Higher Education Decision Making And Decision Support Systems - WSEAS
WSEAS TRANSACTIONS on ADVANCES in ENGINEERING EDUCATIONVasile Paul Bresfelean, Nicolae GhisoiuHigher Education Decision Makingand Decision Support SystemsVASILE PAUL BRESFELEAN, NICOLAE GHISOIUBusiness Information Systems Department,Faculty of Economics and Business Administration,Babeş-Bolyai UniversityStr. Teodor Mihali, Nr. 58-60 400591, , nicolae.ghisoiu@econ.ubbcluj.roAbstract: - The authors illustrate several issues in decision support and decision support systems (DSS), state of the artresearch in these fields, and also their own studies in designing a higher education DSS. The final section contains ourcontribution in outlining the modules of the DSS, involving the present systems and databases of FSEGA and UBB,results and activities belonging to FSEGA students, teaching and research staff, to assist decisions for all the actorsimplicated in the processes, in various specific situations.Key-Words: - decision support, decision support systems (DSS), higher education institutions, Information andCommunication Technologies (ICT).the larger uncertainty from exposure to a further numberof competitors. Higher education institutions, like theorganizations from economic areas, are confronted latelywith increasing pressures to improve the quality ofeducation processes and management, but with a numberof features specific to academics. There should be takeninto consideration the university autonomy, even infinancial issues or other forms according to public andacademic responsibilities. Therefore, universities seek toapply more the accumulated data, invest more resourcesin tools that allow them to collect and manageinformation directly, and involve teaching staff, studentsand local community in decision-making processes.The present paper is an extension of our latest studiesand publications [5]. We bring in several issues in thefield of decision support and decision support systems(DSS), and state of the art research in these fields. In thelast part of the paper we present our contribution indesigning a DSS for higher education environments,based on the present situation of The Faculty ofEconomics and Business Administration (FSEGA) atBabes-Bolyai University of Cluj-Napoca (UBB).1 IntroductionThe mission of a higher education institution is toprepare personnel to the highest level of knowledge atthat time in history [23]. Universities should not be justa neutral setting, but the place in which to create andshare knowledge, an innovative and prolific actor ininteraction with the economic, administrative, andcultural environment. The support received by thedecision takers, whether they are top executives,managers placed on different levels (rector, dean etc.)advisers and other assistants lies primarily in helpingthem to overcome the limits of knowledge regarding theproblem, possible alternatives for action and methods ofanalysis used in the decision [8].The decision-making process in an organization orbusiness should be planned and resolved in acomprehensive, reliable, and transparent manner [32].Managers prepared with information about their relevantorganizational cultures, interrelated with the knowledgetransfer, can amend their knowledge managementstrategies to make their organizations more efficient, andto evaluate and maneuver ICT (Information andCommunication Technologies) in effective strategies.Quality and well-timed decision-making is fundamentalin the success of any organization. They necessitatesuccessful implementation of decision support tools toadequately inform the decision process, but also otherdesirable characteristics such as imagination andcreativity [6].A firm’s capability to take good decisions is mostlyimportant in the face of growing global competition, andISSN: 1790-19792 Decision support and DSS issuesIn the last decades, widespread researchers’ efforts havebeen made on understanding and formalizing the activityof decision making all domains. One of the firstclassifications of the systems qualified to support theactivity was as follows [22]: information retrieval systems - are computerbased systems to capture, manipulate, retrieve and43Issue 2, Volume 7, February 2010
WSEAS TRANSACTIONS on ADVANCES in ENGINEERING EDUCATIONdesigned to help users which rely on knowledge, in arange of decision-making positions to solve theencountered problems that matter for the organization’sprosperity [13]. An important point in most common inall DSS definitions is that decision support systemsliterally refer to ‘applications that are designed tosupport, not replace, decision making’ [4].Up to date classifications of DSS [27] are based onthe leading technology that determines thecharacteristics of the decision-making: communications-driven DSS data-driven DSS document-driven DSS knowledge-driven DSS model-driven DSS.Some DSS are hybrid systems driven by more thanone major component. Kacprzyk & Zadrozny (2007)mention also the Group DSS and Web based andInterorganizational DSS. They can be briefly describedin the next table [20]:transmit organized data necessary to solve a professionaltask according to detailed transactions defined by a user; decision support systems (DSS) – areknowledge-based information systems to capture, handleand analyze information which affects or is intended toaffect decision making performed by people in the scopeof a professional task appointed by a user; expert systems - are knowledge-based systemsto be used instead of or together with a human operatorto make decisions in the framework of a professionaltask with explanations for users.Recent analysis on decision support and expertsystems has shifted from considering these as solelyanalytical tools for assessing best decision options toseeing them as a more comprehensive environment forsupporting efficient information processing based on asuperior understanding of the problem context [17]. DSSembrace various definitions [13], but it is largelyconsidered that they are built to assist decision processesand help to identify and resolve problems [6]. DSSsymbolize a specific class of information systemsDATA DRIVEN DSSCOMMUNICATIONSDRIVEN DSSVasile Paul Bresfelean, Nicolae Ghisoiuemphasize access to and manipulation of internal company data andsometimes external data, and may be based – from the low to high level – firston simple file systems with query and retrieval tools, then data warehouses,and finally with On-line Analytical Processing (OLAP) or data mining tools.use network and communications technologies to facilitate collaboration andcommunication.GROUP GDSSare interactive, computer-based systems that facilitate solution of unstructuredproblems by a set of decision-makers working together as a group.DOCUMENT DRIVENDSSintegrate a variety of storage and processing technologies for a completedocument retrieval and analysis; documents may contain numbers, text, andmultimedia.emphasize access to and manipulation of a model, e.g., statistical, financial,optimization, and/or simulation; use data and parameters, but are not usuallydata intensive.MODEL DRIVENDSSKNOWLEDGE DRIVENDSSare interactive systems with specialized problem- solving expertise consisting ofknowledge about a particular domain, understanding of problems within thatdomain, and “skill” at solving some of these problems.WEB-BASED DSSare computerized system that deliver decision support related informationand/or tools to a manager/analyst using a “thin-client” Web browser(Explorer); TCP/IP protocol, etc.Table 1. DSS classification, based on [20]A decision problem is present when the discrepancybetween the current situation and the target situation canbe reduced and/or overcome through different courses ofaction [16]. There are a number of very different ways inwhich the decision maker can determine which course ofaction should be taken, and how the decision can beapproached [16]:ISSN: 1790-1979 purely intuitively without little reflection aboutthe problem through routine recourse to procedures used inthe past by adopting unquestioningly the solutionssuggested by experts by choosing at random44Issue 2, Volume 7, February 2010
WSEAS TRANSACTIONS on ADVANCES in ENGINEERING EDUCATIONVasile Paul Bresfelean, Nicolae Ghisoiue)Time – an abundance of time acts with a forcesimilar to the economy factor, allowing decisionfactors to wait for favorable opportunities.f)Consensus or negotiation – when there is acomplex level of a problem, a more extendedanalysis of the problem and negotiation orconsensus among the parties concerned isrequired.Another appealing approach to decision-makingprocesses is through complex tools that are utilized toanalyze decisions and offer senior management teams amethod for assigning roles and involving the relevantpeople. RAPID decisional model (Fig. 1) formulated byRogers and Blenko [29] focuses on the following idea:‘The key is to be clear who has input, who gets todecide, and who gets it done’. The five letters in RAPIDcorrespond to the five decisive decision-making roles:recommend, agree, perform, input, and decide. The rolesare not carried out lockstep in this order, for the reasonthat the authors took the liberty for the sake of creating auseful acronym. on the basis of systematic rational thoughtsupported by relevant information.The basis of DSS is to provide the informationalassist required to diminish the effects of limits andrestrictions faced by human decision maker throughouthis activities. Modern research of the decision-makingprocesses presents some of the factors that cancontribute to successful decisions [32]:a)Responsibility and Transparency – there are lawsand penalties to be respected by the individuals ororganizations in decision making processes.b)Expertise – each decision should be rooted in theprofound knowledge of an expert.c)Coordination – the best decision options are notenough if there is no synchronization to transmitthe orders that should be complied with and tomanage the decision-making process.d)Economy Factor – a decision can have a negativeresult or a single battle can be lost, but overall agood sense in decision making can help to makeup for the loss of some encounters.Fig.1 Representation of the RAPID decision model, based on [29]Some of the attributes and benefits of decision supportsystems can be described as follows [4]: Reduced Lead-Time to complete work Greater Consistency Smarter Response (to changes / failures) Worker Empowerment Reduced Cost. Greater Partner Satisfaction (both customers andsuppliers) Increased Innovation Higher RetentionAn additional distinction ought to be drawn amongstages of maturation of the support technologies fordecision making. Some researchers [22] affirmed thatany idea concerning the technologies, to be effectivelyput into service, should have an adequate embodimentTypical Attributes Eased Access (to raw distributed data; oftenupdated in near-real time) Facilitated Analysis (of data often through useof automated intelligence) Rich Communication (of results and new ideasin a meaningful and practical form, often augmented bysophisticated graphical depictions)Common Targeted Benefits Elevated Strategic AdvantageISSN: 1790-197945Issue 2, Volume 7, February 2010
WSEAS TRANSACTIONS on ADVANCES in ENGINEERING EDUCATIONon each of these three levels of problem awareness (Fig2.):a) formal specification,Vasile Paul Bresfelean, Nicolae Ghisoiub) design,c) implementation and maintenance.Fig.2 Problem awareness, levels and technologies in DSS creation, based on [22]DSS can range from a system to answer simplequeries that allow a subsequent decision to be made, to asystem that provides detailed querying across a spectrumof related datasets, and further to complicated systemswhich directly ‘answer’ questions, in particular highlevel ‘what-if’ scenario modeling [28]. The analysis ofsearch and optimization technologies underpins thedevelopment of DSS in a multitude of applicationsacross industry, commerce, science and government[10], with a significant level of diversity amongoptimization and computational search applications.Organizations, such as universities, can frequently dealwith the problem of how to make use of a large varietyof information resources and how to make thisinformation accessible to the community [35]. Decisionsupport area has received significant attention from thescientific community across many different ioinformatics, personnel roistering, medical decisionsupport and timetabling [10]. State of the art research[35] in decision support and DSS for socio-economicareas, include: e-management models that incorporate reliableparticipatory decision making practices andquality management indicators in academia [19], implementation of digital media to allow wellinformed collaborative decision making - casestudies of community participation in land useplanning [25],ISSN: 1790-1979 platforms that support integration andinteroperability of many data sourcesconcerning social, financial, and physicalaspects of the urban environment [3],development of on-line planning supportsystems in the context of public participation[31],systems that take advantage of elements ofcellular automata and define models for situatedcellular agents [2],decision support in intensive care medicine [15],[30], etc.3 DSS for Higher EducationDue to a growing competition in higher educationenvironments, universities try to apply strategies anddevelop new instruments so to enhance the quality ofteaching and research activities and provide thecommunities with relevant services and knowledge.Decision factors in all fields face increasinglydemanding environments, overloaded with information,data distributed throughout the organization, in terms ofrisk and uncertainty.Modern higher education institutions experience theneed of effective decision support tools to accuratelyinform them, and assist in all managerial processes.Some educational systems have long had modules for46Issue 2, Volume 7, February 2010
WSEAS TRANSACTIONS on ADVANCES in ENGINEERING EDUCATIONVasile Paul Bresfelean, Nicolae Ghisoiu Offer feedback for constant development.Universities are at the heart of the community andalso an integrating part of them, with key roles ineducation, training, research and other activities. This iswhy we consider that a DSS designed for highereducation would have to be anchored in on all theexisting data of the institution, on the databases of the allits systems (educational, research and grants, financial,accounting, eLearning portal etc.) [7]. As a result, anintegration of the newest research results in educationmanagerial issues should be essential, at the same timeas taking into account the essential task of a universityas a generator of knowledge via teaching and research.A DSS for higher education should collectinformation on all academic processes, provide feedbackfor their improvement, and offer decision-makingsupport with high integration and direct interaction withall the domains of the problem. Higher educationmanagers would have all important data and informationat their handle, in a clickable form, for quick analysisand access in certain decisional situation.decision support, but mainly for the retrospectiveanalyses of financial and administrative data. One of thefirst steps for the creation of a DSS in higher educationwould be to develop appropriate academic analytic toolsto gather, synthesize, and evaluate relevant data andinformation for effective decision making. Such tools,for example an efficient management informationsystem, would have the role to [6]: Supervise existing activities:o educational activities,o processes,o resources which entail students, teachingand auxiliary staff, curricula, syllabi, and alladministrative services; Collect data on education and researchprocesses; Develop a collaborative environment, monitorits activities and measure the accomplishmentof its objectives; Present important information to assist constantevaluation, and alternatives for performance;Fig.3 Teaching Activity module – processes’ map and “actors”,adapted from [36], [9]ISSN: 1790-197947Issue 2, Volume 7, February 2010
WSEAS TRANSACTIONS on ADVANCES in ENGINEERING EDUCATIONThe higher education ICT based systems comprisegeneral aspects with the design of economic systems,but also have a number of special features regarding: [8] the functioning and organization of educationalinstitutions; academic autonomy, even in financial issues orother forms according to public and academicresponsibilities; universities are entities that generate newknowledge and support the local and globalcommunities; universities have central tasks in education,training, research international and local specific circumstancesetc.Some types of decision-making problems in theeducational system can be described as follows [6]:1. Planning decisions for the programs of study andcurricula, which lead to the establishment of curriculafor long-term education.2. Tactical decisions:a. The curricula and syllabi detailed for eachspecialization and year of study;b.Requirements for the accomplishments ofthe syllabi: specialized frameworks, necessaryinvestment, software, etc.Vasile Paul Bresfelean, Nicolae GhisoiuIt is also important to develop a performanceevaluation instrument, with roles in the optimization ofhigher education institutions’ activities, and theimplementation of efficient management [7]. As a result,it could allow the allocations from the state budgetwhich cover the basic needs of the universities to belinked to how these needs are actually met both of thestate allocated funds and from other revenue [37].The DSS, on whose design we work, has 3 mainmodules: Students, Research and Teaching [9]. It isplanned to assist in diverse decisional issues of ouruniversity, to be applicable for its educational mission,training and academic services offered to the communityand society. The Students module (Fig. 3) represents theresults and activities of FSEGA students, and serves asthe basis for building and providing alternatives indecision-making on students’ issues [7]. The Teachingmodule, which is presented in our latest WSEASpublished article [5], comprises the results and activitiesof FSEGA teaching staff. The last module is based onthe Research activities in our faculty and includes theperformance achieved in scientific research by theteaching and research staff, departments, PhDs, etc.Fig.4 DSS modules and the existing systems, platform and databases,developed from [9]ISSN: 1790-197948Issue 2, Volume 7, February 2010
WSEAS TRANSACTIONS on ADVANCES in ENGINEERING EDUCATIONAll modules rely on the internal procedures ofFSEGA, with data extracted from FSEGA and UBBsystems and databases (Fig. 4): [6],[9] UBB and FSEGA systems:o the research activity managementsystem;o library activity;o administrativeactivitiessystems(financial, accounting etc.);o managementofschoolrecordsapplication;o Web based grade book;o fee management application;o online and distance education (ODL)portal and E-Learning Platform;o email;o research management application; assessments of academic quality concludedperiodically; performance versus that of others faculties oracross the university; learning centers; research and teaching staff evaluation; research versus teaching performance; questionnaires and surveys of graduates, masterdegree and PhD students, employers,departments;DSSMODULE Studies reclassificationDECISIONALSITUATIONS different longitudinal studies etcThe resulted data can possibly be used for qualityassessment, to complete diagnoses and analyses on thepractices of the organization and in management issues.We try to propose a specific design for the DSS so tooffer the higher education managers important tools toassist their actions in decision-making activities. Thesecharacteristics would be accessible through the userinterface, screen formats, menus, graphs, informationand knowledge integrated in the DSS. It would prove tobe a the starting point for building and providingalternatives and suggestions in decision-making onteaching-learning, research, curricula, syllabi, examevaluation issues etc. Consequently, the data, tables,charts, results of data extraction processes could be usedto assist decisions for all the “actors” (deanship,teaching and research staff, students, secretariat, etc.)implicated in the processes, in the subsequentcircumstances (Table 2).Each modules is designed to be integrated with theother modules of the higher education DSS, and to act asa whole. The final DSS design model is under furtherdevelopment and improvement, and would be adapted tofit other universities of local and European areas.Students Module Students’ enrollmentVasile Paul Bresfelean, Nicolae GhisoiuTeaching ModuleResearch Module Syllabi and teaching Scientific researchmaterialsevaluation, Tuition Course schedule Choosing a Specialization Choosing optional courses Scholarships Tutoring activities Salary coefficients Students dorms Teaching-learning activities Human resources Issue Certificates Students’ practical work Web information and Preparation for the bachelorannouncements Students’ transfer Expelling studentsexam Evaluation of the teachingstaff Interruption of studies Exam schedule Extension of studies Partial exams during the 2nd or more specializations Diploma exam in otherinstitutionssemester, and final exams Students’ grading performance issuesand standardsstrategy, Job opening andinterviewing forresearch positions, PhDs activity andevaluation Grants' continuationand management,et cetera.management Tutorial activities Contestation of the Career Guidanceevaluation results Bachelor final examTable 2. DSS modules and the existing systems, platform and databases,developed from [9]ISSN: 1790-197949Issue 2, Volume 7, February 2010
WSEAS TRANSACTIONS on ADVANCES in ENGINEERING EDUCATIONVasile Paul Bresfelean, Nicolae Ghisoiu4 ConclusionsAcknowledgementsThe present work is an integrated part of our latestresearch [5], in which we begin from the study of localand international of aspects of ICT in education, highereducation decisional issues, state of the art decisionmaking processes and DSS, and continue with our owneffort in the design of a decision support system to assistthe higher education managers.In this article, we presented: key figures of the DSS definitions andfundamental characterizations of DSS, state of the art research in decision support andDSS for socio-economic areas, newly formulated decisional model, latest DSS classifications from the researchliterature.The final section contains our contribution indesigning a DSS for higher education environments,based on the present outline of FSEGA and UBB. Itinvolves the results and activities of FSEGA researchand teaching staff, using the data extracted fromdatabases in all existing ICT systems and platforms, toassist decisions for all the “actors” (deanship, teachingand research staff, students, secretariat, etc.) implicatedin the processes, in various circumstances. We detailedseveral features of the higher education ICT basedsystems, particularities and situations of decisionmaking problems in the academic environments, andfeatures of the DSS modules.The designed DSS would be suitable for theuniversity’s educational mission, innovative research,and latest body of knowledge, academic services offeredto society and community, which are an importantmission for national and European higher educationinstitution. Its architecture is under further developmentand improvement and would be extended to other areasof a modern university (financial, public ications required by the labor market etc.). Thedevelopment and integration of a DSS with theuniversity ICT systems may possibly determine areduced cost and time needed to resolve key issues ofdrafting and adopting the most appropriate decisions, forthe representative complexities of higher educationalsystems.Our upcoming research will focus on the direction ofdetailing and developing the components of theeducational DSS, based on databases, data mining anddecision support technologies. Further researchdirections rely on the grants of the Business InformationSystems department and on the general objectives of theStrategic Program of Babeş-Bolyai University of ClujNapoca for 2007-2011 [34].ISSN: 1790-1979The research from this present paper is a part ofCNCSIS (Consiliul National al Cercetarii Stiintifice dinInvatamantul Superior) IDEI Grant 1598 “Invatamantulsuperior si piata muncii. Cercetari bazate pe tehnologiiinformatice privind corelatia dintre calificarile cerute depiata muncii si cunostintele reale ale studentilor”(Higher education and the labor market. IT-basedresearches on the correlation between the qualificationsrequired by the labor market and real knowledge of thestudents), manager Nicolae Ghisoiu, Professor PhD.The authors would also like to thank FSEGAmanagers and students for the support received duringtheir studies.References:[1] Azwina M. Yusof, Kan C.S., An ElectronicCommerce based Decision Support System forDistributed Retail Chain Stores, WSEASTransactions on Communications, Issue 1, Volume3, January 2004, p. 110-116[2] Bandini S., Manzoni S., Vizzari G., CrowdModeling and Simulation, in Recent Advances inDesign and Decision Support Systems inArchitecture and Urban Planning, Springer Scienceand Business Media, 2005, p.161-176[3] Barton J., Parolin B., Weiley V., A SpatialDecision Support System for the Management ofPublic Housing, in Recent Advances in Design andDecision Support Systems in Architecture andUrban Planning, Springer Science and BusinessMedia, 2005, p. 69-84[4] Bendoly E., Excel Basics to Blackbelt. AnAccelerated Guide to Decision Support Designs,Cambridge University Press 2008[5] Bresfelean V.P., Ghisoiu N., DSS Module forTeaching Staff Activities, Recent Advances in EActivities, Information Security and Privacy,WSEAS Press 2009, p. 292-296[6] Bresfelean V.P., Ghisoiu N., Lacurezeanu R., SitarTaut D.-A., Towards the Development of DecisionSupport in Academic Environments, Proceedingsof ITI 2009, Cavtat, Croatia, 2009, p. 343-348[7] Bresfelean V.P., Lacurezeanu R., Ani C., Pop M.,Decisions and the Implications of eedings of EDULEARN09, Barcelona, 2009[8] Bresfelean V.P., Ghisoiu N., Lacurezeanu R., VladM.P., Pop M., Designing a DSS for HigherEducationManagement,ProceedingsofCSEDU2009, Lisbon, Portugal, 2009, p. 335-34050Issue 2, Volume 7, February 2010
WSEAS TRANSACTIONS on ADVANCES in ENGINEERING EDUCATION[9] Bresfelean V.P., ImplicaŃii ale tehnologiilorinformatice asupra managementului institutiiloruniversitare, Ed. Risoprint, Cluj-Napoca, 2008[10] Burke E.K., Kendall G., Search Methodologies.Introductory Tutorials in Optimization andDecision Support Techniques, Springer Scienceand Business Media, 2005[11] Chen Z., Computational Intelligence for DecisionSupport, CRC Press LLC, 2000[12] Doumpos M., Zopounidis C., MulticriteriaDecision Aid Classification Methods, KluwerAcademic Publishers, 2004[13] Filip F.G., Sisteme suport pentru decizii, EdituraTehnica, Bucuresti, 2005[14] Forgionne G.A., An Architecture for theIntegration of Decision Making SupportFunctionalities, Decision Making Support Systems:Achievements, Trends and Challenges for the NewDecade, Idea Group Inc., 2003[15] Gago P., Santos M.F., Closed Loop KnowledgeDiscovery for Decision Support in Intensive CareMedicine, Recent Advances in Computers, 13thWSEAS International Conference on Computers,WSEAS Press, p. 447-452[16] Grünig R., Kühn R., Successful Decision-making.A Systematic Approach to Complex Problems,Springer-Verlag Berlin Heidelberg, 2005[17] Gupta J., Forgionne G.A., Mora M.T., IntelligentDecision-making Support Systems. Foundations,Applications and Challenges, Springer-Verlag;2006[18] Hansson S.O., Decision Theory - A BriefIntroduction, 2005 revision, Royal Institute ofTechnology(KTH)Stockholm,www.infra.kth.se/ soh/decisiontheory.pdf[19] Hashim F., Alam G.M., Siraj S., Ensuringparticipatory based decision-making practice inHigher Education through E-management: Afaculty initiative, Recent Advances in E-Activities,Information, Security and Privacy, WSEAS Press2009, p.280-285[20] Kacprzyk J., Zadrozny S., Towards HumanConsistent Data-Driven Decision Support Systemsvia Fuzzy Linguistic Data Summaries, inPerception-based Data Mining and DecisionMaking in Economics and Finance, SpringerVerlag; 2007.[21] Kopackova H., Komarkova J., Sedlak P., Decisionmaking with textual and spatial information,WSEAS Transactions on Information Science andApplications, Volume 5, Issue 3, March 2008, p.258-266[22] Kryssanov V.V., Abramov V.A., Fukuda Y.,Konishi K., A Decision-Making Support SystemISSN: 33][34]51Vasile Paul Bresfelean, Nicolae GhisoiuBased on Know-How, arXiv e-print service,Cornell University, arxiv.org/pdf/cs.CE/0606010Marga, A., Schimbare, codificare, competitivitate(proiect managerial), UBB Cluj-Napoca, Dec. 2007Panian Z., Just-In-Time Business Intelligence andReal-Time Decisioning, in Recent Advances inApplied Informatics and Communications,Proceedings of AIC '09, WSEAS Press, 2009,p.106-111Pettit C., Nelson A., Cartwright W., Using On-LineGeographical Visualisation Tools to Improve LandUse Decision-Making with a Bottom-UpCommunity Participatory Approach, in RecentAdvances in Design and Decision Support Systemsin Architecture and Urban Planning, SpringerScience and Business Media, 2005, p.53-68Pinson S.D., Louca J.A., Moraitis P.,A distributeddecision support system for strategic planning,Decision Support Systems 20 p.35-51, 1997,Elsevier Science B.V.Power D.J., Categorizing Decision SupportSystems: A Multidimensional Approach, DecisionMaking Su
Key-Words: - decision support, decision support systems (DSS), higher education institutions, Information and Communication Technologies (ICT). 1 Introduction The mission of a higher education institution is to prepare personnel to the highest level of knowledge at that time in history [23]. Universities should not be just
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