dispersion, coordination and performance in gsd: a systematic review
TRANSCRIPT
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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
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Agenda
• Motivation
• Research questions
• Review process
• Review result
• Conclusion
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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
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Motivation• An existing model on team input, process and IS
project outcome [2]:
• 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
Dispersion(Input)
Team coordination(Social- emotional
Process)
Project outcome(Output)
[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
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Research questions
RQ1: Which dimensions of
dispersion are explored?
RQ2: How is team
coordination influenced
by these dispersion
dimensions?
RQ3: How is team
performance influenced
by these dispersion
dimensions?
RQ4: Which context factors
could explain the
heterogeneity among
empirical findings on the
influence directions?
Dispersion
dimension
Team
Coordination
Performance
Context factorsRQ1
RQ2 RQ3
RQ4
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Review process
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Literature review
Protocol
development
Paper selection
Data extraction
Quality
assessment
Data analysis
Purpose: Provide knowledge background
Collect key words to build the search string
Construct data extraction form
Result: 27 seed studies
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Review process
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Literature review
Protocol
development [3]
Paper selection
Data extraction
Quality
assessment
Data analysis
Search string:
Data source: Scopus, ISI Web of Science, Reference list
Exclusion criteria:1. Short papers
2. Not in SE or IS area
3. Not about dispersed context
4. No empirical report or validation
5. Study team coordination without relationships with
project outcomes
(coordinati* or collaborativ* or cooperati* ) AND
(distributed or offshor* or "open source" or outsourc* or
global or dispers*) AND (software or project or team)
[3] B. A. Kitchenham, “Guidelines for performing Systematic Literature Reviews in Software Engineering”, EBSE
Technical Report, 2007
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Review process
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Literature review
Protocol
development
Paper selection
[3]
Data extraction
Quality
assessment
Data analysis
Search result ……………… 11222 unduplicated papers
Selected by reading titles and abstracts ….. 470 papers
Selected by reading full text …….…………….48 papers
Extra papers by reference scan ….…………….8 papers
Total papers to be extracted …...……………..56 papers
[3] B. A. Kitchenham, “Guidelines for performing Systematic Literature Reviews in Software Engineering”, EBSE
Technical Report, 2007
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Review process
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Literature review
Protocol
development
Paper selection
Data extraction
Quality
assessment
Data analysis
Meta data
Study design,
background concept
Context setting
Independent factors
Dependent factors
Control factors
Findings,
threats to validity
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Review process
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Literature review
Protocol
development
Paper selection
Data extraction
Quality
assessment [4]
Data analysis
CHECKLIST
Problem statement
1. Is the aim of the research sufficiently explained
and well motivated?
Research design
2. Is the context of study clearly stated?
3. Is the research design sufficiently prepared
beforehand?
Data collection
4. Are the data collection and measures adequately
described?
5. Are the measures used in the study relevant for
answering the research question?
Data analysis
6. Is the data analysis used in the study adequately
described?
7a. Qualitative study: Are the interpretation of result
clearly described?
7b. Quantitative study: Are the effect size reported
with assessed statistical significance?
8. Are potential confounders adequately controlled
or discussed?
Conclusion
9. Are the findings of study clearly stated and
supported by the results?
10. Does the paper discuss limitations or validity?
Remove 8 papers:
1. Poor research design
2. Insufficient data
3. Poor/ No data analysis
conducted
56 extracted papers
Studies on team
performance: 28 papers
[4] T. Dybå and T. Dingsøyr, “Empirical studies of agile software development: A systematic review”, Information and
Soft- ware Technology, vol 50, pp. 833-859, 2008
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Review process
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Literature review
Protocol
development
Paper selection
Data extraction
Quality
assessment
Data analysis
Tailored thematic analysis [5] (RQ1, RQ2)
Extract code …...………………………………………..
RQ1 ……………………………….....53 codes
RQ2 ………………………………...137 codes
Identify common themes……………………..………..
RQ1 ………………………………….5 themes
RQ2 ………………………………….8 themes
Vote counting (RQ3, RQ4) [6] .….………………………..
Geographical dispersion ………… 14 studies
Temporal dispersion ………………. 8 studies
[5] D. S. Cruzes and T. Dybå, “Recommended Steps for Thematic Synthesis in Software
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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Demographics
0
1
2
3
4
5
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2003 2005 2006 2007 2008 2009 2010 2011
Publication by year
No of study
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Demographics
0
2
4
6
8
10
12
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Publication by research methods
Data collection
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Demographics
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0 2 4 6 8 10 12 14 16 18 20
Laboratory
Open source
Outsourcing
Global branch
Global dispersion type
No. of studies
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ResultRQ1: Which dimensions of dispersion are explored?
Dispersion dimensions
Geographical dispersion
(16)
Temporal dispersion
(8)
Organizational dispersion
(8)
Work process dispersion
(7)
Cultural dispersion
(5)
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Result
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
RQ2: How is team coordination influenced by these
dispersion dimensions?
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Result
Coordination problem Geo. Tem. Org. Wor. Cul.
Frequency of communication and
feedbackX X X X
Choice of communication mean X X X X
Coordination delay X X X X
Perception and attitudes toward
collaborationX X X X
Misinterpretation X X X X
Coordination requirement gaps X X
Team structure configuration X X
Task scheduling complexity X
RQ2: How is team coordination influenced by these
dispersion dimensions?
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Result
Coordination problem Geo. Tem. Org. Wor. Cul.
Frequency of communication and
feedbackX X X X
Choice of communication mean X X X X
Coordination delay X X X X
Perception and attitudes toward
collaborationX X X X
Misinterpretation X X X X
Coordination requirement gaps X X
Team structure configuration X X
Task scheduling complexity X
RQ2: How is team coordination influenced by these
dispersion dimensions?
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Result
Dispersions is associated with
lower team performance
Positive impact on team
performance on project
level
No association with team
performance
Negative impact on team
performance on team &
task level
RQ3: How does the team performance
influenced by these dispersion
dimensions?
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Result
Perception about
team performance
Direct measure of
team performance at
project level
RQ3: How does the team performance
influenced by these dispersion
dimensions?
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Result
No
consistent
picture from
empirical
studies on
the influence
of
dispersions
on team
performance
RQ3: How does the team performance
influenced by these dispersion
dimensions?
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Result
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
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RQ4: Which context factors could explain the heterogeneity
among empirical findings on the influence directions?
Unit of
analysis
Geographical Temporal
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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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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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.
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Q&A
Contact• Anh Nguyen-Duc: [email protected]
• Daniela S. Cruzes: [email protected]
• Reidar Conradi: [email protected]
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