An empirical assessment and categorization of journals relevant to DSS research

This paper reports on an objective empirical study of the decision support system literature for the purpose of assessing journals relevant to DSS research efforts. Here, we provide DSS researchers and those who evaluate them an up-to-date picture of the forums available for scholarly discourse and research. We conducted a citation analysis of the Decision Support Systems journal for the years 1985–1993 to obtain a citation base containing over 7,500 citations. The citation base is then used to (1) examine citation trends for books, proceedings, and journals; (2) determine a relative ranking of journals based on total citations, and (3) organize journals into categories. Guidelines are provided for utilizing the categorization.     

Ranking journals in business and management: a statistical analysis of the Harzing data set

Creating rankings of academic journals is an important but contentious issue. It is of especial interest in the U.K. at this time (2007) as we are only one year away from getting the results of the next Research Assessment Exercise (RAE) the importance of which, for U.K. universities, can hardly be overstated. The purpose of this paper is to present a journal ranking for business and management based on a statistical analysis of the Harzing data set which contains 13 rankings. The primary aim of the analysis is two-fold – to investigate relationships between the different rankings, including that between peer rankings and citation behaviour; and to develop a ranking based on four groups that could be useful for the RAE. Looking at the different rankings, the main conclusions are that there is in general a high degree of conformity between them as shown by a principal components analysis. Cluster analysis is used to create four groups of journals relevant to the RAE. The higher groups are found to correspond well with previous studies of top management journals and also gave, unlike them, equal coverage to all the management disciplines. The RAE Business and Management panel have a huge and unenviable task in trying to judge the quality of over 10,000 publications and they will inevitably have to resort to some standard mechanistic procedures to do so. This work will hopefully contribute by producing a ranking based on a statistical analysis of a variety of measures.     

A Citation Analysis of Influences on Collaborative Computing Research

Collaborative computing has emerged as a majorsubject of study within the field of businesscomputing. It is concerned with the use ofcomputers to facilitate or enable the work ofmultiple participants engaged in collaborativeventures. Researchers and educators canbenefit from an analysis that identifiesjournals with greatest impacts on developmentof the collaborative computing subject area. The benefits include an appreciation of the topoutlets for publishing and the leading sourcesfor monitoring development in collaborativecomputing research, plus the most importantreference discipline journals for findingsupport for these developments. This studyemploys a citation analysis methodology todetermine the journals that have had thegreatest influence on multiparticipant,collaborative computing research. Over 19,000citations from four base journals across an8-year period are collected and analyzed.     

Citation analysis and impact factor trends in the Ergonomics Journal List, 1975–2007

The current study sought to investigate and analyze citation‐based trends in the field of human factors and ergonomics over a relatively long period of time. Journals were selected from the Ergonomics Journal List (EJL), originally formulated by Dul and Karwowski in 2004. Data were extracted from the Thomson Reuters Journal Citation Reports via a custom order in 2008. Various bibliometric indicators were examined and analyzed, including total citation counts, cited half‐lives, immediacy indices, and journal impact factors. Overall, the results suggest that, although citation counts have increased in recent years, trends were less clear regarding cited half‐lives and immediacy indices. Impact factors rose over time, however, with individual journals increasing their scores between 200% and 613%, with an overall increase of 416% for the EJL between 1975 and 2007. © 2009 Wiley Periodicals, Inc.     

A computer-aided bibliometric system to generate core article ranked lists in interdisciplinary subjects

Due to the tremendous increase and variations in serial publications, the impact of every peer-reviewed paper on different subjects is varying continually. Domain experts or researchers want to keep track of those latest and highly cited peer-reviewed papers; however they are finding it difficult to update or collect their subject core paper lists regularly and accurately. The evaluation of serial papers for generating and ranking core paper lists on different subjects becomes a very challenging task for scholars or librarians. Therefore, a computer-aided bibliometric system (CABS) was developed to generate a core article ranked list automatically. Four indicators - subject reference cited counts, subject total cited counts, subject reference period impact and subject reference cited history - were proposed to generate a subject core article ranking list. Seven different subjects including E-commerce, Data Mining, Supply Chain, Image Processing, Enterprise Resource Planning, Microarray and Expert Systems were used as samples. The turning point (TP) was proposed to determine the core article area in the paper citation analysis. The TP patterns observed were that all TPs had the same rate for four different subjects. The usage of TP patterns can also be used to verify the experimental results. This study provides experimental evidence to disprove three myths. Myth 1: the top papers on a subject (for instance, the top 10 papers) were all submitted to (S)SCI journals. Myth 2: the highly cited papers (cited counts >4) on interdisciplinary subjects were almost submitted to (S)SCI journals. Myth 3: the articles published in the top journals on a subject would be highly cited.     

Research and trends in the field of e-learning from 2001 to 2005: A content analysis of cognitive studies in selected journals

This paper provided a content analysis of studies in the field of cognition in e-learning that were published in five Social Sciences Citation Index (SSCI) journals (i.e. Computers and Education, British Journal of Educational Technology, Innovations in Education and Teaching International, Educational Technology Research & Development, and Journal of Computer Assisted Learning) from 2001 to 2005. Among the 1027 articles published in these journals from 2001 to 2005, 444 articles were identified as being related to the topic of cognition in e-learning. These articles were cross analyzed by published years, journal, research topic, and citation count. Furthermore, 16 highly-cited articles across different topics were chosen for further analysis according to their research settings, participants, research design types, and research methods. It was found from the analysis of the 444 articles that “Instructional Approaches,” “Learning Environment,” and “Metacognition” were the three most popular research topics, but the analysis of the citation counts suggested that the studies related to “Instructional Approaches,” “Information Processing” and “Motivation” might have a greater impact on subsequent research. Although the use of questionnaires might still be the main method of gathering research data in e-learning cognitive studies, a clear trend was observed that more and more studies were utilizing learners’ log files or online messages as data sources for analysis. The results of the analysis provided insights for educators and researchers into research trends and patterns of cognition in e-learning.     

In search of Europe's information technology leaders: review of methods and empirical evidence

Abstract. Information technology (IT) leaders — companies that successfully exploit IT to achieve business results — generate immense interest among practitioners and academics. From a practitioner's perspective, IT leaders provide benchmarks of leading IT management practices which others may emulate to achieve success. From an academic perspective, IT leaders provide the 'data' for the creation of frameworks and theories of IT management. While US IT leaders are regularly assessed by academics, trade magazines, consultants and benchmarking firms, there has been no Europe-wide assessment of IT leadership. This neglect is detrimental to European IT practitioners and academics who may discover that American IT management practices are not transferrable in the European context. In this article, we analyse the construct, context and statistical validity of six methods for identifying European IT leaders. Based on this analysis, two methods (expert ratings and citation counts) were used to generate a preliminary list of European IT leaders and laggards. While individual experts were reticent about volunteering their ratings, their collective view appears to generate a worthwhile list with high construct validity. Citation counts represent a more accessible process for list generation, with high statistical validity. However, an attempt to correlate expert ratings with a list based on citation counts confirms that the latter has questionable construct validity.     

Using human factor guidelines for developing expert systems

Abstract: Although MIS professionals had predicted that expert systems would improve productivity enormously, and a number of expert system application success stories have been reported, the expert system revolution has not yet happened. Moreover, there have been many cases, less well publicised, where expert systems have failed. Most problems concerning expert systems failure stem from non-technical issues such as cognitive and psychological problems, rather than such purely technical issues as an inference engine and an expert system shell. Here, the major reasons for expert systems failure and the need to consider human factors are discussed. We then propose human factor principles that can help designers handle most of these non-technical problems and many technical ones elegantly, improving the performance and acceptance of expert systems. Finally, some human factor guidelines for expert systems are presented so that these considerations may be incorporated into expert systems development in a clear and comprehensible manner.     

Thematic orientation of the ISJ within a semantic space of IS research

This study examines research published in the first 24 years of Information Systems Journal's (ISJ) publication history using a thematic space of all information systems (IS) research as the backdrop. To that end, abstracts from all contributing articles published in eight prominent IS journals in the period 1991–2014 were analysed to extract a latent semantic space of five broad research areas. A two‐dimensional projection of the results was used to create a two‐by‐two map, where one dimension represents the European vs. North American style of IS research and another dimension represents a micro vs. macro level of IS research. The ISJ is positioned in the ‘micro and European school’ quadrant. Over the course of the journal's first 24 years, research in the ISJ started with a relative focus on the IT artefact and IS development and gradually moved towards a more balanced position that includes a considerable amount of research on IT for teamwork and collaboration, as well as on IT and individuals.     

An expert system for the identification of environmental impact based on a geographic information system

The identification and assessment of the environmental impacts of engineering projects is an essential step in studies on environmental impact (IES). There are methods that allow both tasks to be performed and methods that allow each of them to be carried out separately. Normally, traditional methods are used to identify and evaluate environmental impacts, such as matrices, cause-effect network diagrams or check lists. Here we report the configuration of an expert system as a tool that allows environmental impacts to be identified. The expert system is based on a geographic information system to configure the knowledge base, the inference motor and the user interface. The knowledge base comprises declarative knowledge (structured in an alphanumeric and spatial database from official cartographic information) and procedural knowledge (via heuristic rules that superimpose project actions over environmental factors). We then describe the application of the expert system to the study of the environmental impact of the R-3 motorway in the Community of Madrid, Spain. As results, running the expert system allows the identification of environmental impacts on environmental factors defined at the 1:5000 and 1:25000 cartographic scales. Finally, analysis of the results or conclusions allows the validity of the use of graphic expert systems to be compared for the identification of environmental impacts.     

Should we be surprised at expert system success ?

Abstract. Expert systems proliferate. They are now a usable and used tool in a variety of organizations. However, little research has been undertaken on the quantification of success or failure of expert system projects. By and large the only test carried out for expert system validation is one of comparison of the conclusions of the system with those of an expert or team of experts. While questioning the validity, this paper accepts that this method is being used and analyses whether or not the results obtained from this type of test should be a surprise. That is, what sort of results should be expected and to what extent do the reported ones live up to these expectations? Earlier research from the field of human information processing casts doubts on the success claims made for current expert systems. The implications of this research are then analysed in order to explore the possible redeeming features of expert systems which are not taken into account in such comparisons. The use of linear models as comparators for expert systems may prove beneficial.     

POMME: a computer-based consultation system for apple orchard management using Prolog

Abstract: Direct dissemination of expert knowledge to agricultural producers through computer programs will increase product quality as well as the profit margin. The construction of an expert system, called POMME, to help farmers manage apple orchards is reported here. The system provides advice regarding specific pest management, treatment of winter injuries, drought control and general pesticide selection. A sample interaction is provided, and the knowledge structures employed in the construction of the system are explained. A model of the apple scab disease cycle is incorporated into POMME to give the system a more fundamental reasoning capability than available from typical rule-based systems.     

Are European IS Journals under-rated? An answer based on citation analysis

A concern that the quality of European IS journals has been under-rated by existing studies was recently addressed in the IS community. In this study, an objective method based on a Citation Analysis was employed to re-examine the quality of four established European IS journals as compared to 11 other well-recognized IS journals. Extensive citation data were collected to derive eight indices as the measures of journal quality. Our research results indicate that the quality of the four leading European IS journals is quite comparable to that of other well-known IS journals reported in prior studies.     

Expert systems and organizations: Predictions and evidence

Expert systems have recently become more commonplace in the United States workplace. Although little is known about the impacts of expert systems in the workplace, many predictions about the nature of these impacts, and the effects of expert systems generally, have been made. We examine some of these predictions, noting that they are very similar to predictions made about the effects of conventional data processing in organizations. We examine how most of the predictions about data processing have been shown to be unfounded, based on empirical research. We also show, using the limited empirical evidence available relating to expert systems and their organizational effects, that most of the predictions made about them are also unfounded.     

Knowledge engineering revisited

About six years ago a paper on Knowledge Engineering was published in this Journal. This paper attempts to extend and elaborate on the ideas and concepts discussed earlier. Four major problems are addressed: Preservation of knowledge, proliferation of knowledge, dissemination of knowledge, and application of knowledge. The design principles for both rule-based expert systems and pattern-directed expert systems are discussed and compared.     

专家系统研究现状及展望*

总结了自2000年以来专家系统在国内外的发展及应用情况,并根据知识表示方法的不同,对专家系统在各个领域的应用进行分类。结果显示：近五年来,伴随网络时代的到来及蓬勃发展,国内外专家系统发展迅速,一些新技术已经应用于专家系统,尤其是XML和W eb技术的应用,为专家系统的研究注入新的活力。同时对目前专家系统存在的一些问题以及今后的研究和发展进行了探讨。     

Minimizing maintenance anomalies in expert systems

Expert systems are emerging as a powerful technology for solving many problems previously requiring human experts. However, maintenance has been identified as a major difficulty in expert system implementations. Surprisingly, the problem of maintenance has only recently begun to receive attention in expert systems research, though it has long been an issue in databases. Databases are in a constant state of change, and the prevention of maintenance anomalies is essential. As similar maintenance operations are performed on rule bases, this paper investigates techniques to avoid maintenance anomalies in expert system rule bases. The result is an expert system rule base structure that is appropriate for volatile production use. In addition to lower maintenance demands, this approach favorably impacts on verification, computational efficiency, and storage requirements.     

Building a financial diagnosis system based on fuzzy logic production system

The purpose of this study is to build a financial expert system based on fuzzy theory and Fuzzy LOgic Production System (FLOPS), which is an expert tool for processing the ambiguity. The study consists if four parts. For the first part, the basic features of expert systems are presented. For the second part, fizzy concepts and the evaluation of classical expert systems to fuzzy expert systems will be presented. For the third part, the expert system shell (FLOPS) used in this study will be described. For the last part, it will be presented the financial diagnosis system, developed by using the Wall's seven ratios, traditional seven ratios and also 34 ratios selected by a financial expert. After analyzing and investigating these three kinds of methods, financial diagnosis system will be developed as a fuzzy expen system which used a membership function based on averages and standard deviation. At the last step, the new approach will be tried by increasing the fuzzy sets for five membership functions. Some practical examples will be given. Throughout the paper, the way of building a financial diagnosis system based on fuzzy expert system is stressed.     

Detecting academic experts by topic-sensitive link analysis

The problem of academic expert finding is concerned with finding the experts on a named research field. It has many real-world applications and has recently attracted much attention. However, the existing methods are not versatile and suitable for the special needs from academic areas where the co-authorship and the citation relation play important roles in judging researchers’ achievements. In this paper, we propose and develop a flexible data schema and a topic-sensitive co-pagerank algorithmcombined with a topic model for solving this problem. The main idea is to measure the authors’ authorities by considering topic bias based on their social networks and citation networks, and then, recommending expert candidates for the questions. To infer the association between authors and topics, we draw a probability model from the latent Dirichlet allocation (LDA) model. We further propose several techniques such as reasoning the interested topics of the query and integrating ranking metrics to order the practices. Our experiments show that the proposed strategies are all effective to improve the retrieval accuracy.