Dr Araz Taeihagh is an Assistant Professor of Public Policy at the Lee Kuan Yew School of Public Policy at the National University of Singapore. Since 2007, his research interest has been on the interface of technology and society. His work is on: a) how to shape policies to accommodate new technologies and facilitate positive socio-technical transitions; b) the effects of these new technologies on the policy process; and c) changing the way we design and analyse policies by developing innovative practical approaches that can be used to address the growth in the interdependence and complexity of our systems. Taeihagh is interested in socio-technical systems and their transitions and focuses on the unique challenges that arise from the introduction of new technologies to society (e.g. crowdsourcing, sharing economy, autonomous vehicles, AI, MOOCs, ridesharing, etc.). These new technologies are creating their own set of issues and concerns that require the understanding and appreciation of both technical and social sciences. For addressing challenges of policy design and analysis, he takes an interdisciplinary approach using artificial and collective intelligence techniques and borrows from engineering, complexity and design sciences alongside the traditional approaches in public policy to address the challenges in policy making. Araz has developed and is continuing the enhancement of a new framework and decision support system for the design and formulation of policies to help decision makers in selecting appropriate policy measures to design sustainable policies and better understand the complex interactions among alternative instruments used.Araz earned his DPhil conducting interdisciplinary research on “A Novel Approach for the Development of Policies in Socio-Technical Systems” at University of Oxford and carried out postdoctoral studies at City Futures Research Centre (Australia’s leading urban policy research centre) at UNSW, and was an Assistant Professor of Public Policy at Singapore Management University before joining LKY School of Public Policy in 2018.
||Araz Taeihagh, (2017). Crowdsourcing: a new tool for policy-making? Policy Sciences Journal. 50(4): 629-647 https://doi.org/10.1007/s11077-017-9303-3|
||Abstract - Crowdsourcing is rapidly evolving and applied in situations where ideas, labour, opinion or expertise of large groups of people is used. Crowdsourcing is now used in various policy-making initiatives; however, this use has usually focused on open collaboration platforms and specific stages of the policy process, such as agenda-setting and policy evaluations. Other forms of crowdsourcing have been neglected in policy-making, with a few exceptions. This article examines crowdsourcing as a tool for policy-making and explores the nuances of the technology and its use and implications for different stages of the policy process. The article addresses questions surrounding the role of crowdsourcing and whether it can be considered as a policy tool or as a technological enabler and investigates the current trends and future directions of crowdsourcing.
Keywords: Crowdsourcing Public policy Policy instrument Policy tool Policy process Policy cycle Open collaboration Virtual labour markets Tournaments Competition |
||Taeihagh, A. (2017). Network-centric policy design. Policy Sciences, 50(2), 317-338.|
||Two important challenges in policy design are better understanding of the design space and consideration of the temporal factors. Moreover, in recent years it has been demonstrated that understanding the complex interactions of policy measures can play an important role in policy design and analysis. In this paper, the advances made in conceptualization and application of networks to policy design in the past decade are highlighted. Specifically, the use of a network-centric policy design approach in better understanding the design space and temporal consequences of design choices are presented. Network-centric policy design approach has been used in classification, visualization, and analysis of the relations among policy measures as well as ranking of policy measures using their internal properties and interactions, and conducting sensitivity analysis using Monte Carlo simulations. Furthermore, through use of a decision support system, network-centric approach facilitates ranking, visualization, and selection of policies using different sets of criteria, and exploring the potential for compromise in policy formulation. The advantage of the network-centric approach is providing the ability to go beyond visualizations and analysis of policies and piecemeal use of network concepts as a tool for different policy design tasks to moving to a more integrated bottom–up approach to design. Furthermore, the computational advantages of the network-centric policy design in considering temporal factors such as policy sequencing and addressing issues such as layering, drift, policy failure, and delay are presented. Finally, some of the current challenges of network-centric design are discussed, and some potential avenues of exploration in policy design through use of computational methodologies, as well as possible integration with approaches from other disciplines, are highlighted.
Keywords: Policy design Networks Policy patching Policy packaging Policy mixes Visualization Virtual environment Decision support system Computer-aided design |
||Taeihagh, A. (2017). Crowdsourcing, Sharing Economies and Development. Journal of Developing Societies, 33(2), 191-222.|
||What are the similarities and differences between crowdsourcing and sharing economy? What factors influence their use in developing countries? In light of recent developments in the use of IT-mediated technologies, such as crowdsourcing and the sharing economy, this manuscript examines their similarities and differences, and the challenges regarding their effective use in developing countries. We first examine each individually and highlight different forms of each IT-mediated technology. Given that crowdsourcing and sharing economy share aspects such as the use of IT, a reliance on crowds, monetary exchange, and the use of reputation systems, we systematically compare the similarities and differences of different types of crowdsourcing with the sharing economy, thus addressing a gap in the current literature. Using this knowledge, we examine the different challenges faced by developing countries when using crowdsourcing and the sharing economy, and highlight the differences in the applicability of these IT-mediated technologies when faced with specific development issues.|
|| Araz Taeihagh, René Bañares-Alcántara, 2014, Towards Proactive and Flexible Agent-Based Generation of Policy Packages for Active Transportation, 47th International Conference on System Sciences (HICSS 47), Jan 4-9 2014 http://dx.doi.org/10.1109/HICSS.2014.118 |
||One of the approaches gaining ground in policy design is the implementation of combinations of policy measures as policy packages with the aim of increasing efficiency and effectiveness of the designed policies. In this paper, we describe the recent advancements in the developments of a virtual environment for the exploration and analysis of policy packages. The virtual environment uses an agent-based modelling approach for the generation of different configurations of policy measures in the policy packages. The benefit of using the approach is the proactive and flexible generation of policy packages as the agents can react to the changes that occur and create packages that are more robust. The system allows faster examination of more alternatives, further exploration of the design space, and testing the effects of changes and uncertainties while formulating policies. The results demonstrate the benefit of using agent-based modelling approaches in the design of complex policies.|
||John Prpić, James Melton, Araz Taeihagh, and Terry Anderson, 2015, MOOCs and crowdsourcing: Massive courses and massive resources, First Monday, 20(12). http://dx.doi.org/10.5210/fm.v20i12.6143|
||Premised upon the observation that MOOC and crowdsourcing phenomena share several important characteristics, including IT mediation, large-scale human participation, and varying levels of openness to participants, this work systematizes a comparison of MOOC and crowdsourcing phenomena along these salient dimensions. In doing so, we learn that both domains share further common traits, including similarities in IT structures, knowledge generating capabilities, presence of intermediary service providers, and techniques designed to attract and maintain participant activity. Stemming directly from this analysis, we discuss new directions for future research in both fields and draw out actionable implications for practitioners and researchers in both domains.|
||Araz Taeihagh, René Bañares-Alcántara and Claire Millican, 2009, Development of a Novel Framework for the Design of Transport Policies to Achieve Environmental Targets, Computers and Chemical Engineering, Volume 33, Issue 10, 1531–1545. http://dx.doi.org/10.1016/j.compchemeng.2009.01.010 |
||The formulation of policies requires the selection and configuration of effective and acceptable courses of action to reach explicit goals. A one-size-fits-all policy is unlikely to achieve the desired goals; as a result, the identification of a suite of alternative policies, together with clear indications of their trade-offs, is crucial to accommodate the diversity of stakeholders’ preferences. At present, the formulation of transport policies is done manually; this fact, together with the size of the space of possible policies, results in a large part of that space being left unexplored. A six-step framework to explore the space of alternative transport policies in order to achieve environmental targets is proposed. The process starts with a user-defined set of specific policy measures, using them as building blocks in the generation of alternative policy packages, clusters and future images according to the user's preferences and goals.
The analysis framework is based on the visioning and backcasting approach used in the VIBAT report [Banister, D., & Hickman, R. (2006a). Visioning and backcasting for UK transport policy (VIBAT) project. Department for Transport's Horizons Research Programme 2004/06. The Bartlett school of planning and Halcrow Group Ltd. Retrieved 1/18/2008 http://www.ucl.ac.uk/∼ucft696/vibat2.html]. The framework is being implemented as a prototype decision support system around a case study: the formulation and analysis of policies required to achieve CO2 emission targets for the transport sector in the UK. Important insights on how to develop the framework have also been elicited from engineering design. The goal is to accelerate the task of policy-making and improve the effectiveness of the resulting policies.
The proposed method and computer implementation is fundamentally different from the tools commonly used in the transport sector and is intended to assist (not replace) transport policy makers, and complement (not substitute nor compete with) existing mathematical modelling tools. This research constitutes the first step towards the development of a general family of computer-based systems that support the design of policies to achieve environmental targets—not only for transport, but also for other sectors such as energy and water.
Decision support systems; Process design; Policy design; Transportation; Emission reduction; Conceptual design|
||John Prpić, Araz Taeihagh, and James Melton, 2015, The fundamentals of policy crowdsourcing. Policy & Internet, 7(3), 340-361. http://dx.doi.org/10.1002/poi3.102 |
||What is the state of the research on crowdsourcing for policymaking? This article begins to answer this question by collecting, categorizing, and situating an extensive body of the extant research investigating policy crowdsourcing, within a new framework built on fundamental typologies from each field. We first define seven universal characteristics of the three general crowdsourcing techniques (virtual labor markets, tournament crowdsourcing, open collaboration), to examine the relative trade-offs of each modality. We then compare these three types of crowdsourcing to the different stages of the policy cycle, in order to situate the literature spanning both domains. We finally discuss research trends in crowdsourcing for public policy and highlight the research gaps and overlaps in the literature.|
||Taeihagh, A., Givoni M., and Bañares-Alcántara, R., (2013). Which policy first? A network-centric approach for the analysis and ranking of policy measures, Environment and Planning B: Planning and Design, 40(4), 595–616. http://dx.doi.org/10.1068/b38058 |
||In addressing various policy problems, deciding which policy measure to start with given the range of measures available is challenging and essentially involves a process of ranking the alternatives, commonly done using multicriteria decision analysis (MCDA) techniques. In this paper a new methodology for analysis and ranking of policy measures is introduced which combines network analysis and MCDA tools. This methodology not only considers the internal properties of the measures but also their interactions with other potential measures. Consideration of such interactions provides additional insights into the process of policy formulation and can help domain experts and policy makers to better assess the policy measures and to understand the complexities involved. This new methodology is applied in this paper to the formulation of a policy to increase walking and cycling.|
||Taeihagh, A., Bañares-Alcántara R., and Givoni, M. (2014). A virtual environment for formulation of policy packages, Transportation Research Part A, Volume 60, Feb 2014, 53–68. http://dx.doi.org/10.1016/j.tra.2013.10.017 |
||The interdependence and complexity of socio-technical systems and availability of a wide variety of policy measures to address policy problems make the process of policy formulation difficult. In order to formulate sustainable and efficient transport policies, development of new tools and techniques is necessary. One of the approaches gaining ground is policy packaging, which shifts focus from implementation of individual policy measures to implementation of combinations of measures with the aim of increasing efficiency and effectiveness of policy interventions by increasing synergies and reducing potential contradictions among policy measures. In this paper, we describe the development of a virtual environment for the exploration and analysis of different configurations of policy measures in order to build policy packages. By developing systematic approaches it is possible to examine more alternatives at a greater depth, decrease the time required for the overall analysis, provide real-time assessment and feedback on the effect of changes in the configurations, and ultimately form more effective policies. The results from this research demonstrate the usefulness of computational approaches in addressing the complexity inherent in the formulation of policy packages. This new approach has been applied to the formulation of policies to advance sustainable transportation.
Policy formulation; Decision support systems; Policy packaging; Virtual environments; Agent-based modelling; Transport policy|
Energy and Natural Resource Policy
Environmental Policy PRIMARY
Science and Technology Policy SECONDARY
Comparative Public Policy
Urban Public Policy
Policy Process Theory PRIMARY
Agenda-Setting, Adoption, and Implementation
Policy Analysis and Evaluation SECONDARY
COMPARATIVE PUBLIC POLICY
ENERGY AND ENVIRONMENT
DECISION SUPPORT SYSTEMS
COMPUTER AIDED DESIGN
SUSTAINABLE URBAN POLICY