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A fuzzy based hybrid decision framework to circularity in dairy supply chains through big data solutions
No full textThis study determines the potential barriers to achieving circularity in dairy supply chains; it proposes a framework which covers big data driven solutions to deal with the suggested barriers. The main contribution of the study is to propose a framework by making ideal matching and ranking of big data solutions to barriers to circularity in dairy supply chains. This framework further offers a specific roadmap as a practical contribution while investigating companies with restricted resources. In this study the main barriers are classified as ‘economic’, ‘environmental’, ‘social and legal’, ‘technological’, ‘supply chain management’ and ‘strategic’ with twenty-seven sub-barriers. Various big data solutions such as machine learning, optimization, data mining, cloud computing, artificial neural network, statistical techniques and social network analysis have been suggested. Big data solutions are matched with circularity focused barriers to show which solutions succeed in overcoming barriers. A hybrid decision framework based on the fuzzy ANP and the fuzzy VIKOR is developed to find the weights of the barriers and to rank the big data driven solutions. The results indicate that among the main barriers, ‘economic’ was of the highest importance, followed by ‘technological’, ‘environmental’, ‘strategic’, ‘supply chain management’ then ‘social and legal barrier’ in dairy supply chains. In order to overcome circularity focused barriers, ‘optimization’ is determined to be the most important big data solution. The other solutions to overcoming proposed challenges are ‘data mining’, ‘machine learning’, ‘statistical techniques’ and ‘artificial neural network’ respectively. The suggested big data solutions will be useful for policy makers and managers to deal with potential barriers in implementing circularity in the context of dairy supply chains
Feminist ögelerin (femvertısıng) reklamlara yansıması: Geleneksel medya ve sosyal medya reklamları üzerine bir analiz
No full textPerformance evaluation of reverse logistics in food supply chains in a circular economy using system dynamics
No full textSupply chains are composed of multiple stakeholders who have complex interrelationships. In addition, the forward and reverse flow of materials, information, human resources, and finance occurs among different stakeholders in closing the loop of supply chBritish Council, UKBusiness; Environmental Studies; ManagementBusiness & Economics; Environmental Sciences & Ecolog
Does the Association Between Illness-Related and Religious Searches on the Internet Depend on the Level of Religiosity?
No full textRecent research suggested that illness-related search predicts religious search on Google. In the current research, I aimed to replicate this finding and investigate whether such association depends on the existing level of religiosity. In Study 1, I reanPsychology, SocialPsycholog
Advanced exergy analysis of waste‐based district heating options through case studies
Get PDFThe heating of the buildings, together with domestic hot water generation, is responsible for half of the total generated heating energy, which consumes half of the final energy demand. Meanwhile, district heating systems are a powerful option to meet this demand, with their significant potential and the experience accumulated over many years. The work described here deals with the conventional and advanced exergy performance assessments of the district heating system, using four different waste heat sources by the exhaust gas potentials of the selected plants (munici-pal solid waste cogeneration, thermal power, wastewater treatment, and cement production), with the real‐time data group based on numerical investigations. The simulated results based on conventional exergy analysis revealed that the priority should be given to heat exchanger (HE)‐I, with ex-ergy efficiency values from 0.39 to 0.58, followed by HE‐II and the pump with those from 0.48 to 0.78 and from 0.81 to 0.82, respectively. On the other hand, the simulated results based on advanced exergy analysis indicated that the exergy destruction was mostly avoidable for the pump (78.32– 78.56%) and mostly unavoidable for the heat exchangers (66.61–97.13%). Meanwhile, the exergy destruction was determined to be mainly originated from the component itself (endogenous), for the pump (97.50–99.45%) and heat exchangers (69.80–91.97%). When the real‐time implementation was considered, the functional exergy efficiency of the entire system was obtained to be linearly and inversely proportional to the pipeline length and the average ambient temperature, respec-tively
Analysis of factors impacting survivability of sustainable supply chain during COVID-19 pandemic: an empirical study in the context of SMEs
Get PDFPurpose Nowadays, many firms are finding ways to enhance the survivability of sustainable supply chains (SUSSCs). The present study aims to develop a model for the SUSSCs of small and medium enterprises (SMEs) during the COVID-19 pandemic. Design/methodology/approach With the help of exhaustive literature review, constructs and items are identified to collect the responses from different SMEs. A total of 278 complete responses are received and 6 hypotheses are developed. Hypotheses testing have been done using structural equation modeling (SEM). Findings Major constructs identified for the study are supply chain (SC) performance measurement under uncertainty (SPMU), supply chain cooperation (SCCO), supply chain positioning (SCP), supply chain administration (SCA), supply chain feasibility (SCF) and the SUSSCs. From statistical analysis of the data collected, it can be concluded that the considered latent variables contribute significantly towardsthe model fit. Research limitations/implications The present study contributes to the existing literature on disruptions and survivability. The study can be further carried out in context to different countries and sectors to generalize the findings. Practical implications The research findings will be fruitful for SMEs and other organizations in developing strategies to improve survivability during uncertain business environments. Originality/value The study has developed a model that shows that the identified latent variables and their indicators contribute significantly toward the dependent variable, i.e. survivability. It contributes significantly in bridging the research gaps existing in context to the survivability of SMEs
Iterative classifier optimizer-based pace regression and random forest hybrid models for suspended sediment load prediction
Get PDFSuspended sediment load is a substantial portion of the total sediment load in rivers and plays a vital role in determination of the
service life of the downstream dam. To this end, estimation models are needed to compute suspended sediment load in rivers. The
application of artificial intelligence (AI) techniques has become popular in water resources engineering for solving complex
problems such as sediment transport modeling. In this study, novel integrative intelligence models coupled with iterative
classifier optimizer (ICO) are proposed to compute suspended sediment load in Simga station in Seonath river basin,
Chhattisgarh State, India. The proposed models are hybridization of the random forest (RF) and pace regression (PR) models
with the iterative classifier optimizer (ICO) algorithm to develop ICO-RF and ICO-PR hybrid models. The recommended models
are established using the discharge and sediment daily data spanning a 35-year period (1980–2015). The accuracy of the
developed models is examined in terms of error; by root mean square error (RMSE) and mean absolute error (MAE); and based
on a correlation index of determination coefficient (R2
). The proposed novel hybrid models of ICO-RF and ICO-PR have been
found to be more precise than their stand-alone counterparts of RF and PR. Overall, ICO-RF models delivered better accuracy
than their alternatives. The results of this analysis tend to claim the appropriateness of the implemented methodology for precise
modeling of the suspended sediment load in rivers
Bi-objective green vehicle routing problem
No full textThe green vehicle routing problem (GVRP) is a variant of the vehicle routing problem (VRP), which increasingly attracts many researchers in recent years due to the growing global environmental issues. As the transportation of the products grows, the number of vehicles in fleets and the pollutants caused by these vehicles also grow, which in turn negatively affects human health. In this paper, a biobjective GVRP was studied. The two objectives are minimizing the total distance and minimizing the total fuel consumption of all vehicle routes. As a solution method, an adaptive large neighborhood search was hybridized with two new local search heuristics. The proposed method was applied to two well-known benchmark problem sets for VRPs and new approximate Pareto fronts were obtained for these benchmark sets. © 2021 The Authors. International Transactions in Operational Researc
Political storytelling of Ekrem İmamoğlu on Instagram during 2019 Istanbul mayoral elections in Turkey
Get PDFThis study aims to shed light on the visual aspect of digital storytelling during elections and its effects on a candidate’s overall campaign narrative. Focusing on Turkey’s 2019 mayoral elections, the study examines how Ekrem İmamoğlu from the main opposition Republican People’s Party (CHP), who was elected mayor of Istanbul used visual imagery in terms of political storytelling on Instagram.The study utilises an image type analysis and reports findings from 261 Instagram posts shared on İmamoğlu’s verified Instagram account during the last month of the initial election on 31 March 2019 (n = 167) and the rerun election on 23 June 2019 (n = 94). This approach reveals that İmamoğlu mostly adopted campaign works, contact with public, and positioning image types. Utilising these image types, he mainly pursued unifying and personal/biographical political storytelling narratives through visuals on Instagram. During the re-election period, he also pursued an incumbent strategy in addition to existing storytelling strategies. © 2021 International Visual Sociology Association
Determining Significant Factors Affecting Vaccine Demand and Factor Relationships Using Fuzzy DEMATEL Method
No full textEven though deadly effects of outbreaks such as SARS, H1N1, EBOLA and COVID-19 took the attention of the community, generating 100% vaccination uptake from people who are expected to be affected by such outbreaks is almost impossible. Hence, determining tYasar University, Bornova, İzmir, Turke