Browsing by Author "Mirbagherimarvili, Sahar"

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Data Monetization Challenges in Established Organizations: A Systematic Literature Review
(2022-08-09) Mirbagherimarvili, Sahar; Ghanbari, Hadi; Rossi, Matti
A4 Artikkeli konferenssijulkaisussa
Over the last decades, researchers and practitioners have looked at data as a valuable asset for improving business processes in organizations. However, nowadays, they see data more as a tradable asset that can be monetized. Data monetization here refers to generating revenue from selling data and data-based products and services. Despite providing opportunities for generating new revenue streams, data monetization is not without challenges, especially in established organizations. Previous research shows that an organization’s data monetization capability is constrained by its existing business model, infrastructure, and organizational culture. Although Information Systems (IS) research and practice have shown an increasing interest in data monetization, we lack a thorough understanding of its challenges. As a first step in addressing this gap, we set out to identify challenges that established organizations face in monetizing their data. To that end, we conducted a systematic literature review and identified 21 challenges reported in the extant literature. Based on their nature, we divided these challenges into five categories, including business model, legal & regulatory, security & privacy, organizational, and data management challenges. Our study has several implications for IS research and practice.
Exploring Data Monetization in Established Organizations: a Dynamic Capability Approach
(2024-01-03) Mirbagherimarvili, Sahar; Ghanbari, Hadi; Rossi, Matti
A4 Artikkeli konferenssijulkaisussa
The exponential growth of data, together with the increasing importance of analytics in a wide range of contexts, has given rise to data monetization, a phenomenon in which data and data-based offerings are traded for monetary value. Data monetization is relevant for established organizations since they often generate significant amounts of data which provides them with many opportunities for added revenue streams. Previous research shows that incumbents are falling short in harnessing this potential either because of the lack of knowledge of data-based business models or insufficient resources and capabilities. There is a paucity of research on how incumbents could develop such capabilities to successfully sell data and data-based offerings. To fill this gap, we conducted a multiple case study to explore what kind of capabilities are required by established organizations to successfully sell data. The paper contributes to the evolving discourse on data monetization by providing a new understanding of the required capabilities for selling data from the dynamic capability perspective.
To Sell or Not to Sell? Drivers and Barriers to Direct Data Monetization in Incumbents
(2025-01-10) Mirbagherimarvili, Sahar
A4 Artikkeli konferenssijulkaisussa
The rapid expansion of data along with the growing significance of analytics across various fields has led to direct data monetization, where data and data-driven products are exchanged for monetary value. Although data monetization provides incumbents with significant opportunities for new revenue streams, they move slowly in monetizing data. This study aims to identify the drivers and barriers to selling data in incumbents. Through a field study, we establish two comprehensive typologies of drivers and barriers. Our results show that endogenous factors, such as strategy and resource access, have a stronger impact on data monetization in incumbents than exogenous factors. Conversely, exogenous barriers, such as lack of demand and market immaturity, negatively affect data monetization more significantly than endogenous barriers. This study provides a deeper understanding of direct data monetization. It helps practitioners see different motivations and barriers related to data monetization, aiding them in scoping their data initiatives.