Cover
PREFACE
1. Invitation to explore
2. What will you learn?
3. What are the components of the book?
4. What is the structure of the book?
5. Who is the book for and how to use it?
6. Before you start
7. References
ACKNOWLEDGMENTS
ABOUT THE COMPANION WEBSITE
INTRODUCING A DURABLE PRODUCT IN A NEW MARKET
1. 1.1 Introduction
2. 1.2 Your briefing for the business challenge in Plutonia
3. 1.3 Managing NewTel’s new business in the simplest scenario: business as usual
4. 1.4 A competitive scenario: compete for customers
5. 1.5 Outcomes of both scenarios in terms of key performance indicators
6. 1.6 Chapter summary
7. 1.7 Questions and challenges
8. References
CAPTURING CUSTOMER DYNAMICS DRIVEN BY DIFFUSION
1. 2.1 Introduction
2. 2.2 Diffusion: a regular dynamic in social systems
3. 2.3 Structure and dynamics of new product diffusion
4. 2.4 Chapter summary
5. 2.5 Questions and challenges
6. References
EFFECTS OF A LIMITED PRODUCT LIFE CYCLE DURATION
1. 3.1 Introduction
2. 3.2 The concept of life cycle duration and its effects on customer dynamics
3. 3.3 Tracking Accumulated purchases and Accumulated customer‐months
4. 3.4 Chapter summary
5. 3.5 Questions and challenges
THE EFFECT OF ADVERTISING SPENDING
1. 4.1 Introduction
2. 4.2 Turning the attention of Potential customers to a product
3. 4.3 The effect of fixed advertising spending
4. 4.4 The effect of constant advertising spending with a limited life cycle duration
5. 4.5 The effect of advertising for one month
6. 4.6 How many Current customers are won by winning one new customer?
7. 4.7 Chapter summary
8. 4.8 Questions and challenges
9. References
FINANCIAL RESOURCES
1. 5.1 Introduction
2. 5.2 The structure of revenues
3. 5.3 The structure of costs
4. 5.4 Behaviour: customer dynamics and the accumulation of profits
5. 5.5 Chapter summary
6. 5.6 Questions and challenges
7. References
ANALYSING THE MARKET SITUATION WITH THE SIMULATION
1. 6.1 Introduction
2. 6.2 Planning the search for the highest possible Accumulated profits
3. 6.3 Searching for optimal values for the decision variables
4. 6.4 Decisions, behaviours, and outcomes in the best case monopoly
5. 6.5 Setting your objectives
6. 6.6 Chapter summary
7. 6.7 Questions and challenges
8. References
MARKET DYNAMICS WITH A COMPETITOR
1. 7.1 Introduction
2. 7.2 Competing for Potential customers: rivalry type I
3. 7.3 Competing for Current customers: rivalry type II
4. 7.4 Competing for Potential and Current customers
5. 7.5 Reflecting on rivalry
6. 7.6 Chapter summary
7. 7.7 Epilogue: your debriefing
8. 7.8 Questions and challenges
9. References
RELAXING ASSUMPTIONS AND ADDING RELEVANT ASPECTS OF REALITY
1. 8.1 Introduction
2. 8.2 The population is not constant
3. 8.3 There are not only Potential customers and Current customers
4. 8.4 Current Customers care about Quality
5. 8.5 Advertising influences word‐of‐mouth and Customers switching
6. 8.6 Mobile phones are not contracts are not customers
7. 8.7 More frequent decisions and a longer time horizon
8. 8.8 Contracts do not change retrospectively
9. 8.9 The number of competitors is higher and varies
10. 8.10 Nonlinear relationships replace causal structure
11. 8.11 The harmonic development of demand and supply capacity: a new book
12. 8.12 Chapter summary
13. References
SYSTEM DYNAMICS
1. 9.1 Introduction
2. 9.2 Your mental model of growth from diffusion
3. 9.3 System dynamics modelling
4. 9.4 System dynamics competence
5. 9.5 Learning and applying system dynamics
6. References
ABBREVIATIONS
INDEX OF PRINCIPLES
INDEX OF GUIDELINES
INDEX OF MANAGEMENT INSIGHTS
INDEX OF SYSTEMS INSIGHTS
INDEX OF TOOLBOXES
INDEX OF DIYS
INDEX
End User License Agreement

List of Tables

Chapter 01
1. Table 1.1 Atomic behaviour modes
2. Table 1.2 Your decision variables
3. Table 1.3 Key performance indicators for both scenarios
Chapter 02
1. Table 2.1 Initial situation and your goal for Current customers
2. Table 2.2 Development of customers over 12 months
3. Table 2.3 How stock and flow variables are stored
4. Table 2.4 Measurement is sometimes direct, sometimes indirect
5. Table 2.5 Typical arithmetic operators representing positive and negative polarity
6. Table 2.6 Time step influences the accuracy of the results
7. Table 2.7 Interdependencies amongst variables
8. Table 2.8 The monthly increase of Current customers
9. Table 2.9 Combinations of parameter values (* indicates equivalent combinations)
10. Table 2.10 Blocks added earlier stay longer, and blocks added later are stacked on top of older blocks.
Chapter 03
1. Table 3.1 Accumulated purchases won or lost by changing the life cycle duration
2. Table 3.2 Accumulated customer‐months won or lost by changing the life cycle duration
Chapter 04
1. Table 4.1 The effect of advertising spending on Accumulated purchases and Accumulated customer‐months over 12 months with an unlimited life cycle duration
2. Table 4.2 Simulation data for evaluating hypotheses H 4.4 to H 4.6
3. Table 4.3 Final values of Accumulated customer‐months and Accumulated purchases resulting from advertising spending in different months. The outcomes without advertising spending are shown as ‘base line’
4. Table 4.4 Gains in Accumulated customer‐months and Accumulated purchases with respect to no advertising spending resulting from different amounts of advertising spending in different months
5. Table 4.5 Total effects of winning one additional new customer
6. Table 4.6 Accumulated purchases and Accumulated customer‐months gained from winning one additional new customer
Chapter 05
1. Table 5.1 The effective monthly prices for different life cycle durations
2. Table 5.2 Search space for the optimal effective monthly price
3. Table 5.3 Comparison of your simulated data with the SellPhone data for the BAU scenario
Chapter 06
1. Table 6.1 Multiple influences of the decision variables on profits
2. Table 6.2 Value ranges of the decision variables
3. Table 6.3 Results for different subscription rates when sales price = $50 and life cycle duration = 9 months
4. Table 6.4 Results for different sales prices when subscription rate = $20 and life cycle duration = 9 months
5. Table 6.5 Results for different life cycle durations when sales price = $50 and subscription rate = $20
6. Table 6.6 Accumulated profits achieved in partial searches by varying one decision variable at a time
7. Table 6.7 Results for combining the values from the partial searches of sales price, subscription rate, and life cycle duration
8. Table 6.8 Results for different subscription rates when sales price = $70 and life cycle duration = $18
9. Table 6.9 Additional Accumulated profits expected from different allocations to advertising spending under BAU assumptions
10. Table 6.10 Additional Accumulated profits from different advertising spending when sales price = $70, subscription rate = $25, and life cycle duration = 18 months
11. Table 6.11 Cost savings due to process improvement spending of $1 million in different months
12. Table 6.12 The most profitable way to allocate $1 million between advertising spending (A) and process improvement spending (PI)
13. Table 6.13 Summary of the search for the best values of the decision variables
14. Table 6.14 The best case monopoly (BCM) values of the decision variables
Chapter 07
1. Table 7.1 Results of the RIPA scenario
2. Table 7.2 The results of the RIMA scenario
3. Table 7.3 Relative monthly effective cost NewTel
4. Table 7.4 Partial effect of rivalry type II on revenues
5. Table 7.5 Multiple influences of the decision variables on Accumulated profits under competition
6. Table 7.6 Results of the BAU and BCR scenarios
7. Table 7.7 Final KPI outcomes of the COOP 1 experiment
8. Table 7.8 Final KPI outcomes of the COMP 1 experiment
9. Table 7.9 Final KPI outcomes of the COMP 2 experiment
10. Table 7.10 Final KPI outcomes of experiment COOP 2
11. Table 7.11 Pay‐off matrix for NewTel and RivTel
Chapter 08
1. Table 8.1 Two different types of Current contracts over time

List of Illustrations

Preface
1. Figure 0.1 A navigation map of the Strait of Magellan (Princeton University Library, 2016)
2. Figure 0.2 A map for switching sides and keeping control of the ball in soccer
Chapter 01
1. Figure 1.1 Map of Plutonia
2. Figure 1.2 Graphs of the three atomic and three composed behaviour modes
3. Figure 1.3 A decision is driven by a policy and informed by the behaviour or variables
4. Figure 1.4 Dynamics of customers in the BAU scenario
5. Figure 1.5 Monthly profits for both companies in the BAU scenario
6. Figure 1.6 Accumulated profits for both companies in the BAU scenario
7. Figure 1.7 Changes to sales price, subscription rate, and the behaviour of customers in the CFC scenario
8. Figure 1.8 Development of Accumulated profits
Chapter 02
1. Figure 2.1 Example of causal links between variables
2. Figure 2.2 New customers and Current customers over 12 months
3. Figure 2.3 A spreadsheet for simulating the variables of the model
4. Figure 2.4 The references in spreadsheet formulae reveal relationships between variables
5. Figure 2.5 Symbolic representation of the two stocks Potential customers and Current customers and the flow of new customers
6. Figure 2.6 The causal structure underneath customer dynamics and its behaviour over time
7. Figure 2.7 The causal structure with the respective equations
8. Figure 2.8 A diagram that does not show all the relevant factors
9. Figure 2.9 A causal link between two variables
10. Figure 2.10 Examples of positive and negative polarity
11. Figure 2.11 Positive polarity between an inflow and a Stock
12. Figure 2.12 Negative polarity between an outflow and a Stock
13. Figure 2.13 The core of the causal structure of the mobile phone case
14. Figure 2.14 Causal loop diagram of the reinforcing loop ‘growth engine’
15. Figure 2.15 SFD of the reinforcing loop in the diffusion model and its behaviour over time (model ‘C2 loop reinforcing’)
16. Figure 2.16 Exponential growth of Current customers
17. Figure 2.17 Different degrees of exponential growth of Current customers for different scenarios. (Legend: pcf is the potential customers fraction, cr is the contact rate and cfWoM is the conversion fraction WoM.)
18. Figure 2.18 The relationship between the multiplied parameter values and the number of months needed to grow to 10 000 Current customers
19. Figure 2.19 The balancing ‘depletion’ feedback loop of the diffusion model as SFD
20. Figure 2.20 Behaviour of Potential customers when only the balancing loop is active
21. Figure 2.21 Causal loop diagram of the balancing ‘depletion’ loop
22. Figure 2.22 Causal loop diagram of a balancing loop ‘control’
23. Figure 2.23 Goal‐seeking behaviour of Potential customers and decreasing monthly number of new customers
24. Figure 2.24 Different goal‐seeking behaviours of Potential customers for varying values of the stock of Current customers
25. Figure 2.25 The causal structures driving the atomic behaviour modes
26. Figure 2.26 A combination of feedback loops drives S‐shaped growth
27. Figure 2.27 Typical variations of S‐shaped growth
28. Figure 2.28 The highest value of new customers is the turning point for the behaviour in Current customers
29. Figure 2.29 How to interpret the causal link between a flow and a stock
30. Figure 2.30 The effect does not look like the cause
Chapter 03
1. Figure 3.1 Stock of Current customers with a homogenous population
2. Figure 3.2 Age composition of Current customers
3. Figure 3.3 If the life cycle duration of the product is limited, the stock of Current customers is reduced over time
4. Figure 3.4 Impact of different life cycle durations on Current customers and customers leaving over 12 months (abbreviated as ‘mo’)
5. Figure 3.5 Customers leaving enter the stock of Potential customers
6. Figure 3.6 Total number of individuals is conserved when customers return from Current customers to Potential customers
7. Figure 3.7 Diffusion of a product with a limited life cycle duration
8. Figure 3.8 Behaviours with a life cycle duration of nine months
9. Figure 3.9 CLD of the three feedback loops
10. Figure 3.10 The effect of different life cycle durations on Current customers, new customers, and customers lost
11. Figure 3.11 Structure for Accumulated customer‐months and Accumulated purchases
Chapter 04
1. Figure 4.1 Advertising spending influences new customers
2. Figure 4.2 The iterative hypothesis development process
3. Figure 4.3 Effects of different amounts of advertising spending on Current customers and new customers
4. Figure 4.4 Advertising spending strengthens the balancing ‘depletion’ loop
5. Figure 4.5 The effect of advertising spending on the potential customers fraction
6. Figure 4.6 Causal structure for advertising spending with a limited life cycle duration
7. Figure 4.7 Graphs of purchases from advertisement for different life cycle durations (abbreviated here as lcd)
8. Figure 4.8 A PULSE function applies a change in a given variable at a specific time with a specific duration and magnitude
9. Figure 4.9 The PULSE function allows you to control the amount and the month parameters for advertising spending
10. Figure 4.10 The total effect of one month of advertising spending on Accumulated customer‐months and Accumulated purchases. The number at the bottom represents in which month the investment is made
11. Figure 4.11 Adding the possibility to experiment with one additional new customer
Chapter 05
1. Figure 5.1 The total revenues, their sources, and their influence on Accumulated profits
2. Figure 5.2 Causal structure of the effective monthly price (EMP)
3. Figure 5.3 Increasing the life cycle duration lowers the effective monthly price
4. Figure 5.4 Capturing the shape of nonlinear relationships
5. Figure 5.5 The nonlinear relationship between effective monthly price and the effect of EMP on demand multiplier
6. Figure 5.6 A higher effective monthly price reduces new customers
7. Figure 5.7 The effective monthly price and the effect of EMP on demand multiplier
8. Figure 5.8 The total costs and connected variables
9. Figure 5.9 Causal structure of how process improvement spending reduces Service costs
10. Figure 5.10 The nonlinear relationship between process improvement spending and process improvement effect on costs
11. Figure 5.11 Causal structure of NewTel’s challenge without competitor
12. Figure 5.12 Comparison of Current customers and monthly profits between the SellPhone BAU scenario from Chapter 1 (with NewTel and RivTel) and the current simulation model
13. Figure 5.13 Behaviour of revenues, costs and profits
14. Figure 5.14 The nonlinear shape of the effect that new customers has on product cost
Chapter 06
1. Figure 6.1 Causal loop diagram of the current simulation model
2. Figure 6.2 Half‐interval search for the best parameter value
3. Figure 6.3 Searching the optimal subscription rate when sales price = 50 and life cycle duration = 9
4. Figure 6.4 Searching the optimal sales price when subscription rate = 20 and life cycle duration = 9
5. Figure 6.5 Searching the optimal life cycle duration when sales price = $50 and subscription rate = $20
6. Figure 6.6 Service costs decrease achieved by dedicating $1 million to process improvement spending during 1, 2, 3, 4, 5 or 6 months
7. Figure 6.7 S‐shaped growth of Current customers
8. Figure 6.8 Customer dynamics in the best case monopoly (BCM) scenario
9. Figure 6.9 Financial flows in the best case monopoly (BCM) scenario
Chapter 07
1. Figure 7.1 Rivalry type I means companies compete for Potential customers
2. Figure 7.2 The causal structure of advertising spending with rivalry type 1
3. Figure 7.3 The causal structure of effective monthly price with rivalry type 1
4. Figure 7.4 Behaviour of Current customers of both companies under rivalry type I, BAU scenario
5. Figure 7.5 Current customers graph for the BAU and BCM scenarios
6. Figure 7.6 Customer dynamics when NewTel implements BAU and RivTel uses the best case values of sales price, subscription rate, and life cycle duration
7. Figure 7.7 New customers and customers leaving in the RIPA scenario
8. Figure 7.8 Customer dynamics when NewTel and RivTel use the optimal values of sales price, subscription rate, and life cycle duration, but only NewTel uses advertising
9. Figure 7.9 New customers and customers leaving in the RIMA scenario
10. Figure 7.10 Competing for each other’s Current customers – Rivalry type II
11. Figure 7.11 Customers net switching between companies
12. Figure 7.12 Net switching from RivTel to NewTel when RivTel uses BAU values and NewTel the BCM values of sales price, subscription rate and life cycle duration
13. Figure 7.13 The effect of net switching of Current customers when NewTel is more expensive than RivTel
14. Figure 7.14 Causal loop diagram of the complete causal structure
15. Figure 7.15 Deciding the sales price in NewTel and RivTel
16. Figure 7.16 Delay fixed
17. Figure 7.17 Diagram representation of the sales price adjustment policy
18. Figure 7.18 Mutual adjustments of the decision variables in the COOP 1 experiment
19. Figure 7.19 Customer dynamics in the COOP 1 experiment
20. Figure 7.20 Customer dynamics in the COMP 1 experiment
21. Figure 7.21 Net switching from RivTel to NewTel in the COMP 1 experiment
22. Figure 7.22 Customer dynamics in the COMP 2 experiment
23. Figure 7.23 Collaborative setting of decision variables in the COOP 2 experiment
24. Figure 7.24 Customer dynamics in experiment COOP 2
Chapter 08
1. Figure 8.1 Additional flows to make the population variable. Unknown variables driving the flows are represented by circles with question marks
2. Figure 8.2 Customers go through several states
3. Figure 8.3 Quality influences satisfaction, which can lead to losing customers
4. Figure 8.4 Additional effects of advertising spending
5. Figure 8.5 Customers, contracts, and telephones as separate stocks
6. Figure 8.6 Avoiding retroactive changes to contract duration
7. Figure 8.7 Replacement of Current contracts from 9 to 18 months
8. Figure 8.8 Reference and simulated behaviour of Current contracts and terminated contracts
9. Figure 8.9 Absolute and relative differences between real and simulated current contracts
10. Figure 8.10 Expanding a model’s boundary
11. Figure 8.11 A causal link with a delay
12. Figure 8.12 The challenges of harmonically developing resources for fostering Demand and for Supply capacity
Chapter 09
1. Figure 9.1 Overview of principles, guidelines, systems insights, and management insights
2. Figure 9.2 Simulation modelling as a process of designing and evaluating policies (based on Sterman, 2000)
3. Figure 9.3 The model boundary separates endogenous from exogenous
4. Figure 9.4 The system dynamics modelling process. (P: problem definition; C: conceptualization; Q: quantification; V: validation; PDE: policy design and evaluation; PI: policy implementation; subscript numbers represent different iterations.)
5. Figure 9.5 The system dynamics skills in the system dynamics competence framework (Schaffernicht and Groesser, 2016)

PREFACE

Invitation to explore

We are inviting you on a journey to explore the different elements of introducing a product into a new market. You will assume the role of a manager responsible for successful product introduction while a competitor strives to do the same. Your potential customers are free to choose either of the products. How should you make your decisions given that you have a direct competitor acting simultaneously? Which strategies can improve your decision making in such a dynamic situation?

Remember, not only managers have goals, make plans, decide, and execute. This is what individuals do irrespective of their profession. What follows are a few general remarks to set the stage.

Making plans requires the ability to know where you currently are, where you want to go, and how to get from here to there. Maps or diagrams are helpful tools. There are many well‐known examples of maps. For instance, explorers developed maps to navigate through a geographical area or topological space.

The map in Figure 0.1 dates back to the year 1630. It was created to help navigators cross the Atlantic Ocean (‘Mar del Norte’) to the Pacific Ocean via the Strait of Magellan. At this time, ships sailed from Europe to the New World, and since navigators always looked in the upward direction, it was useful for them to draw a map and position East at the top.

Image described by caption. — **Figure 0.1** A navigation map of the Strait of Magellan (Princeton University Library, 2016)

‘To navigate’ stems from the two Latin words ‘nāvis’ (ship) and ‘āgis’ (drive); it literally means to steer or drive a ship. However, that what we want to steer is not always a ship, and not all the maps are geographical ones. Architects and planners design maps of buildings or bridges. Systems engineers map information systems with databases and computer programs. Both architectural and information systems maps are construction plans for artificial, man‐made objects. Organizational consultants map, revise, and design business processes and organizational structures, thereby planning how different organizational members interact to carry out their work. In these cases, the maps represent structures, i.e. elements that are essentially static.

However, business managers are often confronted with situations, with or without a map, that defy their ability to anticipate what will happen. Imagine you are a corporate strategist. You must develop a plan for long‐term success and, thereby, need to anticipate the potential actions of your suppliers, competitors, and customers who have also developed their own plans based on their own goals and expectations about your actions. Such structurally interdependent situations are ‘dynamic systems’. A dynamic system consists of several interrelated components with different actors. The components and actors react to one another and have different reasons for influencing and altering the system.

One example of a dynamic system is the strategic planning of football (soccer) matches. The map in Figure 0.2 illustrates the movements a soccer team can perform when the opposing team’s defence players attack a player. The teams have opposing goals and the actions of one team decrease the level of goal achievement of the other team. Further, each team plans and decides its moves considering the respective previous and expected moves of the opposing team. Therefore, the soccer‐planning map not only illustrates structural elements but also considers past or expected moves.

Schematic map for switching sides and keeping control of the ball in football depicting dashed arrows marking the path in the field. — **Figure 0.2** A map for switching sides and keeping control of the ball in soccer

Managers are faced with even more dynamic situations: the ‘game’ they are in is not as well defined as football. Competitors, customers, and other actors are free to decide on their course of action. Let us assume there is a company: NewTel. It is about to introduce mobile phones – a durable consumer good typically used for 9–18 months – to a new market in the presence of one rival of approximately the same size. You are a top manager at NewTel and face the challenge of taking the necessary decisions to lead the product introduction to a success. Uncovering and developing a new market in parallel to your rival is the dynamic challenge at hand: both you and your competitor will strive to capture customers from the same population as quickly as possible. The customers, of course, are influenced by the actions of both companies in the market. The interdependency between you and your competitor in this limited market leads to a highly complex situation, where your decisions may easily generate undesired effects and dynamics.

Which factors should you include in your management map to successfully ‘navigate’ NewTel? How do you determine these factors? How will this map help you to make successful decisions? Since many of those factors will be changing, and at different speeds, you will need to know why and how quickly they are changing and how you can influence them through the decisions you take. What you need are tools for mapping and planning in dynamic systems. You need an approach to determine the relevant factors in messy situations, map their dynamic relationships and show immediate, as well as delayed, effects to determine their impact over time on the relevant outcome of interest. The simulation model‐based management approach will support you in this regard.

What will you learn?

You will learn how to develop maps of dynamic systems, how to formulate candidate decision policies, and how to evaluate them based on simulations. Moreover, you will learn to elaborate and use your own computer simulations to find out what decisions you could and should make (content of the decision), when you should make them (timing of the decision), and how intensive they should be (intensity of the decision). When reaching the end of the book, you will have an intuitive understanding and skills to master dynamic business challenges such as:

Self‐limiting growth: dynamics fuelled by word‐of‐mouth diffusion is self‐reinforcing and displays exponential growth until the shrinking population of potential customers limits growth. Overall customer growth follows an S‐shaped behaviour.
Obsolescence speeds re‐purchases: the product’s life cycle duration determines the relationship between current customers and new sales to potential customers.
Sell earlier, not more: advertising can increase purchases now by anticipating future purchases. It is recognized that a decrease in purchases will follow.
Sources of revenue: revenues depend on new purchases from customers who pay the sales price and current customers who pay the subscription rate. With a limited population, higher revenues from sales cannot be sustained without losing revenues from subscriptions, and vice versa. Your business model must state how you balance these two revenue streams.
Customer net value: advertising can require more financial resources than the value of the additional sales.
Double‐action of prices: an increase in prices leads to higher revenues from sales and revenues from subscription, but it also reduces the new sales and, therefore, the number of current customers paying the subscription, which in turn decreases revenues.
Relative attractivity: in rivalry situations, customers make decisions about purchasing and switching according to the price and the amount of advertising the company displays in comparison to its competitors.
Options for rivalry: companies can compete for potential customers or each other’s current customers. The levers used for each type of rivalry are different.
Competition versus cooperation: competing by lowering prices can lead to acquiring more new customers, but it also decreases the revenue per sale and monthly subscription, thereby reducing the market value. Moreover, it is likely to trigger a price war.

Each chapter guides you through applicable content and questions enabling you to develop these insights yourself. You will first arrive at answers and then elaborate on them while going deeper and deeper into the subject. Methodological concepts such as variables, causal links, and feedback loops will become your normal language, and you will develop and experiment with simulation models. These simulation models will allow you to qualify your answers and to pose new questions. In summary, the book prepares you to approach dynamic management problems in a systematic and consistent way. Moreover, you can use simulation models to reflect upon the dynamics of business and make better grounded decisions. At the end of this journey, you will be able to develop dynamic maps and use simulation models to reflect upon the dynamics of business for designing successful business policies. Such models serve the purpose of designing decision policies. When management relies on such policies, we refer to it as model‐based management (Schwaninger, 2010). This book is designed to help build several skills that belong or relate to the system dynamics competency framework (Schaffernicht and Groesser, 2016).

What are the components of the book?

The book consists of three components.

The printed text. This is the thread in your learning journey. It successively introduces you to management challenges at the company NewTel. In addition, it introduces concepts and examples of possible dynamics, poses relevant questions, guides you through model conceptualization, allows you to develop hypotheses, to test your findings through simulations, and to interpret the simulation results for decision making.

Simulation models. Each chapter is augmented by one or more simulation models. They are available from the companion website. In this cascade of simulation models, each new model builds on the previous ones. The models help you to explore the dynamics resulting from your decision. Each simulation model is explained in a video tutorial.

Business simulator ‘SellPhone’. SellPhone allows you to gain first‐hand experience in your role as a manager of NewTel. You can get a feeling for how complex your task is. After you have mastered the content chapters in the printed text, SellPhone allows to you to double‐check your learning to see how successful you have been at leading your business.

What is the structure of the book?

The book has nine chapters. Chapter 1 introduces you to the telecommunication case. It provides relevant contextual information and identifies the goals and decision variables you have at your disposal to achieve the goals at NewTel. SellPhone is used to provide first‐hand experience in managing NewTel. You will address the following questions: What are the relevant factors in this case? How do the factors interact with the decisions made during the simulation? The following chapters will also address these questions. In Chapter 2, you will explore the dynamics of diffusion by word‐of‐mouth. We will introduce the mapping method. Three simulation models enrich the text of this chapter. Chapter 3 adds a limited product life cycle duration to the basic situation and explores its implications for the diffusion dynamics. Chapter 4 considers the effects of advertising spend on the acquisition of customers. You will discover the fundamental effect of advertising and discover what effect advertising has on purchases and the accumulation of customers. Chapter 5 introduces financial resources to the situation through a limited life cycle duration and advertising spending. You will explore the implications of purchasing price and subscription rate for revenues, and how the changes in the life cycle duration and in advertising spend impact profits. All aspects discussed so far are integrated into one systemic simulation model about NewTel. Chapter 6 helps you to systematically optimize your decisions for NewTel. It concludes the analysis of your company, since now you have the know‐how to ideally introduce your product into the new market. However, what about your direct competitor? Your strategy needs to consider your rival in your environment. How can you optimize NewTel’s success under these circumstances? Chapter 7 introduces your rival company RivTel. You will become familiar with two types of rivalry. The first deals with competing for potential customers and the second deals with competing for each other’s current customers. The simulation models help you to clarify the interdependencies and guide you to design superior policies. To follow, you are again invited to SellPhone to demonstrate what you have learned about managing a business in highly complex environments. Chapter 8 discusses the simplifying assumptions made in the case models. Possible modifications of the assumptions are discussed and a set of scenarios provided. Chapter 9 reviews the methodology used in the book and generalizes the case of NewTel to other management challenges.

Within the book, a number of icons are used.

	The more active you are, the more you will learn. Throughout the journey, new questions arise. If you reflect on them and develop your own answer before you continue reading, your mind will be best prepared for the upcoming content. Therefore, throughout the book we will frequently ask questions or suggest specific activities for you to ‘Do It Yourself’ (DIY). These places are marked with the icon shown to the left. For many DIYs, there are worksheets you can download from the companion website; they guide you through the steps you are asked to do on your own. You will also find a discussion of each DIY on this website.
	In many stages of our analysis, specific concepts and tools are useful. Each time these occur, there is a ‘Toolbox’ marked with the icon shown to the left. Here you will find an explanation of concepts and tools.
	At the end of each chapter, you are invited to assess your understanding and ability to use the new concepts and tools by answering a set of questions.
	This book provides you with an introduction to the management of products and services in new markets using a simulation modelling‐based approach to management. Of course, these initial learning steps can be deepened. Going further requires additional learning engagement from you. For this, we have provided additional challenges; the icon to the left signals them.

In many places in the book, systems insights (SI) and management insights (MI) about the dynamics and structure of the business case can be gained. These SI and MI are relevant because they can be transferred to similar cases you encounter in your work. We also identify a series of principles (P) of dynamic systems that are not bound to the business case but which are fundamental concepts and relationships valid and applicable in any dynamic situation. Whenever appropriate, we have inserted Guidelines (G) as practical recommendations to help you develop good practices as a business modeller.

Who is the book for and how to use it?

Individual learners.

If you are an undergraduate student (sophomore, senior; major as well as non‐major) or a graduate student (master, executive MBA, Ph.D.) in business administration, strategic management, management science, business engineering, industrial engineering, marketing, decision making, economics, public policy, or public management, you will benefit from this book.

The book can also serve as a self‐directed learning journey supported by e‐learning components: an online simulator, video tutorials and worksheets for the DIYs. It is self‐contained and does not require other technical training or theoretical knowledge. Therefore, you can familiarize yourself with the approach, develop intuitive insights concerning the principles of diffusion for durable products, and you will enable yourself to work with specialized consultants.

The book invites you to be active. While you progress through each chapter, we strongly recommend that you replicate the simulation models and experiments and continue to perform your own experiments. As a guideline, you will find video tutorials for each experiment on the companion website. We encourage you to develop the book’s models on your own. Moreover, at the end of each of each chapter, you will find questions and further challenges for self‐study.

Lecturers.

If you are interested in lecturing in business administration, strategic management, management science, business engineering, industrial engineering, marketing, decision making, economics, public policy, or public management with a new and engaging approach, the book is beneficial to you. You can implement the material in undergraduate or graduate courses immediately. The book is purposefully short but is a comprehensive story on growth dynamics in business under rivalry conditions in new markets. Our approach offers a pragmatic and systematic method for studying management challenges and prepares your students for future courses in dynamic systems. Moreover, the book offers value by introducing a visual mapping approach that enables interdisciplinary thinking. The book has the potential to motivate students to follow‐up with more detailed studies on their own. The material accompanying the book requires no further preparation. It can be used directly off the shelf. We suggest using the book in one of the following ways:

For undergraduate students, it belongs to a business or strategy module and requires eight contact sessions (each 45 minutes). The lecturer guides students through each chapter. For Chapters 2–7 there are two possibilities. Firstly, you can have the students read each chapter, reproduce the small simulation models and perform the simulation experiments before the class session. Time in class is used for resolving questions and discussing challenging aspects. Or, secondly, you can introduce each chapter and reproduce the short simulation models; the students then experiment with the models in their self‐study time.
In a generalist MBA course, the book should be used in eight contact lessons. As in case‐based work, students read each chapter before the session and try to reproduce the simulation experiments with the pre‐developed models. The contact session is dedicated to resolving questions and reproducing a project‐like discussion where the lecturer guides the learners through the steps – from raising a question to a simulation model and towards simulation experiments. Students should be able to interpret the results in a plenary discussion.
In master’s courses with students who already have experience in system dynamics, the book can be studied in a reduced number of sessions. After the SellPhone game, students are challenged to develop their own model to design a strategy and decision policy. Each modelling attempt is debriefed in a plenary session in which the lecturer discusses the content of the respective chapter. After two iterations, there should be an additional session where discussion centres on the diverse simplifying assumptions and how to relax them.

If you are a lecturer, and you have questions, ask us: martin@utalca.cl and stefan.groesser@bfh.ch (www.stefan‐groesser.com).

Before you start

We hope that you will gain as many dynamic insights while studying the book as we had while writing it. Moreover, we hope that the book helps you to train your disciplined, systemic, and dynamic thinking skills. Enjoy the time you spend developing hypotheses, formulating simulation models, and experimenting with them to solidify your understanding of management challenges and to develop your decision‐making capabilities in dynamic systems.

References

Princeton University Library. 2016. The Strait of Magellan: 250 Years of Maps (1520–1787). http://libweb5.princeton.edu/visual_materials/maps/websites/pacific/magellan‐strait/magellan‐strait‐maps.html (last accessed 23 October 2017).
Schwaninger, M. 2010. Model‐based management (MBM): a vital prerequisite for organizational viability. Kybernetes, 39(9/10), 1419–1428. https://doi.org/10.1108/03684921011081105.
Schaffernicht, M. and Groesser, S. 2016. A competence development framework for learning and teaching system dynamics. System Dynamics Review, 32(1), 52–81. doi: 10.1002/sdr.1550.

GROWTH DYNAMICS IN NEW MARKETS

Improving Decision Making through Simulation Model‐based Management