Search results

The purpose of this paper is to develop a categorization of sharing practices from a structured interdisciplinary literature review on the Sharing Economy. Instead of striving for a new definition, the authors distinguish nine types of sharing practices and provide an overview of prior investigations on sharing practices across three levels of analysis and 15 research areas. The structured analysis is translated into opportunities for future research on the Sharing Economy.

The study follows a structured literature review approach to uncover practices related to the Sharing Economy and similar phenomena. The authors analyze 210 articles from a broad number of disciplines, and develop a categorizing framework for Sharing Economy practices.

The paper identifies nine different types of sharing practices and provides a structured way for analyzing, comparing and positioning research on the Sharing Economy and related phenomena.

The categorization of sharing practices and the embedded interdisciplinary overview of studies on the Sharing Economy help to explain potentially contradictory research results and uncovers opportunities for future research in the topic area.

Given the variety of disciplines dealing with the Sharing Economy and the plenitude of definitions and related concepts, the categorization and research overview provides a consolidated view of the knowledge in the topic area and an effective tool for identifying paths for future research.

The purpose of this study is to propose and test an integrated model to explain how trust is built in sharing economy (SE) transactions.

Initially, prior literature was systematically selected and synthesized to develop a comprehensive framework applicable to multiple trust-building perspectives and categories of SE platforms. Then, a survey was conducted to validate the constructs and test the model with Airbnb guests. A sample of 351 responses was collected and analyzed using structural equation modeling.

The results indicate that the cues an individual assesses to infer their counterpart’s trustworthiness and the reasons the individual has for engaging in the SE transaction can explain a large variance in their trust in the counterpart. In addition, the individual’s propensity to trust moderates this relationship.

The proposed model can help identify the most effective trust-building mechanisms. It can be taken as a common knowledge base for scholars to compare the four trust-building perspectives and different categories of SE platforms, as well as to investigate the subject over time and across cultures.

This research can also help practitioners understand the complexity of building trust and design platform features to do so.

A unified model clarifies trust in the SE, aiding platform growth and community bonding. This insight guides platforms in feature enhancement and policymakers in drafting balanced regulations.

To the best of the authors’ knowledge, for the first time, there is a comprehensive and parsimonious model applicable to the four trust-building perspectives and different categories of SE platforms.

The alternative arrangements to traditional employment have become a promising area in the gig economy with the technological advancements dominating every work. The purpose of this paper is to explore the barriers to the entry of gig workers in gig platforms pertaining to the food delivery sector. It proposes a framework using interpretive structural modelling (ISM) for which systematic literature review is done to extract the variables. This analysis helps to examine the relationship between the entry barriers to gig platforms. The study further proposes strategies to reduce the entry barriers in gig sector which would help to enhance productivity and generate employment opportunities.

The study uses interpretive structural model (ISM) to ascertain the relationship between various entry barriers of the gig workers to the gig platforms. It also validates the relationship and understand the reasons of their association along with MICMAC analysis. The model was designed by consulting the gig workers and the experts allied to food delivery gig platforms namely Zomato and Swiggy.

It was observed that high competition, longer login hours and late-night deliveries are the significant barriers with high driving power and low dependence power. Poor payment structures and strict terms and conditions for receiving the incentives are interdependent on each other and have moderate driving and dependence power. The expenses borne by the gig workers, such as Internet, fuel and vehicle maintenance expenses have high dependence power and low driving power. Hence, they are relatively less significant than other barriers.

The study is confined to food delivery sector of India, without considering other important sectors of gig economy for generalizing the framework. As the study is based on forming an ISM framework through literature review only, it does not consider other research methods for analysing the entry barriers to the gig platforms.

The study attempts to dig out the low entry barriers for gig workers in food delivery platforms as there is a dearth of analysis of these factors. This study would weave them using ISM framework to help the gig platforms overcome these barriers at various levels, thus adding to the body of literature.

The study discusses the need for understanding relationship between the entry barriers in the form of ISM model to identify the dependent and driving factors of the same.

This paper aims to focus on online hospitality platforms in the collaborative consumption environment. In particular, this paper investigates the impact of trust on the obtainers’ intentions to “inquire about accommodations” and to “request a booking” on Airbnb.com.

This paper takes the perspective of a potential renter, respectively, obtainer and adopts Gefen’s (2000) research model, which incorporates familiarity and trust in the e-commerce industry. In this regard, the paper extends the work on two-sided markets of Mittendorf (2016-2017). To verify the modified research model, a survey was conducted, gathering results from over 426 participants of which 255 valid responses from the Millennials generation were obtained. This paper uses covariance-based structural equation modeling to analyze both measurement and structural relationships regarding the interaction framework.

The results show empirical evidence that both “trust in the intermediary” and “trust in providers” are decisive for the obtainers’ intentions on the online platform. In this regard, this paper advances the understanding of the collaborative consumption mechanisms by adapting trust literature to validate the obtainers’ intentions on contemporary collaborative consumption platforms.

While the unit of analysis of prior research comprises the general intention to share, this paper empirically validates a more deliberate decision of user intentions by focusing on the intention to inquire about accommodations (no registration necessary) and the intention to request a booking (registration necessary). However, this study is dependent on one setting and it is still unclear whether the results are generalizable to other collaborative consumption setups.

This paper is in line with the work of Mittendorf (2016-2017), thus, it uses a sophisticated statistical approach to analyze trust in the collaborative consumption environment, such as confirmatory factor analysis and structural equation modeling.

Despite the perceived role of customer value in post-adoption behaviour in the context of ride-hailing apps such as Uber, there has been limited research on the subject. This paper seeks to enrich the understanding of the relationships between customer perceived value, particularly hedonic value and economic value, customer satisfaction and continued use intentions of ride-hailing apps.

This analysis is based on field data collected from 567 users of ride-hailing apps in Ghana. Data collected from the survey were analysed using the partial least square (PLS) approach to structural equation modelling (SEM).

The paper provides evidence that hedonic value, as well as economic value, positively predicts customer satisfaction and continued use intentions of ride-hailing apps. Further analysis reveals customer satisfaction directly predicts continued use intentions in addition to partially mediating the influence of customer perceived value on continued use intentions of ride-hailing apps. Finally, the findings suggest that hedonic value has a stronger impact on continued use intentions than economic value, while economic value has a greater impact on satisfaction than hedonic value.

The study contributes to post-adoption behaviour research by providing evidence on the relationships among the study constructs in a developing country context. Overall, the findings will stimulate future empirical debates on the subject and guide practitioners in decision-making concerning customers' usage of ride-hailing apps.

Companies are adopting innovative methods for responsiveness and efficiency in the public transport sector. The implementation of air-taxi services (ATS) in the transport sector is a move in this direction. Air taxis have a two-pronged advantage as they can reduce travel times by avoiding traffic congestion and have the potential to reduce carbon footprint compared to traditional modes of public transportation. Many companies worldwide are developing and testing ATS for practical applications. However, many factors may play a significant role in adopting ATS in the transport sector. This paper attempts to unearth such critical success factors (CSFs) and establish the interrelationships between these factors.

Fifteen CSFs were identified by systematically reviewing the literature and taking experts' input. An integrated multi-criteria decision-making (MCDM) technique, Decision-Making Trial and Evaluation Laboratory-Analytic Network Process (DEMATEL-ANP [DANP]) was used to envisage the causal relationships between the identified CSF.

The results reveal that Govt Regulations (GOR), Skilled Workforce (SKF) and Conductive Research Environment (CRE) are the most influential factors that impact the adoption of ATS in the transport sector.

The research implications of these findings will help practitioners and policymakers effectively implement ATS in the public transportation sector.

This is the first kind of study that identifies and explores the different CSFs for ATS implementation in public transportation. The CSFs are evaluated with the help of a framework built with inputs from logistics experts. The study recognizes the CSFs for ATS implementation and provides a foundation for future research and smooth adoption of ATS.