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Record W70494987 · doi:10.17705/1cais.00713

New Developments in Practice I: Risk Management in Information Systems: Problems and Potential

2001· article· en· W70494987 on OpenAlexaff
Heather A. Smith, James D. McKeen, D. Sandy Staples

Bibliographic record

VenueCommunications of the Association for Information Systems · 2001
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicOutsourcing and Supply Chain Management
Canadian institutionsQueen's University
Fundersnot available
KeywordsRisk managementRisk management information systemsRisk analysis (engineering)IT risk managementScope (computer science)Variety (cybernetics)IT riskIdentification (biology)Enterprise risk managementProcess (computing)Action (physics)BusinessRisk management planKnowledge managementProject risk managementProcess managementControl (management)Risk assessmentInformation systemComputer scienceManagement information systemsProject managementEngineeringProject management triangleComputer security

Abstract

fetched live from OpenAlex

Risk management can be an extremely powerful approach to dealing with the complexities and uncertainties that increasingly surround technological change and its management. Conventionally in information technology (IT) projects, risks have been narrowly defined. Today, with IT becoming integral to a company's existence, the stakes are considerably higher and broader in scope. However, risk is sometimes seen a negative concept in information systems (IS) organizations because it implies that something could go wrong with an IT project. To understand effective risk management in IS, the authors convened a focus group of senior IS managers from a number of organizations in a variety of industries. The results of this discussion, the managers' presentations, and a review of the current research on risk management, were integrated and are presented in this paper. The nature of risk, identifying risk in IT initiatives, determining appropriate levels of risk, and dealing with unacceptable types and levels of risk are discussed. The following conclusions were reached. Risk management is a means to an end - whether it is a successful IS project; stable, secure technical operations; or a properly implemented business strategy using technology. It is not a one-time activity, but rather an ongoing process of identification, assessment, and action, which needs to be well integrated into every part of IS management. IS managers must learn to control both the problems and the potential that risk represents. Several general principles to help IS managers deal effectively with risks were identified. Effective risk management involves taking a holistic approach to risk, developing a risk management policy, establishing clear accountabilities and responsibilities, balancing risk exposure against controls, being open about risks to reduce conflict and information hiding, enforcing risk management practices, and learning what works and doesn't from past experience.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.023
metaresearch head score (Gemma)0.033
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.025
Threshold uncertainty score0.120

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0230.033
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.007
Science and technology studies0.0060.023
Scholarly communication0.0250.032
Open science0.0030.009
Research integrity0.0110.014
Insufficient payload (model declined to judge)0.0100.003

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 head0.015
GPT teacher head0.231
Teacher spread0.216 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations33
Published2001
Admission routes1
Has abstractyes

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