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The purpose of this study is to investigate the effects of celebrity endorsers on consumer advocacy, customization and entertainment intentions based on the notion of the stimulus–organism–response (SOR) framework. In addition, this study aims to examine the mediating and moderating role of customization and entertainment intentions on the proposed relationships. The authors also intend to highlight the comparative effects between male and female young social media consumers on those proposed associations.

In the pursuit of comprehensive and rigorous data collection, this study adopted a quantitative methodology using a meticulously crafted questionnaire. The questionnaire survey was conducted in major cities of Malaysia using the convenience and snowball sampling techniques. A total of 576 responses were collected, even though 549 retorts were used for data analysis. In this investigation, the authors strategically used covariance-based structural equation modeling through the use of AMOS v. 24 as the primary data analysis tool. Augmenting the analytical depth, the authors also conducted a supplementary bootstrap analysis. The additional layers of examination were crucial for appraising the mediating and moderating effects inherent within the model, in which the PROCESS MACRO v.4.20 was used.

The results of this study revealed the significant direct positive effects of celebrity endorsers on consumer customization, entertainment and advocacy intentions. Consumer customization and entertainment intentions also found significant direct affirmative effects on consumer advocacy intention, along with the significant direct positive effects of consumer entertainment intention on consumer customization intention. The results further revealed that consumer customization and entertainment intentions cannot mediate the relationship between celebrity endorsers and advocacy intention. The entertainment intention also declined the mediating effects between celebrity endorsers and consumer customization intention. On the contrary, consumer customization intention significantly and positively, and entertainment intention also significantly but negatively, moderate the association between celebrity endorsers and consumer advocacy intention. This study also illustrates that the effects of those examined relationships differ between male and female young social media consumers.

This study investigates the impact of celebrity endorsers on consumer behavior, focusing on their customization, entertainment and advocacy intentions. It extends current SOR framework, enhances source credibility theory, fills gaps in the literature on social media brand engagement and underscores the significance of customization and entertainment intentions. The findings provide insights for managers aiming to harness consumer brand advocacy through celebrity endorsers effectively.

The purpose of this study is to explore the comparative effects of mainstream celebrities and social media influencers on consumer advocacy and relationship intentions. The study also examines the direct and serial mediation effects on those relationships.

The survey questionnaire was used to collect data from 718 respondents throughout Malaysia, with convenience and snowball sampling techniques employed. The data were analyzed based on the structural equation modeling (SEM) approach through the AMOS version 24. The PROCESS MACRO v-4.20 was applied to evaluate mediating effects in the model.

The results reveal that celebrity endorsers' involvement in social media significantly influences the uses of social media, which also impacts the attitudes and, subsequently, consumer relationship and advocacy intentions. The study found that mainstream celebrities and social media influencers effectively promote brands, and it discovered insignificant differences in their effects on the analyzed relationships.

This study has been conducted on consumers in Malaysia; it may have different effects on consumers in other countries.

Brand managers and policymakers may benefit from following the study's guidelines for making consumer relationship and advocacy intentions by celebrity endorsers and uses of social media.

The brand community can benefit from tightening their social bondage by sharing and managing crucial information from celebrities and using social media.

The study explores the effects of mainstream celebrities on consumer relationship and advocacy intentions using social media networks and managing consumer attitudes.

Due to the incredible criticisms by scholars of the excessive use of social media networks, this study aims to explore students’ motivation for social media use (SMU) and its effects on academic performance (AP) in the light of uses and gratification theory.

Using the simple random and snowball sampling techniques, this study has considered 299 responses and critically analyzed them using structural equation modeling through the AMOS version 24. The mediation analysis has been done to explore the effective use of social media networks.

The results reveal that video clip watching and nonacademic learning intentions significantly influence SMU and AP. Besides, socialization through friends and family connections has tremendously fostered SMU intention, while it could not benefit AP. This study found an exceptional result that the entertainment intention of the students did not influence SMU but dramatically impacted their AP. Again, SMU has robust effects on enhancing students’ academic achievement. This study also concluded the results of the mediation analysis.

The learners, professionals, higher education policymakers, etc. may benefit from following this study's guidelines for using social media networks.

This study may tremendously contribute to changing the mindset of youth from addiction to SMU and improving AP.

The prime novelty of this study is to justify the mediation analysis for SMU to explore whether it can truly influence students’ AP and critically examine the deep insight of certain factors associated with SMU.

The goal of this chapter is to respond to the theoretical inquiries by scholars who are interested in how the public–private partnership (PPP) models adapt to China’s context where political power dictates economic strategies. We also want to provide suggestions to policy designers who aim to promote a sustainable investment environment for domestic and international investors. We review the literature that explains the upside and downside of PPP projects in contemporary China. (1) We classify the trajectory of PPP evolution into four phases, i.e., emergence, growth, recession and revival. (2) We note that private companies take a disadvantageous position in the partnership compared with governments and state-owned enterprises because of a lack of specialized legislation, unequal competition between private companies and state-owned enterprises and the opposition from the civic society. (3) We identify political risks as the most influential risks. Political risks also lead to the misallocation of other risks between public and private parties that contributes to the high failure rate of China’s PPP projects. Based on these findings, we recommend governments to draft specialized legislation, stabilize the political environment and provide favourable subsidies to local governments to limit the risks involved in PPP projects. We also advise private enterprises and state-owned enterprises to focus on negotiating over task and risk division with governments when they make decisions to participate in PPP projects. This full review of studies on PPP development in China provides reliable recommendations to scholars, governments and enterprises.

Defects in concrete surfaces are inevitably recurring during construction, which needs to be checked and accepted during construction and completion. Traditional manual inspection of surface defects requires inspectors to judge, evaluate and make decisions, which requires sufficient experience and is time-consuming and labor-intensive, and the expertise cannot be effectively preserved and transferred. In addition, the evaluation standards of different inspectors are not identical, which may lead to cause discrepancies in inspection results. Although computer vision can achieve defect recognition, there is a gap between the low-level semantics acquired by computer vision and the high-level semantics that humans understand from images. Therefore, computer vision and ontology are combined to achieve intelligent evaluation and decision-making and to bridge the above gap.

Combining ontology and computer vision, this paper establishes an evaluation and decision-making framework for concrete surface quality. By establishing concrete surface quality ontology model and defect identification quantification model, ontology reasoning technology is used to realize concrete surface quality evaluation and decision-making.

Computer vision can identify and quantify defects, obtain low-level image semantics, and ontology can structurally express expert knowledge in the field of defects. This proposed framework can automatically identify and quantify defects, and infer the causes, responsibility, severity and repair methods of defects. Through case analysis of various scenarios, the proposed evaluation and decision-making framework is feasible.

This paper establishes an evaluation and decision-making framework for concrete surface quality, so as to improve the standardization and intelligence of surface defect inspection and potentially provide reusable knowledge for inspecting concrete surface quality. The research results in this paper can be used to detect the concrete surface quality, reduce the subjectivity of evaluation and improve the inspection efficiency. In addition, the proposed framework enriches the application scenarios of ontology and computer vision, and to a certain extent bridges the gap between the image features extracted by computer vision and the information that people obtain from images.

The paper aims to provide up-to-date analysis on how a country like Singapore, with a rich tangible and intangible cultural heritage associated with burial customs, approaches heritage preservation while ensuring modernisation and sustainable growth.

The paper is an exploratory analysis of the association between cultural heritage preservation, particularly the one associated with elaborate burials, and the need for modernisation in Singapore. It mainly uses desk research tools, fieldwork and interviews with death services providers to build a set of conclusions. It employs a historical review approach and uses comparative analyses with other countries in the Asian region to substantiate the arguments.

The paper provides insights about how, since its independence, Singapore has switched to pragmatic models of growth and development which imply maximising the limited space available, often at the cost of precious cultural heritage. The rapid development has had a significant impact on the country's burial customs and legacies, particularly on elaborate graves and tombs, which traditionally use a considerable amount of space. The analysis concludes that Singapore is in the constant challenge of exploring alternative ways of handling death and its ramifications.

This paper presents a new outlook on the relationship between the preservation of the tangible and intangible cultural heritage associated with death practices and a sustainable approach to modernisation in the context of Singapore.

The purpose of this study is to better understand distinct solution strategy types for common commissioning and startup problems (Hot Spots) in the construction of industrial facilities. The authors also sought to better understand which solution strategy types offer the best value for the effort required.

The authors used a method of qualitative coding of text-based data to identify themes, patterns and trends from a collection of 178 commissioning and startup (CSU) solution strategies for the CSU Hot Spots. Coding categories emerged after multiple iterations. The authors also mapped high-value, low-effort solution strategies across the categories. Chi-squared testing and analysis of proportion statistics help quantitatively justify this qualitative research.

The authors identified 12 distinct coding categories and showed that they follow a non-uniform distribution via statistical testing. Those strategy types which provide particularly good value for the effort required are identified (such as quality assurance and control strategies), as well as those strategy types that do not.

Research is limited to CSU for the construction of industrial facilities. The findings are also limited to a subset of the most commonly problematic CSU activities. Many findings may be beneficial for heavy civil and commercial CSU as well.

Coding categories, definitions and descriptions provide a good overview of all 178 solution strategies for CSU project professionals. Implementing certain types of solutions or solution programs may allow CSU managers to prevent multiple Hot Spots from becoming problematic or to keep problems already occurring from becoming worse. Managers will also benefit from knowledge about which strategy types are more likely to give a higher value for lower effort.

Qualitative coding and analysis of solution strategies for common CSU problems have never been conducted so rigorously in any other CSU study. This method has yielded results distinct from other CSU studies which have used quantitative methods. Insights from findings have advanced the body of knowledge surrounding problem-solving in the commissioning and startup sub-discipline.

The study analyzes significant parameters defining the credit worthiness, economic viability and managerial efficiency of special purpose vehicles (SPVs) of infrastructure development firms engaged in the execution of road projects under PPP model in India.

The study is based on a comprehensive review of credit rating reports of major rating agencies. In particular, 18 special purpose vehicles (13 BOT-toll–based and 5 BOT-annuity–based road projects) during the period 2010–2019 were considered to conduct a comparative analysis of their rating progression. Considering both financial as well as nonfinancial parameters, their segregation was done on the basis of strengths, constraints and key rating sensitivities influencing the ratings of SPVs involved in road projects under PPP model.

Promoters' credibility emerged as an important factor affecting PPP credit ratings. Other prominent factors included nature of stretch and regulatory terms and conditions and the project's potential to generate cash flows. Inability of PPP projects to generate the projected levels of toll collections was a major constraint and hampered ratings over time. Growth in traffic was a key sensitive area in a toll-based project. Interestingly, despite the fixed nature of revenues, BOT (annuity) projects were impacted by rating changes.

Fewer sample projects (for which the data were available) was a constraint. Future research could consider larger data sets to provide deeper insights. An examination of credit rating parameters using rating reports of projects in other developing nations could provide meaningful implications. The findings of this research however cannot be undermined as the study bridges a gap in existing literature pertaining to the examination of PPP model from a credit rating perspective.

This study would guide project developers, government agencies and awarding agencies of PPP road projects to anticipate the challenges and take adequate steps to mitigate them.

Research in the area of PPP projects is skewed toward risk assessment with respect to financial parameters. The present study emphasizes the rating framework of SPVs. Comprehensive examination of factors affecting project ratings in the form of projects' strengths, constraints and sensitivities would provide inputs to academics and researchers.

Expert systems are computer-based systems that mimic the logical processes of human experts or organizations to give advice in a specific domain of knowledge. Fuzzy expert systems use fuzzy logic to handle uncertainties generated by imprecise, incomplete and/or vague information. The purpose of this paper is to present a comprehensive review of the methods and applications in fuzzy expert systems.

The authors have carefully reviewed 281 journal publications and 149 conference proceedings published over the past 37 years since 1982. The authors grouped the journal publications and conference proceedings separately accordingly to the methods, application domains, tools and inference systems.

The authors have synthesized the findings and proposed useful suggestions for future research directions. The authors show that the most common use of fuzzy expert systems is in the medical field.

Fuzzy logic can be used to manage uncertainty in expert systems and solve problems that cannot be solved effectively with conventional methods. In this study, the authors present a comprehensive review of the methods and applications in fuzzy expert systems which could be useful for practicing managers developing expert systems under uncertainty.

Prefabricated building has been widely applied in the construction industry all over the world, which can significantly reduce labor consumption and improve construction efficiency compared with conventional approaches. During the construction of prefabricated buildings, the overall efficiency largely depends on the lifting sequence and path of each prefabricated component. To improve the efficiency and safety of the lifting process, this study proposes a framework for automatically optimizing the lifting path of prefabricated building components using building information modeling (BIM), improved 3D-A* and a physic-informed genetic algorithm (GA).

Firstly, the industry foundation class (IFC) schema for prefabricated buildings is established to enrich the semantic information of BIM. After extracting corresponding component attributes from BIM, the models of typical prefabricated components and their slings are simplified. Further, the slings and elements’ rotations are considered to build a safety bounding box. Secondly, an efficient 3D-A* is proposed for element path planning by integrating both safety factors and variable step size. Finally, an efficient GA is designed to obtain the optimal lifting sequence that satisfies physical constraints.

The proposed optimization framework is validated in a physics engine with a pilot project, which enables better understanding. The results show that the framework can intuitively and automatically generate the optimal lifting path for each type of prefabricated building component. Compared with traditional algorithms, the improved path planning algorithm significantly reduces the number of nodes computed by 91.48%, resulting in a notable decrease in search time by 75.68%.

In this study, a prefabricated component path planning framework based on the improved A* algorithm and GA is proposed for the first time. In addition, this study proposes a safety-bounding box that considers the effects of torsion and slinging of components during lifting. The semantic information of IFC for component lifting is enriched by taking into account lifting data such as binding positions, lifting methods, lifting angles and lifting offsets.