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The spatial–temporal conflicts in the construction process of concrete arch dams are related to the construction quality and duration, especially for pouring blocks with a continuous high-strength and high-density construction process. Furthermore, the complicated construction technology and limited space resources aggravate the spatial–temporal conflicts in the process of space resource allocation and utilization, directly affecting the pouring quality and progress of concrete. To promote the high-strength, quality-preserving and rapid construction of dams and to clarify the explosion moment and influence degree of the spatial–temporal conflicts of construction machinery during the pouring process, a quantification method and algorithm for a “Conflict Bubble” (CB) between construction machines is proposed based on the “Time–Space Microelement” (TSM).

First, the concept of a CB is proposed, which is defined as the spatial overlap of different entities in the movement process. The subsidiary space of the entity is divided into three layered spaces: the physical space, safe space and efficiency space from the inside to the outside. Second, the processes of “creation,” “transition” and “disappearance” of the CB at different levels with the movement of the entity are defined as the evolution of the spatial–temporal state of the entity. The mapping relationship between the spatial variation and the running time of the layered space during the movement process is defined as “Time–Space” (TS), which is intended to be processed by a microelement.

The quantification method and algorithm of the CB between construction machinery are proposed based on the TSM, which realizes the quantification of the physical collision accident rate, security risk rate and efficiency loss rate of the construction machinery at any time point or time period. The risk rate of spatial–temporal conflicts in the construction process was calculated, and the outbreak condition of spatial–temporal conflict in the pouring process was simulated and rehearsed. The quantitative calculation results show that the physical collision accident rate, security risk rate and efficiency loss rate of construction machinery at any time point or time period can be quantified.

This study provides theoretical support for the quantitative evaluation and analysis of the spatial–temporal conflict risk in the pouring construction process. It also serves as a reference for the rational organization and scientific decision-making for pouring blocks and provides new ideas and methods for the safe and efficient construction and the scientific and refined management of dams.

The hybrid nanofluid flow due to a rotating disk has numerous applications, including centrifugal pumps, paper production, polymers dying, air filtration systems, automobile cooling and solar collectors. This study aims to investigate the convective heat transport and magnetohydrodynamics (MHD) hybrid nanofluid flow past a stretchable rotating surface using the Yamada-Ota and Xue models with the impacts of heat generation and thermal radiation.

The carbon nanotubes such as single-wall carbon nanotubes and multi-wall carbon nanotubes are suspended in a base fluid like water to make the hybrid nanofluid. The problem’s governing partial differential equations are transformed into a system of ordinary differential equations using similarity transformations. Then, the numerical solutions are found with a bvp4c function in MATLAB software. The impacts of pertinent parameters on the flow and temperature fields are depicted in tables and graphs.

Two solution branches are discovered in a certain range of unsteadiness parameters. The fluid temperature and the rate of heat transport are enhanced when the thermal radiation and heat generation effects are increased. The Yamada-Ota model has a higher temperature than the Xue model. Furthermore, it is observed that only the first solution remains stable when the stability analysis is implemented.

To the best of the authors’ knowledge, the results stated are original and new with the investigation of MHD hybrid nanofluid flow with convective heat transfer using the extended version of Yamada-Ota and Xue models. Moreover, the novelty of the present study is improved by taking the impacts of heat generation and thermal radiation.

This paper aims to optimize the air pressure regulation scheme of the aeroengine pressure test bench.

Based on the requirements of pressure regulation process and the operating mechanism of aeroengine pressure test bench, a grey performance evaluation index system is constructed. The combination of principal component analysis and grey theory is employed to assign weights to grey indexes. The grey target evaluation model is introduced to evaluate the performance of historical regulation processes, and the evaluation results are analyzed to derive optimization mechanism for pressure regulating schemes.

A case study based on monitoring data from nearly 300 regulation processes verifies the feasibility of the proposed method. On the one hand, the improved principal component analysis method can achieve rational weighting for grey indexes. On the other hand, the method comparison intuitively shows that the proposed method performs better.

The pressure test bench is a fundamental technical equipment in the aviation industry, serving the development and testing of aircraft engines. Due to the complex system composition, the pressure and flow adjustment of the test bench heavily rely on manual experience, leading to issues such as slow adjustment speed and insufficient accuracy. This paper proposes a performance evaluation method for the regulation process of pressure test bench, which can draw knowledge from historical regulation processes, provide guidance for the pressure regulation of test benches, and ultimately achieve the goal of reducing equipment operating costs.

The host–guest molecules are often used in various fields and applications. This paper aims to discuss the role of host–guest complexes in the textile industry, focusing on calixarenes as a potential adsorbent for hazardous dyes. The paper begins with an introduction to nanotechnology and its many uses, including textiles.

The risks associated with the utilisation of dyes and its adverse effects on the environment are then also highlighted. This paper also discusses the structure and characteristics of calixarenes and their potential use as an adsorbent to extract toxic metals from aqueous solutions. The paper also explains the molecular structure of calixarenes, especially the ability of its upper and lower rims, which can be altered to yield derivatives with various selectivities for diverse guest ions and small molecules. In addition, the application of various host–guest molecules in the textiles industry to extract dyes also had been discussed.

In conclusion, the paper highlights the essential in establishing a systematic review on the significance of selective adsorbents, such as calixarenes, to isolate particular targets from diverse matrices in the textile industry.

Only discussing several applications for several host–guest molecules.

The paper concisely describes various host–guest molecule applications in the textile industry, with each molecule being elaborated upon in detail.

Images and caption descriptions serve as important visual stimuli that influence consumer preferences; therefore, the current study focuses on property images and captions illustrated on the home pages of accommodation-sharing platforms. Specifically, this study investigates the relative importance of hue, brightness and saturation of a property image and caption description styles on potential consumers’ preferences.

A mixed-method approach was used, and a total of 293 valid responses were collected through a discrete choice experiment approach. Interviews were conducted for additional analyses to explore the detailed explanations.

The utility model demonstrated that the image’s saturation was the most critical attribute perceived by the respondents, followed by caption description style, hue and brightness.

This is one of the first studies to investigate the display of attributes on a digital accommodation platform by exploring potential customers’ stated preferences. This study focuses explicitly on images and captions illustrated on the home page of an accommodation booking platform. Detailed image investigation is also a new research area in sharing economy-related research.

Previous studies have focused on explaining the developmental paths and the relevant skills necessary for smart factories, based on an extensive review of the literature. Unfortunately, there is a deficit of empirical analyses that present an in-depth overview of smart factory development. Although the literature supports the benefits of smart factories, it remains unclear whether there should be government intervention (GI) to facilitate or regulate such adoption. This study will provide an in-depth empirical analysis of smart factory adoption (SFA) and its role in manufacturing performance (MP) and sustainable manufacturing (SM).

This study used non-probability convenience and referral sampling techniques for data collection. This approach considered production managers from each company that participated in the survey questionnaire; thus, each production manager represented one firm. A total of 240 managers from several manufacturing companies participated in the study. This study employed direct and moderating hypotheses tested using PROCESS Macro, which Andrew Hayes developed for SPSS.

The study identified three fundamental elements of a smart factory: manufacturing big data (MBD), process automation (PA) and supply chain integration (SCI) and analyzed them individually to see how they affect MP. According to the results, building a smart factory has positive and significant impacts on MP and SM. Furthermore, this study explores the role of GI in promoting smart factory deployment for both production performance and sustainable production. The study found that GI did not have a significant moderating effect but did have a positive relationship with SM.

This study contributes to the literature on smart factories by examining the impact of SFA on MP and SM. This provides a more comprehensive overview of the potential benefits of smart factories across various aspects, such as the application of big data, adoption of automation technology and integration of the supply chain. This study suggests that managers and decision-makers consider investing in smart factory implementation to improve factory productivity and enhance sustainability. Policymakers and government officials can promote the adoption of smart factories by providing incentives, funding, and resources to manufacturing firms.

There is a scarcity of research measuring the actual performance of manufacturing firms that have already adopted smart factories, and this study seeks to address this gap in the literature. This study focuses on the implementation of manufacturing big data, process automation and supply chain integration and how the adoption of these technologies improves MP and provides a SM environment by conducting a real-time study of manufacturing organizations. This study presents an initial effort to explore the role of government involvement in promoting smart factories.

This research investigation aims to explore the factors that affect purchasing behaviour among consumers in India in the context of green electronic products with the aid of the extended theory of planned behaviour (TPB) by incorporating two additional constructs, namely environmental concern and ethical obligation.

The current research adopted a quantitative methodology, utilising a survey (questionnaire) to gather data from respondents residing in Delhi-NCR, India. A convenience sampling technique was used to select these respondents. Both online and offline modes were used to collect the data. Moreover, to evaluate the theoretical foundation of the investigation, the researchers employed PLS-SEM (partial least square structural equation modelling) on 346 useable samples.

The outcome reveals that attitude, subjective norm and perceived behaviour control (PBC) are significant predictors, supplementary constructs such as environmental concern are not significant predictors, whereas ethical obligation is a substantial predictor of purchase intention. Consumer purchase behaviour, in turn, is influenced by consumer purchase intention.

The outcome of this research could help the country’s legislators formulate policies and programs related to current environmental problems faced by our planet. Marketers could understand the factors that drive consumers' purchasing behaviour towards green electronic products and design effective marketing strategies accordingly. Thus, by enhancing the company’s green image, marketers of green products may potentially increase future purchases, all of which contribute to solving worldwide environmental problems.

This research confirms the usefulness of TPB in understanding Indian consumers' purchasing intention and behaviour towards green electronic products. It further extends the TPB by showing that new components, environmental concerns and ethical obligations influence Indian consumers' purchasing intentions and behaviour. Moreover, prior studies mostly used both additional constructs for green products. Current research used specific types of green products, i.e. green electronic products, as very few studies are available on these products that apply TPB, which makes this study novel. In contrast to previous research that primarily examined purchase intention, this study takes a further step by investigating the connection between intentions and consumers' purchase behaviour. It establishes intention as a precursor to behaviour, specifically towards green electronic products. Additionally, this study introduces new constructs and explores the Indian context, significantly contributing to the existing literature.

Asset maintenance in manufacturing industries is a critical issue as organizations are highly sensitive towards maximizing asset uptime. In the advent of Industry 4.0, maintenance is increasingly becoming technology driven and is being termed as Maintenance 4.0. Several barriers impede the implementation of Maintenance 4.0. This article aims at - exploring the barriers to implementation of Maintenance 4.0 in manufacturing industries, categorizing them, analysing them to prioritize and suggesting the digital technologies to overcome them.

Twenty barriers to the implementation of Maintenance 4.0 were identified through literature survey and discussion with the industry experts. The identified barriers were divided into five categories based on their source of occurrence and prioritized using fuzzy-technique for order preference by similarity to ideal solution (TOPSIS), sensitivity analysis was carried out to check the robustness of the solution.

“Data security issues” has been ranked as the most influencing barrier towards the implementation of Maintenance 4.0, whereas “lack of skilled engineers and data scientists” is the least influencing barrier that impacts the implementation of Maintenance 4.0 in the manufacwturing industries.

The outcomes of this research will help manufacturing industries, maintenance engineers/managers, policymakers, and industry professionals for detailed understanding of barriers and identify easy pickings while implementing Maintenance 4.0.

Manufacturing industries are witnessing a paradigm shift due to digitization and maintenance 4.0 forms the cornerstone. Little research has been carried in Maintenance 4.0 and its implementation; this article will help in bridging the gap. The prioritization of the barriers and digital course of actions to overcome those is a unique contribution of this article.

Digital transformation provides a new impetus for the development of declining firms. However, there is currently a lack of sufficient research on whether digital transformation is beneficial for the turnaround of declining firms. This paper aims to explore the relationship between digital transformation and the turnaround of declining firms.

Drawing on the theoretical foundations of the resource-based view and dynamic capabilities theory, this research uses a comprehensive dataset of Chinese A-share listed companies from 2010–2021 to explore the influence of digital transformation on the turnaround of declining firms.

The research findings show that digital transformation contributes to the turnaround of declining firms. Mechanism analyses demonstrate that digital transformation enhances dynamic capabilities and attracts more analysts, thereby facilitating the turnaround process. Moreover, the moderation analysis reveals that CEO equity incentives strengthen the positive correlation between digital transformation and the turnaround of declining firms. Heterogeneity analysis indicates that the association between digital transformation and the turnaround of declining firms is particularly significant for firms with low financing constraints and high-tech firms. Moreover, this research reveals that digital transformation can facilitate the turnaround of firms in deep and long-term decline.

This research contributes to the literature on the digital transformation of enterprises and provides important insights for the turnaround of declining firms.

Safety climate plays an important role in the high-risk construction industry. Advances have been made in the understanding of construction safety climate in terms of four interrelated themes, specifically, its definition, measurement, antecedents and consequences. However, knowledge remains fragmented as the studies are scattered, and a systematic review covering these four themes is lacking. To address this research gap, this study aims to perform a systematic literature review of construction safety climate literature regarding the four themes.

Following the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) protocol guidelines, 178 eligible articles were obtained. This study provided thematic analysis of the 178 papers to identify what is known and what is not yet fully known regarding the four themes of construction safety climate. This study also conducted a descriptive analysis to identify the influential scholars, keywords, theories and research methods used by the literature, and finally presented an integrative framework directing future research.

The literature has not reached a consensus on the definition and measurement of construction safety climate. While it has identified the impact of safety climate on both behavioral and accident consequences, it has paid less attention to the antecedents and their underlying mechanisms regarding safety climate. Fang D. and Lingard H. are identified as the most influential authors in this field. “Questionnaire” and “safety behavior” are the keywords most closely related to safety climate. Unfortunately, the existing evidence for the causal relationships between safety climate and its antecedents and consequences is weak, as many studies lack clear theoretical substance, use a concurrent research design and focus only on individual-level climate perceptions. Finally, to support the development of construction safety climate around the four themes, potential research directions and research methods supporting them are illustrated.

This review makes contributions by integrating existing construction studies covering its definition, measurement, antecedents and consequences. This review also makes contributions to specific themes: no review exists on the antecedents of construction safety climate, and this review fills that gap; with regard to consequences, the existing reviews focus either on safety outcomes or safety behavior, but this review included both of them and further elaborated the different theories underpinning the relationships between safety climate and them. It is hoped that this systematic review will be helpful to the research community toward developing a nomologic network and promoting knowledge integration with respect to construction safety climate.