SDG 9 · Sanayi, Yenilikçilik ve Altyapı · SDG

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MakaleAçık Erişim2022/r/gumushane/17056
Doğu Karadeniz Bölgesi Sahil Otoyol Çevresindeki Karayosunlarında Trafik Kaynaklı Ağır Metal Analizleri
Kaya, Selim; Koz, Bahadir
Bu çalışmanın amacı; Giresun-Samsun otoyol çevresindeki karayosunları kullanılarak Trafik kaynaklı ağır metal kirliliğini belirleyebilmektir. Karayosunları, ağır metalleri biriktirebilme yeteneğinden dolayı, ağır metal hava kirliliğinin belirlenmesinde oldukça uygun biyoindikatörlerdir. Türkiye’nin Doğu Karadeniz bölgesinde yer alan Giresun-Samsun otoyolu çevresindeki karayosunlarının ağır metal analizleri InductivelyCoupledPlasma–MassSpectrometer (ICP-MS) cihazı kullanılarak belirlendi. Karayosunlarının kalitatif analizleri neticesinde Cr, Fe, Mn, V, Zn, Cu, Ni, Pb ve Co olduğu belirlendi. Şehir merkezlerinden toplanan karayosunlarındaki konsantrasyon değerleri sırasıyla 15.12, 6087.31, 301.12, 27.80, 74.20, 38.48, 56.69, 19.40 ve 9.10, mg/kg olarak belirlenirken, şehirler arasından toplanan karayosunlarının ağır metal konsantrasyonları ise 15.56, 4751.23, 247.93, 28.03, 83.71, 33.72, 48.38, 17.20 ve 6,97 kg/kg olarak belirlendi. Genelde karayosunlarında, Krom(Cr), Demir(Fe), Mangan(Mn), Vanadyum(V), Çinko(Zn), Bakır(Cu), Nikel(Ni), Kurşun(Pb) ve Kobalt(Co)’ınkonsantrasyonlarının 2006 ve 2017 yılları arasında azaldığı görüldü. Fakat bu azalmaya rağmen karayosunlarındaki ağır metal konsantrasyonları hala yüksektir.
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MakaleAçık Erişim2022/r/gumushane/17029
Electric Vehicle Charging Station Infrastructure on the Basis of Provinces in Turkey: Analysis through the Metrics
Cakmak, Recep; Turan, Abdullah
The fact that fossil fuels are exhaustible and harmful to the environment, the goals of constituting a sustainable and cleaner environment, and developments in battery technologies have led to a tendency towards electric vehicles instead of the vehicles which have traditional internal combustion engines working with fossil fuels. Especially in the last five years, electric vehicle (EV) sales have increased, and this increase is expected to continue increasing in the coming years. The increasing number of electric vehicles leads to the need for EV charging stations. To make strategic plans, to guide investors and to provide the appropriate infrastructure for the electric vehicle customers, the infrastructure of electric vehicle charging stations in each region needs to be analyzed in detail. In this study, the quantitative situation of the electric vehicle charging station infrastructure on the basis of provinces in Turkey as of the end of 2020 is discussed and two new metrics which use to evaluate EV charging station infrastructure are proposed. In this context, the EV charging station status is presented with tables and infographic maps through the metrics in the literature used in the evaluation of the EV charging station infrastructure and the metrics proposed in this study. 81 provinces of Turkey are compared and presented in terms of EV charging station infrastructure through the metrics. It is foreseen that the obtained and presented findings in this study will be beneficial to electric vehicle customers, electric vehicle charging station investors, the government and other public institutions that could be developed the strategy to increase the proliferation of electric vehicles. In addition, this publication might be used as a reference study to track the pace of improvements in the EV charging station infrastructure and to compare the improvements with 2020.
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MakaleAçık Erişim2022/r/gumushane/16859
High-Risky Sectors in Terms of Work Accidents in Turkey
Ceylan, Hüseyin; Kaplan, Ahmet; Bekar, Murat
Work accidents are serious issues that disrupt harmonious environment in workplace. They cause not only death, injury or disability of employees, but also serious financial loss for businesses and countries. Work accidents are highly preventable incidents, when necessary, precautions are taken. Like the whole world, in Turkey also there are risky sectors where work accidents are intensified. The identification of risky sectors in Turkey, is the first step of being able to fight against work accidents in this sector. Therefore, in this study the riskiest sectors in Turkey were investigated basing on the official accident data from the last ten years. Thus, first of all, the sectoral distribution of work accidents, death and permanent incapacity cases that occurred in Turkey in 2010-2019 was examined. Sectors were evaluated in terms of six different parameters: the number of work accidents, the number of deaths because of work accidents, the number of permanent incapacities because of work accidents, general accident incidence rate, fatal accident incidence rate, and permanent incapacity accident incidence rate. The top ten sectors with intensity have been determined for each parameter. Then, all these data were combined and the ten most risky sectors in Turkey in terms of work accidents were defined. In the last 10 years, the sector of "41-Building Construction" has been found to be the riskiest sector in Turkey, where the most work accidents have occurred, the most employees die and the most employees are permanently disabled. On the other hand, the "05- Mining of Coal and Lignite" sector, in which the general accident incidence rate, fatal accident incidence rate, and permanent incapacity accident incidence rate values are the highest, was the second most risky sector.
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MakaleYalnız künye2022/r/gumushane/16174
Simultaneous autonomous system and powerplant design for morphing quadrotors
Sahin, Huseyin; Kose, Oguz; Oktay, Tugrul
Purpose This study aims to optimize autonomous performance (i.e. both longitudinal and lateral) and endurance of the quadrotor type aerial vehicle simultaneously depending on the autopilot gain coefficients and battery weight. Design/methodology/approach Quadrotor design processes are critical to performance. Unmanned aerial vehicle durability is an important performance parameter. One of the factors affecting durability is the battery. Battery weight, energy capacity and discharge rate are important design parameters of the battery. In this study, proper autopilot gain coefficients and battery weight are obtained by using a stochastic optimization method named as simultaneous perturbation stochastic approximation (SPSA). Because there is no direct correlation between battery weight and battery energy density, artificial neural network (ANN) is benefited to obtain battery energy density corresponding to resulted battery weight found from SPSA algorithm. By using the SPSA algorithm optimum performance index is obtained, then obtained data is used for longitudinal and lateral autonomous flight simulations. Findings With SPSA, the best proportional integrator and derivative (PID) coefficients and battery weight, energy efficiency and endurance were obtained in case of morphing. Research limitations/implications It takes a long time to find the most suitable battery values depending on quadrotor endurance. However, this situation can be overcome with the proposed SPSA. Practical implications It is very useful to determine quadrotor endurance, PID coefficients and morphing rate using the optimization method. Social implications Determining quadrotor endurance, PID coefficients and morphing rate using the optimization method provides advantages in terms of time, cost and practicality. Originality/value The proposed method improves quadrotor endurance. In addition, with the SPSA optimization method and ANN, the parameters required for endurance will be obtained faster and more securely. In addition, the energy density according to the battery weight also contributes to the clean environment and energy efficiency.
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MakaleAçık Erişim2022/r/gumushane/15925
RELATIONSHIPS BETWEEN INVESTMENT INCENTIVES, PUBLIC INVESTMENT EXPENDITURES AND EXPORT: PANEL CAUSALITY ANALYSIS ON PROVINCES IN TURKEY
Recepoglu, Mursit; Doganay, Muharrem Akin; Deger, Mustafa Kemal
The state plays an essential role in the survival of companies under today's global competition conditions. Governments can, directly and indirectly, affect the competitiveness of firms through incentives and public investment expenditures. This study examines the relations between investment incentives, public investment expenditures and exports at the provincial level in Turkey. According to the panel causality analysis findings covering the period 2002-2017, there is a two-way causal relationship between investment incentives and exports. On the other hand, there is a one-way causality from exports to public investment expenditures. These results indicate the importance of the effects of incentives on exports in the short term. However, the absence of the expected export effects of public investments can be attributed to inefficiency in public investments.
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MakaleYalnız künye2022/r/gumushane/15891
Investigating the Influence of Joint Reinforcements of Portland Cement Concrete Slabs Under Asphalt Concrete Overlays on Vertical Deflections Using Accelerated Pavement Testing
Seferoglu, Mehmet Tevfik; Seferoglu, Aysegul Gunes; Çelik, Muhammet; Akpinar, Muhammet Vefa
Joint gaps between slabs in underlying Portland cement concrete (PCC) pavements are critical factors in the life span of asphalt concrete (AC) overlays. Therefore, being informed about the vertical deflections that may occur around the joints is important. In this study the joints were reinforced with three different materials: ethylene propylene diene monomer (i.e., rubber joint filler [RJF] reinforcement), bitumen-based sealant (i.e., rubber plate [RP] reinforcement), and steel plate (SP) (i.e., SP reinforcement), to limit the vertical movement of the underlying PCC. Tests were conducted at the accelerated pavement testing facility for two different AC overlay thicknesses, 50 mm and 100 mm, during 100,000 passages to investigate the influence of AC overlay thickness variations on slab vertical deflections and to also evaluate types of joint reinforcement on slab vertical deflections. For 50-mm thick AC overlay, the most effective joint reinforcements to prevent deformations caused by loading were RP, RJF, and SP; for a 100-mm thickness, this was determined to be RJF, SP, and RP, respectively.
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Kitap BölümüYalnız künye2022/r/gumushane/14942
Technology Application in Turkey’s Tourism Industry
Akdu, Uğur; Akdu, Serap
Today, many sectors continue to offer innovations in order to make people’s lives easier in the digitalized world with technological developments. Thus, more interactive, faster, and easier-to-reach services can be offered; people can reach and experience many things that were previously called inaccessible and can also save time and cost. A sector that benefits from the digital world that offers many opportunities to humanity is the tourism sector. Destinations who want to avoid competitors in an intensely competitive environment by differentiating their services, wishing to increase the pleasure that people receive from their holiday experiences worldwide, and that offer their touristic values to people with different methods strive to achieve its goals by using various digital technologies. This chapter focuses on the technology and digital innovation used in Turkey’s tourism sector. In this context, technologies used in the tourism sector are briefly explained, and examples of applications are given and scrutinized in Turkey.
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MakaleYalnız künye2022/r/gumushane/14884
GIS-based determination of potential instabilities and source rock areas on the Torul-Kürtün (Gümüşhane) motorway, rockfall, and protection structure analyses
Alemdag, Selcuk; Bostanci, Hasan Tahsin; Gacener, Elif
The Torul-Kürtün-Tirebolu motorway, one of the alternative routes for access between the Eastern Anatolia Region and the Black Sea Region, has an important traffic potential in this respect. However, rockfall events that occur frequently in almost every season especially in the part of the route between Torul and Kürtün may occasionally cause loss of life and property and lead to disruption in transportation in a much more common way. Departing from this point, the parts of the motorway that pose a greater threat in terms of slope instability and rockfall potential were selected as the study area. Instability maps produced by the kinematic analysis results showed that the probability of toppling type failure in the study area was quite higher, while the general results were as follows: the probability of toppling type failure was found in 204 different locations and approximately 97,900 m2 of area. Taking account of geographic information system (GIS)–based final instability maps, profile lines were determined for potential rockfalls in the instability-intense source rock areas. The profile lines which were determined were analyzed two-dimensionally in the RocFall 7.0 computer program. The rockfall analyses revealed that the rolling rock blocks in the section SP7 shall remain on the surface of the slope, while the rock blocks in other sections shall reach the road route. The application of barrier types determined by barrier sensitivity analysis on profile lines will minimize or completely prevent potential hazards.
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Kitap BölümüYalnız künye2022/r/gumushane/14809
Use of Innovative Technologies in the Promotion and Marketing of Asian Tourism Destinations: Sample of Turkey Destination
Ödemiş, Murat
In this chapter, it has been sought to illustrate what innovative technologies are mainly used in marketing and branding of Turkey destination, whether these tools are transformed into a competitive tool and what needs to be done in converting them to be competitive tools, which technological tools are in the forefront of the marketing of Turkey destination and whether websites and social media tools (such as Facebook, Twitter, Instagram) are effective in the promotion and marketing of Turkey destination. In addition, it has been explained whether the hospitality businesses operating in Turkey are actively using innovative technologies (websites and social media tools) and how beneficial they have been to the hospitality businesses up to now. The effectiveness of the innovative technologies used in booking, room sales, and hotel preferences has been appraised according to the available researches. Innovative technologies have been reexamined for the competitive position of Turkey destination, and suggestions have been put forward on how to use them more effectively.
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BildiriAçık Erişim2022/r/gumushane/14663
Is COVID-19 Friend or Foe to Industry 4.0: Experiences of Turkish White Goods Suppliers
Demirbag, Kubra Simsek; Yildirim, Nihan
This study, in the two years since the beginning of the COVID-19 pandemic, reveals the most focused issues by the Turkish white goods suppliers regarding Industry 4.0 and the challenges encountered while engaging in Industry 4.0 practices. The data were obtained through a questionnaire form participated by the managers of 36 different companies that are members of the Turkish White Goods Suppliers Association. The collected data were classified, and it was found that the most focused issues of the companies were technology investments, ERP and MES, data collection, business processes, investment plans, organizational transformation, occupational health and safety, and participation in Industry 4.0-related events, respectively. Moreover, the most common challenges companies face concerning Industry 4.0 are related to the not being able to come together, finance, technology providers, postponement of investment plans, and loss of employees. On the other hand, 16% of the participating companies stated that they did not encounter any difficulties.
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MakaleAçık Erişim2022/r/gumushane/14513
Optimization of tuned mass damper inerter for a high-rise building considering soil-structure interaction
Araz, Onur
The dynamic responses of the buildings and the optimum parameters of tuned mass damper inerter (TMDI) may change significantly when soil-structure interaction (SSI) is considered. Thus, it is necessary to consider the effect of the SSI in the optimization of TMDI. The study aims at proposing a methodology for optimization of TMDI parameters in reducing maximum structural responses of a high-rise building under earthquake considering the SSI effects. The equations of motion for time-domain analysis are derived for obtaining seismic-induced vibrations of a multi-story shear building with TMDI when the SSI is considered. An improved particle swarm optimization (IPSO) is used to obtain the optimum parameters. The aim of the optimization is to reduce the amplitude of the acceleration transfer function (ATF). The effectiveness of the optimally designed TMDI is assessed for twelve earthquake records with different frequency contents. The effect of the different mass ratios (µ), inertance ratios (β) and support conditions on control performance of the TMDI are investigated in detail. Numerical results proved that the SSI effect and the inertance ratio have a significant impact on the optimal design and effectiveness of the TMDI. From the seismic analysis results, it is seen that the controlled displacement response usually increases with the increase in the inertia ratio for both the fixed and flexible foundation, and a lower seismic response is obtained in the building controlled by TMD compared with the TMDI with different inertance ratios.
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MakaleAçık Erişim2022/r/gumushane/14485
Optimization insulation thickness and reduction of CO2 emissions for pipes in all generation district heating networks
Terhan, Meryem
District heating systems are provided solutions for the increasing energy problems in high-population cities. Energy costs go up depending on increasing heat loss in DHS's distribution network. Heat loss from the network consists of 5–20% of transferred energy, and this loss is higher than the other losses in the heating system. In the study, heat losses from the pipes such as supply-return pipes, hot water and circulation pipes into heat canals are investigated based on energy, exergy, economic and environmental. Optimum insulation thicknesses, energy savings, reduction of CO2 emissions, the first investment costs and payback periods of the pipes in the network of all-generation district heating systems are investigated by using Life Cycle Cost Analysis (LCCA) method for fuel types like natural gas, fuel oil and coal. Optimum insulation thicknesses are calculated for different nominal sizes of pipes and various insulation materials such as glass wool, and rock wool for the different climatic zones. According to the results of the study, the heat losses from pipes in the 4th generation DHS network are decreased between 38.19% and 33.33% from the warmest climate zone to the coldest climate zone according to the 3rd generation. Energy savings, reduction of CO2 emissions, payback periods and optimum insulation thickness values of supply and return pipes in the network are respectively changed between 7.80–98.86 $/m, 39.61–322.32 kg CO2/year, 0.028–0.38 years and 0.025–0.0105 m depending on various fuel types, insulation materials, nominal size pipes, climatic zones and all generation types.
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Derleme MakaleYalnız künye2022/r/gumushane/14438
Comprehensive review on distributed maximum power point tracking: Submodule level and module level MPPT strategies
Başoğlu, Mustafa Engin
Maximum power point tracking (MPPT) procedure in photovoltaic (PV) systems can be realized with many different methods. Especially in arrays consisting of PV modules (PVMs) connected in series; the maximum power point (MPP) may change due to partial shading conditions (PSC), aging, degradation, fabrication production differences etc. In addition, even in small power systems containing a single PVM, the difference in shading and irradiation between submodules affects the maximum power potential of the PVM. In this study, power electronics-based power processing methods in distributed MPPT (DMPPT) systems are emphasized. Power electronics-based hardware MPPT solutions are examined in two groups as full power processing (FPP) and differential power processing (DPP). In addition, commercially available power optimizers have been examined under many criteria. The literature on the subject has been analyzed in a broad perspective, and it has been comprehensively evaluated according to criteria such as power processing level, converter configuration, MPPT algorithm, MPPT application level and control approaches. This study is an important guide for scientists and hardware engineers doing academic studies on the subject. This study, which examines the topologies and control approaches used in application-oriented studies, has the feature of triggering future studies. The features that commercial power optimizers should have and the examination of the products in the market within the framework of some criteria is one of the original aspects of the study. It is expected that this study will contribute to the PV industry in building applied and building integrated studies, where extreme shading scenario occurs.
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MakaleAçık Erişim2022/r/gumushane/14415
SUPPLIER SELECTION BY INTEGRATED IFDEMATEL-IFTOPSIS METHOD: A CASE STUDY OF AUTOMOTIVE SUPPLY INDUSTRY
Gergin, Ramazan Eyüp; Peker, Iskender; Kısa, A. Cansu Gök
Selecting the best supplier emerges as a crucial subject for all sectors to achieve long term collaborations in supply chains. This study object to select the most suitable supplier for a company engage in activities in the automotive supply industry. For this purpose, a five-stage Intuitionistic Fuzzy Multi-Criteria Decision Making (IFMCDM) model is conducted. Firstly, decision criteria are defined by literature research and expert group opinions. Secondly, the importance weights of these criteria are obtained by IF Decision Making Trial and Evaluation Laboratory (IFDEMATEL). Followingly, the most suitable supplier is assessed by IF Technique for Order Preference by Similarity to Ideal Solution (IFTOPSIS). In the fourth stage, Sensitivity Analysis is utilized to analyze the effect of differentiation in criterion. Lastly, a comparative analysis is carried out. The results of the study has pointed that “Price” is the most important criterion in supplier selection and “Supplier 4” is the best alternative for this case. Main contribution of this study is to integrate IFDEMATEL-IFTOPSIS method for the first time in automotive supplier selection literature and propose a specific decision framework. In addition, proposed model is found robust and valid.
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MakaleYalnız künye2022/r/gumushane/14409
Alleviating the Impact of the Barriers to Circular Economy Adoption Through Blockchain: An Investigation Using an Integrated MCDM-based QFD With Hesitant Fuzzy Linguistic Term Sets
Erol, Ismail; Murat Ar, Ilker; Peker, Iskender; Searcy, Cory
Despite its clear potential to contribute to sustainability, there are many challenges to adopting circular economy (CE). These barriers impede the implementation of CE; however, research to address them is ongoing. For example, novel technologies have become a key enabler for easing the impact of CE adoption barriers. Blockchain is one disruptive technology that has the potential to address some of those barriers, notably technological, organizational, and ecological. Blockchain is particularly well suited to help address supply chain-oriented barriers to CE adoption. However, a review of the literature shows that while there are a limited number of conceptual studies that address the capabilities of blockchain to alleviate the impact of the barriers to CE, no previous study has focused on this vital subject using a decision tool based on expert data. To this end, this paper proposes an integrated decision framework involving Multi-Criteria Decision-Making (MCDM)-based Quality Function Deployment (QFD) method with Hesitant Fuzzy Linguistic Term Sets (HFLTS) to investigate the true potential of blockchain to address the CE adoption barriers. Our findings indicate that enhanced supply chain traceability management, improved collaboration and coordination in supply chain ecosystems, building higher levels of trust in supply chain ecosystems, and enhanced business models are the most significant functions of blockchain to help overcome the CE adoption barriers.
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MakaleAçık Erişim2022/r/gumushane/13329
Comparison of deep learning and regression-based MPPT algorithms in PV systems
Karabi̇Naoğlu, Murat Salim; Çakir, Bekir; Başoğlu, Mustafa Engin; Kazdaloğlu, Abdülvehhab; Güneroğlu, Aziz
Solar energy systems (SES) and photovoltaic (PV) modules should be operated at the maximum power point (MPP) to achieve the highest efficiency in the energy generation processes. Maximum power point tracking (MPPT) applications using conventional methods may not be able to follow the global MPP (GMPP) of the PV system under changing atmospheric conditions and they could oscillate around the local MPP. In this study, a machine learning and deep learning (DL) based long short-term memory (LSTM) model is proposed as an innovative solution for MPPT. Contrary to the traditional MPPT applications using current and voltage sensors, the output resistance of the PV module estimation was made by using environmental parameters (such as temperature and radiation) and artificial intelligence algorithms in this study.The LSTM model was compared with artificial neural networks (ANN) and regression methods regarding mean square error (MSE), root mean square error(RMSE) and mean absolute error (MAE) parameters. It has been determined that the LSTM model has a better performance and could more successfully follow MPP compared to the other methods. Finally, after the comparison with the ANN method, it is proved that LSTM gives 37%, 21%, and 31% more successful MSE, RMSE, and MAE results, respectively.
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MakaleYalnız künye2022/r/gumushane/13035
Detection of damaged buildings after an earthquake with convolutional neural networks in conjunction with image segmentation
Ünlü, Ramazan; Kiriş, Recep
Detecting damaged buildings after an earthquake as quickly as possible is important for emergency teams to reach these buildings and save the lives of many people. Today, damaged buildings after the earthquake are carried out by the survivors contacting the authorities or using some air vehicles such as helicopters. In this study, AI-based systems were tested to detect damaged or destroyed buildings by integrating into street camera systems after unexpected disasters. For this purpose, we have used VGG-16, VGG-19, and NASNet convolutional neural network models which are often used for image recognition problems in the literature to detect damaged buildings. In order to effectively implement these models, we have first segmented all the images with the K-means clustering algorithm. Thereafter, for the first phase of this study, segmented images labeled “damaged buildings” and “normal” were classified and the VGG-19 model was the most successful model with a 90% accuracy in the test set. Besides, as the second phase of the study, we have created a multiclass classification problem by labeling segmented images as “damaged buildings,” “less damaged buildings,” and “normal.” The same three architectures are used to achieve the most accurate classification results on the test set. VGG-19 and VGG-16, and NASNet have achieved considerable success in the test set with about 70%, 67%, and 62% accuracy, respectively.
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MakaleYalnız künye2022/r/gumushane/12915
Resilient active seismic response control of structural systems
Çetin, Gökhan; Fadali, Mohammed S; Pekcan, Gökhan
This paper proposes a dissipative resilient observer and controller (DROC) design for a network controlled system (NCS) that handles faults, implementation errors, or cyberattacks that can be modeled as bounded controller or observer gain perturbations. It presents linear matrix inequality (LMI) conditions for the robust stability of the system in the presence of bounded perturbations in the observer and controller. Furthermore, a new LMI-based time-delay control (TDC) algorithm that mitigates the effects of perturbations due to time-delays in the NCS is introduced. The robust methodology is applied to active control of a scaled model of a structural system equipped with an active mass driver system. The results demonstrate that the proposed methodology is robust and ensures stable system response due to various types of earthquake base excitations.
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MakaleYalnız künye2022/r/gumushane/12872
Scrutinizing blockchain applicability in sustainable supply chains through an integrated fuzzy multi-criteria decision making framework
Erol, Ismail; Ar, Ilker Murat; Peker, Iskender
Sustainability has become increasingly important over the last three decades and has proven to be a key enabler for constructing resilient supply chains. Customers who want their products to be authenticated for sustainability put pressure on Original Equipment Manufacturers and suppliers to become more sustainable on a global scale. Moreover, social sustainability issues have become more challenging to address, and a growing number of stakeholders put emphasis on societal concerns. To this end, decision-makers are becoming increasingly interested in applying disruptive technologies to address societal, environmental, and economic concerns and accomplish sustainability goals. Researchers argue that disruptive technologies such as blockchain may be implemented to assist supply chains towards building sustainability. However, our literature analysis concluded that existing research has not quantitatively examined the critical functions of sustainable supply chain (SSC) for blockchain applicability using a decision framework. Therefore, this research, through Fuzzy SWARA-COPRAS-EDAS and COPELAND-based framework, is aimed at investigating the most feasible functions of a SSC for potential blockchain implementations. Using this framework, the critical functions of a SSC were ranked against the benefits of blockchain. The findings of this study implied that while sourcing, delivery, transformation and product recovery proved to be the most appropriate functions of SSCs for blockchain applications, customers and product use was the least feasible one. This study aids decision-makers in gaining a more thorough understanding of where in a SSC blockchain may create additional value.
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MakaleAçık Erişim2022/r/gumushane/11898
Closing the Loop in Photovoltaic Solar and Wind Power Supply Chains: An investigation in Turkey through Neutrosphopic-DELPHI-based Force Field Analysis and Neutrosphopic-DEMATEL
Erol, Ismail; Peker, Iskender; Turan, İsmet; Benli, Tolga
Since solar panels and wind turbines have limited lifespans, solar photovoltaic energy supply chain (SPvESC) and wind energy supply chain (WESC) in Turkey needs a paradigm shift to improve the efficiency and recyclability of solar panel and wind turbine components. The circular economy (CE) is a viable strategy for reducing the negative effects of linear supply chains in the SPvESC and WESC. However, despite the several drivers of implementing CE in the SPvESC and WESC, there are also barriers to CE initiatives. It is argued that further studies are needed to explore the drivers and challenges for CE adoption in different industries of developing and developed countries. Hence, the goal of this research is to explore the driving and restraining forces for CE adoption in Turkey's SPvESC and WESC through a decision framework that includes Neutrosphopic DELPHI-based Force Field Analysis, Neutrosphopic-DEMATEL, and Nominal Group Technique. The findings of this research suggested that because the total score of restraining forces is higher than that of driving forces in force field analysis, it is critical to investigate the relationships among the restraining forces. Our findings also suggested that nonexistence of effective incentives and regulations proved to be the most prominent restraining force.
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