Empirical research had initially shown that English listeners are able to identify the speakers' sexual orientation based on voice cues alone. However, the accuracy of this voice-based categorization, as well as its generalizability to other languages (language-dependency) and to non-native speakers (language-specificity), has been questioned recently. Consequently, we address these open issues in 5 experiments: First, we tested whether Italian and German listeners are able to correctly identify sexual orientation of same-language male speakers. Then, participants of both nationalities listened to voice samples and rated the sexual orientation of both Italian and German male speakers. We found that listeners were unable to identify the speakers' sexual orientation correctly. However, speakers were consistently categorized as either heterosexual or gay on the basis of how they sounded. Moreover, a similar pattern of results emerged when listeners judged the sexual orientation of speakers of their own and of the foreign language. Overall, this research suggests that voice-based categorization of sexual orientation reflects the listeners' expectations of how gay voices sound rather than being an accurate detector of the speakers' actual sexual identity. Results are discussed with regard to accuracy, acoustic features of voices, language dependency and language specificity.

This paper in the journal "Gruppe. Interaktion. Organisation. (GIO)" presents a study that investigated user experience characteristics as determinants of technology acceptance. Organizations planning to implement new technologies are confronted with the challenge to ensure user acceptance. Barely accepted technologies are used less often, result in lower job satisfaction, and ultimately lead to performance losses. The technology acceptance model (Venkatesh and Bala 2008) incorporates determinants of information technology use. The model's predictors have a strong focus on interindividual user characteristics (such as computer self-efficacy) and the job context (e.g., voluntariness). Yet, what is lacking in the model, are characteristics of the technology itself that can be used as starting points to design better technologies. To bridge this gap, we introduce the User Experience Technology Acceptance Model, and provide a first test of this model. In our online survey (N = 281), we investigated how technological determinants, more specifically user experience characteristics, affected technology acceptance. Except for two paths of our proposed model, all path coefficients were significant with small to large effect sizes (f 2 = 0.02-0.66). User experience predictors resulted in 60.6% of explained variance in perceived ease of use, 38.2% of explained variance in perceived usefulness, and 25.8% of explained variance in behavioral intention. Our results provide mostly support for our extension of the technology acceptance model. The technology-inherent characteristics output quality, perspicuity, dependability, and novelty were significant predictors of technology acceptance. We discuss theoretical and practical implications with the focus on technology designers, change managers, and users.

Abstract. Digitization and connectivity are hot topics for nearly every company today; numerous new technologies offer diverse options. In this project, a specific technology − smart glasses − was implemented in a manufacturing company. The implementation process was innovative, as the employees’ perspective was taken into account from the beginning, rather than solely designing the technological aspects and involving the users after decisions were taken. Employees involved with the new technology were surveyed to take into account the employees’ expectations and fears regarding work design characteristics. This allowed us to customize features of the smart glasses, adapt the work organization, and inform employees about unclear points concerning the implementation process. Moreover, the competencies required for future work were analyzed using a comprehensive work analysis method. We report the results of two quantitative studies and summarize the lessons learned from this project, which can serve as a guideline for other companies.

The manufacturing industry is increasingly being dominated by information and communication technology, leading to the development of cyber-physical systems. Most existing frameworks on the assessment of such technological advancements see the technology as a solitary system. However, research has shown that other environmental factors like organizational processes or human factors are also affected. Drawing on the sociotechnical systems approach, future technologies could be evaluated using scenarios of digitized work. These scenarios can help classify new technologies and uncover their advantages and constraints in order to provide guidance for the digital development of organizations. We developed an instrument for evaluating scenarios of digitized work on the relevant dimensions ‘technology’, ‘human’ and ‘organization’ and conducted a quantitative study applying this instrument on three different scenarios (N = 24 subject matter experts). Results show that our instrument is capable of measuring technological, human and organizational aspects of technology implementations and detecting differences in the scenarios under investigation. The instrument’s practical value is significant as it enables the user to compare and quantify scenarios and helps companies to decide which technology they should implement.