Computer Science Information Systems Research Articles

Bibliometrics of Brand-related Social Media Content

This study presents bibliometric analysis of brand-related content on social media. By filtering by topic in the WOS database, publications between 2000 and 2021 on two types of social media content, firm-generated content (FGC) and user-generated content (UGC), are examined. For FGC, 47 articles in the database are reviewed, while 3502 articles are included in the analysis for UGC. The research results found that while the FGC studies of the researchers mainly were “Business,” the UGC articles were “Computer Science Information Systems” predominantly. In addition, the journal that gives the most place to studies with the FGC topic is the Journal of Marketing. On the other hand, the journals New Media & Society and Sustainability published 46 articles each for UGC studies. As a result of the co-word network analysis, although there were five themes in the map of the FGC articles, more than ten themes were found in the map of the UGC articles. The research results are expected to shed light on researchers who will work on brand-related social media content in the following years.

Is the Concept of Industry 4.0 Still Interesting for Scientists due to the Emergence of Industry 5.0? Bibliometric Analysis

Abstract Research purpose. Through Industry 4.0, also referred to as the fourth industrial revolution, new technologies or traditional production resources have been transformed into intelligent objects enhanced by the possibility of identification, scanning, and networking. In recent years, the concept of Industry 5.0 has already started to be discussed. However, is Industry 4.0 an uninteresting or sufficiently researched topic for scientists? The main aim of the scientific article is to perform a bibliometric analysis of the Industry 4.0 issue. The aim was supported by six research questions that reflect the publication trend in the years 2012–2022, the most publishing countries, the most used keywords, the Web of Science category, and authors and publishers. Design / Methodology / Approach. The data was obtained from the renowned Web of Science database. The monitored period was 2012–2022 for Industry 4.0 and 2016-2022 for Industry 5.0. The year 2023 was excluded from the analysis, as the year 2023 is not finished. The total number of publications that were used in the bibliometric analysis was 20,151 (I4.0) and 293 (I5.0). VOSviewer and MS Excel were used for graphical data processing. Findings. The oldest publication dedicated to Industry 4.0 in the Web of Science database dates back to 2012. The most scientific articles were seen in 2021, namely 4,326 (I4.0) and 201 in 2022 about I5.0. In 2022, 3848 publications were published. In addition, authors from Germany (2,450), Italy (2,318), China (1,515), and the USA (1,220) address the issue of Industry 4.0. All the countries of the Visegrad Group, Poland (859), the Czech Republic (859), Slovakia (539), and Hungary (282) are most concerned with this problem. If the publications are divided into categories according to the Web of Science database, most of them are included in the categories Engineering Industrial, Engineering Manufacturing, Engineering Electrical Electronic, Computer Science Theory Methods, or Computer Science Information Systems. Publications on Industry 4.0 are published mainly by publishers such as IEEE, Elsevier, Springer, and MDPI. The authors who are most devoted to the mentioned issue are Popkova, Martinek, Rauch, Bogoviz, Silva, and Xu. Originality / Value / Practical implications. The added value of the scientific article is the summarisation of theoretical starting points from the field of Industry 4.0 and Industry 5.0. Likewise, the article is original from the point of view of conducting a bibliometric analysis, focused on the development of the number of publications, the authors who are most devoted to the given topic, the most commonly used keywords, or countries that focus on Industry 4.0 and Industry 5.0 issues the most. The originality of the article also lies in the mapping of the publications of the monitored issue for the entire previous year, 2022.

User Experience: A Bibliometric Review of the Literature

User experience is a well-discussed topic in the field of human–computer interaction. To describe the status of research on this topic, a bibliometric analysis of publications concerning user experience from 2011 to 2021 was conducted using the Web of Science database. The main functions of Derwent Data Analyzer software include data cleaning, mining, and visualization. The historical trends of the year, leading countries, leading institutions, major contributors, and leading research fields and journals were investigated, and a keyword analysis of the highly cited literature was performed. The key findings are as follows. The United States, China, and Britain are the three most productive countries. Tsinghua University in China is the most productive organization, and Sungkyunkwan University in South Korea has the highest average citations per publication. User experience has attracted the attention of numerous scholars in 204 research fields, and computer science information systems is the main field. “Usability,” “virtual reality,” “human–computer interaction,” and “augmented reality” are the most used keywords. A recent trend is the focus on molecular biology.

A comparison of journal similarity across six disciplines using citing discipline analysis

Abstract A similarity comparison is made between 120 journals from five allied Web of Science disciplines (Communication, Computer Science-Information Systems, Education & Educational Research, Information Science & Library Science, Management) and a more distant discipline (Geology) across three time periods using a novel method called citing discipline analysis that relies on the frequency distribution of Web of Science Research Areas for citing articles. Similarities among journals are evaluated using multidimensional scaling with hierarchical cluster analysis and Principal Component Analysis. The resulting visualizations and groupings reveal clusters that align with the discipline assignments for the journals for four of the six disciplines, but also greater overlaps among some journals for two of the disciplines or categorizations that do not necessarily align with their assigned disciplines. Some journals categorized into a single given discipline were found to be more closely aligned with other disciplines and some journals assigned to multiple disciplines more closely aligned with only one of the assigned disciplines. The proposed method offers a complementary way to more traditional methods such as journal co-citation analysis to compare journal similarity using data that are readily available through Web of Science.

A Bibliometric Analysis of Electronic Commerce Research from 1996 to 2012

This study identified 19,831 publications to explore global trends of electronic commerce research during 1996-2012, based on all the subject categories of the SCIE and SSCI. A few significant global trends of EC research were revealed. First, proceedings papers and journal articles were the primary document types, contributing 12,200 and 6,707 publications respectively. Journal articles showed stable upward trends from 1996 to 2012. Second, the top three conferences contributed a 10.6% share of total proceedings papers and the top 20 journals published a 31.1% share of total journal articles. Third, “Computer Science Information Systems”, “Business” and “Computer Science Theory Methods” were the top three most popular subject categories.

Best-in-class and strategic benchmarking of scientific subject categories of Web of Science in 2010

Here we show a novel technique for comparing subject categories, where the prestige of academic journals in each category is represented statistically by an impact-factor histogram. For each subject category we compute the probability of occurrence of scholarly journals with impact factor in different intervals. Here impact factor is measured with Thomson Reuters Impact Factor, Eigenfactor Score, and Immediacy Index. Assuming the probabilities associated with a pair of subject categories our objective is to measure the degree of dissimilarity between them. To do so, we use an axiomatic characterization for predicting dissimilarity between subject categories. The scientific subject categories of Web of Science in 2010 were used to test the proposed approach for benchmarking Cell Biology and Computer Science Information Systems with the rest as two case studies. The former is best-in-class benchmarking that involves studying the leading competitor category; the latter is strategic benchmarking that involves observing how other scientific subject categories compete.

Teaching Introductory Programming to IS Students: Java Problems and Pitfalls

Introduction Like many things in life, first impression matters, and programming is no exception. The importance of a properly constructed first course in programming cannot be overstated. Such a course leaves students with good programming habits, the ability to learn on their own, and a favorable impression of programming as a profession. A poor experience may result in a get attitude, bad programming habits, and could lead to a change in majors. Ala-Mutka Uimonen, and Jarvinen (2004) assessed programming style as a function of modularity, typography, clarity, independence, effectiveness, and reliability, whereas Reddy (2000) defines style constructs specific to the Java language. Instilling in students these habits and providing them with an enjoyable first experience in programming is important. Since 2001, enrollment in the course Introduction to Business Programming has shrunk by 50% at my institution. This combined with the 50% attrition rate of students who enter Introduction to Business Programming and of those who complete the course Intermediate Business Programming has made the task of determining the factors that lead to success (or failure) in learning to program all the more important. Because of this our department is reviewing its curriculum, the technology used in courses, and recruiting strategies. Part of this assessment is determining the proper amount of emphasis to place on the programming skills taught to and expected of our graduates and the proper way to teach these skills. During the boom of Computer Science/Information Systems (CS/IS) in the 1990's the loss of students to other disciplines was not a major concern. These students were just written off as not having an aptitude for programming. Nevertheless, this philosophy will change owing to shrinking enrollments in CS/IS fields (Zweben & Aspray, 2004). Hensel (1998) foretold of shrinking enrollment, predicting that enrollment would drop as a result of a decline in college age students, poor preparation for technical classes (leading to failures and reluctance to enroll), and changing interests in students. This added to fears of outsourcing, the dotcom bust, and the slow down in hiring after Y2K conversions have kept students away from CS/IS. Indeed, CS/IS faculty members have little control of national birthrates and the hiring practices of corporations, but we can look for ways to attract more students and retain the ones we now have. This paper examines the impact the use of the Java programming language has had on the way our students learn to program and the success they achieve. The first section provides some background on why Java was selected as the programming language in our program. This is followed by an enumeration of the features and characteristics of Java that have presented particular problems to our students and a review of paradigms and tools used by other educators to overcome such problems. The structure for the Introduction to Business Programming course is then described along with assessment of outcomes. The paper concludes with a discussion of lessons learned and the results achieved. The Move to Java Teaching programming courses to Information Systems (IS) students in the College of Business has much in common with teaching Computer Science (CS) students but there are some differences in student background and prerequisite courses. Unlike CS students, IS students are generally only required to have a semester of statistics and a semester of business calculus to graduate. More often than not, these courses are put off to their senior years. Therefore the mathematical background of IS students consists of what they may or may not have learned in high school and what they may or may not remember of their required learning. In addition, a typical IS major only takes 20-30 credits of computer related courses whereas the CS major is required by ABET (Accreditation Board for Engineering and Technology) standards to have 42 or more hours of required CS study. …