scholarly journals Resource depletion: where is an intervention most effective?

2019 ◽  
Vol 8 (4) ◽  
pp. 307-321 ◽  
Author(s):  
Patrick de Laat
Keyword(s):  
Resource Depletion ◽  
Decision Makers ◽  
Analytic Hierarchy ◽  
Content Type ◽  
New Ways Of Working ◽  
Rules Of Thumb ◽  
Structured Analysis ◽  
Operation Phase ◽  
The Impact ◽  
Hierarchy Process

Purpose Where does one need to intervene in to be most effective? The purpose of this study is to rank areas of the resource system, according to how much of a change can be expected from interventions in an area, in relation to the problem of depleting resources. Design/methodology/approach Principles of structured analysis are used to model how society uses resources. From this model, nine intervention areas are defined. These intervention areas are ranked in terms of effectiveness, through the use of the analytic hierarchy process. Findings To be most effective, one must prioritize intervention areas as follows: material inputs to the operation phase; process inputs to the operation phase; products’ longevity; process inputs to the manufacturing phase; and material inputs to the manufacturing phase. Practical implications Most decisions are not made on the basis of rigorous analysis but by using heuristics (rules of thumb). The results of this study are expressed as rules of thumb. They can help decision makers prioritize what is most important, but without imposing new ways of working. Originality/value In the construction domain, heuristics that generalize the impact of actions (content), instead of intervention areas (context), currently seem to prevail. The heuristics of this study generalize the impact of intervention areas. Therefore, they provide an extra perspective for many decision makers. This extra perspective can help reduce mistakes that are typically made by oversimplifying matters.

Performance of physical asset management using the analytic hierarchy process

2019 ◽  
Vol 37 (3) ◽  
pp. 327-345 ◽  
Author(s):  
Fawzeia Abdulla Al Marzooqi ◽  
Matloub Hussain ◽  
Syed Zamberi Ahmad
Keyword(s):  
Analytic Hierarchy Process ◽  
Asset Management ◽  
Analytic Hierarchy ◽  
Content Type ◽  
Equal Importance ◽  
The Analytic Hierarchy Process ◽  
Physical Asset ◽  
The Impact ◽  
Hierarchy Process ◽  
Asset Managers

Purpose The purpose of this paper is to explore certain resources, capabilities and competencies needed to improve the performance of physical asset management (PAM). Design/methodology/approach The analytic hierarchy process (AHP) is used to select and prioritize the most appropriate factors for improving performance. A multi-criteria approach is used to analyze and compare the importance of 6 main criteria and 18 subcriteria identified from a survey of relevant literature. Findings The study revealed that not all factors are viewed as having equal importance in improving PAM performance, as three of the main factors attained greater importance among the six factors. Research limitations/implications This study explored the factors required for managing assets only within the third stage of asset lifecycle, that is, the utilization stage. It is recommended that future studies be conducted in such a way as to determine the importance of similar factors in the other stages of the asset lifecycle, or to identify new factors and add new criteria. Practical implications Knowledge of the differential impacts of the factors on the performance of PAM can impact asset managers and decision makers in their allocation of resources and focus their work on the highest-ranked rather than the lowest-ranked factors. Also, AHP used provides an effective mean for asset managers to identify priorities among decision criteria in their organization. Originality/value To date, no study has explored the impact of six combined factors on the performance of PAM. Previous studies have found that these factors each had equal importance. However, their relative ranking in practice and when they appear together have remained unrecognized.

scholarly journals How to Influence the Results of MCDM?—Evidence of the Impact of Cognitive Biases

Mathematics ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 121
Author(s):  
Gerda Ana Melnik-Leroy ◽  
Gintautas Dzemyda
Keyword(s):  
Loss Aversion ◽  
Cognitive Biases ◽  
Decision Makers ◽  
Human Information Processing ◽  
Analytic Hierarchy ◽  
Rational Agents ◽  
Criteria Weights ◽  
Ranking Of Alternatives ◽  
The Impact ◽  
Hierarchy Process

Multi-criteria decision-making (MCDM) methods aim at dealing with certain limitations of human information processing. However, cognitive biases, which are discrepancies of human behavior from the behavior of perfectly rational agents, might persist even when MCDM methods are used. In this article, we focus on two among the most common biases—framing and loss aversion. We test whether these cognitive biases can influence in a predictable way both the criteria weights elicited using the Analytic Hierarchy Process (AHP) and the final ranking of alternatives obtained with the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). In a controlled experiment we presented two groups of participants with a multi-criteria problem and found that people make different decisions when presented with different but objectively equivalent descriptions (i.e., frames) of the same criteria. Specifically, the results show that framing and loss aversion influenced the responses of decision makers during pairwise comparisons, which in turn caused the rank reversal of criteria weights across groups and resulted in the choice of a different best alternative. We discuss our findings in light of Prospect Theory and show that the particular framing of criteria can influence the outcomes of MCDM in a predictable way. We outline implications for MCDM methodology and highlight possible debiasing techniques.

Productive workplace behaviour at the governmental sector: the case of the UAE

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Amna Abdallah ◽  
Salam Abdallah
Keyword(s):  
Structural Equation ◽  
Decision Makers ◽  
Analytic Hierarchy ◽  
Content Type ◽  
Innovative Strategies ◽  
Government Sector ◽  
The Government ◽  
Hierarchy Process ◽  
New Criteria ◽  
Practical Implications

PurposeThe purpose of this paper is to explore the factors that influence the improvement of productive work behaviour (PWB) in the dynamic, ergonomic nature.Design/methodology/approachThe analytic hierarchy process (AHP) is used, in experiment 1, to select and prioritise the most relevant criteria for improvement of PWB. A multi-criteria method is used to analyse and compare the importance of four main criteria and 16 sub-criteria identified from previous studies. The structural equation modelling (SEM) is also used to validate the findings of experiment 1.FindingsThis study revealed that not all criteria are considered important for improving PWB. Flexibility and job specifications were the top-scored criteria. These criteria collectively accounted for more than 65% of the four studied criteria. The SEM emphasised the significance of flexibility and job description of the changing dynamics of organisational regulation during the contemporary economic and managerial turmoil.Research limitations/implicationsThis study explored the criteria required to improve PWB. The findings recommend that future studies should be designed to identify new elements and add new criteria and test the newly introduced variables at a physical workplace after the outbreak ends.Practical implicationsKnowledge of the differential impacts of the criteria on the performance of PWB govern decision-makers in private and governmental organisation, especially at such times of economic turmoil and need for innovative strategies.Originality/valueFew studies have explored workplace behaviour and the environment in the government sector. Therefore, the focus of this study is the comprehensive coverage of workplace behaviour and the criteria influencing its productivity before and during the coronavirus outbreak.

Application of analytic hierarchy process (AHP) for sustainable pavement performance management in Qatar

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Okan Sirin ◽  
Murat Gunduz ◽  
Mohammed E. Shamiyeh
Keyword(s):  
Critical Factor ◽  
Decision Makers ◽  
Pavement Performance ◽  
Mechanical And Thermal Properties ◽  
Heavy Vehicles ◽  
Analytic Hierarchy ◽  
Content Type ◽  
Factors Affecting ◽  
Hierarchy Process ◽  
Design Construction

PurposePavement is one of the main elements of the roads network. It is extremely essential to study and understand the factors affecting its performance and highlight the most important ones for decision-makers and pavement experts to consider during the design, construction and maintenance stages. The purpose of this paper was to identify the factors affecting pavement performance and rank them according to their importance using Analytic Hierarchy Process (AHP) for decision-makers and pavement experts to consider during the design, construction and maintenance stages.Design/methodology/approachA survey was developed considering 29 factors found in the literature that affect pavement performance. The survey was sent to pavement professionals in Qatar to rate their perception of factors affecting pavement performance to enhance roads' sustainability. 205 responses were collected and analyzed using AHP.FindingsThe findings indicate that the factor “unconsidered heavy vehicles volume” is the most critical factor that affects pavement performance. The second most critical factor affecting the pavement performance is the “low asphalt content” due to escalating binder aging, reducing fatigue life of the pavement and decreasing the durability of roads. The third and fourth factors are “poor mechanical and thermal properties” and “unexpected high traffic volume,” respectively. These two factors are strongly attached to the first and second factors since the traffic volume affects the pavement performance less but similar to the heavy vehicles and a mix with poor mechanical and thermal properties is related indirectly to the asphalt content in the mix.Originality/valueThe research provides help for decision-makers in the construction industry to improve the performance of pavements using a multi-criteria decision-making tool. This paper's outcome would help the pavement management professionals in the construction industry to improve pavement performance and management, increase the pavement's life cycle and reduce maintenance costs.

Designing a knowledge-based system (KBS) to study consumer purchase intention: the impact of digital influencers in Pakistan

Kybernetes ◽  
2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sherbaz Khan ◽  
Aamir Rashid ◽  
Rizwana Rasheed ◽  
Noor Aina Amirah
Keyword(s):  
Purchase Intention ◽  
Fuzzy Ahp ◽  
Purchase Intentions ◽  
Decision Makers ◽  
Decision Criteria ◽  
Analytic Hierarchy ◽  
Content Type ◽  
Knowledge Based System ◽  
Knowledge Based ◽  
The Impact

PurposeThe purpose of this study is to present a complete framework that defines the link between choices and decision criteria based on existing research on digital influencers (DIs) connected to consumer purchase intentions. The primary goal of this article is to assess the effect of DIs on customer purchase intentions via the creation of an integrated knowledge-based system (KBS).Design/methodology/approachThe suggested KBS is based on the fuzzy analytic hierarchy process (AHP), which creates a link between DI elements and their overall effect on consumer purchase intentions.Findings With the help of a KBS, the performance of DIs may be evaluated. It demonstrates the link between choices connected to factors and decision criteria of various variables, demonstrating the beneficial effect of DIs in molding customer purchase intentions in the organic skincare industry.Practical implicationsThe proposed KBS would aid marketing managers and decision makers in assessing the effect of DIs on customer purchase intentions. This research would also give decision makers with extensive information on influencer marketing and crucial elements that have a significant effect on customer purchase intentions.Originality/valueThis is the first research to employ the fuzzy AHP methodology and KBS in relation to influencers' effect. No prior research has targeted the organic skincare industry to assess the effect of Internet influencers on consumer purchase intentions. Furthermore, the KBS offers a holistic and complete way to studying influencers' effect on cost per impression (CPI) by establishing a linkage between choices and decision criteria.

scholarly journals Quantifying complexity in translational research: an integrated approach

2014 ◽  
Vol 27 (8) ◽  
pp. 760-776 ◽  
Author(s):  
David A. Munoz ◽  
Harriet Black Nembhard ◽  
Jennifer L. Kraschnewski
Keyword(s):  
Translational Research ◽  
Quality Function Deployment ◽  
Integrated Approach ◽  
Analytic Hierarchy ◽  
Content Type ◽  
Technical Requirements ◽  
Three Phase ◽  
The Impact ◽  
Hierarchy Process

Purpose – The purpose of this paper is to quantify complexity in translational research. The impact of major operational steps and technical requirements is calculated with respect to their ability to accelerate moving new discoveries into clinical practice. Design/methodology/approach – A three-phase integrated quality function deployment (QFD) and analytic hierarchy process (AHP) method was used to quantify complexity in translational research. A case study in obesity was used to usability. Findings – Generally, the evidence generated was valuable for understanding various components in translational research. Particularly, the authors found that collaboration networks, multidisciplinary team capacity and community engagement are crucial for translating new discoveries into practice. Research limitations/implications – As the method is mainly based on subjective opinion, some argue that the results may be biased. However, a consistency ratio is calculated and used as a guide to subjectivity. Alternatively, a larger sample may be incorporated to reduce bias. Practical implications – The integrated QFD-AHP framework provides evidence that could be helpful to generate agreement, develop guidelines, allocate resources wisely, identify benchmarks and enhance collaboration among similar projects. Originality/value – Current conceptual models in translational research provide little or no clue to assess complexity. The proposed method aimed to fill this gap. Additionally, the literature review includes various features that have not been explored in translational research.

A Soft Hierarchical Process Approach for Decision Making in A Supply Chain

2015 ◽  
Vol 4 (1and2) ◽  
Author(s):  
Rajeev Dhingra ◽  
Preetvanti Singh
Keyword(s):  
Decision Making ◽  
Process Approach ◽  
Decision Makers ◽  
Analytic Hierarchy ◽  
Conflicting Objectives ◽  
Realistic View ◽  
Hierarchy Process ◽  
Pair Wise Comparison ◽  
Supplier Selection Problem ◽  
Selection Of

Decision problems are usually complex and involve evaluation of several conflicting criteria (parameters). Multi Criteria Decision Making (MCDM) is a promising field that considers the parallel influence of all criteria and aims at helping decision makers in expressing their preferences, over a set of predefined alternatives, on the basis of criteria (parameters) that are contradictory in nature. The Analytic Hierarchy Process (AHP) is a useful and widespread MCDM tool for solving such type of problems, as it allows the incorporation of conflicting objectives and decision makers preferences in the decision making. The AHP utilizes the concept of pair wise comparison to find the order of criteria (parameters) and alternatives. The comparison in a pairwise manner becomes quite tedious and complex for problems having eight alternatives or more, thereby, limiting the application of AHP. This paper presents a soft hierarchical process approach based on soft set decision making which eliminates the least promising candidate alternatives and selects the optimum(potential) ones that results in the significant reduction in the number of pairwise comparisons necessary for the selection of the best alternative using AHP, giving the approach a more realistic view. A supplier selection problem is used to illustrate the proposed approach.

scholarly journals A Multi-Criteria Decision Support Concept for Selecting the Optimal Contractor

2021 ◽  
Vol 11 (4) ◽  
pp. 1660 ◽  
Author(s):  
Ivan Marović ◽  
Monika Perić ◽  
Tomaš Hanak
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Project Performance ◽  
Decision Makers ◽  
Construction Project Management ◽  
Analytic Hierarchy ◽  
Conflicting Demands ◽  
Decision Making Problem ◽  
Scientific Approach ◽  
Hierarchy Process

A way to minimize uncertainty and achieve the best possible project performance in construction project management can be achieved during the procurement process, which involves selecting an optimal contractor according to “the most economically advantageous tender.” As resources are limited, decision-makers are often pulled apart by conflicting demands coming from various stakeholders. The challenge of addressing them at the same time can be modelled as a multi-criteria decision-making problem. The aim of this paper is to show that the analytic hierarchy process (AHP) together with PROMETHEE could cope with such a problem. As a result of their synergy, a decision support concept for selecting the optimal contractor (DSC-CONT) is proposed that: (a) allows the incorporation of opposing stakeholders’ demands; (b) increases the transparency of decision-making and the consistency of the decision-making process; (c) enhances the legitimacy of the final outcome; and (d) is a scientific approach with great potential for application to similar decision-making problems where sustainable decisions are needed.

Identification and prioritization of corporate sustainability practices using analytical hierarchy process

2015 ◽  
Vol 10 (1) ◽  
pp. 23-49 ◽  
Author(s):  
Praveen Goyal ◽  
Zillur Rahman ◽  
Absar Ahmad Kazmi
Keyword(s):  
Manufacturing Sector ◽  
Corporate Sustainability ◽  
Pollution Prevention ◽  
Analytic Hierarchy ◽  
Content Type ◽  
Scarce Resources ◽  
Sustainability Performance ◽  
Corporate Sustainability Performance ◽  
Sustainability Practices ◽  
Hierarchy Process

Purpose – The purpose of this paper is to identify and prioritize the corporate sustainability practices to improve the corporate sustainability performance in the manufacturing sector. Further, these practices are being prioritized to find out the essential practices to ensure logical allocation of limited resources. Design/methodology/approach – It examines the corporate sustainability practices which have been shortlisted from both the literature review and experts judgment. Then, analytic hierarchy process has been used to assess the identified 12 practices of corporate sustainability and to find their priorities for improvement of the corporate sustainability performance. Findings – Based on the hierarchical model developed in this study, the analysis reveals market value, environment management and strategy, research and development, pollution prevention, corporate governance and investor responsibility, which have been found to be the most important practices in improving the corporate sustainability performance. Practical implications – The findings of the study would be useful to the practitioners in the proper allocation of scarce resources to optimize the corporate sustainability performance of firms, especially the manufacturing entities. Originality/value – It is a fact that multi-faceted nature of corporate sustainability includes both subjective and objective dimensions. Therefore, prioritization of corporate sustainability at the factor level is one of the important contributions to the literature that has been addressed in the present study. The results of this paper may be generalized to the other sectors.

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