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Title: A multi method investigation into the costs and into the benefits of measuring intellectual capital assets
Author: Gray, Dina
ISNI:       0000 0001 3512 6517
Awarding Body: Cranfield University
Current Institution: Cranfield University
Date of Award: 2005
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This study sets out to address the question of whether the costs and the benefits of measuring intellectual capital assets differ depending on the driver for that measure. Although pressure is growing on firms to measure and report on their intellectual capital assets no research has yet been published that questions the costs associated with such actions. And although academic research has purported to show links between the management of intellectual capital assets and real business benefits the research carried out thus far'has not focussed specifically on the benefits of measuring intellectual capital assets. Although there are now a variety of intellectual capital asset measurement frameworks there has been no cross comparison as to which intellectual capital asset measures provide the most business insight or where the outcome of that measurement is most effective. Using a multi method approach the thesis is tested in three phases; an extensive literature review covering intellectual capital, performance measurement and organisational effectiveness; a survey and content analysis to explore what and why companies measure; and structured interviewing of six companies to investigate the costs and the benefits of measurement. The thesis is tested through the investigation of thirteen propositions which show that: firstly, there is a difference in the relative cost of measuring intellectual capital assets given the measurement driver, which is explained by the frequency of measurement, the mode of data collection and analysis, and whether the use of the measure is a by product of some other driver, secondly, that the insight provided by an intellectual capital asset measure differs given the measurement driver, thirdly, that the measurement of intellectual capital assets is most effective for planning the future; and lastly, that particular measurement drivers are effective, to differing degrees, in financial, customer, operational, people and future organisational performance domains.
Supervisor: Neely, Andrew Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Measurement drivers ; Effectiveness ; Performance measurement ; Stakeholder Theory ; Resource Based Theory