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The Impact of COVID-19 Pandemic on Tourism Employees: Was It the Last Straw?
No full textTourism, as one of the most vulnerable industries, has survived numerous global crises with substantial negative impact on economies, communities, businesses, and individuals. Despite the circumvention of the industry after those experiences of mild and severe crises, COVID-19 pandemic has been the most serious case with deep global impact in every corner of the world leading to the explosion of academic research on a plethora of pandemic aspects. However, research offering insights on tourism and hospitality employees' experiences, is scarce in the relevant literature in spite of the chronic problems of employee retention, qualified and long-term labor force. Therefore, the aim of this study addresses at examining the experiences of hotel employees in T & uuml;rkiye during and after COVID-19, which caused sudden and deep changes in the lives following the severe decline in tourism employment and economic problems it ushered in. The data was collected through in-depth interviews with 21 individuals who formerly worked in city or resort hotels at various positions and departments. Two sensemaking perspectives were integrated to find out the consequences of the pandemic leading to the causes and factors to end working in the industry. Study findings offer important insights into pandemic-related dynamics and could support the development of effective tourism policy and practices leading to improve crisis management efforts in the tourism and hospitality industry.Social Science Citation Inde
An Integrated Decision-Making Framework to Evaluate the Route Alternatives in Overweight/Oversize Transportation
No full textOverweight and oversized transport (O&OT) has become one of the most critical elements of project logistics, driven by advancements in transportation and lifting technologies that now allow high-volume loads to be moved across long distances. This type of transportation operation, also called abnormal transportation, is greatly affected by technical factors such as the weight and geometry of the load, road surface, axle load limitations, slope, and ground strength, as well as external variables such as weather conditions, traffic density, and legal regulations. In planning and operational processes, Decision-Makers (DMs) and practitioners who plan and execute operations without adequately considering these factors and variables can lead to delays in operations, serious risks, and loss of productivity. This research proposes a flexible decision support model that integrates Step-wise Weight Assessment Ratio Analysis (SWARA) and Logarithmic Percentage Change-driven Objective Weighting (LOPCOW), and a ranking technique; i.e., Mixed Aggregation by Comprehensive Normalization Technique (MACONT) techniques to address the decision problems related to route selection, one of the most critical problems in transporting heavy and bulky loads, and to produce reasonable solutions. The proposed model significantly reduces information losses by processing subjective and objective information and integrating subjective (SWARA) and objective (LOPCOW) methods. Unlike traditional ranking approaches, the MACONT method combines three different normalization techniques to determine the ranking performance of alternatives. In this way, it provides more reliable and accurate results by reducing the deviations of the results provided by the single normalization technique. In addition, it shows each alternative's good and bad performance compared to the others and is more convincing about the results obtained. According to the results obtained by applying the proposed model, fuel consumption (0.096) is determined as the most effective and critical factor in selecting the route on which heavy and bulky loads will be transported. In this context, choosing routes that allow lower fuel consumption can contribute to reducing carbon emissions and external costs arising from transportation. The extensive robustness and validation check to test the proposed model prove that the proposed model is a reliable, robust, and practical decision-making tool for making reasonable and rational decisions in O&OT
Creating Digital Transformation Roadmaps for Independent Audit Firms: An Interval-Valued Q-Rung Orthopair Model
No full textThe primary objective of this study is to develop a structured digital transformation strategy roadmap that independent audit firms can utilize to manage digital transformation processes effectively. Digital transformation extends beyond integrating Industry 4.0 and advanced technologies into business operations. It necessitates restructuring business models, decision-making frameworks, and stakeholder communication mechanisms. Its implications are critical across all industries. In independent auditing, ensuring data accuracy, enhancing audit process transparency, and meeting speed and quality requirements are becoming increasingly vital. Digital transformation addresses these needs and provides independent audit firms with a sustainable competitive advantage. A review of the existing literature reveals a significant research gap in the identification and prioritization of digital transformation strategies, as well as a lack of comprehensive theoretical studies examining the digital transformation practices of enterprises. This study proposes an integrated decision-making model to address these research and theoretical shortcomings. According to the study results, "providing in-depth analysis with big data analytics and artificial intelligence solutions" is the most essential strategy for managing digital transformation processes. Regarding the applicability of this strategy, "agility" is defined as the most critical and practical criterion. Robustness checks confirm the model's validity and consistency
Do We Worry About the Use of Artificial Intelligence and Plagiarism? Students' AI-Giarism Behaviour Through the Fraud Triangle
No full textThe combination of AI and plagiarism is an emerging issue following the coining of the term AI-giarism. However, there has been little research that investigated the factors that lead students to engage in AIgiarism. In response to this gap, the present study adopts the fraud triangle framework to examine students' intentions toward AI-giarism and identify the underlying factors contributing to it. Data were collected from 312 students enrolled in 25 universities and analyzed using structural equation modelling. The results indicate that AI capacity, Justification of plagiarism, unawareness of AI deception, and academic pressure increase AI-giarism behaviour among students. In contrast to previous research, the study found no significant relationship between AI-giarism and either lax enforcement or a lack of understanding of AI. By offering empirical insights into the antecedents of AI-giarism, the present study advances the current body of literature, which has been more conceptual or student perception-centric
Feedback-Based Quantum Strategies for Constrained Combinatorial Optimization Problems
No full textFeedback-based quantum algorithms have recently emerged as potential methods for approximating the ground states of Hamiltonians. One such algorithm, the feedback-based algorithm for quantum optimization (FALQON), is specifically designed to solve quadratic unconstrained binary optimization problems. Its extension, the feedback-based algorithm for quantum optimization with constraints (FALQON-C), was introduced to handle constrained optimization problems with equality and inequality constraints. In this work, we extend the feedback-based quantum algorithms framework to address a broader class of constraints known as invalid configuration (IC) constraints, which explicitly prohibit specific configurations of decision variables. We first present a transformation technique that converts the constrained optimization problem with invalid configuration constraints into an equivalent unconstrained problem by incorporating a penalizing term into the cost function. Then, leaning upon control theory, we propose an alternative method tailored for feedback-based quantum algorithms that directly tackles IC constraints without requiring slack variables. Our approach introduces a new operator that encodes the optimal feasible solution of the constrained optimization problem as its ground state. Then, a controlled quantum system based on the Lyapunov control technique is designed to ensure convergence to the ground state of this operator. Two approaches are introduced in the design of this operator to address IC constraints: the folded spectrum approach and the deflation approach. These methods eliminate the need for slack variables, significantly reducing the quantum circuit depth and the number of qubits required. We show the effectiveness of our proposed algorithms through numerical simulations.Independent Research Fund Denmark (DFF) [0136-00204B]This work was supported by Independent Research Fund Denmark (DFF) , project number 0136-00204B.Science Citation Index Expande
The 'Original Face': Visitors Experience in Buddhist Pilgrimage Tourism through the Lens of Zen Thought
No full textThis study examines the visitors' experience while participating in the Dachaotai in Mount Wutai through the prism of Chinese Zen philosophy. Data was collected through participatory observation, in-depth interviews, and online texts. This study subsequently analyzed the data within the framework of the means-end chain model through which four attributes, six consequences, and three values were identified. The results showed that an attribute-consequence-value hierarchical value map of the original face could be constructed, and the formation process of visitors' original face was deduced. The value stratum of the experience regarding visitors' original face primarily encompassed "Free flow of thoughts", "Being in one's own mind", and "Epiphany",which could be interpreted within the principal tenets of Zen Buddhism. The research findings contribute to the existing body of knowledge about Buddhist pilgrimage tourism and bridge the gap that exists between Chinese Zen philosophy and tourist experience.Zhejiang Provincial Philosophy and Social Sciences Planning Project [24NDJC059YB]; Natural Science Foundation of Ningbo [2023J125]; Annual Philosophy and Social Sciences Planning Program of Zhejiang Province [26NDJC040Z]; Research Project of Philosophy and Social Sciences in Higher Education Institutions of Shanxi Province [2023W152]This research was supported by Zhejiang Provincial Philosophy and Social Sciences Planning Project (Grant No. 24NDJC059YB), Natural Science Foundation of Ningbo (Grant No. 2023J125), Key Project of the 2026 Annual Philosophy and Social Sciences Planning Program of Zhejiang Province (Grant No. 26NDJC040Z), Research Project of Philosophy and Social Sciences in Higher Education Institutions of Shanxi Province (Grant No. 2023W152)
Novel Designs of Fault-Tolerant Nano-Scale Circuits for Digital Signal Processing Using Quantum Dot Technology
No full textDigital signal processing (DSP) is a crucial engineering field dedicated to the processing and analysis of digital signals. DSP is particularly significant in critical sectors such as telecommunications, medical imaging, and secure communications, where it demands high accuracy, reliability, and real-time performance. In addition, the fault-tolerant (F-T) Arithmetic and Logic Unit (ALU) provides a fundamental building block of DSP architectures, enabling the accurate implementation of arithmetic and logical functions that are essential for advanced computational tasks. However, traditional ALUs were designed using complementary metal-oxide semiconductors (CMOS) and very large-scale integration (VLSI), which led to several challenges, such as high energy consumption, high occupied area, and slow operating speed. These limitations can be effectively addressed through nanotechnology, specifically quantum-dot cellular automata (QCA), which offers high speed, reduces occupying area, and has low power consumption. Accordingly, this paper proposes a QCA-based ALU circuit for DSP applications. The proposed designs integrate an F-T full adder (FA), a QCA-based multiplexer (MUX), and an ALU circuit to enhance performance and efficiency for DSP applications. The validation and verification of all suggested designs are performed using the simulation tool QCADesigner. © 2025 Elsevier B.V
Optimizing Location Selection for Foreign Trade Intelligence Centres Using Spherical Fuzzy Methods
No full textThis investigation focuses on a vital research topic that has significant research gaps in the literature, such as the selection of locations for foreign trade intelligence centres, which have a critical role in a country's development, a country's development and export capabilities. Previous studies have primarily addressed site selection in the context of manufacturing industries and retail outlets, focusing on strategies, and often ignored the unique requirements of foreign trade intelligence operations. This study solves the problem by considering the requirements of an innovative and integrated decision-making approach developed in the context of foreign trade intelligence centres, while at the same time filling the relevant research gap. The proposed model provides a mathematical form by extending Delphi management with spherical fuzzy sets to highlight influential evaluation criteria, as well as providing an integrated decision-making model extended with spherical fuzzy numbers to assess alternatives and determine rankings. Ten primary evaluation criteria are established to present a set of criteria for the authorities. The importance level of the criteria and assessments of alternatives for these criteria are aggregated spherical fuzzy numbers. A mixed integer non-linear multi-objective mathematical model is developed for the previous stages' outputs and different parameters. The results of the empirical application in Turkey show that Mersin is the most suitable alternative due to its attractive government incentives and strong commercial vitality compared to other options. The robustness checks verified the model's validity and reliability, proving a consistent decision-making tool for decision-makers and policymakers in the context of systematic decision-making
Spin-Glass Phases and Multichaos in the Ashkin–Teller Model
No full textThe global phase diagram of the Ashkin–Teller spin glass is calculated in d=3 spatial dimensions by renormalization-group theory. Depending on the value of the positive or negative four-spin interaction, qualitatively different topologies are found for the spin-glass phase diagram in the usual variables of temperature and fraction of antiferromagnetic nearest-neighbor interactions. Two different spin-glass phases occur. Both spin-glass phases are chaotic. One spin-glass exhibits phase reentrance that is reverse from the reentrances seen in previous spin-glass phase diagrams. Seven different phases: Ferromagnetic and antiferromagnetic, entropic ferromagnetic and entropic antiferromagnetic, spin-glass and entropic spin-glass, and disordered phases occur. The entropic ferromagnetic phase unusually but understandably occurs at temperatures above one spin-glass phase. A random disorder line is identified and no phase transition occurs on this line. Our calculation is exact on the d = 3 hierarchical lattice and Migdal–Kadanoff approximate on the cubic lattice. © 2025 Elsevier Ltd
Prioritizing Sustainable Energy Strategies Using Multi-Criteria Decision-Making Models in Type-2 Neutrosophic Environment
No full textEmphasis on developing sustainable energy strategies is very important for the energy sector to meet its environmental, economic, and social goals. Energy policy mostly considers the need to improve energy efficiency, cut down on carbon emissions, as well as create a profitable market. One of the major problems faced by decision makers is the complication and multi dimensionality of the decision- making process with regard to assessments, which entails numerous decision criteria. Overlooking these complicating factors has the potential of creating huge bottlenecks such as prolonged energy transition timelines, cost overruns, and derailing of environmental targets. This research introduces an approach based on Type-2 Neutrosophic Fuzzy Sets to rank sustainable energy strategies, using Logarithmic Percentage Change based on Objective Weights (LOPCOW) and Ranking of Alternatives through Functional Mapping of Criterion Sub-Intervals into Single Intervals (RAFSI) methods. The proposed model seeks to improve the effectiveness and efficiency of multi-criteria decision-making model in the areas where decision making is characterized by uncertainty and incompleteness. Energy strategies are evaluated in a comprehensive manner along numerous dimensions, including ecological, economic, technological, as well as societal. This approach helps to identify strategies that effectively support the sustainable development objectives of the energy sector. The analysis indicates that prioritizing Research and Development (R&D) strategies is particularly beneficial in achieving these goals. © 2025 Scrivener Publishing LLC