Guo, H and Lu, W (2023) Measuring competitiveness with data-driven principal component analysis: A case study of chinese international construction companies. Engineering, Construction and Architectural Management, 30(4), pp. 1558-1577. ISSN 0969-9988
Abstract
Purpose: Defining and measuring competitiveness has been a major focus in the business and competition literature over the past decades. The paper aims to use data-driven principal component analysis (PCA) to measure firm competitiveness. Design/methodology/approach: A “3Ps” (performance, potential, and process) firm competitiveness indicator system is structured for indicator selection. Data-driven PCA is proposed to measure competitiveness by reducing the dimensionality of indicators and assigning weights according to the endogenous structure of a dataset. To illustrate and validate the method, a case study applying to Chinese international construction companies (CICCs) was conducted. Findings: In the case study, 4 principal components were derived from 11 indicators through PCA. The principal components were labeled as “performance” and “capability” under the two respective super-components of “profitability” and “solvency” of a company. Weights of 11 indicators were then generated and competitiveness of CICCs was finally calculated by composite indexes. Research limitations/implications: This study offers a systematic indicator framework for firm competitiveness. The study also provides an alternative approach to better solve the problem of firm competitiveness measurement that has long plagued researchers. Originality/value: The data-driven PCA approach alleviates the difficulties of dimensionality and subjectivity in measuring firm competitiveness and offers an alternative choice for companies and researchers to evaluate business success in future studies.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | China; competitive advantage; competitiveness; firm competitiveness; international construction; principal component analysis |
| Index terms: | subjectivity, China, dataset, competition, methodology, firm competitivenes, case study, composite, competitive advantage, future study, competitiveness, profitability, international construction, principal component analysis |
| Subjects: | statistical analysis, market analysis, data management, Geography, research methods, business management, economic analysis, materials science, human factors and perception, strategic management, data collection methods, research design and methodology |
| Topics: | Business Strategy, Construction Materials, Geographical Context, Research Practice, Digital Applications, International Construction |
| Descriptive scope: | 5 PCTEA |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here