When and How to Advertise? An Empirical Study on Mobile Ad Response Based on Contextual Factors

Mobile technologies have enabled marketers to target consumers anywhere and anytime. However, as consumers react and respond differently depending on what situation they are in, there is an apparent need to determine when, where, and what kind of advertisement is most relevant to the consumer. Prior studies have found evidence on the influence of contextual factors such as location, time, and consumer behavior to the effectiveness of mobile ads but there has been little empirical evidence that examines contextual factors simultaneously. This paper proposes a holistic approach to examine the response of consumers when faced with two types of contextual factors (environmental and consumer contexts) through the lens of the Mobile Advertising Effectiveness Framework. Additionally, the influence of advertisement type (push- vs. pull-based) to these factors, along with the interactions among the variables are also investigated to determine which factors elicit the best response from consumers

Put Down that Phone and Talk to Me: Understanding the Roles of Mobile Phone Norm Adherence and Similarity in Relationships

This is the author's accepted manuscript. The published version will be available in 2014 from http://www.sagepub.com/journals/Journal202140.This study uses co-orientation theory to examine the impact of mobile phone use on relational quality across three co-present contexts. It investigates the relationship between perceived similarity, actual similarity, and understanding of mobile phone usage on relationship outcomes, and uses a new measure of mobile relational interference to assess how commitment, satisfaction, and liking are affected by perceptions of relational partners' mobile phone use. Contrary to popular belief, the results from this study of 69 dyads reveals that, at least within a sample of young Americans, failing to adhere to injunctive (i.e., societal) norms regarding mobile phone usage does not impact relational quality. Rather, results indicate that perceived adherence to participants' own internal standards —by both the participant, and the participant's relational partner— and perceived similarity between partners were more influential. Keywords: commitment; co-orientation theory; etiquette; liking; mobile phone; satisfactio

A Consolidated View of Context for Intelligent Systems

This paper's main objective is to consolidate the knowledge on context in the realm of intelligent systems, systems that are aware of their context and can adapt their behavior accordingly. We provide an overview and analysis of 36 context models that are heterogeneous and scattered throughout multiple fields of research. In our analysis, we identify five shared context categories: social context, location, time, physical context, and user context. In addition, we compare the context models with the context elements considered in the discourse on intelligent systems and find that the models do not properly represent the identified set of 3,741 unique context elements. As a result, we propose a consolidation of the findings from the 36 context models and the 3,741 unique context elements. The analysis reveals that there is a long tail of context categories that are considered only sporadically in context models. However, particularly these context elements in the long tail may be necessary for improving intelligent systems' context awareness

Understanding human-machine networks: A cross-disciplinary survey

© 2017 ACM. In the current hyperconnected era, modern Information and Communication Technology (ICT) systems form sophisticated networks where not only do people interact with other people, but also machines take an increasingly visible and participatory role. Such Human-Machine Networks (HMNs) are embedded in the daily lives of people, both for personal and professional use. They can have a significant impact by producing synergy and innovations. The challenge in designing successful HMNs is that they cannot be developed and implemented in the same manner as networks of machines nodes alone, or following a wholly human-centric view of the network. The problem requires an interdisciplinary approach. Here, we review current research of relevance to HMNs across many disciplines. Extending the previous theoretical concepts of sociotechnical systems, actor-network theory, cyber-physical-social systems, and social machines, we concentrate on the interactions among humans and between humans and machines. We identify eight types of HMNs: public-resource computing, crowdsourcing, web search engines, crowdsensing, online markets, social media, multiplayer online games and virtual worlds, and mass collaboration. We systematically select literature on each of these types and review it with a focus on implications for designing HMNs. Moreover, we discuss risks associated with HMNs and identify emerging design and development trends

Identifying Meaningful Places

Place identification refers to the process of analyzing sensor data in order to detect places, i.e., spatial areas that are linked with activities and associated with meanings. Place information can be used, e.g., to provide awareness cues in applications that support social interactions, to provide personalized and location-sensitive information to the user, and to support mobile user studies by providing cues about the situations the study participant has encountered. Regularities in human movement patterns make it possible to detect personally meaningful places by analyzing location traces of a user. This thesis focuses on providing system level support for place identification, as well as on algorithmic issues related to the place identification process. The move from location to place requires interactions between location sensing technologies (e.g., GPS or GSM positioning), algorithms that identify places from location data and applications and services that utilize place information. These interactions can be facilitated using a mobile platform, i.e., an application or framework that runs on a mobile phone. For the purposes of this thesis, mobile platforms automate data capture and processing and provide means for disseminating data to applications and other system components. The first contribution of the thesis is BeTelGeuse, a freely available, open source mobile platform that supports multiple runtime environments. The actual place identification process can be understood as a data analysis task where the goal is to analyze (location) measurements and to identify areas that are meaningful to the user. The second contribution of the thesis is the Dirichlet Process Clustering (DPCluster) algorithm, a novel place identification algorithm. The performance of the DPCluster algorithm is evaluated using twelve different datasets that have been collected by different users, at different locations and over different periods of time. As part of the evaluation we compare the DPCluster algorithm against other state-of-the-art place identification algorithms. The results indicate that the DPCluster algorithm provides improved generalization performance against spatial and temporal variations in location measurements.Paikkatietoiset sovellukset hyödyntävät paikkatietoa tarjotakseen hyödyllistä ja mielenkiintoista tietoa käyttäjille. Paikkatietoiset sovellukset pohjautuvat pääsääntöisesti koordinaattipohjaiseen paikkatietoon (esimerkiksi longitudi ja latitudi), vaikkakin ihmiset arkielämän tilanteissa kommunikoivat paikkatietoa käyttäen merkityksellisiä paikkanimiä (esimerkiksi kotona tai työpaikalla). Merkityksellisten paikkojen tunnistaminen hyödyntää säännönmukaisuuksia ihmisten arkielämässä tunnistaakseen paikkatiedosta alueita, jotka ovat käyttäjille henkilökohtaisesti mielenkiintoisia. Tunnistettuja merkityksellisiä paikkoja voidaan hyödyntää esimerkiksi tarjoamalla personoitua ja paikkariippuvaista tietoa käyttäjälle, tai mobiileissa sosiaalisen verkoston sovelluksissa tarjoamaan käyttäjän ystäville tietoa käyttäjän sen hetkisestä tilanteesta. Tietoa merkityksellisistä paikoista voidaan myös hyödyntää käyttäjätutkimuksessa tarkastelemaan missä käyttäjä on käyttänyt sovellusta. Väitöskirjatyössäni tarkastelen merkityksellisten paikkojen tunnistamiseen liittyviä haasteita järjestelmä- ja algoritmitasolla. Järjestelmätasolla merkityksellisten paikkojen hyödyntäminen vaatii yhteistoimintaa paikannusjärjestelmien (esimerkiksi GPS- tai GSM-pohjainen paikannus), merkityksellisten paikkojen tunnistamisalgoritmien ja sovellusten välillä. Eri järjestelmäkomponenttien välistä yhteistoimintaa voidaan helpottaa hyödyntämällä mobiilia sovellusalustaa, joka muun muassa tarjoaa toimintoja sensoridatan keräämisen sekä tiedon levittämisen helpottamiseksi. Väitöskirjan ensimmäisenä kontribuutiona esitellään BeTelGeuse, vapaasti saatavilla oleva vapaan lähdekoodin sovellusalusta, joka tukee useita eri käyttöjärjestelmiä ja sovellusympäristöjä. Merkityksellisten paikkojen tunnistamisprosessi voidaan tulkita tiedonlouhintaongelmana, jossa analysoidaan käyttäjän paikkatietoa ja pyritään tunnistamaan siitä alueita, jotka ovat käyttäjälle mielenkiintoisia. Väitöskirjan toisena kontribuutiona esitellään uusi merkityksellisten paikkojen tunnistamisalgoritmi, joka pohjautuu Dirichlet-prosessien sekoitemalleihin. Väitöskirjassa vertaillaan algoritmin yleistyvyyskykyä aikaisemmin esitettyihin merkityksellisten paikkojen tunnistamisalgoritmeihin. Tulokset osoittavat että uusi algoritmi pystyy paremmin tunnistamaan merkityksellisiä paikkoja ja yleistyy paremmin paikkatiedossa esiintyville variaatioille