• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.97-121
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• 2013

With the growing importance of knowledge for sustainable competitive advantages and innovation in a volatile environment, many researches on knowledge sharing have been conducted. However, previous researches have mostly relied on the questionnaire survey which has inherent perceptive errors of respondents. The current research has drawn the relationship among primary participant behaviors towards the participation level in knowledge sharing, basically from online user behaviors on Wikipedia, a representative community for online knowledge collaboration. Without users' participation in knowledge sharing, knowledge collaboration for creating knowledge cannot be successful. By the way, the editing patterns of Wikipedia users are diverse, resulting in different revisiting periods for the same number of edits, and thus varying results of shared knowledge. Therefore, we illuminated the participation level of knowledge sharing from two different angles of number of edits and revisiting period. The behavioral dimensions affecting the level of participation in knowledge sharing includes the article talk for public discussion and user talk for private messaging, and community registration, which are observable on Wiki platform. Public discussion is being progressed on article talk pages arranged for exchanging ideas about each article topic. An article talk page is often divided into several sections which mainly address specific type of issues raised during the article development procedure. From the diverse opinions about the relatively trivial things such as what text, link, or images should be added or removed and how they should be restructured to the profound professional insights are shared, negotiated, and improved over the course of discussion. Wikipedia also provides personal user talk pages as a private messaging tool. On these pages, diverse personal messages such as casual greetings, stories about activities on Wikipedia, and ordinary affairs of life are exchanged. If anyone wants to communicate with another person, he or she visits the person's user talk page and leaves a message. Wikipedia articles are assessed according to seven quality grades, of which the featured article level is the highest. The dataset includes participants' behavioral data related with 2,978 articles, which have reached the featured article level, with editing histories of articles, their article talk histories, and user talk histories extracted from user talk pages for each article. The time period for analysis is from the initiation of articles until their promotion to the featured article level. The number of edits represents the total number of participation in the editing of an article, and the revisiting period is the time difference between the first and last edits. At first, the participation levels of each user category classified according to behavioral dimensions have been analyzed and compared. And then, robust regressions have been conducted on the relationships among independent variables reflecting the degree of behavioral characteristics and the dependent variable representing the participation level. Especially, through adopting a motivational theory adequate for online environment in setting up research hypotheses, this work suggests a theoretical framework for the participation level of online knowledge sharing. Consequently, this work reached the following practical behavioral results besides some theoretical implications. First, both public discussion and private messaging positively affect the participation level in knowledge sharing. Second, public discussion exerts greater influence than private messaging on the participation level. Third, a synergy effect of public discussion and private messaging on the number of edits was found, whereas a pretty weak negative interaction effect of them on the revisiting period was observed. Fourth, community registration has a significant impact on the revisiting period, whereas being insignificant on the number of edits. Fifth, when it comes to the relation generated from private messaging, the frequency or depth of relation is shown to be more critical than the scope of relation for the participation level.

• Journal of Global Scholars of Marketing Science
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• v.17 no.4
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• pp.1-22
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• 2007

Customer satisfaction is important in an increasingly competitive and global marketplace. This implies that customer service is a critical factor for many organizations. In service encounter context, customer satisfaction is affected by employees' attitudes and behaviors. Accordingly, service firms have been focusing on selecting high quality of service employees, which resulted the ability to identify and select quality service- or customer- oriented employees to become critical for an organization's success. It was suggested that customer service orientation links to performance and subsequent organizational revenue. Moreover, it was found that service encounter failures were among the major reasons for customers' service switch. Therefore, the selection of customer service oriented employees is a key factor in establishing customer service - a potential source of sustained competitive advantage. However, the measurement of employee service orientation is more confusing than that of definitive answers. The difficulty of measuring service orientation is attributed to the use of broad versus narrow measures of personality. Advocates for the broad perspective prefer using basic personality constructs, such as the Big Five personality traits. On the contrary, the latter prefer a construct-oriented approach of personality research that provides a better measure of job performance because it requires the specification of the relationship of the personality traits with multiple dimensions of job performance. The customer service orientation was defined as "a set of basic individual predispositions and an inclination to provide service, to be courteous and to be helpful in dealing with customers and associates." Similarly, it is a fact that the Big five personality traits are predictors of customer orientation, and employee's self- and supervisor performance. They propose that basic personality traits may be too far removed from focal service behaviors to be able to predict specific service behaviors (customer orientation) and service worker performance. Also, customer orientation is defined as "an employee's tendency or predisposition to meet customer needs in an on-the-job context." This means that people who have job-relevant personality traits such as concern, empathy, and conscientiousness will be more adept at customer service than people who do not possess these traits. However, little attention has been given to the exploration of the service orientation of customer-contact employees who play a key role in creating satisfactory service encounters in the hospitality industry except for Kim, McCahon, & Miller (2003)'s study, especially in family restaurants context. Thus, the purposes of this study are to examine and validate the customer service orientation of customer-contact employees using the instrument developed by Donavan (1999) in Korean family restaurants, because the scale was developed to measure the personality traits related job behaviors. And this study explores the relationships between customer service orientation, job satisfaction, organizational commitment, and self service performance using structural equation modeling (SEM). And this study explores the relationships between customer service orientation, job satisfaction, organizational commitment, and self service performance using structural equation modeling (SEM). For these purposes the author developed several hypotheses as follows: H1: Employee's service orientation is associated with service performance. H2: Employee's service orientation is positively associated with job satisfaction. H3: Employee's service orientation is positively associated with organizational commitment. H4: Service performance is positively associated with job satisfaction. H5: Service performance is positively associated with organizational commitment. H6: Job satisfaction is negatively associated with organizational commitment. The data were collected from 278 employees in 5 deluxe hotels located in Pusan, Korea. The researcher contacted the manager of the restaurants, and managers consented to administer surveys to their employees. The survey was executed during one month period in the October of 2007. The data were analyzed with structural equation modeling with LISREL 8.7 W. The result of the overall model analysis appeared as follows: $X^2$=122.638 (p = 0.00), df=59, GFI=.936, AGFI=.901, NFI=.948, CFI=.971, RMSEA=.0625. Since the result of the overall model analysis demonstrated a good fit, we could further analyze our data. The findings can be summarized as follows: First, the greater the employee service orientation, the greater the service performance. Second, the greater the employee service orientation, the greater the job satisfaction. Third, the greater the employee service orientation, the greater the organizational commitment. Fourth, the greater the service performance, the greater the job satisfaction. Fifth, the greater the service performance, the greater the organizational commitment. Finally, the greater the job satisfaction, the greater the organizational commitment. Seventh, the greater the customer satisfaction, the greater the customer loyalty.

• Asia pacific journal of information systems
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• v.18 no.2
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• pp.15-40
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• 2008

With the explosive growth of the Internet, Internet shopping malls have become recognized as one of the major purchasing channels for consumers, as well as one of the competitive distribution channels for companies that allow them to contact with customers without intermediaries. It has motivated information systems(IS) researchers to examine the factors influencing consumer behavior and the purchase decision process in the context of Internet shopping malls. Despite the extensive research that has been conducted on the purchase decision process of consumers in online shopping malls, the results have demonstrated a need for further understanding of consumer behavior due to the unique features of virtual space and the characteristics of online consumers. Previous studies from marketing and consumer behavior domains have suggested that the concept of involvement plays an important role in explaining consumers' purchase behavior. Despite the critical role of involvement and the explosive growth of e-commerce, little research has examined the role of involvement in the Internet shopping mall context. With this motivation, this study has two research objectives. First, it introduces and tests an theoretical model capable of better explaining consumers' intention to purchase in the Internet shopping mall context. The proposed model extends and integrates existing models on purchase intention by incorporating purchase experience, innovativeness, and perceived self-control as the consumer factors, along with perceived risk, information provision, and perceived price as the Internet shopping mall factors. Second, this study examines how involvement differences may affect consumers' intention to purchase. For this purpose, two factors from involvement theory, involvement type and involvement level, are introduced into the research model as moderating variables. In order to test the proposed model, the overall approach employed was a field study using the structural equation model. We developed our data collection instrument by adopting existing validated questions wherever possible. All question items were measured with a seven-point, Likert-type scale, with anchors ranging from 'strongly disagree' to 'strongly agree.' Two IS researchers reviewed the instrument and checked its face validity. We collected empirical data for this study over a period of two weeks from subjects who had purchase experiences through Internet shopping malls. A total of 473 complete and valid responses were obtained. We carried out data analysis using a two-step methodology with AMOS 4.0. The first step in the data analysis was to establish the convergent and discriminant validity of the constructs. In the second step, we examined the structural model based on the cleansed measurement model. The empirical results partly support the proposed model and identify the moderating effect of involvement differences. Theoretical and practical implications of the study are discussed, along with its limitations.

• Asia Marketing Journal
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• v.14 no.4
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• pp.95-116
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• 2013

AMOREPACIFIC has rapidly grown to become a successful global brand by persistently seeking and achieving success in foreign markets. In 2011, AMOREPACIFIC was ranked as one of the global top 20 cosmetics companies. What makes AMOREPACIFIC's global success noteworthy is that AMOREPACIFIC challenged the France and the US market, where competition level is the toughest. Lolita Lempicka, AMOREPACIFIC's perfume brand, was chosen as one of the top seven most popular brands in the women's perfume market in France. In addition, Amorepacific, AMOREPACIFIC's namesake skincare brand, is currently recognized as a top prestige brand in the USA. Their success played a significant role as a bridgehead for AMOREPACIFIC in becoming a global cosmetics company. The main object of this case study is to analyze how AMOREPACIFIC became a global cosmetic company through building key brands such as Lolita Lempicka and Amorepafic, among others. Therefore, this study reviewed AMOREPACIFIC's unconventional approach in launching Lolita Lempicka in France, and Amorepacific in the US by focusing on how they foresaw the future opportunities and employed innovative marketing strategies. Specifically, we focused on Amorepacific's marketing strategy under the critical period when AMOREPACIFIC achieved great success in France with Lolita Lempicka (between 1997 and 2004) and in US with the brand, Amorepacific (2003-2008). The case of AMOREPACIFIC's success in the global markets can give valuable lessons to companies that want to extend their businesses to foreign countries and ultimately become global. One such lesson is the importance of building a successful pioneer brand in a powerful bridgehead market. While domestic competitors first entered into less competitive markets such as those in South-East Asia, AMOREPACIFIC challenged the toughest markets such as the French and US markets where the incumbent companies waged the most intensive and severe battles against Lolita Lempick and Amorepacific. Through the success in France and US market, however, AMOREPACIFIC built a powerful base for its successful global expansion. Another valuable lesson is the importance of foresight in uncovering great opportunities hidden behind the trends without losing focus on the brand's core character and values. Lolita Lempicka and Amorepacific showed excellence in foresight competition, which led them to succeed against the intense competition from Goliath companies. If Lolita Lempicka and Amorepacific had just followed the popular market trend at the time, they would have never succeeded.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.43-57
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• 2012

To enhance the competitive advantage in a constantly changing business environment, an enterprise management must make the right decision in many business activities based on both internal and external information. Thus, providing accurate information plays a prominent role in management's decision making. Intuitively, historical data can provide a feasible estimate through the forecasting models. Therefore, if the service department can estimate the service quantity for the next period, the service department can then effectively control the inventory of service related resources such as human, parts, and other facilities. In addition, the production department can make load map for improving its product quality. Therefore, obtaining an accurate service forecast most likely appears to be critical to manufacturing companies. Numerous investigations addressing this problem have generally employed statistical methods, such as regression or autoregressive and moving average simulation. However, these methods are only efficient for data with are seasonal or cyclical. If the data are influenced by the special characteristics of product, they are not feasible. In our research, we propose a forecasting framework that predicts service demand of manufacturing organization by combining Case-based reasoning (CBR) and leveraging an unsupervised artificial neural network based clustering analysis (i.e., Self-Organizing Maps; SOM). We believe that this is one of the first attempts at applying unsupervised artificial neural network-based machine-learning techniques in the service forecasting domain. Our proposed approach has several appealing features : (1) We applied CBR and SOM in a new forecasting domain such as service demand forecasting. (2) We proposed our combined approach between CBR and SOM in order to overcome limitations of traditional statistical forecasting methods and We have developed a service forecasting tool based on the proposed approach using an unsupervised artificial neural network and Case-based reasoning. In this research, we conducted an empirical study on a real digital TV manufacturer (i.e., Company A). In addition, we have empirically evaluated the proposed approach and tool using real sales and service related data from digital TV manufacturer. In our empirical experiments, we intend to explore the performance of our proposed service forecasting framework when compared to the performances predicted by other two service forecasting methods; one is traditional CBR based forecasting model and the other is the existing service forecasting model used by Company A. We ran each service forecasting 144 times; each time, input data were randomly sampled for each service forecasting framework. To evaluate accuracy of forecasting results, we used Mean Absolute Percentage Error (MAPE) as primary performance measure in our experiments. We conducted one-way ANOVA test with the 144 measurements of MAPE for three different service forecasting approaches. For example, the F-ratio of MAPE for three different service forecasting approaches is 67.25 and the p-value is 0.000. This means that the difference between the MAPE of the three different service forecasting approaches is significant at the level of 0.000. Since there is a significant difference among the different service forecasting approaches, we conducted Tukey's HSD post hoc test to determine exactly which means of MAPE are significantly different from which other ones. In terms of MAPE, Tukey's HSD post hoc test grouped the three different service forecasting approaches into three different subsets in the following order: our proposed approach > traditional CBR-based service forecasting approach > the existing forecasting approach used by Company A. Consequently, our empirical experiments show that our proposed approach outperformed the traditional CBR based forecasting model and the existing service forecasting model used by Company A. The rest of this paper is organized as follows. Section 2 provides some research background information such as summary of CBR and SOM. Section 3 presents a hybrid service forecasting framework based on Case-based Reasoning and Self-Organizing Maps, while the empirical evaluation results are summarized in Section 4. Conclusion and future research directions are finally discussed in Section 5.