Decision Making: Applications in Management and Engineering

The existence of an asymmetric empirical Lorenz curve requires a measure of asymmetry that directly involves the geometry of the Lorenz curve as a component of its formulation. Therefore, establishing hypothesis testing for Lorenz curve asymmetry is necessary to conclude whether the Lorenz curve exhibits symmetry in actual data. Consequently, this study aims to construct a measure of Lorenz curve asymmetry that utilizes the area and perimeter elements of the inequality subzones as its components and establish a procedure for hypothesis testing the symmetry of the Lorenz curve. This study proposes two types of asymmetry measures, Ra and Rp, constructed based on the ratio of area and perimeter obtained from the inequality subzone. These measures effectively capture the asymmetric phenomenon of the Lorenz curve and provide an economic interpretation of the values Ra and Rp. The Lorenz curve symmetry hypothesis testing, based on Ra and Rp through a nonparametric bootstrap, yields reliable results when applied to actual data.

Muhammad Fajar

Setiawan Setiawan

Nur Iriawan

Decision Making Applications in Management and Engineering

The New Measures of Lorenz Curve Asymmetry: Formulation and Hypothesis Testing

洛伦兹曲线不对称性的新度量方法：公式化与假设检验

The continuous and systematic redesign of key business processes is very important for businesses and organizations that seek to achieve cost savings and efficiency enhancements. Selecting the most impactful processes and ensuring a successful redesign initiative remains an important topic that motivated the authors to conduct a Systematic Literature Review (SLR) on Business Process Redesign (BPR) Evaluation methodologies by applying an established eight-step SLR guide. The review sheds light on the current state of research and highlights the research gap by considering two dimensions of BPR artifacts: (a) the type of evaluation and (b) the generalizability of the existing approaches. The findings indicate that there is a lack of systematic methodologies in literature that properly evaluate the redesign capacity of models prior to implementation. Additionally, the existing methodologies do not cumulatively evaluate the quality characteristics that are necessary for BPR implementation or the applicability of BPR heuristics, and do not bear the generalizability to be readily used in a more general context. This paper aims to provide researchers with the necessary context and motivation to bridge this gap and further systematize BPR methodologies that can preselect the most suitable business processes for redesign.

George Tsakalidis

Kostas Vergidis

Business Process Redesign: A Systematic Review of Evaluation Approaches

业务流程再造：评估方法的系统综述

The purpose of this study is to develop a new approach for decision-making for addressing multi-attribute decision-making problems within a trapezoidal intuitionistic fuzzy environment, while taking into account decision makers' psychological behavior. As a starting point, we propose and apply a distance metric model for trapezoidal intuitionistic fuzzy numbers. Then, by incorporating the expected value, score function, and accuracy value, we create a novel approach by comparing it with the results obtained from the VIKOR multi-criteria decision-making technique, allowing us to account for decision makers' risk tolerance. Through correlation analysis, we assess the similarities and deviations in the resulting rankings. Finally, we illustrate the practical utility and feasibility of our proposed approach by evaluating the digital marketing capabilities of a few metaverse platforms using standards set in line with marketing mix criteria.

Ruth Isabels

Arul Freeda Vinodhini

Anandan Viswanathan

Evaluating and Ranking Metaverse Platforms Using Intuitionistic Trapezoidal Fuzzy VIKOR MCDM: Incorporating Score and Accuracy Functions for Comprehensive Assessment

评估和排名元宇宙平台使用直觉梯形模糊VIKOR多准则决策：结合分数和准确度函数进行综合评估

The global significant rise in the number of sick individuals and fatalities has made the ongoing struggle against the severe and lethal COVID-19 pandemic a global effort. There are several ongoing therapies for COVID-19, and more are being developed. However, selecting the best therapy option for COVID-19 patients is still needed. Patients may easily choose from the available COVID-19 therapies using the multi-criteria decision-making method. As a result, the present study provides an MCDM method that is created to determine COVID-19 therapies. Probabilistic Hesitant Fuzzy Set numbers, values, and ambiguity are introduced. Theorems and characteristics of PHFS numbers are also investigated in depth. The Complex Proportional Assessment technique is used, based on the PHFS, for dealing with ambiguity issues. This study uses ten criteria and three treatment methods: antibacterial medication and plasma treatment, vaccinations, as well as quarantine and in-house isolation. The study results reveal that quarantine and isolation at home mark the most effective treatment, followed by vaccinations with antibiotics and plasma therapy.

Ahmed M. Ali

Ahmed x Ahmed Abdelhafeez

Tamer H.M. Soliman

Khaled ELMenshawy

A Probabilistic Hesitant Fuzzy MCDM Approach to Selecting Treatment Policy For COVID-19

一种基于概率犹豫模糊多准则决策的COVID-19治疗策略选择方法

In modern society, e-commerce logistics services are replacing traditional manual transportation methods. However, fresh transportation challenges have emerged. This study proposes applying the factor constraint algorithm to the e-commerce logistics path transportation problem. The multi-objective constraints and optimization of node tasks, vehicle full load, route closure, and other issues in the process of logistics transportation are firstly carried out. The final target is the shortest path of logistics deliver. Then the genetic algorithm, particle swarm algorithm, and ant colony algorithm are integrated to obtain the HMOAC algorithm, and the logistics path transportation model is constructed. The research findings indicate that the HMOAC algorithm shows a high level of fit, with a 95% match compared to the ant colony algorithm. An example analysis of the algorithm can effectively optimize the target path and achieve the least expensive transportation cost.

Chen Li

Jingying Ke

Linghan Cai

Application Research of Factor Constraint Algorithm in E-Commerce Logistics Route Optimization

电子商务物流路径优化中因子约束算法的应用研究

Investigating algebraic structures in a non-conventional framework supplements mathematics for hard-nosed practical applications to the fields of theoretical biology and computer science. One such algebraic structure is multigroup whose underlying set is a multiset. The genome is the entire set of DNA instructions found within a cell which contains all the information needed for an individual to develop and function. DNA and RNA are the hereditary materials that play a vital role in the metabolism process of living things, especially protein synthesis. In genomic database DNA sequences are stored in the form of string or text data types. The only data that works with machine learning algorithms is numerical. Thus, it is necessary to transform DNA sequence strings to numerical values. This article is organized in the following manner. Firstly, we prove that standard genetic code is a multigroup and genome architecture of the whole population can be interpreted as the sum of multisets. Next, it is described how a numerical representation of DNA bases relates to its algebraic representation. We further employed Gated Recurrent Unit, Long Short-Term Memory, and Bidirectional Long Short-Term Memory to identify changes between the DNA sequences. Experimental results show that GRU with multiset-based numerical values for DNA bases offers 98% accuracy on testing data. This novel technique will aid in the detection of mutations in complex diseases.

Sanaa Anjum

Sajida Kousar

Nasreen Kausar

Nezir Aydin

Oludolapo Akanni Olanrewaju

Bongumenzi Mncwango

Digitizing DNA Sequences Using Multiset-Based Nucleotide Frequencies for Machine Learning-Based Mutation Detection

基于多集核苷酸频率的机器学习突变检测的DNA序列数字化

This review paper offers a comprehensive exploration of blockchain technology's integration in scheduling activities across various industries. It systematically gathered and analyzed literature, identifying 133 relevant documents through rigorous screening from 2017 till 2023. The bibliometric analysis, including co-authorship and co-occurrence maps, revealed key trends, influential authors, and emerging research areas. Content analysis focused on blockchain applications in service optimization, system and resource planning, management, project and production planning, energy optimization, and security enhancement. The research acknowledged significant advancements in these areas, particularly in terms of improved efficiency, transparency, and security. The findings underscore the potential of blockchain in revolutionizing scheduling and management processes across different sectors, highlighting the need for further exploration of its applications and implications in various professional contexts. The paper aims to bridge the gap in the literature by presenting a holistic view of blockchain's role in advancing scheduling methods, driving innovation, and fostering more robust, efficient, and transparent scheduling systems across industries.

Zied Bahroun

Abdulrahim Shamayleh

Moayad Tanash

Mustafa Rawshdeh

Haya Alastal

Integrating Blockchain in Scheduling: A Comprehensive Review of Current Trends and Future Directions

区块链在调度中的整合：当前趋势与未来方向的综合评述

Considering the interior of decision-making units (DMUs) is essential when evaluating a system's performance in the practical and real-world circumstances. Knowing what happens inside a DMU allows a more accurate study of relevant process. It identifies the efficiency, and inefficiency of the sub-units in the system being evaluated. This study focuses on two-stage inverse data envelopment analysis (DEA) problems. In these problems, a portion of the outputs from the first period is used as inputs in the second stage. For this purpose, several models are offered to address the input/output estimation problem, in which decision makers should deal with intermediate products and shared and non-shared inputs in a two-stage system. Furthermore, the proposed models are examined using a window DEA because of the importance of assessing repetitive processes in some two-stage systems. Next, an Iranian bank is considered as a case study to further elucidate using the presented models. Finally, we present a conclusion and suggestions for further research.

Haleh Moradi

Farhad Hosseinzadeh Lotfi

Mohsen Rostamy-Malkhalifeh

Inverse Data Envelopment Analysis Models for Inputs/Outputs Estimation in Two-Stage Processes

两阶段过程中输入/输出估计的逆数据包络分析模型

This paper examines the factors that influence humanitarian resilience, explicitly focusing on the mediating role of community engagement. Humanitarian resilience is a critical aspect of disaster management and response, and understanding the underlying factors and the role of community engagement in enhancing resilience is paramount. This study investigates the multifaceted factors influencing humanitarian resilience among the youth population of the Gaza Strip, focusing on the variables of humanitarian aid funding, logistical support, and humanitarian personnel. Employing quantitative research methodology and Structural Equation Modelling (SEM) techniques, we explore the mediating role of community engagement in shaping the dependent variable of humanitarian resilience. In a sample of 429 youth residing in the Gaza Strip, our research assesses the direct impacts of funding humanitarian assistance, logistical support, and the presence of humanitarian personnel on the participants' resilience levels. Furthermore, we examine how community engagement mediates the relationship between these factors and the overall level of humanitarian resilience. This innovative approach aims to provide a comprehensive understanding of the intricate dynamics in the context of humanitarian assistance in the Gaza Strip. The findings of this study hold significant implications for policymakers and humanitarian organizations operating in conflict-affected regions. By elucidating the mediating influence of community engagement, we shed light on potential strategies to enhance the resilience of individuals and communities in the face of adversity, ultimately contributing to the effectiveness of humanitarian efforts in the Gaza Strip and similar contexts worldwide.

Samia Nassar

Md Billal Hossain

Zsuzsanna Tóth Naár

Laszlo Vasa

Factors Affecting Humanitarian Resilience: A Mediating Approach of Community Engagement

影响人道主义韧性的因素：社区参与的调解方法

There is considerable promising in artificial intelligence (AI) and algorithms, with governments worldwide increasingly investing in this transformative technology. The potential benefits include improved performance, cost reduction, efficient management, and crime prediction and prevention, among others. The AI era holds the promise of revolutionizing various aspects of society. However, as countries prepare to leverage the power of artificial intelligence, questions arise about the validity of rankings published on the readiness of the governments for the application of AI. In this article, the weighting criteria that are analysed in the Oxford Insights AI Readiness Index are scrutinized, aiming to provide a more accurate assessment. Instead of conventional averaging, arithmetic and geometric non-linear functions are employed to analyse and assess the rank of the countries. Through clustering analysis, countries are categorized into three distinct groups based on observed criteria, offering a nuanced perspective on government AI readiness. This clustering approach not only facilitates a more effective categorization of countries based on their AI preparedness, but also accentuates the variations and similarities within each cluster, which enables deeper insights into regional trends and pinpoint targeted strategies for enhancement within each cluster.

Mahyuddin K. M. Nasution

Marischa Elveny

Dragan Pamucar

Milena Popovic

Bisera Andrić Gušavac

Uncovering the Hidden Insights of the Government AI Readiness Index: Application of Fuzzy LMAW and Schweizer-Sklar Weighted Framework

揭示政府人工智能准备指数的隐含洞察：模糊LMAW与Schweizer-Sklar加权框架的应用

ISSN	2560-6018, 2620-0104
h-index	37

涉及主题	计算机科学数学工程类人工智能经济机器学习运筹学业务哲学数学优化语言学物理程序设计语言法学政治学模糊逻辑统计选择（遗传算法）量子力学营销
出版信息	出版商: Regional Association for Security and crisis management，出版周期: ，期刊类型: journal，开源期刊: 是
基本数据	创刊年份: 2018，原创研究文献占比: 0.00%，自引率:N.A.， Gold OA占比: 0.00%
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Decision Making: Applications in Management and Engineering

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