Journals Published by Vilnius Tech
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Assessing SME credit rating in supply chain finance with multi-phase QFD-based MULTIMOORA under uncertainty
Get PDFPresently, financial institutions have tentatively utilized supply chain finance as a means of assessing small and medium-sized enterprise (SME) credit rating. However, traditional techniques cannot satisfy the requirements of such assessments because financial institutions need to assess SME credit rating from the perspective of the supply chain and core enterprise rather than only from the perspective of SME. In this study, a hybrid technique with quantitative and qualitative criteria called multi-phase quality function deployment (QFD)-based MULTIMOORA under interval type-2 fuzzy set (IT2FS) is proposed to overcome the defects of traditional techniques. First, the quantitative values were converted into IT2FSs using the developed formulas. Second, a multi-phase QFD model is proposed to obtain the SME credit rating matrix by integrating the core enterprise credit rating matrix and the criterion relationship matrices among SME, core enterprises and supply chains. Third, IT2FS-MULTIMOORA is enhanced by considering the improved Borda Rule and extended reference point simultaneously to derive the final rankings; therefore, a weight-determining technique is presented based on the correlation coefficients. Finally, the proposed technique was applied to the SME credit rating assessment problem. Comparisons with other techniques and the sensitivity analysis results provide suggestions for financial institutions to provide loans to SMEs.
First published online 31 March 202
The digital economy and city innovation convergence – an empirical research based on the innovation value chain theory
Get PDFWithin China’s strategy for innovation-driven development, digital economy (DE) plays a crucial role, significantly influences city innovation convergence. This study, grounded in the theoretical perspective of the innovation value chain theory (IVCT), divides innovation activities into two major phases: technological research phase and results transformation phase, and uses data from 283 Chinese cities spanning 2011 to 2021, it systematically explores, for the first time, the convergence characteristics of city innovation activities in each phase and delves deeply into the role of DE in this process. The findings reveal that city innovation in China’s cities demonstrates notable convergence characteristics during both technological research and achievements transformation phases. These convergence traits persist in both phases, even when accounting for spatial effects, particularly regarding the engagement of DE. Furthermore, in technological research phase, fiscal pressures faced by local governments diminish the effectiveness of DE in fostering city innovation convergence; but, during achievements transformation phase, such fiscal pressures do not impede DE’s capacity to enhance city innovation convergence. Lastly, the difference of city Innovation and entrepreneurial vitality during both technological research and achievements transformation phases restrict DE’s potential to support city innovation convergence, with a more pronounced diminishing effect observed in technological research phase. This study provides important decision-making support for policymakers and helps further uncover and unleash the potential of DE in promoting city innovation convergence.
First published online 05 June 202
The convergence of environmental innovation, stakeholder pressure, open innovation in logistics firms: pathway to renewable energy in the presence of managerial cognition & competitive advantage
Get PDFThe logistics industry has recently been pressured to adopt sustainable practices due to increasing environmental concerns and regulatory mandates. This study investigates the nexus between ecological innovation, stakeholder pressure, open innovation, and renewable energy adoption in logistics firms, emphasizing the moderating role of managers’ cognition of sustainable opportunities and competitive advantage. In this regard, stakeholder pressure compels organizations to adopt renewable solutions. On the other hand, open innovation and eco-innovation are pivotal in taming firms’ internal limitations and advancing the adoption of renewable technologies. Thereby, analyzing empirical data from China’s logistics firm, the present study demonstrates how open innovation, eco-innovation, and stakeholder pressure affect renewable energy adoption and the firm’s competitive advantage. In addition, the study explicitly outlines the critical role of managers’ cognition of sustainable opportunities and competitive advantage as a moderator. Through SEM, the study reveals a positive and significant relationship between open-innovation, eco-innovation, and stakeholders’ pressures regarding renewable energy adoption. The moderation of managers’ cognition in the case of eco-innovation and open innovation proved significant, whereas, in the case of stakeholder pressure, it is insignificant. Competitive advantage, another moderator, failed to moderate the proposed relationship. Findings explain that managers can realize strategic significance in terms of sustainability. They may shift toward green strategies aligned with market apprehensions and environmental regulations. This cognitive factor enhances the usefulness of open and eco-innovation during renewable adoption. Overall, the study’s findings underscore the significance of managerial insights in leveraging these factors to accelerate the industry toward a sustainable future
Integrated expert model for risk assessment and ensuring the safety of tourist trips: economic and technological aspects
Get PDFThis study aims to develop an integrated expert model for assessing and ensuring the safety of tourist trips, with a particular emphasis on the economic and technological aspects. The model adopts a multi-level approach, spanning from individual perceptions of safety during travel to national assessments of regional tourism security. The economic factors, such as the financial implications of safety measures and their impact on regional tourism development, play a central role in this approach. The methodological foundation includes the theory of fuzzy sets and fuzzy logic, expert evaluations, and knowledge-based intelligent analysis. For the first time, we received: an information model for assessing the safety level of a tourist trip; a fuzzy method for determining the aggregated term risk assessment of one’s safety of a tourist trip; an expert method of assessing the level of the sense of security of the region on the part of the participants of the tourist movement; a hybrid method of determining the degree of risk to the safety of a tourist trip. The model not only provides a quantitative assessment but also highlights the safety risks associated with tourist trips, thereby enabling regional analyses that support decision-making aimed at ensuring tourism safety through both economic and technological means solutions
Forecasting short-term passenger flow on a bus route: a splitting–integrating method based on passenger travel behavior
No full textShort-term passenger flow forecasting is the key to implement real-time dynamic dispatching of buses, which can meet the travel time requirement of passengers with different attributes. In practice, it is difficult to obtain passenger attribute information due to the restriction of bus information systems or other conditions. This article proposes a new perspective on identifying passenger attribute information, that is, the correlation between the bus card number and the travel time is used to analyse passenger travel behaviour. Then using the travel frequency as the splitting boundary, the passenger set is split into different types of subsets, which are predicted by different methods. The total forecast values are obtained by integration, so as to explore the effectiveness of the passenger attribute identification and splitting–integrating method. The result shows that: (1) compared with the forecasting method without considering the passenger travel behaviour, the performance of splitting–integrating method is better, and the passenger attribute identification method is effective; (2) the value of the splitting boundary will affect the size and consistency of the subset, and the optimal value can be sought according to forecast results; (3) different types of subsets should be treated by different forecasting models and combination paths
The perspective of the aviation organizations on the ICAO’s SMS framework: a spherical fuzzy AHP study
Get PDFThe International Civil Aviation Organization (ICAO) has developed a Safety Management System (SMS) to ensure safety in aviation organizations. SMS components are essential to overall safety performance in aviation organizations. However, the importance of these components may be perceived differently among different aviation organizations. This study aims to evaluate the perception of the importance of ICAO SMS components in aviation organizations in Turkey using the Global Fuzzy Analytical Hierarchical Process (SFAHP). The sample of the research consists of managers and employees of different aviation organizations. Data were collected using a survey questionnaire and analyzed via the SFAHP method. The results of this study indicate that all ICAO SMS components were considered important by the participants. In this context, hazard identification, training, and education and safety risk assessment and mitigation are the most important components. The study also revealed that the perception of the importance of SMS components differs between different types of aviation organizations. The SMS components with the highest deviation are listed as the appointment of key safety personnel, safety risk assessment and mitigation and management commitment. Therefore, the study provides valuable information regarding the perception of the importance of ICAO SMS components in aviation organizations
Discrete Gronwall’s inequality for Ulam stability of delay fractional difference equations
Get PDFThis paper investigates Ulam stability of delay fractional difference equations. First, a useful equality of double fractional sums is employed and discrete Gronwall’s inequality of delay type is provided. A delay discrete-time Mittag-Leffler function is used and its non-negativity condition is given. With the solutions’ existences, Ulam stability condition is presented to discuss the error estimation of exact and approximate solutions
Boundary feedback stabilization of quasilinear hyperbolic systems with zero characteristic speed
Get PDFIn this paper, we investigate the boundary feedback stabilization of a quasilinear hyperbolic system with zero characteristic speed and a partially dissipative structure. This structure enables us to construct a Lyapunov function that guarantees exponential stability for the H2 solution. We also introduce another set of stability conditions by restricting terms corresponding to zero eigenvalues to the dissipative part, which still ensures exponential stability. As an application, we achieve feedback stabilization for the modified model of neurofilament transport in axons
Calderón-Zygmund estimates for Schrödinger equations revisited
Get PDFWe establish a global Calderón-Zygmund estimate for a quasilinear elliptic equation with a potential. If the potential has a reverse Hölder property, then the estimate was known in [6]. In this note, we observe that the estimate remains valid when the potential is merely Lebesgue integrable. Our proof is short and elementary
Optimizing chaotic systems by orbit counting and Fourier spectrum: FPGA implementation and image encryption application
Get PDFThe optimization of chaotic systems has been performed by considering dynamical characteristics of the mathematical models. The proposed work shows the application of genetic algorithms (GAs) to optimize the chaotic behavior of three well-known systems, namely: Lorenz, Chen and Lü. The parameters of the chaotic systems are varied in a specific range of values considered as the search space, and the evaluation of the mathematical model is performed by applying the Forward Euler method. The contribution presented herein is that the chaotic behavior is evaluated by counting the orbits in an attractor and the sparsity of them. In addition, the chaotic behavior is guaranteed by evaluating the Fourier spectrum of the time series. The solutions provided by the GA, are then implemented on a field-programmable gate array (FPGA) to verify the experimental generation of chaotic attractors. Finally, two optimized chaotic systems are synchronized and used to encrypt an image, thus confirming the appropriateness of optimizing the chaotic behavior by orbit counting and Fourier spectrum analysis