On doing knowledge management

Firestone, Joseph M.

doi:10.1057/palgrave.kmrp.8500160

Cited by 33 publications

(12 citation statements)

References 11 publications

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“…Knowledge life cycles enable a structured while differentiated process of transformation and change based on knowledge creation, sharing, decision-making and knowledge embodiment. Although life cycle models, such as the knowledge life cycle provided by Firestone andMcElroy (2003, 2004), provide triggers, relations and components for single-and double-loop learning, their implementation so far has led to disruptive business and knowledge processing. However, stakeholders are affected in both types of activities, business and knowledge processing, and also need to be involved at the interface, developing problem formulations towards knowledge claims and incorporating surviving knowledge claims into the business processing environment effectively and efficiently.…”

Section: Resultsmentioning

confidence: 99%

“…Source: Firestone andMcElroy, 2003, 2004 developments not only require a single learning loop for operative change, but rather a double learning loop stepping beyond operation into a knowledge processing environment, as shown in Figure 1.…”

Section: Figure 1 Scheme Of Firestone and Mcelroy's Knowledge Life Cyclementioning

confidence: 99%

“…Hence, underlying knowledge drivers of an organization, namely, knowledge claims and valued interactions among stakeholders, dealing with that knowledge are not tackled explicitly. In that context Firestone (2008) has emphasized the structured dealing with decision-making when distinguishing the DEC interruption approach from the background conditions or ecological approach.…”

Section: Vol 18 No 4 2014 Journal Of Knowledge Management Page 653mentioning

confidence: 99%

“…The systems of differentiation and innovation are addressed by knowledge management (KM) and life cycles models, including Firestone andMcElroy's (2003, 2004) knowledge life cycle (KLC), as they concern processes unique for an organization, thus creating competitive advantage (through effectiveness and efficiency) and processes transforming business putting forward new ideas, and thus being of strategic relevance. Both…”

Section: Introductionmentioning

confidence: 99%

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Non-disruptive knowledge and business processing in knowledge life cycles – aligning value network analysis to process management

Stary

2014

Journal of Knowledge Management

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Purpose – This paper aims to achieve fully intertwined knowledge and business processing in change processes. It proposes streamlining situated articulation work, value network analyses (VNA) and subject-oriented business process modelling (S-BPM) and execution to provide non-disruptive single and double learning processes driven by concerned stakeholders. When implementing knowledge life cycles, such as Firestone and McElroy’s knowledge life cycle, the agility of organizations is significantly constrained, in particular, when surviving knowledge claims should be implemented in the business processing environment in a seamless way. Design/methodology/approach – The contribution is based on a conceptual analysis of knowledge life cycle implementations, learning loop developments and an exploratory case study in health care to demonstrate the effectiveness of the proposed approach. The solution towards non-disruptive knowledge and business processing allows stakeholders to actively participate in single- and double-loop learning processes. Findings – The introduced approach supports problem and knowledge claim formulation, knowledge claim evaluation and non-disruptive knowledge integration into a business process environment. Based on stakeholder articulation, the steps to follow are: holomapping, exchange analysis, impact analysis, value creation analysis, subject-oriented modelling, business process validation and execution. Seamless support of stakeholders is enabled through the direct mapping of stakeholder and activity descriptions from value network representations to behaviour specifications (process models) on the individual and organizational layer. Research limitations/implications – Current knowledge life cycle developments and implementations can now be analyzed in a structured way. Elements of the proposed approach could be integrated in disruptive implementations to overcome current limitations of knowledge life cycles. However, further case studies need to be performed to identify hindrances or barriers of combining VNA and S-BPM, both on the technological and methodological layer. What works for expert service industries might need to be adapted for production industries, and tools or tool chains might need to be configured accordingly. Finally, the socio-economic impact of the approach needs to be explored. Practical implications – The presented case study from health care reveals the potential of such a methodological combination, as cycle times can be reduced, in particular, due to the execution of role-specific process models in the respective business processing environment. It can be considered as a fundamental shift for existing change management procedures, as they require rework of the entire functional process models when addressing business processing. Now, stakeholder- or role-specific behaviour can be handled isolated and in parallel, without affecting the entire organization in case of modifications. Originality/value – The proposed methodological integration has not been done before. It enables stakeholders to perform single- and double-loop change processes in a seamless way.

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Section: Resultsmentioning

confidence: 99%

Section: Figure 1 Scheme Of Firestone and Mcelroy's Knowledge Life Cyclementioning

confidence: 99%

Section: Vol 18 No 4 2014 Journal Of Knowledge Management Page 653mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Non-disruptive knowledge and business processing in knowledge life cycles – aligning value network analysis to process management

Stary

2014

Journal of Knowledge Management

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“…Of course sharing in health professionals increase as information about that thing increase but for more beneficiaries, it should be networked so as to easy and rapid transferring [32]. In contrary, the study conducted in Portugal showed network in large sample compared their contacts, subjects do not connect very much (density=2.5%) [33] and the one in Kentucky where network density of infection prevention staffs in hospitals is 1.8% which seems the actors might use to protect themselves by limiting their contacts in this case [34].…”

Section: Study Definitionsmentioning

confidence: 99%

Assessment of Information Sharing Using Social Network Analysis among Health Extension Workers in Konso Woreda: A Cross-Sectional Case Study

Gilano¹,

Megabiaw²,

Alamirrew³

2017

J Health Med Inform

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Introduction: Social network is systematic means of assessing formation and informal networks by mapping and analysing relationships among people, groups, and units of work group or even entire organizations. In this article information Sharing and problem solving methods of health extension worker in Konso woreda was assessed.Objective: This study is aimed to assess information sharing using social network analysis among health extension workers in Konso woreda. Methods:A cross-sectional survey was conducted on all health extension workers in Konso woreda in Southern Ethiopia, using pretested structured pretested roster type questionnaire. All analysis performed by UCINET. Results:The response was rate 77(93%). For who know who network: Degree (64.8), Betweenness (11.1), Eigenvector (0.11), density (79.28%), and for information sharing network Degree (22.3), Betweenness (54.6), Eigenvector (0.11), density (27.2%). Using MR-QAP indicated significant variables such as experience (B=-0.041, p=0.0085), media (B=-0.0430, p=0.0055), site (B=-0.11, p=0.0005) and who know who B=0.1722, p=0.0005). People share information have positive performance (B=0.0466, p=0.01450) Conclusion:The information sharing in HEWs was inadequate. Sharing was observed among different sites rather than the same, people of different experiences than that of the same, and people who have different knowledge of Medias for information Sharing but for who know each other and have performance. were more likely to interact in most of the cases, in particular, those with similar specialties and organizational affiliations [41]. Other study in Addis Ababa uncovered as much as media of information transferring concerned there a need of more time so that the recipient and the source would be more interacted which means there are more indicators to have smooth transmission [13]. Assessment of Information SharingTherefore, current study outcome was more concerned social and information Sharing networks that might clear what to do to achieve more with HEWs, helps co-coordinators and planners easy way of distributing information using key nodes, and will identify informal connections than expected, which is important to rearrange the program activities.Specific objectives of the study 1. To describe the magnitude of information sharing in health extension workers using network analysis in Konso woreda.2. To compare information sharing and knowing each other network densities 3. To determine factors associated to information sharing among the health extension workers.4. To empirically describe the structure of information flow among health extension workers. Methods and Materials Study design and populationA cross sectional study was conducted using social network analysis from February 1 to May 30, 2012, to elicit information sharing of health extension worker (community health workers). A wholenetwork approach was employed for current study because we use all of the connections between people (HEWs) in the woreda.

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Terminology Entries (Alphabetical Presentation)

Richey

2013

Encyclopedia of Terminology for Educational Communications and Technology

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On doing knowledge management

Cited by 33 publications

References 11 publications

Non-disruptive knowledge and business processing in knowledge life cycles – aligning value network analysis to process management

Non-disruptive knowledge and business processing in knowledge life cycles – aligning value network analysis to process management

Assessment of Information Sharing Using Social Network Analysis among Health Extension Workers in Konso Woreda: A Cross-Sectional Case Study

Terminology Entries (Alphabetical Presentation)

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