Learning dynamics in research alliances: A panel data analysis

The aim of this paper is to empirically test the determinants of Research Joint Ventures’ (RJVs) group dynamics. We develop a model based on learning and transaction cost theories, which represent the benefits and costs of RJV participation, respectively. According to our framework, firms at each period in time weigh the benefits against the costs of being an RJV member. RJV dynamics can then be interpreted as a consequence of this evolving trade-off over time. We look at entry, turbulence and exit in RJVs that have been set up under the US National Cooperative Research Act, which allows for certain antitrust exemptions in order to stimulate firms to co-operate in R&D. Accounting for unobserved project characteristics and controlling for inter-RJV interactions and industry effects, the Tobit panel regressions show the importance of group and time features for an RJVs evolution. We further identify an average RJVs long-term equilibrium size and assess its determining factors. Ours is a first attempt to produce robust stylized facts about co-operational short- and long-term dynamics, a neglected dimension in research co-operations, but an important element in understanding how collaborative learning works.     

Estimation of missing values in astronomical survey data: An improved local approach using cluster directed neighbor selection

The work presented in this paper aims to develop new imputation methods to better handle missing values encountered in astronomical data analysis, especially the classification of transient events in a sky survey from the Gravitational wave Optical Transient Observatory (GOTO) project. In particular, the framework of cluster directed selection of neighbors that has proven effective for benchmark local imputation techniques of KNNimpute and LLSimpute are extended to new multi-stage models. The proposed models, namely Iterative-CKNN and Iterative-CLLS, are novel with an original application to analyze sky survey data. They bring out advantages from both local approaches, where estimates are summarized from neighbors in the same data cluster, within the iterative process to refine previous guesses. Based on experiments with simulated datasets corresponding to different survey sizes and missing rations between 1 to 20%, they usually outperform baseline models and Bayesian Principal Component Analysis (BPCA), which is the well-known global technique. For instance, at 10% missing rate, Iterative-CLLS appears to be the most accurate with NRMSE score of 0.190, while BPCA and the best among its baseline models reaches 0.351 and 0.249, respectively. For their practical implications, these methods have proven to be effective for classifying transients, using common algorithms like KNN, Naive Bayes and Random Forest.     

大数据时代科研管理信息化对策研究

科研管理信息化是提升科研管理水平的重要途径之一。本文就目前科研管理信息存在的问题。通过探讨适于研究院所发展的科研管理模式、科研管理信息系统的功能以及科研管理信息系统在科研管理创新中的作用及效果,提出大数据时代研究院所科研管理信息化建设创新的几点思考。     

中国虚拟团队研究元分析:2000—2008

对国内2000—2008年发表在代表性学术期刊上的虚拟团队研究论文进行系统全面的检索、分类和分析。从参考学科、研究题目、研究方法和应用领域4个层面分析了国内虚拟团队研究的现状,并对国内外研究形势进行了比较。研究发现中国虚拟团队的研究:以管理学、社会学以及心理学作为主要理论基础;研究题目总体集中在虚拟团队的概念、管理建议及其应用于其他领域的介绍等,基于I-P-O模型的研究近几年呈上升趋势,但直至目前研究的涵盖范围仍然不够全面;研究方法以非实证方法为主,实证方法应用很少;应用领域主要集中在高新技术产品研发组织,另有一小部分研究是关于虚拟企业、虚拟软件开发团队等。与西方相比,中国的虚拟团队研究在研究重点、研究方法和应用领域上具有自己的特点,也有需要进一步完善的地方。     

Post-GDPR survey of data protection officers in research and non-research institutions in Croatia: a cross-sectional study

IntroductionGeneral Data Protection Regulation (GDPR) focuses on important elements of data ethics, including protecting people’s privacy, accountability and transparency. According to the GDPR, certain public institutions are obliged to appoint a Data Protection Officer (DPO). However, there is little publicly available data from national EU surveys on DPOs. This study aimed to examine the scope of work, type of work, and education of DPOs in institutions in Croatia.Materials and methodsDuring 2020-2021, this cross-sectional study surveyed DPOs appointed in Croatia. The survey had 35 items. The questions referred to their appointment, work methods, number and type of cases handled by DPOs, the sources of information they use, their experience and education, level of work independence, contacts with ethics committees, problems experienced, knowledge, suggestions for improvement of their work, changes caused by the GDPR, and sociodemographic information.ResultsOut of 5671 invited DPOs, 732 (13%) participated in the study. The majority (91%) indicated that they could perform their job independently; they did not have prior experience in data protection before being appointed as DPOs (54%) and that they need additional education in data protection (82%).ConclusionsMost DPOs indicated that they had none or minimal prior experience in data protection when they were appointed as DPO, that they would benefit from further education on data protection, and exhibited insufficient knowledge on basic concepts of personal data protection. Requirements for DPO appointments should be clarified; mandatory education and certification of DPOs could be introduced and DPOs encouraged to engage in continuous education.     

Big data analytics in health sector: Theoretical framework,techniques and prospects

Clinicians, healthcare providers-suppliers, policy makers and patients are experiencing exciting opportunities in light of new information deriving from the analysis of big data sets, a capability that has emerged in the last decades. Due to the rapid increase of publications in the healthcare industry, we have conducted a structured review regarding healthcare big data analytics. With reference to the resource-based view theory we focus on how big data resources are utilised to create organization values/capabilities, and through content analysis of the selected publications we discuss: the classification of big data types related to healthcare, the associate analysis techniques, the created value for stakeholders, the platforms and tools for handling big health data and future aspects in the field. We present a number of pragmatic examples to show how the advances in healthcare were made possible. We believe that the findings of this review are stimulating and provide valuable information to practitioners, policy makers and researchers while presenting them with certain paths for future research.     

Studying the amateur artist: A perspective on disguising data collected in human subjects research on the Internet

In the mid-1990s, the Internet rapidly changedfrom a venue used by a small number ofscientists to a popular phenomena affecting allaspects of life in industrialized nations. Scholars from diverse disciplines have taken aninterest in trying to understand the Internetand Internet users. However, as a variety ofresearchers have noted, guidelines for ethicalresearch on human subjects written before theInternet's growth can be difficult to extend toresearch on Internet users.In this paper, I focus on one ethicalissue: whether and to what extent to disguisematerial collected online in publishedaccounts. While some people argue thatvulnerable human subjects must always be madeanonymous in publications for their ownprotection, others argue that Internet usersdeserve credit for their creative andintellectual work. Still others argue thatmuch material available online should betreated as ``published.' To attempt to resolvethese issues, I first review my own experiencesof disguising material in research accountsfrom 1992 to 2002. Some of the thorniestissues emerge at the boundaries betweenresearch disciplines. Furthermore, manyhumanities disciplines have not historicallyviewed what they do as human subjects research. Next, I explore what it means to do humansubjects research in the humanities. Inspiredby issues raised by colleagues in thehumanities, I argue that the traditional notionof a ``human subject' does not adequatelycharacterize Internet users. A useful alternatemental model is proposed: Internet users areamateur artists. The Internet can be seen as aplayground for amateur artists creatingsemi-published work. I argue that thisapproach helps make some ethical dilemmaseasier to reason about, because it highlightskey novel aspects of the situation,particularly with regard to disguisingmaterial. Finally, I conclude by proposing aset of practical guidelines regardingdisguising material gathered on the Internet inpublished accounts, on a continuum from nodisguise, light disguise, moderate disguise, toheavy disguise.     

DEA视窗分析的高校科研效率：2009-2015年间的A区数据

对高校科研效率的客观评价,是反映科研效率、提升科技创新力的重要举措。文章利用我国A区省份2009年-2015年科研投入与产出的平衡面板数据,比较了同一窗宽不同窗口以及不同窗宽对决策单元效率的影响,结果表明在不同的窗宽中,高校科研效率呈现出逐渐下降的趋势;在同一窗口下,各个省份的科研效率变化较大;东部地区的总体效率值低于中部地区。总之,近年来政府加大了高校科研活动的投入并没有得到相应程度的提高,我国高校的资源配置效率仍较低,科研活动效率有待提高。     

Research quality and efficiency: An analysis of assessments and management issues in Dutch economics and business research programs

Assessments of quality and productivity of academic research programs become more and more important in gaining financial support, in hiring and promoting research staff, and in building academic reputation. Most assessments are based on peer review or on bibliometric information. In this paper we analyze both bibliometric data and peer review assessments of 169 research groups in economics, econometrics and business administration. The evaluations are achieved in two independent rounds in 1995 and in 2001, permitting replication of our study.The purpose of this study is twofold. In the first part we want to see to what degree bibliometric information relates to peer review judgments. The results convey how evaluators weight different output categories in their final overall judgment of academic quality. The results also have practical meaning, since they indicate what the predictive ability of bibliometric data is for future peer review outcomes. In the second part of this study we aim at explaining differences in research output quality and productivity by organizational factors, like size of the research group, composition of staff, sources of research funding and academic discipline. In this part, a composite indicator is used to represent the review committees’ overall assessment. The bibliometric data most strongly related to the peer reviews’ overall assessment are used to construct data envelopment analyses’ efficiency scores as measure of research productivity.The main conclusions from our study are that the number of publications in international top journals is the best predictor of peer review assessment results. Changes in the classification of bibliometric information, as introduced in the second evaluation round, do not alter this conclusion. Size of the research group appears to be the only permanent characteristic associated with research quality and productivity. Size is positively related to research quality but negatively related to research productivity. Larger groups appear to have the potential to improve quality, but as groups become larger, they also experience problems in maintaining the research productivity of the research team's members. The remaining organizational characteristics appear to be temporarily related to research quality and productivity. In the first evaluation round, research productivity and quality are associated with the discipline variable: research programs in more quantitative areas and characterized by a higher level of paradigm development like econometrics and operations research achieved higher levels of research quality and productivity than programs in more diverse and less quantitative areas like business administration. This relation however is not permanent, since it becomes insignificant in the second evaluation round. Instead, funding relations become more apparent in the second review round. The relative amount of national funding in the research group's funding becomes positively related to academic quality, whereas the portion of income from committed research is negatively related to academic quality of the programs’ research output. This may have been caused by the increased importance of alternative sources of research funding in the period of the second review.     

From user-generated data to data-driven innovation: A research agenda to understand user privacy in digital markets

In recent years, strategies focused on data-driven innovation (DDI) have led to the emergence and development of new products and business models in the digital market. However, these advances have given rise to the development of sophisticated strategies for data management, predicting user behavior, or analyzing their actions. Accordingly, the large-scale analysis of user-generated data (UGD) has led to the emergence of user privacy concerns about how companies manage user data. Although there are some studies on data security, privacy protection, and data-driven strategies, a systematic review on the subject that would focus on both UGD and DDI as main concepts is lacking. Therefore, the present study aims to provide a comprehensive understanding of the main challenges related to user privacy that affect DDI. The methodology used in the present study unfolds in the following three phases; (i) a systematic literature review (SLR); (ii) in-depth interviews framed in the perspectives of UGD and DDI on user privacy concerns, and finally, (iii) topic-modeling using a Latent Dirichlet allocation (LDA) model to extract insights related to the object of study. Based on the results, we identify 14 topics related to the study of DDI and UGD strategies. In addition, 14 future research questions and 7 research propositions are presented that should be consider for the study of UGD, DDI and user privacy in digital markets. The paper concludes with an important discussion regarding the role of user privacy in DDI in digital markets.     

农业科研人员技术推广的意愿研究——基于四川省调查数据的实证分析

通过对四川省512位农业科研人员技术推广意愿的调查,比较了不同特征下农业科研人员的技术推广意愿,并分析了其推广意愿的影响因素。研究结果表明,农业科研人员的整体技术推广意愿较高,达到了76.95%,其推广意愿主要由年龄、性别、受教育水平、职称、科研年限、所在区域、科研项目类别、对单位推广管理的认知及对推广信息关注度等因素共同决定。     

科研不端行为查处程序的比较分析——基于美国、韩国及中国的典型案例

比较分析美国"E.T.波尔曼事件"、韩国"黄禹锡事件"及中国"陈进事件"等科研不端行为典型案件的查处程序表明,已构建健全科研不端行为防范体制和机制的美国,有着正确、及时、秘密的查处程序,并能发挥其应有的公平、公正与效率作用;急功近利而无相关法律规制的韩国,也能正确、及时和有效地查处黄禹锡事件,并积极建立相关防范体制;面对类似突发事件的中国,虽有立法不足、体制不全、程序公正性和效用性欠缺等问题,却也积极推动了相关制度建设。