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Location-based services (LBS) are among the major advancements in mobile internet applications since they take into account the geographic location of an entity and the ubiquitous nature of mobile services, using spatial decision support to provide customer value that exceeds that of traditional channels. However, the growth trajectory and associated adoption and diffusion of LBS have slowed, as challenges related to consumer perceptions persist. This study focuses on check-in services (CIS), a kind of LBS, like Facebook Locations and Foursquare, which use shared user experiences linked to geographical information to recommend places and venues.User adoption of CIS is particularly challenging, as the potential of location tracking is often regarded as a "double-edged sword" that benefits decision-making but risks the loss of privacy.To gain insights into users' voluntary CIS information disclosure, we combine the privacy calculus model (PCM) with the concept of conditional value and explore the effects of various situational stimuli in a true experiment and in data analyses that combine group comparisons with structural equation modelling (N = 296). The study confirms the relevance of conditional value to PCM and outlines direct and indirect effects of the situational factors of place relevance and frequency of location visit. The study makes several theoretical and practical contributions to the field of LBS adoption.

Purpose – By studying the drivers of social collaboration the purpose of this paper is to describe how, and for what job-related purposes, social software is employed in the digital workplace. Focussing on consultants, who are considered to be part of a knowledge-intensive and innovative industry, factors that may influence the adoption of professional social software are explored. In addition, insights about socio-demographic differences as well as distinct consulting segments and use categories are provided. Design/methodology/approach – The Unified Theory of Acceptance and Use of Technologies (UTAUT) is the theoretical backbone of this research. The UTAUT model is expanded to fit the research goals, and the results from a quantitative study (n=341) are used to test the model. Findings – The results suggest that the adoption of social software is associated with the expectation that one’s work performance will improve. There are significant differences regarding age and gender in the use of social software for job-related purposes. Practical implications – Using the results of the study, social software suites can be tailored to users’ needs and preferences, which, in turn, may lead to higher levels of acceptance and intensity of use. Originality/value – Social software is already widely adopted for private purposes, and it is being used more and more within the digital workplace, too. However, little research has been conducted into how, and for what job-related purposes, social software is employed, or into the potential drivers for its adoption. The stakeholders in the research include scholars and practitioners alike.