DSS IN NUMBERS

. Decision Support Systems (DSS) have evolved in time, influenced by technological and organizational developments. The scientists’ interest for DSS has increased over the years and the use of this type of systems has spread in all domains of activity. The paper presents the results of a literature search, made in September 2013, regarding the Decision Support Systems evolution as it is reflected in three scientific databases ( ScienceDirect , IEEE Xplore Digital Library and ACM Digital Library ). The aim of this research is to present the evolution in time of the published DSS research materials and to test the usefulness and relevance, for the topic searched, of the information provided by the above mentioned databases.


Introduction
In Filip (2008), a DSS is defined as "an anthropocentric, adaptive and evolving information system which is meant to implement the functions of a team of assistants that would otherwise be necessary to help the decision-maker to overcome his/her limits and constraints he / she may encounter when trying to solve complex and complicated decision problems that count". The DSS concept was anticipated by the idealized vision of Licklider (1960) over the "precognitive" man-computer systems, which were meant to "[...] enable man and computers to co-operate on making decisions and control complex situations [...]". According to McCosh (2002), the term was first articulated by M. Scott-Morton in a seminar held in February 1964. As many

Method
The DSS concept, launched before the existence of PCs, and the corresponding research area (Alter 2002) have evolved in a strong relation with the information systems developments and have diversified over the years. The development of the web technologies has radically transformed the design, development, implementation and the deployment of the DSS (Bhargava et al. 2007). At present, the term Decision Support Systems designates a wide class of systems which includes various types of technologies and aims at supporting the decision-making activities.
To evaluate the evolution of the domain, a set of numerical data related to the DSS materials published, are presented in the sequel, since the beginning of the DSS research, the publications with the greatest number of DSS materials and topics/subjects/keywords of the DSS materials, as they are reflected in three relevant scientific databases, in comparison with similar data obtained in 2010. The paper aims to identify if the data provided by the scientific databases analysed are useful for future authors and relevant for the research field.
One particular purpose of this study is to make a comparison between the data obtained in November 2010 and those from September 2013, in order to identify the DSS research evolution during the years, by analysing the numbers of the DSS published materials and a series of related data. The method applied involved several queries on three international research databases: ScienceDirect, IEEE Xplore Digital Library and ACM Digital Library.
The DSS-related search terms that were utilised to obtain a wide perspective on the DSS research field are, in both analyses (2010 and 2013): "decision support system", "decision system", "decision tool", "decision making system" and the plural of these words. These concepts were considered to be the most commonly used by researchers to refer to this type of systems.
Searches were made on all the materials (articles, books, reports, etc.), contained in the selected scientific databases, that included at least one of the above concepts in the title, abstract or keywords. The decision to search the selected terms only within the title, abstract and keywords was made after noticing that general searches (within any field) also returned articles which were not relevant for DSS research area. After all, the list of search terms was selected, so as to surely obtain DSS relevant articles.
Since decision support systems are now viewed as a wide range of specific, but very diversified information systems, many others terms, that are relevant for DSS research area (e.g. data warehousing, OLAP, data mining or business intelligence), were not considered for this research.
The information presented in this paper about publication titles or publication year was obtained by using filtering build-in options of the scientific databases.

Results
To update the results of the search completed on the 12th of November 2010 (Suduc et al. 2010), a new search was made at the beginning of September 2013. The returned results indicate a significantly higher number of published materials registered in the selected scientific data bases, both expressed in absolute values ( Fig. 1) and relative increase ratios (Table 1). Those global results will be refined and commented in the sequel.
The dynamics of the scientific databases content includes not only additions, but also removals. For example, in Science Direct, in 2013, there were fewer articles published before 1970 than in 2010. The results of this comparison indicate that: 1. The DSS research production kept the ascendant trend; 2. In IEEE Xplore Digital Library, the indexing rate of the DSS materials is higher than in Science Direct (unlike 2010, in 2013, the results show that the IEEE Xplore Digital Library line is above the Science Direct line, with a higher number of published materials per year); 3. ACM Digital Library, compared to Science Direct and IEEE Xplore Digital Library, reported a slow decrease of DSS articles over the last three years. This might be caused by a lower indexing rate. The authors of this paper consider that this result has another explanation than a lower interest of scientists in this research area (e.g. a low indexing rate of the ACM Digital Library).

Relevant topics
In 2010, all the three searched scientific databases included a refinement criterion by "topics" (ScienceDirect), "subject" (IEEE Xplore Digital Library) or by "discovered terms" (ACM Digital Library), showing a list of the most frequently encountered topics/subjects/discovered terms. These lists were quite useful in discovering the main research topics in DSS area. A search performed per decades (Suduc et al. 2010) indicated the evolution of scientists' interest on decision support systems, which were quite useful for gaining a wide perspective on DSS evolution in time. Unfortunately, in 2013, only Science Direct still included such an option, the other two databases gave up providing this type of search refinement. In 2010, the several main topics/most used terms identified by the databases were: "decision support", "decision support systems", "DS", "decision making", "expert systems", "group decision support systems", "health care", "neural networks", "supply chain". These identified terms indicate several DSS key terms and also some DSS application fields. Arnott and Pervan (2008), who carried out a long-term project meant to critically analyse the academic field of decision support systems based on the content analysis of 1093 DSS articles published in 14 major journals from 1990 to 2004, published a list of major DSS subfields, such as: "personal decision support systems", "group support systems", "negotiation support systems", "intelligent decision support systems", "knowledge management-based DSS", "data warehousing", "enterprise reporting", "analysis systems". Sub-searches in the databases by these subfields and the main DSS terms/topics/subjects identified in 2010, led to the results presented in Table 2. The order of the searched terms is the occurrence order of these terms, from the most used to the less used.
The results show that the most used terms within the articles in the DSS field are: -"decision-making" (93.65% articles in Science Direct include this term, 26.24% in IEEE Xplore Digital Library and 44.17% in ACM Digital Library);

Numbers of DSS published materials between 2001-2013
Science Direct IEEE Xplore Digital Library ACM Digital Library -"decision support systems" (25,07% articles in Science Direct, 90.09% in IEEE Xplore Digital Library and 59.89% in ACM Digital Library). Other quite often encountered terms are: -"expert systems", that is a very popular DSS thread from about 1965 to the mid-1990s (Power 2007); -"management systems", which is not a surprising issue, since most of decision support systems are meant to support managers; -"health care", that is a very important field where there is a growing interest in the use of DSS (named clinical decision support systems) (Osheroff et al. 2007) which have been shown to improve both patient outcomes and the cost of care (Berner, La Lande 2007). The search of the other terms, such as "group decision support systems", "data warehouse", "business intelligence" and "intelligent decision support systems", within the initial results, although relevant for the DSS research field, didn't return very good results (less than 8% of the total number of DSS materials from the analysed scientific databases). An explanation might be that these terms are categories which are often used in other forms. For example, for "group decision support systems" other terms, such as "group support systems" or "electronic meeting systems", are used. Table 3 presents the first ten publications (journals/books/proceedings) indicated, both in 2010 and in 2013, by the scientific databases, as containing the highest number of DSS research papers. The results show that, comparing with 2010 study results, the top ten publications partially changed in 2013. The least changed is the top ten in ScienceDirect which has 8 publications in common with the one from 2010. The ACM Digital Library top has 6 publications in common and IEEE Xplore Digital Library, 5 publications. Also, it can be noticed that all the numbers obtained in 2013 are higher, compared to the ones obtained in 2010.

Relevant publications
The journal with the highest number of articles is Decision Support System, with 978 articles in ACM Digital Library (the first place in top ten) and 351 articles in ScienceDirect (the third place). The second publication with the highest number of DSS articles indexed in the selected scientific databases is Expert Systems with Applications, with 466 articles indexed in ScienceDirect and 406 in ACM Digital Library. Others publications in top ten reported both by ScienceDirect and ACM Digital Library are: Information and Management, Computers and Industrial Engineering and Environmental Modelling & Software. The fact that two databases returned five common publications in top 10 leads us to the conclusion that these reported journals are really relevant for the DSS research field.

Conclusions
The results presented in this paper indicate, by comparison with similar data previously published in Suduc et al. (2010), the steadily increasing interest in the research area of decision support systems, the research trends over the last decade, some DSS main concepts and Continued Table 3 application domains, the journals and conference proceedings with the highest number of DSS research papers in DSS research field. These data are presented as they are reflected by three scientific databases: ScienceDirect, IEEE Xplore Digital Library and ACM Digital Library and analysed so as to determine their relevance for DSS field.
W. T. Lord Kelvin (1824Kelvin ( -1906, the famous British mathematician, physicist and engineer, firmly stated in its lecture entitled "Electrical Units of Measurements", held on 13 th May 1883, "I often say that when you can measure what you are speaking about and express it in numbers, you know something about it; but when you cannot express it in numbers, your knowledge is of a meagre and unsatisfactory kind" (Shell 1998). However, there are also other opinions about the compulsoriness of expressing the knowledge in numbers. Many centuries ago, Marcus Tullius Cicero (106-48 B.C.), a reputed Roman orator, wisely stated (Cicero 1913): "Non enim numero haec judicantur, sed pondere" ("The number does not matter, the quality does").