Scenario planning:teaching how to anticipate perceived environmental uncertainty within strategy development

Scenario Planning is a strategy tool with growing popularity in both academia and practical situations. Current practices in the teaching of scenario planning are largely based on existing literature which utilises scenario planning to develop strategies for the future, primarily considering the assessment of perceived macro-external environmental uncertainties. However there is a body of literature hitherto ignored by scenario planning researchers, which suggests that Perceived Environmental Uncertainty (PEU) influences micro-external or industrial environmental as well as the internal environment of the organisation. This paper provides a review of the most dominant theories on scenario planning process, demonstrates the need to consider PEU theory within scenario planning and presents how this can be done. The scope of this paper is to enhance the scenario planning process as a tool taught for Strategy Development. A case vignette is developed based on published scenarios to demonstrate the potential utilisation of the proposed process.

A systems approach to strategic manpower planning for technological development under conditions of manpower scarcity and centralised control

This thesis deals with the integration of the manpower criterion with the strategic decision making processes of technological projects in developing countries. This integration is to be achieved by ensuring the involvement of the actors, who have relevant roles and responsibilities along the whole life cycle of the project, in the strategic decision making phases of the project. The relevance of the actors is ascertained by the use of a responsibility index which relates their responsibility to the project's constituent stages. In the context of a technological project in a typical centrally-planned developing environment, the actors are identified as Arbiters, Planners, Implementors and Operators and their roles, concerns and objectives are derived. In this context, the actors are usually government and non-government organisations. Hence, decision making will involve multiple agencies as well as multiple criteria. A methodology covering the whole decision-making process, from options generation to options selection, and adopting Saaty's Analytical Hierarchy Process as an operational tool is proposed to deal with such multiple-criteria, multipleagency decision situations. The methodology is intended to integrate the consideration of the relevant criteria, the prevailing environmental and policy factors, and the concerns and objectives of the relevant actors into a unifying decision-making process which strives to facilitate enlightened decision making and to enhance learning and interaction. An extensive assessment of the methodology's feasibility, based on a specific technological project within the Iraqi oil industry is included, and indicates that the methodology should be both useful and implementable.

Perceived environmental uncertainty in scenario planning

Scenarioplanning is a strategy tool with growing popularity in both academia and practical situations. Current practices of scenarioplanning are largely based on existing literature which utilises scenarioplanning to develop strategies for the future, primarily considering the assessment of perceived macro-external environmentaluncertainties. However there is a body of literature hitherto ignored by scenarioplanning researchers, which suggests that PerceivedEnvironmentalUncertainty (PEU) influences the micro-external as well as the internal environment of the organisation. This paper reviews the most dominant theories on scenarioplanning process and PEU, developing three propositions for the practice of scenarioplanning process. Furthermore, it shows how these propositions can be integrated in the scenarioplanning process in order to improve the development of strategy.

An operational research-based integrated approach for mass evacuation planning of a city

Large-scale disasters are constantly occurring around the world, and in many cases evacuation of regions of city is needed. ‘Operational Research/Management Science’ (OR/MS) has been widely used in emergency planning for over five decades. Warning dissemination, evacuee transportation and shelter management are three ‘Evacuation Support Functions’ (ESF) generic to many hazards. This thesis has adopted a case study approach to illustrate the importance of integrated approach of evacuation planning and particularly the role of OR/MS models. In the warning dissemination phase, uncertainty in the household’s behaviour as ‘warning informants’ has been investigated along with uncertainties in the warning system. An agentbased model (ABM) was developed for ESF-1 with households as agents and ‘warning informants’ behaviour as the agent behaviour. The model was used to study warning dissemination effectiveness under various conditions of the official channel. In the transportation phase, uncertainties in the household’s behaviour such as departure time (a function of ESF-1), means of transport and destination have been. Households could evacuate as pedestrians, using car or evacuation buses. An ABM was developed to study the evacuation performance (measured in evacuation travel time). In this thesis, a holistic approach for planning the public evacuation shelters called ‘Shelter Information Management System’ (SIMS) has been developed. A generic allocation framework of was developed to available shelter capacity to the shelter demand by considering the evacuation travel time. This was formulated using integer programming. In the sheltering phase, the uncertainty in household shelter choices (either nearest/allocated/convenient) has been studied for its impact on allocation policies using sensitivity analyses. Using analyses from the models and detailed examination of household states from ‘warning to safety’, it was found that the three ESFs though sequential in time, however have lot of interdependencies from the perspective of evacuation planning. This thesis has illustrated an OR/MS based integrated approach including and beyond single ESF preparedness. The developed approach will help in understanding the inter-linkages of the three evacuation phases and preparing a multi-agency-based evacuation planning evacuation

Decision-making under extreme *uncertainty: Rethinking hazard -related perceptions and action

Understanding who evacuates and who does not has been one of the cornerstones of research on the pre-impact phase of both natural and technological hazards. Its history is rich in descriptive illustrations focusing on lists of characteristics of those who flee to safety. Early models of evacuation focused almost exclusively on the relationship between whether warnings were heard and ultimately believed and evacuation behavior. How people came to believe these warnings and even how they interpreted the warnings were not incorporated. In fact, the individual seemed almost removed from the picture with analysis focusing exclusively on external measures. ^ This study built and tested a more comprehensive model of evacuation that centers on the decision-making process, rather than decision outcomes. The model focused on three important factors that alter and shape the evacuation decision-making landscape. These factors are: individual level indicators which exist independently of the hazard itself and act as cultural lenses through which information is heard, processed and interpreted; hazard specific variables that directly relate to the specific hazard threat; and risk perception. The ultimate goal is to determine what factors influence the evacuation decision-making process. Using data collected for 1998's Hurricane Georges, logistic regression models were used to evaluate how well the three main factors help our understanding of how individuals come to their decisions to either flee to safety during a hurricane or remain in their homes. ^ The results of the logistic regression were significant emphasizing that the three broad types of factors tested in the model influence the decision making process. Conclusions drawn from the data analysis focus on how decision-making frames are different for those who can be designated “evacuators” and for those in evacuation zones. ^

Integrated sensitivity analysis, calibration, and uncertainty propagation analysis approaches for supporting hydrological modeling

The successful performance of a hydrological model is usually challenged by the quality of the sensitivity analysis, calibration and uncertainty analysis carried out in the modeling exercise and subsequent simulation results. This is especially important under changing climatic conditions where there are more uncertainties associated with climate models and downscaling processes that increase the complexities of the hydrological modeling system. In response to these challenges and to improve the performance of the hydrological models under changing climatic conditions, this research proposed five new methods for supporting hydrological modeling. First, a design of experiment aided sensitivity analysis and parameterization (DOE-SAP) method was proposed to investigate the significant parameters and provide more reliable sensitivity analysis for improving parameterization during hydrological modeling. The better calibration results along with the advanced sensitivity analysis for significant parameters and their interactions were achieved in the case study. Second, a comprehensive uncertainty evaluation scheme was developed to evaluate three uncertainty analysis methods, the sequential uncertainty fitting version 2 (SUFI-2), generalized likelihood uncertainty estimation (GLUE) and Parameter solution (ParaSol) methods. The results showed that the SUFI-2 performed better than the other two methods based on calibration and uncertainty analysis results. The proposed evaluation scheme demonstrated that it is capable of selecting the most suitable uncertainty method for case studies. Third, a novel sequential multi-criteria based calibration and uncertainty analysis (SMC-CUA) method was proposed to improve the efficiency of calibration and uncertainty analysis and control the phenomenon of equifinality. The results showed that the SMC-CUA method was able to provide better uncertainty analysis results with high computational efficiency compared to the SUFI-2 and GLUE methods and control parameter uncertainty and the equifinality effect without sacrificing simulation performance. Fourth, an innovative response based statistical evaluation method (RESEM) was proposed for estimating the uncertainty propagated effects and providing long-term prediction for hydrological responses under changing climatic conditions. By using RESEM, the uncertainty propagated from statistical downscaling to hydrological modeling can be evaluated. Fifth, an integrated simulation-based evaluation system for uncertainty propagation analysis (ISES-UPA) was proposed for investigating the effects and contributions of different uncertainty components to the total propagated uncertainty from statistical downscaling. Using ISES-UPA, the uncertainty from statistical downscaling, uncertainty from hydrological modeling, and the total uncertainty from two uncertainty sources can be compared and quantified. The feasibility of all the methods has been tested using hypothetical and real-world case studies. The proposed methods can also be integrated as a hydrological modeling system to better support hydrological studies under changing climatic conditions. The results from the proposed integrated hydrological modeling system can be used as scientific references for decision makers to reduce the potential risk of damages caused by extreme events for long-term water resource management and planning.

Editor's choice Regional trade agreements and export competitiveness: the uncertain path of Nicaragua’s apparel exports under CAFTA

The Central American Free Trade Agreement (CAFTA) has been a mixed blessing for economic development. While exports to the US economy have increased, dependency may hinder economic growth if countries do not diversify or upgrade before temporary provisions expire. This article evaluates the impact of the temporary Tariff Preference Levels (TPLs) granted to Nicaragua under CAFTA and the consequences of TPL expiration. Using trade statistics, country- and firm-level data from Nicaragua’s National Free Zones Commission (CNZF) and data from field research, we estimate Nicaragua’s apparel sector will contract as much as 30–40% after TPLs expire. Our analysis underscores how rules of origin and firm nationality affect where and how companies do business, and in so doing, often constrain sustainable export growth.

Sensor Planning for Bayesian Nonparametric Target Modeling

Bayesian nonparametric models, such as the Gaussian process and the Dirichlet process, have been extensively applied for target kinematics modeling in various applications including environmental monitoring, traffic planning, endangered species tracking, dynamic scene analysis, autonomous robot navigation, and human motion modeling. As shown by these successful applications, Bayesian nonparametric models are able to adjust their complexities adaptively from data as necessary, and are resistant to overfitting or underfitting. However, most existing works assume that the sensor measurements used to learn the Bayesian nonparametric target kinematics models are obtained a priori or that the target kinematics can be measured by the sensor at any given time throughout the task. Little work has been done for controlling the sensor with bounded field of view to obtain measurements of mobile targets that are most informative for reducing the uncertainty of the Bayesian nonparametric models. To present the systematic sensor planning approach to leaning Bayesian nonparametric models, the Gaussian process target kinematics model is introduced at first, which is capable of describing time-invariant spatial phenomena, such as ocean currents, temperature distributions and wind velocity fields. The Dirichlet process-Gaussian process target kinematics model is subsequently discussed for modeling mixture of mobile targets, such as pedestrian motion patterns.

Novel information theoretic functions are developed for these introduced Bayesian nonparametric target kinematics models to represent the expected utility of measurements as a function of sensor control inputs and random environmental variables. A Gaussian process expected Kullback Leibler divergence is developed as the expectation of the KL divergence between the current (prior) and posterior Gaussian process target kinematics models with respect to the future measurements. Then, this approach is extended to develop a new information value function that can be used to estimate target kinematics described by a Dirichlet process-Gaussian process mixture model. A theorem is proposed that shows the novel information theoretic functions are bounded. Based on this theorem, efficient estimators of the new information theoretic functions are designed, which are proved to be unbiased with the variance of the resultant approximation error decreasing linearly as the number of samples increases. Computational complexities for optimizing the novel information theoretic functions under sensor dynamics constraints are studied, and are proved to be NP-hard. A cumulative lower bound is then proposed to reduce the computational complexity to polynomial time.

Three sensor planning algorithms are developed according to the assumptions on the target kinematics and the sensor dynamics. For problems where the control space of the sensor is discrete, a greedy algorithm is proposed. The efficiency of the greedy algorithm is demonstrated by a numerical experiment with data of ocean currents obtained by moored buoys. A sweep line algorithm is developed for applications where the sensor control space is continuous and unconstrained. Synthetic simulations as well as physical experiments with ground robots and a surveillance camera are conducted to evaluate the performance of the sweep line algorithm. Moreover, a lexicographic algorithm is designed based on the cumulative lower bound of the novel information theoretic functions, for the scenario where the sensor dynamics are constrained. Numerical experiments with real data collected from indoor pedestrians by a commercial pan-tilt camera are performed to examine the lexicographic algorithm. Results from both the numerical simulations and the physical experiments show that the three sensor planning algorithms proposed in this dissertation based on the novel information theoretic functions are superior at learning the target kinematics with

little or no prior knowledge

Novel Formulation and Efficient Solution Strategy for Strategic Optimization of an Industrial Chemical Supply Chain Under Demand Uncertainty

This paper is concerned with strategic optimization of a typical industrial chemical supply chain, which involves a material purchase and transportation network, several manufacturing plants with on-site material and product inventories, a product transportation network and several regional markets. In order to address large uncertainties in customer demands at the different regional markets, a novel robust scenario formulation, which has been developed by the authors recently, is tailored and applied for the strategic optimization. Case study results show that the robust scenario formulation works well for this real industrial supply chain system, and it outperforms the deterministic formulation and the classical scenario-based stochastic programming formulation by generating better expected economic performance and solutions that are guaranteed to be feasible for all uncertainty realizations. The robust scenario problem exhibits a decomposable structure that can be taken advantage of by Benders decomposition for efficient solution, so the application of Benders decomposition to the solution of the strategic optimization is also discussed. The case study results show that Benders decomposition can reduce the solution time by almost an order of magnitude when the number of scenarios in the problem is large.

Housing and Planning in London under the Conservative Government: Spatial impacts, social polarisation, sustainable development and social justice

This paper will be based on my continuing research on planning and housing development in London. It will focus on the proposals in the Government’s Housing and Planning Bill, which are likely to be enacted in Spring 2016. It will review the evidence of potential spatial impacts in terms of the supply of existing affordable homes and the location and affordability of new supply. This will be related to a review of the alternative development options for London’s growth in the context of the Mayor of London’s draft 2050 Infrastructure Plan. The paper will analyse the potential impact of new Government policy and legislation on whether London’s housing requirements can be delivered in accordance with the objectives of sustainable planning and social justice, and will also consider the constraints on the ability of the new Mayor of London, to be elected in May 2016 to achieve manifesto commitments.

From brown envelopes to community benefits: the co-option of planning gain agreements under deepening neoliberalism

The provision of physical and social infrastructure in the form of roads, green spaces and community facilities has traditionally been provided for by the state through the general taxation system. However, as the state has been transformed along more neoliberal lines, the private sector is increasingly relied upon to deliver public goods and services. Planning gain agreements have flourished within this context by offering another vehicle through which local facilities are privately funded. Whilst these agreements reflect the broader dynamics of neoliberalism, they are commonly viewed as a tool which can be employed to challenge these very dynamics by empowering local communities to secure more just planning outcomes. This paper counters such claims. Based on evidence gathered from 80 interviews with planners, councillors, developers and community groups in Ireland, the paper demonstrates how planning gain agreements have been strategically redeployed by the holders of political and economic power to serve their own ends. In seeking to understand why and how this has occurred, specific consideration is given to the changing power dynamics between the state and private capital under neoliberalism. The paper highlights how institutional arrangements have enabled developers to infiltrate the political sphere in more subtle and implicit ways than ever before. We conclude by arguing that planning gain must be understood as a mechanism which has been manipulated in ways which essentially work to preserve and enhance, rather than redress, existing power imbalances in the planning system by facilitating large scale transfers of wealth upwards in society.

Uncertainty avoidance: public sector clients and procurement selection

Purpose: Choosing the appropriate procurement system for construction projects is a complex and challenging task for clients particularly when professional advice has not been sought. To assist with the decision making process, a range of procurement selection tools and techniques have been developed by both academic and industry bodies. Public sector clients in Western Australia (WA) remain uncertain about the pairing of procurement method to bespoke construction project and how this decision will ultimately impact upon project success. This paper examines ‘how and why’ a public sector agency selected particular procurement methods. · Methodology/Approach: An analysis of two focus group workshops (with 18 senior project and policy managers involved with procurement selection) is reported upon · Findings: The traditional lump sum (TLS) method is still the preferred procurement path even though alternative forms such as design and construct, public-private-partnerships could optimize the project outcome. Paradoxically, workshop participants agreed that alternative procurement forms should be considered, but an embedded culture of uncertainty avoidance invariably meant that TLS methods were selected. Senior managers felt that only a limited number of contractors have the resources and experience to deliver projects using the nontraditional methods considered. · Research limitations/implications: The research identifies a need to develop a framework that public sector clients can use to select an appropriate procurement method. A procurement framework should be able to guide the decision-maker rather than provide a prescriptive solution. Learning from previous experiences with regard to procurement selection will further provide public sector clients with knowledge about how to best deliver their projects.