• Management & Information Systems Review
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• v.33 no.5
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• pp.185-212
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• 2014

This study investigated the base of marine leisure facilities and studied the future vision for development of marine industry by conducting a systematic analysis on the category of marine leisure products for development of design and specialization of southeast area of Korea. If the age of $20,000 of per capita national income is called 'the age of my car', $20,000 of per capita national income is called 'the age of my boat'. According to the report of UK-based Marine South East, the scale of world's small boat and personal waterborne equipment reached 277 trillion won in 2010 and domestic market scale is expected to be 11 trillion won. Marine leisure facilities are the new growth engine industry that the government should promote as a nation's strategic and core industry, and the government is pushing ahead with promotion of marine industry actively by announcing Marine Leisure Equipment Industry Activation Plan(June 2009, Ministry of Knowledge Economy), Marine Leisure Activation Plan(July 2010, Ministry of Land, Infrastructure and Transport), The 1st General Plan for Marina Port(January 2010, Ministry of Land, Infrastructure and Transport) etc. The purpose of marine design lies in seeking the status of the country and qualitative value in human life through functional, artistic, industrial and cultural development of design elements for all marine activities made around the sea. Related to all activities made in the ocean and cost, marine design is a sphere of design that includes special conditions centering around water. Considering the condition that 3 sides of land are facing the sea, this study systematically analyzed present condition of equipment possessed by each area, type of facilities, operational status, current status of sectoral use of marine leisure facilities and future prospect of marine leisure products that become the basis of value to raise the statue as an advanced marine power in 2010s through development of the qualitative level of the people, establishment of the direction of national strategy, convergence of industry and culture and specialization of area focusing on the actual condition survey of marine leisure facilities. Especially, this study will be predicting the basis of strategy for strengthening marketability and competitiveness by suggesting role and process of design in developing a promising marine leisure product through an actual condition survey of marine leisure products of southeast area.

• Asia pacific journal of information systems
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• v.18 no.4
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• pp.57-81
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• 2008

Knowledge is an essential strategic weapon for sustaining competitive advantage and is the key determinant for organizational growth. When knowledge is shared and disseminated throughout the organization, it increases an organization's value by providing the ability to respond to new and unusual situations. The growing importance of knowledge as a critical resource has forced executives to pay attention to their organizational knowledge. Organizations are increasingly undertaking knowledge management initiatives and making significant investments. Knowledge sourcing is considered as the first important step in effective knowledge management. Most firms continue to make an effort to realize the benefits of knowledge management by using various knowledge sources effectively. Appropriate knowledge sourcing strategies enable organizations to create, acquire, and access knowledge in a timely manner by reducing search and transfer costs, which result in better firm performance. In response, the knowledge management literature has devoted substantial attention to the analysis of knowledge sourcing strategies. Many studies have categorized knowledge sourcing strategies into intemal- and external-oriented. Internal-oriented sourcing strategy attempts to increase firm performance by integrating knowledge within the boundary of the firm. On the contrary, external-oriented strategy attempts to bring knowledge in from outside sources via either acquisition or imitation, and then to transfer that knowledge across to the organization. However, the extant literature on knowledge sourcing strategies focuses primarily on large organizations. Although many studies have clearly highlighted major differences between large and small firms and the need to adopt different strategies for different firm sizes, scant attention has been given to analyzing how knowledge sourcing strategies affect firm performance in small firms and what are the differences between small and large firms in the patterns of knowledge sourcing strategies adoption. This study attempts to advance the current literature by examining the impact of knowledge sourcing strategies on small firm performance from a holistic perspective. By drawing on knowledge based theory from organization science and complementarity theory from the economics literature, this paper is motivated by the following questions: (1) what are the adoption patterns of different knowledge sourcing strategies in small firms (i,e., what sourcing strategies should be adopted and which sourcing strategies work well together in small firms)?; and (2) what are the performance implications of these adoption patterns? In order to answer the questions, this study developed three hypotheses. First hypothesis based on knowledge based theory is that internal-oriented knowledge sourcing is positively associated with small firm performance. Second hypothesis developed on the basis of knowledge based theory is that external-oriented knowledge sourcing is positively associated with small firm performance. The third one based on complementarity theory is that pursuing both internal- and external-oriented knowledge sourcing simultaneously is negatively or less positively associated with small firm performance. As a sampling frame, 700 firms were identified from the Annual Corporation Report in Korea. Survey questionnaires were mailed to owners or executives who were most erudite about the firm s knowledge sourcing strategies and performance. A total of 188 companies replied, yielding a response rate of 26.8%. Due to incomplete data, 12 responses were eliminated, leaving 176 responses for the final analysis. Since all independent variables were measured using continuous variables, supermodularity function was used to test the hypotheses based on the cross partial derivative of payoff function. The results indicated no significant impact of internal-oriented sourcing strategies while positive impact of external-oriented sourcing strategy on small firm performance. This intriguing result could be explained on the basis of various resource and capital constraints of small firms. Small firms typically have restricted financial and human resources. They do not have enough assets to always develop knowledge internally. Another possible explanation is competency traps or core rigidities. Building up a knowledge base based on internal knowledge creates core competences, but at the same time, excessive internal focused knowledge exploration leads to behaviors blind to other knowledge. Interestingly, this study found that Internal- and external-oriented knowledge sourcing strategies had a substitutive relationship, which was inconsistent with previous studies that suggested complementary relationship between them. This result might be explained using organizational identification theory. Internal organizational members may perceive external knowledge as a threat, and tend to ignore knowledge from external sources because they prefer to maintain their own knowledge, legitimacy, and homogeneous attitudes. Therefore, integrating knowledge from internal and external sources might not be effective, resulting in failure of improvements of firm performance. Another possible explanation is small firms resource and capital constraints and lack of management expertise and absorptive capacity. Although the integration of different knowledge sources is critical, high levels of knowledge sourcing in many areas are quite expensive and so are often unrealistic for small enterprises. This study provides several implications for research as well as practice. First this study extends the existing knowledge by examining the substitutability (and complementarity) of knowledge sourcing strategies. Most prior studies have tended to investigate the independent effects of these strategies on performance without considering their combined impacts. Furthermore, this study tests complementarity based on the productivity approach that has been considered as a definitive test method for complementarity. Second, this study sheds new light on knowledge management research by identifying the relationship between knowledge sourcing strategies and small firm performance. Most current literature has insisted complementary relationship between knowledge sourcing strategies on the basis of data from large firms. Contrary to the conventional wisdom, this study identifies substitutive relationship between knowledge sourcing strategies using data from small firms. Third, implications for practice highlight that managers of small firms should focus on knowledge sourcing from external-oriented strategies. Moreover, adoption of both sourcing strategies simultaneousiy impedes small firm performance.

• Management & Information Systems Review
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• v.31 no.3
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• pp.223-248
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• 2012

This study analyses support policy and structural change of textile industry in Daegu Kyungbuk region, and suggests major issues for textile industry's innovation. In Daegu Kyungbuk, it was 1999 that a policy, so called Milano Project, in order to promote a textile industry was devised. In 2004, the Regional Industrial Promotion Plan was devised. The plan was born from a view point of establishing a regional innovation system and of promoting the innovative clusters under a knowledge based economy. After then, the Regional Industry Promotion Project or Regional Strategic Industry Promotion Project became a core of regional textile industrial policy. Research results indicated that the first stage Milano project (1999-2003) showed both positive and negative effects. There were no long-term development plan, clear vision and strategy. But, core industrial infrastructure for differentiated product development, such as New product Development Support Center and Dyeing Design Practical Application Center, was constructed. The second stage Daegu Textile Industry Promotion Plan (2004-2008) displayed a significant technological performance and new product sales with the assistance of Kyungbuk province. Also, textile industry revealed positive fruits such as financial structure, productivity, and profitability as a result of strong restructuring. In industrial structure, there was a important change from clothe textile material to industry textile material. Most of textile companies did not showed high capability in CEO's technology innovation intention, entrepreneurship, R&D and human resource competency in compare with other industry. We suggested that Daegu Kyungbuk has to select and concentrate on the high-tech textile material and living textile for sustainable development and competitiveness. We also proposed a confidence and cooperation based innovation network and company oriented innovation cluster.

• Management & Information Systems Review
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• v.36 no.2
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• pp.277-306
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• 2017

Most past studies on the Critical Success Factors of Company Informatization focused on the completeness of Informatization and its financial effect, and there have not been enough studies on whether a company's management strategies can be supported by establishing Informatization direction. This implies that there must be verification on the followings; whether Informatization focuses on steering the implementation of management strategies, what correlation there are between major mechanism factors and Informatization performance. This also implies that there must be a new study to re-interpret the existing success factors of Informatization into strategic management paradigm. The purpose of this study is to empirically verify the influence of subject, environment, resource, and mechanism factors on informatization achievement, and to analyze the differences in influence of informatization success factors on informatization achievement depending on domestic large corporations and SMEs. This study presented the verification results for seven research hypotheses. It was confirmed through empirical analysis that securing resource factor was significant in informatization performance and that all sub-factors of learning mechanism and coordination mechanism were also significant in enterprise informatization achievement. In addition, it was confirmed through the control effect analysis depending on enterprise size that the differences in informatization performance of large corporations and SMEs are due to support environment factor, learning mechanism, and selection mechanism. The implications of this study are as follows: First, the significance of mechanism factors such as learning, internal coordination, and external coordination are relatively higher than other factors in informatization achievement. Secondly, informatization success factors that SMEs must focus on achieving are presented by analyzing the differences on informatization achievement of large corporations and SMEs. Third, since empirical research for informatization success mechanism factors not covered empirically in the prior research was directly progressed, it is thought that it could provide a comprehensive understanding for mechanism factors. In addition, this study is thought to provide a practical contribution that can be applied to other industrial areas and enterprises.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.33-49
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• 2018

The impact of TV Drama success on TV Rating and the channel promotion effectiveness is very high. The cultural and business impact has been also demonstrated through the Korean Wave. Therefore, the early prediction of the blockbuster success of TV Drama is very important from the strategic perspective of the media industry. Previous studies have tried to predict the audience ratings and success of drama based on various methods. However, most of the studies have made simple predictions using intuitive methods such as the main actor and time zone. These studies have limitations in predicting. In this study, we propose a model for predicting the popularity of drama by analyzing the customer's viewing pattern based on various theories. This is not only a theoretical contribution but also has a contribution from the practical point of view that can be used in actual broadcasting companies. In this study, we collected data of 280 TV mini-series dramas, broadcasted over the terrestrial channels for 10 years from 2003 to 2012. From the data, we selected the most highly ranked and the least highly ranked 45 TV drama and analyzed the viewing patterns of them by 11-step. The various assumptions and conditions for modeling are based on existing studies, or by the opinions of actual broadcasters and by data mining techniques. Then, we developed a prediction model by measuring the viewing-time distance (difference) using Euclidean and Correlation method, which is termed in our study similarity (the sum of distance). Through the similarity measure, we predicted the success of dramas from the viewer's initial viewing-time pattern distribution using 1~5 episodes. In order to confirm that the model is shaken according to the measurement method, various distance measurement methods were applied and the model was checked for its dryness. And when the model was established, we could make a more predictive model using a grid search. Furthermore, we classified the viewers who had watched TV drama more than 70% of the total airtime as the "passionate viewer" when a new drama is broadcasted. Then we compared the drama's passionate viewer percentage the most highly ranked and the least highly ranked dramas. So that we can determine the possibility of blockbuster TV mini-series. We find that the initial viewing-time pattern is the key factor for the prediction of blockbuster dramas. From our model, block-buster dramas were correctly classified with the 75.47% accuracy with the initial viewing-time pattern analysis. This paper shows high prediction rate while suggesting audience rating method different from existing ones. Currently, broadcasters rely heavily on some famous actors called so-called star systems, so they are in more severe competition than ever due to rising production costs of broadcasting programs, long-term recession, aggressive investment in comprehensive programming channels and large corporations. Everyone is in a financially difficult situation. The basic revenue model of these broadcasters is advertising, and the execution of advertising is based on audience rating as a basic index. In the drama, there is uncertainty in the drama market that it is difficult to forecast the demand due to the nature of the commodity, while the drama market has a high financial contribution in the success of various contents of the broadcasting company. Therefore, to minimize the risk of failure. Thus, by analyzing the distribution of the first-time viewing time, it can be a practical help to establish a response strategy (organization/ marketing/story change, etc.) of the related company. Also, in this paper, we found that the behavior of the audience is crucial to the success of the program. In this paper, we define TV viewing as a measure of how enthusiastically watching TV is watched. We can predict the success of the program successfully by calculating the loyalty of the customer with the hot blood. This way of calculating loyalty can also be used to calculate loyalty to various platforms. It can also be used for marketing programs such as highlights, script previews, making movies, characters, games, and other marketing projects.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.111-126
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• 2020

Most industries have recently become aware of the importance of customer lifetime value as they are exposed to a competitive environment. As a result, preventing customers from churn is becoming a more important business issue than securing new customers. This is because maintaining churn customers is far more economical than securing new customers, and in fact, the acquisition cost of new customers is known to be five to six times higher than the maintenance cost of churn customers. Also, Companies that effectively prevent customer churn and improve customer retention rates are known to have a positive effect on not only increasing the company's profitability but also improving its brand image by improving customer satisfaction. Predicting customer churn, which had been conducted as a sub-research area for CRM, has recently become more important as a big data-based performance marketing theme due to the development of business machine learning technology. Until now, research on customer churn prediction has been carried out actively in such sectors as the mobile telecommunication industry, the financial industry, the distribution industry, and the game industry, which are highly competitive and urgent to manage churn. In addition, These churn prediction studies were focused on improving the performance of the churn prediction model itself, such as simply comparing the performance of various models, exploring features that are effective in forecasting departures, or developing new ensemble techniques, and were limited in terms of practical utilization because most studies considered the entire customer group as a group and developed a predictive model. As such, the main purpose of the existing related research was to improve the performance of the predictive model itself, and there was a relatively lack of research to improve the overall customer churn prediction process. In fact, customers in the business have different behavior characteristics due to heterogeneous transaction patterns, and the resulting churn rate is different, so it is unreasonable to assume the entire customer as a single customer group. Therefore, it is desirable to segment customers according to customer classification criteria, such as loyalty, and to operate an appropriate churn prediction model individually, in order to carry out effective customer churn predictions in heterogeneous industries. Of course, in some studies, there are studies in which customers are subdivided using clustering techniques and applied a churn prediction model for individual customer groups. Although this process of predicting churn can produce better predictions than a single predict model for the entire customer population, there is still room for improvement in that clustering is a mechanical, exploratory grouping technique that calculates distances based on inputs and does not reflect the strategic intent of an entity such as loyalties. This study proposes a segment-based customer departure prediction process (CCP/2DL: Customer Churn Prediction based on Two-Dimensional Loyalty segmentation) based on two-dimensional customer loyalty, assuming that successful customer churn management can be better done through improvements in the overall process than through the performance of the model itself. CCP/2DL is a series of churn prediction processes that segment two-way, quantitative and qualitative loyalty-based customer, conduct secondary grouping of customer segments according to churn patterns, and then independently apply heterogeneous churn prediction models for each churn pattern group. Performance comparisons were performed with the most commonly applied the General churn prediction process and the Clustering-based churn prediction process to assess the relative excellence of the proposed churn prediction process. The General churn prediction process used in this study refers to the process of predicting a single group of customers simply intended to be predicted as a machine learning model, using the most commonly used churn predicting method. And the Clustering-based churn prediction process is a method of first using clustering techniques to segment customers and implement a churn prediction model for each individual group. In cooperation with a global NGO, the proposed CCP/2DL performance showed better performance than other methodologies for predicting churn. This churn prediction process is not only effective in predicting churn, but can also be a strategic basis for obtaining a variety of customer observations and carrying out other related performance marketing activities.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.19-36
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• 2015

Social media is an emerging issue in content services and in current business environment. YouTube is the most representative social media service in the world. YouTube is different from other conventional content services in its open user participation and contents creation methods. To promote a content in YouTube, it is important to understand the diffusion phenomena of contents and the network structural characteristics. Most previous studies analyzed impact factors of contents diffusion from the view point of general behavioral factors. Currently some researchers use network structure factors. However, these two approaches have been used separately. However this study tries to analyze the general impact factors on the view count and content based network structures all together. In addition, when building a content based network, this study forms the network structure by analyzing user comments on 22,370 contents of YouTube not based on the individual user based network. From this study, we re-proved statistically the causal relations between view count and not only general factors but also network factors. Moreover by analyzing this integrated research model, we found that these factors affect the view count of YouTube according to the following order; Uploader Followers, Video Age, Betweenness Centrality, Comments, Closeness Centrality, Clustering Coefficient and Rating. However Degree Centrality and Eigenvector Centrality affect the view count negatively. From this research some strategic points for the utilizing of contents diffusion are as followings. First, it is needed to manage general factors such as the number of uploader followers or subscribers, the video age, the number of comments, average rating points, and etc. The impact of average rating points is not so much important as we thought before. However, it is needed to increase the number of uploader followers strategically and sustain the contents in the service as long as possible. Second, we need to pay attention to the impacts of betweenness centrality and closeness centrality among other network factors. Users seems to search the related subject or similar contents after watching a content. It is needed to shorten the distance between other popular contents in the service. Namely, this study showed that it is beneficial for increasing view counts by decreasing the number of search attempts and increasing similarity with many other contents. This is consistent with the result of the clustering coefficient impact analysis. Third, it is important to notice the negative impact of degree centrality and eigenvector centrality on the view count. If the number of connections with other contents is too much increased it means there are many similar contents and eventually it might distribute the view counts. Moreover, too high eigenvector centrality means that there are connections with popular contents around the content, and it might lose the view count because of the impact of the popular contents. It would be better to avoid connections with too powerful popular contents. From this study we analyzed the phenomenon and verified diffusion factors of Youtube contents by using an integrated model consisting of general factors and network structure factors. From the viewpoints of social contribution, this study might provide useful information to music or movie industry or other contents vendors for their effective contents services. This research provides basic schemes that can be applied strategically in online contents marketing. One of the limitations of this study is that this study formed a contents based network for the network structure analysis. It might be an indirect method to see the content network structure. We can use more various methods to establish direct content network. Further researches include more detailed researches like an analysis according to the types of contents or domains or characteristics of the contents or users, and etc.

• Asia pacific journal of information systems
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• v.19 no.4
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• pp.125-148
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• 2009

UGC(User Generated Contents) is emerging as the center of e-business in the web 2.0 era. The trend reflects changing roles of users in production and consumption of contents on websites and helps us to understand new strategies of websites such as web portals and social network websites. Nowadays, we consume contents created by other non-professional users for both utilitarian (e.g., knowledge) and hedonic values (e.g., fun). Also, contents produced by ourselves (e.g., photo, video) are posted on websites so that our friends, family, and even the public can consume those contents. This means that non-professionals, who used to be passive audience in the past, are now creating contents and share their UGCs with others in the Web. Accessible media, tools, and applications have also reduced difficulty and complexity in the process of creating contents. Realizing that users create plenty of materials which are very interesting to other people, media companies (i.e., web portals and social networking websites) are adjusting their strategies and business models accordingly. Increased demand of UGC may lead to website visits which are the source of benefits from advertising. Therefore, they put more efforts into making their websites open platforms where UGCs can be created and shared among users without technical and methodological difficulties. Many websites have increasingly adopted new technologies such as RSS and openAPI. Some have even changed the structure of web pages so that UGC can be seen several times to more visitors. This mainstream of UGCs on websites indicates that acquiring more UGCs and supporting participating users have become important things to media companies. Although those companies need to understand why general users have shown increasing interest in creating and posting contents and what is important to them in the process of productions, few research results exist in this area to address these issues. Also, behavioral process in creating video UGCs has not been explored enough for the public to fully understand it. With a solid theoretical background (i.e., theory of implementation intentions), parts of our proposed research model mirror the process of user behaviors in creating video contents, which consist of intention to upload, intention to edit, edit, and upload. In addition, in order to explain how those behavioral intentions are developed, we investigated influences of antecedents from three motivational perspectives (i.e., intrinsic, editing software-oriented, and website's network effect-oriented). First, from the intrinsic motivation perspective, we studied the roles of self-expression, enjoyment, and social attention in forming intention to edit with preferred editing software or in forming intention to upload video contents to preferred websites. Second, we explored the roles of editing software for non-professionals to edit video contents, in terms of how it makes production process easier and how it is useful in the process. Finally, from the website characteristic-oriented perspective, we investigated the role of a website's network externality as an antecedent of users' intention to upload to preferred websites. The rationale is that posting UGCs on websites are basically social-oriented behaviors; thus, users prefer a website with the high level of network externality for contents uploading. This study adopted a longitudinal research design; we emailed recipients twice with different questionnaires. Guided by invitation email including a link to web survey page, respondents answered most of questions except edit and upload at the first survey. They were asked to provide information about UGC editing software they mainly used and preferred website to upload edited contents, and then asked to answer related questions. For example, before answering questions regarding network externality, they individually had to declare the name of the website to which they would be willing to upload. At the end of the first survey, we asked if they agreed to participate in the corresponding survey in a month. During twenty days, 333 complete responses were gathered in the first survey. One month later, we emailed those recipients to ask for participation in the second survey. 185 of the 333 recipients (about 56 percentages) answered in the second survey. Personalized questionnaires were provided for them to remind the names of editing software and website that they reported in the first survey. They answered the degree of editing with the software and the degree of uploading video contents to the website for the past one month. To all recipients of the two surveys, exchange tickets for books (about 5,000~10,000 Korean Won) were provided according to the frequency of participations. PLS analysis shows that user behaviors in creating video contents are well explained by the theory of implementation intentions. In fact, intention to upload significantly influences intention to edit in the process of accomplishing the goal behavior, upload. These relationships show the behavioral process that has been unclear in users' creating video contents for uploading and also highlight important roles of editing in the process. Regarding the intrinsic motivations, the results illustrated that users are likely to edit their own video contents in order to express their own intrinsic traits such as thoughts and feelings. Also, their intention to upload contents in preferred website is formed because they want to attract much attention from others through contents reflecting themselves. This result well corresponds to the roles of the website characteristic, namely, network externality. Based on the PLS results, the network effect of a website has significant influence on users' intention to upload to the preferred website. This indicates that users with social attention motivations are likely to upload their video UGCs to a website whose network size is big enough to realize their motivations easily. Finally, regarding editing software characteristic-oriented motivations, making exclusively-provided editing software more user-friendly (i.e., easy of use, usefulness) plays an important role in leading to users' intention to edit. Our research contributes to both academic scholars and professionals. For researchers, our results show that the theory of implementation intentions is well applied to the video UGC context and very useful to explain the relationship between implementation intentions and goal behaviors. With the theory, this study theoretically and empirically confirmed that editing is a different and important behavior from uploading behavior, and we tested the behavioral process of ordinary users in creating video UGCs, focusing on significant motivational factors in each step. In addition, parts of our research model are also rooted in the solid theoretical background such as the technology acceptance model and the theory of network externality to explain the effects of UGC-related motivations. For practitioners, our results suggest that media companies need to restructure their websites so that users' needs for social interaction through UGC (e.g., self-expression, social attention) are well met. Also, we emphasize strategic importance of the network size of websites in leading non-professionals to upload video contents to the websites. Those websites need to find a way to utilize the network effects for acquiring more UGCs. Finally, we suggest that some ways to improve editing software be considered as a way to increase edit behavior which is a very important process leading to UGC uploading.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.67-101
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• 2014

The use of new technology greatly shapes the marketing strategies used by companies to engage their consumers. Among these new technologies, social media is used to reach out to the organization's audience online. One of the most popular social media channels to date is the microblogging platform Twitter. With 500 million tweets sent on average daily, the microblogging platform is definitely a rich source of data for researchers, and a lucrative marketing medium for companies. Nonetheless, one of the challenges for companies in developing an effective Twitter campaign is the limited theoretical and empirical evidence on the proper organizational usage of Twitter despite its potential advantages for a firm's external communications. The current study aims to provide empirical evidence on how firms can utilize Twitter effectively in their marketing communications using the association between brand personality and brand engagement that several branding researchers propose. The study extends Aaker's previous empirical work on brand personality by applying the Brand Personality Scale to explore whether Twitter brand communities convey distinctive brand personalities online and its influence on the communities' level or intensity of consumer engagement and sentiment quality. Moreover, the moderating effect of the product involvement construct in consumer engagement is also measured. By collecting data for a period of eight weeks using the publicly available Twitter application programming interface (API) from 23 accounts of Twitter-verified business-to-consumer (B2C) brands, we analyze the validity of the paper's hypothesis by using computerized content analysis and opinion mining. The study is the first to compare Twitter marketing across organizations using the brand personality concept. It demonstrates a potential basis for Twitter strategies and discusses the benefits of these strategies, thus providing a framework of analysis for Twitter practice and strategic direction for companies developing their use of Twitter to communicate with their followers on this social media platform. This study has four specific research objectives. The first objective is to examine the applicability of brand personality dimensions used in marketing research to online brand communities on Twitter. The second is to establish a connection between the congruence of offline and online brand personalities in building a successful social media brand community. Third, we test the moderating effect of product involvement in the effect of brand personality on brand community engagement. Lastly, we investigate the sentiment quality of consumer messages to the firms that succeed in communicating their brands' personalities on Twitter.

• Journal of the Korean Institute of Landscape Architecture
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• v.47 no.2
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• pp.59-75
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• 2019

This study was carried out to explore the 4th Industrial Revolution technology from the perspective of the landscape industry to provide the basic data necessary to increase the virtuous circle value. The 4th Industrial Revolution, the characteristics of the landscape industry and urban regeneration were considered and the methodology was established and studied including the technical classification system suitable for systematic research, which was selected as a framework. First, the 4th Industrial Revolution technology based on digital data was selected, which could be utilized to increase the value of the virtuous circle for the landscape industry. From 'Element Technology Level', and 'Core Technology' such as the Internet of Things, Cloud Computing, Big Data, Artificial Intelligence, Robot, 'Peripheral Technology', Virtual or Augmented Reality, Drones, 3D 4D Printing, and 3D Scanning were highlighted as the 4th Industrial Revolution technology. It has been shown that it is possible to increase the value of the virtuous circle when applied at the 'Trend Level', in particular to the landscape industry. The 'System Level' was analyzed as a general-purpose technology, and based on the platform, the level of element technology(computers, and smart devices) was systematically interconnected, and illuminated with the 4th Industrial Revolution technology based on digital data. The application of the 'Trend Level' specific to the landscape industry has been shown to be an effective technology for increasing the virtuous circle values. It is possible to realize all synergistic effects and implementation of the proposed method at the trend level applying the element technology level. Smart gardens, smart parks, etc. have been analyzed to the level they should pursue. It was judged that Smart City, Smart Home, Smart Farm, and Precision Agriculture, Smart Tourism, and Smart Health Care could be highly linked through the collaboration among technologies in adjacent areas at the Trend Level. Additionally, various utilization measures of related technology applied at the Trend Level were highlighted in the process of urban regeneration, public service space creation, maintenance, and public service. In other words, with the realization of ubiquitous computing, Hyper-Connectivity, Hyper-Reality, Hyper-Intelligence, and Hyper-Convergence were proposed, reflecting the basic characteristics of digital technology in the landscape industry can be achieved. It was analyzed that the landscaping industry was effectively accommodating and coordinating with the needs of new characters, education and consulting, as well as existing tasks, even when participating in urban regeneration projects. In particular, it has been shown that the overall landscapig area is effective in increasing the virtuous circle value when it systems the related technology at the trend level by linking maintenance with strategic bridgehead. This is because the industrial structure is effective in distributing data and information produced from various channels. Subsequent research, such as demonstrating the fusion of the 4th Industrial Revolution technology based on the use of digital data in creation, maintenance, and service of actual landscape space is necessary.