mert ceylan

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	<title>mert ceylan</title>
	<link>https://mertceylan.me</link>
	<description>mert ceylan</description>
	<pubDate>Sun, 22 Jun 2025 18:05:58 +0000</pubDate>
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		<title>Main Page</title>
				
		<link>https://mertceylan.me/Main-Page</link>

		<pubDate>Sun, 22 Jun 2025 14:26:01 +0000</pubDate>

		<dc:creator>mert ceylan</dc:creator>

		<guid isPermaLink="true">https://mertceylan.me/Main-Page</guid>

		<description>
	
&#60;img width="3909" height="3912" width_o="3909" height_o="3912" data-src="https://freight.cargo.site/t/original/i/d18e6908ad0fa0da8d82f2b7e7e091668107055358762c30f0ec3a0826c41115/mert_yeni_circle.png" data-mid="234859748" border="0"  src="https://freight.cargo.site/w/1000/i/d18e6908ad0fa0da8d82f2b7e7e091668107055358762c30f0ec3a0826c41115/mert_yeni_circle.png" /&#62;
Mert Ceylan

Work &#38;amp; ResearchCV
You can reach me at&#38;nbsp;m.ceylanmert@gmail.com

or connect via linkedin.com/in/ceylanmert.


I am a multidisciplinary analyst and project manager with a background in management and a growing specialization in data-driven business strategy. My career began in the design of physical systems; spaces, cities, environments, but along the way, I became increasingly drawn to how decisions were made behind the scenes.
After earning my bachelor's degree in architecture, I pursued an M.Sc. in Management at the Technical University of Munich. There, I developed an interest in digital services, strategic operations, and applied analytics. I’ve since contributed to product strategy and cost optimization projects at the BMW Group as well as worked on process and performance reporting, and internal consulting initiatives at Allianz Services.Along the way, I’ve also developed a strong ability to visually communicate complex ideas, whether in stakeholder presentations, dashboards, or product documentation. My background in design helps me turn abstract insights into accessible narratives that support better decision-making and alignment across teams.
I enjoy helping organizations understand where value is created and how to improve it. My current work focuses on the intersection of data, operations, and digital transformation, particularly in complex, large and layered corporate environments. I am especially interested in how organizations use data to navigate pricing, vendor performance, and service innovation.
Originally from Turkey, I am currently based in Munich, Germany
.


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	<item>
		<title>Work and Research</title>
				
		<link>https://mertceylan.me/Work-and-Research</link>

		<pubDate>Fri, 20 Jun 2025 14:32:20 +0000</pubDate>

		<dc:creator>mert ceylan</dc:creator>

		<guid isPermaLink="true">https://mertceylan.me/Work-and-Research</guid>

		<description>
	&#60;img width="3909" height="3912" width_o="3909" height_o="3912" data-src="https://freight.cargo.site/t/original/i/d18e6908ad0fa0da8d82f2b7e7e091668107055358762c30f0ec3a0826c41115/mert_yeni_circle.png" data-mid="234859634" border="0" data-scale="28" src="https://freight.cargo.site/w/1000/i/d18e6908ad0fa0da8d82f2b7e7e091668107055358762c30f0ec3a0826c41115/mert_yeni_circle.png" /&#62;Mert Ceylan

Work &#38;amp; Research
&#38;nbsp; &#38;nbsp; 
Behavioral &#38;amp; Consumer Research

Consumer Behaviour Research on Rainbow Washing (Q-Methodology)Process Tracing: Response dynamics with mouse trackingFintech in Consumer Finance

&#38;nbsp; &#38;nbsp; Business Analytics &#38;amp; Optimization

Cost optimization and supplier selection using machine learningM.Sc. Thesis
Visual Data Analytics

&#38;nbsp; &#38;nbsp; Built Environment &#38;amp; Urban Studies (Earlier&#38;nbsp;Work)&#38;nbsp; &#38;nbsp; Hobbies and Personal Interests
CV
You can reach me at&#38;nbsp;m.ceylanmert@gmail.com

or connect via linkedin.com/in/ceylanmert.


mert mərd मर्त মরদ mêr մարդ βροτός مَرْد mertä
Behavioral &#38;amp; Consumer Research &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp;&#38;nbsp; 
Understanding how people and companies think, decide, and respond in real life contexts. &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp;&#38;nbsp; 

&#60;img width="1512" height="1556" width_o="1512" height_o="1556" data-src="https://freight.cargo.site/t/original/i/7ae7fc8bd291ee024f7afa9bda6608653f2dc04e009bb8bba65ce38783803982/Screenshot-2025-03-11-at-18.53.56.png" data-mid="234858934" border="0"  src="https://freight.cargo.site/w/1000/i/7ae7fc8bd291ee024f7afa9bda6608653f2dc04e009bb8bba65ce38783803982/Screenshot-2025-03-11-at-18.53.56.png" /&#62;


Built Environment &#38;amp; Urban Studies (Earlier Work) &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; 
Selected earlier projects from my background in architecture and urban research. &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp;&#38;nbsp;


&#60;img width="7016" height="9390" width_o="7016" height_o="9390" data-src="https://freight.cargo.site/t/original/i/797c7b77e2cf319a06a1e54dc6b456dd5e3ed7fd6d878d9964883a53016bdd8f/terraphase11.jpg" data-mid="234840075" border="0" data-scale="99" src="https://freight.cargo.site/w/1000/i/797c7b77e2cf319a06a1e54dc6b456dd5e3ed7fd6d878d9964883a53016bdd8f/terraphase11.jpg" /&#62;

	
Business Analytics &#38;amp; OptimizationUsing data, models, and strategy to improve performance and decision making.

&#60;img width="1047" height="1284" width_o="1047" height_o="1284" data-src="https://freight.cargo.site/t/original/i/667027d9b1067f0de8e13f53e870acaa81bf5dbb0a2fd6d6ccf4212324e3b72e/Screenshot-2024-07-11-at-19.54.42.png" data-mid="234800505" border="0" data-scale="97" src="https://freight.cargo.site/w/1000/i/667027d9b1067f0de8e13f53e870acaa81bf5dbb0a2fd6d6ccf4212324e3b72e/Screenshot-2024-07-11-at-19.54.42.png" /&#62;Hobbies and Personal InterestsI use drawings and photography as a medium to reflect on my travels and journeys.


&#60;img width="4143" height="5781" width_o="4143" height_o="5781" data-src="https://freight.cargo.site/t/original/i/7ffa638501cca336e034f26e551c35aefc9067d69bcab76d71e787499fdeb859/scanning.jpg" data-mid="234800496" border="0" data-scale="96" src="https://freight.cargo.site/w/1000/i/7ffa638501cca336e034f26e551c35aefc9067d69bcab76d71e787499fdeb859/scanning.jpg" /&#62;


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		<title>0. name</title>
				
		<link>https://mertceylan.me/0-name</link>

		<pubDate>Sun, 22 Jun 2025 15:49:37 +0000</pubDate>

		<dc:creator>mert ceylan</dc:creator>

		<guid isPermaLink="true">https://mertceylan.me/0-name</guid>

		<description>
	&#60;img width="3909" height="3912" width_o="3909" height_o="3912" data-src="https://freight.cargo.site/t/original/i/d18e6908ad0fa0da8d82f2b7e7e091668107055358762c30f0ec3a0826c41115/mert_yeni_circle.png" data-mid="234860928" border="0" data-scale="28" src="https://freight.cargo.site/w/1000/i/d18e6908ad0fa0da8d82f2b7e7e091668107055358762c30f0ec3a0826c41115/mert_yeni_circle.png" /&#62;Mert Ceylan

Work &#38;amp; ResearchCV
You can reach me at&#38;nbsp;m.ceylanmert@gmail.com

or connect via linkedin.com/in/ceylanmert.


mert mərd मर्त মরদ mêr մարդ βροτός مَرْد mertä

mert, a Turkish given name, meaning brave, manful and trusthworthy
︎︎︎
mert is a descendant of Ottoman Turkish word mard, borrowed from Persian  مرد (mard)
︎︎︎
Proto-Indo-European language, derived from *mr̥tós (“dead, mortal) 
︎︎︎
mard cognates with मर्त ( marta, mortal man) in Sanskrit and مَرْد • in Urdu, մարդ in Old Armenian( mard, man), βροτός in Ancient Greek and mortuus in Latin. 


mertmərd মরদ مرد האיש mêr मर्तմարդ βροτόςمَرْد &#38;nbsp;mertä


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		<title>0.1 name</title>
				
		<link>https://mertceylan.me/0-1-name</link>

		<pubDate>Sun, 22 Jun 2025 18:05:58 +0000</pubDate>

		<dc:creator>mert ceylan</dc:creator>

		<guid isPermaLink="true">https://mertceylan.me/0-1-name</guid>

		<description>
	&#60;img width="3909" height="3912" width_o="3909" height_o="3912" data-src="https://freight.cargo.site/t/original/i/d18e6908ad0fa0da8d82f2b7e7e091668107055358762c30f0ec3a0826c41115/mert_yeni_circle.png" data-mid="234862995" border="0" data-scale="28" src="https://freight.cargo.site/w/1000/i/d18e6908ad0fa0da8d82f2b7e7e091668107055358762c30f0ec3a0826c41115/mert_yeni_circle.png" /&#62;Mert Ceylan

Work &#38;amp; Research
&#38;nbsp; &#38;nbsp; 
Behavioral &#38;amp; Consumer Research

Consumer Behaviour Research on Rainbow Washing (Q-Methodology)Process Tracing: Response dynamics with mouse trackingFintech in Consumer Finance

&#38;nbsp; &#38;nbsp; Business Analytics &#38;amp; Optimization

Cost optimization and supplier selection using machine learningM.Sc. Thesis
Visual Data Analytics

&#38;nbsp; &#38;nbsp; Built Environment &#38;amp; Urban Studies (Earlier&#38;nbsp;Work)&#38;nbsp; &#38;nbsp; Hobbies and Personal Interests
CV
You can reach me at&#38;nbsp;m.ceylanmert@gmail.com

or connect via linkedin.com/in/ceylanmert.


mert mərd मर्त মরদ mêr մարդ βροτός مَرْد mertä

mert, a Turkish given name, meaning brave, manful and trusthworthy
︎︎︎
mert is a descendant of Ottoman Turkish word mard, borrowed from Persian  مرد (mard)
︎︎︎
Proto-Indo-European language, derived from *mr̥tós (“dead, mortal) 
︎︎︎
mard cognates with मर्त ( marta, mortal man) in Sanskrit and مَرْد • in Urdu, մարդ in Old Armenian( mard, man), βροτός in Ancient Greek and mortuus in Latin. 


mertmərd মরদ مرد האיש mêr मर्तմարդ βροτόςمَرْد &#38;nbsp;mertä


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	<item>
		<title>1. Q Methodology</title>
				
		<link>https://mertceylan.me/1-Q-Methodology</link>

		<pubDate>Sun, 22 Jun 2025 15:17:40 +0000</pubDate>

		<dc:creator>mert ceylan</dc:creator>

		<guid isPermaLink="true">https://mertceylan.me/1-Q-Methodology</guid>

		<description>
	&#60;img width="3909" height="3912" width_o="3909" height_o="3912" data-src="https://freight.cargo.site/t/original/i/d18e6908ad0fa0da8d82f2b7e7e091668107055358762c30f0ec3a0826c41115/mert_yeni_circle.png" data-mid="234860545" border="0" data-scale="28" src="https://freight.cargo.site/w/1000/i/d18e6908ad0fa0da8d82f2b7e7e091668107055358762c30f0ec3a0826c41115/mert_yeni_circle.png" /&#62;Mert Ceylan

Work &#38;amp; Research
&#38;nbsp; &#38;nbsp; 
Behavioral &#38;amp; Consumer Research

Consumer Behaviour Research on Rainbow Washing (Q-Methodology)Process Tracing: Response dynamics with mouse trackingFintech in Consumer Finance

&#38;nbsp; &#38;nbsp; Business Analytics &#38;amp; Optimization

Cost optimization and supplier selection using machine learningM.Sc. Thesis
Visual Data Analytics

&#38;nbsp; &#38;nbsp; Built Environment &#38;amp; Urban Studies (Earlier&#38;nbsp;Work)&#38;nbsp; &#38;nbsp; Hobbies and Personal Interests
CV
You can reach me at&#38;nbsp;m.ceylanmert@gmail.com

or connect via linkedin.com/in/ceylanmert.


mert mərd मर्त মরদ mêr մարդ βροτός مَرْد mertä
Consumer Behaviour Research on Rainbow Washing (Q-Methodology) &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp;&#38;nbsp;

Academic Dr. Corianna AngelCourse ProjectWinter 2022 
Technisches Universität MünchenRainbow washing / Pinkwashing is a strategy that is often implemented by companies to seemingly promote liberalism and democracy through the products or marketing tools using LGBTQ+ symbolism and colors. Companies commonly benefit from this act of marketing, however they are often being accused of not sharing the benefit with the LGBTQ+ community. 
Through Q-Methodology, the general opinion on rainbow washing of self-identified LGBTQ+ people is tried to capture to understand til what extend they are aware of it, what the general stance leans towards and how many clusters the opinions form. 
&#60;img width="1355" height="1100" width_o="1355" height_o="1100" data-src="https://freight.cargo.site/t/original/i/66774cda910a8d699c76f17a97a158957a82d929d83d459d456afd57ac53d410/QMethodReserarch__Factor5__2024-08-16__14-36.png" data-mid="234860583" border="0"  src="https://freight.cargo.site/w/1000/i/66774cda910a8d699c76f17a97a158957a82d929d83d459d456afd57ac53d410/QMethodReserarch__Factor5__2024-08-16__14-36.png" /&#62;
&#60;img width="1460" height="926" width_o="1460" height_o="926" data-src="https://freight.cargo.site/t/original/i/bef1aaa287576c9e88391ad4433fd03648a43b123ee69eb418953e9193f9d8b2/Screenshot-2025-03-11-at-18.53.17.png" data-mid="234860582" border="0" data-scale="66" src="https://freight.cargo.site/w/1000/i/bef1aaa287576c9e88391ad4433fd03648a43b123ee69eb418953e9193f9d8b2/Screenshot-2025-03-11-at-18.53.17.png" /&#62;
&#60;img width="1512" height="1556" width_o="1512" height_o="1556" data-src="https://freight.cargo.site/t/original/i/7ae7fc8bd291ee024f7afa9bda6608653f2dc04e009bb8bba65ce38783803982/Screenshot-2025-03-11-at-18.53.56.png" data-mid="234860581" border="0"  src="https://freight.cargo.site/w/1000/i/7ae7fc8bd291ee024f7afa9bda6608653f2dc04e009bb8bba65ce38783803982/Screenshot-2025-03-11-at-18.53.56.png" /&#62;
Multi-item scale is used, where each Q-Statement is an item to be evaluated by the respondents about their perceptions or thoughts on various aspects of rainbow washing. 
Non-probability sampling and snowball technique were employed as it is an exploratory research topic to understand qualitative insights on the topic.
1. Q-Set
&#38;nbsp; &#38;nbsp; Q-Methodology allows us to systematically study the human subjectivity on the topic. Online literature review is used to gather the most common opinions. 36 statements are created from the most common opinions to represent the variety of the thoughts. 
2. Q-Sort
&#38;nbsp; &#38;nbsp; Methodology was critical that’s why each participant was interviewed while they were doing the sorting and asked questions related to their preferences. Q-Set consists of 36 statements, and participants are asked to sort them on the table. End data is anonymized. 

3. Initial by-person correlation matrix &#60;img width="1955" height="490" width_o="1955" height_o="490" data-src="https://freight.cargo.site/t/original/i/0747a78394ce5811d0ec588d78a9ee8a87edc39b9a12f3f0bd679d2d89761001/Screenshot-2024-08-16-at-15.48.23.png" data-mid="234860585" border="0"  src="https://freight.cargo.site/w/1000/i/0747a78394ce5811d0ec588d78a9ee8a87edc39b9a12f3f0bd679d2d89761001/Screenshot-2024-08-16-at-15.48.23.png" /&#62;

4. Factor Extraction, Rotation, Estimation &#38;amp; Interpretation
&#38;nbsp; &#38;nbsp; &#38;nbsp;Eigenvalues that are bigger than 1 means meaningful factors and the scree plot gives us at how many factors we use. Elbow method provides that we use 3 factors. 
From the factor analysis we come to the conclusion that the most majority of the people’s opinions are overwhelmingly similar. 
Factor analysis and their interpretations give insights on how self-identified LGBTQ+ persons think towards the topic. Qualitative topic is put into quantitative results thanks to factor analysis. 
 
&#60;img width="820" height="600" width_o="820" height_o="600" data-src="https://freight.cargo.site/t/original/i/e2353937208d08ec190c1e6467ddbd8f5c3c900d15fe48666a8418e5b86af0bf/QMethodReserarch-scree_plot_2024-08-16-15-34.png" data-mid="234860586" border="0" data-scale="71" src="https://freight.cargo.site/w/820/i/e2353937208d08ec190c1e6467ddbd8f5c3c900d15fe48666a8418e5b86af0bf/QMethodReserarch-scree_plot_2024-08-16-15-34.png" /&#62;


Factor


Perspective


1


Corporations should stay neutral in LGBTQ+ issues.


2


Rainbow washing is progress, despite its flaws.


3


Selective activism (especially against trans people) is a problem.


4


Trust in corporate LGBTQ+ support.


5


Strategic consumers who research company policies.


6


Corporate Pride efforts are better than in the past.


7


LGBTQ+ workplace policies matter when choosing jobs.


8


Companies exploit diversity for PR.


9


Companies should be held accountable for their profits from Pride.


10


Corporations should implement real inclusion policies.


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	<item>
		<title>2. Process Tracing</title>
				
		<link>https://mertceylan.me/2-Process-Tracing</link>

		<pubDate>Sun, 22 Jun 2025 15:23:13 +0000</pubDate>

		<dc:creator>mert ceylan</dc:creator>

		<guid isPermaLink="true">https://mertceylan.me/2-Process-Tracing</guid>

		<description>
	&#60;img width="3909" height="3912" width_o="3909" height_o="3912" data-src="https://freight.cargo.site/t/original/i/d18e6908ad0fa0da8d82f2b7e7e091668107055358762c30f0ec3a0826c41115/mert_yeni_circle.png" data-mid="234860666" border="0" data-scale="28" src="https://freight.cargo.site/w/1000/i/d18e6908ad0fa0da8d82f2b7e7e091668107055358762c30f0ec3a0826c41115/mert_yeni_circle.png" /&#62;Mert Ceylan

Work &#38;amp; Research
&#38;nbsp; &#38;nbsp; 
Behavioral &#38;amp; Consumer Research

Consumer Behaviour Research on Rainbow Washing (Q-Methodology)Process Tracing: Response dynamics with mouse trackingFintech in Consumer Finance

&#38;nbsp; &#38;nbsp; Business Analytics &#38;amp; Optimization

Cost optimization and supplier selection using machine learningM.Sc. Thesis
Visual Data Analytics

&#38;nbsp; &#38;nbsp; Built Environment &#38;amp; Urban Studies (Earlier&#38;nbsp;Work)&#38;nbsp; &#38;nbsp; Hobbies and Personal Interests
CV
You can reach me at&#38;nbsp;m.ceylanmert@gmail.com

or connect via linkedin.com/in/ceylanmert.


Process Tracing: Response Dynamics with Mouse-Tracking &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; 

Academic Prof Dr. Phil. Thorsten PachurSummer 2022 
Technisches Universität München
Hands-on experiences of various process-tracing techniques ranging from verbal protocols, eye tracking to neuroimaging approaches, and presentation on Response Dynamics of preferential Choice with mouse-tracking paper with Mariaa Hayden. 


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		<title>3. Fintech in Consumer Finance</title>
				
		<link>https://mertceylan.me/3-Fintech-in-Consumer-Finance</link>

		<pubDate>Sun, 22 Jun 2025 15:25:40 +0000</pubDate>

		<dc:creator>mert ceylan</dc:creator>

		<guid isPermaLink="true">https://mertceylan.me/3-Fintech-in-Consumer-Finance</guid>

		<description>
	&#60;img width="3909" height="3912" width_o="3909" height_o="3912" data-src="https://freight.cargo.site/t/original/i/d18e6908ad0fa0da8d82f2b7e7e091668107055358762c30f0ec3a0826c41115/mert_yeni_circle.png" data-mid="234860712" border="0" data-scale="28" src="https://freight.cargo.site/w/1000/i/d18e6908ad0fa0da8d82f2b7e7e091668107055358762c30f0ec3a0826c41115/mert_yeni_circle.png" /&#62;Mert Ceylan

Work &#38;amp; Research
&#38;nbsp; &#38;nbsp; 
Behavioral &#38;amp; Consumer Research

Consumer Behaviour Research on Rainbow Washing (Q-Methodology)Process Tracing: Response dynamics with mouse trackingFintech in Consumer Finance

&#38;nbsp; &#38;nbsp; Business Analytics &#38;amp; Optimization

Cost optimization and supplier selection using machine learningM.Sc. Thesis
Visual Data Analytics

&#38;nbsp; &#38;nbsp; Built Environment &#38;amp; Urban Studies (Earlier&#38;nbsp;Work)&#38;nbsp; &#38;nbsp; Hobbies and Personal Interests
CV
You can reach me at&#38;nbsp;m.ceylanmert@gmail.com

or connect via linkedin.com/in/ceylanmert.


FinTech in Consumer Finance &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp; &#38;nbsp;&#38;nbsp;

Academic Emanuel Renkl (M.Sc.)Summer 2023&#38;nbsp;
Technisches Universität München
Presentation Link 


</description>
		
	</item>
		
		
	<item>
		<title>4. Cost optimization and supplier selection using machine learning</title>
				
		<link>https://mertceylan.me/4-Cost-optimization-and-supplier-selection-using-machine-learning</link>

		<pubDate>Sun, 22 Jun 2025 16:14:34 +0000</pubDate>

		<dc:creator>mert ceylan</dc:creator>

		<guid isPermaLink="true">https://mertceylan.me/4-Cost-optimization-and-supplier-selection-using-machine-learning</guid>

		<description>
	&#60;img width="3909" height="3912" width_o="3909" height_o="3912" data-src="https://freight.cargo.site/t/original/i/d18e6908ad0fa0da8d82f2b7e7e091668107055358762c30f0ec3a0826c41115/mert_yeni_circle.png" data-mid="234861177" border="0" data-scale="28" src="https://freight.cargo.site/w/1000/i/d18e6908ad0fa0da8d82f2b7e7e091668107055358762c30f0ec3a0826c41115/mert_yeni_circle.png" /&#62;Mert Ceylan

Work &#38;amp; Research
&#38;nbsp; &#38;nbsp; 
Behavioral &#38;amp; Consumer Research

Consumer Behaviour Research on Rainbow Washing (Q-Methodology)Process Tracing: Response dynamics with mouse trackingFintech in Consumer Finance

&#38;nbsp; &#38;nbsp; Business Analytics &#38;amp; Optimization

Cost optimization and supplier selection using machine learningM.Sc. Thesis
Visual Data Analytics

&#38;nbsp; &#38;nbsp; Built Environment &#38;amp; Urban Studies (Earlier&#38;nbsp;Work)&#38;nbsp; &#38;nbsp; Hobbies and Personal Interests
CV
You can reach me at&#38;nbsp;m.ceylanmert@gmail.com

or connect via linkedin.com/in/ceylanmert.


Cost optimization and supplier selection using machine learning

Academic Yanfei Shain (M.Sc.)Spring 2024&#38;nbsp;
Technisches Universität MünchenLibraries: pandas, numpy, seaborn, matplotlib, sklearnLink to GitHub repository of the project: ︎


&#60;img width="1183" height="1114" width_o="1183" height_o="1114" data-src="https://freight.cargo.site/t/original/i/e8962d9a1310753108d2c311f23f77d248ba0c817c34887dc41ff6d5d4de46a3/Screenshot-2024-07-11-at-19.54.27.png" data-mid="234861290" border="0"  src="https://freight.cargo.site/w/1000/i/e8962d9a1310753108d2c311f23f77d248ba0c817c34887dc41ff6d5d4de46a3/Screenshot-2024-07-11-at-19.54.27.png" /&#62;
&#60;img width="1151" height="1077" width_o="1151" height_o="1077" data-src="https://freight.cargo.site/t/original/i/e66c1fffb9ed0d144f7a9871098d437f06bd87f6802bbe1334e9e5e9903d5bfa/Screenshot-2024-07-11-at-19.54.35.png" data-mid="234861288" border="0"  src="https://freight.cargo.site/w/1000/i/e66c1fffb9ed0d144f7a9871098d437f06bd87f6802bbe1334e9e5e9903d5bfa/Screenshot-2024-07-11-at-19.54.35.png" /&#62;
&#60;img width="1047" height="1284" width_o="1047" height_o="1284" data-src="https://freight.cargo.site/t/original/i/667027d9b1067f0de8e13f53e870acaa81bf5dbb0a2fd6d6ccf4212324e3b72e/Screenshot-2024-07-11-at-19.54.42.png" data-mid="234861170" border="0"  src="https://freight.cargo.site/w/1000/i/667027d9b1067f0de8e13f53e870acaa81bf5dbb0a2fd6d6ccf4212324e3b72e/Screenshot-2024-07-11-at-19.54.42.png" /&#62;
&#60;img width="2279" height="1351" width_o="2279" height_o="1351" data-src="https://freight.cargo.site/t/original/i/818e8c5424dfffb4be4de0ad0bc5f4ff4f0992bf8a208cfb5effeef9a97863cf/Figure_1.png" data-mid="234861296" border="0"  src="https://freight.cargo.site/w/1000/i/818e8c5424dfffb4be4de0ad0bc5f4ff4f0992bf8a208cfb5effeef9a97863cf/Figure_1.png" /&#62;
&#60;img width="1753" height="1214" width_o="1753" height_o="1214" data-src="https://freight.cargo.site/t/original/i/355ee0926e1a6a957e47f14640c7fcedd6dd3b98f08c6886fc80e7840cdbfc74/Figure_2.png" data-mid="234861294" border="0"  src="https://freight.cargo.site/w/1000/i/355ee0926e1a6a957e47f14640c7fcedd6dd3b98f08c6886fc80e7840cdbfc74/Figure_2.png" /&#62;


</description>
		
	</item>
		
		
	<item>
		<title>5. MSc Thesis</title>
				
		<link>https://mertceylan.me/5-MSc-Thesis</link>

		<pubDate>Sun, 22 Jun 2025 16:22:22 +0000</pubDate>

		<dc:creator>mert ceylan</dc:creator>

		<guid isPermaLink="true">https://mertceylan.me/5-MSc-Thesis</guid>

		<description>
	&#60;img width="3909" height="3912" width_o="3909" height_o="3912" data-src="https://freight.cargo.site/t/original/i/d18e6908ad0fa0da8d82f2b7e7e091668107055358762c30f0ec3a0826c41115/mert_yeni_circle.png" data-mid="234861338" border="0" data-scale="28" src="https://freight.cargo.site/w/1000/i/d18e6908ad0fa0da8d82f2b7e7e091668107055358762c30f0ec3a0826c41115/mert_yeni_circle.png" /&#62;Mert Ceylan

Work &#38;amp; Research
&#38;nbsp; &#38;nbsp; 
Behavioral &#38;amp; Consumer Research

Consumer Behaviour Research on Rainbow Washing (Q-Methodology)Process Tracing: Response dynamics with mouse trackingFintech in Consumer Finance

&#38;nbsp; &#38;nbsp; Business Analytics &#38;amp; Optimization

Cost optimization and supplier selection using machine learningM.Sc. Thesis
Visual Data Analytics

&#38;nbsp; &#38;nbsp; Built Environment &#38;amp; Urban Studies (Earlier&#38;nbsp;Work)&#38;nbsp; &#38;nbsp; Hobbies and Personal Interests
CV
You can reach me at&#38;nbsp;m.ceylanmert@gmail.com

or connect via linkedin.com/in/ceylanmert.


Master of Science Thesis: &#38;nbsp;Digging the holes of future construction sitesMarket Analysis and Business Model for Autonomous Excavators and Wheel Loaders

Academic Examiner: Prof. Dr. Eng. Johannes Fottner Supervisor: Florian Rothmeyer (M.Sc.)Master of Science ThesisSpring 2024 
Chair of Materials Handling, Material Flow and LogisticsSchool of Engineering and Design &#38;amp; School of ManagementTechnisches Universität München
Abstract
Construction and earthwork related sectors are notoriously known for being laggards when it comes to implementing new technologies. Current developments in software, computer vision technology as well as hardware, autonomous robotics and robotic planning have resulted in a successful and suitable implementation on excavation tasks in construction sites. GPS, LiDAR, camera-based multimodal perception, object detection, terrain mapping, motion planning and navigation algorithms have paved the way for the autonomous excavators to be working in the construction site which is inherently volatile and hard to control.

A literature review suggests that currently automation technology in excavation is mature enough to be used in the market. However, current business solutions are not compatible with state-of-the-art technological solutions. Rather than using traditional business models, such as direct sales or brick-and-mortar, new business models have emerged according to the need of the contemporary technology and the needs of the market players. Subscription business models, and many others have provided support for the emergence of the new businesses as well as the established ones to consolidate their position. Due to flexibility, cost efficiency, and risk reduction, usage-based business models are increasingly used in machinery industry. Increasing need of specialization of machinery, volatile global economic states drive the heavy equipment and systems to be offered as a service in construction, infrastructure and mining sectors. The business model is called Equipment as a Service in the equipment industry. Equipment-as-a-Service (EaaS) defines a system where third party companies provide equipment as a service to the parties in the industry. There is room for EaaS to be improved and used in the autonomous excavator market as a business model.

In conclusion, this thesis offers a comprehensive understanding of the current industry landscape and business models for new entrants in the autonomous excavator market, sug- gesting the benefits of Equipment-as-a-Service (EaaS) framework. The proposed business model not only addresses the changing needs of the industry players, but also provides a revenue stream that is predictable and has a sustainable growth potential, by forming strategic partnerships, compelling technological framework and strong customer relationship. The approach serves as a roadmap and guideline to effectively understand the industry and navigate the landscape of autonomous construction equipment.


</description>
		
	</item>
		
		
	<item>
		<title>6. Visual data analytics</title>
				
		<link>https://mertceylan.me/6-Visual-data-analytics</link>

		<pubDate>Sun, 22 Jun 2025 16:27:14 +0000</pubDate>

		<dc:creator>mert ceylan</dc:creator>

		<guid isPermaLink="true">https://mertceylan.me/6-Visual-data-analytics</guid>

		<description>
	&#60;img width="3909" height="3912" width_o="3909" height_o="3912" data-src="https://freight.cargo.site/t/original/i/d18e6908ad0fa0da8d82f2b7e7e091668107055358762c30f0ec3a0826c41115/mert_yeni_circle.png" data-mid="234861442" border="0" data-scale="28" src="https://freight.cargo.site/w/1000/i/d18e6908ad0fa0da8d82f2b7e7e091668107055358762c30f0ec3a0826c41115/mert_yeni_circle.png" /&#62;Mert Ceylan

Work &#38;amp; Research
&#38;nbsp; &#38;nbsp; 
Behavioral &#38;amp; Consumer Research

Consumer Behaviour Research on Rainbow Washing (Q-Methodology)Process Tracing: Response dynamics with mouse trackingFintech in Consumer Finance

&#38;nbsp; &#38;nbsp; Business Analytics &#38;amp; Optimization

Cost optimization and supplier selection using machine learningM.Sc. Thesis
Visual Data Analytics

&#38;nbsp; &#38;nbsp; Built Environment &#38;amp; Urban Studies (Earlier&#38;nbsp;Work)&#38;nbsp; &#38;nbsp; Hobbies and Personal Interests
CV
You can reach me at&#38;nbsp;m.ceylanmert@gmail.com

or connect via linkedin.com/in/ceylanmert.


Visual Data Analytics

Academic Course ReportDr. Johannes KehrerWinter 2024 Technisches Universität MünchenSoftware: Tableau, ParaView


&#60;img width="876" height="987" width_o="876" height_o="987" data-src="https://freight.cargo.site/t/original/i/e94c419025b4d43d8f9c86b44fdf5c8fb4ccd326d97fd42661c58446a48dd50b/3a.png" data-mid="234861498" border="0"  src="https://freight.cargo.site/w/876/i/e94c419025b4d43d8f9c86b44fdf5c8fb4ccd326d97fd42661c58446a48dd50b/3a.png" /&#62;
&#60;img width="872" height="986" width_o="872" height_o="986" data-src="https://freight.cargo.site/t/original/i/0a48d57a5a2bf815fcaecc3d3f9a1c7219a644c5827c3bec447f8fc440b4461b/4a.png" data-mid="234861502" border="0"  src="https://freight.cargo.site/w/872/i/0a48d57a5a2bf815fcaecc3d3f9a1c7219a644c5827c3bec447f8fc440b4461b/4a.png" /&#62;
&#60;img width="373" height="364" width_o="373" height_o="364" data-src="https://freight.cargo.site/t/original/i/4a73267196f8e8069e301d4b60323592f072db447485dd914aa1a2f500f3177e/3b.png" data-mid="234861499" border="0"  src="https://freight.cargo.site/w/373/i/4a73267196f8e8069e301d4b60323592f072db447485dd914aa1a2f500f3177e/3b.png" /&#62;

&#60;img width="2435" height="1497" width_o="2435" height_o="1497" data-src="https://freight.cargo.site/t/original/i/5260c6773c1fa2c27c24441c1389970d255f610768f9eba2ff38accf609d9978/Screenshot-2024-01-27-at-16.49.37.png" data-mid="234861505" border="0"  src="https://freight.cargo.site/w/1000/i/5260c6773c1fa2c27c24441c1389970d255f610768f9eba2ff38accf609d9978/Screenshot-2024-01-27-at-16.49.37.png" /&#62;
&#60;img width="2452" height="1515" width_o="2452" height_o="1515" data-src="https://freight.cargo.site/t/original/i/7f3bdb3d837d315f792f681584f49911a72eb8ad50e2e9437f7f3fa320304ff3/Screenshot-2024-01-27-at-16.46.28.png" data-mid="234861504" border="0"  src="https://freight.cargo.site/w/1000/i/7f3bdb3d837d315f792f681584f49911a72eb8ad50e2e9437f7f3fa320304ff3/Screenshot-2024-01-27-at-16.46.28.png" /&#62;
&#60;img width="2342" height="1217" width_o="2342" height_o="1217" data-src="https://freight.cargo.site/t/original/i/5c2bf8b37c88d30daeab34bbbe73d2fc4a3326186f2cac3f7f6732e6a8a534ff/section-3.png" data-mid="234861506" border="0"  src="https://freight.cargo.site/w/1000/i/5c2bf8b37c88d30daeab34bbbe73d2fc4a3326186f2cac3f7f6732e6a8a534ff/section-3.png" /&#62;
Analyzing the data visualization presented, sales values are quite similar across&#38;nbsp;US states, except some outliers geographically located scattered. If clusters are&#38;nbsp;created according to the total sales values, it can be clearly seen that most of&#38;nbsp;the States they are placed under Cluster 1, which is the dominant cluster among&#38;nbsp;the States.I have placed Profit as color (green) and Sales as the size of the circles. In order&#38;nbsp;to be able to get a city level data, I have placed City under the marks. Finally,&#38;nbsp;with the implementations this visualization returns the correlation between sales&#38;nbsp;and profit across different cities in all US States.


The visualization can be interpreted as such: the trend is that generally the&#38;nbsp;bigger the circle is, the darker the color gets, which means that wherever the&#38;nbsp;Sales are higher, profit values are tend to be higher too. This is a linear trend.&#38;nbsp;Another key point the visualization can be interpreted is that most of the sales&#38;nbsp;as well as profit values are centered around the metropolitan areas, such as New&#38;nbsp;York City and Los Angeles. They are represented with bigger circles, as well as&#38;nbsp;darker green color.


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