Bibliographic record
Abstract
Purpose Managerial mindset and cognitive bias can be barriers to any transformation strategy. In the case of telework, most employees express willingness to telework, yet, few firms formally enable it during regular business hours. The status quo is a daily commute to the traditional workplace. The purpose of this paper is to test framing interventions designed to harness cognitive biases through choice architecture. Design/methodology/approach Drawing upon behavioral strategy and prospect theory, this paper presents two studies: quasi-experiments with 146 senior business students and experiments in the field (replication using random assignment and extension) with 84 senior decision makers. Both studies use a one-way between-subjects design and chi-square analysis. Findings Findings support the proposition that, although cognitive biases can act as barriers to transformation, they can be re-framed through strategic interventions. Specifically, in both studies, there was a drastic increase in adoption simply by changing the way the choice was presented. Findings in the lab were cross-validated in the field. Observed shifts in preferences provide evidence that embedding the right reference point within communications can frame a decision choice more favorably. Findings also support that a bias for an implicitly perceived status quo can be overruled through an explicitly stated reference point. Research limitations/implications It is an assumption of behavioral strategy that most individuals simply respond to the gains/loss framing without being influenced by other psychological or contextual factors, and though these effects dissipate through aggregation, it is a limitation nonetheless. Indeed, using an individual construct to explain an organizational phenomenon is a well-debated topic in the field of strategy, with proponents on both sides. The distinguishing factor, here, is that behavioral strategists are only interested in results at the aggregated level. Practical implications Practitioners attempting to roll out telework adoption, or any transformation, now have proven strategies for designing frames of reference that intervene against and harness the power of loss aversion and the status quo. Social implications This paper measures micro processes that have an effect at the macro level. It explains systematic aversion to adoption as an aggregation of decision-making behavior that is seemingly subconscious. In doing so, it highlights the impact of bounded rationality perpetuated through social systems, while measuring effective interventions designed to make systematic behavior more predictable. Originality/value A novel contribution is made in designing/testing a new frame for systematic resistance to change that frames the status quo as the losing prospect. In this frame, the perceived loss is in the choice not to change, and loss aversion proves to be an effective tool for facilitating systematic change.
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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 | 0.019 | 0.060 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".