Abstract
Prior research found that user personality significantly affects technology acceptance perceptions and decisions. Yet, evidence on the moderating influence of user gender on the relationship between personality and technology acceptance is barely existent despite theoretical consideration. Considering this research gap, the present study reports the results of a survey in which we examined the relationships between personality and technology acceptance from a gender perspective. This study draws upon a sample of N = 686 participants (n = 209 men, n = 477 women) and applied the HEXACO Personality Inventory—Revised along with established technology acceptance measures. The major result of this study is that we do not find significant influence of user gender on the relationship between personality and technology acceptance, except for one aspect of personality, namely altruism. We found a negative association between altruism and intention to use the smartphone in men, but a positive association in women. Consistent with this finding, we also found the same association pattern for altruism and predicted usage: a negative one in men and a positive one in women. Implications for research and practice are discussed, along with limitations of the present study and possible avenues for future research.
Highlights
Regarding the influence of gender on technology acceptance model (TAM) variables, we found that men scored higher in the perceived usefulness (PU) scale assessing TA with regard to the smartphone compared to women
A result of our study is that men scored higher in the PUs scale assessing TA with regard to the smartphone compared to women (Table 1)
We conducted a survey study in which we examined the relationship between personality and technology acceptance from a gender perspective
Summary
The technology acceptance model (TAM) [1] is a theoretical framework which explains user acceptance of technology In essence, this model explains that actual use of a technology is influenced by three core constructs: perceived ease of use of the technology, perceived usefulness of a technology to support task execution, and behavioral intention to use the technology. A wealth of survey research supports the explanative power of TAM (see, for example, meta-analyses and reviews by Lee, Kozar, and Larsen [2], Legris, Ingham, and Collerette [3], or King and He [4]), and several TAM extensions and unifying frameworks were developed during the past decades (e.g., TAM2 [5,6], unified theory of acceptance and use of technology, UTAUT [7]) These extensions added independent variables, as well as mediators and moderators, to increase the model’s explanatory power. A meta-analysis [8] revealed that a user’s perception that most people who are important to him (her) think he (she) should, or should not, use the technology (referred to as “subjective norm”) influences perceived usefulness, behavioral intention, and actual system use
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