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Article
Publication date: 9 August 2021

Hung-Yu Wang, Yu-Lung Lo, Hong-Chuong Tran, M. Mohsin Raza and Trong-Nhan Le

For high crack-susceptibility materials such as Inconel 713LC (IN713LC) nickel alloy, fabricating crack-free components using the laser powder bed fusion (LPBF) technique…

334

Abstract

Purpose

For high crack-susceptibility materials such as Inconel 713LC (IN713LC) nickel alloy, fabricating crack-free components using the laser powder bed fusion (LPBF) technique represents a significant challenge because of the complex interactions between the effects of the main processing parameters, namely, the laser power and scanning speed. Accordingly, this study aims to build up a methodology which combines simulation model and experimental approach to fabricate high-density (>99.9%) IN713LC components using LPBF process.

Design/methodology/approach

The present study commences by performing three-dimensional (3D) heat transfer finite element simulations to predict the LPBF outcome (e.g. melt pool depth, temperature and mushy zone extent) for 33 representative sample points chosen within the laser power and scanning speed design space. The simulation results are used to train a surrogate model to predict the LPBF result for any combination of the processing conditions within the design space. Then, experimental trials were performed to choose the proper hatching space and also to define the high crack susceptibility criterion. The process map is then filtered in accordance with five quality criteria, namely, avoiding the keyhole phenomenon, improving the adhesion between the melt pool and the substrate, ensuring single-scan-track stability, avoiding excessive melt pool evaporation and suppressing the formation of micro-cracks, to determine the region of the process map which improves the relative density of the IN713LC component and minimizes the micro-cracks. The optimal processing conditions are used to fabricate IN713LC specimens for tensile testing purposes.

Findings

The optimal processing conditions predicted by simulation model are used to fabricate IN713LC specimens for tensile testing purposes. Experimental results show that the tensile strength and elongation of 3D-printed IN713LC tensile bar is higher than those of tensile bar made by casting. The yield strength of 791 MPa, ultimate strength of 995 MPa, elongation of 12%, and relative density of 99.94% are achieved.

Originality/value

The present study proposed a systematic methodology to find the processing conditions that are able to minimize the formation of micro-crack and improve the density of the high crack susceptivity metal material in LPBF process.

Details

Rapid Prototyping Journal, vol. 27 no. 8
Type: Research Article
ISSN: 1355-2546

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Article
Publication date: 29 August 2023

Hei-Chia Wang, Martinus Maslim and Hung-Yu Liu

A clickbait is a deceptive headline designed to boost ad revenue without presenting closely relevant content. There are numerous negative repercussions of clickbait, such as…

115

Abstract

Purpose

A clickbait is a deceptive headline designed to boost ad revenue without presenting closely relevant content. There are numerous negative repercussions of clickbait, such as causing viewers to feel tricked and unhappy, causing long-term confusion, and even attracting cyber criminals. Automatic detection algorithms for clickbait have been developed to address this issue. The fact that there is only one semantic representation for the same term and a limited dataset in Chinese is a need for the existing technologies for detecting clickbait. This study aims to solve the limitations of automated clickbait detection in the Chinese dataset.

Design/methodology/approach

This study combines both to train the model to capture the probable relationship between clickbait news headlines and news content. In addition, part-of-speech elements are used to generate the most appropriate semantic representation for clickbait detection, improving clickbait detection performance.

Findings

This research successfully compiled a dataset containing up to 20,896 Chinese clickbait news articles. This collection contains news headlines, articles, categories and supplementary metadata. The suggested context-aware clickbait detection (CA-CD) model outperforms existing clickbait detection approaches on many criteria, demonstrating the proposed strategy's efficacy.

Originality/value

The originality of this study resides in the newly compiled Chinese clickbait dataset and contextual semantic representation-based clickbait detection approach employing transfer learning. This method can modify the semantic representation of each word based on context and assist the model in more precisely interpreting the original meaning of news articles.

Details

Data Technologies and Applications, vol. 58 no. 2
Type: Research Article
ISSN: 2514-9288

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Article
Publication date: 10 July 2017

Jia-Jhou Wu, Hung Yu Kung and Tom M.Y. Lin

The purpose of this paper is to investigate how customer participation (CP) influences the two contrasting relationship maintenance mechanisms: dedication and constraint, and…

911

Abstract

Purpose

The purpose of this paper is to investigate how customer participation (CP) influences the two contrasting relationship maintenance mechanisms: dedication and constraint, and identifies its antecedents in the context of business-to-business information technology (IT) services.

Design/methodology/approach

An empirical study was conducted through a survey of 126 firms receiving IT services in Taiwan. The partial least squares method was used to test the conceptual model of the study.

Findings

The results indicated that CP positively relates to IT service quality, thereby influencing satisfaction (i.e. dedication). In addition, CP was also found to be positively associated with switching costs (i.e. constraint). Both satisfaction and switching costs have significant influences on loyalty. Furthermore, IT capabilities, organizational compatibility, and role clarity are positively related to CP.

Research limitations/implications

Longitudinal studies are needed to explore how CP affects the dual mechanisms in different phases of customer-firm relationships.

Originality/value

The study contributes to a thorough understanding of the influences of CP on relationship maintenance.

Details

Industrial Management & Data Systems, vol. 117 no. 6
Type: Research Article
ISSN: 0263-5577

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Article
Publication date: 2 April 2019

Hei Chia Wang, Yu Hung Chiang and Yi Feng Sun

This paper aims to improve a sentiment analysis (SA) system to help users (i.e. customers or hotel managers) understand hotel evaluations. There are three main purposes in this…

258

Abstract

Purpose

This paper aims to improve a sentiment analysis (SA) system to help users (i.e. customers or hotel managers) understand hotel evaluations. There are three main purposes in this paper: designing an unsupervised method for extracting online Chinese features and opinion pairs, distinguishing different intensities of polarity in opinion words and examining the changes in polarity in the time series.

Design/methodology/approach

In this paper, a review analysis system is proposed to automatically capture feature opinions experienced by other tourists presented in the review documents. In the system, a feature-level SA is designed to determine the polarity of these features. Moreover, an unsupervised method using a part-of-speech pattern clarification query and multi-lexicons SA to summarize all Chinese reviews is adopted.

Findings

The authors expect this method to help travellers search for what they want and make decisions more efficiently. The experimental results show the F-measure of the proposed method to be 0.628. It thus outperforms the methods used in previous studies.

Originality/value

The study is useful for travellers who want to quickly retrieve and summarize helpful information from the pool of messy hotel reviews. Meanwhile, the system will assist hotel managers to comprehensively understand service qualities with which guests are satisfied or dissatisfied.

Details

The Electronic Library , vol. 37 no. 1
Type: Research Article
ISSN: 0264-0473

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Article
Publication date: 23 March 2021

Hung-Yu Tsai

This study aimed to advance the understanding of employees' individual-level absorptive capacity by examining the mechanisms of three dimensions of their work outcomes: contextual…

543

Abstract

Purpose

This study aimed to advance the understanding of employees' individual-level absorptive capacity by examining the mechanisms of three dimensions of their work outcomes: contextual performance, citizenship behaviors toward customers and service sabotage. Drawing on the theory of psychological ownership, the author theorized and assessed how employees' individual-level absorptive capacity predicts different facets of employees' work outcomes through psychological ownership.

Design/methodology/approach

Multisource data were collected from 334 subordinates from the hospitality industry in Taiwan over two time periods. The hypotheses were tested using structural equation modeling, the results of which indicated that employees' individual-level absorptive capacity was positively related to psychological ownership.

Findings

Psychological ownership positively predicted contextual performance and citizenship behaviors toward customers; however, it was negatively associated with service sabotage. Finally, it was found to mediate the effects of employees' individual-level absorptive capacity on contextual performance, citizenship behaviors toward customers and service sabotage.

Originality/value

This study contributed to understanding the relationship between individual-level absorptive capacity and shaping perceptions of service workers and provided several theoretical implications for absorptive capacity and tourism literature.

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Article
Publication date: 3 April 2018

Hei Chia Wang, Yu Hung Chiang and Yen Tzu Huang

In academic work, it is important to identify a specific domain of research. Many researchers may look to conference issues to determine interesting or new topics. Furthermore…

278

Abstract

Purpose

In academic work, it is important to identify a specific domain of research. Many researchers may look to conference issues to determine interesting or new topics. Furthermore, conference issues can help researchers identify current research trends in their field and learn about cutting-edge developments in their area of specialization. However, so much conference information is published online that it can be difficult to navigate and analyze in a meaningful or productive way. Hence, the use of knowledge management (KM) could be a way to resolve these issues. In KM, ontology is widely adopted, but most ontology construction methods do not consider social information between target users. Therefore, this study aims to propose a novel method of constructing research topic maps using an open directory project (ODP) and social information.

Design/methodology/approach

The approach is to incorporate conference information (i.e. title, keywords and abstract) as sources and to consider the ways in which social information automatically produces research topic maps. The methodology can be divided into four modules: data collection, element extraction, social information analysis and visualization. The data collection module collects the required conference data from the internet and performs pre-processing. Then, the element extraction module extracts topics, associations and other basic elements of topic maps while considering social information. Finally, the results will be shown in the visualization module for researchers to browse and search.

Findings

The results of this study propose three main findings. First, creating topic maps with the ODP category information can help capture a richer set of classification associations. Second, social information should be considered when constructing topic maps. This study includes the relationship among different authors and topics to support information in social networks. By considering social information, such as co-authorship/collaborator, this method helps researchers find research topics that are unfamiliar but interesting or potential cooperative opportunities in the future. Third, this study presents topic maps that show a clear and simple pathway in interested domain knowledge.

Research limitations implications

First, this study analyzes and collects conference information, including the titles, keywords and abstracts of conference papers, so the data set must include all of the abovementioned information. Second, social information only analyzes co-authorship associations (collabship associations); other social information could be extracted in the future study. Third, this study only analyzes the associations between topics. The intensity of associations is not discussed in the study.

Originality/value

The study will have a great impact on learned societies because it bridges the gap between theory and practice. The study is useful for researchers who want to know which conferences are related to their research. Moreover, social networks can help researchers expand and diversify their research.

Details

The Electronic Library, vol. 36 no. 2
Type: Research Article
ISSN: 0264-0473

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Article
Publication date: 25 November 2020

Hei Chia Wang, Yu Hung Chiang and Si Ting Lin

In community question and answer (CQA) services, because of user subjectivity and the limits of knowledge, the distribution of answer quality can vary drastically – from highly…

240

Abstract

Purpose

In community question and answer (CQA) services, because of user subjectivity and the limits of knowledge, the distribution of answer quality can vary drastically – from highly related to irrelevant or even spam answers. Previous studies of CQA portals have faced two important issues: answer quality analysis and spam answer filtering. Therefore, the purposes of this study are to filter spam answers in advance using two-phase identification methods and then automatically classify the different types of question and answer (QA) pairs by deep learning. Finally, this study proposes a comprehensive study of answer quality prediction for different types of QA pairs.

Design/methodology/approach

This study proposes an integrated model with a two-phase identification method that filters spam answers in advance and uses a deep learning method [recurrent convolutional neural network (R-CNN)] to automatically classify various types of questions. Logistic regression (LR) is further applied to examine which answer quality features significantly indicate high-quality answers to different types of questions.

Findings

There are four prominent findings. (1) This study confirms that conducting spam filtering before an answer quality analysis can reduce the proportion of high-quality answers that are misjudged as spam answers. (2) The experimental results show that answer quality is better when question types are included. (3) The analysis results for different classifiers show that the R-CNN achieves the best macro-F1 scores (74.8%) in the question type classification module. (4) Finally, the experimental results by LR show that author ranking, answer length and common words could significantly impact answer quality for different types of questions.

Originality/value

The proposed system is simultaneously able to detect spam answers and provide users with quick and efficient retrieval mechanisms for high-quality answers to different types of questions in CQA. Moreover, this study further validates that crucial features exist among the different types of questions that can impact answer quality. Overall, an identification system automatically summarises high-quality answers for each different type of questions from the pool of messy answers in CQA, which can be very useful in helping users make decisions.

Details

The Electronic Library , vol. 38 no. 5/6
Type: Research Article
ISSN: 0264-0473

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Article
Publication date: 11 April 2008

Eddie Chi Man Hui and Ka Hung Yu

This paper aims to find out whether lagging problems exist within Hong Kong's office values.

524

Abstract

Purpose

This paper aims to find out whether lagging problems exist within Hong Kong's office values.

Design/methodology/approach

A State Space Model with the Kalman filter is deployed in detecting the extent of lagging errors in Hong Kong's office price indices, proffered by the ratings and valuation department (RVD).

Findings

The findings suggest that about one year of lagging errors exists in RVD's office price indices compared with the stock market property indices. Also, the finding suggests that the Kalman filter provides a more efficient form of estimates for real estate values and returns.

Originality/value

While most studies investigating lagging problems of appraisal‐based returns concentrate on the US real estate market, studies in this regard for Asian countries (or cities) are few and far between. Hong Kong, in particular, is worth studying, considering its established role as a financial centre in South East Asia. This paper also provides some insights for further studies on the prediction of future real estate values, in particular those with fewer transactions.

Details

Property Management, vol. 26 no. 2
Type: Research Article
ISSN: 0263-7472

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Article
Publication date: 5 October 2022

Amy Wong and Yu-Chen Hung

This paper aims to examine the antecedents of brand passion and brand community commitment, namely, self-congruity and athlete attraction, as well as their effects on online brand…

2177

Abstract

Purpose

This paper aims to examine the antecedents of brand passion and brand community commitment, namely, self-congruity and athlete attraction, as well as their effects on online brand advocacy in online brand communities.

Design/methodology/approach

The sample comprises members of a Facebook football fan club brand community. An online survey measuring athlete-level factors, team-level factors and online brand advocacy provides data to test the conceptual framework using structural equation modeling with partial least squares (PLS-SEM).

Findings

The findings of this paper support the positive spillover effect from athlete subbrand to team brand advocacy, as self-congruity exerted positive effects on brand passion and brand community commitment, while athlete attraction influenced brand community commitment, leading to online brand advocacy.

Research limitations/implications

The findings validate the dimensions of online brand advocacy and advance research on sports brand hierarchy in brand architecture by establishing the transference effect from athlete to the team brand.

Practical implications

To effectively manage their brands online, brand managers need to pay attention to the powerful and multifaceted tool of online brand advocacy. Brand managers can capitalize on their active advocates by working closely with them to co-create uplifting and authentic brand stories that are worthwhile for sharing, especially in times of crisis.

Originality/value

Building on the developmental trajectory of brand love and vicarious brand experience, the findings verify the directionality of the spillover effect and offer insights into the development of brand advocacy across different brand levels.

Details

Journal of Product & Brand Management, vol. 32 no. 2
Type: Research Article
ISSN: 1061-0421

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Article
Publication date: 9 September 2024

Tsung-Kang Chen, Yu-Shun Hung, Yijie Tseng and Kan-Yi Hsiao

According to the management obfuscation hypothesis, managers have incentives to influence the audit reports’ communicative value. This study aims to examine the relationship…

317

Abstract

Purpose

According to the management obfuscation hypothesis, managers have incentives to influence the audit reports’ communicative value. This study aims to examine the relationship between corporate earnings management and the readability of Chinese-text audit reports and the impact of key audit matter (KAM) disclosure requirements on this relationship.

Design/methodology/approach

This research adopts Taiwanese firms from 2010 to 2019 to investigate the association between earnings management and readability of Chinese-text audit reports within the framework of the KAM disclosure requirements implemented in 2016.

Findings

The findings show that auditors tend to issue less readable audit reports to firms undertaking earnings management, particularly after introducing KAM disclosures. Additional analyses indicate that such adverse impacts of client earnings management on audit report readability have become more pronounced for firms audited by a newly pointed or long-tenure lead audit partner, with high business risk, poor monitoring of governance mechanisms or a large amount of nonaudit services. These results suggest that auditor partners may compromise auditor independence and use flexible narratives in audit reports as a form of moral insurance.

Practical implications

As auditors may manage audit report readability to reduce audit liability, authorities must formulate policies concerning audit report disclosure to strengthen its communicative value and simplify language usage. Additionally, authorities should strengthen quality control standards concerning auditor independence to reduce auditor pressure from clients’ economic importance.

Originality/value

This study provides valuable insights into auditors' responses to corporate earnings management behavior, particularly regarding the interplay between earnings management, audit report quality and regulatory changes, thus expanding our understanding of the dynamics within the auditing profession.

Details

Pacific Accounting Review, vol. 36 no. 3/4
Type: Research Article
ISSN: 0114-0582

Keywords

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