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With the development of data mining technology, diverse and broader domain knowledge can be extracted automatically. However, the research on applying knowledge mapping and data visualization techniques to genealogical data is limited. This paper aims to fill this research gap by providing a systematic framework and process guidance for practitioners seeking to uncover hidden knowledge from genealogy.

Based on a literature review of genealogy's current knowledge reasoning research, the authors constructed an integrated framework for knowledge inference and visualization application using a knowledge graph. Additionally, the authors applied this framework in a case study using “Manchu Clan Genealogy” as the data source.

The case study shows that the proposed framework can effectively decompose and reconstruct genealogy. It demonstrates the reasoning, discovery, and web visualization application process of implicit information in genealogy. It enhances the effective utilization of Manchu genealogy resources by highlighting the intricate relationships among people, places, and time entities.

This study proposed a framework for genealogy knowledge reasoning and visual analysis utilizing a knowledge graph, including five dimensions: the target layer, the resource layer, the data layer, the inference layer, and the application layer. It helps to gather the scattered genealogy information and establish a data network with semantic correlations while establishing reasoning rules to enable inference discovery and visualization of hidden relationships.

Defects in concrete surfaces are inevitably recurring during construction, which needs to be checked and accepted during construction and completion. Traditional manual inspection of surface defects requires inspectors to judge, evaluate and make decisions, which requires sufficient experience and is time-consuming and labor-intensive, and the expertise cannot be effectively preserved and transferred. In addition, the evaluation standards of different inspectors are not identical, which may lead to cause discrepancies in inspection results. Although computer vision can achieve defect recognition, there is a gap between the low-level semantics acquired by computer vision and the high-level semantics that humans understand from images. Therefore, computer vision and ontology are combined to achieve intelligent evaluation and decision-making and to bridge the above gap.

Combining ontology and computer vision, this paper establishes an evaluation and decision-making framework for concrete surface quality. By establishing concrete surface quality ontology model and defect identification quantification model, ontology reasoning technology is used to realize concrete surface quality evaluation and decision-making.

Computer vision can identify and quantify defects, obtain low-level image semantics, and ontology can structurally express expert knowledge in the field of defects. This proposed framework can automatically identify and quantify defects, and infer the causes, responsibility, severity and repair methods of defects. Through case analysis of various scenarios, the proposed evaluation and decision-making framework is feasible.

This paper establishes an evaluation and decision-making framework for concrete surface quality, so as to improve the standardization and intelligence of surface defect inspection and potentially provide reusable knowledge for inspecting concrete surface quality. The research results in this paper can be used to detect the concrete surface quality, reduce the subjectivity of evaluation and improve the inspection efficiency. In addition, the proposed framework enriches the application scenarios of ontology and computer vision, and to a certain extent bridges the gap between the image features extracted by computer vision and the information that people obtain from images.

To improve the frequency of adoption of mobile health services (MHSs) by users (consumers), it is critical to understand users' MHS adoption behaviors. However, the literature primarily focuses on MHS adoption-related factors and lacks consideration of the joint impacts of reasons for (RF) and reasons against (RA) on users' attitudes and adoption behaviors regarding MHSs. To fill this gap, this study integrates behavioral reasoning theory (BRT) and protective motivation theory (PMT) to develop a research model by uncovering the reasoning process of personal values, RF and RA, adoption attitudes and behavior toward MHSs. In particular, health consciousness (HC) is selected as the value. Comparative advantage, compatibility and perceived threat severity are considered the RF subconstructs; value barriers, risk barriers and tradition and norm barriers are deemed the RA subconstructs.

A total of 281 responses were collected to examine the model with the partial least squares structural equation modeling (PLS-SEM) method.

The results show that HC positively affects attitude through RA and RF. Additionally, RF partially mediates the relationship between HC and adoption behavior. This study contributes to a deeper understanding of user adoption behavior in MHS and provides practical guidance for the health services industry.

This study contributes to the existing MHS literature by understanding the joint influences of personal values, RF and RA on user attitude, which eventually determines users' adoption decisions regarding MHSs.

This study aims to observe people’s decisions to commit fraud. This study is important in the current time because it provides insights into the development of fraudulent intentions within individuals.

The information used in this study is derived from semi-structured interviews, conducted with 16 high-ranking officials who are employed in Indonesian local government positions.

The study does not have strong evidence to support prior studies assuming that situational factors or social enablers have direct effects on fraud intentions. As suggested, individual factors which are related to moral reasoning (moral judgment and rationalisation) emerge as a consequence of social enablers. The significant role of that moral reasoning is to rationalise any fraud attempt as permissible conduct. As such, when an individual is capable of legitimising his/her fraud attempt into appropriate self-judgement, s/he is more likely to engage in fraudulent behaviours.

This study offers practical prescriptions in guiding the management to develop strategies to curb fraudulent behaviours. The study suggests that moral cognitive reasoning is found to be a parameter of whether fraud is an acceptable option or not. So, an understanding of observers’ moral reasoning is helpful in predicting the likelihood of fraud within an organisation or in detecting it.

This study provides a different perspective on the psychological pathway to fraud. It becomes a complement work for the fraud triangle to explain fraudulent behaviours. Specifically, it provides crucial insights into the underlying motivations that lead individuals to accept invitations to engage in fraudulent activities.

In the era of big data, various industries are generating large amounts of text data every day. Simplifying and summarizing these data can effectively serve users and improve efficiency. Recently, zero-shot prompting in large language models (LLMs) has demonstrated remarkable performance on various language tasks. However, generating a very “concise” multi-document summary is a difficult task for it. When conciseness is specified in the zero-shot prompting, the generated multi-document summary still contains some unimportant information, even with the few-shot prompting. This paper aims to propose a LLMs prompting for multi-document summarization task.

To overcome this challenge, the authors propose chain-of-event (CoE) prompting for multi-document summarization (MDS) task. In this prompting, the authors take events as the center and propose a four-step summary reasoning process: specific event extraction; event abstraction and generalization; common event statistics; and summary generation. To further improve the performance of LLMs, the authors extend CoE prompting with the example of summary reasoning.

Summaries generated by CoE prompting are more abstractive, concise and accurate. The authors evaluate the authors’ proposed prompting on two data sets. The experimental results over ChatGLM2-6b show that the authors’ proposed CoE prompting consistently outperforms other typical promptings across all data sets.

This paper proposes CoE prompting to solve MDS tasks by the LLMs. CoE prompting can not only identify the key events but also ensure the conciseness of the summary. By this method, users can access the most relevant and important information quickly, improving their decision-making processes.

Blockchains provide significant benefits for business operations due to its transparency, traceability and information sharing. However, application to the food and beverage (F&B) industry was scarce. The purpose of this study is to explore how to form F&B managers’ blockchain adoption by applying behavioral reasoning theory (BRT). Additionally, supply chain partnerships (SCPs) were tested for the potential moderating roles within BRT. This study’s findings expand existing knowledge by providing novel information for F&B management.

Data were collected from F&B managers by using an online survey method. A structural equation modeling and multi-group analysis were performed to test the hypothesized relationships.

Findings revealed that the positive effects of “reasons for” on “attitudes,” and “adoption intentions” while “reasons against” did not show such effects. Environmental benefits of blockchains were found to lead more positive attitudes while traditional barriers were the greatest constraints for adopting blockchains. This study supports the significant moderating roles of SCPs within the context of F&B blockchain adoption.

This study contributes to the technology literature in the foodservice context by applying BRT as a theoretical lens. The importance of developing SCPs for F&B blockchain adoption and exploitation is highlighted.

区块链因其透明度、可追溯性和信息共享而为企业运营提供了重要的好处。然而, 将其应用于食品和饮料（F&B）行业却很少见。本研究探讨了如何通过应用行为推理理论（BRT）来形成 F&B 管理者的区块链采用。此外, 本研究还测试了供应链合作（SCPs）在BRT内的潜在调节作用。通过为F&B 管理提供新颖信息, 我们的研究结果扩展了现有知识领域。

采用在线调查方法收集了来自 F&B 管理者的数据。进行了结构方程建模和多组分析, 以测试假设关系。

研究结果显示, “支持的原因”对“态度”和“采用意向”有积极影响, 而“反对的原因”则没有显示出这种影响。区块链的环境优势被发现会导致更积极的态度, 而传统障碍是采用区块链的最大限制因素。本研究还证实了 SCP 在 F&B 区块链采用背景下的重要调节作用。

本研究通过应用 BRT 作为理论视角, 为餐饮服务背景下的技术文献做出了贡献。强调了发展 F&B 区块链采用和利用的供应链合作的重要性。

The purpose of this paper is to demonstrate how critical realism can be mobilised as a meta-theory, or philosophical under-labourer, for research on space accounting and how this may further inquiries into the known as well as the unknown implications of space exploration and commercialisation.

This is a conceptual paper that applies critical realism to the field of space accounting using cost management in space contracts as an illustrative example.

Adopting a naturalised version of critical realism that recognises the complex interplay between natural and social realities, the author nuances the distinction between intransitive and transitive objects of knowledge and advances a framework that may be used as a starting point for a transfactual mode of reasoning. The author then applies this mode of reasoning to the topic of cost management in the space sector and illustrates how it may enhance our insights into what causes cost overruns in space contracts.

By adopting a naturalised version of critical realism, the author establishes a philosophical framework that can support the broadly based, inter-disciplinary research agenda that has been envisaged for research on space accounting and possibly inform policy development.

This paper is the first to apply a critical realist perspective to space accounting and lays a philosophical foundation for future research on the topic.

Does future thinking enhance managers’ innovative behavior? This study aims to posit that the ability to project events while considering current/future variables and their development (i.e. future thinking) – inextricably linked with the knowledge creation process – may enhance the manager’s accuracy and the number of potentially successful innovative ideas for organizations.

The authors use a between-group experiment to examine the innovation choices of 47 subjects with experience in evaluating the market potential of new products when asked to support or otherwise reject real-life innovation-related ideas. The authors test the accuracy of decisions made by participants primed to apply future thinking, practically implemented through abductive reasoning, in their decision-making.

The authors found a significant change in managers’ innovative choices, with participants primed for future thinking making significantly more accurate decisions than the control group. Those participants both correctly chose innovation-related ideas with significant future potential and rejected ideas with limited potential that ultimately failed.

This study explores how future thinking enhances managers’ innovative behavior in organizations. It provides empirical evidence on how future thinking, practiced through abductive reasoning, can work to foster innovative behavior, which is an antecedent of knowledge creation. Organizations that foster future thinking concurrently create knowledge, increasing their competitive advantage in the long run.

The study aims to assess students' perceived mastery of reasoning-for-complexity competency and its sub-competencies in a sample of students in a Latin American university. The intention was to identify statistically significant differences between a population of men and women with similar sociocultural characteristics, assessing whether gender could be a factor for educational institutions to consider when implementing strategies to develop this competency.

The eComplexity instrument was applied to 370 undergraduate students in their first to ninth semesters in a private university in Western Mexico. Descriptive statistics were analyzed to determine the mean and standard deviation indicators and were tested for statistical significance. The convenience sampling methodology ensured that there were students from all semesters and a diversity of majors. The sampling aimed for a balance of men and women, resulting in 189 women and 181 men.

The results confirmed no statistically significant evidence to indicate differences between men and women in their perceived mastery of the reasoning-for-complexity competency in general. However, statistically significant differences were found in the perceived achievements of the sub-competencies of systems, critical and scientific thinking, which comprise the overall competency. Women presented a higher average perception of systemic and critical thinking achievement, and men had a higher perception of scientific thinking. The authors concluded that social and cultural elements influence the perception of achievement that men and women develop in thinking and solving problems.

Governments and educational institutions must establish training programs that do not follow gender stereotypes and promote reasoning-for-complexity skills equitably in men and women. It is necessary to create more scientific and academic spaces and projects involving women in the sciences; countries must emphasize this to improve their scientific competency. Only in this way will it be possible to reverse the perception that men and women have of their problem-solving skills and abilities, which, as this study shows, are more a matter of culture than capabilities.

Unlike previous studies, which analyze the competency of complex thinking in a particular way among its sub-competencies, this research sought comprehensive measurement. Furthermore, beyond measuring competency development, this study aimed to measure the perception of achievement. The authors believe this is the first step towards identifying elements of the social imagination that limit the formation of scientific thinking among women in Latin America.

To the best of the authors' knowledge, this is the first study that aims to present a comprehensive view of the auditing ethics literature by unboxing 40 years of efforts in the field.

This study combined bibliometric, social network and content analysis by analyzing 114 articles published in accounting and top business ethics journals on the Web of Science database from 1980 to 2021.

The results show a rising interest in this topic and reveal auditors’ ethical decision-making and moral reasoning as the most discussed topics in the literature. The work also clusters the literature according to keywords and scopes, identifying literature gaps and suggesting new avenues for future research.

The research results assist provide an overarching image of the auditing ethics field. In addition, these results draw possible future avenues to bridge the void in the current auditing ethics literature by presenting indispensable directions for potential research. For example, future research could pay more attention to whistleblowing, fraud, personal auditor characteristics, auditor ethical sensitivity, auditor ethical conflict, ethical climate and underreporting of time. Moreover, the rapidly changing business environment necessitates the auditing ethics research to move to more practical implications to mitigate previous mistakes and avoid any future risks.

All crises are an ideal breeding ground to motivate fraud and audit failures. In fact, auditing ethics research has been subordinated to the different economic crises. However, despite increasing awareness of the topic’s relevance, no comprehensive study focuses on auditing ethics literature. Now, the devastating effects of the COVID-19 crisis are producing a new wave of financial distresses and avoiding former mistakes is timelier than ever. With this novel and integrated approach, this work goes one step forward, developing a comprehensive picture of the auditing ethics literature.