Effects of Career Horizon and Corporate Governance in China's Construction Industry: Multilevel Study of Top Management Fraud

Ran Wang, Chia Jung Lee, Shu Chien Hsu, Saina Zheng, Jieh Haur Chen

Research output: Contribution to journalArticlepeer-review

16 Scopus citations

Abstract

To investigate the drivers of fraudulent behavior in the construction industry, this study focused on top managers and explored whether individual-level and firm-level characteristics would exert an influence on likelihood of misconduct. It was first proposed that as an executive's career horizon becomes shorter, the executive would become more risk-averse and less likely to participate in wrongdoing. This present research also considered whether the relationship between career horizon and top management fraud would be moderated by firm-specific variables, particularly board monitoring and ownership structure. To investigate these hypotheses, information was collected on 1,052 executives in 70 construction firms in China from 2012 to 2017. This study applied hierarchical linear modeling due to the multilevel structure of the data. The results support that executives with a shorter career horizon are associated with a reduced likelihood of top management fraud. It also found that executives near retirement are less likely to engage in fraudulent actions if their firms have a less independent board and a higher percent of shares held by the state. The findings are not only an obvious echo of upper echelons theory but further emphasize the role of board composition and ownership structure in preventing top management fraud. The multilevel research design helps us to understand the cross-level nature of top management fraud within an organization and contributes to the literature on corporate governance in the construction industry.

Original languageEnglish
Article number04020057
JournalJournal of Management in Engineering
Volume36
Issue number5
DOIs
StatePublished - 1 Sep 2020

Keywords

  • Board monitoring
  • Career horizon
  • Hierarchical linear modeling
  • Ownership structure
  • Top management fraud

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