• Asia pacific journal of information systems
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• v.19 no.3
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• pp.69-98
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• 2009

We investigated what factors motivate gamers to participate in a guild and why they continue to be engaged as members of the guild. We find that, based on the result of focus group interviews with MMORPG gamers, social support and self-esteem factors play important roles. Considering both prior research and the focus group interviews we have conducted, we define social support and character control as independent variables. Character identity, guild identity, and self-esteem are proposed as mediating variables while guild flow and game loyalty as dependent variables. Accordingly, we develop the research model and hypotheses, and verify them empirically. Based on our experiences of playing the WoW game, we proposed a research model and conducted focus-group interviews (FGIs). FGIs involve formulating a hypothesis and then collecting some relevant data. FGIs were conducted face-to-face with students of C University in Korea. We formulated structured interview schedules, and the questions were based on our research variables and personal experiences. The questions for the interviews encompassed the following areas: (a) the demographic characteristics of the focus group; (b) the number of years for which respondents had played online games; (c) the motive for starting a game; (d) the number of game-characters assumed by each gamer; (e) the type of game played; and (f) other issues such as the reasons for involvement in the play, the willingness to reuse the game in case new versions were released, etc. On average, it took two hours to interview each of three groups. A primary set of FGIs was conducted with three groups on the premise that there would be some differences caused by character race (Horde vs. Alliance) or by playable server (Normal vs. Combat). With respect to the manner of playing, we found that guild members shared information, felt a sense of belonging, and played computer games for quite a long time through the guild; however, they did not undergo these experiences when playing alone. Gamers who belonged to a specific guild helped other players without expecting compensation for that, freely shared information about the game, gave away items for free, and more generous with other members who made mistakes. The guild members were aware of the existence other members and experienced a sense of belonging through interactions with, and evaluations from, other players. It was clear that social support was shown within the guild and that it played an important role as a major research variable. Based on the results of the first FGIs, a second set of in-depth FGIs was carried out with a focus on the psychology of the individual within the guild and the social community of the guild. The second set of FGIs also focused on the guild's offline meetings. Gamers, over all, recognize the necessity of joining a community, not only off-line but also online world of the guild. They admit that the guild is important for them to easily and conveniently enjoy playing online computer games. The active behavior and positive attitudes of existing guild members can motivate new members of the guild to adapt themselves to the guild environment. They then adopt the same behaviors and attitudes of established guild members. In this manner, the new members of the guild strengthen the bonds with other gamers while feeling a sense of belonging, and developing social identity, thereby. It was discovered that the interaction among guild members and the social support encouraged new gamers to quickly develop a sense of social identity and increase their self-esteem. The guild seemed to play the role of socializing gamers. Sometimes, even in the real world, the guild members helped one another; therefore, the features of the guild also spilled over to the offline environment. We intend to use self-esteem, which was found through the second set of FGIs, as an important research variable. To collect data, an online survey was designed with a questionnaire to be completed by WoW gamers, who belong to a guild. The survey was registered on the best three domestic game-sites: 'WoW playforum,' 'WoW gamemeca,' and 'Wow invent.' The selected items to be measured in the questionnaire were decided based on prior research and data from FGIs. To verify the content of the questionnaire, we carried out a pilot test with the same participants to point out ambiguous questions as a way to ensure maximum accuracy of the survey result. A total of 244 responses were analyzed from the 250 completed questionnaires. The SEM analysis was used to test goodness-of-fit of the model. As a result, we found important results as follows: First, according to the statistics, social support had statistically significant impacts on character control, character identity, guild identity and self-esteem. Second, character control had significant effects on character identity, guild identity and self-esteem. Third, character identity shows its clear impact on self-esteem and game loyalty. Fourth, guild identity affected self-esteem, guild flow and game loyalty. Fifth, self-esteem had a positive influence on the guild flow. These days, the number of virtual community is rising along with its significance largely because of the nature of the online games. Accordingly, this study is designed to clarify the psychological relationship between gamers within the guild that has been generally established by gamers to play online games together. This study focuses on the relationships in which social support influences guild flow or game loyalty through character control, character identity, guild identity, and self-esteem, which are present within a guild in the MMORPG game environment. The study results are as follows. First, the effects of social support on character control, character identity, guild identity and self-esteem are proven to be statistically significant. It was found that character control improves character identity, guild identity and self-esteem. Among the seven variables, social support, which is derived from FGIs, plays an important role in this study. With the active support of other guild members, gamers can improve their ability to develop good characters and to control them. Second, character identity has a positive effect on self-esteem and game loyalty, while guild identity has a significant effect on self-esteem, guild flow and game loyalty. Self-esteem affects guild flow. It was found that the higher the character and guild identities become, the greater the self-esteem is established. Contrary to the findings of prior research, our study results indicate that the relationship between character identity and guild flow is not significant. Rather, it was found that character identity directly affects game players' loyalty. Even though the character identity had no direct effect on increasing guild flow, it has indirectly affected guild flow through self-esteem. The significant relationship between self-esteem and guild flow indicates that gamers achieve flow, i.e., a feeling of pleasure and excitement through social support. Several important implications of this study should be noted. First, both qualitative and quantitative methods were used to conduct this study. Through FGIs, it was observed that both social support and self-esteem are important variables. Second, because guilds had been rarely studied, this research is expected to play an important role in the online community. Third, according to the result, six hypotheses (H1, H5, H6, H7, H8, and H11) setup based on FGIs, were statistically significant; thus, we can suggest the corresponding relationships among the variables as a guideline for follow-up research. Our research is significant as it has following implications: first, the social support of the guild members is important when establishing character control, character identity, guildidentity and self-esteem. It is also a major variable that affects guild flow and game loyalty. Second, character control when improved by social support shows notable influence on the development of character identity, guild identity and self-esteem. Third, character identity and guild identity are major factors to help establish gamers' own self-esteem. Fourth, character identity affects guild flow through self-esteem and game loyalty. The gamers usually express themselves through characters; the higher character identity is, the more loyalty a gamer has. Fifth, guild identity, established within the guild, has clear effects on self-esteem, guild flow and game loyalty. Sixth, qualitative and quantitative methods are employed to conduct this study. Based on the results of focus group interviews and SEM analysis, we find that the social support by guild members and psychological factors are significant in strengthening the flow of guild and loyalty to the game. As such, game developers should provide some extra functions for guild community, through which gamers can play online games in collaboration with one another. Also, we suggest that positive self-esteem which is built up through social support can help gamers achieve higher level of flow and satisfaction, which will consequently contribute to minimizing the possibility for the players to develop negative attitude toward the guild they belong to.

• Korea Journal of Hospital Management
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• v.9 no.1
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• pp.66-94
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• 2004

The objective of this study is to examine how to maximize the efficiency of hospital management by minimizing the unit cost of hospital operation. For this purpose, this paper proposes to develop a model of the profit maximization based on the cost minimization dictum using the statistical tools of arriving at the maximum likelihood values. The preliminary survey data are collected from the annual statistics and their analyses published by Korea Health Industry Development Institute and Korean Hospital Association. The maximum likelihood value statistical analyses are conducted from the information on the cost (function) of each of 36 hospitals selected by the random stratified sampling method according to the size and location (urban or rural) of hospitals. We believe that, although the size of sample is relatively small, because of the sampling method used and the high response rate, the power of estimation of the results of the statistical analyses of the sample hospitals is acceptable. The conceptual framework of analyses is adopted from the various models of the determinants of hospital costs used by the previous studies. According to this framework, the study postulates that the unit cost of hospital operation is determined by the size, scope of service, technology (production function) as measured by capacity utilization, labor capital ratio and labor input-mix variables, and by exogeneous variables. The variables to represent the above cost determinants are selected by using the step-wise regression so that only the statistically significant variables may be utilized in analyzing how these variables impact on the hospital unit cost. The results of the analyses show that the models of hospital cost determinants adopted are well chosen. The various models analyzed have the (goodness of fit) overall determination (R2) which all turned out to be significant, regardless of the variables put in to represent the cost determinants. Specifically, the size and scope of service, no matter how it is measured, i. e., number of admissions per bed, number of ambulatory visits per bed, adjusted inpatient days and adjusted outpatients, have overall effects of reducing the hospital unit costs as measured by the cost per admission, per inpatient day, or office visit implying the existence of the economy of scale in the hospital operation. Thirdly, the technology used in operating a hospital has turned out to have its ramifications on the hospital unit cost similar to those postulated in the static theory of the firm. For example, the capacity utilization as represented by the inpatient days per employee tuned out to have statistically significant negative impacts on the unit cost of hospital operation, while payroll expenses per inpatient cost has a positive effect. The input-mix of hospital operation, as represented by the ratio of the number of doctor, nurse or medical staff per general employee, supports the known thesis that the specialized manpower costs more than the general employees. The labor/capital ratio as represented by the employees per 100 beds is shown to have a positive effect on the cost as expected. As for the exogeneous variable's impacts on the cost, when this variable is represented by the percent of urban 100 population at the location where the hospital is located, the regression analysis shows that the hospitals located in the urban area have a higher cost than those in the rural area. Finally, the case study of the sample hospitals offers a specific information to hospital administrators about how they share in terms of the cost they are incurring in comparison to other hospitals. For example, if his/her hospital is of small size and located in a city, he/she can compare the various costs of his/her hospital operation with those of other similar hospitals. Therefore, he/she may be able to find the reasons why the cost of his/her hospital operation has a higher or lower cost than other similar hospitals in what factors of the hospital cost determinants.

• Journal of Distribution Research
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• v.15 no.1
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• pp.25-47
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• 2010

CS is one of the major concerns of managers in the world because it is well known to be a key medium construct for firms' superior outcome. One of the major agents for CS management is retailers. Firms try to manage not only employees but also retailers to promote CS behaviors. And so diverse incentives are used to promote their CS behaviors under diverse channel setting such as multi-channel. However in spite of the rising needs there has been scarce studies on the optimal incentive structure for a manufacturer to offer competing retailers at the multi-channel. In this paper, we try to find better way for a manufacturer to promote the competing retailers' CS behaviors. We investigated how to promote the retailers' CS behavior via game-theoretic modeling. Especially, we focus on the possible incentive, CS bonus type reward introduced in the studies of Hauser, Simester, and Wernerfelt(1994) and Chu and Desai(1995). We build up a multi stage complete information game and derive a subgame perfect equilibrium using backward induction. Stages of the game are as following. (Stage 1) Manufacturer sets wholesale price(w) and CS bonus($\eta$). (Stage 2) Both retailers in competition set CS effort level($e_i$) and retail price($p_i$) simultaneously. (Stage 3) Consumers make purchasing decisions based on the manufacturer's initial reputation and retailers' CS efforts.

• Economic and Environmental Geology
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• v.51 no.4
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• pp.381-392
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• 2018

This study examines strategies and implementation plans for commercializing $CO_2$ capture and storage, which is an effective method to achieve the national goal of reducing greenhouse gas. In order to secure cost-efficient business model of $CO_2$ capture and storage, we propose four key strategies, including 1) urgent need to select a large-scale storage site and to estimate realistic storage capacity, 2) minimization of source-to-sink distance, 3) cost-effectiveness through technology innovation, and 4) policy implementation to secure public interest and to encourage private sector participation. Based on these strategies, the implementation plans must be designed for enabling $CO_2$ capture and storage to be commercialized until 2030. It is desirable to make those plans in which large-scale demonstration and subsequent commercial projects share a single storage site. In addition, the plans must be able to deliver step-wised targets and assessment processes to decide if the project will move to the next stage or not. The main target of stage 1 (2019 ~ 2021) is that the large-scale storage site will be selected and post-combustion capture technology will be upgraded and commercialized. The site selection, which is prerequisite to forward to the next stage, will be made through exploratory drilling and investigation for candidate sites. The commercial-scale applicability of the capture technology must be ensured at this stage. Stage 2 (2022 ~ 2025) aims design and construction of facility and infrastructure for successful large-scale demonstration (million tons of $CO_2$ per year), i.e., large-scale $CO_2$ capture, transportation, and storage. Based on the achievement of the demonstration project and the maturity of carbon market at the end of stage 2, it is necessary to decide whether to enter commercialization of $CO_2$ capture and storage. If the commercialization project is decided, it will be possible to capture and storage 4 million tons of $CO_2$ per year by the private sector in stage 3 (2026 ~ 2030). The existing facility, infrastructure, and capture plant will be upgraded and supplemented, which allows the commercialization project to be cost-effective.

• Journal of Service Research and Studies
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• v.5 no.1
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• pp.91-103
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• 2015

We examine the information transmission between the KT Spot and the KT Futures Index, the SK Telecom Spot and the SK Telecom Futures Index, based on the returns data offered by the Korea Exchange. The data includes daily return data from 1 January 2012 to 31 December 2014. Utilizing a dynamic analytical tool-the VAR model, Granger Causality test, Impulse Response Function and Variance Decomposition have been implemented. The results of the analysis are as follows. Firstly, results of Granger Causality test suggests the existence of mutual causality the KT Futures Index and the SK Telecom Futures Index precede and have explanatory power the KT Spot and the SK Telecom Spot However the results also identified a greater causality and explanatory power of the KT Spot and the SK Telecom Spot over the KT Futures Index and the SK Telecom Futures Index. Secondly, the results of impulse response function suggest that the KT Futures Index show immediate response to the KT Spot and are influenced by till time 4. From time 2, the impact gradually disappears. Also the SKT Futures Index show immediate response to the SKT Spot and are influenced by till time 4. From time 2, the impact gradually disappears. Lastly, the variance decomposition analysis shows that the changes of return of the KT Spot and SKT Spot are dependent on those of the KT Futures Index and the SK Telecom Futures Index. This implies that returns on the KT Spot and SKT Spot have a significant influence over returns on the KT Futures Index and the SK Telecom Futures Index. It contributes to the understanding of market price formation function through analysis of detached the KT Spot and the KT Futures Index, the SK Telecom Spot and the SK Telecom Futures Index.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.177-190
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• 2021

Due to the development of the fourth industrial revolution technology, efforts are being made to improve areas that humans cannot handle by utilizing artificial intelligence techniques such as machine learning. Although on-demand production companies also want to reduce corporate risks such as delays in delivery by predicting total production time for orders, they are having difficulty predicting this because the total production time is all different for each order. The Theory of Constraints (TOC) theory was developed to find the least efficient areas to increase order throughput and reduce order total cost, but failed to provide a forecast of total production time. Order production varies from order to order due to various customer needs, so the total production time of individual orders can be measured postmortem, but it is difficult to predict in advance. The total measured production time of existing orders is also different, which has limitations that cannot be used as standard time. As a result, experienced managers rely on persimmons rather than on the use of the system, while inexperienced managers use simple management indicators (e.g., 60 days total production time for raw materials, 90 days total production time for steel plates, etc.). Too fast work instructions based on imperfections or indicators cause congestion, which leads to productivity degradation, and too late leads to increased production costs or failure to meet delivery dates due to emergency processing. Failure to meet the deadline will result in compensation for delayed compensation or adversely affect business and collection sectors. In this study, to address these problems, an entity that operates an order production system seeks to find a machine learning model that estimates the total production time of new orders. It uses orders, production, and process performance for materials used for machine learning. We compared and analyzed OLS, GLM Gamma, Extra Trees, and Random Forest algorithms as the best algorithms for estimating total production time and present the results.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.7
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• pp.802-811
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• 2023

Marine spatial planning (MSP) is a crucial element for rational allocation and sustainable use of marine areas. Particularly, Fishing Activity Protected Areas constitute essential zones accounting for 45.6% designated for sustainable fishing activities. However, the current assessment of these zones does not adequately consider future demands and potential values, necessitating appropriate evaluation methods and predictive tools for long-term planning. In this study, we selected key fish species (Scomber japonicus, Trichiurus lepturus, Engraulis japonicus, and Larimichthys polyactis) within the Fishing Activity Protected Area to predict their distribution and compare it with the current designated zones for evaluating the ability of the prediction tool. Employing the Intergovernmental Panel on Climate Change (IPCC) 6th Assessment Report scenarios (SSP1-2.6 and SSP5-8.5), we used species distribution models (such as MaxEnt) to assess the movement and distribution changes of these species owing to future variations. The results indicated a 30-50% increase in the distribution area of S. japonicus, T. lepturus, and L. polyactis, whereas the distribution area of E. japonicus decreased by approximately 6-11%. Based on these results, a species richness map for the four key species was created. Within the marine spatial planning boundaries, the overlap between areas rated "high" in species richness and the Fishing Activity Protected Area was approximately 15%, increasing to 21% under the RCP 2.6 scenario and 34% under the RCP 8.5 scenario. These findings can serve as scientific evidence for future evaluations of use zones or changes in reserve areas. The current and predicted distributions of species owing to climate change can address the limitations of current use zone evaluations and contribute to the development of plans for sustainable and beneficial use of marine resources.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.19-41
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• 2016

Recently, the proliferation of mobile devices such as smartphones and tablet personal computers and the development of information communication technologies (ICT) have led to a big trend of a shift from single-channel shopping to multi-channel shopping. With the emergence of a "smart" group of consumers who want to shop in more reasonable and convenient ways, the boundaries apparently dividing online and offline shopping have collapsed and blurred more than ever before. Thus, there is now fierce competition between online and offline channels. Ever since the emergence of online shopping, a major type of multi-channel shopping has been "showrooming," where consumers visit offline stores to examine products before buying them online. However, because of the growing use of smart devices and the counterattack of offline retailers represented by omni-channel marketing strategies, one of the latest huge trends of shopping is "webrooming," where consumers visit online stores to examine products before buying them offline. This has become a threat to online retailers. In this situation, although it is very important to examine the influencing factors for switching from online shopping to webrooming, most prior studies have mainly focused on a single- or multi-channel shopping pattern. Therefore, this study thoroughly investigated the influencing factors on customers switching from online shopping to webrooming in terms of both the "search" and "purchase" processes through the application of a push-pull-mooring (PPM) framework. In order to test the research model, 280 individual samples were gathered from undergraduate and graduate students who had actual experience with webrooming. The results of the structural equation model (SEM) test revealed that the "pull" effect is strongest on the webrooming intention rather than the "push" or "mooring" effects. This proves a significant relationship between "attractiveness of webrooming" and "webrooming intention." In addition, the results showed that both the "perceived risk of online search" and "perceived risk of online purchase" significantly affect "distrust of online shopping." Similarly, both "perceived benefit of multi-channel search" and "perceived benefit of offline purchase" were found to have significant effects on "attractiveness of webrooming" were also found. Furthermore, the results indicated that "online purchase habit" is the only influencing factor that leads to "online shopping lock-in." The theoretical implications of the study are as follows. First, by examining the multi-channel shopping phenomenon from the perspective of "shopping switching" from online shopping to webrooming, this study complements the limits of the "channel switching" perspective, represented by multi-channel freeriding studies that merely focused on customers' channel switching behaviors from one to another. While extant studies with a channel switching perspective have focused on only one type of multi-channel shopping, where consumers just move from one particular channel to different channels, a study with a shopping switching perspective has the advantage of comprehensively investigating how consumers choose and navigate among diverse types of single- or multi-channel shopping alternatives. In this study, only limited shopping switching behavior from online shopping to webrooming was examined; however, the results should explain various phenomena in a more comprehensive manner from the perspective of shopping switching. Second, this study extends the scope of application of the push-pull-mooring framework, which is quite commonly used in marketing research to explain consumers' product switching behaviors. Through the application of this framework, it is hoped that more diverse shopping switching behaviors can be examined in future research. This study can serve a stepping stone for future studies. One of the most important practical implications of the study is that it may help single- and multi-channel retailers develop more specific customer strategies by revealing the influencing factors of webrooming intention from online shopping. For example, online single-channel retailers can ease the distrust of online shopping to prevent consumers from churning by reducing the perceived risk in terms of online search and purchase. On the other hand, offline retailers can develop specific strategies to increase the attractiveness of webrooming by letting customers perceive the benefits of multi-channel search or offline purchase. Although this study focused only on customers switching from online shopping to webrooming, the results can be expanded to various types of shopping switching behaviors embedded in single- and multi-channel shopping environments, such as showrooming and mobile shopping.

• Journal of Global Scholars of Marketing Science
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• v.20 no.1
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• pp.89-97
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• 2010

This study researches the effects of common features on a no-choice option with respect to regulatory focus theory. The primary interest is in three factors and their interrelationship: common features, no-choice option, and regulatory focus. Prior studies have compiled vast body of research in these areas. First, the "common features effect" has been observed bymany noted marketing researchers. Tversky (1972) proposed the seminal theory, the EBA model: elimination by aspect. According to this theory, consumers are prone to focus only on unique features during comparison processing, thereby dismissing any common features as redundant information. Recently, however, more provocative ideas have attacked the EBA model by asserting that common features really do affect consumer judgment. Chernev (1997) first reported that adding common features mitigates the choice gap because of the increasing perception of similarity among alternatives. Later, however, Chernev (2001) published a critically developed study against his prior perspective with the proposition that common features may be a cognitive load to consumers, and thus consumers are possible that they are prone to prefer the heuristic processing to the systematic processing. This tends to bring one question to the forefront: Do "common features" affect consumer choice? If so, what are the concrete effects? This study tries to answer the question with respect to the "no-choice" option and regulatory focus. Second, some researchers hold that the no-choice option is another best alternative of consumers, who are likely to avoid having to choose in the context of knotty trade-off settings or mental conflicts. Hope for the future also may increase the no-choice option in the context of optimism or the expectancy of a more satisfactory alternative appearing later. Other issues reported in this domain are time pressure, consumer confidence, and alternative numbers (Dhar and Nowlis 1999; Lin and Wu 2005; Zakay and Tsal 1993). This study casts the no-choice option in yet another perspective: the interactive effects between common features and regulatory focus. Third, "regulatory focus theory" is a very popular theme in recent marketing research. It suggests that consumers have two focal goals facing each other: promotion vs. prevention. A promotion focus deals with the concepts of hope, inspiration, achievement, or gain, whereas prevention focus involves duty, responsibility, safety, or loss-aversion. Thus, while consumers with a promotion focus tend to take risks for gain, the same does not hold true for a prevention focus. Regulatory focus theory predicts consumers' emotions, creativity, attitudes, memory, performance, and judgment, as documented in a vast field of marketing and psychology articles. The perspective of the current study in exploring consumer choice and common features is a somewhat creative viewpoint in the area of regulatory focus. These reviews inspire this study of the interaction possibility between regulatory focus and common features with a no-choice option. Specifically, adding common features rather than omitting them may increase the no-choice option ratio in the choice setting only to prevention-focused consumers, but vice versa to promotion-focused consumers. The reasoning is that when prevention-focused consumers come in contact with common features, they may perceive higher similarity among the alternatives. This conflict among similar options would increase the no-choice ratio. Promotion-focused consumers, however, are possible that they perceive common features as a cue of confirmation bias. And thus their confirmation processing would make their prior preference more robust, then the no-choice ratio may shrink. This logic is verified in two experiments. The first is a $2{\times}2$ between-subject design (whether common features or not X regulatory focus) using a digital cameras as the relevant stimulus-a product very familiar to young subjects. Specifically, the regulatory focus variable is median split through a measure of eleven items. Common features included zoom, weight, memory, and battery, whereas the other two attributes (pixel and price) were unique features. Results supported our hypothesis that adding common features enhanced the no-choice ratio only to prevention-focus consumers, not to those with a promotion focus. These results confirm our hypothesis - the interactive effects between a regulatory focus and the common features. Prior research had suggested that including common features had a effect on consumer choice, but this study shows that common features affect choice by consumer segmentation. The second experiment was used to replicate the results of the first experiment. This experimental study is equal to the prior except only two - priming manipulation and another stimulus. For the promotion focus condition, subjects had to write an essay using words such as profit, inspiration, pleasure, achievement, development, hedonic, change, pursuit, etc. For prevention, however, they had to use the words persistence, safety, protection, aversion, loss, responsibility, stability etc. The room for rent had common features (sunshine, facility, ventilation) and unique features (distance time and building state). These attributes implied various levels and valence for replication of the prior experiment. Our hypothesis was supported repeatedly in the results, and the interaction effects were significant between regulatory focus and common features. Thus, these studies showed the dual effects of common features on consumer choice for a no-choice option. Adding common features may enhance or mitigate no-choice, contradictory as it may sound. Under a prevention focus, adding common features is likely to enhance the no-choice ratio because of increasing mental conflict; under the promotion focus, it is prone to shrink the ratio perhaps because of a "confirmation bias." The research has practical and theoretical implications for marketers, who may need to consider common features carefully in a practical display context according to consumer segmentation (i.e., promotion vs. prevention focus.) Theoretically, the results suggest some meaningful moderator variable between common features and no-choice in that the effect on no-choice option is partly dependent on a regulatory focus. This variable corresponds not only to a chronic perspective but also a situational perspective in our hypothesis domain. Finally, in light of some shortcomings in the research, such as overlooked attribute importance, low ratio of no-choice, or the external validity issue, we hope it influences future studies to explore the little-known world of the "no-choice option."

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.29-44
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• 2017

In Internet commerce, consumers are heavily influenced by product reviews written by other users who have already purchased the product. However, as the product reviews accumulate, it takes a lot of time and effort for consumers to individually check the massive number of product reviews. Moreover, product reviews that are written carelessly actually inconvenience consumers. Thus many online vendors provide mechanisms to identify reviews that customers perceive as most helpful (Cao et al. 2011; Mudambi and Schuff 2010). For example, some online retailers, such as Amazon.com and TripAdvisor, allow users to rate the helpfulness of each review, and use this feedback information to rank and re-order them. However, many reviews have only a few feedbacks or no feedback at all, thus making it hard to identify their helpfulness. Also, it takes time to accumulate feedbacks, thus the newly authored reviews do not have enough ones. For example, only 20% of the reviews in Amazon Review Dataset (Mcauley and Leskovec, 2013) have more than 5 reviews (Yan et al, 2014). The purpose of this study is to analyze the factors affecting the usefulness of online product reviews and to derive a forecasting model that selectively provides product reviews that can be helpful to consumers. In order to do this, we extracted the various linguistic, psychological, and perceptual elements included in product reviews by using text-mining techniques and identifying the determinants among these elements that affect the usability of product reviews. In particular, considering that the characteristics of the product reviews and determinants of usability for apparel products (which are experiential products) and electronic products (which are search goods) can differ, the characteristics of the product reviews were compared within each product group and the determinants were established for each. This study used 7,498 apparel product reviews and 106,962 electronic product reviews from Amazon.com. In order to understand a review text, we first extract linguistic and psychological characteristics from review texts such as a word count, the level of emotional tone and analytical thinking embedded in review text using widely adopted text analysis software LIWC (Linguistic Inquiry and Word Count). After then, we explore the descriptive statistics of review text for each category and statistically compare their differences using t-test. Lastly, we regression analysis using the data mining software RapidMiner to find out determinant factors. As a result of comparing and analyzing product review characteristics of electronic products and apparel products, it was found that reviewers used more words as well as longer sentences when writing product reviews for electronic products. As for the content characteristics of the product reviews, it was found that these reviews included many analytic words, carried more clout, and related to the cognitive processes (CogProc) more so than the apparel product reviews, in addition to including many words expressing negative emotions (NegEmo). On the other hand, the apparel product reviews included more personal, authentic, positive emotions (PosEmo) and perceptual processes (Percept) compared to the electronic product reviews. Next, we analyzed the determinants toward the usefulness of the product reviews between the two product groups. As a result, it was found that product reviews with high product ratings from reviewers in both product groups that were perceived as being useful contained a larger number of total words, many expressions involving perceptual processes, and fewer negative emotions. In addition, apparel product reviews with a large number of comparative expressions, a low expertise index, and concise content with fewer words in each sentence were perceived to be useful. In the case of electronic product reviews, those that were analytical with a high expertise index, along with containing many authentic expressions, cognitive processes, and positive emotions (PosEmo) were perceived to be useful. These findings are expected to help consumers effectively identify useful product reviews in the future.