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The purpose of this paper is to re‐examine the sources of momentum profits by focusing on momentum in monthly returns.

The paper utilizes a decomposition method proposed by Du and Watkins.

Different from previous studies, it is found that momentum may have multiple sources, and that risk or behavioral biases in isolation may not be sufficient to explain momentum.

The paper's finding that momentum may be at least partly due to risk is important for investors to understand the risk of momentum investing.

This paper focuses on the sources of momentum profits in monthly returns. The findings that momentum has multiple sources call for new explanations for momentum because all existing theories of momentum are either rational or behavioral. Furthermore, the finding that lead‐lag relationship plays an important role in momentum suggests that researchers should focus on mis‐reaction to common (market‐wide) information to explain momentum as emphasized by Lo and MacKinlay.

The purpose of this paper is to identify the energy absorption characteristics of arch micro-strut (ARCH) lattice structure (different from traditional straight micro-strut lattice structure) under high-speed impact, and promote the development of special-shaped micro-strut lattice structure.

The study serves to study the anti-impact and energy absorption characteristics of ARCH lattice structure under different strain rates and different unit layers of lattice structure. In this paper, quasi-static compression and Hopkinson compression bar experiments are used for comparative analysis.

The results show that the ARCH lattice structure has obvious strain rate effect. When the strain rate is low, the number of layers of lattice structure has a great influence on the mechanical properties. With the increase of strain rate, the influence of the number of layers on the mechanical properties gradually weakens. So the ARCH lattice structure with fewer layers (less than five layers) should be selected as the impact energy absorbing materials at lower impact rate, while at higher impact rate, the number of layers can be selected according to the actual requirements of components or devices space size.

This study shows that Arch lattice structure has excellent energy absorption performance, and provides a theoretical reference for the application of ARCH lattice structure in energy-absorbing materials. ARCH lattice structure is expected to be applied to a variety of energy absorption and anti-impact components or devices, such as aircraft black box fall buffer components, impact resistant layer of bulletproof and landing buffer device.

This study aims to examine how Confucianism influences corporate digital transformation and explore the underlying mechanisms. Meanwhile, this study also seeks to analyze whether the relationship between Confucianism and corporate digital transformation significantly varies under different contextual conditions.

This study utilizes a sample of Chinese listed firms from 2012 to 2021 to empirically examine how Confucianism influences corporate digital transformation and validate the mechanisms of informal hierarchies, agency costs and financing constraints. Moreover, it explores the moderating effects of political connection and overseas culture. Subsample regressions assess the influence of corporate internationalization, property rights and regional marketization.

The findings of this study highlight the crucial role of Confucianism in driving corporate digital transformation. Confucianism contributes to corporate digital transformation by clarifying informal hierarchies, reducing agency costs and alleviating financing constraints. Nevertheless, political connection and overseas culture weaken the positive impact of Confucianism on corporate digital transformation. Further evidence indicates that Confucianism's influence on digital transformation is particularly pronounced in environments characterized by limited internationalization, heightened marketization and among non-state-owned enterprises.

This study elucidates the role of informal institutions in driving corporate digital transformation, enriching the literatures on the intersection of Confucianism and corporate digitalization. Our findings offer a novel perspective and contribute to management practice by exploring the mechanisms and contextual conditions.

Amid the pressing global need for sustainable development and environmental protection, exploring effective pathways to foster green innovation has become crucial. This study aims to examine the impact of digitalization on green innovation by analyzing its interactions with micro and macro factors.

This paper adopts a multi-level perspective (MLP) with a multi-agent framework to study how different factors impact green innovation efficiency. This paper uses fuzzy-set qualitative comparative analysis (fsQCA) on 30 Chinese provinces from 2012 to 2021 to identify key conditions and pathways for green innovation efficiency.

The findings reveal that digitalization alone does not constitute a necessary condition for green innovation. Rather, digitalization needs to be configured with other factors to form dynamic causal paths. In 2012–2016, a single path type (digitalization coupled with regional innovation and marketization) exists. In 2017–2021, two causal path types [digitalization and foreign direct investment (FDI), digitalization and regional innovation] emerge.

The study has three theoretical contributions. First, while previous research studies often focus on single factors, the study examines the complexity of green innovation from a configurational perspective. Using the fsQCA method, this paper explores complex interactions and asymmetric causal relationships among multi-level factors. Second, this paper presents a novel theoretical framework that integrates the MLP framework with the multi-agent framework, facilitating a multi-dimensional analysis of green innovation. This synthesis elucidates the complex network of relationships, interactions and dependencies that propel green innovation. Third, responding to the call in international dynamic QCA research, this paper uses the multi-period QCA method. This allows for a detailed stage-by-stage comparative analysis, elucidating green innovation paths and revealing evolutionary trends of “configurational diversity” and “factor concentration.” This research offers practical insights for policymakers and stakeholders to develop more effective, tailored strategies for promoting green innovation.

Digitalization alone cannot fully drive green innovation; it must be combined with factors such as marketization, regional innovation and FDI. To achieve this, promote market-oriented reforms to enhance market mechanisms and encourage participation in green innovation projects through incentives. Increase investment in regional innovation, establish platforms for resource sharing and technological exchange and support cooperation between local governments and businesses. Additionally, it attracts FDI by creating favorable policies and a conducive business environment. Adapting policies to evolving conditions is crucial. Regularly assess and update policies to ensure their effectiveness and relevance in the face of changing technological and market landscapes. Optimize approval processes, reduce bureaucratic hurdles and improve policy implementation efficiency. Regions should also tailor strategies to their specific needs: those with high digitalization but lacking FDI should focus on building a robust research and development (R&D) personnel base, while regions with high FDI but insufficient local talent should attract skilled professionals through talent attraction programs and partnerships with international universities. Continuously adapting strategies ensures that regions can effectively drive sustainable development and green innovation.

The research advances the understanding of green innovation by examining multi-level configuration effects, introducing an integrated framework and conducting stage-by-stage comparative analysis. These contributions collectively enhance the theoretical foundation and practical applicability of promoting green innovation in an increasingly digitalized world.

This study offers invaluable theoretical insights and practical pathways for policymakers and decision-makers, providing tailored strategies to promote green innovation. By understanding the complex interactions between digitalization and other factors, decision-makers can better leverage digitalization for sustainable development and environmental protection.

Based on organizational learning theory, this study aims to investigate the performance consequences and potential contextual factors of outward foreign direct investment (OFDI) persistence.

A regression analysis was conducted on a sample of 19,950 OFDI events of 1,425 A-share listed Chinese enterprises from 2008 to 2022. The estimator used was ordinary least squares with residual analysis, which allowed us to obtain robust and reliable results.

The results indicated that persistence in both greenfield investments and cross-border M&As had a significant and positive impact on firm performance, and such relationship was positively moderated by organizational absorptive capacity.

This study only tested the economic performance of OFDI persistence rather than innovation and social performance. Exploring the effects of OFDI persistence on other aspects may also add new insights to the persistence literature. Besides absorptive capacity, it might be useful to conduct a more comprehensive consideration of moderators in the future.

This paper contributes to the research on the temporal dimension of internationalization by introducing the concept of OFDI persistence. Additionally, we used the OFDI spell to capture the notion of OFDI persistence, which is an endeavor to overcome the shortcomings of the traditional indicator. Finally, this paper also contributes to the organizational learning perspective by applying it to analyze persistent OFDI operations.

Sea‐Nine Biocide ‐ Rohm and Haas Company announced that Sea‐Nine 211 biocide has been registered for use in marine paints by the US Environmental Protection Agency. Sea‐Nine 211 is the first new generation organic biocide to earn this registration.

This paper explores what factors influence household textile washing behaviour and how these factors relate to greenhouse gas emissions during the textile use stage.

A questionnaire survey related to textile summer washing and care behavior was conducted among households in 16 administrative districts of Shanghai. This study used the modified Consumer Lifestyle Approach framework of the washing and care ecosystem. The research hypotheses were established by selecting related factors from four aspects: household demographic characteristics, economy and consumption characteristics, washing machines and detergents characteristics.

First, we have demonstrated how some course factors do not significantly affect greenhouse emissions. None of the demographics, detergent-related activities, economy and consumption constructs significantly affect greenhouse emissions. Second, we have identified that washing machine and related activities has a direct positive effect on GHG emissions. The washing machine is not only the de facto carrier of all washing activities but also the core of washing activities. Washing machine is crucial in reducing greenhouse emissions and adjusting consumer behaviors.

This paper conducts a study related to the washing and care behavior of households in Shanghai. The paper examines the factors influencing household washing behavior and the relationship between these factors and greenhouse gas emissions during the textile use phase.

The density peak clustering algorithm (DP) is proposed to identify cluster centers by two parameters, i.e. ρ value (local density) and δ value (the distance between a point and another point with a higher ρ value). According to the center-identifying principle of the DP, the potential cluster centers should have a higher ρ value and a higher δ value than other points. However, this principle may limit the DP from identifying some categories with multi-centers or the centers in lower-density regions. In addition, the improper assignment strategy of the DP could cause a wrong assignment result for the non-center points. This paper aims to address the aforementioned issues and improve the clustering performance of the DP.

First, to identify as many potential cluster centers as possible, the authors construct a point-domain by introducing the pinhole imaging strategy to extend the searching range of the potential cluster centers. Second, they design different novel calculation methods for calculating the domain distance, point-domain density and domain similarity. Third, they adopt domain similarity to achieve the domain merging process and optimize the final clustering results.

The experimental results on analyzing 12 synthetic data sets and 12 real-world data sets show that two-stage density peak clustering based on multi-strategy optimization (TMsDP) outperforms the DP and other state-of-the-art algorithms.

The authors propose a novel DP-based clustering method, i.e. TMsDP, and transform the relationship between points into that between domains to ultimately further optimize the clustering performance of the DP.

Empirical literature is the primary source of understanding how policing can effectively reduce criminal activities. Spatial analyses can identify particular effects that can explain and assist in constructing appropriate regional strategies and policies; nevertheless, studies that use spatial regression methods are more limited and can provide a perspective on specific effects in a more disaggregated regional context.

This research aims to conduct a systematic literature review (SLR) to understand the relationship between crime indicators and police production using spatial regression models. We consider a combination of Kitchenham and Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocols as a methodological strategy in five bibliographic databases for collecting scientific articles.

The SLR suggests a limited amount of evidence that meets the criteria defined in the research strategy. Several particularities are observed regarding police and criminal production metrics, either in terms of aggregation level, indicator transformations or scope of analysis. A broader time perspective did not necessarily indicate statistical significance compared to models with a single-period sample.

The findings suggest the possibility of expanding efforts by the public sector to provide policing data with the intention of conducting appropriate research using spatial analysis. This step could allow for a more robust integration between the public sector and researchers, strengthening policing strategies, evaluating the effectiveness of public security policies and assisting in the development of strategies for future policy actions.

Limited empirical evidence meets the criteria of spatial regression models with temporal components considering police production and criminality indicators. Constructing an SLR with this scope is an unprecedented contribution to the literature. The discussion can enhance the understanding of approaches for studying the relationship between police efforts and crime prevention.