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The purpose of this paper is to provide trilogy in the emerging market for the establishment of business, economy and environment which is the new word for the development of any nation to attain sustainable development. This research explores the prospective crowdshipper's willingness to participate in crowdshipping services through a motivational factor.

To understand the trend and future of this concept, Google Trends Analysis (GTA) has been used. The theoretical model has been validated empirically using a survey of 287 Indian (Generation Y and Z) urban participants, but focused is on Generation “Z” participants and subsequent analysis have been carried out using structural equation modelling.

A theoretical framework has been developed connecting the various factions of the crowdsourcing process thus providing an overall view of the process strategy for logistics start-ups. This conceptual framework of sharing economy in emerging market can benefit the prospective suppliers and their target receivers. Particularly trust in crowdshipper plays a significant mediating role between subject factors and next generation user willingness to participate in crowdshipping services for sustainable last-mile delivery.

The present theoretical foundations and frameworks have been studied to get an idea of the main aspects of the field. It has the potential to provide the impetus for collaboration with the various stakeholders thus achieving the sustainable development process. The practical inference of this study is the usability in terms of the plugin application for e-retailer in emerging markets.

Short food supply chains have the potential to facilitate the transition to more sustainable food systems. Related distribution processes, however, can be challenging for smallholder and family farmers. To extend the market reach of farmers without the need for extensive investments, crowd logistics (CL) can be used. The purpose of this paper is to explore the benefits and trade-offs of implementing CL platforms in short food supply chains (SFSCs).

A decision support system (DSS) based on agent-based and discrete event simulation (DES) modelling is developed, which closely approximates the behaviour of customers and distribution processes at outlets. Different scenarios are explored to evaluate the potential of CL in rural and urban settings using the example of regions from Bavaria, Germany.

Results show that CL can be used to increase the reach of farmers in SFSCs at the cost of minor food quality losses. Moreover, a difference between urban and rural settings is noted: An urban scenario requires less investment in the driver base, whereas the rural scenario shows a higher potential to increase market reach.

Platform-based food delivery services are still mostly unexplored in the context of SFSCs. This research shows that platform services such as CL can be used to support local agriculture and facilitate the distribution of perishable food items, introducing a simulation-based DSS and providing detailed results on various application settings; this research serves as a steppingstone to facilitate successful real-world implementations and encourage further research.

An increasing number of last mile deliveries (LMDs) pose many sustainability challenges that retailers and logistics service providers (LSPs) can address. Using cognitive frames (CFs) as a lens, this study explored how retail and LSP managers make sense of sustainable LMDs.

The methodological approach used is a multiple embedded case study. The data were obtained from interviews with retailers and LSPs, supplemented with secondary data for triangulation.

The findings present the operational aspects of LMDs that managers associate with sustainability and indicate that retail and LSP managers frame sustainability primarily as emission reduction. Managers indicate an externalization of responsibility and a compartmentalization of the supply chain, in which social sustainability is not associated with the last mile. Most managers indicate hierarchical CFs regarding sustainability, in which sustainability is an important topic but is subordinate to economic interests.

Collaboration between retailers, LSPs and other stakeholders is viewed as challenging but could alleviate some of the sustainability shortcomings and aid in the paradoxical framing and inclusion of social issues.

A conceptualization of managerial CFs for sustainable LMDs, together with empirical frame indicators and three propositions, is presented, providing novel insights into how paradoxical CFs could make LMDs more sustainable. This approach illuminates the possibilities for how to untangle the operational manifestations of managerial framing and adds to the empirical exploration of CFs in supply chain management.

Logistics sector is recognized as one of the core enablers of the economic development of a nation. However, inefficiency in logistics operations impedes the achievement of intended targets by increasing the cost of doing business. Also, it is difficult to improve the efficiency of a country’s logistics operations without a metric for evaluating and understanding logistics capabilities and efficiency. Therefore, the present study has developed In-country Logistics Performance Index (ILP Index) to propose a benchmarking tool to measure the in-country logistics competitiveness, particularly in the setting of emerging economies, i.e. India.

This study has developed a unified index using principal component analysis and quintile approach. In addition, the proposed index relies on several dimensions that are developed and illustrated using quantitative secondary panel data.

The findings of this study reveal that the quality of infrastructure, economy, and telecommunications are the three most important dimensions that may significantly support the growth of the transportation and logistics sector. The results reveal that Gujarat, Tamil Nadu, and Maharashtra are the top performers whereas, Bihar, Jharkhand, and Jammu and Kashmir scores the least due to the insufficient logistics infrastructure as compared to other Indian states.

Given the extensive focus on international-level logistics index (like World Bank’s LPI) in the existing literature, this study intends to develop in-country logistics index to evaluate the logistics capabilities at the regional and state level. In addition, unlike prior studies, this study utilizes quantitative secondary data to eliminate cognitive and opinion bias. Moreover, this benchmarking tool would assist decision-makers in idealizing standard practices toward sustainable logistics operations. Additionally, the ILP index could serve the international investors in crucial decision-making, as it provides valuable insights into a country’s logistics readiness, influencing their investment choices and trade preferences. Finally, the proposed approach is adaptable to measuring the overall performance of any other industry/economy.

The study examines the influence of various congruity factors (economic, safety and Health, hedonic, and functional) on tourists' satisfaction with sharing economy-based services.

A single cross-sectional design is used in the study, with 513 travellers surveyed directly at three different tourist destinations in India. The partial least squares-structural equation modelling approach is used to analyse the data.

The research shows that congruity factors significantly influence tourists' satisfaction with sharing economy-based services. Moreover, satisfaction is strongly associated with recommendation intention for these services and customer loyalty. Additionally, the intention to recommend directly leads to increased customer loyalty.

The results offer pertinent insights for stakeholders in the sharing economy, including tourism marketers, policymakers and corporations. Aligning services with the identified congruity factors can enhance user satisfaction, boost recommendation rates and foster long-standing customer loyalty.

This study stands out for its thorough investigation into how congruity factors influence tourist satisfaction within the context of the sharing economy. Additionally, by focusing on specific demographic differentiators, such as age (gen Z or old gen) and gender (male or female), the study provides a nuanced understanding that enriches the existing body of knowledge.

The sharing economy is changing the way people use products and services, and the success of sharing-based apps like bicycle and automobile sharing has drawn a lot of interest across the world. The purpose of this research is to investigate the factors affecting the consumer's adoption of ride-sharing services.

With this aim, the current study integrates the Technology Acceptance Model (TAM) and Expectancy Confirmation Model (ECM) with a further extension of consumer trust and social norms. Using a survey-based research design, data were collected from 558 respondents using multi-stage convenience sampling on 5 point Likert scale. Confirmatory factor analysis is conducted followed by structural equation modelling using IBM AMOS-22.

The findings of the study report crucial determinants for the consumer's continuance intention and actual use of these services. Perceived usefulness, consumer satisfaction, trust and subjective norms were found positively associated with the continuous intention to use ride-sharing services, whereas perceived ease of use was found to be insignificant. This study also highlights antecedents for the consumer's trust towards these services and found reputation, propensity to trust as a significant contributor whereas structural assurance was found insignificant to establish the trust among the users.

The research on consumer adoption towards ride-sharing services are meagre and this study adds the value to the field by integrating TAM and ECM model with further extension of consumer trust and social norms and empirically test the proposed model.

Financial inclusion provides access to financial infrastructure, facilitating money transfers. Therefore, blockchain and cryptocurrencies might boost worldwide financial acceptance. However, the UAE has one of the lowest cryptocurrency adoption rates. This study explores the UAE customer adoption and use of cryptocurrencies.

Using a scale, the authors created a structural model and obtained 270 responses from a snowball-distributed online questionnaire, assessed by five cryptocurrency specialists.

Performance expectations (PE), price value (PV), Hedonic motivation (HM) and consumer innovativeness (CI) were the most significant predictors of behavioural intention (BI). Surprisingly, BI is not a reliable indication of actual consumption. Facilitating conditions (FC) are the most accurate predictor of cryptocurrency usage (CU), indicating that adoption might be increased by providing the necessary structures and processes to lead users.

This research adds to the body of knowledge by examining the adoption and implementation of cryptocurrencies in the UAE and by developing and evaluating new constructs based on current notions. The study also contributes to the current understanding of cryptocurrencies and blockchain adoption.

The conclusions of the research advise marketers on how to boost the commercialisation of cryptocurrencies in the UAE market and may pave the way for other studies to assist impending developments in the UAE cryptocurrency industry.

This research offers novel insights into significant predictors of cryptocurrency product uptake in the financial and banking business.