Index

Rajalakshmi Subramaniam (Talaash Research Consultants Private Limited, India)
Senthilkumar Nakkeeran (Anna University, India)
Sanjay Mohapatra (Xavier Institute of Management, India)

Team Work Quality

ISBN: 978-1-80117-263-9, eISBN: 978-1-80117-262-2

Publication date: 26 April 2021

This content is currently only available as a PDF

Citation

Subramaniam, R., Nakkeeran, S. and Mohapatra, S. (2021), "Index", Team Work Quality, Emerald Publishing Limited, Leeds, pp. 127-129. https://doi.org/10.1108/978-1-80117-262-220211008

Publisher

:

Emerald Publishing Limited

Copyright © 2021 Rajalakshmi Subramaniam, Senthilkumar Nakkeeran and Sanjay Mohapatra. Published under exclusive licence by Emerald Publishing Limited


INDEX

American Psychological Association (APA)
, 13, 56

Analysis of co-variance (ANCOVA)
, 47–48, 79

core activity
, 50

creativity
, 48

ethnic diversity
, 49

team age
, 48

team leader
, 50

team size
, 48

Analysis of variance (ANOVA)
, 44, 78–79

creativity
, 47

ethnic diversity
, 46

team age results
, 45

team’s core activity
, 46

team size
, 45

tenure of team leader
, 47

Atmosphere for work (ATW)
, 27, 86

Attitude to work (AW)
, 27

Capability Maturity Model Integration (CMMI)
, 70

Chi-square test
, 36, 43, 79

Cluster sampling
, 71–72

CMMI DEV V1.3 assessment
, 70–71, 86

Collection technique
, 72

Communication
, 96

Componential model
, 13, 56

Conceptual model
, 61–64

Core activity distribution
, 20–21

Correlations
, 24–27, 29

Cox’s R-squared
, 28

Creative behaviour (CB)
, 27, 86

Creative Climate Questionnaire (CCQ)
, 73–74

Creative work climate (CWC)
, 9, 40

chi-square
, 42–44

cross tabulation
, 42–44

odds ratio
, 42–44

vs. organizational creativity
, 15

Creativity
, 5–6, 40–41, 55, 61, 73–74, 85, 89–90, 96

concept
, 13–15

organizational
, 6–7

Data analysis
, 75–80

Data type
, 72

Deductive approach
, 69

Demographic profile
, 88

Department of Industrial Policy and Promotion (DIPP)
, 2

Dependent variable (DV)
, 73

Descriptive statistics
, 18

Ethnic diversity
, 45–46, 63

Foreign direct investment (FDI)
, 2

F-statistic
, 44

Gender
, 20, 22, 88

pie chart
, 22

Graphical method
, 77

Human resources
, 5

Hypotheses
, 61, 64, 67–68, 87

Indian software organization

communication skills
, 2–3

creativity
, 62, 92–93

development
, 1

export value
, 1

growth life cycle
, 1

market size
, 2

team work quality (TWQ)
, 62, 92

Individual creative behaviour
, 9, 73–74

vs. organizational creativity
, 14–15

Innovation
, 5–6

Interactionist model
, 13–14, 56, 73–74

Logistic regression
, 24, 78

Management practices (MP)
, 27

Members background
, 20–21

Mutual support (MS)
, 24

National Association of Software and Service Companies (NASSCOM)
, 2

Organizational creativity
, 6–7, 9, 56, 73–74, 89

vs. creative work climate
, 15

vs. individual creative behaviour
, 14–15

interactionist model
, 14

Organizational motivation (OM)
, 27, 86

Pearson correlation test
, 77–78

Principal component analysis (PCA)
, 24, 78

Problem definition
, 65–66

Questionnaires
, 98–109

Relationship research
, 69–70

Research gap analysis
, 58–60

Research instrument design
, 73–74

Research methodology

aim
, 66

collection technique
, 72, 82

data type
, 72

deductive approach
, 69

design
, 69–70

epistemology
, 68

ethical considerations
, 81

extension
, 94

hypotheses definition
, 67–68

instrument design
, 73–74

limitations
, 93

methodology
, 68, 82

objectives
, 66–67

ontology
, 68

pilot testing
, 75

problem definition
, 65–66

research questions (RQs)
, 67

sampling
, 70–72

statistical and software tools
, 75–80

techniques
, 80–81

theoretical and managerial implications
, 91

theoretical constructs
, 67–68

Research questions (RQs)
, 67

Respondent’s age
, 21–23

Sampling design
, 70–72

Self-efficacy
, 5

Simple percentage analysis
, 77

Socio-demographic data
, 17

age group distribution
, 21, 23

communalities
, 32–33

core activity distribution
, 20–21

correlations
, 24–27, 29

descriptive statistics
, 18

education
, 23

gender
, 20, 22

hypotheses
, 36–53

members background
, 20–21

omnibus test of model coefficients
, 28, 30

principal components
, 34

respondent’s age
, 21–23

scree plot
, 35–36

team age
, 19

team leader
, 19–20

team role
, 20–21

team size
, 18–19

total variability
, 32–33

variables
, 30–31

work experience
, 23–24

Software Engineering Institute (SEI)
, 70

Software organizations

organizational creativity
, 6–7

team work
, 3–4

Software quality
, 11, 55–56

Software tools
, 80

Statistical techniques
, 76–80

analysis of co-variance (ANCOVA)
, 79

analysis of variance (ANOVA)
, 78–79

chi-square test
, 79

graphical method
, 77

logistic regression
, 78

Pearson correlation test
, 77–78

principal component analysis (PCA)
, 78

simple percentage analysis
, 77

student’s T-test
, 80

Student’s T-test
, 80, 90–91

Team age
, 9, 19, 44, 63

pie chart
, 20

Team characteristics
, 44, 51, 55, 61

moderating effects
, 90

vs. team performance
, 89

Team cohesion (COH)
, 24

Team coordination of expertise (COE)
, 24

Team ethnic diversity
, 10

Team leader
, 10, 19–20

Team performance (TP)
, 24, 89

Team role
, 10, 20–21, 45, 63, 88

Team size
, 63, 97

bar graph
, 19

defined
, 9

Team work quality (TWQ)
, 3–4, 7–8, 55, 61, 85, 89–90

chi-square
, 36–40

components
, 24

concept
, 12

cross tabulation
, 36–40

dimensions of
, 12

odds ratio
, 36–40

research methodology
, 65–68

result comparison
, 90–91

socio-demographic data
, 17–53

t-Tests
, 51–52

Trust (TR)
, 24

Value diversity (VD)
, 24, 96