• Asia Marketing Journal
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• v.16 no.1
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• pp.35-69
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• 2014

The impact of competition on pricing has been studied in the context of counterfactual merger analyses where expected optimal prices in a hypothetical monopoly are compared with observed prices in an oligopolistic market. Such analyses would typically assume static decision making by consumers and firms and thus have been applied mostly to data obtained from consumer packed goods such as cereal and soft drinks. However such static modeling approach is not suitable when decision makers are forward looking. When it comes to the markets for durable products with indirect network effects, consumer purchase decisions and firm pricing decisions are inherently dynamic as they take into account future states when making purchase and pricing decisions. Researchers need to take into account the dynamic aspects of decision making both in the consumer side and in the supplier side for such markets. Firms in a two-sided market typically subsidize one side of the market to exploit the indirect network effect. Such pricing behaviors would be more prevalent in competitive markets where firms would try to win over the battle for standard. While such qualitative expectation on the relationship between pricing behaviors and competitive structures could be easily formed, little empirical studies have measured the extent to which the distinct pricing structure in two-sided markets depends on the competitive structure of the market. This paper develops an empirical model to measure the impact of competition on optimal pricing of durable products under indirect network effects. In order to measure the impact of exogenously determined competition among firms on pricing, we compare the equilibrium prices in the observed oligopoly market to those in a hypothetical monopoly market. In computing the equilibrium prices, we account for the forward looking behaviors of consumers and supplier. We first estimate a demand function that accounts for consumers' forward-looking behaviors and indirect network effects. And then, for the supply side, the pricing equation is obtained as an outcome of the Markov Perfect Nash Equilibrium in pricing. In doing so, we utilize numerical dynamic programming techniques. We apply our model to a data set obtained from the U.S. video game console market. The video game console market is considered a prototypical case of two-sided markets in which the platform typically subsidizes one side of market to expand the installed base anticipating larger revenues in the other side of market resulting from the expanded installed base. The data consist of monthly observations of price, hardware unit sales and the number of compatible software titles for Sony PlayStation and Nintendo 64 from September 1996 to August 2002. Sony PlayStation was released to the market a year before Nintendo 64 was launched. We compute the expected equilibrium price path for Nintendo 64 and Playstation for both oligopoly and for monopoly. Our analysis reveals that the price level differs significantly between two competition structures. The merged monopoly is expected to set prices higher by 14.8% for Sony PlayStation and 21.8% for Nintendo 64 on average than the independent firms in an oligopoly would do. And such removal of competition would result in a reduction in consumer value by 43.1%. Higher prices are expected for the hypothetical monopoly because the merged firm does not need to engage in the battle for industry standard. This result is attributed to the distinct property of a two-sided market that competing firms tend to set low prices particularly at the initial period to attract consumers at the introductory stage and to reinforce their own networks and eventually finally to dominate the market.

• Asia Marketing Journal
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• v.10 no.2
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• pp.31-69
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• 2008

The purpose of this study is to identify the organizational characteristics that enhance CRM performances of a company. Based on a review of diverse definitions of CRM performance, this study examines the relationships among CRM performance measures and organizational characteristics. A questionnaire survey of 123 CRM managers of Korean companies was conducted to test the proposed research model, and a series of structural equation modeling identified the strong effects of organizational characteristics on CRM performance. It was found that top management commitment to CRM and a firm's strategic readiness lead to high levels of CRM investment, which, in turn, enhance directly task-related performance and indirectly customer-related performance. This study also confirmed that customer orientation is significantly related to task-related CRM performance and that the variables of CRM commitment and organizational culture may enhance customerrelated performance indirectly through their effects on the task-related performance. However, organizational members' resistance to change was found to have no effects on CRM performance. Overall our research broadly supports the role of organizational characteristics revealed in the CRM literature.

• Asia Marketing Journal
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• v.8 no.1
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• pp.105-132
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• 2006

The major purpose of this study is to investigate the impact of environmental uncertainties and logistics resources capabilities mediated by relational norms and logistics services on logistics performance in the industrial products. The 272 data were collected from the key informants who were working at the logistics-related departments in the H Heavy Industries & Construction and HSD Engine. The following results were verified using structural equation modeling. First, environmental uncertainties such as dynamism and heterogeneity unexpectedly had insignificant effects on relational norms such as information exchange and flexibility and logistics services such as product availability and on-time delivery. Second, logistics resource capabilities showed unique effects based upon its component's characteristics. For example, Logistics Information Systems did not have direct impact on logistics services but had indirect effect on logistics services via relational norms. On the other hand, logistics resources such as logistics specific assets and transportation service competencies had direct impact on logistics services but not on relational norms. Third, relational norms between transaction partners significantly affected logistics services but had insignificant effects on logistics performance such as logistics costs reduction and delivery qualities. Fourth, consistent with several studies, excellent logistics services between industrial purchaser and suppliers based upon relational norms did have significant effect on logistics performance such as delivery consistency and delivery qualities. Finally, the empirical results in this study could be strategic logistics management guidelines based upon the theoretical relationships among the environmental uncertainties, logistics information systems, logistics resources, relational norms, logistics services, and logistics performance.

• Korean Journal of Culture and Social Issue
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• v.24 no.4
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• pp.519-539
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• 2018

This study investigates the impact of organizational socialization tactics on newcomers' organizational citizenship behaviors. We explains this relationship with the concept of perceived organizational support, which refers to the extent to which individuals perceive that the organization recognizes their contributions and takes care of their well-being. We expect that the more institutionalized the organization's socialization tactics are, the more organizational support individuals perceive, consequently increasing the performance of organizational citizenship behaviors. We performed a survey targeting 450 newcomers in domestic companies, and adopted 382 data for path analyses based on the structural equation modeling. As the result, in all the three dimensions of socialization tactics (content, context, social), the extent to which socialization tactics are institutionalized is positively related to the perception of organizational support. It also has the positive relationship with individuals' organizational citizenship behaviors, being fully mediated by the perceived organizational support. More specifically, context socialization tactics shows the highest level of impact both on the perceived organizational support and organizational citizenship behaviors, whereas social tactics has the lowest level of impact. These results imply that the range of effects the organizational socialization has on the newcomers' attitudes and behaviors should be more extended and detailed.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.309-323
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• 2023

As the role of online reviews has become increasingly crucial, numerous studies have been conducted to utilize helpful reviews. Helpful reviews, perceived by customers, have been verified in various research studies to be influenced by factors such as ratings, review length, review content, and so on. The determination of a review's helpfulness is generally based on the number of 'helpful' votes from consumers, with more 'helpful' votes considered to have a more significant impact on consumers' purchasing decisions. However, recently written reviews that have not been exposed to many customers may have relatively few 'helpful' votes and may lack 'helpful' votes altogether due to a lack of participation. Therefore, rather than relying on the number of 'helpful' votes to assess the helpfulness of reviews, we aim to classify them based on review content. In addition, the text of the review emerges as the most influential factor in review helpfulness. This study employs text mining techniques, including topic modeling and sentiment analysis, to analyze the diverse impacts of content and emotions embedded in the review text. In this study, we propose a review helpfulness prediction model based on review content, utilizing movie reviews from IMDb, a global movie information site. We construct a review helpfulness prediction model by using an explainable Graph Neural Network (GNN), while addressing the interpretability limitations of the machine learning model. The explainable graph neural network is expected to provide more reliable information about helpful or non-helpful reviews as it can identify connections between reviews.

• Journal of Industrial Convergence
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• v.21 no.12
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• pp.11-23
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• 2023

This study aims to investigate the relationship between service recovery justice, residual emotions, and customer behavior. It empirically verifies that low justice in service recovery affects residual emotions and, in turn, has an impact on customers' negative behaviors. Furthermore, this research distinguishes customer-brand relationship quality into emotional relationship quality and cognitive relationship quality and seeks to validate that the type of relationship quality may influence the extent to which the justice of recovery processes affects residual emotions. Data was collected through surveys, and hypotheses were tested using structural equation modeling. The research findings indicate that among the dimensions of service recovery justice, procedural justice and interactional justice significantly influence residual emotions. Moreover, residual emotions have a significant impact on both the intention to revisit and the intention to engage in negative word-of-mouth. In addition, the impact of distributive justice and procedural justice on residual emotions was found to be higher for cognitive relationship quality than emotional relationship quality, and the impact of interactional justice on residual emotions was found to be higher for emotional relationship quality than cognitive relationship quality.

• Information Systems Review
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• v.23 no.4
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• pp.45-67
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• 2021

As the transaction volume of the C2C second-hand market is growing, the number of frauds, which intend to earn unfair gains by sending products different from specified ones or not sending them to buyers, is also increasing. This study explores the model that can identify frauds in the online C2C second-hand market by examining the postings for transactions. For this goal, this study collected 145,536 field data from actual C2C second-hand market. Then, the model is built with the characteristics from postings such as the topic and the linguistic characteristics of the product description, and the characteristics of products, postings, sellers, and transactions. The constructed model is then trained by the machine learning algorithm XGBoost. The final analysis results show that fraudulent postings have less information, which is also less specific, fewer nouns and images, a higher ratio of the number and white space, and a shorter length than genuine postings do. Also, while the genuine postings are focused on the product information for nouns, delivery information for verbs, and actions for adjectives, the fraudulent postings did not show those characteristics. This study shows that the various features can be extracted from postings written in C2C second-hand transactions and be used to construct an effective model for frauds. The proposed model can be also considered and applied for the other C2C platforms. Overall, the model proposed in this study can be expected to have positive effects on suppressing and preventing fraudulent behavior in online C2C markets.

• Journal of Service Research and Studies
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• v.14 no.2
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• pp.158-177
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• 2024

This paper proposes and tests a theoretical model of the relational link between a novel form of customer-perceived fairness for a reward design (distributive peer justice climate) and C2C helping intention via community identification and online C2C interaction (friend-, neighboring customer-, audience-interaction) qualities in a collective consumption context (MMORPG). To test hypotheses, we amassed survey data within a collective consumption context (massively multiplayer online role-playing games, MMORPGs). We used structural equation modeling in analyzing the survey data. The results reveal that user-perceived distributive peer justice climate for a reward design enhances their C2C helping intention via community identification and C2C interactions in MMORPG contexts. Collective consumption-type service managers should focus on promoting the user-perceived distributive peer justice climate for their reward system to enhance users' present C2C co-creation experience (community identification, C2C interaction) and future C2C co-creation behavior (helping intention). By adopting an intra-unit level distributive justice concept (customer-perceived distributive peer justice climate) to a reward design in a collective consumption context (MMORPGs), this study informed collective consumption-type service managers of the importance of its management.

• The Korean Journal of Applied Statistics
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• v.37 no.2
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• pp.119-138
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• 2024

Text indicators are increasingly valuable in economic forecasting, but are often hindered by noise and high dimensionality. This study aims to explore post-processing techniques, specifically noise filtering and dimensionality reduction, to normalize text indicators and enhance their utility through empirical analysis. Predictive target variables for the empirical analysis include monthly leading index cyclical variations, BSI (business survey index) All industry sales performance, BSI All industry sales outlook, as well as quarterly real GDP SA (seasonally adjusted) growth rate and real GDP YoY (year-on-year) growth rate. This study explores the Hodrick and Prescott filter, which is widely used in econometrics for noise filtering, and employs sufficient dimension reduction, a nonparametric dimensionality reduction methodology, in conjunction with unstructured text data. The analysis results reveal that noise filtering of text indicators significantly improves predictive accuracy for both monthly and quarterly variables, particularly when the dataset is large. Moreover, this study demonstrated that applying dimensionality reduction further enhances predictive performance. These findings imply that post-processing techniques, such as noise filtering and dimensionality reduction, are crucial for enhancing the utility of text indicators and can contribute to improving the accuracy of economic forecasts.

• Information Systems Review
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• v.20 no.1
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• pp.41-59
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• 2018

This study analyzed the factors that affect acceptance of online direct marketing in agricultural companies. Empirical analysis was conducted using the research model based on the individual's technology acceptance model (TAM) and the information technology adoption models in organizations. These models have four dimensions: 1) technology characteristics, which include perceived usefulness and perceived ease of use of TAM 2) CEO characteristics, which including the innovativeness and IT capability of CEOs; 3) organizational readiness, which include financial, technological, and human resources capabilities and 4) environment and external pressure, which include government support and changes to the Internet environment. These concepts were empirically tested. A total of 209 valid data were collected through questionnaires and analyzed using confirmatory factor analysis and path analysis through the application of structural equation modeling. Results show that perceived usefulness, IT capability of CEOs, and changes to the Internet environment have significant effects on the adoption intention of online direct marketing. However, perceived ease of use, CEO innovativeness, government support, and the variables of organizational readiness dimension did not have significant effects on adoption intention. This study suggests practical implications for adoption of online direct marketing in agricultural companies.