Multicriteria Decision Making in Sustainable Tourism and Low-Carbon Tourism Research: A Systematic Literature Review

Multicriteria Decision Making (MCDM) is increasingly being utilized as an analytical research tool for sectors that require decision-making with specific objectives and constraints, such as the tourism industry. Sustainable tourism, which examines the balance of numerous aspects, including stakeholders’ interests, is the critical feature propelling the increased usage of MCDM. This paper explores the use of Multicriteria Decision Making (MCDM) methods applied in studies of sustainable tourism and its derivative term, low-carbon tourism, using a systematic literature review (SLR) search from the Scopus database. The analysis has identified 189 relevant studies published between 1987 to April 2022. After selection, screening, and synthesizing processes, we selected 135 pertinent studies, which were analysed in general descriptive data, citation impacts, geographical categorization, categorization of the methodologies’ objectives, and possible trajectories of similar research in the future. We find that highly cited authors and articles are related to sustainable tourism indicators\u27 development and case studies. Furthermore, most relevant studies are concentrated in Asia and Europe rather than other regions. We also categorize the reviewed studies into six classifications depending on each method\u27s intended usage and further suggest four contexts for the studies’ future trajectory

Multi-Criteria Decision Analysis (MCDA) for Agricultural Sustainability Assessment

Multi Attribute Utility Theory (MAUT), Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE) and Elimination methods of Multi-Criteria Decision analysis (MCDA) are tested to assess and compare the sustainability of different agricultural systems. Indicators and composite indicators are derived from data gathered using the agricultural sustainability categories of Productivity, Stability, Efficiency, Durability, Compatibility and Equity (PSEDCE). Agricultural systems around the world face challenges from current agricultural practices, over-exploitation of natural resources, population growth and climate change. As a result, understanding agricultural sustainability has become a global issue. Assessment is a first step in benchmarking and tracking agricultural sustainability and can support related policy and programmes. This thesis applied the PSEDCE categories to understand more about the complexities inherent to agricultural sustainability assessment. Agricultural sustainability assessment (ASA) requires a wide variety of ecological, economic and social information with various methods. In the first part of this thesis, a systematic analysis of the scientific soundness and user-friendliness of eight ASA approaches revealed that MCDA based ASA is the preferred holistic method. MCDA can take into account both qualitative and quantitative indicators of all dimensions of sustainability and analyze them to draw a comprehensive picture. As a multifaceted, complex issue, agricultural sustainability assessment is well-suited to MCDA, which is able to handle large data sets including stakeholders’ perspectives. Given that it is a relatively new analysis procedure in the study of agriculture, only a few researchers have applied this technique to measure sustainability. Considering these findings, three MCDA methods, MAUT, PROMETHEE and Elimination, were tested to measure the relative sustainability of five agricultural systems in coastal Bangladesh. To investigate the performance of MAUT, PROMETHEE, and Elimination, a total of 50 indicators from agricultural sustainability categories of PSEDCE were tested. From these 50 indicators, 15 composite indicators were developed through proportionate normalization and hybrid aggregation rules of arithmetic mean and geometric mean. The 15 composite indicators were used in MAUT and PROMETHEE analysis, and the 50 indicators were used in Elimination analysis. The analyses show that MAUT is able to aggregate diverse information and stakeholders’ perspectives to generate a robust score that enables a comparison of sustainability across the different agricultural systems. PROMETHEE is a non-compensatory approach that can also accommodate a variety of information and provide thresholds for ranking relative agricultural sustainability for each of the five agricultural systems. Elimination ranks the sustainability of agricultural systems through a set of straightforward decision rules expressed in the form of “if … then …” conditions. Elimination appears to be quick and less complex, whereas MAUT and PROMETHEE are regarded as fairly complicated and require software to find potential solutions. Overall, the study shows that MAUT, PROMETHEE and Elimination can handle multidimensional data and can be applied for relative assessment of sustainability of agricultural systems. However, selection of the appropriate criteria, stakeholders’ perspectives and the purpose of the assessment are very important and must be considered carefully for inclusion in MCDA methods for agricultural sustainability assessment. The results of the case studies also demonstrate that these approaches have the potential to become a useful framework for agricultural sustainability assessment and related policy development and decision-making

Multiple Criteria Decision Analysis Theory and Tools for the SDEWES Index

The goal of this work is to apply Multiple Criteria Decision Analysis tools, both theoretical and practical, to analyse, support and possibly enhance composite indexes, in particular those related to sustainability assessment. In this context, the Sustainable Development of Energy, Water and Environment Systems Index represents a paradigmatic example and an emerging reference point, thus it is specifically addressed throughout the work. On the theoretical side, the focus is on the property of “independence”, i.e., of evaluating an alternative independently of the others. It is argued that this property can be appealing for an index that is conceived to address, over time, an increasing number of inherently evolving systems. A viable and theoretically grounded approach for devising a version of the index fulfilling independence is proposed. On the practical side, the contribution concerns visual support tools. A well-known projective method is adapted to work with the index, and a new tool with comparable expressive capabilities is proposed. The new representation is more focused on the index, technically simpler, and less sensitive to changes in the input data. The features of the visual tools are illustrated exploiting currently available (partially aggregated) index data. In particular, the new tool is used to illustrate two issues addressed in the scientific literature on the index, namely, the use of scenario analysis as a predictive tool, and the decoupling of energy usage and carbon dioxide emissions

Evaluation of Corporate Sustainability

As a consequence of an increasing demand in sustainable development for business organizations, the evaluation of corporate sustainability has become a topic intensively focused by academic researchers and business practitioners. Several techniques in the context of multiple criteria decision analysis (MCDA) have been suggested to facilitate the evaluation and the analysis of sustainability performance. However, due to the complexity of evaluation, such as a compilation of quantitative and qualitative measures, interrelationships among various sustainability criteria, the assessor’s hesitation in scoring, or incomplete information, simple techniques may not be able to generate reliable results which can reflect the overall sustainability performance of a company. This paper proposes a series of mathematical formulations based upon the evidential reasoning (ER) approach which can be used to aggregate results from qualitative judgments with quantitative measurements under various types of complex and uncertain situations. The evaluation of corporate sustainability through the ER model is demonstrated using actual data generated from three sugar manufacturing companies in Thailand. The proposed model facilitates managers in analysing the performance and identifying improvement plans and goals. It also simplifies decision making related to sustainable development initiatives. The model can be generalized to a wider area of performance assessment, as well as to any cases of multiple criteria analysis

Regional inclusive development: An assessment of Russian regions

The concept of inclusive development is gaining momentum in both the academic and policy-making arenas. There are a plethora of definitions and several indicators with which to monitor its progress at the national level. However, the regional level has been relatively overlooked in the analyses carried out by academics. This is particularly serious for large countries marked by deep regional disparities. The aim of this paper is to address this gap by proposing and applying a framework to assess inclusive development at the regional level. Drawing on a critical analysis of the concept and existing indexes, the paper proposes an index of Regional Inclusive Development and applies it to the regions of the Russian Federation. Moreover, it compares the suggested index with established indicators of regional socio-economic development, namely quality of life and gross product. The results support the idea that at the regional level, there is a significant correlation and interdependence between all dimensions of the sustainable development concept—environment, the economy, and society—and that inclusiveness should not be ignored or undervalued in the analysis of development processes. Furthermore, the results show significant differences in the positioning of the regions in terms of the inclusive development rankings as compared to their positions in the quality of life and gross product rankings. The results also reveal small interregional differences among Russian regions, which are unexpected given the size of the country.info:eu-repo/semantics/publishedVersio

Reconsidering the calculation and role of environmental footprints

Following the recent Copenhagen Climate Change conference, there has been discussion of the methods and underlying principles that inform climate change targets. Climate change targets following the Kyoto Protocol are broadly based on a production accounting principle (PAP). This approach focuses on emissions produced within given geographical boundaries. An alternative approach is a consumption accounting principle (CAP), where the focus is on emissions produced globally to meet consumption demand within the national (or regional) economy1. Increasingly popular environmental footprint measures, including ecological and carbon footprints, attempt to measure environmental impacts based on CAP methods. The perception that human consumption decisions lie at the heart of the climate change problem is the impetus driving pressure on policymakers for a more widespread use of CAP measures. At a global level of course, emissions accounted for under the production and consumption accounting principles would be equal. It is international trade that leads to differences in emissions under the two principles. This paper, the second in this special issue of the Fraser Commentary, examines how input-output accounting techniques may be applied to examine pollution generation under both of these accounting principles, focussing on waste and carbon generation in the Welsh economy as a case study. However, we take a different focus, arguing that the ‘domestic technology assumption’, taken as something of a mid-point in moving between production and consumption accounting in the first paper, may actually constitute a more useful focus for regional policymakers than full footprint analyses