The imperatives of occupational health and safety (OHS) are increasingly recognised as critical components of business operations, particularly within logistics where manual tasks such as item picking and transportation present notable hazards. This study employs the Fine-Kinney method to conduct a risk analysis of internal transport activities in logistics systems. Hazards associated with various internal transport mediums are systematically identified and categorised. An illustrative case study involves a logistics provider based in Serbia, scrutinising the risks prevalent within warehouse operations. Through application of the Fine-Kinney method, the analysis determines the predominant risk to be collisions involving pedestrians. In response, the study advocates targeted preventive and corrective strategies to diminish these risks. Theoretical and practical contributions arise from addressing these identified risks, offering valuable insights for logistics enterprises. The emphasis on preemptive safety measures underscores their significance in safeguarding worker welfare and enhancing the efficiency of logistics operations.
Investigation into the nexus between financial crises and the current account deficit within Iran’s economy was conducted, utilising time-series data spanning from 1989 to 2022. Augmented Dickey-Fuller (ADF) test validations endorsed stationarity of all variables upon first differencing. Through the deployment of Johansen's cointegration methodology, a long-term positive impact of real exchange rate oscillations on the trade deficit was discerned. Furthermore, the implementation of an error correction model (ECM) furnished additional perspectives regarding the dynamic interplay amongst the variables under consideration. The findings elucidate the repercussions of financial crises on Iran’s current account deficit, revealing a palpable influence of exchange rate volatilities on economic stability and providing insights into the nuanced macroeconomic relationships amidst periods of fiscal turmoil. The research underscores the exigency for robust fiscal and monetary strategies to navigate the intricacies of economic vulnerabilities and fortify against ensuing financial perturbations.
Ordering of quotients is a critical aspect of cost-efficiency problems, which hold significant interest and importance for suppliers of goods and services as well as consumers. Comparisons (ordering) are straightforward when dealing with ordinary numbers, yet in many instances, the data are imprecise, vague, or subject to seasonal variations. Consequently, such data may be unknown or derive from expert opinions. Unlike ordinary numbers, fuzzy data render quotients only partially ordered. This study examines the linear ordering of quotients with fuzzy data, expressed in terms of confidence intervals, $\alpha$-cuts, or piecewise quadratic fuzzy numbers (PQFNs), within the context of cost-efficiency problems. Moreover, the challenges associated with quotient ordering in cost-efficiency problems are introduced.
In the rapidly evolving industrial landscape, the decision-making process concerning which products to manufacture, their quantity, and the methods of their production has become pivotal. This study endeavors to address this need by advocating the most apt functional form of the production process for predominant manufacturing sectors. The central objective has been the maximization of output through the application of the Cobb-Douglas production function, investigated separately for both two-input and three-input scenarios. It is ascertained which of the two models exhibits greater efficacy. Subsequently, parameters of the production function are estimated utilizing advanced optimization subroutines.
In the quest to reduce occupational accidents and diseases, the ergonomic performance levels of industries remain pivotal. Within this context, the metal industry in Türkiye, notorious for ergonomic challenges, was scrutinised regarding its occupational health and safety (OHS) indicators. Five pivotal criteria were employed to delineate the industry's performance: the incidence of occupational accidents, the occurrence of fatal occupational accidents, the reporting rate of occupational diseases, the cumulative days of temporary incapacity, and the overall count of insured individuals obtaining permanent incapacity benefits. A decadal period, spanning 2013-2022, served as the temporal backdrop for this examination. Utilising the VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method, an esteemed Multiple-Criteria Decision-Making (MCDM) technique, an assessment was conducted to ascertain the years marred by sub-optimal ergonomic performance. Notably, 2014, 2013, and 2020 were identified as the least problematic years, whereas 2022 emerged as the most critical year. This investigation underscores the imperative for strategic planning to augment ergonomic conditions in professional settings in light of OHS, particularly in recent times.
IT, increasingly recognized as a vital contributor to competitive advantage, plays an indispensable role in augmenting business value. Effective implementation of IT Governance (ITG) mechanisms, comprising structures of responsibility, control processes, communication protocols, and decision rights, has been found to foster alignment between IT and business objectives. Such alignment is particularly critical for Small and Medium-sized Enterprises (SMEs), where the amplified business value can be realized. Yet, SMEs often grapple with challenges in implementing ITG, owing to resource constraints, communication hurdles, resistance to change, and technological complexity. The present study delves into this complex dynamic within a medium-sized industry located in southern Minas Gerais, Brazil, investigating the deployment of ITG mechanisms as a means to enhance business value through IT. An interpretivist approach characterizes the qualitative, inductive study, drawing on a case study to probe the links between ITG mechanisms, IT capabilities, and business value. Four hypotheses are put forth in the discourse, shedding light on the intricate relationships that these elements share. The findings indicate that ITG mechanisms exert a positive impact on IT business value, albeit with identifiable weaknesses and potential areas for enhancement. More effective alignment between IT and business can be achieved by addressing these shortcomings, thereby mitigating risks such as demotivation among IT professionals and resistance to change.
The prevalent economic principle of weak disposability has been the foundation for studies in environmental assessment using Data Envelopment Analysis (DEA). Recently, a shift from classical free disposability to weak disposability has been observed as an emerging trend for treating undesirable factors in research. Weak disposability is perceived to have significant analytical power in measuring the efficiency of Decision-Making Units (DMUs). Addressing the increment of undesirable inputs, a non-radial model grounded on a non-uniform augment factor is presented. The application of this proposed model anticipates a suitable quantity for the increment of undesirable inputs. Concurrently, the model ensures a corresponding reduction in desirable inputs. Numerical instances illuminate the practicality and robustness of the proposed model and demonstrate its superior performance over its original counterpart.
The prevalence of decision-making methodologies catering to quantitative attributes considerably overshadows those designed for qualitative attributes. This study seeks to address this gap by extending the traditional Ideal Solutions with Constraint on Values (ISOCOV) method to a fuzzy environment, thereby enhancing its capability to handle optimal decision-making based on qualitative attributes. In this improved method, $\alpha$-cut representations are employed for managing linguistic value constraints in performance-oriented data. The proposed approach is then utilized for the selection of nanomaterials, evaluated based on five essential criteria. By subjecting the performance-based decision matrix to the modified fuzzy method, a ranking of alternatives is derived. Compared to its traditional counterpart, this fuzzy-enhanced ISOCOV method demonstrates enhanced efficiency in processing qualitative data, promising its potential compatibility and utility for decision makers dealing with performance-oriented decision-making.
This study introduces a novel approach to decision-making problems, especially in the context of hard disk selection, using the concept of the fuzzy parameterized single-valued neutrosophic soft set (FP-SVNSS). Primarily, the focus is on assigning different levels of importance to each parameter within the set, which enables a more nuanced and flexible evaluation process. This is underpinned by the development of several related concepts and the definition of basic operations such as complement, subset, union, and intersection. In the quest for clarity, the nuances of these operations and the overall framework of the FP-SVNSS method are illustrated via numerous examples. The superiority of the FP-SVNSS method over other decision-making methods is affirmed through a comprehensive comparison. The unique strength of the proposed approach lies in its ability to handle imperfect, ambiguous, and inconsistent data. Consequently, it offers greater accuracy and practicality than existing models. In the latter part of the study, the theory is put to the test by tackling a real-world decision-making problem. The selected case involves the optimal selection of hard disks, a common issue in information technology procurement. The successful application of the FP-SVNSS method to this issue provides a compelling demonstration of its potential value in practical settings. Through the exploration of this innovative decision-making methodology, this research contributes to the broader field of soft computing and decision-making theory. The findings suggest a myriad of future applications of the FP-SVNSS method in dealing with various complex and fuzzy problems in both academic and industrial contexts.
Neutrosophic sets, expanded from the constructs of fuzzy and intuitionistic fuzzy sets, can accommodate degrees of truth, indeterminacy, and falsity for each element. This attribute equips them with an aptitude for a more refined interpretation of ambiguous or uncertain data. This study presents an innovative application of Neutrosophic Data Envelopment Analysis (Neu-DEA), incorporating pentagonal neutrosophic numbers in both input and output data. This novel methodology involves the transformation of traditional DEA models into a Pentagonal neutrosophic DEA model, subsequently converting it into a Crisp Linear Programming (CrLP) model. A unique ranking function is integral to this process. Performance evaluation of decision-making units (DMUs) is accomplished through the resolution of the CrLP model, with subsequent ranking of the DMUs based on their relative efficiency scores. The utility and effectiveness of this novel technique is validated through a numerical example.
This study emphasizes the limitations observed in the prevailing neutrosophic AHP group decision-making model. To address these limitations, an augmented neutrosophic AHP group decision-making model has been established, leveraging the potential of neutrosophic trapezoidal numbers. A comprehensive exploration of a key property of the neutrosophic trapezoidal pairwise comparison matrix is performed in this research, revealing that the current model inadequately maintains the reciprocal property of the neutrosophic trapezoidal pairwise comparison matrix. A real-world decision-making problem is resolved utilizing the introduced model, and a comparative analysis is furnished between the pre-existing neutrosophic AHP group decision-making model and the revised version. The results unequivocally demonstrate the superiority of the enhanced model.
The present study scrutinizes the decision-making strategies and enhancement techniques aimed at minimizing progressive collapse in steel moment frame structures. Comparative analyses of both three-story and five-story frames were carried out, focusing on the reinforcement of external frames through the introduction of bracing. Employing ABAQUS, a sophisticated finite element software, simulations of these frames resulted in the exploration of 16 unique steel frame configurations. In an assessment of column loss impact, the middle column of the lowest story in the supporting frame was deliberately removed. Findings reveal that the axial force of the beams adjacent to the removal site in the three-story frame escalates approximately 2.15 times in relation to the values connected with corner beam extraction. Conversely, the increase in axial force of the beams adjacent to the column removal in the five-story frame varied between 5% and 49% of the respective values for beam removal conditions. Furthermore, a reduction in maximum displacement was found to correlate with an increase in the number of stories. Maximum displacements in five-story frames were observed to be roughly 7% to 22% of the corresponding values in three-story frames, with variability depending on the location of the removed column. These results indicate that the effectiveness of bracing-based reinforcement to prevent progressive collapse in steel moment frame structures intensifies with the increase in the number of stories. This performance enhancement against progressive collapse becomes particularly significant for structures comprising a higher number of stories.
Linear programming problems (LPP) have been widely used to address real-world problems, including the stock portfolio problem. In this study, an approach is proposed that incorporates Pythagorean fuzzy numbers (PFN) in the rate of risked return, portfolio risk amount, and expected return rate. The problem is transformed into a deterministic form using the scoring function, and a solution algorithm is being developed to provide portfolio investment choices. One of the key features of this study is the investor's ability to choose risk coefficients to increase expected returns and set their circumstances while determining their strategies. The optimum return rate is identified using the TORA program. An example is provided to demonstrate the efficiency and reliability of the method.
In today's rapidly changing economic environment, the success of organizations is largely determined by their organizational efficiency. The impact of innovation and strategic planning on organizational performance is the focus of this study, which was conducted in 2022 among middle-level managers and employees of public and private sector hospitals. A total of 63 questionnaires were collected, resulting in a response rate of approximately 72.41%. Structural equation modeling with Smart PLS3 software was utilized to examine the relationships between the variables. The results indicate that organizational performance is positively impacted by innovation. Furthermore, the study found that the performance of organizations is positively influenced by strategic planning. These findings have significant implications for managers and decision-makers in the healthcare sector and can inform the development of effective strategies for improving organizational performance.
Effective decision-making relies on access to timely and accurate information, which is widely regarded as a valuable asset in the capital market. Accounting information is no exception, and it is critical for managers to provide such information promptly to advance their firms' economic activities. This study investigates the relationship between managers' ability and the timeliness of financial reporting, testing three research hypotheses through linear regression analysis. The statistical population comprises 115 firms listed on the Tehran Stock Exchange between 2012 and 2021, with 1150 firm-year observations. The delay in the auditor's report serves as a proxy for financial reporting timeliness. Managers' abilities are measured using Demerjian et al.'s model [1]. The findings reveal a significant, positive relationship between managerial ability and the timeliness of financial reporting, indicating that higher managerial ability is associated with lower financial reporting delay. Additionally, the results suggest that the relationship between managerial ability and financial reporting timeliness is moderated by the size of the auditing firm and the firm itself.
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