استفاده از تحلیل سلسله مراتبی فازی برای مدیریت دارایی های سرمایه فکری : یک برنامه کاربردی برای صنعت خدمات فناوری اطلاعات و ارتباطات

In today’s competitive business environment, Intellectual Capital (IC) management is ever more recognized as a fundamental factor in gaining competitive advantage. Actually, most firms have only a vague idea of how to manage investments in IC and what they should obtain from these investments. As a result, many companies overlook to balance IC investments, overinvesting in some IC components and neglecting other ones. Following this lead, the aim of the paper is to assess the relative importance of IC components, with respect to their contribution to the company value creation, in order to obtain guidelines for IC management and investments. We propose a model for IC evaluation by integrating Fuzzy Logic and Analytic Hierarchy Process (AHP). This Fuzzy AHP approach allows to capture and foster IC dynamics: experts and managers are greatly supported by the use of linguistic variables in the evaluation process of the company intangible assets. Finally, the application of the Fuzzy AHP methodology to a group of ICT service companies is presented.

In order to obtain and maintain competitiveness companies must understand how to manage their intangibles by effectively increasing, spreading and exploiting them in the organization (Stewart, 1997). Indeed, business performance depends in great measure on an efficient management of Intellectual Capital (IC) and, consequently, IC evaluation is a critical obstacle to gain and maintain competitiveness. For this reason, the general attention for Knowledge Management approaches to understanding the nature of the firm and the possible basis for sustained competitive advantage, has been nurturing the interest for developing IC assessment methodologies (Spender & Marr, 2006). Scientific literature on IC regards accounting rules as generally inadequate to completely appraise the economic value of intangible assets (Hand and Lev, 2003, Lev, 2003 and Lev and Zambon, 2003), even after the adoption of IAS 38 (Morricone, Oriani, & Sobrero, 2010). The lack of an exhaustive response to company accounting needs regarding intangibles, caused the rise of alternative IC oriented forms of corporate reporting and the creation of new assessment methods. The new methods of measurement are often founded on different or even conflicting perspectives (e.g. monetary or non-monetary), but they all take into account the essential role that the IC plays in the knowledge-economy (Sveiby, 2001–2010). Actually, most firms have only a vague idea of how to manage investments in IC and what they should obtain from these investments. As a result, many companies overlook to balance IC investments, because they overinvest in some IC components neglecting other ones (Zambon, 2003). Nevertheless, evaluating the importance of IC components is essential for any company that understands the new rules of survival in the knowledge-economy. More specifically, for a company it is important to understand how to manage IC creating and maintaining the right equilibrium among IC components (Lev, 2003). For example, if a service company invest too much in Human Capital neglecting its Structural Capital, tacit knowledge could overgrowth explicit knowledge, exposing the company to a high risk associated with personnel turnover. In a real business scenario, many IC components are intangible in nature, therefore they are difficult or impossible to measure quantitatively. Actually, when measuring what are considered as intangible benefits, most experts provide linguistic assessments rather than exact numerical values to express their opinions (Costa & Evangelista, 2008). Following this lead, in this paper IC evaluation is realized by means of Fuzzy AHP, assessing the contribute of each IC component to the company value creation process. The methodology allows the comparison among companies of the same industry in the perspective of IC management improvement through benchmarking. Indeed, the aim of the analysis is to give guidelines to decision makers in order to create and preserve a valuable balance among IC components. Finally, the presented model is applied to the IC evaluation of a group of ICT service companies.

In this paper, we present a Fuzzy AHP methodology to analyse the impact of IC components on a company value creation process. The aim of the analysis is to provide guidelines to decision makers in order to create and preserve a valuable balance among IC components. Actually, many companies overlook this aspect of IC management, overinvesting in some IC components and neglecting other ones. The direct consequence of this lack of awareness about IC configuration is the ineffective exploitation of the company intangible assets. Following this lead, the purpose of the proposed methodology is to determine which IC investments should be reduce and which ones should be increased in order to improve a company business performance. We suggest to balance IC components by applying a benchmarking approach: a company, called Target, is compared to Best Practices of the same industry with respect to the configuration of their IC components. We choose Fuzzy AHP to determine the ranking (or relative importance) of the IC components, because, as an extension of the classic AHP method, it considers the fuzziness and vagueness of the linguistic judgments expressed by decision makers about the impact of the IC components on business performance. Nonetheless the existence of a large number of methods to handle Fuzzy AHP, we present an innovative approach to determine the relative importance of IC components, which starts from a review of Chang’s extent analysis method (1996). Finally, we apply the proposed Fuzzy AHP approach to a sample of companies operating in the ICT services industry. The presented methodology is a useful tool to support decision makers in managing IC investments, selecting which IC components should be leveraged to improve performance. Actually, the outcomes of the application offer direction for progress, that should constitute the basis for the formulation of future IC strategies.