| With the popularity of the Internet,the advantages of online shopping is becoming more and more prominent,and it has become an important form of shopping,but also a part of people's lives. A review of the development history of the domestic electricity supplier, that ten years has experienced three important periods, from the flow bonus period (2005-2010 years), the brand of the period (2010-2014 years), to a fine operation period (after 2015), with the rise of electricity providers electricity supplier brand service providers, from early extensive to fine. With the popularity of smart phones, online shopping has become a way to spend idle time. Shopping platform in all aspects of efforts, the use of big data to recommend some of the goods and staging strategies and the development of Shopping Festival and other ways to greatly promote the network sales. However, some aspects are still not perfect, the integrity of the problem and the virtual network of goods and the reality does not match the problem is still outstanding,in the refinement of the operational phase of the need to improve the details of all aspects.College students are easy to accept new things, time trivial, limited funds and other characteristics,so it has its own consumer behavior characteristics and is the main force of online shopping. Therefore, from the perspective of college students, the study of online shopping consumer behavior factors has practical significance.This paper uses the combination of theory and empirical methods, according to the relevant theory to determine the index variables, design questionnaire and using relevant sampling theory formulated by two stage sampling method, sampling method, in which the first stage using PPS method of stratified sampling in Shenyang city in second stage extraction,by means of random sampling questionnaire to collect from students the data,so as to achieve the purpose of reducing data error. The data collected by the current status of consumer online shopping behavior of college students was analyzed by using the method of statistical analysis method, and then use structural equation model to explore the consumption tendency, commodity, security, integrity, service, analysis of influence on online shopping satisfaction trust by using path analysis of gender, monthly living expenses, monthly online shopping costs three the potential factors on the behavior and effect of repeat purchase behavior, the correlation analysis method discussed the final clearance strategy, current staging shopping platform provides the recommended measures and effects of shipping insurance services and to repeat purchase behavior potential behavior. The final conclusion is as follows: 1) college students online shopping for money reflects the dominant reason for related activities, offers students more active online shopping integrity problems do exist, for safety, services are also showed a different degree of attention. 2. Good propensity to consume,goods,safety and service have a positive impact on satisfaction and trust. 3. The monthly cost of living and online shopping cost affect the consumption behavior of male and female students in different degrees, and there is a correlation between monthly living expenses and monthly online shopping costs. 4) there was a significant positive correlation between the stage strategy and the repeat purchase behavior, but there was no significant effect on the potential behavior, while the recommendation and freight insurance were significantly positively correlated with the repeat purchase behavior and the potential purchase behavior.The innovation of this paper is not only the basic status quo survey of online shopping satisfaction but from two angles of trust and potential behavior and repeat purchase behavior of College Students' online shopping behavior factors to be studied,and the choice of indicators of the characteristics of their shopping. Based on the theory of sampling design, the data is more representative and the conclusion is more reliable.Combined with the development of the network in recent years to join the big data era of commodity recommendation and staging strategy and freight insurance discussion. |
PDF Full Text Request