The stock market is an indicator of investor sentiment when it comes to new information or innovative firm-level products. Green bonds are both innovative and unique in terms of their higher information disclosures and understanding the impact of sustainable finance on investor outlook for a company’s stock. Using the comparative case of Mainland China and Hong Kong’s stock market, we examine whether green bond announcements from 2016 to 2019 can create significant investor reactions. By employing the event study methodology, we (...) confirm that both markets react in a positive way toward green bond announcements. This reinforces the reputational and financial benefits of green bonds. We find that issuers that are non-banks, environmentally friendly firms as well as those issuing non-general bonds, create a more positive reaction, whereas ownership aspects do not matter as much for investors. However, even among those issuers listed in both markets, certain institutional dynamics like strategic framing and source credibility tend to reinforce a firm’s institutional legitimacy and are seen as being more prominent for investor reaction. The policy implications of our study show that the stock market reaction among two connected economies, where previously varying institutional contexts have resulted in regional differences, are now equally supportive of sustainable financial markets like the green bond. As seen with the positive stock market sentiment, governments and listed issuers can now better align their policies and internal strategies, allowing the low-carbon transition to be a financially attractive opportunity for all investors. (shrink)

Automated reasoning issues are addressed for a finite lattice-valued propositional logic LnP(X) with truth-values in a finite lattice-valued logical algebraic structure—lattice implication algebra. We investigate extended strategies and rules from classical logic to LnP(X) to simplify the procedure in the semantic level for testing the satisfiability of formulas in LnP(X) at a certain truth-value level α (α-satisfiability) while keeping the role of truth constant formula played in LnP(X). We propose a lock resolution method at a certain truth-value level α (α-lock (...) resolution) in LnP(X) and have proved its theorems of soundness and weak completeness, respectively. We provide more efficient resolution based automated reasoning in LnP(X) and key supports for α-resolution-based automated reasoning approaches and algorithms in lattice based linguistic truth-valued logic. (shrink)

Engineering programs in the United States have been experimenting with diverse pedagogical approaches to educate future professional engineers. However, a crucial dimension of ethics education that focuses on the values, personal commitments, and meaning of engineers has been missing in many of these pedagogical approaches. We argue that a value-based approach to professional ethics education is critically needed in engineering education, because such an approach is indispensable for cultivating self-reflective and socially engaged engineers. This paper starts by briefly comparing two (...) prevalent approaches to ethics education in science and engineering: professional and philosophical. While we acknowledge that both approaches help meet certain ethics education objectives, we also argue that neither of these is sufficient to personally engage students in authentic moral learning. We make the case that it is important to connect ethics education to the heart, which is extensively driven by values, and present a value-based approach to professional ethics education. We provide some classroom practices that cultivate a safe, diverse, and engaging learning environment. Finally, we discuss the implications of a value-based approach to professional ethics education for curriculum design and pedagogical practice, including opportunities and challenges for engineering faculty eager to incorporate value-based inquiry into their classrooms. (shrink)

Drawing on social exchange theory, we argue that family-supportive supervisor behavior (FSSB) inhibits employees’ unethical pro-family behavior (UPFB) via the mediation of felt obligation. We further propose that employees’ positive reciprocity beliefs strengthen the hypothesized relationships. Using a sample consisting of 345 full-time employees from an Internet service company located in China, we found that felt obligation partially mediated the negative relationship between FSSB and UPFB and that the FSSB-felt obligation relationship and the mediation relationship were stronger for employees with (...) higher positive reciprocity beliefs. Theoretical and practical implications, limitations, and future directions are discussed. (shrink)

Research investigating the intricacies of how self-regulated writing strategies are used in a finely focused area of the second language writing process is still lacking. This study takes a mixed-methods approach to explore Chinese English as a Foreign Language learners’ use of self-regulated writing strategies when revising based on automated, peer, and teacher feedback in an online EFL writing context. Thirty-six Chinese university learners filled in three questionnaires. In addition, four learners followed a think-aloud protocol while revising and responding to (...) a stimulated recall interview to provide further data. The results revealed that learners employed an array of self-regulated writing strategies to attain their feedback revision goals. Learners used more cognitive strategies when revising based on automated feedback compared with peer and teacher feedback and more motivational strategies when revising based on teacher feedback. The think-aloud data and stimulated recall interviews coincided with the quantitative findings. Textual analysis revealed that feedback type and quantity were associated with self-regulated writing strategy use. (shrink)

The study aims to help characterize the sort of structures about which people can acquire unconscious knowledge. It is already well established that people can implicitly learn n-grams and also repetition patterns. We explore the acquisition of unconscious structural knowledge of symmetry. Chinese Tang poetry uses a specific sort of mirror symmetry, an inversion rule with respect to the tones of characters in successive lines of verse. We show, using artificial poetry to control both n-gram structure and repetition patterns, that (...) people can implicitly learn to discriminate inversions from non-inversions, presenting a challenge to existing models of implicit learning. (shrink)

Along with urban development globally, the NIMBY crisis has been a complex social problem, which requires urgent remedial action. The inevitable management of Municipal Solid Waste has been one of the toughest risk management tasks in the worldwide modernization process. At present, certain fuzzy and unstructured results and methods have been formed for MSW-NIMBY crisis response, mainly focusing on the sociology and politics which scatter in complex and sensitive reports and news. Aiming at enhancing the effectiveness of data mining from (...) specific sparse text of MSW-NIMBY crisis, an improved knowledge extraction method is developed. Through rule-based text mining and complex network analysis, the Entity Relationship network of MSW-NIMBY crisis is reconstructed. Meanwhile, a novel transitivity for relationship between entities in semantic analysis is proposed to improve the feasibility and accuracy of information extraction. Characteristics and regularity of MSW-NIMBY crisis evolution and experience of crisis governance could be identified effectively. Results show that knowledge integration and ER transitivity can enhance knowledge recognition and major other factors, which could help formulate the governance strategies of NIMBY crisis from academic texts. (shrink)

Functional language has been used in many multinational corporations as a way to overcome the problems caused by the coexistence of multiple languages in the workplace. The existing literature has explored the importance, adoption, and effectiveness of functional language. Yet, how functional language shapes host country employees’ moral cognition and behavior is insufficiently researched. Guided by the Social Identity Theory, this manuscript shows that host country employees’ functional language proficiency enhances their unethical pro-organizational behavior through their linguistic group identification and (...) moral disengagement. We tested our predictions using the data collected from 309 full-time host country employees through an online survey, and the results generally supported our hypotheses. The findings make contributions to both international management and language literature and organizational moral behavior literature. (shrink)

Does a board with greater gender diversity make better investment decisions? Drawing on Austrian economic cycle theory and work groups theory, we argue that such board openness will help male board members to overcome gender biases, discrimination, and conflicts; integrate different perspectives under the economic cycle and crisis; and foster an environment in which better decisions are made. The results of an empirical study of 14,609 firm-quarter observations from 1,555 listed firms in China between 2007 and 2009 strongly support our (...) arguments. We find that a Chinese board is more likely to accept female directorship during an economic crisis than during an economic prosperity stage. Boards with greater gender diversity are more likely to make tough, counter-cyclical investments to improve firm performance during a crisis. Our study enriches the board decision-making literature by exploring the impacts of board gender diversity on firm performance within the context of an economic crisis. The results of our study also carry significant managerial implications for overcoming gender stereotypes, biases, and prejudices on a board. (shrink)

Human aesthetic practices show a sensitivity to the ways that the appearance of an artefact manifests skills and other qualities of the maker. We investigate a possible origin for this kind of sensibility, locating it in the need for co-ordination of skill-transmission in the Acheulean stone tool culture. We argue that our narrative supports the idea that Acheulian agents were aesthetic agents. In line with this we offer what may seem an absurd comparison: between the Acheulian and the Quattrocento. In (...) making it we display some hidden richness in what counts as an aesthetic response to an artefact. We conclude with a brief review of rival explanations—biological and/or cultural—of how this skills-based sensibility became a regular feature of human aesthetic practices. (shrink)

Live streaming shopping, the streaming of real-time videos promoting products that consumers can purchase online, has recently been a booming area of e-commerce, especially during the COVID-19 pandemic. The success of live streaming e-commerce largely relies on the extent to which the broadcaster can get consumers engaged by the live stream. Thus, it is important to discover the antecedents of consumer engagement in such a context. Drawing on consumer engagement and neuroscience literature, this study used electroencephalography inter-subject correlation to explore (...) how broadcasters' entrepreneurial passion during live streaming videos influenced consumers' neural engagement as they watched the live streaming videos. We used the framework of displayed passion and preparedness from the entrepreneurial passion literature to predict consumer engagement. We found significant ISC for strong displayed passion, while preparedness had partially significant effects on the first, second, and summed components of ISC. The interaction effects of these two factors on the first and summed components of ISC were partially significant. Strong displayed passion and preparedness activated the left and right prefrontal regions of the consumers' brains. These findings indicate that broadcasters' displayed passion and preparedness can influence consumer engagement in live streaming e-commerce settings. Our findings suggest that a scientific approach could be used to improve a broadcaster's performance by testing ISC during rehearsals before live streaming. (shrink)

Brand rumors can harm brands’ image and bring significant impacts on customers’ decision-making and sharing behavior. Finding practical strategies for preventing the spread of brand rumors continues to be a challenge. Building on the social contagion theory, the current research enriches the discussion on understanding why people spread rumors and how to deal with the spreading of rumors. Sharing brand rumors is motivated by a variety of complex psychological reasons, but prior research didn’t adequately analyze the problem from a complexity (...) perspective. Therefore, using a sample of 416 interviewers within eight types of brand rumors, this study employs fuzzy-set qualitative comparative analysis to investigate the combination of rumor psychological communication motivations in brand activities and solutions to prevent the spread of brand rumors. The current study discoveries three and two first-level configurational solutions, respectively, that can promote positive and negative rumor spreading. To summarize, emotional stimulation is a key component in the spread of rumors; altruism and relationship management motivation can coexist at times; and untrusted rumors are disseminated through other motivation factors. Solutions to prevent rumors from spreading are also provided. Furthermore, the findings help to understand the psychology of configurational motivation and how it can help brands reduce the spread of brand rumors. Finally, these discoveries’ theoretical contributions and practical implications are presented. (shrink)

Crowdsourcing platforms are powerful tools for academic researchers. Proponents claim that crowdsourcing helps researchers quickly and affordably recruit enough human subjects with diverse backgrounds to generate significant statistical power, while critics raise concerns about unreliable data quality, labor exploitation, and unequal power dynamics between researchers and workers. We examine these concerns along three dimensions: methods, fairness, and politics. We find that researchers offer vastly different compensation rates for crowdsourced tasks, and address potential concerns about data validity by using platform-specific tools (...) and user verification methods. Additionally, workers depend upon crowdsourcing platforms for a significant portion of their income, are motivated more by fear of losing access to work than by specific compensation rates, and are frustrated by a lack of transparency and occasional unfair treatment from job requesters. Finally, we discuss critical computing scholars’ proposals to address crowdsourcing’s problems, challenges with implementing these resolutions, and potential avenues for future research. (shrink)

We apply to the art of calligraphy some of the semiotic concepts developed by Nelson Goodman. While this framework cannot describe everything that is interesting and valuable about specific calligraphic traditions, we argue that it can nonetheless elegantly capture some distinctive features of calligraphy and of its position among other major art forms.

The proposed hesitant fuzzy linguistic set is a powerful tool for expressing fuzziness and uncertainty in multiattribute group decision-making. This paper aims to propose novel aggregation operators to fuse hesitant fuzzy linguistic information. First, we briefly recall the notion of HFLS and propose new operations for hesitant fuzzy linguistic elements. Second, considering the Muirhead mean is a useful aggregation technology that can consider the interrelationship among all aggregated arguments, we extend it to hesitant fuzzy linguistic environment and propose new hesitant (...) fuzzy linguistic aggregation operators, such as the hesitant fuzzy linguistic Muirhead mean operator, the hesitant fuzzy linguistic dual Muirhead mean operator, the hesitant fuzzy linguistic weighted Muirhead mean operator, and the hesitant fuzzy linguistic weighted dual Muirhead mean operator. These operators can reflect the correlations among all HFLEs. Several desirable properties and special cases of the proposed operators are also studied. Furthermore, we propose a novel approach to MAGDM in a hesitant fuzzy linguistic context based on the proposed operators. Finally, we conduct a numerical experiment to demonstrate the validity of our method. Additionally, we compare our method with others to illustrate its merits and superiorities. (shrink)

ABSTRACT In this paper we explore how a public national media outlet, the British BBC, represents an international legal case which has a highly political nature. The case is US versus Huawei/meng Wanzhou, which took place between 2018 and 2021. Accusations were that the Chinese technology company committed fraud, leading the global HSBC bank to breach US sanctions against Iran. The charges were made by the US using what is called an ‘extraterritorial law’, which, while rejected as law by governments (...) around the world, is policed by US economic powers and control over international finance. Using Critical Discourse Analysis we show that, while the BBC presents much detail of legal process, the actual nature of the law the US uses to bring criminal charges against international companies and banks, is neither considered nor questioned. Our interest is how such a law, which has a huge influence over global trade and politics, is presented to the public in this particular case. We contribute to the position that the nature of laws, how they are used and known, must always be understood within the prevailing discourses of the moment. (shrink)

Recent experimental evidence indicates that intuitions about inherence and system justification are distinct psychological processes, and that the inherence heuristic supplies important explanatory frameworks that are accepted or rejected based on their consistency with one's motivation to justify the system.

Whereas cognitive models of learning often assume direct experience with both the features of an event and with a true label or outcome, much of everyday learning arises from hearing the opinions of others, without direct access to either the experience or the ground-truth outcome. We consider how people can learn which opinions to trust in such scenarios by extending the hedge algorithm: a classic solution for learning from diverse information sources. We first introduce a semi-supervised variant we call the (...) delusional hedge capable of learning from both supervised and unsupervised experiences. In two experiments, we examine the alignment between human judgments and predictions from the standard hedge, the delusional hedge, and a heuristic baseline model. Results indicate that humans effectively incorporate both labeled and unlabeled information in a manner consistent with the delusional hedge algorithm—suggesting that human learners not only gauge the accuracy of information sources but also their consistency with other reliable sources. The findings advance our understanding of human learning from diverse opinions, with implications for the development of algorithms that better capture how people learn to weigh conflicting information sources. (shrink)

China has undergone a rapid process of modernization since 1949. The modernization process has accelerated with the development of the market economy and rural-to-urban migration after the 1980s. Nevertheless, Chinese regions still exhibit substantial differences in terms of individualist/collectivist cultural orientations. The rice theory and the climato-economic theory have attempted to explain this variation by analyzing provincial-level data. Based on a quantitative analysis of more granular, county-level variables spanning from the early 1990s until 2010, we offer an alternative account of (...) this cultural variety based on lineage development in different Chinese regions. Using the ArcGIS geographic information system, we first present the regional distribution of individualism/collectivism indicators at the county level through descriptive statistics and spatial analysis. We also run a regression model to analyze county-level data on individualism/collectivism that includes three periods. Our multi-level analysis shows that lineage development is a critical variable that explains more regional variation of culture in China when compared to other variables. While rice farming, the key variable of the rice theory, is a significant variable, its explanatory power is less than the lineage variable. Finally, our analysis shows that the climato-economic theory fails to explain the regional variation of culture. (shrink)

The microstructures of cryogenically ball-milled Cu were investigated by high-resolution electron microscopy. It was found that the grain-size reduction is a dislocation-controlled continuous process which consists of the formation of small-angle grain boundaries , a gradual increase in misorientations as a result of accumulation of more dislocations and, finally, the formation of large-angle GBs. The GBs were generally curved, wavy or faceted, and heavily strained, which are typical characteristics of nanostructured materials. In addition, extrinsic dislocations were found in many GBs, (...) indicating that most are in a high-energy non-equilibrium configuration, which is consistent with observations in equal-channel angular pressing processed Cu, Ni, and Al-Mg, repetitive corrugation and straightening processed Cu and room-temperature ball-milled Cu. These results support a still-disputed concept that GBs in nanostructured metals processed by severe plastic deformation are mostly in non-equilibrium states. (shrink)

Short circuit is a key factor which drastically affects the efficiency of metal electrorefining. Infrared image of the intercell busbar region is used to perform short circuit detection. To cope with the high thermal background, a two-level short circuit detection method is designed. Firstly, with background subtraction, high intensity short circuit electrodes, as well as the background, are removed, and normal working electrodes are preserved. In the second stage, suspicious short circuit areas are sifted out by normal electrode detecting and (...) texture period estimation. Gaussian difference filter which is based on the human visual system is improved to match the target gray distribution. A comparative experiment indicates that the proposed orthogonal DoG outperforms the original DoG and top-hat in the accuracy of normal electrode detection. The two-level detection method in this paper is applied in a copper electrolysis plant and exhibits superiority in locating short circuits and avoiding miss detection. (shrink)

The COVID-19 pandemic has caused a dramatic reshaping of passenger risk perception for airline industry. The sharp increase in risk aversion by air passenger has caused a disastrous impact on the tourism service industry, particularly airline industry. Although the existing literature has provided a lot of studies on the impact of the pandemic on travel industry, there are very few studies discussing the impact of change in passenger risk perception on the stock market performance of airline industry. This study considers (...) two types of airline companies, full-service and low-cost. In order to overcome the traditional problem of the Chow test, Quandt–Andrews test is used to identify structural change points during the pandemic in the stock prices of United States airline companies. The result shows that an industry-wide structural change in the stock market performance indeed is found to take place during the pandemic for United States airline companies. Meanwhile, no significant difference is found in the structural change date between the two types of airline companies. The selected airline companies are found to be clustered toward the end of 2020 in their structural change dates. Although the strike of the COVID-19 pandemic on airline industry has proven to be widespread and profound, our investigation implies that air passengers have gradually adapted to the new normal of travel activities at some level and partly rebuild their sense of safety under the strict epidemic-control measures. (shrink)

A novel data-driven model-free adaptive control approach is first proposed by combining the advantages of model-free adaptive control and data-driven optimal iterative learning control, and then its stability and convergence analysis is given to prove algorithm stability and asymptotical convergence of tracking error. Besides, the parameters of presented approach are adaptively adjusted with fuzzy logic to determine the occupied proportions of MFAC and DDOILC according to their different control performances in different control stages. Lastly, the proposed fuzzy DDMFAC approach is (...) applied to the control of particle quality in drug development phase of spray fluidized-bed granulation process, and its control effect is compared with MFAC and DDOILC and their fuzzy forms, in which the parameters of MFAC and DDOILC are adaptively adjusted with fuzzy logic. The effectiveness of the presented FDDMFAC approach is verified by a series of simulations. (shrink)

Employee creativity is fast becoming a part and parcel in the wake of the increasing volatility of the employment market and the complexity of job demands. Drawing from the actor-context interactionist theoretical approach and career construction theory, this paper adds to current research by exploring the serial mediating effect of job crafting and career adaptability in the impact of human resource management strength on employee creativity. Furthermore, we suggest that proactive personality interacts with HRMS to jointly influence creativity. Survey data (...) from samples of 297 and 390 employees largely confirm our model. Our findings show that HRMS positively impacts employee creativity via serial mediation of job crafting and career adaptability, and proactive personality negatively moderates the process. The paper confirms and expands the interactionist theoretical perspective of creativity, highlights the significance of integration of contextual factors, individual characteristics, and career construction, and makes certain practical sense. (shrink)

With the service-dominant logic gradually replacing the traditional commodity-dominant reason, co-creating value with consumers has become an essential marketing practice for enterprises. As a critical information carrier in enterprise marketing communication, the co-creation signal impacts co-creation observers. Enterprises are now exploring how to effectively release co-creation signals to attract most observers to participate in value creation activities actively. Based on self-determination theory, this study investigates the influence mechanism of co-creation signals on observers’ willingness to co-create and the moderating role of (...) mental simulation through the experimental method. The conclusions are as follows: The co-creation signal has a significant positive effect on the co-creation intention of observers. Self-designed co-creation signals generate more important co-creation willingness than self-produced co-creation signals; Self-determination and its dimensions mediate the relationship between co-creation signals and the observer’s co-creation willingness; and Mental simulation moderates the relationship between co-creation signal and self-determination. This study has important theoretical significance in enriching co-creation signals and mental simulation research. It also provides management implications for enterprises to release co-creation signals and optimize co-creation marketing practices effectively. (shrink)

Image-based crowd counting has extremely important applications in public safety issues. Most of the previous studies focused on extremely dense crowds. However, as the number of webcams increases, a crowd with extremely high density can obtain less error by summing the images of multiple close-range webcams, but there are still some problems such as heavy occlusions and large-scale variation. To solve the above problems, this paper proposes a new type of multibranch neural network with a compensator, in which features are (...) extracted through multibranch subnetworks of different scales. The weights between the branches are adjusted by the compensator, and the captured features are distinguished among different branches. To avoid learning nearly the same features in each branch and reducing the training deviation, the dataset is labeled with head scale, and the adaptive grading loss function is used to calculate the estimated loss of the subregions. The experimental results show that the accuracy of the network proposed in this paper is about 10% higher than that of the comparison network. (shrink)