Gender differences in information quality of virtual communities: A study from an expectation-perception perspective. (January 2017)

• Record Type: Journal Article
• Authors: Liu, Yuewen; Li, Yahui; Zhang, Hongyun; Huang, Wei (Wayne)
• Is Part Of: Personality and individual differences. Volume 104(2017)
• Page Start: 224
• Page End: 229
• Publication Date: 2017-01
• Subjects: Information quality -- Gender -- Expectation -- Perception -- Virtual community; Personality -- Periodicals; Individuality -- Periodicals; Individuality -- Periodicals; Personality Development -- Periodicals; Personnalité -- Périodiques; Individualité -- Périodiques; 155.205
• DOI: 10.1016/j.paid.2016.08.011
• Languages: English
• ISSNs: 0191-8869

Abstract

Abstract: Knowing the effect of user characteristics on information quality is important to optimize the quality of content and provide a satisfactory user experience. In this paper, we investigate gender differences in the assessment of information quality in virtual communities. To understand the influence of gender on information quality, this paper measures information quality by the discrepancy between expectation and perception. The proposed conceptualized model is validated by 144 survey observations being collected at a public university. Then, the multivariate analysis of variance is used to analyze the data. The results show that gender could indeed have an influence on information quality through expectations or perceptions. Specifically, males assess representational data quality more highly than females. Females have higher expectations of representational data quality than males. Males regard accessible data quality more highly than females. Managers of virtual communities need to realize that the same information may be perceived differently by different genders. They need to take the gender of users into account and provide customized information accordingly. Highlights: Information quality is measured by the discrepancy between expectation and perception. Males assess representational data quality more highly than females Females have higher expectations of representational data quality than males. Males regard accessible data quality more highly than females.