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Article
Publication date: 20 January 2021

Xueqing Zhao, Min Zhang and Junjun Zhang

Classifying the types of fabric defects in the textile industry requires a way to effectively detect. The traditional textile fabric defects detection method is human eyes, which…

628

Abstract

Purpose

Classifying the types of fabric defects in the textile industry requires a way to effectively detect. The traditional textile fabric defects detection method is human eyes, which performs very low efficiency and high cost. Therefore, how to improve the classification accuracy of textile fabric defects by using current artificial intelligence and to better meet the needs in the textile industry, the purpose of this article is to develop a method to improve the accuracy of textile fabric defects classification.

Design/methodology/approach

To improve the accuracy of textile fabric defects classification, an ensemble learning-based convolutional neural network (CNN) method in terms of textile fabric defects classification (short for ECTFDC) on an enhanced TILDA database is used. ECTFDC first adopts ensemble learning-based model to classify five types of fabric defects from TILDA. Subsequently, ECTFDC extracts features of fabric defects via an ensemble multiple convolutional neural network model and obtains parameters by using transfer learning method.

Findings

The authors applied ECTFDC on an enhanced TILDA database to improve the robustness and generalization ability of the proposed networks. Experimental results show that ECTFDC outperforms the other networks, the precision and recall rates are 97.8%, 97.68%, respectively.

Originality/value

The ensemble convolutional neural network textile fabric defect classification method in this paper can quickly and effectively classify textile fabric defect categories; it can reduce the production cost of textiles and it can alleviate the visual fatigue of inspectors working for a long time.

Details

International Journal of Clothing Science and Technology, vol. 33 no. 4
Type: Research Article
ISSN: 0955-6222

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Article
Publication date: 6 March 2019

Xueqing Zhao, Xin Shi, Kaixuan Liu and Yongmei Deng

The quality of produced textile fibers plays a very important role in the textile industry, and detection and assessment schemes are the key problems. Therefore, the purpose of…

297

Abstract

Purpose

The quality of produced textile fibers plays a very important role in the textile industry, and detection and assessment schemes are the key problems. Therefore, the purpose of this paper is to propose a relatively simple and effective technique to detect and assess the quality of produced textile fibers.

Design/methodology/approach

In order to achieve automatic visual inspection of fabric defects, first, images of the textile fabric are pre-processed by using Block-Matching and 3-D (BM3D) filtering. And then, features of textile fibers image are respectively extracted, including color, texture and frequency spectrum features. The color features are extracted by using hue–saturation–intensity model, which is more consistent with the human vision perception model; texture features are extracted by using scale-invariant feature transform scheme, which is a quite good method to detect and describe the local image features, and the obtained features are robust to local geometric distortion; frequency spectrum features of textiles are less sensitive to noise and intensity variations than spatial features. Finally, for evaluating the quality of the fabric in real time, two quantitatively metric parameters, peak signal-to-noise ratio and structural similarity, are used to objectively assess the quality of textile fabric image.

Findings

Compared to the quality between production and pre-processing of textile fiber images, the BM3D filtering method is a very efficient technology to improve the quality of textile fiber images. Compared to the different features of textile fibers, like color, texture and frequency spectrum, the proposed detection and assessment method based on textile fabric image feature can easily detect and assess the quality of textiles. Moreover, the objective metrics can further improve the intelligence and performance of detection and assessment schemes, and it is very simple to detect and assess the quality of textiles in the textile industry.

Originality/value

An intelligent detection and assessment method based on textile fabric image feature is proposed, which can efficiently detect and assess the quality of textiles, thereby improving the efficiency of textile production lines.

Details

International Journal of Clothing Science and Technology, vol. 31 no. 3
Type: Research Article
ISSN: 0955-6222

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Article
Publication date: 15 June 2021

Xueqing Wang, Yang Li, Zhao Cai and Hefu Liu

This study aims to investigate the impact of experience product portal page aesthetics on bounce rate.

1888

Abstract

Purpose

This study aims to investigate the impact of experience product portal page aesthetics on bounce rate.

Design/methodology/approach

This research collected data from an online shop selling original design furniture on Taobao.com. It employed deep learning algorithm and manual coding to operationalize image and text aesthetics.

Findings

The empirical results indicate that text aesthetics has a U-shaped relationship with bounce rate, whereas the relationship between image aesthetics and bounce rate is insignificant. Moreover, the U-shaped relationship between text aesthetics and bounce rate is weakened by image aesthetics.

Originality/value

This study addresses an important but understudied topic – the bounce rate of experience products in the context of e-commerce. Although the high bounce rate has increasingly gained attention from practitioners, there remains a scarcity of research that addresses the effect of product portal page aesthetics in the specific context of experience products. The authors theorize product portal page aesthetics as the design elements of an e-commerce website and deeply analyzed the role of product portal page aesthetics by classifying it into text aesthetics and image aesthetics. The authors’ findings provide implications for online sellers and platforms to effectively design product profile pages to reduce the bounce rate.

Details

Industrial Management & Data Systems, vol. 121 no. 8
Type: Research Article
ISSN: 0263-5577

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Article
Publication date: 9 April 2019

Yu Zhou, Wenwen Zhao and Xueqing Fan

The purpose of this paper is to examine whether, how and when new venture creation progress (NVCP) affects work-to-family conflict (WFC) by introducing coping behavior strategies…

999

Abstract

Purpose

The purpose of this paper is to examine whether, how and when new venture creation progress (NVCP) affects work-to-family conflict (WFC) by introducing coping behavior strategies as mediators, entrepreneurs’ prior experience and family involvement in business as moderators.

Design/methodology/approach

This study performs multivariate regression analysis based on a sample of 260 nascent entrepreneurs from the Chinese Panel Study of Entrepreneurial Dynamics.

Findings

This study reveals that an entrepreneur’s WFC tends to increase along with the growth of the new venture. Specifically, NVCP impels entrepreneurs to adopt reactive role behavior strategy and meet both entrepreneurial and family demands; meanwhile, NVCP propels entrepreneurs to adopt prioritizing entrepreneurship behavior strategy for the increasing work demands, thus leading to more WFC; the mediation effect of prioritizing entrepreneurship behaviors is stronger than that of reactive role behaviors, which leads to an overall positive main effect. Moreover, the preceding mediating paths are moderated by entrepreneurs’ prior experience and family involvement.

Research limitations/implications

First, the authors have investigated how NVCP influenced WFC. However, the authors did not extend the research to the possible effect of WFC on entrepreneurial performance. Second, in the work-family-conflict literature, unmarried and those without children are often excluded since their private life demands differ significantly from parents’ demands. Although the authors control for marital status in the model, the number of children is still left uncontrolled. Furthermore, the authors only used the first two waves of data, leading to a potential selection bias. In addition, the Chinese context may have influenced the generalizability of the results in a complex manner.

Practical implications

This paper indicates that reactive role behavior strategy will decrease WFC, while prioritizing entrepreneurship behavior strategy will increase WFC. Therefore, the authors suggest entrepreneurs adopt more reactive strategy to reduce WFC. Besides, both prior experience and family involvement strengthen the relationship between NVCP and prioritizing entrepreneurship behavior strategy, thereby leading to more WFC. Therefore, entrepreneurs with prior experience and family involvement should pay more attention to their roles in family. Furthermore, entrepreneurs with family involvement can try to segment the entrepreneurship-family boundary psychologically. For example, entrepreneurs can avoid business talking with families but show concerns for them at rest time.

Social implications

WFC has been found negatively related to individual health and well-being. And entrepreneurs experienced even more WFC than employees in established organizations. Therefore, it is of great importance to focus on the topic of reducing entrepreneurs’ WFC. This research indicates that entrepreneurs can experience less WFC by choosing reactive role behavior strategy. Prior experience and family involvement can induce them to be more attached to new venture creation. This research provides practical suggestions and reminders for entrepreneurs.

Originality/value

This mediated moderation model elaborates whether, how and when NVCP affects WFC, thereby contributing to the knowledge of entrepreneurship-family interface and enlightening nascent entrepreneurs about balancing their start-up responsibilities with their family life.

Details

Management Decision, vol. 58 no. 6
Type: Research Article
ISSN: 0025-1747

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Article
Publication date: 17 May 2024

Meng-Nan Li, Xueqing Wang, Ruo-Xing Cheng and Yuan Chen

Currently, engineering project design lacks a design framework that fully combines subjective experience and objective data. This study develops an aided design decision-making…

48

Abstract

Purpose

Currently, engineering project design lacks a design framework that fully combines subjective experience and objective data. This study develops an aided design decision-making framework to automatically output the optimal design alternative for engineering projects in a more efficient and objective mode, which synthesizes the design experience.

Design/methodology/approach

A database of design components is first constructed to facilitate the retrieval of data and the design alternative screening algorithm is proposed to automatically select all feasible design alternatives. Then back propagation (BP) neural network algorithm is introduced to predict the cost of all feasible design alternatives. Based on the gray relational degree-particle swarm optimization (GRD-PSO) algorithm, the optimal design alternative can be selected considering multiple objectives.

Findings

The case study shows that the BP neural network-cost prediction algorithm can well predict the cost of design alternatives, and the framework can be widely used at the design stage of most engineering projects. Design components with low sensitivity to design objectives have been obtained, allowing for the consideration of disregarding their impacts on design objectives in such situations requiring rapid decisions. Meanwhile, design components with high sensitivity to design objective weights have also been obtained, drawing special attention to the effects of changes in the importance of design objectives on the selection of these components. Simultaneously, the framework can be flexibly adjusted to different design objectives and identify key design components, providing decision reference for designers.

Originality/value

The framework proposed in this paper contributes to the knowledge of design decision-making by emphasizing the importance of combining objective data and subjective experience, whose significance is ignored in the existing literature.

Details

Engineering, Construction and Architectural Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0969-9988

Keywords

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Article
Publication date: 25 January 2022

Jung-Chieh Lee and Xueqing Chen

The development of mobile technology has changed the traditional financial industry and banking sector. While traditional banks have adopted artificial intelligence (AI…

7197

Abstract

Purpose

The development of mobile technology has changed the traditional financial industry and banking sector. While traditional banks have adopted artificial intelligence (AI) techniques to deepen the development of mobile banking applications (apps), the current literature lacks research on the use of AI-based constructs to explore users' mobile banking app adoption intentions. To fill this gap, based on stimulus-organism-response (SOR) theory, two AI feature constructs as stimuli are considered, namely, perceived intelligence and anthropomorphism. This study then develops a research model to investigate how intelligence and anthropomorphism affect task-technology fit (TTF), perceived cost, perceived risk and trust (organism), which in turn influence users' AI mobile banking app adoption (response).

Design/methodology/approach

This study used a convenience nonprobability sampling approach; a total of 451 responses were collected to examine the model. The partial least squares technique was utilized for data analysis.

Findings

The results show that intelligence and anthropomorphism increase users' willingness to adopt mobile banking apps through TTF and trust. However, higher levels of anthropomorphism enhance users' perceived cost. In addition, both intelligence and anthropomorphism have insignificant effects on perceived risk. The results provide theoretical contributions for AI-based mobile banking app adoption and offer practical guidance for bank planning to use AI to retain users.

Originality/value

Based on SOR theory, this study reveals that as features, AI-enabled intelligence and anthropomorphism help us further understand users' perceptions regarding cost, risk, TTF and trust in the context of AI-enabled app adoption intentions.

Details

International Journal of Bank Marketing, vol. 40 no. 4
Type: Research Article
ISSN: 0265-2323

Keywords

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Article
Publication date: 20 October 2023

Dan-Yi Wang and Xueqing Wang

In construction projects, engineering variations are very common and create breeding grounds for opportunistic claims. This study investigates the complementary effect between an…

58

Abstract

Purpose

In construction projects, engineering variations are very common and create breeding grounds for opportunistic claims. This study investigates the complementary effect between an inspection mechanism and a reputation system in deterring opportunistic claims, considering an employer with limited inspection accuracy and a contractor, which can be either reputation-concerned or opportunistic.

Design/methodology/approach

This paper applies a signaling game to investigate the complementary effect between the employer's inspection and a reputation system in deterring the contractor's possible opportunistic claim, considering the information-flow influence of claiming prices.

Findings

This study finds that in the exogenous-inspection-accuracy case, the employer does not always inspect the claim. A more stringent reputation system complements a less accurate inspection only when the inspection cost is lower than a threshold, but may decline the employer's surplus or social welfare. In the optimal-inspection-accuracy case, the employer always inspects the claim. However, only a sufficiently stringent reputation system can guarantee the effectiveness of an optimal inspection in curbing opportunistic claims. A more stringent reputation system has a value-stepping effect on the employer's surplus but may unexpectedly impair social welfare, whereas a higher inspection cost efficiency always reduces social welfare.

Originality/value

This article contributes to the project management literature by combing the signaling game theory with the reputation theory and thus embeds the problem of inspection mechanism design into a broader socio-economic framework.

Details

Engineering, Construction and Architectural Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0969-9988

Keywords

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Article
Publication date: 7 June 2024

Xueqing Gan, Jianyao Jia, Yun Le, Tingting Liu and Yutong Xue

Relationship conflict between the owners and contractors is inevitable, which could induce negative consequences. Yet, the existing literature mostly focused on its direct effects…

113

Abstract

Purpose

Relationship conflict between the owners and contractors is inevitable, which could induce negative consequences. Yet, the existing literature mostly focused on its direct effects on project performance and ignored the process by which relationship conflict gradually deteriorates cooperation as well as corresponding managerial approaches. Given the fact that relationship conflict originates from interdependent tasks, the proposed theoretical model is intended to measure relational behavior as an instant outcome of relationship conflict, and explore the buffering role of contract enforcement approach.

Design/methodology/approach

This paper develops the conceptual model based on the literature review. Then the questionnaire survey was conducted. The dyadic data obtained from 168 Chinese construction project professionals were analyzed by the Partial Least squares Structural Equation Modeling (PLS-SEM) technique.

Findings

The results show that relational behavior partially mediates the link between relationship conflict and project performance. Besides, three types of contract enforcement approaches are found to differentially change the negative link between relationship conflict and relational behavior. Rigid contract enforcement can worsen the adverse effects of relationship conflict on relational behavior, whereas flexible contract enforcement can alleviate these negative effects. The level of mitigation hinges on whether compromising behaviors or obliging behaviors are chosen.

Originality/value

The study extends the knowledge of conflict theory and contract theory in the construction field. Based on the proposed conceptual model and PLS-SEM results, this study contributes to the understanding of relationship conflict’s consequences between the owners and contractors and enriches conflict management approaches in the construction field.

Details

Engineering, Construction and Architectural Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0969-9988

Keywords

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Article
Publication date: 29 July 2020

Dan Wang, Xueqing Wang, Mingshuai Liu, Henry Liu and Bingsheng Liu

The performance of public–private partnerships (PPPs) can be determined by a variety of factors, i.e. influencing factors (IFs). This study is undertaken for a purpose of…

574

Abstract

Purpose

The performance of public–private partnerships (PPPs) can be determined by a variety of factors, i.e. influencing factors (IFs). This study is undertaken for a purpose of identifying how such factors determine the project's performance (i.e. factor transmission patterns), particularly from the key stakeholders' perspectives.

Design/methodology/approach

A hybrid approach, which comprises a Social Network Analysis, ISM (i.e. Interpretive Structural Modeling) and an improved DEMATEL (i.e. Decision-Making Trail and Evaluation Laboratory), was developed to analyze the causal relationships between the identified IFs as well as the transmission patterns of their impacts on PPPs. Data were collected from interviews and questionnaire surveys.

Findings

The transmission patterns of the identified IFs cascade from project environment and features and stakeholders' relationship to the project company capabilities and project process. It is identified that the public authority has a higher level than that of the private entity in PPPs.

Research limitations/implications

It lacks longitudinal studies to investigate the dynamics of PPP stakeholder relationships and social networks. Future research needs to explore the transmission patterns of sub-factors affecting PPP performance and extend the applicability of the developed hybrid approach.

Practical implications

This research provides practitioners with a robust tool that is useful for and insights into enhancing the management of lifecycle performance. It ensures the public authorities and private entities embarking on PPPs will make an informed decision about the monitoring of the life cycle performance.

Originality/value

This study contributes to knowledge of managerial mechanisms that can be adopted to manage factors determining the performance of PPPs. It enables an understanding of stakeholders' roles in driving the life cycle performance of PPPs.

Details

Engineering, Construction and Architectural Management, vol. 28 no. 4
Type: Research Article
ISSN: 0969-9988

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Article
Publication date: 28 December 2023

Na Xu, Yanxiang Liang, Chaoran Guo, Bo Meng, Xueqing Zhou, Yuting Hu and Bo Zhang

Safety management plays an important part in coal mine construction. Due to complex data, the implementation of the construction safety knowledge scattered in standards poses a…

275

Abstract

Purpose

Safety management plays an important part in coal mine construction. Due to complex data, the implementation of the construction safety knowledge scattered in standards poses a challenge. This paper aims to develop a knowledge extraction model to automatically and efficiently extract domain knowledge from unstructured texts.

Design/methodology/approach

Bidirectional encoder representations from transformers (BERT)-bidirectional long short-term memory (BiLSTM)-conditional random field (CRF) method based on a pre-training language model was applied to carry out knowledge entity recognition in the field of coal mine construction safety in this paper. Firstly, 80 safety standards for coal mine construction were collected, sorted out and marked as a descriptive corpus. Then, the BERT pre-training language model was used to obtain dynamic word vectors. Finally, the BiLSTM-CRF model concluded the entity’s optimal tag sequence.

Findings

Accordingly, 11,933 entities and 2,051 relationships in the standard specifications texts of this paper were identified and a language model suitable for coal mine construction safety management was proposed. The experiments showed that F1 values were all above 60% in nine types of entities such as security management. F1 value of this model was more than 60% for entity extraction. The model identified and extracted entities more accurately than conventional methods.

Originality/value

This work completed the domain knowledge query and built a Q&A platform via entities and relationships identified by the standard specifications suitable for coal mines. This paper proposed a systematic framework for texts in coal mine construction safety to improve efficiency and accuracy of domain-specific entity extraction. In addition, the pretraining language model was also introduced into the coal mine construction safety to realize dynamic entity recognition, which provides technical support and theoretical reference for the optimization of safety management platforms.

Details

Engineering, Construction and Architectural Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0969-9988

Keywords

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