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The paper aims to provide a decision-support model to ensure a proper use of the limited resources, financial and not, for the enhancement of the cultural heritage and comprehensive development of small towns from sustainable perspective.

The assessment model is set up using a multi-criteria method that combines elements of linear planning with a performance indicators system that may represent the complexity of the territory’s cultural identity as a result of existing cultural-historical assets.

The model reliability is tested in a case study in a Municipality in southern Italy. The case study’s findings highlight the advantages for the public/private operators, who can consciously choose which preservation and restoration projects to fund while taking into account the effects those decisions will have on the economic, social and environmental context of reference.

Due to the suggested operational approach and the selection of variables for accounting economic, social and environmental impacts by the renewal project, the research findings may not be generalizable. Therefore, it is recommended that researchers look into the suggested theories in more detail.

The study offers implications for designing a user-friendly tool to help decision-making processes from a private–public viewpoint in a reasonable allocation of financial resources among investments for cultural property asset enhancement.

The suggested operational approach provides a reliable information apparatus to depict the decision-making process under small-town development in accordance with sustainability dimensions.

The purpose of this paper is to implement a strategic decision-making framework by selecting clusters of maintainable machines and scheduling their maintenance as part of a company’s manufacturing strategy.

Multi-criteria clustering problem in conjunction with the application of a group technology is used to establish clusters of maintainable machines based on their need for maintenance according to the type of failures they can encounter.

Using the concept of group technology in conducting preventive maintenance will result in the grouping of machines according to the impact of a failure based on the criteria specified by the decision makers. Accordingly, it will facilitate the process of executing the maintenance itself by ordering spare parts and informing the maintenance personnel which will lead to minimize the maintenance cost.

The results presented in this paper are reliable, objective may be used to minimize the total cost of conducting preventive maintenance in a manufacturing environment.

Nowadays, the applications of metal matrix composites are tremendously increasing in engineering fields. Consequently, the demand for precise machining of composites has also grown enormously. The purpose of this paper is to reduce production cost and simultaneously improve desired product quality through optimal parameter setting using WASPAS and MOORA.

Metal matrix composites were fabricated using stir casting process, with aluminum 6063 as matrix and titanium carbide as reinforcement. Fabricated composite samples were machined on medium duty lathe using cemented carbide tool. All the experiments were carried out based on Box–Behnken design. Comparison of multi objective optimization based on ratio analysis and weighted aggregated sum product assessment in optimizing four parameters, namely, “cutting speed,” “feed rate,” “depth of cut” and “reinforcement weight percent of composite samples”; evaluating their influence on material removal rate, cutting force and surface roughness were carried out.

The output achieved by both MOORA and WASPAS are in similar MCDM) techniques in the selection of machining parameters.

The results obtained in the present paper will be helpful for decision makers in manufacturing industries, who work in metal cutting area, to select the suitable levels for the parameters by implementing the MCDM techniques.

The novelty of this paper is making an attempt to select better MCDM technique based on the comparison of results obtained for the individual technique.

This paper aims to present a methodology for the mapping and evaluation of suppliers’ competencies and know-how. The authors operationalize the concept of organizational competence and provide companies with a customized management tool to map suppliers’ critical competencies for screening strategic from non-strategic suppliers and providing inputs for suppliers’ development.

Competencies assessment, carried out through a fuzzy knowledge management system (VINCI), is performed through the aggregation of indicators related to the control of critical resources, the degree of implementation of critical processes, the competitive positioning and the financial situation of a supplier. Competencies description and operationalization are based on the bottom-up elicitation of the subjective knowledge managers actually use to assess suppliers’ capability. Such subjective knowledge is then validated and formalized through a top-down approach based on strategic literature.

The authors tested VINCI on a sample of 38 suppliers of a large company. The results show that the methodology provides its users with a highly customizable knowledge map and its associated decision support tool that keeps into account the peculiar strategic needs of the company in the management of an existing portfolio of suppliers.

VINCI outcomes can be used to perform benchmarking analyses, define entry criteria and thresholds for suppliers’, identify improvement targets and service levels to be considered in the definition of supply contracts, supporting the alignment of supplier’s management with business strategy.

The most important original contribution of this work resides in the operationalization and measurements of firms’ competencies based on the elicitation of subjective knowledge that managers use in the actual assessment. A further distinctive feature of this paper is that the method is applied to small and medium companies, whereas large part of the literature on core or organizational competencies assessment is focused on large companies.

In this chapter, the integrative methodological approach (IMA) of the research project GLOWA Elbe is introduced, which represents a scientific methodology to support water management under uncertainty regarding future paths of global change. The approach paves the way for integration of research work of many disciplines, of different assessment methods, of various policy fields, and the involvement of relevant stakeholders and decision makers. IMA can be roughly described by four research elements (scenario derivation, indicator and criteria identification, model-based impact analysis, and final scenario assessment based on combined benefit–cost and multi-criteria analysis), which lay the basis for the IMA activities of the global change research sequence. Its practical application is demonstrated by a case study on the Spree and Schwarze Elster river basins. Specific results of Chapter 4 (on scenario derivation) and Chapter 11 (on integrating economic evaluation into water management simulation) in this volume are picked up in order to focus on the illustration of the integrated assessment results for this German case study.

Technology assessment is a difficult task at the Mission Control Center (MCC). The difficulty is inherent in the unavailability of structured information and exacerbated by the lack of a systematic assessment process. New technology deployment to the MCC requires testing and certification in three labs: Quest 1, 2, and 3. The Mission Control Center Systems (MCCS) architecture team, a multidisciplinary group of MCC experts and scientists is chartered to redefine the next generation of MCCS by developing a systematic process to assess and certify new technologies. Quest 123 is a benchmarking tool that was successfully implemented at the Johnson Space Center to assess and certify new technology initiatives for each lab before final deployment to the MCC. Quest 123 integrates the analytic hierarchy process with an additive multi‐criteria decision‐making model into a dynamic benchmarking framework.

The decisions taken today relating to urban renewal interventions are rarely supported by logical and operational methodologies capable of effectively rationalising selection processes. For this purpose, it is necessary to propose and implement analysis models with the aim of promoting the sustainable development of the territory. The purpose of this paper is to define a model for the optimal allocation of scarce resources.

The Discrete Linear Programming (DLP) is used for selecting investments aimed at achieving financial, social, cultural and environmental sustainability.

The proposed model lends itself to the construction of investment plans on behalf of both types of decision makers, of both a public and a private nature.

All projects are evaluated according to multi-criteria logics, so that it is possible to find compromise solutions, in accordance with the stakeholders’ different preferences.

The model, written with A Mathematical Programming Language using DLP logics, is tested – case study – so as to define an investment programme finalised for urban renewal of a vast area.

The proposed econometric model makes it possible to obtain the optimal combination of projects for urban renewal with a view to achieving the sustainable development of the territory.

Using the proposed model, all projects are evaluated according to multi-criteria logics, so that it is possible to find compromise solutions, in accordance with the stakeholders’ different preferences.

This paper seeks to take a cautionary stance to the impact of the marketing mix on customer satisfaction, via a case study deriving consensus rankings for benchmarking on selected retail stores in Malaysia.

The ELECTRE I model is used in deriving consensus rankings via multicriteria decision making method for benchmarking base on the marketing mix model 4P's. Descriptive analysis is used to analyze best practice among the four marketing tactics.

Outranking methods in consequence constitute a strong base on which to found the entire structure of the behavioral theory of benchmarking applied to development of marketing strategy.

This study looks only at a limited part of the puzzle of how consumer satisfaction translates into behavioral outcomes.

The study provides managers with guidance on how to generate a rough outline of potential marketing activities that can be used to take advantage of capabilities and convert weaknesses and threats.

The paper interestingly portrays the effective usage of multicriteria decision‐making and ranking method to help marketing managers predict their marketing trends.

This paper aims to present implementation of temporary sheltering areas (TSAs), in case of earthquakes for Quito, as a low-cost mitigation project in developing countries. Four pilot TSAs were built and a limited communication effort was implemented by municipality. Years after, effectiveness of the project was evaluated.

TSA locations were chosen considering technical aspects, using a weighted decision matrix through an analytical hierarchy process defined with private and public sector professionals. Four pilot TSAs were built and information about them was spread including a hazard signage program targeted to the population.

After a year, communication effort conceived by the municipality ended, decision-makers changed and a M5.1 local earthquake hit the city, causing few casualties and structural damage. Population and municipality officials had forgotten about the project. TSA facilities were out of service. Four years later, authorities changed again, TSA changed their use, hazard signage program was abandoned and population was completely unaware about the project.

TSA project is a suitable low-cost disaster management initiative for developing countries. However, if a sustainable communication is not performed, suitable mitigation projects could be ineffective in time.

This paper demonstrates how to implement TSAs in cities with limited resources and following a rational decision procedure. It remarks benefits and mistakes detected years after that could improve decisions in similar preparedness initiatives against earthquakes in other developing countries.

The extended TOPSIS approach including the analytical hierarchy process method is used to solve business recovery priority decision problem mixed with interval data and exact data of an insurance company. The paper aims to discuss these issues.

According to the concept of TOPSIS, the authors construct the normalized decision matrix and the weighted normalized decision matrix. Using the vertex method, the authors calculate the distance of each alternative from the positive or negative ideal solution.

The proposed TOPSIS algorithms on interval data provide a useful framework for systematic risk assessment that an incident or disaster manager can use to prioritize recovery during business discontinuity.

As a managerial implication, the proposed method can be applied to any case for providing information for risk management decision-making in industrial and service organizations. As for a future direction, other decision-making methods can be included in the methodology to ensure more integrated and/or comparative study.

The ratings and weights of the criteria in the decision problem are assessed by means of interval data. The use of the interval data in decision problem is highly beneficial when performance values cannot be expressed by means of numerical values. The authors extended the TOPSIS approach for solving MCDM problem with interval data as well as exact data.

The authors have shown how TOPSIS method on interval data can be used to provide priority decision for business recovery of an insurance company. The proposed method provides the authors a useful way to deal with a business recovery problem, where the values of evaluating items are represented by generalized exact numbers or interval-valued numbers.

The proposed approach has the potential to resolve incident and disaster management and can be applied to the implementation of business recovery plan for business continuity.