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This study aims to analyze and understand mutual relationships between lean and agile enabling factors in the context of the construction domain and put forth the most driving and dependent enablers for a hybrid lean–agile system (HLAS).

A threefold research flow is adopted. First, the content analysis of literature stemmed from the identification of preliminary enablers (n = 26). Second, a questionnaire survey (n = 101) is administered to downsize enablers to ten using the relative importance index. Further, in the third phase, interpretive structural modeling (ISM) and the cross-impact matrix multiplication applied to classification analysis were performed amid the ten key enablers through pairwise interactions from subject matter experts (n = 19). Hierarchical representation of enablers has been presented, which facilitates a conceptual model for application in the construction industry.

The ISM model demonstrates a three leveled classification structure that showcases direct and transitive relationships among various enablers. “Use of project management tools” is the driving enabler, followed by “collaborative and common data platform working” and “institution of team training” are critical enablers to HLAS adoption.

A structured way of identification of interdependent among lean–agile is a vital unique contribution to this study. The results serve as a knowledge base for practical adoption of HLAS and may prove to be influential in developing a framework for easier adoption in developing countries.

Based on Kansei Engineering, this study obtained consumers' emotional preferences aiming to enhance the emotional connection between consumers and clothing to extend the service life of clothing and realize sustainable clothing design.

Six Kansei word pairs that are the most important to consumers were identified through literature reviews, magazines, websites, card sorting of consumers and cluster analysis. Finally, the consumers scored the 32 product specimens through a 5-level rating semantic differential scale questionnaire of six Kansei word pairs. The researchers verified the consumers' emotional preferences through principal component analysis and established the relationship between Kansei words and design elements of color through partial least squares.

The study found consumers' emotional preferences: elegant, minimalist, formal, casual, mature, practical and distinctive style. Besides white, black, gray, blue, consumers will also like red and yellow-red in the future. The crucial findings of this study are to get recommended guidelines that consumers' emotional preferences match the corresponding design elements.

The study's findings can be used to style the design of men's plain-color shirts and guide online marketers and designers to design apparel that meets consumers' emotional needs to develop consumers' sustainability reliance on clothing. This study also explains the overall process and methodology for integrating consumer preferences and product design elements.

Augmented reality is one of the technologies that developed and became widespread, especially after the 2000s. It is seen that innovations such as 3D virtual reality glasses, artificial intelligence-supported smart chatbots that communicate with customers in a virtual environment, keyless hotel systems, the Internet of Things, augmented reality applications, smart personal assistants, digital infrastructure concepts and face recognition systems are used in tourism businesses. The place and use of augmented reality technologies in tourism enterprises are discussed in this study. This study was evaluated from the perspective of UTAUT2. The purpose of this study is to examine the usability of augmented reality technologies in tourism businesses.

Within the scope of the study, interviews were held with augmented reality application developers, digital marketing agencies and accommodation business managers. The obtained data were processed with the MAXQDA analysis program.

It has been determined that augmented reality is a useful and informative technological tool for tourists, it can help sales, promotion and marketing activities, and its usability potency in accommodation businesses is high.

When the literature is reviewed, it is understood that the studies that apply to the opinions of the application developers and the managers of the accommodation establishments are limited. Therefore, this study has been prepared to contribute to the literature in this respect. This study examines and discusses the use of augmented reality technologies in tourism enterprises, the benefits and difficulties they will create from the perspective of application developers and accommodation business managers and their place in tourism enterprises. This study was evaluated from the perspective of UTAUT2. There is a need for research developed using UTAUT models in technology acceptance studies. In this respect, it will contribute to the literature.

This paper aims to develop a vision for the future identifying how digital nomadism affects the labor markets in the tourism industry.

The qualitative research method was used. The research data were collected using a semistructured interview form developed by the researcher. The sample consists of twenty people working in the tourism industry as tour guides, travel agency owners, accommodation sector employees and professional managers. The content analysis method was used to analyze the data.

It was found that employees in the tourism industry are familiar with digital nomadism, interact with employees working as digital nomads and may prefer the digital nomad way of working, while employees in the accommodation sector cannot work as digital nomads due to the nature of their work. It is shown that digital nomadism can be applied to tour guides and travel agency owners.

The data was collected from employees of the accommodation sector, travel agencies, tour guides and employees of the Turkish tourism labor market. It is recommended that the tourism labor markets adapt to the digitalized world and adjust their working models in this context.

This is one of the first studies on the impact of digital nomadism on the tourism labor markets.

This study aims to produce a superhydrophobic fabric surface with a layered rough structure and which are resistant to droplet adhesion. Polydimethylsiloxane (PDMS) systems doped with stearic acid modified titanium dioxide (SA-TiO₂) nanoparticles was sprayed onto the surface of cotton fabric.

This experiment therefore uses a simple method to prepare superhydrophobic textiles by spraying SA-TiO₂ particles mixed with PDMS onto the surface of cotton fabrics. The effects of the ratio of stearic acid to TiO₂, spraying times and tension on the apparent morphological structure and hydrophobic properties of the cotton fabric were investigated.

The results showed that the stearic acid-modified TiO₂ nanoparticles were hydrophobic and more uniformly dispersed in the PDMS solution. When the modification ratio of stearic acid to TiO₂ was 3:5, the water contact angle of cotton fabric was 155.48° and sliding angle was 6.67° under the applied tension for three times of spraying, showing superhydrophobicity. The fabric shows super hydrophobic and anti-adhesive properties to a wide range of liquids such as cola, dyeing liquids, tea, milk and simulated blood. The surface tension of the liquid shows a negative correlation with its adhesion to the fabric.

The SA-TiO₂ and PDMS were applied to the fabric surface by spraying, which not only gave the fabric superhydrophobic properties, but also created anti-adhesion to a wide range of droplets.

The superhydrophobic cotton fabrics prepared by this method showed good anti-adhesive behavior to common stains and simulated blood and can be used in the development of medical protective textiles.

Modification of TiO₂ with stearic acid to prepare SA-TiO₂ with excellent hydrophobic properties, which was mixed with PDMS to make suspensions. Fluorine-free superhydrophobic fabrics were prepared by spraying method. It also exhibited excellent anti-adhesive properties against blood, providing a reference for the preparation of self-cleaning and anti-adhesive surgical gowns.

The purpose of this study is to formulate a new class of vehicle routing problem with an objective to minimise the total cost of raw material collection and derive a new approach to solve optimization problems. This study can help to select the optimum number of suppliers based on cost.

To model the raw material vehicle routing problem, a mixed integer linear programming (MILP) problem is formulated. An interesting phenomenon added to the proposed problem is that there is no compulsion to visit all suppliers. To guarantee the demand of semiconductor industry, all visited suppliers should reach a given raw material capacity requirement. To solve the proposed model, the authors developed a novel hybrid approach that is a combination of block and edge recombination approaches. To avoid bias, the authors compare the results of the proposed methodology with other known approaches, such as genetic algorithms (GAs) and ant colony optimisation (ACO).

The findings indicate that the proposed model can be useful in industries, where multiple suppliers are used. The proposed hybrid approach provides a better sequence of suppliers compared to other heuristic techniques.

The data used in the proposed model is generated based on previous literature. The problem derives from the assumption that semiconductor industries use a variety of raw materials.

This study provides a new model and approach that can help practitioners and policymakers select suppliers based on their logistics costs.

This study provides two important contributions in the context of the supply chain. First, it provides a new variant of the vehicle routing problem in consideration of raw material collection; and second, it provides a new approach to solving optimisation problems.

The imperative to conserve resources and minimize operational expenses has spurred a notable increase in the adoption of lean manufacturing within the context of the circular economy across diverse industries in recent years. However, a notable gap exists in the research landscape, particularly concerning the implementation of lean practices within the pharmaceutical industry to enhance circular economy performance. Addressing this void, this study endeavors to identify and prioritize the pivotal drivers influencing lean manufacturing within the pharmaceutical sector.

The outcome of this rigorous examination highlights that “Continuous Monitoring Process for Sustainable Lean Implementation,” “Management Involvement for Sustainable Implementation” and “Training and Education” emerge as the most consequential drivers. These factors are deemed crucial for augmenting circular economy performance, underscoring the significance of management engagement, training initiatives and a continuous monitoring process in fostering a closed-loop practice within the pharmaceutical industry.

The findings contribute valuable insights for decision-makers aiming to adopt lean practices within a circular economy framework. Specifically, by streamlining the process of developing a robust action plan tailored to the unique needs of the pharmaceutical sector, our study provides actionable guidance for enhancing overall sustainability in the manufacturing processes.

This study represents one of the initial efforts to systematically identify and assess the drivers to LM implementation within the pharmaceutical industry, contributing to the emerging body of knowledge in this area.

The paper aims to examine Indonesian accounting students’ intention to become sustainable accountants (ISAs) using a modified theory of reasoning action model.

Primary data were collected from 239 respondents from five reputable universities in Semarang, Indonesia, using a structured questionnaire. A random sampling technique was employed and used in selecting respondents. The data were then analyzed using smart PLS (version 3.2.9) to obtain the final results.

The results show university sustainability (US) and attitudes toward sustainability (ATS) affect students' intentions to become ISAs. Knowledge has no direct correlation with students' intention to become ISAs. Path analysis shows a significant correlation between US and students' knowledge, attitudes and intentions regarding sustainability.

This is different from previous studies, which only focused on factors influencing students' intentions to pay attention to sustainability. This study focuses on prospective accountants because, in the future, they will be the technical executors of reporting using path analysis. This study further analyzes the relationship between existing antecedent variables. The results show that sustainability at the university is a variable that can influence all other variables.

Throughout human history, the occurrence of disasters has been inevitable, leading to significant human, financial and emotional consequences. Therefore, it is crucial to establish a well-designed plan to efficiently manage such situations when disaster strikes. The purpose of this study is to develop a comprehensive program that encompasses multiple aspects of postdisaster relief.

A multiobjective model has been developed for postdisaster relief, with the aim of minimizing social dissatisfaction, economic costs and environmental damage. The model has been solved using exact methods for different scenarios. The objective is to achieve the most optimal outcomes in the context of postdisaster relief operations.

A real case study of an earthquake in Haiti has been conducted. The acquired results and subsequent management analysis have effectively assessed the logic of the model. As a result, the model’s performance has been validated and deemed reliable based on the findings and insights obtained.

Ultimately, the model provides the optimal quantities of each product to be shipped and determines the appropriate mode of transportation. Additionally, the application of the epsilon constraint method results in a set of Pareto optimal solutions. Through a comprehensive examination of the presented solutions, valuable insights and analyses can be obtained, contributing to a better understanding of the model’s effectiveness.

Night lighting reflects the prosperous development of economic and the increasingly rich and colorful cultural life. Currently, various technical standards, protocols and management specifications have been developed to build a safe, comfortable and economical lighting environment. However, prevailing evaluation systems focus on objective indexes of illumination and have ignored environmental characteristics and subjective feelings and lacked consideration of regional culture, economic benefit, management and maintenance. In this context, a lighting evaluation system combining subjective and objective is proposed for the first time in this study to explore approaches to guide the development of a healthy and comfortable urban night-time environment.

Existing research and relevant lighting standards are analyzed and an evaluation model with a logical hierarchy is constructed by combining with the evaluation theory that is set based on people and the environment. The index weights were scientifically determined on the basis of the analytic hierarchy process (AHP) and fuzzy comprehensive evaluation method. The rationality and validity of the proposed evaluation system is verified in accordance with field projects and case studies.

Taking into account traditional and cultural factors, the evaluation model established has an acceptable accuracy. Evaluation based on subjective-objective combination can provide a scientific basis for the management and optimization of night lighting.

The proposed evaluation system can serve as a guiding reference for other areas of cultural identity and esthetic perspective.