Technovation最新文献_第5页

Digital divide and artificial intelligence for health 数字鸿沟和人工智能促进健康

IF 10.9 1区管理学

Technovation Pub Date : 2026-03-01 Epub Date: 2025-11-08 DOI: 10.1016/j.technovation.2025.103392

Jean Clara , Bussotti Jean-Flavien , Cecere Grazia , Omrani Nessrine , Papotti Paolo

{"title":"Digital divide and artificial intelligence for health","authors":"Jean Clara , Bussotti Jean-Flavien , Cecere Grazia , Omrani Nessrine , Papotti Paolo","doi":"10.1016/j.technovation.2025.103392","DOIUrl":"10.1016/j.technovation.2025.103392","url":null,"abstract":"<div><div>Social media platforms have become key intermediaries for ad campaigns, but concerns persist regarding the veracity of information presented in ads. In the health sector, false or unsupported claims in ad content can have real-world public health consequences. On these platforms, the display of ads is managed by recommendation systems that match the content of the ad to the interests of the user. This paper investigates whether the use of AI algorithms to recommend ads on social media platforms may help progress toward the Sustainable Development Goals (SDGs). We collected ads across all US states on Meta and Instagram during a period marked by increased public health concerns. Using a fine-tuned deep learning model, we fact-checked the content of these ads. The results of the fact-check show that only 0.2 % of the ads were classified as misinformation, and 15.41 % of the ads were classified as ambiguous. Both types of ads are less likely to be recommended to users located in wealthier states especially when health-related. Also, health-related ads classified as misinformation are more likely to be recommended to users in states with high percentage of people without health insurance. We argue that the use of recommendation systems contributes to widening the digital divide, which can hinder the achievement of SDGs.</div></div>","PeriodicalId":49444,"journal":{"name":"Technovation","volume":"151 ","pages":"Article 103392"},"PeriodicalIF":10.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145467478","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}

引用次数: 0

Leveraging AI and generative AI in urban design and planning: Unveiling advantages and challenges through problem structuring methods 在城市设计和规划中利用人工智能和生成式人工智能：通过问题结构化方法揭示优势和挑战

IF 10.9 1区管理学

Technovation Pub Date : 2026-03-01 Epub Date: 2025-12-27 DOI: 10.1016/j.technovation.2025.103465

Amali Çipi , Neuza C.M.Q.F. Ferreira , Fernando A.F. Ferreira , João J.M. Ferreira , Florentin Smarandache

{"title":"Leveraging AI and generative AI in urban design and planning: Unveiling advantages and challenges through problem structuring methods","authors":"Amali Çipi , Neuza C.M.Q.F. Ferreira , Fernando A.F. Ferreira , João J.M. Ferreira , Florentin Smarandache","doi":"10.1016/j.technovation.2025.103465","DOIUrl":"10.1016/j.technovation.2025.103465","url":null,"abstract":"<div><div>The integration of Artificial Intelligence (AI) in general—and its subfield Generative AI (GenAI) in particular—into urban design and planning is revolutionizing traditional methodologies, providing innovative solutions to complex challenges in city development. Despite their transformative potential, existing research underscores a critical need to better understand the multifaceted advantages and challenges associated with these technologies. This study addresses this gap by investigating the causal relationships between the advantages and challenges of AI and GenAI integration in urban design and planning. Leveraging a novel combination of cognitive mapping and neutrosophic DEcision-MAking Trial and Evaluation Laboratory (DEMATEL), the research identifies and evaluates key factors shaping this integration. The findings reveal that dynamic digital city simulations and scenario modeling emerge as the most significant advantages, underscoring their capacity to drive data-informed innovation in urban development. Conversely, ethical concerns surface as the most critical challenge, exhibiting strong interdependencies with other issues, including the “black box” nature of AI systems and the biases embedded in training data. This study provides a comprehensive framework for understanding the interplay between these factors, offering actionable insights to guide both academic research and practical implementation. By addressing a pressing need in the field, the research paves the way for more responsible and effective applications of AI and GenAI in creating smarter, more sustainable urban environments.</div></div>","PeriodicalId":49444,"journal":{"name":"Technovation","volume":"151 ","pages":"Article 103465"},"PeriodicalIF":10.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145839497","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}

引用次数: 0

Balancing resilience and circularity in an artificial intelligence-augmented humanitarian aid supply chain: A practice-based view of Yin–Yang dialectical systems 在人工智能增强的人道主义援助供应链中平衡弹性和循环：基于实践的阴阳辩证系统观点

IF 10.9 1区管理学

Technovation Pub Date : 2026-03-01 Epub Date: 2025-11-21 DOI: 10.1016/j.technovation.2025.103427

Tachia Chin , Zhibin Zhang , Asif Nazrul , Shouyang Wang

{"title":"Balancing resilience and circularity in an artificial intelligence-augmented humanitarian aid supply chain: A practice-based view of Yin–Yang dialectical systems","authors":"Tachia Chin , Zhibin Zhang , Asif Nazrul , Shouyang Wang","doi":"10.1016/j.technovation.2025.103427","DOIUrl":"10.1016/j.technovation.2025.103427","url":null,"abstract":"<div><div>Escalating climate change and geopolitical conflicts are widening humanitarian crises, creating an urgent need for AI-enabled humanitarian aid supply chains (HASCs) that are both resilient and circular. However, in practice, resilience and circularity often compete for crucial resources. To address this issue, this paper conceptualizes an AI-assisted HASC as a stratified system spanning governments, humanitarian organizations, and affected populations. It adopts a practice-based, dialectical systems view grounded in Yin–Yang philosophy to explore the dynamic balance of resilience and circularity in AI-assisted HASCs in different emergencies. More specifically, we create a Yin–Yang dialectical strategic map that characterises eight resource positions with various contradictions between the resource slack and the constraints in an AI-assisted HASC. Based on this, we propose eight possible strategies to resolve the above-mentioned resource tensions. To achieve a better understanding, we also construct a simulation model to examine the applicability of our novel paradigm. The key contribution lies in using an unconventional, practice-oriented Yin-Yang dialectical systems view to holistically explain how to balance resource slack and constraints while co-building resilience and circularity in AI-assisted HASCs. Practically, it highlights leveraging evolving AI as digital innovation to tackle traditional HASC challenges involving resource availability, environmental pressures, and societal concerns.</div></div>","PeriodicalId":49444,"journal":{"name":"Technovation","volume":"151 ","pages":"Article 103427"},"PeriodicalIF":10.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145569259","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}

引用次数: 0

Manifoldness of services firms: Did R&D lead to better performance after the global financial crisis? 服务业多元性：全球金融危机后研发是否带来更好的绩效？

IF 10.9 1区管理学

Technovation Pub Date : 2026-03-01 Epub Date: 2025-11-17 DOI: 10.1016/j.technovation.2025.103426

Sihong Wu , Rekha Rao-Nicholson , Yiyi Su , Di Fan

{"title":"Manifoldness of services firms: Did R&D lead to better performance after the global financial crisis?","authors":"Sihong Wu , Rekha Rao-Nicholson , Yiyi Su , Di Fan","doi":"10.1016/j.technovation.2025.103426","DOIUrl":"10.1016/j.technovation.2025.103426","url":null,"abstract":"<div><div>While prior research on service innovation has primarily emphasized R&D drivers and the characteristics of novel service offerings, limited attention has been given to how R&D impacts firm performance across distinct service sub-sectors—particularly during and after periods of economic disruption such as the global financial crisis (GFC). Adopting a service systems framework, this study classifies service firms according to two dimensions: the degree of service intangibility and the extent of customer involvement. Leveraging an unbalanced panel dataset spanning 2003 to 2013, the analysis investigates how returns on R&D investments vary across different service industry categories and how these patterns shift in the aftermath of the GFC. Results indicate that R&D yields positive returns across both classification criteria, though the effect is more pronounced for firms delivering intangible services and those with intensive customer participation. Post-GFC, however, the advantage of R&D investment appears greater among firms offering more tangible services. Moreover, service providers characterized by high customer engagement continued to derive superior R&D benefits in the post-crisis era. These insights contribute to both theoretical advancement and managerial practice, while also suggesting several avenues for future inquiry.</div></div>","PeriodicalId":49444,"journal":{"name":"Technovation","volume":"151 ","pages":"Article 103426"},"PeriodicalIF":10.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145569325","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}

引用次数: 0

Harnessing artificial intelligence for ambidextrous innovation: Contingent roles of complementary investments 利用人工智能进行双灵巧创新：互补投资的偶然作用

IF 10.9 1区管理学

Technovation Pub Date : 2026-03-01 Epub Date: 2026-01-08 DOI: 10.1016/j.technovation.2026.103475

Yang (Eric) Zhou , Jingjun (David) Xu , Zhiying Liu

{"title":"Harnessing artificial intelligence for ambidextrous innovation: Contingent roles of complementary investments","authors":"Yang (Eric) Zhou , Jingjun (David) Xu , Zhiying Liu","doi":"10.1016/j.technovation.2026.103475","DOIUrl":"10.1016/j.technovation.2026.103475","url":null,"abstract":"<div><div>While a growing body of literature has explored the role of artificial intelligence (AI) in innovation management, current research lacks understanding of how AI adoption affects firms' ambidextrous innovation and what contextual factors may influence this relationship. Drawing on the innovation search perspective and upper echelons theory, this study theorizes the impact of AI adoption on ambidextrous innovation and evaluates the contingent roles of complementary investments. Using panel data from Chinese listed firms between 2011 and 2022, we find strong evidence that AI adoption significantly increases exploratory innovation (ERI) and exploitative innovation (EII). The mechanisms by which AI adoption affect ERI and EII involve broadening and heightening the scope and depth of knowledge search, respectively. Moderating analyses reveal that executives’ features (e.g., educational level and tenure) exert varying contingent effects. Specifically, executive educational level amplifies the positive impact of AI on EII but has no significant role in the AI–ERI relationship. Furthermore, executives with longer tenure tend to diminish the positive effect of AI on ERI and EII. These findings contribute to the existing literature at the intersection of AI and innovation and provide insights into how firms should make complementary investments to fully capture the benefits of AI.</div></div>","PeriodicalId":49444,"journal":{"name":"Technovation","volume":"151 ","pages":"Article 103475"},"PeriodicalIF":10.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145924097","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}

引用次数: 0

Exploring the directions of artificial intelligence in good health and well-being (SDG3) using big data and LDA topic modeling 利用大数据和LDA主题建模，探索健康福祉领域人工智能（SDG3）的发展方向

IF 10.9 1区管理学

Technovation Pub Date : 2026-03-01 Epub Date: 2025-11-03 DOI: 10.1016/j.technovation.2025.103404

Peter Madzík , Lukáš Falát , Raja Jayaraman , Michael Sony , Jiju Antony , Dominik Zimon , Renata Skýpalová

{"title":"Exploring the directions of artificial intelligence in good health and well-being (SDG3) using big data and LDA topic modeling","authors":"Peter Madzík , Lukáš Falát , Raja Jayaraman , Michael Sony , Jiju Antony , Dominik Zimon , Renata Skýpalová","doi":"10.1016/j.technovation.2025.103404","DOIUrl":"10.1016/j.technovation.2025.103404","url":null,"abstract":"<div><div>Artificial Intelligence (AI) holds significant potential for advancing Sustainable Development Goal 3 (SDG3)—Good Health and Well-being—yet the field remains fragmented across numerous topics and disciplines. In this study, we apply Latent Dirichlet Allocation (LDA) to a final corpus of 60,010 Scopus abstracts after filtering, extracting k = 160 latent topics (selected via metric-based tuning; see Appendix A) and organizing them into a process-oriented, Health Technology Assessment–inspired framework that links Drivers, AI Infrastructure and Methods, Implementation, and Results. Key findings include dominant research streams in disease diagnostics (e.g., breast cancer, cardiovascular disease), personalized treatment, and automation, alongside the emergence of large language models (LLMs) like ChatGPT. Geographical mapping highlights Asia, North America, and Europe as research hubs, while underexplored areas such as AI in social media and student education are identified. We also introduce a quadrant-based trend analysis to distinguish “niche excellence” from “leading research areas” and chart short-versus medium-term dynamics. This methodological contribution not only offers a comprehensive “scientific map” of AI–SDG3 research but also provides a scalable blueprint for mapping AI's role across other SDGs and guiding future theory-driven and policy-relevant investigations.</div></div>","PeriodicalId":49444,"journal":{"name":"Technovation","volume":"151 ","pages":"Article 103404"},"PeriodicalIF":10.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145467476","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}

引用次数: 0

Artificial intelligence in technology networks: A catalyst for achieving the SDGs 技术网络中的人工智能：实现可持续发展目标的催化剂

IF 10.9 1区管理学

Technovation Pub Date : 2026-03-01 Epub Date: 2025-10-25 DOI: 10.1016/j.technovation.2025.103398

Vincenzo Varriale, Antonello Cammarano, Francesca Michelino, Mauro Caputo

{"title":"Artificial intelligence in technology networks: A catalyst for achieving the SDGs","authors":"Vincenzo Varriale, Antonello Cammarano, Francesca Michelino, Mauro Caputo","doi":"10.1016/j.technovation.2025.103398","DOIUrl":"10.1016/j.technovation.2025.103398","url":null,"abstract":"<div><div>The rapid adoption of artificial intelligence (AI) and other digital technologies is profoundly transforming business processes and activities, enhancing various aspects of sustainability. These technological developments offer new opportunities to address complex sustainability challenges and contribute to the achievement of the United Nations Sustainable Development Goals (SDGs). This study aims to investigate the networked value of AI within an ecosystem of digital technologies for achieving the SDGs. While extensive literature is based on the individual contributions of AI and other digital technologies to enhance sustainable development, there is a gap in understanding the networked value of AI when integrated with other technologies for sustainability. Based on a comprehensive dataset of 2161 sustainable business practices drawn from scientific literature, social network analysis was applied to map the relationships between AI within a technology ecosystem for achieving the SDGs. The results reveal that AI plays a central role, particularly in supporting SDG 7 (Affordable and Clean Energy), SDG 9 (Industry, Innovation and Infrastructure), and SDG 12 (Responsible Consumption and Production). Moreover, AI is closely connected to key digital technologies such as the Internet of Things, computing, and digital applications. These findings reveal the importance of strategically leveraging AI in conjunction with other technologies to enhance sustainability performance. In contrast to much of the existing literature, which is largely concentrated on environmental aspects, this research demonstrates that AI holds untapped potential to address socially oriented SDGs. It also identifies current gaps in the integration of AI with immersive environments and proximity technologies.</div></div>","PeriodicalId":49444,"journal":{"name":"Technovation","volume":"151 ","pages":"Article 103398"},"PeriodicalIF":10.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145366166","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}

引用次数: 0

When do intrafirm networks accelerate follow-on invention? Evidence from biotechnology firms 企业内部网络何时加速后续发明？来自生物技术公司的证据

IF 10.9 1区管理学

Technovation Pub Date : 2026-03-01 Epub Date: 2025-10-30 DOI: 10.1016/j.technovation.2025.103403

Ding Nan , Arjan Markus , Liukai Wang , Yu Xiong , Yali Zhang

{"title":"When do intrafirm networks accelerate follow-on invention? Evidence from biotechnology firms","authors":"Ding Nan , Arjan Markus , Liukai Wang , Yu Xiong , Yali Zhang","doi":"10.1016/j.technovation.2025.103403","DOIUrl":"10.1016/j.technovation.2025.103403","url":null,"abstract":"<div><div>This study examines how the structure of intrafirm inventor networks influences the speed at which biotechnology firms generate follow-on inventions. We conceptualize follow-on invention speed as how quickly a firm recombines and builds on its own prior knowledge. Drawing on social network theory, we focus on two structural dimensions: network clustering and average path length. We theorize that their effects depend on the firm's knowledge environment and tie characteristics—specifically, team knowledge diversity, tie strength, and invention radicalness. Using longitudinal data from 223 U.S. public biotechnology firms (2004–2013), we find that clustering slows invention speed, while longer average path length accelerates it—but only under specific conditions. Team knowledge diversity and radicalness mitigate the downsides of clustering but dampen the benefits of longer path lengths. Tie strength intensifies the negative effects of clustering while enhancing the value of path length. These findings underscore the need to align intrafirm network structure with the firm's internal knowledge context, offering new insights into the microfoundations underlying the speed of internal knowledge reuse and demonstrating that the value of intrafirm networks is contingent rather than universal. For managers, the results highlight that there is no one-size-fits-all optimal network structure: firms can accelerate follow-on invention only by aligning network features with the diversity, strength, and radicalness of their internal knowledge base and relational context.</div></div>","PeriodicalId":49444,"journal":{"name":"Technovation","volume":"151 ","pages":"Article 103403"},"PeriodicalIF":10.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145420009","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}

引用次数: 0

Artificial intelligence in humanitarian aid: A review and future research agenda 人道主义援助中的人工智能：回顾与未来研究议程

IF 10.9 1区管理学

Technovation Pub Date : 2026-03-01 Epub Date: 2025-11-03 DOI: 10.1016/j.technovation.2025.103415

Sophie Lythreatis , Fulya Acikgoz , Noura Yassine

{"title":"Artificial intelligence in humanitarian aid: A review and future research agenda","authors":"Sophie Lythreatis , Fulya Acikgoz , Noura Yassine","doi":"10.1016/j.technovation.2025.103415","DOIUrl":"10.1016/j.technovation.2025.103415","url":null,"abstract":"<div><div>As crises, both natural and man-made, continue to escalate in frequency and complexity, the need for effective and timely humanitarian interventions has become increasingly critical. Artificial intelligence (AI) has emerged as a transformative tool in enhancing humanitarian aid, addressing all stages of the crisis management cycle. Despite growing interest in AI's application within the humanitarian field, the existing literature remains fragmented, with limited synthesis of its overall impact. This study adopts a systematic literature review approach to provide a comprehensive analysis of AI's utilization in humanitarian aid across the crisis cycle, as well as its role in broader humanitarian settings outside of immediate crisis contexts. Based on 60 selected studies, the findings reveal that AI applications in both the pre- and post-crisis phases can be grouped into four specific categories, and that AI's role in broader humanitarian contexts can similarly be divided into four focus areas. Specifically, the categories in the pre-crisis phase include site selection, medical services enhancement, early warning, and information flow, and the categories in the post-crisis phase include distribution and delivery, damage assessment, online and textual insights, and routing optimization. The review highlights AI's significant potential to enhance the effectiveness and efficiency of humanitarian efforts, offering valuable insights for organizations seeking to harness AI's transformative power.</div></div>","PeriodicalId":49444,"journal":{"name":"Technovation","volume":"151 ","pages":"Article 103415"},"PeriodicalIF":10.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145467479","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}

引用次数: 0

The impact of income inequality on green innovation: Based on the perspective of institutional environment 收入不平等对绿色创新的影响：基于制度环境的视角

IF 10.9 1区管理学

Technovation Pub Date : 2026-03-01 Epub Date: 2025-11-05 DOI: 10.1016/j.technovation.2025.103401

Wenjing Luo , Dali Tao , Tianqi Liu

引用次数: 0