Showing papers by "Yaşar University published in 2021"

Circular economy and the policy: A framework for improving the corporate environmental management in supply chains

Abstract: The transition to the circular economy (CE) creates value through the closed‐loop systems, reverse logistics, product life cycle management, and clean production in terms of corporate environmental management. During this transition process, the organization faces many barriers such as financial, organizational, technology‐based, social, policy‐related, market‐based, and logistics‐based barriers. The objectives of this study are to propose a framework highlighting policy‐related barriers for a supply chain in the transition to CE and finally discuss potential implications on enhancing corporate environmental performance of a business. Further, this study evaluates the causal relationships between the policy‐related barriers using fuzzy Decision‐Making Trial and Evaluation Laboratory (DEMATEL) method. The application was conducted in an apparel firm in Turkey. From findings, lack of legislation for efficient CE (C4), lack of mandatory requirements and responsibilities for manufacturers/suppliers for the CE (C17), and lack of government support for environmentally friendly policies (C2) are revealed as the most important barriers, respectively. It is found that lack of attitude and awareness about CE in government institutions (C19) is the most influencing factor, whereas lack of effective recycling policies to achieve quality in waste management (C8) is the most influenced factor. The recommendations were developed for enhancing the corporate environmental performance of businesses through incentives and unique rewards, improving communication among stakeholders, the government's perception of CE and current linear economy, cooperation with nongovernmental organization (NGOs) and civil actions, the vision of government towards circular principles, the circular public procurement, the local governments in circular policymaking, and awareness of bureaucracy and government officials.

To which world regions does the valence–dominance model of social perception apply?

Abstract: Over the past 10 years, Oosterhof and Todorov’s valence–dominance model has emerged as the most prominent account of how people evaluate faces on social dimensions. In this model, two dimensions (valence and dominance) underpin social judgements of faces. Because this model has primarily been developed and tested in Western regions, it is unclear whether these findings apply to other regions. We addressed this question by replicating Oosterhof and Todorov’s methodology across 11 world regions, 41 countries and 11,570 participants. When we used Oosterhof and Todorov’s original analysis strategy, the valence–dominance model generalized across regions. When we used an alternative methodology to allow for correlated dimensions, we observed much less generalization. Collectively, these results suggest that, while the valence–dominance model generalizes very well across regions when dimensions are forced to be orthogonal, regional differences are revealed when we use different extraction methods and correlate and rotate the dimension reduction solution.

Implementation of hybrid particle swarm optimization-differential evolution algorithms coupled with multi-layer perceptron for suspended sediment load estimation

Abstract: River suspended sediment load (SSL) estimation is of importance in water resources engineering and hydrological modeling. In this study, a novel hybrid approach is recommended for SSL estimation in which multi-layer perceptron (MLP) is hybridized with particle swarm optimization (PSO) and then, integrated with differential evolution algorithm (DE) called as MLP-PSODE. The hybrid MLP-PSODE model is implemented to model the SSL of Mahabad river located at northwest of Iran. For the sake of examination of the MLP-PSODE model performance, several techniques including multi-layer perceptron (MLP), multi-layer perceptron integrated with particle swarm optimization (MLP-PSO), radial basis function (RBF) and support vector machine (SVM) are selected as benchmarks. For this purpose, five different scenarios are considered for the modeling. The results indicated that the new hybrid model of MLP-PSODE is successful in estimating SSL by considering single input of discharge (Q) with high accuracy as compared to its alternatives with RMSE = 1794.4 ton·day−1, MAPE = 41.50% and RRMSE = 107.09%, which were much lower than those of MLP based model with RMSE = 3133.7 ton·day−1, MAPE = 121.40% and RRMSE = 187.03%. The developed MLP-PSODE model, not only outperforms its counterparts in terms of accuracy in extreme values estimation, but also it is found as a parsimonious model that incorporates lower number of input parameters in its structure for SSL estimation.

Analysis of CO 2 emissions and energy consumption by sources in MENA countries: evidence from quantile regressions.

Abstract: The development of economies and energy usage can significantly impact the carbon dioxide (CO2) emissions in the Middle East and North Africa (MENA) countries. Therefore, this study aims to analyze the factors that determine CO2 emissions in MENA under the environmental Kuznets curve (EKC) framework by applying novel quantile techniques on data for CO2 emissions, real income, renewable and non-renewable energy consumption, and urbanization over the period from 1990 to 2015. The results from the estimations suggest that renewable energy consumption significantly reduces the level of emissions; furthermore, its impact increases with higher quantiles. In addition, non-renewable energy consumption increases CO2 emissions, while its magnitude decreases with higher quantiles. The empirical results also confirm the validity of EKC hypothesis for the panel of MENA economies. Policymakers in the region should implement policies and regulations to promote the adoption and use of renewable energy to mitigate carbon emissions.

Psychopathological Consequences Related to Problematic Instagram Use Among Adolescents: The Mediating Role of Body Image Dissatisfaction and Moderating Role of Gender

Abstract: In a minority of cases, problematic use of technology can negatively impact on adolescents and impair some aspects of their social, emotional, and psychological development. The purpose of the present study was to examine the direct and indirect effects of problematic Instagram use (PIU) on different psychopathological outcomes including loneliness, depression, anxiety, and social anxiety via body image dissatisfaction (BID). Additionally, moderating role of gender on the relationships among variables was investigated. A total of 491 adolescents (Mage = 15.92 years, SDage = 1.07; range = 14 to 19 years) were recruited for the study to complete a questionnaire that included the relevant assessment tools for the aforementioned variables. Mediation and moderation analyses showed that among male adolescents, PIU was directly associated with loneliness, depression, general anxiety, and social anxiety and BID partially mediated these associations. Among females, PIU was directly associated with depression and indirectly with general anxiety and social anxiety via BID. Gender significantly moderated the direct relationships of PIU with loneliness, general anxiety, and social anxiety. PIU was directly associated with loneliness, general anxiety, and social anxiety among males only, whereas among females, PIU was indirectly associated with general and social anxiety via BID but was not related to loneliness. Results of this study indicate that PIU has different negative psychological effects on male and female adolescents and that BID appears to be one explanatory factor for these impairments especially among females.

Using system dynamics to analyze the societal impacts of blockchain technology in milk supply chainsrefer

Abstract: The integration of blockchain technologies in the food sector has significant social impacts. The objectives of this research are firstly, to map the milk supply chains to explore information flow among different members for higher traceability; secondly, to investigate the societal impacts of blockchain technology in a milk supply chain to build social sustainability. The systems theory in integration with system dynamics (SD) provides the necessary theoretical underpinning to this research. We collect data from an agricultural development cooperative founded to support dairy farmers in Turkey. This work evaluates the societal impacts of blockchain technology on farmers, the community and animals using parameters such as local embedding, rural development, decreasing food fraud, animal health and welfare, proximity to food markets, food security, educating and promoting people towards healthy eating, assisting food access and social acceptability for transparency. In the last 18 years, the cooperative has encouraged dairy farmers in the district to become partners with a resultant increase in milk production from 30 thousand tons in 2002 to 330 thousand tons in 2019. According to our findings, population growth of the country and adult population increases in the district, it is expected that by 2025 the number of partners will rise to approximately 2800. The increase in number of partners proves the network expansion. Furthermore, blockchain technology can be incorporated into the existing system so that transparent and end-to-end accurate tracking of the supply chain is made possible, while creating decentralized recording of transactions. Moreover, the critical traceability points of a milk supply chain are evaluated with the blockchain adoption. This will help achieve the sustainable development goals (SDGs) of providing safe food, promoting good health and better well-being for everyone.

A multi-objective optimisation study for the design of an AVS/RS warehouse

Abstract: This paper deals with a hierarchical solution approach for multi-objective optimisation of an autonomous vehicle-based storage and retrieval system (AVS/RS) warehouse design. As a result of recent ...

Iterative classifier optimizer-based pace regression and random forest hybrid models for suspended sediment load prediction.

Abstract: Suspended 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.

Problematic Mukbang Watching and Its Relationship to Disordered Eating and Internet Addiction: A Pilot Study Among Emerging Adult Mukbang Watchers

Abstract: Internet technology has facilitated the use of a wide variety of different activities and applications in online contexts. One such activity is watching mukbang (i.e., watching videos of “eating broadcasts” where someone eats a large amount of food while interacting with viewers). In the present study, the relationship of problematic mukbang watching with disordered eating and internet addiction was examined. Participants were 140 emerging adults who watched mukbang at least once in the past 30 days (66% female; Mage = 21.66, SD = 1.88, range = 19–29 years). Structural equation modeling indicated that problematic mukbang watching was positively associated with both disordered eating and internet addiction. The present study is the first to explore the predictive role of problematic mukbang watching on adverse consequences, and suggests that mukbang watching may be problematic for a minority of emerging adults and that problematic mukbang watching warrants further examination of its impact on mental health and wellbeing.

International differences in employee silence motives: Scale validation, prevalence, and relationships with culture characteristics across 33 Countries

Abstract: Employee silence, the withholding of work-related ideas, questions, or concerns from someone who could effect change, has been proposed to hamper individual and collective learning as well as the detection of errors and unethical behaviors in many areas of the world. To facilitate cross-cultural research, we validated an instrument measuring four employee silence motives (i.e., silence based on fear, resignation, prosocial, and selfish motives) in 21 languages. Across 33 countries (N = 8,222) representing diverse cultural clusters, the instrument shows good psychometric properties (i.e., internal reliabilities, factor structure, and measurement invariance). Results further revealed similarities and differences in the prevalence of silence motives between countries, but did not necessarily support cultural stereotypes. To explore the role of culture for silence, we examined relationships of silence motives with the societal practices cultural dimensions from the GLOBE Program. We found relationships between silence motives and power distance, institutional collectivism, and uncertainty avoidance. Overall, the findings suggest that relationships between silence and cultural dimensions are more complex than commonly assumed. We discuss the explanatory power of nations as (cultural) units of analysis, our social scientific approach, the predictive value of cultural dimensions, and opportunities to extend silence research geographically, methodologically, and conceptually.

Building supply chain resilience in the era of COVID-19: An AHP-DEMATEL approach

Abstract: COVID-19 pandemic is the worst humanitarian crisis that economies across the globe have witnessed. Forced lockdowns, social distancing, and restricted mobility have contributed to large scale disruptions in the supply chain network. The purpose of the paper is to identify critical factors affecting global supply chain and evaluate strategies for risk reduction in the supply chain network by making it resilient. Our study incorporates multi-criteria decision approach using Analytic Hierarchy Process (AHP) and Decision-Making Trial and Evaluation Laboratory (DEMATEL) to analyze factors that affected the supply chain networks with the onset of COVID-19. The AHP method enabled to hierarchically rank the factors based on the relative weightage while DEMATEL ascertained the inter-relationships among the factors and classified them into cause and effect groups. The findings of our study identified the cost–optimization as the most significant factor and the human resource management as the least important factor in reducing vulnerabilities of the supply chain network. Our analysis from DEMATEL approach indicate that government support is a significant causal factor which can effectively eliminate the issues plaguing supply chains during this pandemic. The results from our study aim to help policymakers in developing a risk resilient framework that can enhance performance and operational capability of the supply chain, thereby ensuring sustainability and socio-economic well-being of all the stakeholders involved in the entire network.

Public attitudes towards climate change: A cross-country analysis:

Abstract: Addressing climate change requires international effort from both governments and the public. Climate change concern is a crucial variable influencing public support for measures to address climate...

An Adaptive Iterated Greedy algorithm for distributed mixed no-idle permutation flowshop scheduling problems

Abstract: Distributed flow shop scheduling is a very interesting research topic. This paper studies the distributed permutation flow shop scheduling problem with mixed no-idle constraints, which have important applications in practice. The optimization goal is to minimize total flowtime. A mixed-integer linear programming model is presented and an Adaptive Iterated Greedy (AIG) algorithm with the sample length changing according to the search process is designed. A restart strategy is also introduced to escape from local optima. Additionally, to further improve the performance of the algorithm, swap-based local search methods and acceleration algorithms for swap neighborhoods are proposed. Referenced Local Search (RLS), which shows better performance in solving scheduling problems, is also used in our algorithm. In the destruction stage, the job to be removed is selected according to the degree of influence on the total flowtime. In the initialization and construction phase, when a job is inserted, the jobs before and after the insertion position are removed and re-inserted into a better position to improve the algorithm search performance. A detailed design experiment is carried out to determine the best parameter configuration. Finally, large-scale experiments show that the proposed AIG algorithm is the best-performing one among all the algorithms in comparison.

Framework for a sustainable supply chain to overcome risks in transition to a circular economy through Industry 4.0

Abstract: Transition from a linear to a circular economy (CE) is a challenging process for a sustainable supply chain, and innovative process approaches and technologies are needed to deal with the risks inv...

Assessing dairy supply chain vulnerability during the Covid-19 pandemic

Abstract: Frequent occurrence of disruptions in the supply chain due to the Covid-19 pandemic has increased the supply chain vulnerability (SCU), which affects the performance and revenue generation of firms...