Achieving triple bottom line outcomes through strategic reputation management: A role for communications leadership
Bibliographic record
Abstract
This research paper discusses the opportunities for communicators to lead organizations into a new era of stakeholder capitalism within a changing business landscape. Specifically, it explores how companies who hold a triple bottom line (TBL) mandate use strategic reputation management to achieve success in performance management that includes social, environmental, and financial outcomes. This research explores a relationship between strategic reputation management and triple bottom line outcomes wherein reputation management is elevated as a strategic function that leverages an orientation toward stakeholders to support social, environmental, and financial outcomes. Likewise, a focus on triple bottom line, or related frameworks like corporate social responsibility, and ESG (environmental, social, and governance) can help enhance reputation as a direct outcome for organizations. The paper builds upon existing research in the fields of business management, stakeholder theory, public relations theory, and strategic communications. The research examines 10 leading Canadian companies through primary and secondary data collection of corporate publications and in-depth interviews and employs thematic analysis to explore the relationship between the research concepts. The results show five thematic categories that address the research objective of establishing how and to what extent companies who pursue a triple bottom line institutionalize a stakeholder orientation and how they employ strategic reputation management. This research finds the contributions of strategic reputation management to TBL outcomes are centred around two-way symmetrical communications, relationship building, co-orientation with diverse stakeholders, and enterprise integration of a balanced valuation of people, planet, and profit. Given that the tactics connecting these concepts are best executed by communications leaders, this paper presents a framework for adoption by communications leaders in other companies. This research contributes to the literature and to the practice of strategic communications, reputation management, and stakeholder capitalism in business management.
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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 | 0.017 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.011 | 0.010 |
| Scholarly communication | 0.017 | 0.010 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
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".