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Customer Engagement Management (CEM) is a customer-centric strategy focused on improving user experience, satisfaction, and long-term loyalty. This study explores the information needs within the CEM practices of a major international airline by conducting three sequential qualitative investigations involving key stakeholder groups: internal CEM team members, customers, and external travel agents. Through a triangulated analysis of interviews and survey data, the study reveals systemic information gaps and proposes design improvements for digital engagement strategies. Findings emphasize the significance of enhancing e-CEM platforms—such as websites and mobile applications—and integrating social-CEM approaches to improve real-time communication and engagement. The results also highlight how human-computer interaction (HCI) principles can support more effective information flows between organizations and stakeholders, ultimately strengthening customer engagement.

Data practices vary widely across scientific disciplines. While Big Data has significantly transformed research activities across various domains and has been heralded as a revolutionary force in scientific paradigms, its application has not been uniform across all fields. This study examines Big Data research and practices in data-intensive scientific domains, identifying its distinct features and revealing the uneven adoption and impact of Big Data across disciplines. Our findings indicate that discussions on the epistemological concepts and definitions of Big Data in data-intensive scientific domains are limited, with little divergence among scholars. Machine learning emerges as a central technological focus across disciplines, closely integrated with research topics and widely driving scientific advancements. Additionally, this paper highlights the instrumental role of Big Data in scientific inquiry and underscores the disparities in its impact across different disciplines. Through this review, we aim to foster a more comprehensive understanding of Big Data’s evolving role in science, emphasizing the need for continued critical reflection as its influence continues to develop.