Reflections on societal and business model transformation arising from digitization and big data analytics: A research agenda

By Claudia Löbbecke, Arnold Picot. Journal of strategic information systems, 2015

1,144 citations recorded by the source corpus.

Subfields: Industrial and Manufacturing Engineering, Organizational Behavior and Human Resource Management, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/b586d368295482f00e7bc3417599fe757a472f9b

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Citations in the corpus

Artificial intelligence, robotics, advanced technologies and human resource management: a systematic review (2021, background): “In fact, our study responds to several calls to synthesise the current state of knowledge beyond the boundaries of individual academic disciplines in reference to intelligent automation (e.g. AI, machine learning, digitization) and work (Loebbecke & Picot, 2015; Markus, 2015).”
Digital transformation as a springboard for product, process and business model innovation (2021, neutral): “…transformation on different business areas (Erevelles, Fukawa, & Swayne, 2016), business models (Alberti-Alhtaybat, Al-Htaybat, & Hutaibat, 2019; Loebbecke & Picot, 2015), business performances (Ferraris et al., 2019; Ferreira, Fernandes, & Ferreira, 2019) and required capabilities (Muninger,…”
Debating big data: A literature review on realizing value from big data (2017, methodology): “Thus, social value comprises benefits for single users as well as larger societal benefits such as employment growth, productivity, and consumer surplus (Loebbecke and Picot, 2015).”
Mastering digital transformation: The nexus between leadership, agility, and digital strategy (2022, background): “Digital transformation entails various consequences that reshape business models, impact employment among leaders, employees, and knowledge workers, and impact organizational cultures (Scuotto, Nicotra, Del Giudice, Krueger, and Gregori, 2021; Legner et al., 2017; Loebbecke and Picot, 2015).”
Implementing a Digital Strategy: Learning from the Experience of Three Digital Transformation Projects (2020, background): “68 The most important aspect of data usage is that it must be constantly refreshed.”
Digital transformation and the new logics of business process management (2020, positive): “Tensions in agential logic (procedural) result from the diverse implications of digital transformation on organisational restructuring that often a ﬀ ects individual and team roles and even identities (Loebbecke & Picot, 2017; Utesheva et al., 2016).”
How open is innovation? A retrospective and ideas forward (2021, background): “Such business models often rest on the firm’s ability to generate and handle massive amounts of data—supported by technologies previously not available (e.g., Björkdahl, 2020; Loebbecke and Picot, 2015; Sjödin, Parida, Jovanovic, and Visnjic, 2020).”
Conceptualizing Digital Transformation in Business Organizations: A Systematic Review of Literature (2017, neutral): “(2013); Janowski (2015); Loebbecke & Picot (2015); Luna-Reyes & Gil-Garcia (2014); Matt, et.al.”
Automation, Algorithms, and Beyond: Why Work Design Matters More Than Ever in a Digital World (2020, background): “…automated, with some warning that knowledge work and even management can be replaced by AI because the related tasks involve analytical and rational knowledge processing (FerràsHernández, 2018; Loebbecke & Picot, 2015), such as reflected in the notion of algorithmic management (Schildt, 2017).”
Digitalization, business models, and SMEs: How do business model innovation practices improve performance of digitalizing SMEs? (2019, methodology): “Digital transformation is not about optimizing internal processes or incorporating new technologies, but fundamentally changing SMEs’ business models (Loebbecke & Picot, 2015).”