• Fashion & Textile Research Journal
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• v.10 no.1
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• pp.50-58
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• 2008

This study aims to identify whether shopping malls affect customer satisfaction significantly according to the store image assessment of consumers after their purchases. This comparative study on the store image and satisfaction level according to shopping mall type is supposed to offer useful basic data for developing a niche market while establishing market segmentation strategies for internet fashion shopping malls. As a result of an empirical analysis, it was found that important standards for assessing the store image of internet fashion shopping malls include product and information service, customer service after purchase, atmosphere, convenience and reliability, and all five factors were shown to affect the satisfaction level for all general malls significantly. However, product and information service and convenience were shown not to be significantly influential to the satisfaction level for fashion specialty mall. In addition, customer satisfaction was found to affect the customers' intention to repurchase and word of mouth. Therefore, if marketing managers of internet fashion shopping malls elevate customer satisfaction by managing the store image before the customers' purchase, they can attract customers to repurchase intention and ultimately prompt a word of mouth effect.

• Asia pacific journal of information systems
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• v.33 no.3
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• pp.737-767
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• 2023

With the availability of big customer data and advances in machine learning techniques, the prediction of customer behavior at the session-level has attracted considerable attention from marketing practitioners and scholars. This study aims to predict customer purchase conversion at the session-level by employing customer profile, transaction, and clickstream data. For this purpose, we develop a multimodal deep learning fusion model with dynamic and static features (i.e., DS-fusion). Specifically, we base page views within focal visist and recency, frequency, monetary value, and clumpiness (RFMC) for dynamic and static features, respectively, to comprehensively capture customer characteristics for buying behaviors. Our model with deep learning architectures combines these features for conversion prediction. We validate the proposed model using real-world e-commerce data. The experimental results reveal that our model outperforms unimodal classifiers with each feature and the classical machine learning models with dynamic and static features, including random forest and logistic regression. In this regard, this study sheds light on the promise of the machine learning approach with the complementary method for different modalities in predicting customer behaviors.

• Fashion & Textile Research Journal
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• v.16 no.1
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• pp.79-90
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• 2014

With the development of modern society, not only have the Internet and e-commerce been progressed but they also made 'consumption patten' diverse. Despite the internet clothing market growth, there is critical a disadvantage, which is consumers is not able to wear the products presented via online pictures. Thus, pictures on the internet are the only information customers can get, which has caused consciousness on the importance of dealing with 'customer review'. In spite of the fact that 'customer review' has undeniably evolved to be one of customers' essential requisites, the research on this subject is very limited. Until now, the studies on the internet shopping consumers' behavior mostly has to do with the features of 'customer review' such as 'a sense of exaggeration', 'usability', 'duality', 'purity', 'professionalism', 'reliability', and the 'similarity', etc.) Therefore, this study categorizes the characteristics of online shopping reviews to 'the number of reviews', 'the article-length', 'the existence of photos', 'the rewards for reviews', 'the contents of the reviews' and 'the freshness of the reviews' and reviews the impact of an features of 'customers' reviews' affecting the internet shopping sales promotion. Moreover, it is to contribute to the marketing strategies of a shopping mall by analyzing consumers' 'purchasing satisfaction', 'the intention of repurchasing', and 'the factors of viral marketing'.

• Journal of Global Scholars of Marketing Science
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• v.6
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• pp.167-184
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• 2000

Previous models of consumer post-purchase evaluation behavior have treated customer satisfaction as a transaction-specific construct. In the present paper, a conceptual framework that describes customer satisfaction measurement as a process is developed. The framework explains customer satisfaction as a dynamic process encompassing five stages-search, interaction, experience, service, and longevity. It is proposed that organizations should develop information systems to measure customer satisfaction during all five of the stages and disseminate such information throughout the organization as part of their Total Quality Management efforts.

• Asian Journal of Business Environment
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• v.9 no.4
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• pp.15-22
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• 2019

Purpose: Omni-channel retailing is a new retail phenomenon. Consumers in the omni-channel environment do not rely on one channel but integrate different channels from the same retailers freely during a particular shopping journey. The purpose of this study is to better understand omni-channel shoppers in the fashion retailing context. The present study uses consumer characteristics -- fashion innovativeness, technology innovativeness, and fashion purchase involvement -- as determinants predicting consumers' omni-channel shopping intentions for fashion products. Research design, data, and methodology: Data were collected from 403 U.S. consumers, and the Structural Equation Modeling (SEM) was performed to test proposed hypotheses. The survey for this research consisted of three parts. The first part measured consumer traits in terms of their innovativeness and purchase involvement. The second part was designed to measure consumers' omni-channel shopping intentions, and the third part gathered consumer demographic information. Results: The findings confirmed that fashion innovativeness, technology innovativeness, and fashion purchase involvement positively affected consumers' omni-channel shopping intentions. Conclusions: Fashion retailers should integrate various customer touchpoints and offer mobile-enabled technologies to boost consumer traffic to both online and offline stores. They also need to create a shopping environment that is optimized for customer engagement in various shopping processes and allow them to explore different shopping channel options for best purchase decisions.

• Journal of Wellbeing Management and Applied Psychology
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• v.3 no.3
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• pp.21-30
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• 2020

Indonesia is currently intensifying its level of awareness of the importance of starting a business as an entrepreneur. How to respond to technological developments to help support the growth of a start-up entrepreneur. Usually before buying a product, customers always think of many factors that can influence their buying decisions in online shopping. The two factors that most influencing are, Discounts and Promotions, which can greatly determine people's purchase intention, before finally buying the product. The researcher begin research with the aim to understand whether these 2 factors are factors that really affect someone's buying interest before doing online shopping. For this study, information and data collected by the survey by using means of questionnaires. And it standard measurements using a 5-point Likert scale, and processed by IBM SPSS Statistics 25 program. In this study, it has been found that indeed these two factors, Discounts and Promotions, are both influential in encouraging someone's purchase intention in conducting online shopping transactions. We found that both factors are significant and influence each other. The results of this study expected to help broaden the horizons of buyers and sellers about the benefits of discounts and promotions in online shopping.

• Journal of the Korea Society of Computer and Information
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• v.29 no.4
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• pp.177-182
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• 2024

A consumer's decisions are made by affection of product. Affection has types: evaluation, mood, emotion and sensibility that means unconscious changes. Previous researches have clarified weather factors affect to sensibility that means weather factors may have causal effects to consumer's decision making. This research utilize weather information from KMA(Korea Meteorological Administration) and SNS geographical information and text to make weather sensibility model, and clarify the model shows significant change to online shop customer's purchase behavior(purchase frequency) by merging customer's address information and geometric information of the model for apply weather model. As a result, a model utilize daily precipitation, sunshine hours, average ground temperature, and average relative humidity makes significant result to e-commerce purchase behavior frequency.

• Asia Marketing Journal
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• v.9 no.3
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• pp.75-115
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• 2007

This study investigated the effect of service provider's recovery effort and pre-failure customer-employee rapport on post-recovery consumer response such as satisfaction, purchase intention, and positive Word-of-Mouth communication. First, this study explored the interaction effect of recovery effort and customer-employee rapport on post-recovery consumer response. The result shows when the level of pre-failure customer-employee rapport is high, customer's positive responses decreased slightly even though they perceived low recovery effort. However, when the level of pre-failure customer-employee rapport is low, customer's responses were decreased considerably in case of low recovery effort. Second, this study examined 'service recovery paradox' which is post-recovery consumer's satisfaction is greater than the case of no service failure. The result shows recovery paradox was not supported in all samples regardless of the level of recovery effort and customer-employee rapport. Synthetically, customer-employee rapport took a buffering role in customer response after service failure although it's not the same as error-free state.

• Journal of Distribution Science
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• v.18 no.8
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• pp.113-125
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• 2020

Purpose: The purpose of this paper is to investigate the effect of interaction between product category (fresh vs. indulgent product) and shopping options (shipping charge and delivery time) on customer satisfaction and purchase intent in an e-commerce context. When ordering groceries online, consumers begin to allocate a larger share of their grocery budget toward product categories that generally contain healthier items at the expense of product categories that generally contain more indulgent products. Moreover, customers are extremely sensitive to shipping options such as shipping charges and delivery time. Therefore, this research investigates the issue at a more segmented level to focus on the impact that one dimension of logistics service quality - product category, shipping charge, and delivery time have on customer satisfaction and purchase intent. Research design, data, and methodology: To test the theoretically derived priori hypotheses concerning product category, shipping charges, delivery time, satisfaction, and purchase intent, this research presented a scenario-based experiment. Eight treatment groups were assigned by the method of product category (fresh produce vs. indulgent product), shipping charge (free vs. paid), and delivery time (one-day vs. two to three days). A total of 240 subjects were divided into groups and exposed to one of the eight scenarios. Participant's purchase intention was the dependent variable, and ANOVA and L-matrix were used to analyze for main and interactive effects between factors. Conclusions: Results indicated that in tests 1 and 2, free shipping and fast delivery time increased consumer satisfaction as well as purchase intent, and fast delivery moderated the impact of free shipping on consumer satisfaction and purchase intent. Test 3 showed that the effect of free shipping on consumer satisfaction and purchase intent moderated by fast delivery for indulgent products. In contrast, fast delivery for fresh products moderated the effect of paid shipping on consumer satisfaction and purchase intent. Consistent with this proposed mechanism, the relative importance of fresh produce versus indulgent products highlights the effect of shipping options on consumer satisfaction and purchase intent when ordering the target product in an e-commerce context. We conclude with a discussion of the theoretical and practical implications of our findings.

• Management Science and Financial Engineering
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• v.16 no.2
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• pp.81-97
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• 2010

Trust is one of the most important aspects of the relationship between retailers and consumers in e-commerce. Users may have concerns about transaction security or personal information leakage when they engage in transactions over the Internet. It can be difficult to attract customers if the retailers or service providers cannot establish trust with their customers. There have been many studies of trust-building mechanisms between customers and e-storefronts. However, little work has been done on identifying the relationships between customer satisfaction, purchase intention, and trust. In addition, trust building occurs in the pre- and post-purchase phases of an e-commerce transaction, as well as gradually over repeated transactions. Thus we distinguish between cue-based trust and experience-based trust. The objective of this study was to explain the impact of trust on customer satisfaction and purchase intention in relation to e-commerce sites from the perspective of a multi-dimensional concept of trust. We surveyed 350 undergraduate students and obtained 331 responses for analysis. The result of our analysis showed that cue-based trust has a positive relationship with trust based on experience. Although the two concepts of trust have positive relationships with satisfaction, the path coefficient of trust based on experience was higher than that of cue-based trust. In addition, the purchase intention mediates the relationship between cue-based trust and experience-based trust.