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This research investigates the effect of accessibility to points of tourist interest (buffer) and direct and indirect spatial spillover effects of agglomeration economies on tourism industry revenues in Spain.

Data were collected from the Bureau van Dijk's (BvD) Orbis global database. The data were analysed using a spatial econometric model and the Cobb–Douglas production function.

This study reveals that hotels located inside the buffer zone of points of tourist interest achieve better economic outcomes than hotels located outside the buffer. Furthermore, the results show that there is a direct and indirect spatial spillover effect in the hotel industry.

The results provide valuable information for identifying areas where the agglomeration of hotels will produce a spillover effect on hotel revenue and the area of influence of location characteristics. This information is relevant for hotels already established in a destination or when seeking a location for a new hotel.

The results of this study can help city planners in influencing the distribution of hotels to fit desired patterns and improve an area's spatial beauty.

The paper provides insights into how investment, structural characteristics, reputation and location affect hotel revenue.

This paper aims to present a topology optimization (TopO) method for designing heat exchangers (HEx) with two working fluids to be kept apart. The introduction of cut–cells gives rise to the cut-cell TopO method, which computes the optimal distribution of an artificial impermeability field and successfully overcomes the weaknesses of the standard density-based TopO (denTopO) by computing the fluid–solid interface (FSI) at each cycle. This allows to accurately solve the flow and conjugate heat transfer (CHT) problem by imposing exact boundary conditions on the computed FSI and results to correct performances computed without the need to re-evaluate the optimized solutions on a body-fitted grid.

The elements of an artificial impermeability distribution field defined on a background grid act as the design variables and allow topological changes to take place. Post-processing them yields two fields indicating the location of the two flow streams inside the HEx. At each TopO cycle, the FSIs computed based on these two fields are used as the cutting surfaces of the cut-cell grid. On the so-computed grid, the incompressible Navier–Stokes equations, coupled with the Spalart–Allmaras turbulence model, and the temperature equation are solved. The derivatives of the objective and constraint functions with respect to the design variables of TopO are computed by the continuous adjoint method, using consistent discretization schemes devised thanks to the “Think Discrete – Do Continuous” (TDDC) adjoint methodology.

The effectiveness of the cut-cell–based TopO method for designing HEx is demonstrated in 2D parallel/counter flow and 3D counter flow HEx operating under both laminar and turbulent flow conditions. Compared to the standard denTopO, its ability to compute FSIs along which accurate boundary conditions are imposed, increases the accuracy of the flow solver, which usually leads to optimal, rather than sub-optimal, solutions that truly satisfy the imposed constraints.

This work proposes a new/complete methodology for the TopO of two-fluid systems including CHT that relies on the cut-cell method. This successfully combines aspects from both TopO and Shape Optimization (ShpO) in a single framework thus overcoming the well-known downsides of standard denTopO regarding its accuracy or the need for a follow-up ShpO after TopO. Instead of adding the well-known Brinkman penalization terms into the flow equations, it computes the FSIs at each optimization cycle allowing the solution of the CHT problem on a cut-cell grid.

Consumers are increasingly shopping online, and they want reliable and trustworthy information about the quality of goods and all members of the distribution chain. Blockchain and gamification are two technologies that can drive digital transformation across various industries. The current study investigates the application of blockchain and gamification in emerging modern markets. Gamification is a viable method for familiarising individuals with blockchain technology. It is an example of an idea that might be utilised to build a setting as a bargaining strategy. The goal of this research is to investigate how gamification components might be used to engage individuals in blockchain technology and foster a positive attitude towards future use. In this review article, we did a thorough study of the research articles published between 2018 and 2023 on various web search engines for scholarly literature and academic resources. This comprehensive review investigates the incorporation of blockchain technology and gamification in emerging markets. Blockchain, known for its decentralised and secure nature, has the potential to transform a wide range of industries, including marketing. Similarly, gamification has grown in favour as a method of engaging and motivating customers. Marketers may use the benefits of both approaches to build unique and effective marketing campaigns by integrating blockchain and gamification. This review focuses on the digital transformation with focus on major concepts, benefits, problems and real-world applications of using blockchain and gamification into modern marketing techniques in emerging markets.

The escalating integration of AI tools like ChatGPT within academia poses a critical challenge regarding their impact on faculty members’ and researchers’ academic performance levels. This paper aims to delve into academic performance within the context of the ChatGPT era by exploring the influence of several pivotal predictors, such as academic integrity, academic competence, personal best goals and perceived stress, as well as the moderating effect of ChatGPT adoption on academic performance.

This study uses a quantitative method to investigate the impact of essential variables on academic integrity, academic competence, perceived stress and personal best goals by analysing 402 responses gathered from ResearchGate and Academia.edu sites.

While affirming the established direct positive relationship between academic integrity and performance since adopting AI tools, this research revealed a significant moderating role of ChatGPT adoption on this relationship. Additionally, the authors shed light on the positive relationship between academic competence and performance in the ChatGPT era and the ChatGPT adoption-moderated interaction of competence and performance. Surprisingly, a negative association emerges between personal best goals and academic performance within ChatGPT-assisted environments. Notably, the study underscores a significant relationship between heightened performance through ChatGPT and increased perceived stress among academicians.

The research advocates formulating clear ethical guidelines, robust support mechanisms and stress-management interventions to maintain academic integrity, enhance competence and prioritise academic professionals’ well-being in navigating the integration of AI tools in modern academia.

This research stands out for its timeliness and the apparent gaps in current literature. There is notably little research on the use of ChatGPT in academic settings, making this investigation among the first to delve into how faculty and researchers in education use OpenAI.

This study seeks to analyze the effect of the financial distress costs on small and medium-sized enterprises (SME) rebalancing of short-term and long-term debt ratios.

The authors use the system-generalized method of moments (GMM-sys) to treat data collected for a sample of Portuguese manufacturing SMEs for the period 2011–2017.

Financial distress costs positively impact the speed with which SMEs rebalance their short-term and long-term debt ratios The positive effect of financial distress costs on the speed of adjustment (SOA) is higher for the short-term than for the long-term debt ratio. This result suggests that SMEs seek to overcome quicker the financing imbalance in the short run, probably, due to their dependence on short-term debt.

SME owners-managers should seek to rely less on short-term debt to reduce the firm default risk, the financing imbalance and the financial distress costs. Banks should lend long-term loans to SMEs, given that the high financial distress risk of these firms results from their dependence on short-term debt financing. Policymakers should promote SME access to external finance sources with lower transaction costs, to SME rebalance their capital structures.

This study analyzes the effect of financial distress costs on the SOA with which SMEs rebalance their capital structure. We estimate the financial distress costs based on a hazard model, to analyze their effect on the SOA toward the target debt ratios.

The present study investigates a nexus between digital public services (DPS) and international tourism empirically.

This article analyzes the nexus of DPS and international tourism by using the international sample of 23 European countries in the span of nearly 10 years from 2011 to 2019. Various econometric techniques, including the panel-corrected standard error (PCSE) model and the feasible generalized least squares (FGLS) model, are employed to confirm the author’s findings. Furthermore, the autoregressive distributed lag (ARDL) method is applied to measure the short- and long-run effects of DPS on international tourism developments.

Tourism is positively influenced by digitalization, implying that the enhancement of digital public service usage results in the development of the tourism industry. However, when looking at the effect of DPS in the short term, a negative impact can be found on tourism, as the density reported in the previous analysis stated a negative response to the tourism density. This effect spans the course of several facets, such as international tourism arrivals, international tourism receipt, international tourism, receipts (% of total exports) and global tourism expenditure (% of total imports). Although the result is unfavorable in the short term, digitalization promises great prospects for tourism in the long term. Notably, an improvement in economic growth, financial development as well a reduction in the pervasiveness of corruption and an improvement of environmental quality are transmission channels through which DPS have favorable influences on tourism activities.

The author’s findings are vital for managers and policymakers to establish a comprehensive grasp of digitalization's role in deciding tourist adoption. This is because digitalization has been proven to play a role in determining tourism adoption.

The present study is the first to examine the relationship between DPS and international tourism empirically. The author is also the first to distinguish the effects of digitalization in the short and long run.

This study aims to explore and investigate the patient-reported outcome and experience measure (DIALOG) with respect to physical health of service users under the care of a Mental Health and Learning Disabilities National Health Service trust.

Three exploratory statistical analyses (paired samples t-test, a logistic regression on changing from unsatisfied to satisfied and a logistic regression on improving by at least one DIALOG score) were conducted on physical health DIALOG scores (n = 3,077).

The mean score for the DIALOG physical health question increased from 3.28 to 3.43 whilst under the care of secondary care mental health services. Service users living in deprived areas were 35% (OR 0.65, CI [0.45, 0.95]) less likely to be satisfied with their physical health. Service users recorded as long-term sick or disabled were 60% (OR 0.40, CI [0.25, 0.63]) less likely to be satisfied with their physical health. Service users who had not had a physical health assessment were 57% (OR 0.43, CI [0.23, 0.79]) less likely to be satisfied with their physical health.

The routine collection of patient-reported outcome measures and patient-reported experience measures in the UK mental health setting is in its infancy with currently little analysis of data taking place; therefore, this exploratory study generates several discussion points.

This study aims to compare the e-service quality of health-care services during and the post-Covid-19 outbreak in Turkey. In addition, the relationship between patient appointments made through e-services and satisfaction was measured.

Two different studies were conducted during and after the Covid-19 period. Data were evaluated with Fuzzy Importance, Expected Performance and Priority Analysis (FIEPA) with compromise ranking method (VIKOR).

Consumers’ expectations and managers’ priorities differ in both periods. The design dimension is the most critical priority that requires improving e-service quality in health care during a pandemic. In the post-pandemic era, the interaction dimension gained importance and has become a priority in resource allocation. The date of a doctor’s appointment obtained from online appointment systems affects satisfaction, and this situation should be considered in e-services.

Managers should consider these differences and update their e-services by acting quickly in cases such as pandemics. Study 2 showed that the sanctions implemented by the Ministry of Health to prevent inconvenience to patients who fail to attend their appointments despite booking them are effective.

To the best of the authors’ knowledge, this is the first study to compare e-service quality in health care in the Covid-19 pandemic era and the post-Covid-19 pandemic era. The findings have important implications for future research and policy, and this research fills a gap in the literature.

This study aims to provide three biomechanical models that are consistent with the arm forces of elderly women and to design elbow guards that are more suitable for their use. Numerical analysis and experimental methods were used to determine the optimal direction for elbow guard design, focusing on fabric type, arm force distribution and comfort thresholds.

This paper explores the design of elbow guards for older women through predictive finite element modeling and a systematic experimental approach. First, contact anthropometry was used to measure the arm dimensions of older women. Cluster analysis was applied to categorize arm sizes, laying the foundation for the subsequent selection of subjects for 3D scanning. Second, a 3D scanner was used to obtain the external contours of a representative subject’s arm. Finite element models of the arm and elbow guard were constructed with the arm flexed at three different angles. These models were used to simulate the pressure exerted by the elbow guard on the arm. Next, objective measurements of garment pressure were taken using a homemade elbow guard. Finally, subjective comfort evaluation was carried out using the human clothing experiment method. Comfortable pressure thresholds were determined by establishing a correlation between subjective comfort levels and objective pressure values.

The results showed that the developed model effectively predicted the pressure distribution between the elbow guard and the arm. By comparing the simulated pressure distributions of the four materials, it was determined that polyamide and spandex fabrics were the more appropriate materials for the elbow pad design. Additionally, the study pointed out the need to consider the different bending postures of the arm when analyzing pressure, focusing on the amount of pressure control at the elbow of the arm. When the arm’s bending angle ranges between 90° and 180°, the total pressure should remain between a minimum of 2550.0 Pa and a maximum of 4394.4 Pa.

The theoretical approach of ellipses was used to construct the arm model. Numerical simulations were performed to analyze the pressure distribution for three different arm bending postures, and the simulation results provided useful insights for designers in selecting the optimal fabric type. This study provides a theoretical reference for designing comfortable compression elbow guards, while also addressing garment comfort by establishing accurate garment comfort thresholds to guide designers in understanding the appropriate compression dosage.

• (1)

  The theory related to ellipses is introduced in the construction of the model, unlike other studies.

• (2)

  The laws of fabric material, force area and bending angle on pressure distribution were analyzed.

• (3)

  Clothing pressure comfort thresholds were determined for three different postures.

The theory related to ellipses is introduced in the construction of the model, unlike other studies.

The laws of fabric material, force area and bending angle on pressure distribution were analyzed.

Clothing pressure comfort thresholds were determined for three different postures.

The research proposes to quantify the innovation potential within organizations from a contextual approach through their capabilities, results and impacts of innovation. Traditional innovation indicators usually fail to depict the innovation behavior in DEIE (Developing and Emerging Industrial Economies). This research seeks to fill this gap by developing a measurement tool adapted to Ecuador as a case of DEIE countries.

The innovation potential measurement tool (Capabilities, Results and Impacts – CRI questionnaire) has been developed in a six-step methodology path that includes conceptualization, item generation, content validation, data collection, measurement model definition and measurement model assessment.

The main findings highlight the importance of organizational innovation capabilities (C1, C2, C3 and C4) to generate innovations (R1) and societal impacts (I1), in particular innovation objectives (C4) are remarked as key factor to enhance innovation results and impacts.

The CRI questionnaire assesses innovation potential by employing Item Response Theory (IRT) to derive unidimensionally adjusted factors, which represent single measurable criteria for evaluating innovation potential within specific contextual conditions.

The CRI questionnaire considers contextual conditions of DEIE to provide adapted metrics for understanding how innovation dynamics in contexts with low industrialization and low innovation culture.