Software Development Centers In Srilanka

Published Date: 02 Nov 2017

4.1 Introduction

This chapter describes the analysis the structural patterns exhibited in the collected data on virtual team challenges and project management. The objective of this chapter is to provide an interpretation on the collected data and support them to identify the relationship between virtual team challenges and project management by using three different software development project teams in offshore software development centers in SriLanka. This will provide a real life proofs on virtual team challenges impact to project management in different levels and.

4.2 Research Sample

The analysis was done through the selected three projects from three different organizations which are working as the offshore software development centers in SriLanka. The initial sample size was 96 and as mentioned at the section 3.6 questionnaires were distributed among 96 team members with in 3 projects (32 per each) by having a proper team balance based on their project roles. Altogether 87 of completed questions were returned and the breakdown of it based on the project has shown at Table 4.2.

Team

Sample

Percent

Cumulative Percent

Distributed

Received

A

32

30

34.48

34.48

B

32

26

29.89

64.37

C

32

31

35.63

100

Total

96

87

100

100

Table 4.2 Research Sample

4.3 Analysis of the Research Questionnaire

The questions of the questioner were break down based on the variables that used for developing the hypothesis. (Please refer the Appendix B1 for the question breakdown and the response analysis)

The rest of the questions were grouped as follow to measure the variables:

Questions 1-6 : Communication Effectiveness

Questions 7-13 : Team work Effectiveness

Questions 14-18 : Location Based Differences

Questions 19-22 : Use of technology

Questions 23-31 : Project Management (Scope, Time and Cost)

4.3.1 Communication Effectiveness

No

Question

Mean Value

Team A

Team B

Team C

All the facts that communicate by the team members are direct, simple, brief, clear and strong.

3.23

3.73

3.03

All the communication that happens with my team is easy to understand. Misunderstandings happen very rarely.

2.23

3.5

2.93

While communicating my team members they always consider about the duration, unity, rationality and importance.

3

3.46

3.55

During the team communication all the information that presents are specific, definite, and strong and there is no need for search and confirm in order to use them.

2.9

3.34

3.35

All the communication that happens with my team, shows the sender’s expression while respect the receiver.

2.83

3.34

3.13

All my team members show their proficiency in communication and it is very rare to see the absence of proper style of expression, spelling, grammar, format, contents, statistical information etc

2.63

3.38

3.29

Table 4.3.1 Communication Effectiveness Analysis

4.3.2 Team Work Effectiveness

No

Question

Mean Value

Team A

Team B

Team C

The leadership of my team has the behavior and qualities which can facilitate the creation and strengthening the critical values and traits of the team.

2.56

3.73

3.51

Each and every team member of my team aware on their role and responsibilities as well as their desired performance.

2.43

3.69

3.22

Always the decision making in my team happens based on the rationality and logic, keeping in view the ultimate goal of completing the team task successfully.

2

3.65

3.12

All my team members are conscious and focus on organizational, project and the team goals and objectives in all their work.

1.73

3.5

3.35

My team members are enthusiastic on working together and they collaborate to the level that team expected.

3.23

4.03

3.29

My team members are trustworthy and can be count on that they do what they say

2.26

3.5

3.25

Most of the time my team receive the appreciation on their work which inspire them to work.

2.23

3.61

3.22

Table 4.3.2 Team Work Effectiveness Analysis

4.3.3 Location Based Differences

No

Question

Mean Value

Team A

Team B

Team C

I have never experienced members’ unavailability due to time difference or working days/Hours conflicts on the occasions that it needed.

2.5

3.26

3

I have has not experienced any communication issues due to language problems or different accent of speaking.

2.63

3.34

3.12

I have members have not faced any difficulties on expressing the opinions due to customs, belief and culture difference of my team members.

3

3.46

3.22

I have not come across any cultural conflict during the project work

2.53

3.76

2.96

I have has minimal impact from country specific rules, regulations and laws.

2.63

3.46

3.06

Table 4.3.3 Location Based Differences Analysis

4.3.4 Use of Technology

No

Question

Mean Value

Team A

Team B

Team C

In my project always the technology (e.g. Communication media, Software) selection is in line with the purpose.

1.76

3.61

3.25

I have not experienced the unavailability of technology (e.g. Network, Telecommunication) when it is needed.

2.56

3.30

2.70

I was provided the necessary trainings in use of available technologies.(e.g. Audio/Video conferencing )

2.6

3.61

3.25

I have not experienced any difficulties of having mutual levels of understanding with the team members due to technology limitations.

2.5

3.42

2.96

Table 4.3.4 Use of Technology Analysis

4.3.5 Project Management (Scope, Time and Cost)

No

Question

Mean Value

Team A

Team B

Team C

My project has a clearly defined Project Scope Statement and WBS (Work Breakdown Structure) which covers overall project requirements.

2.3

3.34

3.25

In my project I have not experienced on involving to activities which is within the scope but has not defining at the initiation or planning levels.

2.4

3.03

3.12

In my project requirements changes happened very rarely and all the project requirement documentations in my project are up to date.

2.23

3.03

3.06

In my project all the deliverables were break down in to task and their sequence of execution has defined properly based on their dependencies.

2.13

3.53

3

In my project always the tasks were allocation based on team members skills with realistic effort estimation.

2.1

3.61

3.41

In my project the project schedule (release schedule) is always on par with the task duration, allocation and resource availability.

2

3.34

3.03

In my project all deadlines were achieved on time and there were not any changes required to the project schedule.

1.93

3.53

3.03

In my project the project budget has defined based on the cost that required for task in all aspects.

3.5

3.57

3.32

It is rare that my project has to spent additional cost that is not defined for budget. (e.g. Cost for working after hour or weekends, cost on additional technologies)

1.96

3.46

2.93

Table 4.3.5 Project Management Analysis

4.4 Hypothesis Analysis

Hypothesis analysis was done by using three teams which categorized based the responders’ organizations. The teams were appointed as Team A, B & C instead of organization name as some of the collected data are organization specific and confidential. A brief introduction to those organizations as given below:

Team A

Team A was selected from a global IT Services organization which uses offshore delivery model to provide IT consulting, technology implementation and application outsourcing services. The organization is currently located their Headquarters in USA and opened their offices throughout US, Europe and Asia. Their Technology Centers are located in US, UK, Hungary, India and Sri Lanka with the over 6500 of employees. The offshore developments are mainly done at Hungary, India and Sri Lanka technology centers. Among the total employees of 65000 around 3500 are working at their technology center in SriLanka. Most of their clients were from US and UK and the project teams were selected with a combination of their employees belong to Hungary, India and Sri Lanka technology centers.

Team B

Team B was selected from a another global IT Services organization which uses offshore delivery model to provide integrated solutions that include business process outsourcing, infrastructure technology, and application services with development as well as applications maintenance and support services. The organization is currently located their Headquarters in India and opened 29 of their offices around the world covering 14 countries including US, UK, Canada, Germany, Netherlands, Switzerland, New Zealand, Australia, Indonesia, Singapore, SriLanka and India. Most of their offshore technology centers are located in Asian countries like India, SriLanka, Philippine, Singapore etc. They have over 40,000 employees and around 1500 of them are working at their offshore office in SriLanka. They also follow the method of combining employees from different technology centers to perform their teams.

Team C

Team C was selected from a global enterprise software company which provides ERP solutions for agile business with range of services that maximize returns on customer investment. They are having a global customer base of 2,000 customers with 500,000 users and have their headquartered in Sweden and have 50 offices around the world. They maintain development centers in Sri Lanka, Poland and operate as a multinational corporation through subsidiaries in the Americas, Europe North, Europe West, Europe Central, and Africa Asia and Pacific. The organization has over 3000 employees around the world and around 1000 of employees working in their SriLankan development center. They too have their delivery model that based on their development centers. So always the project teams in this organization have to work with virtual teams.

The samples from for Team A.B & C were selected from the above organizations as random samples in order to include different responders from across the projects, tracks and platforms.

Hypothesis 1

H1: There is relationship between virtual teams’ communication effectiveness and management of the project.

H01: There is no a relationship between virtual teams’ communication effectiveness and management of the project.

4.4.1 Communication Effectiveness and Management of Project

As raveled from the literature review many researchers have considered Effective Communication as a key success factor in project management of the virtual teams.

For the analysis, the numbers of respondents were considered as representation of the workforce in offshore software development centers. So, the relationship between communication effectiveness and the management of project in virtual teams is graphed as shown in Figure 4.4.1-1.

Figure 4.4.1-1 Relationship of Communication Effectiveness and Management of Project

According to the best fit line of the graph, it is shown that there is a positive relationship between communication effectiveness and management of the project as Y (Independent Variable = Management of Project) tends to increase when X (Depend Variable = Communication Effectiveness) increases. This was further confirmed through the team based analysis which is presented with Appendix B2.

The correlation coefficient value of the relationship is calculated by using SPSS and the output received is shown at Table 4.4.1-1.

Correlations

Communication Effectiveness

Management Of Project

Spearman's rho

Communication Effectiveness

Correlation Coefficient

1.000

.795**

Sig. (2-tailed)

.

.000

N

87

87

Bootstrapb

Bias

.000

-.009

Std. Error

.000

.044

95% Confidence Interval

Lower

1.000

.695

Upper

1.000

.868

Management Of Project

Correlation Coefficient

.795**

1.000

Sig. (2-tailed)

.000

.

N

87

87

Bootstrapb

Bias

-.009

.000

Std. Error

.044

.000

95% Confidence Interval

Lower

.695

1.000

Upper

.868

1.000

**. Correlation is significant at the 0.01 level (2-tailed).

b. Unless otherwise noted, bootstrap results are based on 87 bootstrap samples

Table 4.4.1-1 Non parametric Correlations of Communication Effectiveness and Management of the Project

As per the data in Table 4.4.1-1 significance (Sig. (2-tailed)) is 0.000, which means it is less than the standards 0.05 (0.000 < 0.05). This is further confirmed through the team based analysis which results the correlation coefficient values as shown in Table 4.4.1-2, where all the Teams were having the significance (Sig. (2-tailed)) less than the standard 0.05. (Please refer the Appendix B2 for the team based analysis in detail)

Team

Spearman’s Correlation Coefficient

Significance (Sig. (2-Tailed))

Team A

0.593

.001

Team B

0.779

.000

Team C

0.752

.000

Table 4.4.1-2 Team Based Analysis: Relationship of Communication Effectiveness & Project Management

Therefore the alternate hypothesis is accepted and null hypothesis is rejected. That means,

"There is relationship between virtual teams’ communication effectiveness and management of the project."

Further, based on the spearman’s correlation coefficient value of the teams (Table 4.4.1-2); the correlation is concluded as follow:

Team A: There is a moderate direct correlation between communication effectiveness and the management of project in Team A

Team B: There is a strong direct correlation between communication effectiveness and the management of project in team B

Team C: There is a strong direct correlation between communication effectiveness and the management of project in Team C

Hence, the spearman’s rank correlation coefficient of the relationship for the sample 87 is 0.795, which means the relationship is positive, strong and direct. It is most likely that as one variable increases so will the other or one decreases so will the other.

"There is a Positive, Very Strong and Direct relationship between virtual teams’ communication effectiveness and management of the project."

The mean value of the overall response showed as 3.16 for ‘Communication Effectiveness’ and 2.96 for ‘Management of Project’. So the communication effectiveness and management of the project considered as Neutral in Likert scale as both values closer to 3.

Team

Mean of Communication Effectiveness

Mean of Management of Project

Team A

2.80

2.36

Team B

3.46

3.38

Team C

3.21

3.13

Total Sample

3.16

2.96

Table 4.4.1-3 Mean Values of Communication Effectiveness & Project Management

The team based analysis also gives the figures that closer to 3, as the mean value of both variables. (Table 4.4.1-3) When consider the mean value distribution base on the respondents, most of the values were distributed within the range of 2 - 4. As per the Likert scale it has distributed with in Disagree to Agree scale. (Figure 4.4.1-2)

<Excel Graph>

Figure 4.4.1-2 Communication Effectiveness Vs Management of Project

As shown at Figure 4.4.1.-3, the most of the respondents were responded with in the scale of Neutral and Agree. It shows 24.14% of the respondents believe that their communication effectiveness within the team is not in satisfied level and 32.18% of respondents believe that their communication effectiveness within the team is in satisfied level. There are 40.23% of respondents who believe their communication is in the level of tend to satisfied or dissatisfied.

Figure 4.4.1-3 Communication Effectiveness & Management of Project Mean Value Distribution

But while consider on the contribution of the selected measurements, Completeness, Conciseness, Clarity, Concreteness, Courtesy and Correctness in total sample, all the measurements have contributed within the range of 15% - 18% for the effectiveness of the communication in total sample. (Figure 4.4.1-4) In total sample Conciseness has shown the lowest contribution where the Completeness and Clarity has shown the highest contribution.

As per the Table 4.4.1-3 and Figure 4.4.1-4 the lowest mean value for the communication effectiveness has marked by Team A with value of 11% in Conciseness. Among the selected teams, Team B had an overall highest mean value for communication effectiveness by showing the equal contribution of selected measurements within the range of 16% - 18%. Team C also had a mean value of 3.21 by having the 15% as lowest contribution in Conciseness and 19% of highest contribution of Clarity.

Total Sample

Team A

Team B

Team C

Figure 4.4.1-4 Measurement Contribution for Communication Effectiveness

As per the measurement based analysis (Figure 4.4.1-5) also it shows that Team A is having 23.4% of contribution to conciseness of total sample which is marked as the lowest contribution from a team to measurements while Team B is having the 41.82% of contribution to conciseness of total sample which is marked as the highest contribution from a team to measurements. (Please refer the Appendix B2:4 for the detailed graphs of Measurement Based Analysis)

Figure 4.4.1-5 Contribution of Teams to the Communication Effectiveness of Total Sample

According to the collected qualitative data through interviews the Senior Members, Project Leads and Management also have similar thoughts and beliefs on their communication effectiveness.

As per the reveals during the discussion proved that members of the Team A were facing to communication challenges due to lack of Conciseness and it has become high challenge for them. The followings were stated by the members of the Team A during the interviews.

"Our project has huge number of requirement defects which are pending as clarification from client side." - PM (Project manager) – Team A

The answer for the above statement was found through the discussion with another member of Team A. As she stated,

"We are wasting time for explaining technical things to non technical people in client site during our calls. So no much time to clarify our requirement related issues from client site."

- One of QA Leads (Quality Assurance Lead) - Team A

Though the Team A has issue with Conciseness of their communication, as they believe the Completeness in their written communication has helped them to recover the impact in to some extends. The following statement is a good example for it.

"For us it is easy to communicate via e-mails than calls. Because, in our technical calls we have spent more time on describing the same thing again and again due to inconsistency in domain knowledge. But once we send a mail by explain everything using relevant images and diagrams, the onsite team easily relay." - One of Dev Leads (Software Development Lead) - Team A

The PM of the Team A revealed the secrete of the richness in their written communication as,

"In our company there is training for improving the e-mail writing skills, which is mandatory for all the new joiners those who are fresher to the industry." - PM (Project manager) – Team A

The interviews with Team B members revealed their good practice which helped them to keep their communication alive and effective. As PM of the Team B said,

"As a practice we always share the agenda for the meeting gat the time it schedule. During the meeting also we are stick to the agenda and our coordinator is there for us to alarm when we breaks the schedule." – PM –Team B

A Dev Team Lead stated and QA teams lead confirmed that this method has helped the Team members to save their valuable time and project to save cost on communication.

"As we always know the things that going to discuss at the meetings only the relevant team members can participate and others can do their work without wasting time for attend to each and every meeting." – QA Lead –Team B

"It is good that coordinator is sharing a meeting report with the team after every meeting. So the whole team can be aware on the points that discussed." – Dev Lead – Team B

The discussion with Team C members is shown that they are facing some challenges on the completeness and correctness in their communication. As Dev Lead of Team C stated,

"We are sick of doing rework. All the requirements are changing time to time. No idea the fault is with BA or the client. But we always have to change the implementation accordingly."

– Dev Lead – Team C

"It is a hectic thing. Once we point out a defect Dev says it is not a defect and it is a new requirement. Requirements are changing day by day so we too confuse. " – QA Lead –Team C

"I have noticed that most of the team members were staying late night due to rework introduced by the requirement changes." – PM –Team B

4.4.2 Team Work Effectiveness and Management of Project

Hypothesis 2

H2: There is a relationship between team work effectiveness of the virtual teams and management of the project.

H02: There is no relationship between team work effectiveness of the virtual teams and management of the project.

As raveled from the literature review many researchers have mentioned trust, relationships and cohesion which affect for the effectiveness of the team, as key success factors in virtual teams.

Based on the total response received the relationship between Team Work Effectiveness and the Management of Project in virtual teams is graphed as shown in Figure 4.4.2-1.

Figure 4.4.2-1 Relationship of Team Work Effectiveness and Management of Project

According to the best fit line of the graph, it is shown that there is a positive relationship between team work effectiveness and management of the project as Y (Independent Variable = Management of Project) tends to increase when X (Depend Variable = Communication Effectiveness) increases. This was further confirmed through the team based analysis which is presented with Appendix B3.

The correlation coefficient value of the relationship is calculated by using SPSS and the output received as shown at Table 4.4.2-1.

Correlations

Team Work Effectiveness

Management Of Project

Spearman's rho

Team Work Effectiveness

Correlation Coefficient

1.000

.820**

Sig. (2-tailed)

.

.000

N

87

87

Bootstrapb

Bias

.000

-.012

Std. Error

.000

.042

95% Confidence Interval

Lower

1.000

.688

Upper

1.000

.874

Management Of Project

Correlation Coefficient

.820**

1.000

Sig. (2-tailed)

.000

.

N

87

87

Bootstrapb

Bias

-.012

.000

Std. Error

.042

.000

95% Confidence Interval

Lower

.688

1.000

Upper

.874

1.000

**. Correlation is significant at the 0.01 level (2-tailed).

b. Unless otherwise noted, bootstrap results are based on 87 bootstrap samples

Table 4.4.2-1 Non parametric Correlations of Team Work Effectiveness and Management of the Project

As per the data in Table 4.4.2-1 significance (Sig. (2-tailed)) is 0.000, which means it is less than the standards 0.05 (0.000 < 0.05). This is further confirmed through the team based analysis which results the correlation coefficient values as shown in Table 4.4.2-2, where all the Teams were having the significance (Sig. (2-tailed)) less than the standard 0.05. (Please refer the Appendix B3 for the team based analysis in detail)

Team

Spearman’s Correlation Coefficient

Significance (Sig. (2-Tailed))

Team A

0.506

.004

Team B

0.698

.000

Team C

0.609

.000

Table 4.4.2-2 Team Based Analysis: Relationship of Team work Effectiveness & Project Management

Therefore the alternate hypothesis is accepted and null hypothesis is rejected. That means,

"There is relationship between virtual teams’ team work effectiveness and management of the project."

Further, based on the spearman’s correlation coefficient value of the teams, the correlation is concluded as follow:

Team A: There is a moderate direct correlation between team work effectiveness and the management of project in Team A

Team B: There is a moderate direct correlation between team work effectiveness and the management of project in team B

Team C: There is a moderate direct correlation between team work effectiveness and the management of project in Team C

Hence, the spearman’s rank correlation coefficient of the relationship for the sample 87 is 0.820, which means the relationship is positive, very strong and direct. It is most likely that as one variable increases so will the other or one decreases so will the other.

"There is a Positive, Very Strong and Direct relationship between virtual teams’ team work effectiveness and management of the project."

The mean value of the overall response showed 3.10 for ‘Team Work Effectiveness’ and 2.96 for ‘Management of Project’. So the team work effectiveness and management of the project considered as Neutral in Likert scale as both values closer to 3.

Team

Mean of Team Work Effectiveness

Mean of Management of Project

Team A

2.35

2.36

Team B

3.67

3.38

Team C

3.28

3.13

Total Sample

3.10

2.96

Table 4.4.2-3 Mean Values of Team Work Effectiveness & Project Management

The team based analysis also gives the figure that closer to 3, as the mean value of variables. (Table 4.4.2-3) When consider the mean value distribution base on the respondents, most of the values were distributed within the range of 2 - 4. As per the Likert scale it has distributed with in Disagree to Agree scale. (Figure 4.4.2-2)

<Excel Graph>

Figure 4.4.2-2 Team Work Effectiveness Vs Management of Project

As shown at Figure 4.4.2-3, the most of the respondents were responded with in the scale of Neutral and Agree. It shows 32.18% of the respondents believe that their team work effectiveness is in satisfied level and 14.94% of respondents believe that their team work effectiveness within the team is not in satisfied level. There are 47.13% of respondents who believe their team work is in the level of tend to satisfied or dissatisfied.

Figure 4.4.2-3 Team Work Effectiveness & Management of Project Mean Value Distribution

But while consider on the contribution of the selected measurements, Leadership Quality, Clarification of Role & Responsibilities, Objective Decision-Making, Focus, Cooperation, Trust and Understanding of Human Behavior in total sample, all the measurements have contributed within the range of 13% - 16% for the team work effectiveness in total sample. (Figure 4.4.2-4) In total sample Focus has shown the lowest contribution where the Cooperation has shown the highest contribution.

As per the Table 4.4.2-3 and Figure 4.4.2-4 the lowest mean value for the team work effectiveness has marked by Team A with value of 10% in Focus. Among the selected teams, Team B had an overall highest mean value for communication effectiveness by showing the equal contribution of selected measurements within the range of 14% - 16%. Team C also had a mean value of 3.28 by keeping all the measurements within the range of 14%-15% which can call as exact equal contribution.

Total Sample

Team A

Team B

Team C

Figure 4.4.2-4 Measurement Contribution for Team Work Effectiveness

As per the measurement based analysis (Figure 4.4.2-5) it shows that Team A is having 20.18% of contribution to Focus in total sample which is marked as the lowest team contribution for a measurement. And Team B is having the 41.6% of contribution to Objective Decision-Making of total sample which is marked as the highest contribution from a team to measurements. (Please refer the Appendix B3:4 for the detailed graphs of Measurement Based Analysis)

Figure 4.4.2-5 Contribution of Teams to the Team Work Effectiveness of Total Sample

According to the collected qualitative data through interviews the Senior Members, Project Leads and Management also have similar thoughts and beliefs on their communication effectiveness. As per the reveals during the discussion proved that members of the Team A were facing to communication challenges due to lack of Conciseness and it has become high challenge for them. The followings were stated by the members of the Team A during the interviews.

"It seems that project have huge number of requirement defects. As per the QA and Dev teams most of them are required clarification from client side."

PM (Project manager) – Team A

The answer for the above statement was found through the discussion with another member of Team A. As she stated,

"During the defect triages, it is wasting time for explanation of technical things to non technical people in client site. So we have no much time to get clarify our requirement related issues."

One of QA Leads (Quality Assurance Lead) - Team A

Though the Team A has issue with Conciseness of their communication, as they believe the Completeness in their written communication has helped them to recover the impact in to some extends. The following statement is a good example for it.

"For us it is easy to communicate via e-mails than calls. Because, in our technical calls we have spent more time on describing the same thing again and again due to inconsistency in domain knowledge. But once we send a mail by explain everything using relevant images and diagrams, the onsite team easily relay."

One of Dev Leads (Software Development Lead) - Team A

Hypothesis 3

H3: There is a relationship between location based differences in virtual teams and management of the project.

H03: There is no a relationship between location based differences in virtual teams and management of the project.

4.4.3 Location Based Differences and Management of Project

As raveled from the literature review many researchers have identified location based differences such as time zone differences, Custom & Culture differences and language barriers cause for many challenges in management of the virtual teams.

Based on the responded questioners the relationship between locations based differences and the management of project in virtual teams is graphed as shown in Figure 4.4.3-1.

Figure 4.4.3-1 Relationship of Location Based Differences and Management of Project

According to the best fit line of the graph, it is shown that there is a negative relationship between communication effectiveness and management of the project as Y (Independent Variable = Management of Project) tends to decrease when X (Depend Variable = Communication Effectiveness) increases. This was further confirmed through the team based analysis which is presented with Appendix B4.

The correlation coefficient value of the relationship is calculated by using SPSS and the output received as shown at Table 4.4.3-1.

Correlations

Location Based Differences

Management Of Project

Spearman's rho

Location Based Differences

Correlation Coefficient

1.000

-.777**

Sig. (2-tailed)

.

.000

N

87

87

Bootstrapb

Bias

.000

.010

Std. Error

.000

.045

95% Confidence Interval

Lower

1.000

-.844

Upper

1.000

-.642

Management Of Project

Correlation Coefficient

-.777**

1.000

Sig. (2-tailed)

.000

.

N

87

87

Bootstrapb

Bias

.010

.000

Std. Error

.045

.000

95% Confidence Interval

Lower

-.844

1.000

Upper

-.642

1.000

**. Correlation is significant at the 0.01 level (2-tailed).

b. Unless otherwise noted, bootstrap results are based on 87 bootstrap samples

Table 4.4.3-1 Non parametric Correlations of Location Based Differences and Management of the Project

As per the data in Table 4.4.3-1 significance (Sig. (2-tailed)) is 0.000, which means it is less than the standards 0.05 (0.000 < 0.05). This is further confirmed through the team based analysis which results the correlation coefficient values as shown in Table 4.4.3-2, where all the Teams were having the significance (Sig. (2-tailed)) less than the standard 0.05. (Please refer the Appendix B4 for the team based analysis in detail)

Team

Spearman’s Correlation Coefficient

Significance (Sig. (2-Tailed))

Team A

-.659

.001

Team B

-.801

.000

Team C

-.748

.000

Table 4.4.3-2 Team Based Analysis: Relationship of Location Based Differences & Project Management

Therefore the alternate hypothesis is accepted and null hypothesis is rejected. That means,

"There is relationship between virtual teams’ location based differences and management of the project."

Further, based on the spearman’s correlation coefficient value of the teams, the correlation is concluded as follow:

Team A: There is a moderately strong inverse correlation between location based differences and the management of project in Team A

Team B: There is a very strong inverse correlation between location based differences and the management of project in team B

Team C: There is a very strong inverse correlation between location based differences and the management of project in Team C

Hence, the spearman’s rank correlation coefficient of the relationship for the sample 87 is (-0.777), which means the relationship is negative, very strong and inverse. It is most likely that as one variable increases the other decreases or vice versa.

"There is a Negative, Very Strong and Inverse relationship between virtual teams’ location based differences and management of the project."

.

The mean value of the overall response showed 2.93 for ‘Location Based Differences’ and 2.96 for ‘Management of Project’. So the location based differences and management of the project considered as Neutral in Likert scale as both values closer to 3.

Team

Mean of Location Based Differences

Mean of Management of Project

Team A

3.34

2.36

Team B

2.54

3.38

Team C

2.92

3.13

Total Sample

2.93

2.96

Table 4.4.3-3 Mean Values of Location Based Differences & Project Management

The team based analysis also gives the figure that closer to 3, as the mean value of variables. (Table 4.4.3-3) When consider the mean value distribution base on the respondents, most of the values were distributed within the range of 2 - 4. As per the Likert scale it has distributed with in Disagree to Agree scale. (Figure 4.4.3-2)

<Excel Graph>

Figure 4.4.3-2 Location Based Differences Vs Management of Project

As shown at Figure 4.4.3.-3, the most of the respondents were responded with in the scale of Disagree and Neutral. It shows 22.29% of the respondents agreed that they are facing the location based differences within the team and 36.44% of respondents believe that their teams do not face location based differences. There are 42.53% of respondents who believe their location based barriers are in the level of tend to affect or not for their teams.

Figure 4.4.3-3 Location Based Differences & Management of Project Mean Value Distribution

But while consider on the contribution of the selected measurements, Team Members’ Unavailability, Communication Difficulties, Difficulties of Expressing Opinions, Behavioral Difference and Difference in Legislation in total sample, all the measurements have contributed within the range of 19% - 21% for the location based differences in total sample. (Figure 4.4.3-4) In total sample Difficulties in Expressing Opinion has shown the lowest contribution where the Team members’ unavailability has shown the highest contribution.

As per the Table 4.4.3-3 and Figure 4.4.3-4 the lowest mean value for the communication effectiveness has marked by Team A and Team B with the value of 18% for the measurements Difficulties of expressing opinion and Behavioral differences. The highest contribution of 21% has shown by all the teams for different measurements. Team A is having 21% on Team member’s unavailability & Behavioral differences, Team B is having it on Team member’s unavailability & communication difficulties and Team C is having it on Behavioral differences.

Total Sample

Team A

Team B

Team C

Figure 4.4.3-4 Measurement Combination for Location Based Differences

As per the measurement based analysis (Figure 4.4.3-5) it shows that Team A is having 39.71% of contribution to behavioral differences of total sample which is marked as the highest team contribution for a measurement while Team B is having 25.55% of contribution to behavioral differences of total sample which is marked as the lowest team contribution for a measurement. (Please refer the Appendix B4:4 for the detailed graphs of Measurement Based Analysis)

Figure 4.4.3-5 Contribution of Teams to the Location Based Differences of Total Sample

According to the collected qualitative data through interviews the Senior Members, Project Leads and Management also have similar thoughts and beliefs on their communication effectiveness. As per the reveals during the discussion proved that members of the Team A were facing to communication challenges due to lack of Conciseness and it has become high challenge for them. The followings were stated by the members of the Team A during the interviews.

"It seems that project have huge number of requirement defects. As per the QA and Dev teams most of them are required clarification from client side."

PM (Project manager) – Team A

The answer for the above statement was found through the discussion with another member of Team A. As she stated,

"During the defect triages, it is wasting time for explanation of technical things to non technical people in client site. So we have no much time to get clarify our requirement related issues."

One of QA Leads (Quality Assurance Lead) - Team A

Though the Team A has issue with Conciseness of their communication, as they believe the Completeness in their written communication has helped them to recover the impact in to some extends. The following statement is a good example for it.

"For us it is easy to communicate via e-mails than calls. Because, in our technical calls we have spent more time on describing the same thing again and again due to inconsistency in domain knowledge. But once we send a mail by explain everything using relevant images and diagrams, the onsite team easily relay."

One of Dev Leads (Software Development Lead) - Team A

Hypothesis 4

H4: There is a relationship between the uses of technology in virtual teams and management of the project.

H04: There is no a relationship between the uses of technology in virtual teams and management of the project.

4.4.4 Use of Technology and Management of Project

As raveled from the literature review ICT plays a major role in virtual teams and some researchers have stated having virtual teams is a dream if the ICT does not exist.

Based on the received response the relationship between use of technology and the management of project in virtual teams is graphed as shown in Figure 4.4.4-1.

Figure 4.4.4-1 Relationship of Use of Technology and Management of Project

According to the best fit line of the graph, it is shown that there is a positive relationship between use of technology and management of the project as Y (Independent Variable = Management of Project) tends to increase when X (Depend Variable = use of technology) increases. This was further confirmed through the team based analysis which is presented with Appendix B5.

The correlation coefficient value of the relationship is calculated by using SPSS and the output received as shown at Table 4.4.4-1.

Correlations

Use of Technology

Management Of Project

Spearman's rho

Use of Technology

Correlation Coefficient

1.000

.867**

Sig. (2-tailed)

.

.000

N

87

87

Bootstrapb

Bias

.000

-.004

Std. Error

.000

.028

95% Confidence Interval

Lower

1.000

.796

Upper

1.000

.913

Management Of Project

Correlation Coefficient

.867**

1.000

Sig. (2-tailed)

.000

.

N

87

87

Bootstrapb

Bias

-.004

.000

Std. Error

.028

.000

95% Confidence Interval

Lower

.796

1.000

Upper

.913

1.000

**. Correlation is significant at the 0.01 level (2-tailed).

b. Unless otherwise noted, bootstrap results are based on 87 bootstrap samples

Table 4.4.4-1 Non parametric Correlations of Use of Technology and Management of the Project

As per the data in Table 4.4.4-1 significance (Sig. (2-tailed)) is 0.000, which means it is less than the standards 0.05 (0.000 < 0.05). This is further confirmed through the team based analysis which results the correlation coefficient values as shown in Table 4.4.4-2, where all the Teams were having the significance (Sig. (2-tailed)) less than the standard 0.05. (Please refer the Appendix B5 for the team based analysis in detail)

Team

Spearman’s Correlation Coefficient

Significance (Sig. (2-Tailed))

Team A

0.606

.001

Team B

0.826

.000

Team C

0.643

.000

Table 4.4.4-2 Team Based Analysis: Relationship of Use of Technology & Project Management

Therefore the alternate hypothesis is accepted and null hypothesis is rejected. That means,

"There is relationship between virtual teams’ use of technology and management of the project."

Further, based on the spearman’s correlation coefficient value of the teams, the correlation is concluded as follow:

Team A: There is a moderate direct correlation between use of technology and the management of project in Team A

Team B: There is a strong direct correlation between use of technology and the management of project in team B

Team C: There is a moderate direct correlation between use of technology and the management of project in Team C

Hence, the spearman’s rank correlation coefficient of the relationship for the sample 87 is 0.867, which means the relationship is positive, strong and direct. It is most likely that as one variable increases so will the other or one decreases so will the other.

"There is a Positive, Strong and Direct relationship between virtual teams’ use of technology and management of the project."

The mean value of the overall response showed 2.96 for ‘Use of Technology’ and 2.96 for ‘Management of Project’. So the use of technology and management of the project considered as Neutral in Likert scale as both values closer to 3.

Team

Mean of Use of Technology

Mean of Management of Project

Team A

2.35

2.36

Team B

3.49

3.38

Team C

3.04

3.13

Total Sample

2.96

2.96

Table 4.4.4-3 Mean Values of Use of Technology & Project Management

The team based analysis also gives the figures that closer to 3, as the mean value of both variables. (Table 4.4.4-3) When consider the mean value distribution base on the respondents, most of the values were distributed within the range of 2 - 4. As per the Likert scale it has distributed with in Disagree to Agree scale. (Figure 4.4.4-2)

<Excel Graph>

Figure 4.4.4-2 Use of Technology Vs Management of Project

As shown at Figure 4.4.4.-3, the most of the respondents were responded with in the scale of Disagree to Neutral. It shows 34.48% of the respondents believe that their use of technology within the team is not in satisfied level and 21.84% of respondents believe that their use of technology within the team is in satisfied level. There are 39.08% of respondents who believe their use of technology is in the level of tend to satisfied or dissatisfied.

Figure 4.4.4-3 Use of Technology & Management of Project Mean Value Distribution

But while consider on the contribution of the selected measurements, Media Selection, Availability, Proficiency and Richness in total sample, all the measurements have contributed within the range of 24% - 27% for the use of technology in total sample. (Figure 4.4.4-4) In total sample Medial selection and Availability has shown the lowest contribution where the Proficiency has shown the highest contribution.

As per the Table 4.4.4-3 and Figure 4.4.4-4 the lowest mean value for the use of technology has marked by Team A with value of 19% in Media selection. Among the selected teams, Team B had an overall highest mean value for communication effectiveness by showing the contribution of selected measurements within the range of 24% - 26%. Team C also had a mean value of 3.04 by having the 22% as lowest contribution in availability and 27% of highest contribution in medial selection and proficiency.

Total Sample

Team A

Team B

Team C

Figure 4.4.4-4 Measurement Combination for Use of Technology

As per the measurement based analysis (Figure 4.4.4-5) it shows that Team A is having 20.45% of contribution to media selection of total sample which is marked as the lowest team contribution for a measurement while Team B is having the 43.39% of contribution to proficiency of total sample which is marked as the highest team contribution for a measurement. (Please refer the Appendix B5:4 for the detailed graphs of Measurement Based Analysis)

Figure 4.4.4-5 Contribution of Teams to the Use of Technology of Total Sample

According to the collected qualitative data through interviews the Senior Members, Project Leads and Management also have similar thoughts and beliefs on their communication effectiveness. As per the reveals during the discussion proved that members of the Team A were facing to communication challenges due to lack of Conciseness and it has become high challenge for them. The followings were stated by the members of the Team A during the interviews.

"It seems that project have huge number of requirement defects. As per the QA and Dev teams most of them are required clarification from client side."

PM (Project manager) – Team A

The answer for the above statement was found through the discussion with another member of Team A. As she stated,

"During the defect triages, it is wasting time for explanation of technical things to non technical people in client site. So we have no much time to get clarify our requirement related issues."

One of QA Leads (Quality Assurance Lead) - Team A

Though the Team A has issue with Conciseness of their communication, as they believe the Completeness in their written communication has helped them to recover the impact in to some extends. The following statement is a good example for it.

"For us it is easy to communicate via e-mails than calls. Because, in our technical calls we have spent more time on describing the same thing again and again due to inconsistency in domain knowledge. But once we send a mail by explain everything using relevant images and diagrams, the onsite team easily relay."

One of Dev Leads (Software Development Lead) - Team A