Technovation最新文献_第8页

Investee peer effect on firm Innovation: An uncertainty-reduction perspective 被投资方同伴效应对企业创新的影响：一个不确定性降低的视角

IF 11.1 1区管理学

Technovation Pub Date : 2025-06-17 DOI: 10.1016/j.technovation.2025.103291

Yusen Dong , Donghong Li , Pengcheng Ma , Yoona Choi

{"title":"Investee peer effect on firm Innovation: An uncertainty-reduction perspective","authors":"Yusen Dong , Donghong Li , Pengcheng Ma , Yoona Choi","doi":"10.1016/j.technovation.2025.103291","DOIUrl":"10.1016/j.technovation.2025.103291","url":null,"abstract":"<div><div>Scholars have extensively examined the impact of industry peers' innovation on focal firms' innovation. However, our study shifts the focus to a significant yet often overlooked category of peers: investee peers, which are firms that share common shareholders with the focal firm. Drawing on the open-system tradition of management research from the uncertainty-reduction perspective, we argue that common shareholders serve as conduits of information, enabling focal firms to access reliable and comprehensive data from their investee peers. As a result, the focal firm can reduce uncertainty by aligning its innovation activities with those of its investee peers. Using data from a sample of Chinese-listed firms between 2008 and 2017, we find empirical support for this argument. Specifically, we show that investee peers' innovation positively influences the focal firm's innovation outcomes. Furthermore, this positive relationship is strengthened when investee firms obtain more “High-Tech Enterprise” (HTE) certifications from the government and when shareholders hold a larger proportion of the focal firm's shares. Conversely, the relationship weakens when the focal firm is a state-owned enterprise (SOE). By focusing on investee peers rather than industry peers, our study contributes to the literature by emphasizing an information-based mechanism for peer effects in innovation. This mechanism is driven not by competition, as in the case of industry peers, but by the shared ownership structure within common shareholder networks.</div></div>","PeriodicalId":49444,"journal":{"name":"Technovation","volume":"146 ","pages":"Article 103291"},"PeriodicalIF":11.1,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144298284","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}

引用次数: 0

How and when does digital transformation promote technological innovation performance? A study of Chinese high-tech firms 数字化转型如何以及何时促进技术创新绩效？对中国高科技企业的研究

IF 11.1 1区管理学

Technovation Pub Date : 2025-06-17 DOI: 10.1016/j.technovation.2025.103294

Yong Xu , Junzhe Ji , Yue Qiao , Jilei Huang

{"title":"How and when does digital transformation promote technological innovation performance? A study of Chinese high-tech firms","authors":"Yong Xu , Junzhe Ji , Yue Qiao , Jilei Huang","doi":"10.1016/j.technovation.2025.103294","DOIUrl":"10.1016/j.technovation.2025.103294","url":null,"abstract":"<div><div>Digital transformation and technological innovations are crucial responses of firms to external competitive dynamics; however, the complex relationship between them remains underexplored and contentious. Drawing on the dynamic capability view, we postulate that digital transformation influences technological innovations by alleviating internal information asymmetry and altering organizational resource distribution, thereby addressing routine and resource rigidities in the transformation process. To further explore the potential crowding-out effect of digital transformation on technological innovation, we designed a set of heterogeneity analyses based on contextual conditions surrounding resources accessible to firms. We examined these relationships using double fixed-effects and mediation models, based on a comprehensive panel dataset of 19 high-tech industries in China, spanning the years 2010–2021. Our results indicate that digital transformation promotes the quantity, quality, and efficiency of technological innovations, with a comparatively greater influence on the former two. These effects are mediated by internal information asymmetry and R&D intensity. Furthermore, the positive and significant effect of digital transformation is evident among firms located in the Eastern region of China and those that are profitable, but becomes negligible among loss-making firms. We conducted a series of robustness checks to validate the results and discussed their theoretical and practical implications.</div></div>","PeriodicalId":49444,"journal":{"name":"Technovation","volume":"146 ","pages":"Article 103294"},"PeriodicalIF":11.1,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144298287","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}

引用次数: 0

AI narratives model: Social perception of artificial intelligence 人工智能叙事模型：人工智能的社会感知

IF 11.1 1区管理学

Technovation Pub Date : 2025-06-17 DOI: 10.1016/j.technovation.2025.103266

Elena Denia

{"title":"AI narratives model: Social perception of artificial intelligence","authors":"Elena Denia","doi":"10.1016/j.technovation.2025.103266","DOIUrl":"10.1016/j.technovation.2025.103266","url":null,"abstract":"<div><div>Narratives surrounding Artificial Intelligence (AI) shape its societal reception, technological development, and regulatory framing. This article proposes a theoretical model to interpret these narratives, especially in the context of growing public engagement with generative AI technologies. The model is structured along three key coordinates: <em>apocalypse</em>, <em>assistance</em> and <em>transcendence</em>. Transitions between them are understood through two dominant narrative frames: the <em>Pandora's Box</em> frame (associated with loss of control), and the <em>Social Progress</em> frame (associated with the improvement of human life), each tending toward dystopian and utopian extremes, respectively. Based on this model, two questions are addressed: What types of AI stories predominate in popular culture? And do audiences actually align with them? To answer these, two empirical analyses are conducted. First, a review of the 300 highest-grossing science fiction films in North America reveals a rich variety of narratives across the entire spectrum, rather than clustering around opposing extremes. Second, focus group discussions with categorized audiences of varying levels of familiarity with AI technology show that they align progressively along the narrative spectrum: the <em>general public</em> tends toward apocalyptic framings, the <em>interested public</em> (in science and technology) focuses on assistance narratives, and the <em>engaged public</em> embraces improvement scenarios. This sequential distribution suggests a strong correlation between AI proximity and narrative positioning, with greater engagement associated with more positive —yet nuanced— views of AI. The model opens multiple avenues for future research, including the use of wider data sources, cross-cultural comparisons, longitudinal studies, tracking of narrative shifts, and focused analyses of more complex representations.</div></div>","PeriodicalId":49444,"journal":{"name":"Technovation","volume":"146 ","pages":"Article 103266"},"PeriodicalIF":11.1,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144298285","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}

引用次数: 0

Conceptualizing the data-driven mindset: An application of the mindset theory of action phases 概念化数据驱动的心态：行动阶段心态理论的应用

IF 11.1 1区管理学

Technovation Pub Date : 2025-06-16 DOI: 10.1016/j.technovation.2025.103293

Minh-Tay Huynh , Valerio Veglio , Marjaana Gunkel

{"title":"Conceptualizing the data-driven mindset: An application of the mindset theory of action phases","authors":"Minh-Tay Huynh , Valerio Veglio , Marjaana Gunkel","doi":"10.1016/j.technovation.2025.103293","DOIUrl":"10.1016/j.technovation.2025.103293","url":null,"abstract":"<div><div>Although employees' Data-Driven Mindset (DDM) plays a key role in developing a data-driven culture and supporting data-driven transformation, research on this concept is still limited. Drawing on the mindset theory of action phases (MTAP), we address this gap by applying the expectancy-value theory to conceptualize DDM, comprising three core components: self-efficacy, values, and costs. These elements influence individuals' behavioral intention and responses. Furthermore, we establish the relationship between personal innovativeness, DDM factors, and intention. Empirical analysis (<em>N</em> = 251) reveals that innovativeness, although linked to the DDM composite, does not affect intention and, therefore, it is not a DDM constituent. Self-efficacy and values positively influence intention, while perceived costs negatively impact it, underscoring their role as DDM factors. This study pioneers the conceptualization of DDM through the proactive lens of MTAP, uncovering the dynamic cognitive orientations driving individuals' data-driven behaviors. We emphasize the importance of fostering a positive DDM to shape individuals' engagement in data-driven transformation by enhancing their self-efficacy and values while reducing perceived costs.</div></div>","PeriodicalId":49444,"journal":{"name":"Technovation","volume":"146 ","pages":"Article 103293"},"PeriodicalIF":11.1,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144298286","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}

引用次数: 0

What “V” of the big data support firms’ radical and incremental innovation? 大数据的哪些“V”支持企业的激进创新和渐进式创新？

IF 11.1 1区管理学

Technovation Pub Date : 2025-06-13 DOI: 10.1016/j.technovation.2025.103295

Giulio Ferrigno, Saverio Barabuffi, Enrico Marcazzan, Andrea Piccaluga

{"title":"What “V” of the big data support firms’ radical and incremental innovation?","authors":"Giulio Ferrigno, Saverio Barabuffi, Enrico Marcazzan, Andrea Piccaluga","doi":"10.1016/j.technovation.2025.103295","DOIUrl":"10.1016/j.technovation.2025.103295","url":null,"abstract":"<div><div>Despite the considerable attention from both academics and practitioners to the effects of big data on firms’ innovation performance, a noticeable research gap remains in understanding how big data influences different types of innovation—namely, radical and incremental innovation. Many studies recognize that big data can be a valuable source of innovation, as it enables firms to gather and incorporate insights from customers, partners, suppliers, and other stakeholders. However, prior research has rarely investigated this relationship through a granular lens, failing to distinguish the specific effects of big data on radical and incremental innovation.</div><div>Focusing on firms’ intent of introducing radical and incremental innovation using big data, we employ the Knowledge Based View and the four well-known dimensions of big data (i.e., volume, velocity, variety, and veracity) to explore if and when big data is a source of knowledge for radical and incremental innovation. Performing an OLS regression analysis on a sample of 155 Italian firms, we find that both big data variety and veracity positively affect firms’ radical and incremental innovation. These findings provide insights about the conditions under which big data can improve firms’ innovation processes, contributing to a more comprehensive theoretical understanding of the opportunities big data bring in the context of firms’ product, service and process innovation. Moreover, our findings offer valuable guidance to managers navigating the complexities of leveraging big data for new product development.</div></div>","PeriodicalId":49444,"journal":{"name":"Technovation","volume":"146 ","pages":"Article 103295"},"PeriodicalIF":11.1,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144279754","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}

引用次数: 0

Global value chains and the innovativeness of firms in Africa 全球价值链与非洲企业的创新能力

IF 11.1 1区管理学

Technovation Pub Date : 2025-06-13 DOI: 10.1016/j.technovation.2025.103276

Gideon Ndubuisi , Emmanuel B. Mensah , Elvis K. Avenyo , Daniel Sakyi

{"title":"Global value chains and the innovativeness of firms in Africa","authors":"Gideon Ndubuisi , Emmanuel B. Mensah , Elvis K. Avenyo , Daniel Sakyi","doi":"10.1016/j.technovation.2025.103276","DOIUrl":"10.1016/j.technovation.2025.103276","url":null,"abstract":"<div><div>Firm-level innovation in developing countries is mostly incremental and depends on non-R&D activities. Integration into global production networks is one such activity that could help firms in developing countries innovate, particularly since new technologies and foreign knowledge diffuse through inter-firm linkages. Accordingly, this paper examines the relationship between Global Value Chain (GVC) participation and firm-level innovation in Africa, using data from the World Bank's Enterprise Survey (WBES). Employing different estimation strategies that enable us to address various empirical challenges, we find strong evidence suggesting that African GVC firms are highly innovative. They are not just more likely to introduce new products and processes but also more likely to jointly introduce both types of innovation as well as radical innovations. In an extended analysis, we found that integrating small and medium enterprises and younger firms into GVC enables them to overcome resource constraints, resulting in higher innovativeness. Finally, we document that the innovation gains from GVC trickle down to non-GVC firms in the same industry and region, implying that firms engaged in GVC activities generate positive spillovers to other firms in the economy. A proposed framework rationalizes our findings. The framework sheds light on the mechanisms that make firm-level innovation possible across African firms in an era where GVC is an important conduit for inter-firm learning, knowledge exchange, and technology transfer.</div></div>","PeriodicalId":49444,"journal":{"name":"Technovation","volume":"146 ","pages":"Article 103276"},"PeriodicalIF":11.1,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144272206","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}

引用次数: 0

Forecasting technology convergence with the spatiotemporal link prediction model 预测技术与时空联系预测模型的融合

IF 11.1 1区管理学

Technovation Pub Date : 2025-06-12 DOI: 10.1016/j.technovation.2025.103289

Jianyu Zhao , Xinjie Su , Xixi Li , Xi Xi , Xinlin Yao

{"title":"Forecasting technology convergence with the spatiotemporal link prediction model","authors":"Jianyu Zhao , Xinjie Su , Xixi Li , Xi Xi , Xinlin Yao","doi":"10.1016/j.technovation.2025.103289","DOIUrl":"10.1016/j.technovation.2025.103289","url":null,"abstract":"<div><div>Technology convergence represents an innovative process wherein two or more existing technologies amalgamate to form hybrid ones, thereby altering the competitive advantage of organizations and restructuring the competition rules and market networks. Consequently, both researchers and managers are actively engaged in comprehending and forecasting the trend of technology convergence to effectively adapt to and embrace environmental uncertainties. However, existing research on technology convergence primarily focuses on spatially single-dimensional predictions with a relatively short-term horizon of 1–2 years. Additionally, these models often fall short in addressing the issue of imbalanced data within technology convergence networks. In response, we propose the Spatiotemporal Feature Concatenation with Graph Gated Network (STFCGG), a deep learning-based spatiotemporal link prediction model. Our link prediction model achieves simultaneous spatiotemporal predictions, provides medium-to long-term forecasts spanning 3–4 years, and addresses the challenge of imbalanced data from an algorithmic perspective. Experimental results with patent data from the Virtual Reality (VR) and Augment Reality (AR) fields have demonstrated our model's superiority and robustness in handling data imbalance issues, thereby offering valuable insights for future technology convergence directions. In addition to the methodology contribution, our novel link prediction model also provides executives with a valuable tool to develop technological management strategies.</div></div>","PeriodicalId":49444,"journal":{"name":"Technovation","volume":"146 ","pages":"Article 103289"},"PeriodicalIF":11.1,"publicationDate":"2025-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144264145","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}

引用次数: 0

Bridging AI innovation and sustainable Development: The effect of AI technological progress on SDG investment performance 连接人工智能创新和可持续发展：人工智能技术进步对可持续发展目标投资绩效的影响

IF 11.1 1区管理学

Technovation Pub Date : 2025-06-11 DOI: 10.1016/j.technovation.2025.103279

Federico Platania , Celina Toscano Hernandez , Imane El Ouadghiri , Jonathan Peillex

{"title":"Bridging AI innovation and sustainable Development: The effect of AI technological progress on SDG investment performance","authors":"Federico Platania , Celina Toscano Hernandez , Imane El Ouadghiri , Jonathan Peillex","doi":"10.1016/j.technovation.2025.103279","DOIUrl":"10.1016/j.technovation.2025.103279","url":null,"abstract":"<div><div>In the age of AI-driven innovation, Artificial Intelligence (AI) has become a transformative force in financial markets, reshaping investment strategies and sustainability-driven asset allocation. This study examines the impact of AI-driven innovation on the financial performance of sustainability-focused investments by analyzing the relationship between AI patent activity and the market returns of exchange-traded funds (ETFs) aligned with the United Nations Sustainable Development Goals (SDGs). Employing a state-space framework and a Kalman Filter model, we capture the dynamic influence of AI advancements on SDG-aligned ETFs, revealing that technological progress significantly enhances excess returns, particularly in the clean energy and water resource sectors. However, our analysis also uncovers sectoral variations in AI's financial impact, indicating that the benefits of AI innovation are unevenly distributed across industries. These findings bridge the gap between sustainable finance and technological innovation, demonstrating that AI serves as both a financial accelerator and a sustainability enabler. By integrating AI-driven innovation into asset pricing models, this study provides actionable insights for investors, policymakers, and corporate strategists, emphasizing the need to incorporate AI-based metrics into investment decision-making, risk assessment frameworks, and regulatory policies to foster sustainable economic growth.</div></div>","PeriodicalId":49444,"journal":{"name":"Technovation","volume":"146 ","pages":"Article 103279"},"PeriodicalIF":11.1,"publicationDate":"2025-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144253491","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}

引用次数: 0

How does work curiosity affect employees' creativity and innovation: Do task characteristics matter? 工作好奇心如何影响员工的创造力和创新能力：任务特征重要吗？

IF 11.1 1区管理学

Technovation Pub Date : 2025-06-11 DOI: 10.1016/j.technovation.2025.103288

Huei-Ying Chen , Yu-Yu Chang , Yun-Ju Yang

{"title":"How does work curiosity affect employees' creativity and innovation: Do task characteristics matter?","authors":"Huei-Ying Chen , Yu-Yu Chang , Yun-Ju Yang","doi":"10.1016/j.technovation.2025.103288","DOIUrl":"10.1016/j.technovation.2025.103288","url":null,"abstract":"<div><div>This study examines how two distinct types of work curiosity, interest induction (I-type curiosity) and deprivation elimination (D-type curiosity), influence employees' creativity and innovation performance in Taiwan's high-tech industry. Drawing on Self-Determination Theory and Person-Environment Fit Theory, we propose a moderated mediation model in which I-type and D-type curiosity enhance incremental and radical creativity. These forms of creativity, in turn, mediate the relationship between work curiosity and innovation performance. Additionally, we investigate how task variety and task specialization moderate the effects of curiosity on creativity. Survey data from 402 employees across high-tech firms reveal that both types of curiosity positively influence creativity, contributing to innovation performance. Notably, task variety amplifies the effects of I-type curiosity on both incremental and radical creativity, whereas task specialization strengthens the impact of D-type curiosity on radical creativity. These findings underscore the importance of aligning task characteristics with specific types of curiosity to optimize creativity and innovation. This study advances theoretical understanding of how workplace curiosity drives innovation outcomes and offers practical insights for human resource management and task design in innovation-driven contexts.</div></div>","PeriodicalId":49444,"journal":{"name":"Technovation","volume":"146 ","pages":"Article 103288"},"PeriodicalIF":11.1,"publicationDate":"2025-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144263953","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}

引用次数: 0

Examining the interplay of industry 4.0, lean, agile, and circular manufacturing practices on sustainability performance 考察工业4.0、精益、敏捷和循环制造实践对可持续性绩效的相互作用

IF 11.1 1区管理学

Technovation Pub Date : 2025-06-09 DOI: 10.1016/j.technovation.2025.103290

Moustafa Elnadi , Mohamed Hani Gheith , Ciro Troise , Stefano Bresciani , Yasser Omar Abdallah

{"title":"Examining the interplay of industry 4.0, lean, agile, and circular manufacturing practices on sustainability performance","authors":"Moustafa Elnadi , Mohamed Hani Gheith , Ciro Troise , Stefano Bresciani , Yasser Omar Abdallah","doi":"10.1016/j.technovation.2025.103290","DOIUrl":"10.1016/j.technovation.2025.103290","url":null,"abstract":"<div><div>This study presents a novel integrative framework to examine how Industry 4.0 (I4.0) technologies interact with lean manufacturing (LM), agile manufacturing (AM), and circular manufacturing (CM) to enhance sustainability performance (SP) in manufacturing firms. Unlike previous research that often investigates these constructs separately, this study uniquely explores their combined and mediating roles within a unified model. Based on data collected from 170 respondents in Saudi Arabia, the study employs partial least squares structural equation modeling (PLS-SEM) to assess both direct and indirect relationships. The results reveal that I4.0 significantly facilitates the adoption of LM, AM, and CM practices, all of which contribute positively to SP. Furthermore, LM plays a foundational role by positively influencing both AM and CM, and the three paradigms mediate the relationship between I4.0 and SP. By situating the research within the context of Saudi Arabia's industrial transformation, this study advances theoretical understanding of how digital and operational paradigms interact to promote sustainability. It also offers practical recommendations for aligning digital transformation initiatives with sustainable manufacturing strategies in emerging economies.</div></div>","PeriodicalId":49444,"journal":{"name":"Technovation","volume":"146 ","pages":"Article 103290"},"PeriodicalIF":11.1,"publicationDate":"2025-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144241412","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}

引用次数: 0