1 interaction routines and opportunistic behaviours in an artificial market. ffv wholesale market:...
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Interaction routines and opportunistic
behaviours in an artificial market.
FFV wholesale market: field observation and model
WEHIA KYOTO – 5 / 27-29 / 2004
Juliette Rouchier GREQAM - Marseille
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General thematic and methodsTo understand the organisation of supply dynamics for a market:
– Indiv.: which information do individuals need to organise their activity?
– Global: what shape does competition actually take? • Are there market powers / coalitions?
• How do prices evolve in time?
• How do offer and demand evolve in time with market events?
The market we are dealing with: – FFV – Fresh Fruits and vegetables
– Professional market (“MIN”)
Two tools that interact:– Field observation and interviews with stakeholders and actors (the demand
originates in the market itself) – capture of the concrete market (Callon, 2004)
– Simulations to test assumptions about this system
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« les Arnavaux »• Marseille wholesale fruits and vegetables market.
– Outside the city, near the port, the airport, the motorway.– Open from 3:30 until 8:30 am. – 3 bars, 2 restaurants, a bank, tobacco retails
• Official rules– Pair wise interactions – “Mercuriales”: previous days’ average values for products– Access for two types of sellers (local producers and wholesale sellers)
and several types of buyers (retailers, restaurant owners, collective restaurants, supermarkets)
• Structural: position of the market– There are other markets in the area, « producer markets ». This is the
one with imported goods (winter mainly). – Formation of prices at the regional scale? (importers, producers,
supermarkets)
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An interaction-focused study• Relations between wholesale sellers and retailers
– No written information: negotiation > transaction – individual offers– Buyers don’t make any prior offer, they ask for the price or declare a
quantity they want (Kirman)– One should not interfere with others’ transactions– Also: explicit information exchange– Diverse services: priority on some goods, advises to anticipate on future
prices/ lacks– Credit
• Wholesale sellers– The wholesale sellers have networks of sellers– Each have an “ecological niche” known by all – have a network of suppliers
• Retailers – Two main types of behaviour (schematic): regular / faithful buyers and
opportunistic ones– (Change of behaviours is apparently linked to age)
« Network vs market » / opportunism vs fidelity
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Aspects emphasised in this workImportance of the transactions for supply renewal Reasons for fidelity:
interesting to get info and good prices “character” ethical speech norms of behaviours, expectations
Some literature, and especially in simulation but with different emphasis (Kirman et Vriend, 2000, 2001), (Brousseau, Codron, 1998) (Galtier et al., 2002) (Rouchier et al, 2001)
>> Economic function to these cohabitation of heterogeneous behaviours?
Assumption: garbage reduction and possibility to get needed goods
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Real life observations: wholesale sellersNumerous aspects to a relation for price setting
– Regularity– Loyalty– Quantity– Feelings – Quality / age of the good
Variation of 5 to 50% off the « basic price »Expectations after a good deal offer: carry on buyingSigns of good relation and trust
– Credit– Information about prices for the next day– Keeps some goods that are ordered by telephone
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Real life observations: RetailersBasic constraints (variable):
– List of goods to acquire (season and past sells)
– Limited time (employees)
– Type / quality of goods (situation of the shop)
Knowledge that determine choices– « les mercuriales » and producers
– Ask wholesale sellers while negotiating
– Ask other retailers « at the bar » or friendly wholesale sellers
Search habits– First go to producers’ area
– « Favourite » wholesale seller
– Extensive search for some goods
– Stick to the list or adapt to offer (time and space)
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Model: wholesale sellers10 wholesale sellers - 10 productsSupply:
Each one has a list of goods and pricesEach one has a « normal supply »: buy at the beginning of the day.Probability to get goods: parameter of the simulations Variation of price among sellers and in time: 20%If unable to supply: increase normal supply ; if throw away: decrease normal supply
Goods agingPrice reduction of 20% for 3 days old product, 40% for 4 days oldThrown away after 4 days
Transaction: Gives cheapest products to regular / or give younger products to regular: parameter 10 % reduction for more than 3 products, and 10 % for regularRegular client bought more than 10 products in the last 10 market days
Normal supply product 1 … Normal supply product 10
(date, price) (date, price)… (date, price)
Average price product 1 Average price product 10
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Model: retailers100 retailers – ratio of Loyal / Opportunistic as a parameter of the simulationsList of goods to acquire, come everydayTime is structured in three time-stepsTime is used for: transacting or information search
Fixed attitude => a strategy to use time Behaviour <= attitude + gathered information
Information = average price for all products for 5 wholesale sellerRequest = list of goods, one unit per type of goodDifferent attitude induces:
Time use Choice process
Loyal buy – info – buy First regular, then as few demands as possible
Opportunistic info – buy – buy Cheapest possible basket (up to 5 demands)
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Simulations - Observation• Simulations defined by:
– Repartition of retailers attitude: 50-50 / 100-0 / 0-100– “Answer simulation”
• The wholesale seller gives cheaper price to regular• The wholesale seller gives freshest products to regular
– Already led: “Price” and “Supply” simulations• Supply probabilities = [40;60], [70-90], [80-100]• Price variation: 5- 20 or 40 %
• Observation (global – average)• Number of thrown units• Quantity of missing products • Evolution of normal supply – average and msd• Average age for bought products• Average price depending on the type of retailer
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quan t it y pur chased
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market days
loyal opportunistic
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simulations 20 / 60-80
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24
68
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1214
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0 20 40 60 80 100 120
number of loyal agents
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missing products for retailers
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0 50 100 150number of loyal
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average lack msd lack
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normal supply simul 20/ 60-80
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0 20 40 60 80 100 120
number of loyal
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average prices with best price for loyal
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market days
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prices for best products for loyal
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market daysloyal opportunistic
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average age for products w ith best prices for loyal
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market daysloyal opportunistic
average age of product purchased w ith best products for loyal
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market daysloyal opportunistic
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Results• Supply and waste: retailers get more goods and wholesale
sellers throw less when there are more loyal
• This increase in waste is mainly due to wholesale agents overstocking to attempt to satisfy sales that are subsequently not made – since in previous days selfish agents ask several wholesale agents to supplier various products. Importance of loyal in the regulation of market
• If wholesale sellers give “best products” to regular, loyal pay more and get fresher products and otherwise pay equivalent
• Better to use the “freshest products” logic because it is closer to other researchers’ results
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And then….• With this model
– Test a higher number of ratio loyal / opportunistic– Test more price variability
• New model– Describe new procedure of supply buying: have a global quantity instead
and get it by queuing model – Find a better way to describe the wholesale sellers’ answer– Have a better description of reaction to prices by adding memory for
opportunists who don’t need to gather all information before choosing– Have faithful agents evaluate their regular seller and change their habits
• New interviews to increase knowledge about– Add price evolution of prices along the day (S. Moulet – A. Kirman)– Model where wholesale sellers have more adaptive price policy with agents
(not just regular vs unknown) – hard to select the “most relevant” indicators for agents
– Importance of the Global price knowledge (O. Chappuis)