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Article
Publication date: 11 June 2021

Wei Du, Qiang Yan, Wenping Zhang and Jian Ma

Patent trade recommendations necessitate recommendation interpretability in addition to recommendation accuracy because of patent transaction risks and the technological…

Abstract

Purpose

Patent trade recommendations necessitate recommendation interpretability in addition to recommendation accuracy because of patent transaction risks and the technological complexity of patents. This study designs an interpretable knowledge-aware patent recommendation model (IKPRM) for patent trading. IKPRM first creates a patent knowledge graph (PKG) for patent trade recommendations and then leverages paths in the PKG to achieve recommendation interpretability.

Design/methodology/approach

First, we construct a PKG to integrate online company behaviors and patent information using natural language processing techniques. Second, a bidirectional long short-term memory network (BiLSTM) is utilized with an attention mechanism to establish the connecting paths of a company — patent pair in PKG. Finally, the prediction score of a company — patent pair is calculated by assigning different weights to their connecting paths. The semantic relationships in connecting paths help explain why a candidate patent is recommended.

Findings

Experiments on a real dataset from a patent trading platform verify that IKPRM significantly outperforms baseline methods in terms of hit ratio and normalized discounted cumulative gain (nDCG). The analysis of an online user study verified the interpretability of our recommendations.

Originality/value

A meta-path-based recommendation can achieve certain explainability but suffers from low flexibility when reasoning on heterogeneous information. To bridge this gap, we propose the IKPRM to explain the full paths in the knowledge graph. IKPRM demonstrates good performance and transparency and is a solid foundation for integrating interpretable artificial intelligence into complex tasks such as intelligent recommendations.

Details

Internet Research, vol. 32 no. 2
Type: Research Article
ISSN: 1066-2243

Keywords

Article
Publication date: 13 March 2020

Wenping Zhang, Wei Du, Yiyang Bian, Chih-Hung Peng and Qiqi Jiang

The purpose of this study is to unpack the antecedents and consequences of clickbait prevalence in online media at two different levels, namely, (1) Headline-level: what…

Abstract

Purpose

The purpose of this study is to unpack the antecedents and consequences of clickbait prevalence in online media at two different levels, namely, (1) Headline-level: what characteristics of clickbait headlines attract user clicks and (2) Publisher-level: what happens to publishers who create clickbait on a prolonged basis.

Design/methodology/approach

To test the proposed conjectures, the authors collected longitudinal data in collaboration with a leading company that operates more than 500 WeChat official accounts in China. This study proposed a text mining framework to extract and quantify clickbait rhetorical features (i.e. hyperbole, insinuation, puzzle, and visual rhetoric). Econometric analysis was employed for empirical validation.

Findings

The findings revealed that (1) hyperbole, insinuation, and visual rhetoric entice users to click the baited headlines, (2) there is an inverted U-shaped relationship between the number of clickbait headlines posted by a publisher and its visit traffic, and (3) this non-linear relationship is moderated by the publisher's age.

Research limitations/implications

This research contributes to current literature on clickbait detection and clickbait consequences. Future studies can design more sophisticated methods for extracting rhetorical characteristics and implement in different languages.

Practical implications

The findings could aid online media publishers to design attractive headlines and develop clickbait strategies to avoid user churn, and help managers enact appropriate regulations and policies to control clickbait prevalence.

Originality/value

The authors propose a novel text mining framework to quantify rhetoric embedded in clickbait. This study empirically investigates antecedents and consequences of clickbait prevalence through an exploratory study of WeChat in China.

Details

Internet Research, vol. 30 no. 3
Type: Research Article
ISSN: 1066-2243

Keywords

Book part
Publication date: 13 November 2014

Maoliang Bu, Shuwen Zhai, Jie Zhang and Wenping Zheng

The central debate on pollution havens concerns whether the level of environmental regulation in developing countries influences foreign investment location decisions…

Abstract

The central debate on pollution havens concerns whether the level of environmental regulation in developing countries influences foreign investment location decisions. Most empirical studies are based on aggregate data, while micro-level evidence is relatively lacking in the literature. To fill this research gap, this paper tests for the existence of intracountry pollution havens in China by estimating the determinants of foreign investment flows based on a large firm-level panel dataset. Evidence from this study supports the existence of pollution havens within China in certain industries. However, the sensitivity of foreign investment to environmental regulation varies significantly across industries with different pollution characteristics. Furthermore, when the impact of government subsidies on foreign investment is accounted for, the results show that subsidies can compensate for pollution treatment costs in provinces with stricter environmental regulation.

Details

Globalization and the Environment of China
Type: Book
ISBN: 978-1-78441-179-4

Keywords

Content available
Article
Publication date: 17 August 2012

402

Abstract

Details

Grey Systems: Theory and Application, vol. 2 no. 2
Type: Research Article
ISSN: 2043-9377

Content available

Abstract

Details

Internet Research, vol. 32 no. 2
Type: Research Article
ISSN: 1066-2243

Article
Publication date: 16 December 2019

Jian Yu, Xunpeng Shi and James Laurenceson

Consumption volatility is a key source of economic growth volatility; thus, it is an important factor in designing macroeconomic policy. The purpose of this paper is to…

Abstract

Purpose

Consumption volatility is a key source of economic growth volatility; thus, it is an important factor in designing macroeconomic policy. The purpose of this paper is to investigate the factors that determine household consumption volatility, using urban household survey (UHS) data over the period 2002–2009 in 18 provinces in China.

Design/methodology/approach

Both a traditional variance decomposition method and an advanced variance decomposition method are used.

Findings

The traditional variance decomposition method suggests that heterogeneity of consumption goods is the key to analyze consumption volatility in China. Consumption of transportation makes the highest aggregate contribution and per-unit volatility in consumption volatility, whereas consumption of food makes the second highest aggregate contribution and the lowest per-unit volatility. Further investigation with the advanced variance decomposition method, which allows the authors to capture intertemporal dynamics and cross-household differences simultaneously, finds that the main factor determining the consumption volatility in China is intertemporal dynamics, rather than cross-household differences.

Research limitations/implications

Future research could fruitfully explore four issues. First, consumption upgrading has increased the volatility of China’s household consumption. How much will this affect economic growth in China under its “new normal” conditions, and how should the Chinese government respond? Second, differences between UHS data and aggregate data in the calculations of consumption risk sharing need to be investigated. Third, it is important to investigate the channels through which the Chinese government can enhance its ability to spread consumption risks and thus reduce consumer consumption volatility. Finally, further study could extend the current 18 provinces to a nation-wide sample and update the data beyond 2009 to estimate the impact of the global financial crisis.

Practical implications

The results suggest that when policy makers design macroeconomic policies to smooth consumption volatility, they should consider heterogeneity in household consumption goods, regional disparity and intertemporal dynamics simultaneously. Well-managed volatility of Chinese household consumption can contribute to a stable economic growth in China and the world.

Social implications

Well-managed volatility of Chinese household consumption can contribute to a stable economic growth in China and the world.

Originality/value

This paper fills this gap by using China’s UHS data to assess consumption volatility from the perspectives of heterogeneity in household consumption goods, cross-household differences and intertemporal dynamics. We make three contributions to the literature. The first contribution of this paper consists of demonstrating the contributions of heterogeneity in household consumption goods to consumption volatility. The second contribution consists of using the advanced variance decomposition method proposed by Crucini and Telmer (2012). This decomposition methodology allows the authors to examine whether household consumption volatility is due to cross-household differences or intertemporal dynamics. The third contribution is that this paper takes Chinese residents’ consumption fluctuations as the starting point to analyze the impact of consumption fluctuations on the future trend of China’s economy.

Details

International Journal of Emerging Markets, vol. 15 no. 4
Type: Research Article
ISSN: 1746-8809

Keywords

Article
Publication date: 28 January 2011

Hong Liu, Qishan Zhang and Wenping Wang

The purpose of this paper is to realize a location‐routing network optimization in reverse logistics (RL) using grey systems theory for uncertain information.

786

Abstract

Purpose

The purpose of this paper is to realize a location‐routing network optimization in reverse logistics (RL) using grey systems theory for uncertain information.

Design/methodology/approach

There is much uncertain information in network optimization and location‐routing problem (LRP) of RL, including fuzzy information, stochastic information and grey information, etc. Fuzzy information and stochastic information have been studied in logistics, however grey information of RL has not been covered. In the LRP of RL, grey recycling demands are taken into account. Then, a mathematics model with grey recycling demands has been constructed, and it can be transformed into grey chance‐constrained programming (GCCP) model, grey simulation and a proposed hybrid particle swarm optimization (PSO) are combined to resolve it. An example is also computed in the last part of the paper.

Findings

The results are convincing: not only that grey system theory can be used to deal with grey uncertain information about location‐routing problem of RL, but GCCP, grey simulation and PSO can be combined to resolve the grey model.

Practical implications

The method exposed in the paper can be used to deal with location‐routing problem with grey recycling information in RL, and network optimization result with grey uncertain factor could be helpful for logistics efficiency and practicability.

Originality/value

The paper succeeds in realising both a constructed model about location‐routing of RL with grey recycling demands and a solution algorithm about grey mathematics model by using one of the newest developed theories: grey systems theory.

Details

Grey Systems: Theory and Application, vol. 1 no. 1
Type: Research Article
ISSN: 2043-9377

Keywords

Article
Publication date: 17 August 2012

Hong Liu, Wenping Wang and Qishan Zhang

The purpose of this paper is to realize a multi‐objective location‐routing network optimization in reverse logistics using particle swarm optimization based on grey…

486

Abstract

Purpose

The purpose of this paper is to realize a multi‐objective location‐routing network optimization in reverse logistics using particle swarm optimization based on grey relational analysis with entropy weight.

Design/methodology/approach

Real world network design problems are often characterized by multi‐objective in reverse logistics. This has recently been considered as an additional objective for facility location problem or vehicle routing problem in reverse logistics network design. Both of them are shown to be NP‐hard. Hence, location‐routing problem (LRP) with multi‐objective is more complicated integrated problem, and it is NP‐hard too. Due to the fact that NP‐hard model cannot be solved directly, grey relational analysis and entropy weight were added to particle swarm optimization to decision among the objectives. Then, a mathematics model about multi‐objective LRP of reverse logistics has been constructed, and a proposed hybrid particle swarm optimization with grey relational analysis and entropy weight has been developed to resolve it. An example is also computed in the last part of the paper.

Findings

The results are convincing: not only that particle swarm optimization and grey relational analysis can be used to resolve multi‐objective location‐routing model, but also that entropy and grey relational analysis can be combined to decide weights of objectives.

Practical implications

The method exposed in the paper can be used to deal with multi‐objective LRP in reverse logistics, and multi‐objective network optimization result could be helpful for logistics efficiency and practicability.

Originality/value

The paper succeeds in realising both a constructed multi‐objective model about location‐routing of reverse logistics and a multi‐objective solution algorithm about particle swarm optimization and future stage by using one of the newest developed theories: grey relational analysis.

Article
Publication date: 3 August 2012

Wenping Wang, Xinhuan Huang and Jie Xie

The paper attempts to analyze the network structure of value activity in manufacturing clusters, propose the model of value creation of cluster's value activity network…

1648

Abstract

Purpose

The paper attempts to analyze the network structure of value activity in manufacturing clusters, propose the model of value creation of cluster's value activity network, and explore the inner mechanism and optimization strategies of value creation in manufacturing clusters from the perspective of cluster's value activity network.

Design/methodology/approach

This paper applies a genetic algorithm to optimally search in the target space, and repeatedly exerts genetic operation (select, cross, variation) on the population to explore the optimal configuration strategy between value creation activity and resource utilization. It also analyzes the relation between object function of value creation and relative parameters.

Findings

The total value created by value activity network was impacted by the degree of effective configuration between all kinds of resources and value activities; the total value created by value activity network is positively related to activity units' elasticity coefficient of value creation of human resource, material resources and relations resource, and is negatively correlated to cost coefficient of human resource, material resources and relations resource; when the cooperative relations between activity units create positive relationship profit, the total value created by value activity network increases with the increase of cooperative relations between activity units.

Practical implications

Enterprises in clusters should reasonably configure and incorporate the resource among value activities through adding, deleting or reconfiguring activities, which makes the value activities network create maximum value; enterprises can transform the type of activity units to increase elasticity coefficient of value creation of human resources, such as transforming production activities into the high value‐added activities; enterprises can optimally incorporate the technical, material resources and human resources among activities to increase value creation elastic coefficient of material resources; enterprises can decrease cost coefficient by maintaining the stability of long‐term cooperation with the suppliers and strengthening the cultivation of talents; enterprises can increase profits from relation resource or reduce cost coefficient of relationship by updating activities, building trust mechanism and communication mechanisms and establishing long‐term cooperation relationship to improve value creation activities.

Originality/value

This paper proposes the model of value creation from the perspective of cluster's value activity network, and applies a genetic algorithm to explore the optimal configuration strategies between value creation activity and resource utilization.

Article
Publication date: 22 July 2021

Wenping Xu, Jinting Cong and David G. Proverbs

The purpose of this study is to undertake an evaluation of the resilient capacity of the infrastructure systems in the city of Wuhan. This evaluation focuses on the…

Abstract

Purpose

The purpose of this study is to undertake an evaluation of the resilient capacity of the infrastructure systems in the city of Wuhan. This evaluation focuses on the ability of the infrastructure to cope with extreme weather from multiple dimensions and to propose effective interventions against such risks.

Design/methodology/approach

This research draws on a review and synthesis of the theory of resilience and adopts the literature induction method to build an evaluation index for five urban systems, namely: roads; water supply and drainage; energy and power; urban disaster reduction; and communications. Index data from the period of 1990–2019 are combined with the views of experts from Wuhan and analyzed using principal component analysis (PCA) to calculate the weightings of the five urban systems. A fuzzy comprehensive evaluation method is then used to investigate the resilient capacity of these five urban infrastructure systems in the city.

Findings

Generally, the results show that the resilience of the infrastructure systems in Wuhan are at a high level. Based on the results, the communications and roads systems are found to have higher levels of resilience, while the disaster mitigation system is found to have a relatively low level of resilience. Recommendations are suggested to help improve resilience and prioritize investments in the development of the city's infrastructure systems.

Research limitations/implications

The development of these specific indicators and quantitative requirements have not been studied in detail, so a more comprehensive, systematic evaluation of quantitative indicators and methods of urban infrastructure resilience is still required. In addition, the research on the resilience of urban infrastructure under extreme weather is still in its infancy, and it is essential to further increase the quantitative assessment of the resilience of urban infrastructure under construction. This will also be indispensable information in the subsequent implementation of a resilient planning process.

Originality/value

This research builds a rigorous and reliable evaluation model that avoids any subjective bias in the results and represents a new approach to evaluate the resilience of the infrastructure systems in the city of Wuhan, which could be applied to other cities.

Details

International Journal of Building Pathology and Adaptation, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2398-4708

Keywords

1 – 10 of 26