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Many European businesses are small and medium enterprises (SMEs), contributing significantly to the well-being of local economies and regions. Even so, SMEs face many challenges in fostering innovation and improving performance. Furthermore, the raw material consumption is increasing globally, necessitating the development of strategies that will reduce the number of raw materials extracted and imported while improving the sustainability of small and medium-sized businesses. Consequently, promoting circular economy (CE) strategies, such as industrial symbiosis (IS) partnerships, whereby waste products from other industries serve as a source of raw materials for companies, is critical. Identifying and analysing enablers or drivers that support IS collaborations among SMEs is necessary to achieve this goal. In this regard, the purpose of this study will explore the enablers of IS among SMEs considering sustainability dimensions (environmental, social and economic). As facing a decision-making (DM) problem, the multiple attribute decision-making (MADM) approach was applied in a hesitant fuzzy (HF) environment in this research to answer the research questions. In this regard, in phase 1, IS enablers were identified and extracted using a literature review and experts’ opinions. In phase 2, the hesitant fuzzy Delphi (HFD) method was implemented to screen and finalise the enablers identified. In phase 3, casual relations among final enablers were determined using the hesitant fuzzy ANP (HF-ANP) method. Finally, in phase 4, the relative importance of enablers was calculated using the hesitant fuzzy best–worst method (HF-BWM). Consequently, this study provided potential strategies for IS that can be implemented quickly and used by local authorities to support SMEs in achieving circular waste management.

The purpose of this paper is to propose a conceptual model to investigate the determinants of information retweeting in microblogging based on Heuristic‐Systematic Model.

Microblogging data about emergency events from Sina microblogging (http://weibo.com) are collected and analyzed with text mining technology. The proposed hypotheses are tested with logistic and multiple linear regressions.

The results show that source trustworthiness, source expertise, source attractiveness, and the number of multimedia have significant effects on the information retweeting. In addition, source expertise moderates the effects of user trustworthiness and content objectivity on the information retweeting in microblogging.

This study provides an in‐depth understanding of what makes information about emergency events in microblogging diffuse so rapidly. Based on these findings the emergency management organizations in China can apply the microblogging to spread useful information, and these findings also provide practical implications for microblogging system designers.

The primary value of this paper lies in providing a better understanding of information retweeting in microblogging based on Heuristic‐Systematic Model. Organizations that would like to adopt the microblogging platform in emergency situations to improve the ability of emergency response can benefit from the findings of this study.

The purpose of this paper is to measure the financial efficiency and productivity of 23 public universities founded in 1992 in Turkey over the period between 2004 and 2013. The results obtained will provide managerial information and act as a guide to public universities’ administrations, in using their resources more effectively.

Data envelopment analysis is applied to assess the relative financial efficiency of these universities, while Malmquist total factor productivity index is used to measure the total factor productivity change concerning financial inputs of the universities.

The number of financially efficient universities and the number of universities showing an increase in their productivity according to their financial inputs change annually and both of them display a rough trend over the years. A decrease of about 5 percent in the financial productivity of the universities is observed which stems from a technological recession. Therefore, public universities in Turkey are not able to develop effective policies to diversify, increase and use their financial resources.

When the lack of studies within the literature measuring the financial efficiency of higher education institutions is taken into account, this study can fill a gap in this area. The analyses conducted here distinguish from existing studies on this subject with regards to the extent and diversity of financial data set and the measurement of both efficiency and productivity change of universities considering financial inputs concurrently.

This study produced epoxy-filled urea-formaldehyde (UF) microcapsules (MCs) and T-403 amine MCs using the in situ technique. The Taguchi method was used to determine the effects of the control factors (temperature, stirring speed, core-shell ratio and surfactant concentration) affecting MCs’ core diameter and core content and optimizing their optimum levels with a single criterion. Optimum control factor levels, which simultaneously provide maximum core diameter and core content of MCs, were determined by the PROMETHEE-GAIA multi-criteria optimization method. In addition, the optimized MC yield was analyzed by thermal camera images and compression test.

Microcracks in materials used for aerospace vehicles and automotive parts cause serious problems, so research on self-healing in materials science becomes critical. The damages caused by micro-cracks need to heal themselves quickly. The study has three aims: (1) production of self-healing MCs, mechanical and chemical characterization of produced MCs, (2) single-criteria and multi-criteria optimization of parameters providing maximum MC core diameter and core content, (3) investigation of self-healing property of produced MCs and evaluation. Firstly, MCs were produced to achieve these goals.

The optimized micro cures are buried in the epoxy matrix at different concentrations. Thermal camera images after damage indicate the presence of healing. An epoxy-amine MC consisting of a 10% by weight filled aluminum sandwich panel was prepared and subjected to a quasi-static compression test. It was determined that there is a strong bond between the UF shell and the epoxy resin.

The optimization of production factors has been realized to produce the most efficient MCs that heal using less expensive and more accessible methods.

The purpose of this study is to perform the preliminary design, flight performance and exhaust emissions calculations of a piston engine powered unmanned aerial vehicle (UAV) during a flight cycle which consists of multiple flight altitudes and airspeeds.

A genuine computer model in Matlab/Simulink was developed to predict the size and weight of UAV and piston engine (using Avgas 100LL fuel) performance together with exhaust emissions in an iterative process.

The amount of emitted exhaust gases including carbon dioxide, carbon monoxide, hydrocarbons and nitrogen oxides were calculated in a typical UAV mission profile as a whole and also divided into mission flight segments.

Emissions were calculated based on fuel flow and engine speed inputs based on ground test data for emission indices. Test data for emission indices was very limited.

As UAV utilization has been increasing around the world, this study presents important and noticeable results on the emissions that need to be considered for environmental purposes.

In literature, emission prediction studies for UAVs are very rare. In fact, UAVs typically have quite different flight speeds and altitudes than regular manned aircraft and emissions change with speed and altitude. Additionally, unlike manned aircraft, UAVs can fly more than 24 h with different operation characteristics. The originality of this study presents the emission predictions of a piston engine UAV which flies with a significantly different mission profile than a manned aircraft.

This study aims to illustrate the developmental and modernizational state management policies in the early Turkish Republic in the 1930s through the establishment of state-owned cotton textile factories in underdeveloped regions of the country. It analyzes the state’s industrial-cum-social engineering policies and their micro-level role in Turkish economic development.

To illustrate the government’s role in regional industrialization and modernization, this study uses an in-depth case analysis conducted in a sample of textile plants based on a microhistorical approach.

Turkey is considered among late developing countries. Following the War of Independence at the beginning of the 20th century, the new government focused on regional industrialization and social transformation through state-owned universal banks[1] acting as state agents of industrialization and modernization. Primary among them, Sümerbank constructed industrial plants in underdeveloped towns which subsequently became the nuclei of growing industrial centers of private enterprise. Sümerbank plants were also micro-level tools of westernization-based modernization of the society under the social engineering objectives of the new government.

This study uses a specific industrial policy measure (establishment of industrial plants) in explaining the state’s role in industrialization, regional development and social engineering. It sheds new light on the literature on state-led industrial-cum-modernization policies during earlier phases of economic development. It contributes to the international literature on the history of state management of economic and social development.

The objective of this study is to assess quantitatively how feasible blockchain is for various industries, such as logistics and supply chain, health, energy, finance, automotive, pharmaceutical and agriculture and food using a comprehensive list of indicators.

A decision aid was applied to the problem of identifying the feasibility of blockchain in Turkish industries. To this end, first, a set of indicators was identified. Then, the fuzzy AHP and fuzzy TOPSIS were utilized to assess the feasibility comparatively using the data gathered from a group of experts. Finally, a scenario analysis was conducted to ensure the consistency of our evaluation.

The findings of this study suggest that comparatively, logistics and supply chain, finance and health industries are the most feasible industries for blockchain. This study further suggests that blockchain is the least feasible for the automotive industry compared to the rest of the identified industries.

It is cumbersome to find out the respondents who have sufficient knowledge of both blockchain and the identified industries. Even if we took the utmost care in identifying the right respondents, we limited our search to the biggest industrial hubs of Turkey.

The findings of this research may help various decision-makers employed in governments, conglomerates, software and consulting firms and national research institutions make more informed decisions and allocate their resources more effectively.

To this date, the current studies have solely investigated possible research opportunities in blockchain and demonstrated several blockchain applications in stand-alone cases. To the best of our knowledge, however, no single study exists that evaluates the feasibility of blockchain comparatively and holistically among a group of industries using various indicators.

The objective of this study is to investigate the role of blockchain in reducing the impact of barriers to humanitarian supply chain management (HSCM) using a list of blockchain benefits.

A decision aid was used to explore the suitability of blockchain in humanitarian supply chains. To achieve that, first, a list of barriers to HSCM was identified. Then, the intuitionistic fuzzy decision-making trial and evaluation laboratory (IF–DEMATEL) method was utilized to determine the relationships and the level of interdependencies among the criteria. Finally, the intuitionistic fuzzyanalytic network process (IF–ANP) technique was employed, as it successfully handles dependencies among the criteria.

The findings of this study suggest that interorganizational barriers are the most suitable ones, the impacts of which blockchain may alleviate. This study further suggests that trust turned out to be the most significant benefit criterion for the analysis.

The readers should construe the findings of this study with caution since it was carried out using the data collected from the experts of a particular country. Moreover, the proposed decision aid contemplates a limited set of criteria to assess a possible role of blockchain in overcoming the barriers to HSCM.

The findings of this study can assist humanitarian supply chain managers to make more judicious assessments on whether they implement the blockchain in humanitarian supply chain operations. Specifically, this research may help decision makers to identify the certain barriers, the impact of which may be reduced by using the blockchain. The findings of this research will also help various decision makers make more rational decisions and allocate their resources more effectively.

To the best of authors’ knowledge, no single study exists to investigate the role of blockchain in reducing the impact of barriers to HSCM using an intuitionistic fuzzy multi-criteria decision-making approach.

The research presented in this study replicates and extends the QSport-10 scale proposed by Rial, Varela, Rial and Real in their 2010 study, by incorporating the Programme dimension into the original measurement of service quality in Physical Activity and Sports Centres (PSCs). The objective of this research is to examine the dimensionality of the QSport-10 scale and extend it to capture the additional Programme service quality dimension. Study results confirmed the dimensionality of the service quality measurement offered by the QSport-10 scale and presented strong empirical support for the existence of Programme, Installations and Staff dimensions. Programme dimension was considered the most important factor for the largest consumer segment in the study.

When the factors affecting health expenditures are examined in the literature, it is seen that one of the most important factors is income. In this context, the purpose of this study is to investigate the relationship between out-of-pocket health expenditures and disposable personal income and revealing the income elasticity of health expenditures.

Therefore, short/long-term coefficients were obtained by analyzing Westerlund (2007) co-integration analysis and pooled mean group (PMG) regression methods for 22 European Union (EU) member states during the period 2003–2017. In addition, a comparison of the long-term coefficients for each country was obtained with augmented mean group (AMG) estimator.

The results of the AMG and PMG tests show that the long-term coefficients between disposable personal income and health expenditures are 0.83 and 0.97, respectively. These results imply that there is a significant relationship between the variables, and that health care should be categorized in the group of normal goods. However, the fact that the long-term coefficient is very close to 1, despite being classified in the category of necessity goods, requires more care to be taken in evaluating whether health services are luxury goods or necessity goods.

The use of second generation econometric tests on both cross-sectional dependence and heterogeneity demonstrates the value of the study. On the other hand, obtaining similar results by investigating the relationship between variables using different appropriate econometric models reveals the importance of the methodology used in this study. It reveals important details in terms of the literature regarding the long-term and short-term results obtained in this study.