Wind-farm layout optimisation using a hybrid Jensen–LES approach

Given a wind farm with known dimensions and number of wind turbines, we try to find the optimum positioning of wind turbines that maximises wind-farm energy production. In practice, given that optimisation has to be performed for many wind directions, and taking into account the yearly wind distribution, such an optimisation is computationally only feasible using fast engineering wake models such as the Jensen model. These models are known to have accuracy issues, in particular since their representation of wake interaction is very simple. In the present work, we propose an optimisation approach that is based on a hybrid combination of large-eddy simulation (LES) and the Jensen model; in this approach, optimisation is mainly performed using the Jensen model, and LES is used at a few points only during optimisation for online tuning of the wake-expansion coefficient in the Jensen model, as well as for validation of the results. An optimisation case study is considered, in which the placement of 30 turbines in a 4 km by 3 km rectangular domain is optimised in a neutral atmospheric boundary layer. Optimisation for both a single wind direction and multiple wind directions is discussed

Big Data in Family Firms: A Socioemotional Wealth Perspective

[eng] Since about 2010, big data analysis has drastically changed the landscape of information management by becoming a central topic in the academic literature of several fields. Despite the significant contribution of family firms to the economic fabric worldwide and their unique decision-making processes, there is a lack of research investigating big data in family-owned businesses. To address this gap, this article draws on the socioemotional wealth (SEW) perspective and its FIBER model to conceptually investigate its role in family firms' decision to implement big data. We introduce a set of propositions and a framework linking the FIBER dimensions to the likeliness of implementing big data in family firms. Our research thus contributes to a more fine-grained understanding of the decision-making process in family firms

Are family female directors catalysts of innovation in family small and medium enterprises?

Research Summary: While family small and medium enterprises (SMEs) increasingly involve women in their boards, the role of female directors as catalysts of innovation is yet to be fully understood. Drawing on upper echelons theory, we examine directors' gender in conjunction with family affiliation to investigate the influence of family female directors on family SMEs' innovation. Moreover, by analyzing the contingent role of socioemotional wealth preferences, we open the black box of noneconomic aspects shaping the cognition and behavior of boards. Our analysis of a unique survey-based sample of 287 Belgian family SMEs reveals that family female directors do exert a positive influence on R&D intensity. However, according to the mixed gamble logic, this influence is filtered by the positive and negative moderation of their socioemotional wealth preferences. Managerial Summary: We examine the role that women who are members of the family owning a business play in the decision making of SMEs. Specifically, we investigate the influence that the involvement of family female directors in the board of family SMEs exerts on innovation decisions. To empirically address this line of inquiry, we conducted a survey on 287 Belgian family SMEs. Our analysis shows that the involvement of family female directors in the board fosters family SME's innovation investments. Yet, such an influence is weakened by the intention of the family to retain control over the business but is enhanced by the identification of family members with the firm and by the desire to renew family bonds through dynastic succession. Therefore, our study cautions family SMEs' owners and managers to pay attention to these important dimensions of diversity when appointing directors to their board