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This study aimed to identify the level of students' academic integration in the physical environment of the classroom.

This study used an experimental approach. The study sample consisted of 60 students, who were divided into an experimental group (n = 30) and a control group (n = 30) in two classrooms (classes 9 and 13). To verify the equivalence of the two groups, an ANOVA test was performed to determine the level of academic integration, and identify any statistically significant differences between the two groups before separating them and controlling all the other variables, except for the classroom environment variable.

The results revealed no statistically significant differences in the mean of pre-application academic integration. Ten days later, the lecturer explained the topic within the academic course and redistributed the scale of academic integration. The results of the second application revealed differences in the average mean of academic integration in favour of the experimental group (class 13). To identify statistically significant differences, a t-test was used for independent samples. The results showed statistically significant differences in the level of academic integration of the experimental group attributed to the variable of physical environment in favour of class 13.

This study recommend to proposing future physical learning environments in classrooms by improving physical aspects. These new learning environments can enhance the cooperation between teachers and students, allow for easier conveyance of ideas and promote students' ability to solve problems more effectively. The use of Metaverse technology in education may create an appropriate virtual physical environment that solves the problem of the physical environment and raises the level of academic integration of students.

We applied a true-experimental randomized control posttest design to collect and analyze quantitative and qualitative data to compare the effects of the AR and traditional board games on students’ SDG learning achievements.

We applied a true-experimental randomized control posttest design to collect and analyze quantitative and qualitative data to compare the effects of AR and traditional board games on students' SDG learning achievements.

Our analysis of the quantitative and qualitative data revealed that the effects of AR and traditional board games on the students' cognitive outcomes differed significantly, indicating the importance of providing a situated learning environment in SDG education. Moreover, the students perceived that the incorporation of the AR game into SDG learning improved their learning effectiveness – including both cognitive and affective dimensions – thus confirming its educational value and potential in SDG learning.

To the best of our knowledge, this is the first study to explore the effectiveness of different learning tools (AR and traditional board games) and to evaluate the importance of providing a situated learning environment through a true-experimental randomized control posttest design.

Restaurant operators often use auspicious connotations embedded in the names and shapes of dishes to increase consumers’ purchase intentions. However, the interaction effect of multiple auspicious cues (i.e. food name and shape) on purchase intentions has rarely been examined in the restaurant context. Thus, grounded in processing fluency theory, this study investigates the direct influence of the two-way interaction effect of food name (auspicious vs nonauspicious) and shape (auspicious vs. nonauspicious) on purchase intentions and its indirect influence via perceived auspiciousness and positive emotions.

Utilizing a 2 (food name: auspicious name vs. nonauspicious name) × 2 (food shape: auspicious shape vs. nonauspicious shape) between-subjects design, the authors conducted two experimental studies with 356 Chinese customers. In Study 1, which focused on a main dish, we investigated the two-way interaction effect food name × food shape on purchase intentions. In Study 2, we replicated this experimental study by focusing on a different food type (i.e. dessert) to test the direct and indirect influences of the two-way interaction of food name × food shape on purchase intentions through perceived auspiciousness and positive emotions.

The results reveal that the congruity condition of auspicious names and shapes significantly influences consumers’ purchase intentions. Congruity with auspicious food cues also indirectly affects purchase intentions through consumers’ perceived auspiciousness and positive emotions. These effects were consistently observed in two experimental studies analyzing different dish types (main dish and dessert).

Restaurateurs should consider utilizing auspicious food cues to attract customers. Specifically, they should combine both food name and shape to increase their perceived auspiciousness and sales.

This study tested processing fluency theory using auspicious food cues. This study contributes to the hospitality literature by improving our understanding of the congruence effect by exemplifying the conceptual alignment between food name and food shape.

This paper aims to examine prospective graduate students' attitudes toward educational loan borrowing in an experimental setting.

Participants were randomly assigned to two treatment groups and one control group. Subjects in experimental group 1 received financial education: a short online course on the economic viability of getting a master's degree and how to finance it with a graduate student loan, while subjects in experimental group 2 received financial education along with information on the availability bias.

Relying on a control group in the assessment of financial literacy education intervention impacts, this research finds positive causal treatment effects on individuals’ attitudes toward debt-financed graduate education. In comparison to the control group, experimental subjects perceived the possibility of going into debt with a graduate loan to complete a master’s degree as less stressful and worrying.

This study has important educational policy implications to prevent students from stopping investing in human capital by perceiving educational loan debt as something stressful or worrying. The results can help potential (and current) grad students develop a feasible financial plan for graduate school by encouraging higher education institutions to implement educational loan information and financial education into university seminar courses for better graduate student loan decision-making.

Student attitudes toward debt have been analyzed in the context of higher education, but only a few researchers internationally have used an experimental design to study personal financial decision-making.

The widespread use of washing machines in textile dyeing and finishing boosts product quality while leading to significant wastewater production. This wastewater poses environmental risks due to the textile industry's high pollution levels and water consumption. Sustainability hinges on minimizing water usage and treating wastewater for reuse. This study employs Matlab R2020a and Python 2023 to model experimental designs for treating textile production wastewater using the Fenton oxidation method, aiming to address sustainability concerns in the industry.

The Fenton oxidation process's efficacy and optimal operating conditions were determined through experimental sets employing the Box–Behnken design. Assessing machine learning algorithms on the data, Matlab R2020a utilized an artificial neural network (ANN), while Python 2023 employed support vector regression (SVR), decision trees (DT), and random forest (RF) models. Evaluation of model performance relied on regression coefficient (R2) and mean square error (MSE) outcomes. This methodology aimed to refine the Fenton oxidation process and identify the most efficient parameters, leveraging a combination of experimental design and advanced computational techniques across different programming platforms.

The study identified optimal conditions: pH 3, Fe+2 concentration of 0.75 g/L, and H2O2 concentration of 5 mM, yielding 87% COD removal. The Box–Behnken design achieved a high R2 of 0.9372, indicating precise predictions. Artificial neural networks (ANN) and support vector regression (SVR) exhibited successful applications, notably achieving an R2 of 0.99936 and low MSE of 0.00416 in the ANN (LOGSIG) model. However, decision trees (DT) and random forests (RF) proved less effective with limited datasets. The findings underscore technology integration in treatment modeling and the environmental imperative of wastewater purification and reuse.

This study, in which water use and wastewater treatment are evaluated with technological integration such as machine learning and data management, reveals how to contribute to targets 6, 9, 12, and 14 within the scope of UNEP 2030 sustainable development goals.

Even though it is widely used, reinforced concrete (RC) is susceptible to damage from various environmental factors. The hazard of a fire attack is particularly severe because it may cause the whole structure to collapse. Furthermore, repairing and strengthening existing structures with high-performance concrete (HPC) has become essential from both technical and financial points of view. In particular, studying the postfire behavior of HPC with normal strength concrete substrate requires experimental and numerical investigations. Accordingly, this study aims to numerically investigate the post-fire behavior of reinforced composite RC slabs.

Consequently, in this study, a numerical analysis was carried out to ascertain the flexural behavior of simply supported RC slabs strengthened with HPC and exposed to a particularly high temperature of 600°C for 2 h. This behavior was investigated and analyzed in the presence of a number of parameters, such as HPC types (fiber-reinforced, 0.5% steel, polypropylene fibers [PPF], hybrid fibers), strengthening side (tension or compression), strengthening layer thickness, slab thickness, boundary conditions, reinforcement ratio and yield strength of reinforcement.

The results showed that traction-separation and full-bond models can achieve accuracy compared with experimental results. Also, the fiber type significantly affects the postfire performance of RC slab strengthened with HPC, where the inclusion of hybrid fiber recorded the highest ultimate load. While adding PPF to HPC showed a rapid decrease in the load-deflection curve after reaching the ultimate load.

The proposed model accurately predicted the thermomechanical behavior of RC slabs strengthened with HPC after being exposed to the fire regarding load-deflection response, crack pattern and failure mode. Moreover, the considered independent parametric variables significantly affect the composite slabs’ behavior.

The purpose of this study is to investigate the influence of IP (Intellectual Property) on the intention for premium consumption of Generation Z, and to construct a theoretical model of IP on the premium consumption of Generation Z. Based on the results of the study, it provides better marketing suggestions to merchants, and is an expansion of previous research on the consumption behavior of Generation Z.

This paper contains two empirical tests and one experimental analysis. First, this study crawl over 5,000 pieces of Generation Z’s consumption data from Poizon, an e-commerce platform and exclusive trending community for Generation Z. Second, this study designs a two-group online experiment to collect 292 valid data from members of the Generation Z. The authors use Stata software for multiple linear regression, t-tests, and ANOVA to test the hypotheses.

The results of the data analysis show that IP has a significant positive effect on the premium consumption intention of Generation Z, and the limited release strategy positively moderates the effect. Self-image congruence and social identification play mediating role in the influence of IP on Generation Z’s premium consumption.

First, this study finds a link between IP and commodity premiums, which is the first study to explore the effect of IP on commodity price changes. Second, this study is the first to examine the marketing science value of IP using a combination of empirical tests and experimental analysis. These fill research gaps. Finally, the mechanism of IP’s influence on Generation Z’s premium consumption is revealed, enriching the literature on Generation Z’s consumption behavior.

In this research, we designed and implemented a unique vignette experiment to study the effect of managers' perceptions of institutional distance on foreign location choice, as well as the moderating effect of managerial international experience and preferred entry mode on this relationship.

We employ an experimental vignette methodology (EVM) approach applied in the context of Chinese managers to test the causal relationships depicted in our hypotheses. In this way, we measure the decision-makers' perceptions ex ante, i.e. in conjunction with and prior to a decision about a foreign location choice.

Our findings show that managers' ex-ante perceptions of institutional distance negatively affect decisions on foreign location choice. Also, we find that managerial international experience and preference for high commitment entry modes mitigate the negative effect of managers' perceptions of institutional distance on foreign location choice.

This research study adds to our understanding of the effect of managers' perceptions of institutional distance and managerial contingencies on foreign location decisions. Further, it advances novel experimental design in international business research in general and on foreign location choice in particular.

Despite increased interest in the Operator 4.0 concept, there has been scarce attention on practice-oriented frameworks that can assist firms in reaping the potential benefits of technologies within the I4.0 framework. The purpose of this paper is to provide an integrative framework on how to engage Operator 4.0 effectively.

Following meta-synthesis logic and integrative conceptual analysis, this study synthesizes and integrates experimental case studies on Operator 4.0 solutions. The analysis is conducted on 24 cases retrieved from peer-reviewed articles.

The analysis revealed several factors that determine the type and extent of benefits that can be realized within a human-cyber-physical system. However, enhancing these capabilities is not straightforward, as several factors can inhibit the realization of these capabilities. Firstly, the benefits vary depending on the type of Operator 4.0. Secondly, the interoperability of the introduced I4.0 solution with the existing systems is crucial. Thirdly, the adaptability of the solution to serve multiple purposes is crucial, as it tends to increase technology acceptance.

The studies reviewed in this research were based on experimental cases, with limited implementation of the solutions they proposed. As such, their implications when implemented on a larger scale are tentative.

The present study has synthesized existing experimental cases and developed an integrative framework to guide the implementation of Operator 4.0. By gathering primary insights from these experiments, we have clarified when and how Operator 4.0 and the required interactions can lead to successful implementation.

The flipped classroom model is an emerging teaching pedagogy in universities, colleges and secondary schools. This model will likely be successful if students prepare and acquire basic knowledge before class hours. Pre-class video lectures are common for students to access knowledge before class hours. However, students often do not watch the pre-class videos or do so only immediately before class hours due to poor engagement and supporting strategies, which can have detrimental effects on their learning achievement. To address this issue, embedding quiz questions into pre-class recorded videos may increase the completion of pre-class activities, students' engagement and learning success. This study examines the effect of a quiz-based flipped classroom (QFC) model to improve students' learning achievement and engagement in a computer science course.

The study involved 173 participants divided into experimental and control groups. The experimental group consisted of 78 students who used the QFC model, while the control group consisted of 73 students who used the conventional flipped classroom (CFC) model.

The 10-week experiment showed that the QFC model effectively improved students' learning achievement and engagement (both behavioral and agentic) compared to the CFC model.

Embedding quiz strategy into the pre-class video demonstrated the potential support to enhance the efficacy of the CFC model. Based on the results of this research, the authors recommended that flipped educators can use the quiz strategy to minimize pre-class issues (especially students' disengagement).

This research adds to the existing literature by evaluating the effect of the newly proposed model on students' learning outcomes and engagement. This study's results can guide colleges and universities intending to implement a blended learning or flipped learning model. The research also gives design, content and course implementation guidelines, which can help engage students to achieve their learning objectives.