[MA] Developing a Context-Sensitive Benchmarking Framework for Smart Cities

Type
  • Master Thesis Business Information Systems
Status
offered
Tutor

Abstract

Background and Motivation

Benchmarking and ranking studies are widely used to assess and compare Smart City development across municipalities. They aim to provide transparency, identify best practices, and support strategic decision-making. However, existing Smart City benchmarking approaches often rely on standardized indicator sets and uniform scoring mechanisms that insufficiently account for the heterogeneous conditions under which cities operate.

Cities differ substantially with regard to size, administrative capacities, financial resources, socio-economic structures, and geographic or institutional contexts. Ignoring these contextual factors can lead to distorted comparisons, misleading rankings, and dysfunctional incentives for municipalities. As a result, Smart City rankings are frequently criticized for lacking fairness, transparency, and analytical validity.

In response to these limitations, there is a growing need for benchmarking approaches that explicitly incorporate contextual factors and enable meaningful comparison between cities with similar structural conditions. Developing such context-sensitive benchmarking frameworks represents a central methodological challenge in Smart City research and comparative urban studies.

Research Objectives

The objective of this master thesis is to develop a context-sensitive benchmarking framework for Smart Cities that enables fair and analytically sound comparison across heterogeneous municipal contexts.

The thesis aims to:

  • Analyze and critically review existing Smart City benchmarking and ranking approaches in academic research and applied studies;

  • Identify key methodological weaknesses, with a particular focus on the treatment of contextual factors;

  • Conceptualize methods for incorporating context into benchmarking, such as comparison groups, normalization techniques, or multi-dimensional assessment models;

  • Develop a coherent benchmarking framework that balances comparability, transparency, and contextual sensitivity;

  • Discuss the implications of the proposed framework for Smart City assessment and comparative urban analysis.

Methodology

The thesis will follow a conceptually and methodologically driven research approach, potentially combining:

  • A structured literature review on benchmarking methodologies, ranking systems, and Smart City assessment frameworks;

  • Comparative analysis of existing Smart City indices and ranking models;

  • Conceptual modeling of alternative benchmarking logics (e.g., clustering, peer-group comparison, normalization);

  • Optional exploratory data analysis to illustrate or assess selected design choices, depending on data availability.

The exact methodological focus will be defined in coordination with the supervisor and aligned with the scope of a master thesis

Expected Contribution

This master thesis will contribute to the methodological advancement of Smart City benchmarking by proposing a context-sensitive assessment framework that addresses key limitations of existing approaches. The results will provide transferable insights for the design of fair, transparent, and learning-oriented benchmarking systems in Smart City research and practice.

Interested students are invited to send an e-mail to: tim.bree@uni-due.de