Endurance: A Game for Current Economic Times 55 Developments in Business Simulations and Experiential Learning, Volume 37, 2010 Endurance©: A Game For Current Economic Times Richard Teach Georgia Institute of Technology Richard.Teach@mgt.gatech.edu Elizabeth Murff Eastern Washington University emurff@ewu.edu ABSTRACT ENDURANCE© is a business simulation designed to replicate an economy that will go into a recession. This simulation’s firms all start with under capacity but the simulated economy is forecasting falling demand. The simulation has five participant-run, competing manufacturing firms and one computer-run competitor firm and last for approximately 16 to 20 rounds. The computer- run firm is designed to prevent ill-conceived decisions on the part of the participants from destroying the learning model of the game. The objective of the simulation is to teach participants how to recognize an oncoming recession early and how to undertake strategies and policies that will maximize the firm’s probabilities of survival. GAME OVERVIEW ENDURANCE© reflects the derived demand nature of most manufacturing operations. The firms sell products through a distribution system, not directly to the consumer. This channel is shown in figure 1. There is a single distributor servicing all manufacturers; his typical gross margin is 25% of his selling price. The retailers purchase from the distributor and typically use a gross margin of 40% of their selling price. Thus, the manufacturers determine the retail price to all consumers except under extreme demand swings. When demand increases greatly, the channel may increase its gross margins and thus consumer prices rise above what otherwise might be expected. When demand slows dramatically, the channel may reduce gross margin levels, thereby lowering consumer prices. At the start of the simulation, the industry is constantly in a state of stock-out; each firm is selling everything it can produce and demand is left unmet by the “domestic” player- firms. Since every firm stocks-out, there is no effect upon the brand switching behavior of the consumers. If consumers are unable to purchase domestically, they fill Figure 1: The Distribution Channel 56 Developments in Business Simulations and Experiential Learning, Volume 37, 2010 their unmet orders from “foreign” suppliers and do not back-order. This is then reported to the player-firms in the industry reports. Consumers will switch to domestic purchases as quickly as they become available. This encourages the manufacturers to increase their capacity. At the end of each round, the manufacturing firms receive an individual income and cash flow statement, an industry-wide sales and distribution channel inventory report, and an economic forecast for the next eight rounds (two years). As time progresses, base industry demand falls. The firms then become in a state of overcapacity and thus the industry needs to contract. In the process of contraction, some of the firms will likely end up in the situation where they do not have enough cash to pay their bills; they have reached a Chapter 11 Bankruptcy. In this simulation, a bankrupt firm has the opportunity to receive bail-out money by filing a plan on how it expects to put the firm on a profitable basis in the future. If the instructor deems the plan as feasible, the game administrator makes the necessary changes in the asset structure. If the plan is inadequate, the instructor requests a better draft plan. If the firm fails again after this reorganization, the firm is now in Chapter 7 Bankruptcy and no longer active in the simulation. At the end of the simulation, the bankrupt firms file reports on why their bail-outs failed. At the same time, the solvent firms develop white papers focusing on the strategies used to avoid bankruptcy and how they expect to take advantage of the coming expansionary period. Both sets of reports are then used by the instructor to grade the participant’s performance in the game. GAME DETAILS 1. Manufacturers Each manufacturing firm makes only seven decisions in each three-month round: 1) The production schedule with a check box on allowing overtime work. 2) The unit price for the product 3) The marketing budget 4) The R&D budget 5) The R&D budget’s division between product improvements and cost reduction 6) The amount of money to borrow. Note: Borrowing zero funds means not-to-borrow and recording negative loans reduces outstanding debts 7) Changes in manufacturing capacity. This small decision set allows each round to be played very quickly. The R&D budget has a component devoted to manufacturing cost savings. As these budget amounts increase, unit variable costs of production go down. Manufacturing costs are affected in the round following the budget increase. The other R&D component is “product Improvement” which, in effect, increases demand by decreasing price elasticity in the period following the decision. Employment is not a decision variable and employment levels are automatically determined by the production scheduling decision as a necessary condition of operations. (1) Figure 2: Price adjustment when median demand price is 100 57 Developments in Business Simulations and Experiential Learning, Volume 37, 2010 Whenever manufacturing is decreased, production employees are laid off to collect supplemental unemployment compensation of one-half wages for four rounds (one year). As manufacturing is increased, laid-off employees are rehired with no training costs. If there are no employees in the lay-off pool, new hires are acquired at a fixed training cost. As a result of these employment conditions, the manufacturing firms in this highly seasonal business will tend to manufacture more than they sell in the slow periods, inventory the excess, and sell this excess off in heavy demand periods. These firms maximize their rate of return on their investments and minimize their total assets devoted to real estate. As a result, they lease their manufacturing facilities and warehouse spaces. The leasing firms require a one-year lease on a continuous basis for manufacturing space with a two round (one-half-year) advance notice on any capacity reductions and a one round (three-month) notice prior to capacity increase. Available space is somewhat lumpy; additions can only be added in 10,000 unit lots. Similar to new employees, new manufacturing capacity has a break-in time of one round in which capacity is halved. After this round, it can produce at full capacity. When the firm is adding capacity, it automatically issues a purchase order for the needed machinery (no player decisions are necessary) and sells a 5-year bond issue to cover the costs of this manufacturing machinery. The manufacturing Machinery is also somewhat lumpy in that it can only be purchased in 1,000 unit increments. The manufacturing machinery has a life expectancy of 5 years and is depreciated on a sum-of- the-years digits basis. The bonds are paid-off, using equal installment of 5% of the purchase price per round, over this same time period. Thus, when the machinery has been worn-out, the machinery has been paid for. The interest is paid on this outstanding debt by a separate transaction at the end of every round and is shown as overhead. Warehousing space for finished goods is leased as well in order to minimize long-term capital investments. Warehouse space is also leased only in 1000 unit lots and on an annual basis. While additions and reductions in warehousing are automatically handled; the firms do not need to make this decision as space is automatically leased for a minimum of one year when they manufacture more than they sell. 2. Distributor The distributor changes prices instantly in response to the prices being charged by the manufacturers. Thus, if prices rise, the distributor keeps the extra profits; if prices fall, the distributor takes the loss on all of their current inventories. The distributor buys in relation to the orders from retailers and prefers to hold one month of inventory. That is, when it orders product from a particular manufacturing firm, it checks its current remaining inventory level and the next quarter’s orders received from the retailers for that product. The distributor then orders one-and-a-third times the orders received less the inventory currently on hand. Thus, if the distributor has no inventory on hand, it orders extra to stock-up; if the distributor has too much of the product on hand, it will order less to reduce the inventory. (2) Figure 3: Quality adjustment when median quality is 1,000,000 58 Developments in Business Simulations and Experiential Learning, Volume 37, 2010 3. Retailers The retailers maintain their current price levels until they have sold the goods currently in stock at the beginning of the term. The retailers charge the original prices until they sell out of the goods on hand at the time of the change in prices. The retailers keep one month’s inventory on-hand to provide their customers maximum choice. They purchase to replenish their inventories in a manner similar to the distributor. 4. Consumers Industry demand (actual retail sales) is based on the state of the economy, the harmonic mean of the manufacturers’ prices (harmonic price) and minimum of the manufacturer’s expenditures on product improvement (min quality). Promotions are a competitive weapon used to increase a manufacturer’s market share. They will not increase industry-level demand. Likewise, stock-outs do not affect industry level demand. In the simulation ENDURANCE©, the end users absolutely prefer “domestic” products. If domestic products are not available, the consumers substitute “foreign” manufactured products rather than back-order. As soon as “domestic” product becomes available, consumers switch back. Under ceteris paribus conditions, demand will fall if the harmonic mean of prices increases and demand will increase as the harmonic prices falls. This price adjustment is based on a variation of the logistic distribution. Only one parameter is needed to define this function, the median demand price. This is the inflection point of the price demand curve, the price at which demand is cut in half. This relationship is described by equation 1 and visualized in figure 2. Please note that “Logistic distributions” are defined by the cumulative distribution function of 1/ (1+e^(-1*(X- mu)/beta)). We omitted the -1 is due to the fact that we need this to be a decreasing function! We are using the median demand price rather than the mean to so this function is robust in the presence of outlier behavior on the part of a team. We are using median demand price / 7 for beta because this gives us a standard deviation that is slightly more than 1/4 of the median. This gave us an operating range that "behaved nicely" for the problem at hand. The poorest quality product carries the quality stigma of the entire product class. Thus, product quality is defined by the minimum of the cumulative sums of the manufacturers’ expenditures allocated to product improvement. As the quality of the product increases, demand increases. Again, this adjustment is based on a variation of the logistic distribution. The quality at which demand is halved, the median quality, defines this function. This relationship is described by equation 2 and visualized in figure 3. Industry demand (actual retail sales) is thus the product of the base product demand as dictated by the state of the economy, the price adjustment as dictated by the manufacturers’ prices, and the quality adjustment as dictated by the least of the manufacturers’ product improvement expenditures. 5. Economy The key to ENDURANCE© is the economic and seasonal index numbers. As the game starts, the economic index is slowly decreasing as the economy slips into a recession. Near the end of the game, the economic index slowly rises as the economy begins to recover. These indices are visualized in figure 4. The economic indices for the next eight rounds (two years) are reported to the manufacturers in the end-of-round reports. These are reported accurately for the next two rounds. After this, the forecasts include random error. This is a normally distributed value with an expected value of zero and a standard deviation that increases the further a forecasted period is into the future. The standard deviations for all eight forecasted rounds are as follows, respectively: 0, 2, 4, 7, 11, 16, 22, and 29. This increasing error reflects Figure 4: Economic indices by game period (round) 59 Developments in Business Simulations and Experiential Learning, Volume 37, 2010 the increasing uncertainty of the forecasts. At the same time, demand runs high in the first two quarters and low in the last two quarters of each year. The seasonal indices for the first through fourth quarters of each year are 110, 115, 90, and 85, respectively. These are always reported accurately in the forecast reports. These values multiply as in equation 3 to control the base amount demanded by all end-users. The net effect of these indices on the base product demand is visualized in figure 5. 6. Market share Each firm’s price is compared with all competitors’ prices to determine the competitive impact of prices. Price increases are noticed immediately (not smoothed), while price reductions are exponentially smoothed. This competitive impact price is used in place of the harmonic mean in equation 1 to obtain a competitive price weight for each firm. Each firm’s marketing budget is similarly compared with all competitors’ marketing budgets to determine the competitive impact of marketing. Promotion expenditures are calculated as the marketing budget added to the change in the R&D budget allocation for product quality from the previous round. The effects are felt instantly (not smoothed) when promotional expenditures are reduced, but exponentially smoothed to even out the impact when the promotional budget increases. This competitive impact marketing budget is divided by the sum of all competitive impact marketing budgets to obtain a competitive marketing weight for each firm. Market share for a particular firm is the product of its competitive price weight and its competitive marketing weight divided by the sum across all manufacturers of the products of the corresponding competitive price weights and competitive marketing weights. Product stock-outs have a detrimental effect upon a firm’s product demand. If a preferred manufacturer’s product is not available, the consumer is forced to switch brands as consumers will not back-order. Unsatisfied demand is pooled and re-allocated according to relative market share among those products that are not stocked-out. If demand is still unsatisfied after this brand-switching process, the consumers will purchase a “foreign” product to meet immediate need. CONCLUDING THOUGHTS ENDURANCE© is a very contemporary game. It models the collapse of an economy as occurred in 2008 and 2009 rather than an expanding economy as the vast majority of business simulations model. The concept behind this scenario is that most managers can succeed when demand is expanding, which is the case in most business simulation, but students and trainees are not trained to effectively evaluate risk. This inference is drawn from Teach (2008) when is a study of 41 competitions showed that emergency loans (a chapter 11 bankruptcy condition) was positively related and highly significant to the simulated firms profits in the game CAPSTONE. This is a very disturbing finding. ENDURANCE© is very different than current business simulations The participant evaluations are to be based upon the reports that are required to be written by the members of each management team. Since teams that manage firms that (3) Figure 5: The Seasonalized and trended base product demand 60 Developments in Business Simulations and Experiential Learning, Volume 37, 2010 go bankrupt need to submit two significant reports and teams that manage firms that do not go bankrupt need only to submit a single report, it is assumed that the required work of the extra written report will cause the student teams to strive to minimize their work load and thus will try very hard to have their firms succeed in the poor economic conditions that exist in the simulated economy. REFFERENCES Teach, Richard (2008), “Forecasting accuracy and learning: The key to measuring simulation performance,” Developments in Business Simulation and Experiential Learning, Vol. 33, pages 48 – 57 Appendix 1 OUTPUT DOCUMENTS The first “results” document that a team receives is an Industry Report. A hypothetical example for round # 3 is shown in Exhibit 1 below. EXHIBIT 1: Hypothetical Industry Report generated at the end of Round #3 Retail Demand (in units) In Round 2 500,000 Domestic Sales (In units) In Round 2 350,000 Sales of imports (in units) In Round 2 150,000 Retail inventories (in units) at the end of Round 2 0 Note that retail sales are reported as of the end of the prior round Retail orders (in units) at the end of Round 2 for Round 3 666,500 Distributors ordered units from manufacturers Distributors Sales (in units) in Round 3 393,000 Distributor Inventories (in units) at end of round 3 0 Distributor orders from Manufacturers for Round 4 (in units) 888,445 Total Industry Capacity (in units) 398,000 Firm Alpha 85,000 Firm Beta 70,000 Firm Gamma 65,000 Firm Delta 60,000 Firm Sigma 50,000 Firm Omega (Computer run Firm) 68,000 Note that the industry has under capacity but, total industry demand is falling Mfg Capacity by firm for Round 4: Capacity added in Round 2 Firm Alpha 95,000 10,000 Firm Beta 100,000 30,000 Firm Gamma 80,000 15,000 Firm Delta 75,000 15,000 Firm Sigma 80000\ 30,000 Firm Omega (Computer run Firm) 78,000 15,000 Total Industry Mfg capacity 428,000 61 Developments in Business Simulations and Experiential Learning, Volume 37, 2010 Prices during round 3 Industry Arithmetic Average Prices (Retailers) $1,240.48 Industry High Price (Retailer) $1,357.14 Industry Low Price (Retailer) $1,142.86 Industry Average Price (Distributor) $620.24 Industry High Price (Distributor) $678.57 Industry Low Price (Distributor) $571.43 Arithmetic Average Manufacturers' Price $434.17 Manufacturer's Highest Price $475.00 Manufacturer's Lowest Price $400.00 Note that the retails normal marks are 40%. However whenever the retailers Have zero inventories they increase their mark-ups to 50% The distributors’ normal mark-up is 25%. However when their inventories are zero, The distributors increase their mark-up to 30% Actual Manufacturers' R&D budgets in Round 3 Split between product improvement and cost reduction Firm Alpha $ 200,000 50% 50% Firm Beta $ 180,000 40% 60% Firm Gamma $ 150,000 60% 40% Firm Delta $ 120,000 20% 80% Firm Sigma $ 175,000 75% 25% Firm Omega (Computer run Firm) $ 160,000 50% 50% Industry Warehouse Capacity for Round 4 In units Firm Alpha 0 Firm Beta 0 Firm Gamma 0 Firm Delta 0 Firm Sigma 0 Firm Omega (Computer run Firm) 0 Total Industry Warehouse capacity 0 Seasonal Indices: Winter 110 Spring 115 Summer 95 Autumn 85 62 Developments in Business Simulations and Experiential Learning, Volume 37, 2010 Macro Economic Indices 1980 = 100 Actual but not shown Forecast Variation Not Shown Starting Round 217 Actual 217 0 Round 1 216 Actual 216 0 Round 2 214 Actual 214 0 Round 3 211 Actual 211 0 Round 4 208 Forecast 208 0 Round 5 203 Forecast 201 2 Round 6 197 Forecast 195 4 Round 7 196 Forecast 189 7 Round 8 187 Forecast 183 11 Round 9 168 Forecast 177 16 Round 10 187 Forecast 174 22 Round 11 197 Forecast 171 29 Round 12 170 Round 13 169 Round 14 170 Round 15 171 Round 16 173 Round 17 178 Round 18 182 Round 19 187 Round 20 193 Round 21 198 Round 22 201 Round 23 211 Round 24 219 Round 25 226 Round 26 232 Round 27 230 63 Developments in Business Simulations and Experiential Learning, Volume 37, 2010 Bad Debts percentage: based upon economic index Not shown to players Economic Index % change From Round 0 Bad Debt % 217 1.00% 216 -0,46% 1.13% 214 -1.38% 1.39% 211 -2.67% 1.79% 208 -4.15% 2.18% 201 -7.37% 3.11% 195 -10.14% 3.90% 189 -12.90% 4.69% 183 -15.67% 5.48% 177 -18.43% 6.27% 174 -18.82% 6.66% 171 -21.20% 7.06% 170 -21.66% 7.19% 169 -22.12% 7.32% 170 -21.66% 7.19% 171 -21.20% 7.06% 173 -20.28% 6.79% 178 -17.79% 6.13% 182 -16.13% 5.61% 187 -13.82 4.95% 193 -11.06% 4.16% 198 -8.76% 3.50% 201 -5.99% 2.71% 211 -2.76% 1.71% 219 +0.92% 1.00% 226 +4.15% 1.00% 232 +6.91% 1.00% 230 +5.99% 1.00% The Interest rate on new manufacturing machinery is 12% per annum (3% per Round) on outstanding balances. The debt for manufacturing machinery is paid off at the rate of 5% of the of the original purchase price per round and paid automatically. The interest is also paid automatically at the end of every period using a separate transaction. 64 Developments in Business Simulations and Experiential Learning, Volume 37, 2010 Actual Manufacturers' unit prices and Sales in Round 3 Price Unit Sales $ Sales Firm Alpha $400 85,000 $34,000,000 Firm Beta $430 70,000 $30,100,000 Firm Gamma $440 65,000 $28,600,000 Firm Delta $450 60,000 $27,000,000 Firm Sigma $475 50,000 $23,750,000 Firm Omega (Computer run Firm) $410 68,000 $27,880,000 Mfg Worker efficiency Paramete rs Initial unit Raw Material cost $60.50 This may be reduced as R&D Process Expenditures make mfg. more efficient Initially Each 2,000 units of production Requires 5 Mfg Workers per Round Total employment costs per mfg. worker is $20,000 Per Round Unemployment costs for laid- off workers are $10,000 Per Round Hiring workers costs $2,000 Each Training new workers $10,000 Each Workers hired from the Lay-off pool have no additional training costs Workers Laid-off for more than 1 year leave the unemployment pool Current Lay-off pools Alpha Beta Gamma Delta Sigma Omega Number of Laid-off Employees in the labor pool 0 0 0 0 0 0 Initial Parameters One unit uses $55.00 of raw material and there is a 10% waste of raw material thus Total raw materials used per unit in Round 0 was $60.50. The wastage rate decreases as R&D expenditures are allocated to cost savings Overtime manufacturing increases labor costs by 150% In Round 0, five employees are needed to produce 2,000 units but labor efficiency can be reduced as R&D expenditures are allocated to cost savings. The total costs per manufacturing employees $25,000 [per round Wages plus benefits The union contract requires the firm to pay one- half wages for all laid-off workers for 1 year. 65 Developments in Business Simulations and Experiential Learning, Volume 37, 2010 Workers in the unemployment pool are the first to be rehired and do not require any additional training. Workers hired outside of the lay-off pool require training at a cost of $10,000 per worker. The manufacturing facility is leased at a cost of $4.00 per square foot and 1,000 unit of production requires 1,000 square feet of manufacturing space. However manufacturing space can only be leased in 50,000 square foot units. And it requires a one year notice to get out of the lease. Notice of canceling unneeded manufacturing space is given automatically when ever manufacturing is cut back. Manufacturing space included room for raw material inventories, but not for finished goods inventories. Newly acquired office space is ordered when capacity increases are ordered and require I Round to be constructed. In the Round that the new manufacturing facility is first used, this new equipment can only produce and one-half of its rated capabilities. If the firm wants to receive the entire output desired, the firm must work at overtime in order to complete its requested units of production. The decision input program alerts the players of this situation and calculate the over- tine costs that will be required. The team then can decide to authorize the overtime or they may choose to authorize no over-time and produce few units. The shortage in the number of units produced will be noted on the decision screen. Warehouse spaced needed to store finished goods inventory costs $2.50 per square foot per round. This is leased automatically as the firm stores finished goods for sale when seasonal demand is slack. Warehouse has a lease which requires a rolling one-year lease. That is if the firm has leased warehouse space and does not use it for one year, the lease on that part of the warehouse is terminated. Warehouse space is only leased in 10,000 square foot units and 10 unit of inventory requires 5 gross square feet of warehouse space Electricity, water and waste disposal cost $50,000 per Round plus $1.05 per unit manufactured and is charged to direct manufacturing overhead. The firm purchases its manufacturing equipment at a cost of $500.00 per unit of output. These purchases are made in 1,000 unit machines. Thus in order to make 1,000 units in one round, the firm must spend $1,000.000. Please note that if the firm needs to produce 1,001 units of output, it must spend $2,000,000 and purchase 2,000 units of capacity. The firm pays for the needed manufacturing equipment by issuing debt instruments that are paid off in 20 equal payments, one each round. These debt instruments carry an interest rate of 12% or 3% per round. The interest costs are charged to overhead. The firm uses sum-of-the-years digits to depreciate this equipment – following the rule to expense as much as possible as soon as possible. In the accounting statement this depreciation is calculated on an annual basis and then equally allocated in each of the 4 rounds that make up a fiscal year. Other costs that are included as parameters include: • The lease of an office building $750,000 per round • Wages and salaries of management personnel $1,750,000 per round These management costs increase (but never decrease) as manufacturing volume increases at the rate of 20% for every 100% increase in the number of units produced. • The interest rate on corporate debt is 8%per annum. • The depreciation of Office equipment is $75,000 per round and remains fixed. • Utilities expenses allocated to Management activities are $25,000 per round. The output data will also include the traditions Income Statement, The Balance Sheet, a Cash flow statement and an Operations Statement noting the Depreciation Schedules, and the detail of the debt structure for the purchased equipment. Table of Contents Volume 37, 2010 A Simulation in Organizational Behavior: Development and Beta Test Simulating Networks: An Experiment Pick Your Group Size: A Better Procedure to Resolve the Free-Rider Problem in a Business Simulation The Impact Of Playing A Marketing Simulation Game On Perceived Decision Making Ability Among Introductory Marketing Students If the Games Work, Why Aren't More Faculty Willing to Play? Modeling Cascading Demand: Accounting for the Effects of Captive Consumer Relationships Issues In Simulation Implementation: Lessons From a Freshman Seminar ENDURANCE: A game for current economic times Simulating Processes: An Application In Supply Chain Management Another Look At The Use Of Forecasting Accuracy On The Assessment Of Management Performance In Business Simulation Games The Effect Of Advertising On Demand In Business Simulations The Relationship Between Learning And Performance In A Total Enterprise Simulation: Revisited And New Data. Is the Gold /Pray Simulation Demand Model Valid and is It Really Robust? Mission Possible - Using Simulation Games For Management Training In A Transition Economy Business Game Modeling For The Negotiation Between General Contractor And Subcontractors The Relationship Between Goal Orientation And Simulation Performance With Attitude Change And Perceived Learning: A Follow-Up Study The Invalidity Of "Natural Market Structure" Pims Validation Of Marketing Games Examining A Beta Test An Experiment On Group Decision-Making Using A Business Game: An International Comparison Of Mba Students In Japan; China; And Russia A Platform for Business Games - From Game Playing to Game Making: The Case of Yokohama National University Checking Financial Balance of Target Brand Portfolio with the Strategic Market Plan Cash Flow Package About Simulations and Bloom's Learning Taxonomy Managing Complexity: Applying the Conscious-Competence Model to Experiential Learning Using Accumulated Profits to Assess Performance in Simulations And Now Let's Really Innovate: The Notion of Perpetual Online Courses Distance Learning: A Game Application Web Based Total Enterprise Simulation Learning Business Administration Using Simulation Software A Review of Experiential Exercises in Absel's Published Proceedings Moving Outside the Classroom: An Experiential Exercise Involving Video Clips Peer To Peer: A New Tool for Student Peer Evaluation Continuing To Assess Project Management: What's Been Done? What's It Means? Looking At New Twists Strategies for Promoting Knowledge Formation and Dissemination in Business Simulation and Experiential Learning Introducing Experiential Exercises To Inexperienced Faculty Members Conveying Concepts Through Cartoons: Preliminary Results From Software Engineers In An Industrial Organization Theory Class Utilizing Institutional Problems as an Experiential Learning Opportunity for Students Considerations in the Design of Vicarious Learning Environments Enhancing Critical Thinking Through Service-Learning As A Consultative Process Encouraging "Established" Faculty to Adopt a "New" Games and Simulations Pedagogy IMA Candy Company: An Experiential Exercise in Managerial Accounting Mustard Seeds as Means for Creative Problem Solving, Ethical Decision Making, Stakeholder Alliance, & Leader Development through Experiential Learning in Management Education Interactive Classroom Technology: Adding a Benefit to the Traditional Classroom Excelling in the Capstone Simulation: An Application of Spreadsheet Technology as a Decision Support Tool GEO: An Entrepreneurship-Oriented Computer-Assisted International Strategy Simulation ERP Simulation Game: A Distribution Game to Teach the Value of Integrated Systems