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Explore the implications and risks of intentional and unintentional knowledge leakage along supply chains, covering impacts on time to market, supplier dependency, market share loss, and productivity. Understand knowledge intensity measurement, capability maturity models, and information flow complexities in supply chain networks.
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Literature Review Topic Presentation Risk Knowledge intensity Capability maturity Information flow along supply chains
Risk • What are the implications of knowledge leakage? • Risks from intentional knowledge leakage • Risks from not undertaking intentional knowledge leakage • Risks from unintentional knowledge leakage
Risks from intentional knowledge leakage • Increases time to market if not carried out effectively • Increased dependency on supplier • Loss of centralised information • Piracy of confidential knowledge • Conflicts between source and entity • Loss of market share • Knowledge loss as suppliers develop ‘local’ knowledge that never returns to the source (see table) • Increased risk of unintentional knowledge leakage • Increased imitability (see table) • Through other information • Loss of knowledge value Autio, Sapienza and Almeida, 1999, Styhre, 2004, Yanow, 2004, Roper and Cronet, 2003, Ndofor and Levitas, 2004 Decarolis, 2003)
Loss of speculative work within in house R&D • EU productivity report showed the EU outperformed the US in industry groups where innovations rose from in-house R&D • R&D investments linked to increased productivity • Small suppliers are less likely to have the resources to plan for new technologies • Small suppliers are less likely to look sideways at potentially disruptive technologies emerging in other industry sectors Reed and Walsh, 2002, O’Mahoy and van Ark
Risks from not undertaking intentional knowledge leakage (benefits really!) • Inability to compete in modern production • Movement to supply chain production is often cheaper and more efficient if organised effectively – increasing productivity. • Inability to gain from knowledge leakage plus point (predictable order flow, reduction of stock/inventory, ,efficient product replenishment, etc) • Increased productivity through divestment • Possible closing of the productivity gap attributed to the promotion of two-way knowledge transfer between enterprise, science based and research institutions and supply chain partners • Reduced productivity growth in the EU has been attributed to the slow exchange of knowledge in response to new technology. (Brynjolfsson and Hitt 2000, O’Mahoy and van Ark, 2003)
Risks from unintentional knowledge leakage • Loss of disembodied or tacit knowledge of production procedure through employee loss leading to disruptions in productivity • Loss of value of ‘weightless good’ • Decreased productivity from loss of knowledge within industries regarding inefficiency of manufacturing processes
Knowledge intensity • Ways of measuring knowledge intensity: • Through R&D expenditure • No of patents • Through the development of a hierarchy of knowledge type tasks? • Through taking stock of managerial and production techniques • Through an audit of current knowledge and future knowledge possibilities based on current knowledge • (Autio, Sapienza and Almeida, 1999, Smith 2002, Shadbolt and Milton, 1999, Roper and Cronet, 2003, Ndofor and Levitas, 2004)
Through identification of technological intensity or the degree of sophistication and customisation of the production process. • By taking a stock of knowledge through a taxonomy of forms of knowledge, and the use of manufacturing techniques as inductive of the strength of the companies knowledge base (see table) • Problems that authors do not explain these techniques fully! (Lepak, Tekeuchi and Snell, 2003, Roper and Cronet, 2003))
Management assessment questionnaires (see figure) • Knowledge Audits? Autio, Sapienza and Almeida, 1999
Derived from software optimisation techniques – generic approaches to developing an entity to its ultimate state. • Levels (4-6) characterised by achievement requirements. • Sequentially ordered from an initial state to a final level, normally perfection • Employed in businesses trying to establish an effective knowledge management system. • Can also be used to make comparisons between companies, to rank companies and for benchmarking. Capability maturity / Knowledge maturity models
Microsoft ‘knowledge landscape’ • 8 levels (‘unaware’ to ‘leadership’) • Ranked via 77 criteria using a 4 level scale • KPMG ‘knowledge journey’ • 5 levels (‘knowledge chaotic’ to ‘knowledge centric’) • Gallagher and Hazletts KMƒ • 4 levels (‘Aware’ to ‘optimisation’) • Split into separate focus’ of culture, infrastructure and technology (Klimko, 2001)
Example of a knowledge maturity model Klimko, 2001
Information flow along supply chains Highly non linear, dynamic, complex adaptive systems that differ between supply chains and between entities within supply chains. Types of information flow Internal flow External flow Pre-product flow Post-product flow Explicit flow Tacit flow Embodied flow Disembodied flow Episodic flow Continuous flow Macro-flow Micro-flow Propriety flow Shared flow
Relationship affecting the information flow Relationship to one another Complementary knowledge portfolios – equal flow (Roper and Cronet have an assessment of complementarity,2003) Relationship between entity and source Supply and demand, continuous development etc Efficient, continuous information flow reduces costs and maintains cycle times. Reduces machine down time.
Mechanisms for information flow Phone, fax, internet, post, person to person etc Electronic data interchanges (EDI’s) Information exchanges Standardised / formalised (Proformas, spreadsheets etc) Less formalised / casual (comments, remarks etc) Three flows : materials information resources (Stefersson, 2002, Johnston 1998, Meer-Kooistra, Jud and Jijlttra, Pittaway, Robertson, Munir, Denver and Neeley,2004, Un and Cuero-Cazura, 2004)
Information mechanisms in companies of varying size (Stefersson, 2002)
Assess knowledge leakage in countries with increased productivity in order to assess if knowledge leakage does effect productivity. Or within companies with similar productivity growth or decline levels (OECD STAN database Sector competitiveness analysis of the software and computer service industry by the DTI found the productivity gap in India was due to high levels of staff turnover (KL through employee loss) and due the the high levels of piracy) Difficulty in assessing effect of KL on productivity as intentional KL (outsourcing) is often linked with other activities Knowledge leakage in relation to the UK productivity GAP – additional comments (Reynolds, Howard, Dragon, Rosewell and Ormerod, 2005, van Ark, Inklaar and Mcgucken, 2003))
EU Report on productivity suggests sector specific improvements in technologies within industries with wide applications in other industries and promoting knowledge flows along product supply chains in order to increase productivity (O’Mahoy and van Ark, 2003)
Bibliography Autio E, Sapienza HJ, Almeida JG (1999) ‘Effects of Age at Entry, Knowledge Intensity, and imitability on international growth’ revised manuscript for the International Entrepreneurship issue of the Academy of Management Journal, March 31 1999 Brennan N ( ) ‘Reporting intellectual capital in annual reports: evidence from Ireland’ Johnston R (1998) The changing nature and forms of knowledge: A review, Department of employment, education, training and youth affairs, Sept 1998 Lepak D P Takeuchi R A. Snell S A 03 (2003) ‘Employment Flexibility and Firm Performance: Examining the Interaction Effects of Employment Mode, Environmental Dynamism, and Technological Intensity’ Journal of Management 2003 29(5) 681–7 Meer-kooistra Jvd and Zijlsttra S M ( ) ‘Reporting on intellectual capital’ Ndofor H A, Levitas E (2004) ‘Signaling the Strategic Value of Knowledge’ Journal of Management 2004 30(5) 685–702 O’Mahory M and van Ark (2003) EU productivity and competativeness: An industry perspective – Can Europe resume the catching up process? European commission, Enterprise Publications
Pittaway L, Robertson M, Munir K, Denyer D and Neely (2004) ‘Networking and Innovation: a systematic review of the evidence’, IJMR Reed F M and Walsh K (2002) ‘Enhancing Technological Capability Through Supplier Development: A Study of the U.K. Aerospace Industry’ IEEE Transactions on Engineering Management, VOL. 49, NO. 3, August 2002 231 Roper S and Cronet M (2003) ‘Knowledge complimentarity and coordination in the local supply chain: Some empirical evidence’, British Journal of management, Vol 14, 339-355 Shadbolt N and Milton N (1999) ‘From knowledge engineering to knowledge management’, British journal of management, Vol 10, 309-322 Smith K (2002) What is the knowledge economy? Knowledge intensity and distributed knowledge bases, The United Nations University, Discussion paper, June 2002 Stefansson G (2002) ‘Business-to-business data sharing: A source for integration of supply chains’ in International Journal of Production Economics 75 (2002)135 –146 Styhre A (2004) ‘Rethinking Knowledge: A bergsonian critique of the notion of tacit knowledge’, British journal of management, Vol 15, 177-188
Un C A and Cuero-Cazura A (2004) ‘Strategies for knowledge creation in firms’, British Journal of Management, Vol 15, S27 – S41 Yanow D (2004) ‘Translating local knowledge at organizational peripheries’, British Journal of Management, Vol 15, S9-S25 Klimko G (2001) knowledge management and maturity models: Building common understanding, proceedings of the 2nd European Conference on knowledge, 2001 Reynolds, Howard, Dragon, Rosewell and Ormerod (2005) Assessing the productivity of the UK retail sector, International Review of retail, distribution and consumer research, Vol 15, No 3, 237 – 280 Sector competitiveness analysis of the software and computer service industry by the DTI – www.dti.gov.uk/industries/software/Sector_Competitiveness_Analysis.doc Van Ark, B, Inklaar R and Mcguckin RH (2003) ICT and productivity in Europe and the United States. Where do the differences come from?, CESifo Economic Studies, Vol 49, No 3 295-318 Brynjolfsson and Hitt (2000) Beyond Computation: Information technology, organizational transformation and business performance, Journal of economic perspectives, Vol 14, No 4, 23-48