Controlling the Urban Fabric: The Complex Game of Distance and Proximity in European Upper‐Middle‐Class Residential Strategies

This article presents an open discussion of the processes of urban secession and gentrification in contemporary European cities, arguing that intergroup social dynamics in urban spaces are generally more complex than either extreme mutual avoidance or the colonization of neighbourhoods by the wealthiest groups. We analyse the residential strategies of urban upper‐middle class managers in various European metropolitan areas through in‐depth semi‐structured interviews to argue that these groups develop complex strategies of proximity and distance in relation to other social groups. The development of these ‘partial exit’ strategies takes place through specific combinations of practices that allow groups to select the dimensions they are willing to share with other social groups, and those in which they prefer a more segregated social environment for themselves and their families. The responses of our interviewees were consistently more nuanced and complex than suggested by a simplistic theory about their drive to withdraw from society, forcing us to develop more sophisticated conceptual frameworks to account for the growing prevalence of multi‐layered identities and spheres of reference and solidarity, specific combinations of elective segregation and local involvement, and more active patterns of mobility combined with local embeddedness.     

Using technology to improve the management of development impacts on biodiversity

The mitigation hierarchy (MH) is a prominent tool to help businesses achieve no net loss or net gain outcomes for biodiversity. Technological innovations offer benefits for business biodiversity management, yet the range and continued evolution of technologies creates a complex landscape that can be difficult to navigate. Using literature review, online surveys, and semi-structured interviews, we assess technologies that can improve application of the MH. We identify six categories (mobile survey, fixed survey, remote sensing, blockchain, data analysis, and enabling technologies) with high feasibility and/or relevance to (i) aid direct implementation of mitigation measures and (ii) enhance biodiversity surveys and monitoring, which feed into the design of interventions including avoidance and minimization measures. At the interface between development and biodiversity impacts, opportunities lie in businesses investing in technologies, capitalizing on synergies between technology groups, collaborating with conservation organizations to enhance institutional capacity, and developing practical solutions suited for widespread use.     

The role of the entrepreneurial encounter in the emergence of opportunities: Vallée’s Dallas Buyers Club

ABSTRACT

This paper aims to explore the conceptual potential of the Deleuzian notion of the encounter in order to better understand the genealogy of opportunities. We adopt a processual perspective of opportunities. In order to translate this notion to the domain of entrepreneurship, we analysed and interpreted Jean-Marc Vallée’s Dallas Buyers Club. This film follows the creation of the first club in the United States that illegally allowed HIV-positive people to supply themselves with foreign antiretroviral drugs from Mexico or Japan. The article highlights encounters in this process that disturb the entrepreneur’s belief systems and allow him or her to be open to potential opportunity. It finally explores how the encounter may improve our understanding of the political becoming of opportunities within the entrepreneurial process.     

INCENTIVES AND SOCIAL NORMS: A MOTIVATION‐BASED ECONOMIC ANALYSIS OF SOCIAL NORMS

Abstract It is now commonplace to regard social norms as a subject of growing interest in the economic literature (e.g. game theoretical approaches based on ‘other‐regarding’ individual preferences, the analysis of the impact of rewards or punishment on individuals’ behaviour through experimental economics as well as field experiments, the revival of the institutionalist tradition spurred on by the influential work of Douglas North and followed by many others and the growing influence of neuroeconomics). In this paper, we focus on the relationship between incentives and social norms and survey the literature that could constitute the foundations of a motivation‐based economic analysis of social norms. Our main findings are that (1) the interaction between incentives and social norms is far from obvious since taking social norms into account involves the introduction of supplementary motives, in addition to self‐interest, into the economic analytical framework; (2) the analysis of the interaction between incentives and social norms resists an approach exclusively in terms of crowding‐in and ‐out effects because it is sensitive to whether it concerns behaviours driven by honour or by social stigma; (3) as a result, it is difficult to precisely evaluate the policy implication of the interactions between incentives and social norms.     

Firms’ human capital, R&D and innovation: a study on French firms

This article investigates the effects of human capital and technological capital on innovation. While the role of technological capital as measured by research and development (R&D) expenditure has been intensively investigated, few studies have been made on the effect of employee training on innovation. This article explores the relationship between innovation and firm employee training. Our methodological approach contributes to the literature in three ways. We propose various indicators of firm employee training. We build a count data panel with a long time-data series to deal with the issue of firms?? heterogeneity. We propose a dynamic analysis. Using dynamic count data models on French industrial firms over the period 1986?C1992, we find positive and significant effects of R&D intensity and training on patenting activity. Whatever the indicators of training our results show that the firm employee training has a positive impact on technological innovation.     

THEORY AND EVIDENCE IN PSYCHOLOGY AND ECONOMICS ABOUT MOTIVATION CROWDING OUT: A POSSIBLE CONVERGENCE?

The empirical relevance of motivation crowding out is a controversial issue in economics and psychology. As already pointed out by Frey and Jegen ( 2001 ), this is partly due to the historical development of two distinct and parallel strands of literature that stem from different theoretical traditions, have radically different tenets and therefore, are difficult to reconcile. In this survey, we go back to the details of the debates that took place independently among psychologists and economists, and sketch an integrative interdisciplinary approach likely to favor a more fruitful collaboration between economics and psychology. From this perspective, experimental economics (both field and laboratory) is viewed as a major research field shedding new light on the conditions of relevance of motivation crowding out.     

论中国经济的繁荣与萧条

本文研究对象是新中国历次繁荣与萧条的运行过程,具体内容是繁荣的形成,繁荣走向萧条,以及萧条如何走向繁荣。     

Does Team-Based Compensation Give Rise to Problems When Agents Vary in Their Ability?

This paper reports the results of an experiment on how team heterogeneity in terms of productivity influences both the revenue sharing proposed by the principal to the team and the employees' performance. Experimental evidence shows that when the team is heterogeneous, the principal does not try to motivate the agents through her sharing offer. Regardless of the level of team-based compensation, a large amount of free riding occurs since each agent is mainly influenced by his teammate's behavior. In contrast, when the team is homogeneous, agents are better able to cooperate, reciprocating the principal's offer.     

Power Relations and Social Mix in Metropolitan Neighbourhoods in North America and Europe: Moving Beyond Gentrification?

Research on spatial segregation has suggested that social mix may be a temporary phase in class displacement, where relations between different groups are at best divided or ‘tectonic’, for instance in England. Political and policy discourses, by contrast, tend to uncritically valorize social mix as a means to breaking up concentrations of poverty and providing neighbourhoods with a middle‐class voice. In the literature, little attention has been paid to power dynamics in socially mixed neighbourhoods and the implications this may have for understanding theory and policy. The five articles that make up this symposium address the ways in which social and ethnic groups interact in major cities in Europe and North America and, as the title suggests, this involves taking into account power relations, domination and negotiation between the different groups. There is a need to connect the experience of the deployment of power within neighbourhoods (and between them) with the discussions of power mechanisms at work in wider urban processes.     

Advances in forecasting with neural networks? Empirical evidence from the NN3 competition on time series prediction

This paper reports the results of the NN3 competition, which is a replication of the M3 competition with an extension of the competition towards neural network (NN) and computational intelligence (CI) methods, in order to assess what progress has been made in the 10 years since the M3 competition. Two masked subsets of the M3 monthly industry data, containing 111 and 11 empirical time series respectively, were chosen, controlling for multiple data conditions of time series length (short/long), data patterns (seasonal/non-seasonal) and forecasting horizons (short/medium/long). The relative forecasting accuracy was assessed using the metrics from the M3, together with later extensions of scaled measures, and non-parametric statistical tests. The NN3 competition attracted 59 submissions from NN, CI and statistics, making it the largest CI competition on time series data. Its main findings include: (a) only one NN outperformed the damped trend using the sMAPE, but more contenders outperformed the AutomatANN of the M3; (b) ensembles of CI approaches performed very well, better than combinations of statistical methods; (c) a novel, complex statistical method outperformed all statistical and CI benchmarks; and (d) for the most difficult subset of short and seasonal series, a methodology employing echo state neural networks outperformed all others. The NN3 results highlight the ability of NN to handle complex data, including short and seasonal time series, beyond prior expectations, and thus identify multiple avenues for future research.