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This paper sets out to examine the operationalisation of knowledge creation. Given the importance of knowledge creation for national and corporate wealth, assessing its measurement is a valuable exercise; however, current research utilises a range of measures, and this lack of agreed construct operationalisation is a barrier to robust empirical investigation. This paper aims to review current measurement methods and to construct a taxonomy of knowledge creation measures.

A four‐step classification method is followed. In order to generate information on the essential properties of measurement methods, relevant empirical research is reviewed and a content analysis performed on the resultant measures. The literature review includes key‐term searches on bibliographic databases, yielding a sample of 63 empirical papers that incorporated knowledge creation measures. Both of the authors independently created a cognitive map of these measures based on three different attributes.

The main contribution of the paper is the development of a hierarchical taxonomy of knowledge creation measures. This taxonomy, in which movement up the hierarchy provides broader conceptual classification and movement down provides conceptual refinement, advances knowledge creation research by categorising measures in a way that facilitates assessment against existing comparable definitions.

The limitations of the research stem from issues of bias. In addition to sampling bias, some bias may have entered the coding with respect to placement of measures into process or output categories.

The research has significant implications for future research in knowledge creation: the taxonomy facilitates consistency between knowledge construct definition and measurement, and differentiation between knowledge creation and other, related constructs, such as innovation. Such a taxonomy makes it easier to clarify similarities and differences among knowledge creation measures, develop new propositions for future investigation, and identify neglected areas of study.

Intellectual capital (IC), knowledge management and intangible assets are important factors in determining the value of an organization, as reflected in the growth of the knowledge management industry. There is however, a lack of effective measurement techniques to specify and optimize the value of IC. This paper presents a detailed review of existing techniques and establish the need for a more comprehensive approach. The proposed framework addresses IC valuation issues across the IC cycle. People, process, and technology are measured and correlated in the final step with social and financial measures, thus providing a new framework.

Knowledge management (KM) is popular within the engineering industry. With increasing investment in KM projects, companies are looking for ways to justify their effort. This research develops a framework to assess the contribution of KM solutions within a business against its corporate objectives. The framework uses a set of key performance indicators (KPIs) as lead indicators. The lead indicators are developed in line with the lag indicators at the strategic level. A number of templates is developed to implement the framework within a company. A real life case study is presented where the templates are used to identify KPIs for a manufacturing solution. The paper also gives guidelines on using the templates effectively.

The purpose of the paper is to compare measures of subjective and objective knowledge as well as usage/experience measures in a credence service environment for two different samples, namely college students and non‐student adults.

Data were collected from two independent samples using self‐administered questionnaires and were analyzed using correlation and reliability analyses, factor analysis, discriminant analysis and one‐way ANOVA.

For the student sample, the results show that even though measures of subjective product knowledge, objective product knowledge, and product usage are correlated with one another, each represents one unique dimension of total product knowledge. The results for the non‐student sample show that subjective and objective knowledge converge into one dimension, product usage is a second dimension, and vicarious product knowledge a third dimension.

One limitation of the present study is that its results are anchored in the context of hospitals and might thus be most relevant to this particular choice of service. In terms of implications, the “vicarious” component of total product knowledge the study uncovers for non‐students is a promising field for future studies because it is identified as one of the dimensions of total knowledge for those non‐student consumers who have a fairly low degree of objective knowledge and direct product experience.

Marketing managers should to take into account that, for adults, subjective knowledge is a better indicator of their objective knowledge than for students (or perhaps similar segments).

The present study is one of the first studies to investigate simultaneously the three dimensions of consumer product knowledge in a credence service environment.

Fundamental classifications of knowledge may be measurable as factors of production and can reveal evidence of specialization between adjacent stages of production even in the presence of shared substantive knowledge. This study of aims to distinguish between, and empirically measure, relative reliance on fundamental classifications of knowledge at the individual level.

In this study, investment managers were asked in an online survey to weigh their relative reliance on tacit, codified and encapsulated knowledge in executing different investment strategies for diverse client groups. Measures of relative reliance on each fundamental classification of knowledge were derived from weights assigned by each survey respondent in a series of six questions.

Survey respondents provided reliable measures of their relative reliance on tacit, codified and encapsulated knowledge. Reliance on these fundamental classifications of knowledge is shown to differ between investment managers, depending on the investment strategies being used and client groups served. These differences were exhibited notwithstanding all the respondents sharing common substantive knowledge.

Measures of relative reliance on three classifications of knowledge were based on self-reported ratings rather than on objectively observed phenomena, making them subject to measurement error. Therefore, researchers are encouraged to observe relative reliance on tacit, codified and encapsulated knowledge in future studies.

The divergences in relative reliance on the fundamentally different knowledge-based factors of production were found in the presence of jointly held substantive knowledge, suggesting that fundamental classifications of knowledge are measurable and can provide evidence of specialization.

The acquisition of knowledge through mergers and acquisition (M&A) may not create value—usually because the knowledge may not be transferred, or transferred but not integrated. The purpose of this paper to develop and test a theoretical model of knowledge and performance in the M&A process.

Theory, model and case analysis.

The literature review led us to distinguish between three main categories of knowledge along the different stages of the M&A process: acquired knowledge in the pre-merger stage; and transferred knowledge and integrated knowledge in the post-merger stage. The application of the model is illustrated in a case study of technology M&A, which includes data collected from annual reports before and after the merger.

The model recommends acknowledging the differences between the acquired knowledge, transferred knowledge and integrated knowledge when examining the relationship between knowledge and performance in M&As. In addition, the model suggests considering several factors that influence future knowledge integration in the pre-merger stage. Ignoring the three categories and the factors may be the reason for the reports of previous studied stating that the acquisition of knowledge-based resources is associated with negative announcement returns to the acquiring firm.

The paper presents new procedures to measure knowledge, collecting data on R&D employees by using annual reports. In addition, the paper suggests adding “in-process R&D” as an “Acquired Knowledge” measure.

To present a measurement framework to capture the importance of the use of knowledge within the new product development (NPD) process.

A literature review enabled 200 product development measures to be compiled. These were categorised into six dimensions: stakeholder contribution, operating context, reuse, invention, exploitation, and NPD performance. Four companies applied selected measures and assessed the cube for its ability to improve measurement and management of their NPD process. This process refined the approach. A web‐based questionnaire (with 130 responses) assessed how a wider population perceived their performance and capability to measure performance in each of the six dimensions.

Respondents consider themselves capable of delivering good products and services, but are less confident in their ability to manage and measure knowledge reuse, invention and exploitation activities.

Full implementation of the measurement cube was not possible. Further research should assess the comprehensiveness, applicability and usefulness of the approach in more detail.

Introduction of the measurement cube and measures in the six dimensions identified would enable companies to go beyond traditional financial measures for their NPD processes and move towards a more performance‐oriented culture.

This paper synthesises the results from many other isolated studies on NPD metrics. In addition, it focuses on the measurement of the NPD process from a knowledge perspective, providing an integrating framework (the measurement cube), which is unique.

The paper examines ways that Knowledge Management (KM) can demonstrate practical value for organizations. It begins by reviewing the claims made about KM, i.e. the benefits KM can provide to organizations. These claims are compared with traditional firm performance metrics to derive a criterion to measure the value of KM. Seven practical outcomes of KM are then presented as methods to persuade managers to invest in KM. These practical outcomes are then evaluated against the value criterion. The paper is based on empirical evidence from a five year longitudinal study.

This paper is based on a longitudinal change project for a large Australian Research Council (ARC) Linkage Project grant in the period 2008-2013. The Project was a transformational change program which aimed to help make the partner organisation a learning organisation. The partner organisation was a large Australian Government Department, which faced the threat of knowledge loss caused by its ageing workforce. The sample was 118 respondents, mainly engineering and technical workers. A total of 150 respondents were invited to participate in the study which involved an annual survey and attendance at regular training workshops and related activities, with a participation rate of 79 per cent.

This paper provides a checklist from which to evaluate KM in terms of financial and non-financial measures and seven practical outcomes from which to identify the organisational problem which may be addressed by KM. Lead and lag indicators – what needs to be done and what will result – are also provided. Managers may use this framework to identify the value proposition in any KM investment.

The research is based on a single case study in a public sector organization. While the longitudinal nature of the study and the rich data collected offsets this issue, it also presents good opportunities for researchers and practitioners to test the ideas presented in this paper in other industry contexts. The seven practical outcomes also vary in the maturity of the empirical evidence supporting KM ' s impact. Strategic alignment, value management, and psychological contract, in particular, are still under-developed and could be areas for specific further research testing the ideas presented here.

This paper argues that investment decisions regarding KM may benefit from focusing on significant and on-going organisational problems, which will connect KM with firm performance and demonstrate financial and non-financial impact. The seven practical outcomes were evaluated against measurement criteria and against KM ' s claims. Overall, common themes were time and cost, as well as capability growth and performance improvements. Financial impact was mainly found in cost savings. Non-financial impact was found across the seven practical outcomes. It provides management with a checklist to make investment decisions regarding KM.

The decision whether to invest in KM begins with methods used to evaluate any organisational project. Managers must determine first whether necessary funds are available; and then whether the project is worthwhile. The standard method for evaluating a project ' s worth is return on investment (ROI). However, calculating ROI for KM investment is problematic. Unless KM can be proven to directly improve performance in financial terms, managers may struggle to see its ROI. The paper begins by reviewing the claims made about KM, i.e. the benefits KM can provide to organizations. These claims are compared with traditional firm performance metrics to derive a criterion to measure the value of KM.

The purpose of this paper is to propose a definition of KMS success.

The paper uses a consensus‐building approach to derive the definition. An expert panel was used to generate a list of possible KM success definitions. A survey was used to identify a likely definition from this list. A second survey was used to further refine the proposed KM success definition. Finally, analysis of the survey comments was used to finalize the proposed definition.

KM success is a multidimensional concept. It is defined by capturing the right knowledge, getting the right knowledge to the right user, and using this knowledge to improve organizational and/or individual performance. KM success is measured by means of the dimensions: impact on business processes, impact on strategy, leadership, and knowledge content.

An additional survey should be performed that tests the constructs of the proposed KM success definition. Additionally, future research should focus on identifying a set of measures that can be used to measure KM success and determining whether KM and KM System (KMS), success are the same or different constructs.

The proposed definition of KM success provides practitioners with four dimensions that can be used to construct organization‐specific measures for indicating when their KM initiative is successful.

This is important, as the literature, while providing much support for identifying KM critical success factors, does not provide a definition of when KM can be considered successful. Knowing when a KM initiative is successful is important for organizations and practitioners.

This research explores perceptions of knowledge management processes held by managers and employees in a service industry. To date, empirical research on knowledge management in the service industry is sparse. This research seeks to examine absorptive capacity and its four capabilities of acquisition, assimilation, transformation and exploitation and their impact on effective knowledge management. All of these capabilities are strategies that enable external knowledge to be recognized, imported and integrated into, and further developed within the organization effectively. The research tests the relationships between absorptive capacity and effective knowledge management through analysis of quantitative data (n = 549) drawn from managers and employees in 35 residential aged care organizations in Western Australia. Responses were analysed using Partial Least Square-based Structural Equation Modelling. Additional analysis was conducted to assess if the job role (of manager or employee) and three industry context variables of profit motive, size of business and length of time the organization has been in business, impacted on the hypothesized relationships.

Structural model analysis examines the relationships between variables as hypothesized in the research framework. Analysis found that absorptive capacity and the four capabilities correlated significantly with effective knowledge management, with absorptive capacity explaining 56% of the total variability for effective knowledge management. Findings from this research also show that absorptive capacity and the four capabilities provide a useful framework for examining knowledge management in the service industry. Additionally, there were no significant differences in the perceptions held between managers and employees, nor between respondents in for-profit and not-for-profit organizations. Furthermore, the size of the organization and length of time the organization has been in business did not impact on absorptive capacity, the four capabilities and effective knowledge management.

The research considers implications for business in light of these findings. The role of managers in providing leadership across the knowledge management process was confirmed, as well as the importance of guiding routines and knowledge sharing throughout the organization. Further, the results indicate that within the participating organizations there are discernible differences in the way that some organizations manage their knowledge, compared to others. To achieve effective knowledge management, managers need to provide a supportive workplace culture, facilitate strong employee relationships, encourage employees to seek out new knowledge, continually engage in two-way communication with employees and provide up-to-date policies and procedures that guide employees in doing their work. The implementation of knowledge management strategies has also been shown in this research to enhance the delivery and quality of residential aged care.