• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.983-992
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• 2021

This study aims to examine the impact of customer experience and customer engagement on customer satisfaction and customer loyalty in e-retailing in Indonesia. This study uses data from 512 respondents in six e-retailing namely; Bukalapak, Tokopedia, Lazada, Blibli, Shopee and Zalora which are often used by students at the Department of Management, Faculty of Economics and Business, Halu Oleo University of Indonesia. The structural model developed in this study was tested using Partial Least Squared (PLS). The results of the study found that there was a reciprocal relationship between customer experience and customer engagement. The results also found that customer experience and customer engagement have a positive and significant effect on customer satisfaction and customer loyalty. Customer satisfaction have a positive and significant effect on customer loyalty. In this study it was also found that customer experience has an indirect effect on customer satisfaction and customer loyalty through customer engagement, and customer engagement also has an indirect effect on customer satisfaction and customer loyalty through customer engagement. This study was focused on relationship between customer experience, customer engagement, satisfaction and loyalty. Therefore, future research is expected to be able to test the determinant factors of customer experience and customer engagement.

• Human Ecology Research
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• v.53 no.6
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• pp.619-628
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• 2015

Baby boomers who have rebuilt the Korean economy over the last half a century are now transitioning into a silver generation who are over 65 years of age. New silver consumers are qualitatively and quantitatively different from the previous generation and are considered to be 'the single most consumption-leading generation.' The number of new silver consumers using department stores and traditional markets has increased. SPSS ver. 21.0 was used with the methods of frequency analysis, t-test, one-way analysis of variance (ANOVA), device master record test, and regression analysis. This research studies consumer satisfaction of new silver consumers on department stores and traditional markets among retailing. The improvement of the parking environment is the most urgent issue for traditional markets because the long-term assessments of parking areas indicate that it is necessary to provide improved convenience for consumers. Salesman satisfaction has improved and consumer satisfaction ranks salesman satisfaction high for traditional markets; however, price satisfaction is low and the distribution system should be improved to supply products at a lower price. Salesman and price satisfaction should be improved at depart stores. Traditional markets should also promote consumer satisfaction through consistent management to make consumers trust information in regards to quality control and production and distribution; in addition, department stores should increase consumer satisfaction by maintaining store systems such as product diversification and display, cleanness, and atmosphere.

• Journal of the Korean Society of Clothing and Textiles
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• v.42 no.1
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• pp.148-158
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• 2018

This study analyzes recent trends in fashion retailing instigated by the fourth industrial revolution and approaches the trends in terms of the convergence of big data and artificial intelligence. The findings are as below. First, companies like 'Edited' and 'Stylumia' offer solutions that support the strategic decisions of fashion brands and fashion retailers by analyzing big data using artificial intelligence. Second, the convergence of big data and artificial intelligence scales personalized service on the web as examples of 'Coded Couture', 'StitchFix', and 'Thread'. Third, the insights gained from artificial intelligence and big data help create new fashion retailing platforms such as 'Botshop' and 'Lyst'. Last, artificial intelligence and big data assist with design. 'Ivyrevel' designs digital fashion, assisted by a macroscopic perspective on fashion trends, market and consumers through the analysis of big data. The Fourth Industrial Revolution brings changes across all industries that will likely accelerate. The fashion industry is also undergoing many changes with advancements in scientific technology. The convergence of big data and artificial intelligence will play a key role in the future of fast-moving industry like fashion, where fickle tastes of consumers are the main drivers.

• Nutrition Research and Practice
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• v.5 no.2
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• pp.163-168
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• 2011

This study was conducted to evaluate recipients' perception of service quality, satisfaction, and behavioral intention in home delivered meals program in the US. Out of 398 questionnaires, 265 (66.6%) were collected, and 209 questionnaires (52.5%) were used for the statistical analysis. A Confirmatory Factor Analysis (CFA) with a maximum likelihood was first conducted to estimate the measurement model by verifying the underlying structure of constructs. The level of internal consistency in each construct was acceptable, with Cronbach's alpha estimates ranging from 0.7 to 0.94. All of the composite reliabilities of the constructs were over the cutoff value of 0.50, ensuring adequate internal consistency of multiple items for each construct. As a second step, a Meals-On-Wheels (MOW) recipient perception model was estimated. The model's fit as indicated by these indexes was satisfactory and path coefficients were analyzed. Two paths between (1) volunteer issues and behavioral intention and (2) responsiveness and behavioral intention were not significant. The path for predicting a positive relationship between food quality and satisfaction was supported. The results show that having high food quality may create recipient satisfaction. The findings suggest that food quality and responsiveness are significant predictors of positive satisfaction. Moreover, satisfied recipients have positive behavioral intention toward MOW programs.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.403-412
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• 2021

The COVID-19 pandemic has a great impact in various ways. It changes the normal routine of lives and businesses. Many businesses encounter tremendous financial pressure, some of them lay off workers or choose to close down. According to the statistics, e-commerce experiences a four-fold growth in sales during the pandemic period. There is an urgency for firms to digitalize their businesses to respond to the change in the landscape of purchasing patterns of consumers. The purpose of this study is to understand the success of a few popular apparel brands in digital businesses. This is a qualitative research, and secondary data is collected for the analysis. The findings reveal that all of them engage in omni-channel methods in digitizing their businesses while utilizing other forms of technologies in their product and operational management. All selected firms agree with the importance of digital business, and omni-channel retailing is their choice. In these unprecedented times, the sustainable success of the apparel firms in digital businesses requires a flexible and innovative approach and a commitment to achieving operational excellence. Continuous renewal and digital transformation are needed so that these companies have the capabilities to adapt to changes and reap the benefits of a satisfactory organizational performance.

• 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.

• International Journal of Human Ecology
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• v.11 no.1
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• pp.11-22
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• 2010

The purpose of this study was to examine how congruity between self-image and store image affects a customer's satisfaction with the retailer, loyalty towards that retailer, and patronage behavior toward that retailer in a fashion retailing context. In addition to the direct effects of selfcongruity on consumer responses, the mediating roles of satisfaction and retailer loyalty were also examined. A convenience sample of 137 college students participated in an online survey. Path analysis showed that self-congruity had a direct effect on satisfaction, but not on retailer loyalty and patronage behavior. However, the effect of self-congruity on retailer loyalty and patronage behavior was fully mediated by satisfaction. Satisfaction had a positive effect on both retailer loyalty and patronage behavior. The effect of satisfaction on patronage behavior was partially mediated by retailer loyalty. As supported in the study, self-congruity can induce retailer loyalty. Given that retailers have direct control over developing a certain store image that affects perceptions of self-congruity of their target market, the findings of the study provide useful information for fashion retailers. The findings of the study add to current selfcongruity literature by extending to fashion retailing and also by examining the mediating roles of satisfaction and retailer loyalty on the effects of self-congruity.

• The Research Journal of the Costume Culture
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• v.29 no.6
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• pp.865-880
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• 2021

The purpose of this study was to examine job competencies for sales training program development to maximize profits in fashion retailing. An empirical online survey was conducted from September to December 2019, and data was collected from 200 salespeople and store managers working in fashion stores. Results were analyzed using frequency analysis, factor analysis, variance analysis, and regression analysis with SPSS 25.0. The major findings of this study were as follows. First, the most important job competencies identified by fashion store managers were: sales sense know-how, customer service skills, and sales person's fashion style sense, product knowledge, fashion marketing and customer management. The job competency factors for sales training programs included empathy with the customer, product knowledge, communications and networking, basic job requirement, and sales skills. These five factors positively influenced the employment intentions and expectations of work performance of graduates. These factors also had a positive influence on the need of sales training program and intention to participate in retraining. Store managers in fashion retail thought the most appropriate period for on-the-job training was either 2-4 days or more than 1 week. The results of this study can be used as a base to develop training programs for job efficiency for salespeople in fashion retailing.

• Journal of Distribution Science
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• v.20 no.1
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• pp.67-76
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• 2022

Purpose: The purpose is to verify the impact of the store environment on interpersonal service quality (ISQ), shopping value and patronage intention, as well as the moderating role of the store format: supermarkets vs hypermarkets. This is significant as previous studies on retailing neglected the effect of interpersonal service quality on the experiential shopping value. The comparison of the model between two retailing formats (hypermarkets and supermarkets) provides a significant contribution and responds to a need to provide insights regarding the moderation of the store types on the contribution of interpersonal service quality and experiential value to customer's retention. Research design, data, and methodology: The hypotheses have been tested after analyzing the data of a survey among 405 consumers exiting stores representing various retailing stores in Tunisia. A Structural model have been finally verified by a path analysis after applying a confirmatory factorial analysis. Multigroup analyses on AMOS allowed to verify the moderation of store types. Results: Results mainly show that patronage intention is affected by the experiential perceived value dimensions. The latter is a direct consequence of ISQ and an indirect outcome of perceived shopping environment. The impact of value, environment and ISQ is moderated by the store type.

• International Journal of Internet, Broadcasting and Communication
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• v.9 no.3
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• pp.59-69
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• 2017

The best 'hub' to communicate with the citizen is using social media to marketing the business. However, there has several issued and the most common issue that face in critical is a capital issue. This issue is always highlight because most of automatic sentiment detection tool for Facebook or any other social media price is expensive and they lack of technical skills in order to control the tool. Therefore, in directly they have some obstacle to get faster product's feedback from customers. Thus, the personal online retailing need to struggle to stay in market because they need to compete with successful online company such as G-market. Sentiment analysis also known as opinion mining. Aim of this research is develop the tool that allow user to automatic detect the sentiment comment on social media account. RAD model methodology is chosen since its have several phases could produce more activities and output. Soppy tool will be develop using Microsoft Visual. In order to generate an accurate sentiment detection, the functionality testing will be use to find the effectiveness of this Soppy tool. This proposed automated Soppy Tool would be able to provide a platform to measure the impact of the customer sentiment over the postings on their social media site. The results and findings from the impact measurement could then be use as a recommendation in the developing or reviewing to enhance the capability and the profit to their personal online retailing company.