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Wellness tourism is growing in importance as increasing numbers of travelers place a priority on their health and well-being by traveling. This study examined the relationships between wellness tourism destination attributes, perceived quality, perceived mental health, eudaimonic well-being, overall satisfaction and behavioral loyalty to corroborate a model explaining wellness tourism destination loyalty in Thailand.

The conceptual model of this study was examined using a survey research design. The survey questionnaire was distributed to Chinese tourists who had previously traveled to Thailand and engaged in wellness tourism activities during their trip.

The findings revealed that healthful food choices, core facilities and staff service significantly influenced perceived quality. This perceived quality was a crucial factor in determining perceived mental health, which in turn impacted eudaimonic well-being. Overall satisfaction was directly influenced by perceived quality, perceived mental health and eudaimonic well-being. Additionally, perceived quality had a direct effect on behavioral loyalty.

With the growing global interest in wellness and travel, this study offers valuable insights for tourism marketers in Thailand to enhance their wellness tourism strategies. Tourism organizations should emphasize the quality of food, facilities and staff service to attract wellness-oriented travelers.

This study highlights the interconnectedness of perceived quality, good mental health and eudaimonic well-being. High-quality experiences contribute to improved mental health and in turn enhance eudaimonic well-being.

In a reflection of individuals’ interest in maintaining a healthy lifestyle, nutraceutical restaurants, which provide health benefits, have emerged on the market. However, little is known about the underlying factors and mechanisms of the consumption of nutraceutical foods. Therefore, grounded in an extended cognitive–affective–conative model, this study examines the role of dining motivations and restaurant attributes in explaining an integrated model that focuses on customers’ loyalty formation process.

Data were collected from 893 Chinese customers who had recently dined at traditional Chinese medicine restaurants. Using partial least squares structural equation modeling, this study examined the structural relationships among dining motivations, restaurant attributes, customers’ perceived benefits, overall satisfaction, place attachment and revisit intentions.

The results of a confirmatory factor analysis revealed that two main motivations (i.e. health and traditional culture) and five restaurant attributes (i.e. food, service staff food recommendation, service staff service quality, furniture and tableware and atmosphere) are stimuli that influence customers’ perceived benefits. This study also revealed that four types of perceived benefits (functional, emotional, social and epistemic) significantly affect overall satisfaction and place attachment, which determine revisit intentions.

The findings of this study help identify not only important dining motivations and restaurant attributes but also their roles in loyalty formation with respect to traditional Chinese medicine restaurants. Thus, the results contribute to an improved understanding of how to satisfy customers’ dining motivations and efficiently manage restaurant attributes to strengthen customer loyalty.

This study is among the first to simultaneously examine the effects of customer motivation and restaurant attributes and to explain how they affect customer loyalty behaviors at traditional Chinese medicine restaurants.

In this digital age and risk society, this study aims to explore innovative strategies for E-retailers during supply chain disruptions to construct a more resilient supply chain system.

Various game theoretical models are constructed to analyze four supply chain scenarios. Meanwhile, sufficient numerical analysis was conducted to observe the impact of key parameters on supply chain strategies.

Multiple crucial factors exert a comprehensive influence on E-retailers’ decisions on sourcing and pricing, leading to the diversity and complexity of decision-making conditions. First, with the increased probability of disruption, the purchase quantities of the E-retailer from different suppliers are not in a linear changing pattern, and the total purchase quantity is allocated variably between different suppliers. Second, the variation in disruption severity (partial or complete) results in the shift of decisions between single-sourcing and dual-sourcing. Responsive pricing is conducive to increasing the purchase quantity and profits under partial disruption; its advantages are diminished when completely disrupted. Third, higher commission rates usually have a detrimental impact on profit, whereas responsive pricing may mitigate this impact.

Unlike the previous single perspective, this study innovatively explores strategies from the hybrid perspective of sourcing and pricing. By extracting two key factors (disruption probability and severity), it realizes the scientific characterization of supply chain disruptions. These achievements boost theoretical innovation. Concentrating on E-retailers, it avoids the generalization of conclusions and enhances the application value.

Bearing friction moments are important factors that affect the vibrations of rotor systems. The bearing friction moments are related to the dimension parameters, lubrication conditions and manufacturing errors of support bearings. This work studies the effects of the bearing friction moments on the vibrations of rotor systems.

The rotor is separated into several shaft elements for formulating a flexible rotor. The time-varying friction moment (TFM) is affected by the time-varying contact loads. The vibrations of FRS from the TFM and Palmgren's friction moment (PFM) calculation methods are compared. Moreover, the effects of the rotor offset and radial clearance on the frequency-amplitude characteristics of FRS are studied.

The TFM method is more consistent with the actual operation mechanisms. The rotor offset and radial clearance can significantly affect the nonlinear vibrations of FRS. This work provides a new reference and research method for the vibration analysis of rotor systems considering the friction effects.

The elastohydrodynamic lubrication (EHL), elastic hysteresis and differential sliding are considered. A flexible rotor system (FRS) dynamic model considering the TFM is proposed. The vibrations of FRS from the TFM calculation method and empirical calculation formula are compared. The effects of the rotor offset and radial clearance on the frequency–amplitude characteristics of FRS are studied.

Recent archiving and curatorial practices took advantage of the advancement in digital technologies, creating immersive and interactive experiences to emphasize the plurality of memory materials, encourage personalized sense-making and extract, manage and share the ever-growing surrounding knowledge. Audiovisual (AV) content, with its growing importance and popularity, is less explored on that end than texts and images. This paper examines the trend of datafication in AV archives and answers the critical question, “What to extract from AV materials and why?”.

This study roots in a comprehensive state-of-the-art review of digital methods and curatorial practices in AV archives. The thinking model for mapping AV archive data to purposes is based on pre-existing models for understanding multimedia content and metadata standards.

The thinking model connects AV content descriptors (data perspective) and purposes (curatorial perspective) and provides a theoretical map of how information extracted from AV archives should be fused and embedded for memory institutions. The model is constructed by looking into the three broad dimensions of audiovisual content – archival, affective and aesthetic, social and historical.

This paper contributes uniquely to the intersection of computational archives, audiovisual content and public sense-making experiences. It provides updates and insights to work towards datafied AV archives and cope with the increasing needs in the sense-making end using AV archives.

According to relevant research, non-uniform speed has a significant impact on the vehicle-track systems. Up to now, research work on it is still very limited. In this paper, the PEM is adopted to further transform it into a deterministic process to solve the vehicle’s problem of running at a non-uniform speed.

The multi-body vehicle model has 10 degrees of freedom and the track is regarded as a finite long beam supported by lumped sleepers and ballast blocks. They are connected via linear Hertz springs. The vertical track irregularity is a Gaussian stationary process in the space domain. It is transformed into a uniformly modulated nonstationary random process in the time domain with respect to the non-uniform vehicle speed. By solving the equation of motion of the coupled vehicle-track system with the pseudo-excitation method, the pseudo-response and consequently the power spectral density and the standard deviation of the structural response can be obtained.

Two kinds of vehicle braking programs are taken in the numerical example and some beneficial conclusions are drawn.

The pseudo-excitation method (PEM) was used to perform the random vibration analysis of a coupled non-uniform speed vehicle-track system. Transforming the track irregularity into a uniformly modulated nonstationary random process in time domain with respect to the non-uniform vehicle speed was undertaken. The pseudo-response of the coupled system is solved by applying the Newmark algorithm with constant space integral steps. The random vibration transfer mechanism of the coupled system is fully discussed.

Digital transformation is essential for commercial banks to maintain long-term competitiveness in the digital economy era. This study aims to investigate the relationship between inside debt and the bank's digital transformation.

This study set up a quasi-natural experiment based on implementing the executive compensation deferral system in the Chinese banking industry. Using the annual panel data of 180 commercial banks in China from 2007 to 2021, this study employed the difference-in-differences (DID) method to conduct an empirical analysis.

This study confirms a significant statistical relationship between inside debt and the bank's digital transformation, and managerial myopia is the transmission channel of inside debt affecting the bank's digital transformation. Furthermore, the development of Internet finance and the enhancement of bankers' confidence will improve the contributions of inside debt to the bank's digital transformation.

This study contributes to the literature on inside debt and the bank's digital transformation. It has specific policy value for the scientific design of the banking compensation mechanism and accelerating banks' digital transformation.

This study aims to test the effects of Technology-related Divestitures (TRDs) on firms' exploratory innovation. The moderating effects of firms' internal and external resource coordination activities, resource buffering and bridging, are also explored.

A set of data including 1,372 Chinese listed firms from 2009 to 2018 is adopted. Based on propensity score matching sample, random-effect Tobit models were employed to test the hypotheses.

The empirical results indicate that TRDs inhibit firms' exploratory innovation, while both resource buffering and bridging can mitigate this negative effect. This implies that to promote exploratory innovation, resource coordination activities are the essential.

The research findings can contribute to both the exploratory innovation and technological divestiture literature. The test on the moderating roles of resource buffering and bridging can also extend our understanding of the effect of TRDs on firms' exploratory innovation. Accordingly, several practical implications can be provided. This is especially important for strategic decisions of firms from emerging and developing countries, which often lack sufficient internal resources and strong technological capabilities to develop exploratory innovation.

Lubricating oil leakage is a common issue in thermal power plant operation sites, requiring prompt equipment maintenance. The real-time detection of leakage occurrences could avoid disruptive consequences caused by the lack of timely maintenance. Currently, inspection operations are mostly carried out manually, resulting in time-consuming processes prone to health and safety hazards. To overcome such issues, this paper proposes a machine vision-based inspection system aimed at automating the oil leakage detection for improving the maintenance procedures.

The approach aims at developing a novel modular-structured automatic inspection system. The image acquisition module collects digital images along a predefined inspection path using a dual-light (i.e. ultraviolet and blue light) illumination system, deploying the fluorescence of the lubricating oil while suppressing unwanted background noise. The image processing module is designed to detect the oil leakage within the digital images minimizing detection errors. A case study is reported to validate the industrial suitability of the proposed inspection system.

On-site experimental results demonstrate the capabilities to complete the automatic inspection procedures of the tested industrial equipment by achieving an oil leakage detection accuracy up to 99.13%.

The proposed inspection system can be adopted in industrial context to detect lubricant leakage ensuring the equipment and the operators safety.

The proposed inspection system adopts a computer vision approach, which deploys the combination of two separate sources of light, to boost the detection capabilities, enabling the application for a variety of particularly hard-to-inspect industrial contexts.

This paper aims to investigate the flow characteristics of lubricating grease in extremely cold weather in which it is difficult to convey the grease due to a huge pressure drop.

The rheological behavior of grease at various temperatures is studied by a rotary rheometer to determine the constitutive equation of lubricating grease. Based on the Herschel–Bulkley (H–B) model, the flow pattern of grease is then simulated by computational fluid dynamics and compared with the test results.

The yield stress increased dramatically when the shear rate was less than 1s⁻¹ in the rheological experiments of continuous shear mode, and the phenomenon was more significant with the decrease in temperature. The rheological data obtained from the continuous shear mode agrees with the H–B equation after the shear thinned. In extremely cold conditions, there is a large yield stress in the lubricating grease; the numerical results show that the viscosity of lubricating grease increased with an increase in temperature, and the viscosity and velocity of lubricating grease showed uneven distribution leading to difficulty of lubricating grease delivery.

This paper focuses on the flow characteristics of lubricating grease in extremely cold area conditions which is studied rarely. In addition, the continuous shear model and oscillatory model are combined to establish the constitutive equations. Experiment and numerical simulation method are all used by establishing the H–B models.