{"title":"Transformative teaching in management statistics: Integrating real-world experiences and artificial intelligence","authors":"Kate Z. Williams, Tatiana Rudchenko","doi":"10.1111/dsji.70019","DOIUrl":"https://doi.org/10.1111/dsji.70019","url":null,"abstract":"<p>Traditional lecture-based teaching methods can fall short of preparing students for the complexities of modern workplaces. With the arrival of generative AI (GenAI) in both workplaces and academia, faculty must choose whether and how to introduce students to the powers of artificial intelligence. This teaching brief explores the implementation of a series of scaffolded lessons using GenAI in a quantitative, undergraduate operations management course. Leveraging Fink's theory of significant learning and Kuh's High Impact Practices (HIPs), the initiative integrates real-world applications of artificial intelligence to enhance student learning and career readiness. This brief explains how the teaching innovation allowed students to compare the practical value of Excel versus ChatGPT in conducting statistical analysis. Industry experts and a site visit provided insights into the use of generative AI in business contexts. Results indicate that these course enhancements elevate student interest in operations management and business analytics and offer a model for future improvements in business education.</p>","PeriodicalId":46210,"journal":{"name":"Decision Sciences-Journal of Innovative Education","volume":"24 1-2","pages":""},"PeriodicalIF":1.0,"publicationDate":"2026-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/dsji.70019","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147715055","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Lawrence V. Snyder, Karmel S. Shehadeh, Luis J. Novoa
{"title":"The Burrito Optimization Game: An educational resource for optimization in operations research, business analytics, and supply chain management","authors":"Lawrence V. Snyder, Karmel S. Shehadeh, Luis J. Novoa","doi":"10.1111/dsji.70018","DOIUrl":"https://doi.org/10.1111/dsji.70018","url":null,"abstract":"<p>The Burrito Optimization Game is a fun, free, and interactive online game that introduces learners to basic concepts behind mathematical optimization (MO) in the fields of operations research (OR), business analytics (BA), and supply chain management (SCM). In the game, players drag and drop burrito trucks onto a city map to serve customers and maximize the burrito company's profits. The game presents a classic MO challenge called a facility location problem. This article discusses an experiment to explore the effectiveness of the game as an aid for teaching MO in a classroom environment. Results show that the game effectively builds understanding and confidence in MO, while also reinforcing prior knowledge when paired with instructor-guided discussion.</p>","PeriodicalId":46210,"journal":{"name":"Decision Sciences-Journal of Innovative Education","volume":"24 1-2","pages":""},"PeriodicalIF":1.0,"publicationDate":"2026-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147715057","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Evaluating stakeholder preferences for MBA programs in Nepal post-COVID-19: An application of the Fuzzy Analytical Hierarchy Process (FAHP)","authors":"Sanjaya Pudasaini, Sarinpas Kornwattanakit","doi":"10.1111/dsji.70021","DOIUrl":"https://doi.org/10.1111/dsji.70021","url":null,"abstract":"<p>This study employs the Fuzzy Analytical Hierarchy Process (FAHP) to assess stakeholder preferences regarding MBA program attributes and delivery modes, specifically online versus on-site, in the post-COVID-19 context of Nepal. Data were collected from three core stakeholder groups: Academic Bodies (faculty and administrators), Business Sector professionals (employers and HR managers), and Decision-Makers (students, alumni, applicants, and parents). Results reveal distinct value orientations: Academic Bodies prioritized curricular frameworks and instructional quality, showing a slight preference for online delivery; the Business Sector emphasized adaptive learning and job readiness, favoring on-site programs; Decision-Makers focused on employability and cost, also preferring on-site formats. The findings provide a structured, comparative view of stakeholder priorities and delivery preferences, offering evidence-based guidance for reforming MBA programs. This study demonstrates the utility of FAHP in triangulating stakeholder input and enhancing policy decisions in management education within developing contexts.</p>","PeriodicalId":46210,"journal":{"name":"Decision Sciences-Journal of Innovative Education","volume":"24 1-2","pages":""},"PeriodicalIF":1.0,"publicationDate":"2026-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147715056","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Application of recurrent neural networks in demand forecasting: A teaching brief","authors":"Charles Changyue Luo","doi":"10.1111/dsji.70017","DOIUrl":"https://doi.org/10.1111/dsji.70017","url":null,"abstract":"<p>Accurate demand forecasting is critical for optimizing supply chains, yet traditional statistical models struggle with complex, nonlinear demand patterns. Recurrent Neural Networks (RNNs) offer a powerful alternative by capturing sequential dependencies and adapting to shifting trends. However, RNNs steep learning curve presents challenges for business students with limited technical backgrounds and instructors with varying technical expertise. This study responds to such challenges by developing a structured instructional framework that bridges the gap between traditional forecasting and RNN-based techniques in business education. Through a scaffolded learning approach with comprehensive implementation support, students progressively transition from statistical models to hands-on RNN implementation using Python. Pre-module and post-module assessments demonstrate significant gains in conceptual understanding, technical proficiency, and the ability to apply RNN-driven forecasts in decision-making contexts. A high level of student engagement further reinforces the effectiveness of this approach. This study contributes to the literature by advancing RNN education beyond purely technical considerations through the development of a structured instructional framework accessible to business students with limited programming experience and instructors across diverse institutional contexts. By establishing an adaptable educational model, this study facilitates the integration of RNN-driven forecasting into business curricula, enhancing students' ability to apply machine learning techniques in real-world contexts.</p>","PeriodicalId":46210,"journal":{"name":"Decision Sciences-Journal of Innovative Education","volume":"24 1-2","pages":""},"PeriodicalIF":1.0,"publicationDate":"2026-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147715059","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Designing a curriculum for AI prompting strategy for business decision-makers—A qualitative approach","authors":"Pavankumar Mulgund, Raghvendra Singh, Srikanth Venkatesan, Sagarika Suresh Thimmanayakanapalya, Srikanth Venkatesan","doi":"10.1111/dsji.70020","DOIUrl":"https://doi.org/10.1111/dsji.70020","url":null,"abstract":"<p>Prompt engineering has emerged as a critical skill for optimizing interactions with Large Language Models (LLMs) across diverse applications. Despite its growing influence in the commercial sector, this discipline remains underrepresented in academic curricula, particularly within business schools. To address this gap, we present a comprehensive syllabus for an introductory prompt engineering course, tailored specifically for future digital product designers and managers. This course equips students with the skills to harness LLMs effectively, transforming them into valuable tools for problem-solving and innovation. By detailing the course's motivation, objectives, key assignments, and expected outcomes, this article demonstrates how integrating prompt engineering education can prepare business students to navigate and lead in an AI-driven marketplace, ultimately bridging the divide between academic learning and industry demands.</p>","PeriodicalId":46210,"journal":{"name":"Decision Sciences-Journal of Innovative Education","volume":"24 1-2","pages":""},"PeriodicalIF":1.0,"publicationDate":"2026-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147715058","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Preparing for tomorrow's supply chain leaders today in the Industry 4.0 era: Student perceptions on learning modes","authors":"Pedro M. Reyes, John K. Visich","doi":"10.1111/dsji.70016","DOIUrl":"https://doi.org/10.1111/dsji.70016","url":null,"abstract":"<p>Preparing for tomorrow's supply chain leaders today involves an understanding of how students perceive the educational value of classroom learning approaches. To better understand how to prepare our students for the Industry 4.0 era, we surveyed current and former students on their perceptions of pedagogical methods that contributed to their learning and preparation to enter the workforce as supply chain management professionals. Results from former students, who are working in the supply chain management field, indicate that real-world teaching methods have a higher impact on learning than methods that are not as real-world. However, both groups rated guest speakers as the most effective learning method and lectures as the least effective. We offer an exploratory study motivated by students’ informal post-discussion of learning via Zoom during COVID-19. This article offers insights into how teachers should deliver supply chain content based on the student's perception of learning, an approach that will prepare students for supply chain management careers in the Industry 4.0 era.</p>","PeriodicalId":46210,"journal":{"name":"Decision Sciences-Journal of Innovative Education","volume":"23 4","pages":""},"PeriodicalIF":1.0,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/dsji.70016","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145062698","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Andrea Ferrari, Anna Corinna Cagliano, Giovanni Zenezini, Antonio Carlin, Giulio Mangano
{"title":"Learning factory in logistics: Evaluation of the effects of a hands-on experience for automated warehouse processes","authors":"Andrea Ferrari, Anna Corinna Cagliano, Giovanni Zenezini, Antonio Carlin, Giulio Mangano","doi":"10.1111/dsji.70015","DOIUrl":"https://doi.org/10.1111/dsji.70015","url":null,"abstract":"<p>In recent years, automated warehouses have become increasingly important to meet the rising demand of supply chain operations. Despite their growing relevance to industry, these systems remain largely underrepresented in academic settings, which contributes to a significant gap in student knowledge and preparedness. Traditional educational approaches often fail to equip future professionals with the practical skills required by modern logistics systems. While the learning factory paradigm partially addresses this gap, it typically places limited emphasis on logistics processes. To bridge this divide between theory and industrial practice, a hands-on learning experience was conducted in a logistics-focused learning factory involving Bachelor's and Master's engineering students. A structured questionnaire was administered to evaluate students’ perceptions of automated warehouses, and statistical methods were employed to analyze both the short- and medium-term impacts of the experience. Findings revealed a strong interest among students in industrial logistics, despite limited prior exposure to automation technologies. Consistent with previous research, the hands-on approach was particularly effective for Master's students, highlighting its potential as a valuable educational tool in logistics engineering.</p>","PeriodicalId":46210,"journal":{"name":"Decision Sciences-Journal of Innovative Education","volume":"23 4","pages":""},"PeriodicalIF":1.0,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/dsji.70015","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144998680","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Piloting with data: Flying into business analytics disciplinary knowledge","authors":"Ellen Belitzky, Yevgeniya Rivers","doi":"10.1111/dsji.70013","DOIUrl":"https://doi.org/10.1111/dsji.70013","url":null,"abstract":"<p>Flying a paper airplane as a standalone activity is hardly a novel instructional practice. However, in a typical university business analytics course where most work is on a computer, such a tactile experience is innovative. Aiming to build a paper airplane as an artifact, measure and record its characteristics, and report results provides an engaging opportunity for students to simulate a supply chain work experience. The paper airplane competition described in this brief provides instructors freedom within a framework to customize the practice of data acquisition for management decision-making. The illustration of key concepts in operations and supply chain management leads students to content and experiences consistent with components of the Education 4.0 framework. Course data include high self-reported levels of engagement; thus, we recommend using the paper airplane activity to demonstrate the business analytics process from data acquisition through visualization.</p>","PeriodicalId":46210,"journal":{"name":"Decision Sciences-Journal of Innovative Education","volume":"23 4","pages":""},"PeriodicalIF":1.0,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144935098","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Valerie L. Christian, Michael Jijin Zhang, Tuvana Rua, Jeanine K. Andreassi
{"title":"Winning the human resources challenge when expanding internationally: Focus on China","authors":"Valerie L. Christian, Michael Jijin Zhang, Tuvana Rua, Jeanine K. Andreassi","doi":"10.1111/dsji.70012","DOIUrl":"https://doi.org/10.1111/dsji.70012","url":null,"abstract":"<p>As educators, we seek engaging ways to demonstrate the crucial importance of developing appropriate management (HR) practices when undertaking international expansion. In this exercise, teams are asked to formulate and justify human resource/talent management policy modifications that contribute to a competitive advantage for a hypothetical North American niche grocery chain (Friendly & Fresh Foods) planning expansion into China. The exercise's unique value is its focus on the interconnectedness between business strategy, talent management, and culture in helping to “win” the local challenge when entering an unfamiliar territory where global leaders may need to adapt both competitive strategy and cultural practices to achieve business entry success. Recommendations are honed after consideration of their assigned home country's business model (differentiation or cost leadership) and the host country's culture. The choice of China as the expansion country serves to magnify the “distances” that must be examined when expanding internationally, in this case when a North American operation decides to expand its operations to China. The exercise's theoretical foundation is informed by international business, global human resource management, and cultural research. The exercise's effectiveness is well supported by graduate students who have experienced the exercise and by faculty evaluations of team presentations.</p>","PeriodicalId":46210,"journal":{"name":"Decision Sciences-Journal of Innovative Education","volume":"23 4","pages":""},"PeriodicalIF":1.0,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144935097","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Anil Singh, Vikram Bhadauria, Lysette Margaret D'souza, Vimlesh Prabhu Desai
{"title":"Who gets how much? Customer segmentation during shortages","authors":"Anil Singh, Vikram Bhadauria, Lysette Margaret D'souza, Vimlesh Prabhu Desai","doi":"10.1111/dsji.70014","DOIUrl":"https://doi.org/10.1111/dsji.70014","url":null,"abstract":"<p>Supply chain disruptions can lead to shortages. To manage this risk, companies often adopt a customer segmentation strategy to prioritize customers when confirming orders. To protect the limited supply for important customers, strategic segments are created, where some segments are given priority at the expense of other segments. In enterprise resource planning (ERP) software, this process is behind the scenes and automated, meaning that students do not have the opportunity to grasp the logic and process involved. To extend student knowledge in this area, we developed an exercise through which students can learn the underlying rationale behind the customer segmentation strategy. In the exercise, students prioritize orders from current and new customers based on the customer segment. The results of a survey on this exercise provided evidence of student learning. Modeling the process in spreadsheets helps students gain knowledge and skills in automated backorder processing in ERP systems.</p>","PeriodicalId":46210,"journal":{"name":"Decision Sciences-Journal of Innovative Education","volume":"23 4","pages":""},"PeriodicalIF":1.0,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/dsji.70014","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144935203","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}