Investigation in to the factors influencing the intention to use social media tools within virtual project teams

Presented at PMI Global Congress – EMEA - 2011

Jerry Giltenane

Introduction

• Work in Dell, Limerick, as a global senior program management advisor.

• This research is based on my 2011 MBA dissertation for Henley Business School.

• Contact me at http://ie.linkedin.com/in/jerrygiltenane

Research Questions

• Explore intention rates to use social media into the future within virtual project teams.

• To establish the key reasons and factors that influence virtual project teams members to adopt social media.

• To understand the implications of such factors when one is involved in managing and setting up virtual project teams.

Why ?• Growth of virtual teams to conduct projects

due to perceived advantages of cost and knowledge.

• But project success rates static (Standish group – 44% of projects challenged).

• Communication key to all projects but particularly for virtual teams and a key project success factor.

• Social media the communication medium of choice for next generation of project managers and teams.

• Social Media allows potential for better communication.

Virtual Teams

• Strong growth in the use of virtual teams to execute projects due to cost advantages, access to skills and experience and local market knowledge.

• Many definition of virtual teams, but they can include any team that depend and use various communication technologies to collaborate – even co-located teams can work virtually !

• Trust is the key issue in virtual working due to team members varied backgrounds, degree of demographic diversity and lack of prior joint work experience.

• Lack of face to face interaction and prior joint work experience can be advantage – no baggage and better conflict resolution.

The Social Network

• There is an argument supported by a McKinsey Quarterly 2007 report that more useful business information flows through informal social networks then official channels within organizations.

• Social media tools are suited to employee to employee communication improvement, lessens the isolation issues for remote employees and tools such as micro-blogging can improve real time communication leading to competitive advantage.

• Elizabeth Harrin (Member of PMI New Media Council) 2010 study : * 62% of respondents believe that use of social media and enterprise collaboration give communication efficiency benefits. * 73% of respondents noted that social media will be a key issue for project management going forward

Technology Adoption models

• Technology adoption models try to explain the factors that influence / predict intention or usage of technology .

• Such models are based on psychology theory. Intention seen as a good predictor of Intent.

• Many model exist such as TRA, TPB, TAM and diffusion of innovation to mention a few.

• UTAUT Model developed in 2003 by Venkatesh to combine all previous models in to one combined model.

• The UTAUT model has shown to be able to explain 70% .

( Adjusted R2) of the variance in intention to adopt a technology.

UTAUT Model

• UTAUT: Unified Theory of use and acceptance of technology model

How Used In This study

• Study applied a revised version of UTAUT to virtual project teams and intent to use social Media.

• Study focused on intent V actual usage.

• Survey based on core predictor UTAUT variable plus the addition of a team trust construct given importance of trust in virtual teams.

• Aim: Can a modified UTAUT model help us understand the key influencing factors.

Definition of Survey Constructs

Performance expectancy: The extent to which an individual perceives that using a system will enhance his or her productivity, and thus lead to performance gains.

Effort expectancy: The extent to which using a system is free from effort

Social influence: The extent to which an individual perceives that important others think that he or she should use the target system.

Facilitating conditions: Is the perception regarding the availability of organizational and technical resources to support use of the target system

Team Trust: degree of trust between each project team member in each other’s ability to get the job done well and efficiently.

Modifying Factors on Intent

As well as investigating whether the UTAUT variables are significant predictors variables for this studies scope, the study also attempted to understand if intention rates to adopt social media varied by:

• Age Group

• Experience within virtual teams

• Whether in IT industry or not

• Gender

Survey Design• Online survey distributed via LinkedIn

groups.

• SurveyMonkey Pro used to create the Survey.

• Each construct such as social influence was broken up into multiple question items on a seven point likert scale.

• Survey was live for three weeks.

• Survey only looked for respondents that worked in virtual project teams.

• Social media defined as internal use of Blogs, IM, Micro-Blogging, Wikis, Webinars and collaboration tools such as Sharepoint.

Research Limitations• Common Methods Variance: False Correlations due to

consistent answers. Question order was Random to counteract.

• Sample Bias: LinkedIn as a distribution channel is a social network – but internal social media technology is a different.

• Self Reported Data: Not a bullet proof way to measure actual intent – but common method in similar studies.

• Facilitating Conditions construct did not pass the reliability test ( Cronbachs’s Alpha test ) – so this variable was not included in the final model

Survey DemographicsSample Size : 84

• Male 70.5% , Female – 29.5%

• =< 40 Years 58%, > 40 Years 42%

• Project Managers 73.9 % ,Other 23.1 %

• =< 3 years of virtual experience 34.1% > 3 years virtual experience 65.9%

• IT Industry 33% , Other 67%

Results

• Descriptive analysis of the key constructs.• Inferential analysis of the proposed model predicitive

ability using multiple regression analysis in SPSS.• Correlation of the constructs to behavioural intent.• Group comparison in terms of intention to use social

media over the next 6 months.

Behavioural IntentOverall summated average 5.63 (closer to Agree than somewhat agree)

Performance ExpectancyOverall summated average 5.44 (closer to Somewhat Agree than agree)

Effort ExpectancyOverall summated average 5.63 (closer to Agree then somewhat agree)

Social InfluenceOverall summated average 4.99 (Somewhat Agree)

Team TrustOverall summated average 5.40 (closer to Somewhat Agree than Agree)

Facilitating ConditionsOverall Summated average 5.33 (closer to Somewhat Agree then Agree)

Model Regression Result

An adjusted R Square of .527 means that taken together, social influence, performance expectancy, effort expectancy and team trust can be seen to account for 52.7 % of the variance in the intention rate to adopt social media technology. This result is a relatively strong outcome and shows the variables taken together as a good predictor on behavioural intention.

Construct Correlations

Beta values here indicate the strength of the contribution of a variable in explaining the dependant variable behavioural intent, when the variance explained by all other variables is controlled. Performance Expectancy the strongest contributor at .421 or 42%. Other three variables still significant contributors. Team Trust has negative correlation indicating the less trust in a team the greater intent to use social media

Behavioural Intent By Group

• Independent Samples t-test method in SPSS was used to understand whether intention to use social media varies by a number of modifying factors.

Gender Age group IT Industry V othersExperience

• In Each case the Sig. 2-tailed value for each test was greater then .05. • This indicates that there was no significant difference between the groups in terms

of intention to adopt social media.

Conclusions• Performance expectancy is the strongest influencing factor in adoption intention.

• Social influence, effort expectancy and team trust are also significant factors.

• Team trust is negatively correlated – perhaps respondents see social media as a way to overcome trust issues.

• The UTAUT model is shown to have a reasonably strong predictive ability.

• Age, experience, gender and industry does not moderate intention to adopt.

Recommendations• Be cognitive of the importance of ensuring that social media tools are designed to

clearly aid staff productivity - Vroom’s expectancy theory of motivation where outcomes and not needs are what motivate people to do certain acts

• Take into account simultaneously both the instrumental and effortless side of technology – make internal tools work and look like public social media tools

• Hire a Internal Social Media Tools manager: help enforce social influence

• Negative trust correlation: further research needed – may indicate that social media technology can help overcome trust issue. Might be important in team formation

• Internal social media adoption does not vary on team composition – reflects

popularity of external social networks

Finally

Andrew S. Grove of Intel Corporation quotation below holds as true today as it did in 1988.

“You have no choice but to operate in a world shaped by globalization and the information revolution. There are two options: Adapt or die.”