The Oxford Handbook of Business and the Natural Environment
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Notice bibliographique
Résumé
Environmental issues now loom large on the social, political, and business agenda. Over the past four decades, "corporate environmentalism" has emerged and been constantly redefined, from regulatory compliance to more recent management conceptions such as "pollution prevention", "total quality environmental management", "industrial ecology", "life cycle analysis", "environmental strategy", "environmental justice, " and, most recently, "sustainable development." As a result, understanding the intersection of business activity and environmental protection has become increasingly complex, and there has emerged a focus in academic research on business decision-making, firm behavior, and the protection of the natural environment. This Handbook reviews the state of the field as it grows into a mature area of study within management science, its achievements, and its future avenues of research. It brings together original contributions in the field along several lines of enquiry. The first six focus on disciplines as delineated in contemporary business schools: business strategy; policy and non-market strategies; organizational theory and behavior; operations and technology; marketing; and accounting and finance. The seventh section reviews emergent and associated perspectives, whilst a concluding section, written by long-standing leaders in the field, discusses the future outlook for research. Contributors to this volume - Michael V. Russo, University of Oregon Amy Minto, University of Oregon Petra Christmann, Rutgers University Glen Taylor, California State University Mike Lenox, University of Virginia Jeffrey G. York, University of Colorado George Kassinis, University of Cyprus Andrew King, Tuck School of Business Andrea M. Prado, Stern School of Business Jorge Rivera, George Washington University David P. Baron, Stanford Graduate School of Business Tom P. Lyon, University of Michigan Cary Coglianese, University of Pennsylvania Ryan Anderson Lisa L. Shu, Harvard University Max H. Bazerman, Harvard University Leigh Plunkett Tost, Duke University Kimberly A. Wade-Benzoni, Duke University Jennifer Howard-Grenville, University of Oregon Stephanie Bertels, Simon Frazer University Michael Lounsbury, University of Alberta Samantha Fairclough, University of Alberta Min-Dong Paul Lee, University of South Florida Magali A. Delmas, UCLA Michael W. Toffel, Harvard Business School Klaus Weber, Northwestern University Sara B. Soderstrom, Northwestern University Robert D. Klassen, Ivey Business School Stephan Vachon, HEC Montreal James D. Abbey, Pennsylvania State University V. Daniel R. Guide, Jr., Pennsylvania State University Reid Lifset, Yale University Frank Boons, Erasmus University Nigel P. Melville, University of Michigan Debra Scammon, University of Utah Jenny Mish, Notre Dame Andrew Gershoff, University of Texas, Austin Julie R. Irwin, University of Texas, Austin Timothy M. Devinney, University of Technology, Sydney Irene Herremans, Calgary Robert Gray, University of St Andrews Nola Buhr, Saskatchewan Charles Cho, Concordia University Dennis Patten, Illinois State University Robin Roberts, University of Central Florida Rob Bauer, Maastricht University Jeroen Derwall, Tilburg University Jean-Louis Bertrand, ESSCA Ecole de Management Bernard Sinclair-Desgagne, HEC Montreal Bryan Routledge, Carnegie Mellon University Krista Bondy, Cranfield University Dirk Matten, York University James E. Post, Boston University Linda C. Forbes, Western Connecticut State University John M. Jermier, University of South Florida Subhabrata Bobby Banerjee, University of Western Sydney David L. Levy, University of Massachusetts Benyamin B. Lichtenstein, University of Massachusetts John R. Ehrenfeld, MIT Nigel Roome, Tilburg University Paul Shrivastava, Concordia University John Elkington, SustainAbility and Volans Charmian Love, Volans Stuart L. Hart, Cornell University Thomas N. Gladwin, University of Michigan
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle