Open topics

The EU General Data Protection Regulation (GDPR) enables citizens to access data that instiutions or companies have on them. These retrieved data can then be donated to scientists to be used in research.

There is a lot that could be done with donated data, for example personalized nutritional advice based on shopping data, or health advice based on data from wearable fitness trackers – just to name a few. As a part of the project DataDonations4SustainableChange, our chair aims to explore the possibilities of using donated data to foster desirable and sustainable changes in behavior.

The aim of this thesis is to …

• … review literature on uses of donated data, ideally focused on a specific sector (like health) or a specific kind of intervention (like personalized feedback).
• … map the evidence and identify research gaps.
• … propose worthwhile avenues for future research in this domain.

Motivation
To address issues of health and sustainability, the scientific community seeks to understand food shopping behavior. To do this, many researchers rely on retrospective self-reports from consumers. This approach can suffer from biases such as respondents’ memory lapses or social desirability (“I only eat organic meat from happy animals!”).
On the other hand, a lot of supermarket chains have some form of loyalty card scheme that collects purchase data from registered consumers (example: LIDL Plus). With the EU General Data Protection Regulation (GDPR), consumers can access their data and “donate” it for the purpose of scientific research.
The aim of this thesis is to evaluate supermarket loyalty card data in terms of its potential for value creation in research.

Tasks

• Describe the process of retrieving loyalty card data from the perspective of a registered customer: Is there an easy way to request it? How long do companies take to respond? Do they comply with the 30-day limit imposed by the GDPR? This can be done in self-trial.
• Describe and evaluate the structure of loyalty card data: What kind of information is included and what is not? In what form is it available? Other aspects include the inclusion of product weights, the form (a single table vs. multiple digital receipts), limits to most recent purchases or availability of the whole purchase history, etc.
• Evaluate how easy it would be to code the data: Are the terms used self-explanatory and easy to read (“cucumber” vs. “Ccmbr”, products clearly coded as “bio“)?
• Give a final rating to each supermarket studied, considering their target groups and market shares

Motivation
Customer Relationship Management (CRM) systems are an extremely important tool for supporting, organizing and steering large sales teams. However, the implementation of CRM systems is challenging, as system adoption is often low, resulting in low usage rates, poor data quality, and thus imitation value creation. Suitable indicators for good system utilization of CRM systems could help to steer and support their adoption.

Methodology:
Literature and internet research, possibly interviews

Task

• Find indicators for the intensity and quality of CRM system usage in the academic literature and in practitioner reports
• Evaluate the quality of the indicators and identify success factors
• If possible, identify different types of system users for different industries and maturity levels.
• Focus the analysis of CRM systems on applications in sales of explanatory industrial goods

Special prerequisites

Reading, interviews, and structuring

Expected results

Students are expected to hand in substantiated report

Level: Bachelor thesis

To address issues of health and sustainability, the scientific community seeks to understand food shopping behavior. To do this, many researchers rely on retrospective self-reports from consumers. This approach can suffer from biases such as respondents’ memory lapses or social desirability (“I only eat organic meat from happy animals!”).

Thanks to digital transformation, more and more supermarket chains offer eBons, digital receipts. These offer a way to analyze actual purchase data, instead of having to rely on self-reports. By self-trial, thesis authors may “create” sample data to analyze by shopping and collecting eBons.

The aim of this thesis is to …

• … establish a solid motivation, based on literature, why purchase data is worth looking at.
• … chose one or multiple providers to analyze, e.g. Rewe, Lidl, EDEKA, based on the convenience of data retrieval, and create sample data by shopping there. 
• … build a system that allows retrieval and conversion of digital receipts (most likely in the form of multiple pdf files) into a format that can be analyzed (ideally, in table-format).
• … create a coding scheme for individual items that allows product aggregation.
• … document the process, as well as lessons learned, and challenges encountered.

Cooperation with other students is possible if the motivation or methods of their theses are aligned.

Interested students should be …

• … interested in a thesis that can pave the way for future research in this area.
• … interested in a thesis that goes beyond the usual quantitative and qualitative methods.
• … confident in their coding skills in order to succeed in text mining and data handling, for example in a programming language like Python or R.

MotivationTo address issues of health and sustainability, the scientific community seeks to understand food shopping behavior. To do this, many researchers rely on retrospective self-reports from consumers. This approach can suffer from biases such as respondents’ memory lapses or social desirability (“I only eat organic meat from happy animals!”).
On the other hand, a lot of supermarket chains have some form of loyalty card scheme that collects purchase data from registered consumers (example: LIDL Plus). With the EU General Data Protection Regulation (GDPR), consumers can access their data and “donate” it for the purpose of scientific research.
The aim of this thesis is to evaluate supermarket loyalty card data in terms of its potential for value creation in research.

Tasks

• Describe the process of retrieving loyalty card data from the perspective of a registered customer: Is there an easy way to request it? How long do companies take to respond? Do they comply with the 30-day limit imposed by the GDPR? This can be done in self-trial.
• Describe and evaluate the structure of loyalty card data: What kind of information is included and what is not? In what form is it available? Other aspects include the inclusion of product weights, the form (a single table vs. multiple digital receipts), limits to most recent purchases or availability of the whole purchase history, etc.
• Evaluate how well the data can be analyzed: Is the data self-explanatory and easy to read (“cucumber” vs. “Ccmbr”, products clearly coded as “bio“)?
• Structure and code loyalty card data into interesting categories: food groups (e.g. fruits and vegetables), certifications (bio, fair-trade, etc.), …
• Give a final rating to each supermarket studied, considering their target groups and market shares.

Programming skills required for coding loyalty card data (for example Python, R, …).

Motivation

Non-residential buildings are responsible for 43% of building-related energy expenditure in Germany, with the majority being used for heating. Many of these buildings are operated as a 24/7 “steady-state” with little or no management. Therefore, there is significant untapped savings potential!

Digital technologies like smart thermostats/meters or window sensors allow building managers to identify and leverage opportunities to save energy. The task of this thesis is to gain an understanding of currently used practices and technologies in the thermal energy management of non-residential buildings.

Tasks

• Internet and literature research on practices and technologies in thermal management (e.g. manual or intelligent regulation depending on time of day or based on occupancy)
• Interviews with people responsible for heating and/or building management, possibly from small-to-medium companies (SMC)
  • Capture currently used practices and their experiences with it
  • Get opinions on currently unused practices
• Qualitative analysis with a focus on
  • Incidence of heating management practices (or lack thereof)
  • Facilitating factors to implement energy conservation measures
  • Challenges/hurdles for implementation
• Note: Interview contents and analysis may evolve over time depending on learnings
• Reflection on gathered information and what kind of solutions could be feasible in the future of non-residential building management

Prerequisites

• Interest in interviews as a qualitative method to gain an deep and interconnected understanding of the topic.
• As we are interested in how companies in Germany operate, German speaking skills are required.
• Successful completion of the course “Digital Transformation in Energy and Mobility” is not a must, but a helpful introduction into the topic.

Note: More topics on thermal building management will be coming soon along with progress in the project “Thermal comfort as a service (TCaaS)”.