The impact of content marketing on attitudes and purchase intentions of online shoppers : the case videos & tutorials and user-generated content

This thesis was written as part of a Double-Degree Masters program in Management, with focus in Marketing. Aligned with the nature of the degree, this study aims to be a useful tool for managers and marketers, which conduct business online. This thesis is a study of Content Marketing in the content of online commercial product pages. Its aim is to understand how to use content marketing to drive conversion, by understanding consumer attitudes and purchase intention towards content. A in-depth study of existing theories and exploratory primary research was developed in other to attain these objectives. Business-to-consumer electronic commerce (B2C e-commerce) has provided consumers and online retailers with a more effective medium to perform online transactions through commercial websites. Although consumers have realized that the benefits of online shopping; such as time saving, minimizing effort, convenience, broader selection, and wider access to information, they are still greatly unwilling to shop online. Consumers shop essentially for two motives, to meet experiential (fun) or goal-oriented (efficiency) needs (Wolfinbarger & Gilly, 2001). The information provided by content marketing seeks to focus on consumers need for information and entertainment, instead of focusing on the brand. Thus, it is expected that the type of content format will have different effects on the attitudes and purchase intention on the online shopper, depending on the online shopping purpose. Concretely, a goal-oriented shopper should find user generated content (UGC) to be more valuable content formats, since they decrease the amount of search effort. While on the other hand, videos & tutorials (VT) might be perceived as more valuable for a consumer looking to spend time and being entertained through online shopping. The exploratory research was characterized by a survey experiment with online consumers. Participants were exposed to stimuli of content marketing tested according to their attitudes and purchase intention. The focus was to understand the impact of two different content marketing tactics—User-generated content and Videos & Tutorials—on attitudes and purchase intentions and how they interact with content complexity. The results indicate that content marketing in commercial product pages is relevant in driving consumer attitudes and purchase intentions. Consumers are not motivated by a specific content marketing tactic, unless that content has a certain level of complexity. In that case, Ur-Generated Content becomes a relevant tactic in product pages, however VT is not.

Object modeling for user-centered development and user interface design: the wisdom approach

João Bernardo de Sena Esteves Falcão e Cunha

Graphical constraints: a graphical user interface for constraint problems

A constraint satisfaction problem is a classical artificial intelligence paradigm characterized by a set of variables (each variable with an associated domain of possible values), and a set of constraints that specify relations among subsets of these variables. Solutions are assignments of values to all variables that satisfy all the constraints. Many real world problems may be modelled by means of constraints. The range of problems that can use this representation is very diverse and embraces areas like resource allocation, scheduling, timetabling or vehicle routing. Constraint programming is a form of declarative programming in the sense that instead of specifying a sequence of steps to execute, it relies on properties of the solutions to be found, which are explicitly defined by constraints. The idea of constraint programming is to solve problems by stating constraints which must be satisfied by the solutions. Constraint programming is based on specialized constraint solvers that take advantage of constraints to search for solutions. The success and popularity of complex problem solving tools can be greatly enhanced by the availability of friendly user interfaces. User interfaces cover two fundamental areas: receiving information from the user and communicating it to the system; and getting information from the system and deliver it to the user. Despite its potential impact, adequate user interfaces are uncommon in constraint programming in general. The main goal of this project is to develop a graphical user interface that allows to, intuitively, represent constraint satisfaction problems. The idea is to visually represent the variables of the problem, their domains and the problem constraints and enable the user to interact with an adequate constraint solver to process the constraints and compute the solutions. Moreover, the graphical interface should be capable of configure the solver’s parameters and present solutions in an appealing interactive way. As a proof of concept, the developed application – GraphicalConstraints – focus on continuous constraint programming, which deals with real valued variables and numerical constraints (equations and inequalities). RealPaver, a state-of-the-art solver in continuous domains, was used in the application. The graphical interface supports all stages of constraint processing, from the design of the constraint network to the presentation of the end feasible space solutions as 2D or 3D boxes.

Power flow for primary distribution networks considering uncertainty in demand and user connection

This paper presents a method for calculating the power flow in distribution networks considering uncertainties in the distribution system. Active and reactive power are used as uncertain variables and probabilistically modeled through probability distribution functions. Uncertainty about the connection of the users with the different feeders is also considered. A Monte Carlo simulation is used to generate the possible load scenarios of the users. The results of the power flow considering uncertainty are the mean values and standard deviations of the variables of interest (voltages in all nodes, active and reactive power flows, etc.), giving the user valuable information about how the network will behave under uncertainty rather than the traditional fixed values at one point in time. The method is tested using real data from a primary feeder system, and results are presented considering uncertainty in demand and also in the connection. To demonstrate the usefulness of the approach, the results are then used in a probabilistic risk analysis to identify potential problems of undervoltage in distribution systems. (C) 2012 Elsevier Ltd. All rights reserved.

Measurement of the t(t)over-bar production cross section in p(p)over-bar collisions at root s=1.96 TeV using lepton plus jets events with lifetime b-tagging

We present a measurement of the top quark pair (t (t) over bar) production cross section (sigma(t (t) over bar)) in pp collisions at root s = 1.96 TeV using 230 pb(-1) of data collected by the DO experiment at the Fermilab Tevatron Collider. We select events with one charged lepton (electron or muon), missing transverse energy, and jets in the final state. We employ lifetime-based b-jet identification techniques to further enhance the t F purity of the selected sample. For a top quark mass of 175 GeV, we measure sigma(t (t) over bar) 8.6(-1.5)(+1.6) (stat. + syst.) +/- 0.6(lumi.) pb, in agreement with the standard model expectation. (c) 2005 Published by Elsevier B.V.

Measurement of B-d mixing using opposite-side flavor tagging

We report on a measurement of the B-d(0) mixing frequency and the calibration of an opposite-side flavor tagger in the D0 experiment. Various properties associated with the b quark on the opposite side of the reconstructed B meson are combined using a likelihood-ratio method into a single variable with enhanced tagging power. Its performance is tested with data, using a large sample of reconstructed semileptonic B ->mu(DX)-X-0 and B ->mu(DX)-X-* decays, corresponding to an integrated luminosity of approximately 1 fb(-1). The events are divided into groups depending on the value of the combined tagging variable, and an independent analysis is performed in each group. Combining the results of these analyses, the overall effective tagging power is found to be epsilon D-2=(2.48 +/- 0.21(-0.06)(+0.08))%. The measured B-d(0) mixing frequency Delta m(d)=0.506 +/- 0.020(stat)+/- 0.016(syst) ps(-1) is in good agreement with the world average value.

Measurement of the t(t)over-bar production cross section in p(p)over-bar collisions at root s=1.96 TeV using secondary vertex b tagging

We report a new measurement of the t (t) over bar production cross section in p (beta) over bar collisions at a center-of-mass energy of 1.96 TeV using events with one charged lepton (electron or muon), missing transverse energy, and jets. Using 425 pb(-1) of data collected using the D0 detector at the Fermilab Tevatron Collider, and enhancing the t (t) over bar content of the sample by tagging b jets with a secondary vertex tagging algorithm, the t (t) over bar production cross section is measured to be sigma(p (t) over bar -> t (t) over bar +X)=6.6 +/- 0.9(stat+syst) +/- 0.4(lum) pb. This cross section is the most precise D0 measurement to date for t (t) over bar production and is in good agreement with standard model expectations.

Using b-tagging to enhance the supersymmetry reach of the CERN Large Hadron Collider

Assuming that supersymmetry is realized with parameters in the hyperbolic branch/focus point region of the minimal supergravity model, we show that by searching for multijet+E-T(miss) events with tagged b jets the reach of experiments at the LHC may be extended by as much as 20% from current projections. The reason for this is that gluino decays to third generation quarks are enhanced because the lightest neutralino has substantial Higgsino components. Although we were motivated to perform this analysis because the hyperbolic branch/focus point region is compatible with the recent determination of the relic density of cold dark matter, our considerations may well have a wider applicability since decays of gluinos to third generation quarks are favored in a wide variety of models.

Heavy-flavor tagging and the supersymmetry reach of the CERN Large Hadron Collider

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Double-Tagging Polymerase Chain Reaction with a Thiolated Primer and Electrochemical Genosensing based on Gold Nanocomposite Sensor for Food Safety

A novel material for electrochemical biosensing based on rigid conducting gold nanocomposite (nano-AuGEC) is presented. Islands of chemisorbing material (gold nanoparticles) surrounded by nonreactive, rigid, and conducting graphite epoxy composite are thus achieved to avoid the stringent control of surface coverage parameters required during immobilization of thiolated oligos in continuous gold surfaces. The spatial resolution of the immobilized thiolated DNA was easily controlled by merely varying the percentage of gold nanoparticles in the composition of the composite. As low as 9 fmol (60 pM) of synthetic DNA were detected in hybridization experiments when using a thiolated probe. Moreover, for the first time a double tagging PCR strategy was performed with a thiolated primer for the detection of Salmonella sp., one of the most important foodborne pathogens affecting food safety. Ibis assay was performed by double-labeling the amplicon during the PCR with a -DIG and -SH set of labeled primers. The thiolated end allows the immobilization of the amplicon on the nano-AuGEC electrode, while digoxigenin allows the electrochemical detection with the antiDIG-HRP reporter in the femtomole range. Rigid conducting gold nanocomposite represents a good material for the improved and oriented immobilization of biomolecules with excellent transducing properties for the construction of a wide range of electrochemical biosensors such as immunosensors, genosensors, and enzymosensors.

Extending SUSY reach at the CERN large hadron collider using b-tagging

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

An extended query-the-user tool for expert systems

An extended version of HIER, a query-the-user facility for expert systems is presented. HIER was developed to run over Prolog programs, and has been incorporated to systems that support the design of large and complex applications. The framework of the extended version is described,; as well as the major features of the implementation. An example is included to illustrate the use of the tool, involving the design of a specific database application.

User Manual for the Gender Equality Observatory for Latin America and the Caribbean

Includes bibliography