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- All HBS Web
(1,380)
- People (1)
- News (192)
- Research (1,007)
- Events (12)
- Multimedia (8)
- Faculty Publications (530)
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- 2019
- Chapter
Spatial Agglomeration and Superstar Firms: Firm-level Patterns from Europe and U.S.
By: Laura Alfaro, Maggie X. Chen and Harald Fadinger
We characterize the agglomeration patterns of industries and plants in Europe, distinguishing Eurozone countries and the United States. Using a micro-level index, we quantify the degree of geographic concentration in industrial activities and explore how firm... View Details
Alfaro, Laura, Maggie X. Chen, and Harald Fadinger. "Spatial Agglomeration and Superstar Firms: Firm-level Patterns from Europe and U.S." In ECB Forum on Central Banking, 17-19 June 2019, Sintra, Portugal: 20 years of European Economic and Monetary Union: Conference Proceedings. Frankfurt: European Central Bank, 2019.
- 2014
- Article
Ascent-Descent Young Diagrams and Pattern Avoidance in Alternating Permutations
By: Ravi Jagadeesan
We investigate pattern avoidance in alternating permutations and an alternating analogue of Young diagrams. In particular, using an extension of Babson and West’s notion of shape-Wilf equivalence described in our recent paper (with N. Gowravaram), we generalize results... View Details
Jagadeesan, Ravi. "Ascent-Descent Young Diagrams and Pattern Avoidance in Alternating Permutations." #P3.9. Electronic Journal of Combinatorics 21, no. 3 (2014).
- Article
Fast Generalized Subset Scan for Anomalous Pattern Detection
By: Edward McFowland III, Skyler Speakman and Daniel B. Neill
We propose Fast Generalized Subset Scan (FGSS), a new method for detecting anomalous patterns in general categorical data sets. We frame the pattern detection problem as a search over subsets of data records and attributes, maximizing a nonparametric scan statistic... View Details
Keywords: Pattern Detection; Anomaly Detection; Knowledge Discovery; Bayesian Networks; Scan Statistics; Analytics and Data Science
McFowland III, Edward, Skyler Speakman, and Daniel B. Neill. "Fast Generalized Subset Scan for Anomalous Pattern Detection." Art. 12. Journal of Machine Learning Research 14 (2013): 1533–1561.
- July 2020 (Revised January 2021)
- Case
Pattern Brands
By: Sunil Gupta, Elie Ofek and Julia Kelley
In March 2020, direct-to-consumer (DTC) company Pattern Brands needed to decide how to allocate resources across its different brands. Pattern Co-Founders Nick Ling and Emmett Shine hoped to avoid the pitfalls faced by some DTC companies—such as inability to scale and... View Details
Keywords: Direct-to-consumer; Brands and Branding; Marketing Channels; Marketing Strategy; Product Marketing; Product Launch; Product Positioning; Business Model; Business Startups; Growth and Development Strategy; Demand and Consumers; Business Strategy; Diversification; Competitive Advantage; Consumer Products Industry; Retail Industry; North and Central America; United States; New York (city, NY); New York (state, US)
Gupta, Sunil, Elie Ofek, and Julia Kelley. "Pattern Brands." Harvard Business School Case 521-009, July 2020. (Revised January 2021.)
- November 2021
- Article
Gaussian Process Subset Scanning for Anomalous Pattern Detection in Non-iid Data
By: William Herlands, Edward McFowland III, Andrew Gordon Wilson and Daniel B. Neill
Identifying anomalous patterns in real-world data is essential for understanding where, when, and how systems deviate from their expected dynamics. Yet methods that separately consider the anomalousness of each individual data point have low detection power for subtle,... View Details
Herlands, William, Edward McFowland III, Andrew Gordon Wilson, and Daniel B. Neill. "Gaussian Process Subset Scanning for Anomalous Pattern Detection in Non-iid Data." Proceedings of Machine Learning Research (PMLR) 84 (2018): 425–434. (Also presented at the 21st International Conference on Artificial Intelligence and Statistics (AISTATS), 2018.)
- January 2021
- Article
Machine Learning for Pattern Discovery in Management Research
By: Prithwiraj Choudhury, Ryan Allen and Michael G. Endres
Supervised machine learning (ML) methods are a powerful toolkit for discovering robust patterns in quantitative data. The patterns identified by ML could be used for exploratory inductive or abductive research, or for post-hoc analysis of regression results to detect... View Details
Keywords: Machine Learning; Supervised Machine Learning; Induction; Abduction; Exploratory Data Analysis; Pattern Discovery; Decision Trees; Random Forests; Neural Networks; ROC Curve; Confusion Matrix; Partial Dependence Plots; AI and Machine Learning
Choudhury, Prithwiraj, Ryan Allen, and Michael G. Endres. "Machine Learning for Pattern Discovery in Management Research." Strategic Management Journal 42, no. 1 (January 2021): 30–57.
- 2013
- Article
Beyond Alternating Permutations: Pattern Avoidance in Young Diagrams and Tableaux
By: Nihal Gowravaram and Ravi Jagadeesan
We investigate pattern avoidance in alternating permutations and generalizations thereof. First, we study pattern avoidance in an alternating analogue of Young diagrams. In particular, we extend Babson-West’s notion of shape-Wilf equivalence to apply to alternating... View Details
Keywords: Pattern Avoidance; Alternating Permutations; Descent Type Permutations; Wilf Equivalence; Shape-Wilf Equivalence; Mathematical Methods
Gowravaram, Nihal, and Ravi Jagadeesan. "Beyond Alternating Permutations: Pattern Avoidance in Young Diagrams and Tableaux." #P17. Electronic Journal of Combinatorics 20, no. 4 (2013).
- July 2007
- Article
Patterned Interactions in Complex Systems
By: J. Rivkin and Nicolaj Siggelkow
Keywords: System
Rivkin, J., and Nicolaj Siggelkow. "Patterned Interactions in Complex Systems." Management Science 53, no. 7 (July 2007).
- January–February 2014
- Article
The New Patterns of Innovation
By: Rashik Parmar, Ian Mackenzie, David Cohn and David Gann
The search for new business ideas—and models—is hit-or-miss at most firms. Tackling the problem systematically, of course, will improve the odds of success. Traditional ways of framing this search examine competencies, customer needs, and shifts in the landscape. This... View Details
Parmar, Rashik, Ian Mackenzie, David Cohn, and David Gann. "The New Patterns of Innovation." Harvard Business Review 92, nos. 1-2 (January–February 2014): 86–95.
- 2007
- Chapter
Career Patterns and Organizational Performance
By: Monica C. Higgins and James R. Dillon
Traditional research on careers examines how organizations and individuals affect career outcomes. This chapter reviews several specific ways in which career histories have been found to influence organizational outcomes. While we incorporate both upper echelons... View Details
Higgins, Monica C., and James R. Dillon. "Career Patterns and Organizational Performance." Chap. 21 in Handbook of Career Studies, edited by M. Peiperl and H. Gunz, 422–436. Sage Publications, 2007.
- March 31, 2023
- Article
What Is the Optimal Pattern of a Customer Journey?
Even though customer experience (CX) leaders are becoming increasingly focused on optimizing their firms’ customer journeys, they face a clear challenge: Which touchpoints along the journey should they invest in? That is, which moments when the customer interacts with... View Details
De Freitas, Julian. "What Is the Optimal Pattern of a Customer Journey?" Harvard Business Review (website) (March 31, 2023).
- 1982
- Working Paper
Pattern of OPEC Capital Flows
By: S. L. Hayes III, Dwight B. Crane and Elaine C. Ide
- Working Paper
Shifting Work Patterns with Generative AI
By: Eleanor W. Dillon, Sonia Jaffe, Nicole Immorlica and Christopher T. Stanton
We present evidence on how generative AI changes the work patterns of knowledge workers using
data from a 6-month-long, cross-industry, randomized field experiment. Half of the 7,137 workers
in the study received access to a generative AI tool integrated into the... View Details
Dillon, Eleanor W., Sonia Jaffe, Nicole Immorlica, and Christopher T. Stanton. "Shifting Work Patterns with Generative AI." NBER Working Paper Series, No. 33795, May 2025.
- May 2022
- Article
The Impact of COVID-19 on Digital Communication Patterns
By: Evan DeFilippis, Stephen Michael Impink, Madison Singell, Jeff Polzer and Raffaella Sadun
We explore the impact of COVID-19 on employees’ digital communication patterns through an event study of lockdowns in 16 large metropolitan areas in North America, Europe, and the Middle East. Using de-identified, aggregated meeting and email meta-data from 3,143,270... View Details
Keywords: Meetings; Email; COVID-19 Pandemic; Communication Technology; Health Pandemics; Time Management
DeFilippis, Evan, Stephen Michael Impink, Madison Singell, Jeff Polzer, and Raffaella Sadun. "The Impact of COVID-19 on Digital Communication Patterns." Humanities and Social Sciences Communications 9, no. 180 (May 2022).
- 2020
- Working Paper
Machine Learning for Pattern Discovery in Management Research
Supervised machine learning (ML) methods are a powerful toolkit for discovering robust patterns in quantitative data. The patterns identified by ML could be used as an observation for further inductive or abductive research, but should not be treated as the result of a... View Details
Keywords: Machine Learning; Theory Building; Induction; Decision Trees; Random Forests; K-nearest Neighbors; Neural Network; P-hacking; Analytics and Data Science; Analysis
Choudhury, Prithwiraj, Ryan Allen, and Michael G. Endres. "Machine Learning for Pattern Discovery in Management Research." Harvard Business School Working Paper, No. 19-032, September 2018. (Revised June 2020.)
- February 2018
- Article
Heterogeneous Technology Diffusion and Ricardian Trade Patterns
By: William R. Kerr
This study tests the importance of Ricardian technology differences for international trade. The empirical analysis has three comparative advantages: including emerging and advanced economies, isolating panel variation regarding the link between productivity and... View Details
Keywords: Exports; Comparative Advantage; Technological Transfer; Innovation; Networks; Patents; Residency; Technology Adoption; Trade; Research and Development; Immigration; United States
Kerr, William R. "Heterogeneous Technology Diffusion and Ricardian Trade Patterns." World Bank Economic Review 32, no. 1 (February 2018): 163–182.
- 2013
- Working Paper
Heterogeneous Technology Diffusion and Ricardian Trade Patterns
By: William R. Kerr
This study tests the importance of Ricardian technology differences for international trade. The empirical analysis has three comparative advantages: including emerging and advanced economies, isolating panel variation regarding the link between productivity and... View Details
Keywords: Exports; Comparative Advantage; Technological Transfer; Innovation; Networks; Patents; Residency; Technology Adoption; Trade; Research and Development; Immigration; United States
Kerr, William R. "Heterogeneous Technology Diffusion and Ricardian Trade Patterns." Harvard Business School Working Paper, No. 14-039, November 2013. (NBER Working Paper Series, No. 19657, November 2013.)
- 05 Dec 2013
- Working Paper Summaries
Heterogeneous Technology Diffusion and Ricardian Trade Patterns
Keywords: by William R. Kerr
- 2010
- Chapter
Cost Structure Patterns in the Asset Management Industry
By: Dennis Campbell and Frances X. Frei
This chapter examines patterns in the cost structure of asset management firms and establishes two important trends in cost behavior. First, when revenues are growing, "indirect" costs related to sales, distribution, marketing, personnel, technology, and occupancy are... View Details