• 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).

• The Journal of Asian Finance, Economics and Business
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• v.8 no.5
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• pp.939-950
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• 2021

The purpose of this study was to measure the significance and contribution of sensory appeal, lifestyle, and health motive in determining coffee drink consumption. The theory adopted is the SOR (stimulus-organism-response) theory and the AISAS (attention-interest-search-action-share) model approach. Data was collected online in April-May 2020, and obtained 413 valid respondent data. The data were processed using SEM (Structural Equation Modeling) framework. The results showed that the variable sensory appeal of coffee drinks, lifestyle variables and health motive variables had a significant effect on coffee consumption. Of the 13 hypotheses proposed, nine hypotheses are accepted and four hypotheses are rejected. Sensory appeal has a positive effect on attitude and action of coffee consumption. Lifestyle has a positive effect on attitude, search, and action, whereas health motive has a positive effect on attitude of coffee consumption. Lifestyle variables have the greatest role in determining coffee consumption, followed by health motive variables and sensory appeal of coffee drinks. The SOR theory and the AISAS approach can both be used to analyze coffee drinking behavior. The research suggests that, to increase coffee consumption, a marketing approach should touch the lifestyle of the community and increase the promotion of the health aspects of coffee drinks.

• Journal of the Korean Society of Food Culture
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• v.34 no.3
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• pp.277-283
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• 2019

This study explore the market segmentation based on beer consumers' purchase motivation 1) to analyze beer consumers and markets more closely and 2) to demonstrate the characteristics of each market segment and contribute to marketing strategies with beer consumer segment. Using -administrated questionnaires asked questions recognizable beer purchase within 6 months by over 20-years-olds, this study 201 surveys online 22 days. The results as follows: beer consumers' purchase motivation consisted of three factors enhancement, social orientation, and value enhancement. Cluster analysis based on beer purchase showed that there were three groups motivation multi-motivation and motivation group based on average value of beer purchase motive factors and relative load per factor. demographic,beer drinking characteristics and group difference according to cluster gender and monthly average income, and beer drinking characteristics also significantly different by preferred beer, preferred beer type, occasion and drinking place.

• Journal of the Korean Society of Food Culture
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• v.34 no.3
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• pp.308-315
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• 2019

This study examined the service quality attributes of the CVS (Convenient Store) packed meal products by applying the Kano model. The main survey was conducted by a research company using an online survey in the form of a self-administered questionnaire. The 499 samples were limited to customers who had experienced CVS packed meal products within the last months. A total of 14 service quality attributes of the CVS premium packed meal products were categorized as four attractive qualities, one must-be quality, three one-dimensional qualities and six indifferent qualities. According to the Better and Worse quotient designed by Timko, 'coupon and sales promotion event', 'healthy menu configuration', and 'balanced nutrition' had higher levels of the Better coefficient. On the other hand, 'hygiene and cleanliness', 'the delicious food', and 'fresh ingredients' showed a higher Worse coefficient. The results also suggest that each service quality attribute is not a single dimension but a complex attribute. As a result, this research suggests that marketing practitioners should immediately identify consumer's changing perception of quality to attract new customers and prevent existing customers from leaving in the CVS premium packed meal products segment.

• 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 Korean Society of Industrial and Systems Engineering
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• v.41 no.4
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• pp.131-137
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• 2018

People write reviews of numerous products or services on the Internet, in their blogs or community bulletin boards. These unstructured data contain important emotions and opinions about the author's product or service, which can provide important information for future product design or marketing. However, this text-based information cannot be evaluated quantitatively, and thus they are difficult to apply to mathematical models or optimization problems for product design and improvement. Therefore, this study proposes a method to quantitatively extract user's opinion or preference about a specific product or service by utilizing a lot of text-based information existing on the Internet or online. The extracted unstructured text information is decomposed into basic unit words, and positive rate is evaluated by using existing emotional dictionaries and additional lists proposed in this study. This can be a way to effectively utilize unstructured text data, which is being generated and stored in vast quantities, in product or service design. Finally, to verify the effectiveness of the proposed method, a case study was conducted using movie review data retrieved from a portal website. By comparing the positive rates calculated by the proposed framework with user ratings for movies, a guideline on text mining based evaluation of unstructured data is provided.

• The Research Journal of the Costume Culture
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• v.27 no.1
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• pp.20-32
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• 2019

This study examined whether and how consumers who seek a bargain in their shopping for luxury fashion brands differ from traditional luxury consumers or non-luxury consumers on their market-related attitudes. To do so, this study compared multi-dimensional perceived values, fairness price perceptions, satisfaction with purchase, brand loyalty, and future purchase intention among luxury consumers, luxury-bargain seekers, and non-luxury consumers. Data was obtained from online surveys and the market-related attitudes were compared using an ANOVA test. The comparion of three types of consumers revealed that luxury-bargain seekers and regular luxury consumers are distinct consumer markets. Overall, luxury consumers displayed high perceived values and brand loyalty and were fairly satisfied with the purchase at full-prices. On the other hand, luxury-bargain seekers showed significantly low perceived social value, perceived fairness toward the original price of the brands, and brand loyalty. They were satisfied with the bargain purchase but not likely to purchase the luxury at full-prices in the future. Understanding these distinct types of consumers and targeting them with different product and pricing strategies are important for luxury brands and retailers to expand luxury consumer base without diluting their brands' prestige image. Potential marketing strategies based on the findings of this study were suggested.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.2
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• pp.1025-1032
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• 2021

The study investigates factors affecting the loyalty of Food Delivery Application (FDA) service in Thailand. This study employs quantitative research methodology with a non-probability sampling method to draw 510 FDA samples from the FDA users in Thailand. The online questionnaires with a Cronbach's alpha coefficient of 0.886 were used as a research tool to collect data from samples. By using the Structural Equation Modeling (SEM) to analyze data, the results show that trustworthiness, social influence, system design, and task-technology fit affect the user's technology acceptance, which also show the significant relationship with the loyalty of FDA users in Thailand. The study checks the harmony with the statistics; χ2 = 258.686, df. =160, χ2/df. = 1.616, p-value = 0.050, CMIN/DF = 1.616, GFI = 0.960, AGFI = 0.969, TLI = 0.953, CFI = 0.965, RMSEA = 0.047, significant level at 0.05, along with testing the weight factor. In conclusion, the research model was harmonious with the empirical data at the significant level 0.05. The finding of this study suggested that the FDA service provider might apply this research finding to develop a greater understanding of the FDA's customer loyalty, as well as determine marketing strategies, identify opportunities, and create a competitive advantage in the future.

• The Journal of Information Systems
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• v.29 no.4
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• pp.137-151
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• 2020

Purpose Domestic asset management fintech companies are expected to grow by leaps and bounds along with the implementation of the "Data bills." Contrary to the market fever, however, academic research is insufficient. Therefore, we want to analyze user reviews of asset management fintech companies that are expected to grow significantly in the future to derive strengths and complementary points of services that have been provided, and analyze key elements of asset management fintech companies. Design/methodology/approach To analyze large amounts of review text data, this study applied text mining techniques. Bank Salad and Toss, domestic asset management application services, were selected for the study. To get the data, app reviews were crawled in the online app store and preprocessed using natural language processing techniques. Topic Modeling and Aspect-Sentiment Analysis were used as analysis methods. Findings According to the analysis results, this study was able to derive the elements that asset management fintech companies should have. As a result of Topic Modeling, 7 topics were derived from Bank Salad and Toss respectively. As a result, topics related to function and usage and topics on stability and marketing were extracted. Sentiment Analysis showed that users responded positively to function-related topics, but negatively to usage-related topics and stability topics. Through this, we were able to extract the key elements needed for asset management fintech companies.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.897-907
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• 2021

The purpose of this study is to investigate the quality of entrepreneurship - motivation, entrepreneurial orientation, and risk behavior - in relation to the odds of micro-, small- and medium-sized enterprises' (MSMEs) financial performance in Indonesia. Additionally, this paper investigates how these qualities apply for the current challenges perceived by MSMEs' entrepreneurs in Indonesia due to Covid-19 crisis; specifically, this paper examines the odds of MSMEs' financial performance during the pandemic in respect to when these qualities are implemented by the entrepreneurs. The empirical data was obtained from an online survey by means of a structured questionnaire. MSMEs surveyed were randomly selected on a national scale. To test the hypotheses, a quantitative approach is employed, using multinomial regression. The main result shows that, under normal economic environment, the more intrinsically-motivated and continuity-driven entrepreneur is, the more likely the MSME will achieve financial growth compared to remaining stagnant. To our surprise, innovativeness leads to less likelihood of MSME's financial growth, suggesting the significance of innovation does not apply to MSMEs in Indonesia. Lastly, MSMEs' risk behavior to operate in a stable business environment is found more likely to result in a better performance and is true for operational and financial risks, but not marketing risks.