scholarly journals A Systematic Literature Review of Multi-Criteria Decision-Making Methods for Sustainable Selection of Insulation Materials in Buildings

2021 ◽  
Vol 13 (2) ◽  
pp. 737
Author(s):  
Indre Siksnelyte-Butkiene ◽  
Dalia Streimikiene ◽  
Tomas Balezentis ◽  
Virgilijus Skulskis
Keyword(s):  
Decision Making ◽  
Literature Review ◽  
Systematic Literature Review ◽  
Energy Demand ◽  
Energy Performance ◽  
Future Research ◽  
Multi Criteria Decision Making ◽  
Insulation Materials ◽  
Advantages And Disadvantages ◽  
Selection Of

The European Commission has recently adopted the Renovation Wave Strategy, aiming at the improvement of the energy performance of buildings. The strategy aims to at least double renovation rates in the next ten years and make sure that renovations lead to higher energy and resource efficiency. The choice of appropriate thermal insulation materials is one of the simplest and, at the same time, the most popular strategies that effectively reduce the energy demand of buildings. Today, the spectrum of insulation materials is quite wide, and each material has its own specific characteristics. It is recognized that the selection of materials is one of the most challenging and difficult steps of a building project. This paper aims to give an in-depth view of existing multi-criteria decision-making (MCDM) applications for the selection of insulation materials and to provide major insights in order to simplify the process of methods and criteria selection for future research. A systematic literature review is performed based on the Search, Appraisal, Synthesis and Analysis (SALSA) framework and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. In order to determine which MCDM method is the most appropriate for different questions, the main advantages and disadvantages of different methods are provided.

scholarly journals A literature review of criteria selection in supplier

2018 ◽  
Vol 11 (4) ◽  
pp. 680 ◽  
Author(s):  
Agus Ristono ◽  
Pratikto ◽  
Purnomo Budi Santoso ◽  
Ishardita Pambudi Tama
Keyword(s):  
Decision Making ◽  
Literature Review ◽  
Supplier Selection ◽  
Research Direction ◽  
Multi Criteria Decision Making ◽  
Advantages And Disadvantages ◽  
Decision Methods ◽  
New Ideas ◽  
Working Out ◽  
Selection Of

Purpose: This paper proposes a new model for further research on how to select criteria in supplier selection, through a literature review and analysis of the advantages and disadvantages of previously used methods.Design/methodology/approach: The methods used to select criteria in supplier selection were extracted from various online academic databases.  The weaknesses and advantages of these methods were then analyzed. Based on these findings, several opportunities for improvement are proposed for further research. Finally, criteria design methods for the selection of suppliers are proposed using statistical multi-criteria decision making (S-MCDM) methods.Findings: Direction and guidance for subsequent research to select the criteria used in supplier selection, based on the advantages and disadvantages of the decision methods used.Research limitations/implications: Limitations of this study are that it is focused on the methods of criteria design in supplier selection.Practical implications: This study can provide a research direction on the selection of criteria for supplier selection.Social implications: This study provides ongoing guidance and avenues for further research.Originality/value: New ideas for working out the developmental strategy for criteria selection are provided by statistical MCDM methods in supplier selection.

Behavioural biases in investment decision making – a systematic literature review

2015 ◽  
Vol 7 (1) ◽  
pp. 88-108 ◽  
Author(s):  
Satish Kumar ◽  
Nisha Goyal
Keyword(s):  
Decision Making ◽  
Literature Review ◽  
Empirical Research ◽  
Systematic Literature Review ◽  
Investment Decision ◽  
Future Research ◽  
Behavioural Finance ◽  
Content Type ◽  
Investment Decision Making ◽  
The Impact

Purpose – The purpose of this paper is to systematically review the literature published in past 33 years on behavioural biases in investment decision-making. The paper highlights the major gaps in the existing studies on behavioural biases. It also aims to raise specific questions for future research. Design/methodology/approach – We employ systematic literature review (SLR) method in the present study. The prominence of research is assessed by studying the year of publication, journal of publication, country of study, types of statistical method, citation analysis and content analysis on the literature on behavioural biases. The present study is based on 117 selected articles published in peer- review journals between 1980 and 2013. Findings – Much of the existing literature on behavioural biases indicates the limited research in emerging economies in this area, the dominance of secondary data-based empirical research, the lack of empirical research on individuals who exhibit herd behaviour, the focus on equity in home bias, and indecisive empirical findings on herding bias. Research limitations/implications – This study focuses on individuals’ behavioural biases in investment decision-making. Our aim is to analyse the impact of cognitive biases on trading behaviour, volatility, market returns and portfolio selection. Originality/value – The paper covers a considerable period of time (1980-2013). To the best of authors’ knowledge, this study is the first using systematic literature review method in the area of behavioural finance and also the first to examine a combination of four different biases involved in investment decision-making. This paper will be useful to researchers, academicians and those working in the area of behavioural finance in understanding the impact of behavioural biases on investment decision-making.

scholarly journals Towards Integration of Security and Safety Measures for Critical Infrastructures Based on Bayesian Networks and Graph Theory: A Systematic Literature Review

Signals ◽  
2021 ◽  
Vol 2 (4) ◽  
pp. 771-802
Author(s):  
Sandeep Pirbhulal ◽  
Vasileios Gkioulos ◽  
Sokratis Katsikas
Keyword(s):  
Graph Theory ◽  
Literature Review ◽  
Bayesian Networks ◽  
Systematic Literature Review ◽  
Future Research ◽  
Critical Infrastructures ◽  
Maritime Industry ◽  
Eligibility Criteria ◽  
Advantages And Disadvantages ◽  
The Impact

In recent times, security and safety are, at least, conducted in safety-sensitive or critical sectors. Nevertheless, both processes do not commonly analyze the impact of security risks on safety. Several scholars are focused on integrating safety and security risk assessments, using different methodologies and tools in critical infrastructures (CIs). Bayesian networks (BN) and graph theory (GT) have received much attention from academia and industries to incorporate security and safety features for different CI applications. Hence, this study aims to conduct a systematic literature review (SLR) for co-engineering safety and security using BN or GT. In this SLR, the preferred reporting items for systematic reviews and meta-analyses recommendations (PRISMA) are followed. Initially, 2295 records (acquired between 2011 and 2020) were identified for screening purposes. Later on, 240 articles were processed to check eligibility criteria. Overall, this study includes 64 papers, after examining the pre-defined criteria and guidelines. Further, the included studies were compared, regarding the number of required nodes for system development, applied data sources, research outcomes, threat actors, performance verification mechanisms, implementation scenarios, applicability and functionality, application sectors, advantages, and disadvantages for combining safety, and security measures, based on GT and BN. The findings of this SLR suggest that BN and GT are used widely for risk and failure management in several domains. The highly focused sectors include studies of the maritime industry (14%), vehicle transportation (13%), railway (13%), nuclear (6%), chemical industry (6%), gas and pipelines (5%), smart grid (5%), network security (5%), air transportation (3%), public sector (3%), and cyber-physical systems (3%). It is also observed that 80% of the included studies use BN models to incorporate safety and security concerns, whereas 15% and 5% for GT approaches and joint GT and BN methodologies, respectively. Additionally, 31% of identified studies verified that the developed approaches used real-time implementation, whereas simulation or preliminary analysis were presented for the remaining methods. Finally, the main research limitations, concluding remarks and future research directions, are presented

Application of Multi-Criteria Decision-Making Methods in Sustainable Manufacturing Management: A Systematic Literature Review and Analysis of the Prospects

2021 ◽  
pp. 1-23
Author(s):  
Renata Pelissari ◽  
Sharfuddin Ahmed Khan ◽  
Sarah Ben-Amor
Keyword(s):  
Decision Making ◽  
Literature Review ◽  
Systematic Literature Review ◽  
Uncertain Data ◽  
Sustainable Manufacturing ◽  
Future Research ◽  
Decision Making Process ◽  
Multi Attribute Decision Making ◽  
Social Environmental ◽  
Cost Of Materials

Due to increasing environmental regulation and customers’ demand for environmentally friendly products, organizations have been required to adopt sustainable manufacturing practices by implementing clean technology (Cleantec) to manufacture green products. By adopting environmental practices, organizations can also achieve qualitative and quantitative benefits that help them remain competitive in the market while meeting governmental environmental policies, such as lowering energy and the cost of materials. The significant number of articles addressing sustainability in manufacturing published in the past few years attests to the importance of the topic. However, not many studies have been developed to understand the decision-making process in sustainable manufacturing. Therefore, the objective of this paper is to conduct a systematic literature review on the application of multi-attribute decision-making (MADM) methods in sustainable manufacturing. A total of 158 papers, published between 2009 and 2018, met the criteria set in the research methodology. The 158 papers were then analyzed and classified into seven categories: (i) SM domain, (ii) activity within the organization, (iii) decision goals, (iv) decision-makers involved (group or individual), (v) uncertain data, (vi) SM aspects (social, environmental, and economic), and (vii) MADM methods. Among the results, we identified that AHP is the most applied MADM method and, regarding the activities of the organization, MADM methods have been the most frequently applied to strategy management and supply chain. We also identified a tendency to consider uncertain and imprecise data in the decision-making process. Another result is that all the three domains — economic, environmental and social — were considered in most of the papers, followed by the combination of the economic and environmental perspectives. In the conclusion, some recent trends and future research directions are highlighted.

Multi-criteria decision making towards selection of industrial robot

2015 ◽  
Vol 22 (3) ◽  
pp. 465-487 ◽  
Author(s):  
Dilip Kumar Sen ◽  
Saurav Datta ◽  
Saroj Kumar Patel ◽  
Siba Sankar Mahapatra
Keyword(s):  
Decision Making ◽  
Selection Problem ◽  
Preference Ranking ◽  
Multi Criteria Decision Making ◽  
Content Type ◽  
Promethee Ii ◽  
Advantages And Disadvantages ◽  
Wide Range ◽  
Robot Selection ◽  
Selection Of

Purpose – Robot selection is one of the critical decision-making tasks frequently performed by various industries in order to choose the best suited robot for specific industrial purposes. In recent marketplace, the number of robot manufacturers has increased remarkably offering a wide range of models and specifications; thus, robot selection has become indeed confusing as well as complicated task. Selection of an appropriate robot is a sensitive process; it may result massive letdown, if not chosen properly. Therefore, for unravel the selection problem; the purpose of this paper is to explore the preference ranking organization method for enrichment evaluation (PROMETHEE) II method. Design/methodology/approach – Apart from a large variety of robotic systems, existence of various multi-criteria decision making (MCDM) tools and techniques may create confusion to the decision makers’ in regards of application feasibility as well as superiority in performance to work under different decision-making situations. In this context, the PROMETHEE II method has been found as an efficient decision-making tool which provides complete ranking order of all available alternatives prudently, thus avoiding errors in decision making. Findings – In this context, the present paper highlights application potential of aforesaid PROMETHEE II method in relation to robot selection problem subjected to a set of quantitative (objective) evaluation data collected from the available literature resources. Advantages and disadvantages of PROMETHEE II method have also been reported in comparison to other existing MCDM approaches. Originality/value – The study bears significant managerial implications. Proper evaluation and selection of appropriate candidate robot would be helpful for the industries in order to improve product quality as well as to increase productivity. Proper utilization of resources could be ensured. Functioning would be accurate with reduced timespan. As a consequence, company can increase its profit margin in long run.

scholarly journals Modeling Energy Demand—A Systematic Literature Review

Energies ◽  
2021 ◽  
Vol 14 (23) ◽  
pp. 7859
Author(s):  
Paul Anton Verwiebe ◽  
Stephan Seim ◽  
Simon Burges ◽  
Lennart Schulz ◽  
Joachim Müller-Kirchenbauer
Keyword(s):  
Literature Review ◽  
Systematic Literature Review ◽  
Energy Demand ◽  
Easy Access ◽  
Percentage Error ◽  
Future Research ◽  
Average Percentage ◽  
Demand Modeling ◽  
Demand Models ◽  
Average Percentage Error

In this article, a systematic literature review of 419 articles on energy demand modeling, published between 2015 and 2020, is presented. This provides researchers with an exhaustive overview of the examined literature and classification of techniques for energy demand modeling. Unlike in existing literature reviews, in this comprehensive study all of the following aspects of energy demand models are analyzed: techniques, prediction accuracy, inputs, energy carrier, sector, temporal horizon, and spatial granularity. Readers benefit from easy access to a broad literature base and find decision support when choosing suitable data-model combinations for their projects. Results have been compiled in comprehensive figures and tables, providing a structured summary of the literature, and containing direct references to the analyzed articles. Drawbacks of techniques are discussed as well as countermeasures. The results show that among the articles, machine learning (ML) techniques are used the most, are mainly applied to short-term electricity forecasting on a regional level and rely on historic load as their main data source. Engineering-based models are less dependent on historic load data and cover appliance consumption on long temporal horizons. Metaheuristic and uncertainty techniques are often used in hybrid models. Statistical techniques are frequently used for energy demand modeling as well and often serve as benchmarks for other techniques. Among the articles, the accuracy measured by mean average percentage error (MAPE) proved to be on similar levels for all techniques. This review eases the reader into the subject matter by presenting the emphases that have been made in the current literature, suggesting future research directions, and providing the basis for quantitative testing of hypotheses regarding applicability and dominance of specific methods for sub-categories of demand modeling.

Cognitive biases and decision-making strategies in times of change: a systematic literature review

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Chiara Acciarini ◽  
Federica Brunetta ◽  
Paolo Boccardelli
Keyword(s):  
Decision Making ◽  
Literature Review ◽  
Systematic Literature Review ◽  
Cognitive Biases ◽  
Future Research ◽  
Strategic Decisions ◽  
Data Set ◽  
Content Type ◽  
The Impact

PurposeIn a work environment marked by unprecedented complexity, volatility and ambiguity, managers must accomplish their objectives while navigating many challenges. This paper aims to investigate potential interrelations among environmental transformations, cognitive biases and strategic decisions. In particular, the purpose of the study is to crystallize the state of art on the impact of cognitive biases on strategic decisions, in the context of environmental transformations.Design/methodology/approachThe authors have conducted a systematic literature review to identify existing relevant work on this topic and to detect potential avenues for future research.FindingsThe findings highlight how decision-making is influenced and enabled by internal (e.g. perception) and external factors (e.g. digitalization). Specifically, the strategic role of cognitive biases appears to be crucial when investigating the related impact on strategic decisions in times of environmental transformation.Practical implicationsImplications are drawn for scholars and practitioners interested in evaluating the role of specific decision-making determinants for the formation and implementation of strategic decisions. In this sense, we stress that decision-makers need to manage their cognitive biases and select the right information out of a wide data set in order to adapt to environmental transformations.Originality/valueBy systematizing the literature review, potential interrelations among environmental transformations, cognitive biases and strategic decisions are identified. Furthermore, the primary phases that drive the decision-making process are proposed (analysis, decision, onboarding and control).

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