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Article
Publication date: 3 August 2020

Huimin Liu, Yanru Yu, Yuxing Sun and Xue Yan

The owners of mega projects typically assemble multiple academic research units and enterprises to form an innovation alliance, which carries out knowledge transfer and knowledge…

1014

Abstract

Purpose

The owners of mega projects typically assemble multiple academic research units and enterprises to form an innovation alliance, which carries out knowledge transfer and knowledge creation targeting technical challenges in the process of engineering construction. Due to high technical and management complexity of mega projects, factors affecting knowledge transfer among innovation subjects are complex and diverse. This study proposes a mixed system dynamics (SD) method to build and simulate the process of knowledge transfer in mega projects innovation and analyzes the driving mechanism that enhances knowledge stock of enterprises and engineering innovation results.

Design/methodology/approach

First, this paper proposes a conceptual model for knowledge transfer in mega projects by adopting event analysis of the data gained from investigations and interviews. Then, a qualitative model of knowledge transfer that considers mutual influences of the owner, academic research unit and enterprises is developed. Based on that, mathematical relationship among variables of the qualitative model is determined and a quantitative model of knowledge transfer that considers heterogeneity of knowledge sender is built. Finally, simulation is achieved using Vensim software.

Findings

The factors affecting knowledge stock of enterprises are analyzed from three aspects: (1) the individual motives and capability of academic research units and enterprises; (2) the gap between academic research units and enterprises; (3) the heterogeneity of academic research units. The results show that the willingness and capability of knowledge reception by enterprises, specific knowledge transfer context such as relational distance and organization distance between academic research units and enterprises and academic research units with high knowledge stock have key influences on the knowledge stock of enterprises.

Research limitations/implications

Factors affecting knowledge transfer within the alliance of innovation in mega projects and their correlations are highly complicated and difficult to determine. Despite massive investigations and interviews on many long-span bridges in China in this study, it is barely possible to directly obtain accurate data for all variables in the model. Limitations of historical data result in limitations on applications of the proposed model.

Practical implications

By building the mega projects knowledge transfer model and conducting simulation analysis, this paper has generated practical values for the owners of mega projects on fostering, organizing, coordinating and managing of innovations. Especially, this study provides specific strategies and suggestions on selection of innovation subjects, motivation and guaranteed efficiency of knowledge transfer and knowledge creation of academic research units and enterprises.

Originality/value

This study proposes a conceptual model for factors affecting knowledge transfer that applies to innovations in mega project context, which fills the gap in the research of knowledge management in mega project innovations. Additionally, combining with the method of SD, the unique role of owner in knowledge transfer of mega projects and the differences among various knowledge senders and their influences on knowledge stocks of enterprises are thoroughly considered, and the research method of modeling and simulation of knowledge transfer mechanism is supplemented and extended.

Details

Engineering, Construction and Architectural Management, vol. 28 no. 3
Type: Research Article
ISSN: 0969-9988

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Book part
Publication date: 4 April 2005

Mirko Cardinale

The paper uses 101 years of Chilean and international financial assets returns to investigate mean-variance optimal portfolio allocations. The key conclusion is that the share of…

Abstract

The paper uses 101 years of Chilean and international financial assets returns to investigate mean-variance optimal portfolio allocations. The key conclusion is that the share of international unhedged investments is substantial even in minimum risk portfolios (20%), unless the period 1980–2002 is assumed to be drawn from a different distribution and previous history is disregarded. In addition to that, the paper finds that mean-variance optimal investors would have generated substantial demand for an asset replicating the return profile of an efficient pay-as-you-go pension scheme. Labour income and departures from log-normality of returns might, however, affect the latter conclusion.

Details

Latin American Financial Markets: Developments in Financial Innovations
Type: Book
ISBN: 978-1-84950-315-0

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Article
Publication date: 21 April 2022

Wei Zong, Songtao Lin, Yuxing Gao and Yanying Yan

This paper aims to provide a process-driven scientific data quality (DQ) monitoring framework by information product map (IP-Map) in identifying the root causes of poor DQ issues…

248

Abstract

Purpose

This paper aims to provide a process-driven scientific data quality (DQ) monitoring framework by information product map (IP-Map) in identifying the root causes of poor DQ issues so as to assure the quality of scientific data.

Design/methodology/approach

First, a general scientific data life cycle model is constructed based on eight classical models and 37 researchers’ experience. Then, the IP-Map is constructed to visualize the scientific data manufacturing process. After that, the potential deficiencies that may arise and DQ issues are examined from the aspects of process and data stakeholders. Finally, the corresponding strategies for improving scientific DQ are put forward.

Findings

The scientific data manufacturing process and data stakeholders’ responsibilities could be clearly visualized by the IP-Map. The proposed process-driven framework is helpful in clarifying the root causes of DQ vulnerabilities in scientific data.

Research limitations/implications

As for the implications for researchers, the process-driven framework proposed in this paper provides a better understanding of scientific DQ issues during implementing a research project as well as providing a useful method to analyse those DQ issues based on IP-Map approach from the aspects of process and data stakeholders.

Practical implications

The process-driven framework is beneficial for the research institutions, scientific data management centres and researchers to better manage the scientific data manufacturing process and solve the scientific DQ issues.

Originality/value

This research proposes a general scientific data life cycle model and further provides a process-driven scientific DQ monitoring framework for identifying the root causes of poor data issues from the aspects of process and stakeholders which have been ignored by existing information technology-driven solutions. This study is likely to lead to an improved approach to assuring the scientific DQ and is applicable in different research fields.

Details

The Electronic Library , vol. 40 no. 3
Type: Research Article
ISSN: 0264-0473

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Article
Publication date: 17 June 2024

Zhenghao Liu, Yuxing Qian, Wenlong Lv, Yanbin Fang and Shenglan Liu

Stock prices are subject to the influence of news and social media, and a discernible co-movement pattern exists among multiple stocks. Using a knowledge graph to represent news…

172

Abstract

Purpose

Stock prices are subject to the influence of news and social media, and a discernible co-movement pattern exists among multiple stocks. Using a knowledge graph to represent news semantics and establish connections between stocks is deemed essential and viable.

Design/methodology/approach

This study presents a knowledge-driven framework for predicting stock prices. The framework integrates relevant stocks with the semantic and emotional characteristics of textual data. The authors construct a stock knowledge graph (SKG) to extract pertinent stock information and use a knowledge graph representation model to capture both the relevant stock features and the semantic features of news articles. Additionally, the authors consider the emotional characteristics of news and investor comments, drawing insights from behavioral finance theory. The authors examined the effectiveness of these features using the combined deep learning model CNN+LSTM+Attention.

Findings

Experimental results demonstrate that the knowledge-driven combined feature model exhibits significantly improved predictive accuracy compared to single-feature models.

Originality/value

The study highlights the value of the SKG in uncovering potential correlations among stocks. Moreover, the knowledge-driven multi-feature fusion stock forecasting model enhances the prediction of stock trends for well-known enterprises, providing valuable guidance for investor decision-making.

Details

The Electronic Library , vol. 42 no. 3
Type: Research Article
ISSN: 0264-0473

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Article
Publication date: 20 February 2025

Xin Huang, Yuxing Peng, Jianfei Li, Guiju Zhu and Han Peng

This article aims to elaborate on the current relevant policies, research literature and technical applications of administrative intelligent decision-making in major countries in…

2

Abstract

Purpose

This article aims to elaborate on the current relevant policies, research literature and technical applications of administrative intelligent decision-making in major countries in the world, to summarize the current focus areas of international competition in administrative intelligent decision-making and to provide references and insights for other countries.

Design/methodology/approach

The knowledge graph tool CiteSpace was used to conduct a quantitative analysis of the field of administrative intelligent decision-making, using the two dimensions of research literature and technology patents to analyze the basic status and evolution process of artificial intelligence applied to administrative decision-making.

Findings

Over the past 30 years, theoretical research on administrative intelligent decision-making has primarily centered on countries like the United States of America, China and Japan. The main themes include leveraging artificial intelligence (AI) technology to enable digital government transformation, enhance administrative efficiency and promote public value through service-oriented initiatives. Countries like South Korea, China and the United States of America have demonstrated significant advantages in technology development and patent applications, focusing on e-government systems, intelligent government auditing, addressing policy mismatches between supply and demand and integrating online and offline administrative services. The international competitive landscape in this field is shaped by three key factors: foundational theories, technological advancements and practical scenario applications.

Originality/value

Despite the rapid advancements in AI technology and the acceleration of enterprise digital transformation, discussions on the intelligent transformation of administrative decision-making leveraging next-generation information technology remain limited. This study summarizes the development trajectory of administrative intelligent decision-making in major countries worldwide, analyzes the international competitive landscape of its theoretical and application research and highlights key focus areas. These findings offer valuable insights for advancing the construction of administrative intelligent decision-making systems in other nations.

Details

Library Hi Tech, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0737-8831

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Article
Publication date: 8 December 2020

Yuxing Qian and Wenxuan Gui

The purpose of this study is to identify the health information needs of senior online communities (SOCs) users, which could provide a basis for improving senior health…

1046

Abstract

Purpose

The purpose of this study is to identify the health information needs of senior online communities (SOCs) users, which could provide a basis for improving senior health information services.

Design/methodology/approach

A total of 14,933 health-related posts in the two most popular senior online communities (Yinling and Keai) in China are crawled as a corpus. Based on the results of word frequency analysis, text classification is performed based on two aspects: medical systems (Western medicine and traditional Chinese medicine) and topics. The health information needs of SOCs users are revealed from the composition, growth trends and popularity of health information. Finally, some key points of senior health information services are discussed.

Findings

The health information needs of senior users can be divided into four types: coping with aging, dietary nutrition, physical exercise and mental health. These needs are comprehensive and involve a variety of health issues. Users are mainly concerned with physical health issues. In terms of medical systems, the number of Western medicine posts is relatively larger, whereas traditional Chinese medicine appears more in posts on coping with aging and physical exercise. The health information needs of SOCs users are in a stable status. Both the medical systems and topics could have an impact on the popularity of health information, but the number of posts is inconsistent with the level of popularity.

Originality/value

This study combines multiple perspectives to identify the health information needs of seniors in China with a comprehensive overview.

Details

Aslib Journal of Information Management, vol. 73 no. 1
Type: Research Article
ISSN: 2050-3806

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Article
Publication date: 26 September 2024

Zhenni Ni, Yuxing Qian, Shuaipu Chen, Marie-Christine Jaulent and Cedric Bousquet

This study aims to evaluate the performance of LLMs with various prompt engineering strategies in the context of health fact-checking.

129

Abstract

Purpose

This study aims to evaluate the performance of LLMs with various prompt engineering strategies in the context of health fact-checking.

Design/methodology/approach

Inspired by Dual Process Theory, we introduce two kinds of prompts: Conclusion-first (System 1) and Explanation-first (System 2), and their respective retrieval-augmented variations. We evaluate the performance of these prompts across accuracy, argument elements, common errors and cost-effectiveness. Our study, conducted on two public health fact-checking datasets, categorized 10,212 claims as knowledge, anecdotes and news. To further analyze the reasoning process of LLM, we delve into the argument elements of health fact-checking generated by different prompts, revealing their tendencies in using evidence and contextual qualifiers. We conducted content analysis to identify and compare the common errors across various prompts.

Findings

Results indicate that the Conclusion-first prompt performs well in knowledge (89.70%,66.09%), anecdote (79.49%,79.99%) and news (85.61%,85.95%) claims even without retrieval augmentation, proving to be cost-effective. In contrast, the Explanation-first prompt often classifies claims as unknown. However, it significantly boosts accuracy for news claims (87.53%,88.60%) and anecdote claims (87.28%,90.62%) with retrieval augmentation. The Explanation-first prompt is more focused on context specificity and user intent understanding during health fact-checking, showing high potential with retrieval augmentation. Additionally, retrieval-augmented LLMs concentrate more on evidence and context, highlighting the importance of the relevance and safety of retrieved content.

Originality/value

This study offers insights into how a balanced integration could enhance the overall performance of LLMs in critical applications, paving the way for future research on optimizing LLMs for complex cognitive tasks.

Peer review

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-02-2024-0111

Details

Online Information Review, vol. 48 no. 7
Type: Research Article
ISSN: 1468-4527

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Article
Publication date: 11 April 2018

Huiyuan Zhao, Yuxing Mao and Tao Cheng

Application environments of wireless sensor networks (WSNs) include heterogeneous nodes with different packet sizes, transmission abilities and tolerable delay times. This study…

108

Abstract

Purpose

Application environments of wireless sensor networks (WSNs) include heterogeneous nodes with different packet sizes, transmission abilities and tolerable delay times. This study aims to design a reasonable network topology and transmission timing for these heterogeneous nodes to improve the quality of service (QoS) of networks.

Design/methodology/approach

In this paper, the authors treat node urgency and data packets as the basis of network clustering and to extend the network lifetime. The flow, energy consumption and residual energy of a node are included in the cluster head election. We also propose a delay evaluation function.

Findings

All the nodes in the network are guaranteed to transmit to the sink nodes efficiently by planning the transmission order in each cluster.

Originality/value

The simulation results show that the proposed method can balance node urgency and data packets path planning, which not only extends the lifetime of the network but also decreases network delay and improves the overall efficiency.

Details

Sensor Review, vol. 39 no. 1
Type: Research Article
ISSN: 0260-2288

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Article
Publication date: 11 February 2025

Lei Chen, Lihong Cheng, Yuxing Cheng and Xuesong Xu

This paper considers an e-tailer planning to distribute a product under one direct sales channel and multiple asymmetric agency platforms. Based on the multinomial logit (MNL…

11

Abstract

Purpose

This paper considers an e-tailer planning to distribute a product under one direct sales channel and multiple asymmetric agency platforms. Based on the multinomial logit (MNL) choice model, this study optimizes the pricing strategy and channel selection strategy to maximize the e-tailer’s profit.

Design/methodology/approach

A two-stage channel selection and pricing problem is formulated, where the profit-maximizing e-tailer first optimally selects a specified number of agency platforms from a set of alternatives to distribute the product and then determines the optimal prices in those channels.

Findings

An optimal pricing strategy is proposed to maximize the e-tailer’s total profit on multiple asymmetric channels. The results show that the e-tailer can obtain a higher profit by selling products on more asymmetric agency platforms. Moreover, an effective channel selection algorithm is provided to help the e-tailer optimally select the M agency platforms from N alternatives.

Originality/value

This study enriches the relevant research on multichannel selection and pricing by proposing an optimal pricing strategy and an effective channel selection algorithm. Evaluation results based on real-world industrial data show that the proposed optimal multichannel pricing strategy in this paper can significantly improve the profit of a real-world e-tailer compared to the e-tailer’s actual profit.

Details

Industrial Management & Data Systems, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0263-5577

Keywords

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