A multiple criteria decision support web-based system for ... - CiteSeerX

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Int. J. Internet and Enterprise Management, Vol. 00, Nos. 0/0, 000

A multiple criteria decision support web-based system for facilities management Edmundas Kazimieras Zavadskas Department of Construction Technology and Management, Vilnius Gediminas Technical University, Sauletekio av. 11, LT-2040 Vilnius, Lithuania Fax: +370-52-700-114 E-mail: [email protected]

Arturas Kaklauskas*, Mindaugas Gikys and Natalija Lepkova Department of Construction Economics and Property Management, Vilnius Gediminas Technical University, Sauletekio av. 11, LT-2040 Vilnius, Lithuania Fax: +370-52-745-235 E-mail: [email protected] E-mail: [email protected] E-mail: [email protected] *Corresponding author Abstract: An analysis of multiple criteria decision support systems and facilities management web-based automation applications that were developed by researchers from various countries assisted the authors to create their own Multiple Criteria Decision Support Web-Based System for Facilities Management (DSS-FM). DSS-FM differs from others in its use of new multiple criteria analysis methods as were developed by the authors. The database of a facilities management was developed and provides a comprehensive assessment of alternative versions from the economic, technical, technological, infrastructure, qualitative, technological, legislative and other perspectives. Based on the above complex databases, the developed Multiple Criteria Decision Support Web-Based System for Facilities Management enables the user to analyse alternatives quantitatively and conceptually (i.e. the text, formula, schemes, etc.). Applying the DSS-FM may increase the efficiency of calculators, analysers, software, neural networks, expert and decision support systems and e-commerce. Keywords: decision support web-based systems; facilities management; multiple criteria analysis. Reference to this paper should be made as follows: Zavadskas, E., Kaklauskas, A., Gikys, M. and Lepkova, N. (0000) ‘A multiple criteria decision support web-based system for facilities management’, Int. J. Internet and Enterprise Management, Vol. 0, Nos. 0/0, pp.000–000. Biographical notes: Edmundas Kazimieras Zavadskas. Academic Experience: Lecturer (1973–1974), Senior Lecturer (1974–1978), Associate Professor (1978–1985), Senior Researcher (1985–1987), Professor (1988–), Head of Construction Technology Department (1987–1990), Rector of Vilnius Technical University (1990–1996), Rector of Vilnius Gediminas Technical University

Copyright © 2004 Inderscience Enterprises Ltd.

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E.K. Zavadskas et al. (1996–2002). E. Zavadskas is participating in two Framework 5 programmes. The spheres of his current research are internet based and e-business systems (property, construction and export), decision-making theory, decision support systems, etc. E. Zavadskas is the author of 527 research publications and nine monographs. Arturas Kaklauskas. Academic Experience (Vilnius Gediminas Technical University): PhD Student (1987–1989), Senior Lecturer (1990–1995), Associate Professor (1995–2000), Chairman of the Department of Construction Technology and Management (1996–2001), Professor (2000), Chairman of the Department of Construction Economics and Property Management (2001). A. Kaklauskas is participating in four Framework five programmes and is the leader of the CIB Study group SG1 ‘The Application of Internet Technologies in Building Economics’. The spheres of his current research are internet based and e-business systems (property, construction ethics, sustainable development, export, etc.), decision-making theory, decision support systems, etc. A. Kaklauskas is the author of 87 research publications and five monographs. Mindaugas Gikys is a PhD student. A Graduate of Vilnius Gediminas Technical University, 1997 (Bachelor of of Construction Management), Master of Construction Management (1999). The spheres of his current research are multiple criteria decision support systems, total quality management, internet (distance studies), facilities management. Natalija Lepkova is a Doctor of technological sciences and the author of 12 research publications. She has undertaken research visits to Aalborg University (Denmark, 2000, 2003) and Poznan Politechnics (Poland, 2000). Her spheres of current research are web-based systems for facilities management, facilities management and internet (distance studies). An earlier version of this paper was presented to the Second International Conference on Electronic Business, Taipei, Taiwan, December 10–13, 2002.

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Introduction

One of the major problems in e-business is to find what you want. The number of alternative products and services on the internet are in the thousands. How can customers find the rational products and services on the internet? Once product or service information is found, the customer usually wants to compare alternatives. There are five types of aids to comparison- shopping:

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Search on hypertext files by agents. Agents can find alternatives with relating information (list prices, and other characteristics), seller’s address, and search for minimally priced products.

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Search alternatives on databases. Many electronic catalogues built using a Dynamic Web-based Database Management system exist today. The software agents are computer programmes that help users to conduct routine tasks, search and retrieve information, support decision-making, and act as domain experts without human intervention. Software agents can find products and make direct comparisons between products from the database.

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Alternative search and tabular comparison. Alternatives can be found and carry out tabular multiple criteria comparisons.

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Comparison of alternative products and services from multiple malls. Search and multiple criteria decision-making. The multiple criteria decision-making methods and multiple criteria decision support systems are used in this type of e-business comparison-shopping.

Applying multiple criteria decision support systems may increase the efficiency of e-business. Recently, a lot of multiple criteria decision support systems used in various fields of human activity have been developed. Theoretical and practical aspects of multiple criteria decision support systems were analysed by various researchers such as, G. Colson [1], S. Purao et al. [2], P. Sen et al. [3] and Sean B Eom [4], etc. For example, C. Zopounidis et al. [5] described the PREFDIS multiple criteria decision support system for the study of sorting out decision-making problems. B.B. Malakooti [6] examined a decision support system’s framework for solving discrete multiple criteria decision-making problems. A. Pór et al. [7] presented a multiple criteria decision support system for production control. M.R. Thomas [8] analysed a decision support system that provides access to state, regional, and local geo-spatial databases, several informational and visualisation tools, and assumptions that are useful in providing a better understanding of issues, options and alternatives in redeveloping brown fields. The decision support system KOSIMEUS, which is a combination of process models simulated with a flow-sheeting programme and a multiple criteria decision support system, is presented and illustrated with an example from the iron and steel making industry by T. Spengler et al. [9]. X. Zhu et al. [10] examined a prototype web-based decision support system (VegMan) for regional vegetation management in the Central Highlands region of Queensland, Australia. The system provides access to facts, policies, strategies and decision support tools relevant to vegetation management in the region. C. Chan et al. [11] described an Expert’s System of Architectural Framework for Engineering Selection. Some multiple criteria decision models that involve user preferences or weights are also incorporated in the framework. J.P. Shim et al. [12] analysed four powerful decision support tools, including data warehouses, OLAP, data mining, and web-based DSS. In J.P. Shim et al.’s [12] opinion, mobile tools, mobile e-services, and wireless Internet protocols will mark the next major set of developments in DSS. According to N.F. Matsatsinis et al. [13], group decision support systems can play a critical role in decision-making situations with multiple individuals and each having his/her own private point of view on the handling of the decision problem. Also N.F. Matsatsinis et al. [13] point out, that multiple criteria decision aid methods can be proven as invaluable tools in handling interpersonal conflicts where the aim is to achieve a consensus between the group members or at least reduce the amount of conflict among the participating individuals. In this paper, we describe the Multiple Criteria Decision Support Web-Based System for Facilities Management (DSS-FM), which provides web-based facilities management analysis through the internet. There are many facilities management automation applications in the world, yet most of these systems have only quantitative descriptions and an analysis of facilities management alternatives. Motivated by the lack of qualitative descriptions and the analysis of facilities management alternatives, we have developed DSS-FM, which provides facilities on the internet for accessing, maintaining and analysing

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quantitative and qualitative information of various facilities management alternatives in Lithuania. In addition, DSS-FM is innovative in that it is designed to provide both online analysis services to clients and facilities managers. The system not only provides a channel for the user to find rational facilities management alternatives, analyse them and, if necessary, provide a basis for negotiations between clients and facilities managers. It also allows facilities managers to market their latest services, update their company’s profile, and generate reports. The overall structure of the rest of the paper is as follows. Section 2 presents an analysis of facilities management web-based automation applications. Section 3, describes the Multiple Criteria Decision Support Web-Based System for Facilities Management as developed by the authors. Section 4 discusses systems’ features, an architectural model and web page interfaces. Section 5 presents a sample solution of space management.

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Analysis of facilities management web-based automation application

The major players in facilities management websites can find calculators, analysers, software, neural networks, expert and decision support systems and e-commerce, etc. According to B.K. Forbes et al. [14,15], the top seven facilities management automation application areas are as follows: real property and lease management, strategic master planning, space management, furniture and equipment management, telecommunications and cable management and building operations management. In E. Teicholz’s [16] opinion, most computer-aided facilities management vendors try to control the web environment of their automation application and do not link very well to other web-based facilities management automation applications. And this model is becoming increasingly unworkable because new vendors are increasingly offering stand-alone facilities management automation application (vehicle (fleet) management, space planning and forecasting, help desk and maintenance work management, furniture layout, asset management, room scheduling, energy management, and construction project management) on the internet. A calculator is a software application that is used for completing mathematical calculations. Calculators range from very cheap software, capable of performing the basic arithmetical operations, to those whose capabilities extend to sophisticated mathematical and statistical manipulation and those that may be programmed with a large number of steps. Facilities management websites sometimes contain calculators: CRESA Space Calculator [17] (calculates office space needs), Comfort calculator [18] (analyses thermal comfort and estimates the optimal temperature), Lighting calculator [19] (identifies and analyses options for reducing lighting costs), Ventilation calculator [20] (examines the supply of outside air ventilation to a space), Moving calculator [21] (estimates how much the local or interstate move might cost) and Home Improvement Calculators [22], etc. Websites might also contain various purpose analysers [23–25] that help customers to analyse various facilities management situations. For example, Analyzer-USA [24] provides Facilities Management Services for business computer systems. Information about facilities management software can be found on the following facilities management websites: ARCHIBUS/FM [26], FM Systems [27], SPAN [28], Drawbase [29], Aperture [30]. The above facilities management software offers various modules and tools: lease management, move management, strategic space planning,

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maintenance management, accounting charge-back, communication/cable management and personnel management. The common activities addressed by most facilities management software includes planning, design, acquisition, use, maintenance, redeployment, and disposal. According to E. Teicholz [16], currently, more than 60 software vendors offer project website software – primarily for managing construction projects (reports, document management services and track project information such as drawings, specifications, request for information, various logs, and so forth). And for example, reports from facilities management software in space management include gross areas by floor and building, rooms by department and standard, employees (occupancy plan, vacant rooms, employees by room and department and employee extensions), etc. In B.K. Forbes et al.’s [14,15] opinion, multimedia technologies in facilities management software include the integration of alphanumeric data, audio, graphics, animation, video, image recognition, and virtual reality data, while videoconferencing, chat rooms, enhanced training, design simulations, and next-generation cellular connectivity are but a few of the multimedia applications in facilities management software. Expert systems [31, etc.] today generally serve to relieve a ‘human’ professional of some of the difficult but clearly formulated tasks. According to B.K. Forbes [14,15], the expert systems cultivated within cyberspace universes for facilities management enable executives to incorporate relevant best practices and benchmarking applications into the daily activities of their organisations. In V. Sauter’s [32] opinion, over the years expert systems have evolved into an integrated component of many decision support systems that were provided to support decision-makers. The major players in facilities management can use various purpose decision support systems [33–35]. The decision support system (DSS) provides a framework through which decision-makers can obtain the necessary assistance for decisions through an easy-to-use menu or command system. Generally, a DSS will provide help in formulating alternatives, accessing data, developing models and interpreting their results, by selecting options or analysing the impacts of a selection. Facilities management DSS developers try their best to help clients in their facilities, financial, and professional services organisations become more efficient in automated asset management, to retrieve, filter, sort and deliver information, and to make decisions. To succeed in this, facilities management DSS developers have developed and managed DSS for senior executives, strategic planners, analysts, and managers who need to have the full-scale information on time in order to make decisions and to increase the overall efficiency. In B.K. Forbes et al.’s [14,15] opinion, the corporation of tomorrow must successfully intertwine facilities management with finance and administrative activities, sales and marketing, human resources, information management, manufacturing, distribution, and must be web centric. Also B.K. Forbes et al. [14,15] emphasise, that the use of e-commerce by facilities management professionals is still new, but there is little doubt that its presence will be lasting and more significant in the years to come. The above calculators, analysers, software, neural networks, decision support and expert systems, e-commerce, etc, are not connected. Therefore, in the future the above FM automation solutions must, to some extent be integrated.

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Multiple criteria decision support web-based system for facilities management

Based on the analysis of the multiple criteria decision support systems and facilities management web-based automation applications and in order to determine the most efficient versions of real estate and facilities management, a Multiple Criteria Real Estate E-Commerce System [36] was developed. The Multiple Criteria Decision Support Web-Based System for Facilities Management (DSS-FM) consisting of a database, database management system, model-base, model-base management system and user interface is a part of the Multiple Criteria Real Estate E-Commerce system and was developed by the authors of this research. A short description of the DSS-FM follows. Facilities management involves a number of interested parties who pursue various goals and have different potentialities, educational levels and experiences. This leads to various approaches of the above parties to decision-making in this field. In order to do a full analysis of the available alternatives and to obtain an efficient compromise solution, it is often necessary to analyse economic, qualitative, legal, social, technical, technological, space and other types of information. This information should be provided in a user-orientated way. The presentation of information needed for decision-making in the DSS-FM may be in a conceptual form (i.e. digital/numerical, textual, graphical, diagrams, graphs and drawing, etc), photographic, sound, video and quantitative forms. The presentation of quantitative information involves criteria systems and subsystems, units of measurement, values and initial weights that fully define the provided variants. Conceptual information means a conceptual description of the alternative solutions, the criteria and ways of determining their values and the weights, etc. In this way, the DSS-FM enables the decision-maker to receive various conceptual and quantitative information on facilities management from a database and a model-base allowing him/her to analyse the above factors and to form an efficient solution. The analysis of database structures in decision support systems according to the type of problem solved reveals their various utilities. There are three basic types of database structures: hierarchical, network and relational. DSS-FM has a relational database structure where the information is stored in the form of tables. These tables contain quantitative and conceptual information. Each table is given a name and is saved in the computer’s external memory as a separate file. Logically linked parts of the table form a relational model. The following tables form the DSS-FM’s database:

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Initial data tables. These contain information about the facilities (i.e. building, complexes, alternative facilities management organisations).

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Tables assessing facilities management solutions. These contain quantitative and conceptual information about alternative facilities management solutions: space management, administrative management, technical management and management of other services, complex facilities management, market, competitors, suppliers, contractors, renovation of walls, windows, roof, etc.

To design the structure of a database and perform its completion, storage, editing, navigation, searching and browsing etc., a database management system was used in this research.

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The user seeking an efficient facilities management solution should provide, in the tables assessing facilities management solutions, the exact information about alternatives under consideration as to the client’s financial situation. It should be noted that various users making a multiple criteria analysis of the same alternatives often get diverse results. This may be due to the diversity of the overall aims and financial positions of the users. Therefore, the initial data provided by various users for calculating the facilities management project differ and consequently lead to various final results. The character of the objective’s choice for the most efficient variant is largely dependent on all available information. It should also be noted that the quantitative information is objective. The actual facilities management services have real costs. The values of the qualitative criteria are usually rather subjective though the application of an expert’s methods contributes to their objectivity. The interested parties have their specific needs and financial situation. Therefore, every time when the party uses the DSS-FM they may make corrections to the database according to their aims and their financial situation. For example, a certain client considers the sound insulation of the external walls to be more important than their appearance while another client is quite of the opposite opinion. The client striving to express his/her attitude towards these issues numerically may ascribe various weights values to them that eventually will affect the general estimation of a refurbishment project. Though this assessment may seem biased and even quite subjective, the solution finally made may exactly meet the client’s requirements, aims and affordability. The tables assessing facilities management solutions are used as a basis for working out the matrices of decision-making. These matrices, along with the use of a model base and models, make it possible to perform a multiple criteria analysis of alternative facilities management projects, resulting in the selection of the most beneficial variants. The efficiency of a facilities management variant is often determined by taking into account many factors. These factors include an account of the economic, aesthetic, technical, technological, management, space, comfort, legal, social and other factors. The model base of a decision support system should include models that enable a decision-maker to do a comprehensive analysis of the available variants and to make a proper choice. The following models of a model base aim at performing the functions of: a model for the establishment of the criteria weights, a model for multiple criteria analysis and for setting the priorities, a model for the determination of a project’s utility degree, a model for the determination of a project’s market value. According to the user’s needs, various models may be provided by a model management system. When a certain model (i.e. search for facilities management alternatives) is used the results obtained become the initial data for some other models (i.e. a model for multiple criteria analysis and setting the priorities). The results of the latter, in turn, may be taken as the initial data for some other models (i.e. determination of utility degree of space management, administrative management, technical management and management of other services, complex facilities management, market, suppliers, contractors, renovation of walls, windows, roof, etc.). The management system of the model base allows a person to modify the available models, eliminate those that are no longer needed and add some new models that are linked to the existing ones. Since the analysis of facilities management is usually performed by taking into account economic, quality, technical, technological, management, legal, social, space and

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other factors, a model base should include models which will enable a decision-maker to carry out a comprehensive analysis of the available variants and make a proper choice. Four multiple criteria analysis methods as developed by the authors are used by the DSS-FM in the analysis of the facilities management alternatives. Application of Multiple Criteria Decision Support Web-Based System for Facilities Management (DSS-FM) allows one to determine the strengths and weaknesses of each phase and its constituent parts. Calculations were made to find out by what degree one version is better than another and the reasons disclosed why it is considered so. Landmarks are set for an increase in the efficiency of facilities management versions. All this was done argumentatively, basing oneself on criteria under investigation and on their values and weights. This saved users’ considerable time by allowing them to increase both the efficiency and quality of facilities management analysis. Below is a list of typical facilities management problems that were solved by users:

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multiple criteria analysis of space management (see Tables 1 and 2), administrative management, technical management and management of other services alternatives

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analysis of complex facilities management alternatives analysis of interested parties (competitors, suppliers, contractors, etc.) determination of efficient loans analysis and selection of rational refurbishment versions (e.g. roof, walls, windows, etc.)

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multiple criteria analysis and determination of the market value of a real estate (e.g. residential houses, commercial, office, warehousing, manufacturing and agricultural buildings, etc.)

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analysis and selection of a rational market determination of efficient investment versions, etc.

The determination of the utility degree and market value of the facilities management alternatives that are under investigation and the establishment of the priority order for its implementation does not present much difficulty, if the criteria system, criteria numerical values and weights have been obtained and multiple criteria decision-making methods are used.

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System features, architectural model and a web page interface

We have carefully studied the requirements of Lithuanian facilities managers and their clients in developing online facilities management services. By reflecting on these requirements, our design of the DSS-FM, aims at a system with the following features: accessibility, reliability, effectiveness, modularity and extendability, easy to use and multimedia. These features are described below. The services provided by the system are widely accessible, by using the internet to reach a wide range of customers and are online updates of information and maintenance of the services. DSS-FM can be unreliable either inherently (unreliable primary data) or become unreliable within the decision support system. The level of reliability depends on

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the reliability of the database and software as well as the ‘quality’ of the users’ work. In general, the information system is considered reliable if it functions properly during the moments when needed by the user and if (when performing the set functions) it retains the necessary operational values for a required period. Also the system deals with multiple users at different locations. According to the user’s needs, various models may be provided by a model-base management system. When a certain model (i.e. determining the initial significance of the criteria) is used the results of the calculations obtained become the initial data for other models (i.e. a model for multiple criteria analysis and setting the priorities). Results of the latter, in turn, may be taken as the initial data for other models (i.e. determining alternatives utility degree, determining alternatives market value) without human interference. A management system of the model base provides the user with a model base allowing him/her to modify the models available, eliminating those which are no longer needed and adding some new models linked with the existing ones. The system provides a user-friendly interface to facilitate easy use of the analysis services. It provides an introduction to the system, a comprehensive window-based menu of services, and other relevant information about the company and its facilities management services. The information in the database can be represented in different ways; i.e. it can be digital, textual, graphic, formula-type, audio, video and combined. Since all the above-mentioned data presentation forms can represent the same project in different ways then the most effective one has to be selected. Together, these features and properties allow an open and flexible framework for providing services that are suited to both clients and facilities managers. To achieve the above goals, the structure of the software system must be well designed. For this purpose, we have chosen a client/server model. This model is a concept that is used for describing the interaction between two entities in a computer system, i.e. the client and the server. The main function of the Web Page Interface is to provide the facilities manager’s customer with an easy way to access the available services. Modules within this component provide functions that implement the services. The modules represent and display the facilities management’s information by using multimedia data. When invoked, it shows the alternative services list and its details, demonstration images, environment images and floor plan images. When the user selects the alternative services from the list box, the module sends a request to the server for details of the services. The server will then provide information pertaining to the selected services, which can be of various types such as digital, textual, graphic, formula-type, audio, video, and combined. It is also desirable for this module to provide the user with a means to manipulate views of the property. In order to maintain a large amount of facilities management data, a well-designed services catalogue is necessary. In addition to the above facilities, for the user to access facilities management information, the web page Interface component is designed so as to also contain modules that provide some useful information about Real Estate. The module displays the status of the web page. When the page is being updated or the server is being shut down, the module will alert the user by displaying a ‘STOP’ sign. This module retrieves the system’s status file from the web server. Therefore, even if the server is down, the system’s status of information will still be available.

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One of the system’s components provides a channel for the facilities manager to market the latest facilities management information and allows the agent to maintain and update the information online. Updating and maintaining facilities management data in the database can be a difficult and arduous task. Many companies employ a team of programmers and web masters to maintain web pages and databases. By having easy use of this component, the maintenance cost can be reduced. The Facilities Management Editor’s Module provides the means for the agent to edit facilities management data, which contains digital, textual, graphic, formula-type, audio, video, and combined data. Since a facilities management company sometimes has more than one branch and each is responsible for different districts, the Module should be capable of handling multiple simultaneous update requests. To handle the complex interactions among clients, the agent users, and the server, a synchronisation mechanism is needed which coordinates accesses to the system data so as to maintain consistency. Otherwise, problems may occur because, for example, files can be corrupted, updated information may get lost and appointment books can be out of order.

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Sample solution of space management

Zˇ irmu¯nai supermarket (Zˇ irmu¯nu˛ Street 68a) is in Vilnius’ Zˇ irmu¯ nai District. The supermarket was built in 1974. It is currently owned and run by the Real Estate Company OBER HAUS. The supermarket building has two floors and a basement. Total floor space of the building is 5,318 m2. The finishing works have not been totally completed. The physical depreciation is not considerable. It has a large car park. At the moment the premises are rented out to various firms, such as Ritos Smukle˙, Cili picerija, Photo Company Fuji, and others. These companies take up around 3,420 m2. A free non-rented area of 1898 m2 still remains unused. While alternatives to space management in Zˇ irmu¯nai supermarket are changing, their price and quality are also changing. Many options of space management in Zˇ irmu¯nai supermarket can be considered. We are analysing this in the article and three space management alternatives were proposed by facilities management organisations, namely Rubikon, JSC Valymo sistemos (i.e. Cleaning systems) Ltd., and JSC Auksinis varnas Ltd. from Vilnius. The first alternative was proposed by Rubikon and a second by JSC Valymo sistemos Ltd., that was for space management alternatives (see Figure 1) and both are described below.

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Figure 1 Table assessing space management alternatives

All the above criteria are qualitative except for the cost. Determination of the cost is based on similar projects, price lists and experts’ advice. The process for determining the criteria initial weights and qualitative criteria numerical values of the project under investigation was based on the use of interviews and an expert’s method. Experts estimated the qualitative criteria by using a one-point system. Semi-structured and open-ended interviews were used as the means for questioning a diverse group of respondents who live in Vilnius (Lithuania) and to describe their expectations and experiences during the space’s management. Twenty-eight persons took part in face-to-face interviews: four interviews were couples and 20 were single individuals. Interviewees were selectively sampled through area clients from the above facilities management organisations (11/28), facilities management organisations that were under consideration (11/28), and with referrals from other interviewees (6/28). To maximise the range of possible experiences and opinions, we included persons of diverse ethnicity, education levels, ages and gender statuses. Interviewees were asked about their space management experiences, etc. After questioning 28 respondents and processing the obtained results by using an expert’s method, values of qualitative criteria and initial criteria weights were calculated.

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The results of the comparative analysis of the space management alternatives are presented as a grouped decision-making matrix where columns contain alternatives, while all quantitative information pertaining to them is found in Figure 1. Quantitative information is based on the criteria system, units of measure, values and initial criteria weights of the projects’ alternatives. Quantitative information is accurate and reliable and allows one to use multiple criteria decision-making methods. Any alternative that has a criterion value worse than the required level was rejected. The multiple criteria analysis of the first and second space management alternatives (see Figure 1) is described below. The following criteria for determining the best spaces management alternative is based on extensive literature study, advice and expert opinions. They are as follows: cost, space organisation, workplace organisation, inventory compilation/updating, building security, reception, cleaning, snow-clearing service, upkeep of outdoor facilities, garden care, plant care in the building, post room, canteen management, central archive, office supplies and safety specialist. When the decision-making matrix is formed web-based, multiple criteria analysis of space management alternatives can be performed. It can also be seen from the data presented in the figures that each alternative has both positive and negative features. Values of all criteria have been estimated by using the one-point system. The cost of the first version (Rubikon) is higher, while space organisation, workplace organisation, building security, upkeep of outdoor facilities, plant care in the building, canteen management, central archive and safety specialist of this version, were more favourable. The second alternative (JSC Valymo sistemos Ltd.), however, differs from the first one in that it possesses other and better characteristics (i.e. inventory compilation/updating, reception, cleaning, snow-clearing service, garden care, post room and office supplies). From Figure 1 we see that each criterion unites with its measurement unit and weight. The magnitude of weight indicates how many times one criterion is more significant than another criterion. For example, the reception weight (q60.06) is twice (q6 : q110.06 : 0.032) times more significant for a customer than the plant care in the building (q110.03). The results of a multiple criteria evaluation of three space management versions are presented in Figure 2. Figure 2 shows that the third version is the best in the utility degree that equals 100%. The second version was second according to priority, and its utility degree was equal to 95.82%. The first version was third according to priority, and its utility degree was equal to 92.26%. The level of usefulness of the comparative alternatives expresses the level of the ability to reach a customer’s goals.

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Figure 2 Fragment of multiple criteria analysis of space management alternatives

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Conclusion

Facilities management is an information business. Technological innovation mainly through changes in the availability of information and communication technology inclusive of calculators, analysers, software, neural networks, decision support and expert systems, e-commerce that have been provided by a variety of new services developed by the facilities management sector. Most of all calculators, analysers, software, decision support and expert systems, neural networks seek to find out how to make the most economic facilities management decisions and most of all these decisions are intended only for economic objectives. Facilities management alternatives under evaluation have to be evaluated not only from the cost (design, construction, indirect expenses, operating and maintenance expenses, renovation costs, the interest paid on loan), but take into consideration qualitative (aesthetic value, flexibility, comfort (noise, air quality, thermal comfort, working conditions)), technical, technological, space and other characteristics as well. Therefore, applying multiple criteria analysis methods and decision support systems may increase the efficiency of facilities management calculators, analysers, software, neural networks, decision support and expert systems and e-commerce. Based on an analysis of multiple criteria decision support systems and facilities management web-based automation applications and in order to determine the most efficient versions of facilities management Multiple Criteria Decision Support Web-Based System for Facilities Management was developed by authors of paper. The related questions were analysed in this paper.

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19 ‘My facilities.com-lighting calculator’ (2002), January, http://www.automationcollege.com/ myfacilities/tools/lightingcalculator.asp 20 ‘My facilities.com-ventilation calculator’ (2002), January, http://www.automationcollege.com/ myfacilities/tools/ventilationcal.asp 21 ‘Homestore.com-moving calculator’ (2002), January, http://www.homefair.com/homefair/ calc/movecalcin.html?type=to 22 ‘Realtor.com – home inprovement calculator’ (2001), October, http://www.homestore.com/ home_improvement/planning/calculators/default.asp?gate=realtor&source1xxxotzzz9 23 ‘QPS, Inc – property analyzer’ (2002), January, http://www.qualityplans.com/ propertyanalyser.htm 24 ‘Analyzer USA, Inc – Analyzer USA’ (2002), January, http://www.analyser-usa.com/ services.htm 25 ‘Expedition analyzer’ (2002), January, http://www.mass-systems.co.uk/analyser.htm 26 ‘Archibus, Inc–ARCHIBUS/FM software’ (2001),October, http://www.archibus.com/ 27 ‘FM: Systems, Inc’–FM:Interact and FM:Space software (2002), January, http://www.fmsystems.com 28 ‘Peregrine Systems’–SPAN. Facility and Real Estate Management software (2002), January, http://sdweb02.peregrine.com/prgn_corp_ap/pstHomePage.cfm?mylanguageen 29 ‘Drawbase software – facilities management’ (2001), September, http://www.drawbase.com/ 30 ‘Aperture technologies, Inc. – facility and real estate management’ (2001), November, http://www.aperture.com 31 ‘NECA’ – safety expert software (2002), January, http://www.vulcanpub.com/ecen/ article.asp?article_id59995 32 Sauter, V. (1997) Decision Support Systems, John Wiley & Sons, Inc., p.408. 33 ‘PCSWMM 2000 – decision support system’ (2002), February, http://www.chi.on.ca/ pcswmmdetails.html 34 ‘Visual DSS’ (2002), January, http://www.trueblue.com.au/vdss/ 35 ‘TATA Infotech Services–DSS’ (2001), September, http://www.tatainfotech.co.in/html/ frames/ServiceFrame.html 36 Kaklauskas, A. and Lepkova, N. (2001) ‘Facilities management object and miltiple criteria analysis’, Proceedings of 7th International Conference on Modern Building Materials, Structures and Techniques, Vilnius, Lithuania, pp.170–171.