Abstract: The paper aims to clarify the relationship between product involvement level and consumer tendency toward online review. It proposes the products in two classes and examines the level of user attention and significant difference between attribute-based areas and experience-based areas in each category. It uses an eye-tracking experiment to simulate the experience of online shopping behavior in order to view the consumers' shopping behavior. Thus, a scenario was designed, and 23 participants were asked step by step to purchase some products and add them to their shopping cart. The fixation durations are used to examine the amount of visual attention of the user in each area of interest (AOI) determined considering two classes of high involvement and low involvement products, and paired sample T-test was used to examine the effect of the product’s types on the online review content. The study results explained that users of high involvement products consider the attribute-based points more highly than the experience-based points.
Abstract: The continued rise of e-commerce is the main driver of the rapid growth of global online purchase. Consumers can nearly buy everything they want at one occasion through online shopping. The purchase behavior models which focus on single product category are insufficient to describe online shopping behavior. Therefore, analysis of multi-category purchase gets more and more popular. For example, market basket analysis explores customers’ buying tendency of the association between product categories. The information derived from market basket analysis facilitates to make cross-selling strategies and product recommendation system.
To detect the association between different product categories, we use the market basket analysis with the multidimensional scaling technique to build an associated map which describes how likely multiple product categories are bought at the same time. Besides, we also build an inter-purchase time model for associated products to describe how likely a product will be bought after its associated product is bought. We classify inter-purchase time behaviors of multi-category products into nine types, and use a mixture regression model to integrate those behaviors under our assumptions of purchase sequences. Our sample data is from comScore which provides a panelist-label database that captures detailed browsing and buying behavior of internet users across the United States. Finding the inter-purchase time from books to movie is shorter than the inter-purchase time from movies to books. According to the model analysis and empirical results, this research finally proposes the applications and recommendations in the management.
Abstract: Online shopping enables consumers to search for information and purchase products or services through direct interaction with online store. This study aims to examine the effect of Internet marketing environment, product characteristics, familiarity and confidence, and promotional offers on consumer online shopping behavior. 200 questionnaires were distributed to the respondents, who are students and staff at a public university in the Federal Territory of Labuan, Malaysia, following simple random sampling as a means of data collection. Multiple regression analysis was used as a statistical measure to determine the strength of the relationship between one dependent variable and a series of other independent variables. Results revealed that familiarity and confidence was found to greatly influence consumer online shopping behavior followed by promotional offers. A clear understanding of consumer online shopping behavior can help marketing managers predict the online shopping rate and evaluate the future growth of online commerce.
Abstract: Knowing about the customer behavior in a grocery has
been a long-standing issue in the retailing industry. The advent of
RFID has made it easier to collect moving data for an individual
shopper's behavior. Most of the previous studies used the traditional
statistical clustering technique to find the major characteristics of
customer behavior, especially shopping path. However, in using the
clustering technique, due to various spatial constraints in the store,
standard clustering methods are not feasible because moving data such
as the shopping path should be adjusted in advance of the analysis,
which is time-consuming and causes data distortion. To alleviate this
problem, we propose a new approach to spatial pattern clustering
based on the longest common subsequence. Experimental results using
real data obtained from a grocery confirm the good performance of the
proposed method in finding the hot spot, dead spot and major path
patterns of customer movements.
Abstract: The consumption capability of people in China has
been a big issue to tourism business. Due to the increasing of China
tourists, Taiwan-s government rescinded the category of people in
China and opened up the non-stopped airline from China to Taiwan.
The “one-day traveling style between China and Taiwan" has formed,
hoping to bring business to Taiwan. Night market, which shows
foreigners the very local character of Taiwan, contains various
merchandise for consumers to purchase. With the increasing numbers
of non-stopped airline, visiting Taiwan-s night markets has also been
one of major activities to China-s tourists. The purpose of the present
study is to understand the consumer behavior of China tourists in
tourist night markets in Taipei and analyze that if their shopping
motives cause the different shopping behaviors and post-purchase
satisfaction and revisiting intention. The results reveled that for the
China tourists, the motives of significant influence to the shopping
behaviors. Also, the shopping behaviors significant influence to the
whole satisfaction and the whole satisfaction significant influence to
post-purchase behavior.
Abstract: The purpose of this study was to explore the
demographic differences of international tourists according to three
main factors, including the value of time, shopping behavior and
shopping motivation. The Chatuchak Weekend Market is known as
one of the biggest weekend markets in the world. Too little academic
studies had been conducted in this area of weekend market, despite its
growth and continuous development. In general, both domestic
visitors and international tourists are attracted to the perception of
cheap and bargaining prices the weekend market. However, systematic
research study can provide reliable understanding of the perception of
the visitors.
This study focused on the group of international tourists who visited
the market and aimed to provide better insights based on the
differences in their demographic factors. Findings indicated that
several differences in value of time, shopping behavior, and shopping
motivation were identified by gender, income and age. Research
implications and directions for further studies were discussed.