Resultados para un SVAR de 5 variables: ciclo económico,

This section outlines and discusses monetary and non-monetary models used in the literature to measure IC efficiency. This section also outlines the conceptual framework used in this study along with the monetary based VAIC model to measure IC efficiency.

2.8.1

IC Measurement Models

The RBV of a firm holds that a firm’s intangible assets contribute equally towards the financial performance as its tangible assets and VA should be recognized as a measure of performance rather than the return to owners. VA augments the true measure when it comes to an economy’s production in today’s knowledge-based economy (Sveiby, 1997). Firer and Williams (2003) argue that different perceptions of accounting income have led to different performance measurementsbased on different theories. For example, under the enterprise resource perspective, an organization acts as a decision making unit on behalf of its stakeholders including employees, shareholders, and creditors, and the profit, the reward for these stakeholders is termed value added.

In accordance with the different theories on a firm’s income, different models have been introduced in the literature to measure IC efficiency. These models can be classified into two broad groups, i.e., monetary and non-monetary. Table 2 summarizes these models.

17 _{See, for example: Rehman et al. (2011).}

Table 2.1 Monetary and Non-Monetary Models Used to Measure IC

Monetary Models Non-Monetary Models

Market Capitalization models

 M/B value model

 Tobin’s Q by Luthy (1998) ROA models

 EVAa _{& MVA}b _{models by Bontis}

(1999)

 Calculated intangible value by Dzinkowski (2000)

 VAIC by Pulic (1998)

 Intangible driven value model by Lev (2000)

 Residual income model by Ohlson (1995)

Scorecard models

 Balance scorecard by Kaplan and Norton (1995)

 Technology broker model by Brooking (1996)

 Skandia Navigator by Edvinsson and Malone (1997)

 IC-Index model by Roos et al. (1997)  Intangible assets monitoring model by

Sveiby (1997)

 Heuristic frame by Joia (2000)

a_{Economic value added}

b_{Market value added}

2.8.2

The Evolution of Prominent IC Models and the Conceptual Framework

The Skandia Navigator model is among the pioneers acknowledging the importance of IC and its disclosure on the balance sheet. The model classifies IC into four elements namely human, process, renewal and customer capital.

Kaplan and Norton (1995) propose an IC measurement model known as the Balance Score Card. The idea was to measure the efficiency of intangible assets which were previously ignored. This model produces results in the form of scores for different elements of IC such as human, structural and innovation capital. Using Skandia Navigator as a base, Bontis (2004) constructed a new measure called National Intellectual Capital Index (NICI) aimed at measuring and managing IC at the national level. The model includes market capital, process capital, renewal capital and human capital as different indicators of the IC of a nation. The author applied NICI model to several Arab countries to measure the national IC and concludes that national IC represents almost 20 percent of the total financial wealth of each country in the study’s sample.

Based partially on the Skandia Navigator framework, Pulic (1998) developed a new but more comprehensive, easy to calculate measure called Value Added Intellectual Coefficient (VAIC). The VAIC model is unique since it measures the IC size and efficiency thereby giving a base for comparison between firms, industries and economies (Pulic, 1998). Unlike previous models, which

are either customized or fit for some specific profile of firms, the VAIC model uses data from audited reports of firms, which increase its authenticity (Pek, 2005).

The VAIC model has been extensively used in the literature to measure IC efficiency. For example, Chen et al. (2005) used the VAIC model to study the relationship between IC and a firm’s financial performance in Taiwan and reports a significant positive relationship. Firer and Williams (2003), studying the relationship between IC and a firm’s financial performance, found the relationship to be limited and mixed. The VAIC model has been extensively used in previous studies (Tan et al., 2007, 2008; Ting & Lean, 2009; Hsu & Wang, 2012; Pal & Soriya, 2012; Joshi et al., 2013; Kweh et al., 2013; Sumedrea, 2013; Berzkalne & Zelgalve, 2014; Lu et al., 2014; Vishnu & Kumar Gupta, 2014) because of its usefulness and ease of understanding. Following the aforementioned studies and the unique characteristics of the VAIC model, we use it to measure IC efficiency. The VAIC model has several benefits. For example, the results of the model provide a basis for comparison of IC efficiency across firms. The VAIC model uses publicly available data from annual reports of firms, which minimizes the risk associated with the results’ authenticity (Pek, 2005).

Since the main objective of this current study is to measure IC efficiency and its impact on firm performance, we use the VAIC model and its individual components, i.e., human, structural and physical capital, to measure IC efficiency along with the performance of individual components. This study uses ROA, ROE, assets turnover and P/B as firm performance measures. Departing from previous studies, this study replaces the structural capital measure of the VAIC model with innovation capital18 _{and introduces an adjusted-VAIC model to overcome criticism of the VAIC model.}

Figure 2.1 outlines the basic conceptual framework of this study.