Pub Date : 2025-11-08DOI: 10.1016/j.jik.2025.100881
Xintian Li , Peng Peng
Knowledge-hiding (KH) behaviors undermine innovation and collaboration, making it critical to understand their antecedents and identify effective countermeasures. Drawing on social information processing theory and social identity theory, this study develops and empirically tests a dual mediation model that links authentic leadership (AL) to employee KH behavior via psychological safety (PS) and relational identification (RI). On the basis of a two-wave survey of 337 knowledge-based employees in China, the results show that AL significantly reduces KH behaviors, both directly and indirectly through enhanced PS and RI. These findings reveal key psychological mechanisms through which AL fosters a more transparent and collaborative work environment. This study contributes to the literature on leadership and knowledge management, providing practical guidance for organizations seeking to promote knowledge sharing.
{"title":"How authentic leadership prevents knowledge hiding: The mediating roles of psychological safety and relational identification","authors":"Xintian Li , Peng Peng","doi":"10.1016/j.jik.2025.100881","DOIUrl":"10.1016/j.jik.2025.100881","url":null,"abstract":"<div><div>Knowledge-hiding (KH) behaviors undermine innovation and collaboration, making it critical to understand their antecedents and identify effective countermeasures. Drawing on social information processing theory and social identity theory, this study develops and empirically tests a dual mediation model that links authentic leadership (AL) to employee KH behavior via psychological safety (PS) and relational identification (RI). On the basis of a two-wave survey of 337 knowledge-based employees in China, the results show that AL significantly reduces KH behaviors, both directly and indirectly through enhanced PS and RI. These findings reveal key psychological mechanisms through which AL fosters a more transparent and collaborative work environment. This study contributes to the literature on leadership and knowledge management, providing practical guidance for organizations seeking to promote knowledge sharing.</div></div>","PeriodicalId":46792,"journal":{"name":"Journal of Innovation & Knowledge","volume":"11 ","pages":"Article 100881"},"PeriodicalIF":15.5,"publicationDate":"2025-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145473083","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 : 2025-11-06DOI: 10.1016/j.jik.2025.100874
Jun 张君 Zhang, Junbo 崔君博 Cui, 柴欣辰 xinchen Chai
Job crafting is a multidimensional construct rather than a one-dimensional variable. However, prior research often treats it as a holistic concept or examines its impacts through isolated dimensions. Employing action theory and fuzzy-set qualitative comparative analysis (fsQCA), this study explores how the four dimensions of job crafting influence employee performance. Given the growing prevalence of job crafting within digital environments, this study integrates digital transformation and digital leadership as task-related and social environmental factors, respectively, to investigate pathways leading to high performance in the context of work reimagining. The findings indicate that the inclusion of enterprise digital transformation and digital leadership elevates the number of high-performance configurations from two to three. This underscores the role of contextual enablers in facilitating more diverse and flexible routes to high performance. This study offers both theoretical contributions and practical implications.
{"title":"Job crafting in innovative digital contexts: A configurational analysis of behavioral pathways to performance","authors":"Jun 张君 Zhang, Junbo 崔君博 Cui, 柴欣辰 xinchen Chai","doi":"10.1016/j.jik.2025.100874","DOIUrl":"10.1016/j.jik.2025.100874","url":null,"abstract":"<div><div>Job crafting is a multidimensional construct rather than a one-dimensional variable. However, prior research often treats it as a holistic concept or examines its impacts through isolated dimensions. Employing action theory and fuzzy-set qualitative comparative analysis (fsQCA), this study explores how the four dimensions of job crafting influence employee performance. Given the growing prevalence of job crafting within digital environments, this study integrates digital transformation and digital leadership as task-related and social environmental factors, respectively, to investigate pathways leading to high performance in the context of work reimagining. The findings indicate that the inclusion of enterprise digital transformation and digital leadership elevates the number of high-performance configurations from two to three. This underscores the role of contextual enablers in facilitating more diverse and flexible routes to high performance. This study offers both theoretical contributions and practical implications.</div></div>","PeriodicalId":46792,"journal":{"name":"Journal of Innovation & Knowledge","volume":"11 ","pages":"Article 100874"},"PeriodicalIF":15.5,"publicationDate":"2025-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145472914","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 : 2025-11-05DOI: 10.1016/j.jik.2025.100877
Ming Fang , Chiu-Lan Chang , Hasan Dinçer , Serhat Yüksel
Environmental, social, and governance (ESG)-based investment strategies aim to integrate not only economic but also ethical and environmental dimensions into financial decision-making processes to promote sustainable economic growth. However, the relative effects of ESG criteria on economic growth have not been sufficiently examined in the existing literature, creating a significant research gap. Consequently, investment priorities and public policies cannot be determined effectively. The main objective of this study is to identify strategies that enable countries with limited resources to prioritize the ESG factors yielding the greatest benefit. The decision-making model proposed in this study is based on the principal component regression (PCR) approach, which minimizes multicollinearity issues. In this process, data from 155 countries for the year 2020 are taken into consideration. This study makes three main contributions to the literature: (1) a comparative examination of the relative effects of ESG factors on economic growth, (2) identifying how these effects differ across country groups, and (3) analyzing multicollinearity among ESG variables more accurately through the PCR method. The findings indicate that environmental burdens negatively affect growth in Asia, whereas education expenditures positively influence growth in developed economies.
{"title":"A data-driven framework for ESG prioritization: PCR-based insights for sustainable governance and growth","authors":"Ming Fang , Chiu-Lan Chang , Hasan Dinçer , Serhat Yüksel","doi":"10.1016/j.jik.2025.100877","DOIUrl":"10.1016/j.jik.2025.100877","url":null,"abstract":"<div><div>Environmental, social, and governance (ESG)-based investment strategies aim to integrate not only economic but also ethical and environmental dimensions into financial decision-making processes to promote sustainable economic growth. However, the relative effects of ESG criteria on economic growth have not been sufficiently examined in the existing literature, creating a significant research gap. Consequently, investment priorities and public policies cannot be determined effectively. The main objective of this study is to identify strategies that enable countries with limited resources to prioritize the ESG factors yielding the greatest benefit. The decision-making model proposed in this study is based on the principal component regression (PCR) approach, which minimizes multicollinearity issues. In this process, data from 155 countries for the year 2020 are taken into consideration. This study makes three main contributions to the literature: (1) a comparative examination of the relative effects of ESG factors on economic growth, (2) identifying how these effects differ across country groups, and (3) analyzing multicollinearity among ESG variables more accurately through the PCR method. The findings indicate that environmental burdens negatively affect growth in Asia, whereas education expenditures positively influence growth in developed economies.</div></div>","PeriodicalId":46792,"journal":{"name":"Journal of Innovation & Knowledge","volume":"11 ","pages":"Article 100877"},"PeriodicalIF":15.5,"publicationDate":"2025-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145447269","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 : 2025-11-04DOI: 10.1016/j.jik.2025.100866
Roberto Cerchione, Giuseppe Liccardo, Renato Passaro
Generative artificial intelligence (GenAI), with its potential to autonomously generate new content in the form of text, video, audio and code, holds disruptive potential to revolutionize knowledge management (KM) processes. An enormous number of studies have been published in recent years on the application of GenAI and this number is expected to increase further. Nevertheless, there are relatively few studies that systematize this research domain, and they are scarce from a KM perspective. For this reason, this study intends to bridge the current gap by offering both qualitative and quantitative insights in this research field using a bibliometric literature review, combining descriptive analysis with science mapping techniques, to analyse the impact GenAI has on KM processes. In particular, the aims of this paper are to provide a structured overview of how GenAI research contributes to the evolution of KM, to identify inconsistencies in the understanding of GenAI’s role in knowledge creation, and to propose directions for future theoretical and empirical research. In addition, our contribution proposes both the introduction of a new conceptual dimension, namely the machine dimension, which may extend traditional knowledge generation models, and a conceptual taxonomy for analysing GenAI readiness that is useful for managers and practitioners.
{"title":"Artificial knowledge generation: investigating the revolutionary role of generative AI in knowledge management","authors":"Roberto Cerchione, Giuseppe Liccardo, Renato Passaro","doi":"10.1016/j.jik.2025.100866","DOIUrl":"10.1016/j.jik.2025.100866","url":null,"abstract":"<div><div>Generative artificial intelligence (GenAI), with its potential to autonomously generate new content in the form of text, video, audio and code, holds disruptive potential to revolutionize knowledge management (KM) processes. An enormous number of studies have been published in recent years on the application of GenAI and this number is expected to increase further. Nevertheless, there are relatively few studies that systematize this research domain, and they are scarce from a KM perspective. For this reason, this study intends to bridge the current gap by offering both qualitative and quantitative insights in this research field using a bibliometric literature review, combining descriptive analysis with science mapping techniques, to analyse the impact GenAI has on KM processes. In particular, the aims of this paper are to provide a structured overview of how GenAI research contributes to the evolution of KM, to identify inconsistencies in the understanding of GenAI’s role in knowledge creation, and to propose directions for future theoretical and empirical research. In addition, our contribution proposes both the introduction of a new conceptual dimension, namely the machine dimension, which may extend traditional knowledge generation models, and a conceptual taxonomy for analysing GenAI readiness that is useful for managers and practitioners.</div></div>","PeriodicalId":46792,"journal":{"name":"Journal of Innovation & Knowledge","volume":"11 ","pages":"Article 100866"},"PeriodicalIF":15.5,"publicationDate":"2025-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145441664","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 : 2025-11-03DOI: 10.1016/j.jik.2025.100860
Khushboo Raina , Gagan Deep Sharma , Babak Taheri , Dhairya Dev , Shubham Chavriya
The rapid evolution of artificial intelligence (AI) from expert systems and fuzzy logic to sophisticated technologies such as deep learning and big data analytics has transformed modern management practices. This study explores how AI-driven management practices can effectively bridge innovation, knowledge creation, and sustainable business practices, thereby contributing to long-term organizational growth and the achievement of the Sustainable Development Goals (SDGs). By employing a comprehensive review research technique and analyzing 1,377 articles from the Scopus database, this study uncovers critical themes, sub-themes, variables, and their interlinkages. The findings demonstrate AI’s transformative potential across diverse domains, including human resource management, consumer service management, strategic leadership, operational efficiency, and customer experience enhancement. This paper addresses the role of AI governance frameworks that prioritize ethical considerations such as accountability, transparency, privacy, and cybersecurity, while fostering innovation-oriented knowledge creation. Despite significant advancements, knowledge gaps remain in integrating AI with innovative business models to achieve sustainability objectives. The study concludes by offering research and policy recommendations to promote AI-driven innovations that are ethically sound, operationally efficient, and socially responsible. This work contributes to the discourse on AI’s role in enhancing knowledge systems and innovation processes, providing valuable insights for scholars, practitioners, policymakers, and business leaders.
{"title":"Artificial intelligence-driven management: Bridging innovation, knowledge creation, and sustainable business practices","authors":"Khushboo Raina , Gagan Deep Sharma , Babak Taheri , Dhairya Dev , Shubham Chavriya","doi":"10.1016/j.jik.2025.100860","DOIUrl":"10.1016/j.jik.2025.100860","url":null,"abstract":"<div><div>The rapid evolution of artificial intelligence (AI) from expert systems and fuzzy logic to sophisticated technologies such as deep learning and big data analytics has transformed modern management practices. This study explores how AI-driven management practices can effectively bridge innovation, knowledge creation, and sustainable business practices, thereby contributing to long-term organizational growth and the achievement of the Sustainable Development Goals (SDGs). By employing a comprehensive review research technique and analyzing 1,377 articles from the Scopus database, this study uncovers critical themes, sub-themes, variables, and their interlinkages. The findings demonstrate AI’s transformative potential across diverse domains, including human resource management, consumer service management, strategic leadership, operational efficiency, and customer experience enhancement. This paper addresses the role of AI governance frameworks that prioritize ethical considerations such as accountability, transparency, privacy, and cybersecurity, while fostering innovation-oriented knowledge creation. Despite significant advancements, knowledge gaps remain in integrating AI with innovative business models to achieve sustainability objectives. The study concludes by offering research and policy recommendations to promote AI-driven innovations that are ethically sound, operationally efficient, and socially responsible. This work contributes to the discourse on AI’s role in enhancing knowledge systems and innovation processes, providing valuable insights for scholars, practitioners, policymakers, and business leaders.</div></div>","PeriodicalId":46792,"journal":{"name":"Journal of Innovation & Knowledge","volume":"11 ","pages":"Article 100860"},"PeriodicalIF":15.5,"publicationDate":"2025-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145441332","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 : 2025-10-30DOI: 10.1016/j.jik.2025.100872
Arshad Ahmad Khan , Sufyan Ullah Khan , Muhammad Abu Sufyan Ali , Ijlal Haider , Jianchao Luo
This study examines the role of science and technology finance (S&TF) and Industry 4.0 innovations in promoting sustainable transformation in China's copper mining industry, with a focus on reducing carbon emissions. Using panel data from 30 Chinese provinces spanning 2011 to 2020, we apply two-way fixed effects and threshold regression models to examine the nonlinear impacts of S&TF on carbon emissions from copper mining (CECM). Our findings demonstrate that a 1 % increase in S&TF is associated with an approximate 0.142 % reduction in CECM, with the effect becoming more pronounced beyond the identified national threshold value of 0.163. The effect is most pronounced in the economically advanced eastern regions but remains relevant across central and western provinces. Furthermore, the effectiveness of S&TF is moderated by regional Industry 4.0 development, which exhibits a U-shaped influence, while economic development strengthens and environmental regulation weakens the impact of decarbonization over time. These findings highlight the need to align financial innovation, regional technological capacity, and governance mechanisms to advance SDG and ESG objectives in resource-intensive industries. The study offers practical insights for developing resilient, innovation-driven financial and governance frameworks that can effectively reduce industrial carbon emissions.
{"title":"The role of financial innovation and Industry 4.0 in decarbonizing resource-intensive industries through threshold effects","authors":"Arshad Ahmad Khan , Sufyan Ullah Khan , Muhammad Abu Sufyan Ali , Ijlal Haider , Jianchao Luo","doi":"10.1016/j.jik.2025.100872","DOIUrl":"10.1016/j.jik.2025.100872","url":null,"abstract":"<div><div>This study examines the role of science and technology finance (S&TF) and Industry 4.0 innovations in promoting sustainable transformation in China's copper mining industry, with a focus on reducing carbon emissions. Using panel data from 30 Chinese provinces spanning 2011 to 2020, we apply two-way fixed effects and threshold regression models to examine the nonlinear impacts of S&TF on carbon emissions from copper mining (CECM). Our findings demonstrate that a 1 % increase in S&TF is associated with an approximate 0.142 % reduction in CECM, with the effect becoming more pronounced beyond the identified national threshold value of 0.163. The effect is most pronounced in the economically advanced eastern regions but remains relevant across central and western provinces. Furthermore, the effectiveness of S&TF is moderated by regional Industry 4.0 development, which exhibits a U-shaped influence, while economic development strengthens and environmental regulation weakens the impact of decarbonization over time. These findings highlight the need to align financial innovation, regional technological capacity, and governance mechanisms to advance SDG and ESG objectives in resource-intensive industries. The study offers practical insights for developing resilient, innovation-driven financial and governance frameworks that can effectively reduce industrial carbon emissions.</div></div>","PeriodicalId":46792,"journal":{"name":"Journal of Innovation & Knowledge","volume":"11 ","pages":"Article 100872"},"PeriodicalIF":15.5,"publicationDate":"2025-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145404593","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 : 2025-10-29DOI: 10.1016/j.jik.2025.100863
Sikandar Ali Qalati , Faiza Siddiqui
As artificial intelligence (AI) adoption accelerates globally, its sustainability implications remain insufficiently integrated into organizational capability frameworks. This study develops and validates the organizational sustainable AI capabilities (OSAIC) construct, extending dynamic capabilities theory by embedding sustainability as a meta-capability in AI governance and innovation processes. OSAIC is conceptualized as a five-dimensional, reflective, higher-order construct, encompassing sustainable AI learning, seizing, sensing, stakeholder integration, and transformation. A multi-phase scale development procedure—including expert Q-sorting, exploratory factor analysis, and confirmatory factor analysis, using partial least squares structural equation modeling—was employed. The scale was assessed and validated using two distinct samples: a pilot study (n = 188) and a main study (n = 364), both comprising managers from diverse industries and regions. The findings indicated robust psychometric attributes, characterized by substantial reliability, convergent, discriminant, and predictive validity. A positive and significant relationship between OSAIC and sustainable innovation indicated nomological validity, addressing the AI sustainability paradox by illustrating that sustainability-oriented AI capabilities enhance rather than constrain innovation. By extending the research on dynamic capabilities and paradoxes and presenting a validated measurement tool, this study contributes theoretically and methodologically, respectively, to the literature. Practically, it offers managers a diagnostic framework to align AI implementation with environmental and social accountability while fostering innovation.
{"title":"Organizational sustainable artificial intelligence capabilities scale development, validation, and implications","authors":"Sikandar Ali Qalati , Faiza Siddiqui","doi":"10.1016/j.jik.2025.100863","DOIUrl":"10.1016/j.jik.2025.100863","url":null,"abstract":"<div><div>As artificial intelligence (AI) adoption accelerates globally, its sustainability implications remain insufficiently integrated into organizational capability frameworks. This study develops and validates the organizational sustainable AI capabilities (OSAIC) construct, extending dynamic capabilities theory by embedding sustainability as a meta-capability in AI governance and innovation processes. OSAIC is conceptualized as a five-dimensional, reflective, higher-order construct, encompassing sustainable AI learning, seizing, sensing, stakeholder integration, and transformation. A multi-phase scale development procedure—including expert Q-sorting, exploratory factor analysis, and confirmatory factor analysis, using partial least squares structural equation modeling—was employed. The scale was assessed and validated using two distinct samples: a pilot study (<em>n</em> = 188) and a main study (<em>n</em> = 364), both comprising managers from diverse industries and regions. The findings indicated robust psychometric attributes, characterized by substantial reliability, convergent, discriminant, and predictive validity. A positive and significant relationship between OSAIC and sustainable innovation indicated nomological validity, addressing the AI sustainability paradox by illustrating that sustainability-oriented AI capabilities enhance rather than constrain innovation. By extending the research on dynamic capabilities and paradoxes and presenting a validated measurement tool, this study contributes theoretically and methodologically, respectively, to the literature. Practically, it offers managers a diagnostic framework to align AI implementation with environmental and social accountability while fostering innovation.</div></div>","PeriodicalId":46792,"journal":{"name":"Journal of Innovation & Knowledge","volume":"11 ","pages":"Article 100863"},"PeriodicalIF":15.5,"publicationDate":"2025-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145397548","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 : 2025-10-29DOI: 10.1016/j.jik.2025.100870
Qianqian Shi, Yuanlei Deng, Tingli Liu, Xiaojun Liu
The deep integration of the digital and real economies provides technological empowerment and strategic support for the innovative development of enterprises in China. This study employs the Latent Dirichlet Allocation model to quantify the balance of ambidextrous innovation by analyzing the textual content of analyst reports on listed companies. It examines how digital-real integration affects this balance, as well as the underlying mechanisms. Empirical results indicate that digital-real integration exerts a significant positive effect on promoting ambidextrous innovation balance in enterprises. This finding holds after addressing potential endogeneity issues and conducting a series of robustness tests. Mechanism analysis reveals that digital-real integration facilitates ambidextrous innovation balance by enhancing management efficiency and optimizing production factor allocation. Furthermore, heterogeneity analysis shows that the positive effect of digital-real integration is more pronounced in enterprises facing lower financial constraints, those operating in more competitive markets, and those located in regions with more advanced digital infrastructure. This study elucidates the mechanism through which digital-real integration influences ambidextrous innovation balance from both theoretical and practical perspectives, offering valuable insights for promoting the synergistic enhancement of corporate innovation capabilities.
{"title":"Does digital-real integration drive enterprise ambidextrous innovation balance?","authors":"Qianqian Shi, Yuanlei Deng, Tingli Liu, Xiaojun Liu","doi":"10.1016/j.jik.2025.100870","DOIUrl":"10.1016/j.jik.2025.100870","url":null,"abstract":"<div><div>The deep integration of the digital and real economies provides technological empowerment and strategic support for the innovative development of enterprises in China. This study employs the Latent Dirichlet Allocation model to quantify the balance of ambidextrous innovation by analyzing the textual content of analyst reports on listed companies. It examines how digital-real integration affects this balance, as well as the underlying mechanisms. Empirical results indicate that digital-real integration exerts a significant positive effect on promoting ambidextrous innovation balance in enterprises. This finding holds after addressing potential endogeneity issues and conducting a series of robustness tests. Mechanism analysis reveals that digital-real integration facilitates ambidextrous innovation balance by enhancing management efficiency and optimizing production factor allocation. Furthermore, heterogeneity analysis shows that the positive effect of digital-real integration is more pronounced in enterprises facing lower financial constraints, those operating in more competitive markets, and those located in regions with more advanced digital infrastructure. This study elucidates the mechanism through which digital-real integration influences ambidextrous innovation balance from both theoretical and practical perspectives, offering valuable insights for promoting the synergistic enhancement of corporate innovation capabilities.</div></div>","PeriodicalId":46792,"journal":{"name":"Journal of Innovation & Knowledge","volume":"11 ","pages":"Article 100870"},"PeriodicalIF":15.5,"publicationDate":"2025-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145383787","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 : 2025-10-27DOI: 10.1016/j.jik.2025.100867
Martínez Córdoba Pedro José , Márquez Arenas Lorena , Povedano Fernández Pablo , Rodríguez Gómez Sara , Zafra Gómez José Luis
The COVID-19 pandemic posed severe challenges for governments, presenting unknown situations and requiring decisions to be made under unprecedented uncertainty. Scientists responded fast, developing vaccines to mitigate the effects of the disease and improve pandemic management. This study examines the evolution of healthcare efficiency during the first year of vaccination against COVID-19 and identifies the impact of related social, economic, and political factors. Using the Global Malmquist-Luenberger index, we measure the evolution of efficiency during the first year of the COVID-19 pandemic. We employ a truncated-regression model estimated by maximum likelihood to determine the impact of various environmental factors on the change in efficiency. The results show that 70% of the countries in the sample, most of which had high vaccination coverage, improved their efficiency during the first year of COVID-19 vaccine deployment. A larger dependent population was associated with lower efficiency levels. Higher governance quality was positively and significantly related to efficiency. In contrast, GDP growth forecasts and government type had no statistically significant effects. The results confirm that homogeneous and complete vaccination in all countries improved the efficient management of this highly contagious disease. These findings can help policymakers analyse their management performance and better understand the factors that contribute to efficient management during pandemics.
{"title":"Knowledge and vaccination in COVID-19 management efficiency: a Global Malmquist-Luenberger index analysis","authors":"Martínez Córdoba Pedro José , Márquez Arenas Lorena , Povedano Fernández Pablo , Rodríguez Gómez Sara , Zafra Gómez José Luis","doi":"10.1016/j.jik.2025.100867","DOIUrl":"10.1016/j.jik.2025.100867","url":null,"abstract":"<div><div>The COVID-19 pandemic posed severe challenges for governments, presenting unknown situations and requiring decisions to be made under unprecedented uncertainty. Scientists responded fast, developing vaccines to mitigate the effects of the disease and improve pandemic management. This study examines the evolution of healthcare efficiency during the first year of vaccination against COVID-19 and identifies the impact of related social, economic, and political factors. Using the Global Malmquist-Luenberger index, we measure the evolution of efficiency during the first year of the COVID-19 pandemic. We employ a truncated-regression model estimated by maximum likelihood to determine the impact of various environmental factors on the change in efficiency. The results show that 70% of the countries in the sample, most of which had high vaccination coverage, improved their efficiency during the first year of COVID-19 vaccine deployment. A larger dependent population was associated with lower efficiency levels. Higher governance quality was positively and significantly related to efficiency. In contrast, GDP growth forecasts and government type had no statistically significant effects. The results confirm that homogeneous and complete vaccination in all countries improved the efficient management of this highly contagious disease. These findings can help policymakers analyse their management performance and better understand the factors that contribute to efficient management during pandemics.</div></div>","PeriodicalId":46792,"journal":{"name":"Journal of Innovation & Knowledge","volume":"11 ","pages":"Article 100867"},"PeriodicalIF":15.5,"publicationDate":"2025-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145381832","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 : 2025-10-26DOI: 10.1016/j.jik.2025.100859
Agnieszka Kowalska-Styczeń, Kinga Juszczyk
This study analyzed 1480 job advertisements for business analysts using natural language processing (NLP) and sentiment analysis. While confirming the demand for technical, analytical and communication skills, the study reveals important patterns that expand upon existing knowledge. Specifically, we observe how skill expectations evolve across career stages: junior positions emphasize language proficiency and communication, whereas senior roles require stronger project management, leadership, and advanced analytical capabilities. Sentiment analysis reveals that employers predominantly use neutral or positive language in job postings, reflecting conscious strategies to attract candidates. Furthermore, the study shows that an increasing number of employers are offering flexible working arrangements, such as hybrid and remote work, as well as non-wage benefits, including private healthcare and career development opportunities. This indicates an increase in competition for talent in the labor market. These findings offer valuable insights for curriculum design and recruitment strategies.
{"title":"Employer expectations of business analysts: Knowledge and insights from job offer analysis","authors":"Agnieszka Kowalska-Styczeń, Kinga Juszczyk","doi":"10.1016/j.jik.2025.100859","DOIUrl":"10.1016/j.jik.2025.100859","url":null,"abstract":"<div><div>This study analyzed 1480 job advertisements for business analysts using natural language processing (NLP) and sentiment analysis. While confirming the demand for technical, analytical and communication skills, the study reveals important patterns that expand upon existing knowledge. Specifically, we observe how skill expectations evolve across career stages: junior positions emphasize language proficiency and communication, whereas senior roles require stronger project management, leadership, and advanced analytical capabilities. Sentiment analysis reveals that employers predominantly use neutral or positive language in job postings, reflecting conscious strategies to attract candidates. Furthermore, the study shows that an increasing number of employers are offering flexible working arrangements, such as hybrid and remote work, as well as non-wage benefits, including private healthcare and career development opportunities. This indicates an increase in competition for talent in the labor market. These findings offer valuable insights for curriculum design and recruitment strategies.</div></div>","PeriodicalId":46792,"journal":{"name":"Journal of Innovation & Knowledge","volume":"11 ","pages":"Article 100859"},"PeriodicalIF":15.5,"publicationDate":"2025-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145381835","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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