;; file: rd7-JPIM, Exploration vs. Exploitation ABM ;; Authors - Paul Rummel / Rosanna Garcia ;;copyright protected 2004 ;;V2.03, 10-16-04, JPIM Model for "Uses of Agent-based Modeling in Innovation/New Product Development Research" ;;deleted market potential ;;corrected sales problem ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;INITIALIZING MODEL;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; breed [ consumer ] breed [ manufacturer ] consumer-own [early-adopter] ;; 1 = early adopter, 0 = late adopter manufacturer-own [ %rsch ;; percent-research = % of funds to research project rstock ;; inventory of innovative products dstock ;; inventory of incremental products rshort ;; shortage of sales of research products dshort ;; shortage of sales of development products rsales ;; # of sales of research products (resulting from exploration) dsales ;; # of sales of development products (resulting from exploitation) totsales ;; total # of sales slack-resources ;; accumulated manufacturer slack-resources build-costs ;; quarterly cost to build products avg-profit ;; every quarter's profits averaged over time avg-sales ;; every quarter's market share averaged over time age ;; age of the manufacturer ] globals [ num-early-adopter ;;total number of early adopters market-potential ;;k1, anticipated market growth rate of customers ;;k2, research variance is a slider in the model ;;k3, organizational adaptiveness is a slider in the model global-price ;;k4, all manufacturers charge the same price controlmanufacturer ;;manufacturer that is being 'watched' - its strategy does not change thru out the iterations quarter ;;which iteration (quarter) manuf-count ;;number of manufacturers in the marketspace running? ;; is the run button ON? pfact1 ;;dummy variable for 1st manufacturer randomly picked by consumer pfact2 ;;dummy variable for 2nd manufactuere randomly picked by consumer pickmanufacturer ;;dummy variable to keep track of which manufacturer was randomly picked by a consumer agent. ;;measurments tracking of performance trackmanufacturer ;;tracking this manufacturer track-market-share ;;track manufacturer market share control-market-share ;;control manufacturer market share control-rshort ;;innovative product shortage for control manufacturer control-dshort ;;incremental product shortage for control manufacturer control-avg-profit ;;running avg profit for control manufacturer max-market-share ;;max market share achieved by ALL manufacturers max-rshort ;;max innovative product shortage for ALL manufacturers, tracked for troubleshooting purposes only track-rshort track-dshort max-dshort ;;max incremental product shortage for ALL manufacturers, tracked for troubleshooting purposes only max-avg-profit ;;max avg profit for ALL manufacturers, tracked for troubleshooting purposes only ] to Setup if running? = 1 [stop] ;;0n/off switch ca set quarter 0 set running? 0 set global-price 4 ;;all products set to $20 type "quarter: " print quarter ;;to keep track of iteration in Command Center ask patches [ set pcolor yellow ] ;;make background of graphics yellow ;;-------------Set up consumers------------------------------------------------------------------------------------------- set-default-shape consumer "person" ;;"person" is a default shape for the graphics create-consumer consumer-population ;;consumer-population is a slider which sets number of consumers in model [set color blue ;;set color of all consumers to be blue setxy random-float world-width ;;randomly place consumers on graphic random-float world-height ] ask consumer [ set early-adopter 0 ] set num-early-adopter (consumer-population * (%-early-adopters) / 100) ;;%-early adopters is a slider which sets % of consumers who are EA ask n-of num-early-adopter consumer [set early-adopter 1 ;; ask random # of consumers to become early adopters set color red] ;;------------Set up manufacturer-------------------- set-default-shape manufacturer "factory" ;;"factory" is a default shape for the graphics create-manufacturer manufacturer-population [ ;;manufacturer-population is a slider of # of manufacturers in model set color black setxy (random-float world-width) (random-float world-height) ;;randomly place manufacturers on graphic set %rsch initial-%-research ;;initial-%-research is a slider of innovation strategy (pr) for all manufacturers except control set slack-resources (consumer-population / (count manufacturer)) set rsales (consumer-population ) * %-early-adopters set dsales (consumer-population ) * (1 - %-early-adopters) set avg-profit 0 set avg-sales 0 set rshort 0 set dshort 0 set age 0 ] set controlmanufacturer turtle consumer-population ;; set the control manufacturer to the first manufacturer set trackmanufacturer turtle (consumer-population + 1) ;set [color] of controlmanufacturer cyan ask controlmanufacturer [set color cyan] ;set [%rsch] of controlmanufacturer %-research ;;%-research is a slider which set the constant research of the control-manufacturer ask controlmanufacturer [set %rsch %-research] set manuf-count manufacturer-population ;;manufacturer-population is a slider for the number of manufacturers in model end ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;RUN;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; to Go ;; this is the main body of the program which follows the flowchart & cognitive map; (1)-(4). ;; the other sections are subroutines. tick set running? 1 set quarter ( quarter + 1 ) type "quarter: " print quarter ask manufacturer [ build-inventory ] ;;(1) routine where manufacturer builds products for the market place ask consumer [ buy-product ] ;;(2) routine where consumers randomly pick 2 manufacturers to buy products from ask manufacturer [ determine-performance ] ;;(3) routine after consumers buy products, manufacturerss determine their profits (performance) collect-data ;;rountine where measurements are recorded plot-%-research ;;routine where % research is plotted on graph plot-market-share ;;routine where market share is plotted on graph plot-relative-performance ;;routine where relative performance is plotted on graph ask manufacturer [ adjust-%-research ] ;;(4) routine where manufacturers adjusts its % research based on performance ;set [%rsch] of controlmanufacturer %-research ;;control manufacturer %research remains constant ask controlmanufacturer [set %rsch %-research] set running? 0 end ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;MANUFACTURER BUILDS INVENTORY;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; to build-inventory let avail-resources 0 let desired-total-stock 0 let dcost 0 let rcost 0 ;;resources - money available to build products without-interruption [ set age age + 1 set desired-total-stock (rshort + dshort + rsales + dsales) ;;desired total stock ;; allocate slack resources to build the products ifelse slack-resources >= desired-total-stock ;;do this for all manufacturers [set avail-resources desired-total-stock] ;;enough slack resources exist [set avail-resources slack-resources] ;;not enough slack resources to meet demand so use them all ;; build dstock set dstock avail-resources * (1 - (%rsch / 100)) ;;set development stock, %rsch changes over time for all except control manufacturer set dcost dstock ;; dcost is the cost of dstock that was built ;; build rstock set rcost avail-resources * %rsch / 100 ifelse Research-variance? ;;is Reseach-variance switch on? [ifelse research-risk > 0 and %rsch > 0 ;;is research variance greater than 0? [set rstock (random-normal rcost (research-risk)) ;;use normal distribution to determine outcome of research activity if rstock < 0 [set rstock 0] ] ;;because normal distribution is used, the random number may come up negative, so this correct for that [set rstock rcost] ] [set rstock rcost] ;;otherwise if research variance is off then outcome is same as input set slack-resources (slack-resources - (dcost + rcost)) ;; use the slack-resources to build the needed products set build-costs (dcost + rcost) ;;total cost of build innovative and incremental products [used in determine-profits] if slack-resources < 0 [set slack-resources 0] ;;if manufacturer loses all its money sets slack-resources back to 0 set rsales 0 ;; '1' to eliminate divide-by-zero possibility in 'adjust-%-research' set dsales 0 set rshort 0 set dshort 0 ] end ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;CONSUMERS BUY PRODUCTS;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; to buy-product let stopit 0 let decision 0 without-interruption [ set stopit false set pickmanufacturer nobody set pfact1 one-of manufacturer ;; find a manufacturer set pfact2 one-of manufacturer ;; find a second one while [pfact1 = pfact2] [set pfact2 one-of manufacturer] ;; not a duplicate manufacturer ;;choose by stock 1st ifelse early-adopter = 1 [ifelse [rstock] of pfact1 > 0 [if [rstock] of pfact2 < 1 [ set pickmanufacturer pfact1 ;set [rshort] of pfact2 (([rshort] of pfact2) + 1)] ] ask pfact2 [set rshort (rshort + 1)] ]] [ifelse [rstock] of pfact2 > 0 [set pickmanufacturer pfact2 ;set [rshort] of pfact1 (([rshort] of pfact1) + 1)] ask pfact1 [set rshort (rshort + 1)]] ; [set [rshort] of pfact1 (([rshort] of pfact1) + 1) [ask pfact1 [set rshort (rshort + 1)] ;set [rshort] of pfact2 (([rshort] of pfact2) + 1) ask pfact2 [set rshort (rshort + 2)] set stopit true] ] ] ;; nobody has stock [ifelse [dstock] of pfact1 > 0 [if [dstock] of pfact2 < 1 [ set pickmanufacturer pfact1 ; set [dshort] of pfact2 (([dshort] of pfact2) + 1)] ] ask pfact2 [set dshort (dshort + 1)]]] [ifelse [dstock] of pfact2 > 0 [set pickmanufacturer pfact2 ;set [dshort] of pfact1 (([dshort] of pfact1) + 1)] ask pfact1 [set dshort (dshort + 1)]] ;[set [dshort] of pfact1 (([dshort] of pfact1) + 1) [ask pfact1 [set dshort (dshort + 1)] ; set [dshort] of pfact2 (([dshort] of pfact2) + 1) ask pfact2 [set dshort (dshort + 1)] set stopit true] ] ] ;; nobody has stock if pickmanufacturer = nobody ;; both companies have stock ;; choose by market share [ifelse manuf-count > 2 [ifelse [totsales] of pfact1 > [totsales] of pfact2 [set pickmanufacturer pfact1] [set pickmanufacturer pfact2]] [ifelse 50 > (random 100) [set pickmanufacturer pfact2] [set pickmanufacturer pfact1]] ] ;; buy if stopit = false [ ifelse early-adopter = 1 ;[ set [rstock] of pickmanufacturer (([rstock] of pickmanufacturer) - 1) ;;decrease inventory of R-products [ ask pickmanufacturer [set rstock (rstock - 1) ] ;set [rsales] of pickmanufacturer (([rsales] of pickmanufacturer) + 1) ];;increase sales of R-products ask pickmanufacturer [set rsales rsales + 1]] ;[ set [dstock] of pickmanufacturer (([dstock] of pickmanufacturer) - 1) ;;decrease inventory of D-products [ ask pickmanufacturer [set dstock dstock - 1] ;set [dsales] of pickmanufacturer (([dsales] of pickmanufacturer) + 1) ];;increase sales of D-products ask pickmanufacturer [set dsales dsales + 1]] ; set [totsales] of pickmanufacturer (([totsales] of pickmanufacturer) + 1) ask pickmanufacturer [set totsales totsales + 1] ] ] end ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;MANUFACTURERS DETERMINE PERFORMANCE;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; to determine-performance let quarter-revenue 0 let quarter-profit 0 let quarter-sales 0 set quarter-revenue (rsales * global-price) + (dsales * global-price) ;;calcualte quarterly revenues set quarter-profit quarter-revenue - build-costs ;;calculate quarterly profit performance if quarter-profit < 0 [set quarter-profit 0] set avg-profit avg-profit + ((quarter-profit - avg-profit) / age) if avg-profit < 0 [set avg-profit 0] set slack-resources slack-resources + quarter-revenue ;;calculate increases to slack resources if slack-resources < 0 [set slack-resources 0] set quarter-sales rsales + dsales set avg-sales avg-sales + ((quarter-sales - avg-sales) / age) ;;calculate average sales end ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;RESULTS ARE RECORDED;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; to collect-data let totalmarket 0 set totalmarket precision (sum [totsales] of manufacturer) 3 if totalmarket < 1 [set totalmarket 1] ;;performance measures of control manufacturer set control-market-share precision ((([totsales] of controlmanufacturer) * 100) / totalmarket) 3 set control-avg-profit precision ([avg-profit] of controlmanufacturer) 3 ;;market share of rest of manufacturers set track-market-share precision ((((totalmarket - [totsales] of controlmanufacturer) * 100) / totalmarket)/ (manuf-count - 1)) 3 ;; get the highest market share of all factories set max-avg-profit precision (max [avg-profit] of manufacturer) 3 set max-market-share precision (((max [totsales] of manufacturer) * 100) / totalmarket) 3 ;;for troubleshooting only set control-rshort precision ([rshort] of controlmanufacturer) 3 set control-dshort precision ([dshort] of controlmanufacturer) 3 set track-rshort precision ([dshort] of trackmanufacturer) 3 ;;only of manufacturer 2 set track-dshort precision ([dshort] of trackmanufacturer) 3 ;;only of manufacturer 2 set max-rshort precision (max [rshort] of manufacturer) 3 ;;of all manufacturers set max-dshort precision (max [dshort] of manufacturer) 3 ;;of all manufacturers end to plot-market-share let totalavg-sales 0 let manufacturerindex 0 without-interruption [ set totalavg-sales sum [avg-sales] of manufacturer if totalavg-sales < 1 [ set totalavg-sales 1 ] ;; so no divide-by-zero in calculating market share set manufacturerindex consumer-population ;; this is the first manufacturer set-current-plot "Market Share" set-plot-y-range 0 int (2 * (100 / count manufacturer)) if count manufacturer > 9 [set-current-plot-pen "fact10" plot-pen-reset plotxy 8.92 0 plot (([avg-sales] of turtle (manufacturerindex + 9)) * 100) / totalavg-sales ] if count manufacturer > 8 [set-current-plot-pen "fact9" plot-pen-reset plotxy 7.99 0 plot (([avg-sales] of turtle (manufacturerindex + 8)) * 100) / totalavg-sales ] if count manufacturer > 7 [set-current-plot-pen "fact8" plot-pen-reset plotxy 7.06 0 plot (([avg-sales] of turtle (manufacturerindex + 7)) * 100) / totalavg-sales ] if count manufacturer > 6 [set-current-plot-pen "fact7" plot-pen-reset plotxy 6.13 0 plot (([avg-sales] of turtle (manufacturerindex + 6)) * 100) / totalavg-sales ] if count manufacturer > 5 [set-current-plot-pen "fact6" plot-pen-reset plotxy 5.2 0 plot (([avg-sales] of turtle (manufacturerindex + 5)) * 100) / totalavg-sales ] if count manufacturer > 4 [set-current-plot-pen "fact5" plot-pen-reset plotxy 4.27 0 plot (([avg-sales] of turtle (manufacturerindex + 4)) * 100) / totalavg-sales ] if count manufacturer > 3 [set-current-plot-pen "fact4" plot-pen-reset plotxy 3.34 0 plot (([avg-sales] of turtle (manufacturerindex + 3)) * 100) / totalavg-sales ] if count manufacturer > 2 [set-current-plot-pen "fact3" plot-pen-reset plotxy 2.41 0 plot (([avg-sales] of turtle (manufacturerindex + 2)) * 100) / totalavg-sales ] if count manufacturer > 1 [set-current-plot-pen "fact2" plot-pen-reset plotxy 1.48 0 plot (([avg-sales] of turtle (manufacturerindex + 1)) * 100) / totalavg-sales ] set-current-plot-pen "fact1" plot-pen-reset plotxy .55 0 plot (([avg-sales] of turtle manufacturerindex) * 100) / totalavg-sales ] end to plot-%-research let totalmarket 0 let manufacturerindex 0 set totalmarket sum [totsales] of manufacturer if totalmarket < 1 [ set totalmarket 1 ] ;; so no divide-by-zero in calculating market share set manufacturerindex consumer-population ;; this is the first manufacturer set-current-plot "Manufacturer % Research" if count manufacturer > 9 [set-current-plot-pen "fact10" plot-pen-reset plotxy 8.92 0 plot [%rsch] of turtle (manufacturerindex + 9) ] if count manufacturer > 8 [set-current-plot-pen "fact9" plot-pen-reset plotxy 7.99 0 plot [%rsch] of turtle (manufacturerindex + 8) ] if count manufacturer > 7 [set-current-plot-pen "fact8" plot-pen-reset plotxy 7.06 0 plot [%rsch] of turtle (manufacturerindex + 7) ] if count manufacturer > 6 [set-current-plot-pen "fact7" plot-pen-reset plotxy 6.13 0 plot [%rsch] of turtle (manufacturerindex + 6) ] if count manufacturer > 5 [set-current-plot-pen "fact6" plot-pen-reset plotxy 5.20 0 plot [%rsch] of turtle (manufacturerindex + 5) ] if count manufacturer > 4 [set-current-plot-pen "fact5" plot-pen-reset plotxy 4.27 0 plot [%rsch] of turtle (manufacturerindex + 4) ] if count manufacturer > 3 [set-current-plot-pen "fact4" plot-pen-reset plotxy 3.34 0 plot [%rsch] of turtle (manufacturerindex + 3) ] if count manufacturer > 2 [set-current-plot-pen "fact3" plot-pen-reset plotxy 2.41 0 plot [%rsch] of turtle (manufacturerindex + 2) ] if count manufacturer > 1 [set-current-plot-pen "fact2" plot-pen-reset plotxy 1.48 0 plot [%rsch] of turtle (manufacturerindex + 1) ] set-current-plot-pen "fact1" plot-pen-reset plotxy .55 0 plot [%rsch] of turtle manufacturerindex end to plot-relative-performance let totalavgprofit 0 let manufacturerindex 0 set totalavgprofit sum [avg-profit] of manufacturer if totalavgprofit < 1 [ set totalavgprofit 1 ] ;; so no divide-by-zero in calculating relative performance set manufacturerindex consumer-population ;; this is the first manufacturer set-current-plot "Relative Performance" set-plot-y-range 0 int (2 * (100 / count manufacturer)) if count manufacturer > 9 [set-current-plot-pen "fact10" plot-pen-reset plotxy 8.92 0 plot (([avg-profit] of turtle (manufacturerindex + 9)) * 100) / totalavgprofit ] if count manufacturer > 8 [set-current-plot-pen "fact9" plot-pen-reset plotxy 7.99 0 plot (([avg-profit] of turtle (manufacturerindex + 8)) * 100) / totalavgprofit ] if count manufacturer > 7 [set-current-plot-pen "fact8" plot-pen-reset plotxy 7.06 0 plot (([avg-profit] of turtle (manufacturerindex + 7)) * 100) / totalavgprofit ] if count manufacturer > 6 [set-current-plot-pen "fact7" plot-pen-reset plotxy 6.13 0 plot (([avg-profit] of turtle (manufacturerindex + 6)) * 100) / totalavgprofit ] if count manufacturer > 5 [set-current-plot-pen "fact6" plot-pen-reset plotxy 5.20 0 plot (([avg-profit] of turtle (manufacturerindex + 5)) * 100) / totalavgprofit ] if count manufacturer > 4 [set-current-plot-pen "fact5" plot-pen-reset plotxy 4.27 0 plot (([avg-profit] of turtle (manufacturerindex + 4)) * 100) / totalavgprofit ] if count manufacturer > 3 [set-current-plot-pen "fact4" plot-pen-reset plotxy 3.34 0 plot (([avg-profit] of turtle (manufacturerindex + 3)) * 100) / totalavgprofit ] if count manufacturer > 2 [set-current-plot-pen "fact3" plot-pen-reset plotxy 2.41 0 plot (([avg-profit] of turtle (manufacturerindex + 2)) * 100) / totalavgprofit ] if count manufacturer > 1 [set-current-plot-pen "fact2" plot-pen-reset plotxy 1.48 0 plot (([avg-profit] of turtle (manufacturerindex + 1)) * 100) / totalavgprofit ] set-current-plot-pen "fact1" plot-pen-reset plotxy .55 0 plot (([avg-profit] of turtle manufacturerindex) * 100) / totalavgprofit end ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;MANUFACTUERS ADJUST % RESEARCH BASED ON ADAPTIVENESS;;;;;;;;;;;;;;;;;;;;;;;;;; to adjust-%-research if manufacturer-adaptiveness = 0 [stop] if rsales = 0 [set rsales 0.001] ;; if no rsales, corrects for division by 0 if dsales = 0 [set dsales 0.001] ;; if no dsales, corrects for division by 0 if (rshort / rsales) > (dshort / dsales) [ set %rsch (%rsch + manufacturer-adaptiveness) if %rsch > 100 [set %rsch 100] ] if (rshort / rsales) < (dshort / dsales) [ set %rsch (%rsch - manufacturer-adaptiveness) if %rsch < 0 [set %rsch 0] ] end @#$#@#$#@ GRAPHICS-WINDOW 203 28 538 384 17 17 9.3 1 10 1 1 1 0 1 1 1 -17 17 -17 17 0 0 1 ticks SLIDER 11 29 195 62 consumer-population consumer-population 10 1000 500 10 1 NIL HORIZONTAL SLIDER 12 139 197 172 manufacturer-population manufacturer-population 2 10 10 1 1 NIL HORIZONTAL BUTTON 295 384 388 417 Run Go T 1 T OBSERVER NIL NIL NIL NIL SLIDER 11 62 195 95 %-early-adopters %-early-adopters 0 100 50 5 1 % HORIZONTAL SLIDER 12 173 196 206 initial-%-research initial-%-research 0 100 50 5 1 % HORIZONTAL SLIDER 9 286 193 319 %-research %-research 0 100 100 5 1 % HORIZONTAL PLOT 544 28 763 165 Market Share Factory NIL 1.0 10.0 0.0 100.0 false false PENS "fact1" 0.47 1 -11221820 false "fact2" 0.47 1 -16777216 false "fact3" 0.47 1 -16777216 false "fact5" 0.47 1 -16777216 false "fact6" 0.47 1 -16777216 false "fact7" 0.47 1 -16777216 false "fact8" 0.47 1 -16777216 false "fact9" 0.47 1 -16777216 false "fact10" 0.47 1 -16777216 false "fact4" 0.47 1 -16777216 false "default" 0.47 1 -16777216 false PLOT 545 295 764 425 Manufacturer % Research Factory NIL 1.0 10.0 0.0 100.0 false false PENS "default" 0.47 1 -16777216 false "fact3" 0.47 1 -16777216 false "fact4" 0.47 1 -16777216 false "fact5" 0.47 1 -16777216 false "fact6" 0.47 1 -16777216 false "fact7" 0.47 1 -16777216 false "fact8" 0.47 1 -16777216 false "fact9" 0.47 1 -16777216 false "fact10" 0.47 1 -16777216 false "fact1" 0.47 1 -11221820 false "fact2" 0.47 1 -16777216 false TEXTBOX 52 11 182 29 Consumer settings 11 0.0 0 TEXTBOX 52 121 166 139 Manufacturer settings 11 0.0 0 BUTTON 203 384 294 417 Initiialize Setup NIL 1 T OBSERVER NIL NIL NIL NIL SLIDER 18 398 170 431 research-risk research-risk 0 100 10 10 1 % HORIZONTAL SLIDER 10 207 195 240 Manufacturer-adaptiveness Manufacturer-adaptiveness 0 10 10 0.2 1 % HORIZONTAL PLOT 545 165 764 295 Relative Performance Factory NIL 1.0 10.0 0.0 75.0 false false PENS "fact1" 0.47 1 -11221820 false "fact2" 0.47 1 -16777216 false "fact3" 0.47 1 -16777216 false "fact4" 0.47 1 -16777216 false "fact5" 0.47 1 -16777216 false "fact6" 0.47 1 -16777216 false "fact7" 0.47 1 -16777216 false "fact8" 0.47 1 -16777216 false "fact9" 0.47 1 -16777216 false "fact10" 0.47 1 -16777216 false "default" 0.47 1 -16777216 false TEXTBOX 16 263 185 281 Control-Manufacturer settings, pr 11 0.0 0 TEXTBOX 340 10 430 28 Agent map 11 0.0 0 TEXTBOX 545 10 643 28 Performance charts 11 0.0 0 TEXTBOX 18 344 178 362 ====Contingency settings ==== 11 0.0 0 SWITCH 18 365 170 398 Research-variance? Research-variance? 0 1 -1000 TEXTBOX 267 423 357 441 Run controls 11 0.0 0 BUTTON 244 456 307 489 NIL go NIL 1 T OBSERVER NIL NIL NIL NIL @#$#@#$#@ --------------------------------------------------------------------------------------- WHAT IS IT? --------------------------------------------------------------------------------------- The Exploratron versus Exploitation Dilemma in Innovation This Netlogo example is meant to accompany Garica (200x), "Uses of Agent-Based Modeling in Innovation/New Product Development Research", Jouranl of Product Innovation Management. This NetLogo Exploration/Exploitation agent-based model has been designed for the observation of how different resource allocation strategies can affect performance and market share in differing consumer markets and competitive environments. It has been proposed that the ecology of competition influences the degree of emphasis of firms on exploration and exploitation activities for producing new products - the greater the competition, the greater the need to exphasize exploration of new technologies (Brenner and Tushman 2003; Ghemawat and Costa 1993). This model looks at the product development strategy made by innovative firms as they create new products for the marketplace. The makeup of the consumers (early adopters of new technologies vs. late adopters of new technologies) and the number of competitors selling similar products to these consumers will affect the firm's new product development strategies and their subdsequent successes in the marketplace. See Garcia, Rummel & Calantone "The Exploratron versus Exploitation Dilemma in Innovation: A Complex Adaptive Systems Approach", working paper at http://igimresearch.cba.neu.edu/netlogo for details. ------------------------------------------------------------------------------------- HOW IT WORKS ------------------------------------------------------------------------------------- CONSUMERS - Consumers either are early adopters (red) or late adopters (blue). Early adopters will only purchase 'innovative research' products and late adopters will only purchase 'incremental development' products. Each turn (buying period) consumers randomly select two firms. Based on their buying preference (early adopter or late adopter) consumers buy from the firm which (a) has inventory of their preferred product and (b) has highest market share. MANUFACTURER - In this model manufacturers compete for consumers by ‘manufacturing’ and ‘selling’ two different types of products, innovative and incremental. The goal of each manufacturer is to determine an innovation strategy, which is the percentage of resources allocated to exploration (innovative) activities and to exploitation (incremental) activities in order to optimize performance. Before each buying period manufacturers follow one rule (see accompanying article for details) - it (re)allocates funds to exploration or exploitation activites to produce new products based on customer demand. When 'selling' products in the marketspace, if there is a shortage in inventory for innovative products (not enough to cover customer purchase requests) the firm allocates more of its resources to more exploration activities; if it has a shortage of products in meeting customer demand from late adopters it does more exploitation; if there is no shortage, the manufacturer doesn't change its mix of resources. If it has product shortages for both types of customers it looks to see which customers had greater demand and allocates resources to this type of activity. CONTROL MANUFACTURER - A control manufacturer chooses either an exploration or exploitation strategy and keeps that strategy despite the make up of the customers in the marketplace. Use the control factory to determine which strategies work best in different types of competitive markets places. ------------------------------------------------------------------------------------ HOW TO USE IT ------------------------------------------------------------------------------------ ‘INITIALIZE’: sets up the model. Clicking on the ‘initialize’ button creates the chosen number of Manufacturer and Consumer agents and randomly places their icons on the agent map. This button also assigns certain characteristics to each of the agents as will be described below. ‘RUN’: starts/stops the model. Clicking the ‘run’ button starts the free running processes of building and buying products. Clicking the button a second time interrupts the process. Any particular run can be started and stopped any number of times but the model can only be initialized when the model is stopped. ‘Command Center’ window: shows the iteration count. The ‘quarter’ was arbitrarily chosen as the unit of cycle time and thus the Command Center window displays: “Quarter xx” where xx is the current cycle count. When the model is initialized, the cycle count starts at ‘Quarter: 0’. CONSUMER SETTINGS: There are two settings for consumers: a. consumer-population b. %-early adopters a. consumer-population The consumer-population setting allows the user to set the population of consumers from 20 to 1000. Alhough the population could be set much higher, the processing time of the model begins to get slow. b. %-early-adopters This setting adjusts the percentage of consumers who only buy innovation (exploration) products. The remainder of the consumer population buys only incremental (exploitative) products. Thus, for instance, if the hybrid automobile market was being simulated, this setting might be set to relatively low percentage early adopters as opposed to a higher setting for a market such as camera-cell phones. MANUFACTURER SETTINGS: There are three settings for manufacturers: a. initial-manufacturer-count b. initial-%-research (global) c. Manufacturer-adaptiveness (global) Those manufacturer settings noted as global variables indicate that all the Manufacturers agents have the same setting except the Control Manufacturer (described in next section). a. initial-manufacturer-count The initial-manufacturer-count setting allows the user to set the initial number of manufacturers from 2 to 10. This population could represent individual manufacturers or groups of manufacturers. The maximum of ten was chosen so that the performances of all manufacturers could conveniently be viewed simultaneously on the performance bar-charts as will be described later. There is no point in evaluating allocation of resource strategy for a market with only one producer so there is a minimum of two manufacturers. b. initial-%-research This setting adjusts the initial percentage of slack resources that manufacturers allocate to exploration type products. This setting does not control the resource allocation for the control manufacturer which has its own setting. c. Manufacturer-adaptiveness Manufacturer-adaptiveness refers to the how adapatable (flexible) the firm is to making strategy changes. In the process of consumers buying products, some manufacturers may run out of stock of one kind of product type or the other. When this occurs, the model keeps track of the stocking shortage. When the Manufacturer-adaptiveness setting is greater than 0%, manufacturers change their percentage for exploration allocation based on the differences between stocking shortages to sales ratios for the two types of products. See Garcia, et al. (2004) http://igimresearch.cba.neu.edu/netlogo for greater details. This setting does not affect the resource allocation for the control manufacturer which has its own manual setting CONTROL MANUFACTURER SETTING There is one settings for the Control Manufacturer: a. %-research The control factory is an agent which does NOT change its allocation strategy throughout the iterations. Its %-research is constant. This allows the user to determine if a particular strategy, for example an all research strategy or 100% initial research, is a winning strategy compared to other strategies. a. %-research This setting adjusts the percentage of slack resources that the control manufacturer (only) allocates to exploration type products. This setting does not control the resource allocation for the other (competing) manufacturers. This setting can be changed during the course of a model ‘run’, however, it is difficult to determine on the performance charts when the change was made so this is not advised. It is best changed in-between run starts and stops. PERFORMANCE CHARTS Three charts along the right side of the model’s user interface show the progress of three important sets of data: a. Market share b. Relative performance c. Manufacturer % Research Each chart is a bar type and shows data for all manufacturers present. The vertical scales are normalized so as to optimize viewing resolution. There are always at least two manufacturer bars and can be up to ten as previously described by the initial-manufacturer-count setting. The Control Manufacturer is always present and is represented by the furthest bar to the left, which is also colored blue. All other Manufacturer bars are black. a. Market share This chart shows the running mean of market share for each Manufacturer. The running mean of market share is defined as the accumulation of total sales of a Manufacturer divided by total market sales of all Manufacturers. b. Relative performance This chart shows the running mean of performance for each Manufacturer. The running mean of performance is defined as the accumulation of profits from the sales of exploration and exploitation type products, divided by the number of cycles. c. Manufacturer % Research This chart shows the relative percentages of resource allocation for all manufacturers as determined by the Manufacturer setting, initial-%-research and the Control manufacturer setting, %-research settings. The chart is not a performance measure but an observation chart useful in seeing how competing manufacturers change their percentages when the Market-adaptability setting is used. If the adaptability setting is not used then this chart simply shows the fixed resource allocation percentages. CONTINGENCY SETTINGS: a. Research-variance? This switch enables the research-risk setting. This setting allows for the reality of outcomes from exploration activities – that exploration investments can be risky. Some markets can be more risky than others. Along with added risk comes the possibility of a bigger payoff. Thus the setting range is from 0 to 100% where the zero (0) setting results in no risk with all resources allocated to exploration result in exploration type products. The usefulness of this feature is that it introduces short-term perturbations into the build-buy cycle that can test the sensitivities of performance to risk. When the switch is off, the research-risk setting is zero. --------------------------------------------------------------------------------------- THINGS TO NOTICE --------------------------------------------------------------------------------------- Run the model with the default settings. Watch how the market share changes for companies taking either a "all research" or "all development" strategy. Which strategy wins in the default mode? --------------------------------------------------------------------------------------- THINGS TO TRY --------------------------------------------------------------------------------------- Change the number of consumers, does this change the overall results? Change the % of early adopters, does this change the overall results? Is there a 'tipping point' when it makes sense for a firm to change its strategy? Change the number of firms competing in the marketspace. Does this change the overall results? Look at a 'Control Manufacturer'. Under what conditions can the Control Manufacturer beat others using an "all exploration strategy"? Using an "all exploitation strategy"? What can be learned about ecological competition? --------------------------------------------------------------------------------------- EXTENDING THE MODEL --------------------------------------------------------------------------------------- One way of extending the model is to add 'contingencies' using multiple switches. What will happen if consumer choice for buying from a manufacturer is related to price, marketshare, and product innovativeness instead of just marketshare alone? How is the model affected if only 50% of slack resources are spent on exploration and exploitation activities. Switches can be added to make these types of environmental changes. See an 'extended model' at http://igimresearch.cba.neu.edu/netlogo. --------------------------------------------------------------------------------------- NETLOGO FEATURES --------------------------------------------------------------------------------------- This model makes use of the slider and switch functions of Netlogo. BehaviorSpace is a tool that allows one to perform experiments with the programmed model. (For more information on how to use BehaviorSpace refer to the Tool menu of any Netlogo model). This feature automatically runs a model many times, systematically varying the model's settings over a designated range of values. BehaviorSpace automatically varies the slider and switch ranges/settings to run 'experiments'. Simulations are run repeatedly where the tool varies the parameters and switch settings in order to observe the effects of the model’s behavior to these changes. This process of varying settings is called ‘parameter sweeping’ or ‘sensitivity analysis’. It allows exploration of the model's "space" of possible behaviors, and helps determine which combinations of settings or types of configurations under which the model best performs in multi-dimension parameter space defined. For this model, the ‘BehaviorSpace’ feature of NetLogo allows the user to map performance and market share in the space modeled by the control sliders and switches. The results of each simulation run are recorded in an Excel file allowing for future statistical analysis. This feature coupled with any statistical package provides for a potentially extremely effective modeling technique for this complex issue. (Netlogo Help Menu 2004) --------------------------------------------------------------------------------------- RELATED MODELS --------------------------------------------------------------------------------------- Cooperation Multi-player Prisoners Dilemma --------------------------------------------------------------------------------------- CREDITS AND REFERENCES --------------------------------------------------------------------------------------- This Netlogo example is meant to accompany Garica (200x), "Uses of Agent-Based Modeling in Innovation/New Product Development Research", Jouranl of Product Innovation Management. To refer to this model in academic publications please use: Garcia, Rosanna and Paul Rummel(2004) Netlogo, Exploratron/Exploitation Dilemma in Innovation Model, @#$#@#$#@ default true 0 Polygon -7500403 true true 150 5 40 250 150 205 260 250 ant true 0 Polygon -7500403 true true 136 61 129 46 144 30 119 45 124 60 114 82 97 37 132 10 93 36 111 84 127 105 172 105 189 84 208 35 171 11 202 35 204 37 186 82 177 60 180 44 159 32 170 44 165 60 Polygon -7500403 true true 150 95 135 103 139 117 125 149 137 180 135 196 150 204 166 195 161 180 174 150 158 116 164 102 Polygon -7500403 true true 149 186 128 197 114 232 134 270 149 282 166 270 185 232 171 195 149 186 Polygon -7500403 true true 225 66 230 107 159 122 161 127 234 111 236 106 Polygon -7500403 true true 78 58 99 116 139 123 137 128 95 119 Polygon -7500403 true true 48 103 90 147 129 147 130 151 86 151 Polygon -7500403 true true 65 224 92 171 134 160 135 164 95 175 Polygon -7500403 true true 235 222 210 170 163 162 161 166 208 174 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