The Joint Influence of Evaluation Mode and Benchmark Signal on Environmental Accounting-Relevant Decisions

Hank C. Alewine and Dan N. Stone

Social and Environmental Accountability Journal, 2016, vol. 36, issue 2, 124-152

Abstract: The assessment of environmental alternatives occurs in one of two evaluation modes: joint (JE) or separate (SE) evaluation. This study explores the combined influence of evaluation mode and the attractiveness of environmental alternatives on decisions based on non-financial environmental accounting information. General Evaluability Theory [GET; Hsee, C. K., and J. A. Zhang. 2010. “General Evaluability Theory.” Perspectives on Psychological Science 5: 343–355] predicts greater decision dependence on benchmark performance signals received in SE than JE mode. However, GET is silent on the influence of the alternatives’ attractiveness on evaluations, e.g. when available environmental alternatives all perform either superior or inferior to a benchmark case. To address this condition, we propose supplementing GET with the ‘negativity bias’, which predicts that negative signals (e.g. worse than benchmark values) receive more decision weight compared to positive signals (e.g. better than benchmark values) [Rozin, P., and E. B. Royzman. 2001. “Negativity Bias, Negativity Dominance, and Contagion.” Personality and Social Psychology Review 5 (4): 296–320]. Accordingly, this study's experiment (n = 77) manipulated evaluation mode (between-participants; JE/SE) and the alternatives’ performances relative to a benchmark (within-participants; available alternatives all better, or worse, than benchmark). Participants made investment allocations (as a proxy for performance ratings) to available factories based on factory environmental accounting performance. Participants invested less (more) in factories when factory performance was inferior (superior) to benchmarks. However, consistent with a combined GET and negativity bias prediction, this difference was more (less) pronounced in SE (JE) mode. Overall, results suggest that joining GET with a negativity bias accurately captures the joint influences of evaluation mode and benchmark signals on decisions based upon environmental accounting information. Further, decision-makers seem to adopt an asymmetric decision heuristic in evaluating environmental accounting information. Specifically, they avoid increasing decision weight on bad environmental performance information in JE compared to SE mode, but decision weights are indifferent across evaluation mode for good environmental performance information.

Date: 2016
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DOI: 10.1080/0969160X.2016.1149343

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