A well-performed recommender system for an e-commerce web site can help customers easily find favorite items and then increase the turnover of merchants, hence it is important for both customers and merchants. In most...A well-performed recommender system for an e-commerce web site can help customers easily find favorite items and then increase the turnover of merchants, hence it is important for both customers and merchants. In most of the existing recommender systems, only the purchase information is utilized data and the navigational and behavioral data are seldom concerned. In this paper, we design a novel recommender system for comprehensive online shopping sites. In the proposed recommender system, the navigational and behavioral data, such as access, click, read, and purchase information of a customer, are utilized to calculate the preference degree to each item; then items with larger preference degrees are recommended to the customer. The proposed method has several innovations and two of them are more remarkable: one is that nonexpendable items are distinguished from expendable ones and handled by a different way; another is that the interest shifting of customers are considered. Lastly, we structure an example to show the operation procedure and the performance of the proposed recommender system. The results show that the proposed recommender method with considering interest shifting is superior to Kim et al(2011) method and the method without considering interest shifting.展开更多
This study analyzed factors influencing consumers in the process of making a decision in online shopping. The findings could inspire suggestions for online marketers in developing either media or infrastructures accor...This study analyzed factors influencing consumers in the process of making a decision in online shopping. The findings could inspire suggestions for online marketers in developing either media or infrastructures accordingly. The variables in the study involved product information, price, service, transaction safety, environment, age, gender, educational background, and income rate as independent variables, while the process of purchasing decision served as a dependent variable. Primary data were gathered in 10 locations within Jabodetabek areas involving 270 respondents which were analyzed using multiple regression analysis. The study revealed that price, information product, and service as significant variables influencing consumers in online shopping. Service became the most important factor for marketers to be considered as it emerged as the most dominant variable influencing the process of making a decision in online shopping.展开更多
Consumer behavior in electronic commerce has been the theme of hundreds of studies conducted by researchers of many nationalities in the past twenty years.The purpose of this study was to review and classify the conce...Consumer behavior in electronic commerce has been the theme of hundreds of studies conducted by researchers of many nationalities in the past twenty years.The purpose of this study was to review and classify the concepts used in papers published between 2003 and 2014 to explain the consumer behavior in electronic commerce.A systematic search of the literature in nine databases was performed and 136 papers published in double-blind peer reviewed journals were selected.Reference models were prepared based on a classification of the concepts found.This article reports only the concepts that displayed statistical significance in the studies analyzed.Finally,we suggest new studies that can be conducted.展开更多
With the proliferation of information and communication technology in rural areas,rural e-commerce has gradually become a new economic phenomenon in China. Usingthe national rural e-commerce comprehensive demonstratio...With the proliferation of information and communication technology in rural areas,rural e-commerce has gradually become a new economic phenomenon in China. Usingthe national rural e-commerce comprehensive demonstration policy as a quasi-naturalexperiment, this study examines the causal linkage between rural e-commerce andcounty-level economic development in China. Its findings, which draw on county-levelpanel data from 2011 to 2018, indicate that the policy had a positive effect on the countyleveleconomy in China, resulting in an overall increase in county GDP by 3.5 percent(0.7 percent annually). Our analysis further shows that the impact of the policy diferedalong the region and human capital dimensions. Further analysis reveals that industrialstructure and nonagricultural employment were the main channels for the policy toexert a county-level economic impact. Infrastructure improvement in China also playsan important role. The findings emphasize the importance of advancing e-commerce inrural areas to stimulate county-level economic development.展开更多
Shopping complexes are widely built for their convenience and multiple functions.However,their complex func-tional areas,result in significantly different thermal environments and various customers’thermal perception...Shopping complexes are widely built for their convenience and multiple functions.However,their complex func-tional areas,result in significantly different thermal environments and various customers’thermal perception.To explain the influence of functional related parameters on the thermal perception of customers in shopping com-plexes,we selected two typical functional related parameters,including customers’thermal expectation level of indoor environment in their current area and the area where the customer was ten minutes before taking the sur-vey.851 valid questionnaires were obtained in two typical shopping complexes during July.Customers’thermal neutral temperature,thermal preference temperature and thermal comfort temperature range were calculated in different functional areas.Customers’thermal expectation level was quantified by using expectancy factor.The results showed that customers’thermal expectation level in entertainment areas was the highest,followed by food courts,retail areas,and transition spaces.Customers’thermal expectation level would influence their thermal neutral temperature and thermal sensitivity.Customers with different thermal experience differed sig-nificantly in their thermal sensation voting(p<0.01).The highest thermal sensitivity,about 0.41/°C,was found in customers moving from high-temperature areas to low-temperature areas.These findings help to clarify how functional related parameters affect the thermal comfort of customers and provide the guidance for designing the indoor temperature in shopping complexes.展开更多
基金supported by theNational High-Tech R&D Program (863 Program) No. 2015AA01A705the National Natural Science Foundation of China under Grant No. 61572072+2 种基金the National Science and Technology Major Project No. 2015ZX03001041Fundamental Research Funds for the Central Universities No. FRF-TP-15-027A3Yunnan Provincial Department of Education Foundation Project (No. 2014Y087)
文摘A well-performed recommender system for an e-commerce web site can help customers easily find favorite items and then increase the turnover of merchants, hence it is important for both customers and merchants. In most of the existing recommender systems, only the purchase information is utilized data and the navigational and behavioral data are seldom concerned. In this paper, we design a novel recommender system for comprehensive online shopping sites. In the proposed recommender system, the navigational and behavioral data, such as access, click, read, and purchase information of a customer, are utilized to calculate the preference degree to each item; then items with larger preference degrees are recommended to the customer. The proposed method has several innovations and two of them are more remarkable: one is that nonexpendable items are distinguished from expendable ones and handled by a different way; another is that the interest shifting of customers are considered. Lastly, we structure an example to show the operation procedure and the performance of the proposed recommender system. The results show that the proposed recommender method with considering interest shifting is superior to Kim et al(2011) method and the method without considering interest shifting.
文摘This study analyzed factors influencing consumers in the process of making a decision in online shopping. The findings could inspire suggestions for online marketers in developing either media or infrastructures accordingly. The variables in the study involved product information, price, service, transaction safety, environment, age, gender, educational background, and income rate as independent variables, while the process of purchasing decision served as a dependent variable. Primary data were gathered in 10 locations within Jabodetabek areas involving 270 respondents which were analyzed using multiple regression analysis. The study revealed that price, information product, and service as significant variables influencing consumers in online shopping. Service became the most important factor for marketers to be considered as it emerged as the most dominant variable influencing the process of making a decision in online shopping.
文摘Consumer behavior in electronic commerce has been the theme of hundreds of studies conducted by researchers of many nationalities in the past twenty years.The purpose of this study was to review and classify the concepts used in papers published between 2003 and 2014 to explain the consumer behavior in electronic commerce.A systematic search of the literature in nine databases was performed and 136 papers published in double-blind peer reviewed journals were selected.Reference models were prepared based on a classification of the concepts found.This article reports only the concepts that displayed statistical significance in the studies analyzed.Finally,we suggest new studies that can be conducted.
基金the National Natural Science Foundation of China(No.72003170)the National Social Science Fund of China(No.21&ZD091)+1 种基金the Major Project of the Key Research Base for Humanities and Social Sciences of the Ministry of Education(No.22JJD790077)the Fundamental Research Funds for the Central Universities in China。
文摘With the proliferation of information and communication technology in rural areas,rural e-commerce has gradually become a new economic phenomenon in China. Usingthe national rural e-commerce comprehensive demonstration policy as a quasi-naturalexperiment, this study examines the causal linkage between rural e-commerce andcounty-level economic development in China. Its findings, which draw on county-levelpanel data from 2011 to 2018, indicate that the policy had a positive effect on the countyleveleconomy in China, resulting in an overall increase in county GDP by 3.5 percent(0.7 percent annually). Our analysis further shows that the impact of the policy diferedalong the region and human capital dimensions. Further analysis reveals that industrialstructure and nonagricultural employment were the main channels for the policy toexert a county-level economic impact. Infrastructure improvement in China also playsan important role. The findings emphasize the importance of advancing e-commerce inrural areas to stimulate county-level economic development.
基金The authors would like to thank the research participants and Ziwei Yan,Lai Wei,Ting Lei for assisting with the field study.This research is financially supported by the National Key Research and Development Program(No.2016YFC0700200)the Natural Science Foundation of Tianjin(No.2017FQ-0013)the Program of Introducing Talents of Discipline to Universities(No.B13011).
文摘Shopping complexes are widely built for their convenience and multiple functions.However,their complex func-tional areas,result in significantly different thermal environments and various customers’thermal perception.To explain the influence of functional related parameters on the thermal perception of customers in shopping com-plexes,we selected two typical functional related parameters,including customers’thermal expectation level of indoor environment in their current area and the area where the customer was ten minutes before taking the sur-vey.851 valid questionnaires were obtained in two typical shopping complexes during July.Customers’thermal neutral temperature,thermal preference temperature and thermal comfort temperature range were calculated in different functional areas.Customers’thermal expectation level was quantified by using expectancy factor.The results showed that customers’thermal expectation level in entertainment areas was the highest,followed by food courts,retail areas,and transition spaces.Customers’thermal expectation level would influence their thermal neutral temperature and thermal sensitivity.Customers with different thermal experience differed sig-nificantly in their thermal sensation voting(p<0.01).The highest thermal sensitivity,about 0.41/°C,was found in customers moving from high-temperature areas to low-temperature areas.These findings help to clarify how functional related parameters affect the thermal comfort of customers and provide the guidance for designing the indoor temperature in shopping complexes.
