Theory Construction in the Social Sciences Alan Dennis

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Theory Construction in the Social Sciences Alan Dennis ardennis@indiana. edu November, 2011

Theory Construction in the Social Sciences Alan Dennis ardennis@indiana. edu November, 2011

Agenda • • • What is Theory What is Interesting Theory Variance Theory versus

Agenda • • • What is Theory What is Interesting Theory Variance Theory versus Process Theory A Process for Theory Construction Testing and Generalizing Theory

What is Theory You say tomato, I say tomato

What is Theory You say tomato, I say tomato

Theory is 1. the explanation of a relationship between two entities: why A influences

Theory is 1. the explanation of a relationship between two entities: why A influences B – Why do people adopt new technologies? 2. the explanation of factors underlying a specific phenomenon – Why was Windows Vista not widely adopted? 3. the explanation of a phenomenon – What does it mean to adopt a technology? Abend, 2008

Theory is 4. the explanation of theoretical meaning – What is Marxist theory? 5.

Theory is 4. the explanation of theoretical meaning – What is Marxist theory? 5. an overall perspective of understanding – Technology can be thought of as a system of people and tools 6. and so on For the purpose of this Workshop, I’ll use definition 1: the explanation of a relationship between two entities: why A influences B Abend, 2008

Components of a Theory Toulmin Claim Reasons Evidence Context Qualifiers Reservations • What •

Components of a Theory Toulmin Claim Reasons Evidence Context Qualifiers Reservations • What • the entities that comprise the relationship • How • the relationship(s) among the entities • Why • the underlying dynamics that link the entities • Who, Where, When • the boundary conditions to the relationship Whetten, 1989

Components of a Theory What How Entity A Entity B Because ……. Why Boundary

Components of a Theory What How Entity A Entity B Because ……. Why Boundary Conditions Who, Where, When Whetten, 1989

Big T Theory versus small t theory • Big T Theories are given a

Big T Theory versus small t theory • Big T Theories are given a name and usually have an acronym, written in capital letters • Little t theories explain a phenomenon within a smaller domain, often an empirical paper Dennis and Valacich, 2001

What Theory is Not • • • References Data Variables and Constructs Boxes and

What Theory is Not • • • References Data Variables and Constructs Boxes and Arrows Hypotheses Theory is a story with a plot that explains how and why the characters (entities) interact with each other Sutton and Staw, 1995

Is This Theory? The intention to adopt a new technology has often been influenced

Is This Theory? The intention to adopt a new technology has often been influenced by the perceived usefulness of that technology, the extent to which the technology can enable the user to accomplish a needed task. Venkatesh et al. (2003) conducted several experiments with undergraduate students and found that perceived usefulness had a significant positive impact on the intention to adopt. As perceived usefulness increased, so did the intention to adopt. This relationship has been observed in many other studies in a variety of experimental and organization settings (Morris, et al. , 2000; Taylor and Todd, 2005; Venkatesh, et al. 2000). Therefore: H 1: The perceived usefulness of a technology has a direct positive relationship with the intention to adopt that technology

What is Interesting Theory Don’t write to get published, Write to get read and

What is Interesting Theory Don’t write to get published, Write to get read and cited

Upending Conventional Wisdom is Interesting • Organization • • Stability • • Something that

Upending Conventional Wisdom is Interesting • Organization • • Stability • • Something that appears to be good/bad isn’t Correlation • • Something that appears to be stable/changing isn’t Evaluation • • Something that appears to be organized/chaotic isn’t Two things that appear to be independent/related aren’t Causation • The independent variable is the dependent variable Davis, 1971

Finding the Essence is Interesting • Starting a New Research Stream • • Formal

Finding the Essence is Interesting • Starting a New Research Stream • • Formal Models • • Studying the uncommon, but not the unnecessary Translating behavior into math Simplifying the Complex • The definition of a Nobel prize in physics is “Oh #$@!, why didn’t I think of that. ” Tesser, 2000

Extending Implications is Interesting • Surprising Implications of the Obvious • • Implications of

Extending Implications is Interesting • Surprising Implications of the Obvious • • Implications of the Bizarre • • When obvious truths leads to unexpected predictions When “impossible” beliefs are true Look for paradox • Scientific discovery does not start with the word “Eureka”; it starts with the words “That’s funny. ” Tesser, 2000

Which is Interesting? 1. As perceived ease of use of a technology increases, so

Which is Interesting? 1. As perceived ease of use of a technology increases, so does the intention to adopt. 2. As Web sites get slower, Internet users search for more information. 3. Novice Internet users are more likely than experienced users to believe that Web sites presented first in a Google search are “better” than others in the list.

Variance Theory versus Process Theory Every good variance theory has a good process theory

Variance Theory versus Process Theory Every good variance theory has a good process theory at its core

Variance Theory • Variance theory strives to understand “What” • What entities explain the

Variance Theory • Variance theory strives to understand “What” • What entities explain the behavior of another entity? • What explains the variance in an entity’s behavior? • Variables with different attributes affect other variables • Often tested with quantitative data Van de Ven, 2007

Technology Acceptance Model is a Variance Theory Perceived Ease of Use Perceived Usefulness Intention

Technology Acceptance Model is a Variance Theory Perceived Ease of Use Perceived Usefulness Intention to Adopt

Process Theory • Process theory strives to understand “How” • How do entities explain

Process Theory • Process theory strives to understand “How” • How do entities explain the behavior of another entity? • How do events explain the behavior of an entity? • Entities move through different stages at different times • Often tested with qualitative data Van de Ven, 2007

Roger’s Theory of Adoption is a Process Theory Knowledge Persuasion Decision Accept Implementation Confirmation

Roger’s Theory of Adoption is a Process Theory Knowledge Persuasion Decision Accept Implementation Confirmation Reject

A Process for Theory Construction How to go from a blank page to a

A Process for Theory Construction How to go from a blank page to a first draft

The Rational Model of Science Theory is a waterfall model Method Data Analysis Conclusions

The Rational Model of Science Theory is a waterfall model Method Data Analysis Conclusions Martin, 1982

The Garbage Can Model of Science Data Method Theory Analysis Conclusions Mine your Garbage

The Garbage Can Model of Science Data Method Theory Analysis Conclusions Mine your Garbage Can Martin, 1982

Get “The Idea” Prior Theory in Other Disciplines Prior Theory Prior Empirical Results The

Get “The Idea” Prior Theory in Other Disciplines Prior Theory Prior Empirical Results The Idea A B Methods Resources Personal Experiences Martin, 1982

Define “The Idea” What How Why Who, When, Where 1. 2. 3. 4. 5.

Define “The Idea” What How Why Who, When, Where 1. 2. 3. 4. 5. 6. 7. 8. 9. The Idea A B Title (the idea) What is the problem or issue (why do I care)? What are the key concepts (i. e. , A and B)? What is the Research Question (RQ)? What answer do you expect to the RQ? Why do you expect that answer? What are the boundary conditions? What are the methods? How will the data answer the RQ? How do I know what I think until I see what I write? Van de Ven, 2007

Write “The Idea” The Idea A B Title (1) Introduction - Setting (7) -

Write “The Idea” The Idea A B Title (1) Introduction - Setting (7) - Problem or Issue (2) - What this paper does (4&9: RQ and its answer) Prior Research and Theory - Prior Research - Hypothesis development - Define concepts (3) - State the relationship (5) - Explain the relationship (6) - State the hypothesis (4) Methods (8)

Refine “The Idea” Targeted Literature Search The Idea A B Thought Experiments

Refine “The Idea” Targeted Literature Search The Idea A B Thought Experiments

Targeted Literature Search Like Qualitative Research • Search for evidence to support or refute

Targeted Literature Search Like Qualitative Research • Search for evidence to support or refute your idea • One hypothesis at a time • Code articles (at the paragraph level) that offer evidence about your idea The Idea A B • Both theoretical processes and data • Review the codings, change the categories, iterate • Multiple raters (authors) debate the evidence and change the idea

Thought Experiments Like Quantitative Research • Set up tests of your idea like experiments

Thought Experiments Like Quantitative Research • Set up tests of your idea like experiments • Think about the manipulations • Run the experiment in your mind • Multiple raters (authors) debate the evidence and change the idea The Idea A B

You Can Change Your “Data” Literature searches and thought experiments guide your thinking, not

You Can Change Your “Data” Literature searches and thought experiments guide your thinking, not dominate it. If you don’t like what the literature tells you can change your “data. ”

Assess “The Idea” • What’s New? • • So What? • • Is the

Assess “The Idea” • What’s New? • • So What? • • Is the underlying logic solid? Well Done? • • Will this change research or practice? Why So? • • Value-added contribution to current thinking Is it complete and thorough? The Idea A B Done Well? • Is it well written and understandable? Whetten, 1989

Testing and Generalizing Theory Every research method is critically flawed

Testing and Generalizing Theory Every research method is critically flawed

The 3 -Horned Dilemma Maximum Precision Lab Experiments Surveys Maximum Generalizability Field Studies Maximum

The 3 -Horned Dilemma Maximum Precision Lab Experiments Surveys Maximum Generalizability Field Studies Maximum Realism Mc. Grath, 1982

Generalization Setting 1 Setting 2 X Generalize Data

Generalization Setting 1 Setting 2 X Generalize Data

Generalization Setting 1 Instantiate Theory Data Generalize Setting 2 Instantiate Theory Draw Conclusions Data

Generalization Setting 1 Instantiate Theory Data Generalize Setting 2 Instantiate Theory Draw Conclusions Data Draw Conclusions Lee and Baskerville, 2003

Is Science Marketing? • Publishing a theory is like marketing a new product •

Is Science Marketing? • Publishing a theory is like marketing a new product • Find the message of theory • Its unique selling proposition • Know the attributes that help sell a theory • Who developed it (halo effect) • Its origins (borrowed theory is easier to sell) • Simplicity sells faster than the complex • Consistency with current Zeitgeist • Test market theory • With colleagues • At conferences Peter and Olson, 1993

Questions I teach BUS S 798 on Theory Development every Spring Semester, but I’m

Questions I teach BUS S 798 on Theory Development every Spring Semester, but I’m on sabbatical this spring, so it won’t be offered.

References Abend, G. (2008) “The Meaning of They, Sociological Theory, 26: 2, 173 -199.

References Abend, G. (2008) “The Meaning of They, Sociological Theory, 26: 2, 173 -199. Davis, M. S. (1971) “That's Interesting: Toward a Phenomenology of Sociology and a Sociology of Phenomenonology, ” Philosophy of Social Science, 1, 309 -344. Dennis, A. R. , and Valacich, J. S. (2001) “Conducting Experimental Research in Information Systems, Communications of the AIS, 7: 5 Lee, Allen S. ; Baskerville, Richard L. , (2003) “Generalizing Generalizability in Information Systems Research, ” Information Systems Research, 14: 3, 221 -243. Martin, J. (1982) "A Garbage Can Model of the Research Process, " in J. E. Mc. Grath (ed. ) Judgment Calls in Research, Beverly Hills: Sage, pp. 17 -39 Mc. Grath, J. E. (1982) "Dilemmatics: The Study of Research Choices and Dilemmas, " in J. E. Mc. Grath (ed. ) Judgment Calls in Research, Beverly Hills: Sage, pp. 69 -80 Peter, J. P. and J. C. Olson, (1983) "Is Science Marketing? " Journal of Marketing, (47) pp. 111 -125. Sutton, R. I. And Staw, B. M. (1995) "What Theory is Not, " Administrative Science Quarterly, (40), pp. 371 -384. Tesser, A. (2000) “Theories and Hypotheses, ” in Sternberg, R. J. (ed) Guide to Publishing in the Psychology Journals, Cambridge University Press, 58 -80. Van de Ven, A. (2007) Engaged Scholarship, Oxford, Whetten, D. A. (1989) “What Constitutes a Theoretical Contribution? ” Academy of Management Review, (14), pp. 490 -495