Implementing Majority Voting Rule to Classify Corporate Value Based on Environmental Efforts

  • Ratna HidayatiEmail author
  • Katsutoshi Kanamori
  • Ling Feng
  • Hayato Ohwada
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9714)


The Japanese understanding of corporate social responsibility (CSR) is linked with the country’s history of industrial pollution. As a result, the top area Japanese companies are addressing is the environment. This study aims to classify the corporate value of Japanese companies calculated by the Ohlson model based on environmental efforts using several classification techniques. The corporate value is divided into high, medium, and low. Since the classification leads to imbalanced classes, five classification techniques (Gradient Boosting, Decision Tree, Support Vector Machine (SVM), and K-Nearest Neighbor (KNN)) were chosen to deal with this problem. KNN, with the lowest accuracy (0.68), was found predict smaller classes better than the others. To improve its accuracy, a majority voting rule is implemented in this study. In the voting rule, three classifiers (KNN, Random Forest, and Decision Tree) are combined. The accuracy for the combination of the three classifiers is 0.71. However, this study found that the impact on biodiversity is the most important variable among Japanese companies. This indicates that recent efforts to differentiate corporate value among Japanese companies based on environmental efforts arises from their understanding of the impact of business activities on biodiversity.


Corporate value Ohlson model Environmental efforts Classifier techniques Majority voting rule 


  1. 1.
    Kamei, Z., Hirano, T.: Issues and Prospects for CSR in Japan Analysis of Japan’s CSR Corporate Survey. (2015) Accessed 18 Jan 2016
  2. 2.
    Yamada, S.: Environmental Measures in Japaneses Enterprises: A Study from an Aspect of Socialisation for Employees. In: Szell, G., Tominaga, K. (eds.) The environmental challenges for japan and germany: intercultural and interdisciplinary perspectives, pp. 297–322. Peter Lang, Frankfurt/Main (2004)Google Scholar
  3. 3.
    Yamada, S.: Corporate social responsibility in Japan. Focused on environmental communication. In: Gyorgy Szell (ed.): Corporate Social Responsibility in the EU & Japan, pp. 341−358. Frankfurt/Main: Peter Lang (2006)Google Scholar
  4. 4.
    Nippon, K.: Japan 2025: Envisioning a Vibrant, Attractive Nation in the Twenty-first Century. Nippon Keidanren, Tokyo (2003)Google Scholar
  5. 5.
    Nakao, Y., Amano, A., Matsumura, K., Genba, K., Nakano, M.: Relationship between environmental performance and financial performance: an empirical analysis of japanese corporations. Bus. Strategy Environ. 16(2), 106–118 (2006)CrossRefGoogle Scholar
  6. 6.
    Tanabe, T.: Kankyō CSR-ron ni arata-na shiten o [a new perspective for environmental CSR theory]. Econ. Rev. Fujitsu Res. Inst. 9(1), 114–115 (2005)Google Scholar
  7. 7.
    Hanada, M.: The trend of environmental reports in Japan: a consideration from the viewpoint of corporate social responsibility. Osaka Sangyo Univ. J. Hum. Environ. Stud. 3, 21–44 (2004)Google Scholar
  8. 8.
    Goo Research: Kankyō hōkokusho hakkō kigyō no ishiki chōsa [Awareness survey of companies issuing environmental reports] (2002). Online poll undertaken in November 2001. Accessed 19 Dec 2015
  9. 9.
    Anjō, T.: CSR keiei to koyō rōdō [CSR management, employment and labor]. Jpn. J. Labour Stud. 46(9), 33–44 (2004)Google Scholar
  10. 10.
    Tanimoto, K., Suzuki, K.: Corporate social responsibility in Japan: analyzing the participating companies. In: Global Reporting Initiative (= European Institute of Japanese Studies Working Paper; 208). Stockholm: European Institute of Japanese Studies (2005)Google Scholar
  11. 11.
    Kuncheva, L.I.: Combining Pattern Classifiers: Methods and Algorithms. Wiley InterScience, Chichester (2004)CrossRefzbMATHGoogle Scholar
  12. 12.
    Madhulatha, T.S.: An overview on clustering methods. IOSR J. Eng. II(4), 719–725 (2012)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Ratna Hidayati
    • 1
    Email author
  • Katsutoshi Kanamori
    • 1
  • Ling Feng
    • 1
  • Hayato Ohwada
    • 1
  1. 1.Department of Industrial Administration, Faculty of Science and TechnologyTokyo University of ScienceNoda-shiJapan

Personalised recommendations