Relationship between Online Shopping and Store Shopping in the Shopping Process: Empirical Study for Search Goods and Experience Goods in Nanjing, China

Author(s):  
Qing Zhai ◽  
Xinyu (Jason) Cao ◽  
Feng Zhen

As online shopping proliferates, many studies have investigated its impact on travel. Most studies, however, treat online shopping as a transaction channel and overlook its interaction with physical shopping at various stages of the shopping process. Using adult internet users in Nanjing, China, this study explores the interactions between online shopping and traditional shopping for search goods (books) and experience goods (clothing) during the shopping process. The results show that experience goods have a stronger stickiness combination between pre-purchase channels and transaction channels than search goods. As a pre-purchase channel for experience goods, stores are more likely to promote cross-channel than internet shopping; the relationship is the opposite for search goods.

2010 ◽  
Vol 38 (5) ◽  
pp. 673-679 ◽  
Author(s):  
Jen-Hung Huang ◽  
Yi-Chun Yang

In this study we investigated the relationship between personality traits and online shopping motivations by comparing Big Five model of personality (McCrae & Costa, 1987) and motivations for Internet shopping. Data were collected from 216 participants using a questionnaire. Regression analysis results indicated that openness was positively associated with adventure and idea motivation, and conscientiousness was positively associated with convenience motivation. Furthermore, extraversion was positively associated with sociality motivation, and neuroticism was positively related to lack of sociality motivation. Implications and further research directions are then discussed.


2018 ◽  
Vol 1 (1) ◽  
pp. 39-45
Author(s):  
Muh. Feroza A. ◽  
M Muhdiyanto ◽  
Diesyana Ajeng Pramesti

The objective of this research is to determine the extent of e-service quality and e-trust influence thee-loyalty in online shopping by combining two research models. This research employs survey by usingpurposive sampling technique to 120 internet users in Magelang, Central Java. The respondents of the research are customer that ever doing transaction more than 2 times in the website. The data analysis was done using SPSS 21.00 and hypothesis testing was through Path Analysis. The research identifiesthat four hypotheses are supported that are the relationship between of e-service quality, e-trust toe-satisfaction and e-satisfaction, e-trust to e-loyalty are positive and significant and one hypothesis isnot supported that is the relationship between e-service quality to e-loyalty is positive but not significant.


2019 ◽  
Vol 2 (2) ◽  
pp. 1-24
Author(s):  
Dr Rizwana Bashir ◽  
Irsa Mehboob ◽  
Waqas Khaliq Bhatti

This research paper examines the relationship between various factors that affect the consumer behavior towards online shopping. Online shopping refers to the recent trends of being able to buy everything from home. The focus of this research is to explain the influence of five major variables that were derived from literature. These variables are trust, time, product variety, convenience and privacy, which determine how consumer-buying behavior is reflecting online shopping trends. Data was collected through the use of a specified measuring instrument. This instrument was a completely self-developed and standardized questionnaire that comprised of two sections. The statistical analysis of the data reflects that trust and convenience will have great impact on the decision to buy online or not. Trust is been considered as the most relevant factor affecting the customer’s buying behavior towards online shopping when it comes to younger generation.


Author(s):  
Young-Mi Ko ◽  
Sungwon Roh ◽  
Tae Kyung Lee

Background: This study examined patterns of problematic shopping behavior by South Korean internet users to investigate the association between problematic internet shopping (PIS) and dissociative experiences.; Methods: Five hundred and ninety eight participants from 20–69 years old were recruited through an online panel survey. We gathered information about sociodemographic characteristics, alcohol use, caffeine intake, and online shopping behaviors. Psychopathological assessments included Korean version of dissociative experience scale (DES-K), Canadian Problem Gambling Index (CPGI-K), the modified Stress Response Inventory (SRI-MF), the Barratt Impulsive Scale-11-Revised (BIS-K). We used multiple logistic regression analysis with the Richmond compulsive buying scale (RCBS-K) as the dependent variable.; Results: The prevalence of shoppers with internet-based problem shopping was 12.5%. The amount of time spent on online shopping was correlated with PIS severity (OR = 1.008, p < 0.01). The risk of PIS was related to an increased tendency toward dissociation (OR = 1.044, p < 0.001) and impulsivity (OR = 1.046, p < 0.05). Conclusions: PIS participants with dissociation showed higher levels of perceived stress, gambling problems, and impulsivity than did PIS participants without dissociation. This study suggests that dissociation was associated with a higher burden of PIS as it was connected to poor mental health problems.


Author(s):  
Ya-Yueh Shih ◽  
Kwoting Fang

Strides in information technology and improvements in networking technology have set the pace for rapid growth in new applications of electronic commerce in a variety of settings. Business to business (B2B), business to customer (B2C), customer to business (C2B), and customer to customer (C2C) have become prevalent business channels and have reshaped the ways that business transactions are conducted in the marketplace. According to Internet Data Corporation (IDC), the number of Internet users worldwide will exeed 1 billion Internet users by 2007 (IDC, 2004). Given recent trends and forecasting, it is clear that no business enterprise can afford to ignore the tremendous potential of these emerging technologies in terms of the rate of creating, processing, and distributing the volume of business. The proliferation of the Web potential for business, together with its profuse customer information, have offered an alternative sales channel for a growing number of firms and have prompted extensive research on the effect of negative critical incidents on customer satisfaction with Internet shopping. The increase in business-to-customer (B2C) channels has made several firms look for new strategies to understand online shopping behavior in order to attract, retain and satisfy customers’ needs (Ranganathan & Ganapathy, 2002). In fact, many researchers have considered that customer satisfaction leading to higher levels of customer retention would depend on the success of critical factors, such as quality design (Huizingh, 2000; Liu & Arnett, 2000; Stefani & Xenos, 2001), security concerns (Belanger, Hiller, & Smith, 2002; La & Kandampully, 2002), and other factors for electronic commerce (Loiacono, Watson, & Goodhue, 2002; Yang, Cai, Zhou, & Zhou, 2005). However, Waterhouse and Morgan (1994) reported an interesting finding that just one factor of dissatisfaction and defection would be enough to cause customers to become disenchanted with Internet shopping. Thus, the call for the managers to find and discriminate the dissatisfaction or defection in the velocity and dynamic nature of the Internet environment becomes loud. According to Fang, Shih, and Liu (2004), the slow response affected overall satisfaction indirectly by quality attributes satisfaction (QASAT) seems to be more important to customers who have less purchase frequency or purchase amount than high one. Furthermore, online bookstores with incomplete content and have untrustworthy transaction would affect overall satisfaction indirectly to customers with high loyalty by QASAT. The main purpose of this study was threefold. First, it designed a set of quality attributes satisfaction, in term of the negative critical incidents concept, to measure individual satisfaction, an online shopping bookstore served as empirical cases. Second, from predictive model standpoint, a method, call multiple discriminant analysis (MDS), was used to analyze customers’ satisfaction based on QASAT and estimated data. Finally, it adopted holdout samples to confirm the ability of generalization with a predictive model.


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