• The Journal of the Korea Contents Association
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• v.15 no.1
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• pp.388-398
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• 2015

This study is to investigate an impact of emotional index, social network, and trust to customers on sales performance with emotional intelligence theory and social relationship theory. We found that the higher is seller's emotional index, the higher are cognitive and affective trust, and the high trust improves sales performance. We also found that the higher emotional index strengthens social network, but does not have an effect on cognitive and affective trust. With these results we provide the sales competency in clothing shop.

• Journal of Technology Innovation
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• v.10 no.1
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• pp.98-123
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• 2002

This study develops a Korean R&D Scoreboard which has originated from the R&D Scoreboard in United Kingdom. The Scoreboard contains details of the R&D investment, sales, growth, profits and employee numbers for Korean companies which are extracted from company annual reports and key ratios calculated, with some movements over time. Companies are classified by the Korea Standard Industrial Classification. The Scoreboard contains 190 companies which consist of 100 largest companies and 30 middle-or small-sized firms listed in Korea Stock Exchange (KSE), and 30 ventures and 30 other firms listed in KOSDAQ. The overall company R&D intensity (R&D as a percentage of sales) is 2.1% compared to the international average of 4.2%. Korea has an unusually large R&D percentage of sales in IT hardware (4.9%) and telecommunication (3.7%). R&D intensity is positively correlated with company performance measures such as profitability, sales growth, productivity and market value. For largest companies listed in KSE and ventures listed in KOSDAQ, the ratio of operating profit to sales is greater for high R&D intensity companies. Sales growth is in proportion to R&D intensity for all companies. Plots of value added per employee or sales per employee vs R&D per employee rise together for the sectors studied, especially for the chemical sectors and automobile sectors, demonstrating a correlation with productivity. The average market value of high R&D companies in the KSE has risen more than 1.6 times that of the KOSPI 200 index. Given the correlation between R&D intensity and company performance and given that R&D is a smaller percentage of surplus (profits plus R&D) than international level (both overall and in several sectors), the challenges facing Korean companies are to maintain the leading position in IT hardware and telecommunication, and to increase the intensity of R&D in many medium-intensive R&D sectors where Korea has an average intensity well below international or US levels.

• The Journal of the Korea Contents Association
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• v.8 no.11
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• pp.296-305
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• 2008

This paper aims to examine the location factors affecting small service business performance, especially hair-style service business sales which are assumed to be dependent on outskirts' residents. In contrast to the prior research, this study measures sales amount as business success factors rather than business man's satisfaction level or customers' royalty. The empirical results show that hair-style service business can be determined by visibility and access level of its shop. In addition, its sales can be influenced by hairstyling chair, but its sales per a designer can impacted by hairstyling chair. This study also presents additional examinations about several independent factors which can have influence on hair-style business performance and several location traits that can have an significant influence on its sales volume.

• East Asian Journal of Business Economics (EAJBE)
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• v.12 no.1
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• pp.1-11
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• 2024

Purpose: This study empirically examines the relations among corporate performance, technology, and corporate capabilities for service companies to find factors that could affect the competitiveness of the service industry. Most study on technology in the service industry have been conducted in developed countries, and yet there exist not sufficient empirical reviews. Research design, data and methodology: This paper, using rare empirical data, examines Korea's service industry and aims to make an academic and managerial contribution to the understanding of the relation between corporate competence and performance. This study analyzes 567 Korean Domestic Companies in Non-manufacturing and Service Industry, using the 2020 Detailed Survey of Venture Businesses (2500) data. Frequency analysis, correlation analysis, and regression analysis are performed. Results: Results show, Hypothesis 1 that internal competence has positive influence on technological strength, is supported. However, Hypothesis 2 that technological strength mediates between internal competence and business performance, Hypothesis 3 that external competence has positive influence on technological strength and Hypothesis 4 that technological strength mediates between external competence and business performance are all partially supported/rejected. Conclusions: This study suggests that technological strength is an important factor that affects both market share and sales. And mediating effect of technology strength emphasized in market share. However, in managing sales, more cautious approach and a more detailed analysis are needed..

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.1-22
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• 2017

Analysis of future business or investment opportunities, such as business feasibility analysis and company or technology valuation, necessitate objective estimation on the relevant market and expected sales. While there are various ways to classify the estimation methods of these new sales or market size, they can be broadly divided into top-down and bottom-up approaches by benchmark references. Both methods, however, require a lot of resources and time. Therefore, we propose a data-based intelligent demand forecasting system to support evaluation of new business. This study focuses on analogical forecasting, one of the traditional quantitative forecasting methods, to develop sales forecasting intelligence systems for new businesses. Instead of simply estimating sales for a few years, we hereby propose a method of estimating the sales of new businesses by using the initial sales and the sales growth rate of similar companies. To demonstrate the appropriateness of this method, it is examined whether the sales performance of recently established companies in the same industry category in Korea can be utilized as a reference variable for the analogical forecasting. In this study, we examined whether the phenomenon of "mean reversion" was observed in the sales of start-up companies in order to identify errors in estimating sales of new businesses based on industry sales growth rate and whether the differences in business environment resulting from the different timing of business launch affects growth rate. We also conducted analyses of variance (ANOVA) and latent growth model (LGM) to identify differences in sales growth rates by industry category. Based on the results, we proposed industry-specific range and linear forecasting models. This study analyzed the sales of only 150,000 start-up companies in Korea in the last 10 years, and identified that the average growth rate of start-ups in Korea is higher than the industry average in the first few years, but it shortly shows the phenomenon of mean-reversion. In addition, although the start-up founding juncture affects the sales growth rate, it is not high significantly and the sales growth rate can be different according to the industry classification. Utilizing both this phenomenon and the performance of start-up companies in relevant industries, we have proposed two models of new business sales based on the sales growth rate. The method proposed in this study makes it possible to objectively and quickly estimate the sales of new business by industry, and it is expected to provide reference information to judge whether sales estimated by other methods (top-down/bottom-up approach) pass the bounds from ordinary cases in relevant industry. In particular, the results of this study can be practically used as useful reference information for business feasibility analysis or technical valuation for entering new business. When using the existing top-down method, it can be used to set the range of market size or market share. As well, when using the bottom-up method, the estimation period may be set in accordance of the mean reverting period information for the growth rate. The two models proposed in this study will enable rapid and objective sales estimation of new businesses, and are expected to improve the efficiency of business feasibility analysis and technology valuation process by developing intelligent information system. In academic perspectives, it is a very important discovery that the phenomenon of 'mean reversion' is found among start-up companies out of general small-and-medium enterprises (SMEs) as well as stable companies such as listed companies. In particular, there exists the significance of this study in that over the large-scale data the mean reverting phenomenon of the start-up firms' sales growth rate is different from that of the listed companies, and that there is a difference in each industry. If a linear model, which is useful for estimating the sales of a specific company, is highly likely to be utilized in practical aspects, it can be explained that the range model, which can be used for the estimation method of the sales of the unspecified firms, is highly likely to be used in political aspects. It implies that when analyzing the business activities and performance of a specific industry group or enterprise group there is political usability in that the range model enables to provide references and compare them by data based start-up sales forecasting system.

• Journal of the Korea Fashion and Costume Design Association
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• v.18 no.3
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• pp.1-19
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• 2016

This study tried to find out implementation factors of internal marketing for a cosmetic retailer, and to look into their effects on Salesperson's job satisfaction, organization commitment, customer orientation and sales performance. For this, this study inquired into the concepts and relationships of internal marketing, job satisfaction, organization commitment, customer orientation and sales performance through literature review; and tested the relationships between the variables by setting up a research model and hypotheses. The findings of this study may be summarized as follows: First, it was found that the better the education & training, the supervisor support and the compensation system among internal marketing factors of a cosmetic retailer were, the higher a door-to-door salesperson's job satisfaction was. Second, it was found that the better internal communication and the education & training among internal marketing factors of a cosmetic retailer were, the higher a door-to-door salesperson's organization commitment was. Third, the higher the job satisfaction of a door-to-door salesperson in a cosmetic retailer was, the higher the organization commitment was. Fourth, it was found that the higher the organization commitment of a door-to-door salesperson in a cosmetic retailer was, the higher the customer orientation was. Fifth, it was found that the higher the organization commitment and customer orientation of a door-to-door salesperson in a cosmetic retailer were, the higher the sales performance was. In conclusion, the internal marketing increases door-to-door Salesperson's job satisfaction, and enhances the sense of belonging to their cosmetic retailer. Further, they come to have a customer-oriented attitude in serving customers, which is directly connected to sales performance, and thus the retailer can create profits through internal marketing. Therefore, a cosmetic retailer will need to strengthen internal communication activities through diverse methods, expand and activate employees' professional education, and develop fair and just compensation system; and supervisors will need to give support to employees, trusting their judgment.

• The Research Journal of the Costume Culture
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• v.29 no.6
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• pp.865-880
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• 2021

The purpose of this study was to examine job competencies for sales training program development to maximize profits in fashion retailing. An empirical online survey was conducted from September to December 2019, and data was collected from 200 salespeople and store managers working in fashion stores. Results were analyzed using frequency analysis, factor analysis, variance analysis, and regression analysis with SPSS 25.0. The major findings of this study were as follows. First, the most important job competencies identified by fashion store managers were: sales sense know-how, customer service skills, and sales person's fashion style sense, product knowledge, fashion marketing and customer management. The job competency factors for sales training programs included empathy with the customer, product knowledge, communications and networking, basic job requirement, and sales skills. These five factors positively influenced the employment intentions and expectations of work performance of graduates. These factors also had a positive influence on the need of sales training program and intention to participate in retraining. Store managers in fashion retail thought the most appropriate period for on-the-job training was either 2-4 days or more than 1 week. The results of this study can be used as a base to develop training programs for job efficiency for salespeople in fashion retailing.

• Journal of Agricultural Extension & Community Development
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• v.27 no.2
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• pp.65-74
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• 2020

The study aims to identify the factors affecting business performance of rural tourism operators. For this study, 1,004 questionnaires were collected by field survey of rural tourism operators. The linear multiple regression analysis were used to identify factors affecting performance of rural tourism business. The result indicate that the factors influencing the sales of rural tourism business were in order of owning sales facilities, perception of multi-functional value of agriculture and rural, group promotion, number of rooms, and gender. In the case of gender, it was found that females had a high probability of positively affecting sales. The factors influencing the satisfaction of the rural tourism business were in the order of management strategy, number of days of operation, perception of multi-functional value of agriculture and rural, and business career. In the case of management strategy, it was found that the differentiation strategy have a positively affecting the satisfaction of the rural tourism business. As for the business career, the shorter the career, the higher the probability of positively affecting the satisfaction of the rural tourism business. The results of this study would be useful for establishing strategies to improve the management performance of the rural tourism business.

• Asia Marketing Journal
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• v.15 no.2
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• pp.175-194
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• 2013

The purpose of this study is to investigate the effects of the locomotion orientation on salespeople' sales performance with the mediating effect of selling behavior(adaptive selling behavior, SOCO). And we figure out the relationship between customer-oriented selling behavior and adaptive selling behavior because those relationships are not clear. The authors infer research hypotheses based on literature review. We have confirmed the reliability and validity test and those results can be acceptable. Hypotheses test were conducted with structural equation modeling, AMOS. All paths in the research model reasoned by authors have been supported statistically at the significant level. This study with the theoretical implications is as follows. First, this study is the first attempt to investigate the path between locomotion orientation and adaptive selling behavior and SOCO. Secondly, there is an empirical conflict between our study and Franke and Park(2006)'s study. Our study was contradictory to Franke and Park(2006)'s consequences. And so, figuring out clearly those causal paths remains. This study with practical implications are as follows. First of all, the salespeople' selling performance was affected by adaptive selling behavior, customer-oriented selling behavior, and sales-oriented activities, such as the importance of selling behavior once again proven. It is necessary to enhance the capabilities that can be transformed into action appropriate to the needs of customers each sales step-by-step in the process of salespeople for various system through education and incentives, and to interact with customers and understand their customers relative to salespeople will. In order to enhance adaptive selling behavior, the company needs to do educational program and monitoring system with the positional promotion when salespeople get the high adaptive selling behavior. Secondly, the locomotion orientation of the salespeople is to cause this selling behavior. Management style to increase locomotion orientation is needed, which means, salespeople' superior about something should be conducted. In order to stimulate the selling behavior of the salespeople, most supervisors should use some managerial tools such as feedback, engagement, and rewards.

• Journal of Internet Computing and Services
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• v.23 no.3
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• pp.125-135
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• 2022

This study aims to explore variables using machine learning and provide analysis techniques suitable for predicting pharmacy sales whether government statistical indicators built to create an industrial ecosystem based on data, network, and artificial intelligence affect pharmacy sales. Therefore, this study explored predictive variables and performance through machine learning techniques such as Random Forest, XGBoost, LightGBM, and CatBoost using analysis data from January 2016 to December 2021 for 28 government statistical indicators and pharmacies in the retail sector. As a result of the analysis, economic sentiment index, economic accompanying index circulation change, and consumer sentiment index, which are economic indicators, were found to be important variables affecting pharmacy sales. As a result of examining the indicators MAE, MSE, and RMSE for regression performance, random forests showed the best performance than XGBoost, LightGBM, and CatBoost. Therefore, this study presented variables and optimal machine learning techniques that affect pharmacy sales based on machine learning results, and proposed several implications and follow-up studies.