Pub Date : 2026-01-21DOI: 10.1109/TEM.2026.3656529
Xinyu Wang;Xinya Liu;Shuhua Zhang
Technological advances have substantially enhanced production flexibility in wind farm operations. This study examines how sponsors facing credit risk choose between flexible and rigid production policies and determine their expansion strategies. We develop a multiscenario optimal stopping model based on real options to characterize sponsors' decisions regarding production suspension, resumption, or default. Our findings indicate that flexible policies are preferred when credit risk is low, whereas higher credit risk makes rigid policies more advantageous. Enhancing production flexibility expands the range in which flexible policies remain optimal. Moreover, lower credit risk incentivizes earlier investment and expansion. Greater flexibility not only reinforces this effect but also promotes mode switching. Notably, under flexible policies, expansion can dynamically align with price signals and credit risks, whereas under rigid policies it relies solely on price fluctuations. Finally, a case study of China Datang New Energy validates the model's applicability. Robustness checks through comparative statics reveal that higher uncertainty suppresses mode switching but stimulates investment and expansion. These tests consistently confirm that flexible policies enable earlier investment and expansion, smaller capacity scales, and higher returns than rigid policies, regardless of volatility or credit risk levels. Overall, this study provides new managerial insights into balancing production flexibility and credit risk under uncertainty.
{"title":"Operational and Expansion Strategies of Wind Farms Under Uncertainty: The Impact of Credit Risk and Production Flexibility","authors":"Xinyu Wang;Xinya Liu;Shuhua Zhang","doi":"10.1109/TEM.2026.3656529","DOIUrl":"https://doi.org/10.1109/TEM.2026.3656529","url":null,"abstract":"Technological advances have substantially enhanced production flexibility in wind farm operations. This study examines how sponsors facing credit risk choose between flexible and rigid production policies and determine their expansion strategies. We develop a multiscenario optimal stopping model based on real options to characterize sponsors' decisions regarding production suspension, resumption, or default. Our findings indicate that flexible policies are preferred when credit risk is low, whereas higher credit risk makes rigid policies more advantageous. Enhancing production flexibility expands the range in which flexible policies remain optimal. Moreover, lower credit risk incentivizes earlier investment and expansion. Greater flexibility not only reinforces this effect but also promotes mode switching. Notably, under flexible policies, expansion can dynamically align with price signals and credit risks, whereas under rigid policies it relies solely on price fluctuations. Finally, a case study of China Datang New Energy validates the model's applicability. Robustness checks through comparative statics reveal that higher uncertainty suppresses mode switching but stimulates investment and expansion. These tests consistently confirm that flexible policies enable earlier investment and expansion, smaller capacity scales, and higher returns than rigid policies, regardless of volatility or credit risk levels. Overall, this study provides new managerial insights into balancing production flexibility and credit risk under uncertainty.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"73 ","pages":"1512-1527"},"PeriodicalIF":5.2,"publicationDate":"2026-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146175821","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-21DOI: 10.1109/TEM.2026.3656422
Siqi Wang;Zhen Li;Jianwei Liu;Xiaofei Zhang;Kee-Hung Lai
Strategically introducing artificial intelligence (AI) chatbots into online health communities (OHCs) to foster user engagement has become increasingly common, but it also creates competitive pressure and replacement risks for professional counselors who make similar prosocial contributions. We investigate how module-targeted AI chatbot deployment affects professional counselors’ prosocial contributions across a focal module (with AI deployment) and another neighbor module (without AI deployment). We developed a theoretical framework by integrating Protection Motivation Theory with the displacement effect, validating our conjectures using a longitudinal dataset from a leading Chinese OHC. Utilizing a difference-in-differences (DID) approach with rigorous robustness checks, we find that AI deployment significantly bolstered counselors’ prosocial contributions in the focal module, while neighbor module activity remained stable. The key mechanism underlying counselors’ heterogeneous responses lies in individual competence rather than economic incentives. Specifically, high-competence counselors exhibited a pronounced bifurcated response: they amplified both the quantity and semantic quality of their contributions in the focal module, while simultaneously retrenching along both dimensions in the neighbor module. Our findings reveal how counselors adapt their prosocial efforts when AI is deployed in a specific module and the displacement effects caused by such asymmetric intervention, providing practical insights for platform managers to deploy module-targeted AI chatbots effectively.
{"title":"Module-Targeted AI Chatbot Deployment and Counselors’ Prosocial Contributions in Online Health Community","authors":"Siqi Wang;Zhen Li;Jianwei Liu;Xiaofei Zhang;Kee-Hung Lai","doi":"10.1109/TEM.2026.3656422","DOIUrl":"https://doi.org/10.1109/TEM.2026.3656422","url":null,"abstract":"Strategically introducing artificial intelligence (AI) chatbots into online health communities (OHCs) to foster user engagement has become increasingly common, but it also creates competitive pressure and replacement risks for professional counselors who make similar prosocial contributions. We investigate how module-targeted AI chatbot deployment affects professional counselors’ prosocial contributions across a focal module (with AI deployment) and another neighbor module (without AI deployment). We developed a theoretical framework by integrating Protection Motivation Theory with the displacement effect, validating our conjectures using a longitudinal dataset from a leading Chinese OHC. Utilizing a difference-in-differences (DID) approach with rigorous robustness checks, we find that AI deployment significantly bolstered counselors’ prosocial contributions in the focal module, while neighbor module activity remained stable. The key mechanism underlying counselors’ heterogeneous responses lies in individual competence rather than economic incentives. Specifically, high-competence counselors exhibited a pronounced bifurcated response: they amplified both the quantity and semantic quality of their contributions in the focal module, while simultaneously retrenching along both dimensions in the neighbor module. Our findings reveal how counselors adapt their prosocial efforts when AI is deployed in a specific module and the displacement effects caused by such asymmetric intervention, providing practical insights for platform managers to deploy module-targeted AI chatbots effectively.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"73 ","pages":"1500-1511"},"PeriodicalIF":5.2,"publicationDate":"2026-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146175814","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-20DOI: 10.1109/TEM.2026.3656330
Gongbing Bi;Dang Wang;Pingfan Wang
Product deterioration poses significant challenges to inventory management and profitability. Highlighting the importance of effective promotion strategies, this article investigates two countermeasures for deteriorating goods: price promotion (price discount) and trade credit promotion (credit period extension), analyzing their differential impacts on mitigating value loss. While both strategies alleviate deterioration effects, their cost structures diverge: price promotion directly erodes marginal profit, whereas trade credit promotion incurs cash opportunity cost from deferred payments. Our findings reveal that both price and trade credit promotions can help mitigate the impact of deterioration and enhance the retailer’s profitability with different scopes of application. Specifically, trade credit promotion results in higher retailer profitability when the unit cash opportunity cost falls below a certain threshold; otherwise, price promotion becomes the more favorable strategy. This threshold inversely correlates with the selling price and positively relates to the sensitivity of market demand to the credit period. Furthermore, we find that the more profitable strategy—whether price promotion or trade credit promotion—not only enhances the retailer’s profitability but also improves consumer surplus, thereby creating a win-win outcome. An extended model accounting for consumer indifference to product deterioration reaffirms the distinct impacts of both promotion strategies while validating the robustness of the baseline model. This article offers managerial insights into how retailers choose and implement promotion strategies when selling deteriorating products.
{"title":"Optimal Promotion Strategies for Deteriorating Products: Price Discount Versus Credit Period Extension","authors":"Gongbing Bi;Dang Wang;Pingfan Wang","doi":"10.1109/TEM.2026.3656330","DOIUrl":"https://doi.org/10.1109/TEM.2026.3656330","url":null,"abstract":"Product deterioration poses significant challenges to inventory management and profitability. Highlighting the importance of effective promotion strategies, this article investigates two countermeasures for deteriorating goods: price promotion (price discount) and trade credit promotion (credit period extension), analyzing their differential impacts on mitigating value loss. While both strategies alleviate deterioration effects, their cost structures diverge: price promotion directly erodes marginal profit, whereas trade credit promotion incurs cash opportunity cost from deferred payments. Our findings reveal that both price and trade credit promotions can help mitigate the impact of deterioration and enhance the retailer’s profitability with different scopes of application. Specifically, trade credit promotion results in higher retailer profitability when the unit cash opportunity cost falls below a certain threshold; otherwise, price promotion becomes the more favorable strategy. This threshold inversely correlates with the selling price and positively relates to the sensitivity of market demand to the credit period. Furthermore, we find that the more profitable strategy—whether price promotion or trade credit promotion—not only enhances the retailer’s profitability but also improves consumer surplus, thereby creating a win-win outcome. An extended model accounting for consumer indifference to product deterioration reaffirms the distinct impacts of both promotion strategies while validating the robustness of the baseline model. This article offers managerial insights into how retailers choose and implement promotion strategies when selling deteriorating products.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"73 ","pages":"1602-1618"},"PeriodicalIF":5.2,"publicationDate":"2026-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146175818","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-19DOI: 10.1109/TEM.2026.3655547
Jéssica de Assis Dornelles;Alejandro Germán Frank
While most studies examine the implementation of digital technologies, this research investigates paradoxical tensions between workers and technology during the design stage and how acceptance strategies can support a smart working environment. We conducted a one-year longitudinal case study in a high-end furniture company, drawing on interviews, participant observations, and document analysis. Guided by paradox theory, we identified eight tensions and four acceptance strategies that help organizations navigate these contradictions. Besides identifying specific tensions at this stage, our study shows—through comparison with prior research—that some paradoxical categories are more pronounced and distinct during the technological design stage, while others persist throughout the entire digital transformation journey, spanning both technological design and implementation. This study expands understandings of paradoxical tensions in digital transformation by focusing on the technology design stage, which is largely underexplored in literature. It also offers practical guidance for aligning technology planning with Industry 5.0 principles.
{"title":"Anticipating Paradoxical Tensions in the Technological Design of Smart Working Environments","authors":"Jéssica de Assis Dornelles;Alejandro Germán Frank","doi":"10.1109/TEM.2026.3655547","DOIUrl":"https://doi.org/10.1109/TEM.2026.3655547","url":null,"abstract":"While most studies examine the implementation of digital technologies, this research investigates paradoxical tensions between workers and technology during the design stage and how acceptance strategies can support a smart working environment. We conducted a one-year longitudinal case study in a high-end furniture company, drawing on interviews, participant observations, and document analysis. Guided by paradox theory, we identified eight tensions and four acceptance strategies that help organizations navigate these contradictions. Besides identifying specific tensions at this stage, our study shows—through comparison with prior research—that some paradoxical categories are more pronounced and distinct during the technological design stage, while others persist throughout the entire digital transformation journey, spanning both technological design and implementation. This study expands understandings of paradoxical tensions in digital transformation by focusing on the technology design stage, which is largely underexplored in literature. It also offers practical guidance for aligning technology planning with Industry 5.0 principles.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"73 ","pages":"1573-1586"},"PeriodicalIF":5.2,"publicationDate":"2026-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146175878","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-16DOI: 10.1109/TEM.2026.3654944
Ziyi Xiong;Rong Liu;Chihoon Lee
Crypto crowdfunding has become a key financing channel for blockchain-based start-ups, yet ineffective project-investor communication contributes to fundraising failures. This study investigates how linguistic framing in project roadmaps, specifically, the presentation of achieved versus planned milestones, influences fundraising success. Drawing on construal level theory, we argue that achieved milestones benefit from concrete language, while planned milestones are more effective when conveyed through coherent language. We analyzed 1507 crypto crowdfunding campaigns and measured milestone concreteness and coherence using established computational linguistics techniques and large language models. Regression results show that fundraising success is positively associated with the concreteness of achieved milestones and the coherence of planned milestones. These findings suggest that aligning linguistic style with information hypotheticality (i.e., achieved vs. planned) can significantly enhance investor confidence, offering actionable guidance for start-up fundraising campaigns.
{"title":"Concrete Achievements and Coherent Plans: Storytelling of Roadmaps in Crypto Crowdfunding","authors":"Ziyi Xiong;Rong Liu;Chihoon Lee","doi":"10.1109/TEM.2026.3654944","DOIUrl":"https://doi.org/10.1109/TEM.2026.3654944","url":null,"abstract":"Crypto crowdfunding has become a key financing channel for blockchain-based start-ups, yet ineffective project-investor communication contributes to fundraising failures. This study investigates how linguistic framing in project roadmaps, specifically, the presentation of achieved versus planned milestones, influences fundraising success. Drawing on construal level theory, we argue that achieved milestones benefit from concrete language, while planned milestones are more effective when conveyed through coherent language. We analyzed 1507 crypto crowdfunding campaigns and measured milestone concreteness and coherence using established computational linguistics techniques and large language models. Regression results show that fundraising success is positively associated with the concreteness of achieved milestones and the coherence of planned milestones. These findings suggest that aligning linguistic style with information hypotheticality (i.e., achieved vs. planned) can significantly enhance investor confidence, offering actionable guidance for start-up fundraising campaigns.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"73 ","pages":"1619-1640"},"PeriodicalIF":5.2,"publicationDate":"2026-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146175907","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-16DOI: 10.1109/TEM.2026.3654537
Juanjuan Qin;Yanan Wang;Ziping Wang
This study investigate a multilevel supply chain subject to cap-and-trade regulation, involving a capital-constrained supplier, a manufacturer, and a retailer. Blockchain technology enhances trust among core firms, cross-level firms, and banks, thereby enabling financing for cross-level firms, and strengthening consumer trust in low-carbon products. This study explores the advance payment without blockchain technology ($AN$ mode), and two blockchain-enabled financing modes: advance payment with cross-level financing ($ACB$ mode) and advance payment with bank financing ($ABB$ mode). First, both $ABB$ and $ACB$ modes reduce carbon emissions more than the $AN$ mode, while which mode achieves greater total supply chain abatement depends on the bank interest rate and carbon abatement efficiency. Blockchain-enabled financing benefits all supply chain participants when blockchain operation costs are low, achieving win–win–win outcomes compared with the $AN$ mode. These results remain robust even when carbon abatement efficiencies are heterogeneous. Second, when all supply chain participants adopt blockchain, an equilibrium emerges where the supplier, manufacturer, and retailer choose the same financing mode. Interestingly, when blockchain operation costs are low and carbon abatement efficiency is high, the $ACB$ mode enables all participants to attain higher profits. Finally, when the supplier’s initial capital and the retailer’s interest rate are either low or high, the $ACB$ mode is the supplier’s optimal choice under blockchain technology. These findings provide managerial guidance for strategically selecting financing modes and adopting blockchain technology. The reliability of the conclusions is verified through sensitivity analyses.
{"title":"Emission Reduction and Financing Decisions in Blockchain-Enabled Supply Chains Under Cross-Level Financing","authors":"Juanjuan Qin;Yanan Wang;Ziping Wang","doi":"10.1109/TEM.2026.3654537","DOIUrl":"https://doi.org/10.1109/TEM.2026.3654537","url":null,"abstract":"This study investigate a multilevel supply chain subject to cap-and-trade regulation, involving a capital-constrained supplier, a manufacturer, and a retailer. Blockchain technology enhances trust among core firms, cross-level firms, and banks, thereby enabling financing for cross-level firms, and strengthening consumer trust in low-carbon products. This study explores the advance payment without blockchain technology (<inline-formula><tex-math>$AN$</tex-math></inline-formula> mode), and two blockchain-enabled financing modes: advance payment with cross-level financing (<inline-formula><tex-math>$ACB$</tex-math></inline-formula> mode) and advance payment with bank financing (<inline-formula><tex-math>$ABB$</tex-math></inline-formula> mode). First, both <inline-formula><tex-math>$ABB$</tex-math></inline-formula> and <inline-formula><tex-math>$ACB$</tex-math></inline-formula> modes reduce carbon emissions more than the <inline-formula><tex-math>$AN$</tex-math></inline-formula> mode, while which mode achieves greater total supply chain abatement depends on the bank interest rate and carbon abatement efficiency. Blockchain-enabled financing benefits all supply chain participants when blockchain operation costs are low, achieving win–win–win outcomes compared with the <inline-formula><tex-math>$AN$</tex-math></inline-formula> mode. These results remain robust even when carbon abatement efficiencies are heterogeneous. Second, when all supply chain participants adopt blockchain, an equilibrium emerges where the supplier, manufacturer, and retailer choose the same financing mode. Interestingly, when blockchain operation costs are low and carbon abatement efficiency is high, the <inline-formula><tex-math>$ACB$</tex-math></inline-formula> mode enables all participants to attain higher profits. Finally, when the supplier’s initial capital and the retailer’s interest rate are either low or high, the <inline-formula><tex-math>$ACB$</tex-math></inline-formula> mode is the supplier’s optimal choice under blockchain technology. These findings provide managerial guidance for strategically selecting financing modes and adopting blockchain technology. The reliability of the conclusions is verified through sensitivity analyses.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"73 ","pages":"1376-1389"},"PeriodicalIF":5.2,"publicationDate":"2026-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146082008","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pay-per-click (PPC) advertising has become a dominant tool for e-tailers to increase product exposure and boost sales. This study investigates a multiproduct newsvendor-like problem that jointly optimizes advertising budget allocation and order quantity decisions. A key feature of the problem is the consideration of the spillover effect of PPC advertising, where the demand for a product depends not only on its own ad clicks, but also on those of related products. We introduce a linear demand function to capture this dependence and validate its predictive power using real-world data. The theoretical analyses reveal that the spillover effect leads to nontrivial interactions between advertising and ordering decisions, while also amplifying demand uncertainty and complicating the computation of the optimal solutions. To address these challenges, we consider two heuristic methods. The first follows the common practice of neglecting the spillover effect, while the second simplifies it by approximating random ad clicks with their mean value. Numerical experiments demonstrate that the first heuristic can lead to substantial performance loss (up to 28.72%), whereas the second yields near-optimal solutions with performance loss within 1%. We further conduct robustness tests with respect to ad-click distributions, market conditions, and ad-click uncertainty to evaluate the performances of both heuristic methods under different scenarios. A sensitivity analysis to assess the impact of changing key parameters (e.g., the coefficients of spillover effects and advertising budget) is also developed to provide more managerial insights.
{"title":"Spillover Effect Matters: A Multiproduct Newsvendor-Like Model With Pay-Per-Click Advertising","authors":"Yugang Yu;Hongyan Zhang;Zhao Cai;Ye Shi;Qitong Zhao","doi":"10.1109/TEM.2026.3651194","DOIUrl":"https://doi.org/10.1109/TEM.2026.3651194","url":null,"abstract":"Pay-per-click (PPC) advertising has become a dominant tool for e-tailers to increase product exposure and boost sales. This study investigates a multiproduct newsvendor-like problem that jointly optimizes advertising budget allocation and order quantity decisions. A key feature of the problem is the consideration of the spillover effect of PPC advertising, where the demand for a product depends not only on its own ad clicks, but also on those of related products. We introduce a linear demand function to capture this dependence and validate its predictive power using real-world data. The theoretical analyses reveal that the spillover effect leads to nontrivial interactions between advertising and ordering decisions, while also amplifying demand uncertainty and complicating the computation of the optimal solutions. To address these challenges, we consider two heuristic methods. The first follows the common practice of neglecting the spillover effect, while the second simplifies it by approximating random ad clicks with their mean value. Numerical experiments demonstrate that the first heuristic can lead to substantial performance loss (up to 28.72%), whereas the second yields near-optimal solutions with performance loss within 1%. We further conduct robustness tests with respect to ad-click distributions, market conditions, and ad-click uncertainty to evaluate the performances of both heuristic methods under different scenarios. A sensitivity analysis to assess the impact of changing key parameters (e.g., the coefficients of spillover effects and advertising budget) is also developed to provide more managerial insights.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"73 ","pages":"1259-1273"},"PeriodicalIF":5.2,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146026355","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-12DOI: 10.1109/TEM.2026.3651889
Melanie E. Kreye
This research investigates how the supply-chain configurations of service offerings in business-to-consumer (B2C) markets enable manufacturers to implement circular practices. We differentiate offerings by service complexity as relevant starting points for this purpose. Following best practices in methodological rigor, we provide empirical evidence from five cases in the household-appliances industry. We detail the respective supply chain (SC) configurations of service offerings and of circular practices. In addition, we identify three mechanisms by which the SC configurations of service offerings connect to the SC configurations of circular practices: complement, enable, and undermine. This research contributes to the debate on the connections between servitization and circularity in B2C markets. Specifically, we identify the supply-chain configuration of service-based business models and circular practices showing their downstream and upstream effects. This enabled us to identify the mechanisms connecting service offerings to circular practices via their respective supply-chain configurations.
{"title":"Implementing Circular Practices Through Supply-Chain Configurations of Service Offerings for Consumer Products","authors":"Melanie E. Kreye","doi":"10.1109/TEM.2026.3651889","DOIUrl":"https://doi.org/10.1109/TEM.2026.3651889","url":null,"abstract":"This research investigates how the supply-chain configurations of service offerings in business-to-consumer (B2C) markets enable manufacturers to implement circular practices. We differentiate offerings by service complexity as relevant starting points for this purpose. Following best practices in methodological rigor, we provide empirical evidence from five cases in the household-appliances industry. We detail the respective supply chain (SC) configurations of service offerings and of circular practices. In addition, we identify three mechanisms by which the SC configurations of service offerings connect to the SC configurations of circular practices: complement, enable, and undermine. This research contributes to the debate on the connections between servitization and circularity in B2C markets. Specifically, we identify the supply-chain configuration of service-based business models and circular practices showing their downstream and upstream effects. This enabled us to identify the mechanisms connecting service offerings to circular practices via their respective supply-chain configurations.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"73 ","pages":"1224-1239"},"PeriodicalIF":5.2,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146026446","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study addresses the importance of enhancing the resilience of supply chain networks (SCNs) in the volatile supply chain environment. It explores how SCN topology characteristics and learning capabilities, such as “learn-to-prevent’’ and “learn-to-recover,’’ influence resilience, with a focus on the ripple effect during disruptions in SCNs. The research highlights oversight of link and partial node disruptions in existing studies, underscoring the need to account for these factors to inform decision-making and develop risk mitigation strategies. To examine the impact of SCNs' topological characteristics and learning capabilities on supply chain resilience (SCR), this study generates a diverse dataset of 5103 SCNs and simulates disruption and recovery processes. Using the Random Forest technique, the research identifies the significance of various factors in determining resilience, which is quantified by three metrics: average functionality, full impact, and recovery duration. Extensive robustness checks, including statistical testing, sensitivity analysis, repeated simulations, and validation through a real-world case study, confirm that the findings remain stable across alternative network structures, parameter settings, and disruption scenarios. The findings emphasize the importance of resilience capacities and learning capabilities acquired during disruptions, as well as specific network topology features, such as the number of strongly connected components, network type, and average path length. The proposed methodology is validated through a case study in Australia, illustrating how network characteristics can influence SCR. Decision-makers are urged to consider these associations for effectively enhancing resilience in SCNs.
{"title":"The Impact of Supply Chain Networks’ Structural Topology and Learning Capabilities on Resilience: A Simulation Study","authors":"Farhad Habibi;Ripon Kumar Chakrabortty;Alireza Abbasi","doi":"10.1109/TEM.2026.3651709","DOIUrl":"https://doi.org/10.1109/TEM.2026.3651709","url":null,"abstract":"This study addresses the importance of enhancing the resilience of supply chain networks (SCNs) in the volatile supply chain environment. It explores how SCN topology characteristics and learning capabilities, such as “learn-to-prevent’’ and “learn-to-recover,’’ influence resilience, with a focus on the ripple effect during disruptions in SCNs. The research highlights oversight of link and partial node disruptions in existing studies, underscoring the need to account for these factors to inform decision-making and develop risk mitigation strategies. To examine the impact of SCNs' topological characteristics and learning capabilities on supply chain resilience (SCR), this study generates a diverse dataset of 5103 SCNs and simulates disruption and recovery processes. Using the Random Forest technique, the research identifies the significance of various factors in determining resilience, which is quantified by three metrics: average functionality, full impact, and recovery duration. Extensive robustness checks, including statistical testing, sensitivity analysis, repeated simulations, and validation through a real-world case study, confirm that the findings remain stable across alternative network structures, parameter settings, and disruption scenarios. The findings emphasize the importance of resilience capacities and learning capabilities acquired during disruptions, as well as specific network topology features, such as the number of strongly connected components, network type, and average path length. The proposed methodology is validated through a case study in Australia, illustrating how network characteristics can influence SCR. Decision-makers are urged to consider these associations for effectively enhancing resilience in SCNs.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"73 ","pages":"1528-1543"},"PeriodicalIF":5.2,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146175835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-12DOI: 10.1109/TEM.2025.3648578
Muhammad Usman;Nadia Zahoor;Erhan Boğan;Muhammad Waheed Akhtar;Bekir Dedeoğlu
Given the growing emphasis on business sustainability and environmental management aimed at protecting the natural environment, this study, drawing insights from organizational information processing theory, investigates the direct association of artificial intelligence-supported Big Data analytics (AI-BDA) with organizations’ green core competencies as well as the indirect association through green data-driven decision-making culture (GDDC). In addition, the role of leader conscientiousness as an important boundary condition is examined. Data collected from 339 managers is analyzed using structural equation modeling in Mplus (8.8). Our findings indicate that AI-BDA has both direct and indirect positive relationships with green core competencies. Moreover, leader conscientiousness moderated the direct impact of AI-BDA on GDDC. Supplementary semi-structured interviews with 12 senior managers provide contextual validation and illustrate how AI-BDA, green data-driven culture, and leader conscientiousness jointly shape green core competencies in practice. Our research provides actionable insights that empower organizations to develop green core competencies, thereby enhancing their impact on initiatives aimed at preserving the natural environment. By integrating technological capabilities with leadership traits, this study highlights a pathway for organizations to align digital transformation with environmental sustainability goals, thereby advancing their corporate responses to environmental challenges.
{"title":"Big Data Analytics and Green Core Competencies: Important Role of Data-Driven Decision-Making Culture and Leader Conscientiousness","authors":"Muhammad Usman;Nadia Zahoor;Erhan Boğan;Muhammad Waheed Akhtar;Bekir Dedeoğlu","doi":"10.1109/TEM.2025.3648578","DOIUrl":"https://doi.org/10.1109/TEM.2025.3648578","url":null,"abstract":"Given the growing emphasis on business sustainability and environmental management aimed at protecting the natural environment, this study, drawing insights from organizational information processing theory, investigates the direct association of artificial intelligence-supported Big Data analytics (AI-BDA) with organizations’ green core competencies as well as the indirect association through green data-driven decision-making culture (GDDC). In addition, the role of leader conscientiousness as an important boundary condition is examined. Data collected from 339 managers is analyzed using structural equation modeling in Mplus (8.8). Our findings indicate that AI-BDA has both direct and indirect positive relationships with green core competencies. Moreover, leader conscientiousness moderated the direct impact of AI-BDA on GDDC. Supplementary semi-structured interviews with 12 senior managers provide contextual validation and illustrate how AI-BDA, green data-driven culture, and leader conscientiousness jointly shape green core competencies in practice. Our research provides actionable insights that empower organizations to develop green core competencies, thereby enhancing their impact on initiatives aimed at preserving the natural environment. By integrating technological capabilities with leadership traits, this study highlights a pathway for organizations to align digital transformation with environmental sustainability goals, thereby advancing their corporate responses to environmental challenges.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"73 ","pages":"1363-1375"},"PeriodicalIF":5.2,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146082075","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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