Liang Hong, Wenjun Hou, Zonghui Wu and Huijie Han
The purpose of this paper is to propose a knowledge extraction framework to extract knowledge, including entities and relationships between them, from unstructured texts in…
Abstract
Purpose
The purpose of this paper is to propose a knowledge extraction framework to extract knowledge, including entities and relationships between them, from unstructured texts in digital humanities (DH).
Design/methodology/approach
The proposed cooperative crowdsourcing framework (CCF) uses both human–computer cooperation and crowdsourcing to achieve high-quality and scalable knowledge extraction. CCF integrates active learning with a novel category-based crowdsourcing mechanism to facilitate domain experts labeling and verifying extracted knowledge.
Findings
The case study shows that CCF can effectively and efficiently extract knowledge from multi-sourced heterogeneous data in the field of Tang poetry. Specifically, CCF achieves higher accuracy of knowledge extraction than the state-of-the-art methods, the contribution of feedbacks to the training model can be maximized by the active learning mechanism and the proposed category-based crowdsourcing mechanism can scale up the effective human–computer collaboration by considering the specialization of workers in different categories of tasks.
Research limitations/implications
This research proposes CCF to enable high-quality and scalable knowledge extraction in the field of Tang poetry. CCF can be generalized to other fields of DH by introducing domain knowledge and experts.
Practical implications
The extracted knowledge is machine-understandable and can support the research of Tang poetry and knowledge-driven intelligent applications in DH.
Originality/value
CCF is the first human-in-the-loop knowledge extraction framework that integrates active learning and crowdsourcing mechanisms; he human–computer cooperation method uses the feedback of domain experts through the active learning mechanism; the category-based crowdsourcing mechanism considers the matching of categories of DH data and especially of domain experts.
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Wenjun Cai, Jianlin Wu and Jibao Gu
Innovation has been identified as a critical element to achieve firms' growth. The purpose of this study is to investigate the impact of chief executive officer (CEO) passion on…
Abstract
Purpose
Innovation has been identified as a critical element to achieve firms' growth. The purpose of this study is to investigate the impact of chief executive officer (CEO) passion on firm innovation, including exploratory and exploitative innovation and examine the moderating roles of market and technological turbulence.
Design/methodology/approach
This study adopts the methodology of survey and uses multisource and time-lagged data of 146 firms in China. Seemingly unrelated regression (SUR) is used to test the hypotheses of this study.
Findings
This study finds that CEO passion promotes exploratory and exploitative innovation. Results also indicate that market turbulence strengthens the effect of CEO passion on exploratory and exploitative innovation, whereas technological turbulence weakens such an effect.
Originality/value
CEO passion is an important, positive affect which inspires CEOs to work for firms, but it has not yet received enough attention in the innovation literature. This study contributes to examining the impact of CEO passion on firm innovation and contributes to the contingency under which CEO passion influences firm innovation. Furthermore, this research finds that the moderating effects of market and technological turbulence are different in the relationship between CEO passion and firm innovation.
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This study aims to solve the problem of job scheduling and multi automated guided vehicle (AGV) cooperation in intelligent manufacturing workshops.
Abstract
Purpose
This study aims to solve the problem of job scheduling and multi automated guided vehicle (AGV) cooperation in intelligent manufacturing workshops.
Design/methodology/approach
In this study, an algorithm for job scheduling and cooperative work of multiple AGVs is designed. In the first part, with the goal of minimizing the total processing time and the total power consumption, the niche multi-objective evolutionary algorithm is used to determine the processing task arrangement on different machines. In the second part, AGV is called to transport workpieces, and an improved ant colony algorithm is used to generate the initial path of AGV. In the third part, to avoid path conflicts between running AGVs, the authors propose a simple priority-based waiting strategy to avoid collisions.
Findings
The experiment shows that the solution can effectively deal with job scheduling and multiple AGV operation problems in the workshop.
Originality/value
In this paper, a collaborative work algorithm is proposed, which combines the job scheduling and AGV running problem to make the research results adapt to the real job environment in the workshop.
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Zhipeng Wang, Zhiqin Qian, Ziye Song, Hongzhou Liu, Wenjun Zhang and Zhuming Bi
Even though multi-rotor aircrafts are becoming more and more prevalent in the fields of aerial photography, agricultural spraying, disaster searching and rescuing, how to achieve…
Abstract
Purpose
Even though multi-rotor aircrafts are becoming more and more prevalent in the fields of aerial photography, agricultural spraying, disaster searching and rescuing, how to achieve higher reliability and robustness of an aircraft still poses a big challenge. It is not a rare case that a multi-rotor aircraft is severely damaged or crushed when an actuator or sensor is malfunctioned. This paper aims at the resilience of an aircraft when a rotor is malfunctioned.
Design/methodology/approach
The reliability of a multi-rotor aircraft can be measured in terms of stability, robustness, resilience and fault tolerance. All of these four aspects are taken into consideration to improve overall reliability of aircrafts. When a rotor malfunction occurs, the control algorithm is cable of adjusting the operation conditions of the rest of rotors to achieve system stability.
Findings
In this paper, the authors first present a research topic on the development of a resilient multi-robot aircraft. A multi-rotor aircraft usually possesses more actuated motions than the required degrees of freedom.
Originality/value
The authors proposed to equip the multi-rotor aircraft with malfunction detecting sensors, and they developed the self-repairing algorithm to re-stabilize the aircraft when a malfunction of a rotor occurs. The design concept and methods were implemented on an eight-rotor aircraft, and the performance of the proposed instrumentation and self-repairing algorithm have been verified and validated.
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Pethmi De Silva, Nuwan Gunarathne and Satish Kumar
The purpose of this study is to perform bibliometric analysis to systematically and comprehensively examine the current landscape of digital knowledge, integration and performance…
Abstract
Purpose
The purpose of this study is to perform bibliometric analysis to systematically and comprehensively examine the current landscape of digital knowledge, integration and performance in the transformation of sustainability accounting, reporting and assurance.
Design/methodology/approach
This research uses a systematic literature review, following the Scientific Procedures and Rationales for Systematic Literature Review protocol and uses various bibliometric and performance analytical methods. These include annual scientific production analysis, journal analysis, keyword cooccurrence analysis, keyword clustering, knowledge gap analysis and future research direction identification to evaluate the existing literature thoroughly.
Findings
The analysis reveals significant insights into the transformative impact of digital technologies on sustainability practices. Annual scientific production and journal analyses highlight key contributors to the adoption of digital technologies in sustainability accounting, reporting and assurance. Keyword cooccurrence analyses have identified key themes in sustainability accounting, reporting and assurance, highlighting the transformative role of digital technologies such as artificial intelligence (AI), blockchain, Internet of Things (IoT) and big data. These technologies enhance corporate accountability, transparency and sustainability by automating processes and improving data accuracy. The integration of these technologies supports environmental, social and governance (ESG) reporting, circular economy initiatives and strategic decision-making, fostering economic, social and environmental sustainability. Cluster-by-coupling analyses delve into nine broader revealing that IoT improves ESG report accuracy, eXtensible Business Reporting Language structures ESG data and AI enhances life cycle assessments and reporting authenticity. In addition, digital transformation impacts environmental performance, big data optimizes resource use and edge computing improves eco-efficiency. Furthermore, this study identifies avenues for future research to advance the understanding and implementation of digital technology in sustainability accounting, reporting and assurance practices.
Research limitations/implications
Academically, this research enriches the understanding of how digital technologies shape sustainability practices and identifies gaps in digital knowledge and integration. Practically, it provides actionable insights for organizations to improve sustainability reporting and performance by effectively leveraging these technologies. Policy-wise, the findings advocate for frameworks supporting the effective implementation of these technologies, ensuring alignment with global sustainability goals.
Originality/value
This study offers a detailed analysis of the performance and intellectual framework of research on implementing digital technology in sustainability accounting, reporting and assurance. It highlights the evolving research landscape and emphasizes the need for further investigation into how emerging technologies can be leveraged to achieve sustainability goals.