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The purpose of this paper is to provide a quantitative assessment model for intellectual capital in companies.

A brief historical review of former approaches to evaluate intellectual capital construction of a new formula for an intellectual capital value. A possible empirical survey of influence factors on intellectual capital is suggested. Both, taken together, are the grounding of an integrative management model for intellectual capital still to be developed.

Shows that a quantitative figure for intellectual capital can be found and that such a figure is needed to convince managers and the public of the usefulness of activities to promote intellectual (and especially human) capital.

A quantitative measure can never picture the complete interrelations of organizational development, influence factors on intellectual capital, and performance of employees. The formula can only be a starting‐point for management and further research. Possible management tools are only touched on briefly.

Gives the manager a tool to argue his decisions regarding the promotion of human and intellectual capital. Managers talk about figures and often dislike purely philosophical arguments. Their awareness of the topic can be raised.

Even though there is a growing scientific body of quantitative models for measuring intellectual capital, this paper uses a new approach: the usage of approximation factors for motivation, commitment and job satisfaction in one formula.

The purpose of this paper is to review extant literature to identify models intended to measure/classify intellectual capital (IC) to establish the current body of knowledge that has been built since the review by Marr et al. (2004).

The study consists of a systematic review of peer-reviewed articles on IC classification. The review was conducted for the period 2004-2014 in order to reach the aim. To ensure that all major models are included, important works developed prior to 2004 were captured as well.

The review resulted in 83 additional models indicating continued research activities with regard to the topic. These models were merged with prior IC models and mapped on a timeline. The timeline clarifies that 2008, 2010, 2011, 2012 and 2013 represent the years of greatest research activity (outcomes). Additionally, the analysis of the list of IC frameworks resulted in the development of an IC Meta model. It synthesizes research activities in the field and highlights the main IC dimensions and sub-dimensions.

This study may not have enabled a complete coverage of all existing peer-reviewed articles in the field of IC classification. Yet, it seems reasonable to assume that the review process covered a large proportion of studies available.

By aggregating and consolidating the IC frameworks covered, the study does not only provide an IC Meta model, but also promising directions for future research.