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SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Stickiness as a Component of Collaboration Readiness Jeremy Birnholtz Presented by Matthew Bietz.

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Presentation on theme: "SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Stickiness as a Component of Collaboration Readiness Jeremy Birnholtz Presented by Matthew Bietz."— Presentation transcript:

1 SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Stickiness as a Component of Collaboration Readiness Jeremy Birnholtz Presented by Matthew Bietz

2 SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Introduction: How this relates Knowledge and context are important to data and information sharing We know from the knowledge management literature that the sharing of knowledge and context is not easy This study investigates specific aspects of this problem that may help us better enable communities to share data and other resources.

3 SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Stickiness The ease with which a technique or routine can be transferred from one organizational unit to another Measured via instrument developed in empirical study by Szulanski (1996) Model relies on sender and receiver, but not a one-way exchange 3 components that Szulanski found to be strong predictors of stickiness: – Causal ambiguity – Lack of absorptive capacity – Poor sender/receiver relationship

4 SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Research Questions What barriers to knowledge sharing are present in Earthquake Engineering? Are there certain practices or social dimensions that exhibit more or fewer of these barriers?

5 SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Methods Sample – Stratified, random sample of 400 earthquake engineers from professional association Survey and measures used – 11 items on a 28-item questionnaire regarding “the last time respondents taught a colleague or student how to use a technique or skill” – Used modified subset of Szulanski’s 3 significant constructs – Choice of online or paper completion Response – 27% usable response, 108 total responses

6 SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Causal Ambiguity up close This was the most interesting variable – Cronbach’s Alpha =.7 – Mean = 3.0, SD=.88, bimodal distribution Variables tested for differences (oneway ANOVA, then combined): – More experienced > less experienced – Researchers > practitioners – Experience * Occupation (marg. sig.)

7 SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Causal Ambiguity: Graph Estimated Marginal Means of Causal Ambiguity

8 SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Explaining these results Practitioners arguably repeat techniques more often than researchers, so their practices are better understood than researchers – Repetition in time, though, yields more tacit knowledge All researchers and older practitioners work at a more abstract, less concrete level.

9 SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Main Implications Data and knowledge sharing may be more difficult in research environments than practice environments. It may be easier for less experienced people to share knowledge and data than more experienced.


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