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Full-Text Articles in Management Sciences and Quantitative Methods
Covid-19 And Management Scholarship: Lessons For Conducting Impactful Research, Gerard George, Gokhan Ertug, Jonathan P. Doh, Johanna Mair, Ajnesh Prasad
Covid-19 And Management Scholarship: Lessons For Conducting Impactful Research, Gerard George, Gokhan Ertug, Jonathan P. Doh, Johanna Mair, Ajnesh Prasad
Research Collection Lee Kong Chian School Of Business
The COVID-19 pandemic provided an opportunity for management scholars to address large-scale and complex societal problems and strive for greater practical and policy impact. A brief overview of the most-cited work on COVID-19 reveals that, compared with their counterparts in other disciplines, leading management journals and professional associations lagged in providing a platform for high-impact research on COVID-19. To help management research play a more active role in responding to similar global challenges in the future, we propose an integrative framework that emphasizes a phenomenon’s impact, the conditions that the phenomenon creates at multiple levels, and the responses of actors …
From The Editors: Mobilizing New Sources Of Data: Opportunities And Recommendations, Denis A. Gregoire, Anne L. J. Ter Wal, Laura M. Little, Sekou Bermiss, Reddi Kotha, Marc Gruber
From The Editors: Mobilizing New Sources Of Data: Opportunities And Recommendations, Denis A. Gregoire, Anne L. J. Ter Wal, Laura M. Little, Sekou Bermiss, Reddi Kotha, Marc Gruber
Research Collection Lee Kong Chian School Of Business
In June 2008, the U.S.-based website Glassdoor.com began posting anonymous company reviews and salary data from current and former employees of various organizations. Doing so not only brought to the world information that had hitherto been restricted to private circles, it spontaneously prompted some organizations to alter their workplace practices (Dineen & Allen, 2016; Dube & Zhu, 2021). At the same time, Glassdoor’s very activities gave rise to a completely new source of data for exploring a wealth of management and organizational phenomena (e.g., Bermiss & McDonald, 2018; Rhee, 2024). As this example illustrates, new data sources can not only …
From Actions To Paths To Patterning: Toward A Dynamic Theory Of Patterning In Routines, Kenneth T. Goh, Brian T. Pentland
From Actions To Paths To Patterning: Toward A Dynamic Theory Of Patterning In Routines, Kenneth T. Goh, Brian T. Pentland
Research Collection Lee Kong Chian School Of Business
This paper demonstrates a new way of seeing and theorizing about the dynamics of organizational routines through the concept of paths – time-ordered sequences of actions or events in performing work. Empirically and conceptually, paths provide the missing link between specific actions and patterns of action. When routines are represented as a narrative network, tracing the formation and dissolution of action paths can generate new insights about the dynamic patterning of actions in routine performances. We traced action paths using longitudinal field data from a videogame development project and found that action patterns change dramatically over time based on the …
Revisiting The Small-World Phenomenon: Efficiency Variation And Classification Of Small-World Networks, Tore Opsahl, Antoine Vernet, Tufool Alnuaimi, Gerard George
Revisiting The Small-World Phenomenon: Efficiency Variation And Classification Of Small-World Networks, Tore Opsahl, Antoine Vernet, Tufool Alnuaimi, Gerard George
Research Collection Lee Kong Chian School Of Business
Research has explored how embeddedness in small-world networks influences individual and firm outcomes. We show that there remains significant heterogeneity among networks classified as small-world networks. We develop measures of the efficiency of a network, which allow us to refine predictions associated with small-world networks. A network is classified as a small-world network if it exhibits a distance between nodes that is comparable to the distance found in random networks of similar sizeswith ties randomly allocated among nodesin addition to containing dense clusters. To assess how efficient a network is, there are two questions worth asking: (a) What is a …
Big Data And Data Science Methods For Management Research: From The Editors, Gerard George, Ernst C. Osinga, Dovev Lavie, Brent A. Scott
Big Data And Data Science Methods For Management Research: From The Editors, Gerard George, Ernst C. Osinga, Dovev Lavie, Brent A. Scott
Research Collection Lee Kong Chian School Of Business
The recent advent of remote sensing, mobile technologies, novel transaction systems, and high performance computing offers opportunities to understand trends, behaviors, and actions in a manner that has not been previously possible. Researchers can thus leverage 'big data' that are generated from a plurality of sources including mobile transactions, wearable technologies, social media, ambient networks, and business transactions. An earlier AMJ editorial explored the potential implications for data science in management research and highlighted questions for management scholarship, and the attendant challenges of data sharing and privacy (George, Haas & Pentland, 2014). This nascent field is evolving rapidly and at …
Big Data And Management: From The Editors, Gerard George, Martine R. Haas, Alex Pentland
Big Data And Management: From The Editors, Gerard George, Martine R. Haas, Alex Pentland
Research Collection Lee Kong Chian School Of Business
Big data is everywhere. In recent years, there has been an increasing emphasis on big data, business analytics, and "smart" living and work environments. Though these conversations are predominantly practice driven, organizations are exploring how large-volume data can usefully be deployed to create and capture value for individuals, businesses, communities, and governments (McKinsey Global Institute, 2011). Whether it is machine learning and web analytics to predict individual action, consumer choice, search behavior, traffic patterns, or disease outbreaks, big data is fast becoming a tool that not only analyzes patterns, but can also provide the predictive likelihood of an event.