• Journal of Distribution Science
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• v.12 no.6
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• pp.49-57
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• 2014

Purpose - The world now recognizes environmental disruption as a serious issue when regarding growth-oriented strategies; therefore, environmental preservation issues become pertinent. Consequently, green distribution is continuously emphasized. However, studying the prediction and association of distribution and the environment is insufficient. Most existing studies about green distribution are about its necessity, detailed operation methods, and political suggestions; it is necessary to study the distribution service industry and environmental service industry together, for green distribution. Research design, data, and methodology - ARIMA (auto-regressive moving average model) was used to predict the environmental service and distribution service industries, and the Granger Causality Test based on VAR (vector auto regressive) was used to analyze the causal relationship. This study used 48 quarters of time-series data, from the 4th quarter in 2001 to the 3rd quarter in 2013, about each business type's production index, and used an unchangeable index. The production index about the business type is classified into the current index and the unchangeable index. The unchangeable index divides the current index into deflators to remove fluctuation. Therefore, it is easy to analyze the actual production index. This study used the unchangeable index. Results - The production index of the distribution service industry and the production index of the environmental service industry consider the autocorrelation coefficient and partial autocorrelation coefficient; therefore, ARIMA(0,0,2)(0,1,1)4 and ARIMA(3,1,0)(0,1,1)4 were established as final prediction models, resulting in the gradual improvement in every production index of both types of business. Regarding the distribution service industry's production index, it is predicted that the 4th quarter in 2014 is 114.35, and the 4th quarter in 2015 is 123.48. Moreover, regarding the environmental service industry's production index, it is predicted that the 4th quarter in 2014 is 110.95, and the 4th quarter in 2015 is 111.67. In a causal relationship analysis, the environmental service industry impacts the distribution service industry, but the distribution service industry does not impact the environmental service industry. Conclusions - This study predicted the distribution service industry and environmental service industry with the ARIMA model, and examined the causal relationship between them through the Granger causality test based on the VAR Model. Prediction reveals the seasonality and gradual increase in the two industries. Moreover, the environmental service industry impacts the distribution service industry, but the distribution service industry does not impact the environmental service industry. This study contributed academically by offering base line data needed in the establishment of a future style of management and policy directions for the two industries through the prediction of the distribution service industry and the environmental service industry, and tested a causal relationship between them, which is insufficient in existing studies. The limitations of this study are that deeper considerations of advanced studies are deficient, and the effect of causality between the two types of industries on the actual industry was not established.

• Journal of the Korean Society of Food Culture
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• v.31 no.4
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• pp.339-347
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• 2016

With the interest on operational efficiency due to the rapid growth of food material distribution industry and food service industry, the study adopts DEA (Data Envelopment Analysis) model and examines to measure the technological, pure technical and scale efficiency those companies engaging in the food material distribution and food service business. As a result of analysis, the companies operating integrated business have relatively higher efficiency than those operating only food material distribution or food service companies while the result indicates that three efficiencies don't have significant difference depending on whether affiliated companies or not. In the results from the measuring by DEA.

• Journal of Distribution Research
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• v.2 no.1
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• pp.59-85
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• 1997

The automobile industry in Korea has grown to the fifth in the world in terms of production capacity. In spite of the production growth, the marketing aspects such as distribution and customer service in the auto industry are still behind the world-class. Thus, the major purposes of this paper are as follows. The first is to analyze competitive structure of the industry and to compare distribution strategies of the major auto firms(Hyundai, Daewoo, and Kia). The second is to theoretically explain the transition from the vertical marketing system to the dealer system using transaction cost analysis. The third is to compare auto distribution channels in Korea with those in the U.S. and Japan. Finally, an optimal channel stucture in the auto industry is suggested after reviewing five alternative channel structures such as corporate-owned VMS, sales-specializing firm, multiplex system(VMS+limited dealer system), dual sales channel, and advanced dealer system. In the short-run, sales-specilizing firm was suggested as an optimal channel system to enhance customer satisfaction by integrating sales and customer service. In the long-run, advanced dealer system through regional differentiation was desirable for an optimal channel structure by organically integrating new car sales, used car sales, and after service to provide total marketing service to customers.

• Journal of Distribution Science
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• v.15 no.4
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• pp.69-78
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• 2017

Purpose - The study was AI as exploratory study on artificial intelligence (AI) shopping information services, to explore the possibility of a new business of the distribution industry. For research, we compare to IBM of consumer awareness surveys an AI shopping information service for retailing channel and target goods group. Finally, we present to service scenario for distribution service using AI. Research design, data, and methodology - First, to identify possible the success of the information service shopping using AI, AI technology for the consumer is very important for the acceptance of judgement. Therefore, we explored the possibility of AI information service for business as a shopping. The experimental data were used to interpret the meaning of the relevant literature and the IBM Institute of Business Value (IBV) Report 2015. This research is based on the use of a technical acceptance model (TAM) to determine whether the consumer would adopt the 'AI shopping information service' technology. Step 1 of the process assumes that the consumer adopts AI technology. In step 2, consumers find their preference channels and goods targeted at them as per their preferences. Finally Step 3, we present scenario for 'AI shopping information service' based on the results of Step 1 and 2. Results - Consumers have expressed their high interests in the new shopping information services, especially the on/off line distribution channels can use shopping information to increase the efficiency in provision of goods. Digital channel (such as SNS, online shopping etc.) is especially high value goods such as cars, furniture, and home appliances by displaying it to an appropriate product group. Conclusions - The study reveals the potential for the use of new business models such as 'AI shopping information service' by the distribution industry. We present seven scenario related AI application refer from IBM suggestion, and the findings would enable the distribution industry to approach target consumers with their products, especially high value goods. 'Shopping advisor' is considered to the most effective. In order to apply to the other field of the distribution industry business, which utilizes AI technology, it should be accompanied by additional empirical data analysis should be undertaken.

• Journal of Distribution Science
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• v.20 no.6
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• pp.87-97
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• 2022

Purpose: In the last few decades, the ceramic industry has become an important industry for Indonesia. The resulting product must be handled properly, because if material & product handling is not carried out properly it will impact on the quality of product. Based on the logistics outsourcing research gaps in the ceramics industry to logistics service provider (LSP), this study aims to analyze the logistics service improvement of LSP in accordance with the needs of the ceramic industry to minimize logistics outsourcing risks. Research design, data and methodology: In the field study, observations, interviews and surveys related to production and logistics activities in the ceramic industry & LSP were carried out. The next step is to analyze logistics service of LSP needed by the ceramic industry. Results: The final findings obtained from this research are the LSP need to improve 1) knowledge; 2) technology capability; 3) relationships; 4) service quality; 5) innovation; 6) commitment in services. Conclusion: In order to reduce logistics outsourcing risks in the ceramic industry, LSP in Indonesia need to improve the logistics services required by the ceramic industry with a focus on six areas of improvement.

• Journal of Distribution Science
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• v.22 no.5
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• pp.117-129
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• 2024

Purpose: This research aims to explore the ramifications of job stress on cabin crews within the air service distribution sector, specifically examining its impact on service quality through mediating variables such as job satisfaction and engagement during the pandemic era. Research design, data and methodology: The study is based on a sample size of 312 individuals, exclusively comprising cabin crews employed in the airline industry. Methodologically, Confirmatory Factor Analysis (CFA) and Structural Equation Modeling (SEM) were employed for statistical analysis. Results: The findings reveal that both performance evaluation and job responsibility exerted a significant impact on both job satisfaction and job engagement. Furthermore, job engagement demonstrated a substantial influence on service quality. However, in contrast, factors like unstable employment and the working environment showed no significant impact on either job satisfaction or engagement. Additionally, job satisfaction did not exert a significant influence on service quality. Conclusions: These insights will offer the valuable guidance to the airline industry in preparing for unforeseen external environments that may affect the industry. As the aviation sector navigates the challenges posed by the pandemic, understanding and addressing the intricate relationships among job stress, satisfaction, engagement, and service quality will be crucial for effective industry resilience and adaptation.

• Journal of Distribution Science
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• v.12 no.11
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• pp.25-34
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• 2014

Purpose - Considering that the governments' official statistics on the optimum scale of the domestic service industry will be crucial in future, this study's results will be used as an important benchmark to develop and verify the parameters in the government's official statistics. Research design, data, and methodology - To identify the appropriate scale of Korea's service industry and its adequacy, I have determined them through estimation using a regression method involving panel data analysis on the panel data of 30 OECD countries. Results - The regression coefficient provided indications of being non-linear. This means that a U-shaped curve relationship exists-that is, the level of the economic growth leverage decreases along with the service industry's growth up to the level of 70.9% in terms of the Korean service industry's adequacy; it increases along with the service industry's growth at a level higher than 70.9%. Conclusions - While the current proportion of the size of the service industry among all industries in Korea stands at 50.7%, its proper proportion estimated by a regression analysis was 70.9%.

• Journal of Distribution Science
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• v.14 no.8
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• pp.45-50
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• 2016

Purpose - This study aimed to develop a new practical and universally applicable service quality model by improving the service quality measurement model proposed by many previous studies. Research design, data, and methodology - An in-depth analysis on what influences such service quality model had on the improvement effect of service quality, and Service Evaluation Model("SEM"), which was revised from the existing service quality measurement model, was developed. The model is divided into the two integrative categories: First, activity, that is the group of service-related activities. Next is item, the group of service-related objects. The level of service is evaluated for each category via survey questionnaire on service level evaluation. Based on the model, SEM has visibility by structuring the whole service industry. Results - For the application of the new service quality model, this study attempted to examine the appropriateness of the newly proposed service quality model by applying it to retail service field. Conclusions - As a result, the proposed service model would be a useful and applicable service quality measurement model required by many organizations. Service company can set up self check service levels. Through these results, they can look for the ways to provide better services to customers. Service users can ensure the objectivity of business plan based upon SEM.

• Journal of Distribution Science
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• v.17 no.11
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• pp.73-79
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• 2019

Purpose: The purpose of this study was evaluated to compare the predictive power of distress prediction models by using discriminant analysis method and logit analysis method for food service franchise industry in Korea. Research design, data and methodology: Forty-six food service franchise industry with high sales volume in the 2017 were selected as the sample food service franchise industry for analysis. The fourteen financial ratios for analysis were calculated from the data in the 2017 statement of financial position and income statement of forty-six food service franchise industry in Korea. The fourteen financial ratios were used as sample data and analyzed by t-test. As a result seven statistically significant independent variables were chosen. The analysis method of the distress prediction model was performed by logit analysis and multiple discriminant analysis. Results: The difference between the average value of fourteen financial ratios of forty-six food service franchise industry was tested through t-test in order to extract variables that are classified as top-leveled and failure food service franchise industry among the financial ratios. As a result of the univariate test appears that the variables which differentiate the top-leveled food service franchise industry to failure food service industry are income to stockholders' equity, operating income to sales, current ratio, net income to assets, cash flows from operating activities, growth rate of operating income, and total assets turnover. The statistical significances of the seven financial ratio independent variables were also confirmed by logit analysis and discriminant analysis. Conclusions: The analysis results of the prediction accuracy of each distress prediction model in this study showed that the forecast accuracy of the prediction model by the discriminant analysis method was 84.8% and 89.1% by the logit analysis method, indicating that the logit analysis method has higher distress predictability than the discriminant analysis method. Comparing the previous distress prediction capability, which ranges from 75% to 85% by discriminant analysis and logit analysis, this study's prediction capacity, which is 84.8% in the discriminant analysis, and 89.1% in logit analysis, is found to belong to the range of previous study's prediction capacity range and is considered high number.

• Journal of Distribution Science
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• v.19 no.12
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• pp.83-89
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• 2021

Purpose: Purpose of this study is to empirically analyze influence of global competitive capability on global performance of distribution industry in South Korea. Also based on the empirical results, give managerial implication to distribution industry and contribute to academies of management. Research design, data and methodology: This study focuses on relationship analysis between global competitive capability and global performance. This study measured global competitive capability with three concepts; human capability, network capability and product/service capability. And measured global performance with export performance. To empirically analyze relationship between variables, this study used 2,316 data of GCL Test by KOTRA and Kdata. This study used SPSS26 and analyzed frequency, reliability, correlation and stepwise regression analysis. Results: Result shows that, in control variable, business period and business field give significant positive influence on export performance. Among antecedents, human capability and network capability give significant positive influence on export performance. However, product/goods/service was not significant. Due to significant influence of business field which is categorical variable. This study additionally analyze relationship by business field group to confirm whether relationship differ by group or similar. Conclusions: Based on the results, this study try to give implication to distribution industry management and contribute to academic.