Conceptualizing the interplay of knowledge accumulation and integration capabilities in service innovation-based competitive strategy : a project-oriented firm context

While past knowledge-based approaches to service innovation have emphasized the role of integration of knowledge in the provisioning of solutions, these approaches fail to address complexities involved with knowledge integration in project-oriented context, specifically, how the firm’s capability to acquire new knowledge from clients and past project episodes influence the development of new service solutions. Adopting a dynamic capability framework and building on knowledge-based approaches to innovation, this paper presents a conceptual model that captures the interplay of learning capabilities and the knowledge integration capability in the service innovation-based competitive strategy. Implications to theory and directions for future research are discussed.

Examining the critical interplay of knowledge acquisition and integration capabilities in service innovation-based competitive advantage in project oriented service firms

While past knowledge-based approaches to service innovation have emphasized the role of knowledge integration in the delivery of customer-focused solutions, these approaches do not adequately address the complexities inherent in knowledge acquisition and integration in project-oriented firms. Adopting a dynamic capability framework and building on knowledge-based approaches to innovation, the current study examines how the interplay of learning capabilities and knowledge integration capability impacts service innovation and sustained competitive advantage. This two-stage multi-sample study finds that entrepreneurial project-oriented service firms in their quest for competitive advantage through greater innovation invest in knowledge acquisition and integration capabilities. Implications for theory and practice are discussed and directions for future research provided.

Identifying the knowledge management structures in enterprise systems projects

Enterprise System (ES) implementation and management are knowledge intensive tasks that inevitably draw upon the experience of a wide range of people with diverse knowledge capabilities. Knowledge Management (KM) has been identified as a critical success factor in ES projects. Despite the recognized importance of managing knowledge for ES benefits realization, systematic attempts to conceptualize KM-structures have been few. Where the adequacy of KM-structures is assessed, the process and measures are typically idiosyncratic and lack credibility. Using the ‘KM-process’, itself based in sociology of knowledge, this paper conceptualizes four main constructs to measure the adequacy of KM-structures. The SEM model is tested using 310 responses gathered from 27 ES installations that had implemented SAP R/3. The findings reveal six constructs for KM-structure. Furthermore, the paper demonstrates the application of KM-structures in the context of ES using the Adaptive Structuration Theory. The results demonstrate that having adequate KM-structures in place, while necessary, is not sufficient. These rules and resources must be appropriated to have greater positive influence on the Enterprise System. Furthermore, the study provides empirical support for knowledge-based theory by illustrating the importance of knowledge use/re-use (vs. knowledge creation) as the most important driver in the process of KM.

From resource base to dynamic capabilities : an investigation of new firms

Despite the numerous observations that dynamic capabilities lie at the source of competitive advantage, we still have limited knowledge as to how access to firm-based resources and changes to these affect the development of dynamic capabilities. In this paper, we examine founder human capital, access to employee human capital, access to technological expertise, access to other specific expertise, and access to two types of tangible resources in a sample of new firms in Sweden. We empirically measure four dynamic capabilities and find that the nature and effect of resources employed in the development of these capabilities vary greatly. For the most part, there are positive effects stemming from access to particular resources. However, for some resources, such as access to employee human capital and access to financial capital, unexpected negative effects also appear. This study therefore provides statistical evidence as to the varying role of resources in capability development. Importantly, we also find that changes in resource bases have more influential roles in the development of dynamic capabilities than the resource stock variables that were measured at an earlier stage of firm development. This provides empirical support for the notion of treating the firm as a dynamic flow of resources as opposed to a static stock. This finding also highlights the importance of longitudinal designs in studies of dynamic capability development. Further recommendations for future empirical studies of dynamic capabilities are presented.

Life cycle modelling and design knowledge development in 3D virtual environments : final report

Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This final report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.

Life Cycle Modelling and Design Knowledge Development in 3D Virtual Environments

Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This Industry focused report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.

The knowledge advantage (K-Adv): unleashing creativity and innovation

The K-Adv has been developed around the concept that it comprises an ICT enabling infrastructure that encompasses ICT hardware and software infrastructure facilities together with an enabling ICT support system; a leadership infrastructure support system that provides the vision for its implementation and the realisation capacity for the vision to be realised; and the necessary people infrastructure that includes the people capabilities and capacities supported by organisational processes that facilitates this resource to be mobilised.

Developing capabilities for ongoing learning and change in intermediary programs

In dynamic environments, firms seek to build capabilities which will permit them to become innovation and change ready. Programs offered by intermediaries, while varying greatly in content and format, are designed to support those firms wishing to enhance their competitiveness. Firms which participate in intermediary programs have displayed their willingness to overcome deficiencies or barriers to competitiveness through acquiring knowledge which is external to the firm. This paper reports on interviews with 24 firms who were involved in a MAP or TAP program offered by QMI Solutions. The findings of the research suggest that knowledge intermediaries serve to disrupt organisational paths and in so doing establish mechanisms for ongoing learning and change. They do this first by disrupting the firm with a positive learning experience and also by establishing processes for developing new relationships and access to knowledge which are critical for learning and change. It is the experience of learning through knowledge exchange which can trigger the pursuit of new paths and it is the processes involving new relations and knowledge processing that provides the micro-foundations for ongoing learning and change. This suggests that the role of intermediaries goes well beyond merely knowledge transfer to include longer term effects on the capability of organisations to innovate, which is critical to economic competitiveness and the survival rate of firms.

Succession management as a knowledge management strategy

One of the most critical issues for building innovation capacity in organisations is the acquisition and maintenance of knowledge. As knowledge is the basis of human capital, then the ability to attract, retain and engage talent is argued to be an important element of innovation. By attracting and retaining good staff, the organisation is retaining organisational knowledge which is necessary particularly for exploitation of current capabilities, but will also contribute to capacity for exploration for future innovation. This paper addresses the importance of retaining and developing staff as a critical issue for knowledge management and addresses the issue of retaining talent through effective succession management practices. The findings from an exploratory study into current practices in the Australian rail sector, provides further insight into the potentially critical issues for the effective use of succession management as a knowledge management and employee retention tool for building innovation capacity.

Systematising knowledge management in projects

Purpose – The purpose of this paper is to provide a practicable systems-based approach to knowledge management (KM) in a project environment, to encourage organisations to unlock the value in their review processes. It relies on knowledge capture and storage at decision review points, to enrich individual, team and organisational learning during the project life cycle. The project's phases are typically represented horizontally with deliverables (objectives) or project "promises" as the desirable outcomes. The purpose of this paper is to give expression through introducing a vertical dimension to facilitate the KM process. A model is proposed that conceptualises project-specific knowledge drawing on and feeding into the organisation's knowledge management system (KMS) at tactical and strategic levels. Design/methodology/approach – This conceptual paper links concepts from systems theory with KM, to produce a model to identify, collate, and optimise project-based knowledge and integrate it into the management process. Findings – The application of the system theory approach enriches the knowledge generated by a project, and feeds it into the next phase of that project. At the same time, it contributes to the individual's and project team's KM, specifies possible courses of action, together with risks, costs and benefits and thus it expands the organisation's higher level KMS. Research limitations/implications – The concept suggests that the knowledge capture, storage and sharing process may best be undertaken holistically, in view of the systems relationships between the tasks. Systems theory structures this process. Research opportunities include studying the interfaces between levels of KM, in relation to the project's progress. Practical implications – Reconceptualisation of the project as a knowledge creation process may improve the project's progress as well as add to the individual's, project team's, and wider organisation's knowledge base. An example is given. Originality/value – This paper illuminates the broader potential of under-utilised opportunities in well-known management approaches to add dimension to the business project, of knowledge creation, storage and sharing.

Managing knowledge in an outsourcing environment

What an organisation does versus what it out-sources to the market is a classic boundaries of the firm question that has previously been dominated by efficiency arguments. However, a knowledge-based view suggests these boundaries are integral to the ability of a firm to deploy existing knowledge stocks efficiently, as well as develop new knowledge through learning that will drive future competitiveness. Furthermore, the nature of these boundaries, in respect of their permeability is critical in understanding the likelihood of knowledge flowing into and out of the organisation. Using these concepts, we present a case study of Main Roads Western Australia to illustrate how these principles have allowed it to start rebuilding its internal capabilities through repositioning its operational boundaries and via ensuring their boundaries are highly porous as they move more major projects into alliance contracts.

Produsage and business : sharing your brand with users

Relations between brands and their users continue to be affected by a traditional perspective that sees the producers and consumers of goods and services as inherently different animals. In the emerging information and knowledge economy, and especially in online contexts, this model is no longer sustainable. Instead, spearheaded by the Web 2.0 phenomenon, there is a trend towards the fusing of production and usage as a new, hybrid process of produsage. This presentation presents the key characteristics driving produsage processes, and describes four guiding principles for businesses as they share their brand with users: * Be open. * Seed community processes by providing content and tools. * Support community dynamics and devolve responsibilities. * Don't exploit the community and its work.

Determinants of knowledge transfer and learning in hybrid public private alliances

This paper uses the case study of a hybrid public-private strategic alliance as data to complement and contrast with the traditional views on knowledge transfer and learning between alliance partners. In particular, the paper explores whether the concept of competitive collaboration conceptualized by Hamel (1991) in his seminal work holds true for all forms of strategic alliances. Conceptualizing the knowledge boundaries of organisations in alliances as a ‘collaborative membrane’, we focus attention on the permeability of these boundaries rather than the actual location of the boundaries. In this vein, we present a case study of a major public sector organization that illustrates how these principles have allowed it to start rebuilding its internal capabilities adopting a more collaborative stance and ensuring their knowledge boundaries are highly porous as they move more major projects into hybrid public private alliance contracts.

Building for competitive advantage in early stage start-ups : the role of entrepreneurial capabilities

Recent theoretical work has suggested “entrepreneurial capabilities” themselves may provide the resource foundations to deliver competitive advantage for entrepreneurial firms. This paper empirically examines how start-ups use such entrepreneurial capabilities to build competitive advantage. We investigate the effects of technological and marketing expertise, knowledge of market trends, flexibility and networking on the ability to obtain a cost leadership or differentiation advantage. Using a large dataset of 1,108 start-ups obtained after random sampling of over 30,193 households, we find that differentiation strategies benefit from most resource advantages. Cost leadership strategies, however, seem only to benefit from technological expertise and flexibility and not related to market-based advantages. By doing so, this study contributes to both entrepreneurship and RBV-theories by showing how entrepreneurial capabilities lead to competitive advantages in nascent and early-stage start-ups.