Commercial Communication in the Digital Age

Gabriele Siegert, M. Bjørn Rimscha, Stephanie Grubenmann, Gabriele Siegert, M. Bjørn Rimscha, Stephanie Grubenmann

• Publisher: De Gruyter Saur
• Year: 2017
• ISBN:
  9783110416831
• Edition: 1
• Topic: Languages & Linguistics
• Subtopic: Communication Studies
• Index: Languages & Linguistics

Die verbreiteten Begriffe 'Informationsgesellschaft' und 'Age of Access' suggerieren die problemlose allseitige Zugänglichkeit von Information. Doch Information ist in der Realität in vielerlei Hinsicht unzugänglich - physisch, wirtschaftlich, intellektuell, sprachlich, politisch, technisch. Zudem entstehen täglich neue Techniken und Praktiken der Zugänglichmachung. Schließlich zeigen sich in verschiedenen Bereichen die Grenzen der Forderung nach Zugänglichkeit. Diese neue Buchreihe bringt Wissenschaftler und Praktiker verschiedenster Prägung zusammen, um die verschiedenen Dimensionen der Unzugänglichkeit von Information auszuloten sowie Prinzipien und Techniken ihrer praktischen und gesellschaftlichen Überwindung aufzuzeigen, aber auch notwendige Grenzen der Zugänglichkeit deutlich zu machen. Herausgegeben von André Schüller-Zwierlein, Universitätsbibliothek Regensburg. Editorial Board:

• Prof. Dr. Herbert Burkert
  (Informationsrecht, Universität St. Gallen)
• Dr. Klaus Ceynowa
  (Stv. Generaldirektor der Bayerischen Staatsbibliothek)
• Prof. Dr. Heinrich Hußmann
  (Angewandte Informatik und Medieninformatik, Ludwig-Maximilians-Universität München)
• Prof. Dr. Michael Jäckel
  (Soziologie, Universität Trier)
• Prof. Dr. Rainer Kuhlen
  (Informationswissenschaft, Universität Konstanz)
• Prof. Dr. Frank Marcinkowski
  (Kommunikationswissenschaft, Westfälische Wilhelms-Universität Münster)
• Prof. Dr. Rudi Schmiede
  (Soziologie, Technische Universität Darmstadt)
• Prof. Dr. Richard Stang
  (Bibliotheks- und Informationsmanagement, Hochschule der Medien, Stuttgart)
  

IIInformation and Disinformation through Advertising

Roland Mangold

2.1Human Processing of Commercial Information in Digital Environments

Abstract: In theories of advertising effects attention is generally considered as being most essential for consumers’ processing of commercial messages. Especially in digital media environments where many different information sources compete for the users’ attention and where the next channel is only a fingertip away it is import to provide content that satisfies the users’ needs and is attractive to them. The good news is: information processing with reduced attention can also result in intended effects. To understand which specific conditions cause such effects and what different kinds of effects are to be expected, active psychological research on advertising in digital media settings is necessary. In this paper, selected results from this research will be discussed in the framework of a limited-capacity model of human information processing.

1Introduction

In almost every model of advertising effects attention is considered as being a crucial factor for commercial information to be effective. As the total capacity that is available in the human mental architecture for the processing of input information is limited (Mangold 2015), and as many different information sources compete for the consumer’s attention, commercial information might not get the capacity necessary to elicit intended effects on memory, attitude formation, or decision behaviour.

In the traditional mass media (printed matter, radio, television), advertisers have been confronted with a balancing act between either making commercial information more salient by putting it in the foreground or by moving it more into the background, and thus being confronted with the risk that it might to be missed by consumers. For example, when a television viewer is watching a commercial spot there is not a high probability that important product information will be missed. However, commercial spots tend to be evaluated negatively by viewers and processing might fail because consumers use commercial breaks to look at the TV guide or their smartphone, to talk to each other, or even to leave the room. Product placements on the other hand, are evaluated more positively and viewers tend to stay in front of the TV and follow the TV programme they are embedded in. But product placements have a significantly higher probability of being overlooked. Consequently, despite their tendentially negative image radio or television spots have been preferred for commercial communication, as long as not too many alternative programme channels have been offered to the radio or TV audience, and as long as it took some effort to switch channels.

The situation is becoming more complicated in digital media environments. Users still have a limited capacity for the processing of input information, but meanwhile there are many more sources from which information can be accessed. Furthermore, switching to another channel is much easier in digital environments: the next video and the next website are only the click of the mouse or the touch of a finger away. That is, consumers tend to be less motivated to stick with the processing of information from media they are not interested in, because it requires so little effort to find a better alternative.

As a consequence, the designers of commercial messages in digital media environments should take consumers’ specific needs relating to the given information into account more carefully, in order to achieve the degree of attention necessary for intensive processing. But as the number of competing information sources is considerably higher, and as a perfect match between the content offered and users’ needs probably might not be possible, research is required on the effects that might be expected even in cases where commercial information is processed with reduced attention.

In the next section an architecture for consumer-information processing will be introduced that offers an appropriate framework for the discussion of the above questions. Then, the specific needs of users that are satisfied during their interaction with digital media will be discussed. A limited number of basic human needs have been identified in empirical studies that are relevant both to the content, as well as the interactivity provided by digital media. In addition, a method will be described that is specifically adapted to revealing the users’ needs that are being satisfied or not during their interaction with digital media. Following that, the effectiveness of processing commercial information with a low receptive capacity will be discussed, and the relationship between allocated capacity and different kinds of effects will be explained. If such an unconscious processing of input information is possible it has to be discussed as to whether this establishes the opportunity to disinform or even manipulate consumers.

2An Architecture for Consumer Information Processing

In this paper a modified version of Lang’s (Lang 2000, 2009) limited capacity model of mediated motivated message processing (LC4MP) has been chosen to explain advertising effects in digital media environments (see fig. 1). A specific feature of this model is an implemented mechanism of capacity allocation that provides an appropriate explanation for the effects of processing information with a varying attention capacity. Cognitive information processing, and motivation and emotion, are controlled by two separate subsystems thus enabling a detailed explanation of interactions between cognitive and motivational/ emotional states.

Figure 1: An architecture for human information processing (modified version based on Lang 2000, 2009)

In the LC4MP humans are conceived of as systems which permanently exchange information with their physical environment. Information processing is performed by an architecture that receives information from the outer world through the senses (predominantly the visual and the auditory senses), decodes this information (i.e. understands it), processes this information (e.g. thinks about it), and possibly acts on its environment according to processing results. Information input from the environment is represented by structured patterns of physical energy that stimulate the human’s sensory organs. Initially, these patterns of energy can be conceived of as data; only if a meaning can be assigned to them, will they become information for the individual. In this view, information is identical to symbolic patterns that are connected to (inner) meaning by the information processing system.

During encoding the system first attempts to find an appropriate meaning for the data pattern transported from the senses to the working memory. If this process succeeds, a representation of the environment will be constructed in the working memory that serves as a basis for subsequent processing (e.g. thinking, problem solving, deciding and judging). To be able to assign a meaning to input data, knowledge has to be retrieved from the long term memory. Important processing results may in turn be stored in the long term memory. As it might be necessary during processing to retain some information for a limited duration (e.g. for intermediate results when performing a calculation), five to nine information elements (e.g. single units such as digits or letters, but also more complex chunks such as numbers or words) can be stored temporarily in the short term memory. Information processing may finally result in an instruction for the motoric system to initiate an action, but this is not a necessary consequence of operations in the working memory.

The upper part of the architecture displayed in fig. 1 is called the cognitive or representational subsystem, because here representations of the environment are constructed. In the lower part of fig. 1 the second subsystem is responsible for dealing with the motivational and emotional states of the individual. Emotions and motivations (needs, goals, and gratifications) are strongly interconnected: if a person’s needs are satisfied, this person will experience positive emotions. If however, an expected need satisfaction is frustrated, the person will experience negative emotions. Emotional and motivational states also affect the way in which information is processed by the representation system.

A central assumption in Lang’s (2000, 2009) LC4MP is that every process being executed in the architecture needs capacity. The amount of capacity that has to be allocated to a process in order to ensure proper execution is variable: “easy” (i.e. superficial) processes that do not require much concentration can be performed with less. For example, well trained and thus automatically running processes (like riding a bicycle or driving a car) are typical low capacity processes. “Deep” (i.e. thorough) processes however, that require concentration for their proper execution need a higher capacity. A process that requires a high capacity for thorough and deep operation but does not get it will operate superficially and will thus be imprecise.

Processes running with a high capacity differ from processes running on low capacity with regard to certain characteristics:

–High capacity processes are voluntarily controllable, their operation is governed by rules, and information is processed in a logical and rational way. During processing, the system searches for the overall best solution for a problem. The individual is consciously aware of the processing that is going on, and the processing details as well as results can be retained in memory.

–Low capacity processes on the other hand, evade voluntary control, and the processing style is heuristic, following “rule of the thumb” rather than the rule of logic and rationality. As a result, low capacity processes provide an approximation of good, but not necessarily the best solutions. They operate unconsciously, and the process details are not stored in memory.

A second central assumption within the LC4MP is that the total amount of capacity available for processing in the system is limited. That is, the allocation of processing capacity is compensatory: if one process gets more capacity for operation, other processes being executed at the same time will get less. This is the reason for the fact that although humans in principle are able to process more than one information source in parallel (e.g. thinking about a problem while riding a bicycle), only one process can be really deep and thorough, while all other processes will operate superficially. This mechanism constitutes no restrictions for habitual and therefore low capacity demanding processes (such as the routine activities already mentioned). But in principle, as soon as at least two require a higher level of capacity for sufficiently deep and thorough operation, only one will get enough capacity, while others will only function in a superficial manner – the person experiences cognitive overload.

To summarize, the demands of different processes for a variable level of capacity are strongly related to the kind of processing (deep and rule-governed or superficial and heuristic). Processes not receiving the capacity they would require for thorough operation will only attain superficially computed results. But what are the principles according to which capacity is allocated to currently operating processes? What are the factors that determine whether a process will get more or less capacity? The following determinants are mentioned in Lang’s (2000, 2009) publications:

–Voluntary control: Despite the fact that people generally tend to assume that they have a strong voluntary influence on the way in which information is processed in their heads, the effects of voluntarily capacity allocation to selected processes is only weak. This becomes obvious from the example where a student is learning for his exam. If he is not very much interested in the topic, learning becomes tedious and even after many repetitions learning success is only moderate. There doesn’t seem to be a way of just voluntarily increasing the capacity allocated to learning and thus with a simple trick improve learning.

–Characteristics of the stimulus: Attention will be very much attracted by stimuli that are salient to a person. Stimulus saliency is determined by stimulus properties like size, colour, movement, or loudness. For example, an ad which is big and displays loud colours will probably get more attention capacity than small and colourless stimuli. If a stimulus with not very salient features per se (e.g. an uncoloured ad) differs considerably from its context (e.g. with coloured text and pictures), it becomes salient by that.

–Motivation: Capacity will be allocated automatically to the processing of stimulus information that is related to a person’s interests, needs, goals, or expected gratifications. Having the right motivation is a much stronger determinant for capacity allocation than any of the other factors listed here.

–Emotions: In numerous empirical studies the influence of mood on the style of thinking has been demonstrated (cf. Bless, Fiedler 2006). When in a bad mood people think in a stricter, more rule-based, and more logical manner. In a good mood however, people think...

Table of contents

• Cover
• Title Page
• Copyright
• Editor’s Preface
• Contents
• I Information and Disinformation about Advertising
• II Information and Disinformation through Advertising
• III Information about Users
• IV Inclusion of Users in the Creation of Advertising
• List of Contributors – Short Biographies