Using visuals to explore the contextual aspects of user-product interactions

Experience underlies all kinds of human knowledge and it is dependent on context. People’s experience within a particular context-of-use determines how they interact with products. Methods employed in this research to elicit human experience have included the use of visuals. This paper describes two empirical studies that employed visual representation of concepts as a means to explore the experiential and contextual component of user- product interactions. One study employed visuals that the participants produced during the study. The other employed visuals that the researcher used as prompts during a focus group session. This paper demonstrates that using visuals in design research is valuable for exploring and understanding the contextual aspects of human experience and its influence on people’s concepts of product use.

General characteristics of anticipated user experience (AUX) with interactive products

Providing a positive user experience (UX) has become the key differentiator for products to win a competition in mature markets. To ensure that a product will support enjoyable experiences for its users, assessment of UX should be conducted early during the design and development process. However, most UX frameworks and evaluation techniques focus on understanding and assessing user’s experience with functional prototypes or existing products. This situation delays UX assessment until the late phases of product development which may result in costly design modifications and less desirable products. A qualitative study was conducted to investigate anticipated user experience (AUX) to address this issue. Twenty pairs of participants were asked to imagine an interactive product, draw their product concept, and anticipate their interactions and experiences with it. The data was analyzed to identify general characteristics of AUX. We found that while positive AUX was mostly related to an imagined/desired product, negative AUX was mainly associated with existing products. It was evident that the pragmatic quality of product was fundamental, and significantly influenced user’s anticipated experiences. Furthermore, the hedonic quality of product received more focus in positive than negative AUX. The results also showed that context, user profile, experiential knowledge, and anticipated emotion could be reflected in AUX. The understanding of AUX will help product designers to better foresee the users’ underlying needs and to focus on the most important aspects of their positive experiences, which in turn facilitates the designers to ensure pleasurable UX from the start of the design process.

Impact of urban traffic and climate change on water quality from road runoff

Urban traffic and climate change are two phenomena that have the potential to degrade urban water quality by influencing the build-up and wash-off of pollutants, respectively. However, limited knowledge has made it difficult to establish any link between pollutant buildup and wash-off under such dynamic conditions. In order to safeguard urban water quality, adaptive water quality mitigation measures are required. In this research, pollutant build-up and wash-off have been investigated from a dynamic point of view which incorporated the impacts of changed urban traffic as well as changes in the rainfall characteristics induced by climate change. The study has developed a dynamic object classification system and thereby, conceptualised the study of pollutant build-up and wash-off under future changes in urban traffic and rainfall characteristics. This study has also characterised the buildup and wash-off processes of traffic generated heavy metals, volatile, semi-volatile and non-volatile hydrocarbons under dynamic conditions which enables the development of adaptive mitigation measures for water quality. Additionally, predictive frameworks for the build-up and wash-off of some pollutants have also been developed.

Individual user behaviour modelling for effective web recommendation

With the growth of the Web, E-commerce activities are also becoming popular. Product recommendation is an effective way of marketing a product to potential customers. Based on a user’s previous searches, most recommendation methods employ two dimensional models to find relevant items. Such items are then recommended to a user. Further too many irrelevant recommendations worsen the information overload problem for a user. This happens because such models based on vectors and matrices are unable to find the latent relationships that exist between users and searches. Identifying user behaviour is a complex process, and usually involves comparing searches made by him. In most of the cases traditional vector and matrix based methods are used to find prominent features as searched by a user. In this research we employ tensors to find relevant features as searched by users. Such relevant features are then used for making recommendations. Evaluation on real datasets show the effectiveness of such recommendations over vector and matrix based methods.

Young, inexperienced and on the road: Do novice drivers comply with road rules?

Young novice drivers are at considerable risk of injury and fatality, particularly when they first drive independently. Graduated Driver Licensing (GDL) has been introduced in numerous jurisdictions to allow more driving experience in conditions of reduced risk and increasing driving privileges over a longer duration. Queensland, Australia, enhanced GDL July 2007. Learners must record 100 hours in a logbook (10 hours at night) over 1 year, no mobile handsfree/loudspeaker by driver or any passenger. Provisional 1 (P1) drivers must not carry 2 or more peer passengers 11pm - 5am, no mobile handsfree/loudspeaker by any passenger. Self-reported compliance with new GDL and general road rules has not been examined.

Evaluating automatic road detection across a large aerial imagery collection

The automated extraction of roads from aerial imagery can be of value for tasks including mapping, surveillance and change detection. Unfortunately, there are no public databases or standard evaluation protocols for evaluating these techniques. Many techniques are further hindered by a reliance on manual initialisation, making large scale application of the techniques impractical. In this paper, we present a public database and evaluation protocol for the evaluation of road extraction algorithms, and propose an improved automatic seed finding technique to initialise road extraction, based on a combination of geometric and colour features.

A review of road traffic noise indicators and their correlation with the LA10(18hour)

This paper outlines a study to determine the correlation between the LA10(18hour) and other road traffic noise indicators. It is based on a database comprising of 404 measurement locations including 947 individual days of valid noise measurements across numerous circumstances taken between November 2001 and November 2007. This paper firstly discusses the need and constraints on the indicators and their nature of matching a suitable indicator to the various road traffic noise dynamical characteristics. The paper then presents a statistical analysis of the road traffic noise monitoring data, correlating various indicators with the LA10(18hour) statistical indicator and provides a comprehensive table of linear correlations. There is an extended analysis on relationships across the night time period. The paper concludes with a discussion on the findings.

Classifying the user intent of web queries using k-means clustering

Purpose: Web search engines are frequently used by people to locate information on the Internet. However, not all queries have an informational goal. Instead of information, some people may be looking for specific web sites or may wish to conduct transactions with web services. This paper aims to focus on automatically classifying the different user intents behind web queries. Design/methodology/approach: For the research reported in this paper, 130,000 web search engine queries are categorized as informational, navigational, or transactional using a k-means clustering approach based on a variety of query traits. Findings: The research findings show that more than 75 percent of web queries (clustered into eight classifications) are informational in nature, with about 12 percent each for navigational and transactional. Results also show that web queries fall into eight clusters, six primarily informational, and one each of primarily transactional and navigational. Research limitations/implications: This study provides an important contribution to web search literature because it provides information about the goals of searchers and a method for automatically classifying the intents of the user queries. Automatic classification of user intent can lead to improved web search engines by tailoring results to specific user needs. Practical implications: The paper discusses how web search engines can use automatically classified user queries to provide more targeted and relevant results in web searching by implementing a real time classification method as presented in this research. Originality/value: This research investigates a new application of a method for automatically classifying the intent of user queries. There has been limited research to date on automatically classifying the user intent of web queries, even though the pay-off for web search engines can be quite beneficial. © Emerald Group Publishing Limited.

Loop closure detection on a suburban road network using a continuous appearance-based trajectory

This paper presents a novel technique for performing SLAM along a continuous trajectory of appearance. Derived from components of FastSLAM and FAB-MAP, the new system dubbed Continuous Appearance-based Trajectory SLAM (CAT-SLAM) augments appearancebased place recognition with particle-filter based ‘pose filtering’ within a probabilistic framework, without calculating global feature geometry or performing 3D map construction. For loop closure detection CAT-SLAM updates in constant time regardless of map size. We evaluate the effectiveness of CAT-SLAM on a 16km outdoor road network and determine its loop closure performance relative to FAB-MAP. CAT-SLAM recognizes 3 times the number of loop closures for the case where no false positives occur, demonstrating its potential use for robust loop closure detection in large environments.

An ontology-based mining approach for user search intent discovery

Discovering proper search intents is a vi- tal process to return desired results. It is constantly a hot research topic regarding information retrieval in recent years. Existing methods are mainly limited by utilizing context-based mining, query expansion, and user profiling techniques, which are still suffering from the issue of ambiguity in search queries. In this pa- per, we introduce a novel ontology-based approach in terms of a world knowledge base in order to construct personalized ontologies for identifying adequate con- cept levels for matching user search intents. An iter- ative mining algorithm is designed for evaluating po- tential intents level by level until meeting the best re- sult. The propose-to-attempt approach is evaluated in a large volume RCV1 data set, and experimental results indicate a distinct improvement on top precision after compared with baseline models.

Acoustic hazard detection for pedestrians with obscured hearing

Pedestrians’ use of mp3 players or mobile phones can pose the risk of being hit by motor vehicles. We present an approach for detecting a crash risk level using the computing power and the microphone of mobile devices that can be used to alert the user in advance of an approaching vehicle so as to avoid a crash. A single feature extractor classifier is not usually able to deal with the diversity of risky acoustic scenarios. In this paper, we address the problem of detection of vehicles approaching a pedestrian by a novel, simple, non resource intensive acoustic method. The method uses a set of existing statistical tools to mine signal features. Audio features are adaptively thresholded for relevance and classified with a three component heuristic. The resulting Acoustic Hazard Detection (AHD) system has a very low false positive detection rate. The results of this study could help mobile device manufacturers to embed the presented features into future potable devices and contribute to road safety.

User behaviour modelling in a multi-dimensional environment for personalization and recommendation

Handling information overload online, from the user's point of view is a big challenge, especially when the number of websites is growing rapidly due to growth in e-commerce and other related activities. Personalization based on user needs is the key to solving the problem of information overload. Personalization methods help in identifying relevant information, which may be liked by a user. User profile and object profile are the important elements of a personalization system. When creating user and object profiles, most of the existing methods adopt two-dimensional similarity methods based on vector or matrix models in order to find inter-user and inter-object similarity. Moreover, for recommending similar objects to users, personalization systems use the users-users, items-items and users-items similarity measures. In most cases similarity measures such as Euclidian, Manhattan, cosine and many others based on vector or matrix methods are used to find the similarities. Web logs are high-dimensional datasets, consisting of multiple users, multiple searches with many attributes to each. Two-dimensional data analysis methods may often overlook latent relationships that may exist between users and items. In contrast to other studies, this thesis utilises tensors, the high-dimensional data models, to build user and object profiles and to find the inter-relationships between users-users and users-items. To create an improved personalized Web system, this thesis proposes to build three types of profiles: individual user, group users and object profiles utilising decomposition factors of tensor data models. A hybrid recommendation approach utilising group profiles (forming the basis of a collaborative filtering method) and object profiles (forming the basis of a content-based method) in conjunction with individual user profiles (forming the basis of a model based approach) is proposed for making effective recommendations. A tensor-based clustering method is proposed that utilises the outcomes of popular tensor decomposition techniques such as PARAFAC, Tucker and HOSVD to group similar instances. An individual user profile, showing the user's highest interest, is represented by the top dimension values, extracted from the component matrix obtained after tensor decomposition. A group profile, showing similar users and their highest interest, is built by clustering similar users based on tensor decomposed values. A group profile is represented by the top association rules (containing various unique object combinations) that are derived from the searches made by the users of the cluster. An object profile is created to represent similar objects clustered on the basis of their similarity of features. Depending on the category of a user (known, anonymous or frequent visitor to the website), any of the profiles or their combinations is used for making personalized recommendations. A ranking algorithm is also proposed that utilizes the personalized information to order and rank the recommendations. The proposed methodology is evaluated on data collected from a real life car website. Empirical analysis confirms the effectiveness of recommendations made by the proposed approach over other collaborative filtering and content-based recommendation approaches based on two-dimensional data analysis methods.

Designing and evaluating mobile multimedia user experiences in public urban places : Making sense of the field

The majority of the world’s population now lives in cities (United Nations, 2008) resulting in an urban densification requiring people to live in closer proximity and share urban infrastructure such as streets, public transport, and parks within cities. However, “physical closeness does not mean social closeness” (Wellman, 2001, p. 234). Whereas it is a common practice to greet and chat with people you cross paths with in smaller villages, urban life is mainly anonymous and does not automatically come with a sense of community per se. Wellman (2001, p. 228) defines community “as networks of interpersonal ties that provide sociability, support, information, a sense of belonging and social identity.” While on the move or during leisure time, urban dwellers use their interactive information communication technology (ICT) devices to connect to their spatially distributed community while in an anonymous space. Putnam (1995) argues that available technology privatises and individualises the leisure time of urban dwellers. Furthermore, ICT is sometimes used to build a “cocoon” while in public to avoid direct contact with collocated people (Mainwaring et al., 2005; Bassoli et al., 2007; Crawford, 2008). Instead of using ICT devices to seclude oneself from the surrounding urban environment and the collocated people within, such devices could also be utilised to engage urban dwellers more with the urban environment and the urban dwellers within. Urban sociologists found that “what attracts people most, it would appear, is other people” (Whyte, 1980, p. 19) and “people and human activity are the greatest object of attention and interest” (Gehl, 1987, p. 31). On the other hand, sociologist Erving Goffman describes the concept of civil inattention, acknowledging strangers’ presence while in public but not interacting with them (Goffman, 1966). With this in mind, it appears that there is a contradiction between how people are using ICT in urban public places and for what reasons and how people use public urban places and how they behave and react to other collocated people. On the other hand there is an opportunity to employ ICT to create and influence experiences of people collocated in public urban places. The widespread use of location aware mobile devices equipped with Internet access is creating networked localities, a digital layer of geo-coded information on top of the physical world (Gordon & de Souza e Silva, 2011). Foursquare.com is an example of a location based 118 Mobile Multimedia – User and Technology Perspectives social network (LBSN) that enables urban dwellers to virtually check-in into places at which they are physically present in an urban space. Users compete over ‘mayorships’ of places with Foursquare friends as well as strangers and can share recommendations about the space. The research field of Urban Informatics is interested in these kinds of digital urban multimedia augmentations and how such augmentations, mediated through technology, can create or influence the UX of public urban places. “Urban informatics is the study, design, and practice of urban experiences across different urban contexts that are created by new opportunities of real-time, ubiquitous technology and the augmentation that mediates the physical and digital layers of people networks and urban infrastructures” (Foth et al., 2011, p. 4). One possibility to augment the urban space is to enable citizens to digitally interact with spaces and urban dwellers collocated in the past, present, and future. “Adding digital layer to the existing physical and social layers could facilitate new forms of interaction that reshape urban life” (Kjeldskov & Paay, 2006, p. 60). This methodological chapter investigates how the design of UX through such digital placebased mobile multimedia augmentations can be guided and evaluated. First, we describe three different applications that aim to create and influence the urban UX through mobile mediated interactions. Based on a review of literature, we describe how our integrated framework for designing and evaluating urban informatics experiences has been constructed. We conclude the chapter with a reflective discussion on the proposed framework.

The rise of co-creative consumers : user experience sharing behaviour in online communities

This thesis examines consumer initiated value co-creation behaviour in the context of convergent mobile online services using a Service-Dominant logic (SD logic) theoretical framework. It focuses on non-reciprocal marketing phenomena such as open innovation and user generated content whereby new viable business models are derived and consumer roles and community become essential to the success of business. Attention to customers. roles and personalised experiences in value co-creation has been recognised in the literature (e.g., Prahalad & Ramaswamy, 2000; Prahalad, 2004; Prahalad & Ramaswamy, 2004). Similarly, in a subsequent iteration of their 2004 version of the foundations of SD logic, Vargo and Lusch (2006) replaced the concept of value co-production with value co-creation and suggested that a value co-creation mindset is essential to underpin the firm-customer value creation relationship. Much of this focus, however, has been limited to firm initiated value co-creation (e.g., B2B or B2C), while consumer initiated value creation, particularly consumer-to-consumer (C2C) has received little attention in the SD logic literature. While it is recognised that not every consumer wishes to make the effort to engage extensively in co-creation processes (MacDonald & Uncles, 2009), some consumers may not be satisfied with a standard product, instead they engage in the effort required for personalisation that potentially leads to greater value for themselves, and which may benefit not only the firm, but other consumers as well. Literature suggests that there are consumers who do, and as a result initiate such behaviour and expend effort to engage in co-creation activity (e.g., Gruen, Osmonbekov and Czaplewski, 2006; 2007 MacDonald & Uncles, 2009). In terms of consumers. engagement in value proposition (co-production) and value actualisation (co-creation), SD logic (Vargo & Lusch, 2004, 2008) provides a new lens that enables marketing scholars to transcend existing marketing theory and facilitates marketing practitioners to initiate service centric and value co-creation oriented marketing practices. Although the active role of the consumer is acknowledged in the SD logic oriented literature, we know little about how and why consumers participate in a value co-creation process (Payne, Storbacka, & Frow, 2008). Literature suggests that researchers should focus on areas such as C2C interaction (Gummesson 2007; Nicholls 2010) and consumer experience sharing and co-creation (Belk 2009; Prahalad & Ramaswamy 2004). In particular, this thesis seeks to better understand consumer initiated value co-creation, which is aligned with the notion that consumers can be resource integrators (Baron & Harris, 2008) and more. The reason for this focus is that consumers today are more empowered in both online and offline contexts (Füller, Mühlbacher, Matzler, & Jawecki, 2009; Sweeney, 2007). Active consumers take initiatives to engage and co-create solutions with other active actors in the market for their betterment of life (Ballantyne & Varey, 2006; Grönroos & Ravald, 2009). In terms of the organisation of the thesis, this thesis first takes a „zoom-out. (Vargo & Lusch, 2011) approach and develops the Experience Co-Creation (ECo) framework that is aligned with balanced centricity (Gummesson, 2008) and Actor-to-Actor worldview (Vargo & Lusch, 2011). This ECo framework is based on an extended „SD logic friendly lexicon. (Lusch & Vargo, 2006): value initiation and value initiator, value-in-experience, betterment centricity and betterment outcomes, and experience co-creation contexts derived from five gaps identified from the SD logic literature review. The framework is also designed to accommodate broader marketing phenomena (i.e., both reciprocal and non-reciprocal marketing phenomena). After zooming out and establishing the ECo framework, the thesis takes a zoom-in approach and places attention back on the value co-creation process. Owing to the scope of the current research, this thesis focuses specifically on non-reciprocal value co-creation phenomena initiated by consumers in online communities. Two emergent concepts: User Experience Sharing (UES) and Co-Creative Consumers are proposed grounded in the ECo framework. Together, these two theorised concepts shed light on the following two propositions: (1) User Experience Sharing derives value-in-experience as consumers make initiative efforts to participate in value co-creation, and (2) Co-Creative Consumers are value initiators who perform UES. Three research questions were identified underpinning the scope of this research: RQ1: What factors influence consumers to exhibit User Experience Sharing behaviour? RQ2: Why do Co-Creative Consumers participate in User Experience Sharing as part of value co-creation behaviour? RQ3: What are the characteristics of Co-Creative Consumers? To answer these research questions, two theoretical models were developed: the User Experience Sharing Behaviour Model (UESBM) grounded in the Theory of Planned Behaviour framework, and the Co-Creative Consumer Motivation Model (CCMM) grounded in the Motivation, Opportunity, Ability framework. The models use SD logic consistent constructs and draw upon multiple streams of literature including consumer education, consumer psychology and consumer behaviour, and organisational psychology and organisational behaviour. These constructs include User Experience Sharing with Other Consumers (UESC), User Experience Sharing with Firms (UESF), Enjoyment in Helping Others (EIHO), Consumer Empowerment (EMP), Consumer Competence (COMP), and Intention to Engage in User Experience Sharing (INT), Attitudes toward User Experience Sharing (ATT) and Subjective Norm (SN) in the UESBM, and User Experience Sharing (UES), Consumer Citizenship (CIT), Relating Needs of Self (RELS) and Relating Needs of Others (RELO), Newness (NEW), Mavenism (MAV), Use Innovativeness (UI), Personal Initiative (PIN) and Communality (COMU) in the CCMM. Many of these constructs are relatively new to marketing and require further empirical evidence for support. Two studies were conducted to underpin the corresponding research questions. Study One was conducted to calibrate and re-specify the proposed models. Study Two was a replica study to confirm the proposed models. In Study One, data were collected from a PC DIY online community. In Study Two, a majority of data were collected from Apple product online communities. The data were examined using structural equation modelling and cluster analysis. Considering the nature of the forums, the Study One data is considered to reflect some characteristics of Prosumers and the Study Two data is considered to reflect some characteristics of Innovators. The results drawn from two independent samples (N = 326 and N = 294) provide empirical support for the overall structure theorised in the research models. The results in both models show that Enjoyment in Helping Others and Consumer Competence in the UESBM, and Consumer Citizenship and Relating Needs in CCMM have significant impacts on UES. The consistent results appeared in both Study One and Study Two. The results also support the conceptualisation of Co-Creative Consumers and indicate Co-Creative Consumers are individuals who are able to relate the needs of themselves and others and feel a responsibility to share their valuable personal experiences. In general, the results shed light on "How and why consumers voluntarily participate in the value co-creation process?. The findings provide evidence to conceptualise User Experience Sharing behaviour as well as the Co-Creative Consumer using the lens of SD logic. This research is a pioneering study that incorporates and empirically tests SD logic consistent constructs to examine a particular area of the logic – that is consumer initiated value co-creation behaviour. This thesis also informs practitioners about how to facilitate and understand factors that engage with either firm or consumer initiated online communities.