Browsing by Author "Ucal, Meltem"

Now showing 1 - 7 of 7

Citation - WoS: 1
Citation - Scopus: 1
AI-Driven Predictive Maintenance for Workforce and Service Optimization in the Automotive Sector
(MDPI, 2025) Yildirim, Senda; Yucekaya, Ahmet Deniz; Hekimoglu, Mustafa; Ucal, Meltem; Aydin, Mehmet Nafiz; Kalafat, Irem
Vehicle owners often use certified service centers throughout the warranty period, which usually extends for five years after buying. Nonetheless, after this timeframe concludes, a large number of owners turn to unapproved service providers, mainly motivated by financial factors. This change signifies a significant drop in income for automakers and their certified service networks. To tackle this issue, manufacturers utilize customer relationship management (CRM) strategies to enhance customer loyalty, usually depending on segmentation methods to pinpoint potential clients. However, conventional approaches frequently do not successfully forecast which clients are most likely to need or utilize maintenance services. This research introduces a machine learning-driven framework aimed at forecasting the probability of monthly maintenance attendance for customers by utilizing an extensive historical dataset that includes information about both customers and vehicles. Additionally, this predictive approach supports workforce planning and scheduling within after-sales service centers, aligning with AI-driven labor optimization frameworks such as those explored in the AI4LABOUR project. Four algorithms in machine learning-Decision Tree, Random Forest, LightGBM (LGBM), and Extreme Gradient Boosting (XGBoost)-were assessed for their forecasting capabilities. Of these, XGBoost showed greater accuracy and reliability in recognizing high-probability customers. In this study, we propose a machine learning framework to predict vehicle maintenance visits for after-sales services, leading to significant operational improvements. Furthermore, the integration of AI-driven workforce allocation strategies, as studied within the AI4LABOUR (reshaping labor force participation with artificial intelligence) project, has contributed to more efficient service personnel deployment, reducing idle time and improving customer experience. By implementing this approach, we achieved a 20% reduction in information delivery times during service operations. Additionally, survey completion times were reduced from 5 min to 4 min per survey, resulting in total time savings of approximately 5906 h by May 2024. The enhanced service appointment scheduling, combined with timely vehicle maintenance, also contributed to reducing potential accident risks. Moreover, the transition from a rule-based maintenance prediction system to a machine learning approach improved efficiency and accuracy. As a result of this transition, individual customer service visit rates increased by 30%, while corporate customer visits rose by 37%. This study contributes to ongoing research on AI-driven workforce planning and service optimization, particularly within the scope of the AI4LABOUR project.
Citation - WoS: 2
Citation - Scopus: 1
Food to Grid: Developing a Multi-Value renewable energy investment ecosystem
(Pergamon-Elsevier Science Ltd, 2022) Xydis, George A.; Efthimiadou, Aspasia; Ucal, Meltem
The paper is focused on building a multi-source small-scale facility that shall be focused on increasing the Renewable Energy Sources share into the grid and at the same time meet the energy, and fresh food needs of the small community that shall operate. The developed facility that shall be utilised is introducing, in practice, a sustainable Energy-Food nexus plan that can be implemented and put into action by the independent power producers and municipalities, meeting also the goal of supporting the grid (a Food to Grid approach). A case study was tested, and it was found that a scheme that couples the curtailed power with a potential mass deployment of vertical farms is beyond sustainable and even with very low marginal price-earnings and the minimum price offered for vertical farms, under specific scenarios can have a full payback in 14 years as an investment. However, in the average optimal case, the investors can get their investments back in 7 years, with an internal rate of return of 17%.
Citation - WoS: 4
Citation - Scopus: 5
Housing Prices in a Market Under Years of Constant Transformation: a County-Based Analysis of Istanbul
(Cracow Univ Economics, 2020) Ucal, Meltem; Kaplan, Uğur
Objective: The objective of the article is to present a comprehensive approach to analysing Istanbul's housing prices, using a hedonic price model with a large dataset and a single variable for locational attributes. Research Design & Methods: The analysis of consequent housing prices in Istanbul's counties with hedonic price modelling and the extrapolation of results by comparing the prices to the human development level of counties. We use multiple regression and Ordinary Least Squares (OLS) methods to estimate two semi-log hedonic price models for two time periods. Findings: The relationship between socioeconomic development levels and housing prices varies for counties under different urban transformation processes. Implications & Recommendations: The results are useful for the housing price analysis in Istanbul. The housing prices appear to follow the socioeconomic development level of the county in which a house is located, thus showing variations between different counties. The relationship between housing prices and urban transformation processes should be approached with caution by policymakers, as the outcomes may disturb both the sociological and economic balance in the long run. Contribution & Value Added: The study contributes to the existing research on housing price analysis by interpreting locational attributes as a whole and housing research at large by combining hedonic price modelling and case study methods.
Citation - WoS: 6
Citation - Scopus: 6
Is Precarity a Fate for Women in Türkiye? Rethinking Energy Poverty From a Gender Perspective
(Springer Heidelberg, 2023) Ucal, Meltem; Gunay, Simge
Energy poverty is a challenging issue that hampers economic and sustainable development and lowers people's standard of living. While trying to understand energy poverty, it is imperative to focus on the disadvantaged individuals mentioned in the literature, as they are often most vulnerable to the problem. Focusing on them is essential to achieving sustainable development goals, especially in developing countries, particularly regarding poverty, energy poverty, and gender equality. Therefore, the paper aims to examine the impact of economic precarity on working-age females' energy poverty perceptions using 2018-2020 TURKSTAT-SILC pooled cross-sectional data. Our findings from the bivariate probit, multivariate probit and Bayesian bivariate probit models suggested that economic precarity has a disruptive role on females' energy poverty perceptions. Furthermore, inefficient energy use is an important factor in influencing females' perceptions of energy poverty. Females' inability to pay required housing expenses increases their perceived energy poverty. Therefore, social-welfare policies and energy policies should be considered together by the policymakers to resolve females' energy poverty problem to achieve a more sustainable future.
The Network Economics: Case Studies
(Kadir Has Üniversitesi, 2013) Demiroluk, Nazlı Tuğçe; Ucal, Meltem
This thesis basically explores the definition of networks different types of networks such as social economic information technological and the positive and negative externalities which occur as the result of the interaction of the networks with the environment. By emphasizing the positive relationship of technology social networks and network economics this paper gives current example from ecommerce sector in the world and tries to be critical to the network economics which may lead to interests for further discussions by those doing research in the same area. This paper also contains the case analyses as the examples of e commerce that is the top point of the economic networks today. The cases Ebay and Alibaba.com show the potential of the network economy and Harley Davidson case focuses on the social effects of the networks. -- Abstract'tan.
Citation - WoS: 1
Citation - Scopus: 2
The Nexus Between Migration and Environmental Degradation Based on Fundamental Climate Variables and Extreme Climate Indices for the Mena Domain
(Elsevier, 2025) An, Nazan; Demiralay, Zekican; Ucal, Meltem; Kurnaz, M. Levent
Environmental migration has recently become primary source of population growth and environmental degradation from extreme events has created the environmental refugee concept with a variety of manners affecting lives. For understanding of the environmental degradation impact on migration, a hybrid approach (regional climate modelling, RegCM4.4 and statistical modelling, ordered logit) has been applied for 65 countries in the Middle East and North Africa (MENA) for the periods of 2021-2050 and 2051-2080. It is aimed to examine how climate change affect migration by applying fundamental climate variables (i.e., maximum temperature, minimum temperature, and precipitation) and the control variables (i.e., the hot days, the tropical nights, and the dry days) in the MENA. While key findings indicate an increase in the minimum temperatures (Tmin) in future in all populous cities, the water amount may further decrease in the mid-latitude and Mediterranean with temperate climates due to precipitation change. While it may pose a high risk in the regions having experienced extreme temperatures e.g., tropical nights (Tn), it may further adversely affect ones not having experienced extremes. Considering statistically significant positive relationship between Tmin, and net migration rate (NMIG), and negative relationship between precipitation and NMIG, it may encourage migration to cooler regions.
The Relationship Between Happiness and Perceived Income Inequality as Well as Some Social Indicators: a Comparative Analysis on Turkey and Selected European Countries
(Kadir Has Üniversitesi, 2016) Günay, Simge; Ucal, Meltem
in recent years the relationship between happiness and income distribution has become an important issue in the economics literature. Underlying reason of this situation is the widening income gap between the rich and the poor since 1980s. Several studies have traced the link between happiness and income inequality especially since the last two decades. it is also very important to study “perceived” income distribution and inequality because they may show different approaches to income distribution and inequality from many individuals. The aim of this study will be to explore the relationship between perceived happiness level and perceived income inequality in Turkey and the other selected OECD countries using the World Values Survey data. The main question will be whether and to what extent perceived income inequality affects happiness level of individuals who live in those countries. in addition some social characterictics and socio-demographic variables will be used to learn whether they affect people’s happiness or not in Turkey and other selected countries more or less than their perceptions to income inequality. Generalized ordered logit model analysis will be used in the study because it fits to the nature of our data. This study is expected to contribute to the literature in the sense that it will give relevant people a point of view about the relationship between perceived happiness of people who live in selected countries and perceived income inequality as well as selected variables because a similar comprehensive and comparative study has not been found in the literature which especially addresses Turkey yet. At the end of the empirical analysis it is seen that perceptions to income inequality impact on happiness level positively however its impact is weaker than other social and demographic variables in the analysis.