1. Introduction
Decision-making (DM) is one of today's most exciting research fields in management, economics, business and other sciences (Holian, 2006). Furthermore, organizational research methods as strong tools for benchmarking and efficiency evaluation play critical roles in organizational and management studies, including qualitative and quantitative approaches (Holian, 2006; Brewerton and Millward, 2001; Plowman and Smith, 2011; Symon and Cassell, 2012). However, in the various challenging real-world problems, especially in management and organizational complexities, the observed values of the data are often imprecise or vague because of incomplete and/or non–obtainable information. Uncertainty modeling plays a crucial role in managing data imprecision by simulating the DM process of humans with incomplete or erroneous facts (Symon and Cassell, 2012; Dequech, 2000; Brown, 2020; Morrison, 2021).
Numerous essential and ground-breaking studies have previously been conducted in uncertainty modeling, which has seen recent rapid advancements. There are various ways to handle these uncertainties. Fuzzy logic is an approach to calculating the values based on “degrees of truth” instead of the usual Boolean “true or false” logic. Zadeh (1965) first introduced the term fuzzy sets (FSs) against certain logic where the membership degree is a real number between zero and one. However, Zadeh's FSs cannot deal with certain cases in which it is difficult to define the membership degree using one specific value. To overcome this lack of knowledge, Atanassov (1986) introduced an extension of the FSs called the intuitionistic fuzzy sets (IFSs). Although these concepts can handle incomplete information in various real-world issues, they cannot address all types of uncertainty, such as indeterminate and inconsistent information. As a generalization of FSs, IFSs, picture FSs, Pythagorean FSs, and spherical FSs, the neutrosophic theory originated by Smarandache (1999). Neutrosophic set (NS) can deal with uncertain, indeterminate and incongruous information where the indeterminacy is quantified explicitly and truth membership, indeterminacy membership and falsity membership are completely independent. It can effectively describe uncertain, incomplete and inconsistent information and overcome some limitations of the existing methods in depicting uncertain decision information. Moreover, some extensions of NSs, including interval neutrosophic set (Ye, 2014; Garg, 2018; Zavadskas et al., 2021), bipolar NS (Akram and Smarandache, 2018; Zhan et al., 2019), single-valued NS (Edalatpanah, 2019; Karabašević et al., 2020), simplified NSs (Köseoğlu et al., 2020), multi-valued NS (Peng et al., 2017), neutrosophic linguistic set (Garg, 2019); and neutrosophic structured element (Edalatpanah, 2020a) have been presented.
Furthermore, this logic has been applied in various domains of science and engineering such as supply chain management (Abdel-Baset et al., 2019) performance evaluation (Edalatpanah, 2020b), knowledge management (Zuñiga et al., 2019), human resource management (Liang et al., 2018), tourism management (Bhaumik et al., 2021), learning management system (Radwan et al., 2016), traffic control management (Nagarajan et al., 2019), quality management system (Refaat and El-Henawy, 2019), medical diagnosis (Dhar, 2021), etc. In addition, some generalizations of NSs, such as the Plithogenic set (Smarandache, 2018), have been proposed in recent years. Therefore, we call NSs with their generalizations and variants, the neutrosophical approach. This special collection aims to compile recent developments in methodologies, techniques and applications of neutrosophical approaches in management and organizational research methods for various practical problems.
2. Published research
The special issue entitled “The neutrosophical approach: applications in management decision and organizational research methods” includes nine accepted publications out of a significant number of submissions after rigorous peer review.
Zhang et al. (2023a) presented a combined TODIM-BSC and neutrosophical method for assessing the performance of a private insurance company. Using the balanced scorecard (BSC) system, they identified the performance assessment indicators, analyzed the performance of the insurance company's agencies, and ranked them utilizing the TODIM DM technique. The practicability and efficacy of the proposed model were validated by a case study of private insurance agencies based on 26 criteria of agencies.
Single-valued neutrosophic sets (SVNSs) are useful measures for addressing potential complexity issues with three components: indeterminacy, truthfulness and falsity. Farid et al. (2023) developed some new aggregation operators (AOs) for information fusion of SVNNs to tackle multi-criteria group decision-making (MCGDM) issues by using SVNSs. Motivated by the characteristics of Einstein operators, they introduced two novel hybrid AOs: the “single-valued neutrosophic Einstein prioritized weighted average (SVNEPWA) operator” and the “single-valued neutrosophic Einstein prioritized weighted geometric (SVNEPWG) operator”. In addition, a comparative analysis and authenticity analysis of the proposed MCGDM technique with existing approaches are provided to evaluate its applicability, validity and superiority.
There are numerous transportation and solid transportation problems (STP) methods in the transportation literature in crisp, FSs and IFSs situations. Nonetheless, STP has never been investigated with NSs. Qiuping et al. (2023) attempted to address this void by developing an alternative method of solving this model with NSs. First, triangular neutrosophic numbers (TNNs) were employed to symbolize demand, transit capacity, accessibility and cost. Then, the neutrosophic STP was transformed into an interval programming problem using the idea of variation degree. The optimal solution's lower and upper bounds were then retrieved using two basic linear programming models. The findings show that the proposed model is not overly complex but more adaptable and applicable to practical problems. The effectiveness of the proposed algorithm is also demonstrated by the fact that it enables decision-makers to define their tolerances for uncertainty, falsity and acceptance.
Hezam et al. (2023) studied sustainable transport investment projects (STIP) based on a discrimination metric. They analyzed the most suitable transport project, one of the most important aspects of transport infrastructure schedules. To address the STIP assessment issue within SVNSs, they discussed a complex proportional assessment (COPRAS) paradigm. A SVNS is a valuable process to handle uncertainty to make the operation more useful when dealing with uncertain characteristics. First, a novel discriminating measure for SVNSs is presented, along with a discussion of its elegant qualities for determining the significance degree or weight values of criteria from a sustainability standpoint. Second, an integrated strategy based on the discrimination measure and the COPRAS method is introduced for SVNSs. Finally, comparison and sensitivity analyses demonstrate the robustness and reliability of the proposed framework.
A NS is more adaptable than an IFS because it evaluates indeterminacy with a second component and does not depend on its uncertain features. As time goes on, it becomes clear that NSs are not up to the task of being a parameterization tool, so the idea of a soft set (SS) is introduced. SS uses approximate mapping to determine the degree to which objects in the initial universe correspond to prescribed attributes, thereby providing a measure of uncertainty. The neutrosophic soft set (NSS) is then characterized to give NS a parameterization mode. In real-world DM scenarios, such as medical diagnosis, product selection, recruiting procedure, etc. additional classification of parameters into their relevant sub-parametric valued non-overlapping groups is often observed. Using its aggregation procedures and decision-support system, Zhao et al. (2023) defined an unique neutrosophic hypersoft set hybrid termed possibility single-valued neutrosophic hypersoft set (psv-NHSS) for evaluating investment projects. The adopted technique is implemented in a real-world situation involving the investment evaluation of a hydroelectric power station project. Single-valued neutrosophic parameterized complex fuzzy hypersoft set (sv-NPCFHSS) is a novel neutrosophic hypersoft set hybrid that Zhang et al. (2023b) characterized, along with its aggregation operations and decision-support system for evaluating real estate residential projects by monitoring various risk factors. The suggested model possesses the characteristics of the majority of existing fuzzy SS-like models and addresses their drawbacks.
As a crucial step in assuring the efficacy of their operations, companies have welcomed the incorporation of sustainable policies and practices throughout the supply chain. Sustainable supply chain management (SSCM) practices provide businesses with a number of benefits, as evidenced by research and operational programs of enterprises. These benefits include, among others, improved environmental, social and economic performance, as well as a heightened ecological consciousness. Therefore, Aytekin et al. (2023) investigated the performance-influencing factors and theories of SSCM in the textile industry using a neutrosophic approach. To accomplish this, the MULTIMOORA-mGqNN process is used to evaluate the literature review's extracted parts. Results demonstrated that SSCM performance is crucial for guaranteeing corporate success and competitiveness, achieving customer satisfaction and leaving the environment in a desirable condition for future generations.
The role of entrepreneurship as a growth engine in economic systems is distinctive. Consequently, governments need to encourage entrepreneurship if they want to thrive in the long run. Practical measurements are the key to elevating the impact of this entrepreneurial advocacy. In light of this, Wang et al. (2023) developed a novel integrated dynamic multi-attribute decision-making (MADM) model based on NS for evaluating government entrepreneurship support. In addition, they presented a dynamic neutrosophic weighted geometric operator to aggregate dynamic neutrosophic information due to the fluctuation in the size of indicators across distinct periods. The results demonstrate the adaptability of the DM-based paradigm.
Smarandache established two distinct neutrosophic components. One of these methods is the neutrosophic numerical components, which consist of the aforementioned three variables. The other variety, which he designated as Neutrosophic Numbers (NN), consists of literal neutrosophic parts. NN consists of a crisp parameter and a value with a literal indeterminacy parameter (I), and can explain the restricted confident and restricted indeterminate information using formula A = a + bI. To evaluate the safety performance in building projects, Li et al. (2023) suggested a framework based on the combination of data envelopment analysis (DEA) and NN to expose deficiencies with the rational measurement and recommend possible strategies. This hybrid model evaluates a new approach as an indicator of safety performance, and several units are compared. Results indicate that initiatives with a greater focus on safety concerns, like as training and equipment, are more efficient.
3. Concluding remarks
In this special issue, nine papers illustrate the application of various modeling and optimization techniques in neutrosophical environments to real-world problems. This collection of scientific works provides us with a rare opportunity to obtain a deeper grasp of the interdisciplinary approach and the relationships between diverse research subjects.
As guest editors, we extend our sincere gratitude to the reviewers who gave us invaluable feedback while revising the articles and evaluating them. Last but not least, we would like to extend our greatest appreciation to the respected individuals who made it possible for us to realize our ideas and who offered an exceptional and welcoming environment for this special edition. Lastly, we would also like to thank all authors for their contributions. This project only materialized due to their diligence, dedication and foresight.
The guest editors would like to thank the authors for their contributions to this Special Issue.
