Scopus İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://gcris.khas.edu.tr/handle/20.500.12469/1248

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Citation Count: 1
A 130 nm CMOS Receiver for Visible Light Communication
(IEEE-Inst Electrical Electronics Engineers Inc, 2022) Baykaş, Tunçer; Yagan, Muhammed Yaser; Uysal, Murat; Pusane, Ali Emre; Baykas, Tuncer; Dundar, Gunhan; Yalcinkaya, Arda Deniz
Visible light communication (VLC) is an emerging technology that has been gaining attention over the last few years. Transmission of data at higher rates in a VLC system is mainly limited by the modulation bandwidth of the employed LED. To alleviate this limitation, equalization is frequently employed. This is usually achieved by either using discrete circuit elements or in digital form. In this paper, we present a power-efficient VLC receiver as a system-on-chip, implemented in 130 nm CMOS technology. The proposed receiver supports LEDs with different bandwidths thanks to the switchable equalizer. We tested the proposed receiver using phosphorescent white LEDs with different bandwidths on an experimental VLC link. For each tested LED, around 20 fold improvement in data rate was achieved compared to the original bandwidth of the LED. For the LED with a modulation bandwidth of 1.6 MHz, data rates of 32 Mbps and 50 Mbps at a BER of 10(-2) were obtained at a distance of 2 meters without and with a blue filter, respectively.
Citation Count: 0
Acceptable 'expats' versus unwanted 'Arabs': Tracing hierarchies through everyday urban practices of skilled migrant women in Istanbul
(Wiley, 2024) Tuncer, Ezgi
This article focuses on ethnic hierarchies found within highly educated migrant women working in Istanbul traced through their everyday urban practices. It introduces the stratified and comparative results of migration and resettlement of those from the Global North and the Global South through a comprehensive analysis on their urban lives, including their social positionings, preferences of neighbourhoods and daily patterns of their use of the city. Contrary to the common conception that skilled migrants are privileged, our research reveals inequalities and discriminatory practices they face that intersect with gender, nationality and ethnicity. Our research, based on qualitative analyses of in-depth interviews along with online subjective mapping representing use of the city, also reveals that regardless of their origin and identity, almost all our participants experience verbal/physical sexual harassment or discrimination in public space in Istanbul, which forces women to produce spatial tactics of everyday life.
Citation Count: 16
Accretion flows in nonmagnetic white dwarf binaries as observed in X-rays By:Balman, S (Balman, Solen)[ 1 ]
(Elsevıer Scı Ltd, 2020) Balman, Şölen
Cataclysmic Variables (CVs) are compact binaries with white dwarf (WD) primaries. CVs and other accreting WD binaries (AWBs) are useful laboratories for studying accretion flows, gas dynamics, outflows, transient outbursts, and explosive nuclear burning under different astrophysical plasma conditions. They have been studied over decades and are important for population studies of galactic X-ray sources. Recent space-and ground-based high resolution spectral and timing studies, along with recent surveys indicate that we still have observational and theoretical complexities yet to answer. I review accretion in nonmagnetic AWBs in the light of X-ray observations. I present X-ray diagnostics of accretion in dwarf novae and the disk outbursts, the nova-like systems, and the state of the research on the disk winds and outflows in the nonmagnetic CVs together with comparisons and relations to classical and recurrent nova systems, AM CVns and Symbiotic systems. I discuss how the advective hot accretion flows (ADAF-like) in the inner regions of accretion disks (merged with boundary layer zones) in nonmagnetic CVs explain most of the discrepancies and complexities that have been encountered in the X-ray observations. I stress how flickering variability studies from optical to X-rays can be probes to determine accretion history and disk structure together with how the temporal and spectral variability of CVs are related to that of LMXBs and AGNs. Finally, I discuss the nature of accretion in nonmagnetic WDs in terms of ADAF-like accretion flows, and elaborate on the solu-tions it brings and its complications, constructing an observational framework to motivate new theoretical calculations that introduce this flow-type in disks, outflow and wind models together with disk-instability models of outbursts and nova outbursts in AWBs and WD physics, in general. (C) 2020 COSPAR. Published by Elsevier Ltd. All rights reserved. Keywords
Citation Count: 31
Acculturation Attitudes and Social Adjustment in British South Asian Children: A Longitudinal Study
(Sage Publications Inc, 2013) Baysu, Gülseli; Baysu, Gülseli; Cameron, Lindsey; Nigbur, Dennis; Rutland, Adam; Watters, Charles; Hossain, Rosa; LeTouze, Dominique; Landau, Anick
A 1-year longitudinal study with three testing points was conducted with 215 British Asian children aged 5 to 11 years to test hypotheses from Berry's acculturation framework. Using age-appropriate measures of acculturation attitudes and psychosocial outcomes it was found that (a) children generally favored an integrationist attitude and this was more pronounced among older (8-10 years) than in younger (5-7 years) children and (b) temporal changes in social self-esteem and peer acceptance were associated with different acculturation attitudes held initially as shown by latent growth curve analyses. However a supplementary time-lagged regression analysis revealed that children's earlier integrationist attitudes may be associated with more emotional symptoms (based on teachers' ratings) 6 months later. The implications of these different outcomes of children's acculturation attitudes are discussed.
Citation Count: 3
Activist communication design on social media: The case of online solidarity against forced Islamic lifestyle
(Sage Publications, 2021) Arda Güney, Talat Balca; Akdemir, Ayşegül
This article explores the relationship between connective and collective group identity through the example of “You Won’t Walk Alone,” a social media platform of solidarity for women suffering from the pressures of Islamic dress code in Turkey. While Turkey has a long history of conservative women’s initiatives against secular institutional code and of secular women against Islamic and misogynist social reactions, the social media platform You Won’t Walk Alone (Yalnız Yürümeyeceksin) illustrates a striking self-reflexivity of women mobilizing against their very own conservative communities. The research is based on multimodal content analysis of the posts including both images and texts in order to grasp to what extent social media offers a genuine public space for anonymous participants of the online platform as opposed to digitally networked movements which primarily reflect personalized agency. We analyze how connective and collective group identity can be correlated in this case in which online participants build solidarity by sharing content anonymously. Hence, this article questions the ways in which activist design of communication affects and shapes activism through this case study.
Citation Count: 4
Addressing climate change with behavioral science: A global intervention tournament in 63 countries
(Amer Assoc Advancement Science, 2024) Vlasceanu, Madalina; Doell, Kimberly C.; Bak-Coleman, Joseph B.; Todorova, Boryana; Berkebile-Weinberg, Michael M.; Grayson, Samantha J.; Van Bavel, Jay J.
Effectively reducing climate change requires marked, global behavior change. However, it is unclear which strategies are most likely to motivate people to change their climate beliefs and behaviors. Here, we tested 11 expert-crowdsourced interventions on four climate mitigation outcomes: beliefs, policy support, information sharing intention, and an effortful tree-planting behavioral task. Across 59,440 participants from 63 countries, the interventions' effectiveness was small, largely limited to nonclimate skeptics, and differed across outcomes: Beliefs were strengthened mostly by decreasing psychological distance (by 2.3%), policy support by writing a letter to a future-generation member (2.6%), information sharing by negative emotion induction (12.1%), and no intervention increased the more effortful behavior-several interventions even reduced tree planting. Last, the effects of each intervention differed depending on people's initial climate beliefs. These findings suggest that the impact of behavioral climate interventions varies across audiences and target behaviors.
Citation Count: 1
Admission control for a capacitated supply system with real-time replenishment information
(Elsevier, 2023) Hekimoğlu, Mustafa; Hekimoglu, Mustafa; Dekker, Rommert
Control towers can provide real-time information on logistic processes to support decision making. The question however, is how to make use of it and how much it may save. We consider this issue for a company supplying expensive spare parts and which has limited production capacity. Besides deciding on base stock levels, it can accept or reject customers. The real-time status information is captured by a k-Erlang distributed replenishment lead time. First we model the problem with patient customers as an infinite-horizon Markov decision process and minimize the total expected discounted cost. We prove that the optimal policy can be characterized using two thresholds: a base work storage level that determines when ordering takes place and an acceptance work storage level that determines when demand of customers should be accepted. In a numerical study, we show that using real-time status information on the replenishment item and adopting admission control can lead to significant cost savings. The cost savings are highest when the optimal admission threshold is a work storage level with a replenishment item halfway in process. This finding is different from the literature, where it is stated that the cost increase of ignoring real-time information is negligible under either the lost sales or the backordering case. Next we study the problem where customers are of limited patience. We find that the optimal admission policy is not always of threshold type. This is different from the literature which assumes an exponential production lead time.
Citation Count: 13
Adoption of Mobile Health Apps in Dietetic Practice: Case Study of Diyetkolik
(Jmır Publıcatıons, Inc, 130 Queens Quay E, 2020) Aydın, Mehmet Nafiz; Aydın, Mehmet Nafiz; Akdur, Gizdem
Background: Dietetics mobile health apps provide lifestyle tracking and support on demand. Mobile health has become a new trend for health service providers through which they have been shifting their services from clinical consultations to online apps. These apps usually offer basic features at no cost and charge a premium for advanced features. Although diet apps are now more common and have a larger user base, in general, there is a gap in literature addressing why users intend to use diet apps. We used Diyetkolik, Turkey's most widely used online dietetics platform for 7 years, as a case study to understand the behavioral intentions of users. Objective: The aim of this study was to investigate the factors that influence the behavioral intentions of users to adopt and use mobile health apps. We used the Technology Acceptance Model and extended it by exploring other factors such as price-value, perceived risk, and trust factors in order to assess the technology acceptance of users. Methods: We conducted quantitative research on the Diyetkolik app users by using random sampling. Valid data samples gathered from 658 app users were analyzed statistically by applying structural equation modeling. Results: Statistical findings suggested that perceived usefulness (P<.001), perceived ease of use (P<.001), trust (P<.001), and price-value (P<.001) had significant relationships with behavioral intention to use. However, no relationship between perceived risk and behavioral intention was found (P=.99). Additionally, there was no statistical significance for age (P=.09), gender (P=.98), or previous app use experience (P=.14) on the intention to use the app. Conclusions: This research is an invaluable addition to Technology Acceptance Model literature. The results indicated that 2 external factors (trust and price-value) in addition to Technology Acceptance Model factors showed statistical relevance with behavioral intention to use and improved our understanding of user acceptance of a mobile health app. The third external factor (perceived risk) did not show any statistical relevance regarding behavioral intention to use. Most users of the Diyetkolik dietetics app were hesitant in purchasing dietitian services online. Users should be frequently reassured about the security of the platform and the authenticity of the platform's dietitians to ensure that users' interactions with the dietitians are based on trust for the platform and the brand.
Citation Count: 1
Adults' recollection of the earliest memories: early parental elaboration mediated the link between attachment and remembering
(Springer, 2022) Oener, Sezin; Guelgoez, Sami
Social interactions are a major factor in organizing the earliest experiences in the memory system. In the current study, we tested the role of parental reminiscing on the relationship between parental attachment and recollection of earliest memories. The present study focused mainly on possible mediating properties of parental elaboration between the relationship of attachment and the recall of the earliest memories. We found a full mediation pattern, showing that high parental avoidance was associated with less parental elaboration, which was then linked to the earliest memories coming from a later age and poor recollection of these memories. On the other hand, although parental anxiety was related to the earliest memories coming from a later age and rich recollection of the earliest memories, the degree of parental elaboration was not found as a mediator. Findings are discussed in line with the role of the early relational and communicative input on adults' recollections of early events.
Citation Count: 13
Alternative models for markets with nonconvexities
(Elsevier Science Bv, 2017) Fuller, J. David; Çelebi, Emre
In many electricity markets, the market operator solves a social welfare maximization (SW) model to determine market prices and generation (and consumption) "dispatch" instructions to firms participating in the market. When generation costs (or consumption benefits) are described as mixed integer programs, linear prices cannot, in general, be found such that all market participants are satisfied that the operator's dispatch instructions maximize profits, i.e., they perceive an opportunity cost. Often, "make whole" payments are made to market participants to bring negative profits up to zero, but not to adjust positive, nonoptimal profits. Make whole payments are added to "uplift" charges to customers for various non market services provided by market participants. In previous research, "uplift" is extended to include the entire opportunity costs, and prices are adjusted to minimize the part of uplift that is due to discrete variables, while keeping the SW quantity instructions. We show that the SW instructions must be modified if the non-dispatchable demand is price sensitive; to allow for this, we define a model that minimizes total opportunity cost (MTOC), and we compare it to three other models - SW, SW with non-negative profit constraints, and a minimum complementarity (MC) model recently proposed by Gabriel et al. We show that the MC model approximates the MTOC model. Two unit commitment problems illustrate the models. In an online appendix, we also present small MTOC and MC two-commodity models for which an SW model cannot be formulated due to nonintegrability of demand. (C) 2017 Elsevier B.V. All rights reserved.
Citation Count: 24
Antecedents and performance outcomes of value-based selling in sales teams: a multilevel, systems theory of motivation perspective
(Springer, 2020) Mengüç, Bülent; Mengüç, Bülent; Panagopoulos, Nikolaos G.
Firms are increasingly deploying a value-based selling (VBS) approach in their sales organizations to drive growth for new offerings. However, VBS adoption remains challenging, signaling that leaders need guidance to motivate VBS. Drawing from the systems theory of motivation, we examine motivational mechanisms at two levels-salesperson and sales team-to understand how to motivate, and benefit from, VBS. Using multisource data (i.e., salespeople, managers, archival performance) from 70 sales teams in a U.S.-based manufacturing and services provider, our findings illustrate drivers and outcomes of VBS. Specifically, we uncover a framework of salesperson, leader, customer, and team factors that help explain salesperson motivation for VBS. Importantly, we link VBS to customers' adoption of new products to support VBS's role for selling new products. Critical for sales team strategy, our model also integrates a team-level motivational mechanism to provide a comprehensive framework for salesperson and sales team motivations and outcomes.
Citation Count: 30
The applications of machine learning techniques in medical data processing based on distributed computing and the Internet of Things
(Elsevier Ireland Ltd, 2023) Aminizadeh, Sarina; Heidari, Arash; Toumaj, Shiva; Darbandi, Mehdi; Navimipour, Nima Jafari; Rezaei, Mahsa; Talebi, Samira
Medical data processing has grown into a prominent topic in the latest decades with the primary goal of maintaining patient data via new information technologies, including the Internet of Things (IoT) and sensor technologies, which generate patient indexes in hospital data networks. Innovations like distributed computing, Machine Learning (ML), blockchain, chatbots, wearables, and pattern recognition can adequately enable the collection and processing of medical data for decision-making in the healthcare era. Particularly, to assist experts in the disease diagnostic process, distributed computing is beneficial by digesting huge volumes of data swiftly and producing personalized smart suggestions. On the other side, the current globe is confronting an outbreak of COVID-19, so an early diagnosis technique is crucial to lowering the fatality rate. ML systems are beneficial in aiding radiologists in examining the incredible amount of medical images. Nevertheless, they demand a huge quantity of training data that must be unified for processing. Hence, developing Deep Learning (DL) confronts multiple issues, such as conventional data collection, quality assurance, knowledge exchange, privacy preservation, administrative laws, and ethical considerations. In this research, we intend to convey an inclusive analysis of the most recent studies in distributed computing platform applications based on five categorized platforms, including cloud computing, edge, fog, IoT, and hybrid platforms. So, we evaluated 27 articles regarding the usage of the proposed framework, deployed methods, and applications, noting the advantages, drawbacks, and the applied dataset and screening the security mechanism and the presence of the Transfer Learning (TL) method. As a result, it was proved that most recent research (about 43%) used the IoT platform as the environment for the proposed architecture, and most of the studies (about 46%) were done in 2021. In addition, the most popular utilized DL algorithm was the Convolutional Neural Network (CNN), with a percentage of 19.4%. Hence, despite how technology changes, delivering appropriate therapy for patients is the primary aim of healthcare-associated departments. Therefore, further studies are recommended to develop more functional architectures based on DL and distributed environments and better evaluate the present healthcare data analysis models.
Citation Count: 80
Applications of ML/DL in the management of smart cities and societies based on new trends in information technologies: A systematic literature review
(Elsevier, 2022) Heidari, Arash; Navimipour, Nima Jafari; Unal, Mehmet
The goal of managing smart cities and societies is to maximize the efficient use of finite resources while enhancing the quality of life. To establish a sustainable urban existence, smart cities use some new technologies such as the Internet of Things (IoT), Internet of Drones (IoD), and Internet of Vehicles (IoV). The created data by these technologies are submitted to analytics to obtain new information for increasing the smart societies and cities' efficiency and effectiveness. Also, smart traffic management, smart power, and energy management, city surveillance, smart buildings, and patient healthcare monitoring are the most common applications in smart cities. However, the Artificial intelligence (AI), Machine Learning (ML), and Deep Learning (DL) approach all hold a lot of promise for managing automated activities in smart cities. Therefore, we discuss different research issues and possible research paths in which the aforementioned techniques might help materialize the smart city notion. The goal of this research is to offer a better understanding of (1) the fundamentals of smart city and society management, (2) the most recent developments and breakthroughs in this field, (3) the benefits and drawbacks of existing methods, and (4) areas that require further investigation and consideration. IoT, cloud computing, edge computing, fog computing, IoD, IoV, and hybrid models are the seven key emerging de-velopments in information technology that, in this paper, are considered to categorize the state-of-the-art techniques. The results indicate that the Conventional Neural Network (CNN) and Long Short-Term Memory (LSTM) are the most commonly used ML method in the publications. According to research, the majority of papers are about smart cities' power and energy management. Furthermore, most papers have concentrated on improving only one parameter, where the accuracy parameter obtains the most attention. In addition, Python is the most frequently used language, which was used in 69.8% of the papers.
Citation Count: 22
Are Fan Tokens Fan Tokens?
(Academic Press Inc Elsevier Science, 2022) Ersan, Oğuz; Ersan, Oguz; Popesko, Boris
Fan tokens, digital assets providing privileges including rewards and promotions as well as voting rights in polls, recently became highly popular among the football clubs and the (fan) investors. Fan tokens differ from the stocks of football clubs with respect to ownership properties. Fan tokens might be associated with investor mood changes and reaction to match results. This paper aims to explore the impact of football match results on token prices of the clubs. We show that both the losses and wins in the most prestigious European tournament, UEFA Champions League affect the fan token abnormal returns, losses with an effect of a larger magnitude. Domestic matches and Europa League matches are not followed by similar reactions from the investors. Our results are robust to the use of alternative model specifications and various benchmark assets.
Citation Count: 0
Assessing and selecting sustainable refrigerated road vehicles in food logistics using a novel multi-criteria group decision-making model
(Elsevier Science inc, 2024) Görçün, Ömer Faruk; Tirkolaee, Erfan Babaee; Kucukonder, Hande; Gargf, Chandra Prakash
In recent years, food loss and waste (FLW) have become an essential issue at the top of the international community's agenda. Since more people are afflicted by this problem every day, the global population would be forced into poverty and starvation without finding an immediate solution. Therefore, in order to decrease FLW, well-designed and sustainable food and cold supply chains (FCSCs) are needed. Additionally, refrigerated transportation systems can be crucial in developing sustainable supply chains. According to some empirical research, the technological capabilities of reefer vehicles or trailers differ significantly. Thus, selecting the reefer vehicle is a complex decision-making problem and selecting appropriate reefer vehicles may have a critical role in constructing successful supply chain systems and reducing food waste and loss. The current research proposes an efficient, robust and practical decision-making framework that can overcome uncertainties to tackle this decision-making problem. The managerial and strategic implications of the study also aid in decreasing FLW and restructuring FSC for industrial context and support to the UN's sustainable development goals (SDGs). Later, an exhaustive sensitivity analysis was conducted to examine the developed model's validity and application, confirming the model's robustness and dependability.
Citation Count: 0
Assessing the effectiveness of OTT services, branded apps, and gamified loyalty giveaways on mobile customer churn in the telecom industry: A machine-learning approach
(Elsevier Sci Ltd, 2024) Çağlıyor, Sendi; Kiygi-Calli, Meltem; Cagliyor, Sendi; El Oraiby, Maryam
Telecom operators allocate a significant amount of resources to retain their customers as the organic growth in the number of customers is slowing down. Gamified loyalty programs, branded apps, and over-the-top (OTT) services emerged as ways to develop customer acquisition and retention strategies. Despite these strategies, some mobile customers still churn; therefore, churn prediction plays an essential role in the sustainable future of telecom businesses. Churn prediction is used both to detect customers with a high propensity to churn and to identify the reasons behind their churn behavior. This study examines several features affecting the churn behavior of mobile customers, including branded apps, gamified loyalty programs, and OTT services. In this study, the secondary data is provided by a telecom operator and contains the attributes of both churner and non-churner mobile customers. Logistic regression and random forest classifiers are compared in terms of their predictive power, and we used the latter as the machine learning algorithm in the churn prediction model. To understand the variable importance, mean decrease in impurity and permutation importance are performed. The key findings of this research reveal that while gamified loyalty giveaways and branded app strategies are effective, OTT service strategies show lower importance in predicting mobile customer churn behavior.
Citation Count: 52
Assessing the importance of international tourism for the Turkish economy: a social accounting matrix analysis
(Elsevier Science, 2012) Akkemik, K. Ali; Akkemik, K. Ali
The international tourism sector has grown rapidly in Turkey since the 1980s and Turkey ranks among the top ten countries in terms of tourist arrivals and receipts. Previous studies on international tourism in Turkey are partial equilibrium studies which emphasized the importance of the sector for foreign exchange earnings employment creation and economic growth. The social accounting matrix (SAM) modeling approach is superior to partial equilibrium analysis as it takes into account intersectoral linkages. This paper analyzes the contribution of international tourism to the Turkish economy using two SAMs for 1996 and 2002 respectively. Two analyses are conducted using the SAM impact model: (i) sectoral comparison of GDP elasticities and (ii) SAM impact analysis of international tourism on output value-added and employment. The results show that the GDP elasticity of international tourism is relatively low and the impact of foreign tourist expenditures on domestic production value-added (GDP) and employment in Turkey are modest. The results imply the possibility of leakage of foreign tourist expenditures out of the economy. (C) 2011 Elsevier Ltd. All rights reserved.
Citation Count: 11
Assessment of chromite liberation spectrum on microscopic images by means of a supervised image classification
(Elsevier Science Bv, 2017) Çavur, Mahmut; Çavur, Mahmut; Hosten, Cetin
Assessment of mineral liberation spectrum with all its aspects is essential for plant control and optimization. This paper aims to estimate 2D mineral map and its associated liberation spectrum of a particular chromite sample from optical micrographs by using Random Forest Classification a powerful machine-learning algorithm implemented on a user-friendly and an open-source software. This supervised classification method can be used to accurately generate 2D mineral map of this chromite sample. The variation of the measured spectra with the sample size is studied showing that images of 200 particles randomly selected from the optical micrographs are sufficient to reproduce liberation spectrum of this sample. In addition the 2D spectrum obtained with this classification method is compared with the one obtained from the Mineral Liberation Analyzer (MLA). Although 2D mineralogical compositions obtained by the two methods are quite similar microscopic analysis estimates poorer liberation than MLA due to the residual noise (misclassified gangue) generated by the classification. Nevertheless we cannot compare the reliabilities of the two methods as there is not a standard produce yet to quantify the accuracy of MLA analysis. (C) 2017 Elsevier B.V. All rights reserved.
Citation Count: 3
Assessment of load and generation modelling on the quasi-static analysis of distribution networks
(Elsevier, 2021) Lamprianidou, I. S.; Papadopoulos, T. A.; Kryonidis, G. C.; Yetkin, E. Fatih; Pippi, K. D.; Chrysochos, A., I
Quasi-static analysis of power systems can be performed by means of timeseries-based and probability density function-based models. In this paper, the effect of different load and generation modelling approaches on the quasi-static analysis of distribution networks is investigated. Different simplified load and distributed renewable energy sources generation timeseries-based models are considered as well as probabilistic analysis. Moreover, a more sophisticated approach based on cluster analysis is introduced to identify harmonized sets of representative load and generation patterns. To determine the optimum number of clusters, a three-step methodology is proposed. The examined cases include the quasi-static analysis of distribution networks for different operational conditions to identify the simplified modelling approaches that can efficiently predict the network voltages and losses. Finally, the computational efficiency by using the simplified models is evaluated in temperature-dependent power flow analysis of distribution networks. (C) 2021 Elsevier Ltd. All rights reserved.
Citation Count: 4
An assessment of mining efficiency in Turkish lignite industry
(Elsevier Science, 2015) Ediger, Volkan S.; Berk, Istemi; Ersoy, Mucella
This article focuses on the mining activities of Turkish Coal Enterprises (TKI) the major lignite supplier in Turkey. First we analyzed the lignite production and overburden removal activities of TKI from a historical perspective and then employed the Principle Component Analysis to build a mining efficiency index of TKI and investigated its historical development since the establishment of the company. We found that labor productivity and operational structure have been the most important factors positively affecting the index. The current article makes two important contributions: (1) by using the most comprehensive data set available on TKI for the first time and (2) by developing a Mining Efficiency Index (MEI) which can be used to analyze productivity in lignite mining activities in different countries. (C) 2015 Elsevier Ltd. All rights reserved.

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