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The sustainable development of the platform economy has been hindered by the absence and alienation of platform corporate social responsibility. Previous studies have mainly focused on the contents and governance models for platform corporate social responsibility. This study seeks to explore which strategy participants choose in the governance of platform corporate social responsibility and their influencing factors.

Using a platform ecosystem approach, a quadrilateral evolutionary game model was developed, and the stabilities of subjects’ behavioral strategies and their combinations in various scenarios were analyzed. Additionally, the effects of key parameters on the system’s evolutionary path were simulated.

The ideal steady state system is achieved when platform enterprises, complementors and consumers adopt positive strategies while the government adopts lax regulation. Moreover, the evolutionary strategies of the subjects are influenced by several factors, including the participation costs of governance, the rewards and punishments imposed by platform enterprises, as well as the reputational losses of platform enterprises and complementors due to media coverage.

This study offers insights into improving the governance effectiveness of platform corporate social responsibility for managers and practitioners.

This study contributes to existing literature by considering the rational orientation of platform ecosystem members and revealing the interaction mechanisms among members. Furthermore, this study combines collective action theory and reputation theory to clarify the influencing factors on members’ behaviors.

It is shown in natural gas proportion mixing experiments that a mixed-source natural gas is the physical combination of end member gas. Both the carbon and hydrogen isotopes in the mixed-source natural gas can be expressed by the weighted average of corresponding components content and isotopes of end member gas. Under certain geological setting, the selection of end member gas is the key to mixed-source ratio calculation. Then, it's better to estimate the mixed-source ratio with δ¹³C₁ and component data according to the weighted average calculation formula. The analysis on natural gas geochemistry characteristics show that the natural gas extracted from Jingbian Gas Field in the Ordos Basin is mainly an upper Paleozoic coal-derived gas. In the analysis of geological conditions for reservoir forming and characteristics of natural gas, natural gas from Longtan 1 Well and Tao 6 Well were selected as the end member gases of lower Paleozoic oil-type gas and upper Paleozoic coal-type gas respectively to calculate the mixed-source ratio of natural gas in Jingbian Gas Field. The ratio of upper Paleozoic coal-derived gas mostly accounts for over 70% and its average ratio reaches 81%. Therefore, the exploration of natural gas of Ordos Basin should be focused on the upper palaeozoic coal source rock, and attention should be paid to the matching of coal source rock in the exploration of weathered crust gas deposit.

The ancient town of Lijiang is a representative place of ethnic minorities in China’s southwest border area jointly built by many ethnic groups. Its rich and diversified history, culture and architecture as well as its artistic and spiritual values need to be better retained and explored.

The protection and inheritance of Lijiang’s cultural heritage will be improved through the construction of digital memory resources. To guide Lijiang’s digital memory construction, this study explores strategies of digital memory construction by analyzing four case studies of well-known memory projects from China and America.

From the case studies analysis, factors of digital memory construction were identified and compared. Factors led to the discussion of strategies for constructing the digital memory of Lijiang within its design, construction and service phases.

The ancient town of Lijiang is a famous historical and cultural city in China, and it is also a representative place of ethnic minorities in the border area jointly built by many ethnic groups. The rich culture should be preserved and digitalized to offer better use for the whole nation.

The purpose of this study is to examine how the implementation of edge computing can enhance the progress of the circular economy within supply chains and to address the challenges and best practices associated with this emerging technology.

This study utilized a streamlined evaluation technique that employed Latent Dirichlet Allocation modeling for thorough content analysis. Extensive searches were conducted among prominent publishers, including IEEE, Elsevier, Springer, Wiley, MDPI and Hindawi, utilizing pertinent keywords associated with edge computing, circular economy, sustainability and supply chain. The search process yielded a total of 103 articles, with the keywords being searched specifically within the titles or abstracts of these articles.

There has been a notable rise in the volume of scholarly articles dedicated to edge computing in the circular economy and supply chain management. After conducting a thorough examination of the published papers, three main research themes were identified, focused on technology, optimization and circular economy and sustainability. Edge computing adoption in supply chains results in a more responsive, efficient and agile supply chain, leading to enhanced decision-making capabilities and improved customer satisfaction. However, the adoption also poses challenges, such as data integration, security concerns, device management, connectivity and cost.

This paper offers valuable insights into the research trends of edge computing in the circular economy and supply chains, highlighting its significant role in optimizing supply chain operations and advancing the circular economy by processing and analyzing real time data generated by the internet of Things, sensors and other state-of-the-art tools and devices.

This paper aims to summarize peer-reviewed journal articles on national cultures and electronic word of mouth (eWOM) behavior, identify the main findings and patterns among those studies and discuss research gaps that need to be addressed in the future.

A systematic review process was utilized to analyze peer-reviewed journal articles on both eWOM and national cultures. The main research questions were defined, then proceeded by the identification of exclusive and inclusive criteria to search for relevant articles, which were further filtered based on abstracts and full texts, and then scrutinized for main findings and major variables such as countries, cultural variables and data collection methods.

An analysis of 52 papers shows that national cultures, primarily Hofstede's dimensions, influence the willingness of individuals to share eWOM, how they write eWOM and the extent to which they use eWOM to make decisions. Although the reviewed studies have provided insightful implications for marketing theory and practice, the present paper has identified a number of important questions that warrant future research attention.

eWOM is continually being employed as a popular source of information for consumers throughout different countries to make their purchase decisions. However, eWOM behavior differs from country to country due to national cultures, and managers' eWOM strategies that work in one country may not be applicable in another. Therefore, there has been an increasing interest in this topic. Nevertheless, it remains unclear which subjects have been addressed and what areas are yet to be investigated. This paper presents a comprehensive review of how national cultures affect eWOM behavior by drawing upon prior research and provides directions for future research contributions.

Cold supply chain (CSC) distribution systems are vital in preserving the integrity and freshness of transported temperature sensitive products. CSC is also known to be energy intensive with a significant emission footprint. As a result, CSC requires strict monitoring and control management system during storage and transportation to improve safety and reduce profit losses. In this research, a systematic review of recent literature related to the distribution of food CSC products is presented and possible areas to extend research in modeling and decision-making are identified.

The paper analyzes the content of 65 recent articles related to CSC and perishable foods. Several relevant keywords were used in the initial search, which generated a list of 214 articles. The articles were screened based on content relevance in terms of food vehicle routing modeling and quality. Selected articles were categorized and analyzed based on cost elements, modeling framework and solution approach. Finally, recommendations for future research are suggested.

The review identified several research gaps in CSC logistics literature, where more focused research is warranted. First, the review suggests that dynamic vehicle modeling and routing while considering products quality and environmental impacts is still an open area for research. Second, there is no consensus among researchers in terms of quality degradation models used to assess the freshness of transported cold food. As a result, an investigation of critical parameters and quality modeling is warranted. Third, and due to the problem complexity, there is a need for developing heuristics and metaheuristics to solve such models. Finally, there is a need for extending the single product single compartment CSC to multi-compartment multi-temperature routing modeling.

The article identified possible areas to extend research in CSC distribution modeling and decision-making. Modified models that reflect real applications will help practitioners, food authorities and researchers make timely and more accurate decisions that will reduce food waste and improve the freshness of transported food.

The pin fin is applied into a Lamilloy cooling structure which is broadly used in the leading edge region of the modern gas turbine vane. The purpose of this paper is to investigate effects of the layout, diameter and shape of pin fins on the flow structure and heat transfer characteristics in a newly improved Lamilloy structure at the leading edge region of a turbine vane.

A numerical method is applied to investigate effects of the layout, diameter and shape of pin fins on the flow structure and heat transfer characteristics in a newly improved Lamilloy structure at the leading edge of a turbine vane. The diverse locations of pin fins are Lp = 0.35, 0.5, 0.65. The diameter of the pin fins varies from 8 mm to 32 mm. Three different ratios of root to roof diameter for pin fins are also investigated, i.e. k = 0.5, 1, 2. The Reynolds number ranges from 10,000 and 50,000. Results of the flow structures, heat transfer on the target surface and pin fin surfaces, and friction factor are studied.

The heat transfer on the pin fin surface gradually decreases and then increases as the location of the pin fins increases. Increasing the diameter of the pin fins causes the heat transfer on the pin fin surface to gradually increase, while a lower value of the friction factor occurs. Besides, the heat transfer on the pin fin surface at a small root diameter increases remarkably, but a slight heat transfer penalty is found at the target surface. It is also found that both the Reynolds analogy performance and the thermal performance are increased compared to the baseline whose diameter and normalized location of pin fins are set as 16 and 0.5 mm, respectively.

The models provide a basic theoretical study to deal with nonuniformity of the temperature field for the turbine vane leading edge. The investigation also provides a better understanding of the heat transfer and flow characteristics in the leading edge region of a modern turbine vane.

This is a novel method to adopt pin fins into a Lamilloy cooling structure with curvature. It presents that the heat transfer of the pin fin surface in a pin-fin Lamilloy cooling structure with curvature can be significantly increased by changing the parameters of the pin fins which may lead to various flow behavior. In addition, the shape of the pin fin also shows great influence on the heat transfer and flow characteristics. However, the heat transfer of the target surface shows a small sensitivity to different layouts, diameter and shape of pin fin.

Supercritical CO₂ (SC–CO₂) fracturing is a potential technology that creates a complex fracturing fracture network to improve reservoir permeability. SC–CO₂-driven intersections of the fracturing fracture network are influenced by some key factors, including the disturbances generated form natural fractures, adjacent multi-wells and adjacent fractures, which increase the challenges in evaluation, control and optimization of the SC–CO₂ fracturing fracture networks. If the evaluation of the fracture network is not accurate and effective, the risk of oil and gas development will increase due to the microseismicity induced by multi-well SC–CO₂ fracturing, which makes it challenging to control the on-site engineering practices.

The numerical models considering the thermal-hydro-mechanical coupling effect in multi-well SC–CO₂ fracturing were established, and the typical cases considering naturally fracture and multi-wells were proposed to investigate the intersections and connections of fracturing fracture network, shear stress shadows and induced microseismic events. The quantitative results from the typical cases, such as fracture length, volume, fluid rate, pore pressure and the maximum and accumulated magnitudes of induced microseismic events, were derived.

In naturally fractured reservoirs, SC–CO₂ fracturing fractures will deflect and propagate along the natural fractures, eventually intersect and connect with fractures from other wells. The quantitative results indicate that SC–CO₂ fracturing in naturally fractured reservoirs produces larger fractures than the slick water as fracturing fluid, due to the ability of SC–CO₂ to connect macroscopic and microscopic fractures. Compared with slick water fracturing, SC–CO₂ fracturing can increase the length of fractures, but it will not increase microseismic events; therefore, SC–CO₂ fracturing can improve fracturing efficiency and increase productivity, but it may not simultaneously lead to additional microseismic events.

The results of this study on the multi-well SC–CO₂ fracturing may provide references for the fracturing design of deep oil and gas resource extraction, and provide some beneficial supports for the induced microseismic event disasters, promoting the next step of engineering application of multi-well SC–CO₂ fracturing.

Passive chipless RFID (radio frequency identification) sensors, devoid of batteries or wires for data transmission to a signal reader, demonstrate stability in severe conditions. Consequently, employing these sensors for metal crack detection ensures ease of deployment, longevity and reusability. This study aims to introduce a chipless RFID sensor design tailored for detecting metal cracks, emphasizing tag reusability and prolonged service life.

The passive RFID sensor is affixed to the surface of the aluminum plate under examination, positioned over the metal cracks. These cracks alter the electrical length of the sensor, thereby influencing its amplitude-frequency characteristics. Hence, the amplitude-frequency profile generated by various metal cracks can effectively ascertain the occurrence and orientation of the cracks.

Simulation and experimental results show that the proposed crack sensing tag produces different frequency amplitude changes for four directions of cracks and can recognize the crack direction. The sensor has a small size and simple structure, which makes it easy to deploy.

This research aims to deploy crack detection on metallic surfaces using passive chipless RFID sensors, analyze the amplitude-frequency characteristics of crack formation and distinguish cracks of varying widths and orientations. The designed sensor boasts a straightforward structural design, facilitating ease of deployment, and offers a degree of reusability.

This study aims to conceptualize the characteristics of artificial intelligence (AI) dogs while exploring their applications in tourism and hospitality settings.

The total of 30 in-depth interviews were conducted, and data were analyzed through thematic analysis.

This study proposed differences between AI dogs and real dogs and human-like robots, core characteristics of AI dogs’ functions, a matrix of appearance and expectation regarding intelligence for AI dogs and human-like robots, the relationship between ethical barriers and task complexity, adoptions of AI dogs in different user segments and practical applications in hospitality and tourism settings, such as restaurants, city tour guides, extended-stay resorts and event organizations.

This research advances the field of tourism and hospitality studies by introducing the new concept of AI dogs and their practical applications. This present study adds new insights into the opportunities and contexts of human–robot interaction in the field of tourism and hospitality.

To the best of the authors’ knowledge, this research is one of the first studies of AI dogs in tourism and hospitality.