Journal of Open Innovation: Technology, Market, and Complexity最新文献

{"title":"Organizing digital innovations","authors":"Peter Schrader ,&nbsp;Joachim Heidelbach ,&nbsp;Roman Ungern-Sternberg ,&nbsp;Erwin Gross ,&nbsp;Thomas Bauernhansl","doi":"10.1016/j.joitmc.2025.100615","DOIUrl":"10.1016/j.joitmc.2025.100615","url":null,"abstract":"<div><div>Digital innovations reshape the competitive landscape for machinery and plant engineering companies, challenging established organizational structures to integrate digital and physical products, and increasingly calling for open-innovation collaborations that leverage external knowledge and ecosystems. This study examines the new requirements of digital innovations. Based on a qualitative coding approach analyzing 19 expert interviews, the research reveals a progression in organizational adaptation and provides criteria to help companies select the appropriate approach. Companies typically begin with reactive, short-term, ad hoc solutions before evolving toward integrated, proactive models. The optimal approach is dictated by influencing factors related to the company and the innovation idea, such as corporate strategy, risk tolerance, degree of digitization, resource availability, and alignment of innovation with core operations. The study contributes a systematic framework for selecting digital innovation strategies, providing practical guidance for aligning organizational structures with digital imperatives, and suggesting future longitudinal and cross-industry research directions.</div></div>","PeriodicalId":16678,"journal":{"name":"Journal of Open Innovation: Technology, Market, and Complexity","volume":"11 3","pages":"Article 100615"},"PeriodicalIF":0.0,"publicationDate":"2025-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144861332","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}

{"title":"Uncovering motivations for innovation in urban commuting: A segmentation of Jakarta’s motorcyclists","authors":"Dedy Firmansyah ,&nbsp;Muhammad Zudhy Irawan ,&nbsp;Mukhammad Rizka Fahmi Amrozi ,&nbsp;Imam Muthohar","doi":"10.1016/j.joitmc.2025.100614","DOIUrl":"10.1016/j.joitmc.2025.100614","url":null,"abstract":"<div><div>Urban commuting in Jakarta, Indonesia, remains heavily reliant on motorcycles, yet riders exhibit diverse travel behaviors and underlying motivations. Drawing on survey data from 1143 commuters from Bogor, Depok, Tangerang, and Bekasi to Jakarta, this study first applies latent class cluster analysis to identify four distinct user segments: solo, regular medium-distance academic commuters; solo, regular medium-distance work commuters; solo, regular long-distance work commuters; and accompanied, occasional long-distance social/recreational commuters. This study then employs the Rasch model to quantify each group’s latent motivational drivers across twelve functional and psychosocial factors. Results indicate that support for unplanned trips is the strongest motivator for academic and long-distance work riders; ease of navigation underpins choices by academic, medium-distance work, and recreational commuters; traffic-congestion avoidance drives academic and recreational users; departure-time flexibility is paramount for medium-distance workers; and personal independence ranks highest for long-distance workers. By contrast, predictable travel time, perceived safety, and limited public-transport coverage consistently rank as weak motivators across all segments. Based on these insights, this study recommends tailored and innovative interventions, such as app-based microtransit for on-demand flexibility, park-and-ride facilities for long-distance commuters, last-mile e-micromobility services for medium-distance users, and integrated campus-shuttle systems for students, complemented by enhanced real-time information and targeted safety measures. Collectively, these strategies aim to match motorcycles’ core advantages while guiding riders toward more sustainable, multimodal options.</div></div>","PeriodicalId":16678,"journal":{"name":"Journal of Open Innovation: Technology, Market, and Complexity","volume":"11 3","pages":"Article 100614"},"PeriodicalIF":0.0,"publicationDate":"2025-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144842199","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}

{"title":"A hybrid approach to financial big data analysis using extended ensemble learning and optimized spark streaming","authors":"Muhammad Babar","doi":"10.1016/j.joitmc.2025.100602","DOIUrl":"10.1016/j.joitmc.2025.100602","url":null,"abstract":"<div><div>The financial sector faces mounting challenges in processing vast volumes of high-velocity data to support intelligent, real-time decision-making. Traditional machine learning models often fall short in accuracy, scalability, and responsiveness when dealing with large, dynamic financial datasets. This study presents a hybrid architecture that integrates extended ensemble learning with an optimized big data processing pipeline based on Apache Spark Streaming to address these limitations. The core ensemble combines K-Nearest Neighbor (KNN), Support Vector Machine (SVM), and K-Neighbors Classifier (KNC) to improve classification robustness and generalization. The system is designed for distributed and parallel execution, leveraging Spark’s map-reduce capabilities for high-throughput, low-latency data handling. Empirical evaluations using the Portuguese Bank Marketing dataset demonstrate that the proposed architecture achieves a high prediction accuracy of 90.9%, outperforming individual models such as Logistic Regression, SVM, and Random Forest. The ensemble model also reports a mean absolute error (MAE) of 0.023 and a mean squared error (MSE) of 0.0018. Regarding system performance, it processes 10,000 records per second with an average latency of 150 ms and maintains memory usage around 4GB, making it suitable for real-time financial analytics. The proposed architecture significantly enhances precision in predicting client behaviors, such as loan subscription decisions, and supports robust, scalable financial decision-making. This research offers valuable insights for integrating ensemble learning with big data technologies in FinTech, enabling more accurate, transparent, and efficient financial systems.</div></div>","PeriodicalId":16678,"journal":{"name":"Journal of Open Innovation: Technology, Market, and Complexity","volume":"11 3","pages":"Article 100602"},"PeriodicalIF":0.0,"publicationDate":"2025-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144809516","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}

{"title":"How and when circular economy practices drive financial performance: The role of organizational agility, operational efficiency, and digital technology adoption","authors":"Amelia Oktrivina ,&nbsp;Syahrul Effendi ,&nbsp;Hendryadi","doi":"10.1016/j.joitmc.2025.100613","DOIUrl":"10.1016/j.joitmc.2025.100613","url":null,"abstract":"<div><div>Despite growing interest in circular economy (CE) practices, the mechanisms for improving financial performance in micro and small enterprises (MSEs) remain underexplored, especially in developing economies. This study examines how CE practices enhance financial performance, both directly and indirectly, through organizational agility and operational efficiency. Additionally, the adoption of digital technology presents itself as a moderator in these relationships. Time-lagged data collection involved 451 Indonesian MSEs in the processing, fashion, and culinary sectors. Data were analyzed using PLS-SEM using SMART PLS 4.0. The findings reveal that CE practices have a positive effect on organizational agility, operational efficiency, and financial performance. Organizational agility and operational efficiency have been confirmed as key determinants of financial performance and partially mediate the relationship between CE practices and financial performance. Moreover, adopting digital technology strengthens the effects of CE practices on agility and operational efficiency. However, this did not directly moderate the relationship between CE practices and financial performance. This study makes three key contributions to the literature on the CE. First, it reveals that CE practices are a significant driver of organizational agility in MSEs. Second, this study empirically validates the parallel mediating roles of organizational agility and operational efficiency in translating CE practices into enhanced financial performance. Third, the findings highlight how MSEs in developing countries have successfully used digital tools to implement circular practices even with limited resources.</div></div>","PeriodicalId":16678,"journal":{"name":"Journal of Open Innovation: Technology, Market, and Complexity","volume":"11 3","pages":"Article 100613"},"PeriodicalIF":0.0,"publicationDate":"2025-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144826459","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}

{"title":"Factors influencing mobile platform adoption for nutritional tracking among Thai elderly: A unified UTAUT and STAM approach","authors":"Shutchapol Chopvitayakun ,&nbsp;Montean Rattanasiriwongwut ,&nbsp;Mahasak Ketcham","doi":"10.1016/j.joitmc.2025.100606","DOIUrl":"10.1016/j.joitmc.2025.100606","url":null,"abstract":"<div><div>The global aging population underscores the need for culturally tailored mobile health (mHealth) solutions to address nutritional challenges among older adults. This study investigates factors influencing the adoption of a culturally adapted mHealth platform for nutritional tracking among Thai elderly (aged ≥60), integrating the Unified Theory of Acceptance and Use of Technology (UTAUT) with the Senior Technology Acceptance Model (STAM). Using Partial Least Squares Structural Equation Modeling (PLS-SEM) with data from 355 Thai elderly, the model explained 65.3 % of the variance in Behavioral Intention (BI). Performance Expectancy (β = 0.237, p &lt; 0.001), Effort Expectancy (β = 0.239, p &lt; 0.001), Social Influence (β = 0.257, p &lt; 0.001), and Facilitating Conditions (β = 0.318, p &lt; 0.001) significantly predicted BI, while Gerontechnology Self-Efficacy was non-significant (β = 0.067, p = 0.074). Notably, Gerontechnology Anxiety (GA) positively influenced BI (β = 0.078, p = 0.044), suggesting a complex emotional effect in Thailand’s collectivist culture. However, Social Influence did not moderate the GA–BI link (β = 0.002, p = 0.96), suggesting limitations in its moderating role. Post hoc analysis showed Effort Expectancy mediated the effects of Gerontechnology Self-Efficacy (β = 0.155, p = 0.007) and GA (β = −0.048, p = 0.043) on BI. These findings highlight the interplay of functional, social, and emotional factors, informing the design of anxiety-aware, localized mHealth tools. This study contributes to gerontechnology by validating the UTAUT–STAM framework in a middle-income, collectivist context.</div></div>","PeriodicalId":16678,"journal":{"name":"Journal of Open Innovation: Technology, Market, and Complexity","volume":"11 3","pages":"Article 100606"},"PeriodicalIF":0.0,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144779623","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}

{"title":"Artificial intelligence and technological unemployment: Understanding trends, technology's adverse roles, and current mitigation guidelines","authors":"Meher Nigar ,&nbsp;Jannatul Ferdous Juli ,&nbsp;Uttam Golder ,&nbsp;Mohammad Jahangir Alam ,&nbsp;Mohammad Kamal Hossain","doi":"10.1016/j.joitmc.2025.100607","DOIUrl":"10.1016/j.joitmc.2025.100607","url":null,"abstract":"<div><div>As artificial intelligence (AI) and automation continue to reshape industries, concerns about technological unemployment are intensifying. This study employs a Systematic Literature Review (SLR) guided by the PRISMA framework to examine peer-reviewed literature from the Scopus database (2015–July 09, 2025). It identifies three core themes: (1) trends in AI-induced labor displacement, including task automation, skill polarization, and industry-specific disruptions in sectors such as healthcare, education, and creative industries; (2) the adverse roles of AI technologies, particularly in affecting white-collar professionals, gig workers, and freelancers by increasing precarity and skill mismatches; and (3) existing mitigation strategies, including responsible AI guidelines proposed by governments, institutions, and firms aimed at balancing technological advancement with employment protection. While a growing body of policy responses encourages human-AI complementarity, current measures remain fragmented and insufficient to address the structural risks of workforce displacement. This study presents a comprehensive synthesis of the evolving relationship between AI and employment, highlighting key areas for further inquiry and policy development.</div></div>","PeriodicalId":16678,"journal":{"name":"Journal of Open Innovation: Technology, Market, and Complexity","volume":"11 3","pages":"Article 100607"},"PeriodicalIF":0.0,"publicationDate":"2025-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144771599","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}

{"title":"Toward sustainable logistics in emerging economies: Identifying ESG barriers using neutrosophic Delphi-DEMATEL model","authors":"Quoc-Hieu Phan ,&nbsp;Thanh-Ngan Le ,&nbsp;Phi-Hung Nguyen ,&nbsp;Lan-Anh Thi Nguyen ,&nbsp;Tra-Giang Vu","doi":"10.1016/j.joitmc.2025.100601","DOIUrl":"10.1016/j.joitmc.2025.100601","url":null,"abstract":"<div><div>The growing global emphasis on Environmental, Social, and Governance (ESG) practices has placed increasing pressure on emerging economies, including Vietnam, to integrate sustainability into key industries such as logistics. However, ESG implementation in Vietnam’s logistics sector faces numerous interrelated challenges. This study employs a two-stage Neutrosophic Delphi-DEMATEL (NS-Delphi and NS-DEMATEL) method to systematically identify and analyze the causal relationships among eight key barrier dimensions: Legal and Compliance, Institutional, Economic, Psychological and Behavioral, Environmental, Social, Governance, and Technological. The results reveal that Legal and Compliance, Institutional, Economic, Psychological, and Behavioral barriers serve as the core causal dimensions that significantly influence the remaining effect dimensions. Notably, weak legal enforcement, unclear regulatory mandates, institutional capacity limitations, financial constraints, and behavioral inertia were the most influential impediments to ESG adoption. In contrast, environmental degradation, poor stakeholder engagement, governance inefficiencies, and low technological uptake were identified as outcome variables shaped by upstream barriers. The study offers practical policy implications, including the need for mandatory ESG regulations, enforcement reforms, capacity building, and targeted green finance mechanisms. Managerial recommendations include conducting ESG audits, aligning sustainability strategies with business objectives, and enhancing ESG-related competencies across organizations. The study contributes to ESG literature by providing a causal framework tailored to emerging market contexts and highlights directions for future research, including comparative analysis and hybrid multi-criteria modeling.</div></div>","PeriodicalId":16678,"journal":{"name":"Journal of Open Innovation: Technology, Market, and Complexity","volume":"11 3","pages":"Article 100601"},"PeriodicalIF":0.0,"publicationDate":"2025-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144771600","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}

{"title":"Ethical consumption through reverse supply chain: Exploring product’s nature as a mediator in the FMCG industry","authors":"Md. Abdur Rouf ,&nbsp;Md. Asaduzzaman Babu ,&nbsp;Kazi Md Yusuf ,&nbsp;Humaira Begum ,&nbsp;Md Rohibul Islam ,&nbsp;Mahmudul Islam","doi":"10.1016/j.joitmc.2025.100608","DOIUrl":"10.1016/j.joitmc.2025.100608","url":null,"abstract":"<div><div>In response to increasing environmental demands and evolving consumer expectations, Reverse Supply Chain Capabilities (RSCC) have emerged as a strategic tool to foster ethical consumption, especially in the Fast-Moving Consumer Goods (FMCG) sector. Grounded in the Resource-Based View (RBV) and Value-Belief-Norm (VBN) theory, this study investigates (1) how RSCC—Return Goods (RG), Recycled Packing Materials (RPM), and Disposal of Goods (DG) influence Ethical Consumption (EC), and (2) whether Product's Nature (PN) mediates this relationship. Partial Least Squares Structural Equation Modeling (PLS-SEM) using SmartPLS 4.1.1.2 was employed for the analysis (n = 350). The finding reveals a statistical analysis of beverage consumption and preferences; soft drinks were the most popular, with 61.71 % of respondents preferring them, while drinking water was the second most preferred, at 38.29 %. No respondents reported consuming alcoholic beverages. The results from the empirical analysis reveal significant positive relationships: RG → RSCC (β = 0.055, p &lt; 0.05), RPM → RSCC (β = 0.274, p &lt; 0.05), and DG → RSCC (β = 0.543, p &lt; 0.001). RSCC positively influences EC (β = 0.471, p &lt; 0.001), and PN partially mediates this relationship (RSCC → PN → EC: β = 0.423, p &lt; 0.001). The RBV framework highlights RSCC as a firm-specific capability, while VBN theory explains how consumer beliefs and norms guide ethical consumption. This innovative, interdisciplinary study links operational capabilities to consumer ethics, providing managers, marketers, and policymakers with practical guidance on building FMCG sustainability and ethical consumption strategies.</div></div>","PeriodicalId":16678,"journal":{"name":"Journal of Open Innovation: Technology, Market, and Complexity","volume":"11 3","pages":"Article 100608"},"PeriodicalIF":0.0,"publicationDate":"2025-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144771598","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}

{"title":"An intuitionistic fuzzy approach to assessing the barriers to quality 4.0 adoption in the footwear manufacturing industry: Implications for sustainability in emerging economy","authors":"Maishat Lubaba ,&nbsp;Md Imran Hosen ,&nbsp;Md Shihab Shakur ,&nbsp;Muhommad Azizur Rahman ,&nbsp;A.B.M. Mainul Bari","doi":"10.1016/j.joitmc.2025.100604","DOIUrl":"10.1016/j.joitmc.2025.100604","url":null,"abstract":"<div><div>The footwear manufacturing industry substantially aids global fashion trends and economic growth. Still, it faces challenges such as excessive raw material waste, increased rework, and inadequate quality control, which hinder sustainability and competitiveness. Integrating Industry 4.0 technologies with quality management, known as Quality 4.0 (Q4.0), offers transformative potential through real-time monitoring, predictive analytics, and sustainable practices. However, adopting Q4.0 technologies is impeded by various barriers that require a thorough understanding to devise effective mitigation strategies. For that purpose, this study investigates the key barriers to Q4.0 adoption in the footwear manufacturing sector, focusing on emerging economies like Bangladesh. Using an integrated multi-criteria decision-making (MCDM) approach that combines interval-valued type 2 intuitionistic fuzzy (IVT2IF) theory and the decision-making trial and evaluation laboratory (DEMATEL) method, 16 barriers were identified, validated by experts, and analyzed for interdependencies. The results highlight “uncertainty about Return on Investment (ROI) and insufficient capital investment,” “lack of adaptive technological infrastructure,” and “difficulty in managing Industry 4.0 technologies” as the most prominent barriers, with prominence scores of 9.141, 9.068, and 8.865, respectively. “Lack of adaptive technological infrastructure” emerges as the most critical causal driver, followed by “lack of commitment from top management” and “poor inter-departmental collaboration and communication.” This research provides valuable insights for improving quality management and fostering innovation in the footwear manufacturing industry, which can guide practitioners and policymakers in overcoming barriers, promoting sustainability, and enhancing competitiveness in this manufacturing sector.</div></div>","PeriodicalId":16678,"journal":{"name":"Journal of Open Innovation: Technology, Market, and Complexity","volume":"11 3","pages":"Article 100604"},"PeriodicalIF":0.0,"publicationDate":"2025-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144738774","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}

{"title":"Strategic stakeholder analysis for Vietnam’s carbon credit system: a neutrosophic approach","authors":"Phi-Hung Nguyen,&nbsp;Lan-Anh Thi Nguyen,&nbsp;Duc-Minh Vu,&nbsp;Tra-Giang Vu,&nbsp;Anh-Phuong Danh-Nguyen,&nbsp;Thi-Lien Nguyen","doi":"10.1016/j.joitmc.2025.100597","DOIUrl":"10.1016/j.joitmc.2025.100597","url":null,"abstract":"<div><div>The global carbon credit market has evolved into a key mechanism for mitigating climate change, yet challenges persist regarding transparency, stakeholder trust, and market efficiency. Vietnam is in the initial phase of developing its carbon credit framework, driven by its pledge to reach net-zero emissions by 2050. Despite regulatory developments, the Vietnamese carbon market remains fragmented, with concerns over pricing disparities, market liquidity, verification standards, and stakeholder engagement. This study assesses stakeholder preferences in Vietnam’s carbon credit system using an advanced Neutrosophic Sets (NS) combined with Multi-Criteria Decision-Making (MCDM) Framework, integrating Delphi and DEMATEL methods. Unlike traditional fuzzy logic-based models, NS offers a more refined depiction of uncertainty through the truth, indeterminacy, and falsity integration, enabling a more accurate stakeholder preference modeling. The NS Delphi method is applied to refine expert consensus, while NS DEMATEL identifies interdependencies among key stakeholder concerns, including policy alignment, financial incentives, verification mechanisms, and market accessibility. Findings reveal that regulatory transparency, price stability, and cross-border certification are critical factors shaping market participation. Moreover, private sector involvement and financial institutions play a pivotal role in market development, requiring stronger incentives and risk mitigation measures. The results contribute to both theoretical advancements in decision science and practical policymaking by offering structured recommendations to enhance Vietnam’s carbon trading system. By integrating stakeholder perspectives with uncertainty modeling, this study provides a strategic foundation for developing a more transparent, efficient, and scalable carbon credit framework in Vietnam, ensuring alignment with global carbon pricing mechanisms and fostering long-term sustainability.</div></div>","PeriodicalId":16678,"journal":{"name":"Journal of Open Innovation: Technology, Market, and Complexity","volume":"11 3","pages":"Article 100597"},"PeriodicalIF":0.0,"publicationDate":"2025-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144738775","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}