Do end-users accept end-user development by using mashups? Using the technology acceptance model, we have investigated the acceptance of the mashup platform FAST (http://demo.fast.morfeo-project.org), which enables end-users to build their own application by simply drag and drop graphical building blocks.
The platform had shown an active interest among 159 individuals worldwide. The outcome demonstrated that perceived usefulness strongly affected the attitude towards using mashups for end-user development. In turn, perceived ease of use did not. With respect to the developed mashup platform, it was found that the available content within the mashup platforms is the main influencing factor on the acceptance of end-user development tools.
Figure 1. Study Design
Our study utilized an extended version of the technology acceptance model (TAM), see Figure 3. The technology acceptance model posits that user acceptance is determined by two key beliefs, namely; perceived usefulness (PU) and perceived ease of use (PEOU). Perceived usefulness is defined as “the degree to which a person believes that using a particular system would enhance his or her job performance”, while perceived ease of use indicates “the degree to which a person believes that using a particular system would be free of effort” (Davis, 1989). Both, PU and PEOU are supposed to be indicators for the attitude toward using (ATU) information systems (Davis, 1993). Computer self-efficacy (CSE) refers to the degree to which an individual believes that he or she has the ability to perform a specific task/job by using a computer. Several empirical studies indicate that computer self-efficacy is important to the successful implementation of systems in organizations, (Compeau & Higgins, 1995a; 1995b; Venkatesh & Bala, 2008).
In Figure 2 the standardized estimates of the model are presented.
- Computer Self-Efficacy (CSE) has a positive impact on ‘Perceived Ease of Use (PEOU)’.
- Perceived Ease of Use (PEOU) influences ‘Attitude towards Using (ATU)’ by a value of 0.22.
The highest influences are the following:
- ‘Perceived Ease of Use (Peou)’ and ‘Perceived Usefullness (PU)’ amounts to a value of 0.51.
- The relations between ‘Perceived Usefullness (PU)’ and ‘Attitude towards Using (Atu)’ gain a value of 0.68.
Figure 2. Results of structural Model
Computer Self-Efficacy (CSE) could explain 7% of the variance of the dimension Perceived Ease of Use (PEOU). Perceived Ease of Use (PEOU) define 26% of the variance of the dimension Perceived Usefullness (PU). Both Perceived Ease of Use (PEOU) and Perceived Usefullness (PU) explicate 67% of the variance of Attitude towards Using (Atu).
More than 60 percent of the participants do have a positive attitude towards using mashups for end-user development, see Figure 3. The research results display that 64.1 percent of the participants are satisfied or very satisfied with the FAST platform, while 27.5 percent are undecided and only 8.4 percent are slightly or extremely dissatisfied.
Figure 3. Attitude towards Using
It was shown that computer self-efficacy has a positive, but very low impact (7%) on perceived ease of use and PEOU influences the attitude towards using a value of 0.22 percent. In that sense it cannot be confirmed that only highly motivated end-users would utilize EUD tools. On the contrary, it can be confirmed that even end-users with no special training on the tool are able to create their own applications by using the FAST platform.
In comparison with perceived usefulness, perceived ease of use has a weak influence on the acceptance of end-user development by using the FAST platform. In other words, improving the ease of use the developed mashup platform, by for example improving usability aspects, would not have a significant impact on the acceptance of the platform. On the other hand, perceived usefulness affects ATU with a value of 0.68, and therefore has a increased impact on user acceptance in comparison to perceived ease of use.
Improving the perceived usefulness implies the development of more relevant building blocks / content. Especially the available resource building blocks (RESTful web services, SOAP-based services, other backend systems) do have an increased impact on the acceptance of the platform. Hence, end users should be empowered to integrate backend systems & services which are of interest within their working domain by themselves.
Compeau, D. R., & Higgins, C. A. (1995a). Computer Self-Efficacy: Development of a Measure and Initial Test. MIS Quarterly, 19(2), 189-211.
Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319.
Davis, F. D. (1993). User acceptance of information technology: system characteristics, user perceptions and behavioral impacts. International Journal of Man-Machine Studies, 38(3), 475-487.
Venkatesh, V., & Bala, H. (2008). Technology Acceptance Model 3 and a Research Agenda on Interventions. Decision Sciences, 39(2), 273–315.