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This paper examines the relationship between traditional timber frame structure and the diasporic identity of the Southern Fujianese Chinese community in West Malaysia. It analyses the cultural semiotics of Southern Fujianese traditional Chinese temple timber frame structure architectural language. This study addresses the under-examined domain of Chinese cultural identity representation through the architecture of traditional Chinese temples in Malaysia. It seeks to understand its underlying structure and process involved in revealing its disposition within the cultural phenomena from the perspective of Chinese cultural semiotics.

Selected Southern Fujianese traditional Chinese temples in West Malaysia built between the 18th to the 19th century that retain the traditional timber frame structure were investigated through field survey and focused publication review. Historical interpretive analysis and typological analysis supplement the cultural semiotics analysis to assess the timber frame structure attributes concerning architectural language expressions.

Findings reveal that the architectural language signifiers of the structural disposition of the timber framework and its corresponding formal articulation establish a clear statement of the Southern Fujian Chinese cultural identity.

The evaluation of the cultural identity signifiers helps to understand the underlying structure and process of the Chinese cultural semiotics in architecture. Results of this research substantiate the significance of timber frame structure in preserving the architectural heritage of the Southern Fujianese traditional Chinese temples. They provide important references for conservation and cultural studies of such building typology.

In light of the lack of subjective criteria and scientific rationality in current sustainability performance assessment, the purpose of this paper is conducted to improve the sustainability performance assessment of high-tech firms by developing a hybrid approach that integrates quantitative and qualitative research methods.

This study proposed a hybrid approach that integrates word frequency analysis, cluster analysis, grey theory and the decision-making and trial evaluation laboratory (DEMATEL) method. Specifically, this study identifies useful criteria using quantitative word frequency analysis as well as qualitative literature research. Then, cluster analysis is used to divide these criteria into different categories. Subsequently, this study applies the grey theory associated with the DEMATEL method to assess the sustainability performance of high-tech firms.

The results reveal that the socio-environment is an important aspect underlying the corporate sustainability performance of high-tech firms. Therefore, high-tech firms should enhance their pollution emission control capabilities and increase investment in energy-conservation and emission-reduction technologies to drive sustainable development. In addition, increasing green product sales revenue and improving the guiding capability of green consumption are core issues that firms must address.

This study assesses the sustainability performance of high-tech firms by applying a hybrid method. This method can be used to construct a framework for scientific sustainability performance assessment and to provide a clear direction for the sustainable development of firms.

This paper aims to evaluate the sulfide stress cracking (SSC) resistance of L80 casing steels with different alloying chemistries (e.g. Ti-B and Mn-Cr-Mo) by correlating the reduction in area ratio with the mechanical property, inclusion and carbide.

SSC tests were conducted in 5.0 Wt.% sodium chloride and 0.5 Wt.% acetic acid solution saturated with H₂S using constant load tensile method. The microstructure and fracture morphology of the steel were observed using scanning electron microscope. The inclusion and carbide were identified by energy dispersive spectroscopy and auger electron microscope.

Among all the testing steels, electric resistance welding (ERW) L80-0.5Mo steel demonstrates the highest SSC resistance because of its appropriate mechanical properties, uniform microstructure and low inclusion content. The SSC resistance of L80 steels generally decreases with the rising yield strength. The fracture mode of steel with low SSC resistance is jointly dominated by transgranular and intergranular cracking, whereas that with high SSC resistance is mainly transgranular cracking. SSC is more sensitive to inclusions than carbides because the cracks are easier to be initiated from the elongated inclusions and oversized oxide inclusions, especially the inclusion clusters. Unlike the elongated carbide, globular carbide in the steel can reduce the negative effect on the SSC resistance. Especially, a uniform microstructure with fine globular carbides favors a significant improvement in SSC resistance through precluding the cracking propagation.

The paper provides the new insights into the improvement in SSC resistance of L80 casing steel for its application in H₂S environment through optimizing its alloying compositions and microstructure.

This paper examines the evolving landscape of accounting and finance research on the Chinese capital market, building on a previous study published at Abacus in 2018.

By incorporating data from 1999 to 2023, our analysis offers a detailed examination of shifts in academic focus, methodological advancements and thematic expansions over the last quarter-century.

The study reveals a substantial increase in accounting and finance publications related to the Chinese capital market in both Tier 1 and Asia-Pacific journals. The dynamic growth of the Chinese capital market during this period reflects profound economic transformations, characterized by technological innovations, sustainability commitments and regulatory reforms.

We conclude that the globally important Chinese capital market has attracted increasing academic attention, significantly advancing the understanding of accounting and finance research in China’s capital market.

This study aims to assess the pitting resistance of austenitic stainless steel welded joints fusion zone (FZ) with high density of inclusions before and after surface treatment, including potentiostatic pulse technique (PPT) and pickling.

The potentiodynamic polarization tests and critical pitting temperature tests were carried out for estimating pitting resistance. The PPT and pickling were performed as surface treatment. Scanning electron microscope (SEM) and energy dispersive spectrometer were used for characterize the microstructure and elemental distribution. Electron back-scattered diffraction (EBSD) was used to assess the portion of phases and morphology of grains.

The weld metal exhibits a higher degree of alloying compared to the base metal, and it contains d-phase and sulfur-containing inclusions. Sulfur-containing inclusions serve as initiation sites for pitting, and they diminish the pitting resistance of weld metal. Both PPT and pickling can remove sulfur-containing inclusions, but PPT causes localized dissolution of the weld metal matrix around the inclusions, while pickling does not. Because of the high density of inclusions, certain pits initiated by PPT are significantly deeper, which makes the formation of stable pitting easier. Because of the high density of inclusions, certain pits initiated by the PPT are deeper. This characteristic facilitates the progression of these initial defects into fully developed, stable pits.

Analysis of pitting initiation in shielded metal arc welding FZ with PPT and ex situ SEM tracking observation. Explanation of why the PPT surface treatment is not able to enhance the pitting resistance of stainless steel with a high inclusion density.

This paper aims to investigate the effects of deposition time on the structure and anti-corrosion properties of a micro-arc oxidation (MAO)/Al coating on AZ31B Mg alloy.

The study describes the fabrication of the coating via a combined process of MAO with multi-arc ion plating. The structure, composition and corrosion resistance of the coatings were evaluated using scanning electron microscopy, energy dispersive spectroscopy, X-ray diffraction and electrochemical methods.

The Al-layer is tightly deposited with a good mechanical interlock along the rough interface due to the Al diffusion. However, the Al layer reduces the anti-corrosion of MAO-coated Mg alloy because of structural defects such as droplets and cavities, which act as channels for corrosive media infiltration towards the substrate. Fortunately, the Al layer improves the substrate corrosion resistance owing to its passive behaviour, and the corrosion resistance can be enhanced with increasing deposition time. All results indicate that a buffer layer fabricated through the duplex process improves the interfacial compatibility between the hard coating and soft Mg alloys.

An MAO/Al duplex coating was fabricated via a combined process of MAO and physical vapour deposition. MAO/Al duplex coatings exhibit obviously passive behaviours on AZ31 Mg alloy. The structure and corrosion resistance of MAO/Al coatings were investigated.

Being an efficient mechanism for the value of money, public–private partnership (PPP) is one of the most prominent approaches for infrastructure construction. Hence, many controversies about the performance effectiveness of these delivery systems have been debated. This research aims to develop a novel performance management perspective by revealing the causal effect of key performance indicators (KPIs) on PPP infrastructures.

The literature review was used in this study to extract the PPPs KPIs. Experts’ judgment and interviews, as well as questionnaires, were designed to obtain data. Copula Bayesian network (CBN) has been selected to achieve the research purpose. CBN is one of the most potent tools in statistics for analyzing the causal relationship of different elements and considering their quantitive impact on each other. By utilizing this technique and using Python as one of the best programming languages, this research used machine learning methods, SHAP and XGBoost, to optimize the network.

The sensitivity analysis of the KPIs verified the causation importance in PPPs performance management. This study determined the causal structure of KPIs in PPP projects, assessed each indicator’s priority to performance, and found 7 of them as a critical cluster to optimize the network. These KPIs include innovation for financing, feasibility study, macro-environment impact, appropriate financing option, risk identification, allocation, sharing, and transfer, finance infrastructure, and compliance with the legal and regulatory framework.

Identifying the most scenic indicators helps the private sector to allocate the limited resources more rationally and concentrate on the most influential parts of the project. It also provides the KPIs’ critical cluster that should be controlled and monitored closely by PPP project managers. Additionally, the public sector can evaluate the performance of the private sector more accurately. Finally, this research provides a comprehensive causal insight into the PPPs’ performance management that can be used to develop management systems in future research.

For the first time, this research proposes a model to determine the causal structure of KPIs in PPPs and indicate the importance of this insight. The developed innovative model identifies the KPIs’ behavior and takes a non-linear approach based on CBN and machine learning methods while providing valuable information for construction and performance managers to allocate resources more efficiently.

Driven by the dual-carbon target and the widespread digital transformation, leveraging digital technology (DT) to facilitate sustainable, green and high-quality development in heavy-polluting industries has emerged as a pivotal and timely research focus. However, existing studies diverge in their perspectives on whether DT’s impact on green innovation is synergistic or leads to a crowding-out effect. In pursuit of optimizing the synergy between DT and green innovation, this paper aims to investigate the mechanisms that can be harnessed to render DT a more constructive force in advancing green innovation.

Drawing from the theoretical framework of resource orchestration, the authors offer a comprehensive elucidation of how DT intricately influences the green innovation efficiency of enterprises. Given the intricate interplay within the synergistic relationship between DT and green innovation, the authors use the fuzzy-set qualitative comparative analysis method to explore diverse configurations of antecedent conditions leading to optimal solutions. This approach transcends conventional linear thinking to provide a more nuanced understanding of the complex dynamics involved.

The findings reveal that antecedent configurations fostering high green innovation efficiency actually differ across various stages. First, there are three distinct configuration patterns that can enhance the green technology research and development (R&D) efficiency of enterprises, namely, digitally driven resource integration (RI), digitally driven resource synergy (RSy) and high resource orchestration capability. Then, the authors also identify three configuration patterns that can bolster the high green achievement transfer efficiency of enterprises, including a digitally optimized resource portfolio, digitally driven RSy and efficient RI. The findings not only contribute to advancing the resource orchestration theory in the digital ecosystem but also provide empirical evidence and practical insights to support the sustainable development of green innovation.

The findings can offer valuable insights for enterprise managers, providing decision-making guidance on effectively harnessing the innovation-driven value of internal and external resources through resource restructuring, bundling and leveraging, whether with or without the support of DT.

The research findings contribute to heavy-polluting enterprises addressing the paradoxical tensions between digital transformation and resource constraints under environmental regulatory pressures. It aims to facilitate the simultaneous achievement of environmental and commercial success by enhancing their green innovation capabilities, ultimately leading to sustainability across profit and the environment.

Compared with previous literature, this research introduces a distinctive theoretical perspective, the resource orchestration view, to shed light on the paradoxical relationship on resource-occupancy between DT application and green innovation. It unveils the “black box” of how digitalization impacts green innovation efficiency from a more dynamic resource-based perspective. While most studies regard green innovation activities as a whole, this study delves into the impact of digitalization on green innovation within the distinct realms of green technology R&D and green achievement transfer, taking into account a two-stage value chain perspective. Finally, in contrast to previous literature that predominantly analyzes influence mechanisms through linear impact, the authors use configuration analysis to intricately unravel the complex influences arising from various combinatorial relationships of digitalization and resource orchestration behaviors on green innovation efficiency.

The integration of blockchain technology (BT) in supply chain management (SCM) is at the forefront of technological advancements, yet it faces significant barriers that hinder its widespread adoption. This study aims to delve into these challenges, employing the diffusion of innovations (DOI) theory to systematically investigate and propose a strategic framework for overcoming the technological barriers to BT adoption within SCM.

Through a comprehensive systematic literature review (SLR) of 155 publications, complemented by rigorous content analysis and expert interviews, this research identifies and categorizes 16 primary technological barriers, including scalability and privacy issues, that impede BT integration.

The proposed framework, informed by DOI theory, outlines tailored strategies across three critical adoption stages: initiation, where the focus is on mitigating high energy consumption and scalability issues; adoption decision, emphasizing the formulating international standards for blockchain architecture, embedding abstraction layers within software projects; and implementation, concentrating on enhancing security, interoperability and system efficiency.

This research contributes significantly to both academic literature and practical applications. Academically, it extends the DOI theory within the SCM context and enriches the blockchain literature by providing a nuanced understanding of the specific barriers to BT adoption. Practically, it offers a roadmap for industry practitioners, delineating actionable strategies to navigate the adoption process effectively. This study not only bridges the gap between theoretical insights and practical implementations but also serves as a vital resource for policymakers and standard-setting bodies in facilitating and regulating BT adoption in SCM, thereby fostering innovation and competitive advantage in the marketplace.