Complexity and Advertising

As mentioned earlier, researchers addressing the complexity of an advertisement message have been biased towards the domain of print ads resulting in a limited number of studies addressing such paradigms in TV/radio commercials (Lowrey,

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2006). Considering this, the complexity of a message can be regarded from two main perspectives. One is the linguistic complexity of a message (e.g. Bradley & Meeds, 2002; Lowrey, 2006; Shapiro et al., 1992) and the other is the informational complexity of a message (e.g. Chen, Shang, & Kao, 2009; Jacoby, Speller, & Kohn, 1974;

Malhotra, 1982; Putrevu, Tan, & Lord, 2004). While the former mainly concerns the syntactic structure and the respective transformations that occur in determining the complexity of a message, the latter concerns the amount of information such as product features included in it.

2.4.4.1 Syntactic Complexity

Syntactic complexity is referred to as syntactic parsing as an analysis of the text with the relationship between words to understand a sentence (Just & Carpenter, 1987).

Processing difficulties may occur in the analysis which can be explained by two-stage theories and constraint-based theories. The former explains that sentence processing happens in two distinct stages, first picking up the possible meanings of a word and then choosing the most appropriate one for the context (MacDonald & Seidenberg, 2006). The latter explains that sentence comprehension is a continuous process that activates possible meanings at the same time and the analysis of the sentence occurs based on the support each source of information provides. Processing difficulty occurring during comprehension is described under two different aspects under each approach. According to two-stage theory, ambiguity is resolved by reanalysis of the first adopted structures. As per the constraint-based theories, ambiguity arises when competing support is received from sources which are closely related, and it is resolved by analysing the other words of the sentence (Pickering & Gompel, 2006 for a review).Accordingly, certain structural arrangements lead to difficulties in comprehending a text while others become comparatively easy (see Lowrey, 1998).

Thus, researchers in various domains took an interest in manipulating complexity syntactically and examined various other effects. For instance, in the area of advertising, some such manipulations include active vs. passive voice (e.g. Bradley &

Meeds, 2002), branching (e.g. Lowrey, 1998), and particle movements (e.g. Bradley &

Meeds, 2002).

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One of the theoretical models in psycholinguistics most referred to is Chomsky’s (1957) Theory of Transformational Grammar (Bradley & Meeds, 2002). Accordingly, there are two main structures in any sentence. One is the primary idea of the sentence called the D-structure (or Deep Structure) and is also known as the kernel of the sentence. The other is the superficial structure that comprises words and phrases to convey the main idea of the sentence. This is called S-structure (Surface Structure) of the sentence. Many S-structures can be constructed to convey the same D-structure and the depending on them the mind has to transform from one to derive the other.

Utilising the psycholinguistic theories in the domain of advertising was not very popular (Lowrey, 1998). Consequently, only limited research can be found in the area and the findings mostly suggest that the scenario of complexity itself is complex (see Lowrey, 2008). Thus, the relationship between script complexity and subsequent effects on the consumer is not direct but rather moderated by a number of factors like involvement, motivation, and media. Furthermore, in some situations the level of complexity defined as low and high (see Bradley & Meeds, 2002; Geissler et al., 2006;

Lowrey, 1998, 2006; McDaniel, 1981 for a comparision) is questionable and in other situations the index used to measure complexity is criticised (see Chamblee et al., 1993).

It is generally believed that high complexity will lead to a low level of memory as it directly relates to the ability to comprehend the message (D'Arcais, 1974; Lowrey, 1998 Exp I; 2006). In this study, it was found that the higher the complexity (with left branching and negations), the lower the memory it results in. However, there was no significant relationship found between the message complexity and the attitude towards the ads. One limitation of this study was that it had not been conducted in a controlled environment and the findings might have been contaminated. The participants were in their homes and material was broadcast through cable TV followed by telephone interviews. The second experiment was conducted in a more controlled environment and revealed no difference in memory with regard to both simple and complex syntaxes. Thus, it failed to replicate the results of the previous experiment. One possibility would be that the second experiment was on print media (see Section 2.4.3for media effects).

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Another important construct is the ability to process the message. Ability affects mainly the comprehension of a message and thus education is a main factor (Chamblee et al., 1993). They found that higher complexity has positive effects on highly educated people. However, this study utilised the Fog index while criticising the Fleshch index, which is the commonly adapted index to measure syntactic complexity. Thus, the level of complexity used in this study is somewhat uncertain to be directly comparable with studies of a similar nature. However, it is apparent that ability overrides the motivation factor at some level. When a message is complex beyond the ability to process, the level of motivation becomes insignificant (Jean-Charles, Gelinas-Chebat, Hombourger,

& Woodside, 2003). Involvement with the advertisement also influences the effects of complexity on consumers. For instance, high involvement users will have positive effects on memory (Bradley & Meeds, 2004; Cacioppo & Petty, 1982). However, these factors are interrelated and influence each other depending on the context.

2.4.4.2 Information Complexity

Information load is defined from several viewpoints in the literature. A pioneering study in the context of marketing defines information load as the variety of stimuli to which the receiver must attend (Jacoby et al., 1974). From the view of measurement, Scammon (1977) defines information load as the number of dimensions per brand where a dimension is an objectively testable fact. The major drawbacks of these definitions would be that they do not provide a reference to the load which could be measured. However, since they describe the information load aspect only, these definitions may be adequate but for this research purpose, it may be more appropriate to bring in the definitions of information overload to acknowledge the boundaries within which the information load operates. In that respect , Eppler and Mengis (2004) identify that though information overload can be simply defined as too much of information, it is recognised by many other terms such as cognitive overload, sensory overload, communication overload and information fatigue syndrome. All these aspects of information overload happen mainly owing to two factors, information processing requirement (IPR) and information processing capacity (IPC). IPR depends on characteristics such as the level of ambiguity, complexity and novelty while some of the factors like personal skills and the level of experience will determine IPC (Eppler &

Mengis, 2004 for a review).

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In spite of manipulating the structure of a sentence to achieve varying levels of complexity, the amount of information a message carries can also be used to achieve the same. Further, it is more relevant to say that treating complexity from the information load aspect would be more appropriate in the context of marketing for the reason that the complexity of a message would be determined by the amount of information in an advertisement message. Syntactic or structural manipulations are more relevant for the print media and it is questionable whether such manipulation brings much value to advertisements in the broadcast media.

Studies of information overload in the area of communication can be traced back to the 1950s to the studies of Miller (1956). Prior to this, the concept of information overload was recognised in the area of clinical psychology (Meyer, 1998) and it gained attention in the area of marketing with the pioneering studies of Jacoby and his associates (1974). Miller (1956) remarked that the amount of information is analogous to the amount of variance as it is used in other settings with a unit of measurement. For instance, the larger the variance is, the larger the amount of information it presents. He argued that if the amount of information provided is explained with a unit, it will get a new perspective to the topic under discussion. Thus, he explained the span of immediate memory with a processing unit called chunk and claimed that it neighboured around seven such units. This limit was then called the span of absolute judgment.

Based on this explanation, later studies came up with the premise that the amount of information that might exceed processing capacity would be detrimental to performance and was referred to as the basis for the concept of information overload (see Eppler & Mengis, 2004; Jacoby et al., 1974; Malhotra, 1982).

The concept was first tested in the field of marketing by considering number of brands and the amount of information presented per brand (Jacoby et al., 1974). They were tested with information on a product package and when multiple products are to be evaluated with different levels of information load, the way a consumer selected the best brand was examined. They found that when the number of brands increases, the preference for not having additional information increases. Further, it is noted that satisfaction, certainty and confusion increase as the amount of information increases. A similar study in a broadcasting context revealed that information load was primarily

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associated with brand knowledge and it had no significant effect on brand preferences (Scammon, 1977). However, in this study, the information was presented in the very last few seconds. Thus, considering the time available to process information, it is somewhat questionable whether consumers got enough time to process. With the purpose of finding the limits of overload, Malhotra (1982) manipulated a number of attributes and alternatives that appeared in a message. For this, he used increments of five in each up to 25 variants and found that information-overload happens with 10-15 alternatives and 15-25 attributes. It also became clear that in the case of overload, these two factors are independent. His explanations of such findings included that people use heuristics in dealing with information. However, another possibility could be that the consumer has to divide the time available to process this information (Scammon, 1977) and hence working memory becomes overloaded causing trouble recalling content and evaluating it at the same time.

The study by Jacoby et. al. (1974) was criticised for its various lapses. Some of them were statistical analysis, unbalanced design that prevents comparisons between findings, and the selection of the stimulus options (Jacoby, 1977; Malhotra, 1982).

Based on critiques of this research and on a few others, concern was raised with the actual existence of information overload (Malhotra, 1982). However, later studies (e.g.

Chen et al., 2009; Malhotra, 1982; Meyer, 1998; Scammon, 1977; Sicilia & Ruiz, 2010) with more advanced statistical analysis subsequently eliminated such doubts.