Predicting construction firm performance: an empirical assessment of the differential impact between industry‐ and firm‐specific factors

Abstract

It is obvious that the performance of firms hinges upon the dynamics of both industry‐ and firm‐specific factors. A less obvious, and perhaps a more important, line of inquiry is that to the extent that they have a bearing on firm performance, how much do these two groups of factors respectively predict firm performance? To date, performance differences among construction firms that stem from industry‐ and firm‐specific differential effect has remained largely unexplored. Using a dataset comprising 526 firms across various construction‐related sectors, the sector‐by‐sector firm performance variation that is attributable to the heterogeneity of both industry‐ and firm‐specific characteristics was empirically examined. That statistically significant results of different effect sizes are found indicates that although these factors are often assumed to be intertwined it is possible to study their respective impact on firm performance. Future studies could usefully replicate and extend this study to construction firms in other countries to further investigate what drives firm performance under different national, industry and firm contexts.

Keywords:

• Firm performance
• performance heterogeneity
• industry‐specific factors
• firm‐specific factors
• institutional environment
• resource‐based view

Notes

1. Whether such level of institutional demands acts as an impediment to firm performance and stifles firm's ability to generate profits is a separate issue, which may be worth considering.

2. The exact scale items and their respective reliabilities will be explained in detail in the following sections.

3. The response rate is considered satisfactory for a reasonably lengthy four‐paged questionnaire and compares well with the response rates reported by other researchers for business surveys in Hong Kong and the Asia Pacific (e.g. Jobber et al., 1991; Harzing, 1996)

4. To avoid ambiguity, for this item, a list of examples was given to clarify what is meant by ‘government agencies’. Examples included Buildings Department, Architectural Services Department, Housing Authority, Construction Industry Training Authority.

5. Examples of professional associations included Hong Kong Institute of Engineers, Hong Kong Institute of Architects, Hong Kong Institute of Surveyors, Hong Kong Institute of Facilities Management.

6. The analysis for manufacturing/supplier and developer sub‐samples were omitted because of their restricted sample size after residual diagnostics were undertaken to remove outliers. The conservative guideline for regression modelling recommends a ratio of five cases to one variable.