Combining GDSS and Games for Decision Support

223COMBINING GDSS AND GAMING FOR DECISION SUPPORTGroup Decision and Negotiation 13: 223–241, 2004

© 2004 Kluwer Academic Publishers. Printed in the Netherlands

Combining GDSS and Gaming for Decision Support

IGOR MAYER AND MARTIN DE JONGDelft University of Technology, Faculty of Technology, Policy and Management (TPM), Jaffalaan 5, 2628 BXDelft, The Netherlands (E-mail: [email protected]; [email protected])

Abstract

Both gaming and group (decision) support systems (GDSS) are frequently used to support decision-making andpolicymaking in multi-actor settings. Despite the fact that there are a number of ways in which gaming and GDSScan be used in a complementary manner, there are only sporadic examples of their combined use. No systematicoverview or framework exists in which GDSS are related to the functions of gaming or vice versa. In this article,we examine, why, how and for what purpose GDSS can be used to enrich and improve gaming simulation fordecision support, and vice versa. In addition to a review of examples found in the literature, four games are dis-cussed where we combined gaming and GDSS for complex decision-making in a multi actor context: INCODELTA,a game about transportation corridors; INFRASTRATEGO, a game about a liberalizing electricity market; CONTAINERS

A DRIFT, a game about the planning of a container terminal, and; DUBES, a game about sustainable urban renewal.Based on the literature and these four experiences, a classification is presented of (at least) four ways in whichGDSS and gaming can be used in a complementary or even mutually corrective, manner: the use of GDSS forgame design, for game evaluation, for game operation and the use of gaming for research, testing and training ofGDSS.

Key words: electronic meeting systems, evaluation, gaming, group decision-making, group decision supportsystems, simulation

1. Introduction

Simulation-games provide a safe environment, based on reality, in which participants canexperiment with decisions and negotiations (Crookall and Arai 1995; Duke 1974, 1980,2000; Geurts et al. 1998; Mayer and Veeneman 2002; Shubik 1975). These experiencesare relevant for a better understanding of how complex social-technological systems workand how decisions can be made about them (Duke 1998). In the pre-decision support era,gaming was largely based on manual procedures or simple arithmetical operations, but theemergence of Information and Communication Technology (ICT) has strongly influencedthe way simulation-games are designed, played and used (Affisco 2000; Duke 2000). Thereare two main reasons for the inclusion of ICT in gaming simulation:

1. ICT opens up new avenues for game design, operation and use – for example, by facili-tating new ways of group communication and interactive decision-making.

2. When ICT is a relevant aspect of real decision-making systems, it should also be includedin the simulation-games that are intended to simulate and support those systems.

224 MAYER AND DE JONG

The above arguments also hold true for Group Decision Support Systems (GDSS) becausethey are specific ICT applications for the support of group interaction and decision-mak-ing. GDSS may be used to enrich group communication and interactive decision-makingin games, and if GDSS are increasingly used for real decision-making, they should also bepart of the simulation-games that want to study or support real decision-making. Affisco(2000), for example, recently argued that innovations in the area of Group Support Sys-tems (GSS) have and will continue to change the use of gaming simulation as a context forcollaborative strategic decision-making. In his view, “simulation-gaming in the GSS eraprovides a superior environment for research into group processes and strategic decision-making” (Affisco 2000, p. 47).

Although there are a number of ways in which gaming and GDSS can be used in a com-plementary or integrated way, there are only sporadic examples of such combined use. Asfar as we know, no systematic overview or framework exists in which GDSS are related tothe functions and objectives of gaming (or vice versa). In this article, we therefore exam-ine why, how, and for what purpose GDSS can be used to enrich and improve gaming simu-lation for decision support. In addition, we will also study how gaming can improve andenrich the development and use of GDSS. Only a very limited number of references to com-binations of GDSS and gaming could be found in the literature. This may be because manyinteresting gaming and GDSS projects are not regularly published in scientific journals butonly in gray literature such as project reports. The review of cases is therefore not claimedto be “exhaustive” but primarily intended to gain a better understanding of the general rangeof possible GDSS-gaming applications.1 In addition to the case reports discussed in theliterature, we draw upon our own personal experience of four games in which we useddifferent types of GDSS in various ways (cf. Mayer and Veeneman 2002).

There are some delineations to this study. First, the study does not focus on the exten-sive theory and practice of single or multi-user computer games and only considers Internetor Local Area Network games (LAN games) as far as they are relevant for GDSS. Second,we are concerned with gaming and GDSS for decision and policy support, either in a pro-fessional or an academic learning context. We will not go into the use of gaming for otherobjectives such as vocational training, practicing skills or entertainment (Geurts et al. 1998).Third, a number of reported GDSS cases were found that related to game theory, but not togaming. Because there is a clear difference between game theory and gaming, we do notinclude those cases in our discussion. Finally, we will focus on gaming and GDSS in aninteractive multi-actor context. We will not discuss single-user modes of Decision SupportSystems (DSS, cf. Khoong 1995) or single-user modes of games and simulations.

The structure of this article is as follows. In the next section, we discuss why and howGDSS and gaming are complementary. We then review the limited body of literature thatreports about gaming-GDSS combinations. Furthermore, we discuss the design of andexperiences with four simulation-games in which GDSS were used for various purposes.The review of cases leads to a basic categorization of possible combinations of GDSS andgaming for decision and policy support. The article concludes with some points of reflec-tion on combinations of games and GDSS.

225COMBINING GDSS AND GAMING FOR DECISION SUPPORT

2. Comparing Gaming and GDSS

Whereas GDSS emerged only a few decades ago (Dennis and Gallupe 1993; Genugten etal. 1998; Nunamaker et al. 1997), the origin of gaming to support military decision-mak-ing goes as far back as ancient times (Brewer and Shubik 1979; Shubik 1975). For non-military decision support – e.g. urban planning, business and management, environmentalpolicy and international relations – simulation-games have been used extensively since aboutthe 1950s (Duke 2000; Shubik 1975). Both gaming and GDSS are now widely applied andhave acquired institutionalized acceptance as methods of supporting strategic decision andpolicy-making in the public and private spheres (Bongers 2000; Dennis and Gallupe 1993;Genugten et al. 1998; Geurts et al. 1998; Nunamaker et al. 1997; Underwood and Duke1987; Vreede and Briggs 1999). Many authors have tried to capture the great diversity ofeither GDSS (McGrath and Hollingshead 1994) or gaming (Klabbers 1987) in a taxonomyor classification. Because of the great variety of both methods, most of these taxonomiesand classifications fall short. For reasons of focus, we will not try to discuss or (re)structurethis diversity of definitions and taxonomies here, but limit ourselves to a brief descriptionof how we will interpret GDSS and simulation-games.

2.1. Group Decision Support Systems

As has been stated in many other publications, computer-based systems appear under sev-eral names for group support, such as GroupWare, Electronic Meeting Systems, Collabo-rative Systems, Computer-Supported Co-operative Work, and Group Decision SupportSystems. In our case, we will make single reference to “GDSS”, meaning a relatively broaddomain of related systems that either support group work and communication (such as withGroupSystems) or facilitate collaborative or interactive group decision-making (such aswith Decision Explorer and Group Explorer) (Eden and Ackerman 1998, 2001).

Here we will not discuss the large number of definitions of GDSS that can be found inthe relevant literature but simply define them as “a system consisting of computer software,computer hardware, meetings procedures, and facilitation that supports groups engaged inintellectual collaborative work” (Eden 1995, Vreede and Mgaya 2001; cf. other definitionsby DeSanctis and Gallupe 1987, p. 589; Huber 1984, p. 195 see also Bongers 2000). Thisrather broad definition allows us to consider and study a range of different types of GDSSin relation to gaming.

First and foremost, we will incorporate systems such as GroupSystems and MeetingWorks.These systems include a number of tools, such as for brainstorming, categorizing and vot-ing, in combination with technical features such as electronic screens, the display of infor-mation or electronic message exchange between participants (Affisco 2000; Nunamakeret al. 1997; Vreede and Briggs 1999). Second, our definition also incorporates group modelbuilding systems such as Decision Explorer, Group Explorer and similar but less familiarapplications such as DANA (Dynamic Actor Network Analysis, DANA, cf. Bots et al. 1999).We consider these systems GDSS because they are computer-based tools to support deci-


sion-making that are to be used in a collaborative (group) environment. Third and last, wealso include some domain specific collaborative decision-making tools, such as MEDIA(a collaborative modeling tool for urban renewal) or a simulation building block tool forthe collaborative planning and design of a container terminal. Although some may arguethat such systems are not truly GDSS, we include them because they allow a group of peo-ple to explore decisions and assess the results in a collaborative, computer supported inter-active environment (Bueren et al. 2002; Valentin and Verbraeck 2002; Verbraeck andValentin 2002).

2.2. Gaming

Simulation-games are a simplification and condensation of a real system, allowing partici-pants to experiment safely with (future) decisions and institutional designs, and reflect onthe outcomes. These experiences are relevant for a better understanding of how complexsocial-technological systems work and how to manage and design them (Mayer andVeeneman 2002). In games of this type, a relatively large group of people (re)enacts a partof reality in order to understand and learn to manage that part of reality better than theywere able to before. This (re)enactment is usually formatted and supported by professionalgame designers and moderators. The heart of each simulation-game is a plot of events calleda scenario. The participants in the simulation-games play various “roles” that are derivedfrom existing organizations and individuals. In a number of rounds, the participants makedecisions, form coalitions and make compromises based on their given and/or self-con-strued goals and interests.

Games used for decision and policy support are usually very open games in many casesmoderately supported by advanced computer technology, in particular for accounting pur-poses (Duke 1998, 2000; Underwood and Duke 1987). Open games imply that the partici-pants are or represent the real stakeholders and face actual problems, and that the outcomeor message of the game is not predefined but is discovered during social interaction. Theoutcomes of the game are not strictly controlled, but a wide range of behavioral patternsmay emerge from actor interactions. In other words, participants are allowed to construetheir own game to a certain extent. Games of this type can have three main functions (Mayerand Veeneman 2002):

1. Learning: The games are experiential environments in which participants can learn (about)the system at hand.

2. Research: The games are experimental environments through which researchers can learnabout the system from the interaction between the participants and the interaction betweenthe participants and (computer) models.

3. Intervention: The games are experimental environments in which both researchers andparticipants can make conceptual and instrumental inferences for real decision-makingand policy-making.


2.3. Differences and complementarities

In a general sense, the similarities between GDSS and gaming are clear. They are highlyinteractive, facilitated group methods used for the support of complex decision-making andpolicy-making (Asselt and Rijkens-Klomp 2002; Geurts and Joldersma 2001). Both meth-ods are suitable for complex, ill structured problems in a multi-actor or inter-organizationalcontext. According to McCartt and Rohrbaugh (1989), GDSS refer to any application ofinformation technology to support the work of groups. Following this definition, any gameusing some form of ICT could even be considered a GDSS in itself (cf. for example theNITROGENIUS game described by Erisman et al. 2002).

However, gaming and GDSS also have a number of different yet complementary char-acteristics. GDSS have a rational-analytical focus, whereas games allow a more experien-tial exploration of a decision-making problem. In a metaphorical and literal sense, GDSSproduce “texts” through interactive analysis. In other words, they lead to a “substantive”analysis that can easily be “formalized” in a (GroupSystems’) “report”. Such a report inmost cases is also meaningful, understandable and useful for people who have not partici-pated. Gaming on the other hand triggers personal and collective learning processes throughthe experience of the game itself. These experiences need to be interpreted during a de-briefing, but they remain ambiguous and difficult to formalize and summarize – in particu-lar for people who have not participated. For complex decision-making however, bothsubstantive analysis – e.g., information structuring – and the (collective) experiences of(strategic) actor and system behavior, are equally important. This is the underlying reasonwhy a combination of the two might be beneficial. This becomes more clear when we ex-amine a number of benefits and downsides of GDSS and gaming.

Among the proclaimed benefits of the GDSS are anonymity to enhance the opennessand equality of communication, parallel input to increase the speed and quantity of com-munication and group-memory to improve the storage and use of information (Vreede andMgaya 2001). The use of GDSS enhances among others group creativity and mutual un-derstanding (Nunamaker et al. 1997). In contrast to gaming, however, GDSS have not beenvery effective in disclosing the unrevealed world of implicit motivations, hidden agendas,political wheeling and dealing and organized chaos that is characteristic of complex deci-sion-making in multi-actor situations. Vreede and de Bruijn (2000), for example, have ar-gued that there are various important differences between the assumptions of GDSS andthe political rationality of complex decision-making in inter-organizational settings. GDSSsystems assume that communication between actors should be fair, open, rational, basedon as much information exchange as possible between participants who are willing andco-operative by nature. In contrast, many decision-making processes are full of conflictand brimming with strategic behavior and manipulation. This might be one of the reasonsthat research of user satisfaction with GDSS meetings indicate that particularly CEOs, toplevel bureaucrats or politicians prefer (more) ordinary face-to-face communication, moretime for ordinary discussions and more in-depth verbal discussion (see also Keller et al.1991; Nunamaker et al. 1991; Vreede and Muller 1997).


Gaming methods in contrast do take the political rationality and the strategic behaviorof decision-making into consideration. Gaming methods are particularly strong in explor-ing what can or will happen in a decision-making context where “the social-political con-text of the system shows many actors that may be strategic or a-rational” (Duke 1980, p.365). Among the proclaimed benefits of gaming are achieving “a dynamic and holistic view”or “getting the big picture” (Duke 1974). Simulation-games show how a variety of mecha-nisms work together, but are not very well suited to gain an in-depth focus on the effects ofa single mechanism, nor in finding instrumental recommendations or solutions to prob-lems.

Furthermore, if the aim of the simulation-game is to communicate the big picture and toget participants to see how actor behavior causes system behavior, it is absolutely neces-sary to keep track of and understand what is happening during a game. Often we find thatthe players lose sight of what is happening in the game, just as they lose sight of what ishappening in reality. It is therefore necessary to confront players afterwards with whathappened outside their immediate perception or to get participants to explain why they actedas they did and draw lessons from the effects (Thiagarajan 1993). In other words, monitor-ing, evaluation, debriefing and drawing conclusions for real decision-making and policy-making are essential but rather complicated issues in gaming. Table 1 displays an overviewof the main characteristics of GDSS and gaming, as we see them.

The above-mentioned characteristics of GDSS and gaming lead to the following assump-tions about how they can be combined:

1. GDSS can provide a number of communication and support tools for game design, op-eration and use. By using GDSS in and for gaming, the efficiency and effectiveness ofgaming for policy and decision support can be enhanced.

Table 1. Overview of characteristics of GDSS and gaming

Characteristics GDSS Gaming

Problems Complex multi actor problems Complex multi actor problemsMethod Interactive facilitated group Interactive facilitated group

method for decision and policy method for decision and policysupport support

Way of thinking Analytical rationality Strategic and political rationality

Leads to . . “Texts”; an analysis of Learning experience: an analysissubstantive aspects of complex of social-political context ofmulti actor problems complex problems

Main advantages Group memory/fast/ Group experience/big picture/anonymous/information holistic view/dynamics ofgeneration and retention/ social interaction/Strategic andInstrumental inferences tactical inferences


2. Gaming can render a dynamic and political multi-actor setting for exploring, testing, andtraining for (existing or new) GDSS. This can lead to better GDSS tools and proceduresthat have been validated for use in complex multi actor contexts.

3. Combining GDSS and gaming; cases and experiences

3.1. ICT in gaming

Over the years, the arrival of smaller and faster computer and ICT technology has openedup many new avenues for gaming simulation. The early business and management games,for example, characteristically lasted several weeks in order to give the participants andthe assessors the opportunity to calculate the decisions and their effects on handheld calcula-tors (Affisco 2000; Duke 2000). Now the players and game operators can use spreadsheetsand computers models. Competitive games, for example, are usually computer-centeredbecause the rules of competition should be uniform, fast and undisputed.

The widespread availability of personal computers makes it possible to arrange directinteraction between players and a computer model (Duke 2000; Thavikulwat 1999). Dur-ing the last few years, significant advances have been made in multi-player-computer in-teraction through (distributed) Local Area Network (LAN) or Internet games (Askawa andGilbert 2003; Dasgupta 2003; Hansmann et al. 2002; Lainema 2003; Pillutla 2003). Forthese and other purposes, Game and Simulation engines (Martin 2000), Intelligent Tutor-ing Systems (Angelides 1999) and Computer Based learning environments (Lainema 2001)have been developed. In addition, modern ICT technology allows the use of email serv-ices, multimedia, 2-D or 3-D animation, Decision Support Systems (DSS) and Group Deci-sion Support Systems in and for games (Affisco 2000; Meinsma et al. 1998; Thavikulwat1999).

3.2. Reported examples in the literature

In an early publication, Khoong (1995) already argued for the development of DecisionSupport Systems for gaming. More recently, Affisco (2000) described a proposal to useGSS for a plant location game with students. However, an extensive literature search onlyrevealed a limited number of cases where gaming and GDSS were combined or related.Very few references to gaming were found in the large body of literature on GDSS, EMSand collaborative decision-making methods. A much wider number of gaming-related caseswere found that accepted a broad and general meaning of GDSS. Most of them were con-cerned with systems dynamics modeling and similar techniques for accounting purposes(cf. Meadows 1989; Vennix 1989). Because these are computer-based or computer-medi-ated simulation-games, they are outside the scope of this study.

However, the limited number of cases that were found, provided interesting startingpoints for a reflection on the combined use of GDSS and gaming. Erisman et al. (2002),


for example, developed a game called NITROGENIUS that was used as a multi-user De-cision Support System to develop the optimal policy for solving the Dutch nitrogen pollu-tion problem. In their overview of lessons from decades of using GDSS, Nunamaker et al.noted that GDSS can reduce the time required for model building (Nunamaker et al. 1997).Although there are obvious similarities, no references were found in GDSS literature ofusing GDSS for game development, but we must assume that GDSS are used for this pur-pose. For example, GroupSystems was used in a session with experts and game designersto develop ideas for the game WATER FOR SPACE (W4S) (Carton et al. 2002). In a simu-lation-game called PORCULO, Mastik et al. (1995) ex-ante evaluated the possible effectsof planned “manure emission” legislation in the Netherlands. In order to be able to vali-date the simulation experiment, they compared the results of the game with the outcomesof a session held with experts in a Group Decision Room. GroupSystems was used in anumber of cases to arrange and facilitate interaction between players during the game(Meinsma 1997; Peperkamp 1996; Vreede and Briggs 1999; Wein et al. 1998). In a gamecalled DUB, de Vreede and Briggs (1999) used GroupSystems for gaming in co-locatedand distributed sessions of scientific education. Gieszen et al. (1998) reported about theuse of a system called CreaLogic for a co-operative business game. In a study on the co-ordination of distributed policy work, Laere (2003) developed and used a tailor madeEMS and distributed communication system for a game called POLITEAM (Laere 2003;Laere et al. 2001). One general example was found in which a gaming context was usedto study the effects or implications of GDSS (Smits and Takkenberg 1998). Table 2presents an overview of the games we were able to find in the literature, in which GDSSwere used.

3.3. Four empirical cases

Between 1999 and 2003, four simulation-games were designed and played in which weused GDSS systems: INCODELTA, INFRASTRATEGO, CONTAINERS A DRIFT andDUBES. In three of the four cases, we used GroupSystems for improving the operation orevaluation of the game itself (Mayer and Veeneman 2002). In two of the four cases, wedeliberately designed and used a simulation-game for developing, testing, studying a newand domain specific GDSS system (Bockstael-Blok et al. 2002; Bueren et al. 2002; Mayeret al. 2002; Valentin et al. 2002). Below, we will briefly introduce the games and discusshow and to what result the GDSS systems were combined with gaming. Table 3 displaysan overview of some general characteristics of the games in terms of time period, numberof sessions, type of participants, etc.

1. INCODELTAThe INCODELTA game was designed in 1999 on commission by a collaborative projectteam consisting of Dutch government departments, regional authorities and private andsocial organizations (Jong and Mayer 2002). The objective of the game was to experimentwith, and evaluate two alternative decision-making models – a Status Quo model and analternative called Bay Area – for a number of modernization plans in the field of freight


transport. The participants were the real decision-makers and stakeholders. The game wasplayed once with professionals and twice with students and provided ideas and recommen-dations for adaptation or improvement of the status quo. The game and its outcome wereboth evaluated positively by the participants (Jong and Mayer 2002).

During the game, the participants negotiated face-to-face, but GroupSystems was usedfor evaluation purposes during and after the game. Because the objective of the game wasto compare two alternative models of decision-making, a method was needed that wouldallow us to evaluate them in a fast and valid way while not disturbing the game. In order torealize that objective, the Vote tool in a mobile version of GroupSystems was used to takea number of interim measurements of participants’ opinions about the two decision-mak-ing models during the game. The immediate feedback from the comparative results greatlyenhanced group discussions at the end of the game. In order to draw lessons and conclu-

Table 2. Cases of GDSS and gaming

Game Subject of game Reported use of GDSS Reference

NITROGENIUS Dutch Nitrogen Pollution Problem. Game is a multi-player GDSS. Erisman et al. 2001

W4S Water management. GDSS used for game Carton et al. 2002

development sessions with

experts and designers.

PORCULO Ex-ante evaluation of manure GroupSystems session used Mastik et al. 1995

emission legislation. as a “control method”.

DUB game Simulation of a government GoupSystems used for Game Vreede and Briggs

department and clients in need of interaction; co-located and 1999

IT changes. For teaching purposes. distributed sessions.

Untitled game Investment decisions at GoupSystems for game Peperkamp 1996

Amsterdam Airport Schiphol. interaction among part.

Untitled Business game Vert. and hor. communication GroupSystems used to improve Wein et al. 1998

in a simulated organization. communication and make game

more effective.

Untitled game Plant location decision-making GroupSystems for game Affisco 2000

exercise. interaction

Untitled Business game Co-operative decision-making CreaLogic groupware for Gieszen et al. 1998

providing game environment.

ELECTRA C0-generation and liberalization Group Decision Room used for Meinsma 1997

power industry game interaction; tailor made

GDSS for game.

POLITEAM Distributed co-ordination of Tailor made EMS and GDSS Laere 2003

Amsterdam police force. system developed for game.


sions, the Categorizer tool of GroupSystems was used for an extensive evaluative discus-sion. This resulted in a large number of conclusions and recommendations that could bediscussed and taken home by the participants. The use of the GDSS for this purpose waspositively evaluated by the game designers, the client and the participants. It strongly in-duced us to experiment with GDSS in other games.

2. INFRASTRATEGOThe INFRASTRATEGO game was developed for academic research purposes between2000 and 2002 (Kuit and Mayer 2002). The objective of the game is to study and evaluatehow strategic behavior in a liberalizing the Dutch power industry will affect the “level play-ing field” and the “public values” in the sector and to draw recommendations for policy-making and regulation. The gradual liberalization and the various roles and tasks of theplayers are based on existing laws and regulations. During the game, the various compa-nies in the power industry negotiate and settle contracts for the supply of electricity whilebeing supervised by the energy regulator and national government and influenced by con-sumer interest groups.

Table 3. Overview of the four gaming cases

INCODELTA INFRASTRATEGO CONTAINERS DUBES

Content of game Decision-making on Liberalization and Planning and design Planning a sustainable

transport corridors. regulation of the Dutch of an inland container urban renewal project

electricity market

2002–2006.

Time period played 1999–2000 1999–2002 2000–now 2000–now

No sessions 3 15 20 5

Players Students and real Students and real Students. Students and real

decision-makers. decision-makers. decision-makers.

Type of GDSS Group Systems. Group Systems. Simulation building Group Systems and

block tool. MEDIA.

Purpose GDSS – 1. Interim 1. Interim 1. Game used for 1. Game used for

gaming combination measurements during measurements during testing of and training testing of and training

game (Vote) game (Vote) for a new GDSS tool. for a new GDSS tool

2. Recommendation 2. Debriefing and (MEDIA)

of conclusions from evaluation at end of 2. GroupSystems used

game (Categorizer). game (Categorizer) for evaluation of

3. Evaluation of Game game and MEDIA

(Survey) (Survey);

4. Interaction between 3. Interaction support

participants and/or (Vote);

game leaders

(Categorizer).


Over the years, INFRASTRATEGO has been played about fifteen times, both with stu-dents and with professionals from the industry and regulatory institutions. In each edition,about forty players divided over 15 roles played the game. INFRASTRATEGO is a highlysocial interactive game, although an extensive computer model of the electricity marketprogrammed in Excel is used as an accounting system. Game operators enter contracts andother decisions made by the players into the computer model. While every half hour rep-resents half a year in reality, the results are fed back periodically to the participants by meansof “past performance” indicators.

Because the game proceeds at a very rapid pace, a monitoring system was needed tokeep track of shifting power relations and mutual trust among the players. Inspired by thepositive experiences during the INCODELTA game, we used GroupSystems for monitor-ing and evaluation purposes. Using the Vote tool, we arranged interim measurements ofthe players” opinions about each other’s trustworthiness, influence, and strategic behavior.At the end of the game, we used Categorizer for a general group discussion on strategicbehavior during the game. The results of these evaluations and discussions were used tostimulate ordinary group discussions. During the INFRASTRATEGO game, we also usedGroupSystems’ Categorizer to arrange chat functions and message exchange between theparticipants. GroupSystems was also used to provide a Bulletin and Media board and pro-vided very effective means of communication between game leaders and players.

3. CONTAINERS A DRIFTThe objective of the game CONTAINERS A DRIFT is to validate and improve a specificGDSS tool for collaborative decision-making about an inland container terminal to be lo-cated near a fictitious but realistic provincial town. The game was developed between 2000–2001.

In this game, we used a different combination of gaming and GDSS than described above.In short, the background of the tool and game is as follows. Discrete event simulation is apowerful methodology for evaluating the (logistical) design of infrastructure systems stillto be built, such as airports, harbors and railways (Banks 1999, see also Valentin andVerbraeck 2002; Verbraeck and Valentin 2002). However, several authors have concludedthat the level of knowledge and the amount of time required to build, adjust and run a simula-tion model constitutes a major obstacle for interactive stakeholder decision-making(Keller et al. 1991; Robinson 1999; Sadowski et al. 2000). Faced with the challenge ofincreasing the speed and ease of making a discrete event-simulation model, we devel-oped a collaborative simulation tool that allows the stakeholders to make a valid modelof a container terminal in a few hours (Bockstael-Blok et al. 2002; Mayer et al. 2002;Valentin et al. 2002). The same approach using different building blocks could be usedfor similar projects.

The use of the GDSS tool starts by defining specific sets of components, called “mentalbuilding blocks” of what the decision-makers may encounter in their system design - forexample, a road, a truck or storage. A visual system design can be constructed by selectingand connecting various Visual Building Blocks. Subsequently, the visual representationof the design can be loaded automatically into dynamic simulation tools such as Arena(www.arenasimulation.com) and Promodel (www.promodel.com). The generated perform-


ance data can be collected as statistics of the domain-specific building blocks and pastedinto a status report tailor made for the problem at hand.

In order to experiment with the tool and evaluate it, we developed the game CONTAIN-ERS A DRIFT. The game is played with 25–35 participants divided over 10 roles. The play-ers explore and negotiate about the container terminal while using the simulation toolinteractively in alternating plenary and parallel working sessions. In practice this meansthat for each working session, one participant facilitates the group discussion, while an-other enters the outcomes of the group discussion in the computer model. The completedesign process can be seen by the group on a projection screen. The performance of thegroup’s design can be assessed within minutes, so that they can restart or refine their nego-tiations on the basis of the outcomes.

In the last two years, about 20 sessions of CONTAINERS A DRIFT have been held.The evaluation results reported in other publications have shown that the GDSS tool is fast,easy to work with, contributes to the quality and progress of negotiation, and generatesmutual understanding (Bockstael-Blok et al. 2002; Mayer et al. 2002; Valentin et al. 2002).The GDSS has since been sufficiently validated and tested in the game and is now ready tobe used and tested in real life decision-making.

4. DUBESBetween 2000 and 2003, a number of researchers working at Delft University of Technol-ogy and two consulting organizations developed a sustainable decision-making method(abbreviated to DuBes in Dutch). This collaborative method helps stakeholders to reducethe complexity of sustainable urban renewal projects. It is based on a domain-specific GDSS,called Modeling Environment for Design Impact Assessment (MEDIA), which is a modi-fication and extension of AIDA (Analysis of Interconnected Decision Areas, see Morgan,1971) (Bueren et al. 2002).

In order to further develop, evaluate and communicate about MEDIA to potential users,the tool was embedded in the DUBES simulation-game. The DUBES simulation-gameallows participants to test the DuBes method in a safe environment while the DuBes projectmembers validate and approve their method and tools at the same time. About 40 partici-pants take part in the game, playing 12 roles. The simulation-game revolves around therestructuring of an existing or fictional post-1945 residential neighborhood. The partici-pants design a program of requirements for the renewal of that neighborhood while usingMEDIA in interactive plenary and parallel working groups. So far, the DUBES game hasbeen played five times with students and professionals working in the field. It has beenapplied to a realistic but fictitious case, as well as an existing case of urban reconstruction.The MEDIA-GDSS system has now been evaluated extensively, and results from experi-ences in the game have been used to improve MEDIA (see Bueren et al. 2002).

GroupSystems has also been used in the DUBES game. At the beginning of the game,the participants prioritize about 150 decision fields in order to pre-structure the discussionand use of the MEDIA tool. The GroupSystems’ Survey tool is used to evaluate MEDIAand the working procedure by taking interim measurements of participants’ opinions dur-ing the game.


Table 3 displays a summary of the specific ways in which GDSS and gaming were com-bined in the four cases (see Table 3, last row). In the section below, we will now restruc-ture the specific combinations we have found in the literature (see Table 1, third column)and our own cases, into a more general classification of possible GDSS and gaming com-binations.

4. A Classification of Gaming-GDSS Combinations

An analysis of the cases discussed above indicates that (at least) four general and effectivecombinations of GDSS and gaming can be distinguished.

1. GDSS for game design.2. GDSS for game evaluation.3. GDSS for game operation.4. Gaming for GDSS research, testing and training.

1. GDSS for game designGDSS systems can be a useful tool in a game design process. Game design – particularlythe stage of conducting a “systems analysis” – can be time-consuming (Duke 1980). It re-quires a sophisticated analysis of stakeholders, their mental models, interests, resources andrelations. Moreover, it implies obtaining relevant information about major problems, fu-ture developments and decision and money flows. Interviews and workshops with clientsand experts in the field are essential at this stage. Here, GroupSystems and other GDSSsuch as group modeling building tools, can play an important role in speeding up gamedesign, enhancing creativity, information retention, and conceptual and visual analysis ofdynamic systems and problems.

2. GDSS for evaluation of the game and during a gameThere are two types of evaluation in gaming: 1. evaluation of the game, and 2. evaluationin the game. Both can be done much more efficiently by using GDSS. First, the quality andvalidity of the game design can be measured by:

1. Anonymously filling out evaluation questionnaires at the end of the game.2. Comparing the results from GDSS sessions with experts and with the results of a simu-

lation-game experiment (cf. Mastik et al. 1995). By doing this, the methods and the re-sults are validated and gain in richness.

Second, keeping track of what happens during a game is an important but difficult task forgame observers and moderators. It is essential for drawing conclusions and recommenda-tions from the game for decision-making and policy-making. And although one can nevercapture everything that happens, it can be useful to use GDSS to more effectively monitorthe process and support the evaluation and debriefing rounds. This has the advantage that


quantitative and qualitative responses and interim measurements can be fed back to thegroup at the end of the game in order to structure the debriefing and evaluation round, butalso to interpret the lessons of the game afterwards and report about them. As describedabove, a GDSS system was used for the following purposes:

1. Repeated interim measurements – for example, regarding the changing perceptions aboutthe power or trustworthiness of other stakeholders or the course of developments duringthe game.

2. A (quick) round of reactions and recommendations at the debriefing and evaluation stage.3. Organizing a session using GDSS with (a selection of) game participants, shortly after a

(series of) game(s) to draw lessons and formulate recommendations for decision-mak-ing or policy-making.

3. GDSS for game operationIn this type of application, GDSS are used to play the game or to moderately support therunning of the game itself (Affisco 2000). From the cases and the experiences describedabove, we have found applications where GDSS were used to:

1. Play the game fast and anonymously and record everything that happens during discus-sions and interactions.

2. To arrange “chat and message exchange” services between participants during the game,for example, in cases of distributed interaction.

3. To enable participants to use techniques such as brainstorming, voting and nominal grouptechniques during the game (for example, for training, research or teaching purposes).

4. To arrange means of communication and support between participants and game opera-tors.

5. To introduce Media messages, bulletin boards and “events” into the game.

4. Gaming for GDSS research, testing and trainingIn this type of application, gaming techniques are used to develop, test and study the effec-tiveness of a (new) GDSS system. A game environment constitutes a safe and controlled,yet realistic environment where the uses and impacts of GDSS on various experimentaland control groups can be observed and measured (cf. Smits and Takkenberg, 1998). Fur-thermore, a number of case studies indicate that simulation-games are excellent inter-or-ganizational testing and research environments for pilot versions of GDSS. The developmentof the MEDIA support tool and the simulation building-block approach greatly benefitedfrom the experiences in the DUBES and CONTAINERS A DRIFT games, respectively. Itallowed us to link new ways of interactive working to decision support systems and viceversa. In short, the simulation-games were used to answer the following questions:

1. Does the Group Decision Support System work?2. How and under what conditions does the Group Decision Support System work?3. Can we show the potential users that it works?4. Can we teach potential users how to work with it?


AnalysisIt is clear that the four ways of combining GDSS and gaming described above are notmutually exclusive and can be used in combination or alternation. An intelligent arrange-ment of GDSS supported meetings before, during and after a simulation-game can evenhave added value to using such methods in a single manner. In fact, the way in which theGDSS and gaming combination create synergies for the further development of both of themis highly dependent on the purposes of the project and the intentions of the client. By at-tempting to provide an exhaustive list of potential combinations or ways in which they canbe combined in practice, the authors would constrain the creative potential of future de-velopers of collaborative and interactive group support systems. However, by means ofillustration, let us just consider an imaginary project where, for instance, a group of keystakeholders and representatives of the client is invited to participate actively in one or moreGDSS meetings that are used to conduct a systems analysis that is the input for a simula-tion-game design. Most likely, such a collaborative stakeholder process by itself contrib-utes to a shared and enriched perception of reality, problems and solutions. It could alsocreate commitment for the game and the possible outcomes among the stakeholders. Thesame group of stakeholders can be invited to help translate the experiences into conclu-sions and recommendations some time after the game. Here, GDSS can also be helpful tolink the analysis that is conducted before the game, the evaluations during and immedi-ately after the game with the reflections and recommendations that are needed in the weeksor months after the game. In this manner, the outcomes of the GDSS sessions before, dur-ing and after the game can also be compared, refined or modified – or even be used forevaluation of the effects of the intervention on the problem perception or type of solutions.In other words, whereas the systems analysis leads to a shared vision on the current systemand to assumptions about the possible effects of certain decisions, the game itself and itsevaluation leads to a refinement and testing of these perceptions and assumptions. How-ever, these game experiences as we have argued are experiential and hard to formalize orturn into actions. Here GDSS sessions can be helpful to converge the lessons of the gameand generate conclusions and recommendations. Vice versa, a simulation-game can con-stitute a safe but realistic environment for studying, testing and demonstrating new GDSSor applications of them. A simulation-game challenges possible users to consider the useof GDSS in a political-strategic context and to specify the social interactive processes thatare needed to make them effective.

5. Conclusions

In this contribution, we have explored the possibilities of combining GDSS and gamingand argued that gaming and GDSS are complementary and at times mutually corrective.We are aware that more questions can and should be raised, for instance with regard to GDSSsystems, distributed collaboration and Internet gaming. Furthermore, systematic empiricalevaluations of new cases are needed to substantiate whether the combined use of gamingand GDSS for instance generates deeper understanding, contributes to a support base orotherwise enhances decision-making. Based on a limited number of cases reported in lit-


erature and four games we designed ourselves, we have presented a classification of (atleast) four ways in which GDSS and gaming can be used complementary. These are, theuse of GDSS for game design, for game evaluation, for game operation and last, the use ofgaming for GDSS research, testing and training. We have illustrated that the use of GDSSsuch as GroupSystems can significantly increase the effectiveness of gaming-simulationfor decision support. As game designers, it allows us to arrange new and more effectiveways of communication and interaction among participants and between participants andgame operators. Furthermore, one of the strongest benefits of GDSS for gaming is that itprovides an answer to a difficult question of game evaluation: how to monitor and possi-bly measure what takes place during a game, without disturbing the game? GroupSystemsprovides a number of tools such as voting and has a number of advantages (fast, anony-mous, immediate feedback) that have been quite useful for evaluation during and at theend of a game. In this sense, it has truly been complementary to some of the disadvantagesof gaming. In our view this is related to the fact that GDSS are effective in acquiring infor-mation on the stated preferences of stakeholders in multi-actor policy-making settings, whilegaming, is better suited for obtaining information on the strategies in action or the revealedpreferences. However, while GroupSystems has proven to be effective, the system itself isnot specifically designed for gaming purposes. Several modifications for instance to theevaluation tools, can and should be made to make it even a more suitable system. Maybeeven an adapted or tailor made system for gaming purposes could be designed.

In our view, the reverse combination, i.e., the use of gaming for GDSS, has also provento be effective. Two of our own cases have shown that gaming can create a realistic, butrelatively safe and controllable environment for (re) developing, testing and studying theuse of existing or new GDSS systems. Both users and developers of such systems can benefitfrom these experiences before they are applied to real world problems with real stakeholders.In this way, a game also supports the teaching and training of students and professionalson how to use these GDSS systems in a real world.

A more general remark is that we strongly believe that more attention should be paid tothe way methods for decision support such as GDSS and gaming, and possibly other meth-ods such as scenarios, can be combined (Mayer et al. 2004). This may contribute to thedevelopment of new and better decision support methods and lead to the development ofa comprehensive methodology for interactive decision support methods.

Notes

1. The authors would greatly welcome reactions and case reports from readers describing their experienceswith combinations of GDSS and gaming.

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