Suchergebnisse

AbstractThis article proposes an innovative approach to evaluate firms' inefficiency accounting for corporate social responsibility. In the first step, we estimate dynamic inefficiency for each factor of production using data envelopment analysis. Next, we explore differences in inefficiencies between groups of firms of which participation is determined using latent class analysis. The empirical application focuses on the United States food and beverage manufacturing firms over the period 2004–2018. The results distinguish three classes of firms that differ in terms of their inefficiency, their association with external covariates as well as in their input–output profiles.

By 2020, Dutch dairy chains envisage to be self-sufficient with regard to energy used by dairy farms and dairy processors. This would require dairy farms to produce 25 PJ per year, possibly by a combination of wind, solar and biogas. This paper focuses on biogas. To evaluate the project's viability we estimated the expected technical and financial performance of 4 types of business models, i.e. "CHP-farm", "CHP-large", "green gas" and "central upgrading of green gas". Data stem from among others 23 biogas plants in the Netherlands. Anticipating that CHP-models and green gas models occur with a likelihood of 40% and 60% respectively, the total number of biogas plants would amount to 232 (1% of dairy farms), including a total of 5 million tons of manure per year (14% of all cattle manure in the Netherlands) and annual government subsidies of Euro 295 million. Aggregated annual profits are expected to be positive, but over the project's total life time there is an expected deficit of Euro 262. For this to change costs of feedstocks or digestate disposal costs would for instance have to go down. Also fully switching to green gas models dampens the deficit. Results are used in current stakeholders debates on the organization of an "energy neutral dairy chain" in the Netherlands. Further analyses incorporating uncertainty around key technical and economic parameters including financial impacts of CO2-reductions are underway.

Sustainable agricultural commodities should be favored in international trade negotiations to meet the growing demand for food in a context of environmental conservation, population growth, and globalization. There is a need for a metric that allows for the differentiation of traded agricultural commodities according to how sustainably they were produced. In this context, this paper develops two single metrics, based on a Total Factor Productivity indexing approach, for benchmarking products in terms of their sustainability performance. Both metrics are adjusted to internalize the social and environmental externalities of food production, and to account for the sustainability effects of stages along agri‐food supply chains. Key aspects such as data availability, the selection of variables, and the selection of sustainability standards and targets are discussed.

"The book takes on a systematic treatment of dynamic decision making and performance measurement. The analytical foundations of the dynamic production technology are introduced and developed in detail for several primal representations of the technology with an emphasis on dynamic directional distance functions. Dynamic cost minimization and dynamic profit maximization are developed for primal and dual representations of the dynamic technology. A dynamic production environment can be characterized as one where current production decisions impact future production possibilities. Consequently, the dynamic perspective of production relationships necessarily involves the close interplay between stock and flow elements in the transformation process, and how current decisions impact the changes in future stocks. Stock elements in the production transformation process can involve physical elements that can be effectively employed in the transformation process that can include the stock of technical knowledge and expertise available to the decision maker during the decision period. The dynamic generalization of concepts measuring the production structure (e.g., economies of scale, economies of scope, capacity utilization) and performance (e.g., allocative, scale and technical inefficiency, productivity) are developed from primal and dual perspectives"--

Productivity and economic performance have generated many studies and considerable discussion in economic policy circles. Yet, theoretical and empirical studies focusing on production efficiency have typically ignored the time interdependence of production decisions and the adjustment firms make over time. This book provides a systematic treatment of dynamic decision making and performance measurement.

Various integrated impact assessment (IIA) frameworks are used by governments and intragovernmental agencies to aid in planning and decision making for the management of natural disasters, such as floods or earthquakes, and planned interventions, such as mining operations or housing development. IIA considers economic, environmental and social impacts. IIA takes a hierarchical approach in which the impacts are decomposed in a stepwise manner down to a point at which they are concrete enough to make an assessment using data, expert judgement or models. The completed partial assessment results are combined using decision rules to achieve overarching assessments. IIA has similar objectives as pest risk analyses made by plant health authorities; however, the principles and approaches of IIA have not been widely applied in plant health. An inherent difficulty in the integrated approach is the assessment of non-monetary societal impacts. The classical approach to pest risk analysis follows the steps of entry, estab lishment, spread and impact, representing the mechanistic pathway towards harm. This approach may not necessarily provide the most effective way to assess the different kinds of impacts that need consideration, such as impacts on plant health, ecosystem functioning, and communities that depend for their livelihoods on agricultural plant production or ecosystem services. The question is what PRA can learn from the practice of IIA. As part of the Horizon 2020 POnTE Project, we will explore options to use IIA to support plant health authorities developing measures for prevention and control that deliver maximum total benefit to society. Applications will focus on Xylella fastidiosa, Candidatus Liberibacter solanacearum, Phytophthora spp. and Hymenoscyphus fraxineus.