The impact of brand and product placements in electronic games

In an environment where it has become increasingly difficult to attract consumer attention, marketers have begun to explore alternative forms of marketing communication. One such form that has emerged is product placement, which has more recently appeared in electronic games. Given changes in media consumption and the growth of the games industry, it is not surprising that games are being exploited as a medium for promotional content. Other market developments are also facilitating and encouraging their use, in terms of both the insertion of brand messages into video games and the creation of brand-centred environments, labelled ‘advergames’. However, while there is much speculation concerning the beneficial outcomes for marketers, there remains a lack of academic work in this area and little empirical evidence of the actual effects of this form of promotion on game players. Only a handful of studies are evident in the literature, which have explored the influence of game placements on consumers. The majority have studied their effect on brand awareness, largely demonstrating that players can recall placed brands. Further, most research conducted to date has focused on computer and online games, but consoles represent the dominant platform for play (Taub, 2004). Finally, advergames have largely been neglected, particularly those in a console format. Widening the gap in the literature is the fact that insufficient academic attention has been given to product placement as a marketing communication strategy overall, and to games in general. The unique nature of the strategy also makes it difficult to apply existing literature to this context. To address a significant need for information in both the academic and business domains, the current research investigates the effects of brand and product placements in video games and advergames on consumer attitude to the brand and corporate image. It was conducted in two stages. Stage one represents a pilot study. It explored the effects of use simulated and peripheral placements in video games on players’ and observers’ attitudinal responses, and whether these are influenced by involvement with a product category or skill level in the game. The ability of gamers to recall placed brands was also examined. A laboratory experiment was employed with a small sample of sixty adult subjects drawn from an Australian east-coast university, some of who were exposed to a console video game on a television set. The major finding of study one is that placements in a video game have no effect on gamers’ attitudes, but they are recalled. For stage two of the research, a field experiment was conducted with a large, random sample of 350 student respondents to investigate the effects on players of brand and product placements in handheld video games and advergames. The constructs of brand attitude and corporate image were again tested, along with several potential confounds. Consistent with the pilot, the results demonstrate that product placement in electronic games has no effect on players’ brand attitudes or corporate image, even when allowing for their involvement with the product category, skill level in the game, or skill level in relation to the medium. Age and gender also have no impact. However, the more interactive a player perceives the game to be, the higher their attitude to the placed brand and corporate image of the brand manufacturer. In other words, when controlling for perceived interactivity, players experienced more favourable attitudes, but the effect was so weak it probably lacks practical significance. It is suggested that this result can be explained by the existence of excitation transfer, rather than any processing of placed brands. The current research provides strong, empirical evidence that brand and product placements in games do not produce strong attitudinal responses. It appears that the nature of the game medium, game playing experience and product placement impose constraints on gamer motivation, opportunity and ability to process these messages, thereby precluding their impact on attitude to the brand and corporate image. Since this is the first study to investigate the ability of video game and advergame placements to facilitate these deeper consumer responses, further research across different contexts is warranted. Nevertheless, the findings have important theoretical and managerial implications. This investigation makes a number of valuable contributions. First, it is relevant to current marketing practice and presents findings that can help guide promotional strategy decisions. It also presents a comprehensive review of the games industry and associated activities in the marketplace, relevant for marketing practitioners. Theoretically, it contributes new knowledge concerning product placement, including how it should be defined, its classification within the existing communications framework, its dimensions and effects. This is extended to include brand-centred entertainment. The thesis also presents the most comprehensive analysis available in the literature of how placements appear in games. In the consumer behaviour discipline, the research builds on theory concerning attitude formation, through application of MacInnis and Jaworski’s (1989) Integrative Attitude Formation Model. With regards to the games literature, the thesis provides a structured framework for the comparison of games with different media types; it advances understanding of the game medium, its characteristics and the game playing experience; and provides insight into console and handheld games specifically, as well as interactive environments generally. This study is the first to test the effects of interactivity in a game environment, and presents a modified scale that can be used as part of future research. Methodologically, it addresses the limitations of prior research through execution of a field experiment and observation with a large sample, making this the largest study of product placement in games available in the literature. Finally, the current thesis offers comprehensive recommendations that will provide structure and direction for future study in this important field.

Predicting effects of monotony on driver’s vigilance

Monotony has been identified as a contributing factor to road crashes. Drivers’ ability to react to unpredictable events deteriorates when exposed to highly predictable and uneventful driving tasks, such as driving on Australian rural roads, many of which are monotonous by nature. Highway design in particular attempts to reduce the driver’s task to a merely lane-keeping one. Such a task provides little stimulation and is monotonous, thus affecting the driver’s attention which is no longer directed towards the road. Inattention contributes to crashes, especially for professional drivers. Monotony has been studied mainly from the endogenous perspective (for instance through sleep deprivation) without taking into account the influence of the task itself (repetitiveness) or the surrounding environment. The aim and novelty of this thesis is to develop a methodology (mathematical framework) able to predict driver lapses of vigilance under monotonous environments in real time, using endogenous and exogenous data collected from the driver, the vehicle and the environment. Existing approaches have tended to neglect the specificity of task monotony, leaving the question of the existence of a “monotonous state” unanswered. Furthermore the issue of detecting vigilance decrement before it occurs (predictions) has not been investigated in the literature, let alone in real time. A multidisciplinary approach is necessary to explain how vigilance evolves in monotonous conditions. Such an approach needs to draw on psychology, physiology, road safety, computer science and mathematics. The systemic approach proposed in this study is unique with its predictive dimension and allows us to define, in real time, the impacts of monotony on the driver’s ability to drive. Such methodology is based on mathematical models integrating data available in vehicles to the vigilance state of the driver during a monotonous driving task in various environments. The model integrates different data measuring driver’s endogenous and exogenous factors (related to the driver, the vehicle and the surrounding environment). Electroencephalography (EEG) is used to measure driver vigilance since it has been shown to be the most reliable and real time methodology to assess vigilance level. There are a variety of mathematical models suitable to provide a framework for predictions however, to find the most accurate model, a collection of mathematical models were trained in this thesis and the most reliable was found. The methodology developed in this research is first applied to a theoretically sound measure of sustained attention called Sustained Attention Response to Task (SART) as adapted by Michael (2010), Michael and Meuter (2006, 2007). This experiment induced impairments due to monotony during a vigilance task. Analyses performed in this thesis confirm and extend findings from Michael (2010) that monotony leads to an important vigilance impairment independent of fatigue. This thesis is also the first to show that monotony changes the dynamics of vigilance evolution and tends to create a “monotonous state” characterised by reduced vigilance. Personality traits such as being a low sensation seeker can mitigate this vigilance decrement. It is also evident that lapses in vigilance can be predicted accurately with Bayesian modelling and Neural Networks. This framework was then applied to the driving task by designing a simulated monotonous driving task. The design of such task requires multidisciplinary knowledge and involved psychologist Rebecca Michael. Monotony was varied through both the road design and the road environment variables. This experiment demonstrated that road monotony can lead to driving impairment. Particularly monotonous road scenery was shown to have the most impact compared to monotonous road design. Next, this study identified a variety of surrogate measures that are correlated with vigilance levels obtained from the EEG. Such vigilance states can be predicted with these surrogate measures. This means that vigilance decrement can be detected in a car without the use of an EEG device. Amongst the different mathematical models tested in this thesis, only Neural Networks predicted the vigilance levels accurately. The results of both these experiments provide valuable information about the methodology to predict vigilance decrement. Such an issue is quite complex and requires modelling that can adapt to highly inter-individual differences. Only Neural Networks proved accurate in both studies, suggesting that these models are the most likely to be accurate when used on real roads or for further research on vigilance modelling. This research provides a better understanding of the driving task under monotonous conditions. Results demonstrate that mathematical modelling can be used to determine the driver’s vigilance state when driving using surrogate measures identified during this study. This research has opened up avenues for future research and could result in the development of an in-vehicle device predicting driver vigilance decrement. Such a device could contribute to a reduction in crashes and therefore improve road safety.

Large area noise evaluation

A software tool (DRONE) has been developed to evaluate road traffic noise in a large area with the consideration of network dynamic traffic flow and the buildings. For more precise estimation of noise in urban network where vehicles are mainly in stop and go running conditions, vehicle sound power level (for acceleration/deceleration cruising and ideal vehicle) is incorporated in DRONE. The calculation performance of DRONE is increased by evaluating the noise in two steps of first estimating the unit noise database and then integrating it with traffic simulation. Details of the process from traffic simulation to contour maps are discussed in the paper and the implementation of DRONE on Tsukuba city is presented

Urban dynamic origin-destination matrices estimation

The aim of this paper is to explore a new approach to obtain better traffic demand (Origin-Destination, OD matrices) for dense urban networks. From reviewing existing methods, from static to dynamic OD matrix evaluation, possible deficiencies in the approach could be identified: traffic assignment details for complex urban network and lacks in dynamic approach. To improve the global process of traffic demand estimation, this paper is focussing on a new methodology to determine dynamic OD matrices for urban areas characterized by complex route choice situation and high level of traffic controls. An iterative bi-level approach will be used, the Lower level (traffic assignment) problem will determine, dynamically, the utilisation of the network by vehicles using heuristic data from mesoscopic traffic simulator and the Upper level (matrix adjustment) problem will proceed to an OD estimation using optimization Kalman filtering technique. In this way, a full dynamic and continuous estimation of the final OD matrix could be obtained. First results of the proposed approach and remarks are presented.

Estimation of travel time on urban networks with midlink sources and sinks

This paper presents a methodology for estimation of average travel time on signalized urban networks by integrating cumulative plots and probe data. This integration aims to reduce the relative deviations in the cumulative plots due to midlink sources and sinks. During undersaturated traffic conditions, the concept of a virtual probe is introduced, and therefore, accurate travel time can be obtained when a real probe is unavailable. For oversaturated traffic conditions, only one probe per travel time estimation interval—360 s or 3% of vehicles traversing the link as a probe—has the potential to provide accurate travel time.

Tactical driver lane change model using forward search

This paper describes the development and evaluation of a tactical lane change model using the forward search algorithm, for use in a traffic simulator. The tactical lane change model constructs a set of possible choices of near-term maneuver sequences available to the driver and selects the lane change action at the present time to realize the best maneuver plan. Including near term maneuver planning in the driver behavior model can allow a better representation of the complex interactions in situations such as a weaving section and high-occupancy vehicle (HOV) lane systems where drivers must weave across several lanes in order to access the HOV lanes. To support the investigation, a longitudinal control model and a basic lane change model were also analyzed. The basic lane change model is similar to those used by today's commonly-used traffic simulators. Parameters in all models were best-fit estimated for selected vehicles from a real-world freeway vehicle trajectory data set. The best-fit estimation procedure minimizes the discrepancy between the model vehicle and real vehicle's trajectories. With the best fit parameters, the proposed tactical lane change model gave a better overall performance for a greater number of cases than the basic lane change model.

Work-related driving safety in light vehicle fleets : a review of past research and the development of an intervention framework

This paper presents a critical review of past research in the work-related driving field in light vehicle fleets (e.g., vehicles < 4.5 tonnes) and an intervention framework that provides future direction for practitioners and researchers. Although work-related driving crashes have become the most common cause of death, injury, and absence from work in Australia and overseas, very limited research has progressed in establishing effective strategies to improve safety outcomes. In particular, the majority of past research has been data-driven, and therefore, limited attention has been given to theoretical development in establishing the behavioural mechanism underlying driving behaviour. As such, this paper argues that to move forward in the field of work-related driving safety, practitioners and researchers need to gain a better understanding of the individual and organisational factors influencing safety through adopting relevant theoretical frameworks, which in turn will inform the development of specifically targeted theory-driven interventions. This paper presents an intervention framework that is based on relevant theoretical frameworks and sound methodological design, incorporating interventions that can be directed at the appropriate level, individual and driving target group.

Vision based control for fixed wing UAVs inspecting locally linear infrastructure using skid-to-turn maneuvers

The following paper proposes a novel application of Skid-to-Turn maneuvers for fixed wing Unmanned Aerial Vehicles (UAVs) inspecting locally linear infrastructure. Fixed wing UAVs, following the design of manned aircraft, commonly employ Bank-to-Turn ma- neuvers to change heading and thus direction of travel. Whilst effective, banking an aircraft during the inspection of ground based features hinders data collection, with body fixed sen- sors angled away from the direction of turn and a panning motion induced through roll rate that can reduce data quality. By adopting Skid-to-Turn maneuvers, the aircraft can change heading whilst maintaining wings level flight, thus allowing body fixed sensors to main- tain a downward facing orientation. An Image-Based Visual Servo controller is developed to directly control the position of features as captured by onboard inspection sensors. This improves on the indirect approach taken by other tracking controllers where a course over ground directly above the feature is assumed to capture it centered in the field of view. Performance of the proposed controller is compared against that of a Bank-to-Turn tracking controller driven by GPS derived cross track error in a simulation environment developed to replicate the field of view of a body fixed camera.

Validation of the MEASURE automobile emissions model : a statistical analysis

The Mobile Emissions Assessment System for Urban and Regional Evaluation (MEASURE) model provides an external validation capability for hot stabilized option; the model is one of several new modal emissions models designed to predict hot stabilized emission rates for various motor vehicle groups as a function of the conditions under which the vehicles are operating. The validation of aggregate measurements, such as speed and acceleration profile, is performed on an independent data set using three statistical criteria. The MEASURE algorithms have proved to provide significant improvements in both average emission estimates and explanatory power over some earlier models for pollutants across almost every operating cycle tested.