Leonardi Model 2

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Default-person Eleanor Anderson (Author)

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Part of project 'Technology Use'
Model group MAM-2013 | Visible to everyone | Changeable by the author
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## WHAT IS IT?

This model is based on Leonardi, P. M. (2012). Car Crashes Without Cars: Lessons About Simulation Technology and Organizational Change from Automotive Design. MIT Press (MA).

It is intended to represent what happens when a new technology is introduced into an organization and people are trying to figure out what it is good for. It models a cyclical set of dynamics between people's interactions with one another ("social interactions"), and interactions with the technology itself ("material interactions") working together to determine whether the tool is actually taken up and used.

The cycle works as follows: Social interactions (i.e. people talking to one another about the new tool) shape people’s expectations for the technology. These expectations turn shape their material interactions with the tool, as people tend to find only the affordances they know to look for. Information from these material interactions (i.e. whether the technology worked as a person expected or not) is then incorporated into future social interactions.

In Leonardi's ethnographic work, he found that these dynamics led to two different patterns:

1. People begin with a widespread expectation that the technology affords something it does not. In the end, most people abandon the technology.

2. People begin without clear expectations of what the technology affords. In the end most people use the technology.

This model is the second in a series designed to model these dynamics. Changes from Model 1 are in **bold**.

## HOW IT WORKS

The agents in this model are people and technologies. People have three important attributes:

1. A set of expectations about what the technology affords, including both a set of features (“a”, “b”, both, or neither) and a valence for each feature present (1 or -1). A valence of 1 represents a belief that the technology does afford that feature. A valence of -1 represents a belief that the technology does not afford that feature. People can also lack any expectation for a particular feature.

2. A usage, which refers to the features of the technology that they use. Usage can also take values of “a,” “b,” both or neither, however it does not hold valence.

3. A level of persistence. This refers to how many times people will interact with the technology before their expectations and usage become permanently fixed.

The technology (there is never more than one technology in a given simulation) holds one attribute: its affordances. The technology’s set of affordances can include “a”, “b”, both, or neither. If a particular feature is present its valence is always positive.

When the model begins, each person follows the following rules at each tick:

1. Turn a little and take a step forward

2. If I am close to any other agents (people or technology) and my persistence has not run out, pick a nearby agent to interact with

1. If I am interacting with another person **adjust one of my expectations to be more like theirs**

2. If I am interacting with the technology:

1. **If can-learn-unexpectedly is turned on, roll a die to see if I will learn one of the technology's affordances.** Either way, next:

2. Try to use the technology for one thing I expect it will be able to do

1. If that feature is among the technology’s affordances, add it to my usage (**if use-can-fail is on, roll a die first to see if I'll be successful**). If not, change my expectations to not believing the technology affords that feature

3. If I have no expectations, learn one feature from the technology itself (**at a chance based on the technology's transparency**)

4. Increment my persistence down

5. (If I have only negative expectations do nothing)

## HOW TO USE IT

Select a set of affordances for the technology.

Select the number of people who will start with expectations of “a,” “b,” both, or neither. All starting expectations are positive.

If auto-total people is set to a number, the model will automatically add people with no expectations to the model until the number of people equals auto-total number. If the user has already selected more than that number of people with starting expectations of "a", "b" or both, an error message will pop up.

Optionally “limited-persistence” can be turned on, which sets starting persistence at 3 for all people. When “limited persistence” is off, people start with a persistence of 1000—-an arbitrarily high number.

**Select a level of transparency for the technology. This determines the chance a person will be able to learn one of its affordances when they interact with it with no expectations.**

**Optionally "can-learn-unexpectedly" can be turned on, which means that people have a 5% chance of trying to learn from the technology before trying to use it.**

**Optionally "use-can-fail" can be turned on, which means that people have only a 95% chance of being able to find a technology's affordance when if they interact with it even if their expectations are correct.**

## THINGS TO NOTICE

People's expectations are represented by little symbols next to their head. Blue represents "a", and yellow represents "b". Dots indicate a positive expectation. Xs indicate a negative expectation.

People's usage is represented by the color of their body. Gray represents no usage, blue represents "a," yellow represents "b" and green represents both "a" and "b."

## THINGS TO TRY

Try to match the reference patterns Leonardi found in his ethnographic work!

## EXTENDING THE MODEL

**What happens if you change the model's stop conditions?**

## NETLOGO FEATURES

Note that both expectations and affordances are coded here using the Tables extension.

## RELATED MODELS

Leonardi Model 1: http://modelingcommons.org/browse/one_model/4072

Leonardi Model 3: http://modelingcommons.org/browse/one_model/4075

## CREDITS AND REFERENCES

http://modelingcommons.org/browse/one_model/4074

Leonardi, P. M. (2012). Car Crashes Without Cars: Lessons About Simulation Technology and Organizational Change from Automotive Design. MIT Press (MA).

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extensions [table]

globals [social-influence material-influence]

breed [people person]
breed [expectations expectation]
breed [technologies technology]


people-own [usage understanding influencer persistence]
expectations-own [feature strength]
technologies-own [affordances]


directed-link-breed [holds hold]

to setup
  ca  
  
  ; If auto-total-people is on, make sure the number of people expecting a, b and both doesn't exceed
  ;; the total number set. 
  ;; Populate the rest of the world (up to the total number set) with people with no expectations.

  ifelse auto-total-people != "off" and #-expecting-a + #-expecting-b + #-expecting-both > auto-total-people
  [ user-message (word "There are too many people. Turn auto-total off, or reduce the number of people expecting a, b or both.")]
  [ if auto-total-people != "off"
    [ set #-no-expectations auto-total-people - (#-expecting-a + #-expecting-b + #-expecting-both)]
  

  ;; create the total number of people who will be in the model
  ;; distribute them randomly around the world
  ;; format their size and shape
  ;; set their usage blank
  ;; format their color to reflect their usage
  ;; give each of them a blank table that will hold their expectations about the technology
  
  create-people total-# 
  [ setxy random-pxcor random-pycor
    set shape "person"
    set size 1.6
    set usage []
    color-code usage .8 
    set understanding table:make ]  
  
  
  ;; for the number of people expecting only a, pick people with blank tables, and set their understanding of feature a to 1 
  ask n-of #-expecting-a people with [ table:length understanding < 1 ]
  [ table:put understanding "a" 1 ]
  
  ;; for the number of people expecting only b, pick people with blank tables, and set their understanding of feature b to 1 
  ask n-of #-expecting-b people with [ table:length understanding < 1 ]
  [ table:put understanding "b" 1 ]
  
  ;; for the number of people expecting a and b, pick people with blank tables, and set their understanding of 
  ;; features a and b to 1   
  ask n-of #-expecting-both people with [ table:length understanding < 1 ]
  [ table:put understanding "a" 1
    table:put understanding "b" 1 ] 
  
  

  ask people
  
  ;;  build a network of expectations to provide a visual representation of each person's table of understanding
  [ update-expectations 
    
    ;; if limited persistence is on, give people a persistence of 3
    ;; if it's off, give people a persistence that is extremely high   
    ifelse limited-persistence
    [ set persistence 3 ]
    [ set persistence 1000 ] ]

  ;; format the network of expectations
  ask expectations
  [ format-expectations ]
  


  ;; set up the technology 
  adopt-technology  

  set social-influence []
  set material-influence []

  reset-ticks

]
end 

to update-expectations
  ;; ask people whose table of understandings doesn't match the visual representation of their expectations
  ask people with [table:length understanding != count out-hold-neighbors]
  
  ;; create a blank slate 
  [ ask out-hold-neighbors 
    [ die ]
  
  ;; build the network of expectations up from the understanding table  
  let instructions table:keys understanding
  while [instructions != []]
  [ hatch-expectations 1
    [ create-hold-from myself
      ask my-in-holds [hide-link] 
      set feature first instructions
      set strength [table:get understanding first instructions] of myself 
      set instructions but-first instructions  ] ] ]
  
  ask expectations
  [ format-expectations ] 
end 

to format-expectations
  
  ;; make expectations color, shape and placement reflect what they indicate
  
if strength > 1
  [ set strength 1 ]
  if strength < -1
  [ set strength -1 ]  
  

  if strength > 0
  [ show-turtle 
    set shape "circle"
    set size .5 ]

  if strength < 0
  [ show-turtle
    set shape "x"
    set size .6 ]

  if strength = 0
  [hide-turtle]
  
  
  if feature = "a"
  [ setxy ( [ xcor ] of one-of in-hold-neighbors - .5) ( [ ycor ] of one-of in-hold-neighbors + .5)  ] 
  if feature = "b"
  [ setxy ( [ xcor ] of one-of in-hold-neighbors + .5) ( [ ycor ] of one-of in-hold-neighbors + .5) ]
  
  color-code feature 1.5
end 

to adopt-technology
 
create-technologies 1
  [ set shape "box"
    set size 3
    
    ;; create a blank table that will hold affordances
    set affordances table:make
    
    ;; fill in the table from the features selected by the user
    let instructions (sentence technology-affordances)
    while [instructions != [] ]
  [ table:put affordances first instructions 1
    set instructions but-first instructions ] 
  
  color-code (table:keys affordances) -2.5]
end 


;; color code expectations, usage and affordances to  provide a visual indication of whether they match.  

to color-code [thing number]

;; I tried to let the number (i.e. the amount of color change) be set within this procedure (see below) but I couldn't 
;; get it to work. When the procedure was called by something that didn't hold one of the possible "things" it would
;; stop during the if statements and return an error message. Not sure why it wouldn't just return false and keep going...
;; But anyway, I relented and made the number I want each element's color adjusted by its own input, that I just list
;; when I call the procedure.
;; It's still much more parsimonious this way than having entirely separate procedures to color code expectations,
;; usage, and affordances which is what I used to have...

;let number 1
;if thing = usage 
;[set number .8]
;if thing = (table:keys affordances)
;[set number -2.5]
;if thing = feature
;[set number 1.5] 

  
  if member? "a" thing and not member? "b" thing
    [ set color blue + number ] 
  if member? "b" thing and not member? "a" thing
    [ set color yellow + number ] 
  if member? "a" thing and member? "b" thing
    [ set color green + number] 
  if not member? "a" thing and not member? "b" thing
    [ set color gray + number ]
end 

to go
  
  ;; stop conditions
  if all? people [persistence = 0] 
    [ stop ]
  if ticks > 99 and (all? people [usage = []] 
    or all? people [usage = ["a"]] 
    or all? people [usage = ["b"]] 
    or all? people [usage = ["a" "b"] or usage = ["b" "a"]]) 
    [ stop ]
  
  ;; running the model
  ask people
  [ move
    interact
    update-expectations ] 
  
  update-influences
  tick  
end   

to move
  
  let path random-normal 0 30
  rt path
  fd 1 

  ;; bring visual expectations along with
  ask out-hold-neighbors
    [ rt path
      fd 1 ]     
end   

to interact
  
  set influencer nobody
  
  if persistence > 0
  
  ;; if I am near the technology or a person, pick one of those entities to influence me  
  [ let potential-influencers (turtle-set technologies in-radius 3 other people in-radius 1)
    set influencer one-of potential-influencers
    
    ;; if I am being influenced by a person (social interaction), then learn from their expectations
    if is-person? influencer 
    [ learn-from ([understanding] of influencer) 1 .2]
    
    ;; if I am being influenced by the technology (material interaction), then if I have some expectation of
    ;; what the technology is for I will try to use it accordingly.
    ;; otherwise I will learn from the technology
    if is-technology? influencer 
    [ ifelse table:length understanding > 0
      [ use-technology ] 
      [ learn-from ([affordances] of influencer) tech-transparency 1 ]  
    ;; increment my persistence down 
    set persistence persistence - 1 ] ]
end  

to learn-from [source chance influence]
  
  ;; set probability of learning
  ;; if the influencer has any features to learn from,
  ;; pick one to be the insight I learn
  if table:length source > 0 and random-float 1 < chance
  [ let insight one-of table:keys source
    
    
    ;; if that feature is new to me, put the insight into my table of understandings
    
    if not table:has-key? understanding insight
    [ table:put understanding insight 0 ]
    
    ;; determine whether this is going to be learning something positive or negative
    let direction 1
    if table:get source insight > 0
      [ set direction 1 ]
    if table:get source insight < 0
      [ set direction -1 ]
    
    ;; change expectation to be more positive/more negative 
    ;; (amount of change is .2 for people influencers, 1 for technology influencer)
    table:put understanding insight table:get understanding insight + influence * direction 
    
    ;; cap expectation strength at >= -1 and <= 1 
    if abs table:get understanding insight > 1
      [table:put understanding insight direction] 
    
    ;; adjust visual version of expectations to match understanding
    ask out-hold-neighbors with [feature = insight ]
    [ set strength [table:get understanding insight] of myself ] ]
end  

to use-technology
  
  ;; if can-learn-unexpectly is on, give a 5% chance of trying to learn from the technology before trying to use it 
  if can-learn-unexpectedly
  [ if random-float 1 < .05
    [ learn-from ([affordances] of influencer) tech-transparency 1 ] ] 
  
  ;; if I have any positive expectations, pick one of those to be the way I try to use the technology 
  if any? out-hold-neighbors with [strength > 0] 
  [ let use [feature] of one-of out-hold-neighbors with [ strength > 0 ]
    
    ;; if use-can-fail is on, set the chance that use will be successful down to 95%
    let chance-use-works 1
    if use-can-fail 
    [ set chance-use-works .95 ]
 
    ;; if the feature I'm trying to use is one of the technology's affordances, then put that feature into my usage (if use is successful)
    ;; and set my expectation for that feature fully to 1
    ;; if not, set my expectation for that feature fully negative and remove it from my usage 
    ifelse table:has-key? [affordances] of influencer use and random-float 1 < chance-use-works
    [ table:put understanding use 1 
      set usage lput use usage
      set usage remove-duplicates usage 
      color-code usage .8 ]
    [ table:put understanding use -1
      set usage remove use usage
      color-code usage .8 ]
    
    ;;ask my visual expectation network to adjust accordingly
    ask out-hold-neighbors with [feature = use ]
    [ set strength [table:get understanding use] of myself ]  ]
end  

to update-influences
  
  ;; list the proportion of people experiencing social and material influences at each tick
  if any? people with [persistence > 0]
  [ set social-influence fput (count people with [is-person? influencer] / count people with [persistence > 0]) social-influence
    set material-influence fput (count people with [is-technology? influencer] / count people with [persistence > 0]) material-influence ]
end 

to-report total-#
  ;; report the total number of people in the world
  report #-expecting-a + #-expecting-b + #-expecting-both + #-no-expectations
end 

to-report %-open-to-influence
  ;; report the % of people who are still open to being influenced out of the total 
  report count people with [persistence > 0 ] / total-#
end 

to-report %-being-influenced
  ;; report the % of people currently being influenced, out of the total (or out of the number open to being influenced)
  report count people with [influencer != nobody] / total-# ;count people with [persistence > 0]
end 

to-report average-social-influence
  ;; report the average % of people influenced by other people out of the number open to being influenced at each tick
  report sum social-influence / (length social-influence)
end 

to-report average-material-influence
  ;; report the average % of people influenced by the technology out of the number open to being influenced at each tick
  report sum material-influence / (length material-influence)
end 

There are 2 versions of this model.

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