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This study aims to explain the market-oriented transformation dilemma of Chinese urban investment and development companies (UIDCs; also known as local government investment and financing companies) and objectively evaluate their transformation efficiency from both static and dynamic perspectives. The results of the research provide methodological bases for improving the transformation efficiency of UIDCs, thus pointing out the direction for the rational planning of their transformation path.

This study takes Chinese UIDCs in market transformation during 2015–2019 as the research object and uses principal component analysis to screen the index system for measuring the efficiency of market transformation. It then uses a three-stage data envelopment analysis model and the Malmquist productivity index to evaluate the market transformation efficiency of these companies during 2015–2019 and comprehensively analyzes the influence of external environmental factors on the market transformation of Chinese UIDCs.

Research results show that the transformation efficiency of Chinese UIDCs is low and slow overall and that large spatial and temporal differences exist. The transformation efficiency of UIDCs located in eastern China is higher than that of UIDCs in central and western China. The higher the external environmental factors of regional GDP, local debt service pressure and credit rating, the more likely they are to cause input redundancy in the transformation process of Chinese UIDCs, which is not conducive to their market-oriented transformation. In addition, the higher the urbanization rate, the more effective it is to improve the efficiency of market-oriented transformation of UIDCs. If the influence of environmental factors is stripped away, both the overall efficiency value and pure technical efficiency value of market-oriented transformation of Chinese UIDCs will increase while the scale efficiency value becomes smaller.

This research measures the transformation efficiency of Chinese UIDCs and comprehensively analyzes the influence of external environmental factors on their market-oriented transformation. The goal is to enrich the study of the market-oriented transformation efficiency evaluation index system of Chinese UIDCs at the theoretical level and provide important reference values for improving the efficiency of market-oriented transformation of Chinese UIDCs at the practical level.

This study aims to investigate the factors influencing the social responsibility performance of Belt and Road Initiative (BRI) megaprojects. Specifically, it examines the role of isomorphic pressures and the joint influence of perceived benefits and top management support on megaproject social responsibility performance (MSRP).

Drawing from institutional theory, social exchange theory, and top management literature, this study established a conceptual model featuring eleven hypotheses. Subsequently, a questionnaire survey was administered to collect data from 238 actively engaged participants in BRI megaprojects. Structural Equation Modelling was utilised to analyse the data.

The empirical findings indicate that mimetic and coercive pressures positively influence MSRP. Perceived benefits and top management support significantly enhance MSRP. Moreover, perceived benefits and top management support partially mediate the effects of coercive and mimetic pressures. However, when it comes to normative pressures, their impact on MSRP is solely channelled through the support of top management.

This study is one of the early endeavours to explore the factors influencing the social responsibility performance of BRI megaprojects. It sheds light on the interplay between external pressures and internal factors in shaping social responsibility efforts in these projects. These findings are of particular significance for BRI actors and stakeholders, offering guidance for enhancing social responsibility strategies within the context of BRI megaprojects.

The purpose of this research is to investigate how WeChat official account marketing activities influence consumer brand loyalty through instrument- and emotion-based paths (i.e. cognitive and affective brand trust) and how these paths operate depending on consumer shopping motivation.

We tested hypotheses using structural equation modeling with a three-wave online survey of two-week intervals administered to 179 individuals who follow the WeChat official account of a yoga gym brand.

WeChat official account marketing activities are positively related to cognitive and affective brand trust. Affective trust mediated the relationship between WeChat official account marketing activities and brand loyalty, and hedonic motivation moderated this relationship.

Our research extends the current knowledge by articulating that the influence of WeChat official account marketing activities on brand loyalty is mediated by affective brand trust, and hedonic motivation as a key contingency affects this mediation effect.

Previous studies have rarely integrated the financing modes of a capital-constrained manufacturer with the choices of online sales strategies. To address this gap, the authors study how a manufacturer selects optimal financing modes under different sales strategies in three dual-channel supply chains.

This paper considers three sales strategies, namely, combining a traditional retailer channel with one of the direct selling, reselling and agency selling channels, and two common financing modes, namely, bank financing and retailer financing. The authors obtain equilibrium outcomes of the manufacturer and traditional retailer and then provide the conditions for them to select optimal financing modes under three sales strategies.

The results indicate that the manufacturer’s financing decisions rely on the initial capital and interest rates, and the manufacturer selects retailer financing only if the initial capital is relatively larger. In terms of financing mode options, the retailer financing mode is more beneficial for the manufacturer under the three sales strategies. From the perspective of sales strategies, the direct selling model is more beneficial. In addition, the higher the consumer acceptance of the online channel, the more profits the manufacturer obtains.

This paper provides suggestions on how the capital-constrained manufacturer chooses financing modes and sales strategies.

This paper integrates the financing mode and different sales strategies to investigate the manufacturer’s optimal operational decisions. These sales strategies allow us to investigate the manufacturer’s optimal financing modes in the presence of both different financing modes and sales strategies.

As the risk of uncertain quality of used products potentially hinders remanufacturing, this study aims to examine the impact of risk aversion under quality uncertainty of used products in a remanufacturing supply chain (RSC) consisting of a manufacturer and an independent remanufacturer.

We develop an RSC model where the manufacturer produces new products, outsources remanufacturing to the independent remanufacturer and sells both new and remanufactured products to end consumers. Using a manufacturer-led Stackelberg game framework, we derive the equilibrium solutions under risk-neutral and risk-averse scenarios. Additionally, we design a two-part tariff contract to achieve coordination.

We show that while risk aversion leads the manufacturer to raise the outsourcing fee, which in turn reduces both the remanufactured quantity and the collection rate of used products. Consequently, consumer surplus and social welfare decline, while environmental impacts rise. The proposed two-part tariff contract can improve the collection rate and social welfare. We also explore two extensions: an authorization remanufacturing scenario and a two-period scenario. We find that risk aversion has no impact on the selection of remanufacturing mode and the equilibria in the first period. Our findings provide timely managerial insights for RSC management.

One of the main risks deterring remanufacturing is the quality uncertainty of used products. However, the risk aversion arising from this uncertainty and its effects have rarely been studied within a game-theoretic framework. This paper fills this gap by analyzing the remanufacturer’s risk aversion under quality uncertainty and investigating its impacts.

This study investigates the impact and role of digital twin technology in building automation (DTBA) from a sustainability viewpoint. It aims to enhance the understanding of how DTBA can boost efficiency, optimize quality and support sustainable practices in contemporary construction. By exploring the integration of DTBA with sustainable practices, the study seeks to demonstrate how DT can revolutionize building management and operations, leading to significant improvements in resource efficiency, environmental impact and overall operational excellence.

This research employs a bibliographic analysis and systematic review of 176 publications from the past five years (January 1, 2019 to December 31, 2023), focusing on the application and development of DTBA. The study methodically analyzes current trends, identifies research gaps and suggests future directions by synthesizing data from various studies, offering a comprehensive overview of the current state of DTBA research. The approach combines quantitative and qualitative analyses to provide robust insights into the advancements and challenges in the field.

The review identifies key development areas in DTBA, such as energy and environmental management, resource utilization within a circular economy and technology integration and interoperability. It highlights the necessity for further research to maximize DTBA’s potential in sustainable building automation. The findings suggest that while significant progress has been made, there is a critical need for innovations in data interoperability, predictive analytics and the integration of renewable energy sources to fully realize the benefits of DTBA in enhancing building sustainability.

This paper provides a thorough review of DTBA from a sustainability perspective, offering valuable insights into its current applications and future development potential. It serves as a crucial resource for researchers and practitioners looking to advance sustainable practices in the construction sector using DT technology. By bridging the gap between theoretical research and practical applications, the paper underscores the transformative potential of DTBA in driving sustainable development and provides a roadmap for future research and innovation in the field.

This study aims to propose a novel acoustic metamaterial waveguide with active switchable channels by changing the magnetic field strength.

Based on the Bragg scattering mechanism and the force-magnetic coupling effect of magnetorheological elastomer (MRE), an acoustic metamaterial waveguide structure containing lead scatterers and an MRE/rubber matrix is constructed. By changing the external magnetic field strength, the bandgap of the acoustic metamaterial can be adjusted, and then the channels of the proposed acoustic metamaterial waveguide can be actively switched. The bandgap ranges of acoustic metamaterials containing scatterers with different sizes are different and by designing the size of the scatterers, an acoustic metamaterial waveguide can be formed. The design and control method of this study will be useful for the design of waveguides and active control of bandgaps.

The proposed switchable multi-channel waveguide and active control method can effectively control the elastic wave propagation, and the opening and closing of the channel are achieved.

This study provides a new control method for waveguides and expands the application range of MRE. The proposed design concept of adjustable waveguides can be extended for the design of waveguides, metamaterials and vibration reduction structures.

This article proposes a waveguide structure controlled by an external magnetic field in a non-contact manner based on the principle of Bragg scattering and the force-magnetic coupling effect. The model is established, and its feasibility is demonstrated through numerical simulations.

Grassland degradation is a global ecological issue that inevitably leads to low livestock production efficiency (LPE). Adoption of appropriate technology is an effective way to improve productivity. However, the rate of technology adoption among herders in less developed pastoral areas is low. Therefore, it is critical to improve the level of technology adoption in order to increase LPE.

Based on remote sensing data and survey datasets of herder households in China’s Qinghai–Xizang Plateau, this paper innovatively constructs a stochastic production frontier model incorporating grassland productivity (i.e. grassland total net primary productivity) to accurately evaluate LPE and uses fractional regression models to determine the impact of technology adoption on LPE.

The results show that grassland productivity is essential to estimating LPE, and failing to account for it will result in overestimation. Technology adopters have a technical advantage with respect to average LPE (0.596) when compared with non-adopters (0.540), and technology adoption positively contributes to LPE. Furthermore, compared with profit-seeking technology, pro-environmental technology contributes more to improving LPE, and the combined adoption of both technologies leads to a markedly greater enhancement in LPE.

Few studies have empirically analyzed the economic benefits of technologies that most smallholders can afford, and few measure LPE considering grassland productivity. This study fills these gaps, and the findings are highly relevant for policies aimed at encouraging technology adoption and facilitating more efficient livestock production.

This study aims to identify the key hotel characteristics and facilities that significantly influence customer satisfaction based on Google review scores. By applying decision tree analysis, the research seeks to determine which aspects, such as service quality, hotel facilities and location, play pivotal roles in shaping customer experiences. The objective is to provide professional with practical recommendations to improve service quality and cultivate enduring customer loyalty.

The research used a data set collected from Hotels.com, featuring various characteristics of 802 hotels in Izmir Province. Decision tree analysis was conducted using Classification and Regression Tree algorithm to explore the relationship between hotel characteristics and facilities with customer satisfaction.

The analysis revealed that the number of rooms is the primary factor influencing hotel ratings, with proximity to the airport and hotel classification also being significant. Additional factors such as public transportation distance and laundry services were important, while facilities such as ATMs, beach access and spas showed no significant impact on customer satisfaction. These findings emphasize the importance of core facilities and accessibility.

This study contributes to the literature by offering a novel approach, using decision tree analysis to assess hotel customer satisfaction with structured data. It provides practical implications for hotel managers, enabling them to make data-driven improvements to achieve customer satisfaction. The integration rules created by the decision tree model into hotel management systems can enhance operational efficiency and competitive advantage in the hospitality industry.

How to support the rapid internationalization of multinational enterprises (MNEs) is a hot topic in academia and industry. The main purpose of this work is to study the role of relational assets (R-assets) in promoting the speed of internationalization of MNEs, and to explore the moderating effect of environmental uncertainty (institutional environment and industry environment) on the relationship between R-assets and internationalization speed of MNEs.

This study uses the outward foreign investment data of China’s A-share listed enterprises from 2009 to 2021, and employs the Cox proportional hazards model to empirically test the research hypothesis.

The empirical results revealed that R-assets can promote enterprise internationalization speed. In addition, the study also finds that the institutional uncertainty of host countries weakens the promotion effect of R-assets on internationalization speed of MNEs, while the industry uncertainty strengthens the promotion effect of those. Heterogeneity analysis illustrates that, compared with state-owned enterprises, non-state-owned enterprises have a more significant effect on the above conclusions.

This study enriches the literature on internationalization speed of MNEs by focusing on the determinants of internationalization speed through R-assets. From the perspective of knowledge, the work also provides a theoretical reference whereby MNEs can use host country R-assets to accelerate knowledge acquisition and then internationalization practice. In conclusion, this study provides valuable insights for managers aiming to develop effective strategies through R-assets to achieve rapid internationalization, contributing to an emerging literature stream on catch-up for emerging-market MNEs.