Decision Support Tool For Policy Makers Research Articles

Designing Efficient and Equitable Freight Services Markets for Sustainable Economic Performance

Despite the indispensability of freight trucking services and truckers’ role as critical stakeholders in supply chains, relatively little attention has been paid to analyzing small independent truckers’ roles. Shippers often prefer working with larger trucking companies to the detriment of smaller independent truckers, who must grapple with an inherently disadvantageous job market. Furthermore, in the presence of uncertainty or peak demand periods, trucker shortages can pose significant economic challenges for shippers and downstream customers. In this paper, we propose an analytical framework to address these challenges in efforts to enhance the sustainability of the freight service industry. We formulate and solve a weighted bi-objective optimization model that simultaneously maximizes the total profits of both shippers and truckers to design a sustainable freight services market. Further, we leverage Monte Carlo simulation trials to examine how all players in this market can achieve a better solution under uncertainty. Ultimately, after evaluating multiple scenarios, we find that shippers and truckers yield the highest economic benefits under a balanced design that leverages principles of supply chain coordination, while satisfying all demand from shippers. This framework can serve as a decision support tool for policymakers who aim to ensure all stakeholders in the market can become and remain profitable. Based on our findings, this study suggests practical implications on how to consider humanitarian policies aimed at promoting equity for truckers and ensuring the timely shipment of essential products for both shippers and truckers.

Ranking Canadian waste management system efficiencies using three waste performance indicators.

Three waste management system (WMS) efficiency indicators are adopted to systematically assess WMS efficiency in Canada from 1998 to 2016. The study objectives are to examine the temporal changes in waste diversion activities and rank the performance of the jurisdictions using a qualitative analytical framework. Increasing Waste Management Output Index (WMOI) trends were identified in all jurisdictions, and more government subsidiaries and incentive packages are recommended. With the exception of Nova Scotia, statistically significant decreasing diversion gross domestic product (DGDP) ratio trends are observed. It appears that the increases in GDP from Sector 562 were not contributing to waste diversion. On average, Canada spent about $225/tonne of waste handled during the study period. Current spending per tonne handled (CuPT) trends are decreasing, with S ranging from + 5.15 to + 7.67. It appears that WMSs in Saskatchewan and Alberta are more efficient. The results suggest that the use of diversion rate alone to evaluate WMS may be misleading. The findings help the waste community to better understand the trade-offs between various waste management alternatives. The proposed qualitative framework utilizing comparative rankings is applicable elsewhere and can be a useful decision support tool for policy-makers.

Negotiating a Future that is not like the Past

ABSTRACT Agent-based models combine data and theory during both development and use of the model. As models have become increasingly data driven, it is easy to start thinking of agent-based modelling as an empirical method, akin to statistical modelling, and reduce the role of theory. We argue that both types of information are important where the past is not a reliable blueprint for the future, which occurs when modelling dynamic complex systems or to explore the implications of change. By balancing theory and data, agent-based modelling is a tool to describe plausible futures, that we call ‘justified stories’. We conclude that this balance must be maintained if agent-based models are to serve as a useful decision support tool for policymakers.

A decision-support tool for policy makers in healthcare supply chains to balance between perceived risk in logistics outsourcing and cost-efficiency

In recent years, governments are increasingly interested in developing public–private partnerships such as outsourcing logistics to service providers to benefit from better performance. A major obstacle to developing such partnerships is the lack of decision-support tools to investigate supply chain and outsourcing decisions, taking into account perceived risk that arises from such partnerships. This paper develops a decision-support tool for policy makers to quantify perceived risk and jointly optimize network design and logistics outsourcing. It is based on a multi-phase approach which quantifies perceived risk as a function of outsourcing decisions using policy makers judgment, solves a multi-objective optimization problem, and constructs efficient frontiers that balance total supply chain cost and perceived risk. The proposed approach is applied to the real case study of the Moroccan supply chain of pharmaceuticals. Several outsourcing strategies are investigated and corresponding efficient frontiers are constructed. Our analysis shows that outsourcing cost-efficiency and the degree of perceived risk have a great impact on the optimal distribution network design and outsourcing strategies.

Oil price fluctuations and economic growth: the case of MENA countries

PurposeThis paper aims to explore the extreme effect of crude oil price fluctuations and its volatility on the economic growth of Middle East and North Africa (MENA) countries. It also investigates the asymmetric and dynamic relationship between oil price and economic growth. Further, a separate analysis for each MENA oil-export and oil-import countries is conducted. Furthermore, it studies to what extent the quality of institutions will change the effect of oil price fluctuations on economic growth.Design/methodology/approachAs the effect of oil price fluctuations is not the same over different business cycles or oil price levels, the paper uses a panel quantile regression approach with other linear models such as fixed effects, random effects and panel generalized method of moments. The panel quantile methodology is an extension of traditional linear models and it has the advantage of exploring the relationship over the different quantiles of the whole distribution.FindingsThe paper can summarize results as following: changes in oil price and its volatility have an opposite effect for each oil-export and oil-import countries; for the former, changes in oil prices have a positive impact but the volatility a negative effect. While for the latter, changes in oil prices have a negative effect but volatility a positive effect. Further, the impact of oil price changes and their uncertainty are different across different quantiles. Furthermore, there is evidence about the asymmetric effect of the oil price changes on economic growth. Finally, accounting for institutional quality led to a reduction in the impact of oil price changes on economic growth.Originality/valueThe study concludes more detailed results on the impact of oil prices on gross domestic product growth. Thus, it can be used as a decision-support tool for policymakers.

Intervention Scalability Assessment Tool: A decision support tool for health policy makers and implementers

BackgroundPromising health interventions tested in pilot studies will only achieve population-wide impact if they are implemented at scale across communities and health systems. Scaling up effective health interventions is vital as not doing so denies the community the most effective services and programmes. However, there remains a paucity of practical tools to assess the suitability of health interventions for scale-up. The Intervention Scalability Assessment Tool (ISAT) was developed to support policy-makers and practitioners to make systematic assessments of the suitability of health interventions for scale-up.MethodsThe ISAT was developed over three stages; the first stage involved a literature review to identify similar tools and frameworks that could be used to guide scalability assessments, and expert input to develop draft ISAT content. In the second stage, the draft ISAT tool was tested with end users. The third stage involved revising and re-testing the ISAT with end users to further refine the language and structure of the final ISAT.ResultsA variety of information and sources of evidence should be used to complete the ISAT. The ISAT consists of three parts. Part A: ‘setting the scene’ requires consideration of the context in which the intervention is being considered for scale-up and consists of five domains, as follows: (1) the problem; (2) the intervention; (3) strategic/political context; (4) evidence of effectiveness; and (5) intervention costs and benefits. Part B asks users to assess the potential implementation and scale-up requirements within five domains, namely (1) fidelity and adaptation; (2) reach and acceptability; (3) delivery setting and workforce; (4) implementation infrastructure; and (5) sustainability. Part C generates a graphical representation of the strengths and weaknesses of the readiness of the proposed intervention for scale-up. Users are also prompted for a recommendation as to whether the intervention (1) is recommended for scale-up, (2) is promising but needs further information before scaling up, or (3) does not yet merit scale-up.ConclusionThe ISAT fills an important gap in applied scalability assessment and can become a critical decision support tool for policy-makers and practitioners when selecting health interventions for scale-up. Although the ISAT is designed to be a health policy and practitioner tool, it can also be used by researchers in the design of research to fill important evidence gaps.

Development of Land-Use/Land-Cover Maps Using Landsat-8 and MODIS Data, and Their Integration for Hydro-Ecological Applications

The Athabasca River watershed plays a dominant role in both the economy and the environment in Alberta, Canada. Natural and anthropogenic factors rapidly changed the landscape of the watershed in recent decades. The dynamic of such changes in the landscape characteristics of the watershed calls for a comprehensive and up-to-date land-use and land-cover (LULC) map, which could serve different user-groups and purposes. The aim of the study herein was to delineate a 2016 LULC map of the Athabasca River watershed using Landsat-8 Operational Land Imager (OLI) images, Moderate Resolution Imaging Spectroradiometer (MODIS)-derived enhanced vegetation index (EVI) images, and other ancillary data. In order to achieve this, firstly, a preliminary LULC map was developed through applying the iterative self-organizing data analysis (ISODATA) clustering technique on 24 scenes of Landsat-8 OLI. Secondly, a Terra MODIS-derived 250-m 16-day composite of 30 EVI images over the growing season was employed to enhance the vegetation classes. Thirdly, several geospatial ancillary datasets were used in the post-classification improvement processes to generate a final 2016 LULC map of the study area, exhibiting 14 LULC classes. Fourthly, an accuracy assessment was carried out to ensure the reliability of the generated final LULC classes. The results, with an overall accuracy and Cohen’s kappa of 74.95% and 68.34%, respectively, showed that coniferous forest (47.30%), deciduous forest (16.76%), mixed forest (6.65%), agriculture (6.37%), water (6.10%), and developed land (3.78%) were the major LULC classes of the watershed. Fifthly, to support the data needs of scientists across various disciplines, data fusion techniques into the LULC map were performed using the Alberta merged wetland inventory 2017 data. The results generated two useful maps applicable for hydro-ecological applications. Such maps depicted two specific categories including different types of burned (approximately 6%) and wetland (approximately 30%) classes. In fact, these maps could serve as important decision support tools for policy-makers and local regulatory authorities in the sustainable management of the Athabasca River watershed.

A new classification of European Union regions: A decision support tool for policymakers

The classification of agricultural and territorial systems is essential to improve the comparability of regions for the development programmers of the Common Agricultural Policy (CAP), to give new tools of intervention to policymakers and to increase farmers’ knowledge. Analysis of the principal characteristics of these systems is essential during a time in which the new CAP is being designed for the period 2021-2027. The research is focused on the analysis of the agricultural features of 228 regional areas (NUTS 2) of the 28 European Union (EU) countries. It considers two specific sets of environmental and socio-economic indicators provided by the Farm Accountancy Data Network (FADN). The main factors that differentiate agricultural systems in EU regions from one another were identified with the application of principal component analysis, while the classification of the same regions in homogeneous groups was carried out through hierarchical cluster analysis. The results clearly show that some groups of “homogeneous” EU regions such as the Natura 2000 area and the family-run agricultural system, which have weaker agricultural structures than the average of the 228 EU regions considered in this study, have a greater need for the restructuring of their agricultural systems than others (e.g., the professional agricultural system and the food industry system). The results confirm that policy design should not consider EU agriculture as a whole, but should take into account the environmental and structural specificities of agricultural holdings, as well as the different training levels of farm managers.

Urbanisation and its effect on risk factors associated with childhood diarrhoea in Mbour, Senegal: A visualisation.

Rapid urbanisation, particularly in secondary cities in Africa, brings along specific challenges for global health, including the prevention and control of infectious diseases such as diarrhoea. Our purpose was to visualise urbanisation trends and its effect on risk factors associated with childhood diarrhoea, e.g. water supply, sanitation, wastewater and solid waste management in Mbour, a secondary city in south-western Senegal. Our visualisation is facilitated by epidemiological and geographical surveys carried out in 2016. A deeper spatial and visual understanding of the urbanisation trends and the disparities of diarrhoea-associated risk factors might lead to the implementation of suitable health interventions and preventive measures. Our visualisation is aimed to serve as a basis for discussion and as a decision support tool for policymakers, municipal officials and local communities to prioritise interventions related to water, sanitation and waste management with a view to reduce the environmental and health risks in the rapidly growing city of Mbour, which is set as an example for other similar secondary cities across low- and middle-income countries in Africa.

Traveler satisfaction in rapid rail systems: The case of Istanbul metro

ABSTRACTMultifaceted characteristics of urban travel have an impact on the passengers' overall satisfaction with the transport system. In this study, we investigate the interrelationships among traveler satisfaction, travel and traveler characteristics, and service performance in a multimodal network that comprises of a trunk line and its feeder lines. We analyze the factors influencing the choices of access to rail transit stations and the satisfaction of transit travelers with the rapid rail transit systems. We quantitatively study these relationships and demonstrate the complexity of evaluating transit service performance. Since the interrelationships among variables affecting this system are mainly stochastic, we analyze the satisfaction with transit system problem using a Bayesian Belief Network (BBN), which helps capture the causality among variables with inherent uncertainty. Using the case of Istanbul, we employ the BBN as a decision support tool for policy-makers to analyze the rapid rail transit services and determine policies for improving the quality and the level of service to increase the satisfaction with transit system. In the case study, satisfaction with accessibility and access mode variables are found to be more effective variables than total travel time for travel time satisfaction, confirming the significant role of access in multimodal travels.

Exploring the interaction between competitiveness of a country and innovation using Bayesian networks

ABSTRACTInnovation cannot be related only to some factors inherent in the environment of a country, nor is it a single entity to be managed without any linkages to the rest of the actors comprising the competitiveness of a country. World Economic Forum (WEF)’s competitiveness model consisting of 12 pillars and 19 sub-pillars is an attempt along these lines. By analysing the interaction between the Innovation pillar and the remaining 11 pillars and their sub-pillars comprising the competitiveness indicators, this paper aims to provide strategic guidelines to policy-makers who search for strategies to improve their country’s innovativeness level. For this purpose, WEF’s Global Competitiveness Index data for the period (2009-2012) is employed. The innovation performance of 148 countries is analysed using an integrated cluster analysis and a Bayesian Network (BN) framework. The use of BNs enables us to discover the probabilistic dependency structure of competitiveness indicators and its innovation performance, which may be analysed in more detail through evidence observation and sensitivity analyses conducted in the network. Thus, with this research, presenting the multidimensional nature between competitiveness indicators and Innovation, a decision support tool for policy-makers is presented, which can be used to form strategy guidelines for enhancing a country’s Innovation level.

A decision-support tool to inform Australian strategies for preventing suicide and suicidal behaviour.

Dynamic simulation modelling is increasingly being recognised as a valuable decision-support tool to help guide investments and actions to address complex public health issues such as suicide. In particular, participatory system dynamics (SD) modelling provides a useful tool for asking high-level 'what if' questions, and testing the likely impacts of different combinations of policies and interventions at an aggregate level before they are implemented in the real world. We developed an SD model for suicide prevention in Australia, and investigated the hypothesised impacts over the next 10 years (2015-2025) of a combination of current intervention strategies proposed for population interventions in Australia: 1) general practitioner (GP) training, 2) coordinated aftercare in those who have attempted suicide, 3) school-based mental health literacy programs, 4) brief-contact interventions in hospital settings, and 5) psychosocial treatment approaches. Findings suggest that the largest reductions in suicide were associated with GP training (6%) and coordinated aftercare approaches (4%), with total reductions of 12% for all interventions combined. This paper highlights the value of dynamic modelling methods for managing complexity and uncertainty, and demonstrates their potential use as a decision-support tool for policy makers and program planners for community suicide prevention actions.

Measuring and monitoring energy access: Decision-support tools for policymakers in Africa

A significant number of African States have adapted energy access targets. In evaluating progress towards these goals, measuring and monitoring energy access becomes relevant. This paper reviews energy access indicators and identifies their utility and challenges in their application. By focusing on Africa, a broader framework for energy access measurement and monitoring is discussed, along with implementation barriers and potential solutions. To demonstrate the utility of energy access decision-support tool in Africa, a scenario analysis in five regional energy pools is conducted using the Energy Spending Model tool. Institutionalizing monitoring and decision-support tools can provide valuable feedback to policymakers aiming to design and implement effective energy access programs serving a growing population in Africa.

Optimising reverse logistics network to support policy-making in the case of Electrical and Electronic Equipment

Due to the rapid growth of Waste Electrical and Electronic Equipment (WEEE) volumes, as well as the hazardousness of obsolete electr(on)ic goods, this type of waste is now recognised as a priority stream in the developed countries. Policy-making related to the development of the necessary infrastructure and the coordination of all relevant stakeholders is crucial for the efficient management and viability of individually collected waste. This paper presents a decision support tool for policy-makers and regulators to optimise electr(on)ic products’ reverse logistics network. To that effect, a Mixed Integer Linear Programming mathematical model is formulated taking into account existing infrastructure of collection points and recycling facilities. The applicability of the developed model is demonstrated employing a real-world case study for the Region of Central Macedonia, Greece. The paper concludes with presenting relevant obtained managerial insights.