Print Email Download Reference This Send to Kindle Reddit This
submit to reddit

Effective Virtual Teams For New Product Development Management Essay

Abstract:

Literature shows the factors that impact on the effectiveness of virtual teams for new product development, are still ambiguous. To address this problem, we developed a research design that included a literature review, a preliminary model and field survey. The literature identified factors which impact on the effectiveness of virtual teams. These factors were then modified by a field survey. We explore the relationship between knowledge worker (people), process and technology in virtual teams. The results of the study suggest that technology and process are tightly correlated and need to be considered early in virtual teams. Software as a service, web solution, report generator and tracking system in effective virtual teams should consider for leading such a new phenomena.

Keywords

Virtual teams, Collaboration, Questionnaires, Communication; Information; Integration; Performance; Success; Cross-Functional Teams; Product Development;

Introduction

Nowadays, a virtual team allows work to be carried out over computer networks and reduces the need for teams to be collocated. Virtual teams are defined as “small temporary groups of geographically, organizationally and/or time dispersed knowledge workers who coordinate their work, predominantly with electronic information and communication technologies to carry out one or more organization tasks” (Nader Ale Ebrahim et al., 2009b). We are becoming more virtual all the time!” is heard in many global corporations today (Chudoba et al., 2005). On the other hand, new product development (NPD) is widely recognized as a key to corporate prosperity (Lam et al., 2007). Different products may need different processes, a new product idea needs to be conceived, selected, developed, tested and launched to the market (Martinez-Sanchez et al., 2006). The specialized skills and talents required for the development of new products often reside (and develop) locally in pockets of excellence around the company or even around the world. Firms, therefore, have no choice but to disperse their new product units to access such dispersed knowledge and skills (Kratzer et al., 2005). As a result, firms are finding that internal development of all technology needed for new products and processes are difficult or impossible. They must increasingly acquire technology from external sources (Stock & Tatikonda, 2004).

Virtualization in NPD has recently started to make serious headway due to developments in technology - virtuality in NPD which is now technically possible (Leenders et al., 2003). As product development becomes more complex, supply chain also have to collaborate more closely than in the past. These kinds of collaborations almost always involve individuals from different locations, so virtual team working supported by information technology (IT), offers considerable potential benefits (Anderson et al., 2007). Although the use of the internet in NPD have received notable attention in the literature, very little is written about collaborative tool and effective virtual teams for NPD (Nader Ale Ebrahim et al., 2009).

This paper is structured as follows. The motivation for the study is initially described. Next, we draw on prior research to explain the derivation of the items that comprise the effectiveness of virtual teams. Then we present our methods and results of our analyses. The paper concludes with a discussion and future guidelines.

What Is Needed for Effective Virtual Team?

A review of the literature shows the factors that influences the effectiveness of virtual teams are still ambiguous (Nader Ale Ebrahim et al., 2009b). Most of the acknowledged challenges of an effective virtual team working, focus on ensuring good communication among all members of the distributed team (Anderson et al., 2007). For example, Jarvenpaa and Leidner (1999) found that regular and timely communication feedback was a key to building trust and commitment in distributed teams. A study by Lin et al. (2008) indicates that social dimensional factors need to be considered early in the virtual team creation process and are critical to the effectiveness of the team. Communication is a tool that directly influences the social dimensions of the team and in addition the performance of the team has a positive impact on satisfaction with the virtual team.

For teams moving from co-location to virtual environments, an ability to adapt and change can be a long process riddled with trial and error scenarios. This process is seen as necessary to encourage effective virtual teams (Kirkman et al., 2002). Despite weak ties between virtual team members, ensuring lateral communication may be adequate for effective virtual team performance. In terms of implementation, lateral communication in both virtual context and composition teams can be increased by reducing the hierarchical structure of the team (i.e. a flatter reporting structure and/or decentralization) and the use of enabling computer-mediated communication tools(Wong & Burton, 2000).

Malhotra and Majchrzak’s (2004) study of 54 effective virtual teams found that creating a state of shared understanding about goals and objectives, task requirements and interdependencies, roles and responsibilities, and member expertise had a positive effect on output quality. As criteria, effectiveness ratings were Hertel et al. (2005) collected from the team managers both at the individual and at the team level. The results of the field study showed good reliability of the task work-related attributes, teamwork-related attributes, and attributes related to tele-cooperative work.

Shachaf and Hara (2005) suggests four dimensions of effective virtual team leadership:

Communication (the leader provides continuous feedback, engages in regular and prompt communication, and clarifies tasks);

Understanding (the leader is sensitive to schedules of members, appreciates their opinions and suggestions, cares about member’s problems, gets to know them, and expresses a personal interest in them);

Role clarity (the leader clearly defines responsibilities of all members, exercises authority, and mentors virtual team members); and

Leadership attitude (the leader is assertive yet not too “bossy,” caring, relates to members at their own levels, and maintains a consistent attitude over the life of the project).

Bal et al. (1999; 2001b) by observation and interview identified 12 elements for effective virtual team working. As illustrated in Figure 1. The Bal and Gundry (1999; 2001b) model is used as the basic framework in this paper.

Figure 1 Model for effective virtual team working (Source (Bal & Gundry, 1999))

VIRTUAL TEAM WORKING: TECHNOLOGY POINT OF VIEW

Selection: Simple transmission of information from a point A to a point B is not enough; the virtual environment presents significant challenges to effective communication (Walvoord et al., 2008). Being equipped with even the most advanced technologies is not adequate to make a virtual team effective, since the internal group dynamics and external support mechanisms must also be present for a team to succeed in the virtual world (Lurey & Raisinghani, 2001). Information richness seemed to be the most important criterion for technology selection; and the greatest impediment to the effectiveness of virtual teams was the implementation of technology (Mikkola et al., 2005). Virtual teams are technology-mediated groups of people from different discipline that work on common tasks (Dekker et al., 2008). So the way the technology is implemented seems to make the virtual team outcome more or less likely (Anderson et al., 2007). Table 1 matrix assists the virtual team facilitator in choosing the appropriate technology based upon the purpose of the meeting.

Table 1 Tools for virtual teams ( Adopted from Thissen et al. (2007))

Tool

Examples

Uses and Advantages

Immediacy

Sensory Modes

Instant Messaging and

Chat

• Yahoo Messenger

• MSN Messenger

• AOL Instant Messenger

• Skype

• Instant interaction

• Less intrusive than a phone call

• View who is available

• Low cost

• Low setup effort

• Synchronous or asynchronous

• Visual

• Text and limited

graphics

Groupware /

Shared Services

• Lotus Notes

• Microsoft Exchange

• Novell Groupwise

• Calendars

• Contact Lists

• Arrange meetings

• Cost and setup effort vary

• Asynchronous

• Visual

Remote Access and Control

• NetMeeting

• WebEx

• Remote Desktop

• pcAnywhere

• User controls a PC without being onsite

• Cost varies

• Setup varies

• Synchronous

• Visual

• Audio

• Tactile

Web Conferencing

• NetMeeting

• WebEx

• Meeting Space

• GoToMeeting

• Live audio

• Dynamic video

• Whiteboard

• Application sharing

• Moderate cost and setup effort

• Synchronous

• Visual

• Unlimited graphics

• Optional audio

File Transfer

• File Transfer Protocol (FTP)

• Collaborative Websites

• Intranets

• Share files of any type

• Cost varies

• Moderate setup effort

• Asynchronous

• Varies with file

content

Email

• Numerous vendors and • free applications

• Send messages or files

• Cost and setup effort vary

• Asynchronous

• Visual

• Audio in attached

files

Telephone

• “Plain Old Telephone Service” (POTS)

• Voice Over Internet Protocol (VOIP)

• Direct calls

• Conference calls

• Cost varies

• Low setup effort

• Synchronous

• Asynchronous for voice mail

• Audio

Location: Virtual team allowed organizations to access the most qualified individuals for a particular job regardless of their location and provide greater flexibility to individuals working from home or on the road (Bell & Kozlowski, 2002). Table 2 illustrates the relationship between tool, time and space in virtual teams.

Training: Suggestions for the training of remote managers and virtual team development can be found in (Hertel et al., 2005). The results of Anderson et al. (2007) systematic lab study confirmed many of the observations including explicit preparation and training for virtual teams as a way of working collaboratively. Fuller et al., (2006) indicated that in the case of computer collective efficacy, computer training related to more advanced skills sets may be useful in building virtual team efficacy. Hertel et al. (2005)suggested that training led to increased cohesiveness and team satisfaction.

Table 2 Time /Space matrix (Adapted from Bouchard and Cassivi (2004))

Same space

Different space

Same time

Synchronous

Face-to-face meeting, Brainstorming,

Vote, PC and projector Electronic white

board, GDSS, Chat

Chat, Tele-conference, Video-conference,

Liaison satellite, Audio-conference, Shared white

board, Shared application

Different time

Asynchronous

Team room, Document management

system, Discussion forum, E-mail,

Workflow, Project management

E-mail, Workflow, Document sharing ,

Discussion forum, Group agenda Cooperative

hypertext and organizational memory, Version

control Meeting scheduler

Security: Virtual team working to involve exchange and manipulation of sensitive information and data through the Internet, therefore, security is always an important issue of concern (Bal & Teo, 2001b). Team leaders should identify the special technological and security level needs of the virtual team and their team members (Hunsaker & Hunsaker, 2008).

VIRTUAL TEAM WORKING: PEOPLE POINT OF VIEW

Team selection: Team selection is a key factor which differentiates successful teams from unsuccessful ones. Virtual teams can be designed to include the people most suited for a particular project (Bell & Kozlowski, 2002). In addition to makeing sure that the project is clearly defined, outcome priorities are established, and a supportive team climate, virtual team needs to select members with the necessary skills (Hunsaker & Hunsaker, 2008). Selection of virtual team members is particularly difficult because of the geographical and organizational separation involved (Bal & Gundry, 1999).

Reward structure: The development of a fair and motivating reward system is another important issue at the beginning of virtual teamwork (Bal & Teo, 2001a; Hertel et al., 2005). Virtual team performance must be recognized and rewarded (Bal & Gundry, 1999). Lurey and Raisinghani (2001) in a survey in an effort to determine the factors that contribute to the success of a virtual team, found that reward systems ranked strongly among the external support mechanisms for virtual teams.

Meeting training: Comparing teams with little and extensive training, Bal and Gundry (1999) observed a significant drop in performance as both teams went live using the system. However, the latter then improved its performance at a faster rate than the former. Training is a key aspect that cannot be neglected in team building. Virtual team members require different types of training compared to ordinary teams. The training includes self-managing skills, communication and meeting training, project management skills, technology training, etc.(Bal & Teo, 2001b).

Specify an objective: While direct leadership strategies are possible in conventional teams, members of virtual teams might be managed more effectively by empowerment and by delegating managerial functions to the members (Hertel et al., 2005). Such an approach changes the role of a team manager from traditional controlling into more coaching and moderating functions (Kayworth & Leidner, 2002). Virtual team leaders should identify commonalities among members early on, while focusing the team on achieving key performance objectives and providing a clear context for recognizing team success.

VIRTUAL TEAM WORKING: PROCESS POINT OF VIEW

Alignment: The company’s processes need to be re-aligned with the capabilities of virtual teams contrary to face to face teams. This involves an understanding of the virtual team processes and the existing processes (Bal & Gundry, 1999). However, the key elements in knowledge sharing are not only the hardware and software, but also the ability and willingness of team members to actively participate in the knowledge sharing process (Rosen et al., 2007).

Meeting structure: Proximity enables team members to engage in informal work (Furst et al., 2004). Virtual team members are more likely to treat one another formally, and less likely to reciprocate requests from one another (Wong & Burton, 2000). Shin (2005) argued that lack of physical interactions and informal relationships decrease the cohesiveness of virtual teams. Formal practices and routines designed to formally structure the task, was reported to lead to higher quality output of virtual teams (Massey et al., 2003). The physical absence of a formal leader exacerbates the lack of extrinsic motivation (Kayworth & Leidner, 2002). In virtual teams that rarely meet face-to-face, team leaders often have no choice but to implement a formal team structure. Synchronous written documents helped virtual teams overcome challenges associated with spoken language, and this enabled teams to overcome challenges associated with asynchronous and lean written communication (Shachaf, 2008).

Performance measurement: Work on the performance of virtual teams by Kirkman and Rosen, et al. (2004) demonstrates a positive correlation between empowerment and virtual team performance. High-performance teams are distinguished by passionate dedication to goals, identification and emotional bonding among team members, and a balance between unity and respect for individual differences.

Team facilitation: Virtual team members must have clear roles and accountabilities. Lack of visibility may cause virtual team members to feel less accountable for results; therefore, explicit facilitation of teamwork takes on heightened importance for virtual teams. Temporal coordination mechanisms such as scheduling deadlines and coordinating the pace of effort are recommended to increase vigilance and accountability (Massey et al., 2003).

New Product Development and Virtuality

Product development is defined by different researchers is slightly different ways, but generally it is the process that covers product design, production system design and product introduction processes and start of production (Johansen, 2005). New product development (NPD) has long been recognized as one of the corporate core functions (Huang et al., 2004). The rate of market and technological changes has accelerated in the past years and this turbulent environment requires new methods and techniques to bring successful new products to the marketplace (González & Palacios, 2002). Particularly for companies with short product life cycles, it is important to quickly and safely develop new products and new product platforms that fulfill reasonable demands on quality, performance, and cost (Ottosson, 2004). The world market requires short product development times (Starbek & Grum, 2002). Therefore, in order to successfully and efficiently get all the experience needed in developing new products and services, more and more organizations are forced to move from traditional face-to-face teams to virtual teams or adopt a combination between the two types of teams (Precup et al., 2006). Given the complexities involved in organizing face-to-face interactions among team members and the advancements in electronic communication technologies, firms are turning toward employing virtual NPD teams (Badrinarayanan & Arnett, 2008; Jacobsa et al., 2005; Schmidt et al., 2001). New product development requires the collaboration of new product team members both within and outside the firm (Martinez-Sanchez et al., 2006; McDonough et al., 2001; Ozer, 2000). NPD teams are necessary in most businesses (Leenders et al., 2003). In addition, the pressure of globalization competition companies faced increased pressures to build critical mass, reach new markets, and plug skill gaps , NPD efforts are increasingly being pursued across multiple nations through all forms of organizational arrangements (Cummings & Teng, 2003). Given the resulting differences in time zones and physical distances in such efforts, virtual NPD projects are receiving increasing attention (McDonough et al., 2001). The use of virtual teams for new product development is rapidly growing and organizations can be dependent on it to sustain competitive advantage (Taifi, 2007). So, virtual teams provide valuable input for new product development (Nader Ale Ebrahim et al., 2009a).

Primary Models and Hypotheses

We adapted from Bal and Gundry (1999; 2001b), a new primary model with respect to the requirements of the company in determining the appropriate design tools and methods for an effective new product development in virtual teams (Figure 2).

Measure the relationships between all components of the model are critical to this model, and are built hypothesizes. Special attention is paid to knowledge worker, technology and process point of view in virtual teams.

HYPOTHESES

Clearly, throughout a review of the existing literature, there remains a gap with respect to the requirements of the company in determining the appropriate design tools and methods for an effective new product development in virtual teams. This research proposes the following hypotheses in order to collects the requirements:

H1. Technology is positively related to process in virtual teams.

H2. Technology is positively related to the knowledge workers in virtual teams.

H3. The process and knowledge worker is positively correlated in virtual teams.

H4. There is not any significant difference between the origins of virtual teams.

Figure 2 The preliminary model for evaluating the effectiveness of virtual teams

Research Methodology and Data Collection

To test the hypotheses, we conducted a web-based survey mainly conducting Malaysian and Iranian Manufacturing companies, in a random sample of small and medium enterprises. A survey was developed to collect the data. A Likert scale from 1 to 5 was used. This set up gave respondents a series of attitude dimensions. For each dimension, the respondent was asked whether, and how strongly, they agree or disagree to each dimension using a point rating scale. The questionnaire was emailed to the managing director, R&D manager, the new product development manager, project and design manager and appropriate people who were most familiar with the R&D activities in the firm. The rapid expansion of Internet users has given web-based surveys the potential to become a powerful tool in survey research (Sills & Song, 2002). Denscombe (2006) findings encourage social researchers to use web-based questionnaires with confidence and the data produced by web-based questionnaires is equivalent to that produced by paper-based questionnaires. Other authors emphasized that the data provided by Internet methods are of at least as good quality as those provided by traditional paper-and-pencil methods (Deutskens et al., 2006; Gosling et al., 2004). Invitation e-mails were sent to each respondent, reaching 1500 valid email accounts, with reminders following one month later. 240 enterprises submitted responses, for an overall response rate of 12%. Table 3 presents respondent demographics (missing data deducted).

Table 3 Frequency Distributions of Demographic Variables (N=240)

Variable

Frequency distribution N (%)

Gender

Male

202 (85.6)

Female

34 (14.4)

Country

Iran

136 (56.7)

Malaysia

74 (30.8)

Others (Developing)

15 (6.2)

Others (Developed)

15 (6.2)

Age group

Up to 21

2 (0.9)

21-34

103 (44.6)

35-49

101 (43.7)

50-64

23 (10.0)

Over 65

2 (0.9)

Job Roles

Managing director

51 (22.7)

R&D Manager

25 (11.1)

New Product Development Manager

27 (12.0)

Project Manager

43 (19.1)

Design manager

7 (3.1)

Others

72 (32.0)

Main Business

Automotive/vehicle and components

89 (37.1)

Electronic products and components

30 (12.5)

Fabricated metal products

13 (5.4)

Electrical machinery, apparatus, appliances, or supplies

12 (5.0)

Machinery/ Industrial equipment

9 (3.8)

Home appliances

12 (5.0)

Pharmaceutical or Chemical products (including cosmetics, paints)

4 (1.7)

Paper products

4 (1.7)

Plastic products

3 (1.2)

Food and Food packaging

1 (0.4)

Instrumentation equipment

4 (1.7)

Textile

2 (0.8)

Oil & Gas

11 (4.6)

Education

14 (5.8)

Others

32 (13.3)

Analysis and Results

In the case of reliability analysis, Cronbach’s Alpha (Cronbach, 1951) was employed to measure internal consistency of each construct. A reliability test was carried out to ensure that the research finding have the ability to provide consistence results. As shown in Table 4, all the iteams with Cronbach’s α greater than 0.6 were included in the analysis and the rest omited from analysis. In general, the reliability of the questionnaire’s instruments is acceptable.

Table 4 Summary of the final measures and reliabilities

Factor and variable name

Items

Mean*

Std. Deviation

Corrected Item-Total Correlation

Cronbach's Alpha if Item Deleted

Knowledge worker (N=218)

Pe1

Working together

4.037

1.029

0.560

0.872

Pe2

Interaction from inside

3.995

0.912

0.641

0.867

Pe3

Interaction from outside

3.824

1.001

0.634

0.867

Pe4

Interact with colleagues

3.982

0.991

0.649

0.866

Pe5

Online training and e-learning

3.401

1.143

0.597

0.87

Pe6

Consulting service

3.472

0.998

0.624

0.868

Pe7

Collaborating and making decisions with co-workers or supplier

3.863

0.943

0.642

0.867

Pe8

Facilitates cooperation between employees

3.876

0.917

0.651

0.867

Pe9

Facilitates introduction of new employees

3.553

1.079

0.654

0.866

Pe10

Facilitates the management of NPD project

3.706

1.014

0.654

0.866

Pe11

Is used by the competitor

3.106

1.238

0.301

0.893

Process (N=211)

Pr1

Project control (such as Intranet based project status tracking system)

3.64

1.101

0.650

0.928

Pr2

Project reporting system (such as MS-Project reporting system)

3.82

1.026

0.666

0.927

Pr3

Making business together

3.648

0.943

0.627

0.928

Pr4

Reduce traveling time and cost

3.862

1.024

0.722

0.925

Pr5

Reduces the number of working hours need to solve the task

3.827

1.008

0.725

0.925

Pr6

Collaborative solutions

3.701

0.916

0.694

0.926

Pr7

Facilitates data collection in new product development project

3.813

0.952

0.744

0.924

Pr8

Interact with customers for gathering new product features

3.83

0.973

0.674

0.926

Pr9

Provide quantities answer

3.384

0.985

0.664

0.927

Pr10

Generate an easy interpret answer

3.333

0.981

0.642

0.927

Pr11

Ease of generating reports

3.678

1.028

0.740

0.924

Pr12

Ease of data entry

3.775

0.937

0.737

0.924

Pr13

Ability to accommodate multiple users

3.905

1.019

0.667

0.927

Technology (N=218)

Te1

Use internet and electronic mail

4.202

0.986

0.528

0.945

Te2

Online meeting on need basis

3.535

1.13

0.764

0.941

Te3

Web conferencing

3.381

1.17

0.778

0.941

Te4

Seminar on the Web

3.134

1.172

0.742

0.942

Te5

Shared work spaces

3.507

1.063

0.749

0.942

Te6

Video conferencing

3.172

1.161

0.737

0.942

Te7

Audio conferencing

3.221

1.146

0.735

0.942

Te8

Online presentations

3.453

1.107

0.809

0.941

Te9

Share documents (off line)

3.601

1.075

0.637

0.944

Te10

Share what’s on your computer desktop with people in other locations (in real time)

3.196

1.206

0.577

0.945

Te11

Do not install engineering software (get service through web browser)

3.179

1.211

0.590

0.945

Te12

Access service from any computer (in Network)

3.542

1.041

0.688

0.943

Te13

Standard phone service and hybrid services

3.576

1.07

0.511

0.946

Te14

Access shared files anytime, from any computer

3.686

1.01

0.625

0.944

Te15

Web database

3.649

0.995

0.704

0.943

Te16

Provide instant collaboration

3.595

1.037

0.654

0.943

Te17

Software as a service (eliminating the need to install and run the application on the own computer)

3.531

1.07

0.666

0.943

Te18

Virtual research centre for product development

3.455

1.078

0.681

0.943

Te19

Can be integrated/compatible with the other tools and systems

3.688

1.139

0.613

0.944

*Frequency values - 1: Not important; 2: Slightly important; 3: Important; 4: Quite important; 5: Extremely important

In order to conclude whether the partial correlation of the knowledge workers, variables were small, the Bartlett’s Chi-square test of Sphericity and Kaiser-Meyer-Olkin (KMO) was used to measure sampling adequacy.(Fathian et al., 2008). Table 5 summarizes the results of KMO, which is 0.878 and significant value for Bartlett's test is less than 0.05, which means there is a good correlation.

Table 5 KMO and Bartlett's Test results

Kaiser-Meyer-Olkin Measure of Sampling Adequacy.

0. 878

Bartlett's Test of Sphericity

Approx. Chi-Square

679.744

df

28

Sig.

.000

An exploratory factor analysis was conducted on eight knowledge worker factors after deducteing Pe1, Pe5 and Pe11 which had Cronbach’s α less than 0.6. Using a Principle Component Analysis with a Varimax Rotation and an Eigenvalue of 1 as the cut-off point (Akgün et al., 2008) and an absolute value of a loading greater than 0.5 (Fathian et al., 2008). Factor loading shows only one component extracted. So, all eight items in the knowledge workers can be grouped into a single factor.

The same procedures were performed on process and technology factors. The items and their factor loadings after Exploratory Factor Analysis, Eigenvalue, and percentage of variance, are shown in Table 6 , Table 7, Table 8 and Table 9. The 13 process items and the 15 technology items are divided into two different groups, which had an Eigenvalue greater than one.

Table 6 Factor analysis results on 13 process items

Component

Initial Eigenvalues

Rotation Sums of Squared Loadings

Total

% of Variance

Cumulative %

Total

% of Variance

Cumulative %

1

7.158

55.062

55.062

4.255

32.733

32.733

2

1.126

8.662

63.724

4.029

30.991

63.724

3

.951

7.314

71.039

4

.737

5.670

76.708

5

.544

4.185

80.893

6

.461

3.544

84.437

7

.445

3.422

87.859

8

.415

3.192

91.051

9

.333

2.558

93.609

10

.304

2.338

95.947

11

.222

1.707

97.654

12

.173

1.331

98.985

13

.132

1.015

100.000

Extraction Method: Principal Component Analysis

Table 7 Rotated Component Matrix sorted by size for 13 process items

Items

Component

1

2

Pr11

.783

.326

Pr9

.781

.225

Pr10

.767

.213

Pr12

.751

.350

Pr8

.724

.302

Pr13

.576

.443

Pr1

.202

.804

Pr2

.229

.792

Pr3

.248

.724

Pr6

.352

.711

Pr5

.484

.620

Pr4

.482

.614

Pr7

.527

.594

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization

Table 8 Factor analysis results on 15 technology items

Component

Initial Eigenvalues

Rotation Sums of Squared Loadings

Total

% of Variance

Cumulative %

Total

% of Variance

Cumulative %

1

8.471

56.471

56.471

5.581

37.205

37.205

2

1.681

11.207

67.677

4.571

30.472

67.677

3

.902

6.011

73.688

4

.642

4.281

77.969

5

.530

3.536

81.505

6

.500

3.336

84.840

7

.406

2.709

87.550

8

.356

2.376

89.926

9

.321

2.143

92.069

10

.297

1.980

94.048

11

.252

1.678

95.726

12

.224

1.495

97.221

13

.164

1.092

98.313

14

.156

1.039

99.352

15

.097

.648

100.000

Extraction Method: Principal Component Analysis

Table 9 Rotated Component Matrix sorted by size for 15 technology items

Items

Component

1

2

Te3

.862

.293

Te7

.846

.232

Te4

.846

.265

Te6

.845

.263

Te2

.840

.272

Te8

.793

.388

Te5

.677

.426

Te9

.566

.386

Te17

.206

.816

Te15

.292

.764

Te14

.203

.737

Te19

.248

.730

Te12

.299

.713

Te18

.384

.687

Te16

.335

.656

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization

We then attempt to identify the confirmed factors based on the principle of being concise without losing clarity of meaning. After extracting the factors, items with higher loadings are considered more important and have greater influence on the name of selected reduced factors. The names and contents of the two derived factors on process items are:

Factor FPr1: it consists of items Pr8 to Pr13 which is “Interact with customers for gathering new product features “, “Provide quantities answer”, “Generate an easy interpret answer”, “Ease of generating reports”, “Ease of data entry” and “Ability to accommodate multiple users” respectively. This factor is named “Reports generator” because of Pr11 has higher loading factor (0.783).

Factor FPr2: It consists of Pr1 to Pr7 which are “Project control”, “Project reporting system”, “Making business together”, “Reduce traveling time and cost”, “Reduces the number of working hours need to solve the task”, “Collaborative solutions”, and “Facilitates data collection in new product development project” respectively. Since Pr1 has a higher loading (0.804), this factor’s named “Tracking system“.

Consequently, the names and contents of two derived factors on technology items are:

Factor FTe1: it consists of items Te2 to Te9 which is “Online meeting “, “Web conferencing”, “Seminar on the Web”, “Shared work spaces”, “Video conferencing”,” Audio conferencing”, “Online presentations”, and “Share documents” respectively. This factor is named “Web solution” because Te3 has a higher loading factor (0.862).

Factor FTe2: It consists of items Te12 and Te14 to Te19 which are “Access service from any computer (in Network)”, “Access shared files anytime, from any computer”, “Making business together”, “Web database”, “Provide instant collaboration”, “Software as a service”, “Virtual research centre for product development”, and “Can be integrated/compatible with the other tools and systems” respectively. Since Te17 has a higher loading (0.816) this factor’s named “Software as a service (SaaS)“.

Analysis of the Pearson’s correlations indicated a number of positive relationships between the variables themselves. The knowledge worker had significant associations to process and technology, respectively (see Table 10). The correlations may vary country to country as illustrated in and Table 12. Fisher's Exact Test analysis supported there are no significant differences (p > 0.427) between selected countries in terms of knowledge worker, process and technology in virtual teams.

Table 10 Descriptive statistics and correlations between variables (N=240)

Variable

Mean

Std. dev.

1

2

1. Knowledge worker

36.65

13.672

2. Process

42.25

17.191

0.792*

3. Technology

58.72

24.153

0.773*

0.853*

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

Table 11 Descriptive statistics and correlations between variables in Iran (N=136)

Variable

Mean

Std. dev.

1

2

1. Knowledge worker

36.14

14.251

2. Process

42.66

17.165

0.791*

3. Technology

60.77

24.429

0.838*

0.865*

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

Table 12 Descriptive statistics and correlations between variables in Malaysia (N=74)

Variable

Mean

Std. dev.

1

2

1. Knowledge worker

38.08

12.210

2. Process

42.78

16.770

0.811*

3. Technology

56.95

21.301

0.684*

0.795*

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

Table 13 Hypothesis testing results

Hypotheses

Correlation/P value

Conclusion

H1. Technology is positively related to process in virtual teams.

0.853*

Supported

H2. Technology is positively related to the knowledge workers in virtual teams.

0.773*

Supported

H3. The process and knowledge worker is positively correlated in virtual teams.

0.792*

Supported

H4. There is not any significant difference between the origins of virtual teams.

0.427**

Supported

Note: *: p < 0:01, **: p < 0:05

The mean scores for frequency of use to exchange business information are illustrated in Table 14. E-mail is the most frequently used tool for all teams in Malaysia and Iran. Personal telephone call is second most frequently used tool in selected countries. Malaysian firms used more face to face interaction than Iranian ones. On the other hand, team base communication technologies such as shared database, group telephone conference, electronic whiteboard and video conference were not often used. Video conference, although used less than once a month in Iranian samples, are most often used by Malaysian firms. Video conferencing may prove effective in bringing remote members together if made available to the teams, and this might be a fruitful area for future research (Lurey & Raisinghani, 2001). Along with Lurey, and Raisinghani (Lurey & Raisinghani, 2001) recommendation, item Te6 asked about the need for video conference as a tool for virtual team and, mean of (N=218) 3.172 was obtained which means it is quite important for the team members.

Table 14 Mean* scores for frequency of use exchange business information tools in Iran and Malaysia

Tools

Iranian teams (N=86)

Malaysian teams (N=31)

E-mail

4.62

4.97

Personal telephone call

4.54

4.63

Fax

4.02

4.00

Face-to-face interaction

3.65

4.23

Shared database/groupware

3.09

2.74

Meeting facilitation software

2.49

2.71

Web collaborative tool

2.42

2.65

Electronic newsletter

2.38

2.59

Voice mail

2.32

3.00

Electronic whiteboard

2.15

2.77

Group telephone conference

2.09

2.76

Video conference

1.85

2.43

*Frequency values- 1: never; 2: once a month; 3: once a week; 4: a few times a week; 5: daily

All factors are summarized in Figure 3. This new model is based on Bal and Gundry (Bal & Gundry, 1999) model with a lot of modification derived from data analysis and survey findings. The model provides an overview of effective virtual teams for new product development in selected developing countries.

Figure 3 The new model for effectiveness of virtual teams (Correlation is significant at the 0.01 level (2-tailed)).

Limitation and future research directions

The model for effective virtual teams developed earlier had made an initial attempt to identify the relationships between the knowledge worker, process and technology factors that were seen as the most critical in the literature. The literature review had focused only on published refereed journal and conference papers, so some important studies may have been excluded from this research. Therefore, it is possible that some factors which were excluded from the framework could be important for evaluation of virtual teams. The study was limited to the sample size and sample population. Future research needs to investigate the model and verify it by a larger sample of virtual teams from different sectors since this study was limited to manufacturing sector. In a larger sample, it is possible to compare the results between countries more precisely. We have identified twelve new crucial factors which differs from preceding for moving from team working to successful virtual teaming in new product development.

Conclusion

This paper is a review by the literature and a field survey identifying the key factors that need to be considered in effective virtual teams. These findings provide an important step in studying how virtual team efficacy is formed and what its consequences are in the context of virtual teams. The results of the study indicate that technology and process are tightly correlated and need to be considered early in virtual teams. Along with Bal and Teo (Bal & Teo, 2001b) and Ale Ebrahim et al. (Nader Ale Ebrahim et al., 2009b) findings, success in implementing virtual team working is more about the knowledge worker than technology and process. The survey result showed, all eight items in the knowledge workers remain while the rest are reduced into two main factors. Software as a service, web solution, report generator and tracking system in effective virtual teams should be taken into account for leading such a new phenomena. E-mail is the most frequently used tool for all teams in Malaysia and Iran; hence, a manager of virtual teams should considerably provide an infrastructure for effective communications between team members.

Future research would now seem to be essential for developing a comprehensive study, combining survey with case study in different size of companies (e.g. multinational companies and small and medium enterprises) and various type of activities (e.g. research and development and new product development). Such a study needs to investigate the model and verify it by a larger sample of virtual teams from different sectors. In a larger sample, it is possible to compare the results between countries more precisely.

Print Email Download Reference This Send to Kindle Reddit This

Share This Essay

To share this essay on Reddit, Facebook, Twitter, or Google+ just click on the buttons below:

Request Removal

If you are the original writer of this essay and no longer wish to have the essay published on the UK Essays website then please click on the link below to request removal:

Request the removal of this essay.


More from UK Essays