Navigation

You are here: Home › Sequence Analysis

Tag Archives | Sequence Analysis

Using Sequence Analysis to Quantify How Strongly Life Courses Are Linked

By on January 19, 2021 in Articles

Tim F. Liao

Sociological Science January 19, 2021
10.15195/v8.a3

Abstract

PDF (1947 views)
0 Citation


Dyadic or, more generally, polyadic life course sequences can be more associated within dyads or polyads than between randomly assigned dyadic/polyadic member sequences, a phenomenon reflecting the life course principle of linked lives. In this article, I propose a method of U and V measures for quantifying and assessing linked life course trajectories in sequence data. Specifically, I compare the sequence distance between members of an observed dyad/polyad against a set of randomly generated dyads/polyads. TheU measure quantifies how much greater, in terms of a given distance measure, the members in a dyad/polyad resemble one another than do members of randomly generated dyads/polyads, and the V measure quantifies the degree of linked lives in terms of how much observed dyads/polyads outperform randomized dyads/polyads. I present a simulation study, an empirical study analyzing dyadic family formation sequence data from the Longitudinal Study of Generations, and a random seed sensitivity analysis in the online supplement. Through these analyses, I demonstrate the versatility and usefulness of the proposed method for quantifying linked lives analysis with sequence data. The method has broad applicability to sequence data in life course, business and organizational, and social network research.
Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.

Tim F. Liao: Department of Sociology, University of Illinois
E-mail: tfliao@illinois.edu

Acknowledgments: The author wishes to acknowledge the benefit of an Australian Research Council Discovery Project (DP#160101063, chief investigators Irma Mooi-Reci and Mark Wooden, and partner investigator Tim Liao). The abovementioned project anticipated the need for the research reported in this article. The author would also like to thank Anette Fasang and Marcel Raab, who kindly shared the Longitudinal Study of Generations data used in their 2014 Demography publication, and Yifan Shen for comments.

Supplemental Material

  • Citation: Liao, Tim F. 2021. “Using Sequence Analysis to Quantify How Strongly Life Courses Are Linked.” Sociological Science 8: 48-72.
  • Received: November 5, 2020
  • Accepted: December 13, 2020
  • Editors: Jesper Sørensen, Olav Sorenson
  • DOI: 10.15195/v8.a3


0

The Entrepreneur's Network and Firm Performance

By on October 18, 2017 in Articles

Victor Nee, Lisha Liu, Daniel DellaPosta

Sociological Science, October 18, 2017
DOI 10.15195/v4.a23

Abstract
PDF (3181 views)
0 Citation

Diverse organizational forms coexist in China’s market economy, adapting and evolving in intensely competitive production markets. We examine the networks of founding chief executive officers of private manufacturing firms in seven cities of the Yangzi River Delta region in China. Through sequence analysis of ties that entrepreneurs relied on for help in the founding and critical events of their businesses, we identify three discrete forms of network governance: traditional kin-based, hybrid nonkin, and rational capitalist. We find that in traditional kin-based network governance, structural holes are linked to higher returns on assets and returns on equity. By contrast, in the rational capitalist form, structural holes and higher firm performance are not linked. We thus show that the content of the tie matters critically in the relationship between structural holes and firm performance.

Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.

Victor Nee: Department of Sociology, Cornell University
Email: victor.nee@cornell.edu

Lisha Liu: Department of Sociology, Cornell University
Email: ll733@cornell.edu.com

Daniel DellaPosta: Department of Sociology and Criminology, Pennsylvania State University
Email: djd78@psu.edu

Acknowledgements: Victor Nee gratefully acknowledges grants from the John Templeton Foundation (2005–2010; 2015–2018), research assistant support from the College of Arts and Sciences at Cornell University, and the Jan Wallander and Tom Hedelius Foundation (2011–2013). We thank Michael Macy, Anne Tsui, Brett de Bary, Rachel Davis, Mario Molina, Lucas Drouhot, and David Strang for their helpful comments on an earlier draft. Victor Nee received helpful feedback on his presentation of the article at the 2017 Conference of the International Network of Analytical Sociologists in Oslo, Norway, on June 5 and 6 and the Annual Meeting of the Academy of International Business in Dubai, United Arab Emirates, from July 3 to 6. Lisha Liu and Daniel DellaPosta share equal responsibility in their contributions.

  • Citation: Nee, Victor, Lisha Liu, and Daniel DellaPosta. 2017. “The Entrepreneur’s Network and Firm Performance.” Sociological Science 4: 552-579.
  • Received: July 12, 2017
  • Accepted: September 5, 2017
  • Editors: Jesper Sørensen, Olav Sorenson
  • DOI: 10.15195/v4.a23


0
SiteLock