组织的经济学与管理学(英文)ch12-Limited-cognition-and-organisat课件.ppt（纯ppt,可能不含音视频素材）

1、Chapter 12Limited cognition and organisationGeorge HendrikseEconomics and Management of Organisations:Co-ordination,Motivation and Strategy Fields Behavioural accounting behavioural finance Economic psychology/consumer behaviour Organisational behaviour Strategic decision makingFigure VI.1:Positioni

2、ng of bounded rationality approaches Behaviou ral hypothesis Opportunistic Self interested Idealistic Complete Rationality Limited X Procedural X X X Firm from an evolutionary perspectiveDeel V:TreeMaking mistakesForgettingLimited reasoning capabilitiesDegree of rationalityRatio of the cognitive cap

3、acities of the decision maker and the complexity of the problem.Types of rationality Complete:ratio is 1 Bounded:ratio between 0 and 1 Procedural:ratio is(almost)0If the degree of rationality is smaller than 1,then there will be a bias in behaviour(compared to the complete rationality case).Increase

4、 ratio by increasing cognitive capacities,e.g.education decreasing the complexity of the problem,e.g.by splitting up the problem,using computersTwo types of bounded rationality1.Deductive2.InductivePartitioningDeductive bounded rationalityHow to optimally allocate a limited number of cognitive units

5、 in a complex problem?How to make(deductive)bounded rationality operational?Number of partitions of the set of possible events/states.Cognitive capacities of a personThe cognitive capacities of a person are the number of partitions a person is able to make in response to a particular problem.Complex

6、ity of a problemThe complexity of a problem is the number of partitions that is needed to distinguish all aspects/states/events of a problem.Example:Colour recognition problemPossible states:R:RedG:GreenW:WhiteD:DarkComplexity of the colour recognition problem R|G|W|DConclusion:3 partitions implies

7、complexity 3.Figure 12.1:Colour recognition capacities of different decision makersDecision maker Partitioning of set of states Degree of rationality Human (R),(G),(W),(D)3/3=1 Pussycat (R,G),(W),(D)2/3 Mole (R,G,W),(D)1/3 Spoon (R,G,W,D)0 Example:Organisational structure Functional DivisionalFuncti

8、onal structureProduct 1 productionProduct 2 productionProduct 1salesProduct 2salesProductionSalesLocal managerOpportunities for improvement?Division managerInformationCEODivisional structureProduct 1 productionProduct 1 salesProduct 2productionProduct 2salesProduct 1Product 2Local managerOpportuniti

9、es for improvement?Division managerIncreased profit?opportunities?CEOInformation compression from employees to the boss is necessary due to limited cognitive capacities of the boss.However,information compression is not neutral.Every structure of information channels leads inevitably to a certain bi

10、as in the provision of information.Example Organisation consists of two divisions Each division consists of two managers CEO only uses advice of each division Divisions base their advice on information of the local managersInformation on local managers Production manager 1(2)indicates always(never)t

11、hat there are possibilities for cost reductions Marketing manager 1(2)is always optimistic(pessimistic)regarding additional sales in the futureInformation aggregation A division reports positively only when both local managers are positive A division reports doubtful when the reports of the local ma

12、nagers are mixed A division reports negatively only when both local managers are negativeInferences in a functional structureProduct 1 productionProduct 2 productionProduct 1salesProduct 2salesYesNoYesNoProductionAmbiguousAmbiguousSalesLocal managerOpportunities for improvement?Division managerInfor

13、mationCEOCEOThe CEO in a functional structure decides to do nothing.Inferences in a divisional structureProduct 1 productionProduct 1 salesProduct 2productionProduct 2salesYesYesNoNoProduct 1Product 2Local managerOpportunities for improvement?Division managerIncreased profit?opportunities?CEOYesNoCE

14、OThe CEO in a divisional structure decides to allocate as many means as possible to division 1 in the future.ConclusionThe structure of the learning environment seems to be at least as important as the meaning of things.Different biases A functional structure creates an aggregation bias towards the

15、generation of product-related data.A divisional structure means an aggregation bias regarding the generation of functionally related data.If the degree of rationality is smaller than 1,then each partitioning entails a certain bias.Complexity and self-organisationInductive bounded rationalityDecision

16、s are based on limited,local information.Missing information is dealt with by making analogies using heuristic rules of thumb constructing plausible,simpler representations of the problemIngredients of theory learning based on feedback adjust rules of thumb based on natural selectionHow do you make(

17、inductive)bounded rationality operational?Specify simple behavioural rules.A transition rule specifies the next state of a cell by its current state and the local environment.Research questionWhich simple rules drive behaviour?How to proceed?Trial and error by computer simulations.How do you model a

18、 local environment?Figure 12.5:(a)von Neuman environment,(b)Moore environment (a)(b)Example:SegregationGhettosSuppose0:blueX:greenFigure 12.6:Starting position0 X X X X 0 0 0 0 X X 0 0 0 X 0 0 0 X X X X 0 X X 0 0 X X X 0 X X X X X X 0 X X X 0 0 0 0 0 X X X X X X 0 0 X 0 X 0 0 X 0 0 X X X 0 0 X 0 0 0

19、 X X X 0 X 0 X X X 0 0 0 X 0 X 0 X X 0 X 0 0 X 0 X 0 0 0 0 X X 0 X X 0 0 0 0 0 X X 0 X X X 0 X 0 X 0 0 X 0 X 0 0 0 0 0 X 0 X 0 0 0 X X Transition rules Do not move when at least half of the persons in the Moore-environment is of the same colur.Move to the most close location where at least half of t

20、he persons in the Moore-environment is of the same colour when less than half of the persons in the current Moore-environment is of the same colour.Figure 12.7:Stationary situation X X X X X X X X X 0 0 X X X X X X X X X X X X X 0 0 X X X X X X X X X X X X X 0 0 X X X X X X X X X X 0 0 0 0 0 0 X X X

21、 X X X X X 0 0 0 0 0 X X X 0 0 X X X 0 0 0 0 0 0 0 0 0 0 0 X X 0 0 0 0 0 0 0 0 X 0 0 0 X 0 0 0 0 0 0 X X 0 0 0 0 0 0 0 0 X X 0 0 0 0 0 0 0 0 0 0 0 0 0 0 X X Example:FinanceInductive,bounded rational decision makersTransition rule/buy-sale of computer programPut more(less)in risky stocks when returns

22、 were positive(negative)in the recent past.Underlying valuePriceValuetImplicationNot an efficient marketArchitecture choiceVacancyAnnual report accountantLaw in parliamentIssue in United NationsScientific journalPossibilities of appealInnovation project in firmMarket systemArchitectureRule for aggre

23、gating local decisions into an organisation decision.Figure 12.12:Firm as a collection of bureaus Collection of bureaus Two architectures Hierarchy PolyarchyHierarchyOrganisation only accepts a project when nobody rejects it.Figure 12.14:Hierarchy Project Office 1 Office 2 Accepted no 1-p no 1-p Rej

24、ected Rejected p yes yes p Decision-making authority is concentrated Local/Individual decision makers have veto power Acceptance requires unanimityPropertiesPolyarchyOrganisation only rejects a project when everybody rejects it.Decision-making authority is not concentrated Every decision maker has t

25、he power to accept a projectPropertiesFigure 12.15:Polyarchy Project Office 1 Office 2 Accept no 1-p no 1-p Reject p yes yes p Accept ConclusionA polyarchy is good at accepting projects,whereas hierarchies are good at rejecting projects.Which organisational choice minimises errors of judgement?There

26、 are two types of mistakes:1.Type I errors2.Type II errorsFigure 12.13:type-I versus type-II errors accept reject accept reject good project bad project desirable decision type-I error type-II error desirable decision 1.Choose a polyarchy when type-I errors are relatively expensive.2.A hierarchy is

27、desirable when type-II errors are relatively expensive.Results Evolutionary approachesEvolutionary psychologyClaims regarding the cognitive capacities of people have to be based in evolutionary biology.Result 1:Global rationalityIt is unlikely that global rationality emerges out of an evolutionary p

28、rocess.Reason 1:Adaptive or optimal behaviour depends to a large extent on the specific situation.Reason 2:Adding more dimensions prevents that even limited general systems will function well.This is due to combinatorial explosion.This results in:modularity hierarchy parallellisationReason 3:General

29、 systems do not perform well in specific situations because crucial details are not taken into account.Result 2:form follows functionThe properties of an evolved system/mechanism/form reflect the structure of the problem that has to be dealt with.The nature of the problem directs therefore the kind of solution that is formulated.Example 1:Structure follows strategy(Chandler,1962)Natural selection results in mechanisms geared towards using information in the form it is presented.