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For those who plan research funds and assess the research performance from the funds, it is necessary to overcome the limitations of the conventional classification of evaluated papers published by the research funds. Besides, they need to promote the objective, fair clustering of papers, and analysis of research performance. Therefore, the purpose of this paper is to find the optimum clustering algorithm using the MATLAB tools by comparing the performances of and the hybrid particle swarm optimization algorithms using the particle swarm optimization (PSO) algorithm and the conventional K-means clustering method.

The clustering analysis experiment for each of the three fields of study – health and medicine, physics, and chemistry – used the following three algorithms: “K-means+Simulated annealing (SA)+Adjustment of parameters+PSO” (KASA-PSO clustering), “K-means+SA+PSO” clustering, “K-means+PSO” clustering.

The clustering analyses of all the three fields showed that KASA-PSO is the best method for the minimization of fitness value. Furthermore, this study administered the surveys intended for the “performance measurement of decision-making process” with 13 members of the research fund organization to compare the group clustering by the clustering analysis method of KASA-PSO algorithm and the group clustering by research funds. The results statistically demonstrated that the group clustering by the clustering analysis method of KASA-PSO algorithm was better than the group clustering by research funds.

This study examined the impact of bibliometric indicators on research impact of papers. The results showed that research period, the number of authors, and the number of participating researchers had positive effects on the impact factor (IF) of the papers; the IF that indicates the qualitative level of papers had a positive effect on the primary times cited; and the primary times cited had a positive effect on the secondary times cited. Furthermore, this study clearly showed the decision quality perceived by those who are working for the research fund organization.

There are still too few studies that assess the research project evaluation mechanisms and its effectiveness perceived by the research fund managers. To fill the research void like this, this study aims to propose PSO and successfully proves validity of the proposed approach.

This paper aims to intend to study the effect of movie production efficiency on eWOM and the moderating effect of efficiency on the relationship between eWOM and review helpfulness for movies.

Production efficiency is suggested by comparing the power of movie resources (e.g. the power of actors, directors, distributors, production companies) against box-office revenue through a data envelopment analysis (DEA).

The study results present that the number of reviews, the number of reviews by reviewers and review extremity are greater in an efficient subsample than in an inefficient subsample. For efficient movies, the review depth and the strength of the sentiments in the reviews are more positively related to review helpfulness. The prediction results for review helpfulness using the k-nearest neighbor method and automatic neural networks show that the efficient subsample provides a significantly lower prediction error rate than the inefficient subsample. The study results can support the effective facilitation of helpful online movie reviews.

As the numbers of online reviews are increasingly used to provide purchase decision support, it becomes crucial to understand which attributes represent average helpful reviews for movies. While previous studies have examined eWOM (online word-of-mouth) variables as predictors of helpfulness on movie websites, the role of the production efficiency of movies has not been examined considering the relationship between eWOM and review helpfulness for movies.

While a number of studies examined the eWOM (online word-of-mouth) factors affecting box office, the studies on the impact of review helpfulness on box office are lacking. The purpose of this paper is to fill the void in previous studies and further extend prior work regarding eWOM and box office. In order to explain the interaction effect of helpfulness with other variables on product sales, this study posits that review characteristics such as number of reviews, review rating, review length interact with review helpfulness to have an influence on box office. Further, as the studies that have examined whether eWOM factors are significant in box office performances for the international markets other than US are lacking, this study is targeting Korean markets to validate the effect of eWOM on box office.

This study used publicly available data from www.naver.com to build a sample of online review data concerning box office. The final sample of the study included 2090 movies.

The results indicated that in cases when the review is helpful, the number of reviews and review length are more greatly influencing box office. Review rating, review extremity, and helpfulness for reviewer are important determinants for review helpfulness.

Managers can concentrate on the review rating and review extremity of online customer reviews in the design of online sites for movies. The design of user review systems can follow the direction that promotes more helpfulness for online user reviews based on an enhanced understanding of what drives helpfulness voting.

Given that previous studies on the effect of review helpfulness on box office are lacking, it contributes to eWOM literature by investigating the impact of review helpfulness on box office revenue.

The purpose of this paper is to suggest important determinants for helpfulness from the reviews’ product data, review characteristics, and textual characteristics, and identify the more crucial factors among these determinants by using statistical methods. Furthermore, this study intends to propose a classification-based review recommender using a decision tree (CRDT) that uses a decision tree to identify and recommend reviews that have a high level of helpfulness.

This study used publicly available data from Amazon.com to construct measures of determinants and helpfulness. To examine this, the authors collected data about economic transactions on Amazon.com and analyzed the associated review system. The final sample included 10,000 reviews composed of 4,799 helpful and 5,201 not helpful reviews.

The study selected more crucial determinants from a comprehensive group of product, reviewer, and textual characteristics through using a t-test and logistics regression. The five important variables found to be significant in both t-test and logistic regression analysis were the total number of reviews for the product, the reviewer’s history macro, the reviewer’s rank, the disclosure of the reviewer’s name, and the length of the review in words. The decision tree method produced decision rules for determining helpfulness from the value of the product data, review characteristics, and textual characteristics. The prediction accuracy of CRDT was better than that of the k-nearest neighbor (kNN) method and linear multivariate discriminant analysis in terms of prediction error. CRDT can suggest better determinants that have a greater effect on the degree of helpfulness.

The important factors suggested as affecting review helpfulness should be considered in the design of websites, as online retail sites with more helpful reviews can provide a greater potential value to customers. The results of the study suggest managers and marketers better understand customers’ review and increase the value to customers by proving enhanced diagnosticity to consumers.

This study is different from previous studies in that it investigated the holistic aspect of determinants, that is, product, review, and textual characteristics for classifying helpful reviews, and selected more crucial determinants from a comprehensive group of product, reviewer, and textual characteristics by using a t-test and logistics regression. This study utilized a decision tree, which has rarely been used in predicting review helpfulness, to provide rules for identifying helpful online reviews.

Although there are a number of studies on the factors affecting the continuance usage intention for social network services (SNS), the studies on the integrated model encompassing SNS qualities (information, system, and service quality, and hedonic value, which are gratifications for SNS usage), flow, relationship quality (which are trust and satisfaction), and continuance intention are almost non-existent. Based on Bagozzi’s self-regulation framework, the IS success model, uses and gratification theory, and flow theory, the purpose of this paper is to examine the qualities and hedonic value of SNS, which have an influence on flow experience and relationship quality which are posited to affect the continuance usage intention.

This study used an e-mail survey method to collect 460 questionnaires for the final sample. The sample of the study includes college students or job workers who have experience in using SNS. Various user categories in terms of gender, school degree, occupation, usage years, and daily time of usage were included.

The study results show that system, service quality, and hedonic value have an impact on flow experience, information and service quality, and hedonic value influence the relationship quality of SNS. The flow experience and relationship quality while using SNS affect the continuance usage intention of SNS. This results show that the consideration of various SNS qualities, hedonic value, flow experience, and relationship quality is necessary to actively explore the factors for continuance usage intention for SNS.

IS managers trying to understand reuse intent can use surveys on information, system, and service quality, and hedonic value. Practitioners should constantly incorporate and develop various activities or useful applications to allow people to reach out to each other, to reinforce users’ attention, interaction, and increase social connections, trust, satisfaction, and further intensify users’ intention to use, increasing SNS value. The findings explain a mechanism through which SNS users’ continuance intention is built. Understanding this mechanism provides valuable information for practitioners to understand the qualities driving SNS users’ intention to revisit SNS.

This study sheds light on the existing literature on website usage that focuses on the design qualities as this paper has combined website quality perspective, i.e., information, system, and service quality, and hedonic value, and the flow and relationship perspective to investigate how these constructs would affect users’ intention to continuously use SNS. On the basis of four theories, Bagozzi’s self-regulation framework, IS success model, users and gratification theory, and flow theory, this study extended the previous studies on SNS by adding information, system, and service quality, hedonic value, flow and relationship quality as second-order constructs affecting continuance intention.

This study aims to analyze the relationship between KM infrastructures, knowledge process capabilities, creative organizational learning, and organizational performance. The primary research focus is on the relationships between the KM infrastructure, which includes cultural, structural, management, and technology related factors, and the knowledge process capability by elaborating on the significance of knowledge processes as the determinants of organizational performance.

The unit of analysis is a company that has adopted a KMS. A mail survey was used to collect the data and an internet‐based survey was also used to provide more convenience in the response. The response sample included 120 responses. The structural relations among variables were tested using the partial least squares (PLS) method.

The results of this study indicate that collaboration, learning culture, top management support, and IT support affect the knowledge process capabilities. Knowledge process capabilities and creative organizational learning in turn mediate the relationship between KM infrastructure and organizational performance, which demonstrate the relevance of KM infrastructure for organizational performance.

Previous studies on KM have been fragmented in that they have explained some aspects of KM performance but have not provided a holistic view of a KM performance framework. Using a holistic view of the KM performance framework, this study has provided insights to KM for researchers because it explains the integrated aspects of KM performance by examining the relationships between the KM infrastructure, knowledge process capabilities, and organizational outcomes.

The purpose of this paper is to compare the web‐based tax filing systems of Turkey and South Korea. The comparison is based on user satisfaction which has parameters such as ease of work, adequacy of the amount of information, display speed, convenience to life, job productivity, and help service.

The tax filing systems are presented along with a background of such systems and their usability parameters. The survey instrument that has been prepared for gauging user satisfaction was applied to the users in both countries. The statistical analyses of the results are performed through t‐test and stepwise regression.

The study shows that users in the two countries felt differently in such factors as ease of work, adequacy of the amount of information, display speed, convenience to life, job productivity, and help service. Although Turkey has a complex tax system Turkish users did not find the tax filing system difficult to use and that may be attributable to the fact that they are accounting professionals who frequently use the system.

Electronic tax filing is an important e‐government application that has become increasingly common all over the world. Beyond the usual benefits of e‐government such as reducing transaction costs and providing convenience, electronic tax filing systems are particularly useful for governments to avoid tax evasion and errors. Although, by definition, web‐based tax filing systems of different countries have to be different, universal design parameters of each system and the resulting user satisfaction levels may provide guidelines for new systems.

Unlike other types of information systems, which have been comparatively analyzed in the context of more than one country, this is not applicable to e‐government systems. To the authors' knowledge the present article is the first attempt to compare and analyze two countries' different e‐government systems.

The purpose of this study is to offer the bibliometric analysis of the Journal of Knowledge Management (JKM) to understand how the literature has developed over time.

This study used bibliometric approaches to analyze a sample of 669 studies from 1997 to 2021. This study focused on performance analysis and scientific mapping of articles using the R package.

The results indicate that the number of publications during the period has significantly increased which shows a growing interest of researchers in the JKM. This study highlights new emerging themes such as change management, change readiness, product innovation and digital libraries which uncover exciting avenues for new research opportunities. USA and UK were the most productive countries in terms of the number of citations followed by few European countries including Spain, Finland, Germany and Sweden. However, it is worth noting that India was the most productive country in the emerging economies.

This study will act as a guide for researchers of various fields to evaluate the development of scientific publications in a particular theme over time, especially for those who are in the field of knowledge management (KM).

This study aims to accomplish the systematic bibliometric analysis of the JKM for more than two decades, providing useful insights into the key developments in the field of KM. This study is more rigorous and comprehensive in terms of the analytical techniques used.

The purpose of this paper is to empirically test the role of knowledge management system (KMS) on the performance of students in higher educational institutions (HEIs).

Building on the extensive review of literature, the authors explored the factors of KMS to arrive at the conceptual model which was then validated using structural equation modeling. For the quantitative analysis, data were collected from undergraduate students using questionnaires distributed both through online and offline modes.

Empirical evidence supports the view that KMS have a direct and significant impact on the student performance (SP) in HEIs.

The data are limited to 311 undergraduate students from the University of Delhi, India.

With the onset of national rankings framework like NAAC (National Assessment and Accreditation Council), NIRF (National Institutional Ranking Framework) and the attempt to achieve global recognition in THE (Times Higher Education), Quacquarelli Symonds and other world university rankings, the HEIs are trying hard to improve their performance comprehensively. In such a scenario, this paper provides insights into how HEIs can enhance performance of its students by harnessing KMS.

The current paper empirically validates the effect of KMS on the performance of students in an educational institution. While the impact of KMS on performance is measured empirically in corporations, such studies are scanty in academic centers. Moreover, while measuring the performance in HEIs using KM, the focus on ranking parameters has never been there. Such an orientation is essential as the rankings are getting wide acceptance from a global audience.

Auditors provide high assurance to executives amidst information and database risk. A framework is provided for auditors within cyber entities. The categories of e‐commerce, business‐to‐business, business‐to‐customers and mobile commerce use different core technologies. The common factor remains unchanged from the auditors' perception, i.e. risk and its potential to harm the integrity and accuracy of the data and decisions based thereon. E‐commerce requires audit to identify risks and show their impact on the information system. The American Institute of CPAs and Canadian Institute of Chartered Accountants jointly offer seals of assurance at Web and system levels. The limitations of these certifications are important for an auditor since they are set by these accounting bodies. The role and functions of an auditor are beyond those of the assurance approval auditors. Organizational decision‐making processes depend on segments of information bases, whereas these assurance providers audit a limited amount related to their interest.