Chantey Castings: A Hands‐On Simulation to Teach Constraint Management and Demand‐Driven Supply Chain Approaches

Grandzol, Christian; Grandzol, John R.

doi:10.1111/dsji.12142

Cited by 6 publications

(4 citation statements)

References 24 publications

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“…Different assessment methods identified in the literature include the use of self‐reported data on whether learning outcomes improved, either directly from students themselves (Arenas‐Márquez, Machuca, & Medina‐López, 2012; Piercy, Brandon‐Jones, Brandon‐Jones, & Campbell, 2012; Scholten & Dubois, 2017; Grandzol & Grandzol, 2018) and/or from teachers (Léger et al., 2012; Scholten & Dubois, 2017), and final test scores (e.g., Arenas‐Márquez et al., 2012) or pre/postimplementation scores (e.g., Manikas et al., 2015). In this study, we use both self‐assessment and test scores.…”

Section: Field Tests Resultsmentioning

confidence: 99%

Classroom Simulations for Teaching Production Control in Nonrepetitive Contexts: Insights for Theory and Practice

Thürer

Cole

Hanna

et al. 2020

Decision Sci J Innov Edu

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When introducing production control solutions, most textbooks focus on a to-stock, repetitive context. In response, we extend the classical match-and-dice game, which also assumes a repetitive context, to teach complexities that emerge in a nonrepetitive setting, such as the appearance of direct and indirect load, and to introduce appropriate production control solutions (e.g., Constant Work-In-Process [ConWIP] and Control of Balance by Card Based Navigation [COBACABANA]). Two field tests were used to prove the playability of our game and assess its teaching effectiveness using postgame scores and self-assessment. Both test results give support to our game and highlight that it helps students to understand complex production control issues. Applying the simulation as part of an iterative design process not only ensured the pragmatic validity of our design, but also provided important insights on the production control systems being taught. During the application, we encountered several issues associated with the implementation of these production control systems in practice. In terms of theory, applying the simulation showed that there is a change in mindset required when switching † Corresponding Author. 568 Thürer et al. 569 from Kanban to COBACABANA, and physics synchronization is essential for logistics synchronization.

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Section: Field Tests Resultsmentioning

confidence: 99%

Classroom Simulations for Teaching Production Control in Nonrepetitive Contexts: Insights for Theory and Practice

Thürer

Cole

Hanna

et al. 2020

Decision Sci J Innov Edu

View full text Add to dashboard Cite

show abstract

“…Simulation games also fall into several categories based on the method of implementation (Grandzol & Grandzol, 2018): spreadsheet-based, tangible product, application software, manual, and online. Spreadsheet-based games are probably the most prevalent, due to the popularity of spreadsheet software, and its tight integration into a typical business curriculum.…”

Section: Literature Reviewmentioning

confidence: 99%

Mixed‐integer linear programming optimization for the Supply Chain Game

Shaltayev

2021

Decision Sci J Innov Edu

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In this article, we describe the use of linear programming in conjunction with an online simulation game in an undergraduate supply chain management class. Supply chain management is a required course for students enrolled in a Business Administration program with a concentration in management. It delivers a broad overview of the supply chain management discipline, using a simulation game by Responsive Learning Technologies to provide students with hands-on experience designing and managing a supply chain. In this teaching brief, I give an overview of the game and present the formulation of an accompanying mixed-integer linear programming model to design an optimal supply chain that meets customers, demand while maximizing company profit. Students use a spreadsheet template to develop their own implementation of the model and then apply the optimal solution during the simulation. Consequently, they gain an understanding of the role of network optimization in supply chain management. I conclude with recommendations for management of game activities using this model and a brief discussion of some of the issues to be monitored as the game is played.

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“…Thus, both demand and the knowledge of the technology are the main instigator of new technology adoption. The customer-vendor paradigm finds its origin in demand conditions rather than technology push [72]. Sepasgozar and Davis [4] explains that technology adoption is not an event occurring in one day; rather, it is a process involving a sequence of consecutive phases a construction company passes through up to the implementation phase as shown in Figure 2.…”

Section: Theoretical Framework and Gap In The Literaturementioning

confidence: 99%

Digital Construction Technology and Job-Site Equipment Demonstration: Modelling Relationship Strategies for Technology Adoption

Sepasgozar

Davis

2019

Buildings

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The construction technology market is competitive and complicated, due to the high-risk of digital technology utilisation in construction projects and the conservative character of construction companies. This complexity affects the process of job-site technology dissemination and adoption in which construction companies make decisions to purchase and utilise the new technology. The complexity is one of the reasons that many new remote technologies, positioning and locating systems, lasers and drones, 3D printing, and robots are not widely adopted in the short term, despite vendors making determined efforts to overcome this. Three objectives are investigated in this paper: (i) to define criteria for examining patterns of vendors’ strategies to support technology adoption; (ii) to present fact-based evidence of different vendors’ demonstration methods; and (iii) to present examples of different technology groups based on their required strategies. This paper presents the results of a longitudinal investigation of the construction technology market, including patterns of technology demonstration and a conceptual model of classifying vendors and their technologies in construction market places. The model involves the three most important factors that distinguish technology exhibitors: Physical appearance, Interpersonal relationship and Technology demonstration. Data was collected from technology exhibitions, involving randomly selected vendors. This data was analysed using hierarchical and c-means clustering techniques. The hard-clustering techniques resulted in vendors being placed in five classes based on the elements of the PIT framework. Fuzzy analysis shows how these classes fit into an underlying strategy spectrum. Understanding the strategies used in each class enables new vendors to select their own dissemination strategies based on their own particular circumstances. The practical implication of this study is to present a set of dissemination strategies to new technology stakeholders involved in Industry 4.0. The identified patterns of technology vendor strategies and the novel conceptual model contribute to the body of knowledge in technology diffusion.

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Chantey Castings: A Hands‐On Simulation to Teach Constraint Management and Demand‐Driven Supply Chain Approaches

Cited by 6 publications

References 24 publications

Classroom Simulations for Teaching Production Control in Nonrepetitive Contexts: Insights for Theory and Practice

Classroom Simulations for Teaching Production Control in Nonrepetitive Contexts: Insights for Theory and Practice

Mixed‐integer linear programming optimization for the Supply Chain Game

Digital Construction Technology and Job-Site Equipment Demonstration: Modelling Relationship Strategies for Technology Adoption

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