Hello,
I'm currently writing my master thesis, and is investigating the behavioral intention of using a help desk ticket system in a company, using the meta-UTAUT model. I'm applying PLS-SEM for my analysis, but have run into some unexpected results.
My measurement model show acceptable validity and reliability metrics. When I run my structural model, effort expectancy has a negative and significant relationship to behavioral intention. This indicates the easier it is to use the system, the less likely the employees are to use it, which makes no sense.
I've checked my items, and none of them are formulated negatively. Unfortunately I do not know what this implies.
Do anyone have any idea, or can guide me in the right direction? Thank you very much in advance!
Hi Anders,
The unexpected results you are seeing in your analysis can be frustrating, but it's important to keep investigating to understand the reasons behind them.
One possible explanation for the negative relationship between effort expectancy and behavioral intention could be that your sample of employees already find the help desk ticket system very easy to use, to the point where making it even easier may not increase their intention to use it. This is known as a "ceiling effect" and can lead to unexpected results in your analysis.
Another possibility is that there could be a confounding variable that you haven't accounted for in your model, which is influencing the relationship between effort expectancy and behavioral intention. This could be something like the perceived usefulness of the system, which may be more important than ease of use in determining whether employees actually intend to use it.
It's important to continue exploring your data and running sensitivity analyses to understand the robustness of your results. You may also want to consider collecting additional data or adjusting your model to better account for potential confounding variables.
I hope this helps!
Alireza Falakdin Thank you very much for your respons, it is very helpful and greatly appreciated!
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