Agent-based modeling as a tool for program design and evaluation

Recently, systems thinking and systems science approaches have gained popularity in the field of evaluation; however, there has been relatively little exploration of how evaluators could use quantitative tools to assist in the implementation of systems approaches therein. The purpose of this paper is to explore potential uses of one such quantitative tool, agent-based modeling, in evaluation practice. To this end, we define agent-based modeling and offer potential uses for it in typical evaluation activities, including: engaging stakeholders, selecting an intervention, modeling program theory, setting performance targets, and interpreting evaluation results. We provide demonstrative examples from published agent-based modeling efforts both inside and outside the field of evaluation for each of the evaluative activities discussed. We further describe potential pitfalls of this tool and offer cautions for evaluators who may chose to implement it in their practice. Finally, the article concludes with a discussion of the future of agent-based modeling in evaluation practice and a call for more formal exploration of this tool as well as other approaches to simulation modeling in the field.     

What is a complex?

This essay evaluates the question of the ‘complex’ in a range of scientific, political and psychoanalytic contexts, asking not only where lines of connection and demarcation occur among specific distributions of meaning, value, theory and practice; but also probing the psychoanalytic corpus, notably Freud’s writings on the notion of a ‘complex’, in order to reframe various implications of the idea that this term tends to resist its own utilisation as both an object and form of analysis.     

The ambivalent effect of complexity on firm performance: A study of the global service provider industry

Prior literature is ambivalent about whether organizational complexity has positive or negative effects on firm performance. Using rich data on global service providers, we explore this ambivalence by disentangling performance consequences of different types of organizational complexity. We show that complexity arising from the coordination of different services and operations negatively influences profit margins through increased coordination costs, whereas complexity coming from the sophistication of particular services may positively influence margins through informational advantages. We also investigate the moderating effects of process commoditization and client-specific investments. Our findings point to critical performance dilemmas facing global service providers in a highly competitive industry, and they help better differentiate performance effects of complexity at different organizational levels.     

逻辑悖论的语义动力学分析及其意义

本文着重介绍了Patrick Grim等人提出的一种分析逻辑悖论的新方法,即悖论的语义动力学方法。然后在此基础上,分析了该方法在逻辑悖论研究中,特别是在悖论语义复杂性结构分析、为语义悖论提供科学分类依据的研究中,乃至在一般性互涉句群语义分析研究中的重要意义。最后运用悖论语义动力学方法的结果．针对悖论式禅境的性质分析,给出了一种实际应用,用以说明悖论语义动力学分析方法的普适性应用价值。     

国有土地资本运营与复杂性研究

国有土地资本运营是资本运营的一种形式 ,即国有土地使用权作为资产在社会、经济活动中的运作和经营。从复杂性研究的思路出发 ,本文认为 ,国有土地资本运营是一个开放的复杂巨系统 ,对其正确的认识范式必然是系统范式。在物理—事理—人理 (WSR)系统方法论的框架下 ,本文建立了国有土地资本运营的WSR系统管理模式 ,并对典型案例作了分析。     

哲学视野中的复杂性——拓展复杂性研究的新视野

复杂性是当代科学的前沿,其深刻思想已渗透到科学、经济、管理、社会等各个领域中,从哲学角度思考复杂性是当下时代的重要使命。文章把复杂性哲学的任务概括为：澄清复杂性思想,建构复杂性范式。依据不同的哲学视野,文章把当代复杂性研究纳入到六个核心主题下：“复杂性转向”、“从存在到演化”、“从对立到互动”、“从构成到生成”、“从寻求确定性到挑战确定性”、“从理解到应对”。通过对复杂性研究视野的拓展,我们可以更好地把握复杂性思想的精髓。     

中国古代哲学中信息、系统、复杂性思想的十大特点

中国古代哲学中蕴涵着丰富而深刻的信息、系统、复杂性思想。本文将这些思想归纳为十个方面的特质:①几乎所有的哲学家都坚持世界具有整体统一性的观念;②在人类哲学史上最早提出了类似于信息结构化的理论;③在一定程度上看到了事物自身显示自身的信息性存在的性质;④在一定程度上看到了事物存在的全息性特征;⑤在人类科学与哲学史上最早提出了信息网络的思想;⑥在某种程度上已经看到了整体性质的涌现性特征;⑦在某种程度上已经提出了关于人的认识的信息中介论理论的萌芽性思想;⑧具有丰富的过程论和生成论的思想;⑨提出了明晰而深刻的非决定论的复杂自组织思想;⑩具有直观性、猜测性、神秘性等缺陷。     

A frequentist understanding of sets of measures

We present a mathematical theory of objective, frequentist chance phenomena that uses as a model a set of probability measures. In this work, sets of measures are not viewed as a statistical compound hypothesis or as a tool for modeling imprecise subjective behavior. Instead we use sets of measures to model stable (although not stationary in the traditional stochastic sense) physical sources of finite time series data that have highly irregular behavior. Such models give a coarse-grained picture of the phenomena, keeping track of the range of the possible probabilities of the events. We present methods to simulate finite data sequences coming from a source modeled by a set of probability measures, and to estimate the model from finite time series data. The estimation of the set of probability measures is based on the analysis of a set of relative frequencies of events taken along subsequences selected by a collection of rules. In particular, we provide a universal methodology for finding a family of subsequence selection rules that can estimate any set of probability measures with high probability.     

Dynamic systems and the role of evaluation: The case of the Green Communities project

The crucial role evaluation can play in the co-development of project design and its implementation will be addressed through the analysis of a case study, the Green Communities (GC) project, funded by the Italian Ministry of Environment within the EU Interregional Operational Program (2007–2013) “Renewable Energy and Energy Efficiency”. The project's broader goals included an attempt to trigger a change in Italian local development strategies, especially for mountain and inland areas, which would be tailored to the real needs of communities, and based on a sustainable exploitation and management of the territorial assets. The goal was not achieved, and this paper addresses the issues of how GC could have been more effective in fostering a vision of change, and which design adaptations and evaluation procedures would have allowed the project to better cope with the unexpected consequences and resistances it encountered. The conclusions drawn are that projects should be conceived, designed and carried out as dynamic systems, inclusive of a dynamic and engaged evaluation enabling the generation of feedbacks loops, iteratively interpreting the narratives and dynamics unfolding within the project, and actively monitoring the potential of various relationships among project participants for generating positive social change.     

Making sense of the emerging conversation in evaluation about systems thinking and complexity science

In the last twenty years, a conversation has emerged in the evaluation field about the potential of systems thinking and complexity science (STCS) to transform the practice of evaluating social interventions. Documenting and interpreting this conversation are necessary to advance our understanding of the significance of using STCS in planning, implementing, and evaluating social interventions. Guided by a generic framework for evaluation practice, this paper reports on an inter-disciplinary literature review and argues that STCS raises some new ways of thinking about and carrying out the following six activities: 1) supporting social problem solving; 2) framing interventions and contexts; 3) selecting and using methods; 4) engaging in valuing; 5) producing and justifying knowledge; and 6) facilitating use. Following a discussion of these issues, future directions for research and practice are suggested.