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Comments on Data Analysis Techniques ofthe Article “Can Knowledge-IntensiveTeamwork Be anaged! "#amining the$oles of %$ &ystems' (eadershi)' andTacit Knowledge

 

*rou) +

Nuzhat Sharmin

Mohammed Almutairi

Chinta Mani Bhattrai

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Overview of the article. Hypotheses Variales

!indin"s Overview of the data analysis techni#ues Stren"ths $valuation and Su""estion

,utlines

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Statistic Criti#ue Balanced appraisal%&o"ical reasonin" and o'ectivity essence

(esearch )ype * $+planatory

(esearch ,esi"n * Cross Sectional

,verview of the Article

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-opulation (/, department of 01 2) 3rm

Sample Size 456 team and 788 teammemers ,ata Collection -rimary

,verview of the Article.

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 )estin" of hypothesis9 -earsonChi*S#uare test %-*:value

Accepted H4a; H4; H6a;H0a; H0

(e'ected H0

%y)otheses

,ata Analysis Statistics ,escriptive

and inferential

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Inde)endent H(M systems

De)endent  )eam

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2ndependent variale encoura"es thedependent variale.

(elationship of H(M system is positive with

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Article ein" cited 1 times since it has eenpulished in !e 6>45. )hat re?ects its reliailityand Validity to e accepted in A@ 'ournal.

reat contriutions to the strate"ic H(M

literature y e+aminin" the role of

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&ources of Data-rimary.

Data analysis Technique

Hierarchical &inear Modelin" %H&M:

De2nition

A comple+ form of ordinary least s#uares %O&S: re"ression that is used to

analyze variance in the outcome variales when the predictor variales are atvaryin" hierarchical levels%oltman et al. 6>46; p. 6:.

Advantages Better in measurin" nested data. Dsin" two levels approach. e+aminin" relationships within a "roup of analysis; as well as; etween or

across "roups relationships.  %Hofmann / avin 4778: %Hofmann 477E:.

Challenges Fmulti*steps and time*consumin" approachF and addin" more levels will

increase the time spent in conductin" it %oltman et al. 6>46; p. 5E:.

,verview of Data AnalysisTechniques

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Data Collection reach lar"e population; ut diGcult to "eneralize. %2)

industry in )aiwn:.

&uggestion

!or future researchers to conduct it in dierentconte+ts.

 )estin" across cultural dierences and "enderdierences

ethodology  $+perience Samplin" Model would help to measure the

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Calder; I 4778; JSurvey research methodsK; MEDICAL EDUCATION; vol. 06; pp. 50556.

Hofmann; ,A 477E; JAn Overview of the &o"ic and (ationale of Hierarchical &inearModelsK; Journal of Management ; vol. 60; no. 5; pp. E60E11.

Hofmann; ,A / avin; MB 4778; JCenterin" ,ecisions in Hierarchical &inear Models 92mplications for (esearch in Or"anizationsK; Journal of Management ; vol. 61; no. ;pp. 560514.

&arson; ( / Csi41; J)he $+perience Samplin" MethodK; in Flowand The Foundations of Positie Ps!"holog! ; pp. 640.

-insonneault; A / =raemer; =& 4770; JSurvey (esearch Methodolo"y in Mana"ement2nformation Systems 9 An AssessmentK; Journal of Management Information #!stems;vol. 4>; no. 6; pp. E4>.

Saunders; M; &ewis; - / )hornhill; A 6>46; $esear"h Methods For %usiness #tudents;Si+th; -earson $ducation &imited; Harlow.

oltman; H; !eldstain; A; Mac46; JAn introduction to hierarchical linear modelin"K; Tutorials in &uantitatieMethods for Ps!"holog! ; vol. 8; no. 4; pp. 657.

Chuan"; C; Iac