• Journal of Information Management
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• v.42 no.2
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• pp.211-234
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• 2011

The development of information technology improves the globalization of the world economy. This change was able to expand the cyber space, and the online community known as the cyber community is made within the existing offline community. From the cyber community's activity, the concept of social network services created, and recently developed social computing. Social computing is the current situation and the next step in the online community. Currently, most CIOs are using social computing for workplace empowerment. As online transactions become more active, the strategy to increase customer loyalty in Internet shopping is an effective tool to increase profit for the company, and as a method to maintain competitive. With the growth of electronic commerce, through insurance of customer loyalty on the Internet, a company can establish a long-term relationship with customers, so for this, it is important to have reliable relationship with customers. Also, through advertisement and commercial information, the cognition of Internet shopping looks can be effective in retaining customers. In this study, it explores how social computing and trust and cognition of Internet shopping are effective in maintaining customer loyalty. As the result of study, the trust and cognition of Internet shopping are significantly effective on customer loyalty, but the sense of social computing. Still, social computing has not matured enough to be as effective in retaining customer loyalty. However, it does indicate that social computing has significantly increased the trust and cognition in Internet shopping. In this study, as the concepts of the social network service and social computing are applied in Internet shopping, which are actively discussed by scholars, it is expected that the basis of the study could improve and present the idea of social shopping.

• Journal of the Korea Society for Simulation
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• v.23 no.4
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• pp.97-109
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• 2014

Personal rapid transit (PRT) is a new transportation system, which is energy efficient and brings high quality of customer service. Customers arrive dynamically at stations and request transportation service. In this paper, we propose a new online PRT dispatching algorithm for pickup and delivery of customers. We adopt the nearest neighbor dispatching rule, which is known as performing well in general. We extend the rule with bipartite matching in order to deal with multiple vehicles and customers at the same time. We suggest a systematic way for selecting vehicles that will be considered to be dispatched, since the scope with which vehicles are selected may affect the system performance. We regard the empty travel distance of vehicles and the customer waiting time as the performance measures. By using simulation experiments, it has been examined that the scope of dispatching affects the system performance. The proposed algorithm has been validated by comparing with other dispatching rules for transportation services. We have shown that our algorithm is more suitable for PRT operating environment than other dispatching rules.

• Journal of Korean Society for Quality Management
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• v.52 no.1
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• pp.23-42
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• 2024

Purpose: This study aims to investigate the impact of two types of information quality, which are platform-oriented information quality and customer-oriented information quality, on customers' decision-making processes in the Online to offline (O2O) platform environment. Grounded in the product brokering efficiency model, which encompasses screening cost, evaluation cost, and decision quality, a model framework was developed. Furthermore, this study explores how these decision-making processes affect customer loyalty. Methods: Given that food delivery apps are the most widely used O2O service in Korea, this study targeted users of these apps for data analysis. We conducted hypothesis testing through a purposive sampling methodology focusing on food delivery app users. A Partial Least Squares Structural Equation Modeling analysis was conducted to analyze the data. The data collection occurred via an online survey from October to December 2021, with a total of 212 respondents participating. Results: The results of this study revealed the significant role of information quality in helping customers' decision processes while using food delivery apps. Specifically, it was found that platform-oriented information positively influences decision quality, while customer-oriented information significantly affects both the reduction of evaluation cost and the enhancement of decision quality. Additionally, the study indicated that lower evaluation costs and higher decision quality lead to increased platform loyalty. However, a reduction in screening cost did not have a significant impact on platform loyalty. Conclusion: While previous studies have overlooked the existence of two sides, service provider and user, in a platform, this research holds significance in its analysis of how information quality impacts loyalty by utilizing the two kinds of information quality. Practitioners can enhance customer loyalty to the platform by enriching customer-oriented information, thereby reducing customers' evaluation costs and encouraging more loyal usage of the platform.

• The Research Journal of the Costume Culture
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• v.21 no.1
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• pp.129-138
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• 2013

Consumers' perception of risk plays a major role in how they make online purchase decisions. Since online shopping is perceived to be riskier than in-store shopping, consumers engage in a variety of risk reduction strategies such as searching online for alternative products and alternative e-tailers. This study examines the influence of risk involvement on risk reduction strategies and customer satisfaction. It discusses three aspects of risk reduction strategies: time spent in making a purchasing decision, searching for alternative e-tailers, and searching for alternative products. Data from 294 female shoppers who had experience in purchasing fashion products online was analyzed. This study found that risk involvement had a positive influence on the time spent in making decisions, while the influence of risk involvement on searching for alternative retailers and alternative products was not significant. However, consumer satisfaction was negatively related to search for alternative retailers and positively related to risk involvement. This study provides a better understanding of customers' risk involvement and risk reduction strategies in online shopping. This information would be beneficial for marketers and retailers to reduce customer perception of risks and to promote online sales.

• The Research Journal of the Costume Culture
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• v.15 no.1 s.66
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• pp.58-67
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• 2007

The popularity of communities on the Internet has captured the attention of marketing professionals and more consumers are involved in online activities of fashion brands. The primary purpose of this research was to explain the process of how online interactivity influence members' relational market behavior. Subjects of this study were male and female members of online communities of fashion brands. Online survey data were obtained from 416 respondents. Empirical findings of this study were suggestive of two types of interaction in fashion online communities: community-customer interaction and customer-customer interaction. Fashion online community customers' relational market behavior (word of mouth and repurchase intention) was significantly influenced by both types of interactivity. The influence of interactivity on relational behavior was stronger for word of mouth intention than for repurchase intention. This study highlights the importance of interactivity in cyberspace as well as relational market behavior and contributes to e-relationship marketing strategies of fashion brands.

• Management Science and Financial Engineering
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• v.20 no.2
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• pp.27-31
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• 2014

This paper studies the assortment optimization problem in online retailing by using a multinomial logit model in order to take consumer choice behavior into account. We focus on two unique features of online purchase behavior: first, there exists increased amount of uncertainty (e.g., size and color of merchandize) in online shopping as customers cannot experience merchandize directly. This uncertainty is captured by the scale parameter of a Gumbel distribution; second, online shopping entails unique shopping-related disutility (e.g., waiting time for delivery and security concerns) compared to offline shopping. This disutility is controlled by the changes in the observed part of utility function in our model. The impact of changes in uncertainty and disutility on the expected profit does not exhibit obvious structure: the expected profit may increase or decrease depending on the assortment. However, by analyzing the structure of the optimal assortment based on convexity property of the profit function, we show that the cardinality of the optimal assortment decreases and the maximum expected profit increases as uncertainty or disutility decreases. Therefore, our study suggests that it is important for managers of online retailing to reduce uncertainty and disutility involved in online purchase process.

• International Journal of Contents
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• v.14 no.2
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• pp.7-15
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• 2018

Online shopping is increasing worldwide. Providing customers actual feeling of the product is essential in online shopping. Various technological aids can be used to support visual feeling. When delivering visual tangibility, it is important to study which attributes are significant in product presentations that best portray the actual tactileness. In this perspective, we suggest 'visual tactility' (VT) as a parameter for delivering tangibility in visual presentation. By measuring visual tactility in different product types, latent factors of visual tactility were identified and their influence on purchase intention was determined in this study. We defined material properties of touch such as surface texture, hardness, temperature, and weight as Visual Tactility (VT), the influential factor of tactility. We investigated the influence of VT on product purchase intention and analyzed tactileness within four online product presentations: single static picture, multi static pictures, zoom, and video. Our purpose was to investigate underlying effects of visual tactile attributes on touch and determine their influences according to online product presentation formats. Our results showed that visual tactility positively affected purchase intention and that each attribute differed in importance according to product type. Moreover, this study revealed a strong relation between online product presentation and VT attributes. These results provide a guide when selecting which presentation is optimal for delivering a product's tactility in online shopping situation.

• The Journal of Industrial Distribution & Business
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• v.10 no.3
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• pp.25-33
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• 2019

Purpose - With the economic development in China, the lifestyle of Chinese customers has changed dramatically. Chinese customers are more likely to have coffee in a shop with the ability to make them happy than those with high quality coffee in a nice physical environment. Happiness becomes a critical driver of customers' intention to purchase a cup of coffee in a specific coffee shop again and again. As a result, happiness becomes an important factor for managers to make strategies for attracting customers. Although managers and scholars pay more attention to emphasize the importance of happiness in customers' consumption, little research has been conducted to investigate the relationship between happiness and coffee shop's continuous usage intention in the Chinese coffee industry. Research design, data, and methodology - A research model is made to explain the impact of happiness on customer's behavior. To understand the influence of happiness better, we consider two dimensions of happiness which are subjective well-being and psychological well-being. In order to confirm the relationships of the variables in the research model, the online survey is constructed in China. Customers who have experienced the services in a coffee shop are asked to do the questionnaire. With 453 reliable questionnaires, structural equation modeling is used to analyze the causal relationships of the coffee quality, physical environment, subjective well-being, psychological well-being, and continuous usage intention. Results - Results indicate that coffee quality and physical environment are not the direct factors that influence customers' continuous usage intention. However, good coffee quality and physical environment are the significant predictors of Chinese customers' happiness associated with subjective well-being and psychological well-being, which in turn affects customers' continuous usage intention. Conclusions - In this study, it is proposed that coffee quality and physical environment may be the key factors influencing customers' happiness. Happiness, including subjective well-being and psychological well-being matters in decision making process. More importantly, happiness increases the continuous usage intention when the coffee shop can serve customers with higher quality coffee at a good atmospheric place. Managers should consider happiness as an important factor in making marketing strategies to compete in this industry.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.3
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• pp.830-860
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• 2022

[Introduction] Nowadays, many companies are shifting their businesses online due to the growing trend among customers to buy and shop online, as people prefer online purchasing products. [Problem] Users share a vast amount of information about products, making it difficult and challenging for the end-users to make certain decisions. [Motivation] Therefore, we need a mechanism to automatically analyze end-user opinions, thoughts, or feelings in the social media platform about the products that might be useful for the customers to make or change their decisions about buying or purchasing specific products. [Proposed Solution] For this purpose, we proposed an automated SentiDecpective approach, which classifies end-user reviews into negative, positive, and neutral sentiments and identifies deceptive crowd-users rating information in the social media platform to help the user in decision-making. [Methodology] For this purpose, we first collected 11781 end-users comments from the Amazon store and Flipkart web application covering distant products, such as watches, mobile, shoes, clothes, and perfumes. Next, we develop a coding guideline used as a base for the comments annotation process. We then applied the content analysis approach and existing VADER library to annotate the end-user comments in the data set with the identified codes, which results in a labelled data set used as an input to the machine learning classifiers. Finally, we applied the sentiment analysis approach to identify the end-users opinions and overcome the deceptive rating information in the social media platforms by first preprocessing the input data to remove the irrelevant (stop words, special characters, etc.) data from the dataset, employing two standard resampling approaches to balance the data set, i-e, oversampling, and under-sampling, extract different features (TF-IDF and BOW) from the textual data in the data set and then train & test the machine learning algorithms by applying a standard cross-validation approach (KFold and Shuffle Split). [Results/Outcomes] Furthermore, to support our research study, we developed an automated tool that automatically analyzes each customer feedback and displays the collective sentiments of customers about a specific product with the help of a graph, which helps customers to make certain decisions. In a nutshell, our proposed sentiments approach produces good results when identifying the customer sentiments from the online user feedbacks, i-e, obtained an average 94.01% precision, 93.69% recall, and 93.81% F-measure value for classifying positive sentiments.

• Journal of Distribution Science
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• v.19 no.7
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• pp.101-111
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• 2021

Purpose: The main purpose of this research is to examine the effect of impulse buying tendencies toward impulse buying, which is mediated by an urge to buy and moderated by the gender of the retail customers. Research design, data and methodology: This study uses a survey design. The sample consisted of several mall customers in Yogyakarta. Purposive sampling was used as the sampling technique. Data collection was carried out in two ways, distributing questionnaires online and directly giving questionnaires to mall customers. Results: The results of data analysis using structural equation modeling show that: 1). Impulse buying tendencies have a positive and significant effect on the urge to buy and impulse buying, 2). The effect of impulse buying tendencies on impulse buying were mediated by an urge to buy and moderated by gender. Conclusions: Theoretical implications of this research strengthen the concept/theory concerning the relationship of the impulse buying tendencies, urge to buy and impulse buying. The results of the study have some managerial implications. It can be used to reference retail store business in increasing the volume of retail customers purchases through impulse buying. The retail businesses can increase impulse buying which will trigger impulsive purchases and the company's sales and profitability