فهرست مطالب فاضل بذرافشان

Business-to-Customer (B2C) e-commerce systems cover a wide geographical area and a wide range of customers. One of the new ways to respond well to customers is a sharing economy. Sharing economy is an innovative business model with an emphasis on community and people that affects the social value of the society. The purpose of this study was to investigate the effect of sharing economy on B2C e-commerce systems with the mediating role of social value. The research method was applied in terms of purpose and in terms of implementation, it was a descriptive-survey and correlational method. The participants of the study comprised of 110 experimental and academic experts and graduate students majoring in information technology management. The sample size was determined according to Krejcie and Morgan Table 86 and a stratified method was used for sampling. Data analysis was performed using structural equations using SmartPLS3 software. Findings indicated that obligation, economic factors, infrastructure, and collaboration had a positive and significant effect on social value. Social value also has a positive and significant effect on B2C e-commerce systems.

Today, business to customer e-commerce systems are the most important business systems in providing services and goods to customers. Startups in these systems need methods to be able to expand their market to respond appropriately to customers. One of the recent innovations to develop services and goods in startups is the use of sharing economy. sharing economy in B2C startups make better use of facilities and resources and helps them to reduce transaction costs and improve productivity. Therefore, the purpose of this study was to present a B2C e-commerce model with an emphasis on sharing economy in startups, which was done in combination. The present research is fundamental in terms of purpose and descriptive-correlation based on the method. In the first step, effective factors were identified based on content analysis and interviews with 15 academic experts. The output of this stage was 14 components in 3 dimensions (technology, social and economic). Then, in the second step, the identified dimensions were graded by interpretive structural method and clustered by Mikmak analysis, which was analyzed using Excel software. Interpretive structural results showed that the components are in 10 levels, also Micmac analysis showed that the components (trust- collaboration- product- communication quality- economic factor) in the dependent cluster, components (website usability- availability- obligation- sharing information- information quality) in the link cluster and components (social value- security- infrastructure-customization) are also in the independent cluster.