As social data become into the spotlight, mainstream web search engines provide data indicate how many people searched specific keyword: Web Search Traffic data. Web search traffic information is collection of each crowd that search for specific keyword. In a various area, web search traffic can be used as one of useful variables that represent the attention of common users on specific interests. A lot of studies uses web search traffic data to nowcast or forecast social phenomenon such as epidemic prediction, consumer pattern analysis, product life cycle, financial invest modeling and so on. Also web search traffic data have begun to be applied to predict tourist inbound. Proper demand prediction is needed because tourism is high value-added industry as increasing employment and foreign exchange. Among those tourists, especially Chinese tourists: Youke is continuously growing nowadays, Youke has been largest tourist inbound of Korea tourism for many years and tourism profits per one Youke as well. It is important that research into proper demand prediction approaches of Youke in both public and private sector. Accurate tourism demands prediction is important to efficient decision making in a limited resource. This study suggests improved model that reflects latest issue of society by presented the attention from group of individual. Trip abroad is generally high-involvement activity so that potential tourists likely deep into searching for information about their own trip. Web search traffic data presents tourists' attention in the process of preparation their journey instantaneous and dynamic way. So that this study attempted select key words that potential Chinese tourists likely searched out internet. Baidu-Chinese biggest web search engine that share over 80%- provides users with accessing to web search traffic data. Qualitative interview with potential tourists helps us to understand the information search behavior before a trip and identify the keywords for this study. Selected key words of web search traffic are categorized by how much directly related to "Korean Tourism" in a three levels. Classifying categories helps to find out which keyword can explain Youke inbound demands from close one to far one as distance of category. Web search traffic data of each key words gathered by web crawler developed to crawling web search data onto Baidu Index. Using automatically gathered variable data, linear model is designed by multiple regression analysis for suitable for operational application of decision and policy making because of easiness to explanation about variables' effective relationship. After regression linear models have composed, comparing with model composed traditional variables and model additional input web search traffic data variables to traditional model has conducted by significance and R squared. after comparing performance of models, final model is composed. Final regression model has improved explanation and advantage of real-time immediacy and convenience than traditional model. Furthermore, this study demonstrates system intuitively visualized to general use -Youke Mining solution has several functions of tourist decision making including embed final regression model. Youke Mining solution has algorithm based on data science and well-designed simple interface. In the end this research suggests three significant meanings on theoretical, practical and political aspects. Theoretically, Youke Mining system and the model in this research are the first step on the Youke inbound prediction using interactive and instant variable: web search traffic information represents tourists' attention while prepare their trip. Baidu web search traffic data has more than 80% of web search engine market. Practically, Baidu data could represent attention of the potential tourists who prepare their own tour as real-time. Finally, in political way, designed Chinese tourist demands prediction model based on web search traffic can be used to tourism decision making for efficient managing of resource and optimizing opportunity for successful policy.
Since 2000, the employment rate of small and medium enterprises (SMEs) has dwindled while the creation of new jobs and the emergence of healthy SMEs have been stagnant. The fundamental reason for these symptoms is that the economic structure is disadvantageous to SMEs. In particular, the greater gap between SMEs and large enterprises has resulted in polarization, and the resulting imbalance has become the largest obstacle to improving SMEs' competitiveness. For example, the total productivity has continued to drop, and the average productivity of SMEs is now merely 30% of that of large enterprises, and the average wage of SMEs' employees is only 53% of that of large enterprises. Along with polarization, rapid industrialization has also caused anti-enterprise consensus, the collapse of the middle class, hostility towards establishments, and other aftereffects. The general consensus is that unless these problems are solved, South Korea will not become an advanced country. Especially, South Korea is now facing issues that need urgent measures, such as the decline of its economic growth, the worsening distribution of profits, and the increased external volatility. Recognizing such negative trends, the MB administration proposed a win-win growth policy and recently introduced a new national value called "ecosystemic development." As the terms in such policy agenda are similar, however, the conceptual differences among such terms must first be fully understood. Therefore, in this study, the concepts of win-win growth policy and ecosystemic development, and the need for them, were surveyed, and their differences from and similarities with other policy concepts like win-win cooperation and symbiotic development were examined. Based on the results of the survey and examination, the study introduced a South Korean model of win-win growth, targeting the promotion of a sound balance between large enterprises and SMEs and an innovative ecosystem, and finally, proposing future policy tasks. Win-win growth is not an academic term but a policy term. Thus, it is less advisable to give a theoretical definition of it than to understand its concept based on its objective and method as a policy. The core of the MB administration's win-win growth policy is the creation of a partnership between key economic subjects such as large enterprises and SMEs based on each subject's differentiated capacity, and such economic subjects' joint promotion of growth opportunities. Its objective is to contribute to the establishment of an advanced capitalistic system by securing the sustainability of the South Korean economy. Such win-win growth policy includes three core concepts. The first concept, ecosystem, is that win-win growth should be understood from the viewpoint of an industrial ecosystem and should be pursued by overcoming the issues of specific enterprises. An enterprise is not an independent entity but a social entity, meaning it exists in relationship with the society (Drucker, 2011). The second concept, balance, points to the fact that an effort should be made to establish a systemic and social infrastructure for a healthy balance in the industry. The social system and infrastructure should be established in such a way as to create a balance between short- term needs and long-term sustainability, between freedom and responsibility, and between profitability and social obligations. Finally, the third concept is the behavioral change of economic entities. The win-win growth policy is not merely about simple transactional relationships or determining reasonable prices but more about the need for a behavior change on the part of economic entities, without which the objectives of the policy cannot be achieved. Various advanced countries have developed different win-win growth models based on their respective cultures and economic-development stages. Japan, whose culture is characterized by a relatively high level of group-centered trust, has developed a productivity improvement model based on such culture, whereas the U.S., which has a highly developed system of market capitalism, has developed a system that instigates or promotes market-oriented technological innovation. Unlike Japan or the U.S., Europe, a late starter, has not fully developed a trust-based culture or market capitalism and thus often uses a policy-led model based on which the government leads the improvement of productivity and promotes technological innovation. By modeling successful cases from these advanced countries, South Korea can establish its unique win-win growth system. For this, it needs to determine the method and tasks that suit its circumstances by examining the prerequisites for its success as well as the strengths and weaknesses of each advanced country. This paper proposes a South Korean model of win-win growth, whose objective is to upgrade the country's low-trust-level-based industrial structure, in which large enterprises and SMEs depend only on independent survival strategies, to a high-trust-level-based social ecosystem, in which large enterprises and SMEs develop a cooperative relationship as partners. Based on this objective, the model proposes the establishment of a sound balance of systems and infrastructure between large enterprises and SMEs, and to form a crenovative social ecosystem. The South Korean model of win-win growth consists of three axes: utilization of the South Koreans' potential, which creates community-oriented energy; fusion-style improvement of various control and self-regulated systems for establishing a high-trust-level-oriented social infrastructure; and behavioral change on the part of enterprises in terms of putting an end to their unfair business activities and promoting future-oriented cooperative relationships. This system will establish a dynamic industrial ecosystem that will generate creative energy and will thus contribute to the realization of a sustainable economy in the 21st century. The South Korean model of win-win growth should pursue community-based self-regulation, which promotes the power of efficiency and competition that is fundamentally being pursued by capitalism while at the same time seeking the value of society and community. Already existing in Korea's traditional roots, such objectives have become the bases of the Shinbaram culture, characterized by the South Koreans' spontaneity, creativity, and optimism. In the process of a community's gradual improvement of its rules and procedures, the trust among the community members increases, and the "social capital" that guarantees the successful control of shared resources can be established (Ostrom, 2010). This basic ideal can help reduce the gap between large enterprises and SMEs, alleviating the South Koreans' victim mentality in the face of competition and the open-door policy, and creating crenovative corporate competitiveness. The win-win growth policy emerged for the purpose of addressing the polarization and imbalance structure resulting from the evolution of 21st-century capitalism. It simultaneously pursues efficiency and fairness on one hand and economic and community values on the other, and aims to foster efficient interaction between the market and the government. This policy, however, is also evolving. The win-win growth policy can be considered an extension of the win-win cooperation that the past 'Participatory Government' promoted at the enterprise management level to the level of systems and culture. Also, the ecosystemic development agendum that has recently emerged is a further extension that has been presented as a national ideal of "a new development model that promotes the co-advancement of environmental conservation, growth, economic development, social integration, and national and individual development."
Since the implementation of economic reforms in 1978, the Chinese economy grows rapidly at an average annul growth rate of 9% over the post two decades. Franchising has been widely recognized as an important source of entrepreneurial activity. Trust is important in that it facilitates relational exchanges by permits partners to transcend short-run inequities or risks to concentrate on long-term profits or gains. In the relationship between the franchisors and franchisees, trust has been described as an important source of competitive advantage. However, little research has been done on the factors affecting trust in Chinese franchisor-franchisee relationships. The purpose of this study is to investigate what factors affect the trust in the franchise system in China, and to provide guidelines and insights to franchisors which enter Chinese market. In this study, according to Morgan and Hunt (1994), trust is defined as the extending when one party has confidence in an exchange partner's reliability and integrity. We offered a conceptual model of the empirical study. The model shows that the factors affecting the trust include franchisor's supports, communication, satisfaction with previous outcome and conflict. We also suggested the franchisor's supports and communication like to enhance the franchisee's satisfaction with previous outcome, and the franchisor's supports, communication and he franchisee's satisfaction with previous outcome tend to decrease conflict. Before the formal study, a pretest involving exploratory interviews with owners from three franchisees was conducted to make sure the questionnaire was relevant and clear to the respondents. The data were collected using trained interviewers to carry out personal interviews with the aid of an unidentified, muti-page, structured questionnaire. The respondents comprised of owners, managers, and owner managers of franchisee-owned food service franchises located in Beijing, China. Even though a total of 256 potential franchises were initially contacted, the finally usable sample consisted of 125 respondents. As expected, the sampling method was successful in soliciting respondents with waried personal and firm characteristics. Self-administrated questionnaires were used for all measures. And established scales were used to measure the latent constructs in this study. The measures tapped the franchisees' perceptions of the relationship with the referent franchisor. Five-point Likert-type scales ranging from "strongly disagree" (=1) to "strongly agree" (=7) were used throughout the constructs (trust, eight items; support, five items; communication, four items; satisfaction, six items; conflict, three items). The reliability measurements traditionally employed, such as the Cronbach's alpha, were used. All the reliabilities were greater than.80. The proposed measurement model was estimated using SPSS 12.0 and AMOS 5.0 analysis package. We conducted A series of exploratory factor analyses and confirmatory factor analyses to assess the convergent validity, discriminant validity, and reliability. The results indicate reasonable overall fits between the model and the observed data. The overall fit of measurement model were
Recently, the diversification and individualization of consumption patterns through the web and mobile devices based on the Internet have been rapid. As this happens, the efficient operation of the offline store, which is a traditional distribution channel, has become more important. In order to raise both the sales and profits of stores, stores need to supply and sell the most attractive products to consumers in a timely manner. However, there is a lack of research on which SKUs, out of many products, can increase sales probability and reduce inventory costs. In particular, if a company sells products through multiple in-store stores across multiple locations, it would be helpful to increase sales and profitability of stores if SKUs appealing to customers are recommended. In this study, the recommender system (recommender system such as collaborative filtering and hybrid filtering), which has been used for personalization recommendation, is suggested by SKU recommendation method of a store unit of a distribution company that handles a homogeneous brand through a plurality of sales stores by country and region. We calculated the similarity of each store by using the purchase data of each store's handling items, filtering the collaboration according to the sales history of each store by each SKU, and finally recommending the individual SKU to the store. In addition, the store is classified into four clusters through PCA (Principal Component Analysis) and cluster analysis (Clustering) using the store profile data. The recommendation system is implemented by the hybrid filtering method that applies the collaborative filtering in each cluster and measured the performance of both methods based on actual sales data. Most of the existing recommendation systems have been studied by recommending items such as movies and music to the users. In practice, industrial applications have also become popular. In the meantime, there has been little research on recommending SKUs for each store by applying these recommendation systems, which have been mainly dealt with in the field of personalization services, to the store units of distributors handling similar brands. If the recommendation method of the existing recommendation methodology was 'the individual field', this study expanded the scope of the store beyond the individual domain through a plurality of sales stores by country and region and dealt with the store unit of the distribution company handling the same brand SKU while suggesting a recommendation method. In addition, if the existing recommendation system is limited to online, it is recommended to apply the data mining technique to develop an algorithm suitable for expanding to the store area rather than expanding the utilization range offline and analyzing based on the existing individual. The significance of the results of this study is that the personalization recommendation algorithm is applied to a plurality of sales outlets handling the same brand. A meaningful result is derived and a concrete methodology that can be constructed and used as a system for actual companies is proposed. It is also meaningful that this is the first attempt to expand the research area of the academic field related to the existing recommendation system, which was focused on the personalization domain, to a sales store of a company handling the same brand. From 05 to 03 in 2014, the number of stores' sales volume of the top 100 SKUs are limited to 52 SKUs by collaborative filtering and the hybrid filtering method SKU recommended. We compared the performance of the two recommendation methods by totaling the sales results. The reason for comparing the two recommendation methods is that the recommendation method of this study is defined as the reference model in which offline collaborative filtering is applied to demonstrate higher performance than the existing recommendation method. The results of this model are compared with the Hybrid filtering method, which is a model that reflects the characteristics of the offline store view. The proposed method showed a higher performance than the existing recommendation method. The proposed method was proved by using actual sales data of large Korean apparel companies. In this study, we propose a method to extend the recommendation system of the individual level to the group level and to efficiently approach it. In addition to the theoretical framework, which is of great value.
I. Introduction The industry of domestic discount store was reorganized with 2 bigs and 1 middle, and then Home Plus took over Home Ever in 2008. In present, Oct, 2008, E-Mart has 118 outlets, Home Plus 112 outlets, and Lotte Mart 60 stores. With total number of 403 outlets, they are getting closer to a saturation point. We know that the industry of discount store has been getting through the mature stage in retail life cycle. There are many efforts to maintain existing customers rather than to get new customers. These competitions in this industry lead firms to acknowledge 'store loyalty' to be the first strategic tool for their sustainable competitiveness. In other words, the strategic goal of discount store is to boost up the repurchase rate of customers throughout increasing store loyalty. If owners of retail shops can figure out main factors for store loyalty, they can easily make more efficient and effective retail strategies which bring about more sales and profits. In this practical sense, there are many papers which are focusing on the antecedents of store loyalty. Many researchers have been inspecting causal relationships between antecedents and store loyalty; store characteristics, store image, atmosphere in store, sales promotion in store, service quality, customer characteristics, crowding, switching cost, trust, satisfaction, commitment, etc., In recent times, many academic researchers and practitioners have been interested in 'dual path model for service loyalty'. There are two paths in store loyalty. First path has an emphasis on symbolic and emotional dimension of service brand, and second path focuses on quality of product and service. We will call the former an extrinsic path and call the latter an intrinsic path. This means that consumers' cognitive path for store loyalty is not single but dual. Existing studies for dual path model are as follows; First, in extrinsic path, some papers in domestic settings show that there is 'store personality-identification-loyalty' path. Second, service quality has an effect on loyalty, which is a behavioral variable, in the mediation of customer satisfaction. But, it's very difficult to find out an empirical paper applied to domestic discount store based on this mediating model. The domestic research for store loyalty concentrates on not only intrinsic path but also extrinsic path. Relatively, an attention for intrinsic path is scarce. And then, we acknowledge that there should be a need for integrating extrinsic and intrinsic path. Also, in terms of retail industry, this study is meaningful because retailers want to achieve their competitiveness by using store loyalty. And so, the purpose of this paper is to integrate and complement two existing paths into one specific model, dual path model. This model includes both intrinsic and extrinsic path for store loyalty. With this research, we would expect to understand the full process of forming customers' store loyalty which had not been clearly explained. In other words, we propose the dual path model for discount store loyalty which has been originated from store personality and service quality. This model is composed of extrinsic path, discount store personality