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Lukas Purwoto
Fakultas Ekonomi Universitas Sanata Dharma Yogyakarta
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance

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MENGGABUNGKAN COMPETING VALUES FRAMEWORK DAN KETERBUKAAN INFORMASI PERUSAHAAN UNTUK MENILAI KEEFEKTIFAN ORGANISASIONAL Lukas Purwoto
Benefit: Jurnal Manajemen dan Bisnis Benefit : Kumpulan Makalah Diskusi Dosen FE UMS Volume 10 No 1 Juni 2006
Publisher : Program Studi Manajemen Fakultas Ekonomi dan Bisnis Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/benefit.v10i1.1227

Abstract

The issue of organizational effectiveness has been one of the most important research subjects sincethe early development of organizational theory. One model widely known in the study of organizationaleffectiveness is competing values framework. Besides that, it is also known that annual report providesinformation to the stakeholders. In order to evaluate organizational effectiveness, this paper discussesthat corporate disclosure could serve as data source to measure many criteria of competing values framework. Apparently, this corporate disclosure based competing values framework is appropriatefor both of the early and the end of organization life cycle. The quantity and quality of disclosures also determine the success of its implementation
KERUMUNAN HARGA SAHAM PADA MULTIFRAKSI Lukas Purwoto
Benefit: Jurnal Manajemen dan Bisnis Benefit : Kumpulan Makalah Diskusi Dosen FE UMS Volume 13 No 1 Juni 2009
Publisher : Program Studi Manajemen Fakultas Ekonomi dan Bisnis Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/benefit.v13i1.1300

Abstract

Price clustering is the tendency of prices to be observed more often at some numbers than others. This study documents the existence and persistence of stock price clustering on the Jakarta Stock Exchange.Over the period from 2001 to 2004, daily closing stock prices are found to cluster at 00 followed by 50. Significant clustering within each different thick sizes is found in transaction prices as well as in order prices and remarkably persistent through all trading days. Moreover, stock price clustering is found to increase with volatility, and decrease with transaction frequency.
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