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This study aims to construct an appropriate framework by incorporating essential components from the most renowned theories to investigate the variables that impact behavioural intentions towards embracing cashless transactions (CLT).

A survey was conducted to ascertain the users’ intention to adopt CLT in Chennai, Tamil Nadu, India. Further, this study used a “partial least squares-based structural equation modelling” technique to analyse the relationships between latent factors.

The results of the proposed model revealed that 11 independent variables together explain the intention to use CLT with a 60.5% explanatory power. Further, perceived usefulness is the most influential factor in predicting users’ willingness to adopt CLT, followed by social influence, perceived costs, attitude, trust and device barriers. Finally, the findings of moderator effects indicate that income and experience interact positively and strongly with behavioural intention to adopt CLT. It indicates that high-income, experienced users are more likely to convert their intentions into actions.

This study integrated critical elements from the major theories, such as Theory of Reasoned Action, Technology Acceptance Model, Decomposed Theory of Planned Behaviour, the unified theory of acceptance and use of technology (UTAUT) model and UTAUT2, to investigate the adoption of CLT. As a result, 11 crucial factors were identified from the existing literature that impacts CLT adoption without overlapping. Consequently, the model presented in this study provides a more profound understanding than previous research regarding why individuals adopt CLT systems. Accordingly, these results could aid policymakers in addressing people’s concerns and facilitating a seamless transition to a cashless society.

This paper aims to develop and validate a cashless transaction adoption model (CTAM) that integrates all essential elements to investigate the adoption of “cashless transactions (CLT)”.

The researchers surveyed 375 respondents from each of Bengaluru’s eight zones in India. In addition, using the respondents’ replies, a “partial least squares-based structural equation modelling (PLS-SEM)” technique was used to analyse the relationship between the components.

The results of CTAM reveal that 12 independent variables explain 84.7% of the variation in behavioural intention to adopt CLT. In addition, performance expectancy is the strongest predictor of users’ intentions to embrace CLT, followed by perceptions of the economy’s security and economic offence reduction, social influence, perceived trustworthiness, the expected level of effort and innovativeness. Furthermore, in terms of impediments, perceived risk and cost are the negative influence factors that affect behavioural intention to adopt CLT.

The research successfully developed and validated a comprehensive CTAM that integrates essential elements to investigate the adoption of CLT. Consequently, this research, for the first time, elucidates the precise role of “Perceived Economic Offense Reduction (PEOR)”, “Perceived Economic Benefit (PEB)” and “Perceived Economy’s Security (PES)” in influencing individuals’ behavioural intentions towards adopting CLT. Accordingly, this CTAM offers a more in-depth explanation than any other research for understanding why individuals embrace CLT systems.

This paper aims to investigate the customers’ response to mandatory activities as per the corporate social responsibility (CSR) laws of India in the Indian hotel industry. Further, it analyzes the influence of mandatory CSR activities of the companies on the purchase intention (PI) of customers with the mediating role of customer satisfaction (CS). It also examines the link between mandatory CSR activities and the customers’ evaluation of corporate.

The customers of five-star hotels in Kerala, India, were surveyed, and the proposed model is analyzed with factor analysis and structural equation modelling with mediation analysis.

The study proves three propositions, namely, the mandatory CSR activities influence the PIs of customers, the CS partially mediates the relationship of CSR activities on the PI of the customers and the mandatory CSR activities demonstrate a positive impact on customers’ evaluation of corporate in the Indian hotel industry.

The comprehensive CSR assessment based on hotel customers’ response by considering CSR law in India is a novel outlook. The study will aid in determining the association between mandatory CSR and PI and evaluate the role of mandatory CSR on favorable corporate evaluation.

This study aims to develop and validate a scale to measure stakeholders' perception of mandatory corporate social responsibility (CSR) activities in the hotel industry in India.

CSR items were generated based on a qualitative approach. The underlying factorial structure of the scale is determined using exploratory factor analysis. The measurement model is verified through confirmatory factor analysis with validity checks. Additionally, the nomological and predictive validity of the proposed scale is confirmed through correlation and regression analysis.

This study proposed a three-dimensional 17-item scale comprising the environment, social and cultural domains to measure stakeholders' perception of mandatory CSR in the Indian hotel industry.

This study adds to the literature by providing a comprehensive approach incorporating CSR activities specified by law on CSR measurement. Validated CSR scales are recommended for future studies to measure CSR in India. This study may also serve as a blueprint for other countries to develop context-specific CSR measurement approaches.

To the best of the authors’ knowledge, this is the first scale development study on mandatory CSR in India. The inclusion of CSR activities prescribed by law on the standardized CSR scale development is a novel outlook.

The ultimate aim of this paper is to contribute an extension of the unified theory of acceptance and use of technology (UTAUT) model. The modified UTAUT provides a better explanation for the adoption of cashless transactions. However, it does not consider individuals’ perceived countries’ advantages when cashless transactions are made in the economy. Hence, this research investigates whether individuals’ perceived countries’ advantages of the cashless economy influence behavioral intentions of using cashless transactions.

A structured questionnaire has administered with 375 respondents in selected commercially vibrant places, such as Shopping Malls, big retail shops, hotels, and the like, covering the 15 zones of Greater Chennai city Corporation, India. From the 375 respondents, 325 respondents returned the filled-in questionnaire in time. For analysis, exploratory factor analyses used for underlying new latent factors from the identified variables used for measuring the individuals’ perceived countries’ advantages of a cashless economy. After identifying the latent factors, the extracted factors regressed with the intention level of using cashless transactions to validate the influence of newly identified factors.

The results of the regression analysis proved that the identified new factors, such as Perceived Economic Offense Reduction (PEOR), Perceived Economic Benefit (PEB), and Perceived Economy’s Security (PES), are positively and significantly influencing the behavioral intention of using cashless transactions.

This study’s unique contribution is the validation of a measurement scale based on individuals’ perception of countries’ advantages when cashless transactions are made in the economy. The scale development in the present study is an essential step toward the advancement of the UTAUT research model, and this study also proved that identified new latent factors such as PEOR, PEB and the PES are positively and significantly influencing individuals’ behavioral intention toward the use of the cashless transaction. Hence, this study’s result may help contribute an extension of the UTAUT model in a comprehensive view, and this extension may enrich UTAUT’s ability to explain and predict the acceptance of cashless transactions.

In recent literature, many conceptual and empirical studies have discussed the countries’ advantages resulting from cashless transactions. This study attempts to integrate those advantages as variables through measurement instruments, whether they influence the behavioral intention to use cashless transactions from the general public perspective.

Though academic study on the subject is still in its early stages, there is growing interest in using blockchain technology for transforming the supply chain. The academic literature is divided and yet only includes studies evaluating how the supply chain has changed organizations. To comprehend the new phenomena, this study aims to investigate the factors of blockchain technology in driving supply chain transformation. To be more precise, the authors developed from the literature the most prevalent criteria for determining if supply chain transformations are ready to be scaled up.

This study followed a combination of two multi-criteria decision making methods evaluation based on distance from average solution and complex proportional assessment) methodology in this research: planning, investigating, executing out, establishing a rating of the criteria and evaluating it.

The study shows that the “organizational driver” and the “technology driver” are the factors most important to the transformation of the supply chain, whereas the “financial driver” and the “regulatory driver” are less important. This study also makes some managerial recommendations to address the factors impeding the supply chain’s transformation. Each factor’s significance was explored, and a proposed study agenda was also presented.

Although the main forces behind the transformation of the supply chain have been recognized, further research into statistical correlation is required to confirm how the various elements interact.

This research aids decision-makers in comprehending the key forces behind supply chain transformation. Managers and decision-makers might better predict and allocate the necessary resources to start the road toward digitization and make well-informed choices once these aspects have been investigated and understood.

In light of the pandemic’s effects on the world and the increase in businesses embracing the digital economy, the supply chain transformation is more important than ever. Beyond blockchain deployment and the pilot studies on digital transformation, there is a gap. The topics and factors this study uncovered will operate as a framework and recommendations for more theoretical investigation and practical applications.

Recent technological advancements, often linked to Industry 4.0, require organizations to be more agile and innovative. Blockchain technology (BT) holds immense potential in driving organizations to achieve efficiency and transparency in supply chains. However, there exist some insurmountable challenges associated with the adoption of BT in organizational supply chains (SC). This paper attempts to categorically identify and systematize the most influential challenges in the implementation of BT in SC.

This study resorts to an extensive literature review and consultations with experts in the field of supply chain management (SCM), information technology and academia to identify, categorize and prioritize the major challenges using VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) and Combined Compromise Solution method (CoCoSo).

The top three classes of challenges revealed in this study are privacy challenges (PC), infrastructure challenges (IC) and transparency challenges (TC). Maintaining a balance between data openness and secrecy and rectification of incorrect/erroneous input are the top two challenges in the PC category, integration of BT with sustainable practices and ensuring legitimacy are the top two challenges in the IC category, and proper and correct information sharing in organizations was the top most challenge in the TC category.

Future scholars and industry professionals will be guided by the importance of the challenges identified in this study to develop an economical and logical approach for integrating BT to increase the efficiency and outcome of supply chains across several industrial sectors.

This study examined the factors impeding the implementation of micro-credentials and accepting it as a credible source of earning professional qualifications and certifications necessary for pursuing higher education or other career goals.

The factors were identified by reflecting on the recent literature and Internet resources coupled with in-depth brainstorming with experts in the field of micro-credentials including educators, learners and employers. Two ranking methods, namely Preference Ranking for Organization Method for Enrichment Evaluation (PROMETHEE) and multi-objective optimization based on ratio analysis (MOORA), are used together to rank the major challenges.

The results of this study present that lack of clear definitions, ambiguous course descriptions, lack of accreditation and quality assurance, unclear remuneration policies, lack of coordination between learning hours and learning outcomes, the inadequate volume of learning, and lack of acceptance by individuals and organizations are the top-ranked and the most significant barriers in the implementation of micro-credentials.

The findings can be used by educational institutions, organizations and policymakers to better understand the issues and develop strategies to address them, making micro-credentials a more recognized form of education and qualifications.

The novelty of this study is to identify the primary factors influencing the implementation of micro-credentials from the educators', students' and employers' perspectives and to prioritize those using ranking methods such as PROMETHEE and MOORA.

Despite the current progress in realizing how Big Data Analytics can considerably enhance the Sustainable Manufacturing Supply Chain (SMSC), there is a major gap in the storyline relating factors of Big Data operations in managing information and trust among several operations of SMSC. This study attempts to fill this gap by studying the key enablers of using Big Data in SMSC operations obtained from the internet of Things (IoT) devices, group behavior parameters, social networks and ecosystem framework.

Adaptive Prospects (Improving SC performance, combating counterfeits, Productivity, Transparency, Security and Safety, Asset Management and Communication) are the constructs that this research first conceptualizes, defines and then evaluates in studying Big Data Analytics based operations in SMSC considering best worst method (BWM) technique.

To begin, two situations are explored one with Big Data Analytics and the other without are addressed using empirical studies. Second, Big Data deployment in addressing MSC barriers and synergistic role in achieving the goals of SMSC is analyzed. The study identifies lesser encounters of barriers and higher benefits of big data analytics in the SMSC scenario.

The research outcome revealed that to handle operations efficiently a 360-degree view of suppliers, distributors and logistics providers' information and trust is essential.

In the Post-COVID scenario, the supply chain practitioners may use the supply chain partner's data to develop resiliency and achieve sustainability.

The unique value that this study adds to the research is, it links the data, trust and sustainability aspects of the Manufacturing Supply Chain (MSC).

This study aims to examine the implementation of agile practices in Industry 4.0 to assess the financial performance measurements of manufacturing firms. It also investigates the relationship between supply chain performance and financial performance.

The study is based on an experimental research design by collecting data from 329 responses from key officials of manufacturing firms. The analyses are carried out to explore this modern concept with the help of the SPSS program, which is used to conduct a confirmatory factor and reliability analysis and Smart-partial least square (PLS) version 4.0 with structural equation modeling.

This research demonstrates the positive effect agile supply chain strategies in Industry 4.0 may have on manufacturing companies' financial performance as a whole. Everything throughout the supply chain in Industry 4.0, from the manufacturers to the end users, is taken into account as a potential performance booster. The values obtained from the model's study show that it is both dependable and effective, surpassing the threshold for such claims. The research is supported by factors like customer involvement (CUS), continuous improvement (CI), integration (INT), modularity (MOD), management style (MS) and supplier involvement (SI) but is undermined by factors including postponement (PPT).

According to the findings of the study, Industry 4.0 firms' financial performance and overall competitiveness are significantly improved when their supply chains are more agile. A more agile supply chain helps businesses to more rapidly adapt to shifts in consumer demand, shorten the amount of time it takes to produce a product, enhance product quality and boost customer happiness. As a consequence of this, there will be an increase in revenue, an improvement in profitability and continued sustainable growth.

There are literary works available on agile practices in various fields, but the current study outlines the need to understand how supply chains perform financially under the mediating effect of agile supply chains in Industry 4.0 which contribute most to the organization's success. The study will aid companies in understanding how agile practices will further the overall performance of the organization financially.