Pub Date : 2024-07-16DOI: 10.1016/j.technovation.2024.103070
Prior literature has long recognized the substantial economic value that patents hold in the market. Yet, we know much less about the valuation process, i.e., how market audiences estimate (or determine) the value of newly granted patents. Building on behavioral economics, we propose the anchoring effect as an important cognitive mechanism, such that a patent's valuation is anchored on the value that preceding patents have secured. Analyzing financial valuation of U.S. patents between 1991 and 2010, we find broad support to the anchoring effect. The effect is more pronounced when focal patents are of lower novelty, when prior anchors are more consistent, and when focal firms have a higher patenting frequency. Furthermore, our extensional analysis suggests that anchoring acts as an important driver for the divergence between patents' economic value and scientific quality, which deserves attention from firms and policy makers.
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Pub Date : 2024-07-16DOI: 10.1016/j.technovation.2024.103068
This study investigates inter-firm relationships’ distinct impacts on entrepreneurial proactiveness (EP) and exploitative innovation strategy. Although the existing literature on entrepreneurs’ innovation strategies has consistently found a positive relationship between EP and exploration, the mechanisms underlying the inconsistent relationship between EP and exploitative innovation strategy remain unclear. We anticipate that applying brokerage position in network theory would offer further insights into the relationship between EP and exploitative innovation strategy. Additionally, we introduced depth of openness as a moderating variable and examined its effect on the moderated mediation relationship. To test hypotheses, this study utilized linear and logistic regression, bootstrapping, and the Johnson-Neyman technique. The findings of the 2020 Korean Innovation Survey, conducted by the Science and Technology Policy Institute, indicate that data from 2352 Korean manufacturing companies exhibits that the brokerage position mediates EP and exploitative innovation strategy. Moreover, the depth of openness mitigated the positive relationship between the brokerage position and the exploitative innovation strategy and the indirect effect of EP on exploitative innovation strategy through the brokerage position. These findings contribute theoretically to entrepreneurial orientation and underscore the practical significance of aligning company goals with social relationships.
本研究探讨了企业间关系对创业主动性(EP)和开拓性创新战略的不同影响。尽管有关企业家创新战略的现有文献一直认为创业主动性与探索之间存在正相关关系,但创业主动性与探索性创新战略之间不一致关系的内在机制仍不清楚。我们预计,运用网络理论中的中介地位将为 EP 与开拓性创新战略之间的关系提供进一步的启示。此外,我们还引入了开放深度作为调节变量,并考察了其对调节中介关系的影响。为了检验假设,本研究采用了线性回归和逻辑回归、引导法和约翰逊-奈曼技术。韩国科学技术政策研究所开展的 "2020 年韩国创新调查 "结果表明,来自 2352 家韩国制造企业的数据显示,经纪地位对 EP 和开拓性创新战略具有中介作用。此外,开放的深度减轻了经纪地位与利用型创新战略之间的正相关关系,以及EP通过经纪地位对利用型创新战略的间接影响。这些发现从理论上促进了创业导向,并强调了将公司目标与社会关系相结合的现实意义。
{"title":"Unpacking the link between entrepreneurial proactiveness and exploitative innovation strategy: The role of brokerage position and open innovation","authors":"","doi":"10.1016/j.technovation.2024.103068","DOIUrl":"10.1016/j.technovation.2024.103068","url":null,"abstract":"<div><p>This study investigates inter-firm relationships’ distinct impacts on entrepreneurial proactiveness (EP) and exploitative innovation strategy. Although the existing literature on entrepreneurs’ innovation strategies has consistently found a positive relationship between EP and exploration, the mechanisms underlying the inconsistent relationship between EP and exploitative innovation strategy remain unclear. We anticipate that applying brokerage position in network theory would offer further insights into the relationship between EP and exploitative innovation strategy. Additionally, we introduced depth of openness as a moderating variable and examined its effect on the moderated mediation relationship. To test hypotheses, this study utilized linear and logistic regression, bootstrapping, and the Johnson-Neyman technique. The findings of the 2020 Korean Innovation Survey, conducted by the Science and Technology Policy Institute, indicate that data from 2352 Korean manufacturing companies exhibits that the brokerage position mediates EP and exploitative innovation strategy. Moreover, the depth of openness mitigated the positive relationship between the brokerage position and the exploitative innovation strategy and the indirect effect of EP on exploitative innovation strategy through the brokerage position. These findings contribute theoretically to entrepreneurial orientation and underscore the practical significance of aligning company goals with social relationships.</p></div>","PeriodicalId":49444,"journal":{"name":"Technovation","volume":null,"pages":null},"PeriodicalIF":11.1,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141636903","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-10DOI: 10.1016/j.technovation.2024.103071
Francesca Zoccarato , Emanuele Lettieri , Giovanni Radaelli , Antonio Ghezzi , Giovanni Toletti
While existing literature acknowledges the role of science fiction in foreseeing technological advancements, a notable gap persists in understanding the underlying factors that drive or hinder individuals from the intention to generate and promote ideas gathered through science fiction. Our research model aims to shed novel light on what factors influence employees’ propensity to generate and promote ideas inspired by science fiction, through the lenses of institutional theory. Purposefully, we frame science fiction methodologies inside the Innovative Work Behavior discourse, as science fiction could be a fruitful tool to generate and promote ideas, and we investigate the interplay of rational and institutional influences on such behaviors. The findings provide valuable insights that can be leveraged to design and implement effective methodologies within organizational settings. Our study, based on data from 480 employees, employs Structural Equation Modeling to reveal the pivotal role of normative influence in idea generation, while idea promotion exhibits a robust association with cultural-cognitive influence, pinpointing the dual phase of science fiction methodologies.
{"title":"Taking Science Fiction seriously: Unveiling its relationship with employee’s Innovative Work Behavior","authors":"Francesca Zoccarato , Emanuele Lettieri , Giovanni Radaelli , Antonio Ghezzi , Giovanni Toletti","doi":"10.1016/j.technovation.2024.103071","DOIUrl":"https://doi.org/10.1016/j.technovation.2024.103071","url":null,"abstract":"<div><p>While existing literature acknowledges the role of science fiction in foreseeing technological advancements, a notable gap persists in understanding the underlying factors that drive or hinder individuals from the intention to generate and promote ideas gathered through science fiction. Our research model aims to shed novel light on what factors influence employees’ propensity to generate and promote ideas inspired by science fiction, through the lenses of institutional theory. Purposefully, we frame science fiction methodologies inside the Innovative Work Behavior discourse, as science fiction could be a fruitful tool to generate and promote ideas, and we investigate the interplay of rational and institutional influences on such behaviors. The findings provide valuable insights that can be leveraged to design and implement effective methodologies within organizational settings. Our study, based on data from 480 employees, employs Structural Equation Modeling to reveal the pivotal role of normative influence in idea generation, while idea promotion exhibits a robust association with cultural-cognitive influence, pinpointing the dual phase of science fiction methodologies.</p></div>","PeriodicalId":49444,"journal":{"name":"Technovation","volume":null,"pages":null},"PeriodicalIF":11.1,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0166497224001214/pdfft?md5=4ae11d46a94032215b58af5bc0af43ec&pid=1-s2.0-S0166497224001214-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141595614","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-01DOI: 10.1016/j.technovation.2024.103062
Yun Liu , Bhakti Stephan Onggo , Jerry Busby
Intertwining users' engagement with the development of new products is becoming increasingly important for improving the products' performance. Therefore, a method to model the dynamics of collective user engagement is essential. This paper proposes a method to model the dynamics of collective user engagement in new product development using agent-based simulation. The model integrates an indirect engagement process – in which users exchange information and knowledge, draw from past experiences, and psychologically invest in the product – with a direct engagement process – in which users interact with the product and the firm to contribute. We demonstrate how the model can be calibrated using a consumer survey. Our findings reveal an overall increase in user engagement, characterised by nonlinear growth during the idea and design stages, followed by a relatively steady increase during the test stage. Moreover, our study identifies the significance of various factors, such as social network parameters, past experience, product connection, and match degree, in shaping user engagement in new product development. This research provides a systematic approach to model user engagement within the context of new product development. It also offers practical implications that can guide management decisions in effectively engaging with users during new product development.
{"title":"Agent-based modelling of user engagement in new product development","authors":"Yun Liu , Bhakti Stephan Onggo , Jerry Busby","doi":"10.1016/j.technovation.2024.103062","DOIUrl":"https://doi.org/10.1016/j.technovation.2024.103062","url":null,"abstract":"<div><p>Intertwining users' engagement with the development of new products is becoming increasingly important for improving the products' performance. Therefore, a method to model the dynamics of collective user engagement is essential. This paper proposes a method to model the dynamics of collective user engagement in new product development using agent-based simulation. The model integrates an indirect engagement process – in which users exchange information and knowledge, draw from past experiences, and psychologically invest in the product – with a direct engagement process – in which users interact with the product and the firm to contribute. We demonstrate how the model can be calibrated using a consumer survey. Our findings reveal an overall increase in user engagement, characterised by nonlinear growth during the idea and design stages, followed by a relatively steady increase during the test stage. Moreover, our study identifies the significance of various factors, such as social network parameters, past experience, product connection, and match degree, in shaping user engagement in new product development. This research provides a systematic approach to model user engagement within the context of new product development. It also offers practical implications that can guide management decisions in effectively engaging with users during new product development.</p></div>","PeriodicalId":49444,"journal":{"name":"Technovation","volume":null,"pages":null},"PeriodicalIF":11.1,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141541762","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-01DOI: 10.1016/j.technovation.2024.103067
Ritika Chopra , Gagan Deep Sharma , Vijay Pereira
The literature on stock forecasting using the innovative technique of Artificial Intelligence (AI) has become overwhelming, making it quite challenging for academics and relevant researchers to gain an elaborative, structured, and organised overview of the relevant information. We fill this gap by contributing and conducting a robust bibliometric review on the application of AI innovations for stock market prediction. More specifically, we conducted a bibliometric review by identifying 241 relevant papers related to stock forecasting using AI by taking a quantitative approach. A quantitative approach uses an examination of linked articles to look at the development of research topics and the structure of existing knowledge. We identified five significant themes based on exploratory factor and hierarchical cluster analyses. We posited that successful AI-based models could aid stock traders, brokers, and investors in better decision-making, a task that had previously been fraught with difficulties. Overall, this paper is aimed at benefiting stock traders, brokers, businesses, investors, government, financial institutions, depositories, and banks. This paper concludes with a future research agenda.
{"title":"Identifying Bulls and bears? A bibliometric review of applying artificial intelligence innovations for stock market prediction","authors":"Ritika Chopra , Gagan Deep Sharma , Vijay Pereira","doi":"10.1016/j.technovation.2024.103067","DOIUrl":"https://doi.org/10.1016/j.technovation.2024.103067","url":null,"abstract":"<div><p>The literature on stock forecasting using the innovative technique of Artificial Intelligence (AI) has become overwhelming, making it quite challenging for academics and relevant researchers to gain an elaborative, structured, and organised overview of the relevant information. We fill this gap by contributing and conducting a robust bibliometric review on the application of AI innovations for stock market prediction. More specifically, we conducted a bibliometric review by identifying 241 relevant papers related to stock forecasting using AI by taking a quantitative approach. A quantitative approach uses an examination of linked articles to look at the development of research topics and the structure of existing knowledge. We identified five significant themes based on exploratory factor and hierarchical cluster analyses. We posited that successful AI-based models could aid stock traders, brokers, and investors in better decision-making, a task that had previously been fraught with difficulties. Overall, this paper is aimed at benefiting stock traders, brokers, businesses, investors, government, financial institutions, depositories, and banks. This paper concludes with a future research agenda.</p></div>","PeriodicalId":49444,"journal":{"name":"Technovation","volume":null,"pages":null},"PeriodicalIF":11.1,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141596013","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}
Recently, Gen AI has garnered significant attention across various sectors of society, particularly capturing the interest of small business due to its capacity to allow them to reassess their business models with minimal investment. To understand how small and medium-sized firms have utilised Gen AI-based tools to cope with the market's high level of turbulence caused by the COVID-19 pandemic, geopolitical crises, and economic slowdown, researchers have conducted an empirical study. Although Gen AI is receiving more attention, there remains a dearth of empirical studies that investigate how it influences the entrepreneurial orientation of firms and their ability to cultivate entrepreneurial resilience amidst market turbulence. Most of the literature offers anecdotal evidence. To address this research gap, the authors have grounded their theoretical model and research hypotheses in the contingent view of dynamic capability. They tested the research hypotheses using cross-sectional data from a pre-tested survey instrument, which yielded 87 useable responses from small and medium enterprises in France. The authors used variance-based structural equation modelling with the commercial WarpPLS 7.0 software to test the theoretical model. The study's findings suggest that Gen AI and EO have a significant influence on building entrepreneurial resilience as higher-order and lower-order dynamic capabilities. However, market turbulence has a negative moderating effect on the path that joins entrepreneurial orientation and entrepreneurial resilience. The results suggest that the assumption that high market turbulence will have positive effects on dynamic capabilities and competitive advantage is not always true, and the linear assumption does not hold, which is consistent with some scholars' assumptions. The study's results offer significant contributions to the contingent view of dynamic capabilities and open new research avenues that require further investigation into the non-linear relationship of market turbulence.
最近,Gen AI 在社会各行各业引起了极大关注,尤其是吸引了小型企业的兴趣,因为它能让它们以最小的投资重新评估自己的商业模式。为了了解中小型企业如何利用基于 Gen AI 的工具来应对 COVID-19 大流行病、地缘政治危机和经济放缓造成的市场剧烈动荡,研究人员开展了一项实证研究。虽然 Gen AI 正受到越来越多的关注,但仍缺乏实证研究来探讨 Gen AI 如何影响企业的创业导向,以及企业在市场动荡中培养创业应变能力的情况。大多数文献提供的都是传闻证据。针对这一研究空白,作者以动态能力的权变观点为基础,建立了自己的理论模型和研究假设。他们使用预先测试过的调查工具中的横截面数据对研究假设进行了检验,该调查工具从法国的中小型企业中获得了 87 份可用的回复。作者使用商业 WarpPLS 7.0 软件的方差结构方程模型来检验理论模型。研究结果表明,作为高阶和低阶动态能力,Gen AI 和 EO 对建立创业复原力有重大影响。然而,市场动荡对创业导向与创业复原力的连接路径具有负向调节作用。研究结果表明,市场动荡程度高会对动态能力和竞争优势产生积极影响的假设并不总是正确的,线性假设也不成立,这与一些学者的假设是一致的。研究结果为动态能力的权变观点做出了重要贡献,并开辟了新的研究途径,需要进一步研究市场动荡的非线性关系。
{"title":"Building entrepreneurial resilience during crisis using generative AI: An empirical study on SMEs","authors":"Adam Shore , Manisha Tiwari , Priyanka Tandon , Cyril Foropon","doi":"10.1016/j.technovation.2024.103063","DOIUrl":"https://doi.org/10.1016/j.technovation.2024.103063","url":null,"abstract":"<div><p>Recently, Gen AI has garnered significant attention across various sectors of society, particularly capturing the interest of small business due to its capacity to allow them to reassess their business models with minimal investment. To understand how small and medium-sized firms have utilised Gen AI-based tools to cope with the market's high level of turbulence caused by the COVID-19 pandemic, geopolitical crises, and economic slowdown, researchers have conducted an empirical study. Although Gen AI is receiving more attention, there remains a dearth of empirical studies that investigate how it influences the entrepreneurial orientation of firms and their ability to cultivate entrepreneurial resilience amidst market turbulence. Most of the literature offers anecdotal evidence. To address this research gap, the authors have grounded their theoretical model and research hypotheses in the contingent view of dynamic capability. They tested the research hypotheses using cross-sectional data from a pre-tested survey instrument, which yielded 87 useable responses from small and medium enterprises in France. The authors used variance-based structural equation modelling with the commercial WarpPLS 7.0 software to test the theoretical model. The study's findings suggest that Gen AI and EO have a significant influence on building entrepreneurial resilience as higher-order and lower-order dynamic capabilities. However, market turbulence has a negative moderating effect on the path that joins entrepreneurial orientation and entrepreneurial resilience. The results suggest that the assumption that high market turbulence will have positive effects on dynamic capabilities and competitive advantage is not always true, and the linear assumption does not hold, which is consistent with some scholars' assumptions. The study's results offer significant contributions to the contingent view of dynamic capabilities and open new research avenues that require further investigation into the non-linear relationship of market turbulence.</p></div>","PeriodicalId":49444,"journal":{"name":"Technovation","volume":null,"pages":null},"PeriodicalIF":11.1,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0166497224001135/pdfft?md5=a9262d49c10eb9d105b45f94960945c1&pid=1-s2.0-S0166497224001135-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141481098","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-01DOI: 10.1016/j.technovation.2024.103066
Elie Abi Saad , Marine Agogué
Living Labs (LLs) are now well-recognized in the development and commercialization of science—that is taking emerging discoveries from research labs to the industry. Whereas their widespread interest seems encouraging, it has been complicated by some inconsistencies regarding what LLs actually are, what types of activities they (should) support, and under what conditions. We conduct a meta-synthesis of 41 LL application patterns, supplemented by an in-depth empirical case study—the application of a MedTech LL in healthcare—to examine effective practices for organizing collaborative innovation within the science-industry nexus. By studying what worked best and under what conditions, we present a typology of eight design elements that underlie four unique LL models. Our analysis reveals that although these different models do fit under the same umbrella concept, they vary in the roles they serve in the collaborative innovation process. Most notably, we find that organizations need to navigate between these models as the collaboration moves from idea inception into impact. Our results offer relevant insights for understanding new forms of organizations for science-industry relations. We discuss practical implications for LL managers, researchers, and sponsoring institutions and conclude by outlining promising areas for future research.
{"title":"Living Labs in science-industry collaborations: Roles, design, and application patterns","authors":"Elie Abi Saad , Marine Agogué","doi":"10.1016/j.technovation.2024.103066","DOIUrl":"https://doi.org/10.1016/j.technovation.2024.103066","url":null,"abstract":"<div><p>Living Labs (LLs) are now well-recognized in the development and commercialization of science—that is taking emerging discoveries from research labs to the industry. Whereas their widespread interest seems encouraging, it has been complicated by some inconsistencies regarding what LLs actually are, what types of activities they (should) support, and under what conditions. We conduct a meta-synthesis of 41 LL application patterns, supplemented by an in-depth empirical case study—the application of a MedTech LL in healthcare—to examine effective practices for organizing collaborative innovation within the science-industry nexus. By studying what worked best and under what conditions, we present a typology of eight design elements that underlie four unique LL models. Our analysis reveals that although these different models do fit under the same umbrella concept, they vary in the roles they serve in the collaborative innovation process. Most notably, we find that organizations need to navigate between these models as the collaboration moves from idea inception into impact. Our results offer relevant insights for understanding new forms of organizations for science-industry relations. We discuss practical implications for LL managers, researchers, and sponsoring institutions and conclude by outlining promising areas for future research.</p></div>","PeriodicalId":49444,"journal":{"name":"Technovation","volume":null,"pages":null},"PeriodicalIF":11.1,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0166497224001160/pdfft?md5=cbbc835f68af8630d7d5284200a66fd0&pid=1-s2.0-S0166497224001160-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141481096","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-01DOI: 10.1016/j.technovation.2024.103064
Nripendra P. Rana , Rajasshrie Pillai , Brijesh Sivathanu , Nishtha Malik
Numerous enterprises employ Generative AI (GenAI) for a plethora of business operations, which can enhance organizational effectiveness. The adoption might be driven by multiple factors influencing the business landscape. Additionally, numerous ethical considerations could impact the deployment of GenAI. This unique study investigated how organizations adopt GenAI and its effects on their performance. Further, this research utilized institutional theory and ethical guidelines for AI design to develop a research framework examining how organizations adopt GenAI and its impact on their performance. A survey of 384 managers from information technology (IT) and information technology-enabled services (ITeS) companies was conducted. Data analysis was done using PLS-SEM to examine and validate the proposed model. The study outcome reveals that institutional pressures, i.e., coercive, normative and mimetic forces, influence the use of GenAI in organizations. It was also found that fairness, accountability, transparency, accuracy and autonomy influence the use of GenAI. Also, the results divulge that the use of GenAI influences organizational performance and is moderated by organizational innovativeness. This study provides insights to developers of GenAI, senior management of companies, the government and IT policymakers by highlighting the institutional pressures and ethical principles influencing the use of GenAI.
{"title":"Assessing the nexus of Generative AI adoption, ethical considerations and organizational performance","authors":"Nripendra P. Rana , Rajasshrie Pillai , Brijesh Sivathanu , Nishtha Malik","doi":"10.1016/j.technovation.2024.103064","DOIUrl":"https://doi.org/10.1016/j.technovation.2024.103064","url":null,"abstract":"<div><p>Numerous enterprises employ Generative AI (GenAI) for a plethora of business operations, which can enhance organizational effectiveness. The adoption might be driven by multiple factors influencing the business landscape. Additionally, numerous ethical considerations could impact the deployment of GenAI. This unique study investigated how organizations adopt GenAI and its effects on their performance. Further, this research utilized institutional theory and ethical guidelines for AI design to develop a research framework examining how organizations adopt GenAI and its impact on their performance. A survey of 384 managers from information technology (IT) and information technology-enabled services (ITeS) companies was conducted. Data analysis was done using PLS-SEM to examine and validate the proposed model. The study outcome reveals that institutional pressures, i.e., coercive, normative and mimetic forces, influence the use of GenAI in organizations. It was also found that fairness, accountability, transparency, accuracy and autonomy influence the use of GenAI. Also, the results divulge that the use of GenAI influences organizational performance and is moderated by organizational innovativeness. This study provides insights to developers of GenAI, senior management of companies, the government and IT policymakers by highlighting the institutional pressures and ethical principles influencing the use of GenAI.</p></div>","PeriodicalId":49444,"journal":{"name":"Technovation","volume":null,"pages":null},"PeriodicalIF":11.1,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0166497224001147/pdfft?md5=fb767bbb6c7b5aca8cea142c3c37b257&pid=1-s2.0-S0166497224001147-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141541761","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-01DOI: 10.1016/j.technovation.2024.103069
Magnus Klofsten, Alexander Brem, Maribel Guerrero, David Urbano
Despite extensive research on academic entrepreneurship and entrepreneurial universities, this special issue challenges conventional beliefs by examining intrapreneurship in academia. It aims to investigate how faculty and staff can adopt entrepreneurial behaviors and cultivate an entrepreneurial approach within their roles as researchers and educators, in diverse academic contexts. The 11 papers included in this issue span various domains of intrapreneurial universities, broadening the original concept beyond initial expectations set forth in the call for papers. Exploring a spectrum of intrapreneurial initiatives, this issue seeks to enhance understanding and broaden perspectives on intrapreneurial behaviors within universities through various research approaches and methodologies. Based on the contributions received, we reflect on theoretical and practical implications and delineate future directions for academic intrapreneurship research.
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Pub Date : 2024-07-01DOI: 10.1016/j.technovation.2024.103065
Matthias Huegel
This study conceptualizes a quadrant model characterizing four profiles by contrasting university scientists’ multiple goals: research performance and commercialization. Since literature shows that these goals are conflicting but not mutually exclusive, social capital theory is drawn to test the influence of scientists’ bonding, bridging, and linking social capital on their profile affiliation. Survey data from 1057 German scientists is utilized to estimate a multinomial logistic regression model relating scientists’ profiles to the different forms of social capital. The results show that only 4.16% of the scientists achieve above-average research performance and also commercialize their research results, whereby all three forms of their social capital positively impact the achievement of these goals. Furthermore, bonding social capital positively relates to scientists with above-average research performance but no commercialized research results. Bridging social capital facilitates scientists to commercialize results, albeit with below-average research performance. In addition, an inverted U-shaped relationship between scientists’ bonding social capital and their research performance is identified, suggesting that an excess of this form of social capital may impede scientists’ ability to achieve multiple goals. The results are discussed and policy recommendations are derived.
本研究通过对比大学科学家的多重目标:研究绩效和商业化,构思了一个四象限模型,描述了四种特征。由于文献表明这些目标相互冲突但并不相互排斥,因此引用社会资本理论来检验科学家的纽带、桥梁和联系社会资本对其特征归属的影响。我们利用对 1057 名德国科学家的调查数据,估算了一个将科学家的个人简介与不同形式的社会资本相关联的多项式逻辑回归模型。结果表明,只有 4.16% 的科学家取得了高于平均水平的研究绩效,并将其研究成果商业化,而他们的三种社会资本形式都对这些目标的实现产生了积极影响。此外,纽带型社会资本与研究绩效高于平均水平但没有商业化研究成果的科学家呈正相关。尽管研究绩效低于平均水平,但桥梁型社会资本有助于科学家将成果商业化。此外,研究还发现科学家的纽带型社会资本与他们的研究绩效之间存在倒 U 型关系,这表明这种形式的社会资本过多可能会阻碍科学家实现多重目标的能力。本文对研究结果进行了讨论,并提出了政策建议。
{"title":"University scientists’ multiple goals achievement: Social capital and its impact on research performance and research commercialization","authors":"Matthias Huegel","doi":"10.1016/j.technovation.2024.103065","DOIUrl":"https://doi.org/10.1016/j.technovation.2024.103065","url":null,"abstract":"<div><p>This study conceptualizes a quadrant model characterizing four profiles by contrasting university scientists’ multiple goals: research performance and commercialization. Since literature shows that these goals are conflicting but not mutually exclusive, social capital theory is drawn to test the influence of scientists’ bonding, bridging, and linking social capital on their profile affiliation. Survey data from 1057 German scientists is utilized to estimate a multinomial logistic regression model relating scientists’ profiles to the different forms of social capital. The results show that only 4.16% of the scientists achieve above-average research performance and also commercialize their research results, whereby all three forms of their social capital positively impact the achievement of these goals. Furthermore, bonding social capital positively relates to scientists with above-average research performance but no commercialized research results. Bridging social capital facilitates scientists to commercialize results, albeit with below-average research performance. In addition, an inverted U-shaped relationship between scientists’ bonding social capital and their research performance is identified, suggesting that an excess of this form of social capital may impede scientists’ ability to achieve multiple goals. The results are discussed and policy recommendations are derived.</p></div>","PeriodicalId":49444,"journal":{"name":"Technovation","volume":null,"pages":null},"PeriodicalIF":11.1,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0166497224001159/pdfft?md5=5bef414f17a0cef4c6e35cf0ed1c7bb1&pid=1-s2.0-S0166497224001159-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141481097","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}