Uslu, Abdullah; Tarinc, Abdullah; Erul, Emrullah; Eren, Ramazan; Andrade-Ruiz, Gricela; Tuncer, Mehmet Arif; Alagöz, Gürkan

This study examines the effects of the e-servicescape on flow experience, positive affect, trust, website loyalty, and e-WOM in the context of online travel platforms, while investigating the moderating role of e-familiarity. Drawing on servicescape theory, the S-O-R framework, and the Technology Acceptance Model (TAM), a comprehensive research model is proposed. Data were collected from 256 consumers residing in Türkiye who had previously used online travel agencies, and the hypotheses were tested using partial least squares structural equation modeling (PLS-SEM). The findings reveal that the e-servicescape has significant positive effects on flow experience, positive affect, and trust. While flow experience was a significant predictor of positive affect, it did not have a significant direct effect on e-WOM. Furthermore, positive affect and trust, in turn, significantly predicted both website loyalty and e-WOM. Moreover, e-familiarity negatively moderated the relationship between e-servicescape and flow experience, suggesting that highly familiar users derive less immersive benefit from enhanced online environments. The study contributes to the digital tourism and consumer behavior literature by highlighting the role of user familiarity in shaping experiential outcomes.

Şen Özdemir, Nurgül; Aydın, Erdinç; Sökmen, Teoman Özgür

Sapanca Lake is a tectonic freshwater lake ecosystem whose water balance and ecological integrity are increasingly threatened by urbanization, pollution, climate change, and declining water levels. To assess recent changes in the fish community, length–weight relationships (LWRs), condition factors (CFs), sex ratios (F/M), and standing stock biomass estimates were determined for eight fish species (Blicca bjoerkna, Scardinius erythrophthalmus, Carassius gibelio, Esox lucius, Silurus glanis, Perca fluviatilis, Abramis brama and Cyprinus carpio) sampled between December 2024 and April 2025. According to standing stock biomass assessments, Cyprinus carpio showed the highest biomass (297.67 tons), while Abramis brama had the lowest (22.72 tons). Most species showed positive allometric growth (b > 3), suggesting generally favorable feeding conditions. In contrast, the main predatory species, E. lucius (b = 2.89) and Silurus glanis (b = 0.21), exhibited negative allometric growth, likely due to limitations in food availability and prey abundance. The CF values were generally >1, indicating good physiological status; however, lower CF values in A. brama (1.18) and B. bjoerkna (1.19) suggest species-specific ecological limitations. Sex ratio analysis revealed pronounced female dominance across species, ranging from complete female dominance (F/M = 1/0) in Carassius gibelio to a female-biased ratio of 1/0.04 in Scardinius erythrophthalmus, likely driven by seasonal sampling effects, sex-specific behavior, and species-specific reproductive strategies. Overall, the results indicate increasing trophic imbalance and ecological stress in Sapanca Lake, emphasizing the need for standing stock biomass assessments and ecosystem-focused fisheries management in tectonic lakes under hydrological pressure.

Özdemir, Hicran; Tarsuslu, Sinan; Agaoglu, Ferhat Onur

Background: Climate change and related environmental issues are among the major global threats affecting health systems. While nurses’ eco-friendly behaviors are critical for reducing the environmental impact of health care services, the psychological mechanisms through which these behaviors influence carbon footprint awareness have not been sufficiently explained. Objective: The aim of this study is to examine the effect of nurses’ eco-friendly behaviors on carbon footprint awareness and to assess the mediating role of climate change anxiety in this relationship. Methods: The study was conducted using a cross-sectional and analytical design. The sample consisted of 386 nurses selected through convenience sampling based on voluntary participation from among nurses working in secondary and tertiary healthcare facilities in Turkey. Results: It was determined that environmentally friendly behavior significantly and positively predicted carbon footprint awareness (B = 0.542, p < 0.001) and climate change anxiety (B = 0.602, p < 0.001). In addition, climate change anxiety was found to have a significant positive effect on carbon footprint awareness (B = 0.458, p < 0.001). Bootstrap analysis showed that climate change anxiety played a significant partial mediating role in the effect of eco-friendly behavior on carbon footprint awareness (indirect effect = 0.176, 95% CI = 0.165–0.369). Conclusions: Nurses’ eco-friendly behaviors increase carbon footprint awareness both directly and through climate change anxiety. The findings highlight the importance of practices that support eco-friendly behaviors and educational programs that strengthen climate change awareness in the development of sustainable health services.

Kumbasaroglu, Hediye

Understanding the long-term dynamics of global tea production is essential for assessing supply stability, climate sensitivity, and producer competitiveness. This study examines annual tea production data for major producing countries—China, India, Kenya, Sri Lanka, Türkiye, Vietnam, and other producer groups—over the period 1961–2023 and provides production forecasts for 2024–2028 using country-specific ARIMA models. Unlike most existing studies focusing on single countries or short-term horizons, this research offers a unified multi-country and long-term comparative framework that integrates time-series forecasting with market concentration indicators. The results reveal pronounced cross-country heterogeneity in production behavior, with China exhibiting strong structural growth, while other producers display more moderate or climate-sensitive patterns. Forecasts suggest a continued increase in global tea production toward 2028, although projections are subject to uncertainty, as reflected by model-based confidence intervals. Overall, the study contributes robust, statistically validated insights to support evidence-based strategies for sustainable tea supply and international market planning. Forecasts suggest a continued increase in global tea production toward 2028, although projections are subject to uncertainty, as reflected by model-based confidence intervals. These forecasts highlight a robust upward trend in global tea supply due to both technological advancements and market expansion.

Bita-Nicolae, Claudia; Yildiz, Faruk; Kaya, Ozkan

The Carpathian region harbors a wide range of threatened species, making it an area of exceptional conservation value. In the Alpine belt, grasslands cover the entire region and this study aims to describe the communities in the Bucegi Massif of the Romanian Carpathians and highlight their importance for conservation. The Braun–Blanquet approach was used to record floristic data from 47 phytosociological surveys, identifying a total of 235 plant species from 40 different families, including 30 threatened species. Canonical correspondence analysis was used to analyze the data, revealing that the distribution of vegetation is mainly influenced by elevation, slope and vegetation cover. Dominant grass species in these communities include Nardus stricta, Festuca violacea, Kobresia myosuroides, Festuca amethystina, Festuca airoides, Sesleria rigida, Festuca versicolor and Festuca carpatica. The alpine and boreal siliceous grasslands of the Carpathian Mountains, identified by Natura 2000 codes 6150, 6130 and 6170, host a wide range of plant species of significant conservation value. The higher altitude grasslands, especially, have outstanding plant species richness. We argue that although the habitats have been grazed, significant parts of the area are still in good ecological condition, having many typical natural features.

Katipoğlu, Okan Mert

The prediction of hydrological droughts is vital for surface and ground waters, reservoir levels, hydroelectric power generation, agricultural production, forest fires, climate change, and the survival of living things. This study aimed to forecast 1-month lead-time hydrological droughts in the Yesilirmak basin. For this purpose, support vector regression, Gaussian process regression, regression tree, and ensemble tree models were used alone and in combination with a discrete wavelet transform. Streamflow drought index values were used to determine hydrological droughts. The data were divided into 70% training (1969–1998) and 30% (1999–2011) testing. The performance of the models was evaluated according to various statistical criteria such as mean square error, root means square error, mean absolute error, and determination coefficient. As a result, it was determined that the prediction performance of the models obtained by decomposing into subcomponents with the discrete wavelet transform was optimal. In addition, the most effective drought-predicting model was obtained using the db10 wavelet and MGPR algorithm with mean squared error 0.007, root mean squared error 0.08, mean absolute error 0.04, and coefficient of determination (R2) 0.99 at station 1413. The weakest model was the stand-alone FGSV (RMSE 0.88, RMSE 0.94, MAE 0.76, R2 0.14). Moreover, it was revealed that the db10 main wavelet was more accurate in predicting short-term drought than other wavelets. These results provide essential information to decision-makers and planners to manage hydrological droughts in the Yesilirmak basin.

Çerçi, Kamil Neyfel; Daş, Mehmet

As a sustainable energy source, solar energy is used in many applications. A greenhouse type dryer, which is a food drying system, directly benefits from solar energy. Convective heat transfer coefficient (hc) is an important parameter in food drying systems, in terms of system design and performance. Many parameters and equations are used to determine hc. However, as it is difficult to manually process and analyze large amounts of data and different formulations, machine learning algorithms are preferred. In this study, natural and forced convective solar greenhouse type dryers were designed. In a solar greenhouse type dryer, grape is dried in natural (GDNC) and forced convection (GDFC). For convective heat transfer coefficient (hc), predictive models were created using a multilayer perceptron (MLP)-which has many uses in drying applications, as mentioned in the literature-and decision tree (DT), which has not been used before in food drying applications. The machine learning algorithms and results of the estimated models are compared in this study. Error analyses were performed to determine the accuracy rates of the obtained models. As a result, the hc value of the dried grape product in a natural convective solar greenhouse type dryer was 11.3% higher than that of the forced type. The DT algorithm was found to be a more successful model than the MLP algorithm in estimating hc values in HDFC according to Root Mean Square Error. (RMSE = 0.0903). On the contrary, the MLP algorithm was more successful than the DT algorithm in estimating hc values in GDNC (RMSE = 0.0815).

Yildiz, Sebahattin; Meydan, Cebrail; Boz, Ilknur Taştan; Sakal, Önder

In the context of corporate governance principles, governments set regulations to increase the sustainable representation of women on boards. This paper seeks to answer the question of whether or not the application of compulsory or voluntary quotas for female board members improves firm performance. Based on difference analyses on the 2011 principles of the Capital Markets Board (CMB), we do not find significant differences between the companies with at least one female member on their board and those without any female board members in terms of financial performance indicators (return on asset (ROA), return on equity (ROE), market value/book value (MV/BV)). Based on difference analyses on the 2014 principles of the Capital Markets Board, we further find that the ROA of the companies with 25% and more female members is lower than the companies with < 25% female members. These results don't support the arguments of agency theory, because government regulations including the efforts of women to increase their representation rate on the board in a sustainable manner don't improve the accounting-based and market-based performance indicators of companies. If the company is successful, a quota for women cannot be imposed, because the obligation may result in a negative effect. Policymakers and practitioners may benefit from the knowledge that women may be improved and prepared for these positions and be accompanied with mentors before filling the compulsory or voluntary quota for women. It is not enough to increase the rate of women. The policy implication of the paper is that women must be equipped with the resources, authority, knowledge, and skills to perform well.