Journal of Open Innovation: Technology, Market, and Complexity最新文献_第4页

The role of innovation dynamics on sustainable development goals: Interaction patterns based on the Triple Helix model 创新动态对可持续发展目标的作用：基于三螺旋模型的交互模式

Q1 Economics, Econometrics and Finance

Journal of Open Innovation: Technology, Market, and Complexity

Pub Date : 2025-12-17 DOI: 10.1016/j.joitmc.2025.100705

Mahshid G. Zadegan, Sepehr Ghazinoory

Since the United Nations introduced the Sustainable Development Goals (SDGs) in 2015, nations worldwide have launched a range of initiatives aimed at achieving these targets. However, the uneven SDGs progress across countries have raised fundamental questions regarding the underlying factors influencing these disparities. This study aims to examine the role of innovation dynamics in explaining the variation in national performance concerning the SDGs. To this end, it operationalizes the conceptual framework of the Triple Helix model of innovation, which identifies the dynamic interaction among three key institutions (universities, government, and industry)as the driving force behind innovation processes. After reviewing the theoretical literature on innovation dynamics and addressing conceptual challenges in existing studies, this research provides a clear and practical definition of the concept, making it suitable for statistical analysis. Building on the theoretical underpinnings of the Triple Helix model, this study evaluates how institutional interaction influences countries’ SDG performance during 2019 and 2024. To test the main hypothesis, four hierarchical regression models were developed. The dependent variable was the variance in sustainable development performance across countries during the specified period, while the independent variables included standardized performance scores of governments, industry, and academia, as well as indicators of bilateral and trilateral institutional interactions. These were analyzed while controlling for economic, political, cultural, and natural conditions. The results reveal that trilateral collaboration among universities, industry, and government has a highly significant and positive impact on sustainable development performance, whereas the isolated effects of individual institutions were limited or statistically insignificant. In addition, bilateral government–industry collaboration showed an independently significant contribution. The findings underscore that innovation dynamics and the structure of institutional interaction play a critical role in determining national success in achieving SDGs. This study offers a structured framework for evaluating institutional collaboration at the national level, and highlights the Triple Helix model as a key framework for sustainable development policymaking.

自2015年联合国提出可持续发展目标（sdg）以来，世界各国发起了一系列旨在实现这些目标的举措。然而，各国在可持续发展目标方面的进展参差不齐，对影响这些差异的根本因素提出了根本性问题。本研究旨在探讨创新动态在解释可持续发展目标相关国家绩效差异中的作用。为此，本文运用了创新三重螺旋模型的概念框架，该模型将三个关键机构（大学、政府和行业）之间的动态互动确定为创新过程背后的驱动力。在回顾了有关创新动力学的理论文献并解决了现有研究中的概念挑战后，本研究提供了一个清晰实用的概念定义，使其适合于统计分析。在三螺旋模型的理论基础上，本研究评估了机构互动如何影响各国在2019年和2024年期间的可持续发展目标绩效。为了检验主要假设，我们建立了四个层次回归模型。因变量是各国在特定时期内可持续发展绩效的差异，而自变量包括政府、行业和学术界的标准化绩效得分，以及双边和三边机构互动的指标。这些都是在控制经济、政治、文化和自然条件的情况下进行分析的。结果表明，大学、产业和政府三方合作对可持续发展绩效具有显著的正向影响，而个别机构的孤立效应有限或统计不显著。此外，双边政府-产业合作也显示出独立的显著贡献。研究结果强调，创新动态和机构互动结构在决定国家能否成功实现可持续发展目标方面发挥着关键作用。本研究为评估国家层面的机构合作提供了一个结构化框架，并强调了三螺旋模型作为可持续发展政策制定的关键框架。

{"title":"The role of innovation dynamics on sustainable development goals: Interaction patterns based on the Triple Helix model","authors":"Mahshid G. Zadegan, Sepehr Ghazinoory","doi":"10.1016/j.joitmc.2025.100705","DOIUrl":"10.1016/j.joitmc.2025.100705","url":null,"abstract":"<div><div>Since the United Nations introduced the Sustainable Development Goals (SDGs) in 2015, nations worldwide have launched a range of initiatives aimed at achieving these targets. However, the uneven SDGs progress across countries have raised fundamental questions regarding the underlying factors influencing these disparities. This study aims to examine the role of innovation dynamics in explaining the variation in national performance concerning the SDGs. To this end, it operationalizes the conceptual framework of the Triple Helix model of innovation, which identifies the dynamic interaction among three key institutions (universities, government, and industry)as the driving force behind innovation processes. After reviewing the theoretical literature on innovation dynamics and addressing conceptual challenges in existing studies, this research provides a clear and practical definition of the concept, making it suitable for statistical analysis. Building on the theoretical underpinnings of the Triple Helix model, this study evaluates how institutional interaction influences countries’ SDG performance during 2019 and 2024. To test the main hypothesis, four hierarchical regression models were developed. The dependent variable was the variance in sustainable development performance across countries during the specified period, while the independent variables included standardized performance scores of governments, industry, and academia, as well as indicators of bilateral and trilateral institutional interactions. These were analyzed while controlling for economic, political, cultural, and natural conditions. The results reveal that trilateral collaboration among universities, industry, and government has a highly significant and positive impact on sustainable development performance, whereas the isolated effects of individual institutions were limited or statistically insignificant. In addition, bilateral government–industry collaboration showed an independently significant contribution. The findings underscore that innovation dynamics and the structure of institutional interaction play a critical role in determining national success in achieving SDGs. This study offers a structured framework for evaluating institutional collaboration at the national level, and highlights the Triple Helix model as a key framework for sustainable development policymaking.</div></div>","PeriodicalId":16678,"journal":{"name":"Journal of Open Innovation: Technology, Market, and Complexity","volume":"12 1","pages":"Article 100705"},"PeriodicalIF":0.0,"publicationDate":"2025-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145837392","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Resistance intention towards mobile payment among Gen X: Evidence from an emerging country X世代对移动支付的抗拒意向：来自一个新兴国家的证据

Q1 Economics, Econometrics and Finance

Journal of Open Innovation: Technology, Market, and Complexity

Pub Date : 2025-12-12 DOI: 10.1016/j.joitmc.2025.100703

Saiful Islam , Muhaiminul Islam , Farjana Rahman , Md. Aftab Uddin

This study explores users' intentions to resist mobile payment (m-payment) adoption in the emerging economy, combining functional and psychological factors from the innovation resistance theory (IRT) and push, pull, and mooring (PPM) theory. Using a mixed research approach, data is collected from 400 respondents through a survey questionnaire, and from 10 participants in a focus group discussion (FGD). The partial least squares structural equation modeling (PLS-SEM) is used to test the hypotheses, and the results in FGD are summarized to analyze and cross-validate the empirical findings. Results indicate that, while psychological factors substantially affect users' intention to resist m-payment, functional factors have no significant impact. Perceived monetary value as a pull factor and switching costs and inertia as mooring factors also significantly influence users' intention to resist m-payment. Users’ intention to resist m-payment can lead to two possible outcomes: a complete rejection of m-payment and postponement of adoption, where personal innovativeness significantly moderates the second outcome. These findings have several theoretical and managerial implications for m-payment developers, policymakers, and other stakeholders in reducing resistance to m-payment adoption.

本研究结合创新阻力理论（IRT）和推拉系泊（PPM）理论的功能因素和心理因素，探讨了新兴经济体中用户抵制移动支付（m-payment）采用的意愿。采用混合研究方法，通过调查问卷从400名受访者中收集数据，并从10名焦点小组讨论（FGD）参与者中收集数据。采用偏最小二乘结构方程模型（PLS-SEM）对假设进行检验，并对烟气脱硫的结果进行总结分析，对实证结果进行交叉验证。结果表明，心理因素对用户抵制移动支付意愿有显著影响，功能因素对用户抵制移动支付意愿的影响不显著。感知货币价值作为拉动因素，转换成本和惯性作为停泊因素也显著影响用户抵制移动支付的意愿。用户抵制移动支付的意图可能导致两种可能的结果：完全拒绝移动支付和推迟采用移动支付，其中个人创新显著地缓和了第二种结果。这些发现对移动支付开发者、政策制定者和其他利益相关者在减少对移动支付采用的阻力方面具有一些理论和管理意义。

{"title":"Resistance intention towards mobile payment among Gen X: Evidence from an emerging country","authors":"Saiful Islam , Muhaiminul Islam , Farjana Rahman , Md. Aftab Uddin","doi":"10.1016/j.joitmc.2025.100703","DOIUrl":"10.1016/j.joitmc.2025.100703","url":null,"abstract":"<div><div>This study explores users' intentions to resist mobile payment (m-payment) adoption in the emerging economy, combining functional and psychological factors from the innovation resistance theory (IRT) and push, pull, and mooring (PPM) theory. Using a mixed research approach, data is collected from 400 respondents through a survey questionnaire, and from 10 participants in a focus group discussion (FGD). The partial least squares structural equation modeling (PLS-SEM) is used to test the hypotheses, and the results in FGD are summarized to analyze and cross-validate the empirical findings. Results indicate that, while psychological factors substantially affect users' intention to resist m-payment, functional factors have no significant impact. Perceived monetary value as a pull factor and switching costs and inertia as mooring factors also significantly influence users' intention to resist m-payment. Users’ intention to resist m-payment can lead to two possible outcomes: a complete rejection of m-payment and postponement of adoption, where personal innovativeness significantly moderates the second outcome. These findings have several theoretical and managerial implications for m-payment developers, policymakers, and other stakeholders in reducing resistance to m-payment adoption.</div></div>","PeriodicalId":16678,"journal":{"name":"Journal of Open Innovation: Technology, Market, and Complexity","volume":"12 1","pages":"Article 100703"},"PeriodicalIF":0.0,"publicationDate":"2025-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145797430","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Consumer intensity drivers and adaptive marketing agility: Empirical evidence of mediating spillovers and co-evolution with moderating algorithmic amplification 消费者强度驱动因素与适应性营销敏捷性：中介溢出和协同进化与调节算法放大的实证证据

Q1 Economics, Econometrics and Finance

Journal of Open Innovation: Technology, Market, and Complexity

Pub Date : 2025-12-09 DOI: 10.1016/j.joitmc.2025.100701

Rohit Bansal , Y. Suryanarayana Murthy , Nishita Pruthi , Aulia Luqman Aziz , Arfendo Propheto

The consumer intensity drivers, such as co-creation, digital brand passion, zealotry orientation, micro-community evangelism, gamification appeal, narrative identity alignment, and sustainability-related brand love are crucial drivers of marketing in the rapidly changing digital ecosystems. This paper empirically investigates the role of these antecedents in increasing the adaptive marketing agility via the two mediation mechanisms of open innovation spillovers and consumer-brand co-evolution, and further hypothesizes the moderating effect of algorithmic social amplification. It used a survey-based design where the responses were collected among the consumers who were participating in online brand communities. Through structural equation modelling (SEM), the analysis established that consumer intensity drivers have a significant impact on the mediators which in turn have a positive impact on adaptive marketing agility. In addition, the mediated pathways were found to be moderated by algorithmic amplification, which enhanced the process of translation of spillovers and co-evolution into agility outcomes. Theoretically, Service-Dominant Logic and Dynamic Capabilities Theory are extended in the study by showing how the intensity of consumers can be translated into organizational adaptability in the context of algorithmically mediated environments. In practice, the results will give managers a strategy to take advantage of consumer intensity drivers, nurture innovation spill-overs, build co-evolutionary relationships, and be platform-congruent to maintain agility in competitive digital markets.

消费者强度驱动因素，如共同创造、数字品牌激情、狂热导向、微社区布道、游戏化吸引力、叙事身份一致性和与可持续性相关的品牌热爱，是快速变化的数字生态系统中营销的关键驱动因素。本文通过开放式创新溢出和消费者-品牌协同进化两种中介机制实证考察了这些前因变量在提高适应性营销敏捷性中的作用，并进一步假设了算法社会放大的调节作用。它采用了基于调查的设计，从参与在线品牌社区的消费者中收集反馈。通过结构方程模型（SEM），分析确定消费者强度驱动因素对中介因素有显著影响，中介因素反过来对适应性营销敏捷性有积极影响。此外，研究还发现，这些中介途径被算法放大所调节，从而增强了溢出效应和协同进化转化为敏捷性结果的过程。从理论上讲，服务主导逻辑和动态能力理论在研究中得到扩展，展示了消费者的强度如何在算法介导的环境中转化为组织适应性。在实践中，研究结果将为管理者提供一种策略，以利用消费者强度驱动因素，培育创新溢出效应，建立共同进化关系，并与平台一致，以在竞争激烈的数字市场中保持敏捷性。

{"title":"Consumer intensity drivers and adaptive marketing agility: Empirical evidence of mediating spillovers and co-evolution with moderating algorithmic amplification","authors":"Rohit Bansal , Y. Suryanarayana Murthy , Nishita Pruthi , Aulia Luqman Aziz , Arfendo Propheto","doi":"10.1016/j.joitmc.2025.100701","DOIUrl":"10.1016/j.joitmc.2025.100701","url":null,"abstract":"<div><div>The consumer intensity drivers, such as co-creation, digital brand passion, zealotry orientation, micro-community evangelism, gamification appeal, narrative identity alignment, and sustainability-related brand love are crucial drivers of marketing in the rapidly changing digital ecosystems. This paper empirically investigates the role of these antecedents in increasing the adaptive marketing agility via the two mediation mechanisms of open innovation spillovers and consumer-brand co-evolution, and further hypothesizes the moderating effect of algorithmic social amplification. It used a survey-based design where the responses were collected among the consumers who were participating in online brand communities. Through structural equation modelling (SEM), the analysis established that consumer intensity drivers have a significant impact on the mediators which in turn have a positive impact on adaptive marketing agility. In addition, the mediated pathways were found to be moderated by algorithmic amplification, which enhanced the process of translation of spillovers and co-evolution into agility outcomes. Theoretically, Service-Dominant Logic and Dynamic Capabilities Theory are extended in the study by showing how the intensity of consumers can be translated into organizational adaptability in the context of algorithmically mediated environments. In practice, the results will give managers a strategy to take advantage of consumer intensity drivers, nurture innovation spill-overs, build co-evolutionary relationships, and be platform-congruent to maintain agility in competitive digital markets.</div></div>","PeriodicalId":16678,"journal":{"name":"Journal of Open Innovation: Technology, Market, and Complexity","volume":"12 1","pages":"Article 100701"},"PeriodicalIF":0.0,"publicationDate":"2025-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145797429","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Understanding the pathway from market-based capability to performance of Korean firms on the basis of Dynamic Capability and Resource-Advantage theory 基于动态能力和资源优势理论的韩国企业从市场能力到绩效的路径研究

Q1 Economics, Econometrics and Finance

Journal of Open Innovation: Technology, Market, and Complexity

Pub Date : 2025-12-07 DOI: 10.1016/j.joitmc.2025.100699

Sungho Lee , Sohyoun Shin

This research identifies market-based capability dimensions based on Teece’s (2007) first two classes of dynamic capability—sensing capability and seizing capability—and investigates their impacts on firm performance. By incorporating Resource-Advantage theory as a complement to the primary framework of dynamic capability, the concept of market positional advantage (MPA) is introduced and empirically tested as an assessment signpost linking the capability dimensions and firm performance. Accordingly, this study addresses a research gap by exploring the full scope of market-based capabilities and clarifying the pathway through which they influence firm performance in a non-Western context, South Korea. Through LISREL structural equation modeling based on survey responses from 245 managers of Korean firms, the study finds that the seizing capability dimension of market-based capability—including product management capability (PMC), customer management capability (CMC), and supply chain management capability (SCMC)—positively influences firm performance via market positional advantage (MPA). As a sensing capability, market-insight capability (MIC) is proven to affect the three capability dimensions, indicating its critical leading role in building organizational capability collection. As the firms’ own idiosyncratic process of continuous feedback and resource recomposition repeats, we argue that the last class of Teece’s (2007) dynamic capability—transformational/reconfiguring capability—can be cultivated. This study advances theoretical perspectives on the marketing capability–performance relationship and offers practical guidance for managers seeking to enhance firm performance and develop strategic investment in capability building.

本研究基于Teece（2007）的前两类动态能力——感知能力和把握能力，确定了基于市场的能力维度，并研究了它们对企业绩效的影响。通过将资源优势理论作为对动态能力基本框架的补充，引入市场位置优势概念，并对其作为连接能力维度与企业绩效的评估标志进行实证检验。因此，本研究通过探索基于市场的能力的全部范围，并阐明它们在非西方背景下（韩国）影响公司绩效的途径，解决了研究空白。基于245位韩国企业管理者的问卷调查，通过LISREL结构方程模型，研究发现市场能力的把握能力维度——包括产品管理能力（PMC）、客户管理能力（CMC）和供应链管理能力（SCMC）——通过市场位置优势（MPA）正向影响企业绩效。市场洞察能力作为一种感知能力，对三个能力维度均有影响，表明其在构建组织能力集合中起着至关重要的主导作用。随着企业自身持续反馈和资源重组的特殊过程不断重复，我们认为Teece（2007）的最后一类动态能力——转型/重新配置能力——是可以培养的。本研究提出了营销能力与绩效关系的理论视角，并为寻求提高企业绩效和在能力建设方面进行战略投资的管理者提供了实践指导。

{"title":"Understanding the pathway from market-based capability to performance of Korean firms on the basis of Dynamic Capability and Resource-Advantage theory","authors":"Sungho Lee , Sohyoun Shin","doi":"10.1016/j.joitmc.2025.100699","DOIUrl":"10.1016/j.joitmc.2025.100699","url":null,"abstract":"<div><div>This research identifies market-based capability dimensions based on Teece’s (2007) first two classes of dynamic capability—<em>sensing</em> capability and <em>seizing</em> capability—and investigates their impacts on firm performance. By incorporating Resource-Advantage theory as a complement to the primary framework of dynamic capability, the concept of market positional advantage (MPA) is introduced and empirically tested as an assessment signpost linking the capability dimensions and firm performance. Accordingly, this study addresses a research gap by exploring the full scope of market-based capabilities and clarifying the pathway through which they influence firm performance in a non-Western context, South Korea. Through LISREL structural equation modeling based on survey responses from 245 managers of Korean firms, the study finds that the seizing capability dimension of market-based capability—including product management capability (PMC), customer management capability (CMC), and supply chain management capability (SCMC)—positively influences firm performance via market positional advantage (MPA). As a sensing capability, market-insight capability (MIC) is proven to affect the three capability dimensions, indicating its critical leading role in building organizational capability collection. As the firms’ own idiosyncratic process of continuous feedback and resource recomposition repeats, we argue that the last class of Teece’s (2007) dynamic capability—transformational/reconfiguring capability—can be cultivated. This study advances theoretical perspectives on the marketing capability–performance relationship and offers practical guidance for managers seeking to enhance firm performance and develop strategic investment in capability building.</div></div>","PeriodicalId":16678,"journal":{"name":"Journal of Open Innovation: Technology, Market, and Complexity","volume":"12 1","pages":"Article 100699"},"PeriodicalIF":0.0,"publicationDate":"2025-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145977072","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Factors influencing circular economy business model adoption: Evidence from NCA and PLS-SEM 影响循环经济商业模式采用的因素：来自NCA和PLS-SEM的证据

Q1 Economics, Econometrics and Finance

Journal of Open Innovation: Technology, Market, and Complexity

Pub Date : 2025-12-04 DOI: 10.1016/j.joitmc.2025.100697

Noor Ul Hadi , M. Imran Khan

Several studies have examined the factors influencing circular economy business model adoption. However, understanding remains limited from the perspective of Necessary Condition Analysis, leaving a notable gap in circular economy research that explicitly applies Necessary Condition Analysis to uncover the hidden conditions necessary for the successful implementation of circular strategies in business organizations. Drawing on the Resource-Based View and Stakeholder Theory, this study combines Partial Least Squares Structural Equation Modeling (PLS-SEM) with Necessary Condition Analysis (NCA) to distinguish “should-have” associations from “must-have” thresholds. Using survey data from 209 marble manufacturing firms, we examine eight factors: circular human resource management, circular entrepreneurship, circular marketing, circular financing, circular manufacturing technologies, circular-oriented workplace culture, circular open innovation, and government support. The integrated results show that several internal capabilities and one institutional factor are both necessary and sufficient (circular human resource management, circular entrepreneurship, circular manufacturing technologies, circular-oriented culture, government support), circular open innovation is necessary-only, circular financing is sufficient-only, and circular marketing is neither in this context. NCA bottleneck thresholds provide actionable benchmarks indicating minimum levels each necessary condition must meet at different target levels of CEBM adoption. Methodologically, the study demonstrates how a dual-logic approach reveals hidden constraints that sufficiency models alone overlook. Theoretically, it reframes selected capabilities and institutional enablers as foundational preconditions rather than merely supportive resources. Practically, it offers a sequenced roadmap: meet the lowest unmet threshold first, then deploy sufficiency levers to scale circular outcomes supporting managers and policymakers seeking credible pathways toward a regenerative, circular economy.

一些研究考察了影响采用循环经济商业模式的因素。然而，从必要条件分析的角度来看，对循环经济的理解仍然有限，在循环经济研究中，明确运用必要条件分析来揭示企业组织成功实施循环战略所必需的隐藏条件的研究仍然存在明显的空白。基于资源基础观点和利益相关者理论，本研究将偏最小二乘结构方程模型（PLS-SEM）与必要条件分析（NCA）相结合，以区分“应该拥有”与“必须拥有”的关联阈值。利用209家大理石制造企业的调查数据，我们考察了8个因素：循环人力资源管理、循环创业、循环营销、循环融资、循环制造技术、循环导向的工作场所文化、循环开放式创新和政府支持。综合研究结果表明，在此背景下，几个内部能力和一个制度因素（循环人力资源管理、循环创业、循环制造技术、循环导向文化、政府支持）是必要和充分的，循环开放式创新是必要的，循环融资是充分的，而循环营销两者都不是。NCA瓶颈阈值提供了可操作的基准，表明在CEBM采用的不同目标级别上，每个必要条件必须满足的最低水平。在方法上，该研究展示了双重逻辑方法如何揭示了单独的充分性模型所忽略的隐藏约束。从理论上讲，它将选定的能力和制度促成因素重新定义为基础先决条件，而不仅仅是支持性资源。实际上，它提供了一个有序的路线图：首先满足最低的未满足阈值，然后部署充足的杠杆来扩大循环成果，支持管理者和政策制定者寻求通向再生循环经济的可靠途径。

{"title":"Factors influencing circular economy business model adoption: Evidence from NCA and PLS-SEM","authors":"Noor Ul Hadi , M. Imran Khan","doi":"10.1016/j.joitmc.2025.100697","DOIUrl":"10.1016/j.joitmc.2025.100697","url":null,"abstract":"<div><div>Several studies have examined the factors influencing circular economy business model adoption. However, understanding remains limited from the perspective of Necessary Condition Analysis, leaving a notable gap in circular economy research that explicitly applies Necessary Condition Analysis to uncover the hidden conditions necessary for the successful implementation of circular strategies in business organizations. Drawing on the Resource-Based View and Stakeholder Theory, this study combines Partial Least Squares Structural Equation Modeling (PLS-SEM) with Necessary Condition Analysis (NCA) to distinguish “should-have” associations from “must-have” thresholds. Using survey data from 209 marble manufacturing firms, we examine eight factors: circular human resource management, circular entrepreneurship, circular marketing, circular financing, circular manufacturing technologies, circular-oriented workplace culture, circular open innovation, and government support. The integrated results show that several internal capabilities and one institutional factor are both necessary and sufficient (circular human resource management, circular entrepreneurship, circular manufacturing technologies, circular-oriented culture, government support), circular open innovation is necessary-only<strong>,</strong> circular financing is sufficient-only, and circular marketing is neither in this context. NCA bottleneck thresholds provide actionable benchmarks indicating minimum levels each necessary condition must meet at different target levels of CEBM adoption. Methodologically, the study demonstrates how a dual-logic approach reveals hidden constraints that sufficiency models alone overlook. Theoretically, it reframes selected capabilities and institutional enablers as foundational preconditions rather than merely supportive resources. Practically, it offers a sequenced roadmap: meet the lowest unmet threshold first, then deploy sufficiency levers to scale circular outcomes supporting managers and policymakers seeking credible pathways toward a regenerative, circular economy.</div></div>","PeriodicalId":16678,"journal":{"name":"Journal of Open Innovation: Technology, Market, and Complexity","volume":"12 1","pages":"Article 100697"},"PeriodicalIF":0.0,"publicationDate":"2025-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145748556","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Economic policy uncertainty and artificial intelligence (AI) innovation: A cross-country analysis 经济政策不确定性与人工智能（AI）创新：一个跨国分析

Q1 Economics, Econometrics and Finance

Journal of Open Innovation: Technology, Market, and Complexity

Pub Date : 2025-12-04 DOI: 10.1016/j.joitmc.2025.100698

Tuan-Hock Ng , Chun-Teck Lye , Ying-San Lim , Ying-Zhee Lim

As nations vie for a strategic edge in artificial intelligence (AI), sustaining innovation has shifted from priority to imperative. Yet, economic policy uncertainty (EPU) presents a particularly salient threat, capable of derailing the investment and research and development (R&D) activities that underpin AI breakthroughs. Against this backdrop, this study examines the relationship between EPU and AI innovation in 34 countries from 2017 to 2023, using quantile regression to delineate heterogeneous effects across the innovation distribution. The results indicate that EPU exerts a significantly negative effect on AI innovation, with disproportionately stronger adverse effects observed in countries at lower innovation quantiles. These results remain robust across pooled ordinary least squares (OLS), fixed and random effects models, generalised method of moments (GMM), and placebo tests. As one of the earliest empirical investigations into the asymmetric effects of EPU on AI innovation, this study contributes novel insights to the open innovation literature and ongoing policy dialogue. Collectively, the findings highlight the importance of stable and predictable policy environments in bolstering national innovation ecosystems and narrowing the global AI innovation gap.

随着各国争夺人工智能（AI）的战略优势，持续创新已经从优先事项转变为当务之急。然而，经济政策的不确定性（EPU）提出了一个特别突出的威胁，能够破坏支撑人工智能突破的投资和研发（R&；D）活动。在此背景下，本研究考察了2017年至2023年34个国家的EPU与人工智能创新之间的关系，使用分位数回归来描述创新分布中的异质性效应。结果表明，EPU对人工智能创新具有显著的负面影响，在创新分位数较低的国家中，这种负面影响尤为明显。这些结果在合并普通最小二乘（OLS）、固定和随机效应模型、广义矩量法（GMM）和安慰剂测试中都保持稳健。作为最早研究EPU对人工智能创新不对称效应的实证研究之一，本研究为开放式创新文献和持续的政策对话提供了新的见解。总的来说，研究结果强调了稳定和可预测的政策环境对于加强国家创新生态系统和缩小全球人工智能创新差距的重要性。

{"title":"Economic policy uncertainty and artificial intelligence (AI) innovation: A cross-country analysis","authors":"Tuan-Hock Ng , Chun-Teck Lye , Ying-San Lim , Ying-Zhee Lim","doi":"10.1016/j.joitmc.2025.100698","DOIUrl":"10.1016/j.joitmc.2025.100698","url":null,"abstract":"<div><div>As nations vie for a strategic edge in artificial intelligence (AI), sustaining innovation has shifted from priority to imperative. Yet, economic policy uncertainty (EPU) presents a particularly salient threat, capable of derailing the investment and research and development (R&D) activities that underpin AI breakthroughs. Against this backdrop, this study examines the relationship between EPU and AI innovation in 34 countries from 2017 to 2023, using quantile regression to delineate heterogeneous effects across the innovation distribution. The results indicate that EPU exerts a significantly negative effect on AI innovation, with disproportionately stronger adverse effects observed in countries at lower innovation quantiles. These results remain robust across pooled ordinary least squares (OLS), fixed and random effects models, generalised method of moments (GMM), and placebo tests. As one of the earliest empirical investigations into the asymmetric effects of EPU on AI innovation, this study contributes novel insights to the open innovation literature and ongoing policy dialogue. Collectively, the findings highlight the importance of stable and predictable policy environments in bolstering national innovation ecosystems and narrowing the global AI innovation gap.</div></div>","PeriodicalId":16678,"journal":{"name":"Journal of Open Innovation: Technology, Market, and Complexity","volume":"12 1","pages":"Article 100698"},"PeriodicalIF":0.0,"publicationDate":"2025-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145748557","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","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 shock in manufacturing: A threat or an opportunity for South Africa’s Labour Market? 制造业的人工智能冲击：对南非劳动力市场是威胁还是机遇？

Q1 Economics, Econometrics and Finance

Journal of Open Innovation: Technology, Market, and Complexity

Pub Date : 2025-12-02 DOI: 10.1016/j.joitmc.2025.100696

Fiyinfoluwa Giwa, Sin-Yu Ho

Existing research on artificial intelligence (AI) has focused predominantly on its productivity effects in advanced economies, leaving a critical gap in understanding its labour market consequences in developing nations. This study addresses this gap by examining how AI shocks shape employment dynamics in South Africa’s manufacturing sector—a pivotal industry characterised by structural unemployment and uneven technological readiness. Using quarterly data (2014–2024) and a Structural Vector Autoregression (SVAR) model, we find that a positive AI shock triggers an immediate and statistically significant contraction in employment. This negative effect, consistent with task-based theory, persists over the short to medium term, with variance decomposition showing that AI shocks account for nearly 30 % of forecast-error variance in manufacturing employment over a ten-quarter horizon. These findings demonstrate the distinct risks of automation in developing economies and underscore the urgent need for policies that foster human-AI complementarity, such as reskilling and incentives for labour-augmenting technologies. Beyond its employment effects, the study contributes to open-innovation research by demonstrating how AI diffusion shapes technological learning and adaptive industrial capacity in South Africa’s manufacturing sector. The results provide policy guidance for aligning AI adoption with labour market priorities to support inclusive and innovation-oriented industrial growth.

关于人工智能（AI）的现有研究主要集中在其对发达经济体的生产率影响上，在理解其对发展中国家劳动力市场的影响方面存在重大空白。本研究通过研究人工智能冲击如何影响南非制造业的就业动态来解决这一差距，制造业是一个以结构性失业和技术准备不均衡为特征的关键行业。使用季度数据（2014-2024年）和结构向量自回归（SVAR）模型，我们发现积极的人工智能冲击触发了就业的立即和统计上显着的收缩。这种负面影响与基于任务的理论一致，在中短期内持续存在，方差分解显示，人工智能冲击占制造业就业预测误差方差的近30% %，超过10个季度。这些发现表明，自动化在发展中经济体中存在明显的风险，并强调迫切需要制定促进人类与人工智能互补的政策，例如再培训和激励劳动力增加技术。除了对就业的影响外，该研究还通过展示人工智能扩散如何影响南非制造业的技术学习和适应性工业能力，为开放式创新研究做出了贡献。研究结果为将人工智能应用与劳动力市场重点结合起来，支持包容性和创新型工业增长提供了政策指导。

{"title":"Artificial intelligence shock in manufacturing: A threat or an opportunity for South Africa’s Labour Market?","authors":"Fiyinfoluwa Giwa, Sin-Yu Ho","doi":"10.1016/j.joitmc.2025.100696","DOIUrl":"10.1016/j.joitmc.2025.100696","url":null,"abstract":"<div><div>Existing research on artificial intelligence (AI) has focused predominantly on its productivity effects in advanced economies, leaving a critical gap in understanding its labour market consequences in developing nations. This study addresses this gap by examining how AI shocks shape employment dynamics in South Africa’s manufacturing sector—a pivotal industry characterised by structural unemployment and uneven technological readiness. Using quarterly data (2014–2024) and a Structural Vector Autoregression (SVAR) model, we find that a positive AI shock triggers an immediate and statistically significant contraction in employment. This negative effect, consistent with task-based theory, persists over the short to medium term, with variance decomposition showing that AI shocks account for nearly 30 % of forecast-error variance in manufacturing employment over a ten-quarter horizon. These findings demonstrate the distinct risks of automation in developing economies and underscore the urgent need for policies that foster human-AI complementarity, such as reskilling and incentives for labour-augmenting technologies. Beyond its employment effects, the study contributes to open-innovation research by demonstrating how AI diffusion shapes technological learning and adaptive industrial capacity in South Africa’s manufacturing sector. The results provide policy guidance for aligning AI adoption with labour market priorities to support inclusive and innovation-oriented industrial growth.</div></div>","PeriodicalId":16678,"journal":{"name":"Journal of Open Innovation: Technology, Market, and Complexity","volume":"12 1","pages":"Article 100696"},"PeriodicalIF":0.0,"publicationDate":"2025-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145692440","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Hybrid early warning system: Integration of Z-score and machine learning for predicting financial performance of IRB in Indonesia 混合预警系统：整合Z-score和机器学习来预测印尼IRB的财务表现

Q1 Economics, Econometrics and Finance

Journal of Open Innovation: Technology, Market, and Complexity

Pub Date : 2025-12-02 DOI: 10.1016/j.joitmc.2025.100694

Imron Mawardi , Andi Estetiono , Tika Widiastuti , Anidah Robani , Muhammad Ubaidillah Al Mustofa , Faris Kurnia Hakim , Qothrotunnidha Almaulidiyah , Eka Puspa Dewi

Purpose

This study aims to develop a hybrid Early Warning System (EWS) that integrates the traditional Z-score method with machine learning algorithms to accurately predict the financial performance and potential failure of IRB in Indonesia.

Design/methodology/approach

The study employs a data science–driven approach using monthly financial and macroeconomic data from 2011 to 2024. A total of 21 independent variables were tested against the Z-score as the dependent variable. Various machine learning models were compared using AutoML (TPOT and LazyRegressor), and model validation was conducted through statistical testing, cross-validation, robustness checks, and feature importance analysis.

Findings

The Extra Trees algorithm emerged as the most accurate and robust predictive model, achieving an R² of 0.95 and the lowest Mean Absolute Error (MAE) of 0.0676. Key predictive variables identified include Non-Performing Financing (NPF), inflation (INF), and istishna'-based Financing. The model successfully anticipates financial distress up to two years in advance and enables the categorisation of IRB conditions into Stable, Vulnerable, and Unstable using Z-score thresholds.

Originality/value

This is the first study to integrate Z-score with advanced machine learning techniques within a hybrid EWS framework tailored to IRB. It offers a novel predictive model that enhances early risk detection and supports regulatory decision-making.

Limitation

The study focuses exclusively on IRB in Indonesia and may require recalibration for broader application in different financial systems or geographies. Reporting accuracy and completeness may also limit the use of secondary data.

Practical implications

The hybrid model provides actionable insights for regulators (OJK, LPS) and financial institutions to monitor IRB's health proactively. It strengthens risk mitigation strategies and contributes to the long-term resilience of the Islamic microfinance sector.

本研究旨在开发一种混合预警系统（EWS），该系统将传统的Z-score方法与机器学习算法相结合，以准确预测印度尼西亚IRB的财务绩效和潜在失败。设计/方法/方法本研究采用数据科学驱动的方法，使用2011年至2024年的月度金融和宏观经济数据。以z分数为因变量，共检验21个自变量。使用AutoML （TPOT和LazyRegressor）对各种机器学习模型进行比较，并通过统计检验、交叉验证、鲁棒性检查和特征重要性分析对模型进行验证。Extra Trees算法是最准确、最稳健的预测模型，R²为0.95，平均绝对误差（MAE）最低，为0.0676。确定的关键预测变量包括不良融资（NPF）、通货膨胀（INF）和基于银行的融资。该模型成功地预测了长达两年的财务困境，并使用z分数阈值将IRB条件分为稳定、脆弱和不稳定。这是第一个将Z-score与先进的机器学习技术集成到为IRB量身定制的混合EWS框架中的研究。它提供了一种新的预测模型，可以增强早期风险检测并支持监管决策。局限性：本研究仅关注印度尼西亚的IRB，可能需要重新调整以更广泛地应用于不同的金融体系或地区。报告的准确性和完整性也可能限制二手数据的使用。实际意义混合模型为监管机构（OJK， LPS）和金融机构主动监测IRB的健康状况提供了可操作的见解。它加强了风险缓解战略，并有助于伊斯兰小额信贷部门的长期复原力。

{"title":"Hybrid early warning system: Integration of Z-score and machine learning for predicting financial performance of IRB in Indonesia","authors":"Imron Mawardi , Andi Estetiono , Tika Widiastuti , Anidah Robani , Muhammad Ubaidillah Al Mustofa , Faris Kurnia Hakim , Qothrotunnidha Almaulidiyah , Eka Puspa Dewi","doi":"10.1016/j.joitmc.2025.100694","DOIUrl":"10.1016/j.joitmc.2025.100694","url":null,"abstract":"<div><h3>Purpose</h3><div>This study aims to develop a hybrid Early Warning System (EWS) that integrates the traditional Z-score method with machine learning algorithms to accurately predict the financial performance and potential failure of IRB in Indonesia.</div></div><div><h3>Design/methodology/approach</h3><div>The study employs a data science–driven approach using monthly financial and macroeconomic data from 2011 to 2024. A total of 21 independent variables were tested against the Z-score as the dependent variable. Various machine learning models were compared using AutoML (TPOT and LazyRegressor), and model validation was conducted through statistical testing, cross-validation, robustness checks, and feature importance analysis.</div></div><div><h3>Findings</h3><div>The Extra Trees algorithm emerged as the most accurate and robust predictive model, achieving an R² of 0.95 and the lowest Mean Absolute Error (MAE) of 0.0676. Key predictive variables identified include Non-Performing Financing (NPF), inflation (INF), and istishna'-based Financing. The model successfully anticipates financial distress up to two years in advance and enables the categorisation of IRB conditions into Stable, Vulnerable, and Unstable using Z-score thresholds.</div></div><div><h3>Originality/value</h3><div>This is the first study to integrate Z-score with advanced machine learning techniques within a hybrid EWS framework tailored to IRB. It offers a novel predictive model that enhances early risk detection and supports regulatory decision-making.</div></div><div><h3>Limitation</h3><div>The study focuses exclusively on IRB in Indonesia and may require recalibration for broader application in different financial systems or geographies. Reporting accuracy and completeness may also limit the use of secondary data.</div></div><div><h3>Practical implications</h3><div>The hybrid model provides actionable insights for regulators (OJK, LPS) and financial institutions to monitor IRB's health proactively. It strengthens risk mitigation strategies and contributes to the long-term resilience of the Islamic microfinance sector.</div></div>","PeriodicalId":16678,"journal":{"name":"Journal of Open Innovation: Technology, Market, and Complexity","volume":"12 1","pages":"Article 100694"},"PeriodicalIF":0.0,"publicationDate":"2025-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145748558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Governing the intelligent factory – Transforming labor law through an open-standards framework for AI governance in industry 4.0 管理智能工厂——通过工业4.0中人工智能治理的开放标准框架改变劳动法

Q1 Economics, Econometrics and Finance

Journal of Open Innovation: Technology, Market, and Complexity

Pub Date : 2025-12-01 DOI: 10.1016/j.joitmc.2025.100690

Nabeel Mehdi , Tooba Naz

Over the past decade, technologies like artificial intelligence (AI) and cloud computing have rapidly transformed manufacturing systems, introducing unprecedented levels of autonomy, precision, and scalability. While these technologies enhance productivity, they also challenge traditional labor relations and regulatory frameworks. Existing laws including the National Labor Relations Act (NLRA) and Equal Employment Opportunity Act (EEOA) were not designed for AI-driven workplaces. Despite growing industrial adoption, limited research examines their implications for human behavior, labor relations, and union law. This manuscript addresses these gaps and proposes an open governance framework based on the Model Context Protocol (MCP) that can enable transparent communication between industrial AI systems and regulatory bodies to strengthen compliance, accountability, and worker protection in the evolving Industry 4.0 landscape.

在过去的十年里，人工智能（AI）和云计算等技术迅速改变了制造系统，带来了前所未有的自主性、精确度和可扩展性。虽然这些技术提高了生产率，但它们也挑战了传统的劳资关系和监管框架。包括《国家劳动关系法》（NLRA）和《平等就业机会法》（EEOA）在内的现行法律并不是为人工智能驱动的工作场所而设计的。尽管越来越多的工业采用，有限的研究考察了它们对人类行为、劳资关系和工会法律的影响。本文解决了这些差距，并提出了一个基于模型上下文协议（MCP）的开放式治理框架，该框架可以实现工业人工智能系统与监管机构之间的透明通信，从而在不断发展的工业4.0环境中加强合规性、问责制和工人保护。

引用次数: 0

Exploring funding channels and innovation in Colombian SMEs: Insights from the service sector 探索哥伦比亚中小企业的融资渠道和创新：来自服务业的见解

Q1 Economics, Econometrics and Finance

Journal of Open Innovation: Technology, Market, and Complexity

Pub Date : 2025-12-01 DOI: 10.1016/j.joitmc.2025.100691

Yaneth Patricia Romero-Alvarez , Lisana B. Martinez , Carolina Pasciaroni , Katherinne Salas-Navarro , Ronald Zamora-Musa

This paper examines how financing channels, capital structures, and asset investments influence innovation outcomes in service-sector SMEs in Colombia. Despite extensive research on innovation finance, most studies focus on manufacturing firms in OECD economies, leaving a gap regarding the dynamics of service-sector SMEs in emerging markets. Using data from the national EDITS 2020–2021 survey, we analyze a sample of 384 innovative firms through ordered logit models. The results show that internal financing is the most frequently used channel but primarily sustains low levels of innovation, with limited effects on high-level outcomes. Public funding is positively associated with medium innovation but negatively linked to high innovation, while private external funding follows a similar pattern. Cooperative financing has the strongest negative impact on advanced innovation, highlighting the risks of informal financial mechanisms. Regarding asset composition, tangible investments foster incremental and medium-level innovation, whereas intangible investments—such as R&D, skills development, and organizational knowledge—significantly increase the probability of high innovation. These findings contribute to the literature on innovation finance in emerging economies by demonstrating that resource composition and institutional context critically condition SMEs’ innovation trajectories. From a policy perspective, the results suggest that supporting intangible assets, strengthening absorptive capacities, and diversifying financial ecosystems beyond traditional credit lines are essential to enable SMEs in Colombia and similar contexts to transition from incremental to high-level innovation.

本文考察了融资渠道、资本结构和资产投资如何影响哥伦比亚服务业中小企业的创新成果。尽管对创新金融进行了广泛的研究，但大多数研究都集中在经合组织经济体的制造业企业上，在新兴市场服务业中小企业的动态方面留下了空白。使用来自全国EDITS 2020-2021调查的数据，我们通过有序logit模型分析了384家创新企业的样本。结果表明，内部融资是最常用的渠道，但主要维持较低的创新水平，对高水平成果的影响有限。公共资金与中等创新呈正相关，但与高创新负相关，而私人外部资金遵循类似的模式。合作融资对先进创新的负面影响最大，非正式融资机制的风险突出。在资产构成方面，有形投资促进了增量和中等水平的创新，而无形投资——如研发、技能发展和组织知识——显著增加了高创新的可能性。这些研究结果表明，资源构成和制度背景对中小企业的创新轨迹至关重要，从而为新兴经济体的创新金融研究提供了文献依据。从政策角度来看，研究结果表明，支持无形资产、加强吸收能力和使金融生态系统多样化，超越传统信贷额度，对于使哥伦比亚和类似国家的中小企业从渐进式创新向高水平创新过渡至关重要。

{"title":"Exploring funding channels and innovation in Colombian SMEs: Insights from the service sector","authors":"Yaneth Patricia Romero-Alvarez , Lisana B. Martinez , Carolina Pasciaroni , Katherinne Salas-Navarro , Ronald Zamora-Musa","doi":"10.1016/j.joitmc.2025.100691","DOIUrl":"10.1016/j.joitmc.2025.100691","url":null,"abstract":"<div><div>This paper examines how financing channels, capital structures, and asset investments influence innovation outcomes in service-sector SMEs in Colombia. Despite extensive research on innovation finance, most studies focus on manufacturing firms in OECD economies, leaving a gap regarding the dynamics of service-sector SMEs in emerging markets. Using data from the national EDITS 2020–2021 survey, we analyze a sample of 384 innovative firms through ordered logit models. The results show that internal financing is the most frequently used channel but primarily sustains low levels of innovation, with limited effects on high-level outcomes. Public funding is positively associated with medium innovation but negatively linked to high innovation, while private external funding follows a similar pattern. Cooperative financing has the strongest negative impact on advanced innovation, highlighting the risks of informal financial mechanisms. Regarding asset composition, tangible investments foster incremental and medium-level innovation, whereas intangible investments—such as R&D, skills development, and organizational knowledge—significantly increase the probability of high innovation. These findings contribute to the literature on innovation finance in emerging economies by demonstrating that resource composition and institutional context critically condition SMEs’ innovation trajectories. From a policy perspective, the results suggest that supporting intangible assets, strengthening absorptive capacities, and diversifying financial ecosystems beyond traditional credit lines are essential to enable SMEs in Colombia and similar contexts to transition from incremental to high-level innovation.</div></div>","PeriodicalId":16678,"journal":{"name":"Journal of Open Innovation: Technology, Market, and Complexity","volume":"11 4","pages":"Article 100691"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145614318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0