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In recent years, additive manufacturing (AM) has started to be used for manufacturing real functional parts and assemblies for critical applications in aerospace, automotive, and machinery industries. Most complex or assembled parts require internal features (IF) such as holes, channels, slots, or guides for locational and mating requirements. Therefore, it is critical to understand and compare the structural and mechanical properties of additively manufactured and conventionally machined IFs.

In this study, mechanical and microstructural properties of Inconel 718 (Inc718) alloy internal features, manufactured either as-built with AM or machining of additively manufactured (AMed) part thereafter were investigated.

The results showed that the average ultimate tensile strength (UTS) of additively manufactured center internal feature (AM-IF) is almost analogous to the machined internal feature (M-IF). However, the yield strength of M-IF is greater than that of AM-IF due the greater surface roughness of the internal feature in AM-IF, which is deemed to surpass the effect of microstructure on the mechanical performance. The results of digital image correlation (DIC) analysis suggest that AM-IF and M-IF conditions have similar strain values under the same stress levels but the specimens with as built IF have a more locally ductile region around their IF, which is confirmed by hardness test results. But this does not change global elongation behavior. The microstructural evolution starting from as-built (AB) and heat-treated (HT) samples to specimens with IF are examined. The microstructure of HT specimens has bimodal grain structure with d phase while the AB specimens display a very fine dendritic microstructure with the presence of carbides. Although they both have close values, machined specimens have a higher frequency of finer grains based on SEM images.

It was shown that the concurrent creation of the IF during AM can provide a final part with a preserved ultimate tensile strength and elongation but a decreased yield strength. The variation in UTS of AM-IF increases due to the surface roughness near the internal feature as compared to smooth internal surfaces in M-IF. Hence, the outcomes of this study are believed to be valuable for the industry in terms of determining the appropriate production strategy of parts with IF using AM and postprocessing processes.

When a large number of project proposals are evaluated to allocate available funds, grouping them based on their similarities is beneficial. Current approaches to group proposals are primarily based on manual matching of similar topics, discipline areas and keywords declared by project applicants. When the number of proposals increases, this task becomes complex and requires excessive time. This paper aims to demonstrate how to effectively use the rich information in the titles and abstracts of Turkish project proposals to group them automatically.

This study proposes a model that effectively groups Turkish project proposals by combining word embedding, clustering and classification techniques. The proposed model uses FastText, BERT and term frequency/inverse document frequency (TF/IDF) word-embedding techniques to extract terms from the titles and abstracts of project proposals in Turkish. The extracted terms were grouped using both the clustering and classification techniques. Natural groups contained within the corpus were discovered using k-means, k-means++, k-medoids and agglomerative clustering algorithms. Additionally, this study employs classification approaches to predict the target class for each document in the corpus. To classify project proposals, various classifiers, including k-nearest neighbors (KNN), support vector machines (SVM), artificial neural networks (ANN), classification and regression trees (CART) and random forest (RF), are used. Empirical experiments were conducted to validate the effectiveness of the proposed method by using real data from the Istanbul Development Agency.

The results show that the generated word embeddings can effectively represent proposal texts as vectors, and can be used as inputs for clustering or classification algorithms. Using clustering algorithms, the document corpus is divided into five groups. In addition, the results demonstrate that the proposals can easily be categorized into predefined categories using classification algorithms. SVM-Linear achieved the highest prediction accuracy (89.2%) with the FastText word embedding method. A comparison of manual grouping with automatic classification and clustering results revealed that both classification and clustering techniques have a high success rate.

The proposed model automatically benefits from the rich information in project proposals and significantly reduces numerous time-consuming tasks that managers must perform manually. Thus, it eliminates the drawbacks of the current manual methods and yields significantly more accurate results. In the future, additional experiments should be conducted to validate the proposed method using data from other funding organizations.

This study presents the application of word embedding methods to effectively use the rich information in the titles and abstracts of Turkish project proposals. Existing research studies focus on the automatic grouping of proposals; traditional frequency-based word embedding methods are used for feature extraction methods to represent project proposals. Unlike previous research, this study employs two outperforming neural network-based textual feature extraction techniques to obtain terms representing the proposals: BERT as a contextual word embedding method and FastText as a static word embedding method. Moreover, to the best of our knowledge, there has been no research conducted on the grouping of project proposals in Turkish.

The purpose of this study is to measure and analyze the national innovation efficiency of organisation for economic co-operation and development (OECD) countries. This is to determine to what extent OECD countries efficiently use the elements that enable innovation activities possible in generating innovation outputs.

An input–output model was constructed to measure efficiency. The inputs and outputs in the research model are the input and output sub-indices of the Global Innovation Index. Data envelopment analysis was used to measure the national innovation efficiency levels of OECD countries.

The results show that national innovation efficiency is generally high in OECD countries. However, some countries lag behind in innovation efficiency. OECD countries’ ability to create and provide the elements that enable innovation activities is higher than their ability to create innovation outputs. OECD countries have a good innovation environment and a high level of resources, but they should focus on how to create more innovation outputs.

This study presents a measurement of national innovation efficiency of OECD countries which contributes “Innovation Strategy” agenda. The results empirically show that overall innovation indices cannot be the only indicator of the performance of national innovation systems. In this study, an innovation efficiency/performance matrix is constructed to present the relative positions of the countries to help in examining countries’ strengths, weaknesses and potentials based on innovation efficiency and innovation performance simultaneously. This study contributes to the literature by presenting a broader perspective and measurement of national innovation efficiency by taking an extensive number of indicators into account.

This paper aims to determine the knowledge and attitudes of the physicians regarding human immunodeficiency virus (HIV)/acquired immune deficiency syndrome (AIDS), to emphasize that these patients exist and they will exist in the future and to raise awareness so as to prevent that their rights to treatment are revoked.

The survey was conducted via a link sent through an online system. Random physicians from 81 cities of the country were invited to the survey. The survey has 41 questions regarding knowledge and attitudes in total, including epidemiological information such as age, gender and title.

A total of 3,107 physicians has voluntarily participated in the study. In total, 2,195 (70.7%) are internal physicians and 912 (29.3%) are surgical physicians among the participant physicians. In total, 1,452 (46.7%) of the participants are specialist physicians, 608 (19.6%) of the participants are practising physician and the rest of it is physician assistants, academicians and dentists, respectively.

In this study, it has been found out that the physicians have a lack of knowledge on HIV/AIDS and they adopt a discriminatory attitude towards HIV-positive persons. HIV-positive patients who are exposed to discrimination and scared of being uncovered refrain from applying to hospitals for treatment, which puts public health into jeopardy due to the high viral load and these patients are faced with difficulties in coping with both medical and emotional load of the disease.

Agricultural sector not only meets the nutritional requirements of all living creatures but also generates the primary source of the raw material provided by various branches of industry to fulfill their functions. It is of great importance to increase studies on oilseeds which have an important role in Turkey's agricultural products. They are grown in almost all of the country, which are vital for the nutrition and many sectors. The main purpose of the study is to offer an integrated approach to determine potential warehouse locations for oilseeds.

This is the first study that integrates Delphi, analytical hierarchical process (AHP), technique for order preference by similarity to ideal solution (TOPSIS), P-Median and Panel data analysis in a real case. This integrated approach consists of the following steps, respectively: (1) The criteria were determined by the Delphi method. (2) The weights of the criteria were calculated by AHP and the provinces with the highest oilseed warehouse potential in seven regions of Turkey were specified by TOPSIS. (3) Oilseed warehouse numbers and locations were obtained by P-Median. (4) In order to answer whether the distribution network is profitable in the future with the determined center locations, a forecast model based on panel data analysis was created. (5) Regional representatives were determined for 2030, and the distribution network was analyzed again. (6) The costs that arose in 2018 and 2030 were computed and compared by cost analysis. (7) The effect of the change in criteria weights on the alternative results was tested by scenario analysis.

The findings indicated that oilseed crop production potential and oilseed crop production area turned out to be the most important criteria. Furthermore, the results showed that this model is robust and suitable for warehouse location selection studies.

The study can serve as a guide for local and central policy makers with both the criteria it uses and the model it develops.

The main contribution of this study is that the integrated approach has been used for the first time in location selection in a real case.

The user experience during the use of activities and services is a fundamental aspect for sports managers and can provide a competitive advantage. The purpose of this study was to identify the dimensions of experiential quality and the relationship of this construct with customer trust and customer satisfaction in achieving behavioral intention.

Using a convenience sampling technique, a total of 322 gym users in Turkey participated. A two-step approach was used to test both the model and the research hypotheses [confirmatory factor analysis (CFA) and structural equation modeling (SEM)].

The interaction quality, physical environmental quality, outcome quality and enjoyment quality were positively related to experiential quality. Similarly, the experimental quality was positively related to customer satisfaction and customer trust. Finally, customer satisfaction was related to behavioral intentions.

This study provides empirical evidence about the importance of experiential quality to gain a competitive advantage in the context of fitness centers.

This study aims to investigate the moderating role of perceived organizational support in the relationship between ethical leadership and innovative work behavior (IWB) among public university academic staff.

Using a quantitative approach, the authors relied on structural equation modeling together with bootstrapping procedure using Process Macro of the SPSS to analyze data from a homogenous sample of 291 academic staff from the university education sector in Uganda.

The finding from bootstrapping procedure using Process Macro of the SPSS as statistic tool support perceived organizational support as a moderator in the ethical leadership–IWB relationship. In general, the present findings suggest that ethical leadership is associated with IWB via perceived organization support.

Enhanced IWB requires diverse and integrated techniques based on ethical leadership principles and perceived organizational support among employees.

There is increasing acknowledgement of the importance of ethical leadership in successful employee IWBs. Within this context, to the best of the authors’ knowledge, no prior study has empirically explored the moderating role of POS in the relationship between ethical leadership and IWB.

This study aims to determine the order of importance of blockchain technology gains for foreign trade management. The second aim of the research is to select the most suitable blockchain type for the foreign trade process.

The data required for the research analysis were collected through comparison matrices scored by foreign trade experts. The data were analyzed with the analytical hierarchy process method, and the gains of blockchain technology for the foreign trade process were prioritized. Finally, the most suitable type of blockchain technology was selected with the PROMETHEE method.

As a result of the study, subject matter experts perceived that the most critical blockchain gain for the foreign trade process would be cost savings. In addition, it has been observed that the general trade process differs compared to the logistics and payment processes. Finally, open blockchain was the most suitable blockchain type for foreign trade processes.

In this study, the positive gains of blockchain technology are considered. In future studies, it is recommended to consider the existing negative factors to be able to use blockchain technology in foreign trade processes. In addition, it is suggested to conduct a study by dividing foreign trade into two, import and export.

All stakeholders who want to integrate blockchain technology into their foreign trade processes, including foreign trade companies, software developers, policymakers and international institutions, can benefit from the results of this study. A blockchain technology software created for foreign trade management can be shaped according to the results of this study.

Although the gains that blockchain technology provides to foreign trade processes are frequently emphasized in the literature, which gain would be greater has not been examined. The lack of an answer to the issue of how blockchain technology should be designed for foreign trade processes has been the missing part of the relevant literature. To the best of the authors’ knowledge, this study is the first experimental study in the literature that prioritizes blockchain gains and selects the appropriate blockchain type for foreign trade processes.

In this study, the author aimed to measure the effect of customer loyalty on customer citizenship behavior as well as the effect of experience value perceptions of tourist railway journey customers on customer loyalty within the scope of social exchange theory.

The author obtained data from 126 participants who had experienced the tourist railway adventure through random sampling. In the next stage, the author extracted the data obtained with the bootstrapping sample technique to 5,000 samples. The author analyzed these obtained data with the PLS-SEM model with the Smart PLS 3 software.

The results of the research show that the most important experience value dimension that creates loyalty in the touristic railway journey is the emotional value dimension; the second important dimension is the hedonic value dimension and other experience value dimensions did not have any effect on customer loyalty intention levels. In addition, an important result of the study is that loyal customers mostly intend to advise other customers, and relatively less of them intend to give feedback to the firm.

The fact that the concepts of touristic railway journeys are different due to the nature of tourism is an important limitation of the study, which is only for individuals who have experienced the Touristic Eastern Express. The fact that the Touristic Eastern Express is a long journey and stops at many destinations on its arrival and departure route can affect customers' perceptions of the experience value.

The values that create customer loyalty in the touristic railway journey are mostly emotional and hedonic values. In addition, customers who are loyal as a result of this journey are more intent on advising other customers than giving feedback to the firm.

The study was carried out on the customers of the touristic eastern express, which started its activities in 2019. Ensuring customer loyalty for the sustainability of this trend has significant tourism potential; Afterwards, the transformation of customer loyalty into customer citizenship has a very important place. In addition, as far as we have examined the literature, the absence of similar studies in the tourism sector is an indicator of the study's originality. Considering these data, it is expected that the study will fill an important gap in terms of both sectoral and academic.