Model of human collective decision-making in complex environments

A continuous-time Markov process is proposed to analyze how a group of humans solves a complex task, consisting in the search of the optimal set of decisions on a fitness landscape. Individuals change their opinions driven by two different forces: (i) the self-interest, which pushes them to increase their own fitness values, and (ii) the social interactions, which push individuals to reduce the diversity of their opinions in order to reach consensus. Results show that the performance of the group is strongly affected by the strength of social interactions and by the level of knowledge of the individuals. Increasing the strength of social interactions improves the performance of the team. However, too strong social interactions slow down the search of the optimal solution and worsen the performance of the group. In particular, we find that the threshold value of the social interaction strength, which leads to the emergence of a superior intelligence of the group, is just the critical threshold at which the consensus among the members sets in. We also prove that a moderate level of knowledge is already enough to guarantee high performance of the group in making decisions.Comment: 12 pages, 8 figues in European Physical Journal B, 201

New performance indicators for industrial symbiosis: an ecosystem approach

This paper proposes new performance indicators for industrial symbiosis networks (ISNs) based on the ecosystem approach. ISNs are framed as ecosystems where the firms correspond to the organisms and perform specific functions, i.e., recovering wastes and saving inputs. Two kinds of indicators are designed: 1) indicators assessing the performance of each waste exchange; 2) indicators assessing how each firm is contributing to these exchanges. The designed indicators can be useful in backing up decision-making tools for ISNs

Analysis of Intended Farmers’ Response to CAP Scenarios: Environmental considerations

This research is a result of the CAP-IRE project which objective is the understanding farmer’s reactions under CAP scenarios by 2020. In particular this research aims to analyze the role of the current CAP design on the farmer’s decision process focusing on several environmental issues. The analysis is based on 2,360 observations of household farmers across 11 cases study in 9 EU countries. Intended responses of farmers to the CAP reforms are analyzed by logistic model regression. According to the results CAP scenarios would influence farmer’s decision on fertilizers and pesticides, as well as water use, while the highest effect is found for decisions on number of animal rearing on the farm. Factors determining reaction to the CAP scenario are monetary and non-monetary, as well as structural and spatial. CAP role appears to be non univocal and strongly case-specific, as it substantially differs across regions according to their socio-economic structureEnvironmental sustainability, Farmer’s intended behaviour, Logistic regression, Agricultural policy, Agricultural and Food Policy, Environmental Economics and Policy, Q18,

Efficacy of landfill tax and subsidy policies for the emergence of industrial symbiosis networks: An agent-based simulation study

Despite the theoretical value of industrial symbiosis (IS), this approach appears to be underdeveloped in terms of practical applications. Different attempts to stimulate IS in practice are noticed, one of them consisting in the application of adequate policy measures. This paper explores the efficacy of two specific policies (landfill tax and economic subsidy for IS exchanges) in supporting the emergence of self-organized industrial symbiosis networks (ISNs). We frame the ISNs as complex adaptive systems and we design an agent-based model to simulate their emergence. We use a real case study and, by means of the simulation model, we assess how the two policy measures are able to enhance the formation of spontaneous IS relationships, thereby forcing the emergence of the ISN. Results show that both policy measures have a positive effect in all scenarios considered, but the extent is strictly dependent on the environmental conditions in which IS relationships occur. The economic implications for the government are finally discussed

Environmental Concerns in Water Pricing Policy:Â Â an Application of Data Envelopment Analysis (DEA)

Water management is subject to conflicting economic and environmental objectives, and policymakers require a clear overview of the different outcomes derived from different water management options. The aim of this paper is to assess the efficiency of several irrigation water pricing policies with a special focus on their environmental implications. Irrigation is chosen here as a crucial sector of water use in large parts of southern Europe, where pressure on the resource is expected to increase due to climate change. A novel methodological approach for performing an ex ante analysis of alternative water pricing policies is proposed here, where environmental and technical performance are simultaneously considered. This approach takes place in two steps: the first is a simulation of alternative water policies through a mathematical programming model, and the second is the analysis of results by using the Data Envelopment Analysis (DEA) technique. A case study is applied in Puglia (southern Italy), where irrigation is the primary factor of strategic relevance for policymakers regarding water management. Our results show that on the one hand alternative pricing policies perform similarly in terms of technical efficiency and environmental efficiency. On the other hand, inefficiency appears to depend mainly on technical rather than environmental concerns. According to the assigned weights, through the DEA technique, the highest improvement for inefficient options may be obtained by better labour use. We conclude that the proposed approach may be a comprehensive and versatile framework for water policy analysis, offering a tool for supporting the decision-making process.Irrigation, Policy assessment, Efficiency, Data Envelopment Analysis, Linear Programming

Stochastic multi-period multi-product multi-objective Aggregate Production Planning model in multi-echelon supply chain

In this paper a multi-period multi-product multi-objective aggregate production planning (APP) model is proposed for an uncertain multi-echelon supply chain considering financial risk, customer satisfaction, and human resource training. Three conflictive objective functions and several sets of real constraints are considered concurrently in the proposed APP model. Some parameters of the proposed model are assumed to be uncertain and handled through a two-stage stochastic programming (TSSP) approach. The proposed TSSP is solved using three multi-objective solution procedures, i.e., the goal attainment technique, the modified ε-constraint method, and STEM method. The whole procedure is applied in an automotive resin and oil supply chain as a real case study wherein the efficacy and applicability of the proposed approaches are illustrated in comparison with existing experimental production planning method

Efficiency of LEADER Programmes in the creation of tangible and intangible outputs: a Data Envelopment Analysis application to Local Action Groups performances

An emerging requirement for the evaluation of the rural development policy is the adoption of an objective method accounting for both material and immaterial achievements, and measuring the performance in order to understand the degree of accomplishment of policy objectives. In this paper we propose a Data Envelopment Analysis (DEA) approach capable of dealing with economic and social indicators, to measure the (relative) technical efficiency of a set of Local Action Groups (LAGs) operating within the LEADER programme. An evaluation exercise referred to eight LAGs located in Italy, is provided to demonstrate the effects of the inclusion of social capital indicator in the evaluation of the LAGs’ performances. In particular, the DEA allows to measure the relative efficiency of the LAGs and to identify the causes of the inefficiency. The outcomes of the analysis may represent a valuable information support for periodical policy review and for the enhancement of best practices.Rural Development, LEADER, social capital, DEA, Agricultural and Food Policy, Q18, R58,

Assessing the benefits of supply chain trust: NK simulation-based methodology and application

Previous literature has emphasized that developing trust among supply chain (SC) firms is a critical element in achieving SC effectiveness. Since developing trust is an expensive task, however, making an informed decision whether to invest or not in trust requires careful assessment of trust benefits. Therefore, we advance a simulation-based methodology to quantify performance improvements associated with trust in SCs. We develop an NK simulation model of a generic SC that captures the SC dynamics under two alternative scenarios, characterized by the presence and absence of trust respectively. A procedure is then illustrated to quantify the benefits of trust in the SC. We also apply our proposed methodology to a real-world SC. Results show that, when trust is pervasive across the SC, performance increases at both the levels of the overall SC and its leading firm

Farmers’ stated responses towards the chemicals use under the CAP liberalization

Th e research aims to analyze the farmers’ preferences towards the chemical input use in the case of the Common Agricultural Policy (CAP) being removed after 2013. Th e analysis is based on a survey of European farmers carried out in 2009. Th e intended responses of farmers to the CAP liberalization are analyzed by the logit model regressions. Although for the majority of respondents there would be no change in their intentions if the CAP were suppressed, about 20% would intend to decrease the amount of chemicals. Th e eff ects of the CAP liberalization appear not to be univocal and strongly case-specifi c, as it substantially diff ers across the European regions, farm locations and socio-economic structures