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This study aims to investigate mechanisms and boundary conditions of the impact of customer engagement strategies (CESs) on customer loyalty (CL) based on goal-framing and well-being theory.

Through a three-stage, time-lagged research design, 246 valid samples were obtained. This study tested and validated the proposed framework using hierarchical regression analysis and a moderated mediation procedure.

First, CESs have a significant positive impact on CL. Second, consumer well-being (CWB) partially mediates the CESs–CL relationship. Third, information processing style (IPS) moderates the impact of CESs on CWB, with a more pronounced effect observed under the affective processing style. Finally, IPS further moderates the indirect effect of CESs on CL, indicating that CESs enhance CL through increased CWB, particularly under the affective processing style.

Revealing the pivotal role of CESs in enhancing CL at the corporate level helps bridge the gap between companies and customers, thereby facilitating the establishment of long-term cooperative relationships. Additionally, introducing the concept of CWB into the study of CL offers a novel perspective for understanding customer behavior.

Surface quality and porosity significantly influence the structural and functional properties of the final product. This study aims to establish and explain the underlying relationships among processing parameters, top surface roughness and porosity level in additively manufactured 316L stainless steel.

A systematic variation of printing process parameters was conducted to print cubic samples based on laser power, speed and their combinations of energy density. Melt pool morphologies and dimensions, surface roughness quantified by arithmetic mean height (Sa) and porosity levels were characterized via optical confocal microscopy.

The study reveals that the laser power required to achieve optimal top surface quality increases with the volumetric energy density (VED) levels. A smooth top surface (Sa < 15 µm) or a rough surface with humps at high VEDs (VED > 133.3 J/mm³) can serve as indicators for fully dense bulk samples, while rough top surfaces resulting from melt pool discontinuity correlate with high porosity levels. Under insufficient VED, melt pool discontinuity dominates the top surface. At high VEDs, surface quality improves with increased power as mitigation of melt pool discontinuity, followed by the deterioration with hump formation.

This study reveals and summarizes the formation mechanism of dominant features on top surface features and offers a potential method to predict the porosity by observing the top surface features with consideration of processing conditions.

Technology innovation in enterprises is a powerful driver of national competitiveness and sustainable corporate development. At the same time, the regional innovation policy mix serves as a core factor at the macro level, guiding and influencing enterprise technology innovation. Therefore, this paper addresses a critical question in innovation studies: the impact of the regional innovation policy mix complexity on enterprise technology innovation. Additionally, we also investigated the internal mechanisms and boundary conditions within this framework.

A dual-mode network model of local government-regional innovation policy is developed to capture the complexity of the regional innovation policy mix. The complexity index is calculated iteratively using the R language. The paper employs quantitative and empirical analysis, drawing on a sample of 622 regional innovation-related policy documents from 31 Chinese provinces (municipalities and autonomous regions).

The results reveal an inverted U-shaped relationship between policy mix complexity and enterprise technological innovation. The analysis further shows that university-industry cooperation intensity mediates this relationship, while regional knowledge absorptive capability moderates the impact of regional innovation policy mix complexity on enterprise technological innovation.

This paper highlights the influence of regional innovation policy mix complexity on enterprise technological innovation and underscores the role of university-industry cooperation intensity and regional knowledge absorptive capability. The findings offer valuable insights into the dynamics of enterprise innovation and inform effective government policy governance for fostering innovation.

This paper aims to clarify the resistance degree of group road logistics to flood disaster resilience. The paper measures the resilience of group road logistics by establishing network structure model. The purpose of this study is to improve the resilience of road log.

This paper adopts Delphi method to collect data, interviews mainly flood management experts and supply chain risk management experts, and then analyzes the data through the network structure model combined with interpretative structure model (ISM) and analytical network process (ANP).

The results show that flood frequency and drainage systems are the main factors affecting the resilience of road transport logistics in urban areas. These research results provide useful guidance for the effective planning and design of urban road construction and infrastructure.

However, the main factors affecting the resilience of road transport logistics are likely to change with the development of factors such as climate, economy and environment. Therefore, in future work, the authors' research will focus on the further application of this evaluation method.

The results show that the impact of flooding on the four dimensions of road logistics resilience varies. This shows that in deciding what intervention measures are to be taken to improve the resilience of the road network to flooding, various measures need to be considered.

This paper provides a more scientific analysis of the risk management ability of the road network in the face of floods. In addition, it also provides a useful reference for urban road planners.

This paper addresses a clear need to study how to build models to improve the resilience of road logistics in flood risk.

This study empirically investigates the impacts of technological innovation and operational efficiency on environmental performance and the moderating effects of environmental orientation.

We develop a conceptual framework based on the Porter Hypothesis. We collect a sample of 850 listed firms in China between 2010 and 2019. The fixed effect model was used to analyse the data.

The empirical findings reveal that technological innovation indirectly enhances environmental performance through operational efficiency and partially mediates this impact. We also find that environmental orientation strengthens the positive impacts of technological innovation and operational efficiency on environmental performance.

This study contributes to the literature by revealing that technological innovation is positively associated with operational efficiency and environmental performance, which suggests that technological innovation can simultaneously enhance business and environmental performance. Hence, this study provides empirical support for the Porter Hypothesis. The results also extend the Porter Hypothesis by revealing how technological innovation affects environmental performance and under what conditions technological innovation has a greater impact on environmental performance.

This study aims to examine the effect of investor sentiment on stock market crash risk in the Asia–Pacific region and the moderating role of uncertainty factors.

This research uses principal component analysis to construct an investor sentiment index of 17 Asia–Pacific stock markets before analyzing the data through hierarchical regression with the feasible generalized least squares method.

The empirical results show that investor sentiment has a positive impact on crash risk in the Asia–Pacific stock markets. This impact is more significant in advanced economies compared to emerging markets and developing economies. The nexus between investor sentiment and stock market crash risk is increased by economic policy uncertainty but decreased by uncertainty from pandemics.

This study only investigates the moderating roles of global uncertainty factors but not local uncertainty factors. In addition, the sentiment of different investor groups has not been examined yet.

The findings of this study are relevant for global investors, portfolio managers and policymakers. Investors and portfolio managers can use sentiment indicators to predict downturns and adjust strategies, whereas policymakers can leverage these insights to design regulations that mitigate systemic risks during global uncertainties.

This study expands the literature on the relationship between investor sentiment and stock market crash risk, providing updated insights into sentimental bias in behavioral finance.

This study explores whether and how financial agglomeration affects enterprise specialization, and whether it weakens the division effects of logistics accessibility.

Using the panel data of A-share listed companies in the Chinese manufacturing industry from 2010 to 2018, the authors test the hypotheses of the research framework by constructing a double fixed effect model.

First, for every 1% increase in financial agglomeration and logistics accessibility, enterprise specialization will increase by 1.8% and 5.6%. Meanwhile, financial agglomeration weakens the division effects of logistics accessibility. After a multiple robustness test, the above conclusions still hold. Second, the mechanism test shows that financial agglomeration can promote enterprise specialization through cost saving effect, scale expansion effect and technological progress effect. Third, financial agglomeration has a stronger positive impact and negative moderating effect on enterprise specialization in periphery areas and small-scale enterprises, but logistics accessibility is more likely to increase enterprise specialization in core regions and small-scale firms.

In the context of the global value chain (GVC) reshaping caused by the transformation of the international situation, exploring the relationship among financial agglomeration, logistics accessibility and enterprise specialization based on China’s experience can be an important insight for other emerging economies to enhance their position in the GVC.

The above findings enrich the literature on the division of labor among firms and contribute to the further improvement of GVC theory and division theory.

This paper aims to identify the impact of the new ambient air quality standards (AAQS) on firm innovation.

Taking listed companies from 2009 to 2014 as the research object, the authors focus on the quasinatural experiment of the pilot policy of the new AAQS and apply the time-varying difference-in-differences (DID) method to conduct the empirical test.

The authors find that the new AAQS has a negative effect on firm innovation, and this negative impact may be caused by the increased environmental expenditures following the implementation of the new AAQS. Furthermore, the authors find that firm profitability and state ownership weaken this negative effect, but the effect of the degree of industrial pollution is statistically insignificant.

The study is an initial effort to explore the causal effect of the new AAQS on firm innovation. This study enriches the literature on the impact of environmental regulations on firm innovation and provides some reference value for the formulation of environmental regulation policies in developing countries.

In recent decades, researchers have increasingly begun to study the effects of transformational leadership on various teachers’ attitudes in K-12 settings. However, studies on the effect of transformational leadership on the job satisfaction of vocational high school teachers are not sufficient. Therefore, in this study, the nature of the relationship between transformational leadership and job satisfaction in Turkish vocational high schools was examined.

The study data came from 847 teachers working at 82 state vocational high schools located in 12 regions in Türkiye. To test the research model, we conducted multilevel structural equation modeling to explore the structural relationships between transformational leadership, teacher professional learning, teacher’ self-efficacy and job satisfaction.

The analysis confirms that teacher professional learning and self-efficacy are prominent mediators in the relationship between transformational leadership and job satisfaction in Turkish vocational high schools.

The present study is expected to contribute to the body of research focusing on the effects of transformational leadership on job satisfaction in vocational high schools. Implications for theory, practice and policy are discussed.