Miao Tian, Ying Cui, Haixia Long and Junxia Li
In novelty detection, the autoencoder based image reconstruction strategy is one of the mainstream solutions. The basic idea is that once the autoencoder is trained on normal…
Abstract
Purpose
In novelty detection, the autoencoder based image reconstruction strategy is one of the mainstream solutions. The basic idea is that once the autoencoder is trained on normal data, it has a low reconstruction error on normal data. However, when faced with complex natural images, the conventional pixel-level reconstruction becomes poor and does not show the promising results. This paper aims to provide a new method for improving the performance of novelty detection based autoencoder.
Design/methodology/approach
To solve the problem that conventional pixel-level reconstruction cannot effectively extract the global semantic information of the image, a novel model with the combination of attention mechanism and self-supervised learning method is proposed. First, an auxiliary task, reconstruct rotated image, is set to enable the network to learn global semantic feature information. Then, the channel attention mechanism is introduced to perform adaptive feature refinement on the intermediate feature map to optimize the correspondingly passed feature map.
Findings
Experimental results on three public data sets show that the proposed method has potential performance for novelty detection.
Originality/value
This study explores the ability of self-supervised learning methods and attention mechanism to extract features on a single class of images. In this way, the performance of novelty detection can be improved.
Details
Keywords
This study aims to explore the factors whereby some international organizations (IOs) are more effective than others in international mediation and proposes three types of…
Abstract
Purpose
This study aims to explore the factors whereby some international organizations (IOs) are more effective than others in international mediation and proposes three types of hypotheses through combining quantitative and qualitative analysis. First, IOs with greater institutional capabilities for gathering, exchanging and disseminating conflict-related information are more likely to mediate effectively. IO bias is another factor of influence in this regard. Second, IOs with greater institutional capabilities for deploying field missions and guaranteeing agreement are more likely to mediate effectively and maintain durable peace. Third, IOs with higher amounts of leverage are more likely to mediate effectively.
Design/methodology/approach
The study establishes two data sets: one on interstate conflict; the other on intrastate conflict, thus to cover as many research samples as possible and avoid sampling bias.
Findings
Results of the statistical analysis indicate that no matter interstate or intrastate conflict, IOs with higher institutional capabilities for diplomatic interventions are more likely to bring conflict parties to an agreement and thereafter maintain short-term peace. IOs with higher institutional capabilities for economic sanctions are similarly effective. Furthermore, IOs with greater institutional capabilities for field mission deployment mediate more effectively, whether in facilitating peace agreements or maintaining short-term and long-term peace after the agreement. IO bias and preference, however, have no significant impact on mediation effectiveness.
Research limitations/implications
This study has made no in-depth explorations of such existing and important research areas as different third-party comparisons of the mediation effect.
Practical implications
This paper attempts to make some contributions to the topic of mediation effectiveness through applying a bargaining model to the research and performing a statistical analysis based on both an interstate conflict data set and an intrastate conflict data set.
Originality/value
This paper provides an in-depth causal analysis and thoroughgoing comparison of the effectiveness of IOs in both interstate conflicts and intrastate conflicts.
Details
Keywords
Given the significance of innovation in enabling firms to maintain a long-term competitive edge and secure excess profits, this paper aims to investigate whether and how…
Abstract
Purpose
Given the significance of innovation in enabling firms to maintain a long-term competitive edge and secure excess profits, this paper aims to investigate whether and how stakeholders’ attention to innovation (SATI) influences corporate innovation.
Design/methodology/approach
This paper introduces a novel variable, SATI, which is achieved by segmenting stakeholders’ attention into two categories: attention to innovation and attention to other facets, using textual analysis methods. Subsequently, this paper empirically examines the influence of SATI on corporate innovation.
Findings
This paper finds that SATI positively affects corporate innovation input, and the result remains true after addressing possible endogeneity issues using instrumental variable regression. Furthermore, the positive effect of SATI on corporate innovation is stronger in firms facing greater financing constraints, thus verifying the financing constraints hypothesis. The positive effect is also stronger in firms with lower risk-taking levels, thus confirming the innovation failure tolerance hypothesis. Further analysis suggests that SATI increases both corporate innovation output and efficiency, thus ruling out the catering hypothesis.
Originality/value
This paper highlights the importance of SATI in driving corporate innovation. It enriches the literature on the repercussions of stakeholders’ attention and determinants of corporate innovation. In addition, it provides practical suggestions for further implementing China’s national innovation-driven development strategy.
Details
Keywords
This paper aims to study the interplay between a risk-averse national brand manufacturer's (NBM) selling mode decision and a risk-neutral e-platform's private brand (PB…
Abstract
Purpose
This paper aims to study the interplay between a risk-averse national brand manufacturer's (NBM) selling mode decision and a risk-neutral e-platform's private brand (PB) introduction decision.
Design/methodology/approach
A game theory model is used to solve selling mode decision, that is whether transform the selling mode from the wholesale mode to the marketplace mode, and PB introduction decision, that is, whether introduce the PB.
Findings
The results show that for the NBM, under certain condition, the NBM's selling mode decision is not affected by the e-platform's PB introduction decision. High revenue-sharing rate is conducive only when the difference in consumer preference between the PB and the national brand (NB) is small. The NBM's risk aversion will improve the applicability of the marketplace mode. For the e-platform, high PB preference of consumers and risk-averse behavior of the NBM is not conducive to PB introduction. For the supply chain, scenarios that the NB monopolizes the market under the wholesale mode and PB introduction under the marketplace mode should be prevented. PB introduction under the wholesale mode will become the only equilibrium with the increase of risk aversion of the NBM. Finally, the authors extend the scenario that consumers prefer the PB and the e-platform is risk-averse enterprise and find that PB introduction under the wholesale mode is detrimental to the NBM but beneficial to the supply chain. The impact of consumers' PB preference on the e-platform's PB introduction is opposite to the basic model. The impact of the e-platform's risk aversion on game equilibrium is opposite to that of the NBM's risk aversion.
Originality/value
This paper is first to study selling mode decision and PB introduction decision when considering enterprises' risk-averse attitude.
Details
Keywords
Qiuping Wang, Subing Liu and Haixia Yan
Due to high efficiency and low carbon of natural gas, the consumption of natural gas is increasing rapidly, and the prediction of natural gas consumption has become the focus. The…
Abstract
Purpose
Due to high efficiency and low carbon of natural gas, the consumption of natural gas is increasing rapidly, and the prediction of natural gas consumption has become the focus. The purpose of this paper is to employ a prediction technique by combining grey prediction model and trigonometric residual modification for predicting average per capita natural gas consumption of households in China.
Design/methodology/approach
The GM(1,1) model is utilised to obtain the tendency term, then the generalised trigonometric model is used to catch the periodic phenomenon from the residual data of GM(1,1) model for improving predicting accuracy.
Findings
The case verified the view of Xie and Liu: “When the value of a is less, DGM model and GM(1,1) model can substitute each other.” The combination of the GM(1,1) and the trigonometric residual modification technique can observably improve the predicting accuracy of average per capita natural gas consumption of households in China. The mean absolute percentage errors of GM(1,1) model, DGM(1,1), unbiased grey forecasting model, and TGM model in ex post testing stage (from 2013 to 2015) are 32.5510, 33.5985, 36.9980, and 5.2996 per cent, respectively. The TGM model is suitable for the prediction of average per capita natural gas consumption of households in China.
Practical implications
According to the historical data of average per capita natural gas consumption of households in China, the authors construct GM(1,1) model, DGM(1,1) model, unbiased grey forecasting model, and GM(1,1) model with trigonometric residual modification. The accuracy of TGM is the best. TGM helps to improve the accuracy of GM(1,1).
Originality/value
This paper gives a successful practical application of grey model GM(1,1) with the trigonometric residual modification, where the cyclic variations exist in the residual series. The case demonstrates the effectiveness of trigonometric grey prediction model, which is helpful to understand the modeling mechanism of trigonometric grey prediction model.
Details
Keywords
Haixia Yuan, Kevin Lu, Ali Ausaf and Mohan Zhu
As an emerging video comment feature, danmaku is gaining more traction and increasing user interaction, thereby altering user engagement. However, existing research seldom…
Abstract
Purpose
As an emerging video comment feature, danmaku is gaining more traction and increasing user interaction, thereby altering user engagement. However, existing research seldom explores how the effectiveness of danmaku on user engagement varies over time. To address this research gap, this study proposes a comprehensive framework drawing on social presence theory and information overload theory. The framework aims to explain how the effectiveness of danmaku in increasing user engagement changes over shorter time intervals.
Design/methodology/approach
A research model was proposed and empirically tested using data collected from 1,019 movies via Bilibili.com, one of China’s most popular danmaku video platforms. A time-varying effect model (TVEM) was used to examine the proposed research model.
Findings
The study finds that the volume of danmaku and its valence exert a time-varying influence on user engagement. Notably, the study shows that danmaku volume plays a more substantial role in determining user engagement than danmaku valence.
Originality/value
This research offers theoretical insights into the dynamic impact of danmaku on user engagement. The innovative conceptualization and measurement of user engagement advance research on pseudo-synchronous communication engagement. Furthermore, this study offers practical guidelines for effectively managing danmaku comments on online video platforms.
Details
Keywords
Yannian Wu, Euisoo Kim, James J. Zhang, Fengyan Li and Haixia Duan
Grounded in social cognitive theory, social exchange theory and “cognition-emotion-behavior intention” analysis framework, a theoretical model of cause-related sport marketing…
Abstract
Purpose
Grounded in social cognitive theory, social exchange theory and “cognition-emotion-behavior intention” analysis framework, a theoretical model of cause-related sport marketing (CRSM) affecting consumers’ purchase intentions was constructed through a case study. This model was then empirically validated to confirm CRSM's impact on consumers' purchase intentions.
Design/methodology/approach
This study embraces a mixed-methods approach that combines both qualitative and quantitative research methodologies to investigate the mechanisms through which CRSM influences consumers' purchase intentions.
Findings
The results indicate that: (1) consumers’ perception of CRSM has no direct impact on purchase intentions; (2) consumers’ perception of CRSM directly affects gratitude; (3) consumer gratitude acts as a complete mediator between perceived CRSM and purchase intentions.
Originality/value
These findings shed light on the role of gratitude in CRSM and offer practical guidance for sports enterprises in improving their philanthropic marketing strategies.
Details
Keywords
Haixia Li, Yongrong Wang and Zhian Chen
Graduated compression shaping pants (GCSPs) are shapewears sharing the same action mechanisms as medical compression stockings (MCSs), setting four stages of pressure on lower…
Abstract
Purpose
Graduated compression shaping pants (GCSPs) are shapewears sharing the same action mechanisms as medical compression stockings (MCSs), setting four stages of pressure on lower limbs that gradually decreasing from the ankle to the thigh root. They are claimed to be able to not only shaping bodies but also promoting blood circulation in legs. However, there are few studies on whether GCSPs perform the advertised functions and how effective GCSPs could be. The purpose of this paper is to explore and evaluate the pressure distribution and body-shaping effectivity of GCSPs.
Design/methodology/approach
The authors first select two graduated compression shaping pants (GCSPs-A, GCSPs-B) and a pair of professional shaping pants as the Controls. Then objective pressure test and 3D body scanning test are conducted. Finally, the pressure distribution and body-shaping effectivity are demonstrated by ORIGIN and MATLAB, compared with controls.
Findings
GCSPs-A perform significant body-shaping effectivity at the calf, thigh and thigh root, which are less effective than the Controls. The body-shaping effectivity of GCSPs-B is predicted weaker than GCSPs-A at the calf and thigh, while better at the thigh root. Both GCSPs-A and GCSPs-B show gradual pressure, which could be classified into Class I or II of MCSs. Comprehensively, GCSPs-A are superior than GCSPs-B.
Originality/value
In this paper, authors evaluate the pressure distribution and body-shaping effectivity of GCSPs, which could provide guidance for enterprises to further optimize and produce GCSPs, performing better functions that meet consumers' needs better.
Details
Keywords
Haixia Wang and Dariusz Ceglarek
Dimensional variation management is a major challenge in multi‐station sheet metal assembly processes involving complex products such as automotive body and aircraft fuselage…
Abstract
Purpose
Dimensional variation management is a major challenge in multi‐station sheet metal assembly processes involving complex products such as automotive body and aircraft fuselage assemblies. Very few studies have explored it at a preliminary design phase taking into consideration effects of part deformation on variation propagation, since early design phase involves the development of imprecise design models with scant or incomplete product and process knowledge. The objective of this paper is to present a variation model which can be built into the preliminary design phase taking into consideration all of the existing interactions between flexible parts and tools in multi‐station sheet metal assembly process.
Design/methodology/approach
The paper addresses this problem by first, presenting a beam‐based product and process model which shares the same data structure of the B‐Rep CAD models, and therefore can be embedded in CAD systems for automatic product skeletal design; second, determining the influence of part deformation, for various, differing joining and releasing schemes, on variation propagation; and third, utilizing this information to generate a vector‐based variation propagation model for multistation sheet metal assemblies.
Findings
This paper presents a beam‐based product and process model which shares the same data structure of the B‐Rep CAD models, and therefore can be embedded in CAD systems for automatic product skeletal design; determines the influence of part deformation, for various, differing joining and releasing schemes, on variation propagation; and utilizes this information to generate a vector‐based variation propagation model for multistation sheet metal assemblies.
Originality/value
A truck cab assembly is presented to demonstrate the advantages of the proposed model over the state‐of‐the‐art approach used in industry for sheet metal assemblies.
Details
Keywords
Debin Fang, Haixia Yang, Baojun Gao and Xiaojun Li
Discovering the research topics and trends from a large quantity of library electronic references is essential for scientific research. Current research of this kind mainly…
Abstract
Purpose
Discovering the research topics and trends from a large quantity of library electronic references is essential for scientific research. Current research of this kind mainly depends on human justification. The purpose of this paper is to demonstrate how to identify research topics and evolution in trends from library electronic references efficiently and effectively by employing automatic text analysis algorithms.
Design/methodology/approach
The authors used the latent Dirichlet allocation (LDA), a probabilistic generative topic model to extract the latent topic from the large quantity of research abstracts. Then, the authors conducted a regression analysis on the document-topic distributions generated by LDA to identify hot and cold topics.
Findings
First, this paper discovers 32 significant research topics from the abstracts of 3,737 articles published in the six top accounting journals during the period of 1992-2014. Second, based on the document-topic distributions generated by LDA, the authors identified seven hot topics and six cold topics from the 32 topics.
Originality/value
The topics discovered by LDA are highly consistent with the topics identified by human experts, indicating the validity and effectiveness of the methodology. Therefore, this paper provides novel knowledge to the accounting literature and demonstrates a methodology and process for topic discovery with lower cost and higher efficiency than the current methods.