• Asia pacific journal of information systems
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• v.22 no.1
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• pp.29-52
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• 2012

Consumers differ in the way they make a purchase. An audio mania would willingly make a bold, yet serious, decision to buy a top-of-the-line home theater system, while he is not interested in replacing his two-decade-old shabby car. On the contrary, an automobile enthusiast wouldn't mind spending forty thousand dollars to buy a new Jaguar convertible, yet cares little about his junky component system. It is product involvement that helps us explain such differences among individuals in the purchase style. Product involvement refers to the extent to which a product is perceived to be important to a consumer (Zaichkowsky, 2001). Product involvement is an important factor that strongly influences consumer's purchase decision-making process, and thus has been of prime interest to consumer behavior researchers. Furthermore, researchers found that involvement is closely related to perceived risk (Dholakia, 2001). While abundant research exists addressing how product involvement relates to overall perceived risk, little attention has been paid to the relationship between involvement and different types of perceived risk in an electronic commerce setting. Given that perceived risk can be a substantial barrier to the online purchase (Jarvenpaa, 2000), research addressing such an issue will offer useful implications on what specific types of perceived risk an online firm should focus on mitigating if it is to increase sales to a fullest potential. Meanwhile, past research has focused on such consumer responses as information search and dissemination as a consequence of involvement, neglecting other behavioral responses like online merchant selection. For one example, will a consumer seriously considering the purchase of a pricey Guzzi bag perceive a great degree of risk associated with online buying and therefore choose to buy it from a digital storefront rather than from an online marketplace to mitigate risk? Will a consumer require greater trust on the part of the online merchant when the perceived risk of online buying is rather high? We intend to find answers to these research questions through an empirical study. This paper explores the impact of enduring product involvement and perceived risks on required trust level, and further on online merchant choice. For the purpose of the research, five types or components of perceived risk are taken into consideration, including financial, performance, delivery, psychological, and social risks. A research model has been built around the constructs under consideration, and 12 hypotheses have been developed based on the research model to examine the relationships between enduring involvement and five components of perceived risk, between five components of perceived risk and required trust level, between enduring involvement and required trust level, and finally between required trust level and preference toward an e-tailer. To attain our research objectives, we conducted an empirical analysis consisting of two phases of data collection: a pilot test and main survey. The pilot test was conducted using 25 college students to ensure that the questionnaire items are clear and straightforward. Then the main survey was conducted using 295 college students at a major university for nine days between December 13, 2010 and December 21, 2010. The measures employed to test the model included eight constructs: (1) enduring involvement, (2) financial risk, (3) performance risk, (4) delivery risk, (5) psychological risk, (6) social risk, (7) required trust level, (8) preference toward an e-tailer. The statistical package, SPSS 17.0, was used to test the internal consistency among the items within the individual measures. Based on the Cronbach's ${\alpha}$ coefficients of the individual measure, the reliability of all the variables is supported. Meanwhile, the Amos 18.0 package was employed to perform a confirmatory factor analysis designed to assess the unidimensionality of the measures. The goodness of fit for the measurement model was satisfied. Unidimensionality was tested using convergent, discriminant, and nomological validity. The statistical evidences proved that the three types of validity were all satisfied. Now the structured equation modeling technique was used to analyze the individual paths along the relationships among the research constructs. The results indicated that enduring involvement has significant positive relationships with all the five components of perceived risk, while only performance risk is significantly related to trust level required by consumers for purchase. It can be inferred from the findings that product performance problems are mostly likely to occur when a merchant behaves in an opportunistic manner. Positive relationships were also found between involvement and required trust level and between required trust level and online merchant choice. Enduring involvement is concerned with the pleasure a consumer derives from a product class and/or with the desire for knowledge for the product class, and thus is likely to motivate the consumer to look for ways of mitigating perceived risk by requiring a higher level of trust on the part of the online merchant. Likewise, a consumer requiring a high level of trust on the merchant will choose a digital storefront rather than an e-marketplace, since a digital storefront is believed to be trustworthier than an e-marketplace, as it fulfills orders by itself rather than acting as an intermediary. The findings of the present research provide both academic and practical implications. The first academic implication is that enduring product involvement is a strong motivator of consumer responses, especially the selection of a merchant, in the context of electronic shopping. Secondly, academicians are advised to pay attention to the finding that an individual component or type of perceived risk can be used as an important research construct, since it would allow one to pinpoint the specific types of risk that are influenced by antecedents or that influence consequents. Meanwhile, our research provides implications useful for online merchants (both online storefronts and e-marketplaces). Merchants may develop strategies to attract consumers by managing perceived performance risk involved in purchase decisions, since it was found to have significant positive relationship with the level of trust required by a consumer on the part of the merchant. One way to manage performance risk would be to thoroughly examine the product before shipping to ensure that it has no deficiencies or flaws. Secondly, digital storefronts are advised to focus on symbolic goods (e.g., cars, cell phones, fashion outfits, and handbags) in which consumers are relatively more involved than others, whereas e- marketplaces should put their emphasis on non-symbolic goods (e.g., drinks, books, MP3 players, and bike accessories).

• Journal of Global Scholars of Marketing Science
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• v.20 no.3
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• pp.269-277
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• 2010

Previous studies have shown that the most important factor affecting customer loyalty in the service industry is service quality. However, on the subject of whether service quality has a direct or indirect effect on customer loyalty, scholars' views apparently vary. Some studies suggest that service quality has a direct and fundamental influence on customer loyalty (Bai and Liu, 2002). However, others have shown that service quality not only directly affects customer loyalty, it also has an indirect impact on customer loyalty by influencing customer satisfaction and perceived value (Cronin, Brady, and Hult, 2000). Currently, there are few domestic articles that specifically address the relationship between service quality and customer loyalty in the mobile communication industry. Moreover, research has studied customer loyalty as a whole variable, rather than breaking it down further into multiple dimensions. Based on this analysis, this paper summarizes previous study results, establishes an effect mechanism model among service quality, customer satisfaction, and customer loyalty in the mobile communication industry, and presents a statistical test on model assumptions by using customer investigation data from Heilongjiang Mobile Company. It provides theoretical guidance for mobile service management based on the discussion of the hypothesis test results. For data collection, the sample comprised mobile users in Harbin city, and the survey was taken by random sampling. Out of a total of 300 questionnaires, 276 (92.9%) were recovered. After excluding invalid questionnaires, 249 remained, for an effective rate of 82.6 percent for the study. Cronbach's ${\alpha}$ coefficient was adapted to assess the scale reliability, and validity testing was conducted on the questionnaire from three aspects: content validity, construct validity. and convergent validity. The study tested for goodness of fit mainly from the absolute and relative fit indexes. From the hypothesis testing results, overall, four assumptions have not been supported. The ultimate affective relationship of service quality, customer satisfaction, and customer loyalty is demonstrated in Figure 2. On the whole, the service quality of the communication industry not only has a direct positive significant effect on customer loyalty, it also has an indirect positive significant effect on customer loyalty through service quality; the affective mechanism and extent of customer loyalty are different, and are influenced by each dimension of service quality. This study used the questionnaires of existing literature from home and abroad and tested them in empirical research, with all questions adapted to seven-point Likert scales. With the SERVQUAL scale of Parasuraman, Zeithaml, and Berry (1988), or PZB, as a reference point, service quality was divided into five dimensions-tangibility, reliability, responsiveness, assurance, and empathy-and the questions were simplified down to nineteen. The measurement of customer satisfaction was based mainly on Fornell (1992) and Wang and Han (2003), ending up with four questions. Based on the study’s three indicators of price tolerance, first choice, and complaint reaction were used to measure attitudinal loyalty, while repurchase intention, recommendation, and reputation measured behavioral loyalty. The collection and collation of literature data produced a model of the relationship among service quality, customer satisfaction, and customer loyalty in mobile communications, and China Mobile in the city of Harbin in Heilongjiang province was used for conducting an empirical test of the model and obtaining some useful conclusions. First, service quality in mobile communication is formed by the five factors mentioned earlier: tangibility, reliability, responsiveness, assurance, and empathy. On the basis of PZB SERVQUAL, the study designed a measurement scale of service quality for the mobile communications industry, and obtained these five factors through exploratory factor analysis. The factors fit basically with the five elements, indicating the concept of five elements of service quality for the mobile communications industry. Second, service quality in mobile communications has both direct and indirect positive effects on attitudinal loyalty, with the indirect effect being produced through the intermediary variable, customer satisfaction. There are also both direct and indirect positive effects on behavioral loyalty, with the indirect effect produced through two intermediary variables: customer satisfaction and attitudinal loyalty. This shows that better service quality and higher customer satisfaction will activate the attitudinal to service providers more active and show loyalty to service providers much easier. In addition, the effect mechanism of all dimensions of service quality on all dimensions of customer loyalty is different. Third, customer satisfaction plays a significant intermediary role among service quality and attitudinal and behavioral loyalty, indicating that improving service quality can boost customer satisfaction and make it easier for satisfied customers to become loyal customers. Moreover, attitudinal loyalty plays a significant intermediary role between service quality and behavioral loyalty, indicating that only attitudinally and behaviorally loyal customers are truly loyal customers. The research conclusions have some indications for Chinese telecom operators and others to upgrade their service quality. Two limitations to the study are also mentioned. First, all data were collected in the Heilongjiang area, so there might be a common method bias that skews the results. Second, the discussion addresses the relationship between service quality and customer loyalty, setting customer satisfaction as mediator, but does not consider other factors, like customer value and consumer features, This research will be continued in the future.

• Journal of Radiation Protection and Research
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• v.33 no.4
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• pp.127-134
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• 2008

Potential economic impact of a hypothetical severe accident at a nuclear power plant(Uljin units 3/4) was estimated by applying the Delphi method, which is based on the expert judgements and opinions, in the process of quantifying uncertain factors. For the purpose of this study, it is assumed that the radioactive plume directs the inland direction. Since the economic risk can be divided into direct costs and indirect effects and more uncertainties are involved in the latter, the direct costs were estimated first and the indirect effects were then estimated by applying a weighting factor to the direct cost. The Delphi method however subjects to risk of distortion or discrimination of variables because of the human behavior pattern. A mathematical approach based on the Bayesian inferences was employed for data processing to improve the Delphi results. For this task, a model for data processing was developed. One-dimensional Monte Carlo Analysis was applied to get a distribution of values of the weighting factor. The mean and median values of the weighting factor for the indirect effects appeared to be 2.59 and 2.08, respectively. These values are higher than the value suggested by OECD/NEA, 1.25. Some factors such as small territory and public attitude sensitive to radiation could affect the judgement of panel. Then the parameters of the model for estimating the direct costs were classified as U- and V-types, and two-dimensional Monte Carlo analysis was applied to quantify the overall economic risk. The resulting median of the overall economic risk was about 3.9% of the gross domestic products(GDP) of Korea in 2006. When the cost of electricity loss, the highest direct cost, was not taken into account, the overall economic risk was reduced to 2.2% of GDP. This assessment can be used as a reference for justifying the radiological emergency planning and preparedness.

• Asia pacific journal of information systems
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• v.23 no.1
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• pp.87-106
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• 2013

In the service-oriented economy, knowledge and skills are considered core resources to secure competitive advantages and service innovation. Knowledge management capability, which facilitates to produce, share, accumulate and reuse knowledge, becomes as important as knowledge itself to create service value. Along with knowledge management capability, dynamic capability and operational capability are the key capabilities related to managing service delivery processes. Previous studies indicated that these three capabilities are related to service innovation. Although separately investigate the relationship between the three capabilities. The purpose of this study is 1) to define variables that have effects on service innovation including knowledge management capability, dynamic capability and operational capability, and 2) to empirically test to identify relationship among variables. In this study, knowledge management capability is defined as the capability to manage knowledge process. Dynamic capability is regarded as the firm's ability to integrate, build, and reconfigure internal and external competences to address rapidly changing environments. Operational capability refers to a high-level routine that, together with its implementing input flows, confers upon an organization's management a set of decision options for producing significant outputs of a particular type. The proposed research model was tested against the data collected through the survey method. The survey questionnaire was distributed to the managers who participated in an educational program for management consulting. Each individual who answered the questionnaire represented a knowledge based service firm. About 212 surveys questionnaires were sent via e-mail or directly delivered to respondents. The number of useable responses was 93. Measurement items were adapted from previous studies to reflect the characteristics of the industry each informant worked in. All measurement items were in, 5 point Likert scale with anchors ranging from strongly disagree (1) to strongly agree (5). Out of 93 respondents, about 81% were male, 82% of respondents were in their 30s. In terms of jobs, managers were 39.78%, professions/technicians were 24.73%, researchers were 12.90%, and sales people were 10.75%. Most of respondents worked for medium size enterprises (47,31%) in their, less than 30 employees (46.24%) in their number of employees, and less than 10 million USD (65.59%) in terms of sales volume. To test the proposed research model, structural equation modeling (SEM) technique (SPSS 16.0 and AMOS version 5) was used. We found that the three organizational capabilities have influence on service innovation directly or indirectly. Knowledge management capability directly affects dynamic capability and service innovation but indirectly affect operational capability through dynamic capability. Dynamic capability has no direct impact on service innovation, but influence service innovation indirectly through operational capability. Operational capability was found to positively affect service innovation. In sum, three organizational capabilities (knowledge management capability, dynamic capability and operational capability) need to be strategically managed at firm level, because organizational capabilities are significantly related to service innovation. An interesting result is that dynamic capability has a positive effect on service innovation only indirectly through operational capability. This result indicates that service innovation might have a characteristics similar to process innovation rather than product orientation. The results also show that organizational capabilities are inter-correlated to influence each other. Dynamic capability enables effective resource management, arrangement, and integration. Through these dynamic capability affected activities, strategic agility and responsibility get strength. Knowledge management capability intensify dynamic capability and service innovation. Knowledge management capability is the basis of dynamic capability as well. The theoretical and practical implications are discussed further in the conclusion section.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.19-38
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• 2017

Collaborative filtering (CF) algorithm has been popularly used for implementing recommender systems. Until now, there have been many prior studies to improve the accuracy of CF. Among them, some recent studies adopt 'hybrid recommendation approach', which enhances the performance of conventional CF by using additional information. In this research, we propose a new hybrid recommender system which fuses CF and the results from the social network analysis on trust and distrust relationship networks among users to enhance prediction accuracy. The proposed algorithm of our study is based on memory-based CF. But, when calculating the similarity between users in CF, our proposed algorithm considers not only the correlation of the users' numeric rating patterns, but also the users' in-degree centrality values derived from trust and distrust relationship networks. In specific, it is designed to amplify the similarity between a target user and his or her neighbor when the neighbor has higher in-degree centrality in the trust relationship network. Also, it attenuates the similarity between a target user and his or her neighbor when the neighbor has higher in-degree centrality in the distrust relationship network. Our proposed algorithm considers four (4) types of user relationships - direct trust, indirect trust, direct distrust, and indirect distrust - in total. And, it uses four adjusting coefficients, which adjusts the level of amplification / attenuation for in-degree centrality values derived from direct / indirect trust and distrust relationship networks. To determine optimal adjusting coefficients, genetic algorithms (GA) has been adopted. Under this background, we named our proposed algorithm as SNACF-GA (Social Network Analysis - based CF using GA). To validate the performance of the SNACF-GA, we used a real-world data set which is called 'Extended Epinions dataset' provided by 'trustlet.org'. It is the data set contains user responses (rating scores and reviews) after purchasing specific items (e.g. car, movie, music, book) as well as trust / distrust relationship information indicating whom to trust or distrust between users. The experimental system was basically developed using Microsoft Visual Basic for Applications (VBA), but we also used UCINET 6 for calculating the in-degree centrality of trust / distrust relationship networks. In addition, we used Palisade Software's Evolver, which is a commercial software implements genetic algorithm. To examine the effectiveness of our proposed system more precisely, we adopted two comparison models. The first comparison model is conventional CF. It only uses users' explicit numeric ratings when calculating the similarities between users. That is, it does not consider trust / distrust relationship between users at all. The second comparison model is SNACF (Social Network Analysis - based CF). SNACF differs from the proposed algorithm SNACF-GA in that it considers only direct trust / distrust relationships. It also does not use GA optimization. The performances of the proposed algorithm and comparison models were evaluated by using average MAE (mean absolute error). Experimental result showed that the optimal adjusting coefficients for direct trust, indirect trust, direct distrust, indirect distrust were 0, 1.4287, 1.5, 0.4615 each. This implies that distrust relationships between users are more important than trust ones in recommender systems. From the perspective of recommendation accuracy, SNACF-GA (Avg. MAE = 0.111943), the proposed algorithm which reflects both direct and indirect trust / distrust relationships information, was found to greatly outperform a conventional CF (Avg. MAE = 0.112638). Also, the algorithm showed better recommendation accuracy than the SNACF (Avg. MAE = 0.112209). To confirm whether these differences are statistically significant or not, we applied paired samples t-test. The results from the paired samples t-test presented that the difference between SNACF-GA and conventional CF was statistical significant at the 1% significance level, and the difference between SNACF-GA and SNACF was statistical significant at the 5%. Our study found that the trust/distrust relationship can be important information for improving performance of recommendation algorithms. Especially, distrust relationship information was found to have a greater impact on the performance improvement of CF. This implies that we need to have more attention on distrust (negative) relationships rather than trust (positive) ones when tracking and managing social relationships between users.

• Journal of the Korean Institute of Landscape Architecture
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• v.48 no.1
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• pp.25-34
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• 2020

Land use in watersheds has been shown to be a major driving factor in determining the status of the water quality of streams. In this light, scientists have been investigating the roles of riparian vegetation on the relationships between land use in watersheds and the associated stream water quality. Numerous studies reported that riparian vegetation could alleviate the adverse effects caused by land use in watersheds and on stream water quality through various hydrological, biochemical and ecological mechanisms. However, this concept has been criticized as the true effects of riparian vegetation must be assessed by comprehensive models that mimic real environmental settings. This study aimed to estimate a comprehensive structural equation model integrating topography, land use, and characteristics of riparian vegetation. We used water quality data from the Nakdong River system monitored under the National Aquatic Ecosystem Monitoring Program (NAEMP) of the Korean Ministry of Environment (MOE). Also, riparian vegetation data and land use data were extracted from the Land Use/Land Cover map (LULC) produced by the MOE. The number of structural equation models (SEMs) were estimated in Amos of IBM SPSS. Study results revealed that land use was determined by elevation, and developed areas within a watershed significantly increased the concentration of Total Nitrogen (TN) in streams and LDI in riparian vegetation. On the contrary, developed areas significantly reduced LPI and PLAND. At the same time, PLAND and LDI significantly reduced the concentration of TN in streams. Thus, it was clear that developed areas in watersheds had both a direct and an indirect impact on the concentration of TN in streams, and spatial pattern and the amount of vegetation of riparian vegetation could significantly alleviate the negative impacts of developed areas on TN concentration in streams. To enhance stream water quality, reducing developed areas in a watershed is critical for long-term watershed management plans, restoration patterns for riparian vegetation could be immediately implemented since riparian areas were less developed than most other watersheds.

• Journal of Korea Water Resources Association
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• v.51 no.2
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• pp.141-150
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• 2018

The purpose of this study is to evaluate the future hydrologic behavior affected by the potential climate and land use changes in upstream of Anseong-cheon watershed ($366.5km^2$) using SWAT. The HadGEM3-RA RCP 4.5 and 8.5 scenarios were used for 2030s (2020-2039) and 2050s (2040-2059) periods as the future climate change scenario. It was shown that maximum changes of precipitation ranged from -5.7% in 2030s to +18.5% in 2050s for RCP 4.5 scenarios and the temperature increased up to $1.8^{\circ}C$ and $2.6^{\circ}C$ in 2030s RCP 4.5 and 2050s 8.5 scenarios respectively based on baseline (1976-2005) period. The future land uses were predicted using the CLUE-s model by establishing logistic regression equation. The 2050 urban area were predicted to increase of 58.6% (29.0 to $46.0km^2$). The SWAT was calibrated and verified using 14 years (2002-2015) of daily streamflow with 0.86 and 0.76 Nash-Sutcliffe model efficiency (NSE) for stream flow (Q) and low flow 1/Q respectively focusing on 2 drought years (2014-2015) calibration. For future climate change only, the stream discharge showed maximum decrease of 24.2% in 2030s RCP 4.5 and turned to maximum increase of 10.9% in 2050s RCP 4.5 scenario compared with the baseline period stream discharge of 601.0 mm by the precipitation variation and gradual temperature increase. While considering both future climate and land use change, the stream discharge showed maximum decrease of 14.9% in 2030s RCP 4.5 and maximum increase of 19.5% in 2050s RCP 4.5 scenario by the urban growth and the related land use changes. The results supported that the future land use factor might be considered especially for having high potential urban growth within a watershed in the future climate change assessment.

• Journal of the Korean Institute of Landscape Architecture
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• v.39 no.5
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• pp.57-75
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• 2011

The purpose of this study is to find ways of evaluating the suitability of sites being considered for development of different types of parks in the vicinity of yangmock-myun kyoung buk, where a large project(as large as about14.0$km^2$) has been planned. The results are as follows. Three surveys for selecting the assessment indicators were performed. ${\cdot}$ The first survey analyzed the importance of 23 selected assessment indicators based on a review of existing literature review and an on-the-spot research. ${\cdot}$ The second survey selected assessment indicators for each park type. ${\cdot}$ The third survey computed additive values of selected assessment indicators by the park types. It used a method of standardizing the average importance of indicators by making their sum equal to 10. These additive values were then multiplied by each grade of indicators to make a final evaluation. An evaluation of the site-suitability of park types was performed twice. The purpose of the first evaluation was to figure out how much each type met the minimum requirements targeted for all landscape types. The minimum requirements were derived by using a relative comparison between the standard of value rating of the assessment indicators, which was over the medium magnitude on the importance analysis, and the result of field research. A second evaluation estimated the targeted sites that met the minimum requirements. Value ratings of second assessment indicators were quantitatively divided as 1 to 3 grade and the evaluation scores were added, giving an additive value for each assessment indicator. The evaluation score on each park type was rated on a scale of 1 to 3 according to their averages, (from lowest to highest). Since this evaluation model of the site suitability on park types only focused on the 'face' of space in this study, additional analysis is necessary for setting the evaluation model and incorporating the overall impact of space, network connection and other factors, considering 'spot', 'line' and 'face' aspects of space.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.53-74
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• 2018

Since South Korea has an economic structure that has a characteristic which market-dependent on overseas, the tourism industry is considered as a very important industry for the national economy, such as improving the country's balance of payments or providing income and employment increases. Accordingly, the necessity of more accurate forecasting on the demand in the tourism industry has been raised to promote its industry. In the related research, economic variables such as exchange rate and income have been used as variables influencing tourism demand. As information technology has been widely used, some researchers have also analyzed the effect of media on tourism demand. It has shown that the media has a considerable influence on traveler's decision making, such as choosing an outbound destination. Furthermore, with the recent availability of online information searches to obtain the latest information and two-way communication in social media, it is possible to obtain up-to-date information on travel more quickly than before. The information in online media such as blogs can naturally create the Word-of-Mouth effect by sharing useful information, which is called eWOM. Like all other service industries, the tourism industry is characterized by difficulty in evaluating its values before it is experienced directly. And furthermore, most of the travelers tend to search for more information in advance from various sources to reduce the perceived risk to the destination, so they can also be influenced by online media such as online news. In this study, we suggested that the number of online media posting, which causes the effects of Word-of-Mouth, may have an effect on the number of outbound travelers. We divided online media into public media and private media according to their characteristics and selected online news as public media and blog as private media, one of the most popular social media in tourist information. Based on the previous studies about the eWOM effects on online news and blog, we analyzed a relationship between the volume of eWOM and the outbound tourism demand through the panel model. To this end, we collected data on the number of national outbound travelers from 2007 to 2015 provided by the Korea Tourism Organization. According to statistics, the highest number of outbound tourism demand in Korea are China, Japan, Thailand, Hong Kong and the Philippines, which are selected as a dependent variable in this study. In order to measure the volume of eWOM, we collected online news and blog postings for the same period as the number of outbound travelers in Naver, which is the largest portal site in South Korea. In this study, a panel model was established to analyze the effect of online media on the demand of Korean outbound travelers and to identify that there was a significant difference in the influence of online media by each time and countries. The results of this study can be summarized as follows. First, the impact of the online news and blog eWOM on the number of outbound travelers was significant. We found that the number of online news and blog posting have an influence on the number of outbound travelers, especially the experimental result suggests that both the month that includes the departure date and the three months before the departure were found to have an effect. It is shown that online news and blog are online media that have a significant influence on outbound tourism demand. Next, we found that the increased volume of eWOM in online news has a negative effect on departure, while the increase in a blog has a positive effect. The result with the country-specific models would be the same. This paper shows that online media can be used as a new variable in tourism demand by examining the influence of the eWOM effect of the online media. Also, we found that both social media and news media have an important role in predicting and managing the Korean tourism demand and that the influence of those two media appears different depending on the country.

• Korean Security Journal
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• no.62
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• pp.35-63
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• 2020

As the frequency and intensity of catastrophic disasters increase, there is widespread public sentiment that government capacity for disaster response and recovery is fundamentally limited, and that the involvement of civil society and the private sector is ever more vital. That is, in order to strengthen national disaster response capacity, governments need to build disaster systems that are more participatory and function through the channels of civil society, rather than continuing themselves to bear sole responsibility for these "wicked problems." With the advancement of smart mobile technology and social media, government and society as a whole have been called upon to apply these new information and communication technologies to address the current shortcomings of government-led disaster management. As illustrated in such catastrophic disasters as the 2011 Tohoku earthquake and tsunami in Japan, the 2010 Haitian earthquake, and Hurricane Katrina in the United States in 2005, the realization of participatory potential of smart technologies for better disaster response has enabled citizen participation via new smart technologies during disasters and resulted in positive impact on the management of such disasters. In this context, this study focuses on the South Korean context, and aims to analyze Korean government officials' readiness for public participation using smart technologies. On this basis, it aims to offer policy suggestions aimed at promoting smart technology-enabled citizen participation. For this purpose, it proposes a particular model, termed SMART (System, Motivation, Ability, Response, and Technology).