Case Study On Article 29 New York

A Sweet Breakfast Memory That Connects With the Wrong Market

By JOHN GROSSMANN

Christopher Pouy founded Cow Wow Cereal Milk to bring a taste of his past to today’s children. But the milk is proving more popular with an older set.

November 13, 2014, Thursday

MORE ON CASE STUDIES AND: Cow Wow Cereal Milk , Advertising and Marketing , Pouy, Christopher , Small Business , Milk

A Small, Spicy Start-Up Prepares for the Demands of Eggnog Season

By JULIE WEED

Addition, a two-person company that makes liquid spices for cocktails and beers, considers how to increase production from 750 bottles a month to 7,500.

October 2, 2014, Thursday

MORE ON CASE STUDIES AND: Small Business , Alcoholic Beverages , Start-ups , Shopping and Retail , Spices , Addition (Spice Co)

A Leader Struggles to Sell Software Meant to Aid Sales

By JOHN GROSSMANN

The chief executive of Yesware has come up with three solutions to address weak software sales. Outside experts offer advice on which path to pursue.

August 21, 2014, Thursday

MORE ON CASE STUDIES AND: Small Business , Executives and Management (Theory) , Yesware Inc , Bellows, Matthew

Select Home Care Weighs New Wage and Labor Regulations

By ESHA CHHABRA

A California-based home care company is pondering three choices in meeting new state and federal work rules regarding its caregivers.

June 18, 2014, Wednesday

MORE ON CASE STUDIES AND: Labor and Jobs , Elder Care , Small Business , California , Select Home Care , Hull, Dylan

A Small Brand Tries to Escape the Confusing Shadow of a Big Brand

By SARAH MAX

Hobby Lobby International has almost the same name as a far larger and socially polarizing company. Experts recommend rebranding.

May 8, 2014, Thursday

MORE ON CASE STUDIES AND: Small Business , Hobby Lobby Stores Inc , Cleveland, Mark A , Trademarks and Trade Names , Hobby Lobby International , Hobby Express

Seeking Even Faster Growth, an E-Commerce Company Stumbles

By ADRIANA GARDELLA

Jimmy Beans Wool, a successful, growing online yarn merchant, expanded and ran into trouble.

April 3, 2014, Thursday

MORE ON CASE STUDIES AND: Zander, Laura , E-Commerce , Jimmy Beans Wool , Zander, Doug , Wool and Woolen Goods , Small Business

A Business Owner Seeks an Alternative to Seven-Day Workweeks

By JOHN GROSSMANN

Carlos Vega, a New Jersey pizzeria owner, faced a decision: Should he expand his small restaurant or concentrate on selling his popular red sauce?

January 2, 2014, Thursday

MORE ON CASE STUDIES AND: Small Business , Restaurants , Father and Son Pizzeria (Guttenberg, NJ)

A Business Owner Who Backed Off Tries to Step Back In

By JOHN GROSSMANN

A cooking business is doing well under hired staff, but the owner wants to increase sales substantially over several years to attract potential buyers.

October 24, 2013, Thursday

MORE ON CASE STUDIES AND: Gignilliat, Bibby , Executives and Management (Theory) , Small Business , Cooking and Cookbooks

A Fast-Growing Tree Service Considers Selling Franchises

By JOHN GROSSMANN

An owner wants to add more locations, but is not sure whether he wants to own the locations or franchise them.

September 12, 2013, Thursday

MORE ON CASE STUDIES AND: Skolnick, Josh , Entrepreneurship , Small Business , Franchises , Monster Tree Service

When Your First Company Is Working, but Another Is Beckoning

By JULIE WEED

A young entrepreneur has created two companies, one established and stable, the other in development and a little flashier, and he is at a crossroad.

May 30, 2013, Thursday

MORE ON CASE STUDIES AND: Start-ups , Small Business , Entrepreneurship , Badshah, Aseem

1. World Health Organization Influenza (Seasonal) 2013. [2014-03-21]. webcitehttp://www.who.int/mediacentre/factsheets/fs211/en/

2. Eysenbach G. Infodemiology and infoveillance tracking online health information and cyberbehavior for public health. Am J Prev Med. 2011 May;40(5 Suppl 2):S154–8. doi: 10.1016/j.amepre.2011.02.006.[PubMed][Cross Ref]

3. Eysenbach G. Infodemiology and infoveillance: framework for an emerging set of public health informatics methods to analyze search, communication and publication behavior on the Internet. J Med Internet Res. 2009;11(1):e11. doi: 10.2196/jmir.1157.http://www.jmir.org/2009/1/e11/[PMC free article][PubMed][Cross Ref]

4. Eysenbach G. Infodemiology: tracking flu-related searches on the web for syndromic surveillance. AMIA Annu Symp Proc; AMIA Annual Symposium; November 11, 2006; Washington, D.C. USA: AMIA; 2006. pp. 244–248. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1839505/[PMC free article][PubMed]

5. Ginsberg J, Mohebbi MH, Patel RS, Brammer L, Smolinski MS, Brilliant L. Detecting influenza epidemics using search engine query data. Nature. 2009 Feb 19;457(7232):1012–4. doi: 10.1038/nature07634.[PubMed][Cross Ref]

6. Doornik J. University of Oxford, Technical Report: 1-21. [2014-09-28]. webcite Improving the timeliness of data on influenza-like illnesses using Google search data http://www.gwu.edu/~forcpgm/JurgenDoornik-final-Doornik2009Flu-Jan31.pdf.

7. Choi H, Varian H. Predicting the present with Google Trends. Economic Record. 2012;88(s1):2–9. doi: 10.1111/j.1475-4932.2012.00809.x.[Cross Ref]

8. Carneiro HA, Mylonakis E. Google Trends: a web-based tool for real-time surveillance of disease outbreaks. Clin Infect Dis. 2009 Nov 15;49(10):1557–64. doi: 10.1086/630200.http://www.cid.oxfordjournals.org/cgi/pmidlookup?view=long&pmid=19845471. [PubMed][Cross Ref]

9. Ritterman J, Osborne M, Klein E. Using prediction markets and Twitter to predict a swine flu pandemic. 1st International Workshop on Mining Social Media; 2009; Sevilla, Spain. 2009. pp. 9–17.

10. Vadileios L, Cristianini N. Tracking the flu pandemic by monitoring the social web. 2nd IAPR Workshop on Cognitive Information Processing (CIP); June 14-16, 2010; Elba Island, Italy. 2010. pp. 411–416.

11. Chunara R, Andrews JR, Brownstein JS. Social and news media enable estimation of epidemiological patterns early in the 2010 Haitian cholera outbreak. Am J Trop Med Hyg. 2012 Jan;86(1):39–45. doi: 10.4269/ajtmh.2012.11-0597.http://www.ajtmh.org/cgi/pmidlookup?view=long&pmid=22232449. [PMC free article][PubMed][Cross Ref]

12. Kim EK, Seok JH, Oh JS, Lee HW, Kim KH. Use of Hangeul Twitter to track and predict human influenza infection. PLoS One. 2013;8(7):e69305. doi: 10.1371/journal.pone.0069305.http://dx.plos.org/10.1371/journal.pone.0069305. [PMC free article][PubMed][Cross Ref]

13. Paul M, Dredze M. You are what you tweet: analyzing Twitter for public health. Artificial Intelligence. 2011:265–272.

14. Cheng Z, Caverlee J, Lee K. You are where you tweet: a content-based approach to geo-locating Twitter users. 19th ACM International Conference on Information Knowledge Management; 2010; Scottsdale, AZ, USA. 2011. pp. 759–768.

15. Achrekar H, Gandhe A, Lazarus R. Twitter improves seasonal influenza prediction. HEALTHINF. 2012:61.

16. Butler D. When Google got flu wrong. Nature. 2013 Feb 14;494(7436):155–6. doi: 10.1038/494155a.[PubMed][Cross Ref]

17. Olson DR, Konty KJ, Paladini M, Viboud C, Simonsen L. Reassessing Google Flu Trends data for detection of seasonal and pandemic influenza: a comparative epidemiological study at three geographic scales. PLoS Comput Biol. 2013 Oct;9(10):e1003256. doi: 10.1371/journal.pcbi.1003256.http://dx.plos.org/10.1371/journal.pcbi.1003256. [PMC free article][PubMed][Cross Ref]

18. Lazer D, Kennedy R, King G, Vespignani A. The parable of Google Flu: traps in big data analysis. Science. 2014 Mar 13;343(6176):1203–1205. doi: 10.1126/science.1248506.[PubMed][Cross Ref]

19. Chew C, Eysenbach G. Pandemics in the age of Twitter: content analysis of Tweets during the 2009 H1N1 outbreak. PLoS One. 2010 Nov;5(11):e14118. doi: 10.1371/journal.pone.0014118.http://dx.plos.org/10.1371/journal.pone.0014118. [PMC free article][PubMed][Cross Ref]

20. Culotta A. Detecting influenza epidemics by analyzing Twitter messages. 2010. [2014-09-30]. webcitehttp://arxiv.org/pdf/1007.4748.pdf.

21. Culotta A. Towards detecting influenza epidemics by analyzing Twitter messages. KDD Workshop on Social Media Analytics; July 25, 2010; Washington, DC. 2010.

22. Signorini A, Segre AM, Polgreen PM. The use of Twitter to track levels of disease activity and public concern in the U.S. during the influenza A H1N1 pandemic. PLoS One. 2011 May;6(5):e19467. doi: 10.1371/journal.pone.0019467.http://dx.plos.org/10.1371/journal.pone.0019467. [PMC free article][PubMed][Cross Ref]

23. Santos J, Sergio M. Predicting flu incidence from Portuguese tweets. IWBBIO Proceedings; IWBBIO; March 18-20, 2013; Granada, Spain. 2013. pp. 11–18.

24. Broniatowski D, Paul M, Dredze M. National and local influenza surveillance through Twitter: an analysis of the 2012-2013 influenza epidemic. PLoS ONE. 2013;8(12):e83672. doi: 10.1371/journal.pone.0083672.[PMC free article][PubMed][Cross Ref]

25. MappyHealth - Social Health Insights. [2014-03-21]. webcitehttp://nowtrending.hhs.gov/

26. Fountin Germ Tracker Map. [2014-03-21]. webcitehttp://fount.in/m.

27. Observatorio da Dengue. [2014-03-21]. webcitehttp://www.observatorio.inweb.org.br/dengue/conteudo/inicial.

28. Infovigil. [2014-09-28]. webcitehttp://www.infodemiology.org/

29. SickWeather. [2014-03-21]. webcitehttp://www.sickweather.com/

30. New York City Department of Health and Mental Hygiene. [2014-03-21]. webcitehttp://www.nyc.gov/html/doh/flu/html/data/data.shtml.

31. WebPlot Digitizer. [2014-03-21]. webcitehttp://sourceforge.net/projects/digitizer/files/Engauge%20Digitizer/digitizer-5.1/

32. Dredze M, Paul M, Bergsma S, Tran H. Carmen: a Twitter geolocation system with applications to public health. AAAI Workshop on Expanding the Boundaries of Health Informatics Using AI (HIAI); 2013; Palo Alto, California. 2013.

33. Lamb A, Paul M, Dredze M. Separating fact from fear: tracking flu infections on Twitter. North American Chapter of the Association for Computational Linguistics (NAACL) 2013:789–795.

34. CrowdBreaks. [2014-03-21]. webcitehttp://www.crowdbreaks.com/

35. Kulldorff M, Heffernan R, Hartman J, Assunção RM, Mostashari F. A space-time permutation scan statistic for the early detection of disease outbreaks. PLoS Medicine. 2005;2:216–224. doi: 10.1371/journal.pmed.0020059.[PMC free article][

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