WoS İndeksli Yayınlar Koleksiyonu

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Accreditation of Communication Education in Turkiye: Research on the Views of Administrator Academicians in Accredited Programs
(Istanbul Univ, Fac Communication, 2023) Kaygusuz, Erdinc
The subject of this study is an examination of how communication programs are accredited in Turkiye in the context of the views of administrator academicians. The research aims to explore the views of administrator academicians who are deans, vice deans, or heads of departments in their institutions regarding the accreditation of communication education in Turkiye. The study interviews 11 administrator academicians working in accredited undergraduate programs under communication faculties or the other faculties in which communication programs are included Turkiye, with the study sample being selected using multi-stage sampling. Proportional stratified and purposive sampling was also used to ensure that the groups in the universe are represented in proportion to their weights. Although minor problems exist in practice, accreditation has been concluded to play a developing role for institutions. Accordingly, accreditation allows institutions to renew, to correct the deficiencies in their organizational chart, to update the curriculum, to strengthen the teaching staff, to increase physical environments and opportunities, and to develop financial resources. In this respect, accreditation in communication education in Turkiye is seen as a concrete output rather than a corporate reputation provider. The findings support other studies that have focused on the benefits of accreditation.
Action Research About Development of Student's Artistic Form of Expression by Conceptual Art Activities
(Ani Publishing, 2019) Basar, Cigdem Tanyel; Ince, Metin
Since the 1960's, rapid changes and transformations in the field of art have been experienced in the light of the technological and social developments that have been experienced, and the expression forms and thought forms of today's art have differentiated. With this change in the art, there was a need for a new structuring and planning in the field of art education. The purpose of this research is to demonstrate how students' original expression patterns in artistic production have been improved through conceptual art practices. The research was designed with an action research model. Participants of the research consist of 12 undergraduate students who took Graphic Design lesson in Fine Arts Education Department of Anadolu University in the fall semester of 2012-2013 and the researcher conducting the course. Data were collected from class video records, semi-structured interviews, student diary, researcher diary, student objects/products and social media interactions. Data of the research were resolved through thematic analysis method. According to findings, it has been seen that the students have developed awareness of their surroundings by experiencing the research and inquiry process. The students have changed their conceptions of art and their distant attitudes to contemporary art and have tried to make meaning. From the research findings, students can be taught various artistic approaches such as art history, visual culture, digital art and contemporary art practices.
Analyzing Cost Efficiency and Project Scope in Post-Disaster Housing: Reconstruction Cases of Toki in Türkiye
(MDPI, 2025) Geylani, Ozlem
The Mass Housing Administration of T & uuml;rkiye (TOKI) operates as the primary public organization responsible for delivering extensive affordable housing throughout T & uuml;rkiye while ensuring disaster resilience. The recent decades of earthquakes and environmental hazards in T & uuml;rkiye have necessitated extensive post-disaster reconstruction initiatives nationwide. In response, TOKI has completed numerous disaster housing projects across the country through an integrated infrastructure framework supporting community recovery. This study presents an extensive statistical evaluation of 664 disaster housing projects constructed by TOKI across 40 provinces. Specifically, a quantitative analysis is conducted on 434 disaster housing projects for which detailed financial data are available. This research examines differences in construction costs between urban mass housing developments and rural village settlements, particularly focusing on the integration of functional structures such as schools, mosques, commercial units, and barns. Although mass housing projects require significantly larger total budgets due to their extensive scale, statistical analysis reveals no significant difference in per-unit construction costs between mass housing and village housing projects. Regression analysis indicates that incorporating barns increased per-unit construction costs, while the presence of schools and mosques significantly decreases these expenses. The findings of this research provide critical insights into the economic and functional factors influencing disaster housing reconstruction in T & uuml;rkiye and offer practical recommendations for improved planning, resource management, and community reconstruction based on an evaluation of functional structures.
Applying Entropy Weighting and 2-Tuple Linguistic T-Spherical Fuzzy MCDM: A Case Study of Developing a Strategic Sustainability Plan for Istanbul Airport
(MDPI, 2024) Mizrak, Filiz; Polat, Levent; Tasar, Sezin Acik
This study presents a novel sustainability plan tailored for Istanbul Airport, leveraging advanced decision-making methodologies to address the urgent need for sustainable practices in aviation. By integrating the entropy weighting and 2-tuple linguistic T-spherical fuzzy multi-criteria decision-making (MCDM) models, the study offers a comprehensive approach to evaluating and prioritizing sustainability criteria based on expert input from 12 professionals. The novelty of this research lies in its unique combination of advanced MCDM techniques with cutting-edge technologies, including IoT-enabled monitoring systems, digital twin models, blockchain-based sustainability reporting, and carbon capture initiatives, tailored specifically for large-scale airport operations. The study develops a phased implementation roadmap comprising three stages: (1) a short-term focus on energy efficiency and renewable energy infrastructure, achieving significant cost reductions within a 3-7.5-year payback period; (2) medium-term initiatives integrating IoT and digital twins to enhance operational efficiency; and (3) long-term measures incorporating carbon capture and blockchain for transparency and compliance. Key implementation steps include upgrading energy systems, deploying IoT sensors, creating digital replicas of airport infrastructure, and establishing regulatory and stakeholder collaboration frameworks. This research contributes a replicable framework for airports worldwide, bridging theoretical models with actionable solutions.
Artificial Intelligence Technologies and Ethics in Educational Processes: Solution Suggestions and Results
(Univ Malaga, 2024) Kolemen, Cansu Sahin
Artificial intelligence is a technology used to imitate the human-like thinking and decision-making abilities of computer systems. This technology enables computers to perform complex tasks such as data analysis, learning, problem solving and decision making. It is used in the field of education as well as in every field. While the use of artificial intelligence in the field of education provides advantages such as providing personalized learning experiences to students, providing teachers with intuition about student performance and developing educational materials, the ethical dimension should not be ignored. Therefore, the aim of this study is to produce solutions to ethical problems in the teaching and evaluation processes of artificial intelligence technologies in education. Qualitative research method was used in this study. It has adopted the phenomenological research approach among qualitative research methods. The concept of phenomenon is also the ethics of artificial intelligence. The working group consists of teachers, educational technologists and academicians. When selecting the working group, it was taken into consideration that there were teachers who use artificial intelligence applications in education and academics and technologists working in this field. Document analysis and focus group interviews were used as data collection tools. Content analysis was performed on the data obtained. According to the results of the study, ethical problems encountered with the use of artificial intelligence in education were identified and solution suggestions were offered.
Binary Particle Swarm Optimization as a Detection Tool for Influential Subsets in Linear Regression
(Taylor & Francis Ltd, 2021) Deliorman, G.; Inan, D.
An influential observation is any point that has a huge effect on the coefficients of a regression line fitting the data. The presence of such observations in the data set reduces the sensitivity and validity of the statistical analysis. In the literature there are many methods used for identifying influential observations. However, many of those methods are highly influenced by masking and swamping effects and require distributional assumptions. Especially in the presence of influential subsets most of these methods are insufficient to detect these observations. This study aims to develop a new diagnostic tool for identifying influential observations using the meta-heuristic binary particle swarm optimization algorithm. This proposed approach does not require any distributional assumptions and also not affected by masking and swamping effects as the known methods. The performance of the proposed method is analyzed via simulations and real data set applications.
Can Commercial Buildings Cope with Australian Bushfires? An IAQ Analysis
(Ubiquity Press Ltd, 2021) Brambilla, Arianna; Candido, Christhina; Sangiorgio, Marco filippo; Gocer, Ozgur; Gocer, Kenan
The Australian 2019/20 summer witnessed an extraordinary bushfire season characterised by unprecedented duration, geographical reach and impact. The aftermath of the bushfires includes increased health-related implications on people due to short and long exposure to poor air quality. The current advice from the Australian authorities in such events is to remain indoors, as it was assumed indoor air quality (IAQ) is healthy. This paper examined that assumption and presents the case study of an office building in Canberra subjected to the 2019/20 bushfires, responding to the need of understanding the ability of air-conditioning buildings to cope with such unprecedented and extreme weather events. Measured data for indoor concentration of CO2, PM10 and PM2.5 recorded a prolonged period of concerning levels, as well as extreme concentration peaks. This poses a significant risk to the occupants' health. The values showed peaks up to 12 times higher for PM10 and 24 times higher for PM2.5 than the recommended critical thresholds. The infiltration factor and protection performance analysis suggest that old filtering systems and low airtightness levels are not optimal in protecting the indoor environment from outdoor air pollutants.
Can Sustainability Reporting Make a Difference?: A Qualitative Analysis on Sustainability Reports of BIST Listed Agri-Food Companies in Turkey
(Ege Univ, Fac Economics & Admin Sciences, 2024) Gürsoy, Özgür Burçak; Akbas, Ilkay
Agri -business is a huge industry, including all operations from farm -level production to storage, manufacture, and distribution of agricultural commodities. This fact, together with worsening social and environmental conditions and pandemic crises, has added to a change in the perception of agriculture in economic construction. The following decades will most probably witness a resurgence of agriculture -based development recipes fed by social, environmental, and governance dimensions of sustainability. This article searches for the sustainability reports of agri-business firms listed in BIST in Turkey. A sampling includes 11 out of 64 listed agri-business firms having recent sustainability reports, which are examined by qualitative data analysis techniques with MAXQDA software. The first argument our findings support is that the agri-food sector is lagging in sustainability reporting compared to other sectors. Second, companies are more ready to comply with issues that are legally regulated. Third, environmental problems are more addressed than social and economic sustainability standards. This study also shows the relative unimportance of topics such as child labor, pesticide use, supply chain traceability, women entrepreneurship, and geographical indication, which can have positive impacts on the Turkish agricultural space if big companies integrate these topics more into their sustainability reporting processes. This article contributes to the literature on sustainability in general and reporting in the agri-food sector in particular.
Case Report: Physiological and Psychological Underpinnings of Muscle Dysmorphia Using EEG, GSR, and Eye-Tracking
(Frontiers Media SA, 2025) Cinaroglu, Metin; Ulker, Selami Varol; Yilmazer, Eda; Sayar, Goekben Hizli
Background Muscle dysmorphia (MD), a subtype of Body Dysmorphic Disorder (BDD), involves an obsessive preoccupation with perceived insufficient muscularity despite an objectively muscular physique. While its psychological features are well-documented, physiological and attentional underpinnings remain underexplored.Objective This exploratory, proof-of-concept case series examines the psychological, physiological, and attentional characteristics of individuals with varying experiences of MD using a multimodal approach combining electroencephalography (EEG), galvanic skin response (GSR), and eye-tracking technologies.Methods Three male participants were purposefully selected to represent distinct clinical profiles: one with active MD and steroid use, one in sustained remission from MD, and one with no MD history. Participants completed validated psychological scales (MDDI, BIDQ, STAI, RSES) and were exposed to personalized visual stimuli (past, current, and idealized body images). A triangulated recording protocol was used to capture EEG, GSR, and eye-tracking data during stimulus exposure.Results Participants with current and past MD showed elevated beta wave activity, increased skin conductance, and attentional biases toward muscular regions, corresponding with higher self-reported distress and anxiety. In contrast, the control participant exhibited stable physiological responses and emotionally neutral reactions. Triangulated data revealed coherent patterns across subjective and physiological domains, supporting the internal validity of the findings despite the small sample.Conclusion These findings illustrate the potential of multimodal assessment in identifying candidate psychophysiological markers of MD. While not generalizable, this case-series provides a valuable framework for future hypothesis-driven research and supports the need for gender-specific diagnostic and intervention strategies in muscle dysmorphia.
Cognitive Behavioral Therapy for Muscle Dysmorphia and Anabolic Steroid-Related Psychopathology: A Randomized Controlled Trial
(MDPI, 2025) Cinaroglu, Metin; Yilmazer, Eda; Ulker, Selami Varol; Sayar, Gokben Hizli
Background/Objectives: Muscle dysmorphia (MD), a subtype of body dysmorphic disorder, is prevalent among males who engage in the non-medical use of anabolic-androgenic steroids (AASs) and performance-enhancing drugs (PEDs). These individuals often experience severe psychopathology, including mood instability, compulsivity, and a distorted body image. Despite its clinical severity, no randomized controlled trials (RCTs) have evaluated structured psychological treatments in this subgroup. This study aimed to assess the efficacy of a manualized cognitive behavioral therapy (CBT) protocol in reducing MD symptoms and associated psychological distress among male steroid users. Results: Participants in the CBT group showed significant reductions in MD symptoms from the baseline to post-treatment (MDDI: p < 0.001, d = 1.12), with gains sustained at follow-up. Large effect sizes were also observed in secondary outcomes including depressive symptoms (PHQ-9: d = 0.98), psychological distress (K10: d = 0.93), disordered eating (EDE-Q: d = 0.74), and exercise addiction (EAI: d = 1.07). No significant changes were observed in the control group. Significant group x time interactions were found for all outcomes (all p < 0.01), indicating CBT's specific efficacy. Discussion: This study provides the first RCT evidence that CBT significantly reduces both core MD symptoms and steroid-related psychopathology in men engaged in AAS/PED misuse. Improvements extended to mood, body image perception, and compulsive exercise behaviors. These findings support CBT's transdiagnostic applicability in addressing both the cognitive-behavioral and affective dimensions of MD. Materials and Methods: In this parallel-group, open-label RCT, 59 male gym-goers with DSM-5-TR diagnoses of MD and a history of AAS/PED use were randomized to either a 12-week CBT intervention (n = 30) or a waitlist control group (n = 29). CBT sessions were delivered weekly online and targeted distorted muscularity beliefs, compulsive behaviors, and emotional dysregulation. Primary and secondary outcomes-Muscle Dysmorphic Disorder Inventory (MDDI), PHQ-9, K10, EDE-Q, EAI, and BIG-were assessed at the baseline, post-treatment, and 3-month follow-up. A repeated-measures ANOVA and paired t-tests were used to analyze time x group interactions. Conclusions: CBT offers an effective, scalable intervention for individuals with muscle dysmorphia complicated by anabolic steroid use. It promotes broad psychological improvement and may serve as a first-line treatment option in high-risk male fitness populations. Future studies should examine long-term outcomes and investigate implementation in diverse clinical and cultural contexts.
Combinatory Play and Infinite Replay Underdefined Causality in the Neon Genesis Evangelion Anime Series and Games
(Stockholm Univ Press, 2021) Bedir, Selen Calik
Comparison of Different Heuristics Integrated with Neural Networks: A Case Study for Earthquake Damage Estimation
(Istanbul Univ, 2022) Malkocoglu, Ayse Berika Varol; Orman, Zeynep; Samli, Ruya
Earthquakes are among the most challenging natural phenomena to predict. Most of these unpredictable earthquakes result in the loss of human lives and property. Seismologists can estimate the probable location and magnitude of such earthquakes. However, the actual time and extent of their impact remain unknown. If the effects of possible earthquakes can be predicted, quick and accurate decisions can be made. For this purpose, developing predictive models about earthquakes is a prevalent and vital issue in the literature. In this study, various Machine Learning (ML) algorithms were compared on a public dataset of earthquakes, which had occurred worldwide and had a local magnitude Ml >= 3, and the algorithm with the highest performance was selected and optimized with various other algorithms. The performances of the models were compared using different performance evaluation metrics such as accuracy, Mean Square Error, Root-Mean Square Error, precision, recall, and f1 score. As a result, it was observed that the Artificial Neural Network (ANN) algorithm optimized with the Particle Swarm Optimization (PSO) algorithm produced the most successful result with an accuracy value of 0.82. Based on the obtained results, it is believed that this model can be used in different earthquake damage prediction studies and as a guide in emergency planning
Comparison of Domino Transplantation with Two-Way Paired Exchange and Normal Transplantation: Acute Rejection, Surgical Complications, and 5-Year Survival Outcomes
(Springer, 2025) Huseynov, Amil; Cicek, Sevim Nuran Kuslu
Background Domino kidney paired donation and Two-Way Paired Exchange have emerged as vital strategies to expand the donor pool in renal transplantation, especially for patients facing ABO or HLA incompatibilities. Despite their potential benefits, concerns remain regarding immunological risks, infectious complications, and long-term graft survival. Methods In this retrospective cohort study conducted at Medicana Transplant Center, 980 adult kidney transplant recipients were categorized into three groups: Domino (n = 144), Two-Way Paired Exchange (n = 350), and Normal Transplant (n = 486). Baseline characteristics, acute rejection rates, and surgical or infectious complications were collected, alongside data on 1-year and 5-year patient and graft survival. Statistical analysis included Kaplan-Meier survival curves and Cox proportional hazards modeling for independent predictors of graft outcomes. Results The Domino group had the highest 1-year acute rejection rate (17.4%) compared to Two-Way Paired Exchange (4.3%) and Normal Transplant (3.7%), yet 1-year graft survival rates remained comparable (92%, 95%, and 96%, respectively; p = 0.271). Infectious complications were more frequent in the Domino group (25%) than in others (p < 0.01). Extended follow-up to 5 years indicated no statistically significant difference in overall graft or patient survival among the three groups (log-rank p = 0.197), despite a trend toward lower 5-year graft survival in the Domino group. Donor-specific antibodies and higher HLA mismatches independently predicted acute rejection. Conclusions Domino transplantation, while associated with higher immunologic challenges, achieves acceptable short-term and 5-year outcomes akin to Two-Way Paired Exchange and Normal Transplant. Careful immunosuppressive strategies, vigilant monitoring, and collaborative protocols are integral for optimizing long-term success in high-risk transplant scenarios.
Consolidating and Contesting Authoritarian Neoliberalism in Turkey: Towards a Framework
(Palgrave Macmillan, 2022) Borsuk, Imren; Dinc, Pinar; Kavak, Sinem; Sayan, Pinar
During the early years of the ruling Adalet ve Kalkinma Partisi (Justice and Development Party, AKP), Turkey was seen as a burgeoning democratic power propped up by economic prosperity in line with the reforms for European Union (EU) accession and International Monetary Fund (IMF) conditionality. However, 20 years later, it is considered an emblematic case of democratic backsliding in line with rising poverty and inequalities that have been amplified as a result of sweeping neoliberal reforms and authoritarian consolidation in the country. The recent literature has identified these concomitant and complementary modes of authoritarian governance and neoliberal policies in Turkey as 'authoritarian neoliberalism'. In this chapter, we discuss the dynamics of consolidation of authoritarian neoliberalism in Turkey as well as the acts of contention against it. Building mainly on the eight case studies presented in this volume, we put forward a framework that explains the consolidation of authoritarian neoliberalism in Turkey through the mechanisms of executive centralisation, autocratic legalism, cronyism, violence-fuelled rentier accumulation, criminalisation and stigmatisation, and contestations against authoritarian neoliberalism through strikes, protests, demonstrations, network building, litigation, everyday struggles, and armed acts of contention.
Correspondence Concerning This Article Should Be Addressed Sent To Fulya Türk
(Int Inst Advanced Studies Psychotherapy & Applied Mental Health, 2025) Turk, Fulya; Kul, Aykut; Hamamci, Zeynep; Sungur, Mehmet Zihni; Sahin, Sengul Kocamer; Elboga, Gulcin
The global COVID-19 pandemic has exerted profound physical and psychological tolls on healthcare professionals, underscoring the urgent need for their mental health support. The objectives of this research are twofold: first, to develop an e-psychological support program based on Cognitive-Behavioral Therapy tailored specifically for healthcare professionals during the COVID-19 pandemic; second, to assess the program's effectiveness in reducing secondary traumatic stress, depression, anxiety, and stress levels, as well as improving healthcare professionals' perception of coping with trauma. Designed as a randomized controlled trial, the study was conducted with 71 healthcare workers employed in a hospital in Gaziantep, Turkey. The developed e-psychological support program consists of six modules: stress model, self-monitoring skills, coping with anxiety, behavioral activation skills, and cognitive restructuring (two modules). The results showing a significant decrease in anxiety, depression, stress and secondary traumatic levels in the intervention group compared to the control group are encouraging. This suggests that the CBT-based e-psychological support program has the potential to have a positive impact on the mental well-being of healthcare professionals. Also, the improvement in healthcare professionals' perception of coping with trauma is an important outcome.CBT has a strong evidence base for treating mental health issues, and adapting it for the specific needs of healthcare workers during a crisis like the pandemic is a promising approach. The development of online interventions for healthcare professionals is valuable not only for the current pandemic but also for future crisis situations. These programs can serve as a template for addressing mental health needs during other global health emergencies.
Current State and Future of Shipping and Logistics
(Elsevier Science Bv, 2013) Tuna, Okan; Duru, Okan
Detection of Damaged Structures from Satellite Imagery Processed by Autoencoder with Boruta Feature Selection Method
(AVES, 2023) Muzoglu, Nedim; Adiguzel, Ertugrul; Akbacak, Enver; Karaslan, Melike Kaya
Many worldwide changing events, including meteorology, weather forecasting, disaster response, and environmental monitoring, are tracked by states or companies via satellite imagery. Early response to disasters is critical for human life. In these cases, artificial intelligence applications are also used to make rapid determinations about large geographical region. In this study, satellite images of flooded and undamaged structures in Hurricane Harvey were used. An autoencoder process has been applied to this dataset to reduce the noise in satellite imagery. AlexNet and VGG16 deep learning (DL) models are used to extract features from both datasets. The most effective features selected by the Boruta feature selection algorithm were classified with the support vector machine, and the highest classification accuracy of 99.35% was obtained. Since disasters involve the evaluation of very big datasets from large geographic areas, presenting the data with the smallest possible feature will facilitate the process. For this reason, by applying dimensionality reduction to the selected attributes, a 98.29% success was achieved in the classification with only 90 attributes. The proposed approach shows that DL and feature engineering are very effective methods to quickly respond to disaster areas using satellite imagery.
Developing a Strategic Framework for Airline Destination Selection: A Multi-Criteria Decision-Making Approach Applied To Turkish Airlines
(Elsevier, 2025) Mizrak, Filiz; Mizrak, Kagan Cenk; Akkartal, Gonca Reyhan
The purpose of this study is to develop a comprehensive decision-making framework that airlines can use to strategically select new destinations, demonstrated here with a case application for Turkish Airlines. Addressing the complexities of route expansion, the study integrates the Entropy weighting method with the 2-Tuple Linguistic T-Spherical Fuzzy Decision by Opinion Score Method (2TLTS-FDOSM) to evaluate potential destinations across critical criteria, including market demand, economic impact, and regulatory environment. Data were collected from industry reports, expert evaluations, and publicly available aviation metrics to support a thorough and adaptable analysis. Findings from the Turkish Airlines case reveal San Antonio, TX (SAT), Portland, OR (PDX), and Nashville, TN (BNA) as top-ranked destinations, each offering distinct economic and operational benefits. This study contributes to aviation management literature by presenting a versatile, data-driven framework that can guide route selection for carriers in competitive markets. The framework's ability to balance quantitative and qualitative insights underscores its potential for broader application in network planning, promoting sustainable growth within the aviation industry.
The Development and Validation of an Integrated Assessment of Irrational Beliefs Concerning Basic Psychological Needs: The Rational Emotive Self-Determination Scale for Workers
(Frontiers Media Sa, 2025) Artiran, Murat; Tinaz, Pinar; Simsek, Omer Faruk; Miller, Anthony; Vione, Katia Correa; Turner, Martin James
Introduction Recently a new approach to understanding human behaviour has emerged that integrates rational emotive behaviour therapy (REBT) from the cognitive behavioural tradition, and self-determination theory (SDT) from the humanistic tradition. In the current study, we develop a psychometric that conceptualizes this new approach in organisational settings; the rational emotive self-determination scale for work (RESD-W). The RESD-W assesses respondents' irrational beliefs (from REBT) concerning the basic psychological needs (from SDT), namely perceptions of autonomy, competence, and relatedness within their work life. The RESD-W builds on initial validations of the RESD in adolescent populations (RESD-A).Methods In the current paper, the psychometric properties of the 16-item RESD-W were examined across five studies, in which the factor structure, the reliability of the scale, and construct and criterion-oriented validity of the RESD-W were assessed.Results Analyses confirmed theoretical expectations and yielded good psychometric properties. Scores in the RESD-W were associated with anxiety and depression, and negative emotions in the workplace.Discussion The results are discussed regarding practice, highlighting that work related psychological wellbeing may be predicated on the integration of irrational beliefs and basic psychological needs.
Differences in Occupants' Satisfaction and Perceived Productivity in High- and Low-Performance Offices
(MDPI, 2019) Gocer, Ozgur; Candido, Christhina; Thomas, Leena; Gocer, Kenan
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 (beta = 0.55, p < 0.001) and noise distraction and privacy (beta = 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.

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