Methodology for measuring the impact of mobile technology change from 2nd to 3th generation percerved by users of smes in Barranquilla

This article presents the results of a research project undertaken to obtain a Masters inBusiness Administration from the Business School at the Universidad del Norte, whosepurpose was to identify and test a methodology to measure the impact exerted by thechange from 2nd to 3rd generation mobile tech, based on the perception of users belongingto Barranquilla SME, motivated by the influence of technological changes in behavior andthe knowledge creation among society members, and the importance it has taken to thesurvival of organizations the adoption of applications for process automation, web-basedapplications, voice, data and video that allow the development of competitive advantages,based on information and creativity for new and better products or services.

"Tell me who you hang out with": Classroom peer effects on psychoactive substances consumption

I look for classroom peer effects for psychoactive substance consumption among Colombian high school students and attempt to identify channels that rationalize for these effects. To do so, I use data for Colombian schools from 2011. I identify peer effects using household consumption behavior to instrument average classroom consumption. I find that an increase of 10% in the proportion of classroom users of alcohol, cannabis, and cocaine increases the probability of students to use alcohol, cannabis, and cocaine in 3.14%, 4.29%, and 2.38% respectively. I find no significant effect on cigarette smoking for the full sample but after exploring heterogeneous effects I find suggestive evidence that the effect is positive in some grades. I find some evidence that indicate that peer effects on alcohol, cannabis, and cocaine consumption operate through risk perception and easiness of access to psychoactive substances, meaning that the increase of likelihood of consumption could be explained because it is easier to access to drugs for students that interact with consumers or because a decrease in the risk students perceive of consuming these substances. Finally, through the use of a SUR and a 3SLS estimator I find strong correlations between smoking cigarettes and consuming cannabis (55 %), and cocaine (60 %).