管理学最新文献

{"title":"Transforming supply chain operations: Unveiling the path ahead by leveraging artificial intelligence (AI) to drive the shift towards carbon neutrality (CN)","authors":"Li Zheng ,&nbsp;Rong Zhou ,&nbsp;Nidhi Singh ,&nbsp;Muhammad Zafar Yaqub ,&nbsp;Saeed Badghish","doi":"10.1016/j.techfore.2025.124280","DOIUrl":"10.1016/j.techfore.2025.124280","url":null,"abstract":"<div><div>The negative impact of carbon emissions has received greater attention and is a significant challenge. Recent research has focused on promoting CN and achieving CN goals through the use of advanced techniques. While there is some debate on the use and influence of different technologies, there is a limited exploration of the use of specific technologies, such as AI, in achieving CN, particularly in the supply chain (SC) domain. This research paper examines the intersection between AI-led CN and SC, exploring the multifaceted aspects that define this evolving landscape. This paper aims to unravel the complexities and outcomes surrounding the use of AI-led disruptive technologies to achieve CN in SC operations. The authors conducted a comprehensive review of 47 relevant studies to facilitate a critical synthesis of the literature. Based on an extensive literature review, the study identified various antecedents and consequences of AI-led CN goals, spanning a geographical expanse under the broad themes of Sustainable Energy, Digital and Technological Transformation, Biomass Conversion, Waste Management, and Carbon Forecasting and Accounting in the SC domain. The findings revealed several antecedents to AI-led CN goals, including discussion on energy supply issues, intelligent systems, access to green financial markets, and slag waste optimization, as well as a few consequences of such implementation, such as AI-based methods to monitor slag waste, biomass concerns, and carbon neutrality, among others. The study also developed a framework, highlighting various AI-led CN strategies at the optimization and operational stages, as well as several AI-led innovations and their importance. The study offers a few policy suggestions, such as designing emission reduction policies, encouraging public-private partnerships, developing a regulatory framework to promote the industrial transformation of intelligent buildings, and managing uncertainties related to slag waste, biomass, energy systems, and other SC issues to ensure proper implementation of AI-led CN systems in the SC domain.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"219 ","pages":"Article 124280"},"PeriodicalIF":12.9,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144680439","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Work-related technology use during nonwork time and its consequences: A resource-oriented perspective","authors":"Svenja Schlachter,&nbsp;Ilke Inceoglu,&nbsp;Almuth McDowall,&nbsp;Mark Cropley","doi":"10.1111/joop.70047","DOIUrl":"https://doi.org/10.1111/joop.70047","url":null,"abstract":"<p>Employees increasingly use information and communication technologies (i.e., ICTs) to work during nonwork time (e.g., responding to e-mails, taking calls), even when not contractually required. Despite potential work-related benefits, voluntary work-related ICT use can affect employees' recovery and well-being. Drawing on the conservation of resources theory and self-regulation, we argue that engaging in voluntary ICT use during workday evenings is a work-related resource investment, requiring self-regulatory resources. Consequently, employees lack such resources to regulate their attention away from work, thus experiencing reduced psychological detachment. This, in turn, can impede employees' ability to engage in mood repair regarding affective well-being at bedtime and the following morning. We propose that employees can alleviate this process through substituting and replacing self-regulatory resources by having control over their evening and good sleep quality, respectively. Conducting a daily diary study over five consecutive workdays and following mornings with 187 participants, we found negative indirect effects of voluntary ICT use on affective well-being the following morning, via reduced psychological detachment. Feeling in control during nonwork time and sleep quality mitigated these effects. Our study contributes to the conceptual understanding of voluntary ICT use and how this behaviour can be managed more actively by individuals.</p>","PeriodicalId":48330,"journal":{"name":"Journal of Occupational and Organizational Psychology","volume":"98 3","pages":""},"PeriodicalIF":4.9,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/joop.70047","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144672980","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Influence of Lighting on Perceived Product Size: The Role of Surface Curvature and Attention","authors":"Itrat Batool ,&nbsp;Patrick J.N. L’Espoir Decosta ,&nbsp;Hamish Simmonds ,&nbsp;Aaron Gazley","doi":"10.1016/j.jbusres.2025.115615","DOIUrl":"10.1016/j.jbusres.2025.115615","url":null,"abstract":"<div><div>While the affective and behavioural effects of bright lighting in retail settings have been widely explored, its influence on visual perception—particularly product size perception—remains overlooked. This research fills that gap by uncovering a novel link between bright lighting and object shape, showing how their interaction shapes consumer perception. Bridging two previously disconnected streams of literature—lighting and perceived product size—we demonstrate that under bright lighting, convex products are perceived as significantly larger, while concave products appear smaller. Across three controlled experiments, we find that bright lighting heightens visual attention, which amplifies the perceived size of products—but critically, only when the surface curvature is convex. These findings advance theoretical understanding of visual processing in retail environments and offer actionable insights for product display, packaging, and lighting design.</div></div>","PeriodicalId":15123,"journal":{"name":"Journal of Business Research","volume":"200 ","pages":"Article 115615"},"PeriodicalIF":10.5,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144679466","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Framework for regenerative entrepreneurship in tourism: fostering reciprocal relationships within place","authors":"Roosa Ridanpää","doi":"10.1080/14616688.2025.2535690","DOIUrl":"https://doi.org/10.1080/14616688.2025.2535690","url":null,"abstract":"","PeriodicalId":48115,"journal":{"name":"Tourism Geographies","volume":"17 1","pages":""},"PeriodicalIF":9.8,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144677956","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}

{"title":"Evaluation of the impact of defining observable time in real-world data on outcome incidence.","authors":"Clair Blacketer, Frank J DeFalco, Mitchell M Conover, Patrick B Ryan, Martijn J Schuemie, Peter R Rijnbeek","doi":"10.1093/jamia/ocaf119","DOIUrl":"https://doi.org/10.1093/jamia/ocaf119","url":null,"abstract":"<p><strong>Objective: </strong>In real-world data (RWD), defining the observation period-the time during which a patient is considered observable-is critical for estimating incidence rates (IRs) and other outcomes. Yet, in the absence of explicit enrollment information, this period must often be inferred, introducing potential bias.</p><p><strong>Materials and methods: </strong>This study evaluates methods for defining observation periods and their impact on IR estimates across multiple database types. We applied 3 methods for defining observation periods: (1) a persistence + surveillance window approach, (2) an age- and gender-adjusted method based on time between healthcare events, and (3) the min/max method. These were tested across 11 RWD databases, including both enrollment-based and encounter-based sources. Enrollment time was used as the reference standard in eligible databases. To assess the impact on epidemiologic results, we replicated a prior study of adverse event incidence, comparing IRs and calculating mean squared error between methods.</p><p><strong>Results: </strong>Incidence rates decreased as observation periods lengthened, driven by increases in the person-time denominator. The persistence + surveillance method produced estimates closest to enrollment-based rates when appropriately balanced. The min/max approach yielded inconsistent results, particularly in encounter-based databases, with greater error observed in databases with longer time spans.</p><p><strong>Discussion: </strong>These findings suggest that assumptions about data completeness and population observability significantly affect incidence estimates. Observation period definitions substantially influence outcome measurement in RWD studies.</p><p><strong>Conclusion: </strong>Standardized, transparent approaches are necessary to ensure valid, reproducible results-especially in databases lacking defined enrollment.</p>","PeriodicalId":50016,"journal":{"name":"Journal of the American Medical Informatics Association","volume":" ","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144692229","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"When help backfires: Exploring the unexpected consequences of helpful reviews on word-of-mouth","authors":"Jonghwan Kim,&nbsp;Shijin Yoo","doi":"10.1016/j.jretconser.2025.104422","DOIUrl":"10.1016/j.jretconser.2025.104422","url":null,"abstract":"<div><div>While helpful reviews are generally seen as catalysts for consumer engagement, their unexpected consequences on electronic word-of-mouth (eWOM) remain underexplored. This paper examined the potential negative impacts of helpful reviews. Although there is a prevailing view that review helpfulness positively influences consumer engagement, the authors addressed that helpful initial reviews may hamper the volume of review. They formulated and tested hypotheses on the potential negative effects of helpful initial reviews, contributing to a deeper understanding of the complex dynamics of online consumer behavior in eWOM. Drawing on product review data from two distinct e-commerce platforms (Amazon and Yelp), two studies investigated the influence of the perceived helpfulness of existing reviews on subsequent review writing. Further, the results demonstrated that the negative effect of helpful reviews was significantly moderated by product type, review length, and reviewer reputation. Overall, this study showed that an increase in review helpfulness may not always result in beneficial outcomes, which has key implications for online merchants, e-commerce platform providers, and consumers.</div></div>","PeriodicalId":48399,"journal":{"name":"Journal of Retailing and Consumer Services","volume":"87 ","pages":"Article 104422"},"PeriodicalIF":11.0,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144678792","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of dual routes of information cues on consumers' willingness to pay a premium in cross-border e-commerce: The role of product involvement and nutrition safety awareness","authors":"Bei Zhang ,&nbsp;Jichan Zhu ,&nbsp;Ruqiu Ma ,&nbsp;Yuanzhen Huang","doi":"10.1016/j.jretconser.2025.104428","DOIUrl":"10.1016/j.jretconser.2025.104428","url":null,"abstract":"<div><div>Although information cues are crucial to consumers' willingness to pay a premium, the mechanism remains unclear. Addressing this gap, we take cross-border e-commerce food consumption as a context to investigate how information cues affect consumers' willingness to pay a premium by the Elaboration Likelihood Model (ELM), and examine the mediating role of product involvement and the moderating role of nutrition safety awareness. Data from 535 consumers in China are analyzed through a combined method with partial least squares structural equation modelling (PLS-SEM) and artificial neural network (ANN). Results show that the central and peripheral routes of information cues exert dual positive influences on product involvement, which in turn positively affects the willingness to pay a premium. We also find that nutrition safety awareness reinforces the effect of product involvement on willingness to pay a premium. Additionally, multigroup analysis suggests gender heterogeneity in the above mechanisms among consumer groups. These conclusions provide practical references for cross-border e-commerce food retailers to optimize their food lead strategies, differentiate their marketing for different genders.</div></div>","PeriodicalId":48399,"journal":{"name":"Journal of Retailing and Consumer Services","volume":"87 ","pages":"Article 104428"},"PeriodicalIF":11.0,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144678879","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Leveraging xAI for enhanced surrender risk management in life insurance products","authors":"Lluís Bermúdez ,&nbsp;David Anaya ,&nbsp;Jaume Belles-Sampera","doi":"10.1016/j.iedeen.2025.100286","DOIUrl":"10.1016/j.iedeen.2025.100286","url":null,"abstract":"<div><div>Explainable Artificial Intelligence (xAI) plays a crucial role in enhancing our understanding of decision-making processes within black-box Machine Learning models. Our objective is to introduce various xAI methodologies, providing risk managers with accessible approaches to model interpretation. To exemplify this, we present a case study focused on mitigating surrender risk in insurance savings products. We begin by using real data from universal life policies to build logistic regression and tree-based models. Using a range of xAI techniques, we gain valuable insight into the inner workings of tree-based models. We then propose a novel supervised clustering approach that integrates Shapley values with a Kohonen neural network (KNN). The process involves three main steps: computing Shapley values from a supervised tree-based model; clustering individuals into homogeneous profiles using an unsupervised KNN; and interpreting these profiles with a supervised decision tree model. Finally, we present several key findings derived from the application of xAI techniques, which have the potential to enhance surrender risk management practices.</div></div>","PeriodicalId":45796,"journal":{"name":"European Research on Management and Business Economics","volume":"31 3","pages":"Article 100286"},"PeriodicalIF":7.1,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144679384","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}

{"title":"An interpretable two-stage adaptive deep learning model for humanitarian aid information prediction and emergency response support","authors":"Yi Feng ,&nbsp;Xinwei Wang ,&nbsp;Dujuan Wang ,&nbsp;Yunqiang Yin ,&nbsp;Joshua Ignatius","doi":"10.1016/j.techfore.2025.124293","DOIUrl":"10.1016/j.techfore.2025.124293","url":null,"abstract":"<div><div>Diverse modes of information in social media posts during emergency responses collectively present an opportunity to advance artificial intelligence (AI) technologies to promote the integration of AI in humanitarian aid operations. To accurately identify humanitarian aid information and its categories, and to facilitate effective emergency responses, we first designed a two-stage humanitarian aid information prediction framework (THAIP). The first stage identifies humanitarian aid information and the second stage predicts the specific categories of information. We then developed an interpretable two-stage adaptive deep learning model (ITADL) based on THAIP, which adaptively determines the optimal data modality, model structure, and parameters based on the tasks at different stages. When applied to a real-world dataset from the social media platform Twitter in the context of emergency response, THAIP and ITADL achieved superior performance compared to models using a single-stage framework and several other deep learning models. Furthermore, the responses predicted by ITADL are interpreted at both global and local levels, enhancing the model's interpretability and providing valuable decision support for humanitarian aid planning and emergency response.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"219 ","pages":"Article 124293"},"PeriodicalIF":12.9,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144680441","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Novel Grey Causal Modelling (GCM) Approach to Enhance Resource Efficiency and Minimizing Waste in the Manufacturing Supply Chain Through Circular Economy","authors":"Thakur Singh Kharayat, Himanshu Gupta","doi":"10.1002/bse.70087","DOIUrl":"https://doi.org/10.1002/bse.70087","url":null,"abstract":"The manufacturing supply chain is under increasing pressure to enhance resource efficiency and minimize waste, driven by rising environmental concerns and resource scarcity. Despite various sustainability initiatives, a significant research gap exists in understanding the interdependencies of Circular Economy (<jats:sc>CE</jats:sc>) factors that influence both resource efficiency and waste reduction. To address this gap, the present study aims to explore the key <jats:sc>CE</jats:sc> factors that can simultaneously improve resource efficiency and minimize waste, using the novel Grey Causal Modelling (GCM) approach. The study focuses on critical <jats:sc>CE</jats:sc> factors, including Material Substitution, Product Lifecycle Extension, Digital Technologies for <jats:sc>CE</jats:sc>, Water Efficiency and Recycling, Stakeholder Collaboration, Design for Disassembly and Closed‐Loop Supply Chains. The GCM methodology is applied to model the causal relationships among these factors, providing a comprehensive analysis of their interactions and overall impact. The findings highlight that Material Substitution is the most effective factor in reducing environmental impact, while Product Lifecycle Extension and Digital Technologies are crucial for optimizing real‐time resource usage and waste minimization. Additionally, Stakeholder Collaboration and Design for Disassembly play pivotal roles in fostering circularity and operational efficiency. This research offers valuable implications for industry leaders and policymakers by providing a structured framework to achieve enhanced resource efficiency and waste reduction in manufacturing. The study contributes both to the theoretical understanding of <jats:sc>CE</jats:sc> in the manufacturing sector and to the development of practical strategies for achieving sustainability goals.","PeriodicalId":9518,"journal":{"name":"Business Strategy and The Environment","volume":"115 1","pages":""},"PeriodicalIF":13.4,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144677358","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}