• Journal of Korean Society of Industrial and Systems Engineering
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• v.33 no.3
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• pp.114-122
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• 2010

The Probabilistic Traveling Salesman Problem (PTSP) is an important topic in the study of traveling salesman problem and stochastic routing problem. The goal of PTSP is to find a priori tour visiting all customers with a minimum expected length, which simply skips customers not requiring a visit in the tour. There are many existing researches for the homogeneous version of the problem, where all customers have an identical visiting probability. Otherwise, the researches for the heterogeneous version of the problem are insufficient and most of them have focused on search base algorithms. In this paper, we propose a simple construction algorithm to solve the heterogeneous PTSP. The Minimum Expected Length Insertion (MELI) algorithm is a construction algorithm and consists of processes to decide a sequence of visiting customers by inserting the one, with the minimum expected length between two customers already in the sequence. Compared with optimal solutions, the MELI algorithm generates better solutions when the average probability is low and the customers have different visiting probabilities. We also suggest a local search method which improves the initial solution generated by the MELI algorithm.

• Fashion & Textile Research Journal
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• v.6 no.2
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• pp.177-183
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• 2004

This study was interested in dissatisfaction in the service encounter from the service employee's viewpoint by exploring employee dissatisfaction and the problem customers as the causes. The study explored the incidents leading to dissatisfactory service encounters from the service employee's viewpoint, the causes of the dissatisfactory incidents, and the attitudinal, verbal and behavioral expressions of the customers involved in the incidents. Employees of the beauty service business were individually interviewed, and 204 incidents were analyzed. The incidents were categorized to identify the events and related behaviors of customers that caused employee dissatisfaction. Three major groups were classified: the way dissatisfied customers complain; customers' misbehaviors; and customers' no harmful behaviors. Further the major groups were classified into 8 categories. Based on the findings the study provided implications for employee and customer management.

• The Korean Journal of Franchise Management
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• v.11 no.3
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• pp.19-26
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• 2020

Purpose: The old axion to put the customers first (e.g., customers are king, customers are always right) has been taken for granted in the service sector. In addition, many companies in South Korea are providing customer-first education for employees at their contact points to strengthen their competitiveness. However, excessive increase in the psychological power of the customer can lead to a problem of abuse of power, called 'Gap-jil.' Despite these concerns, most companies hardly discard policies to give high priority to customers because of the assumption that it enhances customer satisfaction leading to organizational performance. However, in recent years, some franchise catering companies have posted warnings about the abuse of power by customers, and a movement to pursue a power-balancing between service providers and their customers is spreading. Research design, data, and methodology: This research is conducted to reconsider the principle of the customer-first perspective and to create a basis for arguments that can solve the problem of abuse of power, which is recognized as a serious social problem. In this research, we test and analyze the effect of customers' psychological power in the context of a restaurant on expectation for service and response to service failure. Result: The result of an experimental study shows that the effect of psychological power on customer satisfaction can be somewhat negative. Also, customers with high psychological power are more likely to have high service expectations. Especially high psychological power of customers causes a difference in the expectation level of human factors such as employee attitude, while the difference in expectations of non-human factors such as restaurant atmosphere was not statistically significant. In addition, when customers with high psychological power encounter service failure situation, they are more likely to feel disappointment and regret with a service provider. Meanwhile, the effect of psychological power on complaining behaviors are not significant. Conclusions: The findings of this research provide meaningful implications that the service providers should reconsider their existing corporate culture and management policies that put customers first. In addition, the result of this research is provided meaningful opportunities to review the management philosophy for the company's customers and the education philosophy for the employee education.

• Journal of the Korean Operations Research and Management Science Society
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• v.41 no.3
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• pp.75-96
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• 2016

This paper investigates the usefulness of drones in an urban delivery system. We define the vehicle and drone routing problem with time window (VDRPTW) and present a model that can describe a dual mode delivery system consisting of drones and vehicles in the metropolitan area. Drones are relatively free from traffic congestion but have limited flight range and capacity. Vehicles are not free from traffic congestion, and the complexity of urban road network reduces the efficiency of vehicles. Using drones and vehicles together can reduce inefficiency of the urban delivery system because of their complementary cooperation. In this paper, we assume that drones operate in a point-to-point manner between the depot and customers, and that customers in the need of fast delivery are willing to pay additional charges. For the experiment datasets, we use instances of Solomon (1987), which are well known in the Vehicle Routing Problem society. Moreover, to mirror the urban logistics demand trend, customers who want fast delivery are added to the Solomon's instances. We propose a hybrid evolutionary algorithm for solving VDRPTW. The experiment results provide different useful insights according to the geographical distributions of customers. In the instances where customers are randomly located and in instances where some customers are randomly located while others form some clusters, the dual mode delivery system displays lower total cost and higher customer satisfaction. In instances with clustered customers, the dual mode delivery system exhibits narrow competition for the total cost with the delivery system that uses only vehicles. In this case, using drones and vehicles together can reduce the level of dissatisfaction of customers who take their cargo over the time-window. From the view point of strategic flexibility, the dual mode delivery system appears to be more interesting. In meeting the objective of maximizing customer satisfaction, the use of drones and vehicles incurs less cost and requires fewer resources.

• Journal of Information Technology Services
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• v.22 no.1
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• pp.43-56
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• 2023

With the development of the e-commerce market, various types of products continue to be released. However, customers face an information overload problem in purchasing decision-making. Therefore, personalized recommendations have become an essential service in providing personalized products to customers. Recently, many studies on GCN-based recommender systems have been actively conducted. Such a methodology can address the limitation in disabling to effectively reflect the interaction between customer and product in the embedding process. However, previous studies mainly use implicit feedback data to conduct experiments. Although implicit feedback data improves the data scarcity problem, it cannot represent customers' preferences for specific products. Therefore, this study proposed a novel model combining explicit and implicit feedback to address such a limitation. This study treats the average ratings of customers and products as the features of customers and products and converts them into a high-dimensional feature vector. Then, this study combines ID embedding vectors and feature vectors in the embedding layer to learn the customer-product interaction effectively. To evaluate recommendation performance, this study used the MovieLens dataset to conduct various experiments. Experimental results showed the proposed model outperforms the state-of-the-art. Therefore, the proposed model in this study can provide an enhanced recommendation service for customers to address the information overload problem.

• Journal of the Korean Operations Research and Management Science Society
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• v.33 no.2
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• pp.115-135
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• 2008

An interesting problem in capacitated supply chains is how to guarantee customer service levels with limited resources. One of the common approaches to solve the problem is differentiating service depending on customer classes. High-priority customers receive a better service at the cost of low-priority customers' service level. One of common criteria to determine a customer's priority in practice is whether he has made a reservation before arrival or not. Customers with a reservation usually receive service based on the time the reservation was made. We examine the effect this advance information of customer arrival has on customer service levels. We show the trade-offs between the leadtime and other system characteristics such as the proportion of high-priority customers. when the service level is high. We also suggest how to differentiate service using the asymptotic ratio of the service levels for both types of customers.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.28 no.2
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• pp.8-17
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• 2005

This paper dealt with a kind of heterogeneous vehicle routing problem with known demand and time deadline of customers. The customers are supposed to have one of tight deadline and loose deadline. The demand of customers with tight deadline must be fulfilled in the deadline. However, the late delivery is allowed to customers with loose deadline. That is, the paper suggests a model to minimize total acquisition cost, total travel distance and total violation time for a fleet size and mix vehicle routing problem with time deadline, and proposes a heuristic algorithm for the model. The proposed algorithm consists of two phases, i.e. generation of an initial solution and improvement of the current solution. An initial solution is generated based on a modified insertion heuristic and iterative Improvement procedure is accomplished using neighborhood generation methods such as swap and reallocation. The proposed algorithm is evaluated using a well known numerical example.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.10a
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• pp.347-354
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• 1999

The credit rating represents an assessment of the relative level of risk associated with the timely payments required by the debt obligation. In this paper, we present a new approach to credit rating of customers based on the rough set theory. The concept of a rough set appeared to be an effective tool for the analysis of customer information systems representing knowledge gained by experience. The customer information system describes a set of customers by a set of multi-valued attributes, called condition attributes. The customers are classified into groups of risk subject to an expert's opinion, called decision attribute. A natural problem of knowledge analysis consists then in discovering relationships, in terms of decision rules, between description of customers by condition attributes and particular decisions. The rough set approach enables one to discover minimal subsets of condition attributes ensuring an acceptable quality of classification of the customers analyzed and to derive decision rules from the customer information system which can be used to support decisions about rating new customers. Using the rough set approach one analyses only facts hidden in data, it does not need any additional information about data and does not correct inconsistencies manifested in data; instead, rules produced are categorized into certain and possible. A real problem of the evaluation of the evaluation of credit rating by a department store is studied using the rough set approach.

• Journal of Distribution Science
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• v.15 no.9
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• pp.63-74
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• 2017

Purpose - The purpose of this study is to contribute to the literature on casino services by investigating critical service failures using the critical incident technique (CIT) and provide effective recovery strategies that can be adopted in practice. Research design, data, and methodology - The data were collected from Asian casinos' HNI customers in China, Japan, and the Republic of Korea. This is the first study that has investigated VIP casino customers in leading Asian countries. The research used the critical incident technique (CIT) collect and a total of 227 incidents were analyzed. Results - The results show that three main categories and eleven subcategories are deduced. The first group concerns casino service system failures. The second group relates to service providers' responses to VIP customer complaints. The last group covers employees' attitudes and behavior toward customers. Conclusions - First, the most serious service problem in casinos was the service providers' attitudes rather than the service system failures. Second, Tangible recovery strategies such as "all pay" and "additional comps" were proven to enhance a casino's image and lower customers' intentions to switch. Customers, however, preferred intangible recovery strategies such as considerate responses, reliable problem management, sincere apologies, and accurate explanations.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2007.11a
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• pp.316-321
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• 2007

The hierarchical covering location problem emphasizes the issue of locating of hierarchical facilities in order to maximize the number of customers that can be covered. In the classical HCLP(Hierarchical Covering Location Problem), it is assumed that the customers are covered completely if they are located within a specific distance from the facility, and not covered otherwise. The generalized HCLP is introduced that the coverage of customers is measured to be any real value rather than 0 or 1, where the service level may decrease according to the distance. Mixed integer programming formulation for the generalized HCLP is suggested with a partial coverage of service. Solutions are found using OPL Studio, and are evaluated for various cases.