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Record W1567270094

The Effect of Complementarities Between IT and Organizational Resources on Firm Performance

2005· article· en· W1567270094 on OpenAlexaff
Saggi Nevo

Bibliographic record

VenueJournal of the Association for Information Systems · 2005
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInformation Technology Governance and Strategy
Canadian institutionsYork University
Fundersnot available
KeywordsComplementarity (molecular biology)Resource-based viewKnowledge managementBusinessOrganizational performanceVariety (cybernetics)Industrial organizationComputer scienceMarketingCompetitive advantage
DOInot available

Abstract

fetched live from OpenAlex

The business value of IT, as measured through its impact on organizational performance, has been hard to pin down. Previous studies, employing a variety of methods, have produced mixed results. This thesis proposes a modified approach for ascertaining IT-related benefits. Based on the resource-based view (RBV) of the firm and the general systems theory (GST), this thesis develops and tests a conceptual model exploring the effect of complementarities between IT and organizational resources on firm performance. The model is being tested using data from a large scale cross-sectional survey of firms from multiple industries. The thesis also develops a framework that identifies the properties of IT and organizational resources that enhance the propensity for mutual compatibility and complementarity. This framework enables the determination of potential IT business value that, in turn, leads to better informed decisions regarding IT investments. Overall, the thesis extends the RBV to include the evolution of strategic resources, provides a tool for practitioners with which to evaluate IT benefits, and adds to the existing knowledge on the impact of IT on organizational performance.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.802
Threshold uncertainty score0.307

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.202
Teacher spread0.196 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2005
Admission routes1
Has abstractyes

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