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Analysis Of Factors Affecting Platform-based Flexible Employment In The Shared Economy

Posted on:2020-11-27Degree:MasterType:Thesis
Country:ChinaCandidate:J ZhuFull Text:PDF
GTID:2507306560477224Subject:Applied Economics
Abstract/Summary:
Under the shared economic situation,a large number of platform-based enterprises have emerged.As a typical representative case,Didi Travel has created a large number of flexible jobs while subtly changing the habits of consumers.It has attracted many idle laborers to participate in employment,and has been widely accepted by industry scholars for its enormous social value.However,the academic research on the new employment model of laborers participating in platform-based enterprises is still in its infancy,and it cannot provide synchronous theoretical support for the development of shared enterprises.Therefore,clarifying the model of the influential factors of platform-based flexible employment in the sharing economy can provide theoretical guidance for the subsequent development of increasingly vigorous practice.First of all,based on the research of predecessors,the literature on sharing economy and platform-based flexible employment is compiled,The literature links the sharing economy with the platform-based flexible employment,and the research takes the platform driver as the research object to carry out research on the factors affecting the platform work,and establishes the research focus of this paper.Secondly,on the basis of case description,using the coding technology of grounded theory,starting from the perspective of drivers in the industry of Drip,the core categories of platform-based flexible employment are summarized through the three-level coding technology,and the various categories are analyzed.This paper adopts the empirical research method,introduces the technology acceptance model,and combines the actual situation,using the right sharing,perceived cost,perceived benefit,psychological factors,and participation in employment as variables to construct a platform-type flexible employment influencing factor model.Subsequently,the questionnaires were distributed jointly by the field and the network.In the small-scale pre-study to increase the credibility of the questionnaire,278 valid questionnaires were collected after extensive questionnaires were distributed,and the hypotheses were carried out through descriptive statistical analysis,reliability and validity analysis,and structural equation modeling.Research shows: 1.The use of sharing rights has a significant negative impact on perceived costs,and has a significant positive impact on psychological factors.Therefore,the trading mode of ownership under traditional employment is gradually being replaced by the right to use.This sharing method not only brings extra work income to the employed,but also reduces the social contradiction caused by the imbalance between supply and demand.2.Perceived costs have a significant negative impact on participation in employment,and perceived benefits have a significant positive impact on participation in employment.Perceived costs also have a significant negative impact on perceived benefits.This shows that the basic motivation for influencing behavioral decision-making is to be able to perceive a certain product to bring economic benefits to itself,and that workers can participate in platform employment to earn income with little cost,which is a travel platform that can attract labor.3.Psychological factors have a significant positive impact on perceived benefits.This shows that people will experience a series of ideological struggles before participating in an unknown activity,and it is easy to be influenced by the opinions of the people around them.The recommendation and evaluation of others will lead to their own thinking about their actual benefits.Finally,based on the analysis results,the corresponding platform policies are provided for the shared platform enterprises,and more new forms of jobs are created.
Keywords/Search Tags:platform-type flexible employment, shared economy, technology acceptance model, influencing factors, Internet
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