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Prefabricated building (PB) has been a pivotal force in advancing global building industrialization and sustainability. However, the PB supply chain operation faces significant challenges of exhausting negotiations, poor communication and imperfect information, representing high transaction costs (TCs). Existing literature inadequately addresses governance behaviors to mitigate TCs. This study aims to explore PB supply chain inefficiencies through the lens of TC theory, examining the nuanced relationships between hybrid governance behaviors and TCs and exploring effective governance strategies.

Based on the theoretical frameworks of governance behavior and TCs, this study employed semi-structured interviews and questionnaire surveys with PB experts in Anhui, China. Subsequently, integrated backpropagation neural network and ordered logistic regression analyses were conducted to identify critical governance behaviors and explore boundaries for TCs reduction.

TCs of the PB supply chain are elevated (1) from communication and coordination; (2) during the construction and approval stages. Investigation of how governance behaviors influence the TCs indicated that (1) enterprises exert more influence than local governments; (2) governance effectiveness in the transaction and transaction environment dimensions outweighs stakeholder influence and (3) functional TCs exist in PB, associated with component manufacturing, PB contract negotiation and learning cost.

This study extends understanding of TCs in PB by providing nuanced insights into the nature and timing of TCs and elucidates how governance structures shape TCs. Functional TCs intrinsic to PB were identified when exploring the optimization boundaries. These insights equip local governments and enterprises with actionable knowledge to prioritize effective governance behaviors and measures.

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.

Digital transformation and innovation-driven development have become an international consensus. The purpose of this paper is to examine the effects of relationships, mechanisms and economic consequences between digital transformation and enterprise innovation quality in order to provide a benchmark for developing countries to implement digital transformation strategies and innovation-driven strategies and provide a major support for economic recovery in the post-coronavirus disease 2019 (COVID-19) era.

Using microdata from A-share listed enterprises in Shanghai and Shenzhen from 2010 to 2021, this study examines the relationship between digital transformation and enterprise innovation quality and further reveals the internal logic and economic consequences of digital transformation to improve enterprise innovation quality through the mediating effect and moderating effect models.

The results demonstrate that digital transformation is beneficial for improving enterprise innovation quality. The heterogeneity test demonstrates that digital transformation has a larger effect on improving enterprise innovation quality in non-state-owned enterprises and eastern enterprises in China. The mechanism test demonstrates that digital transformation can improve enterprise innovation quality by improving internal control quality and analyst attention. Furthermore, with the increase in enterprise innovation inputs, digital transformation plays a significantly stronger role in improving enterprise innovation quality. The extended analysis demonstrates that digital transformation can significantly improve enterprise financial performance by improving innovation quality.

First, the construction of the core explanatory variable digital transformation index in this study is based on the Python data analysis software, which calculates the frequency of digital transformation in the text of the business situation analysis portion of the annual report of the listed companies and then obtains the degree of digital transformation of the company in this year. There may be some deviation from the degree of digital transformation in the actual production and operation of enterprises. Second, in addition to internal control quality and analyst attention, are there other mediating mechanisms for the impact of digital transformation on the quality of enterprise innovation? Third, whether the moderating effect of innovation input on digital transformation and innovation quality is related to human capital factors of the research and development (R&D) team, such as the technical background of R&D personnel, etc.

This study enriches the relevant theories of digital transformation and broadens the research boundaries of digital transformation and enterprise innovation. This study's result provides an empirical basis for enterprises to improve enterprise innovation quality and financial performance from the perspective of digital transformation at the micro level and points out specific practical directions, combining theory with practice.

The carbon complementary supply chain (CCSC) is a collaborative framework that facilitates internal carbon credit trading agreements among supply chain agents in compliance with prevailing carbon regulations. Such agreements are highly beneficial, prompting agents to consider joint investment in emission reduction initiatives. However, capital investments come with inevitable opportunity costs, compelling agents to weigh the potential revenue from collaborative investments against these costs. Thus, this paper mainly explores carbon abatement strategies and operational decisions of the CCSC members and the influence of opportunity costs on the strategic choice of cooperative and noncooperative investment.

The authors propose a novel biform game-based theoretical framework that captures the interplay of pricing competition and investment cooperation among CCSC agents and assesses the impact of opportunity costs on CCSC profits and social welfare. Besides, the authors also compare the biform game-based collaborative scenario (Model B) to the noncooperative investment scenario (Model N) to investigate the conditions under which collaborative investment is most effective.

The biform game-based collaborative investment strategy enhances the economic performance of the traditional energy manufacturer, who bears the risk of opportunity costs, as well as the retailer. Additionally, it incentivizes the renewable energy manufacturer to improve environmental performance through renewable projects.

This research contributes significantly by establishing a theoretical framework that integrates the concepts of opportunity costs and biform game theory, offering new insights into the strategic management of carbon emissions within supply chains.

Flooding is China’s most frequent and catastrophic natural hazard, causing extensive damage. The aim of this study is to develop a comprehensive assessment of urban flood risk in the Hubei Province of China, focusing on the following three issues: (1) What are the factors that cause floods? (2) To what extent do these factors affect flood risk management? (3) How to build an effective comprehensive assessment system that can be used to reduce flood risk?

This study combines expert opinion and evidence from the extent literature to identify flood risk indicators across four dimensions: disaster risk, susceptibility, exposure and prevention and mitigation. The Criteria Importance Through Intercriteria Correlation (CRITIC) and the Grey Relational Analysis (RA)-based Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) decision-making approach were applied to calculate the weighting of factors and develop a model of urban flood risk. Then, ArcGIS software visualizes risk levels and spatial distribution in the cities of Hubei Province; uncertainty analysis verified method accuracy.

The results show that there are significant differences in the level of urban flood risk in Hubei Province, with cities such as Tianmen, Qianjiang, Xiantao and Ezhou being at high risk, while cities such as Shiyan, Xiangyang, Shennongjia, Yichang, Wuhan and Huanggang are at lower flood risk.

The innovative method of combining CRITIC-GRA-TOPSIS reduces the presence of subjective bias found in many other flood risk assessment frameworks. Regional data extraction and uncertainty analysis enhance result reliability, supporting long-term decision-making and urban planning. Overall, the methodological approach developed provides an advanced, highly effective and efficient analysis and visualization of flood risk. This study deepens the understanding of flood risk assessment mechanisms and more broadly supports the development of resilient cities.

This paper aims to investigate the vertical cooperative relationship between the core enterprise and the manufacturer within the platform ecosystem, specifically analyzing the optimal decision-making processes of both parties under the original equipment manufacturer (OEM) and original brand manufacturer (OBM) modes.

This paper uses game theory to analyze the problem, considering factors such as brand value difference, cross-selling and platform empowerment. It constructs the game models for both OEM and OBM modes and discusses the selection strategies for the cooperation mode.

The results indicate that the choice of cooperation mode by the manufacturer and the core enterprise depends on the relative size of their brand values. In cases of inconsistent choices, cooperation can be improved by designing a transfer payment contract. When the brand value is constant, the product price is comprehensively affected by cross-selling revenue, price elasticity coefficient, cost coefficient of sales effort and cost coefficient of platform empowerment. The enterprise reduces the price only when the potential revenue brought by increasing product sales exceeds the marginal profit brought by increasing product pricing; otherwise, it raises the sales price.

The platform ecosystem is emerging as a future direction for business mode development. However, there is a paucity of research on the cooperation modes between manufacturers and core enterprises within the platform ecosystem.