AMAZÔNIA BEER GAME - Manual de utilização - Jogo de empresa

2021 ◽  
Author(s):  
RUAN GABRIEL ARAUJO FERREIRA FERREIRA ◽  
Robson Antonio tavares Costa
Keyword(s):  
2017 ◽  
Vol 22 (4) ◽  
pp. 297-304 ◽  
Author(s):  
Ming Jin ◽  
Nicole DeHoratius ◽  
Glen Schmidt

Purpose The popular “beer game” illustrates the bullwhip effect where a small perturbation in downstream demand can create wild swings in upstream product flows. The purpose of this paper is to present a methodical framework to measure the bullwhip effect and evaluate its impact. Design/methodology/approach This paper illustrates a framework using SKU-level data from an industry-leading manufacturer, its distributors, end-users and suppliers. Findings Firms benefit from tracking multiple intra-firm bullwhips and from tracking bullwhips pertinent to specific products, specific suppliers and specific customers. The framework presented in this paper enables managers to pinpoint bullwhip sources and mitigate bullwhip effects. Research limitations/implications This paper presents a framework for methodically measuring and tracking intra-firm and inter-firm bullwhips. Practical implications A disconnect exists between what is known and taught regarding the bullwhip effect and how it is actually tracked and managed in practice. This paper aims to reduce this gap. For the various products analyzed herein, the authors show how using this framework has the potential to reduce delivered product cost by 2 to 15 per cent. Social implications Properly managing the bullwhip leads to lower inventories and potentially lower product prices while simultaneously increasing firm profits. Originality/value This paper presents a novel approach to systematically tracking intra-firm bullwhips along with bullwhips specific to a given supplier or customer.


1993 ◽  
Vol 11 (4) ◽  
pp. 412-423 ◽  
Author(s):  
Ann Van Ackere ◽  
Erik Reimer Larsen ◽  
John D.W. Morecroft

2018 ◽  
Vol 32 (3) ◽  
pp. 350 ◽  
Author(s):  
Rossella Pozzi ◽  
Fernanda Strozzi ◽  
Tommaso Rossi ◽  
Carlo Noè
Keyword(s):  

Systems ◽  
2020 ◽  
Vol 8 (4) ◽  
pp. 37
Author(s):  
Benjamin L. Turner ◽  
Michael Goodman ◽  
Rick Machen ◽  
Clay Mathis ◽  
Ryan Rhoades ◽  
...  

Systems involving agriculture and natural resources (AGNR) management and representing integrations of biologic, geologic, socio-economic, and climatic characteristics are incredibly complex. AGNR managers purport using a systems-oriented mental model while many observed management and policy strategies remain linear or symptom-driven. To improve AGNR professionals’ systems thinking abilities, two programs, the King Ranch® Institute for Ranch Management at Texas A&M University-Kingsville (KRIRM) and the Honors College at South Dakota State University (SDSUHC), implemented the famous Production Distribution Simulation Game (a.k.a. the Beer Game) into their programs beginning in 2003 and 2011. A Beer Game database consisting of 10 years of trials or over 270 individual players was compared to seminal work in the literature as well as to one another. We found that AGNR managers and students performed worse than players in a seminal Beer Game study. More interestingly, we found that younger players adapted more readily to inventory surpluses by reducing the order rates and effective inventories significantly when compared to older players (p < 0.10 for retailer and distributors, and p < 0.05 for wholesales and factories). We substantiated our results to those in more recent studies of age-related decision-making and in the context of common learning disabilities. Lastly, we discuss some implications of such decision-making on 21st century AGNR problems and encourage AGNR disciplines to better integrate system dynamics-based education and collaboration in order to better prepare for such complex issues.


Author(s):  
Arianna Alfieri ◽  
Giulio Zotteri
Keyword(s):  

Complexity ◽  
2015 ◽  
Vol 21 (S1) ◽  
pp. 190-199 ◽  
Author(s):  
Mert Edali ◽  
Hakan Yasarcan
Keyword(s):  

2015 ◽  
Author(s):  
Hiroshi Sato ◽  
Tomohiro Shirakawa ◽  
Masao Kubo ◽  
Akira Namatame

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