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Article
Publication date: 1 February 2011

Lynette M. McDonald and Chia Hung Lai

Scant research has investigated retail banking customers' reactions to different corporate social responsibility (CSR) initiatives. This study seeks to investigate whether…

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Abstract

Purpose

Scant research has investigated retail banking customers' reactions to different corporate social responsibility (CSR) initiatives. This study seeks to investigate whether Taiwanese retail banking customers prefer corporate social responsibility (CSR) initiatives that favour themselves or other stakeholder groups (community, environment), and whether these initiatives impact customer attitude and behavioural intentions.

Design/methodology/approach

Using an experimental survey design and a snowball sampling technique, 130 Taiwanese banking customers answered questionnaires examining attitude and behaviour in response to three different CSR initiatives.

Findings

Customer‐centric initiatives more powerfully impacted banking customers' attitude to the bank and behavioural intentions than environmental or philanthropic initiatives. However, the results were significant only for the difference between customer‐centric and environmental initiatives.

Originality/value

This is the first research examining banking customers' attitude and behaviour in response to different CSR initiatives in a Taiwanese setting. It has implications for banks developing CSR strategies.

Details

International Journal of Bank Marketing, vol. 29 no. 1
Type: Research Article
ISSN: 0265-2323

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Article
Publication date: 5 October 2018

Fan Wu, Yung-Ting Chuang and Hung-Wei Lai

The purpose of this paper is to present a system that analyzes trustworthiness and ranks applications to improve the search experience.

228

Abstract

Purpose

The purpose of this paper is to present a system that analyzes trustworthiness and ranks applications to improve the search experience.

Design/methodology/approach

The system adopts pointwise mutual information to calculate comment semantics. It examines subjective (signed opinions, anonymous opinions and star ratings) and objective factors (download numbers, reputation ratings) before filtering, ranking and displaying). The authors invited three experts to check three categories and compared the results using Spearman and two statistics.

Findings

A high correlation between the proposed system and the expert ranking system suggests that the system can act as decision support.

Research limitations/implications

First, the authors have only tested the correlation between the proposed system and an expert ranking system; user satisfaction was not evaluated. The authors plan to conduct a later survey to gather user feedback. Second, the ranking system evaluates applications using fixed weights and disregards time. Therefore, in the future, the authors plan to enable their system to weight recent records over older ones.

Practical implications

User discussion forums, although helpful, have drawbacks. Not all reviews are trustworthy, and forums provide no filtering mechanisms to combat information overload. The solution to this is the authors’ system that crawls a forum, filters information, analyzes the trustworthiness of each comment and ranks the application for the user.

Originality/value

This paper develops a formula to analyze the trustworthiness of opinions, enabling the system to act as decision support when no professional advice is available.

Details

The Electronic Library, vol. 36 no. 5
Type: Research Article
ISSN: 0264-0473

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Article
Publication date: 7 November 2016

Tse-Ping Dong, Chia-Liang Hung and Nai-Chang Cheng

The purpose of this paper is to show how continual enhancement of knowledge management systems (KMSs) enhances knowledge sharing intention.

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Abstract

Purpose

The purpose of this paper is to show how continual enhancement of knowledge management systems (KMSs) enhances knowledge sharing intention.

Design/methodology/approach

This study integrates information system (IS) success with social cognitive theory (SCT) to explain knowledge sharing intention. Based on a survey of 276 KMS users in Taiwan’s information technology industry, the structural equation model has been applied to examine the influence process from a user satisfactory context to personal cognitive beliefs, and thus knowledge sharing intention.

Findings

The results indicate that the user satisfactory context stimulated by continual KMS enhancement increases knowledge sharing intention through the mediation of personal cognition of self-efficacy and outcome expectancy.

Practical implications

The results have empirical implications for learning how to motivate developers’ patience and passion for follow-up improvements to meet user expectations empathically, which has been emphasized for service provision.

Originality/value

The originality of this research is its explanation of system adoption behavior, which combines the core of IS success with SCT, links user satisfaction to intention to use, and concerns behavior within a specific context.

Details

Information Technology & People, vol. 29 no. 4
Type: Research Article
ISSN: 0959-3845

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Article
Publication date: 10 August 2023

Yung-Lien Lai, Fei Luo, Chia-Cheng Kang and Tzu-Ying Lo

While a substantial amount of research has been conducted in western societies exploring public attitudes toward police (ATP) among immigrants in recent decades, the question of…

200

Abstract

Purpose

While a substantial amount of research has been conducted in western societies exploring public attitudes toward police (ATP) among immigrants in recent decades, the question of how recently arrived immigrants view the police in Asian societies has been largely overlooked. This study aims to explore Southeast Asian immigrants' ATP in Taiwan and how assimilation, discrimination, affirmation, procedural justice, bifocal lenses and contact experiences – viewed simultaneously – impact their perceptions.

Design/methodology/approach

Using a combination of convenience and snowball sampling methods, a total of 579 completed survey responses were collected in Taiwan with a response rate of 89%. Structural Equation Modeling (SEM) was used to examine key factors that impact immigrants' attitudes toward the Taiwanese police.

Findings

The findings suggest that procedural justice and assimilation are two robust and direct predictors of immigrants' attitudes toward Taiwanese police. Immigrants from Southeast Asian countries who perceive that they have been treated fairly by Taiwan police tended to report more positive ATP. Likewise, higher levels of assimilation boosted confidence in the police. In addition, both nationality and marital status had a significant impact on perceptions of the police.

Originality/value

This pioneering study examines immigrants' ATP among four groups of Southeast Asians in Taiwan —namely, immigrants from Indonesia, Vietnam, Thailand and the Philippines. The use of SEM strengthens the robustness of the findings derived from this study.

Details

Policing: An International Journal, vol. 47 no. 2
Type: Research Article
ISSN: 1363-951X

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Article
Publication date: 26 January 2021

Chih-Hsuan Huang, Chun-Ting Lai, Cheng-Feng Wu, Yii-Ching Lee, Chia-Hui Yu, Hsiu-Wen Hsueh and Hsin-Hung Wu

Gender difference exists in the perception of the patient safety culture in healthcare organizations. A case from a medical center in Taiwan is presented to examine how different…

197

Abstract

Purpose

Gender difference exists in the perception of the patient safety culture in healthcare organizations. A case from a medical center in Taiwan is presented to examine how different genders perceive the patient safety culture in practice from 2014 to 2017.

Design/methodology/approach

A longitudinal study using the data from 2014 to 2017 is conducted quantitatively. Mann–Whitney U test and one-way analysis of variance are employed for analyses.

Findings

The results showed that female nurses had significantly higher emotional exhaustion than male nurses in 2015 and 2016 indicating male nurses had better fatigue recovery than their female counterparts. In addition, male nurses felt a higher degree of fatigue in 2016 and 2017 than those in 2015 statistically. In contrast, female nurses felt more stressful in 2016 and 2017 than those in 2014 statistically. Female nurses had higher emotional exhaustion in 2016 and 2017 than those in 2014 and 2015 statistically.

Practical implications

To sum up, female nurses were more stressful than before, and their recovery was also relatively poor particularly in 2016 and 2017. There is a need to reduce the degree of fatigue for female nurses in this medical center through employee assistance programs, mindfulness-based stress reduction programs, building up female nurses' positive currency and setting up their appreciative inquiry. In contrast to female nurses, male nurses recovered better from fatigue. This might encourage hospital management to deploy male nurses more effectively in this medical center.

Originality/value

The results enable the hospital management to know there is a gender difference in this case hospital. More attention on female nurses is required.

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Abstract

Details

Library Hi Tech, vol. 42 no. 2
Type: Research Article
ISSN: 0737-8831

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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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Book part
Publication date: 2 December 2024

Sedat Baştuğ, Fevzi Bİtİktaş, Kazim Yenİ, Enes Emİnoglu and Kee-Hung Lai

This study explores technology trends and challenges in the liner shipping industry through the lens of blockchain technology, addressing gaps in the literature with a…

Abstract

This study explores technology trends and challenges in the liner shipping industry through the lens of blockchain technology, addressing gaps in the literature with a comprehensive analysis. By examining blockchain applications in shipping and port contexts, the research fills a significant void, covering trend identification, legal considerations, and implementation challenges. This study extends to examining links between current blockchain projects, revealing trends and challenges in technology applications. The conclusion synthesizes implications and future trajectories of this transformative technology within the broader context of Industry 4.0, positioning this research at the forefront of advancements in maritime technology and supply chain management (SCM).

Details

Impact of Industry 4.0 on Supply Chain Sustainability
Type: Book
ISBN: 978-1-83797-778-9

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Article
Publication date: 15 March 2021

Yung-Ting Chuang and Yi-Hsi Chen

The purpose of this paper is to apply social network analysis (SNA) to study faculty research productivity, to identify key leaders, to study publication keywords and research…

420

Abstract

Purpose

The purpose of this paper is to apply social network analysis (SNA) to study faculty research productivity, to identify key leaders, to study publication keywords and research areas and to visualize international collaboration patterns and analyze collaboration research fields from all Management Information System (MIS) departments in Taiwan from 1982 to 2015.

Design/methodology/approach

The authors first retrieved results encompassing about 1,766 MIS professors and their publication records between 1982 and 2015 from the Ministry of Science and Technology of Taiwan (MOST) website. Next, the authors merged these publication records with the records obtained from the Web of Science, Google Scholar, IEEE Xplore, ScienceDirect, Airiti Library and Springer Link databases. The authors further applied six network centrality equations, leadership index, exponential weighted moving average (EWMA), contribution value and k-means clustering algorithms to analyze the collaboration patterns, research productivity and publication patterns. Finally, the authors applied D3.js to visualize the faculty members' international collaborations from all MIS departments in Taiwan.

Findings

The authors have first identified important scholars or leaders in the network. The authors also see that most MIS scholars in Taiwan tend to publish their papers in the journals such as Decision Support Systems and Information and Management. The authors have further figured out the significant scholars who have actively collaborated with academics in other countries. Furthermore, the authors have recognized the universities that have frequent collaboration with other international universities. The United States, China, Canada and the United Kingdom are the countries that have the highest numbers of collaborations with Taiwanese academics. Lastly, the keywords model, system and algorithm were the most common terms used in recent years.

Originality/value

This study applied SNA to visualize international research collaboration patterns and has revealed some salient characteristics of international cooperation trends and patterns, leadership networks and influences and research productivity for faculty in Information Management departments in Taiwan from 1982 to 2015. In addition, the authors have discovered the most common keywords used in recent years.

Details

Library Hi Tech, vol. 40 no. 5
Type: Research Article
ISSN: 0737-8831

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Article
Publication date: 16 July 2024

Chun-Chia Wang, Hsuan-Chu Chen and Jason C. Hung

This research explored the intersection of cognitive processes, emotions and their impacts on digital game-based vocabulary learning (DGVL) among university students. Recognizing…

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Abstract

Purpose

This research explored the intersection of cognitive processes, emotions and their impacts on digital game-based vocabulary learning (DGVL) among university students. Recognizing the scant research in this area, especially with integrating innovative technologies, this study aims to understand the influence of these elements using advanced monitoring tools.

Design/methodology/approach

This inquiry was carried out as an observational study involving 44 university students segmented into three English language proficiency levels: high, intermediate and low based on their English course scores. The methodological tools included a portable eye tracker to observe visual behaviors and deep learning technology to identify and analyze the participants’ emotional responses and engagement with the DGVL during the learning process.

Findings

The results showed that distinct fixation sequences and variations in visual attention during DGVL were correlated with different levels of competency, suggesting a direct correlation between visual engagement and language competence. In addition, emotional transitions, predominantly from engagement (“flow”) to challenge (“frustration”), were common among participants, reflecting the emotional dynamics of learning. Furthermore, all participants consistently focused on the English vocabulary definitions, indicative of their targeted approach to understanding and test preparation. These findings highlighted the intricate dynamics between emotions and cognitive processes in learning environments.

Originality/value

Contribution of this study shows the interplay of cognitive engagement and emotional experiences in the context of DGVL. It underscored the complex nature of these factors and their collective influence on learners’ visual and emotional engagement, offering valuable implications for educational strategies and technological applications in language learning.

Details

Interactive Technology and Smart Education, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1741-5659

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