Sürdürülebilir Kalkınma Amaçları
Yazarlar
- Kaygusuz, Abdullah(35)
- Sipahi, Ferkan(35)
- Karsli, Orhan(34)
- Dokuz, Abdurrahman(30)
- Duran, Celal(30)
- Kandemir, Raif(29)
- Ozdes, Duygu(28)
- Maden, Nafiz(27)
- Uzun, Sevda(27)
- Merdan, Mehmet(26)
- Vural, Alaaddin(26)
- Öztürk, Serkan(25)
- Araz, Onur(24)
- Kulakaç, Nurşen(24)
- Ashyralyyev, Charyyar(23)
- Yildiz, Salih(23)
- Yilmaz, Ozgur(23)
- Doğan, Kadir Caner(21)
- Arslan, Mehmet(20)
- Aydin, Faruk(20)
- Doğru, Bülent(20)
- Bayraktar, Alemdar(19)
- Kankal, Murat(19)
- Ayaydin, Hasan(18)
- Baltaci, Cemalettin(18)
- Yolcu, Halil(18)
- Cakir, Tufan(17)
- Cengiz, Ekrem(17)
- Demir, Selim(17)
- Gücer, Mehmet Ali(17)
- Akaryali, Enver(16)
- Artan, Seyfettin(16)
- Hayaloğlu, Pınar(16)
- Kaya, Afşin Ahmet(16)
- Tosunoğlu, Büşra(16)
- Uysal, Ibrahim(16)
- Kurt, Kemal(15)
- Ozturk, Samet(15)
- Reis, Hatice Catal(15)
- Aksakal, Vecihi(14)
Yayınlar
- MakaleYalnız künye2025The Impact of Nuclear Energy on Environmental, Economic, and Agricultural Dynamics: New Evidence for More Sustainability
Akar, Gokhan; Akyol, Hikmet; Saritas, Tufan
The extremes caused by climate change threaten the economic and agricultural future of nations. This research examined the impact of NE (nuclear energy) on CO2, GDP and Agro-Production Indices (API) for 24 developed and developing countries. The results of the research showed that the variables are cointegrated in the long run. The estimated results of FMOLS and AMG revealed that the use of NE reduces CO2 and increases environmental quality. In this context, our results show that NE contributes to environmental, economic and agricultural sustainability. We found that oil consumption negatively affects all API, and renewable energy (RE) consumption negatively affects agricultural and food production indices. Causality analyses showed that NE policies are compatible with environmental and RE policies. Therefore, the use of NE can play a crucial role in the transition to clean energy in research countries and in the adaptation of the agricultural sector to RE sources. In these countries, it is important to encourage policies that will reduce the dependence of the agricultural sector on fossil fuel consumption and reduce costs in the transition to clean energy sources in terms of food security and sustainable agriculture practices. The integration of nuclear energy into the agricultural sector can contribute to reducing input costs in the agricultural sector and reducing fluctuations and volatilities in food prices. In addition, the continuity of energy supply, technological innovation and infrastructure investments provided by nuclear energy can play a key role in the transition to clean energy and the achievement of the sustainable development goals of countries.
- MakaleYalnız künye2025Scopus SJRQ1How do green hotel practices affect guests' behavioral intentions? A PLS-SEM approach
Genç, Gokhan; Zengin, Burhanettin
This study examines how guests' perceptions of green hotel practices (GHP) shape their behavioral intentions, drawing on the Theory of Planned Behavior. It explores the extent to which eco-friendly practices influence guests' loyalty and their likelihood of recommending hotels that prioritize sustainability. Data were collected from 642 hotel guests aged 18 and over who had previous experience with green hotel practices. An online survey was employed, and the data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with bootstrapping techniques to assess the relationships among guests' perceptions of GHP, satisfaction, and behavioral outcomes. The findings indicate that favorable perceptions of GHP strongly predict guest loyalty and recommendation intentions, with satisfaction as a critical mediator. These results highlight the pivotal role of sustainable practices in fostering positive guest experiences and behaviors in the hospitality industry. The study offers practical insights for hotel managers, enabling them to design and implement effective sustainability strategies that enhance guest satisfaction and loyalty. Furthermore, it contributes to the literature on sustainable tourism by providing robust empirical evidence on the influence of GHP on guest behavior, thus addressing a key gap in hospitality management research.
AtıfWoS5
İncele - MakaleYalnız künye2025Scopus SJRQ1Performance assessment of solar-powered electric vehicles: Importance of maximum power point tracking, range enhancement and charging frequency analysis under various operating and irradiance conditions
Başoğlu, Mustafa Engin
Decarbonizing the transportation sector is becoming a crucial focus in the 21st century. As the popularity of internal combustion engine vehicles declines, the adoption of hybrid and electric vehicles (EVs) is significantly increasing. One of the main challenges for battery-powered vehicles, aside from safety concerns, is the limited driving range and frequent charging requirements. Integrating a photovoltaic (PV) module onto a vehicle's surface enables continuous battery charging during both motion and stationary periods, thereby extending the vehicle's range on a full charge. This study presents two main contributions: a modified 0.8VOC-based maximum power point tracking (MPPT) method for fast-changing irradiance conditions for flat-roof vehicle-integrated PV (VIPV) systems, and a long-term simulation analysis of classical MPPT methods using two new indicators for range extension and vehicle charging frequency variations under different irradiance profiles. The proposed MPPT method yielded superior energy performance, achieving 16–25 % higher energy generation compared to both the incremental conductance (IC) algorithm and the variable step-sized (VSS) perturb and observe (P&O) method. Long-term simulations conducted for three EV models demonstrated a daily driving range extension of 2–7 km with an 185W PV module, along with up to a 19 % reduction in charging frequency, depending on the battery capacity and vehicle models.
AtıfScopus4WoS4OpenAlex4
İncele - MakaleYayıncıda açık erişim2025Scopus SJRQ1Attitude synchronization of chaotic satellites with unknown dynamics using a neural network based fixed time sliding mode controller
Bingöl, Özhan
This study investigates the synchronization and anti-synchronization of both identical and non-identical chaotic satellite systems. A fixed-time sliding mode control framework, based on a radial basis function (RBF) neural network, has been developed to synchronize the chaotic dynamics of master–slave satellite configurations. The proposed control scheme operates under the assumption that the dynamics of the satellites are not entirely known. The proposed control method guarantees that system errors will converge to negligible levels within a fixed time. Furthermore, the controller exhibits robustness in the presence of parametric uncertainties and external disturbances. The stability of the controlled systems is rigorously validated through Lyapunov analysis, and the controller's effectiveness is confirmed through extensive simulation studies. These simulations are conducted on both identical and non-identical satellite models, with performance comparisons made against recent findings reported in the literature.
AtıfScopus9WoS9OpenAlex9İncele - MakaleYayıncıda açık erişim2025Scopus SJRQ2A structured educational model to improve the education of nurses: Case-based learning
Aydın, Aydanur
Background: Case-based training is a crucial component of nursing education, providing students with opportunities to enhance clinical reasoning, critical thinking, and professional behavior. However, few studies integrate these constructs into measurable educational outcomes. Methods: This study aims to look at the influence of online care training, which is based on case studies in surgical illnesses nursing, on students' care behaviors and self-efficacy levels. Participants were randomly assigned to undergo case-based education or traditional instruction. One hundred and four undergraduate nursing students from one university were chosen to participate. The structure is logical, with causal relationships between claims and a clear order of information. The researcher used an online platform to collect data from students in both groups before and three months after training. The introduction features form comprised the caring behavior scale (CBS) and questions to assess nursing students' self-efficacy. Results: Before the training, there was no discernible difference in the levels of care exhibited by the participants or in their self-efficacy. Nevertheless, a notable alteration was observed in the CBS scores of the intervention group students following the training period. Their CBS and self-efficacy scores surpassed those of the control group. The results of the regression analysis indicated that age, gender, place of residence, and caring assessment scores did not exert a significant influence on the total score of the Caring Behavior Scale. Conclusion: The findings of the research indicated that structured case-based nursing education was an effective method for fostering the development of caring behaviors among students.
AtıfScopus2WoS1OpenAlex2İncele - MakaleYayıncıda açık erişim2025Scopus SJRQ2Convergence on Kirk Iteration of Cesàro Means for Asymptotically Nonexpansive Mappings
Cona, Lale; Şimşek, Deniz
This article addresses the convergence of iteration sequences in Cesàro means for asymptotically nonexpansive mappings. Specifically, this study explores the behavior of Kirk iteration in the Cesàro means in the context of uniformly convex and reflexive Banach spaces equipped with uniformly Gâteaux differentiable norms. The focus is to determine the conditions under which the Kirk iteration sequence converges strongly or weakly to a fixed point. Finally, some examples are given in this article to demonstrate the advantages of the preferred iteration method and to verify the results obtained.
AtıfScopus1WoS1OpenAlex1İncele - MakaleYalnız künye2025Scopus SJRQ1A deep neural network combined with a two-stage ensemble model for detecting cracks in concrete structures
Reis, Hatice Catal; Turk, Veysel; Kaya Yildiz, Cagla Melisa; Bozkurt, Muhammet Furkan; Karagoz, Seray Nur; Ustuner, Mustafa
Detection of cracks in concrete structures is critical for their safety and the sustainability of maintenance processes. Traditional inspection techniques are costly, time-consuming, and inefficient regarding human resources. Deep learning architectures have become more widespread in recent years by accelerating these processes and increasing their efficiency. Deep learning models (DLMs) stand out as an effective solution in crack detection due to their features such as end-to-end learning capability, model adaptation, and automatic learning processes. However, providing an optimal balance between model performance and computational efficiency of DLMs is a vital research topic. In this article, three different methods are proposed for detecting cracks in concrete structures. In the first method, a Separable Convolutional with Attention and Multi-layer Enhanced Fusion Network (SCAMEFNet) deep neural network, which has a deep architecture and can provide a balance between the depth of DLMs and model parameters, has been developed. This model was designed using a convolutional neural network, multi-head attention, and various fusion techniques. The second method proposes a modified vision transformer (ViT) model. A two-stage ensemble learning model, deep feature-based two-stage ensemble model (DFTSEM), is proposed in the third method. In this method, deep features and machine learning methods are used. The proposed approaches are evaluated using the Concrete Cracks Image Data set, which the authors collected and contains concrete cracks on building surfaces. The results show that the SCAMEFNet model achieved an accuracy rate of 98.83%, the ViT model 97.33%, and the DFTSEM model 99.00%. These findings show that the proposed techniques successfully detect surface cracks and deformations and can provide practical solutions to real-world problems. In addition, the developed methods can contribute as a tool for BIM platforms in smart cities for building health.
AtıfScopus2WoS2OpenAlex1İncele - MakaleYalnız künye2025Scopus SJRQ3Interpretable machine learning for rapid prediction and calibration of HPGe detector efficiency: a physics-informed approach and online platform
Yesilkanat, Cafer Mert; Celik, Necati; Celik, Ahmet; Cevik, Ugur
This study introduces a novel, physics-informed, and calibration-friendly hybrid machine learning framework for the rapid and accurate prediction of the Full Energy Peak (FEP) efficiency in High-Purity Germanium (HPGe) detectors. To overcome the limitations of conventional “black-box” models, our two-stage approach first represents the FEP efficiency curve using a physically interpretable logarithmic polynomial. Subsequently, machine learning models were trained to predict the polynomial coefficients directly from the detector geometric parameters using a comprehensive dataset generated via Monte Carlo simulations. Among the various algorithms tested, the Generalized Linear Model yielded superior performance, achieving R2 values of 0.975–0.992 for the coefficients. While raw model predictions showed expected variability, a key feature of our framework (a single-point calibration protocol using one known efficiency value) dramatically improved accuracy, reducing the mean absolute percentage error by an average of 80% on the independent test data. The calibrated model was further validated using an experimental detector. The entire framework was deployed as a user-friendly online platform, enabling researchers to instantly generate and calibrate efficiency curves. Our work successfully harmonizes interpretability, speed, and accuracy, offering a powerful tool for the design, optimization, and routine calibration of HPGe detectors.
AtıfScopus4WoS3OpenAlex3İncele - MakaleYayıncıda açık erişim2025Scopus SJRQ3An Analysis on The Relationship of Organic Honey Production and The Number of Producers with Growth, Employment, and Agricultural Employment in Türkiye; [Türkiye’de Organik Bal Üretimi ve Üretici Sayısı ile Büyüme, İstihdam ve Tarımsal İstihdam Arasındaki İlişkinin Tespitine Yönelik Bir Analiz]
Merdan, Kurtuluş
The growing world population has driven humanity to produce more food, potentially leading to the neglect of quality and safety in food production. Evolving life conditions and technological progress have altered the consciousness level of humanity, bringing about new demands in some communities due to high income. Organic beekeeping has developed within this structure and tends to flourish as a model in Türkiye. Organic beekeeping has increased the income from beekeeping. It is practiced in natural unspoiled areas with no conventional feeding and chemical pesticides and requires supervising all processes through inspection and certification. Besides organic honey, the most common organic beekeeping product, organic bee products include bee pollen, propolis, royal jelly, beeswax, and bee venom. This study presents the economic analysis of organic honey production volume in Türkiye. For this purpose, the short and long-term relationships of organic honey production and the number of producers with economic growth, employment, and agricultural employment were analyzed. In addition, organic honey production and the number of organic honey producers were examined as driving forces for growth, employment, and agricultural employment. In this context, annual time series data between 2004 and 2022 were used as the sample. According to the analysis, organic honey production, an independent variable, had no long-term relationship with employment and agricultural employment variables, whereas it had a long-term relationship with the growth variable. The number of organic honey producers, another independent variable, was found to have no long-run relationship with the employment variable; however, it had a long-term relationship with the growth and agricultural employment variables. The findings of the study indicated that organic honey production did not drive growth, employment, or agricultural employment. On the other hand, the number of organic honey producers led to growth, yet not to employment or agricultural employment.
- BildiriYalnız künye2025Multi Objective Reinforcement Tuning for Responsible Generative AI in Automated Financial Advisory Systems
Bhandarkar, Vishakha D; Genemo, Musa Dima; Muda, Iskandar; Murugan, Rekha; Sreeram, G.; Dharani, N.
Generative AI in a financial context poses risks to the areas of regulatory compliance, accuracy in the content being delivered, and appropriateness in terms of emotion. This research proposes ReFiGen, a framework that can be used to create compliant financial content that is compliant with the regulatory framework and the sentiment of the users. Following domain-specific fine-tuning, ReFiGen blends sentiment alignment with reinforcement learning to optimize on compliance. It demonstrates better performance than baseline models with a high data accuracy rate of 98.35 percent and can generate a fluent output that is emotionally congruent, and regulation-minded. The results of experiments indicate that ReFiGen is both clear and coherent and exactly follows financial guidelines. This practice affirms that the combination of unstructured compliance modeling and affective control is a successful aspect of LLMs. ReFiGen is one of the milestones on the journey of trustworthy and ethically aligned AI in the financial advisory market.
- Kitap BölümüYalnız künye2025Scopus SJRQ4The Robust Method for Solving the Conformable Time-Fractional Klein–Gordon Equation
Anaç, Halil
The present study used the conformable fractional q-Shehu homotopy analysis transform method to investigate the conformable time-fractional Klein–Gordon equations with proportional delay. The numerical answers to this problem are graphed using Maple software. The efficacy and consistency of the proposed method have been demonstrated through numerical simulations.
- Kitap BölümüYalnız künye2025Scopus SJRQ4Investigation of Fractional Order Genesio-Tesi System Using Laplace Transformation
Bekiryazici, Zafer; Sengul, Suleyman; Merdan, Mehmet
In this paper the fractional-order Genesio-Tesi chaotic system is investigated with Laplace transformation method. Genesio-Tesi system is a three-dimensional equation system with quadratic nonlinearity and is frequently used for exemplifying chaotic systems. In this study, Caputo fractional derivative is used to obtain the fractional system and Laplace transformation is applied in order to analyze the explicit solutions of the system.
- MakaleYalnız künye2025Scopus SJRQ2Development of gluten-free cookie using composite flour from corn and lentil flours: Study by response surface methodology
Bursa, Batuhan; İlyasoğlu, Huri
The demand for gluten-free foods has increased due to health-based issues and lifestyle choices. This study aimed to develop a gluten-free cookie with enhanced nutritional value. For this reason, the composite flour from corn flour (CF) and lentil flour (LF) was prepared for cookie formulation. To eliminate the possible negative impact of LF on the sensorial properties of the cookie, lemon peel powder (LPP) was incorporated into the cookie formulation. The effects of the LF level of composite flour and the incorporation level of LPP on the physical, textural, and sensorial properties of the cookie were investigated via response methodology. The optimal levels were found as 16 g LF and 1 g LPP for 100 g composite flour. The physical, textural, and sensorial properties, proximate composition, vitamin C and total phenolic contents, and antioxidant capacity of the developed cookie and control cookies were determined. The developed cookie had a higher nutritional value than the control cookie made from CF in terms of protein, dietary fibre, ash, and vitamin C. Moreover, it presented higher total phenolic content and radical scavenging activity. According to these results, the developed cookie can be proposed for a gluten-free diet.
AtıfScopus3WoS2
İncele - MakaleYalnız künye2025Scopus SJRQ3Golden Distance: A New and Comprehensive Metric Definition Study Facilitating Classification Performance Evaluations
Melek, Mesut; Melek, Negin
Machine/deep learning has great potential in many classification studies that make our lives easier. Performance evaluation of the classification algorithm is of great importance for making accurate predictions in machine learning, which, itself, learns from data without any human intervention. In these learning models, high-dimensional data in classes with complex features belonging to balanced or unbalanced distributions are analysed with different classification algorithms and take their place in the decision stage. While the difficulties in implementing classification algorithms continue today, evaluating the superiority of developed systems over each other continues to be both a time-consuming and very difficult process. In models proposed in the literature, only a single parameter, such as accuracy, is not sufficient to determine model adequacy. In this context, among different classification algorithm performance parameters, some metrics such as sensitivity, specificity, F-measure (F1), Jaccard index, area under the curve, and kappa coefficient are used for system evaluation. As these parameters are placed in the analysis tables, the study should be evaluated at length by including large tables in the article. Instead of using various parameters that make performance analysis difficult in system evaluation, this study defines a new Golden Distance-based parameter that summarizes the model comprehensively from all dimensions. To understand this new metric’s working principle, a detailed comparative analysis of research conducted on three datasets was performed. Based on the final evaluation, the proposed inclusive metric demonstrated successful and fair behaviour in all conditions. Thus, a fair and simple comparison will be achieved with a single metric, and long analyses can be avoided by presenting many performance parameters in systems’ superiority indicator tables.
AtıfScopus9WoS10OpenAlex12İncele - MakaleYayıncıda açık erişim2025Scopus SJRQ2Optimizing Visibility of Historical Structures Using Modified Weighted Differential Evolution: Insights from the Kromni Valley, Gümüşhane, Türkiye
Günen, Mehmet Akif; Öztürk, Kaşif Furkan; Aliyazıcıoğlu, Şener
It is very important for historical structures to see each other in order to reveal the historical and cultural identity of a region. Historical structures in the Kromni Valley of Gümüşhane, located near the Sümela Monastery, served as places of worship, communication, trade, and social activity centers during their period of active use. This study analyses the spatial relationships of 38 historic buildings, including churches, chapels and castles, whose 3D models are created by in-situ measurements and point clouds obtained by unmanned aerial vehicles, using a 3D viewshed analysis using geographic information systems and remote sensing data. The research introduces a modified weighted differential evolution-based viewshed analysis (mWDE-WS) to enhance the visibility of these structures. In order to assess the applicability of the proposed method, a statistical comparison was conducted between four different Differential Evolution (DE) algorithms (standard DE, LSHADE, CobiDE, JADE and WDE) and the mWDE. The Wilcoxon signed-rank test indicates that mWDE is a more effective solution than alternative methods for addressing the relevant real-world issues. The study also integrates drainage network analysis to assess flood risks and the relationship between cultural structures and water flow. Findings show that historical structures in the region were built not randomly but within a rational approach and 64% of the study area is visible from structures and 2% of the area is visible from ten or more structures. mWDE-WS analysis revealed that the visible area could increase by 20% to 84.37% if the historic structures were placed in optimal locations. In addition, the historical structures were built away from 3rd order streams to minimize flood risk and humidity, demonstrating the community's awareness of the local topography and hydrology.
AtıfScopus1OpenAlex3İncele - MakaleYalnız künye2025Scopus SJRQ3The Epiphytic Bryophyte Vegetation of the Karçal Mountains (Artvin, Türkiye)
Batan, Nevzat; Özcan, Osman; Ezer, Tülay; Erata, Hüseyin; Alataş, Mevlüt
Abstract: In this study, the epiphytic bryophyte vegetation of the Karçal Mountains (Artvin) in the Caucasus Region was investigated. Relevés collected from living tree trunks during various vegetation periods in 2022 were analyzed using the Braun-Blanquet method and multivariate analysis techniques. As a result, Anomodontetum attenuati-Ulotetosum crispae subass. nov. was described and characterised as a new epiphytic syntaxa. In addition, Orthotrichetum rupestris, Orthotrichetum speciosi, Uloto crispae-Orthotrichetum striati, and Anomodonto viticulosi-Leucodontetum sciuroidis-Anomodontetosum attenuati were determined for the first time in Türkiye. All syntaxa were presented by analyzing them in terms of their ecological and floristical classifications.
AtıfScopus1İncele - Kitap BölümüYalnız künye2025Assessment of Türkiye's Healthcare Quality Standards Using the FUCOM Method: FUCOM Method
Bolayir, Banu
This study aims to determine the importance ranking of healthcare quality standards in Türkiye. The latest version of the Healthcare Quality Standards-Hospital (Version 6.1) was used as the healthcare quality standards in Türkiye. The FUCOM method, one of the multi-criteria decision-making (MCDM) methods, was employed to rank the importance of these standards. To use this method, a questionnaire based on the healthcare quality standards was filled out by six experts. The data obtained from the questionnaire were transferred to Microsoft Excel Solver, and the FUCOM method was used with this program. Using the FUCOM method, the local importance weights of the main criteria and sub-criteria were initially determined. Then, the criteria were ranked based on these weights. Subsequently, after determining the global importance weights of the sub-criteria considering the local importance weights of both the main criteria and sub-criteria, their rankings were also established based on these weights.
- Kitap BölümüYalnız künye2025Income Inequality and Environmental Protection Expenditures Nexus Bootstrap Panel Rolling Window Causality Analysis.
Sentürk, Nazlı Keyifli; Sentürk, Suat Hayri; Karakurt, Birol
The relationship between environmental protection expenditures and income inequality is undoubtedly a critical issue in terms of social justice and sustainable development. In societies with high income inequality, environmental protection expenditures are generally lower. This is because low-income individuals tend to have less motivation to develop awareness of environmental issues or to support environmental protection policies. On the other hand, in societies where income is more equitably distributed, environmental protection expenditures tend to increase. A key factor behind this is that a larger segment of society views environmental.
- MakaleYalnız künye2025Scopus SJRQ1Discontinuities identification from rock outcrop using auto-encoder and point clouds
Günen, Mehmet Akif; Aliyazıcıoğlu, Şener
Rock slopes and geotechnical structures often exhibit discontinuity planes, which significantly influence their mechanical behavior and stability. The precise identification of these discontinuities is critical for ensuring the safety and cost-effectiveness of construction projects. However, previous methods are often limited by subjectivity, low automation, and challenges in inaccessible or hazardous environments. This study introduces a novel seven-step approach utilizing auto-encoders for estimating the orientation parameters of individual discontinuity sets from point cloud data. The steps include: data collection, filtering point clouds to eliminate outliers, determining neighborhood size, feature extraction, training a stacked auto-encoder for feature learning, estimating discontinuity sets using density-based clustering, and calculating individual discontinuities through the least squares method for orientation parameter estimation. In addition, the methodology incorporates a planarity-based approach for estimating neighborhood size. The statistical performance has been validated through evaluations in two real case studies and one synthetic case study. The classification achieves an accuracy exceeding 95%, highlighting the high efficacy of the approach. Results for orientation parameter estimation show consistency with existing methods and in situ measurements, with average orientation values for discontinuities within 5 degrees for individual sets. This framework represents a considerable advancement in rock discontinuity analysis, offering a robust and automated solution that is particularly effective in hazardous and hard-to-reach areas.
AtıfScopus10WoS10OpenAlex11İncele - MakaleYalnız künye2025Scopus SJRQ2Beyond the Call to Serve: Measuring Donation Motives in Social Work Students
Akinci, Habibullah; Yücel, İbrahim; Kalayci, Erdinç
Understanding the motivations behind charitable giving is crucial, particularly among emerging social work professionals. This study presents the development and validation of a novel “Donation Motives Scale” specifically designed for social work students. Drawing upon established theories of donation behavior and existing measurement tools, a comprehensive item pool was generated. Through rigorous analysis, a 17-item scale emerged, structured around four distinct factors: social dignity and appreciation, social responsibility, personal satisfaction and self-evaluation, and humanity and empathy. The scale demonstrated strong validity and reliability within a sample of university students, indicating its potential as a robust tool for investigating donation motives within this population.
