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Record W2511063810 · doi:10.5539/ibr.v9n10p46

Interrelated Factors Influencing the Adoption Decision of AIS Applications by SMEs in Jordan

2016· article· en· W2511063810 on OpenAlex
Ahamed Al-dmour, Rand Al-Dmour, Ra’ed Masa’deh

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Business Research · 2016
Typearticle
Languageen
FieldComputer Science
TopicOrganizational and Employee Performance
Canadian institutionsnot available
Fundersnot available
KeywordsRespondentIncentiveBusinessMarketingConceptual frameworkOrder (exchange)Conceptual modelSmall and medium-sized enterprisesKnowledge managementComputer scienceEconomicsPolitical scienceSociology

Abstract

fetched live from OpenAlex

<p>This study aims to identify the main factors that either facilitating (motivating) or inhabiting the adoption decision of AIS by small –medium sized companies in Jordan. In order to accomplish the research objectives, a conceptual framework was designed. The conceptual framework includes three major interrelated factors: organizational, technological and environmental factors. The data for this research were collected through email survey with 101 respondents. The target respondents were the small-medium sized companies in Jordan and the key respondent approach was used. A group of twenty factors, employed as variables from the previous studies and models of adoption were listed and examined in a neutral manner, without pre-classifying them as barriers or incentives, through email surveys sent to key respondent in the SMEs. Respondents were asked to indicate how these factors influence their AIS adoption decisions. Furthermore, a comparison analysis has conducted to show how these factors are perceived differently among those who have adopted as AIS, those that will not adopt it all and those that might adopt it in the near future. The finding showed that only twelve of these factors were found significant, eight labeled as incentives and four labeled as barriers. However, the set cost factor was the only shared one perceived as a barrier among all groups. The results showed the three groups adopt perceive factors differently. The research has finalized with some theoretical and practical implications and recommendations.</p>

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.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.267
Threshold uncertainty score0.233

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.036
GPT teacher head0.331
Teacher spread0.295 · 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