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Record W2524908041

Green Decision Making by Organizations: Understanding Strategic Energy Choices

2011· dissertation· en· W2524908041 on OpenAlexaboutno aff
Travis Gliedt

Bibliographic record

VenueUWSpace (University of Waterloo) · 2011
Typedissertation
Languageen
FieldBusiness, Management and Accounting
TopicEnvironmental Sustainability in Business
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessManagement sciencePolitical scienceEngineering
DOInot available

Abstract

fetched live from OpenAlex

There is a growing need to better understand environmental decision making in the context of climate change and limited renewable resources. This dissertation deepens our understanding of such decision making by focusing on strategic green decisions, which can be defined as the individual and collaborative green decisions within or between organizations that help organizations improve their operating position, adapt to changes in their external institutional environments, and simultaneously generate environmental benefits. The particular focus is on decisions related to energy in the North American context. \n \nThe research draws on and contributes to organizational theory with the aim of better understanding those factors that motivate and/or facilitate green decisions by organizations, especially social economy organizations—an area of only limited research to date. Two complementary empirical studies address the overarching research goal. \n \nThe first study focuses on understanding the nature and extent of the association between organizational attributes and those factors that motivate and/or facilitate a green energy decision. Insights are based on a bi-national survey of 212 organizations that voluntarily began to purchase green electricity between 1999 and 2008. Findings indicate that important influences are similar across organizational types. Survey results highlight the importance of organizational culture and internal champions—both individually and in combination—in making the initial decision to purchase green electricity, despite its relatively higher price. These two factors, as well as strategic benefits, emerge as the dominant explanations for why organizations expand their green energy purchases. The relative importance and particular roles of these factors vary across organizational and decision types. \n \nThe second empirical study extends our understanding of how organizations adapt to external changes while maintaining the capacity to innovate in order to address their core objectives. The focus is on the residential energy services market, and is based on 12 interviews with the executive directors of non-profit environmental service organizations (ESOs) that are part of a national network called Green Communities Canada. These organizations survived a funding shock by creating new services and diversifying funding sources with actions that collectively can be referred to as ‘green collaborative entrepreneurship’; collaborative because \nit was facilitated by strategic partnerships with businesses and local governments, as well as the cross-national social capital network connecting the ESOs. The important motivating factors of green collaborative entrepreneurship were the green values and objectives that drive these organizations. The facilitating factors of green collaborative entrepreneurship included human capital, social capital and strategic partnerships, which acted as dynamic capabilities because of their flexibility to help increase the level of entrepreneurship when necessary for organizational survival, and yet, scale-up and deliver core programs during stable funding periods. \n \nThe dissertation provides important insights into broad questions related to green decisions, especially for organizations that are affected by political policy cycles. The findings highlight that organizations are able to be more environmentally sustainable while also improving their own strategic performance by making green decisions that either provide the capacity to adapt to exogenous change for survival, or to create endogenous change for competitive advantage. The research contributes to our understanding of societal transitions to sustainable development by highlighting two green decisions that are occurring in the social economy. The dissertation contributes to organizational theory and in particular the traditional corporate literature by including multiple organizational types. Sustainability researchers should focus on green decisions that both enhance organizational stability and ecological sustainability if they wish to better understand creative green solutions from organizations.

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)0.004
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0020.006
Scholarly communication0.0090.011
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.016
GPT teacher head0.196
Teacher spread0.180 · 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 designQualitative
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

Citations1
Published2011
Admission routes1
Has abstractyes

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