Start Date
14-12-2012 12:00 AM
Description
In order to better explain and predict consumers’ preferential choices of software products, we propose a model that incorporates product attributes and consumer perceptions to estimate users’ software product selections. The influences of product attributes on users’ perceptions of product characteristics are also examined. With a choice-based conjoint study, and the collection of additional data on users’ perceived product characteristics, we demonstrate that the proposed model can better explain and predict users’ software choices than the model with product attributes only or with user perceptions only, in terms of the in-sample fit and the holdout prediction hit rate at the individual-level and the aggregate-level. This study contributes to the literature by providing a better understanding of how product attributes, price, size of user base, vendor support level, and user perceived characteristics jointly determine consumers’ software selection decisions.
Recommended Citation
Hu, Han-fen; Moore, William; and Hu, Paul J., "Incorporating User Perceptions and Product Attributes in Software Product Design and Evaluation" (2012). ICIS 2012 Proceedings. 17.
https://aisel.aisnet.org/icis2012/proceedings/HumanBehavior/17
Incorporating User Perceptions and Product Attributes in Software Product Design and Evaluation
In order to better explain and predict consumers’ preferential choices of software products, we propose a model that incorporates product attributes and consumer perceptions to estimate users’ software product selections. The influences of product attributes on users’ perceptions of product characteristics are also examined. With a choice-based conjoint study, and the collection of additional data on users’ perceived product characteristics, we demonstrate that the proposed model can better explain and predict users’ software choices than the model with product attributes only or with user perceptions only, in terms of the in-sample fit and the holdout prediction hit rate at the individual-level and the aggregate-level. This study contributes to the literature by providing a better understanding of how product attributes, price, size of user base, vendor support level, and user perceived characteristics jointly determine consumers’ software selection decisions.