• Asia Marketing Journal
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• v.16 no.1
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• pp.71-100
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• 2014

While the role of emotional antecedents of effective selling behavior would be important, the issue has not been fully addressed in the sales literature. To fill this gap, we conceptualize and empirically examine the relationships among salesperson's emotional regulation processes such as emotional intelligence (EI) and emotional labor (EL), effective selling behavior, and sales performance on the basis of educational, occupational, social psychology literature and marketing literature (e.g., Henning-Thurau, Groth, Paul, and Gremler 2006; Kidwell et al. 2011; Liu et al. 2008; Mayer, Salovey, and Caruso 2008). First, salesperson's EI is defined as his or her capability that enables correct perceptions about emotional situations in sales interactions. The EI is expected to work as psychological resources for different types of EL (i.e., deep acting and surface acting) to be performed by salesperson as emotional expression strategies (e.g., Lie et al. 2008). It is, then, expected that the features of EL selected by the salesperson would lead to different levels of adaptive selling behavior (ASB) and thereby sales performance (Monaghan 2006). Further, given that salesperson's customer orientation (CO) is found to be an important correlate of ASB (Franke and Park 2006), it is expected that CO would moderate the relationship between EL and ASB (Rozell, Pettijohn, and Parker 2004). Hence, this research attempts to shed additional light on emotionally-driven (EL) as well as cognitively-driven (CO) antecedents of ASB (Frank and Park 2006). The findings of the survey research, done with 336 salespersons in insurance and financial companies, are summarized as follows. First, salespersons with a high level of EI are found to use both deep acting (regulating the emotions themselves) and surface acting (controlling only emotional expressions) in a versatile way, when implementing EL. Second, the more the salesperson performs deep acting, the more he or she shows ASB. It is, then, important for salespersons to use deep acting more frequently in the EL process in order to enhance the quality of interacting with customers through ASB. On the other hand, the salesperson's surface acting did not have a significant relationship with ASB. Moreover, CO was found to moderate the relationship between the salesperson's deep acting and ASB. That is, the context of high CO culture and individual salesperson's deep acting would synergistically make the selling efforts adaptive to customer preferences. Conceptualizing and empirically verifying the antecedent roles of important emotional constructs such as EI and EL in salesperson's effective selling behavior (ASB) and sales performance is a major theoretical contribution in the sales literature. Managerially, this research provides a deeper understanding on the nature of tasks performed by salespersons in service industries and a few guidelines for managing the sales force. First, sales organizations had better consciously assess EI capacity in the selection and nurturing processes of salespersons, given that EI can efficiently drive EL and the resulting effective selling behavior and performance. Further, the concept of EL could provide a framework to understand the salespersons' emotional experiences in depth. Especially, sales organizations may well think over how to develop deep acting capabilities of their sales representatives. In this direction, the training on deep acting strategies would be an essential task for improving effective selling behavior and performance of salespersons. This kind of training had better incorporate the perspectives of customers such that many customers can actually discern whether salespersons are doing either surface acting or deep acting. Finally, based on the synergistic effects of deep acting and CO culture, how to build and sustain CO is always an ever-important task in sales organizations. While the prior sales literature has emphasized the process and structure of highly customer-oriented sales organization, our research not only corroborates the important aspects of customer-oriented sales organization, but also adds the important dimension of competent sales representatives who can resonate with customers by deep acting for sales excellence.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.111-124
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• 2018

This study aims to develop a classification model for predicting the occurrence of hyperlipidemia, one of the chronic diseases. Prior studies applying data mining techniques for predicting disease can be classified into a model design study for predicting cardiovascular disease and a study comparing disease prediction research results. In the case of foreign literatures, studies predicting cardiovascular disease were predominant in predicting disease using data mining techniques. Although domestic studies were not much different from those of foreign countries, studies focusing on hypertension and diabetes were mainly conducted. Since hypertension and diabetes as well as chronic diseases, hyperlipidemia, are also of high importance, this study selected hyperlipidemia as the disease to be analyzed. We also developed a model for predicting hyperlipidemia using SVM and meta learning algorithms, which are already known to have excellent predictive power. In order to achieve the purpose of this study, we used data set from Korea Health Panel 2012. The Korean Health Panel produces basic data on the level of health expenditure, health level and health behavior, and has conducted an annual survey since 2008. In this study, 1,088 patients with hyperlipidemia were randomly selected from the hospitalized, outpatient, emergency, and chronic disease data of the Korean Health Panel in 2012, and 1,088 nonpatients were also randomly extracted. A total of 2,176 people were selected for the study. Three methods were used to select input variables for predicting hyperlipidemia. First, stepwise method was performed using logistic regression. Among the 17 variables, the categorical variables(except for length of smoking) are expressed as dummy variables, which are assumed to be separate variables on the basis of the reference group, and these variables were analyzed. Six variables (age, BMI, education level, marital status, smoking status, gender) excluding income level and smoking period were selected based on significance level 0.1. Second, C4.5 as a decision tree algorithm is used. The significant input variables were age, smoking status, and education level. Finally, C4.5 as a decision tree algorithm is used. In SVM, the input variables selected by genetic algorithms consisted of 6 variables such as age, marital status, education level, economic activity, smoking period, and physical activity status, and the input variables selected by genetic algorithms in artificial neural network consist of 3 variables such as age, marital status, and education level. Based on the selected parameters, we compared SVM, meta learning algorithm and other prediction models for hyperlipidemia patients, and compared the classification performances using TP rate and precision. The main results of the analysis are as follows. First, the accuracy of the SVM was 88.4% and the accuracy of the artificial neural network was 86.7%. Second, the accuracy of classification models using the selected input variables through stepwise method was slightly higher than that of classification models using the whole variables. Third, the precision of artificial neural network was higher than that of SVM when only three variables as input variables were selected by decision trees. As a result of classification models based on the input variables selected through the genetic algorithm, classification accuracy of SVM was 88.5% and that of artificial neural network was 87.9%. Finally, this study indicated that stacking as the meta learning algorithm proposed in this study, has the best performance when it uses the predicted outputs of SVM and MLP as input variables of SVM, which is a meta classifier. The purpose of this study was to predict hyperlipidemia, one of the representative chronic diseases. To do this, we used SVM and meta-learning algorithms, which is known to have high accuracy. As a result, the accuracy of classification of hyperlipidemia in the stacking as a meta learner was higher than other meta-learning algorithms. However, the predictive performance of the meta-learning algorithm proposed in this study is the same as that of SVM with the best performance (88.6%) among the single models. The limitations of this study are as follows. First, various variable selection methods were tried, but most variables used in the study were categorical dummy variables. In the case with a large number of categorical variables, the results may be different if continuous variables are used because the model can be better suited to categorical variables such as decision trees than general models such as neural networks. Despite these limitations, this study has significance in predicting hyperlipidemia with hybrid models such as met learning algorithms which have not been studied previously. It can be said that the result of improving the model accuracy by applying various variable selection techniques is meaningful. In addition, it is expected that our proposed model will be effective for the prevention and management of hyperlipidemia.

• Asia Marketing Journal
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• v.13 no.4
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• pp.55-76
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• 2012

Most people prefer to choose zero-cost products they may get without paying any money. The 'zero-cost effect' can be explained with a 'zero-cost model' where consumers attach special values to zero-cost products in a different way from general economic models (Shampanier, Mazar and Ariely 2007). If 2 different products at the regular prices of ￦200 and ￦400 simultaneously offer ￦200 discounts, the prices will be changed to ￦0 and ￦200, respectively. In spite of the same price gap of the two products after the ￦200 discounts, people are much more likely to select the free alternative than the same product at the price of ￦200. Although prior studies have focused on the 'zero-cost effect' in isolation of other factors, this study investigates the moderating effects of a self-regulatory resource and a construal level on the selection of free products. Self-regulatory resources induce people to control or regulate their behavior. However, since self-regulatory resources are limited, they are to be easily depleted when exerted (Muraven, Tice, and Baumeister 1998). Without the resources, consumers tend to become less sensitive to price changes and to spend money more extravagantly (Vohs and Faber 2007). Under this condition, they are also likely to invest less effort on their information processing and to make more intuitive decisions (Pocheptsova, Amir, Dhar, and Baumeister 2009). Therefore, context effects such as price changes and zero cost effects are less likely in the circumstances of resource depletion. In addition, construal levels have profound effects on the ways of information processing (Trope and Liberman 2003, 2010). In a high construal level, people tend to attune their minds to core features and desirability aspects, whereas, in a low construal level, they are more likely to process information based on secondary features and feasibility aspects (Khan, Zhu, and Kalra 2010). A perceived value of a product is more related to desirability whereas a zero cost or a price level is more associated with feasibility. Thus, context effects or reliance on feasibility (for instance, the zero cost effect) will be diminished in a high level construal while those effects may remain in a low level construal. When people make decisions, these 2 factors can influence the magnitude of the 'zero-cost effect'. This study ran two experiments to investigate the effects of self-regulatory resources and construal levels on the selection of a free product. Kisses and Ferrero-Rocher, which were adopted in the prior study (Shampanier et al. 2007) were also used as alternatives in Experiments 1 and 2. We designed Experiment 1 in order to test whether self-regulatory resource depletion will moderate the zero-cost effect. The level of self-regulatory resources was manipulated with two different tasks, a Sudoku task in the depletion condition and a task of drawing diagrams in the non-depletion condition. Upon completion of the manipulation task, subjects were randomly assigned to one of a decision set with a zero-cost option (i.e., Kisses ￦0, and Ferrero-Rocher ￦200) or a set without a zero-cost option (i.e., Kisses ￦200, and Ferrero-Rocher ￦400). A pair of alternatives in the two decision sets have the same price gap of ￦200 between a low-priced Kisses and a high-priced Ferrero-Rocher. Subjects in the no-depletion condition selected Kisses more often (71.88%) over Ferrero-Rocher when Kisses was free than when it was priced at ￦200 (34.88%). However, the zero-cost effect disappeared when people do not have self-regulatory resources. Experiment 2 was conducted to investigate whether constual levels influence the magnitude of the 'zero-cost effect'. To manipulate construal levels, 4 different 'why (in the high construal level condition)' or 'how (in the low construal level condition)' questions about health management were asked. They were presented with 4 boxes connected with downward arrows. In a box at the top, there was one question, 'Why do I maintain good physical health?' or 'How do I maintain good physical health?' Subjects inserted a response to the question of why or how they would maintain good physical health. Similar tasks were repeated for the 2nd, 3rd, and 4th responses. After the manipulation task, subjects were randomly assigned either to a decision set with a zero-cost option, or to a set without it, as in Experiment 1. When a low construal level is primed with 'how', subjects chose free Kisses (60.66%) more often over Ferrero-Rocher than they chose ￦200 Kisses (42.19%) over ￦400 FerreroRocher. On contrast, the zero-cost effect could not be observed any longer when a high construal level is primed with 'why'.

• Asia pacific journal of information systems
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• v.22 no.1
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• pp.29-52
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• 2012

Consumers differ in the way they make a purchase. An audio mania would willingly make a bold, yet serious, decision to buy a top-of-the-line home theater system, while he is not interested in replacing his two-decade-old shabby car. On the contrary, an automobile enthusiast wouldn't mind spending forty thousand dollars to buy a new Jaguar convertible, yet cares little about his junky component system. It is product involvement that helps us explain such differences among individuals in the purchase style. Product involvement refers to the extent to which a product is perceived to be important to a consumer (Zaichkowsky, 2001). Product involvement is an important factor that strongly influences consumer's purchase decision-making process, and thus has been of prime interest to consumer behavior researchers. Furthermore, researchers found that involvement is closely related to perceived risk (Dholakia, 2001). While abundant research exists addressing how product involvement relates to overall perceived risk, little attention has been paid to the relationship between involvement and different types of perceived risk in an electronic commerce setting. Given that perceived risk can be a substantial barrier to the online purchase (Jarvenpaa, 2000), research addressing such an issue will offer useful implications on what specific types of perceived risk an online firm should focus on mitigating if it is to increase sales to a fullest potential. Meanwhile, past research has focused on such consumer responses as information search and dissemination as a consequence of involvement, neglecting other behavioral responses like online merchant selection. For one example, will a consumer seriously considering the purchase of a pricey Guzzi bag perceive a great degree of risk associated with online buying and therefore choose to buy it from a digital storefront rather than from an online marketplace to mitigate risk? Will a consumer require greater trust on the part of the online merchant when the perceived risk of online buying is rather high? We intend to find answers to these research questions through an empirical study. This paper explores the impact of enduring product involvement and perceived risks on required trust level, and further on online merchant choice. For the purpose of the research, five types or components of perceived risk are taken into consideration, including financial, performance, delivery, psychological, and social risks. A research model has been built around the constructs under consideration, and 12 hypotheses have been developed based on the research model to examine the relationships between enduring involvement and five components of perceived risk, between five components of perceived risk and required trust level, between enduring involvement and required trust level, and finally between required trust level and preference toward an e-tailer. To attain our research objectives, we conducted an empirical analysis consisting of two phases of data collection: a pilot test and main survey. The pilot test was conducted using 25 college students to ensure that the questionnaire items are clear and straightforward. Then the main survey was conducted using 295 college students at a major university for nine days between December 13, 2010 and December 21, 2010. The measures employed to test the model included eight constructs: (1) enduring involvement, (2) financial risk, (3) performance risk, (4) delivery risk, (5) psychological risk, (6) social risk, (7) required trust level, (8) preference toward an e-tailer. The statistical package, SPSS 17.0, was used to test the internal consistency among the items within the individual measures. Based on the Cronbach's ${\alpha}$ coefficients of the individual measure, the reliability of all the variables is supported. Meanwhile, the Amos 18.0 package was employed to perform a confirmatory factor analysis designed to assess the unidimensionality of the measures. The goodness of fit for the measurement model was satisfied. Unidimensionality was tested using convergent, discriminant, and nomological validity. The statistical evidences proved that the three types of validity were all satisfied. Now the structured equation modeling technique was used to analyze the individual paths along the relationships among the research constructs. The results indicated that enduring involvement has significant positive relationships with all the five components of perceived risk, while only performance risk is significantly related to trust level required by consumers for purchase. It can be inferred from the findings that product performance problems are mostly likely to occur when a merchant behaves in an opportunistic manner. Positive relationships were also found between involvement and required trust level and between required trust level and online merchant choice. Enduring involvement is concerned with the pleasure a consumer derives from a product class and/or with the desire for knowledge for the product class, and thus is likely to motivate the consumer to look for ways of mitigating perceived risk by requiring a higher level of trust on the part of the online merchant. Likewise, a consumer requiring a high level of trust on the merchant will choose a digital storefront rather than an e-marketplace, since a digital storefront is believed to be trustworthier than an e-marketplace, as it fulfills orders by itself rather than acting as an intermediary. The findings of the present research provide both academic and practical implications. The first academic implication is that enduring product involvement is a strong motivator of consumer responses, especially the selection of a merchant, in the context of electronic shopping. Secondly, academicians are advised to pay attention to the finding that an individual component or type of perceived risk can be used as an important research construct, since it would allow one to pinpoint the specific types of risk that are influenced by antecedents or that influence consequents. Meanwhile, our research provides implications useful for online merchants (both online storefronts and e-marketplaces). Merchants may develop strategies to attract consumers by managing perceived performance risk involved in purchase decisions, since it was found to have significant positive relationship with the level of trust required by a consumer on the part of the merchant. One way to manage performance risk would be to thoroughly examine the product before shipping to ensure that it has no deficiencies or flaws. Secondly, digital storefronts are advised to focus on symbolic goods (e.g., cars, cell phones, fashion outfits, and handbags) in which consumers are relatively more involved than others, whereas e- marketplaces should put their emphasis on non-symbolic goods (e.g., drinks, books, MP3 players, and bike accessories).

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.31 no.2
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• pp.92-102
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• 2013

This study aimed to reveal the establishment process and spatial composition of TaiSho park in modern Busan. The TaiSho park is an athletic park which combines a playground and a rest facilities. The arguments on construction of playground commenced for commemorating Kameyama, Busan director official, when he moved to Taiwan in 1910. First Proposers which construct to sport park were businessman in that time. However, construction of playground was progress as a commemoration business of accession of Taisho Tenno. Playground construction got into stride by the proposal of the Busan mayor Wakamatsu in 1917. When it looks into process of discussion about a site selection candidate, norms of playground site selection are the paly ground which appropriate with effective site area and distance between park and a section of a city, in other hand, those are accessibility and budget. As a result of several arguments and actual site investigation, it was decide to select a site which enters to elementary school, after the isolation hospital relocates. The cost of construction of the TaiSho park is prepared by donation of the Busan civil. The donation fund raising committee was constituted by local commerce and industry people, a company, government, municipal offices and area, and funds was raised systematically. As a result, total amount of construction cost was made from the donation of local civil. The TaiSho park is broadly into two sectors; exercise area and rest and pleasure space. Entrance was set up in three aspects of the park and the subcontract planted. The baseball field took the seat in the central part of the park, and also prepared two tennis courts. Japanese Sumo field was also prepared for the north side of the park. The significance of the TaiSho park in Korea Park history can be summarized in South Korea's first sports park and which was made from the donation of local civil. The remained subjects from this study are to clarify the disappearance process of TaiSho park and a reason why modern Busan people want to get playground.

• Journal of Korean Society of Environmental Engineers
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• v.36 no.10
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• pp.719-723
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• 2014

For effective implementation of total maximum daily load (TMDL), this study presented the improving plans of non-point source pollution management including the classification of non-point source pollution, calculation of non-point source pollution load (generated, discharged), selection of non-point source pollution management regions and management of non-point source pollutant. First of all, the definition of point source pollution and non-point source pollution based on the legal and scientific viewpoint should be precisely classified and managed. Especially, the forest, grassland and river without occurrence of environmental damage by activity of business and human should be separately classified natural background pollutants. The unit for generated and discharged non-point source pollution should be preferentially changed according to actual condition of watershed. The calculation methods of generated and discharged non-point source pollution should be corrected consideration on the amount and duration of rainfall. While the TMDL is implemented, non-point source pollution management regions should be selected in the watersheds exceed the targeted water quality standards by the rainfall. The non-point source pollution management regions should be selected in the minimal regions where have high values of discharged non-point source pollution density in the urban area, farmland and site area except forest, grassland in the whole watershed. The non-point source pollutant treatment facilities, which take into consideration non-point source pollution load per unit area, duration of the excess concentration, realizable possibility of treatment, effectiveness of treatment cost versus point source pollutant, should be established in the regions with a large generated non-point source pollution load and a high concentration of water quality exceed the targeted water quality standards by the rainfall.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.121-142
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• 2023

As the number and weight of imported food are steadily increasing, safety management of imported food to prevent food safety accidents is becoming more important. The Ministry of Food and Drug Safety conducts on-site inspections of foreign food facilities before customs clearance as well as import inspection at the customs clearance stage. However, a data-based safety management plan for imported food is needed due to time, cost, and limited resources. In this study, we tried to increase the efficiency of the on-site inspection by preparing a machine learning prediction model that pre-selects the companies that are expected to fail before the on-site inspection. Basic information of 303,272 foreign food facilities and processing businesses collected in the Integrated Food Safety Information Network and 1,689 cases of on-site inspection information data collected from 2019 to April 2022 were collected. After preprocessing the data of foreign food facilities, only the data subject to on-site inspection were extracted using the foreign food facility_code. As a result, it consisted of a total of 1,689 data and 103 variables. For 103 variables, variables that were '0' were removed based on the Theil-U index, and after reducing by applying Multiple Correspondence Analysis, 49 characteristic variables were finally derived. We build eight different models and perform hyperparameter tuning through 5-fold cross validation. Then, the performance of the generated models are evaluated. The research purpose of selecting companies subject to on-site inspection is to maximize the recall, which is the probability of judging nonconforming companies as nonconforming. As a result of applying various algorithms of machine learning, the Random Forest model with the highest Recall_macro, AUROC, Average PR, F1-score, and Balanced Accuracy was evaluated as the best model. Finally, we apply Kernal SHAP (SHapley Additive exPlanations) to present the selection reason for nonconforming facilities of individual instances, and discuss applicability to the on-site inspection facility selection system. Based on the results of this study, it is expected that it will contribute to the efficient operation of limited resources such as manpower and budget by establishing an imported food management system through a data-based scientific risk management model.

• Korean Journal of Environment and Ecology
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• v.27 no.2
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• pp.253-265
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• 2013

This study was correlation analysis between provision and management of street green and street environment through field survey about city official roads(93 routes, 629.2km) in Seoul. Green belt under the street trees were 17.5% of all routes. Composition of street green belt width of 1~ 2m was the most common(11.6%). Management status as a protected facilities were protect frame and prtect cover installed inerval(60.1%). Interval of pruning was 63.5%. Type of tree was mainly 47.9%. Road width was mainly more than 8-line(51.3%). Sidewalk width was mainly 3~6m(84.1%)in environment status of street. Landuse was mainly commercial and business(70.3%). Electronic wire complete was mainly compete with crown(33.6%). Use of sidewalk was mainly used(16.3%). ANOVA analysis was conducted between the Street green and environment of Street. Street green belt(more than with 3m) was analyzed to be effective in street green manufacture. Natural green area of city's outside and Industrial area were analyzed to be effective. Use of sidewalk was to be a management. Protection facilities are installed on the narrow sidewalk width lower intensity. There was a higher strength in narrow sidewalk width, road width and compete with crown. And type of tree was higher strength similarly. Pruning and type of tree showd a significant correlation. Thus, ensure sufficient sidewalk width and land use should be considered for street green was effective manufacture and management. Species selection and pruning management was needed by consider electronic wire management, type of tree and landscape.

• Management & Information Systems Review
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• v.34 no.4
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• pp.1-13
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• 2015

This paper presents a mathematical formulation for container slot chartering model through strategic alliance between liner shipping companies. This paper develops a solution procedure to apply the model to real world problems and its applicability is demonstrated by a numerical example. The model presented in this paper has some important features which have never been considered in the previous researches. The model is linear model and pursuits profit maximization. And also it considers slot chartering capacity selection. This paper attempts to perform sensitivity analysis and compares slot chartering model with basic non-collaborating model in which there is no alliance and collaboration. As a result of sensitivity analysis, some interesting findings are obtained; Even though freight rate is more and more decreasing, the profit by slot chartering model is always higher than the basic model but the profit gaps become smaller. But The ratio of the profit gap to the profit of basic model is more increasing.

• Journal of Distribution Science
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• v.13 no.9
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• pp.103-112
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• 2015

Purpose - This paper aims to provide a step-by-step approach to factor analytic procedures, such as principal component analysis (PCA) and exploratory factor analysis (EFA), and to offer a guideline for factor analysis. Authors have argued that the results of PCA and EFA are substantially similar. Additionally, they assert that PCA is a more appropriate technique for factor analysis because PCA produces easily interpreted results that are likely to be the basis of better decisions. For these reasons, many researchers have used PCA as a technique instead of EFA. However, these techniques are clearly different. PCA should be used for data reduction. On the other hand, EFA has been tailored to identify any underlying factor structure, a set of measured variables that cause the manifest variables to covary. Thus, it is needed for a guideline and for procedures to use in factor analysis. To date, however, these two techniques have been indiscriminately misused. Research design, data, and methodology - This research conducted a literature review. For this, we summarized the meaningful and consistent arguments and drew up guidelines and suggested procedures for rigorous EFA. Results - PCA can be used instead of common factor analysis when all measured variables have high communality. However, common factor analysis is recommended for EFA. First, researchers should evaluate the sample size and check for sampling adequacy before conducting factor analysis. If these conditions are not satisfied, then the next steps cannot be followed. Sample size must be at least 100 with communality above 0.5 and a minimum subject to item ratio of at least 5:1, with a minimum of five items in EFA. Next, Bartlett's sphericity test and the Kaiser-Mayer-Olkin (KMO) measure should be assessed for sampling adequacy. The chi-square value for Bartlett's test should be significant. In addition, a KMO of more than 0.8 is recommended. The next step is to conduct a factor analysis. The analysis is composed of three stages. The first stage determines a rotation technique. Generally, ML or PAF will suggest to researchers the best results. Selection of one of the two techniques heavily hinges on data normality. ML requires normally distributed data; on the other hand, PAF does not. The second step is associated with determining the number of factors to retain in the EFA. The best way to determine the number of factors to retain is to apply three methods including eigenvalues greater than 1.0, the scree plot test, and the variance extracted. The last step is to select one of two rotation methods: orthogonal or oblique. If the research suggests some variables that are correlated to each other, then the oblique method should be selected for factor rotation because the method assumes all factors are correlated in the research. If not, the orthogonal method is possible for factor rotation. Conclusions - Recommendations are offered for the best factor analytic practice for empirical research.