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Developments in information and communication systems, organisational structure and the nature of work have contributed to the restructuring of work environments. In these new types of work environments, employees do not have assigned workplaces. This arrangement helps organisations to minimise rent costs and increase employee interaction and knowledge exchange through mobility. This post-occupancy evaluation (POE) study focuses on a flexible office in a Gold Leadership in Energy and Environmental Design-certified building in Istanbul. An integrated qualitative and quantitative POE technique with occupancy tracking via barcode scanning and instant surveying has been introduced. Using this unique approach, we examined the directives/drivers in workplace choice and mobility from different perspectives. The aggregated data was used to discern work-related consequences such as flexibility, workplace choice, work and indoor environment satisfaction, place attachment and identity. The results show that employees who have a conventional working culture develop a new working style: 'fixed-flexible working'. Practitioner Summary: This paper introduces a new POE approach for flexible offices based on occupancy tracking through barcode scanning to explore workplace choice and mobility. More than half (52.1%) of the participants have tended to choose the same desk every day. However, the satisfaction level of the 'mobile' employees was higher than that of the 'fixed flexible' employees.

In most situations managing the strategy execution process include the best practices of Total Quality Management (TQM) through increasing employee job satisfaction. The purpose of this study is to measure the impact of TQM activities on the job satisfaction for small and middle sized companies (SMEs) in the service sector of Turkey with an empirical analysis. Five TQM practices chosen to have a significant impact on job satisfaction are employee training and education, employee relations and teamwork, employee reward and recognition, quality culture and employee empowerment. The variables are analyzed using the Exploratory Factory Analysis (EFA), descriptive statistics analysis, correlation analysis and an independent sample t-test. Results show that employee training and education, and employee relations and teamwork are the most dominant factors on job satisfaction. However, there are some considerable factors such as facilities, job security, rewards and there is little impact of education and salary levels on job satisfaction.

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Due to copyright restrictions, the access to the full text of this article is only available via subscription.In response to rising energy costs and the impetus to reduce environmental impacts, upgrading the large building stock that is responsible for 40% of the total energy consumption to maximum energy efficiency is becoming an important task. Despite the many benefits associated with retrofit projects, they are still only slowly being implemented because of the many challenges that exist. One of these challenges is optimizing the decision between renovation scenarios based on economic and environmental goals, which can be made possible with an accurate pre-retrofit model. The intention of this paper is to introduce a pre-retrofit model that efficiently obtains and integrates multiple forms of building data as a critical step to develop a comprehensive understanding of a building to be renovated. Opportunities for utilizing building information modeling (BIM) and geographical information systems (GIS) for retrofitting projects were explored through the study of a historical campus building. With the use of as-is geometric data and as-is data, building data maps were obtained. The next step of this study is to use the model to conduct scenarios comparison and optimize renovation decision based on economic and environmental goals.Joan & Irwin Jacobs Technion-Cornell Innovation Institute (JTCII) ; TÜBİTA

Bariş (2018) Introduction of a spatio-temporal mapping based POE method for outdoor spaces: Suburban university campus as a case study. Building and Environment, 145. pp. 125-139.

This paper reports the results from a dataset comprising 9794 post-occupancy evaluation (POE) surveys from 77 Australian open-plan offices. This paper specifically focuses on a sub-set of 20 offices (n = 2133), identified from ranking 10 offices each, with the least (n = 1063) and highest (n = 1070) satisfaction scores, respectively. The satisfaction scores were evaluated on the basis of seven factors (i.e., building/office aesthetics and quality, thermal comfort and indoor air quality, noise distraction and privacy, personal control, connection to outdoor environment, maintenance and visual comfort, and individual space). Using the POE survey data from 20 offices, regression analyses and two-way ANOVA tests were carried out to understand the differences in occupants' satisfaction and perceived productivity arising from open-plan offices. According to the statistically significant regression analyses results, it was identified that building/office aesthetics and quality (β = 0.55, p < 0.001) and noise distraction and privacy (β = 0.33, p < 0.001) were the two strongest predictors contributing perceived productivity in low-performance offices. Two-way ANOVA test results for the 10 high-performance offices indicate that the perceived productivity was strongly associated with the office's physical configuration, the employees' working experience, and the working hours at that office.

Purpose In the rise of offices designed to support activity-based working (ABW), parts of industry have fully transitioned to open-plan environments and then later to unassigned seating, whereas other parts, such as tertiary education, are still in the process of moving away from individual offices. There are a few relevant studies to understand how occupants from industry sectors with different levels of adoption of ABW perceived environments designed to support this way of working. This paper aims to contribute to the knowledge gap by providing insight into workers’ satisfaction and dissatisfaction from open-plan offices designed to support ABW along with the key predictors of perceived productivity. Design/methodology/approach A data set of 2,090 post-occupancy evaluation surveys conducted in five sectors – tertiary education, finance, construction, property/asset management and design/engineering – was analyzed. ANOVA and confirmatory factor analysis (CFA) were conducted for the survey questionnaires. First, ANOVA tests were conducted for the whole sample with perceived productivity as the dependent variable. A seven-point Likert scale with five theoretical factors was generated with all survey questionnaires. CFA was performed to show the factor loadings. In addition, regression analyses were carried out for each of factor item taken as the independent variable, where perceived productivity was the dependent variable. Key sources of satisfaction and dissatisfaction per sector were analyzed and differences between occupants reporting a negative or positive impact on their productivity were also investigated. Finally, open-ended comments were analyzed to show the key sources of dissatisfaction based on open-ended comments. Findings Workers from construction were the most satisfied, followed by finance and tertiary education. Occupants from all industry sectors consistently rated their workspaces highly on biophilic and interior design. Distraction and privacy received the lowest scores from all sectors. Open-ended comments showed mismatches between spatial and behavioral dimensions of ABW both for satisfaction and perceived productivity. Interior design was the strongest predictor for perceived productivity for all sectors. Findings dispel the notion that ABW implementation may not be suitable for certain industries, as long as the three key pillars of ABW are fully implemented, including design, behavior and technology. Originality/value This paper provides insight into workers’ satisfaction and dissatisfaction from open-plan offices designed to support ABW in different industry sectors along with the key predictors of perceived productivity.