This work deals with the collection of data from analog sensors, their storage and display using the Raspberry Pi microcomputer. In more detail it deals with selecting the appropriate analog-to-digital converter, selecting the appropriate storage and database server, web server and application to display the measured data.

The thesis deals with a survey of customer´s satisfaction with provided services. The theoretical part focuses on the explanation of different concepts, problems in marketing research and also on a questionnaire as a tool of collecting information. The practical part of the thesis analyses and presents the results from the questionnaire including recommendation and suggestions for improvements. They should be leading into increase in popularity of using public transport.

A data acquisition system was set up to measure gas temperatures and pressures at various points on a liquid-nitrogen-powered vehicle. The experiment was attempted to develop a data acquisition method for applications on engines that use liquid air as the fuel. Two thermocouples and a pressure transducer were connected using data acquisition instruments interfaced to a laptop computer to acquire data.

From the days of Antonio Meucci and Alexander Graham Bell when the telephone was invented, people have been looking for ways to communicate with each other through the use of technology. With the introduction of the Internet new possibilities were created to communicate with other persons around the world. As more and more individuals got access to the Internet more and more data got sent through the network. As with any platform where number of individuals keeps growing, business is to be made. Different companies offer different types of services, and many of these companies are niched in services where people in some way interact with each other. Social communities are some of the largest websites that are used and on these websites a lot of data is being shared. Pictures, life stories and interests are shared and this data is something that advertisement companies pay money to obtain. We can see this since a large part of revenues from social communities come from ad companies. Since these websites save data about individuals one could collect this data to sum up how an individual act online. In this thesis, we wanted to see if there was any interest in collecting this type of data to develop a business model where the data of individuals would be sold to a third party, and how individuals feel about this type data collection. To get an understanding of what type of data that can be collected, different companies that gather data were looked into. To get an understanding if this business model is something wanted recruiters of different IT companies were contacted for interviews. Focus groups and surveys were used to see how individuals close to their college graduation feel about data collection and the business model that is under construction. From the data collected, we saw that recruiters were not interested in a business model that gathered personal data, but rather professional data such as education, projects and other job related facts that can prove what the job applicant have done. And from the public we got the response that data collection of this sort is not something that is desirable. With the data collected we saw that our business model did not fit our targeted audience, but rather that a modified business model aimed on professional data rather than social data is something that could be developed. / Ända sedan den dagen telefonen skapades av Antonio Meucci och Alexander Graham Bell har människan letat efter nya sätt att kommunicera med varandra via teknologin som finns idag. Internet har introducerade nya sätt att dela olika typer av data världen över. Varje dag får fler och fler människor tillgång till internet det betyder då också att mer data skickas via nätet. Som med alla plattform där antalet individer växer skapas då nya affärsmodeller. Olika företag erbjuder olika typer av tjänster och många av dessa företag fördjupar sig inom kommunikationssektorn så att människor kan integrera med varandra. Socialmedia är bland de populäraste webbsidorna idag och här kan användarna dela data och information med varandra. Dessa data är viktiga för annonseringsföretagen då de vill rikta rätt reklam till användarna. Detta ser vi nu eftersom sociala mediernas största inkomstkälla kommer ifrån säljandet av data till annonsering bolagen. Man skulle kunna ta all data som dessa företag har sparat på sina användare för att sammanställa hur de använder tjänsten. I vår rapport ville vi se om det dann något intresse för att samla in denna typ av data för att utveckla vår affärsmodell där individens data och information säljes till en tredje part. Vi ville även undersöka hur användaren känner när det gäller datasamling på internet. För att få en uppfattning på vad för data som kan samlas in på internet har vi undersökt två företag för att se vad för data de tar. När det gäller vår affärsmodell har vi kontaktat och intervjuat rekryterare från olika företag för att se om vår affärsmodell är något som de behöver. Focused Groups och enkäter skickades ut till studenter som nästan har sin examen för att höra vad de har för åsikt är gällande datainsamling och vår affärsmodell. Vår undersökning visade att datainsamling inte var eftertraktad, men de ville däremot samla kompetens information istället. Information så som utbildning, projekt och arbetskarriär. Enkäten och Focused Groups visade även där att personlig datainsamling inte var något som de ville ha. Med de data vi fått under vår undersökning tydde det på att vår affärside inte var riktad mot rätt målgrupp, men en justering av vår affärsmodell i form av datainsamling av kompetens information var något de ville ha.

Vasaloppet is a cross country ski event which has been held in Sweden for about 50 years. Now more than 50,000 people of different ages participate in various cross country ski races during the Vasaloppet winter week in Dalarna County. This increasing demand needs good traffic and transportation planning to avoid congestion and provide safe, on time and environmentally friendly transportation for participants and visitors to the area. The key for a good event traffic planning is reliable and up-to-date traffic data which is not available for the Vasaloppet winter week. This study is an attempt to collect traffic data in order to find the movement patterns in the area and estimate origin-destination matrices for the main event of Vasaloppet week. Based on resources and time limitation it was decided to use a web-base d participants’ survey in order to collect traffic data. The link to the survey was sent to email address of a sample of 5000 participants. About 64% of the participants drove from their home town to the area and about 31 percent travelled by bus. Train and airplane have a very small share in travel mode to the area. Malungsälen, Mora and Älvdalen are three municipalities in Dalarna County with the highest share in accommodating participants. On the day of the race, bus and car have approximately the same share in travel mode with 45% and 47% respectively.

It has become an important part of business development to collect statistical data from online sources. Information about users and how they interact with an online source can help improving the user experience and increasing sales of products. Collecting data about users has many benefits for the business owner, but it also raises privacy issues since more and more information about users are spread over the internet. Tools that collect statistical data from online sources exists, but using such tools gives away the control over the data collected. If a business implements its own analytics system, it is easier to make it more privacy centric and the control over the data collected is kept.  This thesis examines what techniques that are most suitable for a system whose purpose is to collect, store, process, and present large-scale privacy centric data. Research about what technique to use for collecting data and how to keep track of unique users in a privacy centric way has been made as well as research about what database to use that can handle many write requests and store large scale data. A prototype was implemented based on the research, where JavaScript tagging is used to collect data from several online sources and cookies is used to keep track of unique users. Cassandra was chosen as database for the prototype because of its high scalability and speed at write requests. Two versions of the processing of raw data into statistical reports was implemented to be able to evaluate if the data should be preprocessed or if the reports could be created when the user asks for it.   To evaluate the techniques used in the prototype, load tests of the prototype was made where the results showed that a bottleneck was reached after 45 seconds on a workload of 600 write requests per second. The tests also showed that the prototype managed to keep its performance at a workload of 500 write requests per second for one hour, where it completed 1 799 953 requests. Latency tests when processing raw data into statistical reports was also made to evaluate if the data should be preprocessed or processed when the user asks for the report. The result showed that it took around 30 seconds to process 1 200 000 rows of data from the database which is too long for a user to wait for the report. When investigating what part of the processing that increased the latency the most it showed that it was the retrieval of data from the database that increased the latency. It took around 25 seconds to retrieve the data and only around 5 seconds to process it into statistical reports. The tests showed that Cassandra is slow when retrieving many rows of data, but fast when writing data which is more important in this prototype. / Det har blivit en viktig del av affärsutvecklingen hos företag att samla in statistiska data från deras online-källor. Information om användare och hur de interagerar med en online-källa kan hjälpa till att förbättra användarupplevelsen och öka försäljningen av produkter. Att samla in data om användare har många fördelar för företagsägaren, men det väcker också integritetsfrågor eftersom mer och mer information om användare sprids över internet. Det finns redan verktyg som kan samla in statistiska data från online-källor, men när sådana verktyg används förloras kontrollen över den insamlade informationen. Om ett företag implementerar sitt eget analyssystem är det lättare att göra det mer integritetscentrerat och kontrollen över den insamlade informationen behålls. Detta arbete undersöker vilka tekniker som är mest lämpliga för ett system vars syfte är att samla in, lagra, bearbeta och presentera storskalig integritetscentrerad information. Teorier har undersökts om vilken teknik som ska användas för att samla in data och hur man kan hålla koll på unika användare på ett integritetscentrerat sätt, samt om vilken databas som ska användas som kan hantera många skrivförfrågningar och lagra storskaligdata. En prototyp implementerades baserat på teorierna, där JavaScript-taggning används som metod för att samla in data från flera online källor och cookies används för att hålla reda på unika användare. Cassandra valdes som databas för prototypen på grund av dess höga skalbarhet och snabbhet vid skrivförfrågningar. Två versioner av bearbetning av rådata till statistiska rapporter implementerades för att kunna utvärdera om data skulle bearbetas i förhand eller om rapporterna kunde skapas när användaren ber om den. För att utvärdera teknikerna som användes i prototypen gjordes belastningstester av prototypen där resultaten visade att en flaskhals nåddes efter 45 sekunder på en arbetsbelastning på 600 skrivförfrågningar per sekund. Testerna visade också att prototypen lyckades hålla prestandan med en arbetsbelastning på 500 skrivförfrågningar per sekund i en timme, där den slutförde 1 799 953 förfrågningar. Latenstest vid bearbetning av rådata till statistiska rapporter gjordes också för att utvärdera om data ska förbehandlas eller bearbetas när användaren ber om rapporten. Resultatet visade att det tog cirka 30 sekunder att bearbeta 1 200 000 rader med data från databasen vilket är för lång tid för en användare att vänta på rapporten. Vid undersökningar om vilken del av bearbetningen som ökade latensen mest visade det att det var hämtningen av data från databasen som ökade latensen. Det tog cirka 25 sekunder att hämta data och endast cirka 5 sekunder att bearbeta dem till statistiska rapporter. Testerna visade att Cassandra är långsam när man hämtar ut många rader med data, men är snabb på att skriva data vilket är viktigare i denna prototyp.

This study is using an inductive explorative approach to investigate how micro-enterprises within the marketing consulting industry collect and use data for the purpose of increasing sales. A micro-enterprise is considered to be a company that employs no more than 10 people and/or whose annual turnover is no more than 2 million EUR. The research applies the concept of social selling and development of emergent technologies to understand the methods used by examined salespeople within the marketing agencies examined, and to answer the research question: How is customer data from social selling used among micro-enterprises within the marketing consulting industry to build and retain customer relationships? The following paper suggests that social media is used by the seller with the aim of identifying common grounds between buyer and seller, in order to create a personal bond that sets a strong foundation for continuing the relationship long-term. However, it also indicates that social selling activities are used in various ways and in combination with traditional data collection. Even though usage of customer data has been a heated debate over the years, the results of this study point to the fact that the concerns of collecting and utilizing data in regard to customer privacy, are limited among micro-enterprises within B2B-sector. Additionally, the study addresses advantages and disadvantages with the size of being a micro-enterprise related to the methods of social selling.

As Twitter launched with their unique way of limiting posts to only 140 characters the usage of link shorteners was brought forth. This was the only way to fit long URLs in tweets until Twitter solved this by providing their own integrated link shortener. This study investigates how links are used on Twitter. The study include both care fulldata collection including multiple APIs and analysis of the collected data providing new insight into this topic. It was found that a small set of internet domains account for a large part of the links found in posted tweets. This set of top occurring domains did not necessarily reflect the top domains typically on common internet top lists. When looking at link shorteners in posted tweets we found that “bit.ly” was the most common one. Due to our method of collecting data we had the possibility of looking up the amount of clicks “bit.ly” links had received. We compared the click data to the amount of retweets the tweets containing these links had received and this led to some interesting discoveries regarding the ratio between these two.

This dissertation studies economic issues in the digital economy with a specific focus on the economic aspects of how firms acquire and use consumer data. Chapter 1 empirically studies the drivers of digital attention in the space of social media applications. In order to do so I conduct an experiment where I comprehensively monitor how participants spend their time on digital services and use parental control software to shut off access to either their Instagram or YouTube. I characterize how participants substitute their time during and after the restrictions. I provide an interpretation of the substitution during the restriction period that allows me to conclude that relevant market definitions may be broader than those currently considered by regulatory authorities, but that the substantial diversion towards non-digital activities indicates significant market power from the perspective of consumers for Instagram and YouTube. I then use the results on substitution after the restriction period to motivate a discrete choice model of time usage with inertia and, using the estimates from this model, conduct merger assessments between social media applications. I find that the inertia channel is important for justifying blocking mergers, which I use to argue that currently debated policies aimed at curbing digital addiction are important not only just in their own right but also from an antitrust perspective and, in particular, as a potential policy tool for promoting competition in these markets. More broadly, my paper highlights the utility of product unavailability experiments for demand and merger analysis of digital goods. I thank Maayan Malter for working together with me on collecting the data for this paper. Chapter 2 then studies the next step in consumer data collection process – the extent to which a firm can collect a consumer’s data depends on privacy preferences and the set of available privacy tools. This chapter studies the impact of the General Data Protection Regulation on the ability of a data-intensive intermediary to collect and use consumer data. We find that the opt-in requirement of GDPR resulted in 12.5% drop in the intermediary-observed consumers, but the remaining consumers are trackable for a longer period of time. These findings are consistent with privacy-conscious consumers substituting away from less efficient privacy protection (e.g, cookie deletion) to explicit opt out—a process that would make opt-in consumers more predictable. Consistent with this hypothesis, the average value of the remaining consumers to advertisers has increased, offsetting some of the losses from consumer opt-outs. This chapter is jointly authored with Yeon-Koo Che and Tobias Salz. Chapter 3 and Chapter 4 make up the third portion of the dissertation that studies one of the most prominent uses of consumer data in the digital economy – recommendation systems. This chapter is a combination of several papers studying the economic impact of these systems. The first paper is a joint paper with Duarte Gonçalves which studies a model of strategic interaction between producers and a monopolist platform that employs a recommendation system. We characterize the consumer welfare implications of the platform’s entry into the production market. The platform’s entry induces the platform to bias recommendations to steer consumers towards its own goods, which leads to equilibrium investment adjustments by the producers and lower consumer welfare. Further, we find that a policy separating recommendation and production is not always welfare improving. Our results highlight the ability of integrated recommender systems to foreclose competition on online platforms. The second paper turns towards understanding how such systems impact consumer choices and is joint with Duarte Gonçalves and Shan Sikdar. In this paper we study a model of user decision-making in the context of recommender systems via numerical simulation. Our model provides an explanation for the findings of Nguyen et. al (2014), where, in environments where recommender systems are typically deployed, users consume increasingly similar items over time even without recommendation. We find that recommendation alleviates these natural filter-bubble effects, but that it also leads to an increase in homogeneity across users, resulting in a trade-off between homogenizing across-user consumption and diversifying within-user consumption. Finally, we discuss how our model highlights the importance of collecting data on user beliefs and their evolution over time both to design better recommendations and to further understand their impact.

This thesis investigates different aspects of children's computer game world. In the opening chapters are described available computer games for kids, which are split into groups. After that follows theoretical introduction to the problems of sociological research and advantages of using computer and Internet for it. On the basis of observation are introduced three types of applications for investigation of children's interest and abilities in computer games and parents opinions. Two of them were already used for investigation within this thesis. Thesis also presents results of realized survey.