• Journal of Venture Innovation
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• v.4 no.3
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• pp.125-139
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• 2021

As the 4th industrial revolution progresses, new technologies and services are being born, growing, and maturing. Now, beyond the mobile era, the metaverse is being discussed as a new paradigm. Therefore, in this study, in preparation for the metaverse era, we tried to analyze what factors have an important influence when consumers want to use new technologies. In particular, the research was conducted focusing on how the context in which consumers use the technology changes depending on whether they are B2C or B2B. For this, augmented reality (AR) was selected in the B2C context by linking the research subject with the metaverse era, and the smart factory was selected in the B2B context. The research model for the analysis was established by deriving and setting common influence variables by reflecting the characteristics of the research target technology based on the modified extended unified theory of acceptance and use of technology. A survey was conducted for empirical analysis, and 150 AR and 150 smart factory subjects were analyzed. The empirical study results are as follows. The relationship between performance expectancy and intention to use, technology readiness and intention to use was found to have a significant positive (+) effect on both AR and smart factory. On the other hand, it was found that effort expectancy, social influence, and trust had a positive (+) effect on intention to use only in AR. Only in smart factory, facilitating conditions had a significant positive (+) effect on intention to use. It was also found that the perceived risk had a significant negative (-) effect on the intention to use only in the smart factory. The results of this study are academically significant in that we empirically test that influencing factors of technology use varies depending on the context in which it is used by consumers. In practice, it provided an implication of what to focus on first is being implemented.

• Journal of Korean Home Economics Education Association
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• v.19 no.3
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• pp.149-168
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• 2007

The purpose of this study was to analyze the home economics education items in the teacher recruitment examination for secondary school. To achieve the purpose, all the home economics education items, which were carried out for seven times from the school year 2001 to the most recent year 2007, were compared and analyzed. The form of items was analyzed by frequency and rate. Behavioral domain of items was analyzed by content analysis. In this study, some recommendations were suggested for the quality of home economics education items through discussion of science education and society education items, which were abstracted from the school year 2001 to the most recent year 2007. The results of this study were as follows. First, the score ratio of home economics education items was fluid as 20-30% from the school year 2001 to 2004 but it fixed as 30-35% since the school year 2005. In subcategory of home economics education, curriculum items accounted for highest ratio(43%). In the next thing, items of teaching-learning method(35%), evaluation(19%) and philosophy(3%) related to home economics education were followed in order. Second, the form of home economics education items was coexistent form of single item and subordinate item from the school year 2001 to 2004. But it was changed into form of single item by 100% since the school year 2005. Third, regarding the content of home economics education items, most of the curriculum items were related to the content of the 7th National Curriculum. Teaching-learning method items were taken mostly from model of teaching-learning. Evaluation items were taken mostly from performance assessment. Philosophy items related to home economics education were taken only from Habermas's three systems of action on the school year 2005. Fourth, about behavioral domain of home economics education items, most of the curriculum items were level of 'simple knowledge or memory'. Therefore, it was suggested that behavioral domain of curriculum items had to be changed into 'complex knowledge or comprehension and application'. The behavioral domain of teaching-learning method items and education evaluation items was mostly 'complex knowledge or comprehension and application'. However, to bettering the items it was suggested that the behavioral domain of them has to be changed 'comprehension' into more 'application'. Fifth, regarding the coverage of home economics education items, curriculum items were limited only superficial content of the 7th National Curriculum. Therefore, it was suggested that coverage of curriculum items had to be extended to theoretical content, which was philosophical background and various principles of curriculum. It was suggested that coverage of teaching-learning method items had to be extended to the content including various teaching-learning theories and the practical reasoning home economics instruction proved effective as home economics instruction recently. Evaluation items were taken mostly from performance assessment. Therefore, it was suggested that coverage of evaluation items had to be extended to analysis of evaluation result, item validity and reliability, and evaluator's philosophical perspective.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.45-68
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• 2022

The central and local governments of the Republic of Korea provided information necessary for disaster response through wireless emergency alerts (WEAs) in order to overcome the pandemic situation in which COVID-19 rapidly spreads. Among all channels for delivering disaster information, wireless emergency alert is the most efficient, and since it adopts the CBS(Cell Broadcast Service) method that broadcasts directly to the mobile phone, it has the advantage of being able to easily access disaster information through the mobile phone without the effort of searching. In this study, the characteristics of wireless emergency alerts sent to Seoul during the past year and one month (January 2020 to January 2021) were derived through various text mining methodologies, and various types of information contained in wireless emergency alerts were analyzed. In addition, it was confirmed through the population mobility by age in the districts of Seoul that what kind of influence it had on the movement behavior of people. After going through the process of classifying key words and information included in each character, text analysis was performed so that individual sent characters can be used as an analysis unit by applying a document cluster analysis technique based on the included words. The number of WEAs sent to the Seoul has grown dramatically since the spread of Covid-19. In January 2020, only 10 WEAs were sent to the Seoul, but the number of the WEAs increased 5 times in March, and 7.7 times over the previous months. Since the basic, regional local government were authorized to send wireless emergency alerts independently, the sending behavior of related to wireless emergency alerts are different for each local government. Although most of the basic local governments increased the transmission of WEAs as the number of confirmed cases of Covid-19 increases, the trend of the increase in WEAs according to the increase in the number of confirmed cases of Covid-19 was different by region. By using structured econometric model, the effect of disaster information included in wireless emergency alerts on population mobility was measured by dividing it into baseline effect and accumulating effect. Six types of disaster information, including date, order, online URL, symptom, location, normative guidance, were identified in WEAs and analyzed through econometric modelling. It was confirmed that the types of information that significantly change population mobility by age are different. Population mobility of people in their 60s and 70s decreased when wireless emergency alerts included information related to date and order. As date and order information is appeared in WEAs when they intend to give information about Covid-19 confirmed cases, these results show that the population mobility of higher ages decreased as they reacted to the messages reporting of confirmed cases of Covid-19. Online information (URL) decreased the population mobility of in their 20s, and information related to symptoms reduced the population mobility of people in their 30s. On the other hand, it was confirmed that normative words that including the meaning of encouraging compliance with quarantine policies did not cause significant changes in the population mobility of all ages. This means that only meaningful information which is useful for disaster response should be included in the wireless emergency alerts. Repeated sending of wireless emergency alerts reduces the magnitude of the impact of disaster information on population mobility. It proves indirectly that under the prolonged pandemic, people started to feel tired of getting repetitive WEAs with similar content and started to react less. In order to effectively use WEAs for quarantine and overcoming disaster situations, it is necessary to reduce the fatigue of the people who receive WEA by sending them only in necessary situations, and to raise awareness of WEAs.

• Asia pacific journal of information systems
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• v.17 no.4
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• pp.31-59
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• 2007

We frequently use search engines to find relevant information in the Web but still end up with too much information. In order to solve this problem of information overload, ranking algorithms have been applied to various domains. As more information will be available in the future, effectively and efficiently ranking search results will become more critical. In this paper, we propose a ranking algorithm for the Semantic Web resources, specifically RDF resources. Traditionally, the importance of a particular Web page is estimated based on the number of key words found in the page, which is subject to manipulation. In contrast, link analysis methods such as Google's PageRank capitalize on the information which is inherent in the link structure of the Web graph. PageRank considers a certain page highly important if it is referred to by many other pages. The degree of the importance also increases if the importance of the referring pages is high. Kleinberg's algorithm is another link-structure based ranking algorithm for Web pages. Unlike PageRank, Kleinberg's algorithm utilizes two kinds of scores: the authority score and the hub score. If a page has a high authority score, it is an authority on a given topic and many pages refer to it. A page with a high hub score links to many authoritative pages. As mentioned above, the link-structure based ranking method has been playing an essential role in World Wide Web(WWW), and nowadays, many people recognize the effectiveness and efficiency of it. On the other hand, as Resource Description Framework(RDF) data model forms the foundation of the Semantic Web, any information in the Semantic Web can be expressed with RDF graph, making the ranking algorithm for RDF knowledge bases greatly important. The RDF graph consists of nodes and directional links similar to the Web graph. As a result, the link-structure based ranking method seems to be highly applicable to ranking the Semantic Web resources. However, the information space of the Semantic Web is more complex than that of WWW. For instance, WWW can be considered as one huge class, i.e., a collection of Web pages, which has only a recursive property, i.e., a 'refers to' property corresponding to the hyperlinks. However, the Semantic Web encompasses various kinds of classes and properties, and consequently, ranking methods used in WWW should be modified to reflect the complexity of the information space in the Semantic Web. Previous research addressed the ranking problem of query results retrieved from RDF knowledge bases. Mukherjea and Bamba modified Kleinberg's algorithm in order to apply their algorithm to rank the Semantic Web resources. They defined the objectivity score and the subjectivity score of a resource, which correspond to the authority score and the hub score of Kleinberg's, respectively. They concentrated on the diversity of properties and introduced property weights to control the influence of a resource on another resource depending on the characteristic of the property linking the two resources. A node with a high objectivity score becomes the object of many RDF triples, and a node with a high subjectivity score becomes the subject of many RDF triples. They developed several kinds of Semantic Web systems in order to validate their technique and showed some experimental results verifying the applicability of their method to the Semantic Web. Despite their efforts, however, there remained some limitations which they reported in their paper. First, their algorithm is useful only when a Semantic Web system represents most of the knowledge pertaining to a certain domain. In other words, the ratio of links to nodes should be high, or overall resources should be described in detail, to a certain degree for their algorithm to properly work. Second, a Tightly-Knit Community(TKC) effect, the phenomenon that pages which are less important but yet densely connected have higher scores than the ones that are more important but sparsely connected, remains as problematic. Third, a resource may have a high score, not because it is actually important, but simply because it is very common and as a consequence it has many links pointing to it. In this paper, we examine such ranking problems from a novel perspective and propose a new algorithm which can solve the problems under the previous studies. Our proposed method is based on a class-oriented approach. In contrast to the predicate-oriented approach entertained by the previous research, a user, under our approach, determines the weights of a property by comparing its relative significance to the other properties when evaluating the importance of resources in a specific class. This approach stems from the idea that most queries are supposed to find resources belonging to the same class in the Semantic Web, which consists of many heterogeneous classes in RDF Schema. This approach closely reflects the way that people, in the real world, evaluate something, and will turn out to be superior to the predicate-oriented approach for the Semantic Web. Our proposed algorithm can resolve the TKC(Tightly Knit Community) effect, and further can shed lights on other limitations posed by the previous research. In addition, we propose two ways to incorporate data-type properties which have not been employed even in the case when they have some significance on the resource importance. We designed an experiment to show the effectiveness of our proposed algorithm and the validity of ranking results, which was not tried ever in previous research. We also conducted a comprehensive mathematical analysis, which was overlooked in previous research. The mathematical analysis enabled us to simplify the calculation procedure. Finally, we summarize our experimental results and discuss further research issues.

• Cartoon and Animation Studies
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• s.39
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• pp.215-231
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• 2015

The Cultural Revolution in the history of Chinese animation hinder the development of the initial animation, and after a negative assessment instrument provided the cause is to become sluggish growth of the Chinese animation. So this time animation are things that are the subject of academic research studies or analysis has been depreciating almost uniformly without evaluation. However, of all the cultural and artistic creation it is developing in its own specific historical conditions and has the aesthetic results. This paper puts the primary purpose is to hold in consideration the aesthetic principles that led to cultural and artistic creativity and objective perspective the achievements the Chinese animation of the time period of the Cultural Revolution. Cultural Revolution is avoided to the previous period in accordance with the socialist ideology of Mao Ze-dong(毛澤東) sikindaneun highlight the culture of the proletariat and placed our goal to create a new class culture. Therefore, cultural and artistic creation of this period is often inconsistent with this part of our aesthetic principles generally accepted character has a non- elitist and anti properties. Best drama is a creative one hand as a model to implement the principles of aesthetics, art and culture Cultural Revolution period kkophimyeo reference for understanding the aesthetic principles that animated the Chinese Cultural Revolution period of orientation. This paper has San Tu Chu(三突出), Hong Guang Liang(紅光亮), and Gao Da Quan(高大全) at the time of the Cultural Revolution aesthetic principles are reflected in how the concrete work, the Cultural Revolution when the animation is how to accommodate these aesthetic principles and placed emphasis on comparative studies on best pole and correlation of the Cultural Revolution when the Chinese animation to ensure that adaptation in own way. First, after analyzing whether the aesthetic principles of focusing on the similarities of the best pole time of the Cultural Revolution and China, and how to implement animation in the works, these aesthetic principles according to the analysis of positive and negative influence on the creation of Chinese animation It was described as neutral. The detailed analysis and comparative study courses were trying to access in two significant aspects of the characters and scenes directing. In terms of character animation of the Cultural Revolution in China when a young boy or girl, emphasis should emphasize the health tinged with red lips and cheek blush to highlight the desired Gong Nong Bing(工農兵) shape as the main character and smooth texture and sophisticated highlights the glittering feeling to the touch, it was confirmed focused hayeoteum to implement the principle of 'Hong Guang Liang', highlighting the brilliant colors with a clean, bright colors. Highlighting a number of protagoniste compared to the antagonist in the animated scene of the Cultural Revolution a few times in terms of production and, among a number of protagoniste also emphasizes the outstanding hero figure, "yet three outstanding heroes heroic figures also emphasize the leading figures among the the director of the extrusion step-by-step approach "('San Tu Chu')was used. In addition, the hero figure is generally high and low angle by directing a large and perfect aesthetic appearance was to faithfully implement the principle of 'high-charged'('Gao Da Quan').

• Journal of Distribution Research
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• v.16 no.3
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• pp.1-32
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• 2011

I. Introduction: In Chinese electronics industry, the local wholesalers are still dominant but power is rapidly swifting from wholesalers to retailers because in recent foreign big retailers and local mass merchandisers are growing fast. During such transient period, conflicts among channel members emerge important issues. For example, when wholesalers who have more power exercise influence strategies to maintain status, conflicts among manufacturer, wholesaler, and retailer will be intensified. Korean electronics companies in China need differentiated channel strategies by dealing with wholesalers and retailers simultaneously to sell more Korean products in competition with foreign firms. For example, Korean electronics firms should utilize 'guanxi' or relational quality to form long-term relationships with whloesalers instead of power and conflict issues. The major purpose of this study is to investigate the impact of conflict, dependency, and influence strategies between local Korean-products-selling retailers and wholesalers on performance in Chinese electronics distribution channels. In particular, this paper proposes effective distribution strategies for Korean electronics companies in China by analyzing moderating effects of 'Guanxi'. II. Literature Review and Hypotheses: The specific purposes of this study are as follows. First, causes of conflicts between local Korean-products-selling retailers and wholesalers are examined from the perspectives of goal incongruence and role ambiguity and then effects of these causes are found out on perceived conflicts of local retailers. Second, the effects of dependency of local retailers upon wholesalers are investigated on local retailers' perceived conflicts. Third, the effects of non-coercive influence strategies such as information exchange and recommendation and coercive strategies such as threats and legalistic pleas exercised by wholesalers are explored on perceived conflicts by local retailers. Fourth, the effects of level of conflicts perceived by local retailers are verified on local retailers' financial performance and satisfaction. Fifth, moderating effects of relational qualities, say, 'quanxi' between wholesalers and retailers are analyzed on the impact of wholesalers' influence strategies on retailers' performances. Finally, moderating effects of relational qualities are examined on the relationship between conflicts and performance. To accomplish above-mentioned research objectives, Figure 1 and the following research hypotheses are proposed and verified. III. Measurement and Data Analysis: To verify the proposed research model and hypotheses, data were collected from 97 retailers who are selling Korean electronic products located around Central and Southern regions in China. Covariance analysis and moderated regression analysis were employed to validate hypotheses. IV. Conclusion: The following results were drawn using structural equation modeling and hierarchical moderated regression. First, goal incongruence perceived by local retailers significantly affected conflict but role ambiguity did not. Second, consistent with conflict spiral theory, the level of conflict decreased when retailers' dependency increased toward wholesalers. Third, noncoercive influence strategies such as information exchange and recommendation implemented by wholesalers had significant effects on retailers' performance such as sales and satisfaction without conflict. On the other hand, coercive influence strategies such as threat and legalistic plea had insignificant effects on performance in spite of increasing the level of conflict. Fourth, 'guanxi', namely, relational quality between local retailers and wholesalers showed unique effects on performance. In case of noncoercive influence strategies, 'guanxi' did not play a role of moderator. Rather, relational quality and noncoercive influence strategies can serve as independent variables to enhance performance. On the other hand, when 'guanxi' was well built due to mutual trust and commitment, relational quality as a moderator can positively function to improve performance even though hostile, coercive influence strategies were implemented. Fifth, 'guanxi' significantly moderated the effects of conflict on performance. Even if conflict arises, local retailers who form solid relational quality can increase performance by dealing with dysfunctional conflict synergistically compared with low 'quanxi' retailers. In conclusion, this study verified the importance of relational quality via 'quanxi' between local retailers and wholesalers in Chinese electronic industry because relational quality could cross out the adverse effects of coercive influence strategies and conflict on performance.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.79-94
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• 2013

Recently, the high value added business is steadily growing in the culture and art area. To generated high value from a performance, the satisfaction of audience is necessary. The flow in a critical factor for satisfaction, and it should be induced from audience and measures. To evaluate interest and emotion of audience on contents, producers or investors need a kind of index for the measurement of the flow. But it is neither easy to define the flow quantitatively, nor to collect audience's reaction immediately. The previous studies of the group flow were evaluated by the sum of the average value of each person's reaction. The flow or "good feeling" from each audience was extracted from his face, especially, the change of his (or her) expression and body movement. But it was not easy to handle the large amount of real-time data from each sensor signals. And also it was difficult to set experimental devices, in terms of economic and environmental problems. Because, all participants should have their own personal sensor to check their physical signal. Also each camera should be located in front of their head to catch their looks. Therefore we need more simple system to analyze group flow. This study provides the method for measurement of audiences flow with group synchronization at same time and place. To measure the synchronization, we made real-time processing system using the Differential Image and Group Emotion Analysis (GEA) system. Differential Image was obtained from camera and by the previous frame was subtracted from present frame. So the movement variation on audience's reaction was obtained. And then we developed a program, GEX(Group Emotion Analysis), for flow judgment model. After the measurement of the audience's reaction, the synchronization is divided as Dynamic State Synchronization and Static State Synchronization. The Dynamic State Synchronization accompanies audience's active reaction, while the Static State Synchronization means to movement of audience. The Dynamic State Synchronization can be caused by the audience's surprise action such as scary, creepy or reversal scene. And the Static State Synchronization was triggered by impressed or sad scene. Therefore we showed them several short movies containing various scenes mentioned previously. And these kind of scenes made them sad, clap, and creepy, etc. To check the movement of audience, we defined the critical point, ${\alpha}$and ${\beta}$. Dynamic State Synchronization was meaningful when the movement value was over critical point ${\beta}$, while Static State Synchronization was effective under critical point ${\alpha}$. ${\beta}$ is made by audience' clapping movement of 10 teams in stead of using average number of movement. After checking the reactive movement of audience, the percentage(%) ratio was calculated from the division of "people having reaction" by "total people". Total 37 teams were made in "2012 Seoul DMC Culture Open" and they involved the experiments. First, they followed induction to clap by staff. Second, basic scene for neutralize emotion of audience. Third, flow scene was displayed to audience. Forth, the reversal scene was introduced. And then 24 teams of them were provided with amuse and creepy scenes. And the other 10 teams were exposed with the sad scene. There were clapping and laughing action of audience on the amuse scene with shaking their head or hid with closing eyes. And also the sad or touching scene made them silent. If the results were over about 80%, the group could be judged as the synchronization and the flow were achieved. As a result, the audience showed similar reactions about similar stimulation at same time and place. Once we get an additional normalization and experiment, we can obtain find the flow factor through the synchronization on a much bigger group and this should be useful for planning contents.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.163-176
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• 2014

Social media is becoming the platform for users to communicate their activities, status, emotions, and experiences to other people. In recent years, microblogs, such as Twitter, have gained in popularity because of its ease of use, speed, and reach. Compared to a conventional web blog, a microblog lowers users' efforts and investment for content generation by recommending shorter posts. There has been a lot research into capturing the social phenomena and analyzing the chatter of microblogs. However, measuring television ratings has been given little attention so far. Currently, the most common method to measure TV ratings uses an electronic metering device installed in a small number of sampled households. Microblogs allow users to post short messages, share daily updates, and conveniently keep in touch. In a similar way, microblog users are interacting with each other while watching television or movies, or visiting a new place. In order to measure TV ratings, some features are significant during certain hours of the day, or days of the week, whereas these same features are meaningless during other time periods. Thus, the importance of features can change during the day, and a model capturing the time sensitive relevance is required to estimate TV ratings. Therefore, modeling time-related characteristics of features should be a key when measuring the TV ratings through microblogs. We show that capturing time-dependency of features in measuring TV ratings is vitally necessary for improving their accuracy. To explore the relationship between the content of microblogs and TV ratings, we collected Twitter data using the Get Search component of the Twitter REST API from January 2013 to October 2013. There are about 300 thousand posts in our data set for the experiment. After excluding data such as adverting or promoted tweets, we selected 149 thousand tweets for analysis. The number of tweets reaches its maximum level on the broadcasting day and increases rapidly around the broadcasting time. This result is stems from the characteristics of the public channel, which broadcasts the program at the predetermined time. From our analysis, we find that count-based features such as the number of tweets or retweets have a low correlation with TV ratings. This result implies that a simple tweet rate does not reflect the satisfaction or response to the TV programs. Content-based features extracted from the content of tweets have a relatively high correlation with TV ratings. Further, some emoticons or newly coined words that are not tagged in the morpheme extraction process have a strong relationship with TV ratings. We find that there is a time-dependency in the correlation of features between the before and after broadcasting time. Since the TV program is broadcast at the predetermined time regularly, users post tweets expressing their expectation for the program or disappointment over not being able to watch the program. The highly correlated features before the broadcast are different from the features after broadcasting. This result explains that the relevance of words with TV programs can change according to the time of the tweets. Among the 336 words that fulfill the minimum requirements for candidate features, 145 words have the highest correlation before the broadcasting time, whereas 68 words reach the highest correlation after broadcasting. Interestingly, some words that express the impossibility of watching the program show a high relevance, despite containing a negative meaning. Understanding the time-dependency of features can be helpful in improving the accuracy of TV ratings measurement. This research contributes a basis to estimate the response to or satisfaction with the broadcasted programs using the time dependency of words in Twitter chatter. More research is needed to refine the methodology for predicting or measuring TV ratings.

• Journal of Global Scholars of Marketing Science
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• v.18 no.2
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• pp.189-222
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• 2008

This study developed a model to empirically investigate the effects of market orientation and relationship orientation with suppliers on business performance and examine the moderating effects of entrepreneur's characteristics (working tenure) and clinic's location. The data was collected from 200 animal clinics which belong to Korean Animal Hospital Association (KAHA)'s national conference in April, 2007. Descriptive statistic, factor analysis, reliability analysis, and regression analysis were conducted to analyze the data using SPSS/PC+ 12.0. The findings are as follows. First, the market orientation of animal clinics influences significantly both financial and non-financial performance. When the moderating effect of entrepreneur's working tenure is considered, market orientation has significant effect on animal clinic's financial and non-financial performance. However, when the moderating effect of animal clinic's location is considered, market orientation has not significant effect on animal clinic's financial and non-financial performance. Second, animal clinic's relationship orientation with suppliers mostly affects the financial and non-financial performance significantly. When entrepreneur's working tenure in the clinic is longer (above 4 years group), relationship orientation with suppliers significantly affects both financial and non-financial performance. Meanwhile, when the entrepreneur's working tenure in the clinic is shorter (less than 3 years group), relationship orientation with suppliers doesn't affect clinic's financial performance but affect non-financial performance partially. In other words, when entrepreneur's working tenure is shorter (less than 3 years group), market orientation more influences on clinic's financial and non-financial performance while relationship orientation with suppliers does less. It is thought that their relation with suppliers and relationship orientation activities with suppliers are less strongly established and maintained yet. So, they primarily focus on market orientation strategy when entrepreneur's working tenure is shorter. Third, when animal clinics are located in non-metropolitan area, relationship orientation with suppliers significantly affects financial and non-financial performance. However, when animal clinics are located in metropolitan area, it doesn't affect financial and non-financial performance either. It is thought that animal clinics which are located in non-metropolitan area need stronger relationship with suppliers and need support more from them as most of suppliers actively work in metropolitan area not in the non-metropolitan area and animal clinics in metropolitan area can easily get better market information than animal clinics in non-metropolitan area. Lastly, while the effect of the market orientation significantly influences animal clinic's business performance continuously, the effect of the relationship orientation differently influences business performance as it is moderated by entrepreneur's working tenure and animal clinic's location. So, relationship orientation with suppliers can be selectively applied to improve the clinic's financial and no-financial performance. In summary, both of animal clinic's marketing orientation and animal clinic's relationship orientation with suppliers positively influence their business performance. However, entrepreneur's working tenure and animal clinic location moderate the relationship between market orientation and relationship orientation and their business performance differently. This study is quite meaningful to empirically investigate the effects of both of market orientation and relationship orientation with suppliers on business performance and examine the moderating effects of entrepreneur's characteristics (working tenure) and clinic's location. And, as this kind of study has been very few in the context of animal clinic industry, it helps practically understand the effects of market orientation and relationship orientation with suppliers on the financial and non-financial performance in animal clinic industry. Furthermore, as the market conditions in animal clinic industry have been in difficulty for a few years, this study can help improve animal clinic's financial and non-financial business performance together with their suppliers as business partners. Lastly, this study can help find mid-term and long-term cooperation between animal clinics and their suppliers. This study has some limitations. So, care should be taken when generalizing the results of the study. First, our samples were collected from only the animal clinics industry. However, a comparison of the results presented here with those form other marketing contexts (e.g., general hospitals) would be worthwhile. Future comparative research will enhance the generality of our contingency theory cross industry context. Second, this study found that market orientation and relationship orientation affect business performance. However, there may be other antecedents, such as internal market orientation and relationship orientation with customers. Also, this research did not consider other moderators, such as overall market conditions, competitive situations, and power/conflict between suppliers and buyers in the relationship between market and relationship orientation and business performance.

• Asia pacific journal of information systems
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• v.24 no.4
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• pp.443-472
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• 2014

To survive in the global competitive environment, enterprise should be able to solve various problems and find the optimal solution effectively. The big-data is being perceived as a tool for solving enterprise problems effectively and improve competitiveness with its' various problem solving and advanced predictive capabilities. Due to its remarkable performance, the implementation of big data systems has been increased through many enterprises around the world. Currently the big-data is called the 'crude oil' of the 21st century and is expected to provide competitive superiority. The reason why the big data is in the limelight is because while the conventional IT technology has been falling behind much in its possibility level, the big data has gone beyond the technological possibility and has the advantage of being utilized to create new values such as business optimization and new business creation through analysis of big data. Since the big data has been introduced too hastily without considering the strategic value deduction and achievement obtained through the big data, however, there are difficulties in the strategic value deduction and data utilization that can be gained through big data. According to the survey result of 1,800 IT professionals from 18 countries world wide, the percentage of the corporation where the big data is being utilized well was only 28%, and many of them responded that they are having difficulties in strategic value deduction and operation through big data. The strategic value should be deducted and environment phases like corporate internal and external related regulations and systems should be considered in order to introduce big data, but these factors were not well being reflected. The cause of the failure turned out to be that the big data was introduced by way of the IT trend and surrounding environment, but it was introduced hastily in the situation where the introduction condition was not well arranged. The strategic value which can be obtained through big data should be clearly comprehended and systematic environment analysis is very important about applicability in order to introduce successful big data, but since the corporations are considering only partial achievements and technological phases that can be obtained through big data, the successful introduction is not being made. Previous study shows that most of big data researches are focused on big data concept, cases, and practical suggestions without empirical study. The purpose of this study is provide the theoretically and practically useful implementation framework and strategies of big data systems with conducting comprehensive literature review, finding influencing factors for successful big data systems implementation, and analysing empirical models. To do this, the elements which can affect the introduction intention of big data were deducted by reviewing the information system's successful factors, strategic value perception factors, considering factors for the information system introduction environment and big data related literature in order to comprehend the effect factors when the corporations introduce big data and structured questionnaire was developed. After that, the questionnaire and the statistical analysis were performed with the people in charge of the big data inside the corporations as objects. According to the statistical analysis, it was shown that the strategic value perception factor and the inside-industry environmental factors affected positively the introduction intention of big data. The theoretical, practical and political implications deducted from the study result is as follows. The frist theoretical implication is that this study has proposed theoretically effect factors which affect the introduction intention of big data by reviewing the strategic value perception and environmental factors and big data related precedent studies and proposed the variables and measurement items which were analyzed empirically and verified. This study has meaning in that it has measured the influence of each variable on the introduction intention by verifying the relationship between the independent variables and the dependent variables through structural equation model. Second, this study has defined the independent variable(strategic value perception, environment), dependent variable(introduction intention) and regulatory variable(type of business and corporate size) about big data introduction intention and has arranged theoretical base in studying big data related field empirically afterwards by developing measurement items which has obtained credibility and validity. Third, by verifying the strategic value perception factors and the significance about environmental factors proposed in the conventional precedent studies, this study will be able to give aid to the afterwards empirical study about effect factors on big data introduction. The operational implications are as follows. First, this study has arranged the empirical study base about big data field by investigating the cause and effect relationship about the influence of the strategic value perception factor and environmental factor on the introduction intention and proposing the measurement items which has obtained the justice, credibility and validity etc. Second, this study has proposed the study result that the strategic value perception factor affects positively the big data introduction intention and it has meaning in that the importance of the strategic value perception has been presented. Third, the study has proposed that the corporation which introduces big data should consider the big data introduction through precise analysis about industry's internal environment. Fourth, this study has proposed the point that the size and type of business of the corresponding corporation should be considered in introducing the big data by presenting the difference of the effect factors of big data introduction depending on the size and type of business of the corporation. The political implications are as follows. First, variety of utilization of big data is needed. The strategic value that big data has can be accessed in various ways in the product, service field, productivity field, decision making field etc and can be utilized in all the business fields based on that, but the parts that main domestic corporations are considering are limited to some parts of the products and service fields. Accordingly, in introducing big data, reviewing the phase about utilization in detail and design the big data system in a form which can maximize the utilization rate will be necessary. Second, the study is proposing the burden of the cost of the system introduction, difficulty in utilization in the system and lack of credibility in the supply corporations etc in the big data introduction phase by corporations. Since the world IT corporations are predominating the big data market, the big data introduction of domestic corporations can not but to be dependent on the foreign corporations. When considering that fact, that our country does not have global IT corporations even though it is world powerful IT country, the big data can be thought to be the chance to rear world level corporations. Accordingly, the government shall need to rear star corporations through active political support. Third, the corporations' internal and external professional manpower for the big data introduction and operation lacks. Big data is a system where how valuable data can be deducted utilizing data is more important than the system construction itself. For this, talent who are equipped with academic knowledge and experience in various fields like IT, statistics, strategy and management etc and manpower training should be implemented through systematic education for these talents. This study has arranged theoretical base for empirical studies about big data related fields by comprehending the main variables which affect the big data introduction intention and verifying them and is expected to be able to propose useful guidelines for the corporations and policy developers who are considering big data implementationby analyzing empirically that theoretical base.