Ranking Of Options Research Articles

Analysis of Financial Performance of Cement Industry Manufacturing Companies in Tehran Stock Exchange Using the FAHP Technique and the TOPSIS Method

ObjectiveThe aim of this study was to provide a fuzzy model for evaluating the performance of cement industry manufacturing companies listed in Tehran Stock Exchange in 2013, 2014 and 2015 using financial ratios and considering the preferences of different decision makers.MethodologyThis study was based on FAHP and TOPSIS, in which the FAHP was used to determine the weight of different criteria of the decision makers. Finally, the cement industry companies were ranked using the TOPSIS approach. In this study, different financial ratios such as liquidity ratios, leverage ratios, activity ratios, profitability ratios, and growth ratios were used for evaluation.Results & FindingsEleven findings and nineteen results were presented that three Soufian Cement Company, Ghadir Capital and Industry Development Cement Company, and Hegmatan Cement Company from Three East Azarbaijan, Tehran, and Hamedan provinces and from three different geographic regions of Iran have had the most similarity with the ideal solution in the ranking of options (alternatives) by the TOPSIS method. Also, in the light of core values and by maintaining their market share and competent corporate governance, they have gained the highest output of the cement industry by obtaining the first rank respectively in 2013, 2014, and 2015, which, in turn, can be a good representative of the country's cement industry. By modeling the top companies and with the help of science along with analyzes in other sectors of the cement industry, the firms with weaker performance can strengthen their performance. This can become a strong strength for the Iranian cement industry.

An investigation into the relationship between quality of life of the elderly in relation to physical spaces in order to select an ideal residence

The purpose of this research is first to discover and study the design factors associated with increasing quality of life of the elderly in the physical residential spaces and, then, to assess and select the best housing option meeting the needs of the elderly (nursing home, private home, elderly village) in Iran. This study is an applied survey. A researcher-made questionnaire was distributed among 150 elderly to determine quality of life indicators in relation to physical spaces. Then, the relative importance of each indicator in relation to elderly housing options was determined using AHP technique and distribution of the questionnaire among experts. The statistical population in the second stage of research was 35 experts in the field of architecture, rehabilitation, medicine, and nursing which were selected in a non-random purposive manner. In this research, the five main factors of educational and encouraging spaces, environmental desirability and comfort, personal peace and quiet, perception of ownership, and home likeness were identified in relation to the design of physical spaces to increase quality of life of the elderly. The results of the ranking of options based on these five factors indicated that the nursing home ranked first in increasing quality of life of the elderly based on its final weight.

Ranking of options of real estate use by expert assessments mathematical processing

The article is devoted to the development of the real estate assessment concept. In conditions of multivariate using of the real estate method based on calculating, the integral indicator of each variant’s efficiency is proposed. In order to calculate weights of criteria of the efficiency expert method, Analytic hierarchy process and its mathematical support are used. The method allows fulfilling ranking of alternative types of real estate use in dependence of their efficiency. The method was applied for one of the land parcels located on Primorsky district in Saint Petersburg.

Socioeconomic and ecological perceptions and barriers to urban tree distribution and reforestation programs

Tree planting and reforestation initiatives in urban and peri-urban areas often use tree distribution or “giveaway” programs as a strategy to increase tree cover and subsequent benefits. However, the effectiveness of these programs in terms of increasing overall tree cover and providing benefits to low-income and disadvantaged communities has been little studied. We assess these programs by exploring community participation in, and barriers to, an urban tree distribution program in Fort Lauderdale, United States and the role socioeconomic background and tree functional types have on participation. We use a mixed-methods approach, panel data, choice experiments, and econometrics to quantitatively analyze respondent’s ranking of program options. High income, White respondents had the highest level of awareness and participation while low income, African Americans (AA) had the lowest level. Monetary rebates were perceived as positive and significant as the compensation value increased to US$8.00 - $12.00. Fruit-bearing and native tree functional types were more preferred than flowering or shade trees. Latinos, AA, and high income respondents preferred fruit trees, while White, high income preferred native trees. Overall, low income respondents perceived the greatest barriers towards participation. 20% of Broward County residents who participated in the survey were aware of the tree giveaway programs and 13% had previously participated. Findings indicate an adaptive governance mismatch between program objectives to equitably increase city tree cover via planting shade trees versus individual’s knowledge and preference for other tree types and functions. Results can be used for developing and evaluating reforestation initiatives to equitably increase tree cover and improve the governance of urban ecosystems.

Comparing modeling approaches for assessing priorities in international agricultural research.

This article examines how the estimated impacts of crop technologies vary with alternate methods and assumptions, and also discusses the implications of these differences for the design of studies to inform research prioritization. Drawing on international potato research, we show how foresight scenarios, realized by a multi-period global multi-commodity equilibrium model, can affect the estimated magnitudes of welfare impacts and the ranking of different potato research options, as opposed to the static, single-commodity, and country assumptions of the economic surplus model which is commonly used in priority setting studies. Our results suggestthatthe ranking oftechnolo- gies is driven by the data used for their specification and is not affected by the foresight scenario examined. However, net benefits vary significantly in each scenario and are greatly overestimated when impacts on non-target countries are ignored. We also argue that the validity of the singlecommodity assumption underpinning the economic surplus model is case-specific and depends on the interventions examined and on the objectives and criteria included in a priority setting study.

Utilization of Multi Attribute Decision Making Techniques to Integrate Automatic and Manual Ranking of Options

An information fusion system with local sensors sometimes requires the capability to represent the temporal changes of uncertain sensory information in dynamic and uncertain situation to access to a hypothesis node which cannot be observed directly. One of the central issue and challenging problem is the decision of what combination and order of sensors allocation should be selected between sensors, in order to maximize the global gain in the flow of information, when the data association is limited. In this area, Bayesian Networks (BNs) can constitute a coherent fusion structure and introduce different options (the combination of sensors allocation) for achieving to the hypothesis node through a number of intermediate nodes that are interrelated by cause and effect. BNs can rank the options in terms of their probabilities from Bayes' theorem calculation. But, decision making based on probabilities and numerical representations might not be appropriate. Thus, re-ranking the set of options based on multiple criteria such as those of multi-criteria decision aid (MCDA) should be ideally considered. Re-ranking and selecting the appropriate options are considered as a multi-attribute decision making (MADM) problem by user interaction as semi-automatically decision support. In this paper, Multi Attribute Decision Making (MADM) techniques as TOPSIS, SAW, and Mixed (Rank Average) for decision-making as well as AHP and Entropy for obtaining the weights of attributes have been used. Since MADM techniques give most probably different results according to different approaches and assumptions in the same problem, statistical analysis done on them. According to the results, the correlation between compared techniques for re-ranking BN options is strong and positive because of the close proximity of weights suggested by AHP and Entropy. Mixed method as compared to TOPSIS and SAW is the preferred technique when there is no historical (real) decision- making case; moreover, AHP is more acceptable than Entropy for weighting.

Comparison and Screening of Nuclear Fuel Cycle Options in View of Sustainable Performance and Waste Management

Is it true that a nuclear technology approach to generate electric energy offers a clean, safe, reliable and affordable, i.e., sustainable option? In principle yes, however a technology impact on the environment strongly depends on the actual implementation bearing residual risks due to technical failures, human factors, or natural catastrophes. A full response is thus difficult and can be given first when the wicked multi-disciplinary issues get well formulated and “resolved”. These problems are lying at the interface between: the necessary R&D effort, the industrial deployment and the technology impact in view of the environmental sustainability including the management of produced hazardous waste. As such, this problem is clearly of multi-dimensional nature. This enormous complexity indicates that just a description of the problem might cause a dilemma. The paper proposes a novel holistic approach applying Multi-Criteria Decision Analysis to assess the potential of nuclear energy systems with respect to a sustainable performance. It shows how to establish a multi-level criteria structure tree and examines the trading-off techniques for scoring and ranking of options. The presented framework allows multi-criteria and multi-group treatment. The methodology can be applied to support any pre-decisional process launched in a country to find the best nuclear and/or non-nuclear option according to national preferences and priorities. The approach addresses major aspects of the environmental footprint of nuclear energy systems. As a case study, advanced nuclear fuel cycles are analyzed, which were previously investigated by the Nuclear Energy Agency (NEA/OECD) expert group WASTEMAN. Sustainability facets of waste management, resource utilization and economics are in focus.

A New Hybrid Decision Making Framework for Prioritising Port Performance Improvement Strategies

ABSTRACT This study aims to propose a conceptual decision making framework for prioritising port performance improvement strategies. It can be achieved by the concepts of benchmarking-best practices using analytic hierarchy process (AHP) incorporating a fuzzy technique for order preference by similarity to ideal solution (FTOPSIS) method. The leading performer (i.e. Busan New Port) and the poor performer (i.e. Busan North Port) are analysed as real cases to demonstrate the feasibility of the proposed methodology. The findings from the case study reveal that the terminal operating company (TOC) 2 represents a strong desire to choose the given strategies to improve its performance, followed by TOC3, while TOC1 has the least intention to adopt the given strategies. Amongst the 30 strategies of a benefit feature, optimisation of yard stacking planning (S4) is ascertained as the most crucial one to be implemented, followed by optimisation of berth to yard operations (S27) and optimising crane availability (S2). On the other hand, the formal training/education programmes from external professionals (S7) is identified as the most useful strategy among the 8 cost items. The results yielded by the framework present the ranking of strategy options in terms of their preference to different TOCs, which enables decision makers to find optimal solutions to improve performance under their own dynamic business environments.

On the Ground or in the Air? A Methodological Experiment on Crop Residue Cover Measurement in Ethiopia

Maintaining permanent coverage of the soil using crop residues is an important and commonly recommended practice in conservation agriculture. Measuring this practice is an essential step in improving knowledge about the adoption and impact of conservation agriculture. Different data collection methods can be implemented to capture the field level crop residue coverage for a given plot, each with its own implication on survey budget, implementation speed and respondent and interviewer burden. In this paper, six alternative methods of crop residue coverage measurement are tested among the same sample of rural households in Ethiopia. The relative accuracy of these methods are compared against a benchmark, the line-transect method. The alternative methods compared against the benchmark include: (i) interviewee (respondent) estimation; (ii) enumerator estimation visiting the field; (iii) interviewee with visual-aid without visiting the field; (iv) enumerator with visual-aid visiting the field; (v) field picture collected with a drone and analyzed with image-processing methods and (vi) satellite picture of the field analyzed with remote sensing methods. Results of the methodological experiment show that survey-based methods tend to underestimate field residue cover. When quantitative data on cover are needed, the best estimates are provided by visual-aid protocols. For categorical analysis (i.e., >30% cover or not), visual-aid protocols and remote sensing methods perform equally well. Among survey-based methods, the strongest correlates of measurement errors are total farm size, field size, distance, and slope. Results deliver a ranking of measurement options that can inform survey practitioners and researchers.

Essential information: Uncertainty and optimal control of Ebola outbreaks

Early resolution of uncertainty during an epidemic outbreak can lead to rapid and efficient decision making, provided that the uncertainty affects prioritization of actions. The wide range in caseload projections for the 2014 Ebola outbreak caused great concern and debate about the utility of models. By coding and running 37 published Ebola models with five candidate interventions, we found that, despite this large variation in caseload projection, the ranking of management options was relatively consistent. Reducing funeral transmission and reducing community transmission were generally ranked as the two best options. Value of information (VoI) analyses show that caseloads could be reduced by 11% by resolving all model-specific uncertainties, with information about model structure accounting for 82% of this reduction and uncertainty about caseload only accounting for 12%. Our study shows that the uncertainty that is of most interest epidemiologically may not be the same as the uncertainty that is most relevant for management. If the goal is to improve management outcomes, then the focus of study should be to identify and resolve those uncertainties that most hinder the choice of an optimal intervention. Our study further shows that simplifying multiple alternative models into a smaller number of relevant groups (here, with shared structure) could streamline the decision-making process and may allow for a better integration of epidemiological modeling and decision making for policy.

Eliciting Structured Knowledge from Situated Crowd Markets

We present a crowdsourcing methodology to elicit highly structured knowledge for arbitrary questions. The method elicits potential answers (“options”), criteria against which those options should be evaluated, and a ranking of the top “options.” Our study shows that situated crowdsourcing markets can reliably elicit/moderate knowledge to generate a ranking of options based on different criteria that correlate with established online platforms. Our evaluation also shows that local crowds can generate knowledge that is missing from online platforms and on how a local crowd perceives a certain issue. Finally, we discuss the benefits and challenges of eliciting structured knowledge from local crowds.

Voting Advice Applications and Electoral Participation: A Multi-Method Study

Voting Advice Applications (VAAs) help users casting a vote by offering an explicit ranking of viable options. The wide amount of readily available information provided by VAAs to users has been shown to contribute to reducing the transactional costs involved in gathering relevant political information. Available evidence also supports the idea that VAA users are more likely to cast a ballot in elections as a result. The extent to which electoral participation is caused by using a VAA, however, remains unclear. Against this background, we reassess the mobilizing effect of VAAs by means of a multi-method approach. Our cross-sectional analysis of 12 national election study data sets provides further support to the idea that VAA usage increases users’ chances of casting a ballot in elections as compared to non-users. This conclusion is strengthened by the results of a randomized field experiment conducted in the context of the 2013 Italian parliamentary election.

Nuclear Waste Management Decision-Making Support with MCDA

The paper proposes a multicriteria decision analysis (MCDA) framework for a comparative evaluation of nuclear waste management strategies taking into account different local perspectives (expert and stakeholder opinions). Of note, a novel approach is taken using a multiple-criteria formulation that is methodologically adapted to tackle various conflicting criteria and a large number of expert/stakeholder groups involved in the decision-making process. The purpose is to develop a framework and to show its application to qualitative comparison and ranking of options in a hypothetical case of three waste management alternatives: interim storage at and/or away from the reactor site for the next 100 years, interim decay storage followed in midterm by disposal in a national repository, and disposal in a multinational repository. Additionally, major aspects of a decision-making aid are identified and discussed in separate paper sections dedicated to application context, decision supporting process, in particular problem structuring, objective hierarchy, performance evaluation modeling, sensitivity/robustness analyses, and interpretation of results (practical impact). The aim of the paper is to demonstrate the application of the MCDA framework developed to a generic hypothetical case and indicate how MCDA could support a decision on nuclear waste management policies in a “small” newcomer country embarking on nuclear technology in the future.

Ranking of Office-lease Options by Multi-criteria Methods

Due to the growing scales of business and internationalisation, the issue of the office lease is becoming more and more relevant for companies [1,2]. They are becoming an inherent part of business, on which the results of the commercial activity depend. Current methodologies for the assessment of the office-lease options are imperfect as they lack complexity; they are not associated with the objective of the lease, i.e. the improvement of business results; the methods of the quantitative assessment of lease options are far from perfect. The paper aims to formulate the hierarchical indicator system of commercial real estate facilities (offices) adjusted to the multi-criteria assessment and to calculate lease options based on this indicator system. To achieve this goal, the following methods have been used: scientific literature analysis and multi-criteria assessment methods.

Rank-order concordance among conflicting emissions estimates for informing flight choice

Air transport Greenhouse Gas (GHG) emissions estimates differ greatly, depending on the calculation method employed. Among the IPCC, ICAO, DEFRA, and BrighterPlanet calculation methods, the largest estimate may be up to 4.5 times larger than the smallest. Such heterogeneity – and ambiguity over the true estimate – confuses the consumer, undermining the credibility of emissions estimates in general. Consequently, GHG emissions estimates do not currently appear on the front page of flight search-engine results. Even where there are differences between alternative flights’ emissions, this information is unavailable to consumers at the point of choice. When external considerations rule out alternative travel-modes, the relative ranking of flight options’ GHG emissions is sufficient to inform consumers’ decision making. Whereas widespread agreement on a gold standard remains elusive, the present study shows that the principal GHG emissions calculation methods produce consistent rankings within specific route-structure classes. Hence, for many consumers, the flight identified as most GHG efficient is not sensitive to the specific calculation method employed. But unless GHG emissions information is displayed at the point of decision, it cannot enter into consumers’ decision making. A credible and ambiguity-free alternative would thus be to display GHG ranking information on the front page of flight search-engine results.

Multi-criteria ranking of energy generation scenarios with Monte Carlo simulation

Integrated Assessment Models (IAMs) are omnipresent in energy policy analysis. Even though IAMs can successfully handle uncertainty pertinent to energy planning problems, they render multiple variables as outputs of the modelling. Therefore, policy makers are faced with multiple energy development scenarios and goals. Specifically, technical, environmental, and economic aspects are represented by multiple criteria, which, in turn, are related to conflicting objectives. Preferences of decision makers need to be taken into account in order to facilitate effective energy planning. Multi-criteria decision making (MCDM) tools are relevant in aggregating diverse information and thus comparing alternative energy planning options. The paper aims at ranking European Union (EU) energy development scenarios based on several IAMs with respect to multiple criteria. By doing so, we account for uncertainty surrounding policy priorities outside the IAM. In order to follow a sustainable approach, the ranking of policy options is based on EU energy policy priorities: energy efficiency improvements, increased use of renewables, reduction in and low mitigations costs of GHG emission. The ranking of scenarios is based on the estimates rendered by the two advanced IAMs relying on different approaches, namely TIAM and WITCH. The data are fed into the three MCDM techniques: the method of weighted aggregated sum/product assessment (WASPAS), the Additive Ratio Assessment (ARAS) method, and technique for order preference by similarity to ideal solution (TOPSIS). As MCDM techniques allow assigning different importance to objectives, a sensitivity analysis is carried out to check the impact of perturbations in weights upon the final ranking. The rankings provided for the scenarios by different MCDM techniques diverge, first of all, due to the underlying assumptions of IAMs. Results of the analysis provide valuable insights in integrated application of both IAMs and MCDM models for developing energy policy scenarios and decision making in energy sector.

Modelling multicriteria value interactions with Reasoning Maps

Idiographic causal maps are extensively employed in Operational Research to support problem structuring and complex decision making processes. They model means-end or causal discourses as a network of concepts connected by links denoting influence, thus enabling the representation of chains of arguments made by decision-makers. There have been proposals to employ such structures to support the structuring of multicriteria evaluation models, within an additive value measurement framework. However, a drawback of this multi-methodological modelling is the loss of richness of interactions along the means-end chains when evaluating options. This has led to the development of methods that make use of the structure of the map itself to evaluate options, such as the Reasoning Maps method, which employs ordinal scales and ordinal operators for such evaluation. However, despite their potential, Reasoning Maps cannot model explicitly value interactions nor perform a quantitative ranking of options, limiting their applicability and usefulness. In this article we propose extending the Reasoning Maps approach through a multilinear evaluation model structure, built with the MACBETH multicriteria method. The model explicitly captures the value interactions between concepts along the map and employs the MACBETH protocol of questioning to assess the strength of influence for each means-end link. The feasibility of the proposed approach to evaluate options and to deal with multicriteria interactions is tested in a real-world application to support the construction of a population health index.

The social value of candidate HIV cures: actualism versus possibilism

A sterilising or functional cure for HIV is a serious scientific challenge but presents a viable pathway to the eradication of HIV. Such an event would be extremely valuable in...

APPLICATION OF PROMETHEE METHOD FOR DEMAND SIDE MANAGEMENT (DSM) OPTIONS RANKING

Demand Side Management (DSM) is a method used to modify the electrical load profile of a consumer to reduce its electricity bill. There are various types of DSM options available but mostly involve costs to be incurred by consumers. Moreover, the effectiveness of a DSM option depends on various factors including investment cost, saved energy, payback period and more. Multi Criteria Decision Analysis (MCDA) is a tool that can be applied to make decision when a lot of factors to be taken into account. In DSM, Analytical Hierarchy Process (AHP) is one MCDA technique that is widely used in ranking the DSM options. However, AHP requires additive aggregation that may cause lost in detailed information. This paper presents another MDCA method; Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) to perform the ranking of DSM options. PROMETHEE (I and II) were used in a case study and the results shows that PROMETHEE give the same result as AHP. PROMETHEE has an advantage over AHP as it does not require additive aggregation even the problem is multi-dimensional and could provide visual analysis.

A framework for water loss management in developing countries under fuzzy environment: Integration of Fuzzy AHP with Fuzzy TOPSIS

Facing water scarcity conditions water utilities cannot longer tolerate inefficiencies in their water systems. To guarantee sustainable water management one central task is reducing water losses from the supply systems. There are numerous challenges in managing water losses, manifested in a variety of options, their complexities, multiple evaluation criteria, inherent uncertainties and the conflicting objectives and interests of different stakeholders. This study demonstrates the effectiveness of multi criteria decision analysis (MCDA) approaches for decision support in this complex topic. The study covers identifying the key options among a set of options that have been proposed within a framework of strategies to reduce water losses in water distribution systems of developing countries. The proposed methodology was initiated by developing a hierarchical structure of the decision problem that consists of four levels: Overall objective, main criteria, evaluation criteria and options. Different stakeholders were engaged in the process of structuring and evaluating the decision problem. An integrated methodology that combines fuzzy set theory with Analytic Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods was then employed. This methodology has the potential to transform qualitative data into equivalent quantitative measures. Fuzzy AHP was used to create weights for main and evaluation criteria, while Fuzzy TOPSIS was used to aid the ranking of options in terms of their potential to meet the overall objective based on the evaluations and preferences of decision makers. The results showed that pressure management and control strategy was the most prevalent one, followed by employing advanced techniques and establishment of district metered areas. Their dominance was highly connected to the local and boundary conditions of the case study. The sensitivity analysis results showed that strongest and weakest options were less sensitive to changes in weights of evaluation criteria, which could be attributed to the strong consensus in strengthening the best option and neglecting the worst option. This study emphasized the successful application of MCDA in dealing with complicated issues in the context of water loss management. It is anticipated that, the integration of this developed framework in the planning policies of water utilities in developing countries can help in conducting better control over water losses.