San-Yih Hwang, Chih-Ping Wei, Chien-Hsiang Lee and Yu-Siang Chen
The information needs of the users of literature database systems often come from the task at hand, which is short term and can be represented as a small number of articles…
Abstract
Purpose
The information needs of the users of literature database systems often come from the task at hand, which is short term and can be represented as a small number of articles. Previous works on recommending articles to satisfy users’ short-term interests have utilized article content, usage logs, and more recently, coauthorship networks. The usefulness of coauthorship has been demonstrated by some research works, which, however, tend to adopt a simple coauthorship network that records only the strength of coauthorships. The purpose of this paper is to enhance the effectiveness of coauthorship-based recommendation by incorporating scholars’ collaboration topics into the coauthorship network.
Design/methodology/approach
The authors propose a latent Dirichlet allocation (LDA)-coauthorship-network-based method that integrates topic information into the links of the coauthorship networks using LDA, and a task-focused technique is developed for recommending literature articles.
Findings
The experimental results using information systems journal articles show that the proposed method is more effective than the previous coauthorship network-based method over all scenarios examined. The authors further develop a hybrid method that combines the results of content-based and LDA-coauthorship-network-based recommendations. The resulting hybrid method achieves greater or comparable recommendation effectiveness under all scenarios when compared to the content-based method.
Originality/value
This paper makes two contributions. The authors first show that topic model is indeed useful and can be incorporated into the construction of coaurthoship-network to improve literature recommendation. The authors subsequently demonstrate that coauthorship-network-based and content-based recommendations are complementary in their hit article rank distributions, and then devise a hybrid recommendation method to further improve the effectiveness of literature recommendation.
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Jung-Kuei Hsieh, Hung-Chang Chiu, Chih-Ping Wei, HsiuJu Rebecca Yen and Yu-Chun Cheng
– This paper aims to link academic classifications of service innovation with practical activities by firms to detail the essence of service innovation.
Abstract
Purpose
This paper aims to link academic classifications of service innovation with practical activities by firms to detail the essence of service innovation.
Design/methodology/approach
This research employs both qualitative and quantitative analyses. The qualitative study features interviews with senior managers from 590 companies, covering nine industries in Taiwan, to gather practitioners ' perspectives on service innovation. A content analysis details specific forms of service innovation. The quantitative study provides a homogeneity test and two-sample proportions test to examine differences in service innovation perspectives/activities across organizational characteristics.
Findings
The interview data link three types of service innovations to 11 associated elements and 25 labels, derived from 659 potential service innovation incidents (550 new service concepts, 82 new service processes, and 27 new service business models). This study also shows that elements of service innovations vary by company size, service innovation experience, and industry life cycle.
Practical implications
The three types of service innovations enable businesses to benchmark and modify their current service innovation activities. Service managers can use the results of this study to develop their own service innovation strategies and concrete action plans.
Originality/value
This pioneering study links the viewpoints of academics with practical service innovation activities and empirically shows that service innovation is dissimilar, depending on various organization characteristics.
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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…
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.
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Peng Liu, Elia El‐Darzi, Lei Lei, Christos Vasilakis, Panagiotis Chountas and Wei Huang
Purpose – Data preparation plays an important role in data mining as most real life data sets contained missing data. This paper aims to investigate different treatment methods…
Abstract
Purpose – Data preparation plays an important role in data mining as most real life data sets contained missing data. This paper aims to investigate different treatment methods for missing data. Design/methodology/approach – This paper introduces, analyses and compares well‐established treatment methods for missing data and proposes new methods based on naïve Bayesian classifier. These methods have been implemented and compared using a real life geriatric hospital dataset. Findings – In the case where a large proportion of the data is missing and many attributes have missing data, treatment methods based on naïve Bayesian classifier perform very well. Originality/value – This paper proposes an effective missing data treatment method and offers a viable approach to predict inpatient length of stay from a data set with many missing values.
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Xiaopan Wang, Junpeng Guo, Yi Wu and Na Liu
Information asymmetry is an inevitable issue in e-commerce and largely hampers the development of online shopping. The purpose of this paper is to propose a model to investigate…
Abstract
Purpose
Information asymmetry is an inevitable issue in e-commerce and largely hampers the development of online shopping. The purpose of this paper is to propose a model to investigate the emotional content of online customer reviews, which are considered an efficient way to reduce information asymmetry, as a potential signal of product quality. The moderating effects of perceived empathy and cognitive effort are also explored on the basis of signaling theory.
Design/methodology/approach
A laboratory experiment with 120 subjects was used to empirically test the proposed research hypotheses. The subjects were randomly assigned to two treatment groups, with 60 subjects in each group. ANOVA, linear regression and binary logistic regression were used.
Findings
The emotional content of online customer reviews positively influences perceived product quality, which subsequently and positively affects purchase decisions. The emotional content of online customer reviews greatly influences perceived product quality when perceived empathy or cognitive effort is high.
Originality/value
This study is the first to extend extrinsic cues to emotional content on the basis of signaling theory and reveals the important role of emotional content of reviews. Moreover, the mediating effect of perceived product quality and the moderating effect of perceived empathy and cognitive effort illustrate the mechanism of the influence of emotional content on purchase decision. Findings demonstrate the positive signal of emotional content and provide important practical implications for sellers and customers.