Innovation Diffusion through Interpersonal Channels

;; INTERPERSONAL CHANNELS AND INNOVATION DIFFUSION - FIRST VERSION 11.06.2015
;; this model catch the opinion formation among economic agents toward an incremental innovation as influenced by the social interplay with other agents
;; agents are persuaded to adopt if their opinion is positive and exceeds a certin treshold
;; the main drivers of persuation are the opinion of the other agents the subject interact with
;; the model reproduce the web of relations among a real local productive system of agricultural firms 
;; the model is calibrated to obtain a percentage of adopters similar to the one observed in real data
;; the aim is to model policy actions able to make more speedy and effcient the innovation spread (in terms of positive opinion formation)

turtles-own 
[node-id ;;this is tha name of each turtle
  persuation ;; this indicates the level of persuation of each actors
  threshold ;; this is the minimun proportion of the agent neighbor necessary to persuade the agent towards the novelty
  opinion ;; this is the agent's level of acceptance towards the novelty
  edu ;; this is the agent's level of education
  novelty? ;; this is a boolean: false if the persuation is lower than the threshold and true if the persuation is equal or greather than the threshold ]
  influence ;; this is the influence exerted by neighbors on the agent as calculated with the procedure to pass-information
  susceptible? ;; this is a boolean: false if the agent is not suceptible to neighbor influence (its persuation does not variate during the process
               ;; true if the agent is suceptible to neighbor influence (its persuation variates during the process)
  n-strenght ;; is the amount of persuation exerted by the neighbors on the agent              
  injection ;; this is 1 if the agents is used as and injection point and o otherwise
  out-pressure ;; the pressure the agent exert on the others
  out-pressure2 ;; the pressure the agent exert on the others proof 
  in-link
  out-link
]

links-own [strenght]

globals [links-list]

to setup
  clear-all
  set-default-shape turtles "circle"
  import-attributes
  layout-circle (sort turtles) (max-pxcor - 1)
  import-links
  select-agent
  reset-ticks
end 

;; This procedure reads in a files that contains node-specific attributes
;; including an unique identification number

to import-attributes
  ;; This opens the file, so we can use it.
  file-open "ATTRIBUTES_50.txt"
  ;; Read in all the data in the file
  ;; data on the line is in this order:
  ;; node-id attribute1 attribute2
  while [not file-at-end?]
  [
    ;; this reads a single line into a three-item list
    let items read-from-string (word "[" file-read-line "]")
    crt 1 [
      set node-id item 0 items
      set injection 0 ;; item 1 items
      set threshold item 2 items  
      set opinion item 3 items  
      set edu item 4 items  
      set color green
      set novelty? false
      set influence 0
      set susceptible? true
      set n-strenght 0
      set persuation 0
      set out-pressure 0
      set in-link []
      set out-link []       
      ]
   ]
  file-close
end 

to select-agent
  ask turtle me [
    set injection 1
    set susceptible? false
    set persuation 1
    set novelty? true
    set color red] 
end 

;; The following procedure (between **START** and **END**) is replicated from 
;; Network Import Example, by Uri Wilensky (model ID 2214) -- NetLogo 
;; link: http://modelingcommons.org/browse/one_model/2214#model_tabs_browse_procedures
;; **START**
;; This procedure reads in a file that contains all the links
;; The file is simply 3 columns separated by spaces.  In this
;; example, the links are directed.  The first column contains
;; the node-id of the node originating the link.  The second
;; column the node-id of the node on the other end of the link.
;; The third column is the strength of the link.

to import-links
  ;; This opens the file, so we can use it.
  file-open "KN_COOP_HOMOPHILY_50.txt"
  ;; Read in all the data in the file
  while [not file-at-end?]
  [
    ;; this reads a single line into a three-item list
    let items read-from-string (word "[" file-read-line "]")
    ask get-node (item 0 items)
    [
      create-link-to get-node (item 1 items)
        [ set strenght item 2 items ]
    ]
  ]
  file-close
end 
;; **END**

to pass-information
ask patches [
  let Rsk random-float 0.5
    ifelse random-float 1 > Rsk
      [set pcolor gray - 3 ] ;; randomly distribute Risk  - gray means that half revenues are achieved by niche producers
      [set pcolor black ]     
  ]
ask turtles [
    if pcolor = gray - 3
    [
      if susceptible? = true
      [
  let neighbors-persuation (map [[persuation] of ?] sort in-link-neighbors) ;; the list of persuation of my ORDERED neighbors
  let links-strenght (map [[strenght] of ?] sort my-in-links)  ;; the list of my ORDERED in-links strenght
  let neighbors-number count in-link-neighbors
  let neighbors-strenght (map * neighbors-persuation links-strenght)
  set n-strenght sum neighbors-strenght
  if neighbors-number > 0
[  set influence n-strenght / neighbors-number
   if influence > 1 [set influence 1]]
set persuation (persuation + influence) * edu / 21.5 ;; edu / 21 is the factor that catchs the effect of agent's educatnio on the complex of information passed by his neighbors
 if persuation > 1 [set persuation 1]     


if disappoint [ 
 let Rsk random-float 0.5
 let var (14 + random 14)
 if ticks = var [
 if random-float 1 > Rsk [
 let var1 (random 1 + random 3)
 let var2 (random-float -0.5 + random-float 0.5)
 ask n-of var1 turtles [set persuation var2] 
 ]
 ]
  ]
      ]
    ]
] 
end 

to persuade
  
  if ticks mod 4 = 0 [
  ask turtles [
  ifelse persuation >= threshold 
     [set novelty? true]
     [set novelty? false]
     ifelse novelty? = true
     [set color red
         ]
     [set color green]
     let out-links-strenght (map [[strenght] of ?] sort my-out-links)  ;; the list of my ORDERED out-links strenght
     let my-strenght (map [? * persuation] out-links-strenght)
     set out-pressure sum my-strenght 
         
     let out-links-strenght2 [strenght] of my-in-links  ;;  the list of my out-links strenght
     let my-strenght2 (map [? * persuation] out-links-strenght2)
     set out-pressure2 sum my-strenght2 
  ]
   ] 
end   

to-report get-node [id]
  report one-of turtles with [node-id = id]
end 

to go
   pass-information
   persuade
   set-current-plot "Agent Persuaded"
   plot agent-persuaded2
   tick
end 

to-report agent-persuaded
  report count turtles with [novelty? = true]
end 

to-report agent-persuaded2
  report count turtles with [color = red]
end 

to-report average-strenght
  report mean [n-strenght] of turtles
end 

to-report average-influence
  report mean [influence] of turtles
end 

to-report average-persuation
  report mean [persuation] of turtles
end 

to-report persuaded 
 report map [[novelty?] of ? ] sort turtles 
end 

to-report pressure 
  report map [[n-strenght] of ?] sort turtles 
end 

to-report attitude
  report map [[persuation] of ?] sort turtles 
end 

to-report my-pressure
 report map [[out-pressure] of ?] sort turtles
end 

to-report my-pressure2
 report map [[out-pressure2] of ?] sort turtles
end