[논문]Knowledge Management, Business Intelligence, and Business Analytics

Choi, Byounggu; Han, Kunsoo; Cheng, Zhuo (June)

doi:10.14329/apjis.2015.25.3.540

문제 정의

This special issue aims to bring together scholars who investigate organizational performance and sustainable competitive advantage in the domains of knowledge management and business analytics/ intelligence. With the aims, four papers have been selected for publication.
This study contributes to the service orientation literature by introducing service orientation to the financial industry, and measuring and testing team-level service performance. This study also highlights the importance of service-oriented operational practice for improving service performance in the financial field.
The analysis results show that the mean trajectory of a film’s box-office performance is larger when the film is domestic, is released in the summer, enjoyed positive online reviews after its release, or had significant attendance in the first week after its release. This study contributes to expand our knowledge on the impact of online WOM on success of movies measured by cumulative audience size. The study explicitly and systematically models the shapes of the cumulative audience sizes’ trajectories over time through inclusion of movie-level covariates, leading to improved flexibility to explain the various types of the growth curve.
Furthermore, the results show that directed acyclic graph is the most effective and efficient approach in the four multi-class approaches. This study contributes to the literature by showing the applicability of new techniques such as SVM+ and SVM+MTL and the outperformance of SVM+MTL over conventional techniques, thereby enriching our knowledge about the techniques for tackling multi-class problems such as corporate credit rating prediction. In addition, the proposed credit rating approach of this study shows greater explanatory powers by transforming a binary bankruptcy prediction problem into multi-class credit rating analysis.
Service orientation significantly affects the service performance perception of fund managers. This study contributes to the service orientation literature by introducing service orientation to the financial industry, and measuring and testing team-level service performance. This study also highlights the importance of service-oriented operational practice for improving service performance in the financial field.

제안 방법

The fourth paper of this special issue, titled “Capability, Service Orientation, and Performance in the Investment Management Industry” by Kang Duck Lee, Chang Ho Jung, Yong Jin Kim, examines how service orientation conceptualized as a type of dynamic capability affects firm performance. For this purpose, they proposed a research model including job competency, risk management capability, operational capability, service orientation, and service performance, and tested the model using data from 86 teams in 37 investment management companies. The analysis results reveal that job competency positively affects both risk management capability and operational capability, which in turn influence service orientation.
Furthermore, they attempts to identify the most powerful technique to predict corporate credit rating by comparing SVM, SVM+ and SVM+MTL using empirical data from Korea bond rating market. For this purposes, this study adopted four multi-class approaches (i.e., one-against-all, one-against-one, directed acyclic graph, and error correcting output codes) that have been widely used to solve multi-class SVM problems. The analysis results show that SVM+MTL outperformed both conventional SVM and novel SVM+ in the prediction of corporate credit rating.
From a theoretical perspective, this study suggests that the effect of rank may not follow a smooth curve such as linear or quadratic, which is contrary to the extant literature where the effect of rank is modeled as linear or quadratic. From a managerial perspective, this study urges managers in the mobile application market to identify and pay their attention to the critical points where they could benefit from the rank effect in the extended application download.
To improve predictability of movie performance, this study fitted the mean trajectory of the cumulative audience size as a cubic function of time, and allowed the intercept and slope to vary movie-to-movie. Furthermore, the study fitted the linear slope with a function of online word-of-mouth predictors to help determine the shape of the trajectories. The analysis results show that the mean trajectory of a film’s box-office performance is larger when the film is domestic, is released in the summer, enjoyed positive online reviews after its release, or had significant attendance in the first week after its release.
In the second paper, titled “Forecasting the Box Office Performance of Movies Using Hierarchical Linear Models” by Jongmin Park, Yeojin Chung, and Yunho Cho, the authors attempts to identify dynamic structure of a film’s successes across different time points.
The study explicitly and systematically models the shapes of the cumulative audience sizes’ trajectories over time through inclusion of movie-level covariates, leading to improved flexibility to explain the various types of the growth curve.
The third paper, titled “Multi-Class SVM+MTL for the Prediction of Corporate Credit Rating with Structured Data” by Gang Ren, Taeho Hong, and YoungKi Park, attempts to show applicability of new techniques such as support vector machines+ (SVM+) and SVM+MTL (multi-task learning) to a multi-class classification problem in the corporate credit rating.
For this purpose, they propose a method to predict the daily performance trajectory of running movies using hierarchical linear model. To improve predictability of movie performance, this study fitted the mean trajectory of the cumulative audience size as a cubic function of time, and allowed the intercept and slope to vary movie-to-movie. Furthermore, the study fitted the linear slope with a function of online word-of-mouth predictors to help determine the shape of the trajectories.

성능/효과

For this purpose, they proposed a research model including job competency, risk management capability, operational capability, service orientation, and service performance, and tested the model using data from 86 teams in 37 investment management companies. The analysis results reveal that job competency positively affects both risk management capability and operational capability, which in turn influence service orientation. Furthermore, the result indicates that risk management capability affects service performance through service orientation while operational capability influences perceived service performance directly.
, one-against-all, one-against-one, directed acyclic graph, and error correcting output codes) that have been widely used to solve multi-class SVM problems. The analysis results show that SVM+MTL outperformed both conventional SVM and novel SVM+ in the prediction of corporate credit rating. Furthermore, the results show that directed acyclic graph is the most effective and efficient approach in the four multi-class approaches.
The analysis results show that the mean trajectory of a film’s box-office performance is larger when the film is domestic, is released in the summer, enjoyed positive online reviews after its release, or had significant attendance in the first week after its release.

후속연구

This special issue contributes to expanding our understanding of knowledge management and business analytics/intelligence. In addition, we hope more efforts will made to investigate the integration between knowledge management and business analytics/intelligence because such integration is essential to improving the effectiveness of decision making and organizational performance.

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