Mining Deeper into the Data

Sandhya Shekhar
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Sandhya Shekhar: Knowledge and Innovation Strategies

Chapter 10 in Managing the Reality of Virtual Organizations, 2016, pp 203-224 from Springer

Abstract: Abstract In an earlier chapter, the variables that emerge as being significantly correlated to Knowledge Transfer Effectiveness (KTE) and therefore impact performance in a VO were examined. To aid managerial decision-making, this input by itself is not enough. In a situation where multiple factors are at play and an organization has finite resources at its disposal, greater clarity is required on how one should prioritize initiatives or interventions in a manner that is likely to have the maximum impact on outcomes. This requires insights on what is the relative impact of each of these variables on the eventual outcomes and which aspects it should focus on first. Should an organization look at external factors or internal factors to start with? Should it look at projects and teams or should it focus on individuals? Is the employee’s effectiveness and performance based more on an individual’s characteristics or is it governed by factors not within her control? This chapter deals with the second phase of the data analysis. The results obtained through the first level of hypothesis testing are supplemented using multiple regression. The predictive ability of the hypothesized constructs on the dependent construct is examined. The overall research model is tested using hierarchical regression. As a precursor to the same, the pre-requisites for using multivariate techniques are enumerated and the data are tested to see if these are adequately met.

Keywords: Dependent Constructs; Knowledge Transfer Effectiveness (KTE); Hierarchical Regression; Multiple Regression Analysis Results; Partial Regression Plots (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:spr:mgmchp:978-81-322-2737-3_10

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DOI: 10.1007/978-81-322-2737-3_10

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