Conceptual Issues in the Study of Innovation Adoption Behavior

ABSTRACT - This paper focuses upon the relationships among the major behavioral concepts associated with different stages in the consumer innovation decision process. Innovation acceptance, adoption, resistance, rejection, postponement, and their conceptual equivalents tend to lack standardized conceptual and operational definitions. On the basis of an analysis of the available literature, a general framework for innovation related consumer responses is presented. The results of a carefully structured qualitative study provide preliminary evidence as to what concepts may be meaningfully identified and related, and suggest theoretical, methodological, and possible managerial implications.


Mohamed I. Nabih, jaak G. Bloem, and Theo B.C. Poiesz (1997) ,"Conceptual Issues in the Study of Innovation Adoption Behavior", in NA - Advances in Consumer Research Volume 24, eds. Merrie Brucks and Deborah J. MacInnis, Provo, UT : Association for Consumer Research, Pages: 190-196.

Advances in Consumer Research Volume 24, 1997      Pages 190-196


Mohamed I. Nabih, Tilburg University, the Netherlands

jaak G. Bloem, Tilburg University, the Netherlands

Theo B.C. Poiesz, Tilburg University, the Netherlands


This paper focuses upon the relationships among the major behavioral concepts associated with different stages in the consumer innovation decision process. Innovation acceptance, adoption, resistance, rejection, postponement, and their conceptual equivalents tend to lack standardized conceptual and operational definitions. On the basis of an analysis of the available literature, a general framework for innovation related consumer responses is presented. The results of a carefully structured qualitative study provide preliminary evidence as to what concepts may be meaningfully identified and related, and suggest theoretical, methodological, and possible managerial implications.

New products and services represent a major source of business growth and profit. Yet, most of these seem to turn into failures before the stage of maturity (see, e.g. Crawford 1977; Cooper 1979; Booz, Allen, and Hamilton 1982). A relevant distinction can be made between new products and innovations (see, e.g. Robertson 1971), innovations being new products that are unrelated to direct or indirect consumer experience. The bottom line of innovation research findings is that if innovations succeed (fail) to meet consumer needs, wants, and preference, they are likely to encounter consumer adoption (resistance) (Ram 1989). However, the fact that many innovations fail to effectively penetrate markets indicates that, apart from the variance due to consumer needs, wants, and preferences, much variance remains to be explained. As a start, this paper will take a closer look at the adequacy of innovation related concepts and operationalizations presented in the literature. More specifically, it attempts to: 1. discuss the chronological development of behavioral concepts in the adoption literature, 2. assess the nature of the relationships between the major concepts, 3. discuss the different measurements of these concepts, 4. propose a conceptual framework as a synthesis of the previous points, and 5. report the results of a carefully structured qualitative study. Finally, implications for the conceptual framework are discussed.


In the innovation literature two general lines of research can be identified. One focuses on innovation adoption, and the other emphasizes consumer resistance to innovation. The first is the traditional and most dominant stream, which assesses how adoption is influenced by product characteristics (e.g. Feder 1982; Fliegel and Kilvin 1966; Zaltman 1973; Rogers 1962; Srivastava, Mahajan, Ramaswami, and Cherian (1985), personal characteristics (e.g. Robertson, Zielinski, and Ward 1984; Bass 1969), and perceived risk (e.g. Ostlund 1974). Researchers in the second line of research explicitly assume that rejection and adoption are two different types of behavior rather than antagonistic forms (Gatignon and Robertson 1991).

In the adoption literature a variety of behavioral concepts is frequently referred to, for example, adoption, rejection, resistance, acceptance, approval, trial, and postponement. Basically, adoption and rejection are the criterion concepts, with a strong emphasis in the literature on the former. Apparently, adoption is the more interesting behavior type to study, even though adoption and rejection are of equal importance from a practical viewpoint: they present each other’s complement.

Let us start, therefore, with a critical analysis of the concept of adoption which, in the adoption literature, refers to two different types of behavior. The behavior most commonly referred to in the definition of adoption is 'the acceptance and the continued use’ of an innovation (Robertson 1971:56). Alternatively, Rogers (1962) views adoption as 'a decision to continue full-scale use of an innovation’ (p.17). Robertson’s (1971) definition implies that not every innovation purchase results in adoption. In the case of non-durable innovations, for which continued use would pose an evident problem, Robertson (1971) replaced 'continuous use’ by 'repeat purchase decisions’, thus inicating that the operationalization of adoption is dependent upon the nature of the product class under consideration. Apparent operational complexities relate to the time frame and the number of repeat purchases to be considered, and to the necessity to allow for product category differences.

Rogers’ (1962) definition basically refers to the intention to continue full-scale use of the innovation. There are two problems with this definition, the first being that research has shown that intention is a rather weak determinant of the corresponding behavior (see Howard 1994). The second problem is that the definition seems to address a mere determinant of adoption: innovation acceptance. Thus, there is a risk of confusing the determining concept with the determined concept.

The two different definitions of the same concept illustrate the ease by which conceptual confusion arises in the area of innovative behavior. In order to clarify the definitional issue we will attempt to answer the question whether a distinction between acceptance and adoption is theoretically useful at all. Wilkening (1953) was the first to use the concept of acceptance. However, in his definition, acceptance included both approval and adoption. According to Klonglan and Coward (1970), approval is the affirmative evaluation of a practice whether or not innovation trial has occurred, and adoption refers to the incorporation of the innovation into the behavior pattern. Bohlen (1964) explicitly called for a distinction between acceptance and adoption, considering the time lag between mental acceptance and actual adoption. Beal, Klonglan, and Bohlen (1966), Bohlen (1968), and Rogers (1968) introduced the concept of symbolic adoption, to be defined by Rogers (1968) as the adoption of symbolic ideas without material parallel. Examples of symbolic ideas are migration, occupational choice, and partner choice (Bohlen 1964). Klonglan and Coward (1970) were the first to view symbolic adoption as a part of the adoption process, regardless whether the innovation being adopted is material or immaterial. The underlying assumption is that all innovations include an idea component and that some innovations also include a material component (Rogers 1962; Krampf, Burns and Rayman 1993).

In the adoption literature, the adoption decision process is usually conceived of as a 'hierarchy of effects’ model (Gatignon and Robertson 1991). Rogers’ (1962) adoption process model, which assumes an awareness-interest-evaluation-trial-adoption sequence, is the most popular. According to Gatignon and Robertson (1991) the model explains the adoption process under conditions of high involvement or cognitive processing. In contrast, under conditions of low cognitive processing, the adoption process may be described in terms of an adapted sequence: awareness-trial-evaluation-adoption. On the basis of the difference between the two sequences, Gatignon and Robertson (1991) state that 'in any conceptualization of the adoption process, it is essential to separate trial and adoption’ (p.325). Innovation trial is defined by Rogers and Shoemaker (1971) as applying the new idea by an individual on a small scale in order to determine its utility in his or her own situation. Both under conditions of high and low involvement consumers pass through the psychological stage of innovation acceptance before entering the trial stage. However, under high involvement conditions, relative to low involvement conditions, a more active acceptance develops before trial. Passive acceptance can be attributed to low consumer learning requirements, low innovation costs or switching costs, and low social imitation (Krugman 1965; Ray 1973; Robertson 1976; and Gatignon and Robertson 1985).

As in the case of acceptance, a distinction can be made between active and passive resistance. The concept of innovation resistance has been proposed by Sheth (1981) and Ram (1987). Passive resistance, then, takes place under conditions of low involvement or limited or no cognitive processing: a consumer resists the innovation without considering its potential. On the other hand, active resistance is expected under conditions ofhigh involvement or extensive cognitive processing. Engel, Blackwell, and Miniard (1993) distinguish between active and passive rejection. They refer to active rejection after the innovation is considered (for instance, after trying it), and view passive rejection as taking place if the innovation is never really considered by the consumer. Note that the distinction between active and passive rejection seems to add to the conceptual confusion in the innovation literature. Do the authors mean active and passive rejection or active and passive resistance?

It is difficult to be conclusive with regard to the mutual relationships between the concepts of adoption, acceptance, rejection and resistance. Concepts may differ from each other in terms of their psychological meaning and/or because of their respective positions in the adoption sequence. Should adoption and rejection be viewed as each other’s conceptual opposites, or do they reflect different underlying behaviors? Or are they conceptually similar but located at different positions in the adoption process? Are rejection and resistance basically the same, or should they be considered different? How useful is the distinction between active and passive behavior? And what role do trial and postponement play in relation to these concepts? The literature provides no conclusive answers to these questions. Comparisons are reported, but these relate more to individual pairs of concepts than to a systematic overall analysis of conceptual similarities and differences. In the next section we will refer to some of these comparisons.

According to Klonglan and Coward (1970), the two possible outcomes of the evaluation stage in the adoption process are 'mental acceptance’ and 'mental rejection’, the former possibly leading to trial and eventual continued use. Both acceptance and rejection may be related to other concepts. Innovation acceptance may also be viewed as the obverse of innovation resistance. Then, consumer acceptance and consumer resistance are the same type of behavior, are explained by the same factors, but differ in sign. Sheth (1981) and Ram (1989) attributed innovation resistance to two major sources of resistance factors; perceived risk components and habit or cognitive resistance. However, these resistance factors seem to provide an incomplete explanation of consumer resistance to innovations. If attraction factors leading to innovation acceptance are absent, then a reduction of the resistance factors will not increase the probability of acceptance. Also if repulsion factors are absent, a consumer can still resist the innovation in the absence of attraction factors. Therefore, the assessment of innovation acceptance and resistance requires the consideration of both repulsion and attraction forces.

Both rejection and resistance refer to the decision not to adopt the innovation. For instance, Gatignon and Robertson (1989) show that the decision to reject is not explained by the same factors that explain adoption: 'Rejection is not the mirror image of adoption but a different type of behavior. Future research could contribute by specifying factors uniquely tied to innovation resistance’ (p.325, underlining ours). Ram (1987) and Ram and Sheth (1989) define innovation resistance as 'the resistance offered by consumers to an innovation, either because it poses potential changes from a satisfactory status quo or because it conflicts with their belief structure’ (p.6). However, it seems that the same terms can be used to define rejection: the definition does allow for a conceptual distinction between the two concepts. If the concepts are not synonymous, their usage in the literature is rather inconsistent. For example, Ram (1989) states that 'two consumers may resist the same innovation for different reasons, and these reasons will have effects on the adoption process of each consumer. For example, one consumer may perceive the price of the innovation to be very high and reject it.’ (p.21).

Summarizing, adoption and rejection relate to the behavioral stage in the adoption decision model, while acceptance and resistanceare located at the preceding evaluation and intention level. If this interpretation is correct, resistance is not the obverse of adoption, and acceptance preceeds both adoption and rejection.

The consumer may escape from the dilemma between adoption and rejection by postponing the decision. Postponers are unwilling to commit themselves at a given point in time. They are undecided as to whether they need more information or more information-processing time (Gatignon and Robertson 1991), or are forced to delay adoption by external constraints such as, for example, product availability. There are two types of postponement responses toward innovations: trial postponement and adoption postponement. Trial postponement is a state in which consumers are undecided as to whether or not they should try using the innovation, or they have decided about trial but not about the point in time. Adoption postponement is a state in which consumers are undecided as to whether or not they should continue trial use, or they have decided but external constraints keep them from the purchase. Even though innovation postponement is a major type of consumer response, we know of only one study by Holak, Lehmann and Sultan (1987), that indirectly examined consumer postponement responses to innovations.


Another possible cause of confusion in the innovation adoption literature is the lack of standardized operationalizations of the dependent variables acceptance, adoption,rejection, resistance, and postponement. This is not surprising, giving the lack of clear and consistent conceptualizations. Many recent adoption studies operationalize adoption in terms of mere purchase behavior, product ownership, or product possession rather than the extensive and prolonged use of the innovation (see, for example, Dickerson and Gentry 1983; Olshavsky 1980). There are two main techniques used by adoption researchers to assess adoption in terms of the continued and extensive use of the innovation. The relatively common technique is to employ subjective recall measures on both the data of purchase and the frequency of use. The other technique is to employ objective measures where researchers depend upon external information for the assessment of adoption behavior. Adoption researchers show a tendency to group the respondents of their studies into two groups: adopters and non-adopters (for instance, see Dickerson and Gentry 1983; Forsythe, Butler, and Kim 1991; Kundu and Bhayana 1992; Strutton and Lumpkin 1992; Shim and Kotsiopulos 1994). Gatignon and Robertson (1989), studying organizational innovation behavior, state that 'some level of information relevant to adoption decision is lost by grouping all nonadopters as a single category. Organizations may still be in the process of evaluating whether or not they should adopt. Therefore it would be erroneous to classify them as having made a decision to reject the innovation’ (p.42). The same argument applies to consumers: at a particular point in time, nonadopters could be classified as belonging to either resistors, postponers, or rejectors.

It is surprising that in spite of the importance of the differences between these consumer responses to innovations, no standardized measurements of these concepts have been presented in the adoption literature. For the measurement of acceptance and adoption no known scales are available. The only standardized scale to measure consumer resistance to innovation is suggested by Ram (1989). The basic idea of thisscale is that resistance can be measured by assessing the psychological antecedents of innovation resistance (in terms of four perceived risk components and two habit resistance components), and the consumer behavioral resistance to try, purchase, and switch to the innovation. We noted earlier that in a complete approach two types of antecedents should be measured: both repulsion and attraction factors. It can be argued, therefore, that an approach which operationalizes consumer resistance in terms of the repulsion (or attraction) factors only is basically incomplete. Ram’s (1989) resistance scale only assesses repulsion factors.

The measurement of trial postponement involves the assessment of a type of consumer response to innovations which is located later in the adoption process relative to active acceptance and active resistance. The trial postponement response can be operationalized as the consumer’s intention to postpone experiencing a limited application of the innovation to his or her situation after s/he has actively accepted it. The development of scales for the measurement of innovation responses is beyond the scope of the present paper. Conceptual clarity and uniqueness constitute a worthy goal that is to be achieved before specific operationalizations can be presented.


An attempt is made here to summarize the different concepts and their relationships in one overall framework, in which also the adoption sequence is represented. See Figure 1. The conceptual framework may be translated in operational terms (see Figure 2).


A study was set up to make a preliminary assessment of the relevance and validity of the conceptual framework and its operational translation. The operational goal of the study was to find out how and why consumers proceed in their innovation decision process. No specific hypotheses were formulated, but a qualitative study was carefully designed to assess whether a psychologically meaningful distinction can be made between the various concepts of the proposed framework.



16 Respondents were recruited by the Product Evaluation Laboratory of the Delft University of Technlogy. Selection requirements were that the number of men and women should be equal, and that low, medium and high incomes should be approximately equally represented. Respondents received the equivalent of 8 US$ for their participation.

General set up

The qualitative study was structured according to the conceptual/ operational framework depicted in Figures 1 and 2, respectively. Because subjective newness rather than objective newness is the relevant concept, the procedure was to ensure that each respondent had to be confronted with products subjectively viewed as innovations. For this reason, the interviews were on an individual basis.


Respondents had been invited 'to have an interview on new products’. The interviews lasted about 45 minutes. Interviews were videotaped. The interview consisted of two parts. The goal of the first part was to make an inventory of a sufficient number of subjectively relevant innovations. This part was structured as follows:

1. The respondent received an explanation of the word 'innovation’;

2. The respondent was asked to give some examples of innovations (unaided);

3. The respondent was asked to select examples of innovations from a predetermined list of categories of new products (aided). Product categories included in the list were food and drinks, personal care products, cleaning products, audio-visual and information technological products, pharmaceutical products, and a rest-category;

4. For each product category, 3 examples of individual products were provided (e.g. CD-interactive, CD-rom, hand-held telephone, pasta snack, Internet, etc.); The respondent had to indicate whether they were aware of these innovations;

5. All innovations of which a respondent was aware (originated from 2, 3 and 4) were rated in terms of perceived newness according to the operationalization employed by Krampf et al., 1993);

The second part of the interview focused on the adoption process itself. This was done for those products that individual respondents had personally identified as innovations in the previous part. To clarify, respondents were first identified as to the stage in the adoption process. This was done with the scheme presented in Figure 3, based upon the operationalizations as presented in Figure 2. Note that respondents did not receive feedback on this idenification. Next, they were requested to describe the process from beginning to end in an unstructured interview ('Can you describe how you came to this decision, starting from the moment you were first confronted with the product?’). In this interview, the researcher did not provide any information as to structure of the adoption process.








For the sake of clarity, the results will be reported in the form of individual observations.

- Per respondent, the scheme was applied to 4 products consecutively (these products had been individually identified as innovations. A total of 24 products were perceived as innotavations. The nature and combination of these products varied over respondents. In total, the scheme was applied to 64 units of analysis;

- Over respondent-product combinations, a large variety of innovation related responses was observed;

- Respondents reported having no difficulty understanding scheme-related questions;

- With the help of the operational scheme it proved possible to allocate each respondent-product combination to one of the behavior stages. Additional question were not required.

- All innovation related responses in the scheme could be identified. These responses, together with their frequency of observation in parentheses, are: passive resistance (19), adoption (12), adoption postponement (8), rejection (6), active resistance (6), passive acceptance (6), trial postponement (6), active acceptance (5), and trial (1-meaning that one respondent was actually in the stage of trying out one of the products). It should be noted that passive resistance was the behavior most frequently identified;

- For all types of products respondents showed a tendency of proceeding according to a low involvement or 'do-feel-think’ process: low initial knowledge, experience (trial), acquire information. The respondents judged the trial phase very important;

- In the case of actual adoption, it is unclear how often product will be used. This is in line with the concept of adoption as defined by Robertson (1971);

- Respondents spontaneously make a distinction between symbolic and objective qualities innovations (see Klonglan and Coward (1970): accepting the idea or symbolic product qualities versus accepting the actual physical, or objective product qualities. (p.99).

Interpretation of descriptions provided by the respondents was done by two interviewers.

In conclusion, the scheme based upon the conceptual framework could be applied in a meaningful way. Respondents understood the meaning of the concepts and, with the help of the scheme, distinctions between the concepts could be made. If the process is viewed as located on a time-continuum, respondents were capable of locating the different concepts at different points of the continuum. This is important as, to our knowledge, this the first attempt to simultaneously present concepts that show a tendency to be confused in the literature. The results indicate that there is reason to believe that meaning-differences may be identified, although these differences may be small, and may possibly reflect a very small time distance on the continuum representing the adoption process. This study shows also how innovation related behavior may be operationalized. Because all behavior options are included, the likelihood of operational confusion is minimized. The same negative reaction to an innovation may have different psychological meanings, depending upon the stage in the adoption process. This applies, mutatis mutandis, to positive reactions as well. The scheme adopted for this study shows how different psychological meanings may be accounted for, even if consumers express them in equal overt behaviors.

A methodological suggestion implied by the results is that in spite of the risks involved in the adoption of innovations, consumers tend to follow a risk reducing strategy in which trial is a critical tactic. If this suggestion is correct, it may imply that existing scales related to adoption behavior are biased toward high involvement behavior.

The framework presented in this paper may be of practical relevance. A marketeer should be able to correctly identify non-purchase as either reflecting active resistance, passive resistance, rejection, trial postponement or adoption postponement. This is only possible if a conceptual and methodological framework is employed in which the competing concepts are simultaneously included. A correct diagnosis of the nature of the undesired behavior may help determine what practical measures need to be taken.

The next step in research will be a quantitative test of the framework and an assessment of associated antecedents. Knowledge of innovation behavior determinants is required to determine whether the adoption continuum referred to earlier should be broken down in different segments reflecting differences in the nature of behavior, rather than differences in the degree of behavior alone.


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Mohamed I. Nabih, Tilburg University, the Netherlands
jaak G. Bloem, Tilburg University, the Netherlands
Theo B.C. Poiesz, Tilburg University, the Netherlands


NA - Advances in Consumer Research Volume 24 | 1997

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