Forecasting Qualitative Methods

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Forecasting Qualitative Methods

Category : Articles

Overview Forecasting Qualitative Methods
Assoc. Prof. Christian Tanushev, Ph.D. 12 October 2011
??? Quantitative forecasting methods ??“ review ??? Typology of forecasts ??? Qualitative forecasting methods
??“ ??“ ??“ ??“ ??“ ??“ ??“ ??“ Brainstorming Prediction markets Estimate ??“ talk ??“ estimate (Group communication) Delphi Structured analogy Game theory Role playing Conjoint analysis

??? Forecasting and decision making process
??“ Club of Rome??™s Forecast. ???The Limits to Growth.??? 1972 ??“ National Intelligence Council. ???Global Trends 2025. A Transformed World.???

??? Summary
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Forecasting Definitions
??? Forecasting is the process of estimation in unknown situations ??? A forecast is a prediction based on knowledge of past behavior ??? Requirements for a forecast
??“ Validity ??“ Variability ??“ Valuation of probability

Good forecasting is based on science, art, and luck
??? Forecasting is both a science and an art
??“ Science
??? forecasting equations ??? statistics/regression analysis

??“ Art
??? good at guessing (judgmental forecasting) ??? good at picking the correct type of forecasting equation

??? We forecast phenomena and processes which we are unable to control
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Forecasting Basic Steps
???The forecast???

Time Series Models
??? Extrapolation of historical data into the future ??? Plotted on graph and analysed for four basic components of variation
??“ ??“ ??“ ??“ ??“ ??“ ??“ ??“ ??“ ??“
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Step 6 Monitor the forecast Step 5 Prepare the forecast Step 4 Gather and analyze data Step 3 Select a forecasting technique Step 2 Establish a time horizon Step 1 Determine purpose of forecast

Trend – long-term movement in data Seasonality – short-term regular variations in data Cycle ??“ wavelike variations of more than one year??™s duration Irregular variations – caused by unusual circumstances Random variations – caused by chance Simple weighted average, median, mode Simple moving average, double moving average Exponential smoothing Linear regression Multiplicative model
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??? Examples

??? Used where good historical data is available

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Elements of any Good Forecast
Timely

Forecast Requirements
??? Clear definition of final criteria for evaluation of expected results ??? Precise timing (horizon) to achieve the expected affects ??? Evaluation of the cost ??? If the forecast is conditional that circumstances should be realistic, achievable ??? At least two possible opportunities to be considered: to achieve the goal (fully or to some extent) or to fail ??? Evaluation of a probability of forecast occurrence ??? The author and methodology of a forecast should 8 be clearly stated

Reliable

Accurate

Meaningful

Written

Easy to use
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Decision-making without Preliminary Forecasting
??? Routine situations ??? Processes develop in a stable environment ??? The development of a forecast is more expensive than the expected outcome ??? If the time needed to develop the forecast is longer than the forecast horizon ??? Decision making on questions of secondary importance ??? A few required resources and low risk level
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Types of Forecasts by Time Horizon
??? Long-term ??“ over 5 to 10 years. Demographic development, technical infrastructure ??? Mid-term ??“ 2-5 years. Investment projects, development of a new product: MP3 player, disk man, walkman, cassette tape recorder, gramophone ??? Short-term ??“ less than a year. Demand of a product, financing a project
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Types of Forecasts By Subject
??? Demographic ??“ birth rate, mortality, growth in population; educational structure, distribution in rural and city areas. ??? Economic ??“ GDP growth, import, export, consumption, investments, inflation rate ??? Scientific and Technical ??“ inventions, patents, new technologies ??? Ecological ??“ soil fertility, air pollution, water level ??? Political ??“ exit polls, adoption of a new legislation ??? Others ??“ in health care sector, education
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Types of Forecasts
??? By final results presentation
??“ Single figure ??“ A range from??¦ up to??¦. Of crucial importance are the width of the interval, a character of forecasted phenomenon, the goal of the forecast

??? By degree of conditionality
??“ Unconditional ??“ It doesn??™t depend on the occurrence of other events ??“ Conditional ??“ a previous event should happen
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Types of Forecast
??? By scope
??“ Global ??“ they cover the whole world ??“ International ??“ for geographic regions, economic alliances, group of countries ??“ National ??“ country coverage ??“ Regional ??“ for a province, a district, a city

Types of Forecasts by Functional areas
Accounting Finance Human Resources Marketing MIS Operations Product/service design Cost/profit estimates Cash flow and funding Hiring/recruiting/training Pricing, promotion, strategy Demand for IT/IS systems, services Schedules, MRP, workloads New products and services
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??? By types of organizations
??“ Real Sector (Main Street) ??“ Financial Institutions (Wall Street) ??“ banks, insurance companies, mutual funds ??“ Non-profit Organizations ??“ foundations, charity funds ??“ Others

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Methodology Tree for Forecasting

A Demand Forecast

The Methodology Tree for Forecasting classifies all possible types of forecasting methods into categories and shows how they relate to one another. Dotted lines represent possible relationships. Knowledge
Judgmental Others Unstructured Structured Self Role No role Extrapolation models Quantitative analogies Neural nets Linear Classification
Causal models Segmentation

source

Statistical Univariate Multivariate DataTheorybased based Data mining

Region

Product Line

Channel

Features

Product

Customer

Unaided judgment

Role playing (Simulated interaction)

Intentions/ expectations

Revenue Planning Revenue Scenarios Allocation Criteria Commissions & Quotas

Estimating Market Share Pricing Targets Programs & Promotions Margins & Mixes Message to Analysts

Scheduling Factory Volumes Materials Planning Balancing Factory Capacity Assessing Direct Cost & Mixes Analyzing Absorption implications

Conjoint analysis

Rule-based forecasting

Expert Forecasting

Structured analogies

Game theory

Decomposition

Judgmental boot_strapping

Expert systems

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Methodology Tree for Forecasting forecastingprinciples.com JSA-KCG November 2007

Judgmental methods Large changes expected

Sufficient objective data No Yes

Quantitative methods Good knowledge of relationships

Forecasting Methods
Yes Large changes likely Yes No

No Policy analysis No Yes Highly repetitive with learning Yes No Unaided judgment

Yes

No

Conflict among a few decision makers No Yes Policy analysis Yes No No Similar cases exist Yes

Cross-section

Type of data Time series

Policy analysis No Yes

Type of knowledge Domain Self Conjoint analysis

Good domain knowledge Yes No

??? Source of knowledge: When reliable objective data are available they should be used. ??? But one can evaluate the data by subjective methods also. ??? Expert Forecasting
??“ It refers to forecasts obtained in a non-structured or structured way from two or more experts. ??“ The most appropriate method depends on the conditions (e.g., time constraints, dispersal of knowledge, access to experts, expert motivation, need for confidentiality). ??“ The nominal group technique (NGT) can be conducted as a simple one-round survey for situations in which experts possess similar information. All the distributors from different regions. ??“ If experts are expected to possess different information, discussion among participants in an “estimate-talk-estimate” is appropriate. Government-trade unions-employers 18

Expert Judgmental Forecasting bootstrapping/ (Delphi) Decomposition

expectations Game theory

Intentions/ Role playing Structured Quantitative analogies analogies

Expert Rule-based systems forecasting

Extrapolation/ Causal Neural nets/ models/ Data mining Segmentation

No Single method Use unadjusted forecast No

Several methods provide useful forecasts Omitted information

Yes Combine forecasts Use adjusted forecast

Yes

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Pros and Cons of Expert Forecasting
??? No formal procedures are followed ??? Provide accurate predictions in stable environment with small increments ??? Experts use different sources of information and consult each other ??? A prognosis is obtained easily and it is inexpensive ??? A group pressure could be a concern. An idea provided by an authority could prevail ??? Lack of formal procedures requires discipline during the discussion
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Brainstorming
??? Facilitate spontaneous thinking to generate possible ideas while deferring judgment. Enable experts to view a concept from a variety of perspectives and develop creative thinking ??? Define your problem (the word “problem” is not necessarily negative – your problem could be “We need a new product” or “How can we effectively use our departmental budget surplus for this year??? ??? Specify a time limit ??“ 25??™ ??? Everyone must provide solutions to the problem while one person writes them out or enters them into BrainStormer. There must be ABSOLUTELY NO CRITICIZING OF IDEAS ??? Time is up. Select the five ideas which you like best. Make sure everyone involved in the brainstorming session is in agreement
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Brainstorming ??“ 2
??? Determine five criteria for judging which ideas best solve your problem. Criteria should start with the word “should”, for example, “it should be cost effective”, “it should be legal”, “it should be possible to finish before a single date???, etc. ??? Give each idea a score of 0 to 5 points depending on how well it meets each criterion. Once all of the ideas have been scored for each criterion, add up the scores. ??? The idea with the highest score will best solve your problem. But you should keep a record of all of your best ideas and their scores in case your best idea turns out not to be workable.
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Pros and Cons of Brainstorming
??? Reflects the spontaneous reactions of the participants ??? Helps thinking about the problem from different points of view (???Out of the box???) ??? People who are not expensive and qualified experts could also participate and contribute ??? Time-effective ??“ a group quickly agree on final solution ??? Inexpensive ??“ if people from organization are involved ??? Might support the unrealistic ideas, which will never be realised ??? Requires discipline about criticizing the ideas of other participants ??? An idea provided by an authority could prevail
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FFOE Technique
??“ Fluency ??“ is producing many ideas. University: teaching, exams, career ??“ Flexibility ??“ is producing ideas that show a variety of possibilities or different areas of thought. Textbook: computer program, CD, Internet sites ??“ Originality ??“ is producing unique or unusual ideas. Textbook: studying, lift up the projector to get a better image or insert below the table for stability ??“ Elaboration ??“ is producing ideas that are developed fully. Textbook: hard backed, paperbacked, electronic format
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SCAMPER Technique
??“ Substitute ??“ is replacing something with something else. Highlighter: pencil, engraver, brush, pen, crayon, chalk ??“ Combine ??“ is blending or adding together. Highlighter ??“ eraser. Laser beam + gramophone disk = CD ??“ Adapt ??“ is making adjustments to create something different. Highlighter ??“ water-proof, invisible ink. Walkman ??“ Discman ??“ ????3 player ??“ Minimize/Magnify ??“ is reducing or increasing the shape or form. Highlighter ??“ including a couple of colors, increase the size for children. Nanotechnologies ??“ Put To Other Uses ??“ is modifying or creating new ways to use something. Glue a label to a marker and use it as a stick near a plant. Cell phone display as a screen for GPS navigation ??“ Eliminate/Elaborate ??“ is taking away, subtracting from, or building upon Insert a string through the highlighter and use it as a bird??™s swing. ??“ Reverse/Rearrange ??“ is swapping or interchanging something. Engrave the cap, highlight it and use it as a stamp. 24

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Barometer
How can you use a barometer to help you determine the height of a building
??? Drop the barometer from the top of a building and time its descent. Calculate the height based on the acceleration of gravity ??? Walk the barometer up the side of the building, end-to-end. Measure the length of the barometer and calculate the buildings height. ??? On a sunny day, place the barometer vertically on the ground. Compare the ratio of the barometers height to the length of its shadow and the ratio of the buildings height to the length of its shadow ??? Offer to give the architect a barometer to tell 25 you how tall the building is.

Salvador Dali Hallucinogenic Toreador 1968-1970
How much visual information do we need to recognize an image
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Prediction Markets Salvador Dali Face 1972
??? ???Information markets??? are markets where participants trade contracts whose payoffs are tied to a future event, thereby yielding prices that can be interpreted as market aggregated forecasts. ??? People bet on possible outcome. If a prediction market is efficient, then the prices of these contracts perfectly aggregate dispersed information about the probability of each outcome. ??? Prediction markets have been used to forecast
??“ ??“ ??“ ??“ ??“ ??“ ??“ ??“ ??“
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elections movie revenues project completion economic indicators corporate sales research and development outcomes success of new products regulatory outcomes the Pentagon attempted to use markets designed to predict geopolitical risks 28

Theoretical Background
??? The claim that prediction markets can efficiently aggregate information is based on the Efficient Market Hypothesis. ??? Market prices reflect immediately any new information ??? Markets ensure single price and no arbitrage possibilities ??? In most cases, the time series of prices in these markets appears to follow a random walk, and simple betting strategies based on publicly available information appear to yield no profit opportunities. That is, these markets appear to meet the standard definition of weak-form efficiency ??? Pediction markets typically provide quite accurate forecasts and have typically outperformed alternative prediction tools
??“ provide an incentive for information discovery ??“ they provide incentives for truthful revelation of beliefs

Pros and Cons of Prediction Markets
??? The market eliminates unrealistic bets (evaluations) ??? The market provides incentives for participants to seek for information and heighten their profits ??? The market requires liquidity ??? Risk is reflected in prices ??? Some people try to manipulate the market. Short selling of contracts on Bush reelection in 2004 reduce his chance to zero for a short time. ???Bear raid??? 30

??? The Hollywood Stock Exchange has generated forecasts of box office success and of Oscar winners. In 2006 32 of 39 Oscar winners and 8 of 9 main categories were correctly assumed
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Group Communication Techniques
Conference Telephone Call Effective Group Size Occurrence of Interaction by Individual Length of Interaction Number of Interactions Normal Mode Range Small Committee Meeting Small to Medium Formal Conference or Seminar Small to Large Conventional Real-Time Delphi Delphi Small to Large Random Small to Large Random

Group Communication Techniques
Conference Telephone Call Principal Costs Communications
? ?

Formal Committee Conventional Conference or Meeting Delphi Seminar Travel Individuals Time
? ?

Real-Time Delphi
?

Coincident with Coincident with Coincident with group group group Short Medium to Long Long

?

Short to Medium

Short Time Other Characteristics
?

Travel Individuals Time Fees

? ? ?

Monitor Time Clerical Secretarial Forced delays

?

Communications Computer Usage

Multiple, as Multiple, Single Multiple, Multiple, as required by group necessary time necessary time required by delays between delays between individual Equality to Equality to Presentation Equality to monitor Equality to chairman control chairman (directed) control (structured) monitor control or (flexible) control (flexible) group control and no monitor (structured)
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Time-urgent Forced delays considerations Equal flow of information to and from all Can maximize psychological effects
?

Time-urgent considerations

?

Efficient flow of information from few to many

?

?

?

Equal flow of information to and from all Can minimize psychological effects Can minimize time demanded of respondents or conferees
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Guidelines for Problem-Solving Meetings
??? Be problem-centered. Keep any discussion problem-centered and avoid looking for excuses or seeking to blame others for a problem. ??? ??? Explore alternatives. Do not accept the first answer you hear as the answer. Ask, “What else should be considered” “What else might we do” ??? ??? Record suggestions. Keep track of all suggestions for solving a problem or making sense of an issue so that each may be explored fully. ??? ??? Explore. Explore a number of suggestions for addressing an issue, then probing and evaluative questions can be asked. These might include: “How would that work out” “Do I understand the issue or do I need to search out more information” “Am I mistaken in my assumptions about the issue” “What are the advantages or disadvantages of each proposal” “Is there a way to combine suggestions to generate an even better solution” ??? ??? Protect people. Protect individuals from personal attacks and criticism, especially if they present minority or divergent viewpoints. Avoid saying things like, “Thats a really stupid idea.” ??? ??? Understand and resolve differences. Understand differences of opinions in 33 the group and attempt to resolve them.

???Delphi??? Technique
??? Delphi is a forecasting tool that is widely used for aiding decision making. It ?????¦ involves anonymous forecasts made on two or more rounds by a group of independent heterogeneous experts who receive feedback between rounds??? ??? Named after the ancient Greek Oracle at Delphi, the technique was developed by the Rand Corporation in the early 1950s to overcome a number of problematic issues that arise during group decision making
??“ ??“ ??“ ??“ ??“ ??“ ??“ ??“ Long-term trends in science and technology development Scientific breakthroughs Population control Space progress Weapon systems Vehicle-highway systems Intelligent internet Broadband connections

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Stages in application
??? Delphi involves a number of rounds of data collection. In the classical Delphi procedure the first round is unstructured, to allow individual experts relative freedom to identify and elaborate the pertinent issues from their point of view. ??? These issues are then consolidated by the researcher(s) into a structured questionnaire. This questionnaire is subsequently used to elicit the opinions and judgments of the panel of experts in a quantitative form. ??? The responses are analyzed and statistically summarized and presented back to the panelists for further consideration. ??? Respondents are then given the opportunity to alter prior estimates on the basis of feedback ??? The number of rounds varies from two to ten, but seldom go beyond one or two iterations as iteration may lead to boredom
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The Key Characteristics of Delphi
??? Anonymity is meant to exclude group interaction, which can cause: group conflict and individual dominance ??? Iteration aims to produce as many high-quality responses and opinions as possible on a given issue(s) from a panel of experts to enhance decisionmaking ??? Controlled feedback and aggregation of group responses. The form of the feedback varies from medians and inter-quartile ranges for measurement items included in a questionnaire to detailed scenarios ??? The objective is to obtain the most reliable consensus of opinion via a series of intensive questionnaires, interspersed with controlled opinion feedback
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Benefits of Delphi
??? Can be used when there is little or no historical data or when dilemmas are ethically or socially sensitive ??? Captures a wide range of interrelated variables and multidimensional features common to most complex problems ??? Documents facts and opinions ??? Avoids the problems of face to face interaction, such as conflict and individual dominance ??? Panelists contribute anonymously and therefore can revise their views without publicly admitting to it ??? Can consolidate a global opinion even when experts are geographically dispersed ??? Inexpensive to organize ??? Recognises individual contributions which encourages a personal stake for the panellist for the success of the project ??? When panel members are also strategic decision makers, Delphi moves from being a group forecasting tool to facilitating group decision making
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Flaws of Delphi
??? Process Issues
??“ Which methodological adaptations are appropriate for which situation ??“ Difficult to estimate the validity and reliability ??“ Averaging process may weaken full potential of group judgement ??“ Many iterations can lead to boredom ??“ Anonymity can result in compromise rather then consensus ??“ Anonymity provides insufficient interaction

??? Panellist Issues
??“ Difficult to assess expertise and select experts ??“ Non-probability samples, snowball sampling / convenience sampling are not suitable if making generalisation
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Five Steps of Structured Analogies
??? An administrator describes the target situation
??“ An accurate, comprehensive, and brief description ??“ Should seek advice either from unbiased experts or from experts with opposing biases ??“ When feasible, include a list of possible outcomes for the target situation to make coding easier

Graph Model of Analogy
Time Foreign system
?‚ ?? ?‘ ?‚ D

Past

Present

Future

??? Selects experts
??“ Familiar with the target situation ??“ Usually at least five persons

??? The experts each identify and describe analogies. Ask the experts to describe as many analogies as they can without considering the extent of the similarity to the target situation ??? Rate similarity.
??“ List similarities and differences between their analogies and the target situation ??“ Rate the similarity of each analogy to the target
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Forecasted System Year
-1

?? ?‘

D

??? The outcome implied by the top-rated analogy is used as a forecast

0

1
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Judgmental bootstrapping
??? Alows us to derive a model from knowledge of experts??™ forecasts and the factors they used to make their forecasts using regression analysis ??? Useful when expert judgments have validity but data are scarce and where key factors do not change in the historical data (such as where trying to estimate a price elasticity using time series data with little variation in price). ??? When averaged, forecasts made by experts or by forecasting models about, say, macroeconomic indicators are consistently more accurate than the typical estimate, and sometimes even the best estimate. This phenomenon is known as the wisdom of crowds. ??? This can be illustrated using the concept of bracketing. If two estimates are on the same side of the truth (i.e., do not ???bracket??? the true value), averaging them will be as accurate, on average, as randomly choosing one estimate. But if two estimates bracket the true value (i.e., one overestimates it and the other underestimates it), averaging the two will yield a smaller absolute error than randomly choosing one of the estimates 41

Decomposition
??? The problem is addressed in parts. ??? The parts may either be multiplicative
??“ to forecast a brands sales, one could estimate total market sales and market share

??? or additive
??“ estimates could be made for each type of item when forecasting new product sales for a division
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Game Theory
??? An attempt to explain, model, and predict behavior in the social world. ??? A game is a multi-person decision situation, defined by its players, its “rules” (the order of players decisions, their feasible decisions at each point, and the information they have when making them); how players decisions determine the outcome; and players preferences over outcomes. ??? Game theorists seek to identify the rules of the situation including the utility to each party of possible outcomes. ??? Some scientists argue that while game theory can provide ex post analysis that appears insightful, there is no evidence that the method can provide useful forecasts. 43

Pareto Optimum
??? A position is said to be a Pareto optimum if it would be impossible to improve the well-being of one individual without harming at least one other individual. ??? Pareto Optimality is defined as the efficiency of a market which is unable to produce more from the same level of inputs without reducing the output of another product ??? A hundred dollar bill at the seashore
??“ The waves sweep it away ??“ non optimal solution ??“ The person who finds them take it ??“ everybody is better of ??“ Two persons find the bill we have at least three solutions. The first one takes the bill. They divide the money (even not at equal parts). If they split just part of the money ??“ that??™s not a Pareto optimum.
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??? We have two companies

An Information Technology Example

Nash Equilibrium
??? Both players can be better off, on net, if an advanced system is installed ??? But the worst that can happen is for one player to commit to an advance system while the other player stays with the proven one. In that case there is no deal, and no payoffs for anyone ??? The problem is that the supplier and the user must have a compatible standard, in order to work together ??? We have a Nash Equilibrium if each participant chooses the best strategy, given the strategy chosen by the other participant. No one of the participants have an incentive to change his behavior 46 ??? We observe two points

??“ The first one is a consumer willing to implement a new technology and is able to choose between a technically advanced or a more proven system with less functionality ??“ The second one is a supplier considering which system it shall produce (digital or analogous)

Consumer Advanced technology Supplier Advanced technology Proved Proved

20; 20 0; 0

0; 0 5; 5
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Cooperative Game
??? We have assumed that the payoffs are known and certain. In the real world, every strategic decision is risky — and a decision for the advanced system is likely to be riskier than a decision for the proven system. Thus, we would have to take into account the players subjective attitudes toward risk, their risk aversion, to make the example fully realistic. ??? The example assumes that payoffs are measured in money. We are leaving out of the picture all other subjective rewards and penalties that cannot be measured in money ??? Real choices of information systems are likely to involve more than two players, at least in the long run – the user may choose among several suppliers, and suppliers may have many customers ??? The user and the supplier dont have to just sit back and wait to see what the other person does – they can sit down and talk it out, and commit themselves to a contract. In fact, they have to do so, because the amount of payment from the user to the supplier – a strategic decision we have ignored – also has to be agreed upon
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Zero-Sum Games
??? We will think of two companies that sell mineral water. ??? Each company has a fixed cost of $5000 per period, regardless whether they sell anything or not. ??? We will call the companies Devin and Bankia ??? The two companies are competing for the same market and each firm must choose a high price ($2 per bottle) or a low price ($1 per bottle). ??? Here are the rules of the game:
??“ At a price of $2, 5000 bottles can be sold for a total revenue of $10000. ??“ At a price of $1, 10000 bottles can be sold for a total revenue of $10000. ??“ If both companies charge the same price, they split the sales evenly between them. ??“ If one company charges a higher price, the company with the lower price sells the whole amount and the company with the higher price sells nothing. 48 ??“ Payoffs are profits — revenue minus the $5000 fixed cost.

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Cournot Price Competition
??? The maximin criterion — that is, each player chooses the strategy that maximizes her minimum payoff. ??? In this game,Devin??™s minimum payoff at a price of $1 is zero, and at a price of $2 it is -5000, so the $1 price maximizes the minimum payoff. ??? Here is the reasoning behind the maximin solution: Devin knows that whatever she loses, Perrier gains; so whatever strategy she chooses, Perrier will choose the strategy that gives the minimum payoff for that row.

Role playing/Simulated interaction
??? In role playing, people are expected to think in ways consistent with the role and situation described to them. ??? If this involves interacting with people with different roles for the purpose of predicting the behavior of actual protagonists, we call it simulated interaction. ??? That is, people act out prospective interactions in a realistic manner. ??? The role-players decisions are used as forecasts of the actual decision
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Bankia Price $1 Price $1 Devin Price $2 Price $2

0; 0 – 5000; 5000

5000; – 5000 0; 0
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Intentions/expectations
??? Survey people about their intentions or expectations regarding their future behaviour or those of their organization. Direct observations, questionnaires,interviews ??? The principles relating to using intentions to forecast behavior:
??“ ??“ ??“ ??“ Intentions need to be adjusted to remove biases Respondents should be segmented prior to adjusting intentions Intentions can be used to develop best- and worst-case forecasts More reliance should be placed on predictions from intentions for behaviors in which respondents have previously participated ??“ Measuring intentions can change behavior ??“ Respondents who recall the time of their last purchase inaccurately may make biased predictions of their future purchases

Conjoint analysis
??? Elicit preferences from consumers (or other actors) for various offerings (e.g. for alternative computer designs or for different political platforms) by using combinations of features (e.g. power and weight for a laptop computer.) ??? Regression-like analyses are then used to predict the most desirable design. ??? For example a computer may be described in terms of attributes such as processor type, hard disk size and amount of memory. Each of these attributes is broken down into levels – for instance levels of the attribute for memory size might be 1GB, 2GB, 3GB and 4GB
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??? Analyze the survey data to derive forecasts
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Applying a Causal Model
??? A famous example of a large causal model was fabricated by the socalled Club of Rome in 1972. This model, published in the book The Limits to Growth, consists of dozens of variables, including the world population, birth rate, industrial and agricultural production, the non renewable resources, and pollution. ??? In the model, the levels, or physical quantities which can be measured directly, were indicated with rectangles, rates that influence those levels with valves, and auxiliary variables that influence the rate equations with circles. Time delays were indicated by sections within rectangles. Real flows of people, goods, money, etc. were shown by solid arrows and causal relationships with broken arrows. Clouds represent sources or “sinks” (exits of material) that are not important to the model behaviour. ??? The Club of Rome started building their “World Model” by first constructing five sub-models. These concentrated on the five “basic quantities”: population, capital, food, non-renewable resources remaining (measured as now remaining fractions of the 1900 reserves), and pollution
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The Club of Rome. 1972.
The Limits to Growth. The World Model

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The Club of Rome in 1972. The Limits to Growth. Basic Scenario Variables Follow their Historical Values from 1900 to 1970

The Club of Rome in 1972. The Limits to Growth. Doubled Resources
The other Variables Follow their Historical Values from 1900 to 1970.

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The Club of Rome. 1972. The Limits to Growth. Constant Population The other Variables Follow their Historical Values from 1900 to 1970

Presentation of the Forecast
??? The likely variation. You will be able to calculate an expression for the dispersion of the responses, e.g. their range. Sometimes, it will also be possible to calculate the probability that the factual outcome will not exceed the range. ??? A fuzzy curve. This can be accomplished by drawing the curve as a thick line or by free hand. ??? A fuzzy scale. For example, the Club of Rome deliberately chose to omit the vertical scales of the variables and also made the horizontal scale somewhat vague (consisting of just the values 1900 and 2100). This was because they wanted to indicate that the numerical values were approximate ??? Verbal explanation, even when the forecast has been quantitative, can be used to describe the likelihood of the forecast. The drawback is that people have quite differing notions of what is meant by “probable” or “likely”, for example. ??? Parallel scenarios 58

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Major weaknesses of qualitative forecasting methods
??? Anchoring events ??“ allowing recent events to influence perceptions about future events, e.g. the city hosting a recent major convention influencing perceptions about future room taxes ??? Information availability ??“ over-weighting the use of readily available information ??? False correlation ??“ forecasters incorporating information about factors that are assumed to influence revenues, but do not ??? Inconsistency in methods and judgements ??“ forecasters using different strategies over time to make their judgements, making them less reliable
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Major weaknesses of qualitative forecasting methods
??? Selective perceptions ??“ ignoring important information that conflicts with the forecaster??™s view about causal relationships ??? Wishful thinking ??“ giving undue weight to what forecasters and government officials would like to see happen ??? Group think ??“ when the dynamics of forming a consensus tends to lead individuals to reinforce each other??™s views rather than maintaining independent judgements ??? Political pressure ??“ where forecasters adjust estimates to meet the imperatives of budgetary constraints or balanced budgets.
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Summary
??? The forecast is a reasonable estimate for possible outcomes or development in a specific area and the probabilities they will occur ??? Forecasts are a statement (a prediction) about the future value of a variable of interest ??? There are a lot of methods: qualitative and quantitative ??? The accuracy of a forecast supports the strategy formation process
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