Eric Weisz, David M. Herold and Sebastian Kummer
Although scholars argue that artificial intelligence (AI) represents a tool to potentially smoothen the bullwhip effect in the supply chain, only little research has examined this…
Abstract
Purpose
Although scholars argue that artificial intelligence (AI) represents a tool to potentially smoothen the bullwhip effect in the supply chain, only little research has examined this phenomenon. In this article, the authors conceptualize a framework that allows for a more structured management approach to examine the bullwhip effect using AI. In addition, the authors conduct a systematic literature review of this current status of how management can use AI to reduce the bullwhip effect and locate opportunities for future research.
Design/methodology/approach
Guided by the systematic literature review approach from Durach et al. (2017), the authors review and analyze key attributes and characteristics of both AI and the bullwhip effect from a management perspective.
Findings
The authors' findings reveal that literature examining how management can use AI to smoothen the bullwhip effect is a rather under-researched area that provides an abundance of research avenues. Based on identified AI capabilities, the authors propose three key management pillars that form the basis of the authors' Bullwhip-Smoothing-Framework (BSF): (1) digital skills, (2) leadership and (3) collaboration. The authors also critically assess current research efforts and offer suggestions for future research.
Originality/value
By providing a structured management approach to examine the link between AI and the bullwhip phenomena, this study offers scholars and managers a foundation for the advancement of theorizing how to smoothen the bullwhip effect along the supply chain.
Details
Keywords
Research consistently shows that non-scientific bias, equity, and diversity trainings do not work, and often make bias and diversity problems worse. Despite these widespread…
Abstract
Purpose
Research consistently shows that non-scientific bias, equity, and diversity trainings do not work, and often make bias and diversity problems worse. Despite these widespread failures, there is considerable reason for hope that effective, meaningful DEI efforts can be developed. One approach in particular, the bias habit-breaking training, has 15 years of experimental evidence demonstrating its widespread effectiveness and efficacy.
Design/methodology/approach
This article discusses bias, diversity, equity, and inclusion (DEI) efforts from the author’s perspective as a scientist–practitioner – the author draws primarily on the scientific literature, but also integrates insights from practical experiences working in DEI. The author provides a roadmap for adapting effective, evidence-based approaches from other disciplines (e.g. cognitive-behavioral therapy) into the DEI context and review evidence related to the bias habit-breaking training, as one prominent demonstration of a scientifically-validated approach that effects lasting, meaningful improvements on DEI issues within both individuals and institutions.
Findings
DEI trainings fail due to widespread adoption of the information deficit model, which is well-known as a highly ineffective approach. Empowerment-based approaches, in contrast, are highly promising for making meaningful, lasting changes in the DEI realm. Evidence indicates that the bias habit-breaking training is effective at empowering individuals as agents of change to reduce bias, create inclusion, and promote equity, both within themselves and the social contexts they inhabit.
Originality/value
In contrast to the considerable despair and pessimism around DEI efforts, the present analysis provides hope and optimism, and an empirically-validated path forward, to develop and test DEI approaches that empower individuals as agents of change.