THE IMPACT OF CLUSTERING ON COMPETITIVENESS AND BUSINESS PERFORMANCE OF SMEs: EVIDENCE FROM THE SERBIAN AUTOMOTIVE INDUSTRY

Abstract

Clusters are widely regarded by scientific researchers and policymakers as effective tools for addressing the size constraints faced by SMEs. The increased involvement of local SME suppliers in supply chain restructuring has led to the extensive adoption of clusters in the automotive industry. Despite a wealth of literature supporting the economic advantages of clustering, the absence of quantitative evidence has constrained policy support for cluster development in numerous developing countries. This research aims to empirically compare the performance of clustered and non-clustered SMEs within the same industry. The primary objective is to quantify the impact of the Serbian Automotive Cluster on the competitiveness and business performance of Serbian automotive SMEs. Utilizing Stochastic Frontier Analysis and statistic tests, the methodology examines a balanced panel of 29 SMEs in Serbia’s automotive industry spanning from 2016 to 2018. The impact of clustering is analysed in terms of efficiency and effectiveness, crucial dimensions of business success. Total revenue is used to measure efficiency, reflecting an integral competitive indicator. Effectiveness is assessed using profitability indicators such as profit margin, asset turnover ratio, and return on assets. The research reveals that clustered SMEs in the automotive industry exhibit higher efficiency (competitiveness) and effectiveness (profitability) compared to non-clustered SMEs. The proposed methodology holds significance for evidence-based policymaking, providing empirical support for cluster policy. The paper introduces a novel quantitative assessment methodology for gauging the impact of clusters on SME members’ competitiveness and business performance. The unique approach adds value to the paper, as similar methodologies have not been previously applied in assessing the impact of clustering on efficiency and effectiveness, fundamental dimensions of business success. The suggested methodology holds importance due to its potential applicability in evaluating how clusters influence the performance and competitiveness of SMEs across diverse industry sectors in developing nations. Acknowledging the limitations of our research, notably the small sample size that focused solely on SMEs with publicly available financial statements, excluding numerous enterprises from the analysis, we underscore the significance of clustering in enhancing the business performance of SMEs in the automotive industry. This emphasizes the need for additional research in quantitatively measuring the impact of clusters, paving the way for further exploration in this direction.