globals

[ 
; number-of-repeats
round-counter
run-counter

; consumers
nOfConsumers 

reach

; shops
totalDemand 
meanCapacity sdCapacity
sdCapacityCost
sdVariableCost 
sdUtilisationRate%

; adjustment variables

nOfNewShops  unmetDemand 
 
; to draw demand and supply curves etc
tempPrice  demandCurve supplyCurve excessDemand 

; trading
totalSupply 
totalRevenue 

; data collection
lossmakingShops breakevenShops profitableShops

sizeOfIndustry accumSizeOfIndustry
accumSizeOfIndustry4 accumSizeOfIndustry8 accumSizeOfIndustry20 accumSizeOfIndustry28 accumSizeOfIndustry40  
meanAccumSizeOfIndustry4 meanAccumSizeOfIndustry8 meanAccumSizeOfIndustry20 meanAccumSizeOfIndustry28 meanAccumSizeOfIndustry40

newShops accumNewShops
accumNewShops4 accumNewShops8 accumNewShops20 accumNewShops28 accumNewShops40
meanAccumNewShops4 meanAccumNewShops8 meanAccumNewShops20 meanAccumNewShops28 meanAccumNewShops40

averagePrice accumAveragePrice 
accumAveragePrice4 accumAveragePrice8 accumAveragePrice20 accumAveragePrice28 accumAveragePrice40
meanAccumAveragePrice4 meanAccumAveragePrice8 meanAccumAveragePrice20 meanAccumAveragePrice28 meanAccumAveragePrice40 

sdShopPrices accumSDShopPrices 
accumSDShopPrices4 accumSDShopPrices8 accumSDShopPrices20 accumSDShopPrices28 accumSDShopPrices40
meanAccumSDShopPrices4 meanAccumSDShopPrices8 meanAccumSDShopPrices20 meanAccumSDShopPrices28 meanAccumSDShopPrices40

totalQuantitySold accumQuantitySold 
accumQuantitySold4 accumQuantitySold8 accumQuantitySold20 accumQuantitySold28 accumQuantitySold40
meanAccumQuantitySold4 meanAccumQuantitySold8 meanAccumQuantitySold20 meanAccumQuantitySold28 meanAccumQuantitySold40

capacityOfIndustry accumCapacityOfIndustry
accumCapacityOfIndustry4 accumCapacityOfIndustry8 accumCapacityOfIndustry20 accumCapacityOfIndustry28 accumCapacityOfIndustry40
meanAccumCapacityOfIndustry4 meanAccumCapacityOfIndustry8 meanAccumCapacityOfIndustry20 meanAccumCapacityOfIndustry28 meanAccumCapacityOfIndustry40
]

breed [consumers consumer]
breed [shops shop]

consumers-own 
  [ 

    nOfSuppliers
    wtp
    consumerType
    ownDemand
    pricePaid 
    supplier 
    purchase-history
    boughtThisRound
    spendingThisRound
    spending-history

  ]     

shops-own 
  [    
    ownCapacity
    ownUtilisationRate
    ownCapacityCost
    ownFixedCosts
    ownVariableCost
    ownTotalCost   
    ownMarkUp 
    ownPrice
    shopType
    ownSupply  
    customer
    ownLastDeal
    lastStock
    ownStock
    lastSales
    ownSales 
    revenue  
    pastProfit
    profit
    profit-history
    sales-history
    stock-history
    price-history
    capacity-history
    capacityIncrease 
    utilisation-history
    birthdate ; round at which created
    competitors
   ]

;________________________________________________________________________________________________________________________________________________
to setup 

  clear-all
  ask patches  [set pcolor white]
    
  set nOfConsumers 1000
  
  set accumQuantitySold4 [  ]  set accumQuantitySold8 [  ]  set accumQuantitySold20 [  ]  set accumQuantitySold28 [  ] set accumQuantitySold40 [  ]
  set accumCapacityOfIndustry4 [  ] set accumCapacityOfIndustry8 [  ] set accumCapacityOfIndustry20 [  ] set accumCapacityOfIndustry28 [  ] set accumCapacityOfIndustry40 [  ]
   
  set accumAveragePrice4 [  ]  set accumAveragePrice8 [  ]  set accumAveragePrice20 [  ] set accumAveragePrice28 [  ]  set accumAveragePrice40 [  ]   
  set accumSDShopPrices4 [  ] set accumSDShopPrices8 [  ] set accumSDShopPrices20 [  ] set accumSDShopPrices28 [  ] set accumSDShopPrices40 [  ]
    
  set accumSizeOfIndustry4 [  ] set accumSizeOfIndustry8 [  ]  set accumSizeOfIndustry20 [  ] set accumSizeOfIndustry28 [  ]  set accumSizeOfIndustry40 [  ] 
  set accumNewShops4 [  ]  set accumNewShops8 [  ]  set accumNewShops20 [  ]  set accumNewShops28 [  ]  set accumNewShops40 [ ]
   
 
reset-ticks
end

;--------------------------------------------------------------------------------------------------

to go 
  
  
 repeat number-of-runs

 [  
  ; at start ot each run

   reset-globals

   repeat number-of-rounds
   [   
      set round-counter round-counter + 1     
      
      if round-counter = 1 
         [ ask consumers [ ifelse search = "About half"  
                              [ set nOfSuppliers count shops in-radius reach ] 
                              [ set nOfSuppliers "All" ]
                         ]       
            ]
      
      ifelse round-counter > 1  and remainder ( round-counter - 1 )  4  = 0 
          [ make-yearly-adjustments ]
          [ make-quarterly-adjustments ]      
      
      draw-demand-and-supply-curves ; has to be done at this stage otherwise does not work properly
      
      trade 
   
      collect-data-at-end-of-round  
   
   ]
   
    collect-data-at-end-of-run 
 
 ] 
  collect-data-at-end   

  
end

;____________________________________________________________________________________________________________________________________________________
; PROCEDURES
;____________________________________________________________________________________________________________________________________________________

to reset-globals
; This cannot be done in setup because it needs to be done for each run.  

; general
  
set run-counter run-counter + 1  
set round-counter 0

if search = "All" [ set reach 500 ]
if search = "About half" [ set reach 125 ]

clear-turtles 

; consumers

create-consumers nOfConsumers  ; fixed at 1000 in set-up
  [
   set shape "person"
   set color black
   set size 5 
   setxy random-pxcor random-pycor  
     if any? other turtles-here [ 
      let empty-patches patches with [ not any? turtles-here ] 
      if not any? empty-patches [ show "Run out of empty patches!"]
      move-to one-of empty-patches ]
   set spending-history [ ] ; to check purchases etc
   set purchase-history [ ] ; to check purchases etc
   ] 

; set willingness-to-pay (wtp:) gives random figure between 5 and 15 to ensure that all can afford the product
  ask consumers [ set wtp 5 + random 11 ] ; 


 set totalDemand count consumers with [ wtp >= 10 ]

; shops
 

 set meanCapacity precision ( floor totalDemand / nOfShops ) 0


create-shops nOfShops [ define-shops ]


; to record results
  set accumQuantitySold [  ]
  set accumAveragePrice [  ]
  set accumSDShopPrices [  ]
  set accumSizeOfIndustry [  ]
  set accumCapacityOfIndustry [  ] 
  set accumNewShops [  ]
    
; to draw demand and supply curves etc
  set tempPrice 0
  set demandCurve 0
  set supplyCurve 0
  set excessDemand 0

end

;-----------------------------------------------------------------------

to round-reset
ask consumers
  [
   set color black
   set supplier nobody 
   set boughtThisRound "No"
 ]

ask shops
 [ 
  set color red
  set customer nobody 
  set ownSupply 0  
  set ownStock 0
  set ownLastDeal 0
  set ownSales 0
  set revenue  0
  set profit 0
 ] 

end  

; ------------------------------------------------------------------------
to define-shops
  
; need to be able to call on this to create new shops  
; is prefaced automatically by "ask shops".

  set shape "pentagon"
  set color red
  set size 7
  setxy random-pxcor random-pycor  
    if any? other turtles-here [ 
      let empty-patches patches with [ not any? turtles-here ] 
      if not any? empty-patches [ show "Run out of empty patches!"]
      move-to one-of empty-patches ]
  ifelse round-counter = 0 [ set birthdate round-counter + 1] 
                           [ set birthdate round-counter ]
                              
if scenario = "Perfect" ; all shops the same
 [ 
      set ownCapacity meanCapacity
      set ownCapacityCost meanCapacityCost
      set ownVariableCost meanVariableCost 
      set ownUtilisationRate meanUtilisationRate%      
  ]

if scenario = "Real" ; standard deviations set to 10% of means
  [ 
       set ownCapacity  precision ( random-normal meanCapacity ( meanCapacity * 0.1 ) ) 0  
        if ownCapacity = 0 [ set ownCapacity  meanCapacity ] 
        if ownCapacity > 1000 [ set owncapacity 1000 ]
       set ownCapacityCost precision ( random-normal meanCapacityCost ( meanCapacityCost * 0.1 ) ) 1  
        if ownCapacityCost = 0 [ set ownCapacityCost  meanCapacityCost ]
       set ownVariableCost precision ( random-normal meanVariableCost ( meanVariableCost * 0.1 ) ) 1  
        if ownVariableCost = 0 [ set ownVariableCost  meanVariableCost ]            
       set ownUtilisationRate precision (  random-normal meanUtilisationRate% ( meanUtilisationRate% * 0.1 ) / 100 ) 2 
        if ownUtilisationRate > 1 [ set ownUtilisationRate 1 ]    
      
   ]
       
     calculate-supply 
     set ownFixedCosts precision ( ownCapacity * ownCapacityCost ) 1 
  
     ; markup
     set ownMarkUp precision ( ownCapacityCost / ownVariableCost ) 3
     set ownPrice precision ( ownVariableCost * ( 1 + ownMarkUp ) ) 1 

 
                          
  set price-history [ ]
  set profit-history [ ] 
  set sales-history [ ]
  set stock-history [ ]
  set capacity-history [  ]
  set utilisation-history [  ]
   
end

;---------------------------------------------------------

to draw-demand-and-supply-curves 
; this ignores any restrictions on searching

 if run-counter = 1 and round-counter = 1
 [ 
; initialise
  set tempPrice 1

  repeat 25
  [  
 ; demand
;  set price tempPrice
  set demandCurve count consumers with [ wtp >= tempPrice ]
  
 ; supply                                              
  set supplyCurve ( sum [ ownSupply ] of shops with [ ownPrice <= tempPrice ]  ) 
  
 ; draw demand and supply curves 

  set-current-plot "Demand and Supply at start of first run"
  set-plot-x-range 0 1000
  set-plot-y-range 0 25
  set-current-plot-pen "demand"
  plotxy demandCurve tempPrice 
  set-current-plot-pen "supply"
  plotxy supplyCurve tempPrice  
 
; roll forward
  set tempPrice tempPrice + 1 
   ] 
]

  
end

;-----------------------------
to calculate-supply
; shops  
; keep separate as used more than once!

  set ownSupply precision ( ownUtilisationRate * ownCapacity ) 0 

end          

;--------------------------
to trade

  ask shops [ 
              set ownStock ownSupply
              set ownSales 0
            ]

  set totalSupply sum  [ ownSupply ] of shops

  ask consumers [ set boughtThisRound "No" 
                  set color black
                ]

; Consumers seek lowest price 
; Need to set out group by group to ensure actions taken in correct order - otherwise can find shops selling stock they haven't got!

          
  ask consumers 
    [ 
         set supplier min-one-of shops in-radius reach with [ ownStock > 0 ]  [ ownPrice ]  
         go-shopping 
    ]

end

;---------------------------
to go-shopping
  
    if supplier != nobody and [ ownPrice ] of supplier <= wtp ; 
      [
       ask supplier 
              [     
                set ownStock ownStock - 1
                set ownSales ownSales + 1
                set color blue
              ] 
        ; consumer   
        set pricePaid [ ownPrice ] of Supplier
        set boughtThisRound "Yes" 
        set color green     
      ]  
 
end

;--------------------------------
to make-quarterly-adjustments
; shops
  
; Each quarter change supply, price and variable costs according to sales 

; Shops selling all their stock and operating below capacity, increase their utilisation rate by 10%

     ask shops with [ lastStock = 0 and ownUtilisationRate < 1 ] [ set ownUtilisationRate  precision ( ownUtilisationRate * (1 + utilisationRateIncrease% / 100 )) 3 ]

; Shops not selling all their stock reduce their supply, costs, prices.
     
     ask shops with [ lastStock > 0 ] 
       [ 
         set ownStock precision ( ownCapacity - ( ownCapacity - lastSales ) / 2 ) 2
         set ownUtilisationRate precision ( ownStock / ownCapacity ) 2
         
         set competitors  count other shops in-radius reach 

         ; if monopoly, reduce price by 10%
         if competitors = 0 [ set ownPrice precision ( ownPrice *  0.9 ) 1 ]
         if competitors > 0
                 [ 
                   let competitorsPrice precision ( mean [ ownPrice ] of other shops in-radius reach ) 1
                   if  ownPrice > competitorsPrice  [ set ownPrice  precision ( competitorsPrice ) 1 ]
                 ]  
         if ownMarkUp > 0.33  [ set ownMarkUp 0.33 ]
         set ownVariableCost precision ( ownPrice / ( 1 + ownMarkUp )) 1
       ]                    

; to ensure that no shops supply above their capacity
     ask shops with  [ ownUtilisationRate > 1 ] [ set ownUtilisationRate  1 ]


; recalculate supply     
     ask shops [ calculate-supply ]

end


;----------------------------------

to make-yearly-adjustments
; Shops
; Every year (i.e. every 4 quarters) i.e. round 5, 9 etc
; Exisiting shops change capacity according to profitability.

; Shops making a cumulative loss over the last 4 rounds die
 ask shops with [ pastProfit < 0 ]  [ die ]
 
; Shops making a cumulative profit  over the last 4 rounds and whose utilisation rate is less than 100%, increase their utilisation by the amount set by the utilisationRateIncrease% slider 
 ask shops with [ pastProfit > 0 and ownUtilisationRate < 1 ] [ set ownUtilisationRate precision ( ownUtilisationRate * (1 + utilisationRateIncrease% / 100 ) ) 1 ] 

; Shops making a profit  over the last 4 rounds and whose utilisation rate is 100%, increase their capacity by the amount set by the capacityIncrease% slider 
 ask shops with [ pastProfit > 0 and ownUtilisationRate = 1 ] [ set ownCapacity precision ( ( 1 + capacityIncrease% / 100 ) * ownCapacity  ) 0 
                                                                set capacityIncrease "Yes" ]    
; to keep number of shops constant
  set nOfNewShops ( nOfShops - count shops )
  if nOfNewShops > 0 [ create-shops nOfNewShops [ define-shops ] ]
 
  ask shops [ set pastProfit 0 ] ; reset pastProfit to 0 

; utilisation cannot exceed 1
  ask shops with  [ ownUtilisationRate > 1 ] [ set ownUtilisationRate 1  ]

end

;________________________________________________________________________________________________________
; RESULTS
;________________________________________________________________________________________________________


to collect-data-at-end-of-round

 ask shops
         [     
           set revenue precision ( ownPrice * ownSales)  0       
           set ownTotalCost  precision (( ownVariableCost * ownSupply ) + ownFixedCosts ) 0   
           set profit precision ( revenue - ownTotalCost ) 0 
           set price-history lput ownPrice price-history     
           set profit-history lput profit profit-history 
           set sales-history lput ownSales sales-history
           set stock-history lput ownStock stock-history 
           set capacity-history lput ownCapacity capacity-history
           set utilisation-history lput ownUtilisationRate utilisation-history
           set lastStock ownStock
           set lastSales ownsales
           set pastProfit profit + pastProfit 
         ] 
 

; prices and sales
;  set accumEquilibPrice  lput equilibriumPrice accumEquilibPrice 
  set totalQuantitySold  sum [ ownSales ] of shops 
  set totalRevenue sum [ revenue ] of shops 
  ifelse totalQuantitySold > 0  
     [ set averagePrice precision ( totalRevenue /  totalQuantitySold ) 1 ] 
     [ set averagePrice 0 ]
  set accumQuantitySold lput totalQuantitySold accumQuantitySold
  set accumAveragePrice  lput averagePrice accumAveragePrice 
  ifelse count shops > 1 
     [ set sdShopPrices precision ( standard-deviation [ ownPrice ] of shops ) 1 ]
     [ set sdShopPrices 0 ]
  set accumSDShopPrices lput sdShopPrices accumSDShopPrices 


; capacity and size of industry
  set capacityOfIndustry sum [ ownCapacity ] of shops
  set accumCapacityOfIndustry lput capacityOfIndustry accumCapacityOfIndustry
  set sizeOfIndustry count shops
  set accumSizeOfIndustry lput sizeOfIndustry accumSizeOfIndustry
  set newShops ( count shops with [ birthdate > 1 ] )
  set accumNewShops lput newShops accumNewShops


if run-counter = 1
[
 set-current-plot "Industry size"
  set-current-plot-pen "Size"
  plotxy round-counter sizeOfIndustry
  set-current-plot-pen "New"
  plotxy round-counter newShops
  
 set-current-plot "Average price"
  plotxy round-counter averagePrice
  
 set-current-plot "Price variation"
  plotxy round-counter sdShopPrices
   
 set-current-plot "Quantities"
    set-current-plot-pen "Sold"
    plotxy round-counter totalQuantitySold
    set-current-plot-pen "Capacity"
    plotxy  round-counter  capacityOfIndustry

  
  set-current-plot "Profit and loss"
    set-current-plot-pen "Loss"
    plotxy  round-counter lossmakingShops  
    set-current-plot-pen "BE"
    plotxy round-counter breakevenShops
    set-current-plot-pen "Profit"
    plotxy round-counter profitableShops
  
]
end

; -----------------

to collect-data-at-end-of-run
  
  if number-of-rounds > 3 
 [ let averagePrice4 item 3 accumAveragePrice  
   set accumAveragePrice4 ( lput averagePrice4 accumAveragePrice4  )

   let sdShopPrices4 item 3 accumSDShopPrices
   set accumSDShopPrices4 ( lput sdShopPrices4 accumSDShopPrices4 )
   
   let quantitySold4 item 3 accumQuantitySold
   set accumQuantitySold4 ( lput quantitySold4 accumQuantitySold4  )   
    
   let capacityOfIndustry4 item 3 accumCapacityOfIndustry
   set accumCapacityOfIndustry4 ( lput capacityOfIndustry4 accumCapacityOfIndustry4  )
   
   let sizeOfIndustry4 item 3 accumSizeOfIndustry   
   set accumSizeOfIndustry4 ( lput sizeOfIndustry4 accumSizeOfIndustry4 )
   
   let newShops4 item 3 accumNewShops  
   set accumNewShops4 ( lput newShops4 accumNewShops4 )
   
 ] 
  
 
 if number-of-rounds > 7 
 [ let averagePrice8 item 7 accumAveragePrice  
   set accumAveragePrice8 ( lput averagePrice8 accumAveragePrice8  )
   
   let sdShopPrices8 item 7 accumSDShopPrices
   set accumSDShopPrices8 ( lput sdShopPrices8 accumSDShopPrices8 )
   
   let quantitySold8 item 7 accumQuantitySold
   set accumQuantitySold8 ( lput quantitySold8 accumQuantitySold8  )   
   
   let capacityOfIndustry8 item 7 accumCapacityOfIndustry
   set accumCapacityOfIndustry8 ( lput capacityOfIndustry8 accumCapacityOfIndustry8  )
   
   let sizeOfIndustry8 item 7 accumSizeOfIndustry   
   set accumSizeOfIndustry8 ( lput sizeOfIndustry8 accumSizeOfIndustry8 )
   
   let newShops8 item 7 accumNewShops  
   set accumNewShops8 ( lput newShops8 accumNewShops8 )
   
 ]
 
 if number-of-rounds > 19 
 [ let averagePrice20 item 19 accumAveragePrice  
   set accumAveragePrice20 ( lput averagePrice20 accumAveragePrice20  )
   
   let sdShopPrices20 item 19 accumSDShopPrices
   set accumSDShopPrices20 ( lput sdShopPrices20 accumSDShopPrices20 )
   
   let quantitySold20 item 19 accumQuantitySold
   set accumQuantitySold20 ( lput quantitySold20 accumQuantitySold20  )  
   
   let capacityOfIndustry20 item 19 accumCapacityOfIndustry
   set accumCapacityOfIndustry20 ( lput capacityOfIndustry20 accumCapacityOfIndustry20  ) 
   
   let sizeOfIndustry20 item 19 accumSizeOfIndustry   
   set accumSizeOfIndustry20 ( lput sizeOfIndustry20 accumSizeOfIndustry20 )
   
   let newShops20 item 19 accumNewShops  
   set accumNewShops20 ( lput newShops20 accumNewShops20)
   
    
 ]  
 
  if number-of-rounds > 27
 [ let averagePrice28 item 27 accumAveragePrice  
   set accumAveragePrice28 ( lput averagePrice28 accumAveragePrice28  )
   
   let sdShopPrices28 item 27 accumSDShopPrices
   set accumSDShopPrices28 ( lput sdShopPrices28 accumSDShopPrices28 )
   
   let quantitySold28 item 27 accumQuantitySold
   set accumQuantitySold28 ( lput quantitySold28 accumQuantitySold28  )   
   
   let capacityOfIndustry28 item 27 accumCapacityOfIndustry
   set accumCapacityOfIndustry28 ( lput capacityOfIndustry28 accumCapacityOfIndustry28  ) 
   
   let sizeOfIndustry28 item 27 accumSizeOfIndustry   
   set accumSizeOfIndustry28 ( lput sizeOfIndustry28 accumSizeOfIndustry28 )
   
   let newShops28 item 27 accumNewShops  
   set accumNewShops28 ( lput newShops28 accumNewShops28)
      
 ]  
 
 if number-of-rounds > 39 
 [ let averagePrice40 item 39 accumAveragePrice  
   set accumAveragePrice40 ( lput averagePrice40 accumAveragePrice40 )
   
   let sdShopPrices40 item 39 accumSDShopPrices
   set accumSDShopPrices40 ( lput sdShopPrices40 accumSDShopPrices40 )
   
   let quantitySold40 item 39 accumQuantitySold
   set accumQuantitySold40 ( lput quantitySold40 accumQuantitySold40  )  
   
   let capacityOfIndustry40 item 39 accumCapacityOfIndustry
   set accumCapacityOfIndustry40 ( lput capacityOfIndustry40 accumCapacityOfIndustry40  ) 
   
   let sizeOfIndustry40 item 39 accumSizeOfIndustry   
   set accumSizeOfIndustry40 ( lput sizeOfIndustry40 accumSizeOfIndustry40 )
   
   let newShops40 item 39 accumNewShops  
   set accumNewShops40 ( lput newShops40 accumNewShops40 )

   
 ] 
  
end

;--------------------------------------------------
to collect-data-at-end 

;industry size

if number-of-rounds > 3  [ set meanAccumSizeOfIndustry4 mean accumSizeOfIndustry4 
                           set meanAccumAveragePrice4  mean accumAveragePrice4 
                           set meanAccumSDShopPrices4 mean accumSDShopPrices4 
                           set meanAccumQuantitySold4  mean accumQuantitySold4 
                           set meanAccumCapacityOfIndustry4 mean accumCapacityOfIndustry4
                           set meanAccumNewShops4 mean accumNewShops4    
                          ]

if number-of-rounds > 7  [ set meanAccumSizeOfIndustry8 mean accumSizeOfIndustry8 
                           set meanAccumAveragePrice8  mean accumAveragePrice8 
                           set meanAccumSDShopPrices8 mean accumSDShopPrices8
                           set meanAccumQuantitySold8  mean accumQuantitySold8 
                           set meanAccumCapacityOfIndustry8 mean accumCapacityOfIndustry8
                           set meanAccumNewShops8 mean accumNewShops8    
                          ]

if number-of-rounds > 19  [ set meanAccumSizeOfIndustry20 mean accumSizeOfIndustry20 
                            set meanAccumAveragePrice20  mean accumAveragePrice20
                            set meanAccumSDShopPrices20 mean accumSDShopPrices20 
                            set meanAccumQuantitySold20  mean accumQuantitySold20 
                            set meanAccumCapacityOfIndustry20 mean accumCapacityOfIndustry20 
                            set meanAccumNewShops20 mean accumNewShops20    
                          ]
 

if number-of-rounds > 27  [ set meanAccumSizeOfIndustry28 mean accumSizeOfIndustry28 
                            set meanAccumAveragePrice28  mean accumAveragePrice28
                            set meanAccumSDShopPrices28 mean accumSDShopPrices28 
                            set meanAccumQuantitySold28  mean accumQuantitySold28
                            set meanAccumCapacityOfIndustry28 mean accumCapacityOfIndustry28
                            set meanAccumNewShops28 mean accumNewShops28    
                          ] 

if number-of-rounds > 39 [ set meanAccumSizeOfIndustry40 mean accumSizeOfIndustry40 
                           set meanAccumAveragePrice40  mean accumAveragePrice40 
                           set meanAccumSDShopPrices40 mean accumSDShopPrices40 
                           set meanAccumQuantitySold40  mean accumQuantitySold40 
                           set meanAccumCapacityOfIndustry40 mean accumCapacityOfIndustry40 
                           set meanAccumNewShops40 mean accumNewShops40    
                          ] 
 

 file-open (word "Shops-"scenario"-"description".csv" ) 
 
 file-print (word "Scenario " scenario ": Description " description)
 file-print " " 

 
 file-print " " 
 file-print ( word "Results over "  number-of-runs " runs with " number-of-rounds " rounds")
 file-print " "  
 
  file-print (word "Round 4"  )
  ifelse empty? accumAveragePrice8
   [ file-print  (word " No prices" ) ]
   [ file-type  (word "  Mean price  = " precision ( meanAccumAveragePrice4 ) 1 )
     if number-of-runs > 1 [ file-print (word " sd = " precision ( standard-deviation accumAveragePrice4  ) 1 )  ] ]  
  ifelse empty? accumQuantitySold4
   [ file-print  (word " No sales" ) ]
   [ file-type  (word "  Mean quantity sold  = " precision ( meanAccumQuantitySold4 ) 1 )
     if number-of-runs > 1 [ file-print (word " sd = " precision ( standard-deviation accumQuantitySold4  ) 1 )  ] ] 
  ifelse empty? accumSizeOfIndustry4
   [ file-print  (word " No shops" ) ]
   [ file-type  (word "  Mean industry size  = " precision ( meanAccumSizeOfIndustry4 ) 1 )
     if number-of-runs > 1 [ file-print (word " sd = " precision ( standard-deviation accumSizeOfIndustry4  ) 1 )  ] ]
  ifelse empty? accumNewShops4
   [ file-print  (word " No shops" ) ]
   [ file-type  (word "  Mean no. of new shops  = " precision ( meanAccumNewShops4 ) 1 )
     if number-of-runs > 1 [ file-print (word " sd = " precision ( standard-deviation accumNewShops4  ) 1 )  ] ]
  

 file-print (word "Round 8"  )
  ifelse empty? accumAveragePrice8
   [ file-print  (word " No prices" ) ]
   [ file-type  (word "  Mean price  = " precision ( meanAccumAveragePrice8 ) 1 )
     if number-of-runs > 1 [ file-print (word " sd = " precision ( standard-deviation accumAveragePrice8  ) 1 )  ] ]  
  ifelse empty? accumQuantitySold8
   [ file-print  (word " No sales" ) ]
   [ file-type  (word "  Mean quantity sold  = " precision ( meanAccumQuantitySold8 ) 1 )
     if number-of-runs > 1 [ file-print (word " sd = " precision ( standard-deviation accumQuantitySold8  ) 1 )  ] ] 
  ifelse empty? accumSizeOfIndustry8
   [ file-print  (word " No shops" ) ]
   [ file-type  (word "  Mean industry size  = " precision ( meanAccumSizeOfIndustry8 ) 1 )
     if number-of-runs > 1 [ file-print (word " sd = " precision ( standard-deviation accumSizeOfIndustry8  ) 1 )  ] ]
  ifelse empty? accumNewShops8
   [ file-print  (word " No shops" ) ]
   [ file-type  (word "  Mean no. of new shops  = " precision ( meanAccumNewShops8 ) 1 )
     if number-of-runs > 1 [ file-print (word " sd = " precision ( standard-deviation accumNewShops8  ) 1 )  ] ] 
  
   
 file-print (word "Round 20"  )
  ifelse empty? accumAveragePrice20
   [ file-print  (word " No prices" ) ]
   [ file-type  (word "  Mean price  = " precision ( meanAccumAveragePrice20 ) 1 )
     if number-of-runs > 1 [ file-print (word " sd = " precision ( standard-deviation accumAveragePrice20  ) 1 )  ] ]  
  ifelse empty? accumQuantitySold20
   [ file-print  (word " No sales" ) ]
   [ file-type  (word "  Mean quantity sold  = " precision ( meanAccumQuantitySold20 ) 1 )
     if number-of-runs > 1 [ file-print (word " sd = " precision ( standard-deviation accumQuantitySold20  ) 1 )  ] ] 
  ifelse empty? accumSizeOfIndustry20
   [ file-print  (word " No shops" ) ]
   [ file-type  (word "  Mean industry size  = " precision ( meanAccumSizeOfIndustry20 ) 1 )
     if number-of-runs > 1 [ file-print (word " sd = " precision ( standard-deviation accumSizeOfIndustry20  ) 1 )  ] ]  
  ifelse empty? accumNewShops20
   [ file-print  (word " No shops" ) ]
   [ file-type  (word "  Mean no. of new shops  = " precision ( meanAccumNewShops20 ) 1 )
     if number-of-runs > 1 [ file-print (word " sd = " precision ( standard-deviation accumNewShops20  ) 1 )  ] ] 
  
   
 file-print (word "Round 28"  )
  ifelse empty? accumAveragePrice28
   [ file-print  (word " No prices" ) ]
   [ file-type  (word "  Mean price  = " precision ( meanAccumAveragePrice28 ) 1 )
     if number-of-runs > 1 [ file-print (word " sd = " precision ( standard-deviation accumAveragePrice28  ) 1 )  ] ]  
  ifelse empty? accumQuantitySold28
   [ file-print  (word " No sales" ) ]
   [ file-type  (word "  Mean quantity sold  = " precision ( meanAccumQuantitySold28 ) 1 )
     if number-of-runs > 1 [ file-print (word " sd = " precision ( standard-deviation accumQuantitySold28  ) 1 )  ] ] 
  ifelse empty? accumSizeOfIndustry28
   [ file-print  (word " No shops" ) ]
   [ file-type  (word "  Mean industry size  = " precision ( meanAccumSizeOfIndustry28 ) 1 )
     if number-of-runs > 1 [ file-print (word " sd = " precision ( standard-deviation accumSizeOfIndustry28  ) 1 )  ] ]  
  ifelse empty? accumNewShops28
   [ file-print  (word " No shops" ) ]
   [ file-type  (word "  Mean no. of new shops  = " precision ( meanAccumNewShops28 ) 1 )
     if number-of-runs > 1 [ file-print (word " sd = " precision ( standard-deviation accumNewShops28  ) 1 )  ] ]   
   
  
 file-print (word "Round 40"  )
 ifelse empty? accumAveragePrice40
   [ file-print  (word " No prices" ) ]
   [ file-type  (word "  Mean price  = " precision ( mean accumAveragePrice40 ) 1 )
     if number-of-runs > 1 [ file-print (word " sd = " precision ( standard-deviation accumAveragePrice40  ) 1 )  ] ]    
 ifelse empty? accumQuantitySold40
   [ file-print  (word " No sales" ) ]
   [ file-type  (word "  Mean quantity sold  = " precision ( meanAccumQuantitySold40 ) 1 )
     if number-of-runs > 1 [ file-print (word " sd = " precision ( standard-deviation accumQuantitySold40  ) 1 )  ] ]   
  ifelse empty? accumSizeOfIndustry40
   [ file-print  (word " No shops" ) ]
   [ file-type  (word "  Mean industry size  = " precision ( meanAccumSizeOfIndustry40 ) 1 )
     if number-of-runs > 1 [ file-print (word " sd = " precision ( standard-deviation accumSizeOfIndustry40  ) 1 )  ] ]
     ifelse empty? accumNewShops40
   [ file-print  (word " No shops" ) ]
   [ file-type  (word "  Mean no. of new shops  = " precision ( meanAccumNewShops40 ) 1 )
     if number-of-runs > 1 [ file-print (word " sd = " precision ( standard-deviation accumNewShops40  ) 1 )  ] ]   


export-all-plots (word "Shops-"scenario"-"description".csv" ) 

file-close
end

;__________________________________________________________________________________________________________________________________________________
;__________________________________________________________________________________________________________________________________________________


  
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Demand and Supply at start of first run
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"demand" 1.0 0 -13840069 true "" ""

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1 000 consumers (Green if bought)\nFirms = red blobs (Blue if traded)\n
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PLOT
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Average price
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MONITOR
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MONITOR
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MONITOR
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Utilisation 100%
count shops with [ ownutilisationrate = 1 ]
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Shops breaking even
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 Price variation
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description
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@#$#@#$#@
## WHAT IS IT?

Model of a simple market, based on small shops.

## HOW IT WORKS

### Consumers

Number of consumers is fixed at 1,000. Each consumer is allocated a willingness-to-pay, lying between 5 and 15. Consumers buy once each round: 

    ask consumers [ set ownDemand  floor ( wtp / price ) ]

Consumers seek out the cheapest shops within their range.

### Shops

Mean capacity is determined by the number of shops / number of consumers to ensure that the market can clear. Mean capacity unit costs, mean varaible costs and mean utilisation rate are set by the modeller.

Shops price on the basis of cost plus markup, so that if the shop operates at full capacity (i.e. utilisation = 100% ) it breaks even: 

markup x utilisation =  cost per unit of capacity / variable cost

See Box 6.3 for the underlying mathematics. Thus the coding is:

     set ownMarkUp precision ( ownCapacityCost / ownVariableCost ) 3
     set ownPrice precision ( ownVariableCost * ( 1 + ownMarkUp ) ) 1 


### Scenarios
There are two scenarios: 

####Perfect
All the shops are the same. 
     
      set ownCapacity meanCapacity
      set ownCapacityCost meanCapacityCost
      set ownVariableCost meanVariableCost 
      set ownUtilisationRate meanUtilisationRate%   

####Real

Shops' capacity, capacity costs, variable costs and utilisation rate is set at + or - 10% of the means.

    set ownCapacity  precision ( random-normal meanCapacity ( meanCapacity * 0.1 ) ) 0  
    set ownCapacityCost precision ( random-normal meanCapacityCost ( meanCapacityCost * 0.1 ) ) 1   
    set ownVariableCost precision ( random-normal meanVariableCost ( meanVariableCost * 0.1 ) ) 1  
    set ownUtilisationRate precision (  random-normal meanUtilisationRate% ( meanUtilisationRate% * 0.1 ) / 100 ) 2 



### Adjustment process

Every round - representing a quarter - shops change supply, price and variable costs according to sales 

- shops selling all their stock and operating below capacity, increase their their utilisation rate by 10%

- shops not selling all their stock reduce their supply, prices (based on comparison with competitors) and costs
  - supply is reduced by half the difference between their capacity and their last sales

    set ownStock precision ( ownCapacity - ( ownCapacity - lastSales ) / 2 ) 2

  - prices
      - if there are no competitors, prices are reduced by 10%

      - if there are competitors, the price is based on the average price of other shops within the distance set by the reach

       - the markup is set to 33%  

Every fourth round - to represent once a year 

- existing shops making a cumulative loss over the last 4 rounds die

- existing shops making a profit  over the last 4 rounds 

  - and whose utilisation rate is less than 100%, increase their utilisation rate by 10% 

  -  and whose utilisation rate is 100%, increase their capacity by the 10%
 
- The number of shops is kept constant. New shops are created using same capacity formula as original shops.

### Outputs

Price, quantity and industry size are recorded at rounds 4, 8 20, 28 and 40 (i.e. at the end of year 1,2,5,7 and 10).

For the first run, the results for all rounds is plotted.

All the results, including the plots, are sent to a .csv file called "Shops-scenario-description".


## HOW TO USE IT

Set the scenario.

Set the number of shops and the search option.

Set the number of rounds and runs required.

If desired, set a description to help you identify the output file.

WARNING: This model takes a long time to run. For example, 10 runs with 40 rounds can take 2 hours!


## THINGS TO TRY
 
Experiment with the options offered by the sliders. For example:
•	what happens when the capacity costs are very low compared to the variable costs? (Change the meanCapapcity Costs and the meanVariableCosts)
•	what happens when capacity can be expanded quickly? (Change the capacity increase%)
•	what happens when the initial values are set far from the zero profit values? (Use the formulae in Box 6.3 to calculate the zer profit values.)

Advanced: requiring programming: 
•	change the set variables such as the mean and standard deviations of capacity, capacity and variable costs and utilisation rate. 
•	change the adjustment process. 
o	change the utilisationRateIncrease% or the capacityIncrease%
o	make more sophisticated changes
•	use this program as the basis for other models of markets



## CREDITS AND REFERENCES
Runs on NetLogo 5.2.

For more information, see Hamill, L. & Gilbert, N. (2016) Agent-based Modelling in Economics. Wiley: Chapter 6.

To refer to this model: Hamill, L. & Gilbert, N. (2016) Shops model.
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