Scenario Planning Approach Research Articles

Scenario based approach to re-imagining future of higher education which prepares students for the future of work

Purpose The world of work and education is changing at a rapid pace, driven by continued technological disruption and automation. The future is uncertain and difficult to envisage. A futures thinking scenario planning approach is used in exploring and guiding education policy makers on how best to respond to the range of possible futures. The paper aims to discuss this issue. Design/methodology/approach This study utilizes elements of prior scenario planning methodologies to devise a practical model of preferred and plausible likely scenarios in the context of rapid and continuing technology disruption. Based on the notion of “impact and uncertainty,” two possible future alternatives of work and learning were developed. Incorporating elements of the possibility space scenario framework and a vignette approach of current emergent technologies, this paper assessed the usefulness of the preferred and likely outcomes. Findings While preferred future scenarios entailing collaborative styles such as human–machine cooperation, smart virtual active learning campuses and living knowledge learning environments may produce more desirable benefits for education stakeholders, the more likely plausible scenario is one based on continued disruptive technologies. Automation, artificial intelligence and the advent of 5G network technologies will drive customization and personalization in higher education delivery and revolutionize the work landscape in the immediate future. Universities will need to embrace and respond to these changes. Originality/value The paper gives insights into how universities can prepare their students for future of work and improve their employability. In addition, this author recommends ways in which HEIs can leverage these newer technologies to drive educational services and commercial value.

Possibilities for the future of global mental health: a scenario planning approach

BackgroundGlobal mental health is a widely used term describing initiatives in policies, research and practice to improve the mental health of people worldwide. It has been gaining momentum over the last 10 years, reflected in increasing funding opportunities, training programmes, and publications. In light of the rising importance of global mental health and the various uncertainties about its future directions, this paper explores what the future may hold for global mental health in 30 years’ time.MethodA scenario planning method was used, involving a workshop with experts from four continents and a range of backgrounds, including clinical and academic psychiatry, psychology, art and music therapy, service user advisory role, funder of global health research and post-graduate students.ResultsSix distinct scenarios that describe potential future situations were developed: universal standards for care; worldwide coordination of research; making use of diversity; focus on social factors; globalised care through technology; mental health as a currency in global politics.ConclusionsThese scenarios consider different social, economic, scientific and technological drivers and focus on distinct aspects. Some reflect a global application of possible trends in mental health, whilst others apply general global developments to mental health care. They are not fixed forecasts, but instead may help to promote discussion and debate about further developments and decisions.

Divergent agricultural water governance scenarios: The case of Zayanderud basin, Iran

There is an urgent need to consider adaptation strategies for agricultural water resources in response to the ever-growing demand for freshwater around the world. This is especially poignant in arid and semi-arid regions, like the Middle East and North Africa (MENA) where water resources have been extremely limited historically. Today, water resources are declining due to a variety of factors, including climate change, population growth and changing food preferences. Research on this topic typically seeks to assess the impact of discreet alternative interventions in isolation. However, it is necessary to analyze the broader factors affecting agricultural water management as interconnected components of a complex water governance system within a specific geographic context. This research uses an exploratory, formative scenario planning approach to a) identify important adaptation strategies, b) use those adaptation strategies to construct a small set of coherent, plausible and diverse regional agricultural water governance scenarios, and c) analyze future scenarios of the Zayandehroud watershed in Iran in the year 2040. The research shares five scenarios that exemplify divergent adaptation and mitigation approaches to agriculture water demand in Zayandehroud watershed, including adhering to the status quo. Each scenario embodies different economic and political priorities to reveal how those priorities impact the ecological, social, and economic sustainability of this watershed. These scenarios provide insights into the long-term implications of near-term decisions about water and food security, resilience of local communities and the ecological integrity of the regional watershed. This research explores the conceptual relationships between components of the water governance system and demonstrates an approach to analyzing alternative constellations of factors that will impact agricultural water management. Policy-makers can make more effective policies if they consider how to transform the broader system of regional water governance, rather than only evaluating discrete agricultural water management projects on a project-by-project basis.

A foresight study on urban mobility: Singapore in 2040

PurposeThe transportation system in any city is complex and evolving, shaped by various driving forces and uncertainties in the social, economic, technological, political and environmental situations. Its development and demands upon it cannot be projected by simply extrapolating past and current trends. This paper aims to present a foresight study examining the future of urban mobility, focusing on the dense Asian city-state of Singapore. The objective is to develop scenarios for the future of urban mobility, to facilitate future policy implementation by highlighting long term challenges and opportunities for transportation planning in cities.Design/methodology/approachTo create future scenarios, the authors first sought to identify key drivers of change through environmental scanning, expert interviews, focus group discussions and technology scanning. These drivers of change were subsequently used in a scenario planning workshop, organized to co-create alternative future visions for urban mobility 2040 with experts and local stakeholders.FindingsTwo scenarios emerged, called the Shared World and the Virtual World. For each scenario, the authors described the key features in terms of dominant transport modes for the movements of passengers and freight. Subsequently, the authors discussed possible implications of each scenario to the individual, society, industry and government.Originality/valueAs cities grow and develop, city and transport planners should not only address daily operational issues but also develop a well-informed, long-term understanding of the evolving mobility system to address challenges that lie beyond the five- or even ten-year horizon. By using scenario planning approach, the authors hope to prepare stakeholders for the uncertain futures that are continuously shaped by the decisions today.

Reckoning construction cost overruns in building projects through methodological consequences

The construction cost is considered as the most important parameter to analyze the project success. It is essential to measure the variance from the budgeted cost to understand the cost impact on project performance and profitability. Though sufficient knowledge on cost overrun has been largely shared in the extant literature, it is not adequately explained why the cost overrun keeps occurring. Hence it is necessary to investigate the relationships among cost overrun factors to improve current construction cost and controlling practices. A conceptual framework is proposed based on causal mapping, systemic and scenario understandings. The traditional forecasting methods such as trend analysis, regression models are dependent on the history while predicting the future, whereas the scenario planning and cause mapping approach suggest the alternative for the future up comings and make ready for anticipating changes. With overwhelming statistical and cognitive significance, it is evident that the cost overrun risk indicators caution the project managers in the execution of building projects. From the findings of this study, decision-makers can act on early warnings of cost variances and commendably mitigate cost overruns. The findings are expected to bridge the gap in the current construction cost management practices.

Optimal design and planning of biodiesel supply chain network: a scenario-based robust optimization approach

Effective design of biodiesel supply chain network can reduce many of its high production costs. There are various uncertain parameters in real world that if ignored may greatly affect the optimal configuration of the designed biodiesel supply chain. Scenario planning is a powerful tool which can help the decision makers for long-term planning under uncertainties. Therefore, in this paper, a scenario-based robust optimization model is presented for designing the biodiesel supply chain networks under uncertainties. Some of the parameters including demand, supply, costs, and environmental impacts have uncertain nature. For the first time, in this study, the values of these uncertain parameters are estimated by a proposed scenario-planning method. The presented scenario-planning approach is based on cross-impact analysis and visualization methods. Non-edible sources such as Jatropha, Norouzak, and waste cooking oil are considered as raw materials of biodiesel production, and for the first time Norouzak has been used as one of the sources in designing biodiesel supply chain. In addition, an environmental constraint is considered and the environmental impacts of all processes are obtained by Eco-indicator 99 method. The presented model can determine the number, location, and capacity of the facilities. The proposed model is implemented in a real case study in Iran for a 7-year planning horizon. The results show the effectiveness of the presented approach in designing the biodiesel supply chain networks under uncertainties.

Future of beekeeping in Northwestern Ethiopia: Scenarios, local adaptation measures and its implications for farmers’ livelihoods

Abstract. Tassew A, Alemayehu G, Sölkner J, Wurzinger M. 2019. Future of beekeeping in Northwestern Ethiopia: Scenarios, local adaptation measures and its implications for farmers’ livelihoods. Biodiversitas 20: 1633-1643. For this study, a participatory scenario planning approach was used to understand the driving forces, generate the plausible future scenarios of beekeeping, explore local adaptation measures and its implications for farmers’ livelihoods in Northwestern Ethiopia. Data were collected from three watersheds representing different agro-ecological zones. To identify the driving forces, different methods including key informant interviews, focus group discussions, workshops, researchers observations and literature search were applied. The data were analyzed by ranking followed by controllability, cross-impact and consistency analysis. The results show that nineteen driving forces were identified that are contributes to changes in beekeeping. Out of nineteen six most relevant and locally controllable driving forces (watershed development, deforestation, agrochemicals use, government emphasis for beekeeping development, technical support, and farmers' awareness) were selected to develop different plausible and contrasting scenarios. The three plausible and contrasting scenarios for beekeeping in 2025 are: ‘‘repressive'', ‘‘beekeeping advance'' and ‘‘beekeeping on the margins''. The results show that beekeeping significantly contributes to the livelihoods of farmers to 2025 under ‘‘beekeeping advance'' scenario. In the ‘‘beekeeping on the margins'' scenario, beekeeping has low contribution to the livelihoods of farmers. But the beekeeping is in a system of involution in ‘‘repressive'' scenario and has very low contribution to the livelihoods of farmers. The stakeholders were checked the plausibility of the scenarios and selected the ‘‘repressive’’ scenario as the worst, the ‘‘beekeeping advance’’ scenario as the best, and the ‘‘beekeeping on the margins’’ scenario as the business as usual and intervention strategies were developed to transform the current beekeeping into ‘‘beekeeping advance'' scenario. The study has shown that the participation of stakeholders in the scenario planning process provides knowledge relevant for understanding the dynamics and future scenarios of beekeeping. Hence, interventions to be made by concerned stakeholders to improve the beekeeping in the study areas need to focus on addressing the various and complex driving forces through a system wide and context-specific approach.

Demand scenario planning approach using regression techniques and application to network sectors in Portugal

Abstract This paper aims to develop and apply an approach for short-, medium- and long-term scenario planning. Construction of water demand scenarios is of the utmost importance for planning, design and operation of distribution systems, providing useful information to promote more efficient use of water resources. The proposed approach offers a new perspective for water utilities to obtain coherent and plausible descriptive scenarios as well as realistic water demand projections. This approach was applied to network sectors in existing water distributions systems, using extensive network flow data. Descriptive scenarios for water demand, considering trends and the uncertainties of the future, were obtained, together with improved Multiple Linear Regression (MLR) models, with the inclusion of the key variable temperature and by using historical billed consumption, socio-demographic and infrastructure data. In addition, water demand projections for short- and long-term periods were obtained through the inclusion of future trends in the MLR models. Results from MLR models show enhanced empirical relations between water demand variables and water consumption key factors. This approach was validated using different distribution systems and the results have demonstrated the efficiency of the developed models for the projection of water demand.

Using a quantitative model for participatory geo-foresight: ISIS-Fish and fishing governance in the Bay of Biscay

This study investigated the use of a complex quantitative simulation model for participatory geo-foresight for the governance of the marine socio-ecosystem in the Bay of Biscay. The approach is simulation-based combining qualitative and quantitative expert-knowledge focusing on the demersal fishery in the Bay of Biscay. A three-stage approach was carried out : (i) translation by stakeholders of a narrative scenario drawn up during the geo-foresight into quantitative sub-scenarios that could be parameterized in ISIS-Fish; (ii) simulation with ISIS-Fish and study of the consequences of the sub-scenarios on the dynamics of the fishery; and (iii) participants feedback on the relevance of the model, on the possibility to detail the narrative scenario further and on the general contribution of ISIS-Fish to geo-foresight. The study created discussions on input data, mechanisms and spatial features of the model and on some limits of simplistic translations of the scenario. The model and simulations highlighted the relevance of using a spatial model to explore sub-scenarios derived from geo-foresight. The flexibility of ISIS-Fish and the synergy between the quantitative modeling and scenario planning approaches allowed for demystification of complex models for fisheries management and illustrated their potential for decision-making for fisheries management.

DESIGNING PRECINCTS IN THE DENSIFYING CITY – THE ROLE OF PLANNING SUPPORT SYSTEMS

Abstract. Australia’s cities face significant social, economic and environmental challenges, driven by population growth and rapid urbanisation. The pressure to increase housing availability will lead to greater levels of high-density and medium-density stock. However, there is enormous political and community pushback against this. One way to address this challenge is to encourage medium-density living solutions through “precinct” scale development. Precinct-scale development has the potential to include additional hard and soft infrastructure that may offset the perceived negativities of higher densities. As part of Australian research into precinct-scale development, and as part of our broader Smart Cities approach, or more specifically City Analytics approach, new digital planning tools – Envision and ESP – have been developed to support scenario planning and design needs. They utilise a data-driven and scenario planning approach underpinned by Geographic Information System (GIS) functionality.We focus on a case study in the City of Blacktown, Western Sydney, New South Wales, Australia. By 2036 Blacktown is forecast to grow to approximately 500,000 people (an increase of over 30 %) and 180,000 dwellings. Most new dwellings will be delivered through urban infill. The Blacktown master plan promotes higher density housing, mixed employment uses and continued improvements to the public domain. Our study provides a unique opportunity to implement this broad strategy within a specific case and location. Specifically, this paper provides information on how these digital planning tools supported Blacktown planners in identifying, co-designing and implementing a new approach for precinct level planning. It also presents the results of an evaluation of digital-planning tools in the context of the Blacktown case study.

Staging option application to residential development: real options approach

PurposeReal option valuation is capable of accounting for uncertainties in residential development projects but still lacks practical adoption due to limited evidence to support application of the theory in practice. The purpose of this paper is to use option valuation to value staging option embedded in residential projects and compare with results from DCF to determine which of the two methods delivers superior results.Design/methodology/approachThe fuzzy payoff method (FPOM), a real options model that uses scenario planning approach to generate a range of figures, from which a single-numerical value is computed for decision-making.FindingsThe results showed that the use of a range of figures was able to represent uncertainties to a higher degree of accuracy than the static DCF. As a result, the FPOM was able to capture about 3 per cent of the value of the project that was missed by the DCF. The staging option offers an opportunity to abandon unprofitable phases of a project, thereby limiting downside losses. Thus, real option models are practically applicable to cases in property sector.Practical implicationsResidential property developers must consider flexibility in financial feasibility evaluation of development because of the embedded value in uncertain property projects. It is important to account for optionality in financial evaluation of property projects for value maximisation.Originality/valueThe FPOM has been used for the first time to evaluate a horizontal phasing of a residential development project.

Cloning animals for tourism in the year 2070

What role do animals have in a future tourism world – in the year 2070? Contemplating over meat and fish delights on restaurant menus, hunting for sport and leisure purposes, and the presence of safaris and zoos have aspects in common, significantly animals are central to their existence and tourists are key consumers. Importantly, these pastimes, social activates, and leisurely pursuits have their ancestral roots that pre-date modern society. Humans have long been associated with eating meat, hunting animals and holding animals in some form of captivity for recreation and education. Distinctively, this paper explores animal cloning and how it could support the extension and existence of these tourism pursuits in the future, focusing on the year 2070. The paper applies a scenario planning approach as its methodological approach to research. The study contributes innovative and original concepts to the future tourism landscape. Through rigorous analysis and discussions in the fields of animal cloning and its relationship with tourism and tourists in potential future settings, a gap in the future market is presented. This research paper presents three scenarios in which cloning could support future tourism markets, Food tourism 2070: A Japanese restaurant perspective, Sport Hunting and tourism 2070: Designated hunting reserves in South Africa; and Safari-zoo tourism 2070: Into the Wild, cloning for education & conservation in the U.S.A. The paper offers interesting research for the futures field and tourism studies, offering scholars and industry with novel concepts for debating.

Multi-period maintenance planning for public buildings: A risk based approach for climate conscious operation

Improving the environmental performance of built environments has received wider interest in the recent past. Asset management is an under-utilized strategy to enhance and maintain desired environmental performance of a building at low life cycle costs (LCC). Current asset management decision-making methods are not fully capable of incorporating future technological changes and complex time sensitive environmental demands. There is a knowledge gap in incorporating factors such as environmental performance, risk and time sensitivity to foster dynamic asset management decision making. This paper presents a multi-period asset management method for public buildings to minimize LCC and attain climate action goals. A scenario planning approach is used to incorporate future changes in technologies, costs and organizational policies. Risk based prioritization is used to compare and select maintenance alternatives in a given period. Value at risk is used to identify the lowest risk capital planning strategy for an organization. The proposed approach was demonstrated using an operating aquatic centre building in British Columbia, Canada. Three possible future scenario were considered. Proposed method was used to develop multi-period maintenance plans for future scenarios. Based on the analysis, Great Transitions scenario is expected to achieve the least financial risk. The proposed approach enable capital asset planning by complying with changing climate action targets in a stochastic environment.

A new hybrid fuzzy cognitive map-based scenario planning approach for Iran's oil production pathways in the post–sanction period

In today's competitive dynamic world/markets, providing a desirable framework for exploring future perspectives is a crucial challenge to support robust decision making and proper policy making process. This research proposes a novel framework that develops plausible future energy scenarios through the Fuzzy Cognitive Map (FCM) technique. As a new method in scenario planning, FCM attempts to present a set of rational, reliable and credible scenarios together with analyzing dynamic behaviors of parameters. The integrated approach encompasses STEEP analysis to identify parameters, Cross Impact Analysis (CIA) to determine key drivers, Morphological analysis for scenario selection, and FCM to develop semi-quantitative scenarios. The new proposed scenario development approach brings the benefits of both quantitative and qualitative analysis together, which is not limited to the investigation of few pre-defined scenario drivers. As a research case, the proposed methodology was examined to detect plausible trends for Iran's oil production in the post-sanction era. The implemented FCM simulations indicated that in three scenarios oil production rises, as growth would be significant for the first two. The fourth projection is the most pessimistic future that can be imagined in the post-sanction era where the country faces massive investment backlogs.

Transport emissions in Beijing: a scenario planning approach

This paper explores and analyses how to reduce smog-related air pollutants and carbon dioxide emissions generated by passenger transport systems in Beijing. In-depth surveys with experts and practitioners in China are used to examine the current business-as-usual projection for emissions in Beijing, the drivers and trends affecting current projections, and to develop alternative scenarios that might help reduce projected emissions significantly. These are based around different variants of population and migration growth and environmental stewardship. Current levels of smog caused by transport emissions are much higher in Beijing than internationally accepted safety standards, partly because of high levels of motorised traffic. Carbon dioxide emissions always tend to be overlooked because economic growth is prioritised. The sustainable model represents one of the best models for Beijing to follow; however, Beijing faces major challenges in becoming more environmentally sustainable over the next few years, mainly due to population growth and increased migration, even if there is powerful top-down government environmental stewardship. The aspiration to reduce smog-related air pollutants and carbon dioxide emissions in Beijing by implementing sustainable transport mitigation measures seems very ambitious; however, it is perhaps in this context that the real innovations in transport planning will emerge.

Blending science and community voices for multi-scale disaster risk reduction and climate resilience: a participatory scenario planning approach

Climate change is a major development challenge to Ethiopia. Unless adaptation measures are widely implemented, climate change can set back development efforts and achievements by years. Recognizing this, the Government of Ethiopia (GoE) and civil society organizations have since recently been making considerable efforts to tackle the climate change problem. This paper documents the experience of CARE International in Ethiopia in facilitating bottom-up approaches to promote community-led disaster risk management and climate change adaptation planning through a participator scenario planning (PSP) methodology. PSP is a coordinated approach which leverages a variety of stakeholders' skills and mandates to explore potential climate change risks and their impacts, and then develop locally relevant and shared adaptation action plans that support livelihoods, social capital and ecosystem resilience. The approach has facilitated timely access to and communication of seasonal climate advisories which in turn is empowering communities to take advantage of opportunities that climate presents, which is a key part of adapting to climate change. The institutionalization of the approach by district and regional disaster prevention and food security coordination offices in the southern pastoral regions of Ethiopia encouraged integration of PSP into community livelihood adaptation and local government development planning, hence continuity of the process. Sustainability is expected to be fully achieved when local government planning processes recognize the importance of and provides resources for the participation of meteorological services and community forecasting experts to help refine plans on a seasonal basis, and for systems for dissemination of advisories. Key Words: Climate change, Disaster risk management, Pastoralism, Participatory scenario planning

Integrating electric vehicles and residential solar PV

This study compares the lifecycle costs and greenhouse gas (GHG) emissions of electric vehicle (EV) ownership to that of other popular and similar cars in Hawaii. It focuses on the interaction of EV costs with Hawaii's rapid solar PV uptake, using a scenario planning approach for future fuel and electricity prices. EVs include battery electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs). We find that the total cost of ownership (TCO) of EVs tends to be higher than their internal combustion engine vehicle (ICEV) or hybrid electric vehicle (HEV) counterparts. Once accounting for the federal tax credit, however, some EVs become relatively cost-effective. Moreover, access to residential solar PV makes EVs quite attractive. Layering the federal EV subsidy with solar PV charging makes the full lifecycle cost of the Nissan Leaf about $1200 less expensive than the next lowest cost vehicle, the Toyota Corolla (over a 150,000-mile lifetime). Nonetheless, it may be too early to tout EVs in Hawaii as a GHG abatement strategy. Based on today's mix of electricity generation, the best performing PHEV and BEV emit 2 and 5 MTCO2, respectively, more over their lifetime than the best performing HEV. However, many EVs become on par with the high performing HEVs when considering Hawaii's adoption of aggressive renewable energy goals for the electric sector. If the electric sector meets its 2030 Renewable Portfolio Standard (RPS) target of 40% renewables through low carbon sources like wind and solar, the Toyota Plug-in Prius, Nissan Leaf and Toyota Prius become comparable in terms of their GHG impacts. Integrating residential solar PV, even for just weekend charging, makes all EVs outperform the Toyota Prius in regards to lifetime GHG emissions. In addition, at this level of charging from renewable sources of electricity, all BEVs now outperform PHEVs. The environmental benefits of EVs depend critically on the electricity system from which they derive their power. Given the wide variation in the mix of electricity generation throughout the U.S., and even throughout the day with the adoption of intermittent sources of renewable energy, additional policy tools are needed to match places and times with high levels of renewables with EV charging. In particular, we suggest that 1) a regional approach to EV subsidies that can account for the emissions intensity of electricity systems may be more appropriate than the current blunt federal tax credit; and 2) adoption of time-of-use pricing that accounts for GHG impacts may be critical to supporting EVs as a GHG abatement tool. Currently, however, EVs are a relatively costly GHG abatement strategy.

A MOBILE COMPUTING TECHNOLOGY FORESIGHT STUDY WITH SCENARIO PLANNING APPROACH

Although the importance of mobile computing is gradually being recognized, mobile computing technology development and adoption have not been clearly realized. This paper focuses on the technology planning strategy for organizations that have an interest in developing or adopting mobile computing technology. By using scenario analysis, a technology planning strategy is constructed. In this study, thirty mobile computing technologies are classified into six groups, and the importance and risk factors of these technologies are then evaluated under two possible scenarios. The main research findings include the discovery that most mobile computing software technologies are rated high to medium in importance and low risk in both scenarios, and that scenario changes will have less impact on mobile computing devices and on mobile computing software technologies. These results provide a reference for organizations interested in developing or adopting mobile computing technology. To cite this document: Wei-Hsiu Weng and Woo-Tsong Lin, A mobile computing technology foresight study with scenario planning approach, International Journal of Electronic Commerce Studies, Vol.6, No.2, pp.223-232, 2015. Permanent link to this document: http://dx.doi.org/10.7903/ijecs.1242 Â

A Hybrid Scenario Planning Methodology for Interactive Digital Media

In this article, we present a scenario planning approach that is a hybrid of three main schools of thought. We propose such an approach in order to develop scenarios for a contemporary, technology-driven and fast-moving industry such as Interactive Digital Media. Our approach, while essentially qualitative in nature, nevertheless draws from the rigors of quantitative methods in identifying and then tracking the significant Dimensions of Analysis that impact the industry. The capture and analysis of real-time events was automated by an off-the-shelf web crawler with analytic functions, thus making our approach scalable over a larger scope and for longer periods of time. A morphological technique using Multidimensional Scaling isolated strands within the events leading to the identification of trends. This was followed by the mapping of strands to three emergent themes — ownership, distribution and innovation — which were used in an expert construction exercise to formulate plausible scenarios. We suggest that the approach we describe is particularly applicable for dynamic scenario planning that requires revisiting key assumptions and market conditions on a regular basis. We conclude that the ability to develop strategic narratives is the overriding benefit of scenario planning rather than the purported ability to predict the future.

A scenario planning approach for propositioning rescue centers for urban waterlog disasters

An urban waterlog disaster can produce severe results, such as residents’ property loss, environmental damages and pollution, and even casualties. This paper presents a system specification for urban waterlog disasters according to the analysis of urban waterlog disaster risks. Then, a two-stage stochastic mixed-integer programming model is formulated. The model minimizes the total logistics cost, and risk-induced penalties. Moreover, a deterministic counterpart of the stochastic model is proposed to study the expected value of perfect information. The multi-attribute utility theory is used to build assessment functions that assess the utility of the rescue system and the degree contributed to disaster relief for each rescue center. Finally, a real example of rescue logistics is examined for the urban waterlog disasters in Pudong District of Shanghai, China. Using the proposed model, two main results can be obtained. First, the expected value of perfect information experiment reveals that an additional ¥45,005 logistics cost and an additional ¥2417 risk-induced penalties can be incurred due to the presence of uncertainty. Second, as the weight of risk-induced penalty increases from 0.1 to 0.9, the logistics cost is increased by 41.21%, which thus contributes to a decrease of risk-induced penalty by 97.44%. Some managerial implications are discussed based on the numerical studies.