Month: June 2025

Subject: Data Localization Laws

Title: Navigating data localization: A Case Study of Signify’s Compliance with China’s PIPL and Transferable Lessons for India’s DPDP

Abstract: 

This thesis investigates how Signify, a multinational lighting corporation, operationalized compliance with China’s strict data localization laws under the Personal Information Protection Law (PIPL) and thereby identifies lessons for India’s emerging Digital Personal Protection (DPDP) Act. Through the use of a qualitative, abductive single case study with semi-structured interviews across Legal, IT and GRC (Governance, Risk and Compliance) departments, the study explores how Signify navigated through these complex regulatory landscapes.
Findings reveiled that while technical compliance was largely achieved due to earlier adaptations to the Chinese Great Firewall, the legal team led the compliance process by employing an external counsel and set standard contract to manage cross-border data transfers.
These processes have not been executed without any complexities. Key challenges emerged around regulatory ambiguity, risk-based decision making, and cross-functional communication gaps. The legal and IT department often struggled with their differences in business language, leading to different interpretations of the compliance requirements, often needing mediation from GRC or another external stakeholder.
This thesis proposes the adaptation of the McKinsey 7S model at a project level to adress these challenges. The McKinsey 7S model is expected to improve strategic alignment and foster a shared language accross departments. This approach thereby aims to transform compliance efforts from reactive siloed responses, into more proactive, structured initiatives which will align operational feasibility with legal obligations.
The findings emphasize that successful data localization compliance is not attributed to legal and technical requirements alone. Strong organizational coordination and clear communication structures are needed as well. By examining Signify’s experience, this study offers a blueprint for multinational companies facing similar regulatory challenges. Giving insights in how structured frameworks and risk-based compliance, through the use of the 7S model, navigate the evolving landscape of data localization laws effectively.

Key words: Data, Data Localization, Data Transfers, Cross-border, China, Framework, McKinsey 7S, model, qualitative study, abductive, case study, semi-structured interviews, Signify, Multinational company

Subject: Information System Science

Title: Business Intelligence Adoption in Heritage Luxury Organizations: A TOE Framework Extension

Abstract: 

This thesis examines the adoption and appropriation of Business Intelligence (BI) tools within heritage luxury. While BI technologies are increasingly adopted across various industries, their deployment in luxury environments remains under-researched, particularly in situations where brand heritage, aesthetic coherence, and artisanal values are core strategic assets.
Drawing on the Technology–Organization–Environment (TOE) framework, the article conducts a qualitative case study in a large French luxury house. The empirical data was collected through six semi-structured interviews with employees involved in BI-related projects across different métiers, including retail operations, finance, and digital analytics. Thematic analysis reveals that although the TOE model captures important factors such as top management support, technical complexity, and external pressures, it overlooks crucial symbolic and cultural factors specific to luxury contexts.
The findings contribute by introducing sector-specific extensions to the TOE framework. In particular, the study identifies symbolic compatibility, aesthetic alignment, and post-adoption negotiation as significant mediating effects on BI appropriation. The research provides practical lessons for implementation teams and luxury organizations, including the inclusion of brand aesthetics in BI design, anticipate resistance linked to heritage protection, and build governance structures that balance standardization with creative autonomy.
While the scope lies within a single-case environment, the thesis offers analytical implications for future research and practice in digitalization in symbolically dense fields, with a need for more culturally aware frameworks in IS adoption research.

Key words: Business Intelligence, luxury industry, technology adoption, TOE framework, heritage brands, digital transformation

Subject: Information System Science

Title: Selecting an Optimal Stream Processing Tool in an E-commerce Environment

Abstract: 

The rapid growth of data volume and velocity in e-commerce has heightened the demand for real-time
analytics and adaptive business strategies. Selecting an optimal stream processing tool is critical, yet
challenging, due to the wide array of available platforms and the complexity of requirements in modern
e-commerce environments. This thesis addresses the gap by applying a structured decision-making framework,
based on the Analytic Hierarchy Process (AHP), to guide e-commerce organizations in evaluating
and selecting stream processing tools aligned with their operational and strategic needs.
The research employs a multi-method case study within an European e-commerce company, combining
qualitative data from stakeholder interviews, documentation analysis, and observations, with quantitative
pairwise comparisons to establish and weight key selection criteria. Six stream processing platforms:
Apache Flink, Apache Spark Structured Streaming, Apache Kafka Streams, Apache Storm, Apache Samza,
and Google Cloud Dataflow are systematically evaluated against criteria such as fault tolerance, performance,
state and event handling, integration, operability, and cost within a dynamic pricing case study. The
findings demonstrate how a criteria-driven methodology can support organizations in making informed and
context-aware technology choices.

Key words: Stream processing, E-commerce, Real-time analytics, Analytic Hierarchy Process
(AHP), Tool selection, Dynamic pricing

Subject: Information System Science

Title: LLM-Powered Business Process Modelling in Small and Medium Enterprises: Benefits,
Success Factors and Implementation Challenges

Abstract: 

Small and Medium Enterprises (SMEs) face significant barriers in adopting traditional Business Process
Modelling (BPM) due to resource constraints, expertise requirements, and complex notation systems. Large
Language Models (LLMs) offer potential solutions by generating process models from natural language
descriptions, yet empirical evidence of their effectiveness in real SME contexts remains limited. This research
investigates the benefits, success factors, and failure factors when implementing LLM-powered BPM in SMEs.
Existing literature demonstrates clear BPM organizational benefits but identifies expertise requirements and
resource constraints as primary SME adoption barriers (Papademetriou & Karras, 2017; Viegas & Costa,
2022). Recent AI-powered BPM research shows technical feasibility for generating BPMN-compliant models
from textual descriptions (Grohs et al., 2023; Kourani et al., 2024) but lacks empirical investigation of
organizational adoption factors in real business contexts. The study employs the Technology-Organization-
Environment (TOE) framework to analyse adoption factors, combined with established BPM quality
assessment frameworks (SEQUAL for multi-dimensional quality evaluation, 7PMG for objective diagram
assessment) to create a comprehensive evaluation approach for AI-generated process models. A qualitative
multiple case study approach examines three French SMEs across different industries (IT consulting,
manufacturing, perfume production) with varying digital maturity levels. Using GPT-4 mini, BPMN 2.0
compliant process models were generated from organizational documentation and evaluated using the
established quality frameworks. Semi-structured interviews with key stakeholders captured organizational
perceptions, adoption challenges, and value recognition patterns. The technical assessment revealed consistent
strengths in activity labelling and gateway selection, alongside universal weaknesses including multiple
start/end event violations and excessive element proliferation. Stakeholder evaluation demonstrated a
fundamental dichotomy between communication effectiveness and operational completeness. While all
participants recognized value for external communication and training purposes, semantic gaps rendered
models insufficient for internal process management. The most significant finding involved universal
requirements for human verification despite AI accessibility benefits, creating capability demands that
potentially exceeded SME resources. The research contributes a Multi-Factor Alignment Framework
organizing success factors across technical, organizational, and environmental dimensions. The study
concludes that LLM-powered BPM represents a transformation from operational tool to communication
medium, requiring hybrid approaches leveraging AI for communication while maintaining traditional methods
for operational requirements.

Key words: Business Process Modelling, Large Language Models, SME Digital Transformation,
AI Adoption, Process Management, BPMN.

Subject: Employee-AI Collaboration

Title: Socio-Technical Factors Shaping Employee-AI Collaboration

Abstract: 

Despite significant organisational investments in AI technologies, 70-85% of AI initiatives fail to achieve their projected value due to inadequate understanding of the human factors driving successful employee-AI collaboration. Using a socio-technical systems perspective to analyse intricate relationships between technological, organisational and individual components, this study explores the socio-technical characteristics that impact employee-AI collaboration in digital workplaces. This study examines five key factors: AI literacy, AI explainability, organisational support, task variety and paradoxical tensions. A quantitative cross-sectional survey was conducted at Doctolib, a European healthcare technology company that implemented enterprise-wide AI capabilities in February 2025. Data from 73 employees were analyzed using PLS-SEM to test relationships between five socio-technical factors and employee-AI collaboration outcomes. The key finding demonstrates that AI literacy serves as the most critical factor in determining collaborative success (β = 0.498, p = 0.016), providing empirical validation of Wang et al.’s (2022) four-dimensional AI literacy framework in a real organisational setting. However, contrary to theoretical expectations, AI explainability, task variety and paradoxical tensions showed no significant relationships with collaboration. Most surprisingly, organisational support failed to demonstrate any moderating effects, challenging traditional technology acceptance frameworks. The research validates AI literacy theory whilst challenging dominant narratives in explainable AI research. For practitioners, the findings suggest that organisations should prioritise comprehensive AI literacy programs addressing awareness, usage, evaluation and ethics dimensions rather than focusing on traditional organisational support mechanisms. This research demonstrates that successful employee-AI collaboration requires AI-specific approaches to implementation and capability development, highlighting the need for new theoretical frameworks that move beyond conventional technology adoption models.

Key words: Employee-AI collaboration, socio-technical systems, AI literacy, organisational support, PLS-SEM

Subject: Information System Science

Title: Onboarding Business Domains into a Data Mesh: A Kotter-Based Change Enablement Framework Tested at Toyota Motor Europe

Abstract: 

As organisations adopt decentralised data architectures like Data Mesh, many struggle to operationalise new roles such as Data Product Owner or Domain Data Steward. While technical aspects are well-documented, the organisational and behavioural dimensions, particularly the onboarding of business stakeholders, remain underexplored. This thesis investigates how large enterprises can enable successful role adoption during a Data Mesh transformation. Based on a qualitative case study at Toyota Motor Europe and using abductive reasoning, the study proposes the Data Mesh Change Enablement Framework, an adapted eight-step change model inspired by Kotter’s theory but tailored to decentralised contexts. The framework emphasises contextualised urgency, multi-level coalitions, co-created role narratives, peer-driven acceleration, and institutional anchoring. Grounded in empirical data, the framework offers a practical yet flexible tool for guiding change in large-scale data transformations.

Key words: Data Mesh, Change Management, Decentralised Data Governance, Business Stakeholder Onboarding, Data Product Owner, Federated Architecture, Kotter’s 8-Step Model, Qualitative Case Study, Toyota Motor Europe.

Subject: Information System Science

Title: The optimization of change management processes via automation and performance metrics in IT systems.

Abstract: 

The thesis investigates how organizations can manage new technology by adding automation and performance evaluation to what they already do. Since digital transformation is growing more complicated and happening faster, the research examines how technological tools, organizational methods and people are interacting. Using a qualitative method, the researcher study how institutions organize, execute and review changes in complicated conditions. Focus is placed on how firms deal with bringing together technological progress, strategic planning and staff cultural acceptance. The thesis adds to current debates on how data, systems and people help shape successful and lasting change.

Key words: IT Change Management, Automation, Performance metrics, Artificial Intelligence, Resistance to Change, Robotic Process Automation (RPA), Key Performance Indicators (KPIs).

Subject: OS Migrations

Title: Managing End-User Satisfaction and Compliance during OS Migrations in Multinational Research Organizations

Abstract: 

This thesis investigates how structured IT governance frameworks can support end-user compliance and satisfaction during operating system (OS) migrations, focusing on the case of ITER’s transition from Windows 10 to Windows 11. While existing governance models such as COBIT and ITIL provide structured guidance for managing risk and standardizing processes, their application during OS migrations remains underexplored. The study addresses this gap through a mixed methods case study, combining the analysis of 176 service desk tickets with seven semi-structured interviews conducted across IT and non-IT roles. The findings reveal that compliance emerged through negotiated behaviours shaped by user perception of change, and that workarounds bordering on non-compliance were also part of a healthy approach to change. While technical execution greatly improved over time, some persistent gaps in perspectives between end users and managers were observed. The study proposes that integrating governance frameworks with change management models (such as ADKAR and Kotter) enables organizations to adapt formal controls to contextual realities. This approach is especially relevant in multinational scientific institutions, where strict compliance requirements coexist with diverse user expectations and operational constraints.

Key words: IT governance, end-user compliance, OS migration, change management, Windows 11, ITER

Subject: Culture influence on ERP implementations in the MENA region

Title: Culture Influence on ERP implementation : a MENA perspective

Abstract: 

Enterprise Resource Planning (ERP) systems are widely adopted by multinational organizations to integrate business processes, yet their implementation success remains inconsistent across cultural contexts. This thesis investigates how national cultural differences influence ERP implementation outcomes in the Middle East and North Africa (MENA) region, with a specific focus on SAP projects.
While Critical Success Factors (CSFs) frameworks are frequently used to guide ERP deployment, most existing literature disregards culture or treats it as a peripheral factor. Moreover, these frameworks tend to be predominantly Western-oriented. Drawing on Hofstede’s cultural dimensions, this research explores how cultural values actively impact key CSFs such as top management support, project management, user training, ERP team composition and Business Process Reengineering. It employs a qualitative methodology based on semi-structured interviews with ERP consultants who have implemented SAP in Egypt, Jordan, Morocco, and Saudi Arabia.
This study reveals that Hofstede’s cultural dimensions translate into specific behavioral patterns that systematically influence Critical Success Factor effectiveness. Four consistent areas of influence emerged: hierarchical decision-making patterns, team dynamics, communication styles, and change resistance behaviors. The findings challenge the assumption that CSFs operate uniformly across cultures, revealing instead that cultural values fundamentally reshape how each success factor must be implemented.
This thesis extends ERP theory by positioning culture as a contingent factor that fundamentally shapes CSF effectiveness rather than treating it as a separate element. For practitioners, it offers concrete guidelines for adapting implementation approaches to local cultural contexts in the MENA region.

Key words: ERP implementation, SAP, National Culture, Critical Success Factors, MENA Region, Behaviours

Subject: Digital Addiction and Interface Design

Title: Designing for Control: Embedded Digital Interventions to Counter Compulsive Short-Form Video Use

Abstract: 

Short-form video (SFV) platforms like TikTok have become dominant in the digital media landscape, driven by immersive design features such as algorithmic personalization, continuous scroll, and high sensory stimulation. While these features maximize engagement, growing evidence links SFV use to compulsive behavior, impaired attention, and weakened self-regulation. Traditional awareness tools—such as screen time apps—often fail in such environments, as they rely on voluntary self-control despite the platform’s intent to suppress it. This thesis investigates whether embedded digital interventions, implemented directly within the consumption flow, can counteract compulsive SFV usage. A between-subjects experiment was conducted using a custom-built SFV platform, testing and comparing two conditions: a friction-based timer and a targeted motivational warning. The study measured behavioral outcomes, perceived control, and future intervention acceptance. Findings show that both intervention types significantly reduced perceived overconsumption and increased user reflection. Tailored warnings were also rated as more supportive, though behavioral outcomes were similar across types. These results suggest that embedded interventions can help restore user agency in digital environments explicitly designed to undermine it, offering practical insights for platform designers and policymakers.

Key words: Short-form video, Digital interventions, Interface design, Compulsive media use, Behavioral nudges, Friction awareness, Digital well-being