Is more always better? Investigating the task-technology fit theory in an online user context

doi:10.1016/j.im.2013.10.003

Information & Management

Volume 51, Issue 4, June 2014, Pages 391-397

https://doi.org/10.1016/j.im.2013.10.003 Get rights and content

Abstract

We used Task-Technology Fit (TTF) theory to examine the drivers and consequences of successful task completion by a user in an online context. The theory suggests that the fit between characteristics of the task and those of the website predicts user performance and behavioral intentions. Our hypotheses were tested using the input of two large scale studies performed in twelve industries and involving 13,135 participants. Results, which were replicated in a proximate culture, lend support to the predictions of Task-Technology Fit theory. The site information quality and ease of use were the only technology factors that significantly drove the users to a successful completion of their information tasks, rather than the site's graphical attractiveness, interactivity, security and privacy factors. The findings further suggested that focusing on the enhancement of site characteristics that have low fit with the task is not effective as it resulted in slowing the successful completion of the online task.

Introduction

Recent reports suggest that there are low conversion rates of commercial websites (below 4% in 2012) and large cart abandonment rates (60% in 2012).² Academic research has also noted the low rates of successful completion of online tasks (e.g., below 60% for shopping tasks [8]). It is therefore necessary to investigate the factors that affect users’ achievement of their online tasks. By identifying the IT characteristics that drive the success of online tasks, this research could contribute to efficient website design and its management.

Task-Technology Fit theory (TTF) [6] has been applied mainly at the organizational rather than the end user level [7]. Researchers however indicate the potential implications of TTF at the individual level. Recent work on the behavior of online users suggests that the site characteristics or the site quality dimensions positively influence the user task completion and behavioral intentions [10]. An unanswered question nonetheless is whether enhancing the IT characteristics has comparable and positive effect on performance; in other words, is more always better?

According to TTF, some technology characteristics exert positive effects on performance, subject to the task at hand and environmental factors. Thus, only a subset of the site characteristics may significantly improve outcomes.

We therefore decided to study the application of TTF to an individual user context in order to pinpoint the technology factors that facilitate users’ successful completion of online tasks and to show the relative importance of these factors in predicting task completion and then compare these results with actual user characteristics as captured in a survey. Our second objective was to investigate the effects of task completion and website characteristics on the user behavioral intentions.

Section snippets

The user online task

Tasks are user actions causing system outputs. Subordinate (concrete and specific) tasks closely affect superordinate (abstract and value-laden) tasks and jointly affect user decision making and outcome [1]. The significance of studying subordinate tasks results from the fact that users focus more on the task at hand (involving proximal and concrete goals) in order to solve more abstract tasks. For instance, users have been seen to abandon their shopping carts because of poor site navigation,

Research hypotheses

Both task and technology characteristics affect performance of users of an on-line systems task. User beliefs about the technology, such as ease of use, are strongly related to TTF [9]. Performance is affected by the site capacity to deliver the desired information with the least amount of errors and frustration. Among various characteristics, perceived risk and ease of use have been found to be salient in determining the intent to complete a transactional task [12]. It is therefore expected

Research studies

Data was provided from two large scale studies performed in collaboration with a leading Canadian market research company, whose online panel (a self-selected sample of consumers who opted-in to participate in commercial studies) is composed of about 350,000 consumers, constituted the sampling frame. Various industries and multiple websites in each industry were used to help controlling for the effects of industry (product category), firm, and site-related factors (e.g., site accessibility,

Analysis and results

Whereas logistical regression was used to test Hypotheses 1 and 2 (with success/failure in task completion as the dependent variable), linear regression was used to test Hypothesis 3 (with behavioral intentions as the dependent variable). Because tasks varied for multiple attributes (difficulty, ambiguity, cognitive load, and valence), there was a need to control for the different tasks assigned. This was performed by including the task (i.e., industry) in the equation as a dummy variable.

General discussion

The Task-Technology Fit theory appears to encompass important applications for the field of IT design and user performance. The confirmation of Hypotheses 1 and 2 shows that only a subset of the technology characteristics exerts major impact on user performance as reflected by the successful completion of the online task. The site ease of use and the site information quality were the only factors to positively and significantly predict the successful completion of the tasks. Contrary to prior

Conclusion

The results from two large scale studies involving over 13,000 consumers and encompassing twelve different industries lend support to our main hypotheses. While both the website and user characteristics influence the successful completion of informational tasks, the role of the website characteristics was greater. However, not all website characteristics positively or significantly influence task completion. The optimization of user task completion requires a focused approach in which the fit

Muhammad Aljukhadar is an Assistant Professor of Marketing at the Faculty of Economics and Administration, King Abdulaziz University. He holds a PhD in Marketing from HEC Montreal and an MBA from Concordia University. His main research interest is online consumer behavior. His research has appeared in the International Journal of Electronic Commerce, Canadian Journal of Administrative Science, Marketing Intelligence and Planning, Advances in Consumer Research, and Journal of Research in

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Sylvain Senecal is a Professor of Marketing, RBC Financial Group Chair of Electronic Commerce, and Tech3Lab Co-director at HEC Montreal. His teaching and research interests include online consumer behavior and consumer neuroscience. He serves on several editorial boards and has published his research in marketing and e-commerce journals such as Journal of Retailing, International Journal of Electronic Commerce, Journal of Business Research, Industrial Marketing Management, and Journal of the Association for Information Systems.

Jacques Nantel is a Professor of Marketing at HEC Montreal. He is the author or co-author of five marketing textbooks some of which have been translated in more than 12 languages. He has published several scientific articles in journals such as the Journal of Retailing, Journal of Advertising Research, Journal of Interactive Marketing, International Journal of Electronic Commerce, Journal of Business Research, European Journal of Marketing, Journal of Social Behavior and Personality, and Journal of Business Ethics.

¹: Tel.: +966 543 147242.

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Is more always better? Investigating the task-technology fit theory in an online user context

Abstract

Introduction

Section snippets

The user online task

Research hypotheses

Research studies

Analysis and results

General discussion

Conclusion

J. Bus. Res.

Inf. Manage.

Inf. Manage.

Inf. Manage.

J. Bus. Res.

J. Retail.

Goal setting and goal striving in consumer behaviour

J. Mark.