• Title/Summary/Keyword: robustness improvement

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The Effect of K-IFRS Adoption on Goodwill Impariment Timeliness (K-IFRS 도입이 영업권손상차손 인식의 적시성에 미친 영향)

  • Baek, Jeong-Han;Choi, Jong-Seo
    • Management & Information Systems Review
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    • v.35 no.1
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    • pp.51-68
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    • 2016
  • In this paper, we aim to analyze the effect of accounting policy change subsequent to the adoption of K-IFRS in Korea, whereby the firms are required to recognize impairment losses on goodwill on a periodic basis rather than to amortize over a specific period. As a principle-based accounting standard, the K-IFRS expands the scope of fair value measurement with a view to enhance the relevance and timeliness of accounting information. In the same vein, intangibles with indefinite useful life, of which goodwill is an example, are subject to regulatory impairment tests at least once a year. Related literature on the impact of mandatory change in goodwill policy document that impairment recognition is more likely to be practiced opportunistically, mainly because managers have a greater discretion to conduct the tests under K-IFRS. However, existing literature examined the frequency and/or magnitude of the goodwill impairment before versus after the K-IFRS adoption, failing to notice the impairment symptoms at individual firm level. Borrowing the definition of impairment symptoms suggested by Ramanna and Watts(2012), this study performs a series of tests to determine whether the goodwill impairment recognition achieves the goal of communicating timelier information under the K-IFRS regime. Using 947 firm-year observations from domestic companies listed in KRX and KOSDAQ markets from 2008 to 2011, we document overall delays in recognizing impairment losses on goodwill after the adoption of K-IFRS relative to prior period, based on logistic and OLS regression analyses. The results are qualitatively similar in robustness tests, which use alternative proxy for goodwill impairment symptom. Afore-mentioned results indicate that managers are likely to take advantage of the increased discretion to recognize the impairment losses on goodwill rather than to provide timelier information on impairment, inconsistent with the goal of regulatory authority, which is in line with the improvement of timeliness and relevance of accounting information in conjunction with the full implementation of K-IFRS. This study contributes to the extant literature on goodwill impairment from a methodological viewpoint. We believe that the method employed in this paper potentially diminishes the bias inherent in researches relying on ex post impairment recognition, by conducting tests based on ex ante impairment symptoms, which allows direct examination of the timeliness changes between before and after K-IFRS adoption.

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A Mobile Landmarks Guide : Outdoor Augmented Reality based on LOD and Contextual Device (모바일 랜드마크 가이드 : LOD와 문맥적 장치 기반의 실외 증강현실)

  • Zhao, Bi-Cheng;Rosli, Ahmad Nurzid;Jang, Chol-Hee;Lee, Kee-Sung;Jo, Geun-Sik
    • Journal of Intelligence and Information Systems
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    • v.18 no.1
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    • pp.1-21
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    • 2012
  • In recent years, mobile phone has experienced an extremely fast evolution. It is equipped with high-quality color displays, high resolution cameras, and real-time accelerated 3D graphics. In addition, some other features are includes GPS sensor and Digital Compass, etc. This evolution advent significantly helps the application developers to use the power of smart-phones, to create a rich environment that offers a wide range of services and exciting possibilities. To date mobile AR in outdoor research there are many popular location-based AR services, such Layar and Wikitude. These systems have big limitation the AR contents hardly overlaid on the real target. Another research is context-based AR services using image recognition and tracking. The AR contents are precisely overlaid on the real target. But the real-time performance is restricted by the retrieval time and hardly implement in large scale area. In our work, we exploit to combine advantages of location-based AR with context-based AR. The system can easily find out surrounding landmarks first and then do the recognition and tracking with them. The proposed system mainly consists of two major parts-landmark browsing module and annotation module. In landmark browsing module, user can view an augmented virtual information (information media), such as text, picture and video on their smart-phone viewfinder, when they pointing out their smart-phone to a certain building or landmark. For this, landmark recognition technique is applied in this work. SURF point-based features are used in the matching process due to their robustness. To ensure the image retrieval and matching processes is fast enough for real time tracking, we exploit the contextual device (GPS and digital compass) information. This is necessary to select the nearest and pointed orientation landmarks from the database. The queried image is only matched with this selected data. Therefore, the speed for matching will be significantly increased. Secondly is the annotation module. Instead of viewing only the augmented information media, user can create virtual annotation based on linked data. Having to know a full knowledge about the landmark, are not necessary required. They can simply look for the appropriate topic by searching it with a keyword in linked data. With this, it helps the system to find out target URI in order to generate correct AR contents. On the other hand, in order to recognize target landmarks, images of selected building or landmark are captured from different angle and distance. This procedure looks like a similar processing of building a connection between the real building and the virtual information existed in the Linked Open Data. In our experiments, search range in the database is reduced by clustering images into groups according to their coordinates. A Grid-base clustering method and user location information are used to restrict the retrieval range. Comparing the existed research using cluster and GPS information the retrieval time is around 70~80ms. Experiment results show our approach the retrieval time reduces to around 18~20ms in average. Therefore the totally processing time is reduced from 490~540ms to 438~480ms. The performance improvement will be more obvious when the database growing. It demonstrates the proposed system is efficient and robust in many cases.