Pub Date : 2024-10-28DOI: 10.1016/j.techfore.2024.123830
Iulian Adrian Sorcaru, Mihaela-Carmen Muntean, Ludmila-Daniela Manea, Rozalia Nistor
Sustainable business practices are vital for tourist destinations because they help tackle social and environmental challenges while addressing profit-oriented concerns. The purpose of this study was to explore pro-environmental behaviors in families. The values-identity-personal norm model was combined with the concept of destination social responsibility via normative influences. Partial least squares structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA) were applied in a mixed-methods approach. The findings confirm the values-identity-personal norm model's normative path to family pro-environmental behavior. The research contributes to theory and practice by introducing two new destination social responsibility perspectives: descriptive and injunctive. Based on social media normative influences on family endorsement of destination social responsibility messages, the analysis showed a significant direct effect of descriptive destination social responsibility and injunctive destination social responsibility on family personal norms. However, the mediating effect of family personal norms on family pro-environmental behavior was significant only for descriptive destination social responsibility. Perceived destination social responsibility activities during family vacations had a nonsignificant effect on family personal norms and family pro-environmental behavior. The fsQCA highlights multiple scenarios leading to family pro-environmental behavior. The findings are valuable for helping destination management organizations (DMOs) develop social marketing strategies for family ecotourism.
{"title":"From social norms to pro-environmental behavior: The role of destination social responsibility for families traveling with children","authors":"Iulian Adrian Sorcaru, Mihaela-Carmen Muntean, Ludmila-Daniela Manea, Rozalia Nistor","doi":"10.1016/j.techfore.2024.123830","DOIUrl":"10.1016/j.techfore.2024.123830","url":null,"abstract":"<div><div>Sustainable business practices are vital for tourist destinations because they help tackle social and environmental challenges while addressing profit-oriented concerns. The purpose of this study was to explore pro-environmental behaviors in families. The values-identity-personal norm model was combined with the concept of destination social responsibility via normative influences. Partial least squares structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA) were applied in a mixed-methods approach. The findings confirm the values-identity-personal norm model's normative path to family pro-environmental behavior. The research contributes to theory and practice by introducing two new destination social responsibility perspectives: descriptive and injunctive. Based on social media normative influences on family endorsement of destination social responsibility messages, the analysis showed a significant direct effect of descriptive destination social responsibility and injunctive destination social responsibility on family personal norms. However, the mediating effect of family personal norms on family pro-environmental behavior was significant only for descriptive destination social responsibility. Perceived destination social responsibility activities during family vacations had a nonsignificant effect on family personal norms and family pro-environmental behavior. The fsQCA highlights multiple scenarios leading to family pro-environmental behavior. The findings are valuable for helping destination management organizations (DMOs) develop social marketing strategies for family ecotourism.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"209 ","pages":"Article 123830"},"PeriodicalIF":12.9,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142535825","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}
The aim of this paper is to identify the characteristics of advertising in the metaverse and its implications for brands and society. A group of 35 experts representing advertising agencies and brands from Central and Eastern Europe were interviewed. The findings are presented in the form of a conceptual model that provides a cartography for the landscape of metaverse advertising. Our results demonstrate that metaverse advertising uses existing formats (e.g. billboards, product placement), while also developing new ones (e.g. automated avatars, virtual products, and branded spaces). In addition, metaverse advertising is more focused on brand building than on direct, measurable impact. Advertising in the metaverse is not as precisely targeted as it is on the internet. Given their high up-front costs, these activities are currently more suitable for multinationals and well-known global brands. Metaverse advertising is not perceived to be associated with elevated brand risk. However it is burdened with myopia, understood as a lack of long-term perspective. Our findings reveal three stakeholder personas representing different approaches to metaverse advertising; including Cautious Pioneers, Empathic Pragmatists, and Blockchain Enthusiasts. We conclude by documenting the social consequences, capturing shifts towards automated communication, digital ownership, and the metaverse's potential to replace social media.
{"title":"Advertising in the metaverse and its implications for brands and society: A multi-stakeholder perspective","authors":"Tymoteusz Doligalski , Nikodem Sarna , Bernadett Koles , Aneta Siejka , Robert Kozielski","doi":"10.1016/j.techfore.2024.123832","DOIUrl":"10.1016/j.techfore.2024.123832","url":null,"abstract":"<div><div>The aim of this paper is to identify the characteristics of advertising in the metaverse and its implications for brands and society. A group of 35 experts representing advertising agencies and brands from Central and Eastern Europe were interviewed. The findings are presented in the form of a conceptual model that provides a cartography for the landscape of metaverse advertising. Our results demonstrate that metaverse advertising uses existing formats (e.g. billboards, product placement), while also developing new ones (e.g. automated avatars, virtual products, and branded spaces). In addition, metaverse advertising is more focused on brand building than on direct, measurable impact. Advertising in the metaverse is not as precisely targeted as it is on the internet. Given their high up-front costs, these activities are currently more suitable for multinationals and well-known global brands. Metaverse advertising is not perceived to be associated with elevated brand risk. However it is burdened with myopia, understood as a lack of long-term perspective. Our findings reveal three stakeholder personas representing different approaches to metaverse advertising; including Cautious Pioneers, Empathic Pragmatists, and Blockchain Enthusiasts. We conclude by documenting the social consequences, capturing shifts towards automated communication, digital ownership, and the metaverse's potential to replace social media.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"209 ","pages":"Article 123832"},"PeriodicalIF":12.9,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142535822","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}
Pub Date : 2024-10-28DOI: 10.1016/j.techfore.2024.123837
Annu Kotiranta , Kaisu Puumalainen , Helena Sjögren , Léo-Paul Dana
Social enterprises' motivations for growth arguably stem from their social missions, which can result in moderate business growth due to conflicting interests and the trade-off costs of impact scaling and growing their business. Digitalization has been suggested as one method of enabling the simultaneous growth of business and social or environmental impact. In this study, we analyze the digital orientation of social enterprises and test whether our hypotheses regarding the superior business benefits of digitalization for social enterprises can be empirically confirmed. Our results show social enterprises as early adopters of digitalization, who have higher expectations that digitalization will benefit them and tend to invest more in digital technologies and capabilities than commercial companies do. However, the strong digital orientation of social enterprises does not manifest better business growth. Furthermore, the findings suggest that social enterprises' investment in social media has hampered their productivity. Our findings challenge current theoretical arguments that claim that digitalization has particular benefits for social enterprises, and we suggest that the digital antecedents of social enterprise growth are, after all, very similar to those of other small and medium-sized enterprises.
{"title":"Digitalization as a growth driver for social enterprises","authors":"Annu Kotiranta , Kaisu Puumalainen , Helena Sjögren , Léo-Paul Dana","doi":"10.1016/j.techfore.2024.123837","DOIUrl":"10.1016/j.techfore.2024.123837","url":null,"abstract":"<div><div>Social enterprises' motivations for growth arguably stem from their social missions, which can result in moderate business growth due to conflicting interests and the trade-off costs of impact scaling and growing their business. Digitalization has been suggested as one method of enabling the simultaneous growth of business and social or environmental impact. In this study, we analyze the digital orientation of social enterprises and test whether our hypotheses regarding the superior business benefits of digitalization for social enterprises can be empirically confirmed. Our results show social enterprises as early adopters of digitalization, who have higher expectations that digitalization will benefit them and tend to invest more in digital technologies and capabilities than commercial companies do. However, the strong digital orientation of social enterprises does not manifest better business growth. Furthermore, the findings suggest that social enterprises' investment in social media has hampered their productivity. Our findings challenge current theoretical arguments that claim that digitalization has particular benefits for social enterprises, and we suggest that the digital antecedents of social enterprise growth are, after all, very similar to those of other small and medium-sized enterprises.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"209 ","pages":"Article 123837"},"PeriodicalIF":12.9,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142535826","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}
The next revolutionary technology that will have an impact on society in the coming decades is called metaverse, which allows immersive encounters in both virtual and real-world environments. Metaverse, while still in the concept stage, merges the digital and physical realms, allowing users to move easily between them. How does metaverse influence sustainable development, organizational competitiveness and business innovation? This is the question from which this research started. In addition to identifying future obstacles, the paper proposes research options to help organisations fully exploit the opportunities and capabilities of metaverse. Investigating the current limitations and expansion potential of metaverse, including the impact on different industries and economic sectors, is the main focus of this research. The data collection tool was the questionnaire that we distributed to groups in different companies in Romania, being completed by employees from both executive and management departments. In this study, we developed a conceptual model to investigate the factors that could positively influence the evolution of innovative business models in Romania. We opted for structural equation modelling using SmartPLS4 software. The present research also contributes to identifying and addressing the challenges and risks associated with metaversion. The analysis indicates that although the adoption of digital business models and innovative management practices is significant, their immediate impact on the long-term success of companies in the metaverse is somewhat limited. The metaverse represents both a risk and an excellent opportunity for entrepreneurs to leverage digital services for growth. We believe this research is necessary to uncover new innovative business opportunities, as understanding rapid technological change allows companies to remain competitive and adopt new technologies effectively.
{"title":"The metaverse, a new frontier for innovative business models","authors":"Nicoleta CRISTACHE , Oana PRICOPOAIA , Marian NĂSTASE , Julia-Anamaria ȘIȘU , Andrei-Constantin TÎRNOVANU , Cosmin MATIȘ","doi":"10.1016/j.techfore.2024.123838","DOIUrl":"10.1016/j.techfore.2024.123838","url":null,"abstract":"<div><div>The next revolutionary technology that will have an impact on society in the coming decades is called metaverse, which allows immersive encounters in both virtual and real-world environments. Metaverse, while still in the concept stage, merges the digital and physical realms, allowing users to move easily between them. How does metaverse influence sustainable development, organizational competitiveness and business innovation? This is the question from which this research started. In addition to identifying future obstacles, the paper proposes research options to help organisations fully exploit the opportunities and capabilities of metaverse. Investigating the current limitations and expansion potential of metaverse, including the impact on different industries and economic sectors, is the main focus of this research. The data collection tool was the questionnaire that we distributed to groups in different companies in Romania, being completed by employees from both executive and management departments. In this study, we developed a conceptual model to investigate the factors that could positively influence the evolution of innovative business models in Romania. We opted for structural equation modelling using SmartPLS4 software. The present research also contributes to identifying and addressing the challenges and risks associated with metaversion. The analysis indicates that although the adoption of digital business models and innovative management practices is significant, their immediate impact on the long-term success of companies in the metaverse is somewhat limited. The metaverse represents both a risk and an excellent opportunity for entrepreneurs to leverage digital services for growth. We believe this research is necessary to uncover new innovative business opportunities, as understanding rapid technological change allows companies to remain competitive and adopt new technologies effectively.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"209 ","pages":"Article 123838"},"PeriodicalIF":12.9,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142535824","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}
Supply chain management is changing rapidly due to increasing complexity, uncertain demand, and the requirement for sustainable methods. Advanced technologies like Bidirectional Long Short-Term Memory networks (BiLSTM) and Convolutional Neural Networks (CNNs) can enhance supply chain processes. This paper proposes integrating CNNs and BiLSTM models to improve supply chain efficiency and sustainability. The proposed model employs CNNs to optimize resource allocation, uncover trends, and evaluate supply chain spatial linkages. Using BiLSTM models to capture temporal correlations allows accurate demand forecasting and proactive decision-making. Combining these models explains supply chain dynamics. CNNs and BiLSTM models' adaptive learning and real-time monitoring boost efficiency by responding quickly to changing situations. Predictive analytics optimizes inventory, lowers stock outs, and cuts lead times. Sustainability factors include transportation route optimization, carbon footprint minimization, and intelligent green-sourcing decision assistance. The proposed Hybrid Model achieved 94.65 % Specificity, 96.57 % Accuracy, 95.67 % Sensitivity and 0.85 % MCC. The result analysis demonstrates that the proposed model significantly improved the accuracy level. This research sheds light on supply chain difficulties from all sides. CNNs and BiLSTM models can boost operational efficiency and link supply chain practices with sustainability goals to produce a more sustainable global supply network.
{"title":"Improving efficiency and sustainability via supply chain optimization through CNNs and BiLSTM","authors":"Surjeet Dalal , Umesh Kumar Lilhore , Sarita Simaiya , Magdalena Radulescu , Lucian Belascu","doi":"10.1016/j.techfore.2024.123841","DOIUrl":"10.1016/j.techfore.2024.123841","url":null,"abstract":"<div><div>Supply chain management is changing rapidly due to increasing complexity, uncertain demand, and the requirement for sustainable methods. Advanced technologies like Bidirectional Long Short-Term Memory networks (BiLSTM) and Convolutional Neural Networks (CNNs) can enhance supply chain processes. This paper proposes integrating CNNs and BiLSTM models to improve supply chain efficiency and sustainability. The proposed model employs CNNs to optimize resource allocation, uncover trends, and evaluate supply chain spatial linkages. Using BiLSTM models to capture temporal correlations allows accurate demand forecasting and proactive decision-making. Combining these models explains supply chain dynamics. CNNs and BiLSTM models' adaptive learning and real-time monitoring boost efficiency by responding quickly to changing situations. Predictive analytics optimizes inventory, lowers stock outs, and cuts lead times. Sustainability factors include transportation route optimization, carbon footprint minimization, and intelligent green-sourcing decision assistance. The proposed Hybrid Model achieved 94.65 % Specificity, 96.57 % Accuracy, 95.67 % Sensitivity and 0.85 % MCC. The result analysis demonstrates that the proposed model significantly improved the accuracy level. This research sheds light on supply chain difficulties from all sides. CNNs and BiLSTM models can boost operational efficiency and link supply chain practices with sustainability goals to produce a more sustainable global supply network.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"209 ","pages":"Article 123841"},"PeriodicalIF":12.9,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142535827","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}
Pub Date : 2024-10-24DOI: 10.1016/j.techfore.2024.123824
Taelim Choi , Nancey Green Leigh
The paper explores the dynamics of labor demand creation and displacement from adopting artificial intelligence (AI) in US metropolitan statistical areas (MSAs). We combine unique online job postings and patent data to identify AI innovation and AI-skilled labor demand for specific industry sectors and locations. Our analysis shows that AI technologies are increasingly penetrating major industries and disproportionally generating new labor demand for AI-skilled workers in the MSAs in which AI innovation occurs. Our empirical model provides nascent evidence that demand for non-AI labor declines slightly in sectors and MSAs with higher AI skill adoption rates. This decline in labor demand is associated with non-routine cognitive analytical and inter-personal tasks in jobs not previously susceptible to displacement computerization.
{"title":"Artificial intelligence's creation and displacement of labor demand","authors":"Taelim Choi , Nancey Green Leigh","doi":"10.1016/j.techfore.2024.123824","DOIUrl":"10.1016/j.techfore.2024.123824","url":null,"abstract":"<div><div>The paper explores the dynamics of labor demand creation and displacement from adopting artificial intelligence (AI) in US metropolitan statistical areas (MSAs). We combine unique online job postings and patent data to identify AI innovation and AI-skilled labor demand for specific industry sectors and locations. Our analysis shows that AI technologies are increasingly penetrating major industries and disproportionally generating new labor demand for AI-skilled workers in the MSAs in which AI innovation occurs. Our empirical model provides nascent evidence that demand for non-AI labor declines slightly in sectors and MSAs with higher AI skill adoption rates. This decline in labor demand is associated with non-routine cognitive analytical and inter-personal tasks in jobs not previously susceptible to displacement computerization.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"209 ","pages":"Article 123824"},"PeriodicalIF":12.9,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142535820","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}
Pub Date : 2024-10-23DOI: 10.1016/j.techfore.2024.123828
Longda Li
With respect to the carbon reduction effects of digital transformation (DT), the literature focuses mainly on individual firms' performance, ignoring the environmental spillovers arising from supplier-buyer interactions from a supply chain perspective. By examining the positive impact of buyers' DT on suppliers' carbon emission reduction (CER), we validate the existence of buyers' DT environmental spillovers. This study collects and analyzes supply chain data of Chinese A-share listed firms during 2008–2021. We construct an ordinary least squares (OLS) model and perform a cluster-robust estimation with supplier-buyer pairs as clusters. Mechanism analysis identifies two environmental spillover mechanisms—the pushback and technology spillover effects. Moreover, we find a spatial decay pattern in the buyers' DT environmental spillovers. Heterogeneity analysis indicates that such spillovers are more pronounced when suppliers are identified as polluters or when the digitization gap is narrower. This study complements the green supply chain management (GSCM) literature and provides relevant suggestions for governments and manufacturing firms in emerging economies.
关于数字化转型（DT）的碳减排效应，文献主要关注单个企业的绩效，而忽视了从供应链角度看供应商与买方互动所产生的环境溢出效应。通过研究买方数字化转型对供应商碳减排（CER）的积极影响，我们验证了买方数字化转型环境溢出效应的存在。本研究收集并分析了 2008-2021 年中国 A 股上市公司的供应链数据。我们构建了一个普通最小二乘法（OLS）模型，并以供应商-买家对作为聚类进行了集群稳健估计。机制分析发现了两种环境溢出机制--倒逼效应和技术溢出效应。此外，我们还发现买方的 DT 环境溢出效应存在空间衰减模式。异质性分析表明，当供应商被认定为污染者或数字化差距较小时，这种溢出效应更为明显。本研究是对绿色供应链管理（GSCM）文献的补充，为新兴经济体的政府和制造企业提供了相关建议。
{"title":"The environmental spillovers of buyers' digital transformation: Evidence from China","authors":"Longda Li","doi":"10.1016/j.techfore.2024.123828","DOIUrl":"10.1016/j.techfore.2024.123828","url":null,"abstract":"<div><div>With respect to the carbon reduction effects of digital transformation (DT), the literature focuses mainly on individual firms' performance, ignoring the environmental spillovers arising from supplier-buyer interactions from a supply chain perspective. By examining the positive impact of buyers' DT on suppliers' carbon emission reduction (CER), we validate the existence of buyers' DT environmental spillovers. This study collects and analyzes supply chain data of Chinese A-share listed firms during 2008–2021. We construct an ordinary least squares (OLS) model and perform a cluster-robust estimation with supplier-buyer pairs as clusters. Mechanism analysis identifies two environmental spillover mechanisms—the pushback and technology spillover effects. Moreover, we find a spatial decay pattern in the buyers' DT environmental spillovers. Heterogeneity analysis indicates that such spillovers are more pronounced when suppliers are identified as polluters or when the digitization gap is narrower. This study complements the green supply chain management (GSCM) literature and provides relevant suggestions for governments and manufacturing firms in emerging economies.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"209 ","pages":"Article 123828"},"PeriodicalIF":12.9,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142535750","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}
Estimating the reliability of future energy supply chains is a vital yet complex task driven by environmental and energy security concerns in the context of the ongoing energy transition. This transition necessitates the integration of new technologies and systems into interconnected networks or supply chains. In this context, hydrogen plays a crucial role in the transition to green energy, as it is anticipated a surge in the establishment of “green” hydrogen supply chains (HSC), necessitating the assurance of reliability in meeting international roadmap targets. Technological reliability is typically evaluated by applying quantitative methods to current technologies. For future HSCs, the reliability assessment challenge is related to their prospective nature, with additional uncertainty due to the technologies' interdependencies. When stakeholders rely solely on technology readiness levels, essential aspects of the supply chain are not considered. This work introduces a novel methodology to assess the technological and organizational reliability of future HSCs, contributing to the literature on hydrogen reliability and strategic foresight. It also offers macro-level reliability projections for green HSCs by 2030, integrating input from energy experts and providing valuable insights for the scientific community, academia, and professionals. The proposed methodology's novelty lies in its ability to integrate various nodes of prospective HSCs. The study employs mixed methods, incorporating quantitative (multi-attribute utility theory) and qualitative approaches (horizon scanning). Variables such as capacity, flexibility, infrastructure vulnerability, and consequences of disruption are considered to quantify reliability, with twenty-four metrics included. Data collection employs the perspective of 2030 through a participatory study based on surveys and interviews, drawing insights from twenty-nine international experts associated with various HSCs-related technologies. The methodology is applied to a case study for a green HSC involving solar/wind energy, electrolysis, transportation, storage, and refueling stations. This paper presents the quantitative results, projecting moderate reliability for green HSCs by 2030. Solar HSCs have been considered slightly more reliable than wind HSCs. The interdependence of electrolysis technology and several aspects related to hydrogen transportation are perceived as vital risks affecting the reliability of green HSCs. Having a constant hydrogen supply is seen as a more significant challenge than HSC's response to unexpected interruptions. The research found specific disparities in expert opinions that enriched the data collection process with complementary viewpoints, benefiting from the former's heterogeneous profiles.
{"title":"A holistic approach to assessing reliability in green hydrogen supply chains using mixed methods","authors":"Sofía De-León Almaraz , Tchougoune Moustapha Mai , Iris Rocio Melendez , M.K. Loganathan , Catherine Azzaro-Pantel","doi":"10.1016/j.techfore.2024.123816","DOIUrl":"10.1016/j.techfore.2024.123816","url":null,"abstract":"<div><div>Estimating the reliability of future energy supply chains is a vital yet complex task driven by environmental and energy security concerns in the context of the ongoing energy transition. This transition necessitates the integration of new technologies and systems into interconnected networks or supply chains. In this context, hydrogen plays a crucial role in the transition to green energy, as it is anticipated a surge in the establishment of “green” hydrogen supply chains (HSC), necessitating the assurance of reliability in meeting international roadmap targets. Technological reliability is typically evaluated by applying quantitative methods to current technologies. For future HSCs, the reliability assessment challenge is related to their prospective nature, with additional uncertainty due to the technologies' interdependencies. When stakeholders rely solely on technology readiness levels, essential aspects of the supply chain are not considered. This work introduces a novel methodology to assess the technological and organizational reliability of future HSCs, contributing to the literature on hydrogen reliability and strategic foresight. It also offers macro-level reliability projections for green HSCs by 2030, integrating input from energy experts and providing valuable insights for the scientific community, academia, and professionals. The proposed methodology's novelty lies in its ability to integrate various nodes of prospective HSCs. The study employs mixed methods, incorporating quantitative (multi-attribute utility theory) and qualitative approaches (horizon scanning). Variables such as capacity, flexibility, infrastructure vulnerability, and consequences of disruption are considered to quantify reliability, with twenty-four metrics included. Data collection employs the perspective of 2030 through a participatory study based on surveys and interviews, drawing insights from twenty-nine international experts associated with various HSCs-related technologies. The methodology is applied to a case study for a green HSC involving solar/wind energy, electrolysis, transportation, storage, and refueling stations. This paper presents the quantitative results, projecting moderate reliability for green HSCs by 2030. Solar HSCs have been considered slightly more reliable than wind HSCs. The interdependence of electrolysis technology and several aspects related to hydrogen transportation are perceived as vital risks affecting the reliability of green HSCs. Having a constant hydrogen supply is seen as a more significant challenge than HSC's response to unexpected interruptions. The research found specific disparities in expert opinions that enriched the data collection process with complementary viewpoints, benefiting from the former's heterogeneous profiles.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"209 ","pages":"Article 123816"},"PeriodicalIF":12.9,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142535751","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}
Pub Date : 2024-10-22DOI: 10.1016/j.techfore.2024.123820
Rabia Akram , Qiyuan Li , Mohit Srivastava , Yulu Zheng , Muhammad Irfan
With the continuous evolution of the new technological revolution and industrial transformation, industrial robots' widespread application of artificial intelligence has profoundly influenced the economic growth model. The improvement of natural resource utilization efficiency is an essential indicator for measuring the high-quality development of the economy (HQED). This paper empirically analyzes the impact of artificial intelligence on the HQED using data from 275 cities in China from 2011 to 2020. The research results of this paper show that artificial intelligence significantly promotes the HQED, which is still maintained after a series of robustness tests. The mechanism analysis of this paper indicates that artificial intelligence promotes the HQED by enhancing energy transition, fostering green technology innovation, and mitigating climate policy uncertainty. Heterogeneity analysis shows that in non-old industrial base cities, non-resource-based cities, cities with more robust intellectual property protection, and cities with abundant human capital, the promoting effect of artificial intelligence on high-quality economic development is more substantial.
{"title":"Nexus between green technology innovation and climate policy uncertainty: Unleashing the role of artificial intelligence in an emerging economy","authors":"Rabia Akram , Qiyuan Li , Mohit Srivastava , Yulu Zheng , Muhammad Irfan","doi":"10.1016/j.techfore.2024.123820","DOIUrl":"10.1016/j.techfore.2024.123820","url":null,"abstract":"<div><div>With the continuous evolution of the new technological revolution and industrial transformation, industrial robots' widespread application of artificial intelligence has profoundly influenced the economic growth model. The improvement of natural resource utilization efficiency is an essential indicator for measuring the high-quality development of the economy (HQED). This paper empirically analyzes the impact of artificial intelligence on the HQED using data from 275 cities in China from 2011 to 2020. The research results of this paper show that artificial intelligence significantly promotes the HQED, which is still maintained after a series of robustness tests. The mechanism analysis of this paper indicates that artificial intelligence promotes the HQED by enhancing energy transition, fostering green technology innovation, and mitigating climate policy uncertainty. Heterogeneity analysis shows that in non-old industrial base cities, non-resource-based cities, cities with more robust intellectual property protection, and cities with abundant human capital, the promoting effect of artificial intelligence on high-quality economic development is more substantial.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"209 ","pages":"Article 123820"},"PeriodicalIF":12.9,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142535829","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}
Pub Date : 2024-10-22DOI: 10.1016/j.techfore.2024.123825
Xin Li, Yan Wang
With rapid developments in science and technology, knowledge transfer from science to technology and technology convergence from different fields are accelerating. Technology convergence has become a main source of disruptive technologies (DTs). To facilitate enterprise R&D strategic decision-making and government innovation policies formulation, it is necessary to quantify the convergence processes of DTs and understand the DTs' emergence characteristics from science to technology. Existing research on technology convergence measurement mainly used patent citation information, patent co-classification analysis, and text mining. However, since these studies have limited analysis of the sources and causes of technology convergence from the perspective of knowledge memes, resulting in insufficient revelation of the processes and characteristics of DTs' emergence. Knowledge meme theory helps to reveal the relationships between knowledge diffusion, knowledge convergence, and technology convergence. Therefore, in this paper, we proposed a research framework for quantifying the convergence of DTs from science to technology. In this framework, we analyzed the knowledge diffusion and technology convergence of DTs from science to technology based on knowledge meme theory. We also integrated patent citation analysis, text mining, and cascade network models to quantitatively measure knowledge diffusion and technology convergence characteristics. We tried to understand the generation mechanisms of DTs from the perspective of technology convergence. We took smartphones as a case study to verify the framework's validity and flexibility. This paper provides a novel approach for quantifying the convergence of DTs from science to technology, which can help us to understand the emergence and development trends of DTs. This paper will also be of interest to smartphone technology R&D experts.
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