A measurement system for managing performance of industrial clusters

Abstract

Purpose -The purpose of this article is to present and discuss a conceptual model for performance measurement and management of a cluster based on the concepts of the Balanced Scorecard and other models. Design/methodology/approach -This paper was based on a case research as the field research methodology for theory testing and refinement. Findings -The proposed model adequately captures the perspectives of performance management of a cluster, emphasizing the importance of measuring leading and lagging dimensions of performance such as collective efficiency and economic/social results. Research limitations/implications -Research is still at an early stage and applications of the model need to be carry on further so as to review and validate it. Practical limitations -Absence of a culture of decision making based on analysis of information and lack of resources may create some difficulty in using metrics for a cluster of SMEs. Originality/value -The paper proposes applying the concepts and techniques of business performance management and measurement to manage performance of clusters of companies, offering a new approach on how to improve the collective efficiency of a cluster.

Institutions for collaboration in industrial clusters: proposal of a per-formance and change management model

“…Indeed, performance management in industrial clusters has drawn considerable attention from several authors and has been viewed as a basis for the management of a cluster (Sölvell et al 2003;DTI, 2005;Gerolamo et al, 2008;Carpinetti et al, 2008). Furthermore, the use of numerical means to demonstrate the benefits of collaboration in organizational networks would motivate companies to collaborate more and establish new partnerships (Camarinha-Matos and Affsarmanesh, 2007).…”

Analyzing industrial clusters using measures of structural complexity management

“…In literature, many approaches exist to evaluate clusters' efficiency or performance (Bergman et al, 1996;Czamanski and Ablas, 1979;Feser and Bergman, 2000;Kozhinova and Ferova, 2012;Morkovina et al, 2014;Mukhiddini and Bobojonov, 2014;Padmore and Gibson, 1998;Ribeiro Carpinetti et al, 2008). There are several approaches, whose focus lies in algorithms and methods to cluster or to identify clusters, or to evaluate the suitability of companies for the cluster (Bergman et al, 1996;Czamanski and Ablas, 1979;Feser and Bergman, 2000;Kozhinova and Ferova, 2012).…”

“…For this reasons, those measures are not relevant for our considerations, as we want to analyze industrial clusters by identifying their strengths and weaknesses. Other authors focus on the actual state of industrial clusters to evaluate their current level of performance (Morkovina et al, 2014;Mukhiddini and Bobojonov, 2014;Padmore and Gibson, 1998;Ribeiro Carpinetti et al, 2008). Mukhiddini and Bobojonov (2014) use criteria like "number of workers and the general assets of the company" or "labor productivity" to indicate the development stage of an industrial cluster.…”

“…Furthermore, this methodology lacks in analyzing the interactions between different companies. Ribeiro Carpinetti et al (2008) took ideas from the balanced scorecard (Kaplan and Norton, 1992) to evaluate clusters performance and used metrics like "labor productivity", "total labor force" or "percentage of companies involved with cooperation" (Padmore and Gibson, 1998). They consider more abstract measures to assess the performance.…”

Relações verticais e horizontais no processo de inovação e aprendizagem interativa: estudo em um aglomerado produtivo

“…This is the basic idea behind industrial clusters since they can promote and facilitate innovation through close relationships between partners and suppliers, facilitate monitoring of competitors in a cluster, enable the high availability and exchange of information, and allow the easy observation of technological trends and shifts in habits and customer needs (Becattini, 1990;Porter, 1999;Mytelka & Farinelli, 2000;Casarotto Filho & Pires, 2001;Suzigan et al, 2001;Carpinetti et al, 2008;Amato, 2009). In particular, this is the crucial role of clusters in the processes of innovation, considered learning by the interacting process (Salom & Albertos, 2006;Maehler et al, 2011;Kim et al, 2014).…”