Does the sharing economy change conventional consumption modes?

2022 | International Journal of Information Management | Citations: 1

Authors: Fang, Yu-Hui; Li, Chia-Ying

Abstract: The development of peer-to-peer platforms has reduced the profitability of exist ... Expand

Abstract: The development of peer-to-peer platforms has reduced the profitability of existing business operations. How­ ever, relatively few studies have explored consumer switching between sharing economy platforms and existing business operations. By using the push–pull–mooring framework, this study explores the predictors that affect consumer switching between a third-party online travel agent (OTA) platform and Airbnb to understand spe­ cifically how push, pull, and mooring factors shape consumers’ switching behaviors. Data are collected from 347 users of third-party OTA platforms and Airbnb through an online questionnaire survey. Confirmatory factor analysis and structural equation modeling are performed using AMOS 24.0. The findings reveal that push factors (low structural assurance and low standardization), pull factors (monetary saving, sustainability, interactivity, and authenticity), and mooring factors (substitutability) positively influence switching behavior. Substitutability moderates the positive effects of push factors on switching behavior. This study contributes to the PPM frame­ work by identifying factors that influence consumers’ behavior of switching between a third-party OTA platform and Airbnb. In addition, this study is the first to consider substitutability and network externalities as mooring variables that facilitate switching by consumers. Airbnb and traditional hotels compete across various market segments, which results in substitutability as well as complementary relationships between them in some cities. Traditional business sections may also consider leveraging their strengths to distinguish themselves from new sharing economy services, thus delivering distinct value propositions to their consumers. This study provides reference that managers of third-party OTA platforms can use to differentiate their services from Airbnb and to maintain or increase profit by encouraging or discouraging switching among consumers. Collapse

Topics: Airbnb network effect sharing platform anonymity online community

Methods: survey structural equation modeling SEM tool chi squared test confirmatory factor analysis

Theories: push-pull-mooring theory

Developing a Taxonomy for Sustainable Digital Finance

2021 | International Conference on Information Systems | Citations: 3

Authors: Puschmann, Thomas; Shiba, Sayaka

Abstract: The financial system is currently being transformed by digitization and sustain ... Expand

Abstract: The financial system is currently being transformed by digitization and sustainability. However, existing research on the topic of sustainable digital finance, which bridges both areas, is still rare and a more comprehensive understanding of the domain is a missing component in existing research. Therefore, this paper develops a taxonomy based on a comprehensive literature analysis to structure this emerging field more precisely. The taxonomy includes a strategic, an organizational, a systems and a sustainability benefits perspective. The application of the taxonomy to 126 startups reveals that their solutions primarily focus on applications in the energy, financial services and government sector and their major focus is only on five of the seventeen SDGs, which shows a clear preference for climate, energy, infrastructure, cities, and partnerships as the primary goals. Surprisingly, the startups focus merely on operational efficiency optimization like improved processes rather than disruptive innovations in product or customer-related areas. Collapse

Topics: electronic finance business model green IS blockchain business process management

Methods: literature study test of association between categorical variables Pearson's chi-squared test design methodology literature sample

Mining Semantic Soft Factors for Credit Risk Evaluation in Peer-to-Peer Lending

2020 | Journal of Management Information Systems | Citations: 0

Authors: Wang, Zhao; Jiang, Cuiqing; Zhao, Huimin; Ding, Yong

Abstract: While Peer-to-Peer (P2P) lending is rapidly growing, it is also accompanied by h ... Expand

Abstract: While Peer-to-Peer (P2P) lending is rapidly growing, it is also accompanied by high credit risk due to information asymmetry. Besides conventional hard information, soft information also enters into the lending decision process. The descriptive loan texts submitted by borrowers have great potential for exploiting useful soft factors, but also pose great challenges due to the semantic sensitivity to context and the complexity of content representation. We propose a novel text mining method for automatically extracting semantic soft factors from descriptive loan texts. The method maps terms to an embedding space, assembles semantically related terms together into semantic cliques, and then defines semantic soft factors corresponding to the semantic cliques. Empirical evaluation shows that the extracted semantic soft factors contributed to significant improvement on credit risk evaluation in terms of both discrimination performance and granting performance. This work advances our knowledge of soft information indicative of a borrower's credit risk. Collapse

Topics: crowdsourcing peer-to-peer lending information retrieval peer-to-peer model missing data

Methods: machine learning computational algorithm classification method lasso regression natural language processing