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This study aims to improve detection efficiency of fluorescence biosensor or a graphene field-effect transistor biosensor. Graphene field-effect transistor biosensing and fluorescent biosensing were integrated and combined with magnetic nanoparticles to construct a multi-sensor integrated microfluidic biochip for detecting single-stranded DNA. Multi-sensor integrated biochip demonstrated higher detection reliability for a single target and could simultaneously detect different targets.

In this study, the authors integrated graphene field-effect transistor biosensing and fluorescent biosensing, combined with magnetic nanoparticles, to fabricate a multi-sensor integrated microfluidic biochip for the detection of single-stranded deoxyribonucleic acid (DNA). Graphene films synthesized through chemical vapor deposition were transferred onto a glass substrate featuring two indium tin oxide electrodes, thus establishing conductive channels for the graphene field-effect transistor. Using π-π stacking, 1-pyrenebutanoic acid succinimidyl ester was immobilized onto the graphene film to serve as a medium for anchoring the probe aptamer. The fluorophore-labeled target DNA subsequently underwent hybridization with the probe aptamer, thereby forming a fluorescence detection channel.

This paper presents a novel approach using three channels of light, electricity and magnetism for the detection of single-stranded DNA, accompanied by the design of a microfluidic detection platform integrating biosensor chips. Remarkably, the detection limit achieved is 10 pm, with an impressively low relative standard deviation of 1.007%.

By detecting target DNA, the photo-electro-magnetic multi-sensor graphene field-effect transistor biosensor not only enhances the reliability and efficiency of detection but also exhibits additional advantages such as compact size, affordability, portability and straightforward automation. Real-time display of detection outcomes on the host facilitates a deeper comprehension of biochemical reaction dynamics. Moreover, besides detecting the same target, the sensor can also identify diverse targets, primarily leveraging the penetrative and noninvasive nature of light.

We examine how superstition shapes corporate tax avoidance and do so by taking a risk perspective and focusing on the zodiac-year belief prevalent in China.

We adopt a difference-in-differences research design to compare the degree of corporate tax avoidance in the CEOs’ zodiac year with that in the adjacent years. We do propensity-score matching to form a sample of Chinese listed firms for the regression analysis.

We find causal evidence that firms exhibit a greater magnitude of tax avoidance in the CEOs’ zodiac years, a result attributable to relatively weak tax enforcement in the Chinese context. We also find that the zodiac-year effect on corporate tax avoidance is more pronounced for firms with tight financial constraints, firms with high business risk, firms headquartered in regions with a high degree of superstition and non-state-owned firms.

This study is the first to show that superstition is a determinant factor of tax avoidance and contributes to the tax literature by shedding light on the behavioral risk factors that shape corporate tax avoidance. We take the perspective of CEOs’ risk appetite to analyze how tax avoidance is influenced by the CEOs’ trade-off between the costs and benefits of avoiding taxes. Our results suggest that, when CEOs are more risk-averse, they attach more importance to financial risk than the risk of reputational losses and litigation associated with corporate tax avoidance. The findings imply that tax avoidance can be curbed by increasing (or decreasing) the tax (financial) risk confronting the CEOs.

This study aims to reveal the triggering mechanism and boundary conditions of tourists’ cross-border travel anxiety (CBTA) from different crisis information sources.

Drawing on the heuristic-systematic model (HSM), this study constructs a theoretical formation path of tourists’ CBTA. Based on competence-based and moral-based crises, hypotheses were examined through three situational experiments, targeting Chinese and Malaysian potential tourists.

Organization-released crisis information triggers higher tourists’ CBTA than government ones, with perceived uncertainty mediating it. Crisis communication message appeals (CCMAs) (rational vs emotional) negatively moderate the above relationships. Rational CCMAs work for governmental crisis communication, while emotional CCMAs work for organizational ones.

This study proposes a heuristic cross-border tourism crisis information dissemination strategy for destination management organizations and highlights the advantages of CCMAs in preventing secondary crises.

This study reexamines the cause-and-effect and the intervention mechanisms of tourists’ reactions to crisis information, which expands the cross-border tourism crisis management research and the application of the HSM in such a context.

本研究旨在从不同的危机信息源中揭示游客跨境旅行焦虑的触发机制和边界条件。

本研究借鉴启发式-系统式模型（HSM）, 构建了游客跨境旅游焦虑的理论形成路径。基于能力型和道德型目的地危机事件, 以中国及马来西亚潜在游客为例, 通过三组情境实验验证所提出的假设。

与政府发布的危机信息相比, 组织发布的危机信息会引发更高的游客跨境旅游焦虑, 而感知不确定性会对该路径起到中介作用。危机沟通信息诉求（理性vs.感性）对上述关系起负向调节作用。理性的信息诉求适用于政府危机沟通, 而感性的信息诉求适用于组织危机沟通。

本研究为目的地管理组织提出了启发式跨境旅游危机信息传播策略, 并强调了危机沟通信息诉求在预防二次危机方面的优势。

本研究重新审视了游客对危机信息反应的因果关系和干预机制, 拓展了跨境旅游危机管理研究和HSM在此背景下的应用。

Este estudio pretende revelar el mecanismo desencadenante y las condiciones límite de la ansiedad de los turistas ante los viajes transfronterizos (CBTA) a partir de diferentes fuentes de información sobre crisis (CIS).

Basándose en el modelo heurístico-sistemático (HSM), este estudio construye una vía teórica de formación de la CBTA de los turistas. A partir de las crisis basadas en la competencia y en la moral, se examinaron las hipótesis mediante tres experimentos situacionales, dirigidos a turistas potenciales chinos y malayos.

La información sobre crisis difundida por organizaciones desencadena una mayor CBTA de los turistas que la gubernamental, con la incertidumbre percibida como mediadora. Los recursos de los mensajes de comunicación de crisis (CCMA) (racionales frente a emocionales) moderan negativamente las relaciones anteriores. Los CCMA racionales funcionan para la comunicación de crisis gubernamental, mientras que los CCMA emocionales para las organizativas.

Los resultados proponen que las organizaciones de gestión de destinos (OGD) deberían considerar estrategias heurísticas a la hora de difundir información sobre crisis turísticas transfronterizas. Prestar atención al efecto diferencial de las CCMA ayuda a prevenir crisis secundarias.

Este estudio reexamina la causa-efecto y los mecanismos de intervención de las reacciones de los turistas a la información sobre crisis, lo que amplía la investigación sobre la gestión de crisis turísticas transfronterizas y la aplicación de la HSM en dicho contexto.

This study aims to examine the impact of board characteristics on firm performance while also exploring the influential mechanisms that help Chinese listed companies establish effective boards of directors and strengthen their corporate governance mechanisms.

This paper uses machine learning methods to investigate the predictive ability of the board of directors' characteristics on firm performance based on the data from Chinese A-share listed companies on the Shanghai and Shenzhen stock exchanges in China during 2008–2021. This study further analyzes board characteristics with relatively strong predictive ability and their predictive models on firm performance.

The results show that nonlinear machine learning methods are more effective than traditional linear models in analyzing the impact of board characteristics on Chinese firm performance. Among the series characteristics of the board of directors, the contribution ratio in prediction from directors compensation, director shareholding ratio, the average age of directors and directors' educational level are significant, and these characteristics have a roughly nonlinear correlation to the prediction of firm performance; the improvement of the predictive ability of board characteristics on firm performance in state-owned enterprises in China performs better than that in private enterprises.

The findings of this study provide valuable suggestions for enriching the theory of board governance, strengthening board construction and optimizing the effectiveness of board governance. Furthermore, these impacts can serve as a valuable reference for board construction and selection, aiding in the rational selection of boards to establish an efficient and high-performing board of directors.

The study findings unequivocally demonstrate the superiority of nonlinear machine learning approaches over traditional linear models in examining the relationship between board characteristics and firm performance in China. Within the suite of board characteristics, director compensation, shareholding ratio, average age and educational level are particularly noteworthy, consistently demonstrating strong, nonlinear associations with firm performance. Within the suite of board characteristics, director compensation, shareholding ratio, average age and educational level are particularly noteworthy, consistently demonstrating strong, nonlinear associations with firm performance. The study reveals that the predictive performance of board attributes is generally more robust for state-owned enterprises in China in comparison to their counterparts in the private sector.

Managing knowledge is relevant for the innovativeness of an organization. The innovation of the organization currently aligns with the environment and applies green innovation concepts. Knowledge management (KM) is a key to fostering green innovation and to saving the environment from unnecessary pollution. In line with this, this study aims to evaluate the relationship between KM and green innovation in the literature from 2000 to 2023 synthesize and suggest future directions.

This study used the preferred reporting items for systematic review and meta-analysis technique to identify eligible articles. The papers were identified from the Web of Science core collection and ScienceDirect databases. The results were presented using tables, graphs and the co-occurrence of citations was analyzed using VOSviewer software.

From the review, the authors were assured that there is a strong relationship between KM practices and green innovation in different organizations. Some papers were supported by different theories. From the total of 48 papers, 16 have not mentioned the theories applied in their studies. The geographical distribution of the papers is asymmetrical. Asian and European scholars published more papers. The papers distribution across publishers also varies. For instance, Elsevier and Emerald Group Publishing Ltd. published 29 papers and the remaining papers were published in BMC, Springer, Frontiers Media Sa, IEEE-Inst Electrical Electronics Engineers Inc., MDPI, Routledge Journals and Taylor & Francis Ltd. Major themes were identified and future research directions were forwarded.

The limitation of this review is the authors generated the papers from two databases (WoS and ScienceDirect). This paper does not consider other databases (Scopus, dimensions, etc.) papers. This can be considered as a limitation of this review.

The review is original by integrating PARISMA and bibliometric analysis method (VOS Viewer). The paper tried to explore the role of KM on green innovation.

The purpose of this study is to provide evidence that government financing behavior has an impact on the outward foreign direct investment (OFDI) of enterprises.

This paper uses debt data from local government financing vehicles to measure the local government debt in China. Based on the data of listed manufacturing firms in China from 2010 to 2018, this paper uses the Tobit model to verify the impact of local government debt and firms' OFDI.

The results indicate that local government debt impedes firms' OFDI, with a more pronounced impact on state-owned enterprises (SOEs) and those with higher political connections. Furthermore, our study suggests that the dampening effect of local governments on firms' OFDI is mitigated in regions following the implementation of the Local Government Debt Management Act.

This study verifies the negative impact of local government debt activity on firms' overseas investments. This is not due to debt crowding out, but rather to the fact that local governments prefer to keep resources locally to stimulate the economy. This paper offers novel insights into the theoretical mechanisms by which local government behavior influences firms' investment activities in emerging markets.

Performance optimization algorithms based on node attributes are of great importance for sharding blockchain systems. Currently, existing studies on blockchain sharding algorithms consider only random selection sharding strategies. However, the random selection strategy does not perfectly utilize the performance of a node to break the bottleneck of blockchain performance.

This paper proposes a blockchain sharding algorithm called TOPSIS Optimization Sharding System (TOSS), which is based on entropy weight method, relative Euclidean distance and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). It defines a multi-attribute matrix to assess node performance and applies TOPSIS for scoring nodes. Then, an algorithm based on the TOPSIS method is proposed to calculate the performance score of each data node. In addition, an entropy weighting method is introduced to obtain the weights of each attribute to balance the impact of dimensional differences of attributes on the attribute weights. Nodes are ranked by composite scores to guide partitioning.

The effectiveness of the proposed algorithm in this paper is verified by comparing it with various comparative algorithms. The experimental results show that the TOSS algorithm outperforms the comparison algorithms in terms of performance improvement for the blockchain system, and the throughput metrics are improved by about 20% in comparison.

This study introduces a novel approach to blockchain sharding by incorporating the entropy weight method and relative Euclidean distance TOPSIS into the sharding process. This approach allows for a more effective utilization of node performance attributes, leading to significant improvements in system throughput and overall performance, addressing the limitations of the random selection strategy commonly used in existing algorithms.

By using Technology Acceptance Model, the purpose of this study is to investigate how the perceived usefulness and ease-of-use of shopping mobile apps affects consumer’s flow experience, attitude, impulsive buying tendency (IBT) and urge to impulsive buying on halal fashion products.

A quantitative study was done on 357 Indonesian online shoppers to find out how perceived usefulness and ease of use of mobile shopping apps affect impulsive buying tendencies and urges on halal fashion products. Flow experience and attitude were used as mediating variables, and the research hypotheses were tested using Partial Least Square Structural Equation Modeling (PLS-SEM).

This study confirmed significant positive relationships between perceived usefulness and ease of use of mobile apps, flow experience, attitude, IBT and urge to impulsive buying. The results of this study show that perceived usefulness and ease of use influence flow experience. Ease of use also influences attitude, but perceived usefulness did not impact attitude. In addition, flow experience did not impact attitude. However, both flow experience and attitude influence IBT. Furthermore, IBT significantly mediated flow experience and attitude into urge to impulsive buying.

This study only captured consumers in one country, so its results cannot be generalized to other nations. Random sampling may limit result generalization. In this study, three mobile shopping applications were investigated and the results would have been different if more mobile shopping applications were investigated.

The study gives a better understanding of how the perceived usefulness and ease of use of mobile shopping apps affect a consumer's tendency and urge to impulsive buying on halal fashion products by using flow experience as mediating variable.

This literature review aims to portray the thematic landscape of the Pacific Accounting Review (PAR) from 2013 to 2023. This paper also synthesises the special issues in PAR and identifies the main research streams that facilitate contemplating the dialogic interactions between PAR and real-world challenges. Furthermore, this paper aligns these streams with the emerging concerns in Sustainable Development Goals (SDGs) and technological disruptions to propose impactful future directions for publications in PAR.

This review adopts bibliometric analysis to establish the main research streams and objective measures for directing future publications. This paper acquires the data of 310 PAR articles from the Web of Science and ensure the data integrity before the analysis. Based on this technique, this paper also analyses PAR’s productivity, authorship and local and global impacts.

Our bibliometric analysis reveals three key research streams: (1) ESG practices and disclosures, (2) informal institutions in accounting and (3) accounting in transition. This finding affirms PAR’s relevance to real-world accounting challenges. Using a thematic map, this paper portrays the current state of PAR’s topics to identify potential directions for future publications. Further, this paper proposes three future paths for PAR: (1) the research agenda for non-financial reporting, (2) research relating to and from diverse countries considering both formal and informal contemporary contextual factors and (3) the future of the evolving accounting profession.

This study adds value to the existing PAR reviews by extending our knowledge with the latest publications, demonstrating an objective and replicable approach, and offering future directions for PAR publications.

Green technology innovation is the organic combination of green development and innovation driven. It is also a powerful guarantee for shaping sustainable competitive advantages of manufacturing enterprises. To explore what kind of executive incentive contracts can truly stimulate green technology innovation, this study aims to distinguish the equity incentive and reputation incentive, upon their contractual elements characteristics and green governance effects, and then put forward suggestions for green technology innovation accordingly.

This study establishes an evaluation model and uses empirical methods to test. Concretely, using data from A-share listed manufacturing companies for the period from 2007 to 2020, this study compares and analyzes the impact of equity and reputation incentive on green technology innovation and explores the relationship between internal green business behavior and external green in depth.

This study finds that reputation incentives focus on long-term and non-utilitarian orientation, which can promote green technology innovation in enterprises. While equity incentives, linked to performance indicators, have a inhibitory effect on green technology innovation. Internal and external institutional factors such as energy conservation measures, the “three wastes” management system, and environmental recognition play the regulatory role in the relationship between incentive contracts and green technology innovation.

Those findings validate and expand the efficient contracting hypothesis and the rent extraction hypothesis from the perspective of green technology innovation and provide useful implications for the design of green governance systems in manufacturing enterprises.