are maintaining a balance between collaborative delivery networks through route optimization which is a very discussable theme in recent literature.

The research provides fresh insights into how perishable food shelf life parameters and the use of distribution networks within the short supply chain can be taken into consideration when redesigning the storage, packaging and distribution system for food supply chains.

This study aims to conceptualise a customer-centric model based on an online customer experience (OCE) construct, mediated by e-loyalty (EL) and e-trust (ET), to improve the continuous usage intention (CUI) of Indian digital banks from Generation Y and Z perspectives.

This study used an online survey method to gather data from a sample of 466 digital banking users, from which usable questionnaires were obtained. The obtained data were subjected to thorough analysis using PLS-SEM to further study the research hypotheses.

The main factors that determine digital banks’ OCE are perceived enjoyment, e-service quality, information quality and e-convenience. Additionally, relevant constructs were evaluated using an importance-performance map analysis.

This study used convenience sampling for the urban population using digital banking; therefore, the outcome may be generalised to a limited extent. It would be valuable to imitate studies in other countries to strengthen digital banking further.

There is a lack of research on digital banking and OCE in India; thus, this study helps rectify this issue while providing valuable insights. This study differs from others in that it examines the connections between OCE, EL, ET and the bottom line of financial institutions, using these factors as dependent variables instead of traditional measures.

Blockchain technology (BCT) has emerged as a powerful tool for enhancing transparency and trust. However, the relationship between the benefits of BCT and agri-food supply chain performance (AFSCperf) remains underexplored. Therefore, the current study investigates the influence of BCT on AFSCperf and sustainability issues.

Through a comprehensive literature review, various benefits of BCT are identified. Subsequently, a research framework is proposed based on data collected from questionnaire surveys and personal visits to professionals in the agri-food industry. The proposed framework is validated using partial least square structural equation modelling (PLS-SEM).

The findings reveal that BCT positively impacts AFSCperf by improving traceability, transparency, food safety and quality, immutability and trust. Additionally, BCT adoption enhances stakeholder collaboration, provides a decentralised network, improves data accessibility and yields a better return on investment, resulting in the overall improvement in AFSCperf and socio-economic sustainability.

This study offers valuable practical insights for practitioners and academicians, establishing empirical links between the benefits of BCT and AFSCperf and providing a deeper understanding of BCT adoption.

Stakeholders, managers, policymakers and technology providers can leverage these findings to optimise the benefits of BCT in enhancing AFSCperf. Moreover, it utilises rigorous theoretical and empirical approaches, drawing on a multidisciplinary perspective encompassing food operations and supply chain literature, public policy, information technology, strategy, organisational theory and sustainability.

This study aims to integrate Delone and McLean’s information system success (DMISS) model with the innovation resistance model to evaluate the relationship between behavioural intention to use (BIU) and innovation resistance in the context of neo-banking. The primary objective of this study is to identify the drivers of neo-banking adoption and the barriers to its adoption and incorporate constructs such as e-trust (ETR) and personal innovativeness (PIV) to provide a more comprehensive understanding of the factors influencing neo-banking adoption.

A structured survey-based questionnaire was used to gather data from a diverse sample population in India. The Partial Least Squares Structural Equation Modeling (PLS-SEM) model was employed to further examine the adoption of neobanking services and users' intention to use neobanking services.

This study reveals a significant correlation between BIU and the uptake of neobanking services, demonstrating the value of consumers' readiness to embrace these offerings. However, resistance to usage has emerged as a major obstacle for consumers concerned about data security, technology reluctance and perceived risks associated with digital-only neobanks.

Analysing the driving and restraining factors will provide substantial information on the formation of consumers' decision-making processes in the Indian banking industry, which is undergoing rapid digital transformation. This information is of great importance to scholars, practitioners and policymakers, as it highlights the factors that may facilitate or impede the adoption of neobanking in India. The outcomes of this analysis will be of particular interest to researchers, experts and stakeholders in the field as they will provide valuable insights into the dynamics of consumer behaviour in the Indian banking sector.

This study represents an initial effort to examine BIUs and usage resistance within the rapidly developing neobanking sector in India. The findings of this study build on the existing research in this area and contribute to the ongoing discussion on the adoption of neo-banking.

The current research elucidates the role of empathy in design of artificial intelligence (AI) systems in healthcare context, through a structured literature review, analysis and synthesis of academic literature published between 1990 and 2024.

This study aims to advance the domain of empathy in AI by adopting theory constructs context method approach using the PRISMA 2020 framework.

The study presents a current state-of-the-art literature to review the connections between empathy and AI and identifying four clusters showing the emerging trajectories in the field of AI and empathy in healthcare setting.

Despite a rise in empirical research, the potential pathways enhancing AI accountability by incorporation of empathy is unclear. The research aims to contribute to the existing literature on AI and empathy in the healthcare sector by carving out four distinct clusters depicting the future research avenues.