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This paper aims to examine how different contextual contingency factors and organizational goals influence construction clients’ decision-making when procuring contractors in the housing sector. More specifically, it investigates how clients’ choice of procurement strategies and organizational control systems is contingent upon various contextual factors and organizational goals.

It is based on an explorative interview study of clients and contractors in the Swedish housing sector underpinned by a review of organizational control literature.

The client's knowledge and resources, as well as project complexity and uncertainty, are the most important contextual contingency factors, while property management and sustainable development are the most important organizational goals that housing clients consider when designing procurement strategies.

The paper contributes to the understanding of how construction clients choose procurement strategies, by providing new insights into effects of the mentioned contextual contingency factors and organizational goals on clients’ choice of control systems through their procurement strategies.

Property owners who continuously procure housing projects with sustainability requirements and high degrees of complexity and uncertainty should develop knowledge and resources related to their client role, to enable the design and implementation of appropriate procurement strategies.

Novel aspects of the paper are the demonstration of the value of a holistic approach, considering both contextual contingency factors and organizational goals, when selecting control systems and explicit discussion of how the client's knowledge and resources influence possibilities to implement different control systems.

This study aims to provide empirical evidence to verify the dimensional structure of artificial intelligence (AI) Chatbot quality and examine the impact of these dimensions on consumer satisfaction and brand advocacy among Gen Z in the fast food industry in Egypt.

The empirical data was obtained with an electronic self-administered survey instrument from 397 young consumers who had prior experience using AI Chatbots across multiple fast food brands in Egypt. Structural equation modeling was used to analyze the formulated hypotheses.

The results showed that AI Chatbot quality dimensions, specifically information authenticity and system compliance, significantly enhance young consumers’ satisfaction. In addition, information authenticity of AI Chatbot quality was observed to wield a significant influence on young consumers’ advocacy. In contrast, an insignificant relationship was noticed between satisfaction and advocacy. Moreover, the mediating role of consumer satisfaction was not established.

Given that Gen Z is more technology savvy and computer literate, marketers and practitioners of fast food brands should invest in AI tools to respond to young consumers’ expectations and improve their perception of their services.

This study uses stimulus-organism-response theory to understand the mediating effect of young consumers’ satisfaction in the relationship between AI Chatbot quality and consumer brand advocacy within the fast food industry. Also, it introduced two novel main constructs of AI Chatbot quality, namely, information authenticity and system compliance.

This study investigates the moderating effects of consumers’ occupations on their purchase intentions (PIs) for food takeout services using a modified unified theory of acceptance and use of technology model. It evaluates how different occupations influence the relationships between social influence (SI), expectation confirmation (EC), facilitating conditions (FC) and PI.

The study collected data from individuals in various occupations, including technical/associate professionals, executives/professionals, administrative/service workers and manual/operative workers. The data were analyzed using structural equation modeling, while hierarchical analysis assessed how occupation moderated the relationships between latent variables (SI, EC and FC) and PI.

Different occupations have a certain moderating effect on the relationships between SI/EC/FC and PI. For the technical and associate professionals and manual and operative occupations, the moderating effect of FC on PI is stronger than that of EC and SI. For executives and professionals and administrative and service occupations, the moderating effect of EC on PI is stronger than that of SI and FC.

This study provides new insights into how occupational differences influence consumer behavior in the context of online food ordering services. The results expand the application of the unified theory of acceptance and use of technology model and the understanding of the influence of occupation on consumer’ behavior.

Cracks are prevalent signs of pavement distress found on highways globally. The use of artificial intelligence (AI) and deep learning (DL) for crack detection is increasingly considered as an optimal solution. Consequently, this paper introduces a novel, fully connected, optimised convolutional neural network (CNN) model using feature selection algorithms for the purpose of detecting cracks in highway pavements.

To enhance the accuracy of the CNN model for crack detection, the authors employed a fully connected deep learning layers CNN model along with several optimisation techniques. Specifically, three optimisation algorithms, namely adaptive moment estimation (ADAM), stochastic gradient descent with momentum (SGDM), and RMSProp, were utilised to fine-tune the CNN model and enhance its overall performance. Subsequently, the authors implemented eight feature selection algorithms to further improve the accuracy of the optimised CNN model. These feature selection techniques were thoughtfully selected and systematically applied to identify the most relevant features contributing to crack detection in the given dataset. Finally, the authors subjected the proposed model to testing against seven pre-trained models.

The study's results show that the accuracy of the three optimisers (ADAM, SGDM, and RMSProp) with the five deep learning layers model is 97.4%, 98.2%, and 96.09%, respectively. Following this, eight feature selection algorithms were applied to the five deep learning layers to enhance accuracy, with particle swarm optimisation (PSO) achieving the highest F-score at 98.72. The model was then compared with other pre-trained models and exhibited the highest performance.

With an achieved precision of 98.19% and F-score of 98.72% using PSO, the developed model is highly accurate and effective in detecting and evaluating the condition of cracks in pavements. As a result, the model has the potential to significantly reduce the effort required for crack detection and evaluation.

The proposed method for enhancing CNN model accuracy in crack detection stands out for its unique combination of optimisation algorithms (ADAM, SGDM, and RMSProp) with systematic application of multiple feature selection techniques to identify relevant crack detection features and comparing results with existing pre-trained models.

Intellectual experiences focus on users’ information processing and critical thinking toward stimuli. The deployment of humanoid service robots as novel stimuli in tourism and hospitality has influenced users’ perceptions and may affect their intellectual engagement. This paper aims to connect four contemporary theoretical concepts: the service robot acceptance model, technological fear, the uncanny valley theory and the stereotype content model, to investigate users’ perceptions and intellectual experiences toward humanoid service robots.

Scale development procedures were conducted: literature review, checking face and content validity, factorizing items and dimensions, achieving construct and criterion validity and testing predictive validity.

Through literature review and free-response tasks, 43 measurement items were generated. Next, 1,006 samples from two cross-cultural groups refined the scale. Finally, a reliable and valid scale with four dimensions measuring users’ perceptions of humanoid service robots was determined.

Humanoid service robots should be designed to enhance functionality and innovativeness while minimizing stiffness, inflexibility, unsafety and danger to improve users’ intellectual engagement.

This study provides a novel examination of users’ intellectual experiences toward humanoid service robots by connecting four contemporary theories of users’ perceptions. This study enriches human–robot experience through an integrated perspective and presents a rigorous examination of the scale’s psychometric properties. A reliable and valid scale for measuring users’ perceptions toward humanoid service robots fills the gaps and serves as an effective predictor of intellectual experience in human–robot literature.

World heritage sites (WHSs) contribute significantly to preserving local identity and the exponential growth of the local economy through tourism. Therefore, it is important to protect landmarks or areas declared as one of the United Nations Educational, Scientific and Cultural Organization (UNESCO) WHSs so that the structure can be preserved and the legacies of the monuments and cultures can be uplifted and sustained. Therefore, it is crucial to consider the idea of charging a premium for some tourism-related goods and services in order to make them more sustainable.

This study utilizes the Choice Experiment (CE) method to evaluate the preferences and willingness to pay (WTP) of visitors at the WHS in Melaka, Malaysia. Through a structured survey and choice modeling approach, we assess visitors' preferences for various site attributes and potential management strategies, enabling us to estimate their WTP for heritage preservation.

This paper focuses on assessing the monetary worth visitors associate with preserving a UNESCO WHS in Melaka, Malaysia. The study utilizes a CE methodology to estimate visitors' preferences and their WTP for heritage site preservation. The findings contribute to understanding the economic viability and sustainability of establishing a preservation fund for the site. Overall, this research provides valuable information for decision-makers involved in the preservation and management of cultural heritage sites.

External Validity: The research focuses specifically on the UNESCO WHS in Melaka, Malaysia. The findings may not be directly applicable to other heritage sites or locations with different cultural, socioeconomic or environmental characteristics. Thus, the generalizability of the study’s results to other contexts might be limited.

Conservation Fund Design: The research provides valuable insights into visitors' WTP for a preservation fund. These findings can inform policymakers, site managers and relevant stakeholders in designing and implementing effective conservation funding mechanisms for the UNESCO WHS in Melaka. Understanding visitors' preferences and their willingness to contribute financially can help ensure the sustainable preservation of the site. Revenue Generation: By quantifying visitors' WTP, the study offers practical implications for generating revenue for the preservation fund. Policymakers and site managers can leverage this information to establish appropriate pricing strategies, such as entrance fees or voluntary donations, that align with visitors' valuation and support long-term financial sustainability for site conservation.

Enhanced Conservation Efforts: Understanding visitors' WTP can contribute to increased public engagement and awareness regarding the importance of preserving the UNESCO WHS in Melaka. The findings can be used to foster a sense of ownership and responsibility among visitors, encouraging them to actively participate in conservation efforts and advocate for the site’s protection. Stakeholder Collaboration: The research highlights the need for collaboration between various stakeholders, including government agencies, local communities, NGOs and visitors, to ensure the successful preservation of the heritage site. The study’s insights can facilitate dialogue and cooperation among these groups, promoting shared responsibility and effective decision-making processes for the sustainable management of the site.

The paper brings valuable insights and originality to the field of tourism and heritage preservation. It adds to the discourse on sustainable tourism practices and financial mechanisms to support cultural heritage preservation, offering practical insights for effective site management.

The review paper aims to understand the development of workplace ostracism as a field in organizational studies from 2000 to the present. The study provides a comprehensive synthesis of the current state of the domain by exploring its antecedents, consequences, underlying mechanisms and buffering mechanisms.

The present study analyses 134 published peer-reviewed empirical and non-empirical articles retrieved from the Scopus database. A systematic literature review and bibliometric analyses (using VOS viewer) have been used to gain insights into the development and trends within the field. Bibliometric analyses involved science mapping techniques such as co-citation analysis, co-occurrence of keywords and bibliographic coupling. Combining these three techniques, the study aimed to provide a comprehensive overview of the workplace ostracism research domain's historical, current and future landscape.

In the present study, through descriptive analyses, the authors uncovered publishing trends, productive journals, countries and industries that contribute to this research field. The systematic review enabled the showcasing of the current landscape of workplace ostracism. The bibliometric analyses shed light on major authors, influential articles, prominent journals and significant keywords in workplace ostracism.

This study enriches the existing literature by offering a comprehensive research framework for workplace ostracism. It goes beyond that by presenting significant bibliographic insights by applying bibliometric analyses. Furthermore, this study identifies and emphasizes future research directions using the theory, characteristics, construct and methodologies framework, aiming to expand the knowledge base and understanding of this topic.

While previous research has explored how tourists’ food-related perceptions influence their attitudes and behaviors toward a destination, there is limited understanding of how their psychological perception of a destination’s food affects their behavior. This study examines the relationship between tourists’ food-based self-congruity, attitudes toward local food, destination attachment and behavioral intentions. It also investigates the moderating effect of food cultural proximity on these relationships.

Data were collected through a questionnaire completed by 369 tourists who recently experienced local cuisine during international travels. Structural equation modeling (PLS-SEM) was used to test the research model.

The results showed that as international tourists’ self-congruity with a destination’s cuisine increased, they developed more positive attitudes toward local food and a stronger attachment to the destination. These attitudes and attachments, in turn, positively influenced their behavioral intentions. The perceived cultural proximity of the food moderated the relationship between self-congruity and both tourist attitudes and destination attachment, with lower perceived proximity strengthening these effects. Additionally, self-congruity directly influenced behavioral intentions.

By examining tourists’ food perceptions from the lens of self-congruity, this study uncovers new ways to leverage the symbolic and psychological values of food in destination marketing. Marketers can use these insights to align local food offerings with target tourists’ identities.

This study enhances the understanding of tourists’ food-related perceptions, highlighting the significance of food-based self-congruity in shaping their attitudes and behaviors toward a destination. The findings confirm the influence of symbolic and psychological connections to food on tourists’ attitudes and behaviors.

Recognition of the complexity of job embeddedness in the work environment has grown, highlighting the need for a deeper understanding of the factors that contribute to this phenomenon. This study analyzed how and when job crafting and leisure crafting are linked to job embeddedness by investigating employee resilience as a mediator and employee adaptivity as a moderator.

Data were gathered from 568 Taiwanese hotel employees. The PROCESS macro was used to verify all hypotheses.

Both job crafting and leisure crafting increased job embeddedness. Employee resilience mediated the impacts of job and leisure crafting on job embeddedness. The positive relationship between employee resilience and job embeddedness was stronger when employee adaptivity was high. Employee adaptivity moderated the indirect impacts of job and leisure crafting on job embeddedness through employee resilience.

Hotel managers should foster a workplace culture that encourages employees to engage in job crafting. Additionally, managers can offer employee assistance programs to proactively encourage workers to participate in leisure crafting. Providing training and wellness programs to strengthen employee resilience, along with allocating resources and designing learning programs to enhance employee adaptability, can further promote job embeddedness.

This research contributes to the literature through the construction of a moderated mediation model that explored how and when job and leisure crafting affect job embeddedness.

This study aims to minimize the warpage issue in memory-computing integrated chiplets with 2.5D packaging on a large-scale wafer subjected to multistress through synergistic optimization of key structure paraeters.

In this study, memory-computing integrated chiplet-based 2.5D packaging was designed and the warpage optimization under electro-thermal-vibration coupling was conducted with finite element analysis simulation. Compared studies were also conducted with the imposing condition of single electrical and thermal stress.

The research results indicated that electrical and thermal stress had a significant impact on the packaging warpage while that of vibration on warpage was minimal. For structure parameters, the chiplet thickness had a significant effect on the warpage of the model, while the influence of chiplet size was relatively small. When the chiplet thickness decreased to 100 µm, the warpage was reduced by 8.96%. Under thermal stress loading, the impact of packaging density on the overall warpage of the chiplet-based 2.5D packaging model is relatively small. However, under the loading of electrical stress or electro-thermal coupling, the packaging density has a severe impact on warpage, with the maximum approaching 1.3011 µm for just one chiplet. Compared with vibration alone, electro-thermal-vibration coupling slightly increased the warpage, which is primarily evident in the exacerbation of warpage in stacked chiplets and edge locations. Lower packaging density with 150 µm chiplet thickness contributed to a minimal warpage in stacked chiplet, the edge locations of which exhibited a relatively severe warpage.

The research provides a theoretical basis for warpage optimization of memory-computing integrated chiplets with 2.5D packaging subjected to multistress coupling.

When designing the layout of chips for large-sized high-reliability silicon substrates, this method can be used to control the most severely warped areas at the edges, thus making it easier to optimize warpage.

With the approaching of physical limits dictated by Moore’s Law, advanced packaging technologies, primarily centered around 2.5D packaging and three-dimensional packaging, were attached importance to. It can integrated multifunctional chips, which have become increasingly complex, leading to greater difficulty in design and implementation, and an obvious increase in overall manufacturing costs. In this context, chiplets offered a viable approach for future chip designs. With the high demand for high-performance computing, memory-computing integrated chiplets were designed. The warpage of 2.5D packaging by altering structural parameters under multiphysical field coupling conditions was studied to provide a theoretical basis for warpage optimization of memory-computing integrated chiplets with 2.5D packaging.