message perception within context-aware recommender systems

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Thus far implementation of Context Aware Recommender Systems have primarily focused on what to recommend by deriving results from patterns of behavior and environment to determine optimum product selection for recommendation. Our experiment demonstrates that a purchasers affective state also has an effect on their perception of information presented via a mobile device. We posit that the how and when to recommend are important considerations that have not been fully addressed when considering the display of recommendations. Together with user behaviors associated with purchasing traits, e.g. impulse buying, we explore the information processing styles of mental imagery and analytical processing; risk acceptance; involved user effort; and marketing techniques of positive and negative appeals. Results show that these different methods of presenting information to the purchaser will be successful in obtaining a positive user perception within different affective states. Together an understanding of these information presentation and processing techniques is used to build a representation of a purchasers perception that could be used in m-commerce systems.

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  • Message Perception within Context-Aware Recommender Systems

    Mark A. Hooper, Paul Sant

    University of Bedfordshire,

    Department of Computer Science and Technology,

    University Square, Luton, UK, LU1 3JU

    mark.hooper@beds.ac.uk, paul.sant@beds.ac.uk

    ABSTRACT

    Thus far implementation of Context Aware

    Recommender Systems have primarily focused

    on what to recommend by deriving results

    from patterns of behavior and environment to

    determine optimum product selection for

    recommendation. Our experiment

    demonstrates that a purchasers affective state

    also has an effect on their perception of

    information presented via a mobile device. We

    posit that the how and when to recommend

    are important considerations that have not been

    fully addressed when considering the display

    of recommendations. Together with user

    behaviors associated with purchasing traits,

    e.g. impulse buying, we explore the

    information processing styles of mental

    imagery and analytical processing; risk

    acceptance; involved user effort; and

    marketing techniques of positive and negative

    appeals. Results show that these different

    methods of presenting information to the

    purchaser will be successful in obtaining a

    positive user perception within different

    affective states. Together an understanding of

    these information presentation and processing

    techniques is used to build a representation of

    a purchasers perception that could be used in

    m-commerce systems.

    KEYWORDS

    Recommender systems, personalization, user

    interfaces, affective computing, context-aware

    1 INTRODUCTION

    Research is beginning establish an under-

    standing of user affective, social and phys-

    ical states and their relevance within con-

    text-aware systems [1]. However it is only

    now with the advance of smart-phone sen-

    sor technology that research can truly lev-

    erage this knowledge within the area of

    mobile recommender systems [2]. Though

    research into context-aware recommender

    systems is now showing positive results

    through multi-criteria evaluation of both

    user generated content and environmental

    context the utilisation of contextual infor-

    mation is still thus far limited.

    The focus of this paper is to demonstrate

    that user context can be used to understand

    how an individual reacts to information

    presentation styles via a mobile device. We

    posit that understanding user behavior

    within context is critical to fully realise the

    potential for recommender system results

    through message customisation, especially

    within the developing area of m-commerce

    environments. To support this we define

    and partly verify a framework for recom-

    mender system personalisation that intro-

    duces a new layer of system intelligence

    through the use of message customisation

    based on user contextual behavior.

    We discuss the theory that mood and emo-

    tions influence our selection of cognitive

    processing modes which in turn provide an

    Proceedings of the Third International Conference on E-Technologies and Business on the Web, Paris, France 2015

    ISBN: 978-1-941968-08-6 2015 SDIWC 59

  • insight into the level of message persua-

    sion. To develop our perception trait model

    we have developed hypotheses that focus

    on the relationships between affective

    states, cognitive capacity and behavior. It

    is generally agreed that positive moods re-

    sult in reduced capacity and therefore a

    favouring towards heuristic processing,

    whereas negative moods can facilitate

    more complex detail analysis [3].

    Different affective states can also influence

    different purchaser traits including, moti-

    vation [4], [5], impulse buying [6], com-

    pulsive buying [7], brand attitude and ad-

    claim recall [8], risk-taking and self-image

    [9]. Myers and Sar [8] provide valuable

    insight into how a pre-existing mood af-

    fects a users response to imagery inducing

    advertisements. We show that understand-

    ing these cognitive ability and behaviors

    should strengthen recommendation con-

    version when coupled with standard rec-

    ommender techniques.

    The rest of this paper is structured as fol-

    lows. We investigate a number of affect

    behavior relationships and their affect user

    perception in section 2. We then discuss

    our implementation of an Android applica-

    tion used to capture in the wild user per-

    ception of specific messaging styles, see

    section 3. In section 4 we present and ana-

    lyse our results and in section 5 we discuss

    limitations and opportunities for further

    research. Section 6 presents our final con-

    clusions.

    2 AFFECTIVE PURCHASING BEHAVIOR

    2.1 Consumer Behavior and Advertisement Techniques

    We hypothesise that understanding behav-

    ior towards a set of situational contexts can

    be utilised to optimise context-aware sys-

    tems by providing a reasoned reaction to-

    wards, not only the presented options, but

    also the method of presentation to the user.

    We stipulate that the addition of affective

    phenomena to the contextual picture is to

    also consider the users behavior as reac-

    tional and not just as an additional element

    of the context that influences preferences.

    We can thus potentially indicate behavior

    towards the advertisement content and the

    medium (i.e. text, image or video), as dis-

    cussed in the paper by [10]. This hypothe-

    sis leads us to consider behavior as a key

    concept to advance research within Con-

    text-Aware Recommender Systems (CARS),

    thus providing further potential for solu-

    tions to commercial recommender system

    that operate in complex environments tar-

    geting audiences with distinct catalogue

    product types numbering in their millions.

    Though an everyday occurrence the act of

    purchasing an item, whether in store or on-

    line, is a complex process that includes

    both environmental factors and consumer

    characteristics, marketing and environment

    stimuli, motivation and personality factors.

    There are many drivers that form an indi-

    viduals approach to the purchasing cycle.

    These complex emotional drivers include

    social potency and closeness, stress reac-

    tion, control, harm avoidance, traditional-

    ism, and absorption [6], enjoyment [11],

    and perception of risk [12]. These in turn

    influence purchasing behaviors of impulse

    [6], need for convenience and information

    search [13]. Personality traits generally

    form our emotional responses to situations

    so are key to understanding particular pur-

    chasing behaviors such as impulse buying

    [6]. As its name implies, impulse buying is

    an unplanned event that is made through a

    snap judgment process. By reviewing

    stimuli to form a quick, convenient repre-

    sentation of a situation it is often character-

    ized as a type of holistic processing that

    has advantages of speed, and reduced cog-

    Proceedings of the Third International Conference on E-Technologies and Business on the Web, Paris, France 2015

    ISBN: 978-1-941968-08-6 2015 SDIWC 60

  • nitive effort [14].

    A typical example of a holistic processing

    technique is mental imagery, this is an in-

    fluential tool for advertisers for enhancing

    brand attitudes while engaging consumers

    [8]. The process not only includes the mar-

    keting message cues of visual, auditory,

    tactile and emotional [15], but also draws

    upon the purchasers previous experience,

    memories and daydreams to fully form a

    visual image of the situation [13]. This

    contrasts with analytical processing which

    forms a comprehensive understanding of a

    situation through analysis of individual

    stimulus characteristics. Burroughs [14],

    determines that the style of processing is

    selected depending on the characteristics

    of task, stimulus and the individual con-

    sumer.

    An individuals purchase behavior can be

    predicted through their perception of risk,

    a consumer will avoid impulse buying

    when perception of risk is high [16].

    Bhatnagar et al. [12] report on relation-

    ships between risk, convenience and on-

    line shopping stating that certain product

    categories. Music and CDs, are not gener-

    ally considered risky because of the practi-

    calities of shopping on-line, i.e. reduction

    of costs and an increase in convenience to

    make purchases more likely [12]. Products

    with higher value are perceived as to have

    a higher risk, however they could be

    viewed as being more convenient to be

    purchased on-line if more involved [12], or

    are likely to require an evaluation process

    or other pre-purchase activity [13].

    Evaluation processes used in information

    search rely upon analytical information

    processing to produce a comprehensive

    understanding [14]. Information search vi

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