An extensive body of literature indicates the growing influence of virtual communities not only on social interaction, spending free time and working, but also on the interaction of companies with their customers to exchange information on products and to develop innovative ideas. However, engaging in virtual communities poses certain challenges to companies which more often than not results in failure to establish a successful collaboration with customers. This leads to the following questions:
What are virtual communities and how can companies establish successful interaction? Why and how can interaction with a community lead to an improvement of the innovation process? This article develops a comprehensive concept of the collaboration between companies and virtual communities called communitycompany interaction quality (CCIQ). Based on insights from academic literature, this paper reviews factors influencing the quality of community-company interaction, suggesting an integrative framework. After developing a working definition for virtual communities in innovation, a summary of findings regarding interaction quality in context of humantechnology interaction and behaviour related to innovation is proposed.
Automated recording units are commonly used by consultants to assess environmental impacts and to monitor animal populations. Although estimating population density of bats using stationary acoustic detectors is key for evaluating environmental impacts, estimating densities from call activity data is only possible through recently developed numerical methods, as the recognition of calling individuals is impossible.
We tested the applicability of generalized random encounter models (gREMs) for determining population densities of three bat species (Common pipistrelle Pipistrellus pipistrellus, Northern bat Eptesicus nilssonii, and Natterer's bat Myotis nattereri) based on passively collected acoustical data. To validate the results, we compared them to (a) density estimates from the literature and to (b) Royle–Nichols (RN) models of detection/nondetection data.
Our estimates for M. nattereri matched both the published data and RN‐model results. For E. nilssonii, the gREM yielded similar estimates to the RN‐models, but the published estimates were more than twice as high. This discrepancy might be because the high‐altitude flight of E. nilssonii is not accounted for in gREMs. Results of gREMs for P. pipistrellus were supported by published data but were ~10 times higher than those of RN‐models. RN‐models use detection/nondetection data, and this loss of information probably affected population estimates of very active species like P. pipistrellus.
gREM models provided realistic estimates of bat population densities based on automatically recorded call activity data. However, the average flight altitude of species should be accounted for in future analyses. We suggest including flight altitude in the calculation of the detection range to assess the detection sphere more accurately and to obtain more precise density estimates.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.