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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.

Although skilled migrants have a high capacity for integration, many report experiences of exclusion which impacts their ability to contribute fully to the host country. This experience of exclusion, which can diminish their self-efficacy at work, is especially acute for skilled migrants from non-English speaking backgrounds when functioning in a new or exclusionary environment. In this paper, we explore the relationship between workplace inclusion and self-efficacy and identify factors that contribute to perceived inclusion for skilled migrant workers.

Participants were recruited through social network groups representing migrant workers via LinkedIn. Through snowball sampling, participants were asked to recommend recent (3–5 years) skilled migrants to participate. A total of 210 skilled migrant workers to Australia completed the survey. Structural equation modelling (SEM) is used to test our model on the relationship between inclusion and self-efficacy.

Migrants' perceptions of inclusion at work are related to their self-efficacy at work. We also find that some dimensions of inclusion are more important than others in enhancing self-efficacy for skilled migrants. Meaningful exchanges with supervisors, a sense of belonging at work and workgroup cohesion (being accepted by co-workers) are more important than senior management support or getting involved in organizational social activities as determinants of perceived inclusion.

Although skilled migrants are often assumed to be a self-select group of highly motivated, high achieving workers, many experience poor adjustment and feel excluded after arriving in the host country. Public policies have limited effects in promoting inclusion of skilled migrant workers in organizations. These policies may be supplemented with an inclusive organizational climate to improve migrant worker success. Organizations and employers are thus critical partners in fostering migrant workers' sense of inclusion and supporting the career outcomes of skilled migrant workers in the host country.

This study supports the link between perceived inclusion and self-efficacy among skilled migrant workers. It also sharpens the evidence of organizational-level factors that contribute to perceived inclusion for migrant workers.

The pressing issues of climate change and environmental degradation call for a reevaluation of how we approach economic activities. Both leaders and corporations are now shifting their focus, toward adopting practices and embracing the concept of circular economy (CE). Within this context, the Food and Beverage (F&B) sector, which significantly contributes to greenhouse gas (GHG) emissions, holds the potential for undergoing transformations. This study aims to explore the role that Artificial Intelligence (AI) can play in facilitating the adoption of CE principles, within the F&B sector.

This research employs the Best Worst Method, a technique in multi-criteria decision-making. It focuses on identifying and ranking the challenges in implementing AI-driven CE in the F&B sector, with expert insights enhancing the ranking’s credibility and precision.

The study reveals and prioritizes barriers to AI-supported CE in the F&B sector and offers actionable insights. It also outlines strategies to overcome these barriers, providing a targeted roadmap for businesses seeking sustainable practices.

This research is socially significant as it supports the F&B industry’s shift to sustainable practices. It identifies key barriers and solutions, contributing to global climate change mitigation and sustainable development.

The research addresses a gap in literature at the intersection of AI and CE in the F&B sector. It introduces a system to rank challenges and strategies, offering distinct insights for academia and industry stakeholders.

The Indian pharmaceutical industry has contributed significantly to global healthcare by securing superior-quality, inexpensive and reachable medicines worldwide. However, supply chain management (SCM) has been challenging due to constantly shifting requirements for short lifecycles of products, the convergence of industry and changeable realities on the ground. This study aims to identify, assess and prioritize the strengths, weaknesses and opportunities of the pharmaceutical SCM environment in India.

The paper employs a Strength, Weakness, Opportunity, Threat (SWOT) analysis and recognizes strategies to utilize the advantages of the strengths and opportunities, rectify weaknesses and resolve threats.

A variety of strategies that could have a positive effect on the Indian pharmaceutical business are presented. Findings and suggested strategies can significantly advance knowledge, enhance understanding and contribute to the growth of a successful SCM for the Indian pharmaceutical sector.

This paper would act as a roadmap to greater comprehension of the market leaders and market leaders' operating climate. The findings from this study will offer academic scholars and business practitioners deeper insights into the environment of SCM.

After analyzing these uncountable benefits of digital or cashless payment, many European countries like Sweden, Finland and Canada has been trying to convert their payment system into cashless. Following these developed countries, the Bangladesh Government has taken a decision to transfer society as a cashless society by using information technologies for adopting the fourth industrial revolution over the world. Digital payment system is among the various options available for transforming a cashless society. First, this empirical study presents demographic information and digital payment characteristics on the basis of income levels. This study identifies influential factors of adopting digital payment systems. Finally, this study aims to justify how digital payments transform the Bangladeshi economy into a cashless society in developing countries.

The study was administered to a sample of 1,000 Bangladeshi customers who had engaged in online banking transactions for the purpose of acquiring items and services through both social media platforms in Google Form format and face-to-face interactions in hard copy format. Among these, 647 questions were deemed usable and were used for data analysis, where the response rate was 68%. The SmartPLS is used to create and validate the structural equation modeling model presented for the research, as well as to evaluate the hypothesized correlations between the different constructs.

This cross-sectional study conducted the extended technology acceptance model (TAM) with perceived security (PS) and personal innovation (PI) variables to identify the influencing adoption factors of digital payment systems. This study finds that perceived ease of use, PI and perceived usefulness have a favorable impact on individuals’ attitudes toward adopting digital payment methods (DPMs). The study also indicated that PS did not influence negatively the adoption of digital payment system. Besides this, the adoption of digital payment will help to transform society into a cashless society in the future.

Increasingly prevalent across the nation. Several variables are required to facilitate the transition toward a cashless society. This study exclusively focuses on DPMs. Additionally, the data has been obtained exclusively from a single urban area. The adoption of DPMs has become increasingly prevalent across the nation.

This study would help policymakers, marketers and bankers understand which factors affect digital payment infrastructure expansion. So, they can produce digital payment apps that are compatible with different devices, have fast transactions, are user-friendly, easy to use and highly secure to maintain good attitudes toward digital payment systems.

Few studies have examined how DPMs affect cashless societies in developing countries like Bangladesh. According to researchers, to the best of the authors’ knowledge, this is the first study to explore how digital payments affect cashless society in Bangladesh and raise awareness about it.

The study extended the TAM model to PS and PI. This paper is also unique in the conceptual arguments and the subject theme of the research area.

This paper aims to conduct a systematic literature review on the fintech services and financial inclusion of the developing nations that particularly focuses on lower middle-income group nations (LMIGN) and upper middle-income group nations (UMIGN) to highlight the research areas that have not received attention and present opportunities for future research.

This paper adopts a systematic approach to examine 65 research articles published from 2016 to 2021, adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.

The study identifies research gaps in two key themes: backward and outward linkages. In backward linkages, the literature on UMIGN should pay attention to the behavioural patterns associated with lending, investment and market provision-related fintech services. Further research is needed to understand the relationship between fintech services on the usage and quality dimension of financial inclusion in both LMIGN and UMIGN. For outward linkages, future research work should explore the role of fintech and financial inclusion in the development of LMIGN. This study provides valuable insights and guides future research directions by comprehensively mapping the existing studies.

This study does not use quantitative tools, such as meta and bibliometric analysis, to validate the findings.

This research paper offers new perspectives that introduce a novel framework for analysing literature on fintech, financial inclusion and its impact on the overall development of UMIGN and LMIGN.