Matching Platforms and HIV Incidence: An Empirical Investigation of Race, Gender, and Socioeconomic Status

被引:92
作者
Greenwood, Brad N. [1 ]
Agarwal, Ritu [2 ]
机构
[1] Temple Univ, Fox Sch Business, Philadelphia, PA 19122 USA
[2] Univ Maryland, Robert H Smith Sch Business, College Pk, MD 20742 USA
关键词
public health; two-sided matching; platforms; natural experiment; HIV; digital divide; SEXUAL RISK BEHAVIOR; UNITED-STATES; INTERNET; MEN; CARE; COST; INFORMATION; PREVALENCE; INFECTION; PATTERNS;
D O I
10.1287/mnsc.2015.2232
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
Although recent work has examined the adverse implications of Internet-enabled matching platforms, limited attention has been paid to whom the negative externalities accrue. We examine how the entry of platforms for the solicitation of casual sex influences the incidence rate of human immunodeficiency virus (HIV) infection by race, gender, and socioeconomic status. Using a census of 12 million patients subjected to a natural experiment in Florida, we find a significant increase in HIV incidence after platform implementation, with the largest effect accruing to historically at-risk populations (i.e., African Americans) despite documented lower rates of Internet utilization. Strikingly, our analysis reveals that HIV incidence increases in historically low-risk populations as well (e.g., individuals of higher socioeconomic status) and that men and women experience similar penalties. Identifying granular effects across subpopulations allows us to offer additional insight into the mechanisms by which matching platforms increase HIV incidence. We estimate the cumulative effect of platform entry over the five-year period of the study as 1,149 additional Floridians contracting HIV at a cost of $710 million.
引用
收藏
页码:2281 / 2303
页数:23
相关论文
共 82 条
[1]   The Digital Transformation of Healthcare: Current Status and the Road Ahead [J].
Agarwal, Ritu ;
Gao, Guodong ;
DesRoches, Catherine ;
Jha, Ashish K. .
INFORMATION SYSTEMS RESEARCH, 2010, 21 (04) :796-809
[2]   Interaction terms in logit and probit models [J].
Ai, CR ;
Norton, EC .
ECONOMICS LETTERS, 2003, 80 (01) :123-129
[3]   Fixed-effects negative binomial regression models [J].
Allison, PD ;
Waterman, RP .
SOCIOLOGICAL METHODOLOGY 2002, VOL 32, 2002, 32 :247-265
[4]  
Angrist JD, 2009, MOSTLY HARMLESS ECONOMETRICS: AN EMPIRICISTS COMPANION, P1
[5]  
[Anonymous], 2013, EXPL DIG NAT AM EM O
[6]  
[Anonymous], 2011, UNAUTHORIZED IMMIGRA
[7]  
[Anonymous], 2013, Socioeconomic status. APA.org
[8]  
[Anonymous], 2004, TECHNOLOGY SOCIAL IN
[9]  
[Anonymous], 2011, Dorland's illustrated medical dictionary, V32nd
[10]  
Bailey J. P., 1997, International Journal of Electronic Commerce, V1, P7