Zhenkang Fu , Qinghua Zhu , Bingxiang Liu , Chungen Yan
{"title":"Patent lifespan prediction and interpreting the key determinants: An application of interpretable machine learning survival analysis approach","authors":"Zhenkang Fu , Qinghua Zhu , Bingxiang Liu , Chungen Yan","doi":"10.1016/j.techfore.2025.124104","DOIUrl":"10.1016/j.techfore.2025.124104","url":null,"abstract":"<div><div>While the lifespan of patents is widely regarded as a key indicator for assessing their economic value, its utility in patent valuation is significantly constrained, as it can only be accurately measured at the time of patent expiration. Addressing this limitation necessitates proactively predicting the expected patent lifespan and thoroughly analyzing the complex relationships among various factors that affect patent lifespan. In response, this study constructs an interpretable machine learning framework to predict patent lifespan and explores the factors influencing it. The framework integrates features from five dimensions: technical, legal, market, patentee, and textual. It develops five distinct machine learning survival analysis models and employs post-hoc interpretable machine learning techniques on the optimal model to investigate the intricate relationships between these features and patent lifespan. The results of an empirical study of patents in China's Yangtze River Delta region demonstrate that the machine learning survival analysis approach significantly outperforms the traditional Cox proportional hazards model (Cox-PH) in terms of predictive performance. Furthermore, the post-hoc interpretation technique provides precise descriptions of the effects of various features on patent lifespan, revealing previously unidentified nonlinear relationships. This study holds substantial significance for the research and application of patent valuation, early patent warning, patent pledge financing, and patent management.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"215 ","pages":"Article 124104"},"PeriodicalIF":12.9,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143644985","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}
Yasanur Kayikci , Md. Ramjan Ali , Sharfuddin Ahmed Khan , Augustine Ikpehai
{"title":"Examining dynamics of hydrogen supply chains","authors":"Yasanur Kayikci , Md. Ramjan Ali , Sharfuddin Ahmed Khan , Augustine Ikpehai","doi":"10.1016/j.techfore.2025.124101","DOIUrl":"10.1016/j.techfore.2025.124101","url":null,"abstract":"<div><div>Hydrogen is poised to play a pivotal role in achieving net-zero targets and advancing green economies. However, a range of complex operational challenges hinders its planning, production, delivery, and adoption. At the same time, numerous drivers within the hydrogen value chain present significant opportunities. This paper investigates the intricate relationships between these drivers and barriers associated with hydrogen supply chain (HSC). Utilising expert judgment in combination Grey-DEMATEL technique, we propose a framework to assess the interplay of HSC drivers and barriers. Gaining insight into these relationships not only improves access to hydrogen but also foster innovation in its development as a low-carbon resource. The use of prominence scores and net influence rankings for each driver and barrier in the framework provides a comprehensive understanding of their relative significance and impact. Our findings demonstrate that by identifying and accurately mapping these attributes, clear cause-and-effect relationships can be established, contributing to a more nuanced understanding of the HSC. These insights have broad implications across operational, policy, scholarly and social domains. For instance, this framework can aid stakeholders in recognizing the range of opportunities available by addressing key barriers to hydrogen adoption.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"215 ","pages":"Article 124101"},"PeriodicalIF":12.9,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143641852","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Investigating the systemic nature of knowledge networks of regions","authors":"Adi Weidenfeld , Nick Clifton","doi":"10.1016/j.techfore.2025.124079","DOIUrl":"10.1016/j.techfore.2025.124079","url":null,"abstract":"<div><div>Studying inter-regional knowledge exchange has recently shifted to a more systematic analysis of regional groups of actors, defined as a knowledge network of regions, which have grown rapidly in number and impact. Although arbitrary or top-down decisions on network membership often result in low commitment and inefficient use of time and financial resources, studies on such networks' knowledge exchange mechanisms remain rare. Addressing a research gap and elaborating the inter-regional knowledge exchange concept, this paper is the first to study such a mechanism within national boundaries and explore its role, structure, membership, scope, communication channels, power relations, geopolitical environment, systemic qualities, and their impact on knowledge and learning practices. Based on in-depth interviews with 15 key informants from member and partner organisations of the Northern Ireland Local Government Association as a case study of a knowledge network of regions, augmented by analysis of a variety of online documentation and descriptive data, it suggests policy recommendations on improving the efficiency of knowledge networks of regions and how this benefits its members as well as directions for future studies. It also helps understand the role of the network management team in its facilitation of interactions that result in increasing network capital.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"215 ","pages":"Article 124079"},"PeriodicalIF":12.9,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143636522","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mingyue Lu , Yiqin Xi , Yiqun Sun , Zexin Lin , Haoyan Zhang , Shiyue Luo , Asyraf Afthanorhan , Yu Hao
{"title":"How does carbon awareness impact corporate sustainable development? Evidence from China","authors":"Mingyue Lu , Yiqin Xi , Yiqun Sun , Zexin Lin , Haoyan Zhang , Shiyue Luo , Asyraf Afthanorhan , Yu Hao","doi":"10.1016/j.techfore.2025.124097","DOIUrl":"10.1016/j.techfore.2025.124097","url":null,"abstract":"<div><div>Amid growing global concerns about greenhouse gas emissions, carbon awareness has emerged as a critical indicator of corporate commitment to low-carbon strategies. Drawing on data from 3690 A-share listed companies across 372 cities in China between 2001 and 2020, this study explores the positive relationship between corporate carbon awareness and sustainable development capability (SUSDEV) within the framework of the Porter Hypothesis. The findings reveal that a 1 % increase in carbon awareness leads to a significant 0.551-point rise in the SUSDEV evaluation score, accounting for approximately 4 % of the average SUSDEV score (13.394) among the sampled firms. Key drivers of this effect include increased government subsidies, environmental investments, enhanced Tobin's Q, and improved innovation capability. Analysis using the PSM-DID model further substantiates these findings, demonstrating that the implementation of the “Low-Carbon City” pilot policy significantly bolsters the contribution of carbon awareness to long-term sustainable development. Additionally, the study provides a heterogeneous analysis of the impact of carbon awareness across firms with varying characteristics. These findings expand the theoretical boundaries of the Porter Hypothesis, offering valuable insights for businesses seeking to achieve long-term operational sustainability while actively fulfilling environmental responsibilities.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"215 ","pages":"Article 124097"},"PeriodicalIF":12.9,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143619400","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":"The possibilities of using AutoML in bankruptcy prediction: Case of Slovakia","authors":"Mário Papík, Lenka Papíková","doi":"10.1016/j.techfore.2025.124098","DOIUrl":"10.1016/j.techfore.2025.124098","url":null,"abstract":"<div><div>Using machine learning (ML) and artificial intelligence to make predictions to increase efficiency will drive the upcoming fifth industrial revolution. This study investigates the application of automated machine learning (AutoML) in the prediction of company bankruptcies, with a focus on two key novelties: (1) a comprehensive comparison of five state-of-the-art AutoML tools (AutoGluon, AutoKeras, H2O-AutoML, MLJar, and TPOT) against traditional statistical methods and ensemble ML techniques based on predictive performance and development time, and (2) an in-depth impact analysis of three distinct data resampling approaches (without resampling, random oversampling and SMOTE) on model performance and development time. Using financial data from 2019 to 2021, this study demonstrates that AutoML tools, particularly H2O-AutoML and AutoGluon, outperform traditional and ensemble ML methods (achieving AUC values of 0.913 and 0.894 respectively, compared to 0.880 for XGBoost) and significantly reduce model-development time, often completing tasks in one-third to half the time required by conventional approaches. Furthermore, the findings highlight the robustness of H2O-AutoML and AutoGluon in handling imbalanced datasets- a critical challenge in bankruptcy prediction. Therefore, selected AutoML methods can already help to democratise access to advanced risk management models for smaller companies and institutions to leverage high-performing predictive tools with minimal expert intervention.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"215 ","pages":"Article 124098"},"PeriodicalIF":12.9,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143609888","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Muhammad Farrukh Abid , Amjad Shamim , Park Thaichon , Sara Quach , Junaid Siddique
{"title":"Designing an information technology-enabled framework in the retail service ecosystem","authors":"Muhammad Farrukh Abid , Amjad Shamim , Park Thaichon , Sara Quach , Junaid Siddique","doi":"10.1016/j.techfore.2025.124078","DOIUrl":"10.1016/j.techfore.2025.124078","url":null,"abstract":"<div><div>Despite the significant importance of service innovation in a value-centered retail environment, less is explored regarding its conceptualization through firms' information technology (IT) based strategic capabilities to promote the value formation process in a retail service ecosystem. To address this gap, this study aims to develop an integrated framework based on the concepts of service-dominant logic and resource advantage theory. By conducting 24 in-depth interviews (12 with employees and 12 with customers) across various non-fuel retail stores commonly referred to as tuck shops, this study highlights the significant role of firms' strategic IT-enabled capabilities in enhancing service process innovation and customer service. These IT capabilities, combined with service process innovation and customer service, not only create opportunities for value co-creation through resource exchange (<em>value-in-exchange</em>) but also enable customers to create value through individual service consumption (<em>value-in-use</em>). The findings further suggest co-creation experience within the retail ecosystem is shaped by customers' emotional involvement, role projection, and escapism, which collectively determine their <em>value-in-experience</em>. Finally, the proposed framework offers valuable implications for practitioners, emphasizing the need to design more integrative IT-enabled platforms to achieve improved customer value outcomes.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"215 ","pages":"Article 124078"},"PeriodicalIF":12.9,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143609384","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Raluca Bunduchi , Dan-Andrei Sitar-Tăut , Daniel Mican
{"title":"A legitimacy-based explanation for user acceptance of controversial technologies: The case of Generative AI","authors":"Raluca Bunduchi , Dan-Andrei Sitar-Tăut , Daniel Mican","doi":"10.1016/j.techfore.2025.124095","DOIUrl":"10.1016/j.techfore.2025.124095","url":null,"abstract":"<div><div>Controversial technologies are technologies where social concerns play a disproportionate role in shaping the public attitudes to their adoption. An example of such controversial technologies is Generative Artificial Intelligence (GenAI), whose rapid diffusion is fuelled by expectations for significant performance improvements, while also facing concerns at individual (trust in technology), technology (accuracy and quality), and institutional (cultural, ethical and regulatory) level. Individual and technology factors are well accounted for by rational choice-based models which underpin most technology acceptance research. Such models are less suited to explore the role of institutional factors in shaping technology acceptance. Drawing from legitimacy and technology lifecycle research, we develop a legitimacy-based model of GenAI adoption which accounts for the institutional context in which technology use happens, and for technology characteristics, namely its maturity, in shaping users' acceptance. Surveying 483 information systems students who are GenAI users, we find that users' perceptions of technology uncertainty and variation positively affect their technology legitimacy evaluations and that their pragmatic and cognitive legitimacy evaluations, but not moral, affect their intention to use. We answer recent calls to examine alternative theoretical predictors of technology acceptance, and to consider the role of context in examining the acceptance of controversial technologies.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"215 ","pages":"Article 124095"},"PeriodicalIF":12.9,"publicationDate":"2025-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143577064","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hafiz Muhammad Usman Khizar , Aqsa Ashraf , Jingbo Yuan , Mohammed Al-Waqfi
{"title":"Insights into ChatGPT adoption (or resistance) in research practices: The behavioral reasoning perspective","authors":"Hafiz Muhammad Usman Khizar , Aqsa Ashraf , Jingbo Yuan , Mohammed Al-Waqfi","doi":"10.1016/j.techfore.2025.124047","DOIUrl":"10.1016/j.techfore.2025.124047","url":null,"abstract":"<div><div>The widespread and rapidly increasing usage of ChatGPT in education and research has attracted a considerable attention and controversies. Although its application has several benefits, various potential negative impacts and risks exist. To this end, drawing on the insights from the Behavioral Reasoning Theory (BRT), this study aims to investigate the factors that influence ChatGPT's adoption (or resistance) in research practices. We employed an exploratory qualitative research design and conducted semi-structured interviews with academic researchers to identify the reasons for and against the use of ChatGPT. The interview participants were purposefully selected management researchers with appropriate knowledge and experience of ChatGPT, who supervise research students and are actively publishing their research. We delineated themes and subthemes that emerged from the interviews to provide a more comprehensive understanding of the factors that influence the adoption (or resistance) of ChatGPT. This study contributes to the literature by extending the application of BRT in academic research and highlight the reasons for (and against) the adoption of ChatGPT among academic researchers. Moreover, these findings inform policy and practice to develop appropriate strategies for promoting ethical and responsible AI adoption.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"215 ","pages":"Article 124047"},"PeriodicalIF":12.9,"publicationDate":"2025-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143577065","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}
Anrafel de Souza Barbosa , Maria Cristina Crispim , Luiz Bueno da Silva , Jonhatan Magno Norte da Silva , Aglaucibelly Maciel Barbosa , Lucas Miguel Alencar de Morais Correia , Sandra Naomi Morioka
{"title":"Empirical analysis of workers' perceptions of ESG impacts on corporate sustainability performance: A methodological innovation combining the PLS-SEM, PROMETHEE-ROC and FIMIX-PLS methods","authors":"Anrafel de Souza Barbosa , Maria Cristina Crispim , Luiz Bueno da Silva , Jonhatan Magno Norte da Silva , Aglaucibelly Maciel Barbosa , Lucas Miguel Alencar de Morais Correia , Sandra Naomi Morioka","doi":"10.1016/j.techfore.2025.124091","DOIUrl":"10.1016/j.techfore.2025.124091","url":null,"abstract":"<div><div>The perceptions of workers regarding Environmental, Social, and Governance (ESG) criteria are not only reflective of their immediate work environment but also serve as indicators of broader corporate sustainability performance. This research provides empirical insights into workers' perceptions of ESG impacts on corporate sustainability performance in the Brazilian electrical industry. It demonstrates the methodological strengths of Partial Least Squares Structural Equation Modeling (PLS-SEM), combined with the Preference Ranking Organization METHod for Enrichment Evaluations with the Rank-Order Centroid (PROMETHEE-ROC) and Finite Mixture Partial Least Squares (FIMIX-PLS) methods. A structured questionnaire administered across various sectors of two large companies captured comprehensive data on workers' ESG views. Cluster Analysis (CA) and Factor Analysis (FA) grouped and validated the data, while PLS-SEM assessed associations between latent and observable variables. FIMIX-PLS analyzed sample segmentation, and PROMETHEE-ROC ranked significant ESG criteria. Findings revealed that ESG criteria significantly influence workers' perceptions of corporate sustainability, with multidimensional FA elucidating 71 % of latent traits and PLS-SEM parameters demonstrating strong model fit. This study contributes to theory and practice by validating the PLS-SEM structure for capturing worker perceptions and by introducing a novel methodology combining PLS-SEM, PROMETHEE-ROC, and FIMIX-PLS methods.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"215 ","pages":"Article 124091"},"PeriodicalIF":12.9,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143577053","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}
Hongxu Lu , Ting Wu , Xin-Miao Yao , Chen-Ming Huangfu
{"title":"How and when digital transformation intensity influences employees' safety-related helping behaviors","authors":"Hongxu Lu , Ting Wu , Xin-Miao Yao , Chen-Ming Huangfu","doi":"10.1016/j.techfore.2025.124092","DOIUrl":"10.1016/j.techfore.2025.124092","url":null,"abstract":"<div><div>In the context of safety management in safety-critical organizations, this study leveraged the job demands–resources model to scrutinize the divergent effects of digitalization on safety-related helping behavior. A two-stage survey of 367 employees from 41 teams in a safety-critical organization revealed that the employees' self-efficacy mediated the positive relationship between the intensity of digital transformation and safety-related helping behavior, whereas ego depletion mediated the negative relationship between the intensity of digital transformation and safety-related helping behavior. In addition, employees' positive perception of the organization's motivation for adopting digitalization amplified the indirect effect of the intensity of digital transformation on safety-related helping behavior via self-efficacy, while diminishing this indirect effect via ego depletion. These findings help to deepen the current understanding of the relationship between digitalization and employees' safety-related helping behaviors, and provide suggestions for managers in safety-critical organizations on how to use digital technologies to encourage employees to help each other in safety management. We emphasize that it is important for organizations to ensure that employees understand that digital transformation are motivated by a desire to help them avoid safety hazards, rather than to supervise them in safety management.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"215 ","pages":"Article 124092"},"PeriodicalIF":12.9,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143577052","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}