Intellectual capital and performance of listed companies: empirical evidence from Italy. Issue 1 (2014)

• Record Type: Journal Article
• Other Names: Special Editor.
• Is Part Of: Measuring business excellence. Volume 18:Issue 1(2014)
• Page Start: 22
• Page End: 35
• Publication Date: 2014
• Subjects: Intellectual capital -- Financial performance -- Value added intellectual coefficient (VAIC) -- Italian stock market -- Market to book value; Organizational effectiveness -- Periodicals; Success in business -- Periodicals; Performance -- Periodicals; 658
• DOI: 10.1108/MBE-10-2013-0054
• Languages: English
• ISSNs: 1368-3047

Abstract

Abstract : Purpose – The aim of this paper is to investigate the relationship between corporate performance and Value Added Intellectual Coefficient (VAICTM) on the one hand, and the relationship between the variations in market value and the variations in VAIC on the other hand. Design/methodology/approach – Starting from the VAIC model, 23 Italian listed companies were examined with the aim of investigating the relationship between VAIC and the performance of the firms in the sample. The analysis was divided into two stages. In the first stage, eight models of linear regression were estimated to verify the presence of a positive and statistically significant relationship between M/BV and VAIC and between accounting performance indicators (ROE, ROI, ROS) and the VAIC. In the second stage, six other models were tested, considering as an independent variable the variations in VAIC and the variations in profitability indicators. Findings – The outcomes of the application stress the importance of VAIC in the explanation of the variations in MV and its role as "additional coefficient" in the analysis of equity performance. Originality/value – This methodology highlights some very interesting aspects. In particular, whereas the relationship between M/BV and VAIC and between profitability indicators (ROI, ROE, ROS) and VAIC is statistically insignificant, the subsequent analysis highlights the importance of VAIC as a variable capable of increasing the explanatory power of the regression in a cross‐sectional perspective.