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Numerical literature shows that agricultural insurance can affect pesticide investments, but few of them are devoted to explain how agricultural insurance affects farmers’ selection on green or traditional pesticides. This paper aims to develop a theoretical model about how agricultural insurance influences on green pesticides selections and tests our conclusions by using the data from China land economic survey (CLES) from 2020 to 2021.

We employ probit model to capture the effects of agricultural insurance on green pesticides adoption.

We indicate that green pesticides have a stronger effect on stabilizing yield and increasing income than traditional pesticides, but there are still risks disturbing farmers’ decisions on green pesticides usage. By providing premium subsidies after the farmers are affected by natural risk, agricultural insurance improves the farmers’ expected income and encourages farmers to use green pesticides. Further, we further confirm these conclusions by considering different scenarios such as climate risks, farmers’ entrepreneurship and credit constraints. We find that the effects are more salient if croplands are under higher natural risks and, farmers are equipped with entrepreneurship and formal credit. This paper implies that the agricultural insurance decoupled with green technologies also have salient positive effects on agricultural pollution control.

The potential contributions of this paper can be outlined in three aspects in detail. Firstly, this paper aims to revel the effects of agricultural insurance on pesticide selection by structuring a general theoretical model. By using the CLES data from 2020 to 2021, we confirm that agricultural insurance increases the probability for adopting green pesticides. Secondly, this paper discusses the effects of farmers’ characteristics on the results and finds that if farmers have entrepreneurship, the effects of agricultural insurance on green pesticide usage will be more salient. Thirdly, it uncovers some practices in China, which will supply experiences for other developing countries. For example, this paper further demonstrates that “insurance + credit” plan the present Chinese government carried out will be an important measure for strengthening effects of agricultural insurance on green pesticides usage. Moreover, it shows that decouple agricultural policies will also guide farmers to use green technologies eventually if the technologies are reliable and farmers can afford.

Investigation of the anomalies associated with crashes and jackpots in the Chinese stock market.

We propose a logit model to predict the events of crashes and jackpots in the Chinese stock market. The model introduces a new variable of the price-to-sales ratio and takes into account the market states, Up and Down.

The anomalies associated with crashes and jackpots are not related to variations in economic conditions, but are associated with limits to arbitrage. High-liquidity stocks have strong mispricing effects. The institutions’ speculative trading will push liquid stock prices further away from their fundamentals but avoid buying illiquid stocks with a higher probability of price crashes and jackpots.

We propose a logit model to predict the extreme events of both crash and jackpot in the Chinese stock market. Our model effectively disentangles from CRASHP and JACKP. Compared with the traditional model, it substantially enhances in-sample and out-sample predictions. Based on the predictions of the extreme events, we find two strong and robust pricing effects associated with ex ante CRASHP and JACKP in the Chinese stock market.

This study examines how project uncertainties (environmental uncertainty and participant uncertainty) affect guanxi and contractual governance and assesses the mediating role of guanxi governance between project uncertainty and contractual governance.

Data were collected in two stages from Chinese contractors. First, in-depth interviews were conducted with nine construction engineering project practitioners in different contracts as a pilot for questionnaire designing. Second, a cross-sectional questionnaire survey was conducted with professionals and practitioners of construction enterprises to collect primary data. Partial least squares structural equation modeling (PLS-SEM) was used to test seven hypotheses based on data collected from 198 respondents.

Project environmental uncertainty promotes the use of guanxi governance, while project participant uncertainty hinders it; the relationship between both types of uncertainty and contractual governance is the same as with guanxi governance. Furthermore, guanxi governance promotes contractual governance and partially mediates project environmental uncertainty and contractual governance and a complete mediating role between project participant uncertainty and contractual governance.

As the interviewed samples are mainly from China, the study should be replicated using large representative samples from East Asian countries, such as Japan and South Korea, to gain a more comprehensive understanding of the influence of guanxi governance. Further, while the internal consistency reliability and convergent validity of the questionnaire data in this study align with the standards, a larger sample size would improve the reliability and validity of the research results and better represent the overall work situation of contractors, owners and public policymakers.

The results provide insights into project governance research and have implications for construction practitioners in deploying governance-related resources.

The purpose of this study is to investigate the antecedents of metaverse adoption intention amongst Muslim students by expanding the technology acceptance model (TAM) to incorporate factors viz. perceived cyber risk (PCR), perceived enjoyment (PE), personal innovativeness in IT (PIT), self-efficacy (SE), trust (TR) and religiosity (RL).

An online survey was circulated using a Google questionnaire to gather information on the study constructs. Purposive and snowball sampling techniques were adopted to reach the targeted students. The proposed associations were examined through the application of structural equation modelling with the use of AMOS software.

The findings suggest that the empirical results derived from the study present a compelling and effective model, and the model is designed to elucidate the intentions of Indian Muslim students regarding their willingness to embrace or adopt the metaverse. The research has identified and showcased a robust conceptual framework that provides insights into the factors influencing the metaverse adoption intentions among Muslim students.

This research adds value to the existing literature by expanding the understanding of metaverse adoption amongst Muslim students. This thorough framework offers an intricate comprehension of metaverse adoption, offering a theoretical framework beyond traditional technological determinants. This study provides important insights that can assist educationists, administrators and policymakers in various ways in chalking out essential strategies, policies and programmes related to metaverse adoption amongst Muslim students.

This study is unique as the six additional constructs, viz. PCR, PE, PIT, SE, TR and RL, are included in the original TAM model, thus filling the literature gap. It also augments the comprehension of the metaverse and unfolds the antecedents of metaverse adoption intention amongst Muslim societies through the lens of students.

The paper proposes a two-level closed-loop supply chain (CLSC) dynamic competitive model based on different competitive cooperation situations, and explores the impact of competitive cooperation methods on the pricing strategies, recycling and remanufacturing strategies and competitive model selection strategies of supply chain firms.

This paper establishes a CLSC game consisting of a manufacturer and two retailers. Firstly, five CLSC models are established in both horizontal and vertical dimensions, each of which competes with one another. Secondly, the recycling and remanufacturing pricing strategies are analyzed under different competition or cooperation models. Finally, the results are verified through numerical analysis.

The overall profitability of the CLSC is highest when the manufacturer–retailer partnership alliance is in place. The relationship between retailers and manufacturers is also found to be the best way to achieve overall optimization of the CLSC.

The paper investigates the relationship between the competitive partnership and the total profit of the CLSC, taking into account how to optimize the overall benefit, and focusing on how to optimize the individual interests of each participating enterprise. The results can provide basis and guidance for managers' pricing decision and competition cooperation.

Laser point clouds are a 3D reconstruction method with wide range, high accuracy and strong adaptability. Therefore, the purpose is to discover a construction point cloud extraction method that can obtain complete information about the construction of rebar, facilitating construction quality inspection and tunnel data archiving, to reduce the cost and complexity of construction management.

Firstly, this paper analyzes the point cloud data of the tunnel during the construction phase, extracts the main features of the rebar data and proposes an M-E-L recognition method. Secondly, based on the actual conditions of the tunnel and the specifications of Chinese tunnel engineering, a rebar model experiment is designed to obtain experimental data. Finally, the feasibility and accuracy of the M-E-L recognition method are analyzed and tested based on the experimental data from the model.

Based on tunnel morphology characteristics, data preprocessing, Euclidean clustering and PCA shape extraction methods, a M-E-L identification algorithm is proposed for identifying secondary lining rebars in highway tunnel construction stages. The algorithm achieves 100% extraction of the first-layer rebars, allowing for the three-dimensional visualization of the on-site rebar situation. Subsequently, through data processing, rebar dimensions and spacings can be obtained. For the second-layer rebars, 55% extraction is achieved, providing information on the rebar skeleton and partial rebar details at the construction site. These extracted data can be further processed to verify compliance with construction requirements.

This paper introduces a laser point cloud method for double-layer rebar identification in tunnels. Current methods rely heavily on manual detection, lacking objectivity. Objective approaches for automatic rebar identification include image-based and LiDAR-based methods. Image-based methods are constrained by tunnel lighting conditions, while LiDAR focuses on straight rebar skeletons. Our research proposes a 3D point cloud recognition algorithm for tunnel lining rebar. This method can extract double-layer rebars and obtain construction rebar dimensions, enhancing management efficiency.

The host–guest molecules are often used in various fields and applications. This paper aims to discuss the role of host–guest complexes in the textile industry, focusing on calixarenes as a potential adsorbent for hazardous dyes. The paper begins with an introduction to nanotechnology and its many uses, including textiles.

The risks associated with the utilisation of dyes and its adverse effects on the environment are then also highlighted. This paper also discusses the structure and characteristics of calixarenes and their potential use as an adsorbent to extract toxic metals from aqueous solutions. The paper also explains the molecular structure of calixarenes, especially the ability of its upper and lower rims, which can be altered to yield derivatives with various selectivities for diverse guest ions and small molecules. In addition, the application of various host–guest molecules in the textiles industry to extract dyes also had been discussed.

In conclusion, the paper highlights the essential in establishing a systematic review on the significance of selective adsorbents, such as calixarenes, to isolate particular targets from diverse matrices in the textile industry.

Only discussing several applications for several host–guest molecules.

The paper concisely describes various host–guest molecule applications in the textile industry, with each molecule being elaborated upon in detail.

The purpose of this study is to examine the impact of cross-ownership on corporate digital innovation and their specific mechanisms. Cross-ownership, who hold equity in two or more companies simultaneously, have two different types of governance effects in the capital market: governance synergistic effects and competitive collusion effects.

This paper uses a panel model, selecting A-share company data from 2011 to 2021 in China. In total, 23,853 valid data were obtained, which came from the CSMAR database and Wind database. For some missing data, they were manually supplemented by consulting the company's annual report and Sina Finance. Data processing was conducted using EXCEL and Stata16.0 software.

The results show that cross-ownership promote corporate digital innovation by leveraging governance synergies. Further grouping tests show that the synergistic effects of cross-ownership are significant in non-state-owned, high-tech, weakly competitive and higher analyst attention enterprises. Mechanism testing shows that cross-ownership can empower corporate digital innovation in three ways: reducing information asymmetry, alleviating financing constraints and improving corporate governance.

The conclusion of this paper provides new empirical evidence for a comprehensive understanding of the role of cross-ownership in corporate development, enriches the economic consequences research of chain institutional investors in China and broadens the research perspective of corporate digital innovation. It also provides important references for the digital transformation of enterprises and the healthy development of the capital market.

Online reviews derived from peer communications have been increasingly viewed as an important approach for consumers to gather pre-purchase information. This study aims to examine factors affecting online reviews adoption in social network communities and then indicates the underlying mechanism of this process based on an extended information adoption model (IAM).

Using the data collected from 242 users of a social network community via an online survey, the proposed model is empirically assessed by partial least squares-based structural equation model (PLS-SEM).

The results show that both perceived diagnosticity and perceived serendipity are drivers of online reviews adoption in social network communities. Meanwhile, community identification is not only an antecedent of diagnosticity and serendipity perceived by community members, but also motivates source credibility which, in turn, positively influences argument quality. Finally, the importance of argument quality and source credibility in reviews adoption process is also presented.

This study extends the IAM and enriches the literature regarding online reviews adoption. It deepens the understanding of serendipitous experiences and community identification in social networking context by addressing their important roles in the authors' extended IAM.

Platform owners need to encourage yet control complementors in ways that generate benefits. Retaining too much control can restrict innovation and knowledge flows; giving up too much control can lead to poor quality and platform instability. Studies provide mixed findings that make it difficult to draw generalizable conclusions. We aim to provide a more accurate understanding of the link between platform control and platform benefits.

We conducted a meta-analysis of empirical research in this area.

Access-based control positively influences realization benefits, but it does not appear to affect creation benefits. Authority-based control does not appear to affect creation or realization benefits. Control is positively linked to benefits on transaction platforms but not on innovation platforms. Platform control is positively related to platform benefits in studies that use objective measures and in studies that measure control from the complementor’s perspective. However, the relationship between control and benefits is uncertain in studies that use perceptual measures and in studies that measure control from the owner’s perspective.

Tighter restrictions on who can join the platform can lead to greater use of platform innovations. Platform control is also an effective driver of benefits on transaction platforms. Researchers should carefully think through the manner in which they measure platform control and platform benefits. Our study is limited by a small sample size, four moderators and a set of empirical-only studies.

Our findings can guide future research and help practitioners better understand when platform control is related to platform benefits.