The Cost Impact of Spam Filters: Measuring the Effect of Information System Technologies in Organizations
AbstractMore than 70% of global e-mail traffic consists of unsolicited and commercial direct marketing, also known as spam. Dealing with spam incurs high costs for organizations, prompting efforts to try to reduce spam-related costs by installing spam filters. Using modern econometric methods to reduce the selection bias of installing a spam filter, we deploy a unique data setting implemented at a German university to measure the costs associated with spam and the costs savings of spam filters. The applied methodological framework can easily be transferred to estimate the effect of other IS technologies (e.g., SAP) implemented in organizations. Our findings indicate that central IT costs are of little relevance since the majority of spam costs stem from employees who spend working time identifying and deleting spam. The working time losses caused by spam are approximately 1,200 minutes per employee per year; these costs could be reduced by roughly 35% through the installation of a spam filter mechanism. The individual efficiency of a spam filter installation depends on the amount of spam that is received and on the level of knowledge about spam.
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Bibliographic InfoPaper provided by Institute for the Study of Labor (IZA) in its series IZA Discussion Papers with number 3755.
Length: 38 pages
Date of creation: Oct 2008
Date of revision:
Publication status: published in: Information Systems Research, 2012, 23 (3, Part II), 1068-1080
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Find related papers by JEL classification:
- M12 - Business Administration and Business Economics; Marketing; Accounting - - Business Administration - - - Personnel Management; Executives; Executive Compensation
- M15 - Business Administration and Business Economics; Marketing; Accounting - - Business Administration - - - IT Management
This paper has been announced in the following NEP Reports:
- NEP-ALL-2008-10-28 (All new papers)
- NEP-ICT-2008-10-28 (Information & Communication Technologies)
- NEP-KNM-2008-10-28 (Knowledge Management & Knowledge Economy)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- A. Smith, Jeffrey & E. Todd, Petra, 2005.
"Does matching overcome LaLonde's critique of nonexperimental estimators?,"
Journal of Econometrics,
Elsevier, vol. 125(1-2), pages 305-353.
- Jeffrey Smith & Petra Todd, 2003. "Does Matching Overcome Lalonde's Critique of Nonexperimental Estimators?," University of Western Ontario, CIBC Centre for Human Capital and Productivity Working Papers 20035, University of Western Ontario, CIBC Centre for Human Capital and Productivity.
- Michael Lechner, 2005.
"Some practical issues in the evaluation of heterogeneous labour market programmes by matching methods,"
Labor and Demography
- Michael Lechner, 2002. "Some practical issues in the evaluation of heterogeneous labour market programmes by matching methods," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 165(1), pages 59-82.
- Falkinger, Josef, 2007.
Journal of Economic Theory,
Elsevier, vol. 133(1), pages 266-294, March.
- Robert Kraut & Shyam Sunder & Rahul Telang & James Morris, 2005. "Pricing Electronic Mail to Solve the Problem of Spam," Yale School of Management Working Papers amz2638, Yale School of Management, revised 01 Oct 2005.
- Il-Horn Hann & Kai-Lung Hui & Yee-Lin Lai & S.Y.T. Lee & I.P.L. PNG, 2006. "Who gets spammed?," Natural Field Experiments 00271, The Field Experiments Website.
- Sanjeev Dewan & Charles Shi & Vijay Gurbaxani, 2007. "Investigating the Risk-Return Relationship of Information Technology Investment: Firm-Level Empirical Analysis," Management Science, INFORMS, vol. 53(12), pages 1829-1842, December.
- Marco Caliendo & Sabine Kopeinig, 2008.
"Some Practical Guidance For The Implementation Of Propensity Score Matching,"
Journal of Economic Surveys,
Wiley Blackwell, vol. 22(1), pages 31-72, 02.
- Marco Caliendo & Sabine Kopeinig, 2005. "Some Practical Guidance for the Implementation of Propensity Score Matching," Discussion Papers of DIW Berlin 485, DIW Berlin, German Institute for Economic Research.
- Caliendo, Marco & Kopeinig, Sabine, 2005. "Some Practical Guidance for the Implementation of Propensity Score Matching," IZA Discussion Papers 1588, Institute for the Study of Labor (IZA).
- Seung-Hoon Yoo & Chul-Oh Shin & Seung-Jun Kwak, 2006. "Inconvenience cost of spam mail: a contingent valuation study," Applied Economics Letters, Taylor & Francis Journals, vol. 13(14), pages 933-936.
- Sascha O. Becker & Marco Caliendo, 2007.
"mhbounds - Sensitivity Analysis for Average Treatment Effects,"
Discussion Papers of DIW Berlin
659, DIW Berlin, German Institute for Economic Research.
- Sascha O. Becker & Marco Caliendo, 2007. "Sensitivity analysis for average treatment effects," Stata Journal, StataCorp LP, vol. 7(1), pages 71-83, February.
- Becker, Sascha O. & Caliendo, Marco, 2007. "mhbounds – Sensitivity Analysis for Average Treatment Effects," IZA Discussion Papers 2542, Institute for the Study of Labor (IZA).
- Heckman, James J. & Lalonde, Robert J. & Smith, Jeffrey A., 1999. "The economics and econometrics of active labor market programs," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 3, chapter 31, pages 1865-2097 Elsevier.
- DiPrete, Thomas A. & Gangl, Markus, 2004. "Assessing bias in the estimation of causal effects: Rosenbaum bounds on matching estimators and instrumental variables estimation with imperfect instruments," Discussion Papers, Research Unit: Labor Market Policy and Employment SP I 2004-101, Social Science Research Center Berlin (WZB).
- Barbara Sianesi, 2002. "An evaluation of the Swedish system of active labour market programmes in the 1990s," IFS Working Papers W02/01, Institute for Fiscal Studies.
- James Heckman & Hidehiko Ichimura & Jeffrey Smith & Petra Todd, 1998.
"Characterizing Selection Bias Using Experimental Data,"
Econometric Society, vol. 66(5), pages 1017-1098, September.
- James Heckman & Hidehiko Ichimura & Jeffrey Smith & Petra Todd, 1998. "Characterizing Selection Bias Using Experimental Data," NBER Working Papers 6699, National Bureau of Economic Research, Inc.
- Glenn W. Harrison & John A. List, 2004.
Journal of Economic Literature,
American Economic Association, vol. 42(4), pages 1009-1055, December.
- Oecd, 2005. "Spam Issues in Developing Countries," OECD Digital Economy Papers 99, OECD Publishing.
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