Range-based Multi-Actor Multi-Criteria Analysis: A combined method of Multi-Actor Multi-Criteria Analysis and Monte Carlo simulation to support participatory decision making under uncertainty

Concerns about environmental and social effects have made Multi-Criteria Decision Making (MCDM) increasingly popular. Decision making in complex contexts often – possibly always – requires addressing an aggregation of multiple issues to meet social, economic, legal, technical, and environmental objectives. These values at stake may affect different stakeholders through distributional effects characterized by a high and heterogeneous uncertainty that no social actors can completely control or understand. On this basis, we present a new process framework that aims to support participatory decision making under uncertainty: the range-based Multi-Actor Multi-Criteria Analysis (range-based MAMCA). On the one hand, the process framework explicitly considers stakeholders’ objectives at an output level of aggregation. On the other hand, by means of a Monte Carlo analysis, the method also provides an exploratory scenario approach that enables the capture of the uncertainty, which stems from the complex context evolution. Range-based MAMCA offers a unique participatory process framework that enables us (1) to identify the alternatives pros and cons for each stakeholder group; (2) to provide probabilities about the risk of supporting mistaken, or at least ill-suited, decisions because of the uncertainty regarding to the decision-making context; (3) to take the decision-makers’ limited control of the actual policy effects over the implementation of one or several options into account. The range-based MAMCA framework is illustrated by means of our first case study that aimed to assess French stakeholders’ support for different biofuel options by 2030.     

Structuring decision problems: A case study and reflections for practitioners

This article reviews several approaches to problem structuring and, in particular, the three-step structuring process for decision analysis proposed by von Winterfeldt and Edwards: (1) identifying the problem; (2) selecting an appropriate analytical approach; (3) developing the a detailed analytic structure. This three-step process is re-examined in the context of a decision analysis of alternative policies to reduce electromagnetic field exposure from electric power lines. This decision analysis was conducted for a public health organization funded by the California Public Utilities Commission and it was scrutinized throughout by interested stakeholders. As a result a significant effort went into structuring this problem appropriately, with some successes and some missteps. The article extracts lessons from this experience, updating existing guidance on structuring problems for decision analysis, and concluding with some general insights for problem structuring.     

Simulating resistances in innovation diffusion over multiple generations: an agent-based approach for fuel-cell vehicles

Central European Journal of Operations Research - Innovation resistances play a major role in innovation diffusion, as they do not only hinder the adoption, but might also change a decision...     

Efficiency analysis in banking firms: An international comparison

The intensive process of financial European integration, together with the profound transformation and deregulation that has taken place in the Spanish banking system, justifies the evaluation of its efficiency in comparison with that of other banking systems. In this context, the aim of this study is to analyze the productivity, efficiency and differences in technology of several banking systems. Using a non-parametric approach together with the Malmquist index, we compare the efficiency, productivity and differences in technology of different European and US banking systems for the year 1992.     

Sustainable energy futures: Methodological challenges in combining scenarios and participatory multi-criteria analysis

This paper analyses the combined use of scenario building and participatory multi-criteria analysis (PMCA) in the context of renewable energy from a methodological point of view. Scenarios have been applied increasingly in decision-making about long-term consequences by projecting different possible pathways into the future. Scenario analysis accounts for a higher degree of complexity inherent in systems than the study of individual projects or technologies. MCA is a widely used appraisal method, which assesses options on the basis of a multi-dimensional criteria framework and calculates rankings of options. In our study, five renewable energy scenarios for Austria for 2020 were appraised against 17 sustainability criteria. A similar process was undertaken on the local level, where four renewable energy scenarios were developed and evaluated against 15 criteria. On both levels, the scenario development consisted of two stages: first an exploratory stage with stakeholder engagement and second a modelling stage with forecasting-type scenarios. Thus, the scenarios consist of a narrative part (storyline) and a modeled quantitative part. The preferences of national and local energy stakeholders were included in the form of criteria weights derived from interviews and participatory group processes, respectively. Especially in the case of renewable energy promotion in Austria, the paper systematically analyses the potentials and limitations of the methodology (1) for capturing the complexity of decision-making about the long-term consequences of changes in socio-economic and biophysical systems and (2) for appraising energy futures. The paper concludes that assessing scenarios with PMCA is resource intense, but this methodology captures successfully the context of technology deployment and allows decision-making based on a robust and democratic process, which addresses uncertainties, acknowledges multiple legitimate perspectives and encourages social learning.     

基于自组织理论的技术创新系统演化机理及模型分析

创新是人类财富之源,是经济发展的巨大动力。本文从复杂系统理论角度说明了技术创新系统的自组织特性;分析了创新过程的不稳定性、分岔、突变和随机"涨落"等演化特征和作用机理;随后结合进化经济学理论,构建了技术创新系统自组织竞争与协同演化过程的定量模型,并对模型的稳定性和演化趋势进行分析,应用统计和数学工具软件对模型的参数变化进行函数模拟,对模拟结果进行了讨论;随后以我国通信产业发展为例进行了相关案例分析。此研究旨在通过自然科学与社会科学的有效结合,对技术创新系统的演化机理及过程提供一种新的研究思路。     

科技型中小企业技术创新基金的价值测度实证研究

科技型中小企业技术创新基金的价值如何测度和实现价值最大化是政府和企业迫切需要解决的问题.基于波特的价值链模型以及科技型中小企业的特点,分析了科技型中小企业的价值链,并以价值链和利益相关者作为理论基础分析了创新基金的作用机理,得出创新基金的价值体现为资金杠杆、社会资本杠杆和带动效应,通过对每种价值进行细化形成完整的国家创新基金的价值测度指标体系,同时结合115份有效的调查问卷,对国家创新基金的价值测度进行实证研究,为有关政府部门制定政策和科技型中小企业实施创新基金项目提供了理论指导.     

基于政府支持的军民合作技术创新演化博弈研究

如何促进军民合作技术创新是军民深度融合战略背景下军民双方亟需解决的重要问题。基于演化博弈的基本理论和方法,构建了包含民企、军企与政府在内的三方博弈模型,寻找出能使整个系统处于均衡状态的稳定策略,并利用数值仿真分析了政府支持不同方式对军民合作技术创新的影响。结果表明:在政府不同支持方式下,民企和军企相互促进,双方均向合作技术创新的方向演化,并最终保持稳定;随着时间的推进,政府最终均会选择退出支持,不同支持方式下退出速度不同;政府应对不同支持方式进行优化。     

Predictive modeling of inbound demand at major European airports with Poisson and Pre-Scheduled Random Arrivals

This paper presents an exhaustive study of the arrivals process at eight major European airports. Using inbound traffic data, we define, compare, and contrast a data-driven in-homogeneous Poisson and Pre-Scheduled Random Arrivals (PSRA) point process with respect to their ability to predict future demand. As part of this analysis, we show the weaknesses and difficulties of using a non-homogeneous Poisson process to model the arrivals stream. On the other hand, our novel and simple data-driven (PSRA) model captures and predicts the main properties of the typical arrivals stream with good accuracy. These results have important implication for the modeling and simulation-based analyses of inbound traffic and can improve the use of available capacity, thus reducing air traffic delays. In a nutshell, the results lead to the conclusion that, in the European context, the (PSRA) model provides more accurate predictions.     

Multiple goals and ownership structure: Effects on the performance of Spanish savings banks

Spanish savings banks (SBs) are financial institutions with a wide mission that includes different stakeholders’ goals. Profit maximization is only one among several goals, and the widespread use of cost or profit efficiency as the only comparative performance measure may prove to be insufficient in this context. To overcome this problem, we build an aggregate performance index for organizations with multiple goals. Furthermore, we show how the ownership structure of SBs influences their economic behavior in two basic ways: (1) the performance level and (2) their goal priorities. In particular, we distinguish two types of ownership structures in our application, namely, organizations controlled by Public Administrations and those controlled by insiders (i.e. managers and workers). Our results indicate that each type has different priorities and differ in their performance indexes. More specifically, the empirical analysis shows that insider-controlled SBs favor goals related to profit maximization and the universal access to financial services and, furthermore, they perform better. In contrast, contributing to regional development becomes the most favored goal when Public Administrations have a majority in the bank.     

Implementation of MGWR-SAR models for investigating a local particularity of European regional innovation processes

Central European Journal of Operations Research - This study puts emphasis on spatial effects, spatial autocorrelation and heterogeneity in the context of European regional innovation activities....     

平台动态激励、消费采纳与数字内容创新——基于三方主体演化博弈分析

为探索多元参与主体对数字内容创新过程的影响机制,本研究对数字内容创新活动利益相关者进行界定并分析其行为逻辑与影响因素,通过构建数字内容平台方、数字内容提供方和数字内容消费方三方演化博弈模型,运用复制动态方程分析以及Matlab软件仿真分析,模拟三方博弈主体在数字内容创新中的策略演化路径。研究结果表明,数字内容创新机制是在数字内容平台方主导创新激励、数字内容提供方选择性创新,数字消费方采纳支持创新的三方动态博弈中不断协同演进的过程,数字内容平台方对数字内容消费方创新采纳行为决策的补偿力度与数字内容提供方收益分成比例两大因素对数字内容创新有决定性影响。其研究结论为完善平台经济视角下的数字内容创新机制提供了相关对策建议。     

Measuring inefficiency for specific inputs using data envelopment analysis: evidence from construction industry in Spain and Portugal

This article contributes to the efficiency literature by defining, in the context of the data envelopment analysis framework, the directional distance function approach for measuring both technical and scale inefficiencies with regard to the use of individual inputs. The input-specific technical and scale inefficiencies are then aggregated in order to calculate the overall inefficiency measures. Empirical application focuses on a large dataset of Spanish and Portuguese construction companies between 2002 and 2010 and accounts for three inputs: materials, labor and fixed assets. The results show, first, that for both Spanish and Portuguese construction companies, fixed assets are the most technically inefficient input. Second, the most inefficient scale concerns the utilization of material input in both samples; the reason for this inefficiency is that firms tend to operate in the increasing returns to scale portion of technology set. Third, in both samples, large firms have the lowest input-specific technical inefficiencies, but the highest input-specific scale inefficiencies, compared to their small and medium-sized counterparts, and tend to suffer from decreasing returns to scale. Finally, in both samples, input-specific technical inefficiency under constant returns to scale increased during the period of the recent financial crisis, mainly due to the augmentation in scale inefficiency.

     

Disruptive technologies in agricultural operations: a systematic review of AI-driven AgriTech research

The evolving field of disruptive technologies has recently gained significant interest in various industries, including agriculture. The fourth industrial revolution has reshaped the context of agricultural technology (AgriTech) with applications of artificial intelligence (AI) and a strong focus on data-driven analytical techniques. Motivated by the advances in AgriTech for agrarian operations, the study presents a state-of-the-art review of the research advances which are, evolving in a fast pace over the last decades (due to the disruptive potential of the technological context). Following a systematic literature approach, we develop a categorisation of the various types of AgriTech, as well as the associated AI-driven techniques which form the continuously shifting definition of AgriTech. The contribution primarily draws on the conceptualisation and awareness about AI-driven AgriTech context relevant to the agricultural operations for smart, efficient, and sustainable farming. The study provides a single normative reference for the definition, context and future directions of the field for further research towards the operational context of AgriTech. Our findings indicate that AgriTech research and the disruptive potential of AI in the agricultural sector are still in infancy in Operations Research. Through the systematic review, we also intend to inform a wide range of agricultural stakeholders (farmers, agripreneurs, scholars and practitioners) and to provide research agenda for a growing field with multiple potentialities for the future of the agricultural operations.

     

基于ABMS的主流与新流创新资源动态配置机制研究

现有研究普遍认为领导者需要平衡二元创新中主流创新与新流创新之间的资源配置,但针对具体的资源平衡机制研究较少。本文采用基于主体建模与仿真(ABMS)的方法,将领导风格和资源柔性纳入二元创新资源配置动态模型,并在考虑风险和不确定性的条件下开展模拟仿真,研究发现：企业二元创新绩效与变革型领导风格倾向成正相关,与交易型领导风格倾向成负相关;变革型领导企业的创新绩效随资源柔性提高而增长,交易型领导企业与之相反;领导风格与资源柔性之间存在匹配性：变革型领导与高资源柔性正向促进企业创新绩效,交易型领导与低资源柔性更利于取得高绩效;企业创新绩效与创新风险呈“倒U形”关系。研究成果拓展了企业领导理论和二元创新理论,也为领导者适应风险、转变领导风格、调整资源柔性开展二元创新提供决策依据。     

Application of Compromise Programming to a semi-detached housing development in order to balance economic and environmental criteria

European Energy Performance of Buildings Directives DE promote energy efficiency in buildings. Under these Directives, the European Union States must apply minimum requirements regarding the energy performance of buildings and ensure the certification of their energy performance. The Directives set only the basic principles and requirements, leaving a significant amount of room for the Member States to establish their specific mechanisms, numeric requirements and ways to implement them, taking into account local conditions. With respect to the Spanish case, the search for buildings that are more energy efficient results in a conflict between users’ economic objectives and society's environmental objectives. In this paper, Compromise Programming is applied to help in the decision-making process. An appropriate distribution of types of dwellings, according to their energy performance and to the climatic zone considered in Spain, will be suggested. Results provide a compromise solution between both objectives.     

Using DEA for planning in UK universities—an institutional perspective

This paper is focused on the process of performance measurement undertaken by different stakeholders in the UK higher education sector, focusing on the institutional perspective. Different classes of stakeholders have different motivations to measure performance. Institutions will be affected on the one hand by the state evaluation of them, and on the other by the applicant's. The contribution of Data Envelopment Analysis (DEA) to inform management is explored and illustrated in an application to the University of Warwick, using concepts from a technique to support strategic option formulation, the Boston Consulting Group (BCG) matrix.     

A framework for participatory decision support using Pareto frontier visualization,goal identification and arbitration

There is a growing interest in promoting participation of lay stakeholders in public decision-making processes, possibly with the aid of Internet-based systems. This implies supporting non-sophisticated users and, consequently, developing user-friendly, yet rigorous, participatory decision support methods. We outline a framework to develop such methods based on interactive Pareto frontier visualization combined with expression of preferences in terms of feasible goals and using feasible goal-based arbitration.     

考虑信息粘滞性和知识溢出的企业创新策略演化分析

企业创新发展已成为企业可持续发展的关键,是国家经济发展的重要助推器。企业创新研发过程会出现知识溢出行为,而知识溢出行为一方面将打击创新企业的创新积极性,但另一方面会促进企业与其他合作成员的合作关系。从知识传播过程入手,运用信息粘滞性去控制知识溢出程度,根据企业创新进程构建企业创新策略演化模型。研究发现独立创新阶段,采取知识投入策略的企业短期内会通过增加信息粘滞性来避免知识溢出,当企业双方都进行知识投入时,合作逐渐向协同创新发展;协同创新阶段,企业双方同时采用知识投入策略时,知识转移促进企业形成“溢出-吸收-反吸收”合作回路,知识内化能力、知识投入水平与政府补贴正向激励合作,信息粘滞性影响被合作优势消除。     

Combination of Statistical Similarity Measure and Derivative Morphological Profile Approach for Oil Slick Detection in SAR Images

Synthetic Aperture Radar (SAR) is widely used to detect and monitor oil pollution on the sea surface. As it is sensitive to surface roughness, the presence of oil film on the sea surface decreases the backscattering of this target type resulting in a dark feature patches in SAR images. In this paper, a new approach for oil slicks detection is presented. It is mainly based on SAR image texture analysis using the combination of a statistical similarity measure and a derivative morphological profile. Oil slicks signature is extracted trough two steps procedure. First, SAR image inspection is performed in order to highlight the dark spots suspected to be oil slicks. The inspection is achieved through a similarity measure between a local probability density function (lpdf) of clean water and the lpdf of the area to be inspected. The local distribution is estimated in the neighbourhood of each pixel and compared to a reference one using the Kullback-Leibler KL distance between distributions. Second, and once spots highlighted, texture features extraction using the Derivative Morphological Profile is porformed in order to improve the detection results. algorithm has been applied to Envisat Advanced Synthetic Aperture Radar (ASAR) and European Remote Sensing (ERS) images and it yields an accurate segmentation results. Indeed, the features extraction improves the detection slicks probability Pd of ASAR, respectively ERS, images from 93.08 %to 97.37 %and from 96.32 to 99.57 % on one hand, and reduces the false alarms probability respectively from 6.92 to 2.63 %and from 3.68 to 0.59 % on the other hand.