Integrated fuzzy model for assessing cultural tourism potential in ethno-villages

This research examines the alignment of ethno-villages with cultural tourism to assess their commitment to preserving cultural values but attracting tourists in order to increase the efficiency of the economy, also. By engaging tourism experts, this research categorizes criteria into distinct groups and uses an integrated fuzzy set approach to assess the cultural tourism potential of these destinations. By combining Improved Fuzzy SWARA (Step-Wise Weight Assessment Ratio Analysis) and fuzzy WASPAS (Weighted Aggregates Sum Product Assessment) methods with the Fuzzy DOMBI operator, the research presents a methodology to address uncertainties in decision-making. The IMF SWARA method determined the criteria’s significance by assigning weights, while the fuzzy WASPAS method introduced uncertainty into the decision-making process through Z-numbers. The findings highlight ethno-villages like Ljubačke Doline and Kotromanjić, demonstrating admirable dedication to cultural immersion in their tourism offerings. These ethno-villages can serve as examples of how culture, tradition, and customs can be smoothly integrated to improve the tourism experience and economic system as a whole

Gamification and its impact on improving training and business innovation processes

The aim of this study was to analyze the impact of gamification on employee motivation and engagement in business innovation processes. A systematic literature review (SLR) was conducted, including 55 articles retrieved from the Scopus database, following the PRISMA statement guidelines. Inclusion and exclusion criteria were applied to ensure the relevance and quality of the reviewed studies. Regarding materials and methods, a specific search equation was used to identify articles addressing the relationship between gamification and productivity in the workplace. Key data were extracted from the selected articles, including information on the study population, the gamification techniques implemented, and the observed benefits. The findings were categorized to identify recurring patterns and themes. Results showed that gamification enhances employee motivation and engagement, thereby improving business innovation processes. Various gamification techniques were identified as effective, along with contextual factors that influenced outcomes. The review also highlighted the need to tailor gamification strategies to maximize their benefits. It is concluded that this work provides a critical overview of the current state of knowledge in the field of gamification and its application in business innovation. Areas requiring further research were identified, suggesting that gamification can be a valuable tool for improving productivity and creativity within organizations

Investigating effects of ICT infrastructure on economic growth: data flow perspective based on China’s evidence

This study employs a mediating effect model and the Generalized Method of Moments (GMM) approach to examine the direct effect of ICT on the economy and the mediating role of data flow in the ICT – economic growth nexus. The results indicate that ICT significantly enhances data flow intensity, which in turn promotes economic growth. Moreover, both the direct effect of ICT and the mediating role of data flow are more pronounced in developed regions compared to underdeveloped areas. Further analysis shows that with the implementation of the policy, the mediating effect of data flow shifted from being insignificant (2006–2010) to significant (2011–2019). This study contributes to the understanding of the digital divide, highlighting potential drivers such as disparities in ICT infrastructure and data flow inequality. The government should develop tailored ICT development policies based on the region’s economic level to fully harness the benefits of digitalization. First published online 18 May 202

Integration of Lean Six Sigma into earned value management using system dynamics

A Few Lean Six Sigma (LSS) papers were studied during the construction project’s progress. This study proposes the integration of LSS, system dynamics (SD), and earned value management (EVM) as a comprehensive toolkit for datadriven decision-making. Significant waste- and quality-related interdependencies were identified using DEMATEL techniques with 27 Saudi construction experts. SD with two interdependent models of waste causes (WCs) and quality causes (QCs) were utilized to assess the project’s performance. Two metrics were employed: the sigma rating and the value-added ratio in the EVM generated by the developed SD model. The findings indicated that eliminating WCs had little impact on enhancing the project performance in the early stages of the project. The impact increased with the progress of the project. The improvement of the project quality was minimal for “increases of errors and omissions in design documents” and maximum for “increasing morale and attitude affect the quality of the project”

Well-posedness and exponential stability for the logarithmic Lamé system with a time varying delay

The focus of this paper revolves around the initial–boundary value problem associated with a logarithmic Lamé system within a bounded domain, and incorporating a time-varying delay. We demonstrate the system’s well-posedness through the application of semigroup theory. Subsequently, we establish the existence of global solutions by employing the well-depth method. Furthermore, we establish exponential decay of solutions under adequate constraints concerning the weight of the time-varying delay and the frictional damping

Research on multiple improvement paths of innovation performance in regional innovation ecosystem based on fuzzy qualitative comparative analysis

Prioritizing the development of regional innovation ecosystems (RIE) is essential for advancing China’s innovation-driven strategy. This study investigates how combinations of innovation elements, namely resources, services, achievements, and environment, affect regional innovation performance. Drawing on both innovation value-chain and ecosystem perspectives, we analyze the data from 31 Chinese provinces using fuzzy-set qualitative comparative analysis (fsQCA) and artificial neural networks (ANN). Our findings identify five distinct configurations that lead to high innovation performance and three that result in low or medium performance. High performance configurations include: resource achievement dual drive, outcome driven, and resource driven. Low performance configurations include talent shortage type, service deficiency type, and resource service dual weakness type. These results illustrate the principle of equifinality, indicating that different regions can achieve similar innovation outcomes through different pathways, and they underscore both the substitutability of certain elements and the synergy among them. Theoretically, the study advances configurational approaches in innovation research by integrating ecological and value-chain perspectives. Practically, it provides differentiated policy insights, suggesting that regions should tailor their innovation strategies to leverage specific strengths and thereby foster high-performance outcomes. First published online 4 March 202

A second order method for a drug release process defined by a differential Maxwell-Wichert stress-strain relation

Polymeric drug delivery platforms offer promising capabilities for controlled drug release thanks to their ability to be custom-designed with specific properties. In this paper we present a model to simulate the complex interplay between solvent absorption, polymer swelling, drug release and stress development within these platforms. A system of nonlinear partial differential equations coupled with an ordinary differential equation is introduced to avoid drawbacks from other models found in the literature. These incorporated a memory effect but from a numerical standpoint, required storing all previous time steps, making them computationally expensive. This paper proposes a new numerical method to simulate such devices based on nonuniform grids and an implicit midpoint time discretization. Our main results are the second order convergence of the method for nonsmooth solutions and the scheme’s stability under the assumption of quasiuniform grids and a small enough timestep

On shifts of periodic zeta-function in short intervals

The periodic zeta-function $\zeta(s; a)$, $s = \sigma + it$, $a = \{a_m \in \mathbb{C} : m \in \mathbb{N}\}$, in the half-plane \sigma > 1 is defined by Dirichlet series with periodic coefficients $a_m$, and has the meromorphic continuation to the whole complex plane. The function $\zeta(s; a)$ is a generalization of the Riemann zeta-function and Dirichlet $L$-functions. In the paper, using only the periodicity of the sequence $a$, we obtain that the shifts $\zeta(s + i\tau; a)$, $\tau \in \mathbb{R}$, approximate a certain class of analytic functions, defined in the strip \{s \in \mathbb{C} : 1/2 < \sigma < 1\}. For $T^{23/70} \leqslant H \leqslant T^{1/2}$, the set of such shifts has a positive lower density in the interval $[T, T + H]$, $T \to \infty$. The case of positive density is also discussed. For the proof, the mean square estimate in short intervals for the Hurwitz zeta-function, and probabilistic limit theorems are applied

Generalized practical stability of Hopfield-type neural networks differential equations

This paper investigates the boundedness and practical stability properties of solutions for a class of neural differential equations inspired by Hopfield-type neural networks. Specifically, we develop a novel analytical framework that extends beyond traditional Lyapunov stability theory, Barbalat-type arguments, and fixed-point methods by relaxing common structural assumptions such as smoothness and global Lipschitz continuity. Our approach broadens the class of admissible systems to include nonlinearities with weaker growth conditions and time-varying perturbations that are not easily handled by classical techniques. Sufficient conditions are established to ensure the existence of a globally exponentially stable neighborhood of the origin, even in the presence of varying perturbation conditions. Furthermore, numerical examples are provided to demonstrate and validate the main result

Stimulating collective creativity in fashion small and medium enterprises: towards a resource-sensitive innovation model

Creativity is an essential factor for the success of the fashion industry, but small and medium enterprises often face significant barriers when it comes to systematically developing innovation. Unlike major companies, small businesses do not have dedicated research and development infrastructure and are therefore highly dependent on collaborative and resource-efficient processes. This article discusses the gap in existing systems and proposes a conceptual model to stimulate collective creativity that is adapted to the realities of fashion small and medium enterprises. The model emphasizes resource sensitivity, less formalized management, and measurable results, including product novelty, go-to-market time, and customer engagement. By treating creativity as a collective capability, this study contributes both to theoretical insights into small and medium enterprises innovation processes and to practical guidelines for fashion industry practitioners seeking to increase competitiveness. The study concludes with recommendations for managers, policymakers, and future research on the applicability of the creativity model