• Journal of Global Scholars of Marketing Science
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• v.20 no.1
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• pp.80-88
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• 2010

There has been considerable research examining the relationship between stockholders equity and various marketing strategies. These include studies linking stock price performance to advertising, customer service metrics, new product introductions, research and development, celebrity endorsers, brand perception, brand extensions, brand evaluation, company name changes, and sports sponsorships. Another facet of marketing investments which has received heightened scrutiny for its purported influence on stockholder equity is television advertisement embedded within specific sporting events such as the Super Bowl. Research indicates that firms which advertise in Super Bowls experience stock price gains. Given this reported relationship between advertising investment and increased shareholder value, for both general and special events, it is surprising that relatively little research attention has been paid to investigating the relationship between advertising in the Olympic Games and its subsequent impact on stockholder equity. While attention has been directed at examining the effectiveness of sponsoring the Olympic Games, much less focus has been placed on the financial soundness of advertising during the telecasts of these Games. Notable exceptions to this include Peters (2008), Pfanner (2008), Saini (2008), and Keller Fay Group (2009). This paper presents a study of Olympic advertisers who ran TV ads on NBC in the American telecasts of the 2000, 2004, and 2008 Summer Olympic Games. Five hypothesis were tested: H1: The stock prices of firms which advertised on American telecasts of the 2008, 2004 and 2000 Olympics (referred to as O-Stocks), will outperform the S&P 500 during this same period of time (i.e., the Monday before the Games through to the Friday after the Games). H2: O-Stocks will outperform the S&P 500 during the medium term, that is, for the period of the Monday before the Games through to the end of each Olympic calendar year (December 31st of 2000, 2004, and 2008 respectively). H3: O-Stocks will outperform the S&P 500 in the longer term, that is, for the period of the Monday before the Games through to the midpoint of the following years (June 30th of 2001, 2005, and 2009 respectively). H4: There will be no difference in the performance of these O-Stocks vs. the S&P 500 in the Non-Olympic time control periods (i.e. three months earlier for each of the Olympic years). H5: The annual revenue of firms which advertised on American telecasts of the 2008, 2004 and 2000 Olympics will be higher for those years than the revenue for those same firms in the years preceding those three Olympics respectively. In this study, we recorded stock prices of those companies that advertised during the Olympics for the last three Summer Olympic Games (i.e. Beijing in 2008, Athens in 2004, and Sydney in 2000). We identified these advertisers using Google searches as well as with the help of the television network (i.e., NBC) that hosted the Games. NBC held the American broadcast rights to all three Olympic Games studied. We used Internet sources to verify the parent companies of the brands that were advertised each year. Stock prices of these parent companies were found using Yahoo! Finance. Only companies that were publicly held and traded were used in the study. We identified changes in Olympic advertisers' stock prices over the four-week period that included the Monday before through the Friday after the Games. In total, there were 117 advertisers of the Games on telecasts which were broadcast in the U.S. for 2008, 2004, and 2000 Olympics. Figure 1 provides a breakdown of those advertisers, by industry sector. Results indicate the stock of the firms that advertised (O-Stocks) out-performed the S&P 500 during the period of interest and under-performed the S&P 500 during the earlier control periods. These same O-Stocks also outperformed the S&P 500 from the start of these Games through to the end of each Olympic year, and for six months beyond that. Price pressure linkage, signaling theory, high involvement viewers, and corporate activation strategies are believed to contribute to these positive results. Implications for advertisers and researchers are discussed, as are study limitations and future research directions.

• Journal of Life Science
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• v.18 no.1
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• pp.16-22
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• 2008

In this study to evaluate the involvement of EGFR, HER-2/neu and ALCAM (CD166) oncogene products in canine mammary neoplastic lesions, sections of archived paraffin-embedded samples of 49 mammary tumors were analyzed immunohistochemically using antibodies against human EGFR and HER-2/neu and ALCAM. These 49 tumors were divided into 2 groups: 22 benign (19 adenoma, 3 benign mixed tumors) and 27 malignant tumors (2 simple adenocarcinomas, 5 complex adenocarcinomas, 3 solid carcinoma, 5 sclerosing carcinoma, 8 malignant mixed tumors and 4 malignant myoepithelioma). As a result of immunostaining, 31.8% (7/22) of the benign tumors and 29.6% (8/27) of the malignant tumors expressed the HER-2/neu oncogene product, EGFR expression was detected in 27.3% (6/22) of benign tumors and in 22.2% (6/27) of the malignant tumors. ALCAM expression was detected in 40.9% (9/22) of benign tumors and in 7.4% (2/27) of the malignant tumors. These results suggest that some of the biological and morphological characteristics of the tumor are associated with canine mammary gland tumors, as also reported for human breast cancer, the possibility of using anti-HER-2/neu antibodies in the treatment of canine mammary tumors.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.8 no.4
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• pp.853-860
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• 2007

In this modern era, human beings lead their life in complex environment where there are lots of parameters such as temperature, light, smell, sound, visual stimulus etc. that play important role for quality life. These parameters affect physical and mental behavior of a human being immensely. To ensure quality life the demand for quality products is always associated with human emotion and sensibility. Due to human sensibility and emotion involvement with quality life, the design stages of any kind of product must include some certain features related with emotion and sensibility. The cues for optimizing artificial environment are the physiological responses of human in that environment. The conventional approach of environmental physiology is to measure the relationship between environmental physical parameters and human psychological parameters under artificial conditions. Using that approach we tried to design an artificial environment for our daily lives and activities associated with both physiological and psychological behavior. We developed the technique to present the mock environment and software to measure and evaluate sensibility physiologically or psychologically and a simulator to measure and evaluate sensibility that can be utilized for large scale industrial production and design of environment. Simulator to measure and analyze human sensibility (SMAS) was constructed, which was utilized to estimate human sensibility and to simulate living and office environment.

• Asia pacific journal of information systems
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• v.20 no.3
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• pp.139-166
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• 2010

The supply chain management (SCM) systems have emerged as strong managerial tools for manufacturing firms in enhancing competitive strength. Despite of large investments in the SCM systems, many companies are not fully realizing the promised benefits from the systems. A review of literature on adoption, implementation and success factor of IOS (inter-organization systems), EDI (electronic data interchange) systems, shows that this issue has been examined from multiple theoretic perspectives. And many researchers have attempted to identify the factors which influence the success of system implementation. However, the existing studies have two drawbacks in revealing the determinants of systems implementation success. First, previous researches raise questions as to the appropriateness of research subjects selected. Most SCM systems are operating in the form of private industrial networks, where the participants of the systems consist of two distinct groups: focus companies and vendors. The focus companies are the primary actors in developing and operating the systems, while vendors are passive participants which are connected to the system in order to supply raw materials and parts to the focus companies. Under the circumstance, there are three ways in selecting the research subjects; focus companies only, vendors only, or two parties grouped together. It is hard to find researches that use the focus companies exclusively as the subjects probably due to the insufficient sample size for statistic analysis. Most researches have been conducted using the data collected from both groups. We argue that the SCM success factors cannot be correctly indentified in this case. The focus companies and the vendors are in different positions in many areas regarding the system implementation: firm size, managerial resources, bargaining power, organizational maturity, and etc. There are no obvious reasons to believe that the success factors of the two groups are identical. Grouping the two groups also raises questions on measuring the system success. The benefits from utilizing the systems may not be commonly distributed to the two groups. One group's benefits might be realized at the expenses of the other group considering the situation where vendors participating in SCM systems are under continuous pressures from the focus companies with respect to prices, quality, and delivery time. Therefore, by combining the system outcomes of both groups we cannot measure the system benefits obtained by each group correctly. Second, the measures of system success adopted in the previous researches have shortcoming in measuring the SCM success. User satisfaction, system utilization, and user attitudes toward the systems are most commonly used success measures in the existing studies. These measures have been developed as proxy variables in the studies of decision support systems (DSS) where the contribution of the systems to the organization performance is very difficult to measure. Unlike the DSS, the SCM systems have more specific goals, such as cost saving, inventory reduction, quality improvement, rapid time, and higher customer service. We maintain that more specific measures can be developed instead of proxy variables in order to measure the system benefits correctly. The purpose of this study is to find the determinants of SCM systems success in the perspective of vendor companies. In developing the research model, we have focused on selecting the success factors appropriate for the vendors through reviewing past researches and on developing more accurate success measures. The variables can be classified into following: technological, organizational, and environmental factors on the basis of TOE (Technology-Organization-Environment) framework. The model consists of three independent variables (competition intensity, top management support, and information system maturity), one mediating variable (collaboration), one moderating variable (government support), and a dependent variable (system success). The systems success measures have been developed to reflect the operational benefits of the SCM systems; improvement in planning and analysis capabilities, faster throughput, cost reduction, task integration, and improved product and customer service. The model has been validated using the survey data collected from 122 vendors participating in the SCM systems in Korea. To test for mediation, one should estimate the hierarchical regression analysis on the collaboration. And moderating effect analysis should estimate the moderated multiple regression, examines the effect of the government support. The result shows that information system maturity and top management support are the most important determinants of SCM system success. Supply chain technologies that standardize data formats and enhance information sharing may be adopted by supply chain leader organization because of the influence of focal company in the private industrial networks in order to streamline transactions and improve inter-organization communication. Specially, the need to develop and sustain an information system maturity will provide the focus and purpose to successfully overcome information system obstacles and resistance to innovation diffusion within the supply chain network organization. The support of top management will help focus efforts toward the realization of inter-organizational benefits and lend credibility to functional managers responsible for its implementation. The active involvement, vision, and direction of high level executives provide the impetus needed to sustain the implementation of SCM. The quality of collaboration relationships also is positively related to outcome variable. Collaboration variable is found to have a mediation effect between on influencing factors and implementation success. Higher levels of inter-organizational collaboration behaviors such as shared planning and flexibility in coordinating activities were found to be strongly linked to the vendors trust in the supply chain network. Government support moderates the effect of the IS maturity, competitive intensity, top management support on collaboration and implementation success of SCM. In general, the vendor companies face substantially greater risks in SCM implementation than the larger companies do because of severe constraints on financial and human resources and limited education on SCM systems. Besides resources, Vendors generally lack computer experience and do not have sufficient internal SCM expertise. For these reasons, government supports may establish requirements for firms doing business with the government or provide incentives to adopt, implementation SCM or practices. Government support provides significant improvements in implementation success of SCM when IS maturity, competitive intensity, top management support and collaboration are low. The environmental characteristic of competition intensity has no direct effect on vendor perspective of SCM system success. But, vendors facing above average competition intensity will have a greater need for changing technology. This suggests that companies trying to implement SCM systems should set up compatible supply chain networks and a high-quality collaboration relationship for implementation and performance.

• Journal of Distribution Research
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• v.16 no.1
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• pp.95-115
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• 2011

Food service is the major part of franchise business in Korea, accounting for 69.9% of the brands in the market. As the food service industry becomes mature, many franchisees have struggled to survive in the market. In general, consumers have higher levels of expectation toward service quality of franchised outlets compared that of (non-franchised) independent ones. They also tend to believe that franchisees deliver standardized service at the uniform food price, regardless of their locations. Such beliefs seem to be important reasons that consumers prefer franchised outlets to independent ones. Nevertheless, few studies examined the impact of qualify features of franchisees on customer satisfaction so far. To this end, this study examined the characteristics of various quality features of franchisees in the food service industry, regarding their relationship with customer satisfaction and dissatisfaction. The quality perception of heavy-users was also compared with that of light-users in order to find insights for developing differentiated marketing strategy for the two segments. Customer satisfaction has been understood as a one-dimensional construct while there are recent studies that insist two-dimensional nature of the construct. In this regard, Kano et al. (1984) suggested to categorize quality features of a product or service into five types, based on their relation to customer satisfaction and dissatisfaction: Must-be quality, Attractive quality, One-dimensional quality, Indifferent quality, and Reverse quality. According to the Kano model, customers are more dissatisfied when Must-be quality(M) are not fulfilled, but their satisfaction does not arise above neutral no matter how fully the quality fulfilled. In comparison, customers are more satisfied with a full provision of Attactive quality(A) but manage to accept its dysfunction. One-dimensional quality(O) results in satisfaction when fulfilled and dissatisfaction when not fulfilled. For Indifferent quality(I), its presence or absence influences neither customer satisfaction nor dissatisfaction. Lastly, Reverse quality(R) refers to the features whose high degree of achievement results in customer dissatisfaction rather than satisfaction. Meanwhile, the basic guidelines of the Kano model have a limitation in that the quality type of each feature is simply determined by calculating the mode statistics. In order to overcome such limitation, the relative importance of each feature on customer satisfaction (Better value; b) and dissatisfaction (Worse value; w) were calculated following the formulas below (Timko, 1993). The Better value indicates how much customer satisfaction is increased by providing the quality feature in question. In contrast, the Worse value indicates how much customer dissatisfaction is decreased by providing the quality feature. Better = (A + O)/(A+O+M+I) Worse = (O+M)/(A+O+M+I)(-1) An on-line survey was performed in order to understand the nature of quality features of franchisees in the food service industry by applying the Kano Model. A total of twenty quality features (refer to the Table 2) were identified as the result of literature review in franchise business and a pre-test with fifty college students in Seoul. The potential respondents of our main survey was limited to the customers who have visited more than two restaurants/stores of the same franchise brand. Survey invitation e-mails were sent out to the panels of a market research company and a total of 257 responses were used for analysis. Following the guidelines of Kano model, each of the twenty quality features was classified into one of the five types based on customers' responses to a set of questions: "(1) how do you feel if the following quality feature is fulfilled in the franchise restaurant that you visit," and "(2) how do you feel if the following quality feature is not fulfilled in the franchise restaurant that you visit." The analyses revealed that customers' dissatisfaction with franchisees is commonly associated with the poor level of cleanliness of the store (w=-0.872), kindness of the staffs(w=-0.890), conveniences such as parking lot and restroom(w=-0.669), and expertise of the staffs(w=-0.492). Such quality features were categorized as Must-be quality in this study. While standardization or uniformity across franchisees has been emphasized in franchise business, this study found that consumers are interested only in uniformity of price across franchisees(w=-0.608), but not interested in standardizations of menu items, interior designs, customer service procedures, and food tastes. Customers appeared to be more satisfied when the franchise brand has promotional events such as giveaways(b=0.767), good accessibility(b=0.699), customer loyalty programs(b=0.659), award winning history(b=0.641), and outlets in the overseas market(b=0.506). The results are summarized in a matrix form in Table 1. Better(b) and Worse(w) index indicate relative importance of each quality feature on customer satisfaction and dissatisfaction, respectively. Meanwhile, there were differences in perceiving the quality features between light users and heavy users of any specific franchise brand in the food service industry. Expertise of the staffs was labeled as Must-be quality for heavy users but Indifferent quality for light users. Light users seemed indifferent to overseas expansion of the brand and offering new menu items on a regular basis, while heavy users appeared to perceive them as Attractive quality. Such difference may come from their different levels of involvement when they eat out. The results are shown in Table 2. The findings of this study help practitioners understand the quality features they need to focus on to strengthen the competitive power in the food service market. Above all, removing the factors that cause customer dissatisfaction seems to be the most critical for franchisees. To retain loyal customers of the franchise brand, it is also recommended for franchisor to invest resources in the development of new menu items as well as training programs for the staffs. Lastly, if resources allow, promotional events, loyalty programs, overseas expansion, award-winning history can be considered as tools for attracting more customers to the business.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.155-175
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• 2017

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.