A General Process for Developing Business Simulations Games

Claudia Ribeiro, Jos

e Borbinha, Jo

ao Pereira and Jos

e Tribolet

INESC-ID, Rua Alves Redol, Lisbon, Portugal

Department of Information Systems and Computer Science, IST/UTL, Lisbon, Portugal

Keywords:

Business Simulations Games, Simulation Development Process, Enterprise Modelling, Agent-based Models.

Abstract:

Nowadays people, groups and organizations are increasingly confronted with problems and situations that

show an increasing level of complexity. However, human abilities to deal with complex dynamic systems and

processes, while behaving in a sustainable way, have not improved to the required extent. One way to deal

with complex situation is the simulation approach: build a simpliﬁed model of this reality, learn from this

simpliﬁed model, and, ﬁnally, translate the ﬁndings or knowledge back to reality. Simulation games are based

on this idea. Nevertheless, if we want to make inferences about reality based on experiences and knowledge

acquired in a simulation game, we have to be sure that the underlying conceptual model is a good, or valid,

representation of the real situation. Based on knowledge gather from the simulation development process and

Agent-based Modelling, this paper proposes a general process for developing business simulation games.

1 INTRODUCTION

A computer simulation is a computer program that

attempts to simulate an abstract model of a particu-

lar system and conduct experiments with that model

(Smith, 2009). Computer simulations are being used

as a tool to explore and gain new insights in many

scientiﬁc areas such as physics, astrophysics, chem-

istry, biology, human systems in economics, psychol-

ogy, social science and engineering. In this context

simulation typically emphasizes a more academic and

throughout exercise, often involves a model of a pro-

cess, and typically supports learning speciﬁc content

or about decision making. Another important use of

simulations is for educational purposes where they are

often denominated simulation games. Some exam-

ples where they have been successfully applied are

the following. Medical researchers and surgeons are

increasingly trying out operating techniques on a vir-

tual patient before testing or using them on real pa-

tients; navigation and ﬂight simulators are used to try

out complicated manoeuvres by ships or aeroplanes;

preliminary designs of complex machines like nuclear

reactors, products and processes are tested by way of

three-dimensional simulation software, and so forth

(Berends and Romme, 1999).

There isn’t an agreement regarding the boundaries

of what is a game and what is a simulation and where

do these two concepts meet. In this paper we regard

simulation both as a tool to explore and gain new in-

sights in scientiﬁc areas and also as a tool for educa-

tional purposes, therefore we have adopted the deﬁ-

nition given in (Galv

ao et al., 2000): ”A simulation

game is a mixed feature of a game - competition, co-

operation, participants and rules, etc, with those of

simulation - incorporation of critical features of re-

ality. While the beneﬁts outlined above have been

known for long, today we ﬁnd limited use of simula-

tion games in organizational contexts both for learn-

ing or to support decision making. Several factors

contribute to this, namely current simulation games:

have lack of ﬂexibility; lack of level-of-detail; lack

of multi-state frameworks consisting of theoretical

concepts; and the inability to support the creation of

complex business models (Peters et al., 1998; Galv

et al., 2000; Garris et al., 2002).

Given these limitations, this article proposes a

general process for developing business simulation

games. We start by describing (section 2) the over-

all process of developing a simulation game. This

process is based on proposals made by different re-

searchers developing simulation games for different

contexts. Next (section 3), we give an overview of

the underlying concepts of Agent-Based Modelling.

Then we move on (section 4) to a discussion where

a general process for developing business simulation

games is described as well as the current challenges

in this area. Finally (section 5) conclusions are drawn

190

Ribeiro C., Borbinha J., Pereira J. and Tribolet J..

A General Process for Developing Business Simulations Games.

DOI: 10.5220/0004061001900193

In Proceedings of the 2nd International Conference on Simulation and Modeling Methodologies, Technologies and Applications (SIMULTECH-2012),

pages 190-193

ISBN: 978-989-8565-20-4

 2012 SCITEPRESS (Science and Technology Publications, Lda.)

pointing to the future scope for development that lies

ahead on this vast and interesting ﬁeld.

2 THE SIMULATION

DEVELOPMENT PROCESS

Over the last decades several development processes

have been proposed to devise business simulations

(Mikkelsen. H and Riis, 1995; Peters et al., 1998;

Martin, 2000; Galv

ao et al., 2000; Garris et al., 2002;

Kriz, 2003; Smith, 2009). Most of these processes are

directed at developing environments that are suitable

for learning but a few also take into account the po-

tential for promoting organizational change through

aligning actors mental models or experimenting dif-

ferent situations. Although the development pro-

cesses underlying the approaches described by those

authors use different terms and their extent is at some

level according to different stages it is also possible

to, in a higher level of abstraction, to identify a num-

ber of stages that are common to all. Accordingly, we

identiﬁed ﬁve different stages with three broad rela-

tionships, namely conceptualization, application and

reﬂection. The general simulation game development

process can be depicted in ﬁgure 1. Conceptualization

Figure 1: The general simulation game development pro-

cess.

is composed by three main principles: reduction; ab-

straction; and symbolization (Peters et al., 1998). Re-

duction means that we make a selection of elements

from the reference system (the domain of the prob-

lem at hand) that have to be included in the game

model: We include the elements that seem relevant to

us, and we leave out the elements that are less impor-

tant. Abstraction implies that the elements included

in the game model are not necessarily as detailed as

they are in reality: We deliberately simplify them to

make our model less complex. Finally, symboliza-

tion deals with the fact that the elements and rela-

tions of the reference system are modelled into a new

symbolic structure, namely, into scenario, roles, rules,

and symbols, which are the most important basic el-

ements of a game. Some game elements may quite

resemble their counterparts in reality, but other ele-

ments may undergo a metamorphosis and have a com-

plete different appearance in the game model. The

second relationship - application - is related to the

game play. When players interact with the simulation

game speciﬁc game reality emerges. The ﬁnal rela-

tionship - reﬂection - is related to the acquisition of

knowledge and the evaluation of the game play. After

the game play, the players have access to a debrieﬁng

where they can view the overall progress throughout

the game and also critically evaluate the level of in-

terest of the situation that emerged in the simulation

game.

As described previously, one of the factors that

contributes to the limited use of simulation games

in organizational contexts is the inability of current

simulation to support the creation of complex busi-

ness models. This is directly connected with the

ﬁrst two stages of the general simulation game de-

velopment process, namely the deﬁnition of the prob-

lem space and designing the respective conceptual

model. Next, we summarize the underlying concepts

of Agent-based Modelling.

3 AGENT-BASED MODELLING

Formally, agent-based modelling is a computational

method that enables a researcher to create, anal-

yse, and experiment with models composed of agents

that interact within an environment (Gilbert, 1998).

Agent-based modelling has been successfully used

in behavioural economics, political science and so-

cial sciences for studying social phenomena. It has

been argued that these models include more realis-

tic assumptions about behaviour, structure, and tim-

ing therefore, representing a powerful engine for gen-

erating insights in complex adaptive systems (Miller

and Page, 2007). Agent-based models are character-

ized by the following (Chang and Harrington, 2006;

Miller and Page, 2007; Macal and North, 2010):

• A Set of Agents, Their Attributes and Be-

haviours: The behaviour can be either accord-

ing to rational models, behavioural models or rule

based models.

• A Set of Agent Relationships and Methods of

Interaction: An underlying topology of connect-

AGeneralProcessforDevelopingBusinessSimulationsGames

191

edness deﬁnes how and with whom agents inter-

act.

• The Agents Environment: Agents interact with

their environment in addition to other agents.

• Model Outcomes: Simulating a set of agents in-

teracting in an environment provides insights into

phenomena related to the part of reality being sim-

ulated.

The underlying assumption for using agent-based

models to model reality in organizations is to view or-

ganizations as complex adaptive systems that emerge

from the interactions among human agents. Under

this assumption organizations have properties such as

emergent behaviour, self-organization and evolution

(Magalh

aes, 2004). In this context, to take an agent-

based approach means not having to assign an ob-

jective to an organization and instead modelling the

agents that comprise it with explicit attention to how

decisions are made and how interaction of these de-

cisions produce organizational output. In this sense

researchers using this approach are interested in un-

derstanding how can organization behaviour be sim-

ulated using agent-based models, and which agents

intrinsic properties have an impact on organizational

performance. Therefore, in addition to the standard

model building tasks, practical ABM and simulation

requires one to (Macal and North, 2006) (i) iden-

tify the agents and get a theory of agent behaviour,

(ii) identify the agent relationships and get a theory of

agent interaction, (iii) get the requisite agent-related

data, (iv) validate the agent behaviour models in ad-

dition to the model as a whole, and (v) run the model

and analyse the output from the standpoint of link.

4 A GENERAL PROCESS FOR

DEVELOPING BUSINESS

SIMULATIONS GAMES

Based on the concepts presented (ABM) we have re-

visited the general simulation game development pro-

cess and added intermediate steps that address the in-

clusion of social-human domain in the business sim-

ulation game conceptual model. Speciﬁcally we have

added two steps related to the integration of ABM

simulation during the development of a business sim-

ulation game. The complete process can be depicted

in ﬁgure 2 and further details are explained next.

The general development starts with the deﬁni-

tion of the problem space that consists in deﬁning

which part of the organization, speciﬁcally the situ-

ations that which to be analysed and experienced by

players. Social systems are constructions. However,

their meaning emerges from processes of participa-

tion and reiﬁcation (Wenger, 2002). They are not

structured by external information they receive but by

internal structural conditioning and negotiated mean-

ing (Klabbers, 2003). In the next phase the part of the

reality chosen is observed as a social system and the

underlying assumptions concerning decision models

are deﬁned. This assumptions can either be accord-

ing to three main models for specifying human de-

cision models: rational models; behavioural models;

and rule-based models.

In the Validate Decision Models step the simu-

lated data is analysed in order to veriﬁed the assump-

tions made in the previous step. Some researchers ar-

gue that ABM is a third way of doing science (Axel-

rod, 1997). Like deduction, it starts with a set of ex-

plicit assumptions. But unlike deduction, it does not

prove theorems. Instead, an agent-based model gen-

erates simulated data that can be analysed inductively.

Unlike typical induction, however, the simulated data

comes from a rigorously speciﬁed set of rules rather

than direct measurement of the real world. Whereas

the purpose of induction is to ﬁnd patterns in data and

that of deduction is to ﬁnd consequences of assump-

tions, the purpose of agent-based modelling is to aid

intuition. In the next step the conceptual model is

deﬁned. This conceptual model besides the organi-

zational agents decision models also has to include

other related concepts from the organizational per-

spective of Enterprise Modelling approaches, like role

and activities and also concepts necessary to integrate

player modelling representation. The resulting con-

ceptual model is then experience by players during a

situation of play. This experience allows the player

to interact with the simulation and visualize the re-

sults of doing certain actions, how decisions are made

and how iterations of these decisions produce orga-

nizational output. In the Debrieﬁng phase the con-

ceptual model and the output results of the simula-

tion game are compared to veriﬁed the correctness of

the devised assumptions and conceptual model. Also,

in this phase the acquired knowledge and skills are

assimilated through reﬂective observation (Kolb and

Kolb, 2008) and plans for organizational change to

real situation are made. Finally, the complete process

is evaluated and recommendations for improvements

are proposed for the next iteration of the development

cycle.

5 CONCLUSIONS

The use of simulation games in a organization, can

serve as a tool to create a better understanding of

SIMULTECH2012-2ndInternationalConferenceonSimulationandModelingMethodologies,Technologiesand

Applications

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Figure 2: General simulation development process.

the prevailing organizational culture, structure, and

processes to access the risks, chances, and neces-

sities of organizational changes. Simulation games

are a method used to support people and organiza-

tions in dealing with the sustainable (re)construction

of their reality. Simulation games imitate organiza-

tional processes and changes them in an experien-

tial and playful way. This aids organizations in their

search for creative problem solution in a real-life sit-

uations. Nevertheless, if we want to make inferences

about reality based on experiences and knowledge ac-

quired in a simulation game, we have to be sure that

the game model is a valid representation of the real

situation. Therefore, the underlying simulation game

conceptual model has to integrate the different per-

spectives of business. In this paper we describe a gen-

eral simulation game development process. This de-

velopment process is a cyclic process that has seven

main steps that guide the implementation of a simu-

lation game from the deﬁnition of the problem space

until the evaluation of the output results. Future work

will include the practical application of the proposed

development process in case studies based on real-

world situations. This study will provide further in-

sights and will help to better characterized each step

of the development process and respective results.

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