An IPA model was used to evaluate customer service encounters at a large food court; also the gaps between importance and performance from were also evaluated from both perspectives. The findings of this study will be applied in order to improve service quality at various large food service operations. A total of 298 customers from a large shopping mall food court completed the study questionnaire, asking them to evaluate the important and performance attributes of service. Seven underlying dimensions were identified and labeled by factor analysis: factor 1 was "safety": factor 2 "time": factor 3 "atmosphere": factor 4 "quality of food": factor 5 "menu attributes": factor 6 "comfort": and the last and seventh factor was "comprehension". As a result of IPA analysis the overall mean scores between the importance attributes and performance attributes showed significant differences by independent t-tests(p<0.001). Quadrant I was classified with unnecessary items including interior design, proper lighting, suitable chairs, and proper room temperature. In quadrant II thirteen variables showed high scores for both importance and performance, such as various menu choices, hygienic food, dishes, chairs, food court, kitchen, and employees; proper ventilation, employee kindness, waiting time to order, and received food; automatic system for ordering-serving. Quadrant III included eight variables identified as low priority, including appearance of food, nutrient content of food, proper portions, new menu, proper music, proper location of cashier, services for children and efficiency of movement. In quadrant IV six variables were included as areas to focus management's efforts, such as food taste, proper food temperature, use of safe food materials, maintenance of food quality, existence of preferred foods, and proper food prices. These results suggest that food court customers have interests that are distinct from restaurant customers and may need to be treated differently. It is anticipated that this data will be useful to the foodservice industry in order to segment customer characteristics by different dinning behaviors.
Journal of Korean Society of Industrial and Systems Engineering
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v.39
no.2
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pp.138-149
/
2016
Quality function deployment (QFD) is a widely adopted customer-oriented product development methodology by translating customer requirements (CRs) into technical attributes (TAs), and subsequently into parts characteristics, process plans, and manufacturing operations. A main activity in QFD planning process is the determination of the target levels of TAs of a product so as to achieve a high level of customer satisfaction using the data or information included in the houses of quality (HoQ). Gathering the information or data for a HoQ may involve various inputs in the form of linguistic data which are inherently vague, or human perception, judgement and evaluation for the information and data. This research focuses on how to deal with this kind of impreciseness in QFD optimization. In this paper, it is assumed as more realistic situation that the values of TAs are taken as discrete, which means each TA has a few alternatives, as well as the customer satisfaction level acquired by each alternative of TAs and related cost are determined based on subjective or imprecise information and/or data. To handle these imprecise information and/or data, an approach using some basic definitions of fuzzy sets and the signed distance method for ranking fuzzy numbers is proposed. An example of a washing machine under two-segment market is provided for illustrating the proposed approach, and in this example, the difference between the optimal solution from the fuzzy model and that from the crisp model is compared as well as the advantage of using the fuzzy model is drawn.
Most banks use only demographic information such as gender, age, occupation and address to segment customers, but they do not reflect financial behavior patterns of customers. In this study, we aim to solve the problems by using various big data in a bank and to develop customer segmentation method which can be widely used in many banks in the future. In this paper, we propose an approach of segmenting clustering blocks with bottom-up method. This method has an advantage that it can accurately reflect various financial needs of customers based on various transaction patterns, channel contact patterns, and existing demographic information. Based on this, we will develop various marketing models such as product recommendation, financial need rating calculation, and customer churn-out prediction based on this, and we will adapt this models for the marketing strategy of NH Bank.
Purpose: We consider export of Korea for Muslim population of Cairo residents in Egypt. Product instant cup noodle and yuzu tea are mainly focused on Kano model and Timko's customer satisfaction factor (CS - Coefficient) analysis and conjoint analysis. Methods: Based on the evaluation and conjoint analysis, cluster analysis was additionally applied to further exploratory research as to what kind of population the target customer has. A total of 120 people, each 60 people each, were prosecuted for Muslim women, middle middle class who had over 3,000 Korean won annual income for that study, and in Cairo in August 18. Results: The Kano analysis result Instant cup noodles act as attractive elements for packaging state, cooking method, smell and convenience, and Yuzu tea acted as an attractive element of taste, eating method, raw materials, efficacy, packaging form. Customer satisfaction factor, instant cup noodles, capacity and noodle thickness was a factor of indifference in Kano analysis, but acted as an attractive factor, the way to eat citron tea was classified as a factor of indifference. Conclusion: In the case of instant cup noodles, we first set up the taste of chicken-based soup with high appreciation as a whole, a group that likes chicken-based soup taste and oil noodles for each market segment, a taste of beef based soup And popular group that likes raw noodles Appears that diversification is necessary, and it has been found that it is necessary to develop a product type by hierarchy and marketing with different size priority from group packaging container. In the case of Yuzu tea, it is indispensable to emphasize the efficacy, in particular, energy recovery preference appears high, appealing point matching the needs of energy recovery is necessary, release the citrus fruit as a product without buckwheat in Bisson Ho, the packaging container, The group that likes cups and sticks is different and we found that it is necessary to prepare all two types.
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.
One of the recent research trends that universities are increasingly adopting the concept of 'customer' and the customer-oriented strategy has urged us to research enterprise-wide CRM strategy adaptable to university administration. As the first step of CRM strategy for university management, we try to validate the difference of CRM strategic factors among university types. Drawing upon both CRM process and customer equity drivers, which have been recognized as core frameworks for CRM strategy, we developed those survey instruments adoptable into university industry, and validated statistically-significant difference among 12 types of university group constructed by the levels of university evaluation and the location of the universities. We collected 261 responses from 177 universities from all over the country and analyzed the data to see the levels of CRM processes consisting of customer acquisition, retention, and expansion, and customer equity drivers consisting of value equity, brand equity, and relationship equity by using multivariate ANOVA(MANOVA). The result confirms the explicit differences of the levels of CRM processes and customer equity drivers between the groups by university evaluation levels(high/middle/low). However, the analysis failed to show the significant differences of those between the group by university locations(the capital/the suburbs/the six megalopolises/other countries). More specifically, the level of activities for customer acquisition and retention of the universities in the higher-graded group are significantly different from those in the lower-graded group from the perspective of CRM process. In terms of customer equity drivers, the levels of both brand equity and relationship equity of the higher-graded group are significantly higher than those of both middle and lower-graded group. In addition, we found that the value equity between the higher and lower-graded groups, and the brand equity between the middle and lower-graded groups are different each other. This study provides an important meaning in that we tried to consider CRM strategy which has been mainly addressed in profit-making industries in terms of non-profit organization context. Our endeavors to develop and validate empirical measurements adoptable to university context could be an academic contribution. In terms of practical meaning, the processes and results of this study might be a guideline to many universities to build their own CRM strategies. According to the research results, those insights could be expressed in several messages. First, we propose to universities that they should plan their own differentiated CRM strategies according to their positions in terms of university evaluation. For example, although it is acceptable that a university in lower-level group might follow the CRM process strategy of the middle-level group universities, it is not a good idea to imitate the customer acquisition and retention activities of the higher-level group universities. Moreover, since this study reported that the level of universities' brand equity is just correlated with the level of university evaluation, it might be pointless for the middle or lower-leveled universities if they just copy their brand equity strategies from those of higher-leveled ones even though such activities are seemingly attractive. Meanwhile, the difference of CRM strategy by university position might provide universities with the direction where they should go for their CRM strategies. For instance, our study implies that the lower-positioned universities should improve all of the customer equity drivers with concerted efforts because their value, brand, and relationship equities are inferior compared with the higher and middle-positioned universities' ones. This also means that they should focus on customer acquisition and expansion initiatives rather than those for customer retention because all of the customer equity drivers could be influenced by the two kinds of CRM processes (KIm and Lee, 2010). Surely specific and detailed action plans for enhancing customer equity drivers should be developed after grasping their customer migration patterns illustrated by the rates of acquisition, retention, upgrade, downgrade, and defection for each customer segment.
Journal of the Korean Operations Research and Management Science Society
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v.33
no.1
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pp.1-17
/
2008
Market segmentation is a key strategic factor in increasing the expected profits, especially in the practice of revenue management. A manufacturing firm should manage both manufacturing quantities and pricing decisions over its segmented markets to maximize the expected profits, setting different price for each different segment. Also, market segments should be kept separate in order to prevent demand leakages between different market segments. In fact, even though the markets for different products are firmly segmented, it is not easy to keep separate segmentation because many products might be substitutable by customer buying behavior. That is, customers respond to price changes by purchasing other market's products instead of purchasing the originally requested products, which causes demand substitution effect ; This kind of substitution is referred to as price-driven substitution. Therefore, decisions on optimal prices should take into account the differences in customers' valuation of the different products. We consider a deterministic model for deciding optimal prices in the presence of price-driven substitution, and we compare both symmetrical-and asymmetrical-type demand substitutions between two segmented markets. The objective of this study is to develop analytical and numerical models to examine the impact of price-driven substitution on the optimal price levels and the total expected profits.
Kim, Jong-Kook;Park, Youn-Jae;Park, Ju-Young;Choi, Ja-Young
Journal of Distribution Research
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v.12
no.4
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pp.1-25
/
2007
The purpose of this study is to provide the strategic implication of the Korean open air market by examining the factors affecting customer loyalty for various market segments as their competitive environment becomes more turbulent. We have undertaken empirical research that uses the methodology of a mixture regression modeling, as a way to ascertain the determinants of customer loyalty toward the Korean open air market, which should form the base of strategy for each segment. We construct a mixture regression model which uses perceived the Korean open air market value dimensions as explanatory variables, an income as a covariate variable, and a customer loyalty as a dependent variable. The analysis of results show that customers are statistically divided into four segments: 'Accessibility'(33.7%), 'Price'(29.7%), 'Shopping environment,'(22.0%), and 'Merchandising,'(14.5%) groups. The findings also showed that parameter estimates are different for each group, which indicates that the sensitivity to changes in the Korean traditional market perceived value and the income variable affecting customer loyalty vary among segments.
Journal of the Korean Data and Information Science Society
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v.20
no.4
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pp.673-684
/
2009
Lower Prices are offered through sales by telemarketing. This is to serve our customers by the fastest and most appropriate referral product that is most important to attract insurance. Therefore, Considering the time the customer's preferred products and preferred customer for screening and targeting, depending on what is the difference between the premiums. This study of the logistic regression model using datamining techniques, the life insurance companies in outbound telemarketing to support sales of the effect you want to validate. To join existing life insurance companies for the customer response and sales strategy based on the L segment and by age group, family-love insurance, accident insurance, and cancer insurance were in progress for the modeling. Set model based on the progress of the campaign to existing customers marketing methods and how to extract and run the model results has proven the superiority of the model. In addition, over time, depending on the aging model is set to a decline in operating profit to maximize the profits th update the model which was derived.
Journal of the Korean Operations Research and Management Science Society
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v.42
no.2
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pp.1-17
/
2017
Based on increased popularity and use of social network services as a marketing tool, social commerce became an emerging trend in e-commerce platforms. Social commerce involves sellers offering potential consumers the products and services at a lower price in a limited time period. Through comparison of the performances of domestic social commerce websites, we found that the buying environment such as price, number of available products, and the remaining time period for sale has a significant difference influencing on the purchase decisions of consumers. This study aims to analyze the interaction effects and preference levels of four characteristics (price, discount rate, number of purchases and purchase time) by conducting choice-based conjoint analysis. Survey experiment was performed using a sample of 146 undergraduate and graduate students. The results showed that consumers importantly consider purchase time, discount rate, price, number of purchases in the order of their preference. Also, discount effect is more significant on purchase decisions than price effect and consumers distinguish less the differences among the buying environment characteristics in the closing days of purchase period. Customer segmentation using the preference levels of characteristics indicates that the preference levels have different effects in the purchase utility of each segment. The proposed customer segmentation and differences in feature utilities are expected to be valuable in forming future sales promotion strategies in social commerce.
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