Stickiness as a Component of Collaboration Readiness

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Stickiness as a Component ofCollaboration
Readiness

• Jeremy Birnholtz

Presented by Matthew Bietz
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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.

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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

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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?

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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 Szulanskis 3 significant
  constructs
• Choice of online or paper completion
• Response
• 27 usable response, 108 total responses

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Causal Ambiguity up close

• This was the most interesting variable
• Cronbachs Alpha .7
• Mean 3.0, SD.88, bimodal distribution
• Variables tested for differences (oneway ANOVA,
  then combined)
• More experienced gt less experienced
• Researchers gt practitioners
• Experience Occupation (marg. sig.)

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Causal Ambiguity GraphEstimated Marginal Means
of Causal Ambiguity
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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.

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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.