• Journal of the Korean Society of Clothing and Textiles
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• v.41 no.1
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• pp.170-183
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• 2017

The rapid growth of digital consumption has significantly changed the shopping behavior of consumers. The consumption paradigm is changing; subsequently, an omni-channel has been introduced that empowers consumers to interact with firms through a myriad of touch points in multiple channels. This study is to understand the perceptions and behavioral characteristics of consumers in the purchase process (e.g., information search and purchase phase). A qualitative method was adopted for this study and data were collected through semi-structured in-depth interviews with 15 omni-channel consumers. The results of this study were as follows. At the information search stage, consistency was the most important consideration for consumers who also wanted to retain channel-specific benefits. Consumers also searched for differentiated information among distribution channels. At the purchase stage, participants choose a shopping channel according to shopping values. They utilized newly introduced services (e.g., "online purchase, offline pick-up", FinTech) that combine retail channels. Our findings provide significance in managing omni-channel services. First, it is recommended that fashion retailers provide seamlessly integrated experience to consumer and adopt a consumer-centered channel choice strategy. Second, fashion retailers must maintain a constant attitude toward shopping experience to fashion, such as shopping enjoyment and exclusiveness.

• Journal of Global Scholars of Marketing Science
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• v.19 no.4
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• pp.57-63
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• 2009

With an exponential increase in electronic commerce (e-commerce), marketers are attempting to gain a competitive advantage by emphasizing service quality and post interaction service aspects, which leads to customer satisfaction or behavioral consequence. Particularly for apparel, service quality is one of the key determinants in encouraging customer e-loyalty, and hence the success of apparel retailing in the context of electronic commerce. Therefore, this study explores e-service quality (E-SERVQUAL) factors and their unique effects on e-loyalty for apparel online shopping based on Parasuraman et al' s (2005) framework. Specific objectives of this study are to identify underlying dimension of E-SERVQUAL, and analyze a structural model for examining the effect of E-SERVQUAL on e-loyalty for online apparel shopping. For the theoretical framework of service quality in the context of online shopping, literatures on traditional and electronic service quality factors were comparatively reviewed, and two aspects of core and recovery services were identified. This study hypothesized that E-SERVQUAL has an effect on e-loyalty; customer satisfaction has a positive effect on e-service loyalty for apparel online shopping; and customer satisfaction mediates in the effect of E-SERVQUAL on e-loyalty for apparel online shopping. A self-administered questionnaire was developed based on literatures. A total of 252 usable questionnaires were obtained from online consumers who had purchase experience with online shopping for apparel products and reside in standard metropolitan areas, in the United States. Factor analysis (e.g., exploratory, confirmatory) was conducted to assess the validity and reliability and the structural equation model including measurement and structural models was estimated via LISREL 8.8 program. Findings showed that the E-SERVQUAL of shopping websites for apparel consisted of five factors: Compensation, Fulfillment, Efficiency, System Availability, and Responsiveness. This supports Parasuraman (2005)'s E-S-QUAL encompassing two aspects of core service (e.g., fulfillment, efficiency, system availability) and recovery related service (e.g., compensation, responsiveness) in the context of apparel shopping online. In the structural equation model, there are five exogenous latent variables for e-SERVQUAL factors; and two endogenous latent variables (e.g., customer satisfaction, e-loyalty). For the measurement model, the factor loadings for each respective construct were statistically significant and were greater than .60 and internal consistency reliabilities ranged from .85 to .88. In the estimated structural model of the e-SERVEQUAL factors, the system availability was found to have direct and positive effect on e-loyalty, whereas efficiency had a negative effect on e-loyalty for apparel online shopping. However, fulfillment was not a significant predictor for explaining consequences of E-SERVQUAL for apparel online shopping. This finding implies that perceived service quality of system available was likely to increase customer satisfaction for apparel online shopping. However, it was not supported that e-loyalty was determined by service quality, because service quality has an indirect effect on e-loyalty (i.e., repurchase intention) by mediating effect of value or satisfaction in the context of online shopping for apparel. In addition, both compensation and responsiveness were found to have a significant impact on customer satisfaction, which influenced e-loyalty for apparel online shopping. Thus, there was significant indirect effect of compensation and responsiveness on e-loyalty. This suggests that the recovery-specific service factors play an important role in maximizing customer satisfaction levels and then maintaining customer loyalty to the online shopping site for apparel. The findings have both managerial and research implications. Fashion marketers can establish long-term relationship with their customers based on continuously measuring customer perceptions for recovery-related service quality, such as quick responses to problem and returns, and compensation for customers' problem after their purchases. In order to maintain e-loyalty, recovery services play an important role in the first choice websites for consumers to purchase clothing. Given that online consumers may shop anywhere, a marketing strategy for improving competitive advantages is to provide better service quality, maximize satisfaction, and turn to creating customers' e-loyalty for apparel online shopping. From a researcher's perspective, there are some limitations of this research that should be considered when interpreting its findings. For future research, findings provide a basis for the further study of this important topic along both theoretical and empirical dimensions. Based on the findings, more comprehensive models for predicting E-SERVQUAL's consequences can be developed and tested. For global fashion marketing, this study can expand to a cross-cultural approach into e-service quality for apparel by including multinational samples.

• Journal of the Korean Society of Clothing and Textiles
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• v.46 no.1
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• pp.80-98
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• 2022

Artificial intelligent chatbot services have recently become common in fashion e-retailing and are expected to improve online shopping by making it easy to recommend products. This study examines whether the perceived quality of a fashion chatbot affects consumers' trust and perception of usefulness, which in turn influences satisfaction and intention to use, in accordance with the information system success model. The study also investigates differences in perceived quality and consumer response variables between high and low groups of self-efficacy. A total of 341 consumers participated in an online survey. The results revealed that information quality and system quality had a significant impact on perceived usefulness and trust, and that service quality significantly impacted trust. Perceived usefulness and trust had a positive effect on consumer satisfaction, which in turn had a positive effect on intention to use. In addition, the findings revealed that people who had higher self-efficacy showed higher scores on perceived usefulness, trust, satisfaction, and intention to use chatbots as compared to people who had lower self-efficacy. This study suggested theoretical implications by applying the information system success model theory to fashion chatbot studies. It also suggested practical implications for e-commerce marketers developing retail strategies.

• Nutrition Research and Practice
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• v.6 no.6
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• pp.551-558
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• 2012

The purpose of this research was to investigate how university students' nutrition beliefs influence their health behavioral intention. This study used an online survey engine (Qulatrics.com) to collect data from college students. Out of 253 questionnaires collected, 251 questionnaires (99.2%) were used for the statistical analysis. Confirmatory Factor Analysis (CFA) revealed that six dimensions, "Nutrition Confidence," "Susceptibility," "Severity," "Barrier," "Benefit," "Behavioral Intention to Eat Healthy Food," and "Behavioral Intention to do Physical Activity," had construct validity; Cronbach's alpha coefficient and composite reliabilities were tested for item reliability. The results validate that objective nutrition knowledge was a good predictor of college students' nutrition confidence. The results also clearly showed that two direct measures were significant predictors of behavioral intentions as hypothesized. Perceived benefit of eating healthy food and perceived barrier for eat healthy food to had significant effects on Behavioral Intentions and was a valid measurement to use to determine Behavioral Intentions. These findings can enhance the extant literature on the universal applicability of the model and serve as useful references for further investigations of the validity of the model within other health care or foodservice settings and for other health behavioral categories.

• Fashion & Textile Research Journal
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• v.22 no.1
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• pp.25-37
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• 2020

This study investigates the clothing purchase behavior of active seniors in their 50s and 60s. Differences of clothing purchase behaviors were examined according to gender and the group classified by shopping orientation. Data were collected from September 2 to September 9, 2019 using a professional internet research panel; subsequently, 246 sets of useful data were analyzed by descriptive statistics, factor analysis, reliability analysis, t-test, chi-squared test, ANOVA and Duncan-test using SPSS 21.0. The results of this study were as follows. First, there were significant differences in clothing purchase behavior of purchase frequency, purchase item, purchase price, and purchase channel according to gender; therefore marketers need plan different merchandising and retailing strategies between man's wear and woman's wear. Second. the result of cluster analysis by shopping orientation showed that active seniors were categorized into four groups including 'active shopping pursuit', 'economic/pleasure pursuit', 'convenience/brand pursuit', and 'passive shopping pursuit'. Third, there were significant differences in demographic variables such as gender and occupation according to four categorized groups. In addition, the significant differences of clothing purchase behaviors were verified according to four groups. 'Active shopping pursuit' group was shown to make the best use of offline channels and online channels in information research and product purchase.

• Journal of Fashion Business
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• v.18 no.3
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• pp.1-13
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• 2014

This study investigated the store switching behavior of fashion stores targeting college students. A random sample of college students completed a questionnaire that contained measurements of store property, relationship quality, switching intent of store, preference of on/offline store, purchase of brand/non-brand product and monthly clothing expenses. The factors extracted as switching behavior of on/offline fashion store are store property, relationship quality and switching intent of store. Dimensions of store switching behavior in online shopping mall is revealed to be composed of diversity/ easy to search, store reliability, home page layout, sales promotion, reliability, commitment and switching intent of store. Also those of offline store is revealed to be composed of store comfort/salespeople service, product diversity, store location, product price, reliability, commitment and switching intent of store. The significant differences were found between store switching behavior of college students by preference of on/offline store and purchase of national brand/non brand. It is expected that this results can be used as a basic material for further study and setting up the fashion retailing strategies in fashion store for selling non brand products.

• Journal of Distribution Science
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• v.19 no.5
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• pp.23-34
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• 2021

Purpose: This study identifies the critical elements of relationship management required to be studied in distribution sciences to create a relational bond of watch manufacturers with their retailers in India. The offline watch retail market is undergoing a rapid transformation due to technology intervention in the product portfolio and the advent of online retailing. The study identifies the interrelationships amongst the constructs of interdependence, trust, affective commitment, and information exchange to form long-lasting relational bonds in the watch industry. Research design, data and methodology: We used a path analysis to investigate the relationship between interdependence, trust, affective commitment, and information exchange. Data has been collected from 143 watch retailers using judgmental sampling method. Results: The data analysis suggested the establishment of measurement and structural model. The absolute and relative goodness of fit models in the causal analysis are 0.628 and 0.959 suggesting a sufficient fit index. Based on the analysis of direct and indirect effects, the results indicate that trust fully mediates the effect of interdependence and information exchange of retailers with the manufacturer. Conclusions: Trust plays an important role in driving commitment and information exchange between watch manufacturers and retailers. Interdependence in the manufacturer-channel relationships would lead to affective commitment only when trust exists in the relationship. [AMAWATE, Vibhas.] in Web of Science and Scopus).

• Knowledge Management Research
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• v.19 no.4
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• pp.59-76
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• 2018

With the arrival of the big data era, customer data and data mining analysis have gradually dominated the process of Customer Relationship Management (CRM). This phenomenon indicates that customer data along with the use of information techniques (IT) have become the basis for building a successful CRM strategy. However, some companies can not discover valuable information through a large amount of customer data, which leads to the failure of making appropriate business strategy. Without suitable strategies, the companies may lose the competitive advantage or probably go bankrupt. The purpose of this study is to propose CRM strategies by segmenting customers into VIPs and Non-VIPs and identifying purchase patterns using the the VIPs' transaction data and data mining techniques (K-means clustering and association rules) of online shopping mall in Korea. The results of this paper indicate that 227 customers were segmented into VIPs among 1866 customers. And according to 51,080 transactions data of VIPs, home product and women wear are frequently associated with food, which means that the purchase of home product or women wears mainly affect the purchase of food. Therefore, marketing managers of shopping mall should consider these shopping patterns when they build CRM strategy.

• Journal of Distribution Science
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• v.20 no.3
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• pp.1-11
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• 2022

Purpose: This study aims at understanding the impacts of three omnichannel attributes (channel transparency, channel uniformity, channel convenience) and four customer perceptions (perceived innovativeness, perceived personalization, perceived risk, perceived credibility) on customer experience and channel selection decision. Research design and methodology: A quantitative online survey with 356 shoppers was executed. The partial least squares linear structural model (PLS-SEM) and Smart PLS were adopted to analyze the collected data and test the proposed hypotheses. Results: The research findings indicate four dominant results: (i) The customers' channel selection is directly determined by customer experience; perceived innovativeness; perceived personalization; perceived risk; and perceived credibility; and (ii) among these, the perceived risk shows negative impact on the customer's experience and customers' channel selection whereas others reveal the positive status; (iii) The customer experience represents the most decisive impact on the channel selection, then perceived personalization, perceived credibility, perceived innovativeness, and perceived risk. (iv) Three proposed channel attributes (transparency, uniformity, convenience) significantly influence the overall customer experience. Conclusions: This research adds to the body of knowledge in omnichannel retailing, customer experience, and customer channel selection. Furthermore, this research provides omnichannel retailers with practical implications for improving customer channel selection.

• Journal of Distribution Science
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• v.15 no.4
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• pp.69-78
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• 2017

Purpose - The study was AI as exploratory study on artificial intelligence (AI) shopping information services, to explore the possibility of a new business of the distribution industry. For research, we compare to IBM of consumer awareness surveys an AI shopping information service for retailing channel and target goods group. Finally, we present to service scenario for distribution service using AI. Research design, data, and methodology - First, to identify possible the success of the information service shopping using AI, AI technology for the consumer is very important for the acceptance of judgement. Therefore, we explored the possibility of AI information service for business as a shopping. The experimental data were used to interpret the meaning of the relevant literature and the IBM Institute of Business Value (IBV) Report 2015. This research is based on the use of a technical acceptance model (TAM) to determine whether the consumer would adopt the 'AI shopping information service' technology. Step 1 of the process assumes that the consumer adopts AI technology. In step 2, consumers find their preference channels and goods targeted at them as per their preferences. Finally Step 3, we present scenario for 'AI shopping information service' based on the results of Step 1 and 2. Results - Consumers have expressed their high interests in the new shopping information services, especially the on/off line distribution channels can use shopping information to increase the efficiency in provision of goods. Digital channel (such as SNS, online shopping etc.) is especially high value goods such as cars, furniture, and home appliances by displaying it to an appropriate product group. Conclusions - The study reveals the potential for the use of new business models such as 'AI shopping information service' by the distribution industry. We present seven scenario related AI application refer from IBM suggestion, and the findings would enable the distribution industry to approach target consumers with their products, especially high value goods. 'Shopping advisor' is considered to the most effective. In order to apply to the other field of the distribution industry business, which utilizes AI technology, it should be accompanied by additional empirical data analysis should be undertaken.