Shared Paths to the Lab

Kabo, Felichism; Hwang, Yongha; Levenstein, Margaret C.; Owen‐Smith, Jason

doi:10.1177/0013916513493909

Cited by 78 publications

(40 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The results of the MMNL model showed no significant relationships between contact person(s) characteristics and the location choice of ftf interactions. On the contrary, previous studies did show that people from different groups have different ftf interaction patterns (e.g., Wineman, Kabo, and Davis 2009;Kabo et al 2015). The findings might suggest that personal characteristics and ftf interaction characteristics might be more important indicators for choosing a specific location type than contact person(s) characteristics.…”

Section: Discussionmentioning

confidence: 71%

Location choices of face-to-face interactions in academic buildings: an experience sampling approach

et al. 2019

View full text Add to dashboard Cite

Although it is recognised that face-to-face interactions are important for sharing interests and (new) knowledge, it remains unknown how and where students and university employees interact in academic buildings. Therefore, the aim of this study is to analyse the location choice for face-to-face interactions in an academic building, including several personal-and interaction characteristics. An Experience Sampling Method (ESM) was used to collect data on 643 face-toface interactions during two weeks in the Flux building at Eindhoven University of Technology, the Netherlands. In general, students more often interacted in meeting rooms than teaching staff, and support staff interacted less in eat/drink areas and the hallways than other users. Unexpectedly, some of the lectures took place outside of traditional project-/lecture space. Real estate managers of university campuses could use these results to create better interactive work environments that stimulate face-to-face interactions among employees and students of different departments.

show abstract

Section: Discussionmentioning

confidence: 71%

Location choices of face-to-face interactions in academic buildings: an experience sampling approach

et al. 2019

View full text Add to dashboard Cite

show abstract

“…These socio-organizational relationships manifest themselves both digitally and physically, though research continues to show that physical interactions are the cornerstone of collaboration and meaningful ties (Waber et al, 2014). Because of the importance of these physical exchanges, the design of the physical workspace-the commercial building-can have an impact on the nature and frequency of interactions among members of organizations (Sailer and McCulloh, 2012), which can be critical to the success of the organization (Kabo et al, 2015). However, learning the true social and organizational ties among workers, which would be helpful in designing and managing these spaces, remains a challenge.…”

Section: Introductionmentioning

confidence: 99%

“…In the domain of workspace and organizational theory, researchers have noted a strong relationship between office design/layout and occupant satisfaction and performance (Sailer, 2011;Sailer and McCulloh, 2012;Kabo et al, 2015). Recently, researchers have noted that the physical designs of buildings can have large impacts on different metrics related to productivity, such as communication, collaboration, creativity, and innovation (Sailer, 2011;Kabo et al, 2015). Using the language of space syntax (Bafna, 2003), researchers have defined metrics defined by physical layout and correlated them with occupant outcomes.…”

Section: Introductionmentioning

confidence: 99%

Learning socio-organizational network structure in buildings with ambient sensing data

Sonta

Jain

2020

DCE

View full text Add to dashboard Cite

We develop a model that successfully learns social and organizational human network structure using ambient sensing data from distributed plug load energy sensors in commercial buildings. A key goal for the design and operation of commercial buildings is to support the success of organizations within them. In modern workspaces, a particularly important goal is collaboration, which relies on physical interactions among individuals. Learning the true socio-organizational relational ties among workers can therefore help managers of buildings and organizations make decisions that improve collaboration. In this paper, we introduce the Interaction Model, a method for inferring human network structure that leverages data from distributed plug load energy sensors. In a case study, we benchmark our method against network data obtained through a survey and compare its performance to other data-driven tools. We find that unlike previous methods, our method infers a network that is correlated with the survey network to a statistically significant degree (graph correlation of 0.46, significant at the 0.01 confidence level). We additionally find that our method requires only 10 weeks of sensing data, enabling dynamic network measurement. Learning human network structure through data-driven means can enable the design and operation of spaces that encourage, rather than inhibit, the success of organizations.

show abstract

“…Previous studies have shown that different types of workspaces are required when comparing academics to commercial workers [29]. While open-plan office layouts with increasing path overlap seem to increase collaboration [30], concentration may improve in cellular offices due to enhanced privacy and less interruptions.…”

Section: Introductionmentioning

confidence: 99%

Does the Number of Occupants in an Office Influence Individual Perceptions of Comfort and Productivity?—New Evidence from 5000 Office Workers

2019

View full text Add to dashboard Cite

Purpose—The purpose of this article is to present evidence of occupants’ perception of their work environment in five different office types (Solo, Duo, 2–4, 5–8 and 8Plus offices). The study examined the influence of the number of office occupants on individual perception of indoor environment quality (IEQ) in office environments. Design/methodology/approach—A dataset of 5000 respondents in 67 commercial and institutional office buildings was analysed using IBM SPSS v23. The dataset contained user response on the BUS Methodology questionnaire that is designed to retrieve occupants’ perception of their work environments. Analysis of Variance (ANOVA) and multiple regression analysis were conducted to calculate the impact of the office environment on occupants’ perception of comfort and productivity. Findings - This study showed that occupants in Solo and Duo offices perceived higher satisfaction with their environment (except for temperature in summer), better health and productivity; and more control over the office environment than those in 5–8 and 8Plus offices. Occupants in 8Plus offices were most satisfied with the temperature in summer. It was also noted that the IEQ factors that predicted comfort were observed to not predict productivity. Noise was the only IEQ factor that had predictive power for both comfort and productivity in all the office spaces. Originality/value—This article provides intriguing findings on occupants’ perception of various types of office environment that contributes significantly to the debate on open-plan versus cellular office environments.

show abstract

Shared Paths to the Lab

Cited by 78 publications

References 28 publications

Location choices of face-to-face interactions in academic buildings: an experience sampling approach

Location choices of face-to-face interactions in academic buildings: an experience sampling approach

Learning socio-organizational network structure in buildings with ambient sensing data

Does the Number of Occupants in an Office Influence Individual Perceptions of Comfort and Productivity?—New Evidence from 5000 Office Workers

Contact Info

Product

Resources

About