This systematic review examined the impact of different dimensions of dispersion (geographical, temporal, organizational, etc.) on team coordination and performance in global software teams. The review analyzed 56 papers and identified key themes. Dispersion was found to influence coordination by impacting communication, perceptions, and task complexity. The findings on performance impact were mixed, depending on the dispersion type and unit of analysis. More research is needed on different types of dispersion and their context to better understand their influence.

1. 1
Dispersion, coordination and
performance in global software
teams: a systematic review
Anh Nguyen-Duc, Daniela S. Cruzes, Reidar Conradi
Department of Computer and Information Science,
Norwegian University of Science and Technology
2/21/2013

2. 2
Agenda
• Motivation
• Research questions
• Review process
• Review result
• Conclusion
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3. 3
Motivation
• Global software development are becoming more
and more popular:
– offshore team, outsourcing, virtual team and open source
projects
– 30% of US IT jobs are expected to be offshored by 2015 [1]
– 160.000 projects registered in Source Forge in the end of
2011
• Challenges in globally dispersed projects
– More complicated task dependencies
– More difficult team coordination
[1] ACM Job Migration Task Force, “ Globalization and Offshoring of Software”, Association for Computing Machinery, 2006

4. 4
Motivation
• An existing model on team input, process and IS
project outcome [2]:
Team coordination
Dispersion Project outcome
(Social- emotional
(Input) (Output)
Process)
• Existing empirical studies is inconclusive about the
impact of dispersion on team coordination and project
outcomes
– Dispersion dimensions
– Team coordination context
– Project outcomes measure
– Influence direction
[2] J. A. Espinosa, W. DeLone, and G. Lee, "Global boundaries, task processes and IS project success: A field study," Information
Technology and People, vol. 19, pp. 345-370, 2006

5. 5
Research questions
RQ1: Which dimensions of
dispersion are explored?
RQ2: How is team RQ1 Context factors RQ4
coordination influenced
by these dispersion
dimensions?
Dispersion
Performance
RQ3: How is team dimension
performance influenced
by these dispersion
dimensions? RQ2
Team
RQ3
Coordination
RQ4: Which context factors
could explain the
heterogeneity among
empirical findings on the
influence directions?
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6. 6
Review process
Literature review  Purpose:
 Provide knowledge background
Protocol  Collect key words to build the search string
development  Construct data extraction form
 Result:
Paper selection  27 seed studies
Data extraction
Quality
assessment
Data analysis
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7. 7
Review process
Literature review  Search string:
(coordinati* or collaborativ* or cooperati* ) AND
Protocol (distributed or offshor* or "open source" or outsourc* or
development [3] global or dispers*) AND (software or project or team)
 Data source:
Paper selection  Scopus, ISI Web of Science, Reference list
 Exclusion criteria:
Data extraction 1. Short papers
2. Not in SE or IS area
3. Not about dispersed context
Quality 4. No empirical report or validation
assessment 5. Study team coordination without relationships with
project outcomes
Data analysis
[3] B. A. Kitchenham, “Guidelines for performing Systematic Literature Reviews in Software Engineering”, EBSE
Technical Report, 2007 2/21/201

8. 8
Review process
Literature review
Search result ……………… 11222 unduplicated papers
Protocol
development Selected by reading titles and abstracts ….. 470 papers
Paper selection
[3]
Selected by reading full text …….…………….48 papers
Data extraction
Extra papers by reference scan ….…………….8 papers
Quality
assessment
Total papers to be extracted …...……………..56 papers
Data analysis
[3] B. A. Kitchenham, “Guidelines for performing Systematic Literature Reviews in Software Engineering”, EBSE
2/21/201

9. 9
Review process
Meta data
Literature review
Study design,
Protocol background concept
development
Context setting
Paper selection Independent factors
Dependent factors
Data extraction
Control factors
Quality
assessment
Findings,
threats to validity
Data analysis
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10. 10
Review process
CHECKLIST
Literature review Problem statement
56 extracted papers
1. Is the aim of the research sufficiently explained
and well motivated?
Research design
Protocol 2. Is the context of study clearly stated?
3. Is the research design sufficiently prepared
development beforehand?
Data collection
4. Are the data collection and measures adequately
Remove 8 papers:
described? 1. Poor research design
Paper selection 2. Insufficient data
5. Are the measures used in the study relevant for
answering the research question? 3. Poor/ No data analysis
Data analysis conducted
6. Is the data analysis used in the study adequately
Data extraction described?
7a. Qualitative study: Are the interpretation of result
clearly described?
7b. Quantitative study: Are the effect size reported
Quality with assessed statistical significance?
Studies on team
assessment [4] 8. Are potential confounders adequately controlled
performance: 28 papers
or discussed?
Conclusion
9. Are the findings of study clearly stated and
Data analysis supported by the results?
10. Does the paper discuss limitations or validity?
[4] T. Dybå and T. Dingsøyr, “Empirical studies of agile software development: A systematic review”, Information and
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Soft- ware Technology, vol 50, pp. 833-859, 2008

11. 11
Review process
Tailored thematic analysis [5] (RQ1, RQ2)
Literature review
Extract code …...………………………………………..
RQ1 ……………………………….....53 codes
Protocol RQ2 ………………………………...137 codes
development Identify common themes……………………..………..
RQ1 ………………………………….5 themes
Paper selection RQ2 ………………………………….8 themes
Vote counting (RQ3, RQ4) [6] .….………………………..
Data extraction Geographical dispersion ………… 14 studies
Temporal dispersion ………………. 8 studies
Quality
assessment
[5] D. S. Cruzes and T. Dybå, “Recommended Steps for Thematic Synthesis in Software
Data analysis Engineering”, pp. 275–284, ESEM, Calgary, Canada, 2011
[6] L.M. Pickard, B.A. Kitchenham, and P.W. Jones, “Combining empirical results in software
engineering,” Journal on Information and Software Technology, vol. 40, Dec. 1998, pp 811-821
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12. 12
Demographics
Publication by year
7
6
5
4
3 No of study
2
1
0
2003 2005 2006 2007 2008 2009 2010 2011
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13. 13
Demographics
Publication by research methods
14
12
10
8
6
4
2 Data collection
0
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14. 14
Demographics
Global dispersion type
Global branch
Outsourcing
Open source No. of studies
Laboratory
0 2 4 6 8 10 12 14 16 18 20
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15. 15
Result
RQ1: Which dimensions of dispersion are explored?
Dispersion
dimensions
Geographical Temporal Organizational Work process Cultural
dispersion dispersion dispersion dispersion dispersion
(16) (8) (8) (7) (5)
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16. 16
Result
RQ2: How is team coordination influenced by these
dispersion dimensions?
Coordination problem
Frequency of communication and
feedback
Choice of communication mean
Coordination delay
Perception and attitudes toward
collaboration
Misinterpretation
Coordination requirement gaps
Team structure configuration
Task scheduling complexity
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17. 17
Result
RQ2: How is team coordination influenced by these
dispersion dimensions?
Coordination problem Geo. Tem. Org. Wor. Cul.
Frequency of communication and
X X X X
feedback
Choice of communication mean X X X X
Coordination delay X X X X
Perception and attitudes toward
X X X X
collaboration
Misinterpretation X X X X
Coordination requirement gaps X X
Team structure configuration X X
Task scheduling complexity X
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18. 18
Result
RQ2: How is team coordination influenced by these
dispersion dimensions?
Coordination problem Geo. Tem. Org. Wor. Cul.
Frequency of communication and
X X X X
feedback
Choice of communication mean X X X X
Coordination delay X X X X
Perception and attitudes toward
X X X X
collaboration
Misinterpretation X X X X
Coordination requirement gaps X X
Team structure configuration X X
Task scheduling complexity X
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19. 19
RQ3: How does the team performance
Result influenced by these dispersion
dimensions?
Dispersions is associated with
lower team performance
Negative impact on team
performance on team &
task level
Positive impact on team
performance on project
level
No association with team
performance
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20. 20
RQ3: How does the team performance
Result influenced by these dispersion
dimensions?
Perception about
team performance
Direct measure of
team performance at
project level
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21. 21
RQ3: How does the team performance
Result influenced by these dispersion
dimensions?
No
consistent
picture from
empirical
studies on
the influence
of
dispersions
on team
performance

22. 22
Result
RQ4: Which context factors could explain the heterogeneity
among empirical findings on the influence directions?
Variables:
– Lack of data: dispersion type, number of sites, level of
communication technology and practices
– Study subject, sample size, quality of study
– Team performance measure type, Unit of analysis
Unit of Geographical Temporal
analysis Pos. Neg. Neu. Pos. Neg. Neu.
Task 0 5 1 0 0 0
Team 0 4 1 0 3 1
Project 1 1 1 3 1 0
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23. 23
Implication for future research
Research Include and distinguish among different type of
dispersions
Report dispersion context and level of communication
technology and practices
Further research on how work process & cultural
dispersion impact team performance
Further research on impact of dispersion on
mechanistic coordination
Further research on dispersion on open source projects
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24. 24
Implication for practice
Practice Understand that impact of dispersion is context-specific
Promote technology and working style that support
effective informal communication
Configure team structure that addresses coordination
requirement
Be aware of positive effect of temporal dispersion on
team performance
Look for evidence at team and work unit level to decide
the cost-benefit of being distance.

25. 25
Q&A
Contact
• Anh Nguyen-Duc: anhn@idi.ntnu.no
• Daniela S. Cruzes: dcruzes@idi.ntnu.no
• Reidar Conradi: Reidar.Conradi@idi.ntnu
2/21/201