R&D cooperation in collaborative consumption of research equipment: An ERGM approach

High-tech research infrastructure is essential for state-of-the-art research, but requires many resources. Relatively weak actors, such as SMEs, cannot secure enough of those. Applying the concept of collaborative consumption via digital platforms, we examine the cooperative behavior of Korean SMEs that share research equipment to overcome their lack of resources. Also, we analyze configurations of a collaborative consumption network using the Exponential Random Graph Model. Network structural factor analysis shows sufficient effects of network positive feedback through cooperative consumption with a variety of popular providers and attributes analysis shows that SMEs frequently engage in collaborative consumption with their counterparts in the same region. This new cooperative model can achieve a virtuous cycle of policies, as it increases the efficiency of research infrastructure, preventing the unnecessary building of new research equipment and enabling relocation of underutilized infrastructure and online reservation of equipment.     

Financing Innovation Development in the Context of Foreign Experience and Domestic Practice

The importance of innovation development is determined by the strategic role that true innovations play in the development of the state and the formation of a healthy, competitive economy. The organization of massive industrial production—which applies advanced technological achievements and science-intensive knowledge to form an infrastructure for innovation—should be a key component of the government’s strategic policy to develop the national economy. In Russia, the infrastructure for innovation is less developed than other industrialized countries. This article considers the consequences of this underdevelopment, and proposes several ways of financing basic and applied research on the basis of foreign precedent and domestic practice.     

An Integrated Risk Assessment Model of Township‐Scaled Land Subsidence Based on an Evidential Reasoning Algorithm and Fuzzy Set Theory

Land subsidence risk assessment (LSRA) is a multi‐attribute decision analysis (MADA) problem and is often characterized by both quantitative and qualitative attributes with various types of uncertainty. Therefore, the problem needs to be modeled and analyzed using methods that can handle uncertainty. In this article, we propose an integrated assessment model based on the evidential reasoning (ER) algorithm and fuzzy set theory. The assessment model is structured as a hierarchical framework that regards land subsidence risk as a composite of two key factors: hazard and vulnerability. These factors can be described by a set of basic indicators defined by assessment grades with attributes for transforming both numerical data and subjective judgments into a belief structure. The factor‐level attributes of hazard and vulnerability are combined using the ER algorithm, which is based on the information from a belief structure calculated by the Dempster‐Shafer (D‐S) theory, and a distributed fuzzy belief structure calculated by fuzzy set theory. The results from the combined algorithms yield distributed assessment grade matrices. The application of the model to the Xixi‐Chengnan area, China, illustrates its usefulness and validity for LSRA. The model utilizes a combination of all types of evidence, including all assessment information—quantitative or qualitative, complete or incomplete, and precise or imprecise—to provide assessment grades that define risk assessment on the basis of hazard and vulnerability. The results will enable risk managers to apply different risk prevention measures and mitigation planning based on the calculated risk states.     

A modified LGB method for detecting significant effects based on a half-normal probability plot

In analyzing data from unreplicated factorial designs, the half-normal probability plot is commonly used to screen for the ‘vital few’ effects. Recently, many formal methods have been proposed to overcome the subjectivity of this plot. Lawson (1998) (hereafter denoted as LGB) suggested a hybrid method based on the half-normal probability plot, which is a blend of Lenth (1989) and Loh (1992) method. The method consists of fitting a simple least squares line to the inliers, which are determined by the Lenth method. The effects exceeding the prediction limits based on the fitted line are candidates for the vital few effects. To improve the accuracy of partitioning the effects into inliers and outliers, we propose a modified LGB method (hereafter denoted as the Mod_LGB method), in which more outliers can be classified by using both the Carling’s modification of the box plot (Carling, 2000) and Lenth method. If no outlier exists or there is a wide range in the inliers as determined by the Lenth method, more outliers can be found by the Carling method. A simulation study is conducted in unreplicated $2^4$ designs with the number of active effects ranging from 1 to 6 to compare the efficiency of the Lenth method, original LGB methods, and the proposed modified version of the LGB method.     

The arithmetic of outcome editing in financial and social domains

Outcome editing refers to a set of mental rules that people apply when deciding whether to evaluate multiple outcomes jointly or separately, which subsequently affects choice. In a large-scale online survey (n = 2062) we investigate whether individuals use the same outcome editing rules for financial outcomes (e.g., a lottery win) and social outcomes (e.g., a party with friends). We also test the role of numeric ability in explaining outcome editing. Our results show that people’s preferences for combining or separating events depend on whether those events are in the financial or the social domain. Specifically, individuals were more likely to segregate social outcomes than monetary outcomes, except for when all outcomes were negative. Moreover, numeric ability was associated with preferences for outcome editing in the financial domain but not in the social domain. Our findings extend the understanding of the arithmetic operations underlying outcome editing and suggest that people rely more on calculations when making choices involving multiple financial outcomes and more on feelings when making choices involving social outcomes.     

Majority size and conformity behavior in charitable giving: Field evidence from a donation-based crowdfunding platform in Japan

A charitable donor typically imitates the majority contribution of other donors. This study examines the relationships between majority size and this so-called donor’s conformity behavior, by empirically investigating the impacts of multiple earlier donations on the donation of a subsequent donor to JapanGiving, a donation-based crowdfunding platform in Japan. This analysis is possible because the platform’s webpage displays the previous donation amounts in chronological order, thus allowing us to examine the modal amount of more recent donations. By using data on 9989 actual donations, our dynamic panel analysis suggests that when the number of most recent continuous modal donations increases, the likelihood that a subsequent donor matches the modal amount increases. This result supports the notion that a donor’s conformity behavior is more likely to occur when a greater proportion of other donors give a similar amount. Furthermore, the effects of continuous modal donations are strongly observed for low monetary ranges. We interpret that initiating further cooperation among a large number of less cooperative other donors would become harder, or individuals would obtain an excuse for less cooperation due to the others’ behaviors. Finally, we discuss how our findings connect economic studies of charity and social psychology studies of conformity and could help improve the effectiveness of fundraising by charities.     

Do changes in patent policy influence firms’ technology strategy? Evidence from manufacturing in India

India made patent policy changes to comply with TRIPs agreement that increased the rights of patent owners. Considering that such policy changes influence both in-house research and development investments and technology licensing from external sources, the firms have to accordingly devise their technology strategy. This study employs a simple and fixed effects multinomial logit regression models to study the impact of policy changes on the technology strategy of 402 firms operating in Indian manufacturing sector from 1999 to 2014. The results show that changes in patent policy have a significant impact on technology strategy of firms.     

Business reform outcomes: Why so different?

Post-crisis policy making increasingly focuses on doing business reforms. We argue that the effects of those reforms will be different across countries. To understand the reasons for the reform outcome divergence, we advance a novel firm-size distribution (FSDs) argument. At the center of the argument is the fact that FSDs are different across countries and stable over time. Then, if a given doing business reform induces firms of different size to grow differently, this will produce a variety of reform outcomes across countries. To advance the argument, we set up a tractable general equilibrium (GE) model and study how firms of different size grow after a doing business reform. The model predicts that larger firms will grow faster than smaller firms after the reform. The model predictions are tested on the Enterprise Surveys (ES) data, merged with the Doing Business indicators. We confirm that firms of different size grow differently after a Doing Business reform. Thus, based on the notable differences of firm size distributions across countries, identical reforms to start, operate and close a business will produce a variety of reform outcomes across countries.     

研发过程中知识产权风险的控制

企业知识产权包括商标、专利和著作权等，它是企业重要的无形资产。目前，国内大多数企业还不够重视企业的知识产权保护，尤其是专利保护。在研发过程中的专利申请及保护不及时、不到位，导致企业从项目研发到市场占有的整个过程蒙受巨大风险。从知识产权保护角度，探讨了企业研发过程中有关风险的防范措施。