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Quantitative, Positivist Research Methodsin Information Systems

Section 1. Welcome

We lcome to the s ection on Q uantitative, Positivist Research (QPR) Methods in InformationSystems (IS). This section attempts to address the ne eds of quantitative, positivistresearchers in IS both seaso ned veterans, and those just beginning to learn to usethese methods. The rese arch tasks that are a ddress ed include many stages in thescholarly process, including literature review and theo ry development s tage s, and thelater stage of design.

1.1 Acknowledgments: We wish to thank the CIS Dept. at Georgia State University forhosting this site. Suggestions on how bes t to improve on the site a re very we lcome.Pleas e contact us directly if you wish to make sug ges tions on how to improve the s ite. Nofaults in content or design should be attributed to any persons o ther than ourse lves s incewe made a ll relevant decisions on these matters.

1.2 Objective of this WebsiteThis se ction is de dicated to exploring issues in the use of quantitative, pos itivist researchmethod s in Information Systems (IS). W e intend to provide basic in formation about themethods an d techniques a ssociated wi th QPR and to offer the visit or links to othe r usefulsites and to se minal works.

1.3 Explanation for Extent of Self-Cit ationOne o f the main reaso ns the co-editors were interes ted in initiating this site is that wehave already published a fair number of articles on the subject. We felt that we nee ded tocite our ow n wo rks as readily as others to give the We b surfer as much information athis/her fingertips as poss ible. For this reason, we also include hyperlinks (Section 9,below) so use rs can dow nload the last working paper version of the pape rs that we we reeventua lly fortunate e nough to have published.

Please note that a version of the material on this w ebsite has a lso been published as:Straub, Detmar W., David Gefen and Marie-Claude Boudreau, "Quantitative Research," InResearch in Information Systems: A Handbook for Research Supervisors and Their Students ,D. Avison a nd J. Pries -Heje (Ed.), Elsevier, Amste rdam, 2005, 221-238.

1.4 What is Quantitative, Positivist ResearchQPR is a set of methods and techniques tha t allow IS researchers to answ er researchques tions about the interaction of humans and computers. There are tw o cornerstones inthis approach to research. The first cornerstone is the emphasis on q uantitative da ta. The

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second cornerstone is the e mphasis on positivist philosophy . Regarding the firstcornerstone, these methods and techniques tend to specialize in quantities in the sensethat numbers come to represe nt values and levels of theoretical constructs and conceptsand the interpretation of the numbers is viewe d as s trong scientific evidence of how apheno menon wo rks. The presence of quantities is so predo minant in QPR that statisticaltools and packages are an e sse ntial element in the resea rcher's toolkit. Sources of dataare o f less concern in identifying an approach as being QP R than the fact that empiricallyderived numbers lie at the core of the scientific evidence ass embled. A QPR researchermay use archival data or ga ther it through structured interviews . In both cases, therese archer is motivated by the numerical outputs and ho w to de rive meaning from them.This e mphas is on numerical ana lysis is also key to the second cornerstone, pos itivism,which defines a scientific theory as one that can be falsified.

1.5 What it is Not and How it Differs from Analytical Modeling, Design Research andQualitative ResearchQPR is orthogonal to the analytical modeling (a.k.a. math mode ling) that typically dependson mathematical de rivations and assumptions. This difference stress es that e mpirical datagathe ring or da ta exploration is part and parcel of QPR, while the positivist philosophydea ls with problem-solving and the testing of the theories de rived to te st theseundersta ndings. It is also not design rese arch , in w hich IT artifacts are de signed toimprove processe s. Mode ls and prototypes a re freque ntly the products of design rese arch.First, in QPR, the models employed are most often causal models whereas de sign researchplaces its stress on onto logical mode ls. Second, there is also the difference that QPR

validates its findings through data whe reas des ign resea rch can find acceptable validationof a new des ign through a mathematical proof of concept. Nevertheles s, it should benoted that des ign rese archers are increasingly using QP R, spe cifically experimentation, tovalidate their mode ls and prototypes so QPR is also becoming a key tool in the arse nal of design researchers.

To the qualitative resea rcher, a phenomenon can best be interpreted by studying speechacts, relationships betw een peo ple and computers, archival documents, diagrams of thewo rkplace, and the like. If a qualitative researcher believes that the se sources o f data andthe techniques such as interviewing that are used to gather the da ta can be renderedinto numbers, then this rese archer would be classified as a qualitative, positivistresearcher in Michae l Myers ' classification s cheme for qua litative research.

1.6 QPR Epistemology and OntologyThe underlying view o f nature that leads a scholar to conclude tha t QPR can produceknowledge is that the w orld has an objective reality that can be captured a nd translatedinto tes table hypothe ses, usually in the form of statistical or other numerical analyses. Theoriginal inspiration for this came from the scientific epistemology of logical positivism thatwa s de veloped by the Vienna Circle of Pos itivists, mostly Karl Popper , during the 1920sand 1930s. This "pure" positivist attempt at viewing scientific exploration as a sea rch forthe Truth has be en rep laced in recent years w ith the recognition that un timately allmeasurement is base d on theory and hence capturing an "objective" truth is impossible.Even the measurement of a purely physical attribute, such as temperature, depe nds onthe theory of how materials expand in heat. Hence interpreting the readings of athermomete r cannot be regarded as a pure obse rvation but itself as an instance of theory.

In recent years, there have been e fforts to even combine the te chniques and viewpointsof positivists and non-positivists to triangulate on pheno mena (Kaplan and Duchon, 1988) .Lacity and Janson (1994) argue that both approaches can be viable, and both can beshow n to be valid for the ir circumstances .

At the heart of the p ositivist mind frame is the concept of deduction . There a re four steps indeduction:

1. Testing interna l consistency, i.e., verifying that there are no interna l contradictions .2. Distinguishing betwee n the logical bas ics of the theory and its empirical, tes table,

predictions.3. Comparison with existing theory, show ing that the new the ory advances

knowledge. Specifically, it is neces sary to show that the ne w the ory has supe rior

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empirical subs tance and hence more predictive pow er.4. Empirical testing aimed a t falsifying the theory with data . When the d ata do not

contradict the hypothes ized p redictions of the the ory, it is te mporarily corroborate .The objective of this test is to falsify, not to verify, the predictions of the theory.Verifications can be found for almost any theory if one can pick and choose wha t tolook at.

The qualitative researcher in contrast tends to se e the w orld as a social construction thatwill demonstrate large variance depending on the obs erver and the interpreter of thepheno menon. Reality is usually seen a s highly subjective by a qua litative researcher.

Saying that QPR tends to se e the w orld as having an objective reality is not equivalent tosaying that QPR ass umes tha t constructs and measures of thes e constructs are movingtow ard pe rfection over the years. In fact, Cook and Campbe ll (1979) make the pointrepeated ly that QPR will always fall short of the mark of perfect represe ntation. For thisreason, they argue for a "critical-realist" pe rspective, pos iting tha t "causa l relationshipscannot be perceived w ith total accuracy by our imperfect sensory and intellectivecapacities" (p. 29).

There are many ontologies or typologies of QPR. We offer one ourselves in the ne xtsection, in fact. The important point to remember about these ontologies is that rese archmethod s a re no t naturally occurring a rtifacts. Distinctions be twe en them will be sociallyconstructed, on the one hand, or based on practice, on the othe r. Resea rchers need toknow s omething about the capabilities of these methods so that they can match them to

their research problems and evaluate them when they are asked to review. Otherwise,these a re distinctions without a difference tha t matters. At any rate, it is imperative torecognize that any obse rvation is itself inherently based on theory.

1.7 CaveatsThis W ebs ite focuses on the most common QPR types of within the IS community. Thereare many other types of quantitative res ea rch that w e can only gloss over here. This isnot to s uggest in any wa y that these methods and tools cannot be invaluable to an ISrese archer. Only that they are not a s common.

Pleas e se nd sugges tions for improvement to the Section Co-Editors at: dstraub@gsu.edu ,gefend@dredxel.edu and mcboudre@terry.uga.edu .

Citation information: Electronic source: Straub, Detmar, David Gefen, and Marie-ClaudeBoudreau (2004). "The ISWorld Quantitative, Pos itivist Rese arch Methods We bsite," (Ed)Dennis Galletta, http://www.dstraub.cis.gsu.edu:88/quant/ . Last upda ted: January 7,2005."

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