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|Title:||A study of the relationship between intellectual capital and innovation performance based on complexity theory||Authors:||Fan Ng, Irene Yuen Han||Keywords:||Intellectual capital -- Management.
Technological innovations -- Management.
Hong Kong Polytechnic University -- Dissertations
|Issue Date:||2012||Publisher:||The Hong Kong Polytechnic University||Abstract:||Systemic innovation capability is the key driver of sustainable growth and competitive advantage in enterprises. However, imitating other innovative organization and best practices does not guarantee success. Business organization can be described as a complex system in a competitive business environment that constantly changes. Each organization can be analogically viewed as striving to reach higher performance on its own rugged landscape. Nevertheless, each unique landscape is formed by the characteristics of an organization that are intangible, difficult to uncover and measure, and cannot be altered in a simple mechanical way. Organizational DNA has been used to describe such complex and organic nature of an organization in equivalent to living organisms. Organizational DNA is particularly crucial for innovation. Intellectual capital is defined as all intangible resources of an organization that, when combined, will produce future benefits. Research studies have shown that there is a tight relationship between intellectual capital and innovation performance. It is appropriate to use intellectual capital as the organizational DNA for innovation studies. The aim of the study is to construct an innovation assessment model based on Kauffman's biological model. Strategies utilizing intellectual capital for better innovation performance can be simulated, analyzed and implemented.
This study adopted the design science research methodology with cycles of empirical research and model validation. Combinations of quantitative and qualitative research approaches were applied. Three studies were carried out in the Information and Communication Technology industry in different geographical locations. Each study comprised a survey, statistical analysis and model simulation. Survey questionnaires were designed based on literature review and prior studies in intellectual capital and innovation. Partial Least Square regression was used with its capability of multicollinearity identification, nonlinear path estimation and the relaxed requirement of sample data size. Six main intellectual capital components were proposed and confirmed: self-efficacy of knowledge workers, transformational leadership, innovative culture, systems and processes, internal and external social networks. Their nonlinear relationships among one another and with innovation performance were verified. The findings were validated through interviews. These statistical findings were then input into a simulation model built based on the Kauffman's NK model. The NK model was an evolutionary biology model for stochastic combinatorial optimization. The original model described the interactions between genes as Boolean relationships. It was not sufficient to describe the interrelationships in organizational studies. The model was extended by using the correlation matrix from the statistical analysis as the interaction matrix of the NK model. A comparative study of two groups within the same organization was carried out and demonstrated that their organizational DNA fingerprints were unique, and different innovation strategies were needed. This study is significant as it offers a systemic approach to the interdisciplinary study of organizational DNA and innovation with a pioneering use of an intellectual capital framework. It contributes to the field of innovation management with a new attempt of its kind to integrate management research and mathematical simulation model to cover both the qualitative and quantitative aspects. In practice, it enables organizations to formulate effective management strategies for innovation performance.
|Description:||xi, 234 p. : ill. ; 30 cm.
PolyU Library Call No.: [THS] LG51 .H577P ISE 2012 Fan Ng
|URI:||http://hdl.handle.net/10397/5709||Rights:||All rights reserved.|
|Appears in Collections:||Thesis|
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Citations as of Mar 19, 2018
Citations as of Mar 19, 2018
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