Internet‐based information systems use in organizations: an information studies perspective
Bibliographic record
Abstract
Abstract. This case study investigates various ways in which different internet‐based information systems (IS) are used by organizational participants. Borrowing theoretical insights on information behaviour accumulated over 50 years of information studies research, a conceptual framework is presented to help understand and assess the social and organizational impacts of internet‐based IS. The framework describes the use of internet‐based IS as a dynamic cycle of information needs–seeking–use activity situated in the context of a firm's information environment. Research questions pertain to the process of how individuals in organizations seek and use information from internet‐based IS to satisfy information needs. In terms of information needs, this involves understanding the problem situations that lead participants to use internet‐based IS, as well as the characteristics of those problems beyond subject matter. With respect to information seeking, this involves analysing how information from internet‐based systems is displayed and formatted to signal their potential usefulness. In terms of information use, this involves how information obtained from internet‐based systems is used in practice to resolve or redefine problems. Both quantitative and qualitative research methods are used. Data collection involves web tracking to identify significant episodes of internet‐based IS activity, as well as one‐on‐one interviews to explore the context behind these episodes. Results suggest that it is possible and valuable to identify scenarios of internet‐based IS use dominant in an organizational work setting. Doing so can help to identify ways to improve the situated use of internet‐based IS that ameliorate the information needs–seeking–use cycle in firms.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.012 | 0.015 |
| Scholarly communication | 0.019 | 0.017 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".