• Journal of Korean Society of Industrial and Systems Engineering
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• v.47 no.2
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• pp.176-189
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• 2024

Vertical takeoff and landing (VTOL) is a core feature of unmanned aerial vehicles (UAVs), which are commonly referred to as drones. In emerging smart logistics, drones are expected to play an increasingly important role as mobile platforms. Therefore, research on last-mile delivery using drones is on the rise. There is a growing trend toward providing drone delivery services, particularly among retailers that handle small and lightweight items. However, there is still a lack of research on a structural definition of the VTOL drone flight model for multi-point delivery service. This paper describes a VTOL drone flight route structure for a multi-drone delivery service using rotary-wing type VTOL drones. First, we briefly explore the factors to be considered when providing drone delivery services. Second, a VTOL drone flight route model is introduced using the idea of the nested graph. Based on the proposed model, we describe various time-related attributes for delivery services using drones and present corresponding calculation methods. Additionally, as an application of the drone route model and the time attributes, we comprehensively describe a simple example of the multi-drone delivery for first-come-first-served (FCFS) services.

• Journal of Korean Society for Quality Management
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• v.43 no.3
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• pp.397-408
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• 2015

Purpose: Express mail service(EMS) supplied by 'Korea POST'is an international postal service which brings letters, documents and parcels to a destination abroad in the fastest and safest way. This service is in a tough competition with global companies such as TNT, FedEx, DHL or UPS. To build an effective strategy for being competitive, an intensive study on EMS service quality should be accomplished from a customer's perspective. Methods: Kano model and improvement gap analysis are used to categorize and prioritize EMS service quality attributes. A 5-point Lickert scale is employed to apply the Kano model and improvement gap analysis. Each quality attribute can be classified as weak in comparison with competitors, critical for improvement, or potentially competitive. Results: Price, on-time delivery and delivery quality are to be kept as is; fast delivery, parking convenience and staff expertise can be potentially competitive; and the other attributes are considered to be critical for improvement. Conclusions: Fast reimbursement and proper compensation when shipping items are lost or damaged are to be improved with high priority. Efforts to secure fast delivery, parking convenience and staff expertise are needed to be competitive in the future.

• Journal of the Korea Society for Simulation
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• v.28 no.1
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• pp.1-9
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• 2019

Recently, as the importance of warehouses has increased, much efforts are being made to improve the picking process in order to cope with a small amount of high frequency and fast delivery. This study proposes an algorithm to assign orders to pickers in the situation where Single Order Picking policy is used. This algorithm utilizes five attributes related to picking such as picking processing time, elapsed time after receipt of order, inspection/packing workstation situation, picker error, customer importance. A measure of urgency is introduced so that the units of measure for each attribute are the same. The higher the urgency, the higher the allocation priority. In the proposed algorithm, the allocation policy can be flexibly adjusted according to the operational goal of the picking system by changing the weight of each attribute. Simulation experiments were performed on a hypothetical small logistics warehouse. The results showed excellent performance in terms of system throughput and flow time.

• Journal of the East Asian Society of Dietary Life
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• v.16 no.1
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• pp.29-36
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• 2006

The purpose of this study was to measure the pizza purchasing behavioral characteristics of respondents and importances of factors affecting pizza purchase, to estimate the effects of attributes on pizza restaurant choice, and to predict probability of selecting a particular pizza restaurant The questionnaire consisted of two parts: The paired experimental profiles, purchasing behavior and importances of factors affecting pizza purchase. This study generated profiles of 16 hypothetical pizza restaurant based on the seven attributes. The profiles comprised 16 discrete sets of variables, each of which had two levels. For this study, researcher randomly selected 150 students of university as respondents. Twenty students did not complete the survey instrument, resulting in a final sample size of 129. All estimations were carried out using frequency, correlation, phreg procedure of SAS package. The results were as followed Based on the estimated model, the -2LL(B) statistic for a model with all explanatory variables was 5585.761 and the Chi-square statistic is 134.786 with 7 df (p<0.001). At p<0.001, we would reject the null hypothesis that the attributes do not influence choice. The parameter estimate for price was highest, followed by late delivery time, promised delivery time, money-back guarantee, discount, pizza variety, and pizza temperature. The result from this study suggested that there was an opportunity to increase market share and profit by improving operations so that customers receive discount and money-back guarantee simultaneously, and by reducing price, delivery time.

• Journal of KIISE:Databases
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• v.37 no.4
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• pp.177-184
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• 2010

In these day, many data including sensor, delivery, credit and stock data are generated continuously in massive quantity. It is difficult to learn from these data because they are large in volume and changing fast in their concepts. To handle these problems, learning methods based in sliding window methods over time have been used. But these approaches have a problem of rebuilding models every time new data arrive, which requires a lot of time and cost. Therefore we need very simple incremental learning methods. Bayesian method is an example of these methods but it has a disadvantage which it requries the prior knowledge(probabiltiy) of data. In this study, we propose a learning method based on attribute values. In the proposed method, even though we don't know the prior knowledge(probability) of data, we can apply our new method to data. The main concept of this method is that each attribute value is regarded as an expert learner, summing up the expert learners lead to better results. Experimental results show our learning method learns from data very fast and performs well when compared to current learning methods(decision tree and bayesian).

• Culinary science and hospitality research
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• v.5 no.2
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• pp.447-467
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• 1999

Most published work on product quality focuses on manufactured goods. The subject of service quality has received less attention. This distinction is important because some of the quality-improving strategies avaliable to manufacturers may be inappropriate for service firms. Services are performances, not objects. They are often produced in the presence of the customer, as in the cause of hotel restaurant services, quality occurs during service delivery, usually in an interaction between the customer and contact personnel of service firm. for this reason, service quality is highly dependent on the performance of employees, an organizational resource that cannot be controlled to the degree that components of tangible goods can be engineered. The study has begun as a basic study for customer satisfaction-oriented management in understanding the service quality of food & beverage products and through a systematic analysis of it. The major purpose of the study was to examine the relationship of the customer satisfaction and service quality in consideration of reliability, empathy, responsiveness, tangibility and assurance. An empirical research was conducted based on the previous theoretical studies. 286 customer at first class hotels in Seoul were selected as samples of this study. The time period of research was from February through March 1999, and answers were processed by SAS to yield frequency analysis, multivariate statistical analysis and regression analysis. The finding of the statistical treatment are frequencies, factor analysis, multiple regression analysis, path analysis. SERVQUAL method was used the service quality evaluation methods. After factor analysis, it was resulted to 3 factors. those were factor 1(assurance.empathy.responsiveness), factor 2(reliability), factor 3(tangibility). The findings of the statistical treatment are as follows. First, the attribute measurement of performance service quality was affected by customer satisfaction. Second, the attribute measurement of performance service qualify was affected by repurchase intention. Third, The attribute measurement of performance customer satisfaction was affected by repurchase intention. The result of study model was followed, service quality was affected repurchase intention than customer satisfaction. indirected effect through, service duality and customer satisfaction was affected repurchase intention.

• Journal of the Korean Society of Food Culture
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• v.21 no.1
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• pp.57-64
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• 2006

The purpose of this study was to measure the pizza purchasing behavioral characteristics of respondents and importances of factors affecting pizza purchase, to estimate the effects of attributes on pizza restaurant choice, and to predict probability of selecting a particular pizza restaurant. The questionnaire consisted of two parts: The paired experimental profiles, purchasing behavior and importances of factors affecting pizza purchase. This study generated profiles of 16 hypothetical pizza restaurant based on the seven attributes. The profiles comprised 16 discrete sets of variables, each of which had two levels. For this study, researcher randomly selected 150 students of university as respondents. Twenty students did not complete the survey instrument, resulting in a final sample size of 129. All estimations were carried out using frequencies, $X^2$, independent samples t-test, phreg procedure of SAS package. The results are as follows. Some purchasing behavioral characteristics and importances of factors affecting pizza purchase were significantly different by gender. Based on the estimated models developed for male student group and female student group, the Chi-square statistics were significant at p<0.001. The parameter estimate for late delivery time with male student group was highest, and the parameter estimate for price with female student group was highest. The pizza restaurant that charged \20,000, offered 100% discount on eleventh pizza, promised to deliver pizza in 40 mins, usually delivered the pizza as promised time, offered only 1 type of pizza crust, delivered warm pizza, offered the money-back guarantee was favored by each of male student group and female student group. The results from this study suggested that there was an opportunity to increase market share and profit by improving operations so that customers receive discount and money-back guarantee simultaneously, and by reducing price, delivery time.

• Korean Journal of Human Ecology
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• v.15 no.3
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• pp.491-499
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• 2006

The purpose of this study is to measure the pizza purchasing behavioral characteristics of respondents and importances of factors affecting pizza purchase, to estimate the effects of attributes on choice of pizza restaurant, and to predict probability of selecting a particular pizza restaurant. The questionnaire consisted of two parts: The paired experimental profiles, purchasing behavior and importances of factors affecting pizza purchase. This study generated profiles of 16 hypothetical pizza restaurants based on seven attributes. The profiles comprised 16 discrete sets of variables, each of which had two levels. For this study, researcher randomly selected 150 university students as respondents. Twenty one students did not complete the survey instrument, resulting in a final sample size of 129. All estimations were carried out using frequencies, $X^2$, independent samples t-test, phreg procedure of SAS package. The results were as followed: Some purchasing behavioral characteristics and importances of factors affecting pizza purchase were significantly different by purchase frequency. Based on the estimated models developed for the two purchase frequency groups, the Chi-square statistics were significant at p<0.001. The parameter estimate for late delivery time with frequently purchase frequency group was highest, and the parameter estimate for price with frequently purchase frequency group was highest. The pizza restaurants that charged 20,000 won, offered 100% discount on eleventh pizza, promised to deliver pizza in 20 min, usually delivered the pizza as promised, offered 2 or more types of pizza crust, delivered steaming hot pizza, and did not offer a money-back guarantee which was favored by each of the two purchase frequency groups. The results from this study suggested that there was an opportunity to increase market share and profit by improving operations so that customers can receive discount and money-back guarantee simultaneously, and by reducing price, delivery time.

• Journal of Distribution Science
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• v.13 no.1
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• pp.83-91
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• 2015

Purpose - Despite the structural irrationality of multi-level transportation and the oil price rise, the domestic freight transportation market continues to grow, mirroring the rise in e-commerce and resultant increase in courier services and freight volumes. Several studies on courier services have been conducted. However, few studies or statistics have been published regarding regular freight services although they have played a role in the freight service market. The present study identifies the characteristics of regular freight service users to seek competitiveness enhancement measures specific to regular freight services. Research design, data, and methodology - IPA is a comparative analysis of the relative importance of and satisfaction with each attribute simultaneously. This study used IPA because it facilitates the process of analyzing importance and performance, deriving implications and a visual understanding of results. To enhance the competitiveness of regular freight services, this study surveyed its current users regarding the importance of the regular freight service factors. A total of 200 copies of a questionnaire were circulated and 190 copies were returned. In addition to demographics, respondents answered questions about the importance of and satisfaction with services on a 5-point Likert scale. Excluding 3 inappropriate copies, 187 out of 190 copies were analyzed. PASW Statistics 18 was used for statistical analysis. A total of 20 question items were selected for the service factors presented in the questionnaire based on the 1st pilot survey and previous studies. Results - According to the IPA performed to compare the importance of and satisfaction with service factors, both importance and satisfaction are high in the 1st quadrant, which involves the economic advantage of using regular freight services, quick arrival at destinations, weight freight handling, and less time constraints on freight receipt/dispatch. This area requires continuous management. Satisfaction is higher than importance in the 2nd quadrant, which involves the adequacy of freight, cost savings over ordinary courier services, notification on freight arrival, and freight tracking information. This area requires intensive investment and management. Satisfaction is lower than importance in the 3rd quadrant, involving the credit card payment system, courier delivery service, distance to freight handling sites, easy access to freight handling sites, and prompt problem solving. This area requires further intensive management. Both importance and satisfaction are low in the 4th quadrant, involving the availability of collection service, storage space at freight handling sites, kindness of collection/delivery staff, kindness of outlet staff, and easy delivery checks. This area is a set of variables should be excluded from priority control targets. Conclusions - Based on the IPA, service factors that need priority controls because of high importance and low satisfaction include the credit card payment system, delivery service, distance to freight handling sites, easy access to freight handling sites, and prompt problem solving. The findings need to be applied to future marketing strategies for regular freight services and for developing competitiveness enhancement programs.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.1
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• pp.17-24
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• 2020

The traveling salesman problem is an algorithmic problem tasked with finding the shortest route that a salesman visits, visiting each city and returning to the started city. Due to the exponential time complexity of TSP, it's hard to implement on cases like amusement park or delivery. Also, TSP is hard to meet user's demand that is associated with multi-dimensional attributes like travel time, interests, waiting time because it uses only one attribute - distance between nodes. This paper proposed Top-n Skyline-Multi Dimension TSP to resolve formerly adverted problems. The proposed algorithm finds the shortest route faster than the existing method by decreasing the number of operations, selecting multi-dimensional nodes according to the dominance of skyline. In the simulation, we compared computation time of dynamic programming algorithm to the proposed a TS-MDT algorithm, and it showed that TS-MDT was faster than dynamic programming algorithm.