Computational Text Analysis for Qualitative IS Research: A Methodological Reflection

Qualitative analysis is an essential component of the dynamic process of sensemaking, where researchers sift through data to extract innovative insights that can contribute to new theoretical perspectives. In most cases, this involves analyzing unstructured text data gathered from naturalistic inquiries and secondary data material. However, due to the predominantly manual nature of qualitative text analysis, there is often a trade-off between feasibility and expanding the scope of a study, giving rise to criticism by quantitative scholars that theoretical generalizations from qualitative research often lack a larger empirical backing, are not reproducible, or are subjectively biased. As computational text analysis (CTA) gradually becomes more accessible, also new research opportunities for qualitative scholars arise, which must be aligned with traditional qualitative thinking and evaluation criteria. In this article, we explore the value and purpose, process, and validation of CTA in qualitative IS research. Drawing from a specific case illustration, we examine potential issues concerning data collection and sampling, analysis, and interpretation of findings. Additionally, we discuss the potential obstacles that qualitative researchers using CTA may encounter when conducting the study but also when submitting their work for consideration for publication in IS journals

Empowering digital transformation: The roles of platforms

This study investigates how digital platforms can drive the digital transformation of participant firms in their surrounding business ecosystems. To do so, we conduct an in-depth case study of Alibaba’ cross-border e-commerce platform and eleven seller firms operating on the platform. Our results highlight the importance of proper empowerment in platform-driven digital transformation. In particular, we observe that Alibaba attempts to facilitate the digital transformation of seller firms through three types of activities: resource empowerment, psychological empowerment, and structural empowerment. Moreover, we find that the sequence of these empowerment activities plays a critical role. Without being psychologically empowered first, seller firms react quite passively to Alibaba’s resource provision and structural support. Psychological empowerment provides the activation triggers for the sellers to renew their mindsets and become receptive to Alibaba’s support and guidance, which ultimately contribute to the digital transformation of their businesses

Legal Compliance and the Open Texture of Law

The law is often vague and ambiguous, especially when applied to novel and unusual cases. Legal scholars have referred to this as “the open texture of law.” Legal compliance is seldom straightforward, requiring interpretation before conceiving and designing mechanisms for compliance. Organizations find themselves having to plan for and ultimately tackle compliance under uncertainty. This policy editorial discusses closure in legal compliance in the context of the open texture of law, using the example of the EU Artificial Intelligence Act. This example is of particular concern for information systems (IS) research and practice. This policy editorial aims to offer some guidance in this complex area

From Detractors to Enhancers: Harnessing the Power of Ad Customization for User Engagement on Media Websites

Media websites (e.g., news, video platforms) rely on user engagement to ensure profitability, growth, and relevance. To this end, they often offer customization options to encourage users to spend more time on pages, visit more pages, and return to the website. Previous studies have focused on web customization for desirable editorial content (e.g., topics of news articles). Our research examines ad quantity customization (AQC), or how users interact with websites that offer choice-based versus direct-exposure advertising models. We reveal a counterintuitive dynamic: While ads are typically viewed as detrimental to user engagement, they can be strategically leveraged to enhance it. In a randomized field experiment covering 17,289 visits to a European music news website, only two thirds (66.6%) of visitors used AQC to eliminate ad exposure, while the remaining one third (33.4%) opted for a reduced or regular ad quantity. The provision of AQC was associated with 20.5% more time spent on the website, 9.5% more unique pages visited, and a 37.8% higher return rate. Furthermore, the impact of AQC on visit duration was particularly strong for users who visited the website using mobile (vs. stationary) devices. Supplementary analyses further revealed that participants accessing an AQC-enabled website spent 13.7% more time on the site and visited 6.4% more unique pages compared to participants accessing an ad-free website. This study counterintuitively reveals that elements that typically detract from user engagement can be strategically utilized to enhance it and outlines specific circumstances where users may prefer the presence over the absence of ads

User Behavior Mining

Studying the behavior of users in software systems has become an essential task for software vendors who want to mitigate usability problems and identify automation potentials, or for researchers who want to test behavioral theories. One approach to studying user behavior in a data-driven way is through the analysis of so-called user interaction (UI) logs, which record the low-level activities that a user performs while executing a task. In the paper, the authors refer to the analysis of UI logs as User Behavior Mining (UBM) and position it as a research topic. UBM is conceptualized by means of a four-component framework that elaborates how UBM data can be captured, which technologies can be applied to analyze it, which objectives UBM can accomplish, and how theories can guide the analytical process. The applicability of the framework is demonstrated by three exemplary applications from an ongoing research project with a partner company. Finally, the paper discusses practical challenges to UBM and derives an agenda for potential future research directions

Roles and Requirements for Effective Knowledge Exchange in an IT Company’s Academic Ecosystem: Insights from Modeling the SAP University Alliances Ecosystem

Many students and lecturers desire tangible and conceivable teaching content. In the information systems (IS) domain, access to real-life information technology (IT) is required. Nevertheless, it often needs more than access, such as contract processing, suitable curricula, or lecturer training. In many cases, these activities are managed bilaterally between an educational institution and a company. The resulting partnerships, however, bear the risk of dispersing as soon as strategic, technological, or staffing conditions change. To address this issue, we examine the ecosystemic approach toward academic-industry partnerships. The ecosystemic approach applies the concept of competence centers as independent intermediary hubs. Using the SAP University Alliances (SAP UA) program as an example of the ecosystemic approach, we iteratively develop an e3 value model of the ecosystem by interviewing its stakeholders and validating the resulting model at a conference with the SAP UA community. Further, we develop six role concepts and respective requirement dimensions that facilitate effective knowledge exchange in IT companies’ academic ecosystems. Our contributions provide insights into how such an ecosystem can be structured and critically assess application fields by considering the continuous changes affecting the IS education community. Implications for practitioners and researchers in the field of academic-industry collaboration are discussed

Non-profit organisations in the digital age: A research agenda for supporting the development of a digital transformation strategy

Digital transformation (DT) research is moving to new frontiers of investigation, exploring the nexus between multi-scale and multi-level stimuli and effects. This article contributes to the literature examining how DT phenomena affect multiple and connected ecosystems among industries, governments, economies, and societies. Identifying DT outcomes in a given context includes considering the organisations’ unequal development and digital presence. Non-profit organisations (NPOs) are flagships of a unique organisational nature based on non-distributional constraints and the primacy of nonfinancial outcomes. Assuming DT as a process that could improve, transform, or change an entity’s property, this research examines which specific aspects link to DT outcomes in the context of NPOs, investigating preconditions, value-creation structures, and strategic development. The study performs a meta-synthesis by developing a taxonomy of 124 journal articles strictly discussing DT in NPOs to identify objects and characteristics describing the debate. Subsequently, it questions the validity of adopting insights resulting from other organisational forms to study and develop DT strategies for NPOs by comparing two frameworks. This study contributes to the current body of knowledge by suggesting a lens of analysis helpful in assessing the (DT) value-creation structures of NPOs, a research agenda outlining future directions, and recommendations intended to support NPOs’ policymakers and managers in undertaking DT projects

Disruptive change within financial technology: A methodological analysis of digital transformation challenges

The digital transformation of the FinTech industry has revealed a plethora of significant challenges for industry decision makers and wider stakeholder groups as organisations contend with the onset of new regulatory frameworks, legacy systems, flexible business models and alignment with corporate social responsibility practice. The reshaping of organisations and drive to greater levels of decentralisation and employee centric practice, presents a cultural shift for the sector, with implications for the success and resulting benefits of change across the industry. This study aims to develop novel insight to the ‘lived in’ impact of digital transformation within the FinTech industry from a factor interdependency perspective. This research adopts a mixed methods approach incorporating Interpretive Structural Modelling, Analytical Hierarchy Process and interviews with expert participants, to offer a unique perspective on the challenges and unintended consequences of industry level technological change. The findings highlight the high levels of interdependency and priority for challenges related to the investment in products and infrastructure for new markets, criticality of stakeholder support and development of a digital mindset for the adoption of new technologies

The Impact of Gamification on Cybersecurity Learning: Multi-Study Analysis

Gamification is a popular learning technique that can be employed to enhance learner’s interest in their careers by presenting them with realistic scenarios and practical problem-solving experiences. However, the effectiveness of this method has not been fully investigated in the context of cybersecurity learning. This study aims to systematically assess the impact of gamification on cybersecurity learning. Through a multi-study approach, we conducted a four-semester-long experiment to integrate gamification into an undergraduate cybersecurity course, comparing learning outcomes in gamified and traditional labs as well as analyzing learners’ perceptions, motivation, and career interests in gamified cybersecurity lab experiences. In addition, qualitative interviews reveal how students interact with these labs and identify game elements that significantly impact their learning experience. Our findings provide theoretical contributions by expanding the literature on gamification\u27s role in cybersecurity learning and practical strategies for seamlessly incorporating gamification into cybersecurity learning experience