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The purpose of this paper is to analyze the stiffness reliability of harmonic drive (HD) considering contact pairs wear.

In terms of theoretical calculation, the contact pairs wear of HD are calculated based on Archard wear formula and the relative motion characteristics of contact pairs. According to the motion trajectory of flexspline teeth, the teeth backlash and the number of meshing teeth, the meshing stiffness and overall stiffness of HD are analyzed considering the wear and its randomness of contact pairs. Combined with Monte Carlo Simulation, the stiffness reliability evaluation method considering contact pairs wear is proposed, and the result of this method is verified by the stiffness reliability result deduced from the stiffness degradation measurement data.

Considering contact pairs wear, during operation, the teeth backlash increases, the number of meshing teeth decreases, the meshing stiffness decreases, ultimately leading to a gradual decrease in the overall stiffness of HD. When only one type of contact pair wear is considered, the influence of flexspline and circular spline contact pair wear on HD stiffness reliability is greater. Compared with the stiffness reliability evaluation results obtained from the stiffness degradation data in the literature, the mathematic expectation of stiffness degradation failure life distribution obtained from the proposed method is relatively bigger.

The stiffness reliability evaluation method of HD considering contact pairs wear is firstly proposed. The stiffness reliability evaluation result from theoretical calculation is verified by the stiffness reliability results deduced from HD stiffness degradation measurement.

Many studies on entrepreneurial intention have explored the impact of different factors; however, few have examined the relationship between and impact mechanisms of informal social networks and entrepreneurial intention. This study aimed to bridge this research gap.

This study is based on social capital and ambidexterity theories. After surveying the data of 302 college students from different provinces and universities in China, a mediation model for research is constructed.

Informal social networks help enhance college students’ entrepreneurial intentions, whereas entrepreneurial learning (exploratory and exploitative learning) partially mediates this relationship.

This study empirically explores the impact of informal social networks on the entrepreneurial intentions of Chinese college students and indicates the crucial role played by entrepreneurial learning (divided into exploratory and exploitative learning).

This study aims to investigate the cause of high-order wheel polygonization in a plateau high-speed electric multiple unit (EMU) train.

A series of field tests were conducted to measure the vibration accelerations of the axle box and bogie when the wheels of the EMU train passed through tracks with normal rail roughness after re-profiling. Additionally, the dynamic characteristics of the track, wheelset and bogie were also measured. These measurements provided insights into the mechanisms that lead to wheel polygonization.

The results of the field tests indicate that wheel polygonal wear in the EMU train primarily exhibits 14–16 and 25–27 harmonic orders. The passing frequencies of wheel polygonization were approximately 283–323 Hz and 505–545 Hz, which closely match the dominated frequencies of axle box and bogie vibrations. These findings suggest that the fixed-frequency vibrations originate from the natural modes of the wheelset and bogie, which can be excited by wheel/rail irregularities.

The study provides novel insights into the mechanisms of high-order wheel polygonization in plateau high-speed EMU trains. Futher, the results indicate that operating the EMU train on mixed lines at variable speeds could potentially mitigate high-order polygonal wear, providing practical value for improving the safety, performance and maintenance efficiency of high-speed EMU trains.

The purpose of this paper is to present a wall-climbing robot platform for heavy-load with negative pressure adsorption, which could be equipped with a six-degree of freedom (DOF) collaborative robot (Cobot) and detection device for inspecting the overwater part of concrete bridge towers/piers for large bridges.

By analyzing the shortcomings of existing wall-climbing robots in detecting concrete structures, a wall-climbing mobile manipulator (WCMM), which could be compatible with various detection devices, is proposed for detecting the concrete towers/piers of the Hong Kong-Zhuhai-Macao Bridge. The factors affecting the load capacity are obtained by analyzing the antislip and antioverturning conditions of the wall-climbing robot platform on the wall surface. Design strategies for each part of the structure of the wall-climbing robot are provided based on the influencing factors. By deriving the equivalent adsorption force equation, analyzed the influencing factors of equivalent adsorption force and provided schemes that could enhance the load capacity of the wall-climbing robot.

The adsorption test verifies the maximum negative pressure that the fan module could provide to the adsorption chamber. The load capacity test verifies it is feasible to achieve the expected bearing requirements of the wall-climbing robot. The motion tests prove that the developed climbing robot vehicle could move freely on the surface of the concrete structure after being equipped with a six-DOF Cobot.

The development of the heavy-load wall-climbing robot enables the Cobot to be installed and equipped on the wall-climbing robot, forming the WCMM, making them compatible with carrying various devices and expanding the application of the wall-climbing robot.

A heavy-load wall-climbing robot using negative pressure adsorption has been developed. The wall-climbing robot platform could carry a six-DOF Cobot, making it compatible with various detection devices for the inspection of concrete structures of large bridges. The WCMM could be expanded to detect the concretes with similar structures. The research and development process of the heavy-load wall-climbing robot could inspire the design of other negative-pressure wall-climbing robots.

The purpose of this review paper is to address the need for mapping the thematic structure of fuzzy-set qualitative comparative analysis (fsQCA) in the context of tourism and hospitality research, in response to the growing interest in this methodology.

This study conducts a comprehensive systematic review using the SPAR-4-SLR procedure to produce a scientific map of top-tier research using the fsQCA technique in tourism and hospitality studies.

A major finding of this review investigation is the identification of six knowledge clusters: business competitiveness in the hospitality sector; psychoanalysis of tourist behaviour and satisfaction; entrepreneurship in the tourism and hospitality sector; tourism business ecosystem; sustainable tourism; and service quality in the tourism and hospitality sectors.

Although this review assessment relied heavily on articles published in prestigious journals, it does not rule out the idea that other sources, such as conference proceedings, can provide valuable insight.

Novel insights into the intellectual structure of tourism and hospitality research using the fsQCA technique, as well as ideas for future exploration in this domain, are presented in this review.

In the era of digitalization, digital technology has transformed businesses and created enormous opportunities for organizations worldwide. Unsurprisingly, research on digital transformation has garnered significant interest among academics in recent decades. However, this study aims to recognize the key and holistic antecedents influencing digital transformation in manufacturing firms. This study also investigates the indirect relationships of antecedents with firm performance.

The hypothesis was investigated using the partial least squares structural equation modeling (PLS-SEM) approach. The data was collected from 279 employees through a self-administered survey of manufacturing firms.

The results described a significant and positive impact of competitive pressure, leadership role, organization culture, organization mindfulness, government regulation, and IT readiness on digital transformation and firm performance. Furthermore, digital transformation partially mediates the relationship between antecedents and firm performance.

The study finds a holistic perspective of the critical antecedents of digital transformation using the mediation role of digital transformation and moderating effects of firm agility. Additionally, all antecedents have a significant association with Firm Performance.

The changing roles of the United Nations (UN) and national institutions have made addressing climate change a critical concern for many multinational enterprises’ (MNEs) survival and growth. This chapter discusses how such institutions, which vary in their nature and characteristics, shape firm strategies for climate change adaptation. Exploring different versions of institutional theory, the chapter demonstrates how and why institutional characteristics affect typical patterns of firm ownership, governance, and capabilities. These, in turn, influence companies’ internationalisation and climate-change strategies. Climate change poses challenges to how we understand firms’ strategic decisions from both an international business (IB) (HQ–subsidiary relations) and global value chains (GVC) (buyer–supplier relations) perspective. However, climate change also provides opportunities for companies to gain competitive advantages – if firms can reconfigure and adapt faster than their competitors. Existing IB and GVC research tends to downplay the importance of climate change strategies and the ways in which coherent or dysfunctional institutions affect firms’ reconfiguration and adaptation strategies in a globally dispersed network of value creation. This chapter presents a perspective on the institutional conditions that affect firms’ climate change strategies regarding ownership, location, and internalisation (OLI), and GVCs, with ‘investment’ and ‘emerging standards’ playing a significant role. The authors illustrate the discussion using several examples from the Global South (i.e. Bangladesh) and the Global North (i.e. Denmark, Sweden, and Germany) with a special emphasis on the garment industry. The aim is to encourage future research to examine how a ‘business systems’, or varieties of capitalism, institutional perspective can complement the analysis of sustainability and climate change strategies in IB and GVC studies.

A small-world network is a type of network structure in which nodes are highly clustered and at short distances without being directly linked. This article analyzes whether the network of interlocking directorates among the largest Brazilian corporations follows a small-world network structure and if the small-world properties (high clustering and short distance between nodes) influence the occurrence of M&A at the domestic and international level.

The authors tested hypotheses regarding the relationship between small-world network properties and M&A based on a sample of large publicly-listed corporations in Brazil for the time series of 2000–2015 and using network analysis and regression techniques (probit and OLS).

The results show that while the Brazilian corporate network fits the small-world features of high clustering and short path lengths, only the distance among connected firms has a significant effect on international M&A: the shorter the distance between firms, the more likely firms undertake M&A abroad. Moreover, being integrated into the main component has a significant positive effect on national and international M&A. These findings suggest that the information and knowledge to undertake M&A can be better acquired by belonging to large business communities and not local cohesive clusters.

This research contributes to theories and ongoing debates about the network effects on organizational decisions and the determinants of M&A in emerging markets. In addition, this is the first study to analyze the impact of small-world networks on international M&A while controlling for country-level variables.

The swivel construction method is a specially designed process used to build bridges that cross rivers, valleys, railroads and other obstacles. To carry out this construction method safely, real-time monitoring of the bridge rotation process is required to ensure a smooth swivel operation without collisions. However, the traditional means of monitoring using Electronic Total Station tools cannot realize real-time monitoring, and monitoring using motion sensors or GPS is cumbersome to use.

This study proposes a monitoring method based on a series of computer vision (CV) technologies, which can monitor the rotation angle, velocity and inclination angle of the swivel construction in real-time. First, three proposed CV algorithms was developed in a laboratory environment. The experimental tests were carried out on a bridge scale model to select the outperformed algorithms for rotation, velocity and inclination monitor, respectively, as the final monitoring method in proposed method. Then, the selected method was implemented to monitor an actual bridge during its swivel construction to verify the applicability.

In the laboratory study, the monitoring data measured with the selected monitoring algorithms was compared with those measured by an Electronic Total Station and the errors in terms of rotation angle, velocity and inclination angle, were 0.040%, 0.040%, and −0.454%, respectively, thus validating the accuracy of the proposed method. In the pilot actual application, the method was shown to be feasible in a real construction application.

In a well-controlled laboratory the optimal algorithms for bridge swivel construction are identified and in an actual project the proposed method is verified. The proposed CV method is complementary to the use of Electronic Total Station tools, motion sensors, and GPS for safety monitoring of swivel construction of bridges. It also contributes to being a possible approach without data-driven model training. Its principal advantages are that it both provides real-time monitoring and is easy to deploy in real construction applications.

Advances in material agency driven by artificial intelligence (AI) have facilitated breakthroughs in material adaptivity enabling smart objects to autonomously provide individualized smart services, which makes smart objects act as social actors embedded in the real world. However, little is known about how material adaptivity fosters the infusion use of smart objects to maximize the value of smart services in customers' lives. This study examines the underlying mechanism of material adaptivity (task and social adaptivity) on AI infusion use, drawing on the theoretical lens of social embeddedness.

This study adopted partial least squares structural equation modeling (PLS-SEM), mediating tests, path comparison tests and polynomial modeling to analyze the proposed research model and hypotheses.

The results supported the proposed research model and hypotheses, except for the hypothesis of the comparative effects on infusion use. Besides, the results of mediating tests suggested the different roles of social embeddedness in the impacts of task and social adaptivity on infusion use. The post hoc analysis based on polynomial modeling provided a possible explanation for the unsupported hypothesis, suggesting the nonlinear differences in the underlying influencing mechanisms of instrumental and relational embeddedness on infusion use.

The formation mechanisms of AI infusion use based on material adaptivity and social embeddedness help to develop the business strategies that enable smart objects as social actors to exert a key role in users' daily lives, in turn realizing the social and economic value of AI.

This study advances the theoretical research on material adaptivity, updates the information system (IS) research on infusion use and identifies the bridging role of social embeddedness of smart objects as agentic social actors in the AI context.