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How ICT-Sector Firms are Perceived to Respond to Business-Stakeholder Engagement Models

2016· article· en· W2766712340 on OpenAlexaff
Muhammad Umair Shah, Paul Guild

Bibliographic record

VenueAcademy of Management Proceedings · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovation and Socioeconomic Development
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsInformation and Communications TechnologyStakeholderCorporate social responsibilityBusinessValue (mathematics)Stakeholder engagementStakeholder theoryExploratory researchMarketingPublic relationsBusiness modelPolitical scienceSociology

Abstract

fetched live from OpenAlex

This research explores how managers and leaders of the information and communications technology (ICT) firms perceive receptiveness of start-up, growth, or mature developmental stage organizations toward ‘corporate social responsibility’ (CSR), ‘creating shared value’ (CSV), and ‘creating value for all stakeholders’ (VAS) business- stakeholder engagement models. Drawing from the three fundamental tenets of stakeholder theory, defined as ‘jointness of interest’, ‘cooperative strategic posture’ and ‘rejection of a narrowly economic view of the firm’, we found that the start-up, growth, and mature stage ICT-sector firms are perceived to be at least receptive toward VAS, CSR, and CSV models, respectively. These exploratory findings are important as they suggest that even though a society that seeks to encourage technology companies to broaden their range of stakeholders for innovation, such as their communities or the environment, they might best direct instrumental change toward start-up firms as appreciative of VAS model - even if these new firms require some time to develop perspectives of ‘jointness of interest’ as they strive to become growth or mature firms.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.469
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.085
GPT teacher head0.247
Teacher spread0.162 · 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.

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

Citations0
Published2016
Admission routes1
Has abstractyes

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