Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395
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Article Citation - WoS: 211Citation - Scopus: 227The Roles of Technology and Kyoto Protocol in Energy Transition Towards COP26 Targets: Evidence From the Novel GMM-PVAR Approach for G-7 Countries(Elsevier Science inc, 2022-08) Dogan, Eyup; Chishti, Muhammad Zubair; Alavijeh, Nooshin Karimi; Tzeremes, Panayiotis; Karimi Alavijeh, NooshinThe investigation of the determinants of energy transition has become very attractive and popular due to the Sustainable Development Goals and COP26 targets. However, one shortcoming of the existing studies is the inability to understand the effects of technology and environmental policy to energy transition while the other criticism is the use of conventional techniques that do not handle the endogeneity issue. Thus, this study investigates the impacts of technology and Kyoto Protocol in addition to several control variables to energy transition by applying the novel econometric method of Sigmund and Ferstl (2021) on the annual data from 2000 to 2019 for G-7 countries. The empirical results confirm the positive and significant link between technology and energy transition, such that, a 1% rise in technology enhances the energy transition by 0.32%. Similarly, Kyoto Protocol has a significantly positive impact on energy transition. An explanation is that the Protocol is based on principles and policies that emphasize the advanced and industrialized economies to enhance the environmental quality by promoting the renewable energy resources and reducing the greenhouse gases. Furthermore, the G-7 authorities should start to provide subsidies to clean energy and technology-related investors and levy multiple disincentives (i.e., higher tax rates) on the industries deploying the conventional and polluting methods for energy production. Further policy implications are discussed in the study.Article Citation - WoS: 26Citation - Scopus: 33Solitary-Wave Solutions of the GRLW Equation Using Septic B-Spline Collocation Method(Elsevier Science inc, 2016-10) Karakoc, S. Battal Gazi; Zeybek, HalilIn this work, solitary-wave solutions of the generalized regularized long wave (GRLW) equation are obtained by using septic B-spline collocation method with two different linearization techniques. To demonstrate the accuracy and efficiency of the numerical scheme, three test problems are studied by calculating the error norms L-2 and L-infinity and the invariants I-1, I-2 and I-3. A linear stability analysis based on the von Neumann method of the numerical scheme is also investigated. Consequently, our findings indicate that our numerical scheme is preferable to some recent numerical schemes. (C) 2016 Elsevier Inc. All rights reserved.Article Citation - WoS: 244Citation - Scopus: 325Productive Employment and Decent Work: The Impact of AI Adoption on Psychological Contracts, Job Engagement and Employee Trust(Elsevier Science inc, 2021-07) Braganza, Ashley; Chen, Weifeng; Canhoto, Ana; Sap, SerapThis research examines the tension between the aims of the United Nations' Sustainable Development Goal 8 (SDG 8), to promote productive employment and decent work, and the adoption of Artificial Intelligence (AI). Our findings are based on the analysis of 232 survey results, where we tested the effects of AI adoption on workers' psychological contract, engagement and trust. We find that psychological contracts had a significant, positive effect on job engagement and on trust. Yet, with AI adoption, the positive effect of psychological contracts fell significantly. A further re-examination of the extant literature leads us to posit that AI adoption fosters the creation of a third type of psychological contract, which we term "Alienational". Whereas SDG 8 is premised on strengthening relational contracts between an organization and its employees, the adoption of AI has the opposite effect, detracting from the very nature of decent work.Article Citation - WoS: 9Citation - Scopus: 12Not All Emerging Markets Are the Same: A Classification Approach With Correlation Based Networks(Elsevier Science inc, 2017-12) Sensoy, Ahmet; Ozturk, Keyser; Hacihasanoglu, Erk; Tabak, Benjamin M.Using dynamic conditional correlations and network theory, this study brings a novel interdisciplinary framework to define the integration and segmentation of emerging countries. The individual EMBI+ spreads of 13 emerging countries from January 2003 to December 2013 are used to compare their interaction structure before (phase 1) and after (phase 2) the global financial crisis. Accordingly, the unweighted average of dynamic conditional correlations between cross country bond returns significantly increases in phase 2. At first glance, the increased co-movement degree suggests an integration of the sample countries after the crisis. However, using correlation based stable networks, we show that this is not enough to make such a strong conclusion. In particular, we reveal that the increased average correlation is more likely to be caused by clusters of countries that exhibit high within-cluster co-movement but not between-cluster co-movement. Potential reasons for the post-crisis segmentation and important implications for international investors and policymakers are discussed. (C) 2016 Elsevier B.V. All rights reserved.Article Citation - WoS: 40Citation - Scopus: 57How Do Firms Benefit From Customer Complaints(Elsevier Science inc, 2016-02) Yilmaz, Cengiz; Varnali, Kaan; Kasnakoglu, Berna TariThe study explores the effects of two sets of factors relating to complaint management on firm performance, namely, (1)customer response factors and (2) organizational learning factors, thereby integrating organizational learning into the conceptualization of complaint management Symmetric testing using hierarchical regression analysis of data obtained from complainants and firm managers revealed the joint effects of the two main paths on firm performance, independently from one another. Learning from complaints is shown to influence both short- and long-term firm-level performance measures positively. However, contrary to expectations, complainants' and managers' perceptions of fairness in the complaint handling processes of firms are found to (1) be nonrelated to short-term firm performances and (2) influence long-term performance expectancies negatively. Asymmetric analyses involving contrarian cases and further utilizing the fuzzy-set qualitative comparative analysis (fsQCA) disclosed distinct sets of antecedents that are sufficient for explaining short- and long-term firm performance. (C) 2015 Elsevier Inc. All rights reserved.Article Citation - WoS: 11Citation - Scopus: 12Enhanced Mass Transfer Rate and Solubility of Methane via Addition of Alcohols for Methylosinus Trichosporium OB3b Fermentation(Elsevier Science inc, 2017-02) Kim, Kwangmin; Kim, Yujin; Yang, Jeongmo; Ha, Kyoung-Su; Usta, Hakan; Lee, Jinwon; Kim, ChoongikThe effect of alcohol on methane-water volumetric mass transfer coefficient (1(0) and solubility of methane was investigated in this study. Various alcohols including methanol, ethanol, 1-propanol, butanol, and pentanol were added to aqueous solution and enhancement of both methane-water k(L)a (from 72h(-1) to 471 h(-1)) and solubility (from 21.72 mg/L to 30.41 mg/L) was observed, depending on alcohol type and concentration. Among all alcohols, 1-propanol exhibited largest enhancement via bubble coalescence inhibition effect. Enhanced methane-water kLa and methane solubility in aqueous solution were employed for the fermentation of Methylosinus trichosporium OB3b, and cell growth rate and maximum optical density were increased by 700% and 730%, respectively, by addition of 1-propanol. (C) 2016 The Korean Society of Industrial and Engineering Chemistry. Published by Elsevier B.V. All rights reserved.Article Citation - WoS: 61Citation - Scopus: 68Cross-Functional Integration in the Sustainable New Product Development Process: The Role of the Environmental Specialist(Elsevier Science inc, 2015-10) Genc, Ebru; Di Benedetto, C. AnthonyCompanies in the twenty-first century are exposed to a variety of pressures to respond to environmental issues, and responding to these pressures affects several aspects of business such as purchasing, marketing and logistics. Managers increasingly view sustainability as a complement to their corporate agendas, or even as an opportunity. It is important to understand how firms integrate environmental issues into their businesses and how these integration strategies affect performance. The process of sustainable new product development (SNPD) is a key strategic focus to achieve economic and environmental sustainability. This paper examines the integration of environmental specialists into new product development teams that are composed of other functional specialists including marketing, manufacturing, and R&D personnel, and its impact on SNPD project performance across three stages; concept development, product development, and product commercialization. We empirically test our theoretical model using a sample of 219 firms from a range of business-to-business industries. We present evidence that integrating an environmental specialist into a new product team has a positive influence on SNPD project performance beyond what the traditional members of such a team would accomplish. We analyze this relationship across the stages of SNPD to obtain a clearer picture of the effects of this integration. In particular, the integration of the environmental specialist was more effective on SNPD project performance in the final stage of the SNPD process when the product was being launched; this effect is even greater for high-innovative projects. Published by Elsevier Inc.Article Citation - WoS: 23Citation - Scopus: 32Can Artificial Intelligence and Green Finance Affect Economic Cycles?(Elsevier Science inc, 2024-12) Chishti, Muhammad Zubair; Dogan, Eyup; Binsaeed, Rima H.The COVID-19 recession and the Ukraine-Russia War (URW) crisis have added a new layer of complexity to global economic cycles, necessitating the evolution of economic systems and proactive responses to emerging economic challenges. In this context, the recent article introduces artificial intelligence (AI) as a new driver of economic cycles and analyzes its dynamic role alongside the Belt and Road Initiative (BRI), the Paris Agreement (PA), green finance (GB), and economic shocks (ES) in determining global economic cycles. The article employs novel econometric tools, namely the CAViaR-TVP-VAR model, the Quantile Coherence method, panel Quantile on Quantile Kernel-Based Regularized Least Squares (PQQKRLS), and the Quantile-Quantile Granger causality (QQGC) test for robust findings. The outcomes reveal that AI influences economic cycles in the short run while significantly mitigating these cycles in the medium and long run. Furthermore, the BRI exhibits a positive link with economic cycles during the short and medium run; however, it can contribute to economic stability in the long run by impeding economic fluctuations. Similarly, green finance and the PA show mixed influences across various time horizons, except for the long run, which confirms their negative association with economic cycles. Additionally, ES has a direct link with economic cycles across most periods. The robustness check based on the QQGC test and PQQKRLS method supports the main results. Our results identify AI, BRI, and the PA as new drivers of economic cycles with the potential to counter global economic cycles. Therefore, based on these findings, the study proposes several policy implications tailored to different time horizons.Article Citation - WoS: 10Citation - Scopus: 11An Update on Molecular Biology and Drug Resistance Mechanisms of Multiple Myeloma(Elsevier Science inc, 2015-12) Mutlu, Pelin; Kiraz, Yagmur; Gunduz, Ufuk; Baran, YusufMultiple myeloma (MM), a neoplasm of plasma cells, is the second most common hematological malignancy. Incidance rates increase after age 40. MM is most commonly seen in men and African-American population. There are several factors to this, such as obesity, environmental factors, family history, genetic factors and monoclonal gammopathies of undetermined significance (MGUS) that have been implicated as potentially etiologic. Development of MM involves a series of complex molecular events, including chromosomal abnormalities, oncogene activation and growth factor dysregulation. Chemotherapy is the most commonly used treatment strategy in MM. However, MM is a difficult disease to treat because of its marked resistance to chemotherapy. MM has been shown to be commonly multidrug resistance (MDR)-negative at diagnosis and associated with a high incidence of MDR expression at relapse. This review deals with the molecular aspects of MM, drug resistance mechanisms during treatment and also possible new applications for overcoming drug resistance. (C) 2015 Elsevier Ireland Ltd. All rights reserved.Article Citation - WoS: 4Citation - Scopus: 4A Multimodal, Multicommodity, and Multiperiod Planning Problem for Coal Distribution to Poor Families(Elsevier Science inc, 2020-12) Akgun, Ibrahim; Ozkil, Altan; Goren, SelcukTackling poverty has been one of the greatest global challenges and a prerequisite to sustainable development of countries. Countries implement nationally appropriate social protection systems and measures to address poverty. This paper addresses an aid system adopted by the government in Turkey where significant amounts of coal is distributed to poor families each year. The objective of the coal aid system is to complete the delivery of coal to poor families by the start of winter. However, an analysis of the data from previous years indicates that the distribution to many families cannot be completed on time. This results from the fact that planning is done manually and by trial-and-error as there is no system that can be used for distribution planning. This paper describes the planning problem encountered and develops a mathematical model to solve it. The proposed model is a multimodal, multicommodity, and multiperiod linear programming (LP) model. The model can be used to develop and update a distribution plan as well as to answer several what-if questions with regard to capacities, time constraints, and so forth. The model is solved using CPLEX for several problem instances obtained under different scenarios using data for the year 2012. The results show that at least 9% cost savings and about 40% decrease in distribution completion time can be achieved when the model is used. We analyze scenario results qualitatively and quantitatively and provide several insights to the decision makers. As a part of quantitative analysis, we develop regression models to predict optimal costs based on several factors. Our main contribution is to provide an efficient and effective tool to handle a large-scale real-world problem. The model has also helped to prove that the organization responsible for distribution planning may move from the current planning practice to an all-encompassing top-down approach.