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This paper aims to conduct a systematic literature review of Socially Conscious Investment (SCI) articles published in premier journals. Its objective is to shed light on the publication trend, leading authors, journals, countries and themes in contemporary SCI research. The article also provides a conceptual model of SCI to enhance understanding of the knowledge structure and the future research direction.

A systematic review followed the PRISMA guidelines and encompasses 264 full-text articles indexed in A* and A category journals listed in ABDC is reviewed. The literature synthesis adopts the theories, contexts, characteristics and methodology (TCCM) framework.

The article has identified the research trends related to author impact, journal impact, article impact and the outcomes derived from the TCCM framework. Additionally, it highlights three key themes: Performance of SCI, Behavioural issues and SCI development literature.

The insight on various aspects of SCI was explored for a comprehensive understanding. The authors also developed a conceptual model for socially conscious investment.

The purpose of this paper is to actively calibrate power density to match the application requirements with as small an actuator as possible. So, this paper introduces shape memory alloy to design variable stiffness elements. Meanwhile, the purpose of this paper is also to solve the problem of not being able to install sensors on shape memory alloy due to volume limitations.

This paper introduces the design, modeling and control process for a variable stiffness passive ankle exoskeleton, adjusting joint stiffness using shape memory alloy (SMA). This innovative exoskeleton aids the human ankle by adapting the precompression of elastic components by SMA, thereby adjusting the ankle exoskeleton’s integral stiffness. At the same time, this paper constructs a mathematical model of SMA to achieve a dynamic stiffness adjustment function.

Using SMA as the driving force for stiffness modification in passive exoskeletons introduces several distinct advantages, inclusive of high energy density, programmability, rapid response time and simplified structural design. In the course of experimental validation, this ankle exoskeleton, endowed with variable stiffness, proficiently executed actions like squatting and walking and it can effectively increase the joint stiffness by 0.2 Nm/Deg.

The contribution of this paper is to introduce SMA to adjust the stiffness to actively calibrate power density to match the application requirements. At the same time, this paper constructs a mathematical model of SMA to achieve a dynamic stiffness adjustment function.

This study aims to explore the COVID-19 impact on the sustainability of gharimin (genuine debtors) in Islamic financial institutions (IFI) in Malaysia. The analysis was further conducted to expand the interpretation of gharimin in zakat institutions (ZI) to use the role of zakat distribution during the post-pandemic period due to income shock and long-term unemployment.

This study adopted a qualitative research approach with grounded theory analysis to integrate theoretical insights into the interpretation of gharimin and current practices from the perspectives of ZI and IFI. An in-depth interview with 18 informants was conducted, and data were collected from senior management positions in the zakat distribution department, academicians who are experts in the area of zakat, and heads of Shariah departments in IFI.

Expanding the interpretation of gharimin could help ZI and IFI recover the sustainability of gharimin for preparedness during post-pandemic and any emergency crisis in the future.

This study implies the potential role of ZI in combating the risk of defaulting debtors in IFI to prepare for pandemic recovery in the future.

The new interpretation assists gharimin in reducing the burden debt using the zakat fund and protects genuine debtors by preventing IFI from declaring default or bankruptcy.

This study narrows the literature gaps about gharimin in IFI in the context of the pandemic. To the best of the authors’ knowledge, this is, perhaps, the first paper to present the expansion of interpretation for gharimin into mu’sir in IFI in Malaysia.

The purpose of this study is to investigate whether negative reports by state-controlled media affect firms’ CSR performance. Negative reports by state-controlled media indicate the signals of deteriorating relationships between firms and the government and then generate greater political pressure on firms, which may force firms to engage in more CSR activities. This study first examines the influence of negative reports by state-controlled media on CSR performance. Then, we further figure out whether the degree of dependence on the government exhibits an impact on the relationship between negative reports by state-controlled media and firms’ CSR performance.

The sample for this study is based on all Chinese A-listed firms from 2010 to 2020. The study employs CSR scores data released by HEXUN to measure firms’ CSR performance. HEXUN is one of the most professional institutions that sell CSR-related products. Following You et al. (2018) and An et al. (2022), the authors identify the nine most popular media consisting of state-controlled media. The ordinary least squares (OLS) method is adopted for regression, and various robustness tests are conducted including using alternative measures, expanding the regression model and instrumental variable method.

The empirical results show a significant positive relationship between negative reports by state-controlled media and firms’ CSR performance. The cross-sectional analyses indicate that the effect of negative reports by state-controlled media on firms’ CSR performance is stronger for firms with mandatory CSR disclosure requirements, firms with political connections and firms with more severe financial constraints. Furthermore, improved CSR performance resulting from negative reports by state-controlled media indeed helps repair firms’ relationship with the government and thus leads them to attain government benefits, such as more government subsidies and lower tax rates.

This study finds that media reports issued by state-controlled media can be treated as signals of the relationships between firms and the government, which generate political pressure to push firms to take CSR as a strategic management tool to repair their relationships with the government. It helps policymakers and investors more comprehensively understand firms’ incentives behind their improved CSR performance and develop more effective policies. This study focuses on firms’ overall CSR performance. We anticipate that future research can extend the analysis of the impact of negative reports by state-controlled media on specific aspects of CSR investment.

This study illustrates the significantly positive effect of negative reports by state-controlled media in promoting CSR performance. It fills the research gap in studying the role of state-controlled media in CSR, especially for emerging markets. Moreover, the study also contributes to the strand of literature on strategic CSR management.

Fine-tuning pre-trained language models (PLMs), e.g. SciBERT, generally require large numbers of annotated data to achieve state-of-the-art performance on a range of NLP tasks in the scientific domain. However, obtaining fine-tuning data for scientific NLP tasks is still challenging and expensive. In this paper, the authors propose the mix prompt tuning (MPT), which is a semi-supervised method aiming to alleviate the dependence on annotated data and improve the performance of multi-granularity academic function recognition tasks.

Specifically, the proposed method provides multi-perspective representations by combining manually designed prompt templates with automatically learned continuous prompt templates to help the given academic function recognition task take full advantage of knowledge in PLMs. Based on these prompt templates and the fine-tuned PLM, a large number of pseudo labels are assigned to the unlabelled examples. Finally, the authors further fine-tune the PLM using the pseudo training set. The authors evaluate the method on three academic function recognition tasks of different granularity including the citation function, the abstract sentence function and the keyword function, with data sets from the computer science domain and the biomedical domain.

Extensive experiments demonstrate the effectiveness of the method and statistically significant improvements against strong baselines. In particular, it achieves an average increase of 5% in Macro-F1 score compared with fine-tuning, and 6% in Macro-F1 score compared with other semi-supervised methods under low-resource settings.

In addition, MPT is a general method that can be easily applied to other low-resource scientific classification tasks.

We use the extended finite element method (XFEM) to model the whole process of initiation and propagation of cracks in the inner dense pyrolytic carbon (IPyC) layer of tri-structural isotropic (TRISO) particle induced by the microdefect in an irradiation-induced thermomechanical coupling environment and study the effect of microdefect sizes on the propagation path.

The irradiation-induced thermal–mechanical coupling analysis is first conducted for the representative volume element (RVE) of the TRISO particle by using the conventional finite element method (CFEM) so that the stress distribution is obtained. The stress results are then restored for the enriched elements, and the simulation of crack initiation and propagation is eventually carried out by using the XFEM.

1. As a crack initiates in the IPyC layer, it will terminate at the free edge of the RVE TRISO particle in the end. 2. The size of the microdefect has a significant impact on the propagation path.

The ceramic dispersion microencapsulated (CDM) fuel is a good accident-resistant fuel whose safe operation is crucial to the safety and reliability of the whole nuclear reactor. It is of great scientific significance and practical value to study the irradiation-induced thermomechanical coupling stress distribution and cracking behavior in the IPyC layer of TRISO particles for the CDM fuel. Crack initiation and propagation analysis is challengeable for this complex multi-layer structure. This can help understand the failure mechanism of TRISO particles and evaluate the operation safety of the reactor.

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.

Empirical examinations of initial public offering (IPO) initial returns often rely heavily on linear regression models. However, these models can prove inefficient owing to their susceptibility to outliers, a common occurrence in IPO data. This study introduces a machine learning method, known as random forest, to address issues that linear regression may struggle to resolve.

The study’s sample comprises 352 fixed-priced IPOs from the year 2004 until 2021. A unique aspect of this research is its application of the random forest method. The accuracy of random forest in comparison to other methods is evaluated. The findings indicate that the random forest model significantly outperforms other methods in all of the evaluated aspects.

The variable importance measure indicates that investors’ demand, divergence of opinion among investors and offer price are the most crucial predictors of IPO initial returns. These determinants hold particular significance due to the widespread use of the fixed-price method in Malaysia, as this method amplifies the information asymmetry in the IPO market.

To the best of the authors’ knowledge, this study is among the pioneering works in Malaysian literature to apply the random forest method to address the constraints of conventional linear regression models. This is achieved by considering a more extensive array of factors and acknowledging the influence of outliers. Additionally, this study adds value to Malaysian literature by ranking and identifying the ex-ante information that best signals the issuing firm’s quality. This contribution facilitates prospective investors’ decision-making processes and provides issuing firms with effective means to communicate their value and quality to the IPO market.

This study is among the first to integrate the technology acceptance model (TAM) and value-based adoption model (VAM) in the context of augmented reality (AR) shopping. It assesses how consumers' rational (TAM) and emotional (VAM) factors influence their intention to use AR in online shopping via perceived value and consumer engagement.

This study uses a quantitative research approach and employs a standardized survey questionnaire distributed on social media platforms to recruit Gen Z members who are potential buyers or users of AR technology. SmartPLS 4.0 was used to test the responses of 204 respondents.

The results indicate that consumers who perceive a higher value of AR in shopping are inclined to use AR in their future shopping when AR shopping is easy to use, useful, personalized, innovative and provides a highly engaging experience. Interestingly, perceived sacrifice did not influence perceived value. This study confirms that integrating TAM and VAM is instrumental in capturing value, which in turn influences engagement and the intention to use AR in online shopping.

This study further extends the conceptualization of AR perceived value by combining rational components derived from TAM and VAM, thus leading to a sturdy and theoretically grounded framework. In addition, this study contributes to the literature on extended reality, namely AR shopping, and helps brand managers manage highly evolving AR experience for Gen Z.

This study examines two distinct bearing stiffness calculation methods, both of which are based on the displacement-load function. Previous research typically incorporated one type of bearing stiffness into their system mechanics or vibration analysis. However, these two methods of calculating stiffness lead to different vibration models. This implies that the choice for vibration investigation is not merely about selecting one of the two types of stiffness, but also about how to appropriately implement that chosen stiffness within a model. The primary objective of this work is to compare these two methods of bearing calculation and to discuss the suitable applications of each method in both static and dynamic analyses.

This study compares two distinct methods for calculating bearing stiffness. It explores the relationships between varying bearing stiffnesses, their internal structures, and contact features. Furthermore, it examines the impact of external loads on the static properties and dynamic characteristics of different bearing stiffnesses. Finally, based on the outcomes observed under various operating conditions, the study discusses the suitability of each method for static and dynamic analysis.

Mean stiffness is more suitable for calculating load transmissibility in a static state or capturing the delivery performance at instantaneous equilibrium positions in a dynamic state. Since the variation of the equilibrium positions is ignored, the alternating stiffness model is better suited for capturing the fluctuating properties of the vibration behaviors, especially under variable external load conditions.

We compare the two bearing calculation methods and discuss the appropriate applications of each method for static and dynamic analysis.