APPLICATION OF HYBRID DIBR-FUCOM-LMAW-BONFERRONI-GREY-EDAS MODEL IN MULTICRITERIA DECISION-MAKING

The selection of unmanned aerial vehicles for different purposes is a frequent topic of research. This paper presents a hybrid model of an unmanned aerial vehicle (UAV) selection using the Defining Interrelationships Between Ranked criteria (DIBR), Full Consistency Method (FUCOM), Logarithm Methodology of Additive Weights (LMAW) and grey - Evaluation based on Distance from Average Solution (G-EDAS) methods. The above-mentioned model is tested and confirmed in a case study. First of all, in the paper are defined the criteria conditioning the selection, and then with the help of experts and by applying the DIBR, FUCOM and LMAW methods, the weight coefficients of the criteria are determined. The final values of the weight coefficients are obtained by aggregating the values of the criteria weights from all the three methods using the Bonferroni aggregator. Ranking and selection of the optimal UAV from twenty-three defined alternatives is carried out using the G-EDAS method. Sensitivity analysis confirmed a high degree of consistency of the solutions obtained using other MCDM methods, as well as changing the criteria weight coefficients. The proposed model has proved to be stable; its application is also possible in other areas and it is a reliable tool for decision-makers during the selection process

Analyzing factors affecting patient satisfaction using the Kano model

Customer needs associated with the healthcare sector are constantly evolving with the technological advancements, rising costs, and shifts in patient demographics. Challenges associated with understanding patient needs impact the quality of care and life, safety, and satisfaction. The objective of this research was to develop a methodology to collect and analyze the needs associated with healthcare units that differ based on the type of care and services and patient perceptions over time. The proposed methodology provides insights into the voice of the customer through visualization of the relationship between the performance of quality attributes and customer satisfaction. Cronbach\u27s alpha is employed in the proposed methodology to ensure internal consistency of the instrument used to gather the voice of the customer. In addition, the chi-square test for goodness of fit is included in the proposed methodology to test the distribution. The Fisher\u27s exact test value (p) from the Chi-square test of independence is used to evaluate patients\u27 responses and effect sizes were analyzed using Cramer\u27s V to determine the magnitude of effect between the variables. These steps enabled patient responses to be compared by demographics. The proposed methodology was validated through a study of the factors affecting patient satisfaction related to health services. The analysis suggests that the patient responses can be evaluated using the demographic factors. The study suggests that the proposed methodology is beneficial in understanding the growing patient complexity, and maintaining ongoing efforts into understanding patient needs by tracking them over time and with shifts in the demographic environments --Abstract, page iv

Integrated supplier selection framework in a resilient construction supply chain: An approach via analytic hierarchy process (AHP) and grey relational analysis (GRA)

Construction supply chain management is a unique and problematic issue within the construction industry due to its inevitable external risks and variations. The resilience capability of a supplier is of significance in supplier selection; a supplier selected in the context of a resilient construction supply chain (RCSC) is referred to in this research as a "resilient construction supplier". This paper proposes a supplier selection framework tailored to effective information integration for supply chain management. The proposed framework works by integrating building information modeling (BIM) and a geographic information system (GIS) in a RCSC. BIM and GIS together provide highly transparent construction material information, enhanced supply chain status visualization, and workable access information for supplier selection. Supplier performance is evaluated via seventeen resilient criteria under a combined methodology consisting of the analytic hierarchy process (AHP) and grey relational analysis (GRA); AHP and GRA weigh the criteria and rank the suppliers respectively. By varying the weightings given to each criterion, sensitivity analysis was conducted to identify the criteria of resilience which impact the selection priorities of suppliers. An illustrative example is also provided to show the overall process of the proposed framework

ERP implementation methodologies and frameworks: a literature review

Enterprise Resource Planning (ERP) implementation is a complex and vibrant process, one that involves a combination of technological and organizational interactions. Often an ERP implementation project is the single largest IT project that an organization has ever launched and requires a mutual fit of system and organization. Also the concept of an ERP implementation supporting business processes across many different departments is not a generic, rigid and uniform concept and depends on variety of factors. As a result, the issues addressing the ERP implementation process have been one of the major concerns in industry. Therefore ERP implementation receives attention from practitioners and scholars and both, business as well as academic literature is abundant and not always very conclusive or coherent. However, research on ERP systems so far has been mainly focused on diffusion, use and impact issues. Less attention has been given to the methods used during the configuration and the implementation of ERP systems, even though they are commonly used in practice, they still remain largely unexplored and undocumented in Information Systems research. So, the academic relevance of this research is the contribution to the existing body of scientific knowledge. An annotated brief literature review is done in order to evaluate the current state of the existing academic literature. The purpose is to present a systematic overview of relevant ERP implementation methodologies and frameworks as a desire for achieving a better taxonomy of ERP implementation methodologies. This paper is useful to researchers who are interested in ERP implementation methodologies and frameworks. Results will serve as an input for a classification of the existing ERP implementation methodologies and frameworks. Also, this paper aims also at the professional ERP community involved in the process of ERP implementation by promoting a better understanding of ERP implementation methodologies and frameworks, its variety and history

Analysis of Decision Support Systems of Industrial Relevance: Application Potential of Fuzzy and Grey Set Theories

The present work articulates few case empirical studies on decision making in industrial context. Development of variety of Decision Support System (DSS) under uncertainty and vague information is attempted herein. The study emphases on five important decision making domains where effective decision making may surely enhance overall performance of the organization. The focused territories of this work are i) robot selection, ii) g-resilient supplier selection, iii) third party logistics (3PL) service provider selection, iv) assessment of supply chain’s g-resilient index and v) risk assessment in e-commerce exercises. Firstly, decision support systems in relation to robot selection are conceptualized through adaptation to fuzzy set theory in integration with TODIM and PROMETHEE approach, Grey set theory is also found useful in this regard; and is combined with TODIM approach to identify the best robot alternative. In this work, an attempt is also made to tackle subjective (qualitative) and objective (quantitative) evaluation information simultaneously, towards effective decision making. Supplier selection is a key strategic concern for the large-scale organizations. In view of this, a novel decision support framework is proposed to address g-resilient (green and resilient) supplier selection issues. Green capability of suppliers’ ensures the pollution free operation; while, resiliency deals with unexpected system disruptions. A comparative analysis of the results is also carried out by applying well-known decision making approaches like Fuzzy- TOPSIS and Fuzzy-VIKOR. In relation to 3PL service provider selection, this dissertation proposes a novel ‘Dominance- Based’ model in combination with grey set theory to deal with 3PL provider selection, considering linguistic preferences of the Decision-Makers (DMs). An empirical case study is articulated to demonstrate application potential of the proposed model. The results, obtained thereof, have been compared to that of grey-TOPSIS approach. Another part of this dissertation is to provide an integrated framework in order to assess gresilient (ecosilient) performance of the supply chain of a case automotive company. The overall g-resilient supply chain performance is determined by computing a unique ecosilient (g-resilient) index. The concepts of Fuzzy Performance Importance Index (FPII) along with Degree of Similarity (DOS) (obtained from fuzzy set theory) are applied to rank different gresilient criteria in accordance to their current status of performance. The study is further extended to analyze, and thereby, to mitigate various risk factors (risk sources) involved in e-commerce exercises. A total forty eight major e-commerce risks are recognized and evaluated in a decision making perspective by utilizing the knowledge acquired from the fuzzy set theory. Risk is evaluated as a product of two risk quantifying parameters viz. (i) Likelihood of occurrence and, (ii) Impact. Aforesaid two risk quantifying parameters are assessed in a subjective manner (linguistic human judgment), rather than exploring probabilistic approach of risk analysis. The ‘crisp risk extent’ corresponding to various risk factors are figured out through the proposed fuzzy risk analysis approach. The risk factor possessing high ‘crisp risk extent’ score is said be more critical for the current problem context (toward e-commerce success). Risks are now categorized into different levels of severity (adverse consequences) (i.e. negligible, minor, marginal, critical and catastrophic). Amongst forty eight risk sources, top five risk sources which are supposed to adversely affect the company’s e-commerce performance are recognized through such categorization. The overall risk extent is determined by aggregating individual risks (under ‘critical’ level of severity) using Fuzzy Inference System (FIS). Interpretive Structural Modeling (ISM) is then used to obtain structural relationship amongst aforementioned five risk sources. An appropriate action requirement plan is also suggested, to control and minimize risks associated with e-commerce exercises

A Novel Evaluation Approach for Tourist Choice of Destination Based on Grey Relation Analysis

The decision-making process of choosing an ideal tourism destination is influenced by a number of psychological and nonpsychological variables. Tourists need a method to quickly and easily select a suitable destination. Driven by this practical decision issue, a novel approach of tourist destination evaluation, grey relation analysis (GRA), is developed and applied to the ranking evaluation of Taiwan tourism destinations in China. In the evaluating process, we apply entropy to calculate the weight of each index, which is a more objective method of calculating weights. The results of the study indicate that although the same size is small and the distribution of data is unknown, GRA can still be successfully used in evaluating tourist destinations. In addition, we compare the GRA results with the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and show that more accurate ranking results can be obtained

Analysis of industry 4.0 implementation in mobility sector: An integrated approach based on QFD, BWM, and stratified combined compromise solution under fuzzy environment

The role of new technologies in industrial and service sector is inevitable. Various sectors like transport / mobility have decided to remodel and redesign their infrastructures by implementing innovative devices and strategies. Transport / mobility sector is one of the most fast-growing industries which demands innovative solutions, however, it will be complex to derive optimal decision while one confront uncertain conditions and variables. In this paper, we develop a decision support system for technology adoption in transport / mobility division within the context of Industry 4.0 considering a case study in Spain. To find the adopted technology in this sector, several alternatives (options) and variables (criteria) should be assumed. We propose an integrated decision-making system including quality function deployment (QFD) and best-worst method (BWM) to find the importance weight of each criterion. After we apply the stratified Combined compromise solution (S-CoCoSo) to rate the alternatives and rank them under a multi-scenario perspective. The results will be analyzed through some sensitivity analysis actions. The novelty of our proposed decision support model contributes to the mobility sector and releases guidelines to managers and policy makers