Presentation on theme: "Question 1 How can we succeed? –in a Business School Context –Competition comes from Economics, Strategy, and Organizational Perspectives –which draw on."— Presentation transcript:
Question 1 How can we succeed? –in a Business School Context –Competition comes from Economics, Strategy, and Organizational Perspectives –which draw on more widely employed reference disciplines
Assumptions to Argue About “Competition” implies a zero sum game It is unusual to cite cognitive literature (see the work of experimental economics and behavioral accountants) Our work does not cite economics, strategy, or organizational research: 3 dissertations: –Studied effects of different utility theory cost and probability parameters in softlifting experiment (Peace) –Studying effects of problem-solving cues on strategy development (Sampler) –Group spreadsheet debugging work cited group problem-solving literature (Joseph)
Assumptions to Argue About Those fields are secure –Colleagues in strategy consider their field as the champion of identity crisis –If economics is Arnold Shwarzzeneger, strategy might be Woody Allen. –What is Cognitive IT? Somewhere between Jean-Claude Van Damme and Regis Philbin Our work does not cite widely-used reference disciplines –Which disciplines are we missing? Pure math? If that is required, we would have schools of Finance/Econ.
So, Regis, How do We Succeed? Study Interesting Problems (or problems that will become interesting) Attract something: –Students –Colleagues –Grants –Reporters
Publicity Please visit your school’s PR function Much of what we do is interesting to regular people, too. I found new respect from others after: –Chatting with Chris Arnold on All Things Considered about applying results of response time research to Web browsing (1996—result of a Washington Post op-ed)
WSJ Report Pam Sebastian’s column Word of mouth’s interference on learning a package Ironic Philippe Kahn juxtaposition Also reported in Computerworld, etc. ICIS & CACM articles
CNN TV Study cited by CNN, Business Week, dozens of news- papers, 4 radio programs To appear in CACM Intended to show how a word processing aid needs to fit cognitive abilities of users
Question 2a: Are we Doomed always to be a Minority? Yes, unless we act. –We must be represented on editorial boards and must not turn over all of the crown jewels to hostile forces One person can make a difference: calmly noted the lack of any relevant track for HCI/cognitive research in ICIS 2003 to a program chair; now we have an entire mini-track as a direct result of that conversation Our SIGs will help a great deal. –We should broaden our data collection beyond college sophomores at least once in a while –We should write carefully, write well, and explain effectively the relevance of our studies
Question 2b: What Happened to the Experiments of the 70s and 80s? Experiments are hard to construct that have: –Basis in theory, but (like Goldilocks and the 3 Bears): Not too soft (supported too little by previous studies): A stretch? Not too hard (supported too much by previous studies): Obvious? –Relevance and Rigor –Realism of manipulation –Representativeness of sample –Reasonable magnitude of findings –Capture of appropriate constructs How many studies can do all of these? Is it zero? Perhaps. If not zero, do we read them as “guilty until proven innocent?” –A recent submission: a big flaw: we didn’t cite an article released 90 days after submission
Question 3: What Should We Do? Let’s figure out how to fairly evaluate experiments: what bed is just right? Let’s ask/plead/demand our journals to provide balanced editorial boards Let’s market our work properly: –Don’t oversell it by promising silly implications –Don’t undersell it by hiding implications –Don’t try to sell it if no implications!
What to Do (continued)? Make agreements to have regular, formal or informal research exchanges –Discuss experiments you are designing. –Be brutally critical at this stage; the best gift to your colleagues. –Withholding criticism is not being kind to them. Pilot tests are not just for PhD Theses! Fix materials; debug procedures; ascertain magnitude of effect size to choose appropriate sample size.
What to Do (continued)? Before a large investment in the experiment, inventory support for hypotheses –If support is meager, perhaps save your energy. –If support is widespread, emphasize your contribution Before a large investment in subjects, –Do you own tasks before any other steps. –You will find obvious difficulties. Fix them. –Remove any confounds. –Make sure tasks are debugged.