report on “the fortune sellers” mis 696a october 23, 2002
TRANSCRIPT
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Report on “The Fortune Sellers”
MIS 696a
October 23, 2002
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Order of Business
•Jack: Introduction
•Jack: The Second Oldest Profession
•Amit: When Chaos Rains (The Weather)
•Mark: The Dismal Scientists (Economics)
•Kelly: The Market Gurus
•Surendra: Checking the “Unchecked Population”
•Jason: Science Fact & Fiction
•Rong: The Futurists
•Sherry: Corporate Chaos
•Jack: The Certainty of Living in an Uncertain World
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Introduction
Prognostication Inherent Human Need Can Also be Extremely Profitable Despite Scientific and Technological
Advances, Experts Have Poor Track Record
Future is Fundamentally Unpredictable - Chaos and Complexity Theories
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Chapter 1: “The Second Oldest Profession”
Economics
Financial Services
Technology
Business Planning
Weather
Population
Futurists
Fortune Telling
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Chapter 2: “When Chaos Rains”
Weather Forecasting & Chaos Theory The Interaction The Result What’s in for us as researchers?
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“Chaotic” Weather in our lives
1588 – storm destroyed Spanish ships – English ruled Winter of ’41-’42 – Germans could not win Soviet
Union ’70 – A single cyclone drowned 200,000 Bangladeshis Feb. ’78 – Disastrous blizzard struck New England Oct. ’87 – Worst storm to strike UK since 1703 Aug. ‘91 – US East Coast – $1.5 billion loss ’92 – Hurricane Andrew – $25 billion loss !! Mar. ’93 – winter storm – accurate forecast by NWS Summer ’93 – worst flood in Mississippi River Valley
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$35 Billion Losses/year Due to Weather
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Source of Data: US Dept. of Com m erce National Technical Inform ation Service
$ B
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Weather Forecasting
Variables – have we considered them all?
Data – is it “precise”?
Top Forecasters:• UK’s National
Meteorological Office
• US’s National Weather Service (NWS)
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What is Chaos “really”?
Order, Stability ? Disorder, Instability ? Zoom In – smaller
pieces of the system
• Total Disorder Zoom Out – the system
as a whole
• All possible behaviors
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Mathematics of Chaos Theory
Poincaré (1892): The Father of Mathematics of Chaos Theory
Lorenz (1961): Revived the study of Chaos Theory
Sensitive Dependence on Initial Conditions
• The Butterfly Effect Transitivity Order within Disorder Global Stability with Local Instability
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Evaluating Weather Prediction
“If persistence or climatology forecasts are right most of the time, which they often are, then how smart does a forecaster have to be to be right most of the time: Not very!”
“So much fuss about measuring skill (improvement over some standard – usually stupid – forecasting method, such as random guessing, climatology or persistence), rather than accuracy!”
- Charles Doswell III, Meteorologist at NWS
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Long Term Weather Forecasting
Patterns are decieving …
There’s an almost infinite number of weather patterns that could result from any of the persistent environmental conditions or combinations of conditions.
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Value of Weather Forecasting Forecasts have value…from the resources that are
saved
Savings in human lives alone justifies the $4 billion spent on modernization
$20 - $40 billion in saved property also…
But, no reason to spend on providing long-range forecasting … Research should continue though …
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Learning for us as Researchers
Need to understand Global Stability … Breadth of the field …
Appreciate the Interdisciplinary Nature of Management Information Systems
Small, but significant contribution can be a major revolution in the field
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Learning for us as Researchers
Beware of deceiving patterns; it’s a chaotic world, things hardly ever repeat
Long-term prediction is difficult … Be best at short-term prediction, at the least … appreciate our role as “Fortune Sellers”!!
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Chapter 3: “The Dismal Scientists”
Economic Forecasting• Arguably, everything we care about is, in one way or
another, economics....
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Background
Economists used to focus on the social sciences, the laws that govern government, commerce, and society.
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The Leading Intellectuals of the 19th Century were Economists
Adam Smith
John Stewart Mills
Karl Marx
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“The Dismal Scientists”, A Name that Stuck
The Term “Dismal Scientists” comes from Thomas Malthus’s treatise, An essay on the the ever-expanding human population and possible future ramifications
Its been continued in use in part due to the terrible track record economists have in predicting the future
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Everyone Wants to Predict the Economy, Most Really Try
European Governments
International Corporations Japan
United States Government
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The Problem with Forecasting the Economy
Its not chaotic, just Complex!• It’s impossible to understand a “starting Point”
• Feed-back and Feed-forward loops
Economic Forecasting has a dismal track record• Cannot Predict “Turning Points” Economy
• Cannot beat the “Naive” forecast
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And Economists Are Not Helping The Matter
Economists forecast depending on their particular “religion” of economics.
Many Economists treat forecasting as more of an arcane art then a scientific endeavor
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The Ironic mix of Economics and Information Science
The funny thing about economics is that it requires so much information, even information science can’t help it!
Of course, it doesn’t help that Economics doesn’t have a full complement of natural laws, people act erratically, (although experimental economics is helping that).
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Key Points on Forecasting the Economy
The Economy is too complex to forecast Economists forecast anyway, with the
expected dismal results What economists forecast often depends on
their particular “economic religion” Part of the problem is a lack of accurate
information, something information systems could theoretically assist with, but which in reality is beyond the scope of current technology.
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Applying This to the Future of IS
The utilization/impact of information systems is dependent upon the economic state of the companies seeking to implement them, which in turn depends on the general economy
If the general economy cannot be forecast accurately, then the use and implementation of IS cannot be forecast accurately.
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And Hence
If the use of information systems cannot be forecast, then:• It is very difficult to determine future areas of
beneficial research with any certainty.
• Work whose relevance is dependent upon forecasts should be eschewed for work which is forecast-independent whenever possible.
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Chapter 4: “The Market Gurus”
The Stock Market is a complex system:• Much like the economy, only faster
• A “form of synthetic life with a brain composed of millions of minds”
• Driven by the concept of self-interest
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Predicting the Market…
Technicians Vs. Fundamentalists
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Technicians
Use historical price data to predict future trends
Believe that the Market is driven by “psychological momentum”
Use various techniques including charts, trend theories, and astrology
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Fundamentalists
Estimation of a stock’s intrinsic value Determination of market over-value or
under-value of the stock Assume a rise or fall in the price as
proper value is attained
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Problems with prediction…
Stock prices are random Corporate earnings growth is random Efficient Market Hypothesis
• Strong: Market knows all
• Semi-strong: Market knows almost all
• Weak: Past stock prices cannot be used to predict future stock prices
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15 Minutes of Fame
Roger Babson – Crash of 1929
Elaine Garzarelli – Black Monday
Joseph Granville – Granville Market Letter
Robert Prechter – Elliot Wave Theorist
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The Value Line Enigma
Predictions for 1800 stocks using ‘timeliness’
Seems to defy the EMH Problems
• Requires transactions that are temporally infeasible
• Does not account for risk
• “Not invincible, just enormously influential”
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“While rational forces drive the market toward its fair value, irrational forces of speculation and panic cause the market to diverge from rational value. These irrational forces give rise to explosive nonlinearities that make the market unpredictable.”
-p. 118
Is the Market Rational?S
pe
cula
tion
Pa
nic
Un
de
rvalu
ed
Ove
rvalu
ed
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Is Chaos the Key?
Stock prices not precisely random. May exhibit some element of chaos
Search for chaotic structure involves “massive data mining” (MIS!!!)
Patterns, if existent, are so complex and deeply embedded that they are unlikely to be discovered
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Implications for MIS
MIS is a multidisciplinary field• Shaped by expectations, rationalities, and
irrationalities of practitioners and users across many disciplines
• Influenced by complex (and sometimes chaotic) interactions between people with divergent motives, intentions, aspirations, and visions of the future
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Implications for Research
Researchers must anticipate the ‘bears’ and the ‘bulls’ of the ‘research market’
Researchers must be proactive, implicitly predicting the future by guiding the direction of the discipline
Researchers must understand the needs, expectations, and motives of those who need and use their work
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Research is Networking
Research has a Substantive-Intellectual side and a Community side• “How well will your research fit certain social and
political requirements of the research community”
Become valuable on the outside in order to become valuable on the inside
Adopt a sound research strategy (i.e. the Porter Business Model)
-Source: Lee, Allen S. Researching is Networking: Three Stories about How to Do Research
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A way of conceptualizing IS Research as a System
the emergent interactions between the behavioral subsystem and the technological subsystem
Research Culture • values, norms,
traditions • editors, reviewers,
colleagues • tenure committees • funding agencies
the behavioral subsystem
the technological subsystem
Research Technology • knowledge:theories,
frameworks, concepts
• reasoning: positivist, interpretive, critical, and other methods
Source: Lee, Allen S. “Four Lessons for New Information Systems Scholars,” Keynote address at the Doctoral Consortium of the Pacific Asia Conference on Information Systems (PACIS), Hong Kong SAR, China: June 1, 2000.
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MIS Researcher:Average Lifespan > 15 minutes
Like the stock market, the MIS research domain is multifaceted, dynamic, and the product of a multitude of participants. As researchers, we can prolong our ‘15 minutes’ by identifying trends, actively working to shape the future, recognizing the community side of research, and developing a sound research strategy.
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Chapter 5: “Checking the ‘Unchecked Population’”
Why Predict the population? Factors that effect population Current prediction techniques and
accuracy How can MIS help?
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Why predict the population?
Applications Infrastructure
Planning Govt Policy Budgeting Marketing
Parameters Growth rate Emigration Average age Male-Female ratio Health
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Factors
Economics Weather Political climate Culture War
Emigration Health Male-Female ratio Growth rate Average age
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Current status
Forecasts quite accurate Prediction effect on predictions
• AIDS Case
• GM Food Case
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How can MIS help?
Databases Data mining, patterns Meaningful correlations Micro level planning
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Implications for MIS Research
Effect of external factors on MIS • Economy
• Technology
• Culture
Awareness and Diversification
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MIS
TECHNOLOGYPEOPLE and
ORGANIZATIONS
MIS as an Interface
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Chapter 6: Science ------ Right or Wrong??
Computer program Virus
Painkiller Drug
Powder War
Robot Enemy
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Science and Human beings
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Science Fiction
“the first seeds of the idea were shown by that great, fantastic author, Jules Verne”
--Konstantin Tsiolkovsky
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Science Fiction & Prediction Science fiction spawned
science prediction
Science prediction emerged as a specialized field in 1960s
(H.G.Wells “the Time Machine”)
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80% Science prediction failed
Much more promisesNew habitat
Programmable dream
Longer life expectancy
Robot slave
Out of blueElectricity
Telephone
Light bulb
Cellular telephone
Compact disk
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Science prediction---high-stakes
$160 billion on research per year 2.5 million scientists involved 33 million patents and 1 million more each year
80% new products failed
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Technological Lock-in
Creative destruction
Technological Darwinism Path
Technological synergies
Unworkable Concepts
Unknown applications
Unproved Value
Chance event
A few success technologies
Tens of Millions of Research Project
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Unworkable Concepts
First computers Hot fusion Superfluidity
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Unknown Applications
MASER Laser Fiber Optics
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Unproved Value
Market success depends on customers’ perception of value
Nintendo
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Technological Synergies
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Technological Lock-In Win standard, win the game
VHS vs Betamax
Microsoft’s success
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Chance Events
World War II deferred semiconductors while hastening aerospace, nuclear power, radar…
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Where is MIS?
Multiple, Interdisciplinary Science
Young research domain also with unpredictable future
Resolve the real-world problem
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What should MIS researcher do?
Everyday constructs the future
Failure is the mother of success
Sell powerful tools to Fortune Seller
Doubt other results and try to synergies with other results
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Chapter 7: “The Futurists” Futurists predict societal changes. Mission Impossible?
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Are Social Changes Predictable?
Society is a complex system that is affected by almost everything.
All of these forces are unpredictable, then society itself must be unpredictable.
There can be no prediction of the course of human history by scientific or any other rational methods…We must reject the possibility of social science that would correspond to the theoretical physics.
--------Karl Popper
...),,( 321 XXXFSociety
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Principles of Social Predictions History does not repeat itself. Major social trends, movements, and revolutions
surprise those closest to the event. Social theories are necessarily weak and ephemeral in
their application to social phenomena. Social predictions are subjective and accordingly,
susceptible to situational bias, political agendas and wishful thinking.
Social predictions tend to be wrong.
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What’s Wrong in Futurology?
Beliefs about futurology movement:• There is no single futures…
• We can influence the future…
• We have a moral obligation to use our capability to anticipate and to influence the future.
However, it is not necessarily what futurists actually do.
•“It will be.” OR “It can be.”
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Social Prediction Is Dangerous
Evil side to social prediction:• The misuse of prophecy by
demagogues to control the masses in order to achieve their master plan for society, which they claim is “inevitable” or “inexorable”.
The cost of failed social programs can be immense.
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Zhuge Liang 诸葛亮 The greatest Chinese wisdom,
strategist, politician, inventor, futurist, and
the earliest “FORTUNE SELLER”. (AD 200)“孔明未出茅庐,而知三分天下” Foretell(sell) the Three-Kingdom Era to
Liu Bei, and became the military counselor & premier of Shu Kingdom.
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Fortune Seller And Buyer
Futurists foretell and sell the societal trends to accomplish their political ambition.
Political leaders choose and buy the appropriate and promising “Fortune” as their direction.
魏蜀吴三足鼎立
Yes! That’s my direction!
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Question?
The future is unpredictable. Shall we predict or not? And how?
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What should we do in research?
Review others’ ideas with suspect. Be sensitive of details and chances. Be adaptable of the uncertainty. Base our research on firm scientific
theory and model. Action is more important than prediction. Sell and promote our ideas.
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What else?
Let’s introduce Zhuge Liang’s brother….
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Post Zhuge Liang 事后诸葛亮
Originally, Post Zhuge Liang is a person who always say “I told you…” or “You should have…”• For example, CIA after “9/11”
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Do We Need Post Zhuge Liang?
Yes, we do!!! Future is never independent with the past. We cannot make sound prediction without
understanding the past experience, no matter success or failure.
How to collect, integrate and analyze the information?• MIS can help us.
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Chapter 8: “Corporate Chaos”
History of corporate planning• 1970 GE had a planning department
staffed with193 planners
• BCG’s growth share matrix
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More recently
Management idea• Strategy Space – a two dimension grid
• 1990 Reengineering
Why planning and forecasting• Foresight gives a company potentials
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Organization is unpredictable
A complex system• Highly interacted
Irrational decision making• Lack sufficient information
• Have faulty memories
Can’t expect laws of management • Formulas are not useful
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Organization is not directly controllable
Attempt to control unintended results
Can’t control innovation• Innovation comes naturally
• Control stifles innovation
Self-organization• Flexibility at the lowest level
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Future
Anything is possible
Future possibility bounded by the present reality
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Opportunity
Two type of opportunities Type I: conventional wisdom
• More obvious
Type II: breakthrough• A discontinuity, an innovation, a quantum leap
• Hard to see
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Vision
Discover type II opportunities Future – not fixed entity
• What can be done today?
• Shape the future by vision, courage and wisdom
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Guideline 1 - Self-organization
Give authority, skills, and freedom to employees at all levels to their jobs
Applications in our teaching activities:• Are the students self-organized?
• As a teacher, can we give a student certain flexibility?
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Guideline 2 - Intelligence
Definition• quickly adapt to the environment and learn to
capitalize on new opportunities
What affects the organization learning process?• Information sharing
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Guideline 2 - Intelligence (cont)
As a MIS researcher, what can we do?• Impact of IT on information distribution
• Impact of IT intra-organization collaboration
• Data warehouse and data mining can help organization to learn from historical data
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Guideline 3 - Natural reflexes
Prepare for unexpected surprise event Methods:
• “what-if” questions
Use “what-if” questions in our research• Identify the reasons for unexpected results
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Guideline 4 - Mutation
Definition: • Accident can provide a quantum leap
Methods:• Hire executive from outside the company’s
industry
• Explore the inner workings of unrelated industries
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Guideline 4 - Mutation (Cont)
Application in MIS research:• MIS is an interdisciplinary study
• A broad knowledge background will be helpful
• Advantages of the diversified research areas in our department
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Guideline 5 - Symbiosis
Mutually beneficial relationships between organizations• Supply Chain Management
As a MIS researcher, what can we do?• research on the inter-organization collaboration
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Guideline 5 - Symbiosis (Cont)
Applications in MIS research:• Collaborate with different people
• Example• CMI: IBM, AT&T, US Navy, NSF
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Guideline 6 - Competitive challenge
Evolve to become tough and resilient in a competitive environment
Applications in MIS research:• Position ourselves in a competitive
environment
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More thinking
Uncertainty in research• Unexpected factors, unexpected results
What can we do?• Good literature review
• What if questions
• Concepts and tools from other areas
• Research partnership
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Chapter 9: “The Certainty of Living in an Uncertain World”
Think Critically
Scientific Basis
Methodology
Credentials
Track Records
Personal Biases