Social relationship of a firm and the CSP-CFP relationship in Japan

Using artificial neural networks

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

As a criterion of a good firm, a lucrative and growing business has been said to be important. Recently, however, high profitability and high growth potential are insufficient for the criteria, because social influences exerted by recent firms have been extremely significant. In this paper, high social relationship is added to the list of the criteria. Empirical corporate social performance versus corporate financial performance (CSP-CFP) relationship studies that consider social relationship are very limited in Japan, and there are no definite conclusions for the studies in the world, because of scant data and the inappropriate methods, especially for supporting linear hypothesis which these studies are based on. In this paper, the CSP-CFP relationship is analyzed by an artificial neural networks model, which can deal with a non-linear relationship, using 10-year follow-up survey data.

Original languageEnglish
Pages (from-to)117-132
Number of pages16
JournalJournal of Business Ethics
Volume87
Issue number1
DOIs
Publication statusPublished - 2009 Jun

Fingerprint

neural network
Japan
firm
performance
profitability
Social relationships
Artificial neural network
Corporate financial performance
Corporate social performance
Social Relationships
Artificial Neural Network
Network model
Survey data
Profitability
Social influence
Nonlinear relationships

Keywords

  • Artificial neural networks
  • Corporate social performance versus corporate financial performance relationship
  • Corporate social responsibility
  • Growth potential
  • Japan
  • Linearity
  • Profitability
  • Social relationship

ASJC Scopus subject areas

  • Business and International Management
  • Economics and Econometrics
  • Business, Management and Accounting(all)
  • Law

Cite this

Social relationship of a firm and the CSP-CFP relationship in Japan : Using artificial neural networks. / Okamoto, Daisuke.

In: Journal of Business Ethics, Vol. 87, No. 1, 06.2009, p. 117-132.

Research output: Contribution to journalArticle

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