No abstract

Purpose -This paper seeks to argue that creativity in the workplace is a very complex construct that is difficult to measure not only in its own right, but also in its interrelation with physical space. Since creativity is a social process, this paper aims to suggest studying interaction patterns as a fundamental feature of creativity. Design/methodology/approach -Based on the literature, two criteria for creativity in workplaces were developed: spaces for chance encounters with people from different teams; and a balance of spaces for communication and concentration. Using a mixed-methods research design, a UK media company was studied before and after a relocation and refurbishment project in 2007-2008. The case study included structured interviews, satisfaction surveys, social network surveys, space observations, and a Space Syntax analysis of floor plans. Findings -The paper showed that only the first criterion was successfully met in the media company studied, and that the pressure on the industry inhibited the full implementation of the second.Research limitations/implications -Owing to the nature of the research results cannot be generalised. The relationship between creativity, interaction and space requires further investigation. Practical implications -The findings highlight the need to balance spaces for communication and concentration, as well as the importance of bringing people together to enhance creativity. This knowledge may be useful for workplace professionals in design, architecture and facility management. Originality/value -The paper presents a valuable data set comparing one organisation in a pre-post research design, where the impact of spatial changes on working processes can be monitored. It combines innovative approaches normally used in separation.

The ability to detect and distinguish interactions in the workplace can shed light over productivity, team work and on employees' use of space. Questionnaires and direct observations have often been used as mechanisms to identify office based interactions, however, these are either very time consuming, yield coarse grained information or do not scale to large numbers of people. Technology has been recently employed to cut costs and improve output, however precise interaction dynamics gathering often requires individuals to wear custom hardware. In this paper, we present an extensive evaluation of Bluetooth Low Energy (BLE) as a technology to monitor people proximity in the workplace. We examine the key parameters that affect the accuracy of the detected contacts and their impact on power consumption. We study how this system can be implemented on popular wearable devices (i.e., Android Wear and Tizen) and the resulting limitations. Through a real world deployment in a commercial organisation with 25 participants we evaluate the performances of a BLE-based proximity detection technique. Our results show the suitability of BLE for workplace interaction detection and give guidance to vendors and Operating System (OS) developers on the impact of the restrictions regarding the use of BLE on commodity wearables.

Face-to-face social contacts are potentially important transmission routes for acute respiratory infections, and understanding the contact network can improve our ability to predict, contain, and control epidemics. Although workplaces are important settings for infectious disease transmission, few studies have collected workplace contact data and estimated workplace contact networks. We use contact diaries, architectural distance measures, and institutional structures to estimate social contact networks within a Swiss research institute. Some contact reports were inconsistent, indicating reporting errors. We adjust for this with a latent variable model, jointly estimating the true (unobserved) network of contacts and duration-specific reporting probabilities. We find that contact probability decreases with distance, and that research group membership, role, and shared projects are strongly predictive of contact patterns. Estimated reporting probabilities were low only for 0–5 min contacts. Adjusting for reporting error changed the estimate of the duration distribution, but did not change the estimates of covariate effects and had little effect on epidemic predictions. Our epidemic simulation study indicates that inclusion of network structure based on architectural and organizational structure data can improve the accuracy of epidemic forecasting models.