Technological Forecasting and Social Change最新文献_第6页

Climate transition risk and industry returns: The impact of green innovation and carbon market uncertainty

IF 12.9 1区管理学

Technological Forecasting and Social Change Pub Date : 2025-02-25 DOI: 10.1016/j.techfore.2025.124056

Qi Zhou , Jiajun Ni , Cunyi Yang

{"title":"Climate transition risk and industry returns: The impact of green innovation and carbon market uncertainty","authors":"Qi Zhou , Jiajun Ni , Cunyi Yang","doi":"10.1016/j.techfore.2025.124056","DOIUrl":"10.1016/j.techfore.2025.124056","url":null,"abstract":"<div><div>This study explores how climate transition risk, green innovation, and carbon market uncertainty influence industry returns in economic cycles, providing crucial insights for industry-level low-carbon transition pathways. Utilizing an input-output (IO) life-cycle assessment model, we measure the total carbon emissions and carbon intensity of 28 industries in China from 2002 to 2020, distinguishing between direct and indirect emissions. We investigate the risk premium associated with transition risk and industry returns and analyze the moderating effects of physical risk, carbon market uncertainty, and green innovation. Our findings indicate that higher transition risk correlates with lower industry returns, with physical risk exacerbating this negative impact, while carbon market uncertainty and green innovations mitigate it. The heterogeneity analysis reveals that direct carbon emissions primarily drive the negative premium. Notably, the adverse effect of transition risk on industry returns has diminished since the Paris Agreement and is more evident in industries with lower concentration levels and higher centrality degree. This research offers new evidence on the interplay between climate transition risk and economic cycles, emphasizing the role of green finance and technological innovation in forecasting and navigating future economic developments.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"214 ","pages":"Article 124056"},"PeriodicalIF":12.9,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143478603","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

Can gold hedge against uncertainty in the cryptocurrency and energy markets?

IF 12.9 1区管理学

Technological Forecasting and Social Change Pub Date : 2025-02-25 DOI: 10.1016/j.techfore.2025.124050

Meng Qin , Xuefeng Shao , Chengming Hu , Chi Wei Su

{"title":"Can gold hedge against uncertainty in the cryptocurrency and energy markets?","authors":"Meng Qin , Xuefeng Shao , Chengming Hu , Chi Wei Su","doi":"10.1016/j.techfore.2025.124050","DOIUrl":"10.1016/j.techfore.2025.124050","url":null,"abstract":"<div><div>Studying gold's ability to shield against uncertainties in energy and cryptocurrency markets could aid investors in refining investment portfolios. A novel wavelet quantile correlation methodology is developed to dissect the relationships between the cryptocurrency policy uncertainty index (CPUI) and gold price (GP), energy-related uncertainty index (ERUI) and GP across various quantiles and time horizons. We find that CPUI mainly correlates positively with GP across most quantiles. Gold offers stronger hedging against cryptocurrency policy uncertainty over medium- to long-term horizons than short-term. ERUI's mixed correlations with GP suggest that gold's ability to hedge against energy-related uncertainty is not permanent. By comparison, CPUI has a stronger link with GP than ERUI, indicating gold's more significant hedging potential during cryptocurrency policy uncertainties. During COVID-19, CPUI positively correlated with GP in the short term but negatively in the medium run, confirming gold's short-term hedging against cryptocurrency policy uncertainty. However, EPUI generally negatively correlates with GP, showing limited hedging capacity against energy-related uncertainty. During the Russia-Ukraine conflict, CPUI and ERUI strongly positively correlated with GP, highlighting gold's safe haven role against these uncertainties. Considering these results, valuable insights are furnished for investors and governments to respond flexibly to changes in financial markets.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"214 ","pages":"Article 124050"},"PeriodicalIF":12.9,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143487578","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

A maturity model for assessing the implementation of Industry 5.0 in manufacturing SMEs: learning from theory and practice

IF 12.9 1区管理学

Technological Forecasting and Social Change Pub Date : 2025-02-24 DOI: 10.1016/j.techfore.2025.124045

Maria Elena Latino

{"title":"A maturity model for assessing the implementation of Industry 5.0 in manufacturing SMEs: learning from theory and practice","authors":"Maria Elena Latino","doi":"10.1016/j.techfore.2025.124045","DOIUrl":"10.1016/j.techfore.2025.124045","url":null,"abstract":"<div><div>Digitalization is facing the transition from Industry 4.0 to Industry 5.0, enlarging the technocentric vision of technologies to embrace sustainable, resilience and human-centered design objectives. Although aware of the benefits of digitalization, many companies have not yet undertaken this process or are only at the beginning stages, seeking support and expertise. Firstly, it is important to understand the company's current technological level and, therefore, establish an improvement strategy. Over time, several authors have made efforts to develop maturity models capable of assessing a company's Industry 4.0 technological level. However, given the recent shift toward Industry 5.0, it is necessary to understand how such tools can effectively address the three pillars of Industry 5.0 when evaluating digital maturity. This study contributes to the literature on Industry 5.0 by proposing a tool to assess the maturity of companies in Industry 5.0 practices, focusing on sustainability, resilience and human centricity in manufacturing processes. This Industry 5.0 Maturity Model consists of a self-assessment questionnaire, designed to assess the current maturity level of the company across seven maturity dimensions (double assessment Industry 5.0 integrated and pillar-based), and a roadmap that outlines improvement strategies and operational information to enhance the company’ maturity across these dimensions. The proposed maturity model is applied in a multiple case study to collect empirical evidence from four Italian SMEs operating in the manufacturing industry. The results show a good Industry 5.0 maturity, with differences across the various dimensions influenced by the characteristics of the analyzed sectors and products. The low level of embedded technologies leaves room for future improvements in products and services, aligned with sustainability, resilience and human-centric perspectives. Theoretical and practical implications of the study are also discussed.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"214 ","pages":"Article 124045"},"PeriodicalIF":12.9,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143478600","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}

引用次数: 0

Collaboration before competition: How smart city entrepreneurs co-create temporary ecosystems to build capacity for learning

IF 12.9 1区管理学

Technological Forecasting and Social Change Pub Date : 2025-02-24 DOI: 10.1016/j.techfore.2025.124046

Paul G. Oliver , Luca Mora , Jun Zhang

{"title":"Collaboration before competition: How smart city entrepreneurs co-create temporary ecosystems to build capacity for learning","authors":"Paul G. Oliver , Luca Mora , Jun Zhang","doi":"10.1016/j.techfore.2025.124046","DOIUrl":"10.1016/j.techfore.2025.124046","url":null,"abstract":"<div><div>This article explores how smart city entrepreneurs (SCEs) learn to address urban sustainability challenges with innovative digital products and services. SCEs embody social, digital, and urban entrepreneurialism features and play a pivotal role in advancing smart city development. But despite their importance, little is known about the knowledge, skills, and competencies required to become an SCE. Grounded in entrepreneurial learning theory, our study helps fill this gap. Using the city of Edinburgh, UK, as our empirical setting, we examine the learning process of 34 SCEs. Our findings offer three core contributions. First, we show that collaborative learning is a key driver of innovation in the smart city domain. SCEs significantly benefit from collaborative efforts rather than competitive strategies alone. Second, we show that these collaborations develop in temporary ecosystems that contribute to enhancing the innovative capacities of SCEs. Building on these findings, we expand entrepreneurial learning theory, highlighting the critical yet overlooked role of temporary ecosystems and intermediaries in stimulating collaboration and knowledge exchange among SCEs. Third, we provide practical recommendations for policymakers, emphasizing the importance of supporting the development of strategic learning capacities and diverse learning modalities for SCEs.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"214 ","pages":"Article 124046"},"PeriodicalIF":12.9,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143478591","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}

引用次数: 0

Registers of beneficial owners based on blockchain technology: Implications for the accounting profession

IF 12.9 1区管理学

Technological Forecasting and Social Change Pub Date : 2025-02-24 DOI: 10.1016/j.techfore.2025.124051

Paul Gilmour , Durgesh Pandey , Doron Goldbarsht

引用次数: 0

Bitcoin trade volume in decentralized markets: International evidence

IF 12.9 1区管理学

Technological Forecasting and Social Change Pub Date : 2025-02-23 DOI: 10.1016/j.techfore.2025.124054

Gabriel A. Giménez Roche , Antoine Noël , Loïc Sauce

引用次数: 0

The curvilinear relationship between digitalization and export propensity: The role of home country corruption in emerging economies

IF 12.9 1区管理学

Technological Forecasting and Social Change Pub Date : 2025-02-22 DOI: 10.1016/j.techfore.2025.124043

Joan-Lluís Capelleras , Victor Martin-Sanchez , Chao Zhang

引用次数: 0

Recognition of promising technologies considering inventor and assignee's historic performance: A machine learning approach 考虑发明人和受让人的历史业绩，识别有前途的技术：机器学习方法

IF 12.9 1区管理学

Technological Forecasting and Social Change Pub Date : 2025-02-22 DOI: 10.1016/j.techfore.2025.124053

Liang Gui , Jie Wu , Peng Liu , Tieju Ma

{"title":"Recognition of promising technologies considering inventor and assignee's historic performance: A machine learning approach","authors":"Liang Gui , Jie Wu , Peng Liu , Tieju Ma","doi":"10.1016/j.techfore.2025.124053","DOIUrl":"10.1016/j.techfore.2025.124053","url":null,"abstract":"<div><div>Recognition of promising technologies is important for enterprises that are eager to occupy the center position in future markets, considering it can provide valuable R&D (research and development) intelligence and industrial reform signal. Accordingly, many approaches have been introduced in the literature to identify promising technologies; however, most previous studies have relied heavily on technologies' bibliometric and text features. The promisingness of a technology is often determined by various other factors, including the inventor and assignee's historic performance (IAHP) features. To overcome the limitations of previous approaches, we propose a machine learning approach that integrates the bibliometric, text, and IAHP features to accomplish promising technology recognition (named MLIFPR) in this paper. The proposed MLIFPR approach was applied to five fields, including the electrical communication, ship, road construction, electric power, and electric vehicle fields, and its usability was verified. Experiments showed that the approach considering bibliometric, text, and IAHP features achieved an average promising technology recognition precision of 95.9 %, which outperformed existing studies. The recognition performance was significantly improved by >3.3 % after the addition of IAHP features. The proposed MLIFPR approach of this study is a novel data mining tool to assist enterprises in developing and following unhatched disruptive technologies to occupy a leading position in the future market. Besides, the introduced IAHP features as new low-dimensional signals representing the technologies' promisingness can provide a reference for other technological innovation works.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"214 ","pages":"Article 124053"},"PeriodicalIF":12.9,"publicationDate":"2025-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143464964","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

Uncertainty management tensions in radical open innovation projects between established firms and startups

IF 12.9 1区管理学

Technological Forecasting and Social Change Pub Date : 2025-02-22 DOI: 10.1016/j.techfore.2025.124026

Leonardo Augusto de Vasconcelos Gomes , Ana Lucia Figueiredo Facin , Ximena Alejandra Flechas , Rafaela Ferreira Maniçoba , Fabio Emanuel Farago , Francisca Nicole Urra Moraga , Lucas Emmanuel Nascimento Silva

{"title":"Uncertainty management tensions in radical open innovation projects between established firms and startups","authors":"Leonardo Augusto de Vasconcelos Gomes , Ana Lucia Figueiredo Facin , Ximena Alejandra Flechas , Rafaela Ferreira Maniçoba , Fabio Emanuel Farago , Francisca Nicole Urra Moraga , Lucas Emmanuel Nascimento Silva","doi":"10.1016/j.techfore.2025.124026","DOIUrl":"10.1016/j.techfore.2025.124026","url":null,"abstract":"<div><div>This study investigates how established firms and startups deal with tensions regarding uncertainty management in radical open innovation projects. Tensions might emerge for various reasons—including contradictory divergences in how managers and entrepreneurs perceive and assess an uncertainty, distinct preferences or biases regarding the optimal approach to cope with uncertainties, and difficulties coping with the non-anticipated consequences of uncertainty management. Although open innovation projects between established firms and startups represent a unique, fast-growing phenomenon crucial for accelerating innovation, current scholarship has paid less attention to these tensions and how managers and entrepreneurs cope with them. By studying 14 open innovation projects between established firms and startups in 9 companies, we identify tensions and responses to these tensions. The critical insight of our framework is that the way firms dynamically handle themselves with respect to the tensions is central to understanding why some open innovation projects lead to a positive trajectory, whereby both the established firm and startup have their goals, outcomes, expectations, and perceptions transformed. This trajectory generates effective learning for both sides, while other projects face a growing dissociation effect, which might result in failure. This study's implications and opportunities for future research are highlighted.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"214 ","pages":"Article 124026"},"PeriodicalIF":12.9,"publicationDate":"2025-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143471396","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

Can digital technology break the financing dilemma of innovative SMEs? Based on the perspective of enterprise innovation

IF 12.9 1区管理学

Technological Forecasting and Social Change Pub Date : 2025-02-21 DOI: 10.1016/j.techfore.2025.124030

Kang Wang , Kang Sun , Yifei Li , Qian Xie

{"title":"Can digital technology break the financing dilemma of innovative SMEs? Based on the perspective of enterprise innovation","authors":"Kang Wang , Kang Sun , Yifei Li , Qian Xie","doi":"10.1016/j.techfore.2025.124030","DOIUrl":"10.1016/j.techfore.2025.124030","url":null,"abstract":"<div><div>Based on Signaling theory, this paper examines the mechanisms and effects of SMEs adopting digital technology to alleviate their own financing constraints from an innovation perspective. Empirical testing was conducted using data from enterprises in Zhongguancun, China, spanning the years 2014 to 2019. The study finds that the application of digital technology can effectively alleviate the financing constraints faced by enterprises. Additionally, the impact varies depending on the specific digital technology employed and the level of its adoption. The mechanism analysis reveals that enhancing innovation capability and integrating into innovation networks are crucial pathways through which digital technology alleviates financing constraints. Specifically, the application of digital technology improves firms' innovation capabilities, facilitates their integration into innovation networks, attracts external investment by effectively signaling high-quality attributes to the market, and thereby mitigates financing constraints. Further analysis of heterogeneity indicates that the alleviating effect of digital technology on financing constraints is more pronounced when entrepreneurs' cognitive abilities are stronger, when industry competition is intense, and when enterprise scale is larger. This paper provides an empirical foundation for addressing SMEs' financing dilemmas in the digital era and supports high-quality development of enterprises.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"214 ","pages":"Article 124030"},"PeriodicalIF":12.9,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143464963","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