J. Design Research, Vol. 5, No. 2, 2006
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Build your seaport in a game and learn about complex systems Geertje Bekebrede* and Igor Mayer Faculty of Technology, Policy and Management, Delft University of Technology, P.O. Box 5015, 2600 GA Delft, The Netherlands Fax: + 31 (0) 15 2786439 E-mail:
[email protected] E-mail:
[email protected] *Corresponding author Abstract: The authors demonstrate how simulation games can be used to test and explore initial infrastructure designs before they are implemented. Games can provide important learning experiences for (future) designers and managers. The case study of a computer-supported simulation game, SIM Maasvlakte 2 (SIM MV2), uses a game whose object is to design and allocate land for the Maasvlakte 2 port area, to be built between 2006 and 2036 in the Port of Rotterdam, the Netherlands. The evaluation aimed at improving the game, examining the system complexity of the seaport, and establishing corresponding learning effects among the participants. Keywords: complex systems; decision support; gaming; infrastructures; ports; port development; planning; learning.
simulation;
Reference to this paper should be made as follows: Bekebrede, G. and Mayer, I. (2006) ‘Build your seaport in a game and learn about complex systems’, J. Design Research, Vol. 5, No. 2, pp.273–298. Biographical notes: Geertje Bekebrede is a PhD Researcher at the Faculty of Technology, Policy and Management of Delft University of Technology. Igor Mayer is an Associate Professor in the Faculty of Technology, Policy and Management of Delft University of Technology and a Director of the Delft Rotterdam Centre for Process Management and Simulation (CPS).
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Introduction
The discipline of design has a wide scope and is clearly not limited to such technological artifacts as iPods or airplanes. Yet, designing such artifacts is extremely intricate because its intrinsic social complexity requires collaboration and coordination among various designers. In addition, the complexity of the social political environment also plays a role. The design environment tends to have several sets of stakeholders: clients, competitors, governments, and societal stakeholders. These complexities and stakeholders are some of the main reasons why design curricula increasingly focus on communication skills for aspiring designers and develop non-linear and collaborative
Copyright © 2006 Inderscience Enterprises Ltd.
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design approaches and methods. Thus, the design of technological artifacts is a complex socio-political process as much as an engineering process. But ‘design’ becomes even more complicated when the object of design is not an artifact but an institution, such as public policy reform or a socio-technological system. Seaports, for example, are socio-technological systems. They not only consist of many artifacts (roads, cranes, railways, and quays), but also of many different and often conflicting actors, such as port authorities, building contractors, terminal operators, (potential) clients, shipping companies, governments, and pressure groups. And even when the various technological and logistical components in the port system – the reclaiming of land, the cranes, docks, ships, and quays – have been well designed and optimised, at a higher systems level the long-term behaviour and performance of the port infrastructure (5–30 years or more) can be very uncertain. Thus, while the subparts of the system seem manageable or under control, the system as a whole may show emerging complex behaviour. Studies of the long-term behaviour of complex systems, such as global environmental systems, have shown that rational design and deliberate and well-intended interventions can lead to unanticipated and undesirable results (Suh, 1999). For example: in health care reform or energy liberalisation, system behaviour can cause prices to rise and services to decrease, even when the intervention was designed to achieve the opposite results. We are only just beginning to understand how such mechanisms work, perhaps they may be the result of strategic or calculating behaviour by stakeholders or the physical or social rules built in the system. But in any case, the emergence of complexity in socio-technological systems (ports or other infrastructures) has significant implications for their designers and managers. And because infrastructures are crucial for the economy and human welfare, it is important to discover how designers can be assisted in their tasks. In this paper we will argue that designers and managers need to have a better understanding of complex system behaviour. To this end they can benefit from experiencing the long-term behaviour and unanticipated and sometimes undesirable consequences of their complex system design before it has been implemented. The ability to manage complexity begins with an awareness of and insights in the nature of complex systems. Direct experience of what can happen or what can go wrong is often very effective for raising awareness and insights. Nevertheless, in most cases, such direct experience is difficult to obtain from real infrastructures or other real-world systems without possibly serious consequences. Therefore, games are a good substitute because they can generate learning experiences in a relatively fast and safe manner. In this paper we will argue that games are very suitable for experiencing the behaviour of infrastructures as complex systems, and aspiring professionals can learn and benefit from that experience. We will demonstrate this on the basis of a case study in which players build a seaport as part of a game. We will explain in more detail what complex systems are and how games can be used to understand them. Then we will describe the computer-supported simulation game, SIM Maasvlakte 2 (abbreviated as SIM MV2). The SIM MV2 game was developed by an interdisciplinary team of staff and students at the Faculty of Technology, Policy and Management (TPM) at Delft University of Technology (TU Delft) at the request of and in close cooperation with the PoR in the Netherlands. The game deals with the design and allocation of land for the new Maasvlakte 2 area between 2006 and 2036. We will describe how the game was evaluated and present the preliminary results and insights
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from six trial sessions with a first version of the game played by professionals of the PoR and graduate students.
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Complex systems and games
2.1 A systems perspective In this paper we maintain that the long-term behaviour of technological infrastructures can best be considered from a systems perspective (Holland, 1995; Weijnen et al., 2003; Brown et al., 2004). In brief, systems theory helps make designers and managers aware that the effects of deliberate and rational interventions can sometimes be surprising, that while short-term effects may be positive, that may not be true for the long term. Sometimes side effects occur or results can be the opposite of what was expected. Our task here is not to elucidate a detailed or extensive account of the evolution and different branches of systems theory, such as chaos theory (Gleick, 1988; Stewart, 1989), complex adaptive systems (Kauffman, 1993; Holland, 1995), system dynamics (Goodwin, 1951; Forrester, 1958), or general systems theory (Bertalanffy, 1968). For our purposes, we will draw on insights derived from authors from different schools, especially Senge (Senge, 1990; Senge et al., 1994), Meadows (Sweeney and Meadows, 2001), and Holland (1995, Centre for the Study of Complex Systems). We first examine what a complex system is and provide a few examples of how such a system applies to infrastructures. •
A system is composed of parts that interact and affect each other: “A system is a perceived whole whose elements ‘hang together’ because they continually affect each other over time and operate toward a common approach.” (Senge et al., 1994, p.90)
The ‘elements’ referred to in this definition can be diverse. They can be intelligent software agents, technological artifacts, or socio-political actors (individuals, organisations). In infrastructure systems, such elements can be switches, cables, power plants, energy companies, wind farms, government agencies, regulators, consumers, and many others. •
A system is more than the sum of its parts: “A system is a collection of parts that interact with another to function as a whole. A system subsumes its parts and can itself be part of a larger system.” (Maani and Cavana, 2000, p.6)
Infrastructures do not exist without connections between the parts: for example, to transport energy to the place where it is used. •
A system combines nature (natural environment), technology (artifacts), and human behaviour: systems are “structures that combine people and the natural environment with various artifacts of man and his technology …” (Miser and Quade, 1985, p.1). Infrastructures consist of a technical network, such as institutions to regulate the system, and infrastructures are affected by various things, such as, for example, the weather.
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2.2 Complex systems The three characteristics of systems described above (parts, interaction, and structure) do not explain the complexity of (infrastructure) systems, nor how this can lead to unexpected behaviour. The Centre for the Study of Complex Systems in Michigan defines six characteristics of complex systems (http://www.pscs.umich.edu/complexity.html). These can be used to explore infrastructures as complex systems: •
Complex systems are agent based. A system includes the characteristics and activities of agents, which are active elements, diverse in both form and capability (Holland, 1995). This suggests that the system complexity of infrastructures is caused by the fact that they rely on so many highly interdependent and sophisticated technological and social agents.
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The agents are heterogeneous. Agents within a complex system are not uniform, but have various characteristics, functions, and (cap)abilities to learn. This means that interaction among these different types of agents is complicated and easily disrupted. The behaviour of infrastructure systems, for example, relies on very intelligent software agents as well as on formal or informal regulation by political and social actors. Policy science theory shows that social and political agents have many different values, preferences, objectives, and resources, which makes decision making and management extremely complex (Koppenjan and Klijn, 2004). Likewise, information and organisational sciences show that there can be many communication problems between different computer systems, let alone the many problems inherent in human-computer interaction or between organisations and computer systems.
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Complex systems are dynamic. A system changes over time because it adapts to changes in its environment. System changes can appear as evolutionary or as almost autonomous, perhaps resulting from exogenous influences from outside the system, or they may be manifested as planned or deliberate changes such as policy measures. In most cases it is a combination of these types. The dynamics of a system can be caused by structural changes in the system (e.g., when new elements are added to the system, such as a situation in which the power generated by small privately owned wind farms is fed to a national energy network, or when influential new actors enter the political arena). Technological and social agents must learn how to cope with the exogenous and endogenous changes in the system.
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Complex systems show feedback mechanisms. The complex and dynamic behaviour of a system is determined by feedback relations among its various elements or agents. These feedback relations can cause positive (i.e., self-reinforcing) effects, or negative (i.e., mitigating) effects. Time delays in feedback relations can be another important factor in complex system behaviour. Large-scale power blackouts, for example, are often caused by several loops of positive or self-reinforcing feedback effects in the energy system.
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•
Complex systems are organised. Although complex systems may seem to be chaotic, they do have an underlying structure or organisation. Social and technological agents are structured in subsystems that have the characteristics of hierarchies or networks. One way to understand the relationship between structure and behaviour is by looking at the rules of the system. These rules, like those of physics, law, negotiations, etc., determine the behaviour of agents, subsystems, and systems.
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Complex systems show emergent behaviour. Complex behaviour ‘emerges’ from the system characteristics but is manifested at the macro level, which means at the level of the system as a whole. Emergent behaviour is the ultimate manifestation; it shows when “a system becomes more that the sum of its parts” (Maani and Cavana 2000). Complex behaviour cannot be easily explained or managed by decomposition into parts.
Even relatively simple systems that are comprised of only a few agents and relations can show very complex, counter-intuitive behaviour (Sweeney and Meadows, 2001). But in many cases systems will be comprised of a great many agents and links, which are impossible to know in advance, let alone predict or control (Jennings, 2000). Therefore, Senge (1994), Sweeney and Meadows (2001), and others have argued that managers and decision-makers need to develop capacities for systems thinking. In The Fifth Discipline Senge (1990) describes eleven “laws of the fifth discipline”. We will only use a few of these to clarify the importance of looking at infrastructures from a system perspective. Unanticipated responses of the system When a person intervenes in the operations of a system, the system can respond in a number of different ways. One possible response is compensating feedback: “when well intentioned interventions call forth responses from the system that offset the benefits of the intervention” (Senge, 1990, p.58). Another possible response is ‘self-organisation’, which causes the system to re-organise but not necessarily with the desired effect (Holland, 1995; Stacey et al., 2002). A third type of response can occur when system growth becomes excessive. The system’s attempts to mitigate that growth may lead to unforeseen consequences. For example, problems may result if a company grows very rapidly. These problems can include poorer quality of its goods or services, and miscommunication. Cause and effect may be greatly separated over time Many decisions are based on a favourable estimate of the short-term effects, without considering what effect these decisions may have in the long run. One immediate result of energy liberalisation, for example, can be an improvement in service, but in the long run, possibly because of underinvestment, blackouts may occur or less satisfactory customer service may develop. These discrepancies between short and long-term behaviour are caused by the characteristics of dynamics and feedback. This is especially relevant for infrastructures because of long investment and planning horizons. The importance of maintaining the system as a whole “Dividing an elephant in half does not produce two small elephants” (Senge, 1990, p.66). From the perspective of the system, it is not possible to understand system behaviour by looking at only a small part. Therefore, to understand the (future) behaviour of an
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infrastructure system in all its social, economic, and physical aspects, we need to see and understand the system as a whole and in a multidisciplinary way.
2.3 Games One way of trying to understand the complexity of an infrastructure system is to become system thinkers – and that is how games can help. According to Sweeney and Meadows (2001, pp.3, 4), systems thinkers need to see the whole picture, and be able to change their perspectives. Managers must also look for interdependencies, pay attention to long-term effects, perceive complex cause-effect relations, and identify the emergence of the system. Although it is not possible to model the whole world, managers must try to look at the system from a higher level and develop a complete view of the situation. Therefore, the system needs to be modelled (mentally or otherwise) in a dynamic but complete way, focusing on feedbacks, non-linear development, and system behaviour over both short and long term. Because complexity is not only caused by technical factors but also by socio-political actors, both factors and actors must be included in the model or simulation. That is why we (and other authors) believe that simulation games are among the best methods for understanding complex systems. Simulation games are probably the only decision support methods that can incorporate human players and social interactions, social and physical rules, mental and computer models, and individual and collective goals. Thus, games mimic real-world systems in a controlled fashion. They are useful for arriving at a complete view of a given issue (Duke and Geurts, 2004) and for integrating different perspectives and disciplines (Kriz, 2003). By switching roles, players can adapt and learn to understand different perspectives, experience the system from different angles, and learn from these differences (Duke and Geurts, 2004; Mayer and Jong, 2004). The use of computers and other gaming techniques enables simulation of long-term processes within a couple of hours. We will illustrate how a simulation game about the Maasvlakte 2 was used exactly for this. But before doing that, we will introduce the port expansion case and explain why it is complex.
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The Port of Rotterdam (PoR) as a complex system
3.1 Port expansion The Dutch PoR, one of the largest seaports in the world, needs to be expanded in the coming years. Prognoses indicate that it will be expected to handle greater quantities of cargo and that many more commercial enterprises will want to locate in the immediate area of the port (Gemeente Rotterdam, 2004). Current estimates suggest that available space in the Maasvlakte Area will be fully occupied by 2010, making it impossible to meet any further space demands after that. The growth of the harbour is not only beneficial for the city of Rotterdam itself, but will also support the economic development of the Netherlands as a whole. Therefore, after a long, highly controversial public decision-making process, the Dutch government recently decided to reclaim some 1000 ha net of new land from the sea in the PoR area. This new land is known as the Maasvlakte 2 Area. The objective of the project is to reinforce the position of Rotterdam as a principal port. Within the PoR authority, a
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Maasvlakte 2 project team has been established, which has full responsibility for the strategic, commercial, and infrastructure preparations. This responsibility includes design of master, zoning, and building plans, as well as issuing tenders for contractors and builders, finding clients, and managing all legal, political, and environmental issues.
3.2 How to design and build a seaport In the coming decades, various parcels of the new seaport area will need to be reclaimed in several phases. Recent issues have delayed the expected start of contractor activities until sometime in 2008, and the development phase can take up to ten years or longer, depending on decisions and uncertainties along the way. Given the uncertainty of future market demand and the legal obligation to compensate for damage to nature, the extension and construction of the outer contour (i.e., the main sea barrier) will very likely be undertaken in two phases: the second will involve moving the outer contour further offshore to create additional parcels of land. Only after the parcels have been reclaimed and the land apportioned, can the general infrastructure (energy, roads, docks, jetties, etc.) be put in place. Then, clients can be identified and contracts agreed to. Market and customer demand will be taken into account at three decision points that have been incorporated in the development process. The first of these is the go/no-go decision for constructing the outer contour (that is, the decision to start building in 2008 or to postpone it to a later date). The central government and the PoR will make this decision jointly, on the basis of actual demand at that time. It will only be able to go forward if at least one commercial organisation announces its intention to locate in the new MV2. The second decision point precedes the commencement of the second phase of the project, where, again, there must be adequate demand. The third decision point is when land use must be designated and apportioned in parcels for allocation; this stage calls for a zoning or allocation plan for clients in four sectors: chemistry, containers, distribution, and alternative or atypical clients. Before construction of embankments and dockside quays can begin, an initial client must have committed to occupancy to launch the project. This client must have already signed a firm contract with the PoR. Because it will involve considerable investment, and costs can only be recouped if enough clients are attracted to the new area, the slogan is “build on the basis of customer demand, with respect for nature”.
3.3 A highly complex system The scope and intricacy of the project requires a thorough, well planned approach (PoR, 2004). But even then designers and managers face many strategic uncertainties and risks: unanticipated delays in the building process, not enough demand by preferred clients, unoccupied land, inefficient and sub-optimal clustering, coordination problems between infrastructure and commerce departments, strategic behaviour of contractors, clients, and stakeholders, and many others. The MV2 project contains many characteristics of a complex socio-technical system in which different agents must work together to design and manage it. This design process consists of several subsystems.
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•
Complexity in the building subsystem. The Maasvlakte 2 area will be constructed in several steps. The size of each of these steps depends on the strategy chosen. The PoR may decide on a system of maximum flexibility for the construction process, contracting and building only those parcels of land for which there are customers. Or they could decide to build it all in one go, which is cheaper but is commercially riskier. The project involves very high investment costs, which may reach 2.9 billion euros in a 15–20 year time-frame. Revenues are uncertain, but will only start to be generated after the first customer becomes operational. By definition, investments must precede income, but if there is insufficient demand, there may be unoccupied space and a high cost-return ratio. Further, the system shows patterns of path-dependency and lock-in effects. This means that once a strategy has been chosen and the process begun, the ability to alter course decreases markedly. For example, once construction activities have begun, legal, commercial, or technical factors may make it virtually impossible to halt or alter the building process. After a strategy has been settled upon, it influences and restricts subsequent decisions in the building process. But it is difficult to know which decision would be best under particular economic conditions, or what the long-term consequences or side effects of the strategic options will be. How can the PoR ensure that the building decisions taken today will not be regretted 10 or 20 years later?
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Complexity in the commercial subsystem. While the port authority has extensive experience negotiating with customers, this experience does not guarantee success: other, equally experienced port areas have sometimes taken decisions that led to inefficient distribution of land. Nevertheless, having learned from its experience, the PoR intends to follow a strategy aimed at efficient clustering of customers and achieving economies of scale. The port could try to stay on top of things by establishing clear criteria for land allocation that maximise long-term revenues (over 50 years). But clients may have different criteria and preferences. If the port is not flexible enough to accommodate these, it may have an unfavourable affect on client satisfaction or negotiating positions. Based on individual client decisions, demand can be flexible and uncertain. Is it feasible to reject less profitable clients when there is less overall demand for land, especially in the early years of exploitation? How can the PoR convince lukewarm, but interesting and profitable clients? What if client demands do not accord with allocation or zoning plans?
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Decision making in a network. As indicated above, the construction process and the commercial negotiations are complex in themselves, but they are also strongly interrelated. It is very difficult to forecast with any accuracy how many customers there will be, what type of commercial activities they will represent, and what their specific requirements will be. Nevertheless, the building of general infrastructures has to start many years in advance, which means there will be feedback between the two systems, and both systems are dynamic. This will require close coordination among the infrastructure departments and the commercial departments. The professionals working in those departments can have different backgrounds and orientations: engineers vs. marketers, long vs. short-term views. Despite common objectives (making a profit), such differences may well lead to communication and coordination problems. Moreover, many influences come from outside the system, especially those in the political and legal areas.
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Emergence in the long run. The business case for the Maasvlakte 2 area has a time span of 50 years. This makes the system highly dynamic, with many possible feedback loops and uncertain outcomes. Likewise, the nature of the first customer and its location in the port area will have significant influence on the location of subsequent customers. Furthermore, there can be discrepancies between short and long-term performance. Strategies or decisions that may not be good for short-term performance (such as rejecting less profitable or interesting clients) may have a very favourable effect on long-term performance. In addition, many decisions in the building and commercial processes are interwoven and interdependent. The feedback loops can also affect areas outside the direct area of Maasvlakte 2. Transportation of goods also influences the Dutch economy; and projects that stress the ecological balance result in new recreational areas.
The above questions and uncertainties require a system view. Therefore, the PoR requested that the authors design and run a simulation game that could be used to try out different scenarios and strategies and allow the players to experience the consequences of their decisions.
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Research and evaluation approach
4.1 The development of SIM MV2 SIM MV2 is a computer supported simulation game that mimics the real processes involved in planning, equipping, and exploiting the Maasvlakte 2 (MV2) in the PoR. The simulation game was primarily intended for staff of the PoR. But its emphasis on strategising, project management, and teamwork make it appropriate for others as well, such as graduate students and other (young) professionals as part of their education and training. While the game requires no specific prior knowledge of seaports or the Maasvlakte, players’ interest and willingness to explore this subject using the simulation game would be helpful.
4.2 Objectives In line with the analysis of learning about the behaviour of complex systems, the PoR has three aims with respect to SIM MV2: •
gain better insight into any unforeseen, undesirable, and unintentional effects of one or more development strategies and design variations in the medium term (10–30 years) as a result of exogenous uncertainties (economic, market, technological) and the strategic behaviour of the parties involved
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stimulate thinking about the project as a whole and in a multidisciplinary way within the PoR, considering the commercial and technical/infrastructural aspects, interests, and choices
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improve the results of negotiations with respect to contracts (customers) and equipment (infrastructure) in the port area.
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4.3 Validation The simulation game was developed in 2004–2005 by an interdisciplinary team of staff members and students in CPS, a gaming research centre established by Delft University of Technology and Erasmus University Rotterdam (EUR) (www.cps.tbm.tudelft.nl). The game was developed at the request of and in close cooperation with professionals working in the PoR. The development team, consisting of nine individuals, combined expertise in public administration, organisation and management, port development and management, game design, interface design, and computer programming. To obtain a clear picture of the MV2 project, many meetings and interviews with experts from various departments in the PoR were held. Furthermore, real, up-to-date information was made available for our use by the PoR. The information contained data about the construction parcels (costs, time-frame, and dependencies), as well as actual business cases, forecasts, and real data about potential customers. The names are all fictitious, and we modified and simplified the data to make the game more exciting and protect confidential information. The computer model consists of a Java based simulation with a Macromedia Flash user interface. The players use three laptop computers connected by a local network. A fourth computer functions as a server and laptop for the game administrator.
4.4 Sessions so far Up to now, the game has been played with two teams of professionals (10 players in all) from the PoR and four teams of graduate students (20 players in all). Before starting the game, the graduate students listened to a one-hour explanation of the Maasvlakte 2 project given by one of our contacts at the PoR. In one of the two sessions with students, two representatives from the PoR were also present, which seemed to encourage the students. Although the sessions were announced as trials, the game and computer model functioned properly (except for an occasional bug that was solved on the spot). In all sessions the participants were able to play the game completely. We are currently working on a second version of the computer model that will have more features. We also anticipate holding about 20 more sessions with professionals and graduate students in the first half of 2006.
4.5 Evaluation approach All sessions were evaluated extensively. To do this we used observation, questionnaires, and analyses of game log files and port maps. In the trial session with the professionals, the evaluation was mainly aimed at getting feedback to improve the game, but the session with students focused more on the learning experience. As the game becomes more robust, evaluations will increasingly focus on the complexity of the project, and we will try to establish corresponding learning effects among the participants. At the end of each game session, extensive debriefings were held on what had occurred in the game and why. Players also completed a survey with closed and open questions about various aspects of the game (quality, learning effects, etc.) (n = 28). The computer model of the game logs all information and decisions by the players. It also provides feedback on the team’s performance that is based on criteria such as revenues, costs, and client satisfaction. These data are used to calculate the team’s score for in-game comparisons.
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Furthermore, it was instructive to see the comparisons and differences in the evolution of the port maps for the years ‘16, ‘26, and ‘36. In this paper we present the main preliminary results from observations, questionnaires, and maps.
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SIM MV2: “create your own future”
How does the game proceed? Imagine you are going to play SIM MV2. You had the opportunity to read the game manual a few days before the session and are now somewhat familiar with it (see Table 1 for main features). When you arrive at the location where the game is to be played, you are welcomed by the hosts who will inform you that for the next couple of hours your team will be faced with a difficult and serious challenge: to bring into being the new Maasvlakte 2 port area in the PoR. Your task is as follows: Make appropriate planning and implementation decisions, individually and collectively, that will lead to a satisfactory design and exploitation of the second Maasvlakte (1,000 ha) over a 30-year period. Table 1
Main features of SIM MV2
Players
Minimum: 3 players, Maximum: 6, professionals or students
How to play
In teams, partly interacting with the computer model, but also including a good deal of discussion and communication among the players. The game is played in one large room
Duration
5–8 hours
Competition
Several teams can play against one another. The winner is the team with the highest score, which is determined by comparing the outcomes and results from the different teams after the game’s completion
Passage of time
The speed at which time passes can be changed any time during the game. The starting year is 2006. The simulation time begins to run after round 1, in which the players choose their strategies. During the game time passes steadily over a period of 30 years. The current date in the simulation game (month and year) is always displayed on screen for the participants to see
Evaluations
To assess the progress of the game and the players’ interim performance, internal team evaluations are made following each 10-year period
Debriefing
After completion of the game, an overall evaluation is conducted that covers strategy, procedures, collaboration, and the end result. Lessons are drawn that apply to the real world
Computers
The simulation game is played on three laptop computers, connected in a local network. A fourth laptop functions as a server. Each role in the game uses one of the laptops. The players enter their own decisions into the computers. Installation and operation of the equipment, as well as support and clarifications during the game, are done by a game administrator (at least one per team)
Other equipment
Magnetic planning board (part of SIM MV2) Maps (A3–A0) of the port (part of SIM MV2)
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5.1 Roles in the game Collectively, your team (3–6 individuals) is charged with virtually all responsibilities and competencies to plan, coordinate, and implement the decisions necessary to build, equip, and exploit the MV2 in the coming years. Most likely you will play the game in competition with one or two other teams in the same session. Of course, your team wants to be first. And because team scores are stored by team names, your team may even meet or break the best score to that point. When the game begins, you will be requested to divide roles among the team members. Each management team works under the supervision of the General Director and also includes one or more directors from the Commercial Department and the Infrastructure and Management Department. The players in your team depend on one another to succeed. Some of your responsibilities overlap. A good division of tasks and coordination is therefore crucial. You will also be provided with some background documents and fact sheets.
5.2 Rounds The game is played in four rounds, each lasting a minimum of one hour (see Table 2). At the end of the second and third rounds, your team will have some time to look back on how you worked together and what you decided and achieved. When the game is finished, all teams will compare and discuss their strategies, team work, and results. All players and facilitators will then try to identify important lessons for the real world. Table 2
Schedule for play
Introduction
Game facilitators present game objectives, rules, and tasks
Round 1
Determining the building and commercial strategies and drawing up an allocation plan. Time stands still in this round (2006)
Round 2
First period of 10 years (2006–2016). The building process must be started, and the first negotiations with customers can be conducted. In 2016 there is a review and update of performance to that point
Team evaluation
Based on the internal team evaluation, the players can make adjustments in role division, strategy, etc
Round 3
Second period of 10 years (2016–2026). The building process is complete, negotiations with customers are in full swing, and customers are assigned land in the port. In 2026 there is another performance update. Again the players can fine tune the process
Team evaluation
Based on the internal team evaluation, the players can make adjustments in role division, strategy, etc
Round 4
Third and last period of 10 years (2026–2036). In 2036 there is a final performance update
Debriefing
Upon completion of the game, there is an evaluation of several aspects such as strategy, processes, collaboration, and the end result. Lessons are drawn that can apply to the real world
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5.3 Becoming familiar with the interfaces After you have decided on your team’s name and divided the roles, it is time to familiarise yourself with the software. One of the first things you and your team mates must do is to enter your team’s name in the simulation: for example, “professional port planners”. Your team’s decisions, performance, and scores are maintained under that name. Figure 1 shows an image of the opening screen where the players enter their team name. Figure 1
Opening screen
Each of the three roles in the team uses one of the player laptops for inputting decisions in the game. If you have never played a computer game, you may feel hesitant in the beginning, but you will soon get used to playing. You will also be assisted by a team of virtual advisors who will tell you where you are in the game and what you must or may do. The advisors automatically appear the first time a screen is opened. Figure 2 shows an image of the virtual advisors. Time is important in the game, which is why there is a clock at the top of the screen showing the current month and year of the simulation time. Time is at a standstill during round 1 (the strategy phase). The clock begins to run only at the beginning of phase 2. The game administrator can slow down, speed up, or stop the clock at any time. In its fastest mode, the software can simulate about ten years in 5 minutes, which is very useful when your team finishes its tasks early, for example, in 2026, if your team is finished early but wants to view the results into the future (2036). At the left side of the screen, a log file registers and lists all relevant events and team decisions.
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Figure 2
Virtual advisors
5.4 Round 1: strategy After you have become familiar with what you are expected to do in the game, you can begin the tasks for the first round. In round one the team decides on a building strategy, a commercial strategy, and an allocation plan. After the team has made its choices and entered them in the computer, the strategy phase is finished. Only then does the game leader start the time clock for the simulation.
5.4.1 Building strategy Your team can choose one of four building strategies; these will influence costs, flexibility, and lead times in the actual building process later on. There are many trade offs and choices: for example, more flexibility requires more coordination among team members, as well as higher costs and a longer lead time. Each building strategy is comprised of various building packets: building the outer contours, reclaiming the various parcels of land, and others. Each of these aspects contributes to the final realisation of Maasvlakte 2. The number of building packets varies with the strategy, from a minimum of two to a maximum of eleven. The four building strategies are as follows: •
fast forward: two building packets, quick, but little flexibility
•
carrying on, but not rushing it: five building packets that represent a compromise between speed and flexibility
•
maximum flexibility: eleven building packets, with maximum flexibility but slow and requiring a great deal of coordination
•
all at one go: four building packets, the outermost contours of the project are placed in their definitive location.
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The start date and the desired date of completion for the various building packets in the strategy chosen are determined from round two onward. To assist in planning, each team may also use a magnetic planning board.
5.4.2 Commercial strategy In this rubric your team must choose one of two commercial strategies and provide reasons for that choice in a text box. The two commercial strategies are: •
come as they may: a suitable solution is sought for each individual customer
•
on top of things: the port authority establishes a number of criteria, and customers must comply with these to get a contract.
In the first strategy, the port waits for clients to show interest, while in the second strategy the port is proactive; only clients who fit in with the allocation plan are of interest. Unlike the building strategy, the choice of commercial strategy has no direct quantitative repercussions on the simulation model and can be changed at any time during the game.
5.4.3 Allocation plan During the strategy phase, your team also draws up an allocation plan for the future port area. This plan shows where each business cluster will be located. The team may make changes to this plan in the course of the game. Allocation plan locations on the map are shaded according to a set colour scheme, with different colours representing different business sectors. Figure 3 shows an image of an allocation plan. Figure 3
Drawing up the allocation plan
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5.5 Round 2 and beyond: building and commercial activities In round 2 and beyond, your team implements various building and commercial activities and evaluates how they perform. These activities include: selecting and beginning building activities, negotiating and contracting with customers, assigning land to customers, and performance-based evaluation.
5.5.1 Selecting and beginning building activities In round 2 the various building packets are set in motion. The Infra Director of your team selects the various building packets, and then inputs the required data, which include the starting date for building and the speed (normal or fast) for implementation. In addition to the building packets, other projects must be initiated in the building phase, such as a rail service centre, a chemical logistics service centre, an inland shipping terminal, and distribution centres. The entire building process, from sea to 1000 ha of useable land, can take 15 years or more, and shows many path dependencies. Planning errors and external delays in the building process are very likely to occur, which will impact the commercial process and port performance. The team’s challenge is to minimise errors and manage uncertainties. Figure 4 shows an image of the building activities. Figure 4
Building activities
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5.5.2 Negotiating and contracting with customers The simulation model contains names and information on more than a hundred potential customers, divided among four sectors: container terminal operators, chemical companies, distribution companies, and alternative clients (a category that includes new types of industry such as a biomass production plant or firework storage facility). The computer models allow you to request information from potential customers, view incoming messages from customers, contact a customer, negotiate with customers about lots, prices, etc., and enter into contracts.
5.5.3 Long and short lists A long list contains the names and summarised data for all companies included in the simulation model; a short list contains names and data for the companies that have sent a request to your team or whom you have sought to contact. After the game leaders have begun the simulation time, some customers from the long list will automatically seek contact with the management team. You may also seek contact with a company. After a request/offer is received from a company, you can make a one-time counter offer, or accept or reject the company immediately. You enter the counter offer in the computer and send it to the company, which accepts or rejects it. Companies that reject the counter offer are unlikely to seek contact again in the near future. When your team and a company have reached agreement, a contract is signed, and the client information can be transferred to the Infra Director for planning and building. Figure 5 shows an image of the negotiation with customers. Figure 5
Customer negotiations
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5.5.4 Assigning land to customers During negotiations your team must ascertain where a customer wants to be situated and where they can in fact be placed on the map. The location chosen must comply with Infrastructure Department criteria as well as commercial criteria. After a contract has been signed, the Infra Director must place the customer on the port map. This means that if and when the parcel of land is reclaimed and ready, customer operations can start. Only then will income be generated for the port. This income is tallied on the performance pages.
5.5.5 Performance-based evaluation After each 10-year period, a performance update is automatically provided for the preceding play period(s). Your team is given a summary of incomes (based on port dues and land rental), of expenditures (construction costs), and client satisfaction (calculated on aspects such as waiting time, parcels delivered on time and the right place, etc.). A port map reveals the status of construction work, how many parcels have been rented out, the types of company that have located there, and whether there is any clustering of specific industrial activities. Your team results can now be compared with the results of other teams, for previous rounds or the current one in the same session. Figure 6 shows an image of the performance evaluation. Figure 6
6
Performance evaluation
Preliminary results
6.1 Limitations As stated above, the game has been played with two teams of professionals from the PoR and four teams of students; in all, 30 players have been involved up to now. The objective of the game is to generate learning among (future) professionals about the system
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complexity of Maasvlakte 2, contributing to better project performance as well as better players. But three important conditions and limitations make the results from these sessions only preliminary. First, in evaluating the sessions so far, we focused on getting feedback from the players about the game itself in order to improve it. Second, we used version 1.0 with the professionals and version 1.2 with the students. Some features, such as fast forward/slow down and your team/best team comparisons, were available only in the student sessions. For future sessions version 2.0, with even more and better features, will be available. Thus, the results from different sessions are not strictly comparable. Third, there is a large amount of data generated by the game log and the computer model; this data can and will be used to examine the teams’ decisions, the underlying arguments, the performance of the project, and the patterns of system and team behaviour. Analysis of these data is time-consuming, and it will be informative only when we can compare it with more sessions. Nevertheless, the game and computer model were better than we had expected. In all sessions the game could be played completely.
6.2 Focus of the present evaluation Taking into account these limitations, we outline the main and preliminary results of our evaluation as follows. •
The quality of the game. Did the participants enjoy the game? Which aspects of the game were not as good as others?
•
Learning. Did the participants indicate they learned in and through the game, and if so, what did they learn?
•
Complex system behaviour. What aspects of complex system behaviour were identified? What aspects of complexity are worth exploring more in depth in future sessions, or through in-depth analysis of system behaviour?
We will use information and illustrations from the questionnaires, the various port maps, and observations to provide preliminary answers to the above questions.
6.2.1 Quality of the game One of the first and most obvious aspects to establish in the evaluation is the quality of the game itself. Indicators such as player satisfaction, degree of immersion and playability are relatively simple but important; not only for improving the game, but also to establish if the initial conditions for learning have been met. How did SIM MV2 perform on general quality criteria? Table 3 shows an overview of the participants’ ratings for the quality dimensions of the game. Our observations during the game and the results from the questionnaires indicate that generally the players very much enjoyed the game. The game’s degree of immersion was fairly good: we had to urge a couple of teams to stop for a lunch break, and then found that they had come back early to start playing again. The active presence of two of our contacts from the PoR in one of the student sessions seemed to engage the students even more and improve their performance. It triggered interesting discussions and interactions between the professionals and the students, and also demonstrated to our client-partners the value of the game for education and training. Our observations on game quality and degree of immersion are corroborated by the results from the
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questionnaires. Table 3 shows an overview of the participants’ ratings for the game’s quality dimensions. The average total score for game appreciation was 4.4 on a 5-point scale (Table 3). Important aspects, such as the objective of the game, the instructions, the background materials, the tasks, rules, and facilitators, showed fairly high scores: in the range of 3.5–3.8 (max = 5). All in all, participants indicated that SIM MV2 is an interesting and enjoyable game, with relevant objectives for the PoR. Seventy eight percent of the respondents indicated that they would like to play it again and expected that their performance would improve. Table 3
Quality of the game
Statements The aim of SIMMV2 was clear The aim of the simulation game was relevant for the PoR The game was built up in an interesting and stimulating way The game materials (role descriptions and manual) were understandable and clearly written The game was well facilitated The rules of the game were clear and straightforward Given the aims of the simulation game, SIMMV2 was sufficiently detailed Given the aims of the simulation game, SIMMV2 was sufficiently realistic I enjoyed taking part in SIMMV2 with others I would like to play the game again sometime
Professionals (n = 7) 4.1 (0.90) 3.6 (0.79)
Students (n = 21) 4.1 (0.79) 4.1 (0.77)
Total (n = 28) 4.1 (0.80) 4.1 (0.74)
4.0 (0.58)
4.3 (0.64)
4.2 (0.63)
3.7 (0.76)
3.7 (0.73)
3.8 (0.723)
4.1 (0.38) 2.7 (0.95)
3.8 (0.89) 3.8 (0.70)
3.9 (0.80) 3.5 (0.88)
3.8 (1.17)
3.6 (0.74)
3.7 (0.83)
3.4 (0.79)
3.5 (0.87)
3.5 (0.83)
4.1 (0.38) 4.0 (0.82)
4.5 (0.60) 3.7 (1.15)
4.4 (0.57) 3.8 (1.07)
6.2.2 Interaction with the computer Player interaction with the computer model is an important aspect of the game’s ‘playability’. Table 4 shows an overview of participants’ ratings for human-computer interaction. Most improvements following the session with professionals (using version 1.0) were directed at giving the players more sense of and control over ‘simulated time’, and improving the user interfaces, the performance sheets, and the map tools. A comparison between versions 1.0 and 1.2 shows moderate improvements in that respect. Table 4
Interaction with the computer
Statements It was easy to interact with the game’s software I enjoyed using the computer to play the game I had sufficient control of the interactions during the game The style attributes on the computer screens are attractive and suitably designed
Professionals (n = 7)
Students (n = 21)
Total (n = 28)
3.4 (0.98) 3.9 (0.69) 3.4 (1.13)
3.2 (1.12) 3.8 (0.83) 3.2 (0.98)
3.3 (1.08) 3.8 (0.79) 3.3 (1.00)
3.9 (0.38)
3.9 (0.73)
3.9 (0.65)
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Interaction with the computer (continued)
Statements The digital mapping materials in the game were understandable Navigation through the user screens was logical and easy to use The user screens in the game provided a good sense of the changes in the port area I had a clear feeling of time IN the game The user interfaces provided sufficient insight in the performance of Maasvlakte2
Professionals (n = 7)
Students (n = 21)
Total (n = 28)
3.4 (0.79)
4.0 (0.59)
3.8 (0.67)
3.7 (0.95)
3.9 (0.93)
3.8 (0.92)
3.0 (0.82)
3.6 (0.87)
3.4 (0.88)
2.0 (0.82) 2.9 (0.69)
3.1 (1.15) 3.4 (1.12)
2.8 (1.18) 3.2 (1.08)
6.3 Learning Did the participants gain new insight in the complexities of the project? Table 5 shows an overview of the results from the questionnaire. By and large both professionals and students indicated (by scores in the range of 3.7 and 4, respectively) that SIM MV2 provided insights in the strategic, technical, and commercial complexities of the project. There were marked differences between the answers given by the professionals and those by the students to the statement, “By participating in SIM MV2, I have gained a number of new insights about the real MV2”. These differences are most likely related to the greater knowledge the professionals brought to the game. Professional involvement in the project also plays a role in the minor differences among the answers to the statements, “I think that SIM MV2 can promote cooperation … (and) better communication between different departments …” The professionals valued this aspect more than the students did. Table 5
Learning from SIM MV2 Professionals (n = 7)
Students (n = 21)
Total (n = 28)
I think that SIM MV2 can promote cooperation between departments
4.2 (0.4)
3.9 (0.75)
3.9 (0.69)
I think that SIM MV2 can promote better communication between the different departments and individuals
4.0 (0.00)
3.8 (0.85)
3.8 (0.74)
By participating in SIM MV2, I have gained a number of new insights about the real MV2
2.4 (0.79)
4.1 (0.91)
3.7 (1.15)
SIM MV2 provided insights in the technical complexity of MV2
3.7 (0.82)
3.8 (1.12)
3.8 (1.05)
SIM MV2 provided insights in the strategic complexity of MV2
3.7 (0.82)
4.1 (0.77)
4.0 (0.79)
SIM MV2 provided insights in the commercial and economic complexity of MV2
3.7 (1.03)
4.0 (0.89)
3.9 (0.92)
SIM MV2 provided a clear picture of how MV2 could develop in the long term
3.0 (0.89)
3.8 (0.93)
3.6 (0.97)
Statement
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6.4 Complex system behaviour The characteristics of a complex system, such as multiple and heterogeneous agents, feedback, and emergence, can lead to unanticipated outcomes in real-world interventions. At this stage the main question is what system behaviours (and unanticipated and undesirable effects) can be identified from the limited number of game sessions so far. Our preliminary analysis of factors such as team behaviour, team strategies, decisions, and the evolution of port performance suggests several tentative observations and starting points for further analysis. At this stage we can only provide a few examples.
6.4.1 Complex behaviour in the building subsystem The strategic decisions that are made early on in the game have clear, direct implications for later stages, as well as for the commercial process. The strategy chosen can affect how long it takes for the land to be ready: it can take four to ten years before the first parcels of land will be finished and 10–13 years before parcels of land are operational. In the meantime, there is increasing pressure from the commercial side to deliver as soon as possible. Since most teams started up all working packets as soon as possible, players sometimes faced a situation where there were empty lots of land for many years. Another manifestation of the system’s complexity is the effect on the building and commercial processes when there were unforeseen delays in the building process. Although there are four building strategies in the game, all teams of players so far opted for “carrying on but not rushing it” or “building all in one go”. In the debriefing the players stated that their choice was affected by such arguments as: “we trusted that customer demand would be high enough” (for the “all in one go”), and “we wanted to go forward but still wanted to have some flexibility” (for ‘carrying on’). The difference observed in performance between the two strategies was that parcels of land were finished in different time-frames. This affects the delivery dates of the first parcels to clients and therefore, generation of income for the port and the time-frame for return on investment.
6.4.2 Complex behaviour in the commercial subsystem In the sessions so far, most of the groups chose to be “on top of things” in the commercial process. They argued that they wanted to contract exclusively with the ‘high potential’ clients for the new port area. Especially in the beginning, this strategy is not easy to maintain because the commercial director must take into account many aspects: building process lead time, various parcels’ delivery times, specific client demands, balancing among four categories of clients, and an allocation plan. The selection criteria for high potential clients can also conflict. In some instances the teams wanted to contract with distribution clients but only chemical clients were interested. In others the contracting changed to “come as they may”, which meant accepting any interested clients. Later on, when the port area has already contracted with a number of clients, negotiations become less difficult. The building stage has then been completed, there is less possibility for choosing among different alternatives or options, and the port can be much more selective. The average negotiation time at that stage is much shorter than in the beginning.
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6.4.3 Decisionmaking in a network The building and commercial processes run parallel and are closely interwoven, which makes it necessary for the actors to coordinate and communicate effectively. But this is far from easy, both in the game and in the real world. Contracts were signed in the game, yet poor construction planning prevented promised delivery dates from being met. Efforts (detailed plans) to reduce uncertainty in one process can generate more uncertainty: as things progress, there is much more information to take into account and much less flexibility in the other processes. Moreover, differences in interests and backgrounds between engineers and marketers can interfere with coordination and communication, which requires that even more processes need to be taken into account. Players begin to learn that communication and coordination are crucial and that construction, land allocation, and commercial processes are closely interwoven. They also need to put mechanisms in place for continuously improving coordination.
6.4.4 Emergence in the long run At the beginning of the game the teams design an allocation plan for MV2, indicating the location for each type of industry. The game shows whether the teams are able to succeed in that plan or if they are forced to diverge from it. It is also interesting to see how the teams develop the port area. Since it is beyond the scope of this paper to provide a full analysis of port developments with respect to performance, we can only briefly present two teams’ port maps: one of the teams opted for the “all in one go” strategy, and the other for “carrying on but not rushing it”. Figures 7–9 show images of how the decisions of each team influenced the development and final lay-out of port. Figure 7
Images of the port maps after 10 years (2016): (a) 2016 all in one go and (b) 2016 carrying on but rushing it
(a)
(b)
As can be seen in Figure 7(a) and (b), the outer contour for each is different. This is the result of different building strategies. In the “all in one go” strategy (Figure 7(a)), the final outer contour is built at one time, which makes building time longer and means that customers could not yet be placed on Maasvlakte 2. Figure 8 shows the situation in 2016. In Figure 8(a) all the parcels are already assigned, and in Figure 8(b) only the first part has been completed. On the other hand, in Figure 8(a) some parcels are empty, while in Figure 8(b) Maasvlakte 2 is almost full.
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Figure 8
Images of port maps after 20 years (a) 2026 all in one go and (b) 2026 carrying on but rushing it
(a)
(b)
Figure 9 shows the lay-out in 2036. In both situations the entire MV2 has been built and almost all the parcels are full. The team responsible for the options shown in Figure 9(a) chose the “on top of things” strategy. They did that well, so there is almost no difference between the allocation plan and the final lay-out. The other group chose “carrying on but not rushing it”, and this decision also led to a clustering of activities. It can be seen from these figures that initial decisions can lead to different outcomes after 30 years. Figure 9
Images of port maps after 30 years (a) 2036 all in one go and on top of things and (b) 2033 carrying on but not rushing it and come as they may
(a)
7
(b)
Conclusion and discussion
In a recent publication on strategic planning of Canadian ports, one contributor convincingly argued that: Today’s port managers need to help their staff see the ‘big’ picture – understand how the parts of the logistics chain interact, how local actions often have longer-term and broader impacts than initially realized, and why certain operating policies are needed for the port as a whole. (Ircha, 2001, p.132)
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In this paper we have shown how systems thinking and games can contribute to filling these needs. In our experience the SIM MV2 game can help managers see the overall picture of building and land allocation for the Second Maasvlakte. It is also clear that there are still many more questions and a need for further in-depth analyses. We also plan to develop the game further, and to hold many more sessions with students and professionals. Preliminary findings, however, suggest that the game is of high quality, that players enjoy it and find it educational and instructive. Student players emphasised that they learned much about the complexity of the port project, while professionals stressed that the game can enhance communication and cooperation with the PoR. But most important of all may be the fact that the game provided an opportunity for professionals and students to look at the future of a complex project in an engaging and entertaining way.
Acknowledgements The authors wish to thank Anne-Kirsten Meijer, Jan-Willem Koeman, and Maurits van Schuylenburg of the PoR for their support and significant contributions to the game. Maxim Knepfle and Jeroen Warmerdam, third-year students of information sciences at TU Delft and now directors of Tygron, provided skilled and untiring programming for the game. Tjhien Liao, a recent graduate in industrial design, did an excellent job in designing the interfaces. Our (former) TPM students, Gijs Buijsrogge and Teun Veldhuizen, were indispensable in assisting game design activities. Roy Chin, a PhD in the systems engineering department of TPM, developed most of the map tools. Last but not least, we wish to thank the management of the PoR for their willingness to explore new territories in gaming and port management and the players for their engagement and enthusiasm.
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