Pub Date : 2025-12-24DOI: 10.1016/j.jik.2025.100929
Federico Caviggioli
Independent inventors are considered important contributors to technological progress. However, empirical studies on individuals who retain the intellectual property rights in patented inventions are relatively scarce. This work analyzes a sample of more than 20k inventors who debuted between 1994 and 2017 and who filed at least one patent at the Italian Patent Office (UIBM) as independent: i.e., they were also the applicant/assignee. UIBM reports independent inventors’ national tax IDs, which allow identification of sex, date of birth, and place of birth. Inventors’ patent portfolios are reconstructed using their names and through filtering criteria to reduce the presence of false positives and negatives. The analyses confirm the presence of female underrepresentation (slowly declining), and sex-related differences in mean age and age distribution at the patenting debut. The dynamic process from independent to organizational inventor is then examined. Results of the survival analyses suggest that, ceteris paribus, female inventors are less likely to become organizational inventors than their male counterparts, while the role of age is negligible. However, within the subsample of inventors becoming organizational, female innovators transition more quickly, suggesting a potential selection effect that excludes many female patentees from pursuing their careers.
{"title":"Independent inventors in Italy: The role of sex and age in career development","authors":"Federico Caviggioli","doi":"10.1016/j.jik.2025.100929","DOIUrl":"10.1016/j.jik.2025.100929","url":null,"abstract":"<div><div>Independent inventors are considered important contributors to technological progress. However, empirical studies on individuals who retain the intellectual property rights in patented inventions are relatively scarce. This work analyzes a sample of more than 20k inventors who debuted between 1994 and 2017 and who filed at least one patent at the Italian Patent Office (UIBM) as independent: i.e., they were also the applicant/assignee. UIBM reports independent inventors’ national tax IDs, which allow identification of sex, date of birth, and place of birth. Inventors’ patent portfolios are reconstructed using their names and through filtering criteria to reduce the presence of false positives and negatives. The analyses confirm the presence of female underrepresentation (slowly declining), and sex-related differences in mean age and age distribution at the patenting debut. The dynamic process from independent to organizational inventor is then examined. Results of the survival analyses suggest that, ceteris paribus, female inventors are less likely to become organizational inventors than their male counterparts, while the role of age is negligible. However, within the subsample of inventors becoming organizational, female innovators transition more quickly, suggesting a potential selection effect that excludes many female patentees from pursuing their careers.</div></div>","PeriodicalId":46792,"journal":{"name":"Journal of Innovation & Knowledge","volume":"13 ","pages":"Article 100929"},"PeriodicalIF":15.5,"publicationDate":"2025-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145823828","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 : 2025-12-20DOI: 10.1016/j.jik.2025.100917
Alexandra Horobet , Arindam Banerjee , Ioana-Alexandra Radu , Cosmin-Alin Botoroga
This study examines the impact of a commitment to Sustainable Development Goal 9 (SDG 9) objectives by exploring sectoral and regional disparities in how companies aligned with this goal leverage digital technologies and knowledge, foster innovation ecosystems, and deliver measurable contributions to sustainable infrastructure development. Using the SDG-aligned revenue share as the main metric for SDGs commitment across 5,323 global companies provided by the Upright platform, we employed a machine-learning-based k-means clustering algorithm to detect patterns of net impacts created across the Society, Knowledge, Health, and Environment (SKHE) dimensions. We also uncovered sectoral and geographical patterns of the companies investigated. Our findings show that alignment with SDG 9 (Industry, Knowledge, and Innovation) is associated with corporate commitment to SKHE dimensions, as well as sectoral and, to some extent, geographical scope. The results offer practical implications for investors, policymakers designing regulations and guidelines to improve sustainability disclosure, and company executives who are developing sustainability strategies.
{"title":"Corporate alignment to innovation and knowledge: detecting patterns in multidimensional impact across global industries","authors":"Alexandra Horobet , Arindam Banerjee , Ioana-Alexandra Radu , Cosmin-Alin Botoroga","doi":"10.1016/j.jik.2025.100917","DOIUrl":"10.1016/j.jik.2025.100917","url":null,"abstract":"<div><div>This study examines the impact of a commitment to Sustainable Development Goal 9 (SDG 9) objectives by exploring sectoral and regional disparities in how companies aligned with this goal leverage digital technologies and knowledge, foster innovation ecosystems, and deliver measurable contributions to sustainable infrastructure development. Using the SDG-aligned revenue share as the main metric for SDGs commitment across 5,323 global companies provided by the Upright platform, we employed a machine-learning-based k-means clustering algorithm to detect patterns of net impacts created across the Society, Knowledge, Health, and Environment (SKHE) dimensions. We also uncovered sectoral and geographical patterns of the companies investigated. Our findings show that alignment with SDG 9 (Industry, Knowledge, and Innovation) is associated with corporate commitment to SKHE dimensions, as well as sectoral and, to some extent, geographical scope. The results offer practical implications for investors, policymakers designing regulations and guidelines to improve sustainability disclosure, and company executives who are developing sustainability strategies.</div></div>","PeriodicalId":46792,"journal":{"name":"Journal of Innovation & Knowledge","volume":"13 ","pages":"Article 100917"},"PeriodicalIF":15.5,"publicationDate":"2025-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145785781","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 : 2025-12-20DOI: 10.1016/j.jik.2025.100882
Lauren Lindow , Catherine Campbell , Coleman Longwater , Ying Zhang , Ana Martin-Ryals , Ziynet Boz
Controlled environment agriculture (CEA) enables farmers to manage all aspects of crop growing environments. However, the complexity of operations necessitates decision-support tools (DSTs) that integrate and analyze large datasets for optimized management. Despite their benefits, the adoption of DSTs is influenced by factors beyond technical effectiveness, such as cost, usability, and perceived value. This study aimed to evaluate the experiences and perceptions of CEA operators regarding DSTs, identify barriers to adoption, and determine the characteristics necessary for widespread acceptance, using the Diffusion of Innovation Theory as a framework. A mixed-methods approach was employed, consisting of a survey of 44 CEA operators across the United States by in-depth interviews with 14 respondents. The survey and interviews explored DST experiences, concerns, and desired features, with data analyzed using thematic analysis. Farmers desired general farm management tools that could be easily customized to their specific needs and operations. Key preferences included seamless data integration across tools, automation, and Artificial Intelligence (AI) integration for predictive modeling and decision suggestions, while maintaining human oversight. Cost and trialability were major barriers, with farmers requiring financial benefits that outweigh costs. Complexity of use and incompatibility with existing workflows were significant deterrents to adoption. The findings underscore the importance of user-centered design, financial feasibility, and demonstrable tool performance. This study highlights critical factors influencing DST adoption in CEA and provides actionable insights for developers to design tools that are cost-effective, user-friendly, and customizable. Addressing these barriers can enhance adoption rates and optimize farm operations, ultimately advancing the CEA industry.
{"title":"Diffusion of innovation in controlled environment agriculture: A mixed-methods study of digital decision support tool adoption","authors":"Lauren Lindow , Catherine Campbell , Coleman Longwater , Ying Zhang , Ana Martin-Ryals , Ziynet Boz","doi":"10.1016/j.jik.2025.100882","DOIUrl":"10.1016/j.jik.2025.100882","url":null,"abstract":"<div><div>Controlled environment agriculture (CEA) enables farmers to manage all aspects of crop growing environments. However, the complexity of operations necessitates decision-support tools (DSTs) that integrate and analyze large datasets for optimized management. Despite their benefits, the adoption of DSTs is influenced by factors beyond technical effectiveness, such as cost, usability, and perceived value. This study aimed to evaluate the experiences and perceptions of CEA operators regarding DSTs, identify barriers to adoption, and determine the characteristics necessary for widespread acceptance, using the Diffusion of Innovation Theory as a framework. A mixed-methods approach was employed, consisting of a survey of 44 CEA operators across the United States by in-depth interviews with 14 respondents. The survey and interviews explored DST experiences, concerns, and desired features, with data analyzed using thematic analysis. Farmers desired general farm management tools that could be easily customized to their specific needs and operations. Key preferences included seamless data integration across tools, automation, and Artificial Intelligence (AI) integration for predictive modeling and decision suggestions, while maintaining human oversight. Cost and trialability were major barriers, with farmers requiring financial benefits that outweigh costs. Complexity of use and incompatibility with existing workflows were significant deterrents to adoption. The findings underscore the importance of user-centered design, financial feasibility, and demonstrable tool performance. This study highlights critical factors influencing DST adoption in CEA and provides actionable insights for developers to design tools that are cost-effective, user-friendly, and customizable. Addressing these barriers can enhance adoption rates and optimize farm operations, ultimately advancing the CEA industry.</div></div>","PeriodicalId":46792,"journal":{"name":"Journal of Innovation & Knowledge","volume":"13 ","pages":"Article 100882"},"PeriodicalIF":15.5,"publicationDate":"2025-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145785790","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 : 2025-12-19DOI: 10.1016/j.jik.2025.100920
Margarita Núñez-Canal , María de las Mercedes de Obesso Arias , Carlos Alberto Pérez-Rivero , Ignacio Álvarez-de-Mon
This research answers the following question: How do the competencies and attitudes of university faculty toward artificial intelligence (AI) impact student learning? Using human capital theory and stakeholder theory, this research highlights the importance of university faculty. The research uses an adaptation of a digital competence framework specifically for AI competence. A total of 105 responses from professors in business studies (e.g., entrepreneurship, strategy, finance, and marketing) were collected from university faculty. Four hypotheses were proposed, two of which were confirmed. Professors' ability to leverage AI for feedback, assessment, and pedagogy is linked to their commitment to enhancing student learning. Professors' attitudes toward the use of AI, data governance, and ethical considerations are also associated with their focus on improving student learning. The study finds that faculty AI competence can enhance institutional effectiveness. Educators are a crucial resource for higher education institutions. Equipping them with the necessary skills for the effective use of AI can enhance both institutional capacity and pedagogical innovation.
{"title":"Stakeholder engagement and strategic innovation in higher education through AI competency","authors":"Margarita Núñez-Canal , María de las Mercedes de Obesso Arias , Carlos Alberto Pérez-Rivero , Ignacio Álvarez-de-Mon","doi":"10.1016/j.jik.2025.100920","DOIUrl":"10.1016/j.jik.2025.100920","url":null,"abstract":"<div><div>This research answers the following question: How do the competencies and attitudes of university faculty toward artificial intelligence (AI) impact student learning? Using human capital theory and stakeholder theory, this research highlights the importance of university faculty. The research uses an adaptation of a digital competence framework specifically for AI competence. A total of 105 responses from professors in business studies (e.g., entrepreneurship, strategy, finance, and marketing) were collected from university faculty. Four hypotheses were proposed, two of which were confirmed. Professors' ability to leverage AI for feedback, assessment, and pedagogy is linked to their commitment to enhancing student learning. Professors' attitudes toward the use of AI, data governance, and ethical considerations are also associated with their focus on improving student learning. The study finds that faculty AI competence can enhance institutional effectiveness. Educators are a crucial resource for higher education institutions. Equipping them with the necessary skills for the effective use of AI can enhance both institutional capacity and pedagogical innovation.</div></div>","PeriodicalId":46792,"journal":{"name":"Journal of Innovation & Knowledge","volume":"13 ","pages":"Article 100920"},"PeriodicalIF":15.5,"publicationDate":"2025-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145785784","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 : 2025-12-19DOI: 10.1016/j.jik.2025.100925
Adam W. Smith , Amir Pezeshkan
We examine the concept of opportunity conviction as a key indicator of the resilience of countries’ entrepreneurial ecosystems during crises. For entrepreneurship, opportunity conviction constitutes a joint-threshold outcome: it materializes only when opportunity visibility (the presence of credible signals of near-term demand and cash-flow potential) is sufficiently high, and deterrent risk (the perceived downside given institutional stability, available buffers, and hazard control) is sufficiently low. Using data from the Global Entrepreneurship Monitor (GEM) and applying fuzzy-set Qualitative Comparative Analysis (fsQCA), we identify how configurations of foundational contextual factors combine with policy measures to foster high opportunity conviction in 2021. Five configurations demonstrate the alternative recipes of contextual and policy conditions that achieve opportunity conviction in times of crisis. Theoretical and practitioner implications are discussed.
{"title":"Foundations of opportunity conviction: A configurational analysis of the COVID-19 recovery","authors":"Adam W. Smith , Amir Pezeshkan","doi":"10.1016/j.jik.2025.100925","DOIUrl":"10.1016/j.jik.2025.100925","url":null,"abstract":"<div><div>We examine the concept of opportunity conviction as a key indicator of the resilience of countries’ entrepreneurial ecosystems during crises. For entrepreneurship, opportunity conviction constitutes a joint-threshold outcome: it materializes only when opportunity visibility (the presence of credible signals of near-term demand and cash-flow potential) is sufficiently high, and deterrent risk (the perceived downside given institutional stability, available buffers, and hazard control) is sufficiently low. Using data from the Global Entrepreneurship Monitor (GEM) and applying fuzzy-set Qualitative Comparative Analysis (fsQCA), we identify how configurations of foundational contextual factors combine with policy measures to foster high opportunity conviction in 2021. Five configurations demonstrate the alternative recipes of contextual and policy conditions that achieve opportunity conviction in times of crisis. Theoretical and practitioner implications are discussed.</div></div>","PeriodicalId":46792,"journal":{"name":"Journal of Innovation & Knowledge","volume":"13 ","pages":"Article 100925"},"PeriodicalIF":15.5,"publicationDate":"2025-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145785787","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 : 2025-12-19DOI: 10.1016/j.jik.2025.100927
Luis Díaz-Marcos , Óscar Aguado Tevar , Alberto Tomás Delso Vicente , María García de Blanes Sebastián
Music consumption has undergone a transformation with digitalization, establishing streaming platforms as the primary channel for accessing musical content. This transformation has been driven by ease of use, algorithmic personalization, and seamless integration with mobile devices. The objective of this research is to analyze the factors influencing the adoption of music streaming platforms, based on the UTAUT2 model. Four key variables are incorporated: ease of use, perceived usefulness, hedonic motivation, and habit, along with the additional variable of perceived innovation. A survey was conducted among 202 young people using streaming platforms, and the data were analyzed through Structural Equation Modeling (SEM) using IBM SPSS V.27 and AMOS V.27. The proposed model identifies the factors that determine usage intention and those that have no significant impact. The results show that habit is the primary predictor of usage, surpassing other variables such as ease of use, perceived usefulness, hedonic motivation, and innovation. This finding suggests that repeated behaviors automate platform use, reducing the influence of other factors on user decision-making. This research contributes to a deeper understanding of the central role of habit in the adoption of music streaming platforms, providing key insights for the development of user retention and loyalty strategies.
{"title":"Knowledge and behavior of young people on music streaming platforms: Factors driving their use","authors":"Luis Díaz-Marcos , Óscar Aguado Tevar , Alberto Tomás Delso Vicente , María García de Blanes Sebastián","doi":"10.1016/j.jik.2025.100927","DOIUrl":"10.1016/j.jik.2025.100927","url":null,"abstract":"<div><div>Music consumption has undergone a transformation with digitalization, establishing streaming platforms as the primary channel for accessing musical content. This transformation has been driven by ease of use, algorithmic personalization, and seamless integration with mobile devices. The objective of this research is to analyze the factors influencing the adoption of music streaming platforms, based on the UTAUT2 model. Four key variables are incorporated: ease of use, perceived usefulness, hedonic motivation, and habit, along with the additional variable of perceived innovation. A survey was conducted among 202 young people using streaming platforms, and the data were analyzed through Structural Equation Modeling (SEM) using IBM SPSS V.27 and AMOS V.27. The proposed model identifies the factors that determine usage intention and those that have no significant impact. The results show that habit is the primary predictor of usage, surpassing other variables such as ease of use, perceived usefulness, hedonic motivation, and innovation. This finding suggests that repeated behaviors automate platform use, reducing the influence of other factors on user decision-making. This research contributes to a deeper understanding of the central role of habit in the adoption of music streaming platforms, providing key insights for the development of user retention and loyalty strategies.</div></div>","PeriodicalId":46792,"journal":{"name":"Journal of Innovation & Knowledge","volume":"13 ","pages":"Article 100927"},"PeriodicalIF":15.5,"publicationDate":"2025-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145785782","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}
Artificial intelligence (AI) holds transformative potential for human resources (HR), yet its adoption remains limited, particularly within the broader context of digital transformation (DT). Although trust is widely recognised as a critical enabler of AI adoption, little is known about the organisational conditions under which this trust develops, especially in firms with low digital maturity. This study investigates how configurations of organisational factors, namely technology, digital skills, culture supporting DT and HR’s involvement in DT initiatives, can shape trust in AI adoption within HR practices. The methodological approach followed two steps: (1) the questionnaire design was validated through insights derived from interviews conducted during a case study analysis, and (2) a fuzzy-set qualitative comparative analysis using survey data was employed. The findings contribute to shedding light on trust enablers and hindering factors that positively influence AI adoption in HR practices. Results show that trust can emerge even in digitally less mature firms when HR functions are strategically involved in broader DT initiatives. Conversely, HR digital skills and functional involvement together with cultural readiness can foster trust independently without top-down managerial involvement. These findings challenge conventional assumptions that digital maturity and leadership engagement are conditions for fostering trust in the adoption of new technologies. By uncovering multiple pathways to trust, this study contributes theoretically by framing trust as a configurational, organisational-level outcome. This work aims to advance the discourse on technological innovation in HR, providing valuable insights for practitioners and scholars to support digitally lagging organisations navigating the challenges of AI adoption.
{"title":"AI adoption in HR: AI trust in digitally lagging organisations","authors":"Alessia Zoppelletto , Ludovico Bullini Orlandi , Eleonora Veglianti , Cecilia Rossignoli","doi":"10.1016/j.jik.2025.100912","DOIUrl":"10.1016/j.jik.2025.100912","url":null,"abstract":"<div><div>Artificial intelligence (AI) holds transformative potential for human resources (HR), yet its adoption remains limited, particularly within the broader context of digital transformation (DT). Although trust is widely recognised as a critical enabler of AI adoption, little is known about the organisational conditions under which this trust develops, especially in firms with low digital maturity. This study investigates how configurations of organisational factors, namely technology, digital skills, culture supporting DT and HR’s involvement in DT initiatives, can shape trust in AI adoption within HR practices. The methodological approach followed two steps: (1) the questionnaire design was validated through insights derived from interviews conducted during a case study analysis, and (2) a fuzzy-set qualitative comparative analysis using survey data was employed. The findings contribute to shedding light on trust enablers and hindering factors that positively influence AI adoption in HR practices. Results show that trust can emerge even in digitally less mature firms when HR functions are strategically involved in broader DT initiatives. Conversely, HR digital skills and functional involvement together with cultural readiness can foster trust independently without top-down managerial involvement. These findings challenge conventional assumptions that digital maturity and leadership engagement are conditions for fostering trust in the adoption of new technologies. By uncovering multiple pathways to trust, this study contributes theoretically by framing trust as a configurational, organisational-level outcome. This work aims to advance the discourse on technological innovation in HR, providing valuable insights for practitioners and scholars to support digitally lagging organisations navigating the challenges of AI adoption.</div></div>","PeriodicalId":46792,"journal":{"name":"Journal of Innovation & Knowledge","volume":"13 ","pages":"Article 100912"},"PeriodicalIF":15.5,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145785783","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 : 2025-12-17DOI: 10.1016/j.jik.2025.100924
Annas Vijaya , Faris Dzaudan Qadri , Linda Salma Angreani , Hendro Wicaksono
Environmental, social, and governance (ESG) reporting faces persistent challenges, including fragmented standards, inconsistent metrics, misalignment with global sustainability goals, and limited stakeholder usability. Numerous studies prove that ontology-based solutions can address several challenges that occur during ESG reporting activities. Although semantic technologies offer valuable benefits for ESG reporting, their utilization in this field remains constrained. Most ontology-based solutions remain in developmental stages, and they are not broadly utilized since organizations lack an understanding of how these tools would help address their reporting problems. This study performs a systematic literature review (SLR) that investigates 19 peer-reviewed studies obtained from Scopus and Web of Science under Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) standards. The SLR identifies critical gaps: (1) existing ontology-driven solutions can address key problems in current ESG reporting; (2) quantitative evaluation methods are rarely integrated with semantic tools, limiting actionable insights; and (3) alignment with evolving standards like the Sustainable Development Goals (SDGs) remains superficial. Based on the SLR insights, this research develops a novel framework through SLR findings by combining ontology-driven methods with quantitative assessment techniques. The framework achieves standardization of various reporting standards through an ESG ontology system that maps essential concepts to build an extensive taxonomy. SDG targets become mutually compatible through established SDG ontologies to allow businesses to measure their activities against international sustainability goals. Fuzzy Multi-Criteria Decision-Making (MCDM) techniques used in combination with an ESG maturity model create quantitative measures to assess ESG performance. The method produces measurable performance indicators that are supported by clear semantic links that allow valid benchmark assessments combined with better data unification and improved decision-making capabilities. The research creates operational frameworks that enable ESG information interoperability, which advance sustainability governance innovation and guide ESG ontology transformations.
环境、社会和治理（ESG）报告面临着持续的挑战，包括支离破碎的标准、不一致的指标、与全球可持续性目标的不一致以及有限的利益相关者可用性。大量研究证明，基于本体的解决方案可以解决ESG报告活动中出现的几个挑战。尽管语义技术为ESG报告提供了宝贵的好处，但它们在该领域的应用仍然受到限制。大多数基于本体的解决方案仍处于开发阶段，由于组织缺乏对这些工具如何帮助解决报告问题的理解，因此它们没有被广泛使用。本研究进行了系统文献综述（SLR），调查了从Scopus和Web of Science获得的19项同行评议研究，这些研究遵循了系统综述和荟萃分析（PRISMA 2020）的首选报告项目标准。SLR指出了关键的差距：(1)现有的本体驱动解决方案可以解决当前ESG报告中的关键问题；(2)定量评估方法很少与语义工具相结合，限制了可操作的见解；(3)与可持续发展目标（sdg）等不断发展的标准保持一致仍然是肤浅的。基于单反的见解，本研究通过将本体驱动方法与定量评估技术相结合，通过单反的发现开发了一个新的框架。该框架通过ESG本体系统实现各种报告标准的标准化，该系统映射基本概念以构建广泛的分类法。可持续发展目标通过既定的可持续发展目标本体相互兼容，使企业能够根据国际可持续发展目标衡量其活动。模糊多准则决策（MCDM）技术与ESG成熟度模型相结合，可创建定量指标来评估ESG绩效。该方法产生可测量的性能指标，这些指标由清晰的语义链接支持，允许有效的基准评估，结合更好的数据统一和改进的决策能力。该研究创建了实现ESG信息互操作性的操作框架，从而推进可持续性治理创新并指导ESG本体转换。
{"title":"From fragmentation to interoperability: How semantic models transform environmental, social, governance (ESG) reporting, knowledge, and sustainability governance","authors":"Annas Vijaya , Faris Dzaudan Qadri , Linda Salma Angreani , Hendro Wicaksono","doi":"10.1016/j.jik.2025.100924","DOIUrl":"10.1016/j.jik.2025.100924","url":null,"abstract":"<div><div>Environmental, social, and governance (ESG) reporting faces persistent challenges, including fragmented standards, inconsistent metrics, misalignment with global sustainability goals, and limited stakeholder usability. Numerous studies prove that ontology-based solutions can address several challenges that occur during ESG reporting activities. Although semantic technologies offer valuable benefits for ESG reporting, their utilization in this field remains constrained. Most ontology-based solutions remain in developmental stages, and they are not broadly utilized since organizations lack an understanding of how these tools would help address their reporting problems. This study performs a systematic literature review (SLR) that investigates 19 peer-reviewed studies obtained from Scopus and Web of Science under Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) standards. The SLR identifies critical gaps: (1) existing ontology-driven solutions can address key problems in current ESG reporting; (2) quantitative evaluation methods are rarely integrated with semantic tools, limiting actionable insights; and (3) alignment with evolving standards like the Sustainable Development Goals (SDGs) remains superficial. Based on the SLR insights, this research develops a novel framework through SLR findings by combining ontology-driven methods with quantitative assessment techniques. The framework achieves standardization of various reporting standards through an ESG ontology system that maps essential concepts to build an extensive taxonomy. SDG targets become mutually compatible through established SDG ontologies to allow businesses to measure their activities against international sustainability goals. Fuzzy Multi-Criteria Decision-Making (MCDM) techniques used in combination with an ESG maturity model create quantitative measures to assess ESG performance. The method produces measurable performance indicators that are supported by clear semantic links that allow valid benchmark assessments combined with better data unification and improved decision-making capabilities. The research creates operational frameworks that enable ESG information interoperability, which advance sustainability governance innovation and guide ESG ontology transformations.</div></div>","PeriodicalId":46792,"journal":{"name":"Journal of Innovation & Knowledge","volume":"13 ","pages":"Article 100924"},"PeriodicalIF":15.5,"publicationDate":"2025-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145786063","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}
With the acceleration of digital transformation, the issue of the digital divide between enterprises has become increasingly prominent. However, prior studies have primarily examined how digital transformation levels affect an enterprise’s operations and innovation; limited attention has been paid to the effects of differences in digital transformation between different enterprises. Drawing on knowledge-based theory, this study employs supply chain data from China between 2007 and 2022 to examine the impact of the digital divide between enterprises and customers (DDEC)1 on enterprise performance. Empirical analysis indicates that the DDEC significantly adversely affects enterprise performance; this remains consistent even after conducting various robustness tests. The mechanism test reveals that the DDEC in the supply chain mainly affects enterprise performance by negatively affecting the width and depth of enterprises’ knowledge search. While the information integration capability (IIC)2 of enterprises can weaken the above relationship, then alleviate the effect of the DDEC on the enterprise performance. First, this study innovatively extends the research perspective to the supply chain scenario by assessing the digital divide between enterprises and their customers, thereby enriching the existing literature. Second, it adopts the knowledge-based theory to explore the “black box” of the DDEC affecting enterprise performance. Finally, it proposes operable suggestions for alleviating the negative impact of the digital divide at the enterprise level, providing important practical insights to enterprises.
{"title":"How does the digital divide between enterprises and customers affect enterprise performance?","authors":"Chaoyue Meng , Xiaoxia Yu , Junmei Luo , Zhonghui Jiang","doi":"10.1016/j.jik.2025.100914","DOIUrl":"10.1016/j.jik.2025.100914","url":null,"abstract":"<div><div>With the acceleration of digital transformation, the issue of the digital divide between enterprises has become increasingly prominent. However, prior studies have primarily examined how digital transformation levels affect an enterprise’s operations and innovation; limited attention has been paid to the effects of differences in digital transformation between different enterprises. Drawing on knowledge-based theory, this study employs supply chain data from China between 2007 and 2022 to examine the impact of the digital divide between enterprises and customers (DDEC)<span><span><sup>1</sup></span></span> on enterprise performance. Empirical analysis indicates that the DDEC significantly adversely affects enterprise performance; this remains consistent even after conducting various robustness tests. The mechanism test reveals that the DDEC in the supply chain mainly affects enterprise performance by negatively affecting the width and depth of enterprises’ knowledge search. While the information integration capability (IIC)<span><span><sup>2</sup></span></span> of enterprises can weaken the above relationship, then alleviate the effect of the DDEC on the enterprise performance. First, this study innovatively extends the research perspective to the supply chain scenario by assessing the digital divide between enterprises and their customers, thereby enriching the existing literature. Second, it adopts the knowledge-based theory to explore the “black box” of the DDEC affecting enterprise performance. Finally, it proposes operable suggestions for alleviating the negative impact of the digital divide at the enterprise level, providing important practical insights to enterprises.</div></div>","PeriodicalId":46792,"journal":{"name":"Journal of Innovation & Knowledge","volume":"13 ","pages":"Article 100914"},"PeriodicalIF":15.5,"publicationDate":"2025-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145791963","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 : 2025-12-12DOI: 10.1016/j.jik.2025.100918
Li Yue , Liang Han
Using panel data encompassing 282 cities across China from 2010 to 2022, this study delves into the ramifications of government environmental concern on green technological innovation, with a focus on intellectual property (IP) protection. It elucidates the mechanisms through which government environmental attention promotes green technological innovation, examining the effects of Research and Development (R&D) investment, resource allocation and talent aggregation. The findings indicate that government environmental attention markedly enhances green technological innovation. However, the impact of this attention significantly varies across diverse urban typologies, being more pronounced in second-tier metropolises, non-resource–reliant cities and municipalities governed by three-tier fiscal systems. Furthermore, the moderation effect test indicates that IP protection considerably enhances the efficacy of government environmental attention on green technological innovation. Further scrutiny suggests that optimal outcomes in IP protection are achieved when the average tenure of local government officials ranges from 39.64 to 43.55 months, particularly when these officials have an environmental background. In addition, in-depth analysis reveals that the effects of R&D investment, resource allocation and talent agglomeration constitute the pivotal transmission mechanisms through which government environmental attention stimulates green technological innovation. The conclusions of this study not only enrich the theoretical foundation for green technological innovation by government environmental attention but also provide empirical validation for exploring pathways through which IP protection can empower it.
{"title":"How does government environmental attention drive regional green technology innovation?","authors":"Li Yue , Liang Han","doi":"10.1016/j.jik.2025.100918","DOIUrl":"10.1016/j.jik.2025.100918","url":null,"abstract":"<div><div>Using panel data encompassing 282 cities across China from 2010 to 2022, this study delves into the ramifications of government environmental concern on green technological innovation, with a focus on intellectual property (IP) protection. It elucidates the mechanisms through which government environmental attention promotes green technological innovation, examining the effects of Research and Development (R&D) investment, resource allocation and talent aggregation. The findings indicate that government environmental attention markedly enhances green technological innovation. However, the impact of this attention significantly varies across diverse urban typologies, being more pronounced in second-tier metropolises, non-resource–reliant cities and municipalities governed by three-tier fiscal systems. Furthermore, the moderation effect test indicates that IP protection considerably enhances the efficacy of government environmental attention on green technological innovation. Further scrutiny suggests that optimal outcomes in IP protection are achieved when the average tenure of local government officials ranges from 39.64 to 43.55 months, particularly when these officials have an environmental background. In addition, in-depth analysis reveals that the effects of R&D investment, resource allocation and talent agglomeration constitute the pivotal transmission mechanisms through which government environmental attention stimulates green technological innovation. The conclusions of this study not only enrich the theoretical foundation for green technological innovation by government environmental attention but also provide empirical validation for exploring pathways through which IP protection can empower it.</div></div>","PeriodicalId":46792,"journal":{"name":"Journal of Innovation & Knowledge","volume":"12 ","pages":"Article 100918"},"PeriodicalIF":15.5,"publicationDate":"2025-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145731899","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}
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