Can location-based mobile marketing enhance the customer experience and increase customer satisfaction and loyalty?

This study intends to explore the impact of customer experience on customer satisfaction and loyalty by trying to understand how location-based mobile marketing might enhance the customer experience. Primary data was collected from 201 smartphone users in 24 countries. Results have indicated that targeted location-based marketing positively influences customers’ experiences. Besides, the analysis has also shown a favorable impact on customers’ satisfaction and self-perceived loyalty. This suggests that location-based mobile marketing has the potential to positively add value to a customer’s experience and should therefore be considered an important tool in marketing communications.

Evaluation of the welfare impact of regulating mobile termination rates in Portugal

Following the European Commission’s 2009 Recommendation on the Regulatory Treatment of Fixed and Mobile Termination Rates in the EU, the Portuguese regulatory authority (ANACOM) decided to reduce termination prices in mobile networks to their long-run incremental cost (LRIC). Nevertheless, no serious quantitative assessment of the potential effects of this decision was carried out. In this paper, we adapt and calibrate the Harbord and Hoernig (2014) model of the UK mobile telephony market to the Portuguese reality, and simulate the likely impact on consumer surplus, profits and welfare of four different regulatory approaches: pure LRIC, reciprocal termination charges with fixed networks, “bill & keep”, and asymmetric termination rates. Our results show that reducing MTRs does increase social welfare, profits and consumer surplus in the fixed market, but mobile subscribers are seriously harmed by this decision.

How to design and develop There App: A mobile app focused on live video streaming, promoting new social interactions

This work project aims to demonstrate how to design and develop an innovative concept of video streaming app. The project combines technology push and market pull theories into developing a product that is more suitable for the customer needs, with the particularity that there is no other way of seeing any place in the world, live and ondemand. An analysis on the bigger influencers in terms of design-thinking and new product development, as Tim Brown or Paul Trott, lead to a better understanding on how There App should evolve, keeping in mind the customer desires and technical features.

Impact of mobile app user acquisition on managerial decisions: Evidence from empirical experiment

In this research we conducted a mixed research, using qualitative and quantitative analysis to study the relationship and impact between mobile advertisement and mobile app user acquisition and the conclusions companies can derive from it. Data was gathered from management of mobile advertisement campaigns of a portfolio of three different mobile apps. We found that a number of implications can be extracted from this intersection, namely to product development, internationalisation and management of marketing budget. We propose further research on alternative app users sources, impact of revenue on apps and exploitation of product segments: wearable technology and Internet of Things.

A business plan for a new mobile application to the consumer foodservice industry

The Portuguese consumer foodservice industry is experiencing a boost in technology adoption, driven by significant changes in consumer behavior and business dynamics, due to mobile increasing penetration. Accordingly, the present work project consists on developing a business plan for meeting an identified opportunity in the technological foodservice landscape. Therefore, this report is divided into three sections, each of which addressing different objectives: (A) External Environment, providing key external insights that support the opportunity; (B) Strategy Formulation, establishing a strategic direction; and (C) Action Plan, determining an implementation plan for starting the business

Mobile E-commerce business model – A value web based approach to business models in mobile gaming industry

Tämän tutkimuksen tavoitteena oli tutkia langattomien internet palveluiden arvoverkkoa ja liiketoimintamalleja. Tutkimus oli luonteeltaan kvalitatiivinen ja siinä käytettiin strategiana konstruktiivista case-tutkimusta. Esimerkkipalveluna oli Treasure Hunters matkapuhelinpeli. Tutkimus muodostui teoreettisesta ja empiirisestä osasta. Teoriaosassa liitettiin innovaatio, liiketoimintamallit ja arvoverkko käsitteellisesti toisiinsa, sekä luotiin perusta liiketoimintamallien kehittämiselle. Empiirisessä osassa keskityttiin ensin liiketoimintamallien luomiseen kehitettyjen innovaatioiden pohjalta. Lopuksi pyrittiin määrittämään arvoverkko palvelun toteuttamiseksi. Tutkimusmenetelminä käytettiin innovaatiosessiota, haastatteluja ja lomakekyselyä. Tulosten pohjalta muodostettiin useita liiketoimintakonsepteja sekä kuvaus arvoverkon perusmallista langattomille peleille. Loppupäätelmänä todettiin että langattomat palvelut vaativat toteutuakseen useista toimijoista koostuvan arvoverkon.

Privacy-friendly Business Models for Location-Based Mobile Services

This paper presents a theoretical model to analyze the privacy issues around location based mobile business models. We report the results of an exploratory field experiment in Switzerland that assessed the factors driving user payoff in mobile business. We found that (1) the personal data disclosed has a negative effect on user payoff; (2) the amount of personalization available has a direct and positive effect, as well as a moderating effect on user payoff; (3) the amount of control over user's personal data has a direct and positive effect, as well as a moderating effect on user payoff. The results suggest that privacy protection could be the main value proposition in the B2C mobile market. From our theoretical model we derive a set of guidelines to design a privacy-friendly business model pattern for third-party services. We discuss four examples to show the mobile platform can play a key role in the implementation of these new business models.

Development of a Business Model that Supports Mobile Value-Added Services Market Creation in Emerging Countries

Tutkielman tavoitteena on luoda liiketoimintamalli, joka tukee langattomien matkaviestintäpalveluiden markkinoiden luomista kehittyvillä markkinoilla. Teoreettinen osa tarkastelee langattomien matkaviestintäpalveluiden liiketoimintamallin kehittämisen tärkeimpiä elementtejä CIS maissa. Teoreettisen kappaleen tuloksena saadaan puitteet, jonka avulla liiketoimintamalli matkaviestintäpalveluille voidaan kehittää. Tutkielman empiirinen osa on toteutettu case tutkimuksena, jonka tavoitteena on ollut langattomien matkaviestintäpalvelujen markkinoiden luominen CIS maissa. Pääasiallinen empiirisen tiedon lähde on ollut teemahaastattelut. Tuloksena saatuja empiirisen osan tietoja verrataan teoriakappaleen vastaaviin tuloksiin Tulokset osoittavat, että radikaalin korkean teknologian innovaation markkinoiden luominen on hidas prosessi, joka vaatii kärsivällisyyttä yritykseltä. Markkinoiden, teknologian ja strategian epävarmuustekijät tuovat epävarmuutta kehittyvälle toimialalle ja markkinoille, joka vaikeuttaa liiketoimintamallin kehittämistä. Tärkein tekijä on palvelujen markkinointi ennemmin kuin teknologian. Avain kyvykkyys markkinoiden luomisessa on oppiminen, ei tietäminen.

Mobile Protocol Stack Simulator

Nykypäivän maailma tukeutuu verkkoihin. Tietokoneverkot ja langattomat puhelimet ovat jo varsin tavallisia suurelle joukolle ihmisiä. Uusi verkkotyyppi on ilmestynyt edelleen helpottamaan ihmisten verkottunutta elämää. Ad hoc –verkot mahdollistavat joustavan verkonmuodostuksen langattomien päätelaitteiden välille ilman olemassa olevaa infrastruktuuria. Diplomityö esittelee uuden simulaatiotyökalun langattomien ad hoc –verkkojen simulointiin protokollatasolla. Se esittelee myös kyseisten verkkojen taustalla olevat periaatteet ja teoriat. Lähemmin tutkitaan OSI-mallin linkkikerroksen kaistanjakoprotokollia ad hoc –verkoissa sekä vastaavan toteutusta simulaattorissa. Lisäksi esitellään joukko simulaatioajoja esimerkiksi simulaattorin toiminnasta ja mahdollisista käyttökohteista.

Evaluation of Machine Learning Classifiers for Mobile Network Intrusion Detection Systems

Mobile malwares are increasing with the growing number of Mobile users. Mobile malwares can perform several operations which lead to cybersecurity threats such as, stealing financial or personal information, installing malicious applications, sending premium SMS, creating backdoors, keylogging and crypto-ransomware attacks. Knowing the fact that there are many illegitimate Applications available on the App stores, most of the mobile users remain careless about the security of their Mobile devices and become the potential victim of these threats. Previous studies have shown that not every antivirus is capable of detecting all the threats; due to the fact that Mobile malwares use advance techniques to avoid detection. A Network-based IDS at the operator side will bring an extra layer of security to the subscribers and can detect many advanced threats by analyzing their traffic patterns. Machine Learning(ML) will provide the ability to these systems to detect unknown threats for which signatures are not yet known. This research is focused on the evaluation of Machine Learning classifiers in Network-based Intrusion detection systems for Mobile Networks. In this study, different techniques of Network-based intrusion detection with their advantages, disadvantages and state of the art in Hybrid solutions are discussed. Finally, a ML based NIDS is proposed which will work as a subsystem, to Network-based IDS deployed by Mobile Operators, that can help in detecting unknown threats and reducing false positives. In this research, several ML classifiers were implemented and evaluated. This study is focused on Android-based malwares, as Android is the most popular OS among users, hence most targeted by cyber criminals. Supervised ML algorithms based classifiers were built using the dataset which contained the labeled instances of relevant features. These features were extracted from the traffic generated by samples of several malware families and benign applications. These classifiers were able to detect malicious traffic patterns with the TPR upto 99.6% during Cross-validation test. Also, several experiments were conducted to detect unknown malware traffic and to detect false positives. These classifiers were able to detect unknown threats with the Accuracy of 97.5%. These classifiers could be integrated with current NIDS', which use signatures, statistical or knowledge-based techniques to detect malicious traffic. Technique to integrate the output from ML classifier with traditional NIDS is discussed and proposed for future work.

Memoria informativa per i marchesi di Colle, Petriolo e Petrella, relativamente alla immunità ed esenzione dei medesimi contro i rappresentanti Cortonesi...

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