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The sensitivity and fragility of the construction industry’s economic system make the economic resilience of the construction industry (ERCI) a key concern for stakeholders and decision-makers. This study aims to measure the ERCI, identify the heterogeneity and spatial differences in ERCI, and provide scientific guidance and improvement paths for the industry. It provides a foundation for the implementation of resilience policies in the construction industry of developing countries in the future.

The comprehensive index method, Theil index method, standard deviation ellipse method and geographic detector model are used to investigate the spatial differences, spatiotemporal evolution characteristics and the influencing factors of the ERCI from 2005 to 2020 in China.

The ERCI was “high in the east and low in the west”, and Jiangsu has the highest value with 0.64. The Theil index of ERCI shows a wave downward pattern, with significant spatial heterogeneity. The overall difference in ERCI is mainly caused by regional differences, with the contribution rates being higher by more than 70%. Besides, the difference between different regions is increasing. The ERCI was centered in Henan Province, showing a clustering trend in the “northeast-southwest” direction, with weakened spatial polarization and a shrinking distribution range. The market size, input level of construction industry factors, industrial scale and economic scale are the main factors influencing economic resilience. The interaction between each influencing factor exhibits an enhanced relationship, including non-linear enhancement and dual-factor enhancement, with no weakening or independent relationship.

Exploring the spatial differences and driving factors of the ERCI in China, which can provide crucial insights and references for stakeholders, authorities and decision-makers in similar construction economic growth leading to the economic growth of the national economy context areas and countries.

The construction industry development is the main engine for the national economy growth of most developing countries. This study establishes a comprehensive evaluation index on the resilience measurement and analyzes the spatial effects, regional heterogeneity and driving factors on ERCI in the largest developing country from a dynamic perspective. Moreover, it explores the multi-factor interaction mechanism in the formation process of ERCI, provides a theoretical basis and empirical support for promoting the healthy development of the construction industry economy and optimizes ways to enhance and improve the level of ERCI.

Mental health problems are a grave concern in construction. Although the distinction between high job demands and low job resources, as reflected in the Job Demands-Resources (JD–R) model, has been used to examine the extent to which psychosocial hazards influence mental health for construction practitioners, limited research has reflected on the nature of these psychosocial hazards by exploring experiences of site-based construction practitioners.

This study adopted a phenomenological approach to examine people’ experiences and thoughts of the complex phenomena of psychosocial hazards and mental health in construction. In total, 33 semi-structured interviews were undertaken with site-based construction practitioners in Australia to unveil construction-focused psychosocial hazards and their effects on mental health. The data were analysed via content analysis, employing an interpretation-focused coding strategy to code text and an individual-based sorting strategy to cluster codes.

Eighteen psychosocial hazards were identified based on the JD–R model. Six of these represented a new contribution, describing salient characteristics inherent to the construction context (i.e. safety concerns, exposure to traumatic events, job insecurity, task interdependency, client demand and contract pressure). Of particular importance, a number of interrelationships among psychosocial hazards emerged.

The significance of this qualitative research lies in elucidating psychosocial hazards and their complex interrelatedness in the context of the mental health of construction practitioners, enriching the understanding of this central health and safety issue in the high-risk setting of construction work. The findings contribute to addressing mental health issues in the Australian construction industry by identifying higher order control measures, thereby creating a mentally healthy workplace.

Traditional multivariable grey prediction models define the background-value coefficients of the dependent and independent variables uniformly, ignoring the differences between their physical properties, which in turn affects the stability and reliability of the model performance.

A novel multivariable grey prediction model is constructed with different background-value coefficients of the dependent and independent variables, and a one-to-one correspondence between the variables and the background-value coefficients to improve the smoothing effect of the background-value coefficients on the sequences. Furthermore, the fractional order accumulating operator is introduced to the new model weaken the randomness of the raw sequence. The particle swarm optimization (PSO) algorithm is used to optimize the background-value coefficients and the order of the model to improve model performance.

The new model structure has good variability and compatibility, which can achieve compatibility with current mainstream grey prediction models. The performance of the new model is compared and analyzed with three typical cases, and the results show that the new model outperforms the other two similar grey prediction models.

This study has positive implications for enriching the method system of multivariable grey prediction model.

This study aims to compares the effects of different human-like appearances (low vs. medium vs. high) of service robots (SRs) on consumer trust in service robots (CTSR), examines the mediating role of perceived warmth (WA) and perceived competence (CO) and demonstrates the moderating role of culture and service setting.

The research design includes three scenario-based experiments (Chinese hotel setting, American hotel setting, Chinese hospital setting).

Study 1 found SR’s human-like appearance can arouse perceived anthropomorphism (PA), which positively affects CTSR through parallel mediators (WA and CO). Study 2 revealed consumers from Chinese (vs. American) culture had higher CTSR. Study 3 showed consumers had higher WA and CO for SRs in the credence (vs. experience) service setting. The authors also had an exploratory analysis of the uncanny valley phenomenon.

The findings have practical implications for promoting the diffusion of SRs in the hospitality industry. Managers can increase CTSR by augmenting the anthropomorphic design of SRs; however, they must consider the differences in this effect across all service recipients (consumers from different cultures) and service settings.

The authors introduce WA and CO as mediators between PA and CTSR and set the culture and service setting as moderators.

Ultracapacitors find extensive applications in various fields because of their high energy density and long cycling periods. However, due to the movement of ions and the arrangement patterns on rough/irregular electrode surfaces during the charge and discharge process of ultracapacitors, the parameters of ultracapacitors usually change with the variation of operating conditions. The purpose of this study is to accurately and quickly identify the parameters of ultracapacitors.

A variable forgetting factor recursive least square (VFFRLS) algorithm is proposed in this paper for online identifying the equivalent series resistance and capacitance C of ultracapacitors. In this work, a real-time error-based strategy is developed to adaptively regulate the value of the forgetting factor of traditional forgetting factor recursive least square (FFRLS) algorithm. The strategy uses the square of the average time autocorrelation estimation of the prior error and the posterior error between the predicted output and the actual output as the adjustment basis of forgetting factors.

Experiments were conducted using the proposed scheme, and the results were compared with the estimation results obtained by the recursive least squares (RLS) algorithm and the traditional FFRLS algorithm. The maximum root mean square error between the estimated values and actual values for VFFRLS is 3.63%, whereas for FFRLS it is 9.61%, and for RLS it is 19.33%.

By using the proposed VFFRLS algorithm, a relatively high precision can be achieved for the online parameter estimation of ultracapacitors. Besides, the dynamic balance between parameter stability and tracking performance can be validated by dynamically adjusting the forgetting factor.

This study aims to obtain governance strategies for managing the complexity of megaprojects by analyzing the impact of individual factors and their configurations using the fuzzy-set qualitative comparative analysis (fsQCA) method and to provide references for project managers.

With the continuous development of the economy, society and construction industry, the number and scale of megaprojects are increasing, and the complexity is becoming serious. Based on the relevant literature, the factors affecting the complexity of megaprojects are determined through case analysis, and the paths of factors affecting the complexity are constructed for megaprojects. Then, the fsQCA method is used to analyze the factors affecting the complexity of megaprojects through 245 valid questionnaires from project engineers in this study.

The results support the correlation between the complexity factors of megaprojects, with six histological paths leading to high complexity and seven histological paths leading to low complexity.

It breaks the limitations of the traditional project complexity field through a “configuration perspective” and concludes that megaproject complexity is a synergistic effect of multiple factors. The study is important for enriching the theory of megaproject complexity and providing complexity governance strategies for managers in megaproject decision-making.

This paper examines the impact of corporate digital transformation on employee satisfaction. Therefore, this study extends our understanding of the economic consequences of corporate digital transformation from employees’ perspectives.

The data used to construct our main proxy of employee satisfaction are collected from Kanzhun.com, which provides reviews by rank-and-file employees on their employers. This study uses a large sample of Chinese firms and adopts various empirical methods to examine the impact of digital transformation on employee satisfaction.

We find a significant positive relationship between corporate digital transformation and employee satisfaction. Moreover, we document that the relationship between corporate digital transformation and employee satisfaction is more pronounced in firms with higher labor intensity and in state-owned enterprises (SOE).

One significant limitation is that corporate digital transformation is constructed based on word frequency analysis. This approach may be influenced by variations in corporate disclosure practices and might not accurately capture the true extent of corporate digital transformation. This limitation is not only present in our research but is also pervasive in many other studies that utilize similar methodologies. Therefore, our results should be interpreted with this caveat in mind.

Our study suggests that corporate digital transformation enhances employee satisfaction, providing direct evidence for managers and regulators to promote corporate digital transformation. Through digital transformation, companies can not only improve operational efficiency but also foster employee satisfaction. This dual benefit underscores the importance of investing in corporate digital transformation for long-term success.

Our study suggests that corporate digital transformation enhances employee satisfaction, providing direct evidence for managers and regulators to promote corporate digital transformation. Through digital transformation, companies can not only improve operational efficiency but also foster employee satisfaction. This dual benefit underscores the importance of investing in corporate digital transformation for long-term success.

Our study contributes to the literature on the economic consequences of corporate digital transformation and extends existing research on the determinants of employee satisfaction. Additionally, it provides a novel measurement of employee satisfaction for a large sample of Chinese firms.

A review of sustainability challenges of flame retardants (FRs) for textiles has been conducted. Specifically, the purpose of this paper is to identify and recommend solutions to sustainability challenges emanating from the raw material, processing technology and performance of the FRs used for textiles.

The approach used in preparing this paper was based on the review of various scholarly databases about the subject matter. The review approach is designed to inform the readers about the sustainability challenges of FRs for textiles. The science of burning and FRs for synthetic and cellulosic fibres were reviewed. Both synthetic and natural biodegradable FRs for textiles has been identified. The obtained literature was then synthesised to get information about sustainable challenges of non-halogenated FRs both synthetic and natural biodegradable. Finally, possible approaches for mitigating the identified challenges have been recommended.

The sustainability challenges of the FRs in terms of raw material, processing, affordability and performance have been identified. Synthetic FRs suffer from sustainability challenges in terms of raw materials, processing and non-renewability. Despite the environmental friendliness and sustainability in terms of being renewability, processability and biodegradability, natural biodegradable FRs have poor performance compared to synthetic ones. Moreover, natural biodegradable FRs depend on geographical condition and lack economic variability data. Potentially, the challenges of FRs can be mitigated through eco-friendly synthesis, chemical modification and sustainable methods of applications. Because of its renewability and environmental friendliness, biodegradable FRs have a potential to becoming sustainable if researched more.

In this review, a collection of literature about sustainability challenges of FRs and the approaches to overcome the challenges has been provided. The collected information was analysed and synthesised to bring understanding of the science of burning, types and application of FRs for textiles and biodegradable FRs. Sustainability challenges have been identified, and mitigation approaches are provided.

Emerging market multinationals often face a variety of legitimacy challenges as they engage in cross-border acquisitions in developed countries, which requires an assortment of legitimacy strategies best aligned with the legitimacy challenges they face. This study advocates for a configurational perspective that examines how different configurations of legitimacy challenges, organizational characteristics, and legitimacy strategies influence the likelihood of deal completion in cross-border acquisitions by emerging market multinational enterprises (EMNEs).

Based on 328 cross-border acquisition cases by Chinese firms, this study adopts the fuzzy-set qualitative comparative analysis to examine the combined effects of institutional distance, political affinity, equity sought, architecture design, sensitive·industry and state-owned and enterprise (SOE) on cross-border acquisition completion.

This study identifies six pathways with different configurations for deal completion, suggesting that a deal's overall legitimacy falls at the intersection of the country-level institution and the firm-level characters and strategy evaluations.

This study investigates how nested legitimacy influences cross-border acquisition completion by offering a holistic and configurational understanding of the deal completion of cross-border acquisitions by EMNEs and yields useful insights for future research on cross-border acquisition completion and legitimacy.

Existing research has predominantly concentrated on examining the factors that impact consumer decisions through the lens of potential consumer motivations, neglecting the sentiment mechanisms that propel guest behavioral intentions. This study endeavors to systematically analyze the underlying mechanisms governing how negative reviews exert an influence on potential consumer decisions.

This paper constructs an “Aspect-based sentiment accumulation” index, a negative or positive affect load, reflecting the degree of consumer sentiment based on affect infusion model and aspect-based sentiment analysis. Initially, it verifies the causal relationship between aspect-based negative load and consumer decisions using ordinary least squares regression. Then, it analyzes the threshold effects of negative affect load on positive affect load and the threshold effects of positive affect load on negative affect load using a panel threshold regression model.

Aspect-based negative reviews significantly impact consumers’ decisions. Negative affect load and positive affect load exhibit threshold effects on each other, with threshold values varying according to the overall volume of reviews. As the total number of reviews increases, the impact of negative affect load diminishes. The threshold effects for positive affect load showed a predominantly U-shaped course of change. Hosts respond promptly and enthusiastically with detailed, lengthy text, which can aid in mitigating the impact of negative reviews.

The study extends the application of the affect infusion model and enriches the conditions for its theoretical scope. It addresses the research gap by focusing on the threshold effects of negative or positive review sentiment on decision-making in sharing accommodations.