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Purpose Workplace space utilization data reveals patterns of space usage, the occupants’ presence and mobility within the office building. Nowadays, emerging technology such as smart sensors and devices can revolutionize the measurement of space utilization data, which is originally dominated by human observers with paper and pencil. However, these novel instruments are often used in an old fashion, which restricts the exploitation of their full potential. This study aims to shed new light on the benefits and limits of using smart technology in measuring space utilization data and discusses the challenges and opportunities in analyzing the data measured by smart sensors. Design/methodology/approach First, the literature regarding common methods and previous studies about office space utilization measurement was reviewed. Then, a data set consisting of space utilization data collected through Passive Infra-Red sensors for 35 meeting rooms in a bank building was carefully evaluated. Finally, the space utilization results based on methods calculated in two different granularities were compared. Findings The number of occupied hours calculated at an hour level was 1.32-hour larger than that calculated at a minute level. As both results show the concept of space utilization, which was the amount of time that the space was occupied, this paper revealed a gap between the two space utilization calculation methods and further discussed the issues and challenges for future space utilization data analysis and benchmarking. Originality/value To the best of the authors’ knowledge, this is the first study critically addressing office space utilization issues by comparing calculation methods in different granularity.

Purpose The purpose of this paper is to study whether the use of a shared study space played a role in shaping graduate students’ social networks by exploring how the copresence in space was related to the structure of friendship and advice networks. The authors first proposed two concepts of spatial copresence: measured spatial-temporal copresence and perceived copresence. The authors then examined the role of copresence through a case study of a shared study space occupied by 27 graduate students in the same department. Design/methodology/approach Copresence relations were first constructed through a six-month room access history data set and self-reported data to examine whether measured spatial-temporal copresence was consistent with perceived copresence. Friendship and advice network relations were then analyzed with copresence, social media connections, class project collaboration relations and social homophily (nationality, gender, cohort) through quadratic assignment procedure (QAP) and MQAP analysis. Findings The authors found that students who used the shared study space more often reported more friendship and advice ties. The perceived copresence and the measured spatial-temporal copresence were highly correlated. Copresence relations, as measured by survey and room access history, were both significantly correlated with advice relation, which was associated with perceived social support. Originality/value This study contributes to the debate about whether “space” continues to play significant roles in graduate students’ social networks in the context of flexible learning environments. The results also reveal new directions for research methods in studying spatial proximity in flexible settings.

Purpose The purpose of this paper is to review the use of technologies for measuring space occupancy to guide the selection of appropriate tools for workplace post-occupancy evaluation (POE) studies. The authors focus on how actual space occupancy was measured in previous studies and the pros and cons of the different technologies and tools. This paper also addresses research gaps and directions for future research. Design/methodology/approach The space occupancy measures/tools are categorized based on the three types of technologies: environmental/ambient sensors, wearable sensors/smartphones and computer vision. A total of 50 studies are reviewed to identify the capabilities and limitations of these measurements. Findings Based on review results, the authors propose that although sensor technology can be a useful addition to the measures/tools list, a comprehensive review of the research goal, the occupants' behavior, and the environmental settings' characteristics should be conducted beforehand. Selecting appropriate technology is critical for collecting the proper behavioral data type, with a lower level of surveillance and increased validity. Originality/value This paper urges critical thinking about existing occupancy measures/tools across various fields, to inform the adoption and creation of new building occupancy measures. The knowledge of emerging sensor technology allows researchers to better study the temporal patterns of occupant behavior over extended periods and in a wide range of settings.