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In order to extend the application of the original octagonal Goodman–Smith fatigue limit diagram, which is commonly used for the evaluation of structure fatigue stress in engineering, a modification of it is proposed for the structure made of S355 steel (commonly used in high-speed electric multiple units (EMUs) bogie frame).

The modification is made based on Deutscher Verband für Schweißen und verwandte Verfahren e. V. (DVS) 1612 standard and the γ-P-S-N curve, with consideration of the fatigue evaluation requirements of different survival rates and confidence levels. The verification of the modification is performed for three welded joints and for the comparison with the experimental data.

The results indicate that the design survival rate, the design safety margin and the fatigue stress evaluation of welded joint types are all improved by using the modified diagram.

There are relatively few studies on modifying octagonal Goodman–Smith fatigue limit diagram. In this paper, a modified diagram is proposed and applied in order to ensure the safety and durability of key welded structures of rail vehicles.

This study aims to test the link between enterprise digital transformation and technological innovation and the mechanisms and channels behind this link.

This study systematically examines whether and how enterprise digital transformation affects technological innovation in China.

Enterprise digital transformation effectively improves technological innovation. This result remains stable in robustness and endogeneity checks. The channel mechanisms of this promoting effect are internal (improvement of internal control quality and alleviation of agency costs) and external (increased attention of analysts and reduction of customer concentration). Moreover, this promoting effect is more significant for state-owned enterprises, small and medium-sized enterprises, enterprises in areas with low marketization and enterprises that do not enjoy digital subsidies from the government.

Enterprises need to attend to the mechanisms behind the link between digital transformation and technological innovation and to the unique effects of different enterprise attributes and capital markets, such as size, the ownership nature, the degree of regional marketization and government subsidies. Doing so will effectively promote digital transformation and technological innovation and strengthen core competitiveness.

This study provides systemic evidence of the link between enterprise digital transformation and technological innovation. The findings enrich the research literature on enterprise digitization and the factors of influencing enterprises’ technological innovation and provide a reasonable explanation for how enterprise digital transformation affects technological innovation.

The highly uncertain and turbulent environments nowadays intensify the paradoxical effects of supply base concentration (SBC) on improving cost efficiency while increasing idiosyncratic risk (IR). Digitalization is regarded as a remedy for this paradox, yet digitization's potentially curative effect has not been empirically tested. Leveraging the lenses of paradox theory and information processing theory (IPT), this study explores how two distinct dimensions of digitalization, i.e. digitalization intensity (DI) and digitalization breadth (DB), reconcile the paradoxical effects of SBC.

Using a panel dataset of 1,238 Chinese manufacturing firms in the period of 2012–2020, this study utilizes fixed-effects regression models to test the proposed hypotheses.

The authors discover that SBC enhances a firm's cost efficiency but induces greater IR. More importantly, there is evidence that DI restrains the amplifying effect of SBC on IR. However, DB weakens the enhancing effect of SBC on cost efficiency and aggravates the SBC's exacerbating effect on IR.

This study advances the understanding of the paradoxical effects of SBC on cost efficiency and IR from a paradox theory perspective. More importantly, to the best of the authors' knowledge, the authors' study is the first to untangle the differential roles of DI and DB in reconciling the paradox of SBC. This study also provides practitioners with nuanced insights into how the practitioners should use appropriate tactics to deploy digital technologies effectively.

This paper aims to evaluate and compare the performance of different computer vision algorithms in the context of visual servoing for augmented robot perception and autonomy.

The authors evaluated and compared three different approaches: a feature-based approach, a hybrid approach and a machine-learning-based approach. To evaluate the performance of the approaches, experiments were conducted in a simulated environment using the PyBullet physics simulator. The experiments included different levels of complexity, including different numbers of distractors, varying lighting conditions and highly varied object geometry.

The experimental results showed that the machine-learning-based approach outperformed the other two approaches in terms of accuracy and robustness. The approach could detect and locate objects in complex scenes with high accuracy, even in the presence of distractors and varying lighting conditions. The hybrid approach showed promising results but was less robust to changes in lighting and object appearance. The feature-based approach performed well in simple scenes but struggled in more complex ones.

This paper sheds light on the superiority of a hybrid algorithm that incorporates a deep neural network in a feature detector for image-based visual servoing, which demonstrates stronger robustness in object detection and location against distractors and lighting conditions.

This study aims to explore the relationship between folk religious place-making and the development of urban public spaces and summarize its influence on community network construction and daily behavior to discover the authentic practices and role of folk faith culture in social space.

Taking Macau's Shi Gandang Temple and its belief culture as an example, on-site research, historical evidence and interviews were used to elaborate and analyze the processes of place-making, social functions, management mechanisms and folk culture to establish a new perception of folk religious place-making in contemporary urban spaces.

The article argues that the culture of folk beliefs profoundly influences urban spaces and the social management system of Macau and has a positive significance in building the local community and geopolitical relations. In addition, it suggests that the participation of folk religious places in local practices is important as key nodes and emotional hubs of local networks, reconciling conflicts between communities of different backgrounds and driving urban spaces toward diversity while forming a positive interaction and friendly cooperation between regional development and self-contained management mechanisms, governance models and cultural orientations.

This study takes an architectural and anthropological perspective of the impact of faith on urban spaces and local governance, using the Shi Gandang Temple in Macau as an example, to complement related studies.

Drawing on cultural intelligence and social exchange theories, this study examines cultural intelligence and its effects on proactive service performance and the mediating role of leader's collaborative nature and the moderating role of cultural training and emotional labor, particularly deep acting and surface acting, in the relationship between cultural intelligence and proactive service performance.

The study sample comprised 510 healthcare practitioners. Structural equation modeling was used to examine the hypotheses.

The results show that cultural intelligence positively influences proactive service performance. Additionally, leadership's collaborative nature influences proactive service performance. The moderating effect of cultural training and deep acting positively influences the relationship between cultural intelligence and proactive service performance. In contrast, surface acting reveals a reverse effect, thus exhibiting a positive effect on this relationship.

These findings suggest that public healthcare organizations should pay more attention in improving deep acting, cultural training and leadership's collaborative nature for optimal service performance.

The novelty of this study lies in its presentation of an integrated framework based on cultural intelligence and social exchange theories that can solve the contemporary challenges facing healthcare firms operating in emerging markets in integrating cultural intelligence and service performance.

This research aims to extract Industry 4.0 technological building blocks (TBBs) capable of value generation in collaborative consumption (CC) and the sharing economy (SE). Furthermore, by employing a mixed methodology, this research strives to analyse the relationship amongst TBBs and classify them based on their impact on CC.

Due to the importance of technology for the survival of collaborative consumption in the future, this study suggests a classification of the auxiliary and fundamental Industry 4.0 technologies and their current upgrades, such as the metaverse or non-fungible tokens (NFT). First, by applying a systematic literature review and thematic analysis (SLR-TA), the authors extracted the TBBs that impact on collaborative consumption and SE. Then, using the Bayesian best-worst method (BBWM), TBBs are weighted and classified using experts’ opinions. Eventually, a score function is proposed to measure organisations’ readiness level to adopt Industry 4.0 technologies.

The findings illustrated that virtual reality (VR) plays a vital role in CC and SE. Of the 11 TBBs identified in the CC and SE, VR was selected as the most determinant TBB and metaverse was recognised as the least important. Furthermore, digital twins, big data and VR were labelled as “fundamental”, and metaverse, augmented reality (AR), and additive manufacturing were stamped as “discretional”. Moreover, cyber-physical systems (CPSs) and artificial intelligence (AI) were classified as “auxiliary” technologies.

With an in-depth investigation, this research identifies TBBs of Industry 4.0 with the capability of value generation in CC and SE. To the authors’ knowledge, this is the first research that identifies and examines the TBBs of Industry 4.0 in the CC and SE sectors and examines them. Furthermore, a novel mixed method has identified, weighted and classified pertinent technologies. The score function that measures the readiness level of each company to adopt TBBs in CC and SE is a unique contribution.

With the increasing complexity of public–private partnership (PPP) projects, the amount of data generated during the construction process is massive. This paper aims to develop a new information management method to cope with the risk problems involved in dealing with such data, based on domain ontologies of the construction industry, to help manage PPP risks, share and reuse risk knowledge.

Risk knowledge concepts are acquired and summarized through PPP failure cases and an extensive literature review to establish a domain framework for risk knowledge using ontology technology to help manage PPP risks.

The results indicate that the risk ontology is capable of capturing key concepts and relationships involved in managing PPP risks and can be used to facilitate knowledge reuse and storage beneficial to risk management.

The classes in the risk knowledge ontology model constructed in this research do not yet cover all the information in PPP project risks and need to be further extended. Moreover, only the framework and basic methods needed are developed, while the construction of a working ontology model and the relationship between implicit and explicit knowledge is a complicated process that requires repeated modifications and evaluations before it can be implemented.

The ontology provides a basis for turning PPP risk information into risk knowledge to allow the effective sharing and communication of project risks between different project stakeholders. It can also have the potential to help reduce the dependence on subjectivity by mining, using and storing tacit knowledge in the risk management process.

The apparent suitability of the nine classes of PPP risk knowledge (project model, risk type, risk occurrence stage, risk source, risk consequence, risk likelihood, risk carrier, risk management measures and risk case) is identified, and the proposed construction method and steps for a complete domain ontology for PPP risk management are unique. A combination of criteria- and task-based evaluations is also developed for assessing the PPP risk ontology for the first time.