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Titanium dioxide (TiO₂) has high opacity, high brightness and whiteness, owing to its high refractive index value. It is mainly used in the coating industry and continuous efforts have been made to replace some of the TiO₂ in paint with new pigments. This study aims to replace part of TiO₂ pigment with various percentages of BaSO₄, CaCO₃ and kaolin in styrene butyl acrylate-based paint formulations, without changing the properties of paints using only titanium dioxide.

To determine the optimum use rate of new pigment mixing, opacity, gloss, scrub resistance and weather resistance properties have been investigated in the water-based paint formulation. The morphological properties of these samples were examined by scanning electron microscopy analysis.

In the total color change (ΔE) measurements, it was observed that the sample coded 85Ti/15Ba produced extremely similar results to the situation when TiO₂ was used alone. It was seen that the best results were obtained when 85Ti/15Ba was used instead of TiO₂.

Comparison research on the impact of replacing TiO₂ with BaSO₄, CaCO₃ and kaolin on the performance characteristics of water-based styrene butyl acrylate-based paint formulations has not been done in the literature, according to the literature search.

This study explores tourists' virtual reality experiences during the transition to the Metaverse.

Qualitative approach was employed to capture tourists' virtual reality experiences and knowledge of the Metaverse at two five-star hotels in Kusadasi (Republic of Turkey). The data were collected from Kusadasi using a purposive sampling technique. The research design focused on data collection with the structured interview technique. The interview form consisted of 7 questions in total, and a voice recorder was used to record the answers of the participants. After the first 4 questions were asked, the participants were presented a virtual reality experience with the virtual reality (VR) glasses. The interview was held face-to-face with thirty-five participants consisting of domestic and foreign tourists in two five-star hotels in the summer season of 2022. The collected data were analyzed with the content analysis technique and themes were created.

This study's findings enhance the conceptual capital in this emerging field and provide insights into many of the participants who have and have never experienced virtual reality applications and who are familiar and unfamiliar with the Metaverse as a concept.

This study generates empirical data that informs contemporary debates about virtual reality and the Metaverse.

The findings show that most participants have never experienced a virtual reality application. Hotels and travel agencies should be aware of this new futuristic technology before the Metaverse transition. Metaverse is for generation Y and Z instead of Baby Boomers and generation X.

This study is unique in terms of depth and fills the gap as it provides useful insights regarding the evaluation of tourists' virtual reality experiences in the transition process to the Metaverse.

This study aims to develop a predictive model using machine learning techniques to forecast construction dispute outcomes, thereby minimizing economic and social losses and promoting amicable settlements between parties.

This study develops a novel conceptual model incorporating project characteristics, root causes, and underlying causes to predict construction dispute outcomes. Utilizing a dataset of arbitration cases in Türkiye, the model was tested using five machine learning algorithms namely Logistic Regression, Support Vector Machines, Decision Trees, K-Nearest Neighbors, and Random Forest in a Python environment. The performance of each algorithm was evaluated to identify the most accurate predictive model.

The analysis revealed that the Support Vector Machine algorithm achieved the highest prediction accuracy at 71.65%. Twelve significant variables were identified for the best model namely, work type, root causes, delays from a contractor, extension of time, different site conditions, poorly written contracts, unit price determination, penalties, price adjustment, acceptances, delay of schedule, and extra payment claims. The study’s results surpass some existing models in the literature, highlighting the model’s robustness and practical applicability in forecasting construction dispute outcomes.

This study is unique in its consideration of various contract, dispute, and project attributes to predict construction dispute outcomes using machine learning techniques. It uses a fact-based dataset of arbitration cases from Türkiye, providing a robust and practical predictive model applicable across different regions and project types. It advances the literature by comparing multiple machine learning algorithms to achieve the highest prediction accuracy and offering a comprehensive tool for proactive dispute management.

This study aims to prevent occupational accidents occurring in the manufacturing industry by means of touch sensors. When the occupational accidents occurring in the manufacturing industry around the world are examined, it is seen that approximately 88% of occupational accidents occur from “dangerous movement” and 10% from “dangerous situation.” Although some studies related to safety culture studies, safety studies in design and collective or personal protective measures have been started, they have not been brought to an adequate level. It is observed that studies on dangerous movements continue even in many developed countries. In this study, first of all, a literature study was conducted. Occupational accidents experienced in the manufacturing sector in Turkey have been examined. In line with these investigations, a prototype circuit protection system has been developed that can prevent accidents caused by dangerous movement. With the circuit, its applicability and effectiveness were measured by conducting experiments on different manufacturing machines. The prototype circuit applied in this paper was made based on the logic of protective measures made on sawstop machines used in different sectors. In the experimental study conducted, it was observed that in 30 experiments conducted with a prototype on ten separate manufacturing machines, it stopped the machines 26 times at minimum and 29 times at maximum. On average, when looking at the system efficiency values, it was seen that the system was 81.6% effective, and it was observed that positive results could be obtained when converted into a real product.

In this study, their contribution to the prevention of work accidents caused by presses and rotary accents from machines used in the manufacturing industry by means of touch sensors used in Industry 4.0 was examined.

With Industry 4.0, different automation systems began to be switched in many areas and sectors. Studies have started on different sensors used also in Industry 4.0 in occupational health and safety studies, but it is seen that they have not been applied at an adequate level. It should be designed in such a way as to prevent errors or stop these errors in the studies performed. Today, sensors are produced at much lower costs than before. In addition, the constantly developing technology provides great convenience for these applications.

This study was applied for press and cylinder machines from manufacturing machines. This study has been tried for machines producing a maximum pressure of 300 tons.

A prototype was designed. Trials were done on some machines by prototype. There could be improve and find different solutions for safety problems in the industry with this perspective.

This qualitative study has two aims. The first is to explore the cognitive, affective, and behavioural dimensions of Eurasian self-initiated expatriates’ (SIEs) work and non-work adjustments in Korea. The second is to understand how the Confucian-oriented Korean culture influences Eurasian SIEs' work and non-work domains, in particular their organisational practices and relations with locals.

This study was conducted through a qualitative analysis of interviews conducted with 27 Eurasian SIEs working in Korea. The interviews were conducted face-to-face with open-ended questions.

Eurasian SIEs in Korea express different cognitive, affective, and behavioural life and work adjustment processes that affect their future careers. A high level of language proficiency and knowledge of cultural and social expectations does not guarantee work and life adjustment success. Due to the heavy presence of Korean culture in work and living environments, SIEs face challenges in joining social and work networks and balancing work and life domains, which slows down adjustment. Results indicate that SIEs adjusted well regarding cognitive and behavioural dimensions in work and non-work domains. However, affective adjustment is difficult to achieve, even for SIEs who have lived in the country for many years, and many have the intention to leave if there were other options.

This study contributes to the literature by focussing on the multidimensionality of SIEs' work and life adjustments, with cognitive, affective, and behavioural components. SIEs have been in a complicated process of adaptation and integration for a long time. This study attempts to contribute to SIE literature by analysing the elements of Confucianism-oriented Korean culture and organisational practices prevalent in SIEs' multidimensional adjustment and career challenges.

This study aims to present a novel Genetic Algorithm-Based Design Model (GABDM) to provide reduced-risk areas, namely, a “safe footprint,” in interior spaces during earthquakes. This study focuses on housing interiors as the space where inhabitants spend most of their daily lives.

The GABDM uses the genetic algorithm as a method, the Nondominated Sorting Genetic Algorithm II algorithm, and the Wallacei X evolutionary optimization engine. The model setup, including inputs, constraints, operations and fitness functions, is presented, as is the algorithmic model’s running procedure. Following the development phase, GABDM is tested with a sample housing interior designed by the authors based on the literature related to earthquake risk in interiors. The implementation section is organized to include two case studies.

The implementation of GABDM resulted in optimal “safe footprint” solutions for both case studies. However, the results show that the fitness functions achieved in Case Study 1 differed from those achieved in Case Study 2. Furthermore, Case Study 2 has generated more successful (higher ranking) “safe footprint” alternatives with its proposed furniture system.

This study presents an original approach to dealing with earthquake risks in the context of interior design, as well as the development of a design model (GABDM) that uses a generative design method to reduce earthquake risks in interior spaces. By introducing the concept of a “safe footprint,” GABDM contributes explicitly to the prevention of earthquake risk. GABDM is adaptable to other architectural typologies that involve footprint and furniture relationships.

This article aims to question the role of attitude towards behavior and bank reputation in the relationship between consumer compatibility and behavioral intention.

Using survey data from 640 mobile bank users in a developing country setting, the authors explored the conditional effects of users' compatibility on their future intention to use mobile banking services through attitude towards use as a function of perceived corporate reputation.

The results indicated that the attitude towards using mobile banking services has a partial mediating role in the relationship between compatibility and future intention to use. This indirect path depends on the reputation of the bank.

The original contribution of this study is to detail the mechanism between compatibility and usage intention that emerges within the scope of the model the authors propose and to realize this through the Johnson-Neyman approach.

In this chapter, a situation analysis was made on the use of technology in gastronomy, an ever-growing and exciting research area. The use of technology is essential in food production processes as well as in all sectors, and accordingly, the number of research on the subject has increased in recent years. Therefore, in the study, information is also given about trend applications today in addition to the use of technology in gastronomy. It is aimed to present the studies conducted by different disciplines together, to reveal the current situation in the light of the studies carried out on a national and international scale and to support possible future studies.

Ultrasonic welding is an emerging apparel manufacturing technique. However, the applications are widely explored in the field of technical textiles, with less exploration in the apparel endues. The purpose of this study is to explore the application of ultrasonic welding in apparel by analyzing the impacts of different parameters.

This study analyzed the influence of ultrasonic welding parameters, including pressure, welding speed and ultrasonic power on the seam performances (seam strength, seam bursting strength, seam thickness and seam stiffness). The parameters are optimized using Box–Behnken experimental design to achieve better seam performances.

The properties of ultrasonic seams are influenced by welding and fabric properties. Ultrasonically welded seams showed better performances in the case of comfort properties of seams, whereas the functional properties are lesser compared to conventional seams.

The findings of the research clearly outline the level of influence of different parameters on the performance of the ultrasonically welded seams in knitted fabrics, which can greatly help in applying ultrasonic welding manufacturing methods in apparel manufacturing.

Repeat customers play an important role in the restaurant sector. Previous studies have confirmed the positive effect of managerial responses on customer relationship management. However, the practice of managerial response strategies toward repeat customers in the restaurant sector remains unclear. This study aims to explore how social influence and the revisit intention of customers affect the responding behavior of restaurant managers.

This study collects information of 251,944 customer reviews and managerial responses from 1,272 restaurants on Yelp (a leading restaurant review website around the world) and builds four econometric models (with restaurant and month fixed effects) to test the hypotheses empirically.

The empirical results show that restaurant managers are less likely to respond to reviews posted by repeat customers (10% lower than that of new customers). This effect is moderated by customer social influence, which entails that repeat customers with great social influence are more likely to receive managerial responses. Moreover, reviews from repeat customers who have had a longer time since their last consumption are also more likely to receive managerial responses.

The results present implications for restaurant managers in business practice regarding managerial response. Managers should take advantage of platform designs and tools (i.e. customer relationship management programs to keep track of repeat customers) to locate repeat customers and avoid the potential negative effects caused by their selected response strategies.

To the best of the authors’ knowledge, this study is among the first attempts to examine empirically how restaurant managers respond to reviews generated by repeat customers in real business practice and reveals what drives such activities from the perspectives of social influence and revisit intention.