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Ph.D. Dissertation Defense

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Sylvester Ngoma

on 16 September 2013

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Transcript of Ph.D. Dissertation Defense

An Investigation of the Impact of
Virtual Collaboration and Collaboration
Technologies on Knowledge Transfer and Team Performance in Distributed Organizations
Ph.D. Dissertation Research by Sylvester Ngoma
August 2013
Introduction
Virtual Teams have become a potent driver of competitive advantage
There is increasing reliance on virtual tools in distributed organizations (Bell & Kozlowski, 2002)
Virtual tools are used for business process or business effectiveness improvement (Kock, 2005)
60% of knowledge workers are involved in virtual teams (Kanawattanachai & Yoo, 2002)
By 2016, virtual team workers will increase by 61% (Lister & Harnish, 2011)

Research Problem
Ineffective performance (Staples & Zhao, 2006)
40% of virtual teams underperform (RW3 Culture Wizard, 2010)
Dysfunctional conflict due to the nature of virtual teams (Gibson & Cohen, 2003)
Cultural differences may impede virtual team success (Nemiro, Beyerlein, Bradley, & Beyerlein, 2008)
Misunderstandings caused by organizational, cultural, and technological diversity of virtual teams (Greenberg, 2007)
Geographic and time zone dispersion (Cramton, 2001)
Other challenges: Ineffective leadership, mistrust and differing understanding, and ineffective use of communication technologies (Dyer, Dyer, & Dyer, 2007)

Purpose of the Study
Investigate the extent of the relationship between
virtual collaboration influence, collaboration technologies
support, knowledge transfer, and team performance.

Research Questions
Can collaboration technologies and virtual collaboration support knowledge transfer and, subsequently, influence team performance?
Sub-Q1: Is there a relationship between virtual collaboration and the overall efficiency of knowledge transfer?

Sub-Q2: Is there a relationship between
knowledge transfer and the use of collaboration
technologies?

Sub-Q3: Is there a relationship between team performance and the overall efficiency of knowledge transfer?

Hypotheses
Ho1 : Virtual collaboration will not be positively related to knowledge transfer.

H1a: Virtual collaboration will be positively related to knowledge transfer.

Ho2 : The use of collaboration technologies will not be positively related to knowledge transfer.

H2a: The use of collaboration technologies will be positively related to knowledge transfer.

Ho3 : Knowledge transfer will have no mediating effect on team performance in distributed organizations.

H3a: Knowledge transfer will have a mediating effect on team performance in distributed organizations

Validity and Reliability
Theoretical Framework
Social Impact Theory (SIT) by Latané (1981)

i = f (SIN), where i denotes the magnitude of impact, f denotes a function, S the strength of sources (e.g.: their authority or power of persuasion), and I the immediacy of the sources (e.g. their closeness in time and space), and N the number of sources.

Impact is a direct function of strength (team member’s educational attainment or proven expertise), immediacy (spatial distance), and number of sources (number of people or number of sources of knowledge).
Research Model
Methodology
38 Questions
First part included 9 questions related to virtual collaboration (VC)
Second part encompassed 9 questions pertaining to collaboration technologies (CT)
Third part examined knowledge transfer (KT)
Fourth part explored team performance (TP). It had 10 questions.
Instrumentation

Triangulation of Virtual Team Survey (VTS) developed by Lurey and Raisinghani (2001), Relationship Questionnaire (RQ), and Performance Questionnaire (PQ) adapted from Nelson and Cooprider (1996) and Papoutsakis (2008).

Variables
Independent variables
:

Virtual collaboration
Use of collaboration technologies

Mediating variable

Knowledge transfer

Dependent variable

Team performance

Sample
n = 219 key informants (Participants were screened).
Minimum sample size required: 107 participants (GPower)
Inclusion criteria: Participation in virtual team projects, full-time employment status, and familiarity with electronic or virtual collaboration technologies.
Target population: Distributed organizations knowledge workers

Data Analysis
Path analysis
Regression
Correlation

Software Programs:
Statistical Package for the Social Sciences (SPSS) Statistics 21 professional edition
Amos version 17

Results
Web-based Survey
Questionnaire
Research Findings
Research Question One

Is there a relationship between virtual collaboration and the overall efficiency of knowledge transfer?

There was a significant, positive relationship between virtual collaboration and the overall efficiency of knowledge transfer,
β = .38, p < .001.

Hypothesis One

There was a significant, positive relationship between virtual collaboration and the overall efficiency of knowledge transfer, β = .38, p < .001. Therefore, H1a is supported. The null hypothesis is rejected.

Research Question Two

Is there a relationship between the use of
virtual collaboration technologies and knowledge transfer?

There was a significant, positive relationship between the use of virtual collaboration technologies and knowledge transfer,
β = .48, p < .001.

Hypothesis Two

There was a significant, positive relationship between the use of virtual collaboration technologies and knowledge transfer, β = .48, p < .001. Therefore, H2a is supported. The null hypothesis is rejected.

Research Question Three

Is there a relationship between the overall efficiency of knowledge transfer and team performance?

There was a significant, positive relationship between the overall efficiency of
knowledge transfer and team performance, β = .58, p < .001.

Hypothesis Three

There was a significant, positive relationship between the overall efficiency of knowledge transfer and team performance, β = .58, p < .001. Therefore, H3a is supported. The null hypothesis is rejected.

Contributions
One of the first studies to probe the dynamic interplay between virtual collaboration, collaboration technologies support, knowledge transfer, and team performance in virtual environment. One of the unique contributions of this study is the combination of four variables.

This study conceptually and empirically substantiates and validates the relationships between these variables.

Prior research has focused on two or three of the variables. This study addressed the research gap found in the literature.

Another contribution is the theoretical approach used. Most studies have approached virtual team realities from theoretical perspectives compiled by Schiller and Mandviwalla (2007). This study departed from the tradition.



Conclusions
A strategic planning framework interlacing the four variables discussed is needed before deploying virtual teams in a distributed organization. This may prevent wasted CT/IT investments and misuse of VT resources.

Usage of several mainstream collaboration technologies such as desktop conferencing systems, bulletin boards, and groupware is still patchy at best in virtual teams.

Virtual collaboration technologies are ever-evolving. Proper training is constantly required for virtual team members to operate these technologies efficiently and to interact effectively.

Misalignment between virtual team goals, business goals, and CT infrastructure can pose difficult challenges.


Recommendations
Further research is needed to validate the relationships between virtual collaboration, collaboration technologies, knowledge transfer, and team performance. Future research should try different instruments.

Researchers are encouraged to explore Virtual team realities through different philosophical and theoretical lenses such as the Social Impact Theory (Latané, 1981), the Compensatory Adaptation Theory (Kock, 2005) or the Social Influence Model (Tanford & Penrod, 1984). A study can suggest, for example, the types of communication behaviors needed to compensate for lack of physical presence in virtual interactions.

Further empirical research is needed to illuminate the extent of the relationship between the four variables using a more inclusive audience and an experimental approach.


Virtual Tools
Netmeeting
Global Crossing
Webex
Microsoft Live Meeting
Document-Management Systems
E-room
Groove
Online Scheduling and Time Tracking
Microsoft Project Server
Quickaround
PDAs and Smartphones
Blackberry
Palm Treo
T-Mobile Sidekick
Instant Messaging (IM)
Short Messaging Services (SMS)

Literature Review
Corroboration
Compensatory Adaptation Theory

Data Screening
Browser-based
Non-browser-based
Full transcript