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Interconnectivity in diffusion of innovations and market competition
Journal of Business Research 57 (2004) 1295 – 1302
Interconnectivity in diffusion of innovations and market competition$ William H. Redmond* Department of Marketing, College of Business Administration, Bowling Green State University, Bowling Green, OH 43403, USA
Abstract Competition among firms frequently involves product innovation and subsequent promotional activity. When these innovations involve new communication technologies, their adoption enhances the overall communications infrastructure which, in turn, facilitates information flow about innovations throughout society. In this way, market competition has the unintended effect of accelerating the diffusion of innovations, particularly of new communication technologies. Interconnectivity occurs because marketers employ new communications technology for promotional purposes and because consumers use the new communication technologies to learn about yet other innovations. Factors associated with the interconnectivity phenomenon involve social comparison, the network structure of interpersonal communications, and prestige seeking. The broad-scale impacts of this interaction include a shift in the social evaluation of newness and a shortening of product life cycles. Implications for firms and society are discussed. D 2002 Elsevier Inc. All rights reserved. Keywords: Diffusion; New product development; Social impacts; Product life cycle
1. Introduction The focus of diffusion studies is usually on a single innovation, where attention is drawn to microlevel mechanisms surrounding the adoption decision. These mechanisms are important because the timing of adoptions regulates the speed of diffusion of the innovation. Communications are of central interest in this process, particularly those involving advertising, observation, and word-ofmouth communications. Such communications have traditionally been thought to inform the individual about the functional advantages, costs, and risks associated with adoption. In a broader sense, however, the process of diffusion involves the spread of newness through society, which entails broad-scale changes in both behaviors and perceptions. Consequently, a macrolevel perspective seeks to understand social change by examining the ways in which $
This paper takes a different approach to diffusion by considering the joint effect of multiple innovations, instead of the more common approach of focusing on one innovation at a time. The prior diffusion of communication innovations accelerates the diffusion of subsequent innovations. The role of marketing in accelerating overall patterns of diffusion is examined as an unintended consequence of competition. * Tel.: +1-419-372-8944; fax: +1-419-372-2875. E-mail address: [email protected] (W.H. Redmond). 0148-2963/$ – see front matter D 2002 Elsevier Inc. All rights reserved. doi:10.1016/S0148-2963(02)00453-8
communication mechanisms are themselves shaped and reshaped by the adoption of new technologies. Marketers compete by communicating both about and through the new technologies. In the act of competing, marketers unintentionally affect the means by which individuals communicate. Some of the most significant technological innovations of the past century served to enhance and amplify communications and, as a result, these have contributed new streams of information, social meanings, and imagery. In comparison with the beginnings of the 20th century, opportunities are now vastly magnified for learning about new products, and also for the observation of others, the comparison of life styles, and the discussion of innovations. Radio and television made a quantum jump in terms of revealing the lives and lifestyles of distant others. The Internet, being an inherently borderless medium, is making a worldwide exposure a matter of routine and thus renders the personal experience of globalization an everyday experience for millions (Giddens, 1990). At the same time, e-mail, cell phones, fax machines, and pagers serve to enhance and extend interpersonal communications with closer networks of individuals. It is well established that the introduction of an innovation may affect the diffusion process of another innovation, provided the two are sufficiently related by function or
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application (Alpert, 1994). For example, Peterson and Mahajan (1978) developed diffusion models for complementary innovations. However, the Peterson and Mahajan approach anticipates a direct interdependency between the innovations, such as the relationship between computing hardware and software. In contrast, the focus of the present paper is on a technological relationship of a different nature, specifically the propensity of communication innovations to accelerate the diffusion of indirectly related or unrelated innovations. The purpose is to develop a conceptual foundation with which to examine the role of market competition in fostering the diffusion of communication innovations and thus of impacting the diffusion of innovations generally.
of information from others and the transmission of information to others (Dholakia et al., 1996; Vattimo, 1992). The diffusion of any communications enhancing technology expands the collective ability of adopters to communicate about any subsequent innovation. These prior adoptions have a positive feedback effect, which accelerates the diffusion of subsequent innovations (Arthur, 1988; Redmond, 1991). Over the course of the 20th century, adoptions of communication innovations have accumulated so that the infrastructure for communication has expanded significantly. Interconnectivity in the diffusion of unrelated innovations is a technological issue, in the sense that it involves the capability to communicate. It is also subject to economic forces in the sense that unintended effects of market competition serve to magnify the interconnectivity phenomenon.
2. Communication and competition 2.2. The effects of market competition on diffusion processes This section examines two fundamental underpinnings of the interconnectivity of diffusion and competition. First is the role of communication in the process of diffusion. Second is the role of market competition in advancing communication technologies. 2.1. Communication and communication technology There is broad agreement that the diffusion process reflects a communication process, especially as concerns the spread of information and the timing of individual adoptions (Rogers, 1962, 1995; Gatignon and Robertson, 1985, 1991; Mahajan et al., 1990a,b). What makes new communication technology a uniquely interesting subject is that its adoption enhances the ability to communicate. That is, the opportunities for communication, and therefore the facilitation of diffusion, are expanded via new modes of contact. For the present purpose, communication innovations are considered a broad category, which includes any innovation that can convey information about new products or that allows one individual to observe another’s use or possession of a new item. As Von Hipple (1988) points out, new modes of transportation are partial substitutes for electronic technologies in terms of communication effects. Rogers’ (1962) classic example of the diffusion of hybrid corn illustrates a key difference between communication innovations and other types of innovations. When two farmers discuss hybrid corn, the adoption of hybrid corn has no subsequent impact on their ability to communicate about other innovations. By contrast, their adoption of telephone or radio helps to spread information and spur adoptions of the next innovation (Rogers, 1995). If the next innovation is also a communication technology, it in turn further increases communication flows and speeds the adoption of yet other innovations (Brown, 1981; Hagerstrand, 1967). Most salient for purposes of this paper is the point that the adoption of communication technologies expands the adopter’s ability to learn about subsequent innovations and shortens the time lag in both the receipt
A familiar role of marketing in the new product arena is a strategic one. Competition through the introduction of new products has become a centerpiece of corporate strategy in the last two decades. Growth through product development and market pioneering are an attractive strategic option, resulting in unprecedented levels of new product introductions (e.g., Varadarajan and Jayachandran, 1999). Many of these introductions are of a relatively mundane character, but true innovations have resulted as well. Although competition via new product launches is intended to enhance a firm’s performance in its own product/ market endeavors, it has the unintended effect of exposing consumers to newness on a widespread scale. As a result of this exposure, consumers in developed economies are habituated to a continuous flow of new products and services and accept them more readily than in the past (see below). This unintended effect applies to innovations of all types and is not confined to communications innovations. Another familiar role of marketing is more tactical in nature and is particular to communication technology. Since advertising is a communication process, new communication technologies are of intense interest to advertisers. In order to utilize new media, advertisers often subsidize new communication technologies by way of sponsorships. Advertisers underwrote programming expenses for radio, for broadcast television, for cable television, and for satellite television. Advertisers now subsidize, partially or fully, a number of new Internet services. Whether by furnishing a broader range of programming or by reducing (sometimes to zero) the price of services, advertisers make new communication technologies more beneficial and acceptable to potential adopters, thus accelerating their diffusion. Like competition via new products, competitive advertising is intended only to influence a firm’s own market performance but has the unintended effect of accelerating the diffusion of a new technology. The subsidization effect is also capable of generating positive feedback effects. The higher the audience response
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to the new medium, the more attractive is further subsidization, which attracts additional adopters of the technology, in turn making the new medium even more attractive to advertisers. In this way, the adoption of new communication technology by consumers is accelerated and their ability to communicate about subsequent innovations is expanded. The social setting in which these communications take place is discussed next.
3. The social context of diffusion As noted above, diffusion studies have most frequently examined one innovation at a time. Consequently, the focus of attention has been on the spread of an innovation throughout society. At the macrolevel, however, attention is drawn to ways in which the spread of multiple innovations changes society. Specifically, the focus is on social changes, which affect the conditions or pathways of diffusion. Adoption and diffusion theory rests on an extraordinarily rich and varied history of empirical and conceptual works (Rogers, 1962, 1995). However, some of the most basic perspectives on communication were established in studies set in rural and underdeveloped areas. In these studies, an emphasis on the utilitarian, essentially economic aspects of the innovation was central to motivation, while face-to-face contact of the communicators was critical. The following discussion outlines a social context for diffusion, which is more characteristic of developed economies. 3.1. Social structure and diffusion In conventional adoption/diffusion theories, the rate of communication was believed to be influenced by physical proximity (Hagerstrand, 1967; Brown, 1981). Although some localized effects have been detected in recent diffusion studies (Redmond, 1994), current research pays considerably more attention to social relationships among the individuals doing the communicating rather than physical relationships (Rogers, 1995; Midgley and Dowling, 1998). Research traditions grounded in face-to-face, word-ofmouth communication modes may be responsible for the paucity of attention to the broad role of modern communication technologies and communications infrastructure in the overall diffusion process. The social structure within which individuals communicate has implications for both who is involved and what content is communicated. The social structures relevant for analyzing interpersonal communications in diffusion processes are known as networks. Burt (1982) summarizes the pivotal role of networks as follows: ‘‘Actors find themselves in a social structure. That social structure defines their social similarities, which in turn pattern their perceptions of the advantages to be had by taking each of several alternative actions. At the same time, social structure differentially constrains actors in their ability to take actions.’’ In terms
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of diffusion, the network is salient in favoring or inhibiting adoption through the clarification of each actor’s interests in the innovation. Networks assist the individual in identifying innovations of particular relevance, in clarifying the meanings of advertisements or promotions, and in interpreting the social significance of adopting the new product. Networks are islands of dense communication and influence, which serve as a primary social unit for individuals. These networks are not, however, isolated from one another. An individual may have both ‘‘strong’’ and ‘‘weak’’ ties (Granovetter, 1973). Strong ties constitute a personal network, while weak ties serve to connect an individual with more distant individuals. Granovetter (1973) highlights the importance of the weak interpersonal ties that supplement strong network ties. These weak ties connect an individual in one network with an individual in another network. In this way, one network is linked to another. Because individuals in a network may have weak ties to different outside networks, ideas may flow from one network through numerous others. Network theory recognizes two types of motivation to adopt an innovation: cohesion and equivalence. The cohesion model of diffusion indicates that individuals are likely to copy the adoption decisions of familiar individuals, such as other network members (Burt, 1987). This mode of diffusion involves a cooperative spirit of communication among interested individuals (Frenzen and Nakamoto, 1993), and is a familiar notion in the spread of innovations. Communication between individuals with similar statuses and interests is thought to be significantly more effective in stimulating diffusion of innovations, as compared with random contacts (Rogers, 1995). The alternative to the cohesion model is the structural equivalence model of diffusion, in which individuals are motivated by competition with other individuals (Burt, 1987). While structurally equivalent individuals may not directly interact with each other, they maintain a high level of awareness of each other’s behavior via weak ties (i.e., observation and third-party communication). In the structural equivalence model, a potential adopter weighs the social costs and benefits of adoption (or failure to adopt) in light of his or her position and, in doing so, seeks information, which will clarify the social meaning attached to the innovation by others in similar positions. Both cohesion and equivalence depend upon the receipt of information about others’ adoption and use of innovations. The communications infrastructure, which has been built up in developed nations by previous adoptions, supports a level of information flow that is unprecedented in history. The ability to compare oneself with others has never been greater. 3.2. Motivation to adopt While the central focus of this paper rests on changes in the ability of potential adopters to communicate, changes in
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willingness to adopt cannot be ignored as an important social phenomenon affecting the course of diffusion processes. Willingness to adopt has traditionally been regarded in adoption/diffusion theory as a function of the properties of the innovation. That is, potential adopters were assumed to be averse to the risk of newness but could be induced to adopt by a clear and convincing demonstration of functional superiority. Qualities of the innovation relevant to adoption included costs, risks, and related matters (Brown, 1981; Morrill et al., 1988; Hagerstrand, 1967). Rogers (1962) provided a more detailed assessment of the qualities of innovations that affect their rate of adoption: relative advantage, compatibility, complexity, trialability, and observability. In focusing on relative advantage as the most critical element, traditional adoption/diffusion theory relied on utilitarian motives to explain adoption (Rogers, 1962). By the time of his fourth edition, however, Rogers (1995) supplemented his discussion of the utilitarian value of relative advantage with social status aspects. Rogers notes that status aspects have been understudied in diffusion research and that adoptions motivated in this fashion may be not only commonplace but can accelerate diffusion to the point of overadoption in pursuit of prestige. New products have social meaning as well as utilitarian function and this meaning is relevant to social position, status, and identity (Schor, 1998; Belk, 1988). To the extent that possession of new communication technologies confers prestige, the rate of diffusion is accelerated. To the extent that this social meaning is transmitted in the very process of using the new technology, diffusion is further accelerated. The notion that individuals may deploy objects in the competition for social prestige is certainly not a new one. Indeed, Veblen (1961/1899) outlines a picture of generally pervasive inclinations toward conspicuous consumption for this very purpose. It is interesting to note, however, that Veblen did not include new products among the examples of objects that might confer prestige. Between the turn of the 20th century and today, innovations have come to possess considerable power to enhance prestige. By the middle of the century in the US, advertisers of new products exerted great effort to ‘‘equate newness with betterness’’ (Packard, 1960), while consumers were keen to display earning power through new products (Galbraith, 1958). More recently, ownership of the latest innovations is thought to be an integral element of new styles of consumerism (Schor, 1998). One study of adoption behavior estimates that 40% of individuals adopt from motives of status maintenance (Midgley and Dowling, 1998). Although examples proliferate, one in particular illustrates the advanced state of prestige attached to newness in recent times. The example in question is that of the shortlived, but once thriving, market for fake cell phones. As readers may have been aware from news accounts, phony cell phones were realistic in appearance but had no commu-
nications capability whatsoever. In the mid to late 1980s, real cell phones were expensive and reflected considerable prestige in the eyes of would-be imitators; at that time, real cell phones were priced at around US$1000 and had cumulative sales of about 1 million units. For under US$20, ‘‘electronic social climbers’’ could sport a hollow handset and auto antenna, while the more budget-minded could opt for the antenna only at US$5 (Kellner, 1987; Krasner, 1988). One US firm reported sales of 40,000 phoney handsets between 1986 and 1988. The unique and salient feature of fake cell phones is the brief existence of twin markets, which segregated social representation from utilitarian function. The general case is that these two aspects are not cleanly separable either as market phenomena or, more importantly, in the minds of potential adopters themselves. Clearly, fake cell phones are not typical of consumer adoption situations, but do constitute the instance par excellence of the fact that social relevance can exercise a powerful influence on decision processes. Consumer goods convey cultural meanings, which people use to construct identities and relationships with others (Bourdiew, 1984; DiMaggio, 1994). In this way, consumption objects become tokens of recognition and membership in networks, which are increasingly replacing more rigid structural categories such as social class (Belk, 1988). In contemporary urbanized, developed areas, cultural categories are more flexible and indeterminate than in previous times and other places, thus providing wider scope for the selection or modification of identity (McCracken, 1986). Whereas utilitarian motives for adoption necessitate explicit communications detailing economic costs and benefits, status or identity motives may be informed simply by observation. What is important is to know who has adopted which innovation at a given time.
4. Interconnectivity in diffusion The context of diffusion in developed economies is characterized by a relative ease in making communications links among individuals. Both strong and weak network links are facilitated by the communications infrastructure, while status motivations abbreviate the amount of information that serves to justify an adoption decision. Social proximity (instead of physical proximity) is the relevant aspect of social structure while the status of adopters (instead of expertise of adopters) is the relevant content of communications. As noted earlier, the adoption of communication innovations creates the basis for interconnectivity in the diffusion of two innovations, whether or not the second innovation has any direct relation to the first. To be more precise, it is the interconnectivity among individuals that produces the interconnectivity in the diffusion of innovations.
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The interconnectivity phenomenon is of the indirect type, i.e., macrolevel effects are produced through microlevel behaviors. In this context, diffusion is the macrolevel
phenomenon while individual adoption is the microlevel phenomenon. The following diagram follows Coleman’s (1987, 1990) method of evaluating macro – micro linkages.
Here, the upper level is macro (representing diffusion), while the lower level is micro (representing adoption). The solid lines are direct effects; the broken line is the indirect effect (representing interconnectivity of diffusion). Assume that Innovation A is a new communication technology and that Action a is the adoption of A by an individual. This adoption subsequently facilitates the individual’s knowledge of, and desire for, Innovation B (which may or may not be a communications technology). The result is the individual’s accelerated adoption (Action b), which accelerates the rate of diffusion of Innovation B. Sequential adoptions of communication technology provide an infrastructure that is increasingly effective for the observation of new products and interaction with network members. The microlevel does not represent individuals reacting to innovations in isolation, but involves networks of individuals who observe, interpret, and reinterpret one another’s actions (Haferkamp, 1987). That is, diffusion is not simply a process of aggregation of autonomous behaviors (Munch and Smelser, 1987). The actions of one individual can and do change the actions of others, whether in the case of cohesion model or the structural equivalence model. A previous section outlined two mechanisms for unintended consequences of competitive marketing on adoption and diffusion. First is reliance on new products as a competitive strategy. This accelerates the A ! a link by making newness more familiar and acceptable. When A is a communication innovation, then the a ! b and b ! B links are subsequently accelerated. The modern social context for diffusion has implications for promotional strategy in the A ! a link, which are different from the traditional context. In traditional diffusion theory, advertising is thought to directly impact only the initial set of adopters (Bass, 1969). However, where social relevance is a substantial motivating factor in adoption, advertising plays a much more significant role in diffusion, a role which is considerably longer in duration and wider in terms of direct influence. While word-of-mouth and observation remain relevant for later adopters, advertising has an important and continuing role in positioning the innovation to potential adopters. The second type of unintended consequence is subsidization of new communication technology by sponsorship.
This also accelerates the A ! a link, with subsequent acceleration of the a ! b and b ! B links. Traditional diffusion theory does not explicitly recognize subsidization as an unintended consequence; however, the effect has parallels in the intentional subsidization of diffusion by change agents, such as governments (Brown, 1981). As noted above, the subsidization effect may produce a positive feedback loop, which significantly advances diffusion in the A ! a link. Early adopters of (real) cellular telephones offer an illustration of essential features of technological interconnectivity. On the whole, early adopters were somewhat notorious for finding a pretext to signal recipients that the call was being placed from a cell phone, usually by making casual mention of background noise, other drivers, etc. (Kellner, 1987). Consider two recipients of such a call, identical in all respects save that Recipient 1 does not own a cell phone while Recipient 2 does. Recipient 1 can reduce the status discrepancy between the caller and himself/herself by purchasing a cell phone. The adoption could be motivated by cohesion or by structural equivalence, depending upon the relationship between caller and recipient: in either case, the A ! a link is accelerated. On the other hand, Recipient 2 is likely to reciprocate by making some mention of his/her ownership of a cell phone. The establishment of a common interest in new technologies raises the likelihood of future mentions of newer technologies as they appear, accelerating the a ! b and b ! B links. The Recipient 1 call accelerates diffusion of an innovation currently on the market, while the Recipient 2 call accelerates the future diffusion of innovations not yet on the market. The case of cell phones (real and fake) illustrates the general phenomenon of willingness to embrace newness. Subsidization through sponsorship has not played a large role in cell phones but may play a role in third-generation cell phones with Internet video capabilities. Subsidization is a significant factor in adoptions of certain Internet e-mail services, such as Hotmail or Yahoo (Economist, 2000). While the individual-level motivations of status and position are important elements of diffusion, other factors pertinent to diffusion theory are omitted here for the sake of clarity. These include, but are not limited to, venturesomeness, education level, risk orientation, self-confidence, opinion leadership, and financial resources (Rogers, 1995;
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Gatignon and Robertson, 1985). For this reason, this research should be seen as applicable to the analysis of broad-scale developments in diffusion rather than to the more finely grained individual adoption decision, particularly those involving the identification and assessment of innovators or early adopters. Also omitted for clarity are certain supply side activities, which can affect the diffusion process. These activities are strategic in nature and typically affect the timing of new product availability, rate of diffusion, or viability of older technologies. Among these strategies are preemptive launch (Karakaya and Stahl, 1991), penetration pricing (Redmond, 1989), and early exit (Porter, 1980).
time delay between successive generations was relatively brief in the products they studied, and the authors note that over longer spans, the diffusion parameter may depart from equality (Norton and Bass, 1992). In the cases of TV and telephones, successive generations were more widely spaced. A higher rate of diffusion over successive generations is consistent with the interconnectivity argument, assuming that sufficient time separates the introductions of successive generations. Specifically, changes in communications infrastructure and in the social context over time can result in altered behavioral responses.
5. Conclusions 4.1. Accelerated diffusion rates A principal outcome of increasing interconnectivity is a general speeding up of diffusion rates. Two phenomena illustrate the effects of interconnectivity on the speed of diffusion. The first involves the widely noted shortening of product life cycles (PLCs) over time, while the second involves successive generations of a technology. Qualls et al. (1981) investigated the length of introductory and growth stages of household appliances and found a dramatic shortening. Specifically, they found an average of 46.3 years for innovations introduced in the 1922 –1942 period, 26.5 years for innovations introduced in the1945 – 1964 period, and 8.8 years for innovations introduced in the 1965 –1979. The authors tested, and rejected, the explanation that price differences were associated with PLC shortening. The authors concluded that the causes for shortening were uncertain and complex. Among possible explanations, they identified two that are consistent with the interconnectivity and social motivation, namely technological improvements in communications and a more favorable attitude toward innovations. Successive generations of a technology are the second phenomenon of interest. Norton and Bass (1987) propose, and find empirical support for, the thesis that successive generations of electronic components have equivalent diffusion rates (i.e., nearly identical Q parameters in the Bass, 1969 model). In a subsequent article, the authors extend this finding to other types of innovations including consumer products (Norton and Bass, 1992). Examination of still other consumer products fails to support the hypothesis of equivalent diffusion rates of successive generations. In these cases, the later generation has a diffusion rate substantially higher than the earlier. For example, color TV in the US had a diffusion rate over three times that of black and white TV (color Q = 0.836 vs. B&W Q = 0.251). Cell phones in the US have a diffusion rate more than twice that of wired telephones (cell Q = 0.386 vs. wired Q = 0.167). Norton and Bass argue that the postulated cross-generational equivalence springs from cross-generational similarities in the behavioral processes of adoption. However, the
The phenomenon of interconnectivity in the diffusion of innovations has two central elements. First, the diffusion process of an otherwise unrelated innovation is affected by the prior adoption of communication innovations. Second, the accumulating communications infrastructure has an accelerating influence on rates of diffusion. In both elements, the mechanism is a microlevel (adoption) linkage to macrolevel (diffusion) processes. The strategy of market competition via new product introductions and the subsidization of new communications technologies via advertising have impacted both the social meaning of adoption and the availability of communication innovations. In sum, the processes of adoption and diffusion in developed nations appear to have undergone a substantive change in the past century. Implications for businesses and society are outlined below. 5.1. Managerial implications of acceleration Organizational adaptations to the speeded-up technological environment may take a number of forms. For example, one widely employed method of coping with the effect of shorter PLCs is accelerated new product development processes (Millson et al., 1992). Pressures for acceleration are likely to increase in the areas of marketing research, technological development, and production planning. Widespread use of this approach is likely to have a further impact on consumers’ perceptions of the rate of product and market change, which may add to the acceleration effects. Another adaptive approach is the use of forecasting tools to anticipate the speed of diffusion of innovations. Because of its origins in diffusion theory, the Bass (1969) model is a suitable platform for incorporating new behavioral assumptions in forecasting (e.g., Mahajan et al., 1990a,b). The ramifications of complementary products for forecasting are relatively straightforward in terms of a positive cross-elasticity of demand. The interconnectivity phenomenon indicates that prior adoption of a communication innovation is complementary to the adoption of any subsequent innovation, which is likely to be communicated on or promoted via
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the first. The interconnectivity phenomenon sheds light on why forecasts for second-generation consumer innovations may be biased to the low side. It thus provides a rationale for selecting higher Q parameters for forecasting models than would otherwise be indicated by analogy with previous innovations (or with earlier generations of the same innovation). 5.2. Social implications of connectivity The accumulated impact of multiple communication innovations exerts a transformative influence on social structures and communications, generating higher degrees of connectivity. Social entrainment is the term given to the tendency toward a synchronization of temporal patterns of connected individuals (McGrath and Kelly, 1986). That is, there is a tendency for groups to move in tempo with each other, a mutual adjustment to faster patterns of information and reduced reaction times. Nowotny (1994) notes that communication technologies increasingly act to merge the space and time of workplace, free time, home, and travel. Office workers can work from home or shop from work or monitor their child’s day care from a laptop on an airplane. These are no longer separate spheres of activity with separate time patterns, but an increasingly unified fabric of time. To maintain a sense of identify, the suite of communication devices can also be used to create communication spaces that are at once private, individual, and insular (Dholakia et al., 1996). Extensive and intensive participation in communication technologies makes, simultaneity, the constant real or virtual presence of others an increasingly dominant aspect of everyday life (Nowotny, 1994). Friends, family, and coworkers are never distant, but are summoned at the touch of a button. Likewise, far-flung events, organizations, or individuals can be monitored in real time with ease. Hence, our daily experience of life is likely to become an increasingly close approximation of McLuhan’s vision of the global village. 5.3. Implications for social division While this paper deals with generalized effects of interconnectivity, participation is not universal. Unplugged individuals, or groups lacking relevant communication technologies, may lag behind. As noted above, social networks play an important role in encouraging the adoption of new technologies; however, it is also true that some networks inhibit or discourage such adoptions. Individuals strongly connected to networks whose members lack newer technology, or oppose its use, are much less likely to adopt the new themselves and this can create an ongoing pattern of negative reinforcement that inhibits future adoptions (Redmond, 1994). The unintended effects of marketing competition, which support acceleration of diffusion, are simply felt less and
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less by individuals with few contacts to newer media. Concerns about the ‘‘digital divide’’ are not about a temporary disparity, but about a permanent and possibly widening disparity, which is developing along income and ethnic lines (Hoffman and Novak, 2000). For example, lack of Internet access not only inhibits a potential adopter’s discussion about the Internet with its most knowledgeable users, it also blocks receipt of any Internet-based discussion of newer innovations. In this way, nonadopters may be increasingly isolated from the mainstream of society. Individuals on the wrong side of the digital divide may come to occupy an increasingly distanced and restricted communications space, a position increasingly out of synch with the social mainstream. Coser and Coser (1990) observe that the dominant American culture has an orientation which is future-looking and optimistic with respect to progress. In contrast, the disenfranchised are more oriented to the present and less optimistic about future possibilities. Thus, some see a real risk that society may be increasingly divided into groups with opposing orientations, in which the slower are left behind socially as well as economically (Nowotny, 1994).
References Alpert F. Innovator buying behavior over time: the innovator buying cycle and the cumulative effects of innovations. J Prod Brand Manag 1994; 3(2):50 – 62. Arthur B. Self-reinforcing mechanisms in economics. In: Anderson P, Arrow K, Pines D, editors. The economy as an evolving complex system. Reading (MA): Addison Wesley; 1988, p. 15–26. Bass F. A new product growth model for consumer durables. Manage Sci 1969;15(January):215 – 27. Belk R. Possessions and the extended self. J Consum Res 1988;15(September):139 – 68. Bourdiew P. Distinction: a social critique of the judgement of taste. London: Routledge and Kegan Paul; 1984. Brown L. Innovation diffusion: a new perspective. London: Methven; 1981. Burt R. Toward a structural theory of action: network models of social structure, perception and action. New York: Academic Press; 1982. Burt R. Social contagion and innovation: cohesion versus structural equivalence. Am J Sociol 1987;92(May):1287 – 335. Coleman J. Microfoundations and macrosocial behavior. In: Alexander J, Gieson B, Munch R, Smelser N, editors. The micro – macro link. Berkeley (CA): University of California Press; 1987, p. 153–73. Coleman J. Foundations of social theory. Cambridge (MA): Harvard Univ. Press; 1990. Coser L, Coser R. Time perspective and social structure. In: Hassard J, editor. The sociology of time. New York: St. Martin’s Press; 1990, p. 184–205. Dholakia N, Bakke J, Dholakia R. Institutional patterns of information technology diffusion. In: Belk R, Dholakia, Venkatesh, editors. Consumption and marketing: macro dimensions. Cincinnati: South-Western; 1996, p. 329–50. DiMaggio P. Culture and economy. In: Smelser N, Swedberg R, editors. The handbook of economic sociology. Princeton (NJ): Princeton Univ. Press; 1994, p. 25–57. Survey: e-entertainment. Economist 2000;October 7:5 – 26. Frenzen J, Nakamoto K. Structure, cooperation and the flow of market information. J Consum Res 1993;20(December):360 – 75.
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Galbraith JK. The affluent society. Boston: Houghton Mifflin; 1958. Gatignon H, Robertson T. A propositional inventory for new diffusion research. J Consum Res 1985;11(March):849 – 67. Gatignon H, Robertson T. Innovative decision processes. In: Robertson, Kassarjian, editors. Handbook of consumer behavior. Englewood Cliffs (NJ): Prentice-Hall; 1991, p. 313–33. Giddens A. The consequences of modernity. Stanford (CA): Stanford Univ Press; 1990. Granovetter M. The strength of weak ties. Am J Sociol 1973;78(May): 1360 – 80. Haferkamp H. Complexity and behavior structure, planned associations and creation of structure. In: Alexander J, et al, editors. The micro – macro link. Berkeley (CA): University of California Press; 1987, p. 177–92. Hagerstrand T. Innovation diffusion as a spatial process. Chicago: University of Chicago Press; 1967. Hoffman D, Novak T. The growing digital divide: implications for an open research agenda. In: Brynjolfsson E, Kahin B, editors. Understanding the digital economy. Cambridge (MA): MIT Press; 2000, p. 246–67. Karakaya F, Stahl M. Entry barriers and market entry decisions. New York: Quarum Books; 1991. Kellner J. Bus Week 1987;September 21:84 – 92. Krasner J. Status without the static. Venture 1988;10(August):11 – 2. Mahajan V, Muller E, Srivastava R. Determination of adopter categories by using innovation diffusion models. J Mark Res 1990a;27(February): 37 – 50. Mahajan V, Muller E, Bass F. New product diffusion models in marketing: a review and directions for research. J Mark 1990b;54(January):1 – 26. McCracken G. Culture and consumption: a theoretical account of the structure and movement of the cultural meaning of consumer goods. J Consum Res 1986;13(June):71 – 84. McGrath J, Kelly J. Time and human interaction: toward a social psychology of time. New York: Guilford Press; 1986. Midgley D, Dowling G. A longitudinal study of product form innovation: the interaction between predispositions and social messages. J Consum Res 1988;19(March):611 – 25. Millson M, Raj SP, Wilemon D. A survey of major approaches for accelerating new product development. J Prod Innov Manag 1992;9(1):53 – 69.
Morrill R, Gaile G, Thrall G. Spatial diffusion. Newbury Park (CA): Sage Publications; 1988. Munch R, Smelser N. Relating the micro and macro. In: Alexander J, et al, editors. The micro – macro link. Berkeley (CA): University of California Press; 1987, p. 356–87. Norton JA, Bass F. A diffusion theory model of adoption and substitution for successive generations of high technology products. Manage Sci 1987;33(September):1069 – 86. Norton JA, Bass F. Evolution of technological generations: the law of capture. Sloan Manage Rev 1992;33(Winter):66 – 77. Nowotny H. Time: the modern and postmodern experience. Cambridge: Polity Press; 1994. Packard V. The waste makers. New York: McKay; 1960. Peterson R, Mahajan V. Multi-product growth models. In: Sheth J, editor. Research in marketing. Greenwich (CT): JAI Press; 1978, p. 201–31. Porter M. Competitive advantage. New York: Free Press; 1980. Qualls W, Olshavsky R, Michaels R. Shortening of the PLC—an empirical test. J Mark 1981;45(Fall):76 – 80. Redmond WH. Effects of new product pricing on the evolution of market structure. J Prod Innov Manag 1989;6(June):99 – 108. Redmond WH. When technologies compete: the role of externalities in nonlinear market response. J Prod Brand Manag 1991;8(September): 170 – 84. Redmond WH. Diffusion at sub-national levels: a regional analysis of new product growth. J Prod Innov Manag 1994;11(June):201 – 12. Rogers E. Diffusion of innovations. New York: Free Press; 1962. Rogers E. Diffusion of innovations, vol. 4E. New York: Free Press; 1995. Schor J. The overspent American. New York: Basic Books; 1998. Varadarajan PR, Jayachandran S. Marketing strategy: an assessment of the state of the field and outlook. J Acad Mark Sci 1999;27(Spring): 120 – 43. Vattimo G. The transparent society. Baltimore: Johns Hopkins Press; 1992. Veblen T. The theory of the leisure class. New York: Modem Library; 1961/ 1899. Von Hipple E. The sources of innovation. New York: Oxford Univ. Press; 1988.
Interconnectivity in diffusion of innovations and market competition$ William H. Redmond* Department of Marketing, College of Business Administration, Bowling Green State University, Bowling Green, OH 43403, USA
Abstract Competition among firms frequently involves product innovation and subsequent promotional activity. When these innovations involve new communication technologies, their adoption enhances the overall communications infrastructure which, in turn, facilitates information flow about innovations throughout society. In this way, market competition has the unintended effect of accelerating the diffusion of innovations, particularly of new communication technologies. Interconnectivity occurs because marketers employ new communications technology for promotional purposes and because consumers use the new communication technologies to learn about yet other innovations. Factors associated with the interconnectivity phenomenon involve social comparison, the network structure of interpersonal communications, and prestige seeking. The broad-scale impacts of this interaction include a shift in the social evaluation of newness and a shortening of product life cycles. Implications for firms and society are discussed. D 2002 Elsevier Inc. All rights reserved. Keywords: Diffusion; New product development; Social impacts; Product life cycle
1. Introduction The focus of diffusion studies is usually on a single innovation, where attention is drawn to microlevel mechanisms surrounding the adoption decision. These mechanisms are important because the timing of adoptions regulates the speed of diffusion of the innovation. Communications are of central interest in this process, particularly those involving advertising, observation, and word-ofmouth communications. Such communications have traditionally been thought to inform the individual about the functional advantages, costs, and risks associated with adoption. In a broader sense, however, the process of diffusion involves the spread of newness through society, which entails broad-scale changes in both behaviors and perceptions. Consequently, a macrolevel perspective seeks to understand social change by examining the ways in which $
This paper takes a different approach to diffusion by considering the joint effect of multiple innovations, instead of the more common approach of focusing on one innovation at a time. The prior diffusion of communication innovations accelerates the diffusion of subsequent innovations. The role of marketing in accelerating overall patterns of diffusion is examined as an unintended consequence of competition. * Tel.: +1-419-372-8944; fax: +1-419-372-2875. E-mail address: [email protected] (W.H. Redmond). 0148-2963/$ – see front matter D 2002 Elsevier Inc. All rights reserved. doi:10.1016/S0148-2963(02)00453-8
communication mechanisms are themselves shaped and reshaped by the adoption of new technologies. Marketers compete by communicating both about and through the new technologies. In the act of competing, marketers unintentionally affect the means by which individuals communicate. Some of the most significant technological innovations of the past century served to enhance and amplify communications and, as a result, these have contributed new streams of information, social meanings, and imagery. In comparison with the beginnings of the 20th century, opportunities are now vastly magnified for learning about new products, and also for the observation of others, the comparison of life styles, and the discussion of innovations. Radio and television made a quantum jump in terms of revealing the lives and lifestyles of distant others. The Internet, being an inherently borderless medium, is making a worldwide exposure a matter of routine and thus renders the personal experience of globalization an everyday experience for millions (Giddens, 1990). At the same time, e-mail, cell phones, fax machines, and pagers serve to enhance and extend interpersonal communications with closer networks of individuals. It is well established that the introduction of an innovation may affect the diffusion process of another innovation, provided the two are sufficiently related by function or
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application (Alpert, 1994). For example, Peterson and Mahajan (1978) developed diffusion models for complementary innovations. However, the Peterson and Mahajan approach anticipates a direct interdependency between the innovations, such as the relationship between computing hardware and software. In contrast, the focus of the present paper is on a technological relationship of a different nature, specifically the propensity of communication innovations to accelerate the diffusion of indirectly related or unrelated innovations. The purpose is to develop a conceptual foundation with which to examine the role of market competition in fostering the diffusion of communication innovations and thus of impacting the diffusion of innovations generally.
of information from others and the transmission of information to others (Dholakia et al., 1996; Vattimo, 1992). The diffusion of any communications enhancing technology expands the collective ability of adopters to communicate about any subsequent innovation. These prior adoptions have a positive feedback effect, which accelerates the diffusion of subsequent innovations (Arthur, 1988; Redmond, 1991). Over the course of the 20th century, adoptions of communication innovations have accumulated so that the infrastructure for communication has expanded significantly. Interconnectivity in the diffusion of unrelated innovations is a technological issue, in the sense that it involves the capability to communicate. It is also subject to economic forces in the sense that unintended effects of market competition serve to magnify the interconnectivity phenomenon.
2. Communication and competition 2.2. The effects of market competition on diffusion processes This section examines two fundamental underpinnings of the interconnectivity of diffusion and competition. First is the role of communication in the process of diffusion. Second is the role of market competition in advancing communication technologies. 2.1. Communication and communication technology There is broad agreement that the diffusion process reflects a communication process, especially as concerns the spread of information and the timing of individual adoptions (Rogers, 1962, 1995; Gatignon and Robertson, 1985, 1991; Mahajan et al., 1990a,b). What makes new communication technology a uniquely interesting subject is that its adoption enhances the ability to communicate. That is, the opportunities for communication, and therefore the facilitation of diffusion, are expanded via new modes of contact. For the present purpose, communication innovations are considered a broad category, which includes any innovation that can convey information about new products or that allows one individual to observe another’s use or possession of a new item. As Von Hipple (1988) points out, new modes of transportation are partial substitutes for electronic technologies in terms of communication effects. Rogers’ (1962) classic example of the diffusion of hybrid corn illustrates a key difference between communication innovations and other types of innovations. When two farmers discuss hybrid corn, the adoption of hybrid corn has no subsequent impact on their ability to communicate about other innovations. By contrast, their adoption of telephone or radio helps to spread information and spur adoptions of the next innovation (Rogers, 1995). If the next innovation is also a communication technology, it in turn further increases communication flows and speeds the adoption of yet other innovations (Brown, 1981; Hagerstrand, 1967). Most salient for purposes of this paper is the point that the adoption of communication technologies expands the adopter’s ability to learn about subsequent innovations and shortens the time lag in both the receipt
A familiar role of marketing in the new product arena is a strategic one. Competition through the introduction of new products has become a centerpiece of corporate strategy in the last two decades. Growth through product development and market pioneering are an attractive strategic option, resulting in unprecedented levels of new product introductions (e.g., Varadarajan and Jayachandran, 1999). Many of these introductions are of a relatively mundane character, but true innovations have resulted as well. Although competition via new product launches is intended to enhance a firm’s performance in its own product/ market endeavors, it has the unintended effect of exposing consumers to newness on a widespread scale. As a result of this exposure, consumers in developed economies are habituated to a continuous flow of new products and services and accept them more readily than in the past (see below). This unintended effect applies to innovations of all types and is not confined to communications innovations. Another familiar role of marketing is more tactical in nature and is particular to communication technology. Since advertising is a communication process, new communication technologies are of intense interest to advertisers. In order to utilize new media, advertisers often subsidize new communication technologies by way of sponsorships. Advertisers underwrote programming expenses for radio, for broadcast television, for cable television, and for satellite television. Advertisers now subsidize, partially or fully, a number of new Internet services. Whether by furnishing a broader range of programming or by reducing (sometimes to zero) the price of services, advertisers make new communication technologies more beneficial and acceptable to potential adopters, thus accelerating their diffusion. Like competition via new products, competitive advertising is intended only to influence a firm’s own market performance but has the unintended effect of accelerating the diffusion of a new technology. The subsidization effect is also capable of generating positive feedback effects. The higher the audience response
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to the new medium, the more attractive is further subsidization, which attracts additional adopters of the technology, in turn making the new medium even more attractive to advertisers. In this way, the adoption of new communication technology by consumers is accelerated and their ability to communicate about subsequent innovations is expanded. The social setting in which these communications take place is discussed next.
3. The social context of diffusion As noted above, diffusion studies have most frequently examined one innovation at a time. Consequently, the focus of attention has been on the spread of an innovation throughout society. At the macrolevel, however, attention is drawn to ways in which the spread of multiple innovations changes society. Specifically, the focus is on social changes, which affect the conditions or pathways of diffusion. Adoption and diffusion theory rests on an extraordinarily rich and varied history of empirical and conceptual works (Rogers, 1962, 1995). However, some of the most basic perspectives on communication were established in studies set in rural and underdeveloped areas. In these studies, an emphasis on the utilitarian, essentially economic aspects of the innovation was central to motivation, while face-to-face contact of the communicators was critical. The following discussion outlines a social context for diffusion, which is more characteristic of developed economies. 3.1. Social structure and diffusion In conventional adoption/diffusion theories, the rate of communication was believed to be influenced by physical proximity (Hagerstrand, 1967; Brown, 1981). Although some localized effects have been detected in recent diffusion studies (Redmond, 1994), current research pays considerably more attention to social relationships among the individuals doing the communicating rather than physical relationships (Rogers, 1995; Midgley and Dowling, 1998). Research traditions grounded in face-to-face, word-ofmouth communication modes may be responsible for the paucity of attention to the broad role of modern communication technologies and communications infrastructure in the overall diffusion process. The social structure within which individuals communicate has implications for both who is involved and what content is communicated. The social structures relevant for analyzing interpersonal communications in diffusion processes are known as networks. Burt (1982) summarizes the pivotal role of networks as follows: ‘‘Actors find themselves in a social structure. That social structure defines their social similarities, which in turn pattern their perceptions of the advantages to be had by taking each of several alternative actions. At the same time, social structure differentially constrains actors in their ability to take actions.’’ In terms
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of diffusion, the network is salient in favoring or inhibiting adoption through the clarification of each actor’s interests in the innovation. Networks assist the individual in identifying innovations of particular relevance, in clarifying the meanings of advertisements or promotions, and in interpreting the social significance of adopting the new product. Networks are islands of dense communication and influence, which serve as a primary social unit for individuals. These networks are not, however, isolated from one another. An individual may have both ‘‘strong’’ and ‘‘weak’’ ties (Granovetter, 1973). Strong ties constitute a personal network, while weak ties serve to connect an individual with more distant individuals. Granovetter (1973) highlights the importance of the weak interpersonal ties that supplement strong network ties. These weak ties connect an individual in one network with an individual in another network. In this way, one network is linked to another. Because individuals in a network may have weak ties to different outside networks, ideas may flow from one network through numerous others. Network theory recognizes two types of motivation to adopt an innovation: cohesion and equivalence. The cohesion model of diffusion indicates that individuals are likely to copy the adoption decisions of familiar individuals, such as other network members (Burt, 1987). This mode of diffusion involves a cooperative spirit of communication among interested individuals (Frenzen and Nakamoto, 1993), and is a familiar notion in the spread of innovations. Communication between individuals with similar statuses and interests is thought to be significantly more effective in stimulating diffusion of innovations, as compared with random contacts (Rogers, 1995). The alternative to the cohesion model is the structural equivalence model of diffusion, in which individuals are motivated by competition with other individuals (Burt, 1987). While structurally equivalent individuals may not directly interact with each other, they maintain a high level of awareness of each other’s behavior via weak ties (i.e., observation and third-party communication). In the structural equivalence model, a potential adopter weighs the social costs and benefits of adoption (or failure to adopt) in light of his or her position and, in doing so, seeks information, which will clarify the social meaning attached to the innovation by others in similar positions. Both cohesion and equivalence depend upon the receipt of information about others’ adoption and use of innovations. The communications infrastructure, which has been built up in developed nations by previous adoptions, supports a level of information flow that is unprecedented in history. The ability to compare oneself with others has never been greater. 3.2. Motivation to adopt While the central focus of this paper rests on changes in the ability of potential adopters to communicate, changes in
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willingness to adopt cannot be ignored as an important social phenomenon affecting the course of diffusion processes. Willingness to adopt has traditionally been regarded in adoption/diffusion theory as a function of the properties of the innovation. That is, potential adopters were assumed to be averse to the risk of newness but could be induced to adopt by a clear and convincing demonstration of functional superiority. Qualities of the innovation relevant to adoption included costs, risks, and related matters (Brown, 1981; Morrill et al., 1988; Hagerstrand, 1967). Rogers (1962) provided a more detailed assessment of the qualities of innovations that affect their rate of adoption: relative advantage, compatibility, complexity, trialability, and observability. In focusing on relative advantage as the most critical element, traditional adoption/diffusion theory relied on utilitarian motives to explain adoption (Rogers, 1962). By the time of his fourth edition, however, Rogers (1995) supplemented his discussion of the utilitarian value of relative advantage with social status aspects. Rogers notes that status aspects have been understudied in diffusion research and that adoptions motivated in this fashion may be not only commonplace but can accelerate diffusion to the point of overadoption in pursuit of prestige. New products have social meaning as well as utilitarian function and this meaning is relevant to social position, status, and identity (Schor, 1998; Belk, 1988). To the extent that possession of new communication technologies confers prestige, the rate of diffusion is accelerated. To the extent that this social meaning is transmitted in the very process of using the new technology, diffusion is further accelerated. The notion that individuals may deploy objects in the competition for social prestige is certainly not a new one. Indeed, Veblen (1961/1899) outlines a picture of generally pervasive inclinations toward conspicuous consumption for this very purpose. It is interesting to note, however, that Veblen did not include new products among the examples of objects that might confer prestige. Between the turn of the 20th century and today, innovations have come to possess considerable power to enhance prestige. By the middle of the century in the US, advertisers of new products exerted great effort to ‘‘equate newness with betterness’’ (Packard, 1960), while consumers were keen to display earning power through new products (Galbraith, 1958). More recently, ownership of the latest innovations is thought to be an integral element of new styles of consumerism (Schor, 1998). One study of adoption behavior estimates that 40% of individuals adopt from motives of status maintenance (Midgley and Dowling, 1998). Although examples proliferate, one in particular illustrates the advanced state of prestige attached to newness in recent times. The example in question is that of the shortlived, but once thriving, market for fake cell phones. As readers may have been aware from news accounts, phony cell phones were realistic in appearance but had no commu-
nications capability whatsoever. In the mid to late 1980s, real cell phones were expensive and reflected considerable prestige in the eyes of would-be imitators; at that time, real cell phones were priced at around US$1000 and had cumulative sales of about 1 million units. For under US$20, ‘‘electronic social climbers’’ could sport a hollow handset and auto antenna, while the more budget-minded could opt for the antenna only at US$5 (Kellner, 1987; Krasner, 1988). One US firm reported sales of 40,000 phoney handsets between 1986 and 1988. The unique and salient feature of fake cell phones is the brief existence of twin markets, which segregated social representation from utilitarian function. The general case is that these two aspects are not cleanly separable either as market phenomena or, more importantly, in the minds of potential adopters themselves. Clearly, fake cell phones are not typical of consumer adoption situations, but do constitute the instance par excellence of the fact that social relevance can exercise a powerful influence on decision processes. Consumer goods convey cultural meanings, which people use to construct identities and relationships with others (Bourdiew, 1984; DiMaggio, 1994). In this way, consumption objects become tokens of recognition and membership in networks, which are increasingly replacing more rigid structural categories such as social class (Belk, 1988). In contemporary urbanized, developed areas, cultural categories are more flexible and indeterminate than in previous times and other places, thus providing wider scope for the selection or modification of identity (McCracken, 1986). Whereas utilitarian motives for adoption necessitate explicit communications detailing economic costs and benefits, status or identity motives may be informed simply by observation. What is important is to know who has adopted which innovation at a given time.
4. Interconnectivity in diffusion The context of diffusion in developed economies is characterized by a relative ease in making communications links among individuals. Both strong and weak network links are facilitated by the communications infrastructure, while status motivations abbreviate the amount of information that serves to justify an adoption decision. Social proximity (instead of physical proximity) is the relevant aspect of social structure while the status of adopters (instead of expertise of adopters) is the relevant content of communications. As noted earlier, the adoption of communication innovations creates the basis for interconnectivity in the diffusion of two innovations, whether or not the second innovation has any direct relation to the first. To be more precise, it is the interconnectivity among individuals that produces the interconnectivity in the diffusion of innovations.
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The interconnectivity phenomenon is of the indirect type, i.e., macrolevel effects are produced through microlevel behaviors. In this context, diffusion is the macrolevel
phenomenon while individual adoption is the microlevel phenomenon. The following diagram follows Coleman’s (1987, 1990) method of evaluating macro – micro linkages.
Here, the upper level is macro (representing diffusion), while the lower level is micro (representing adoption). The solid lines are direct effects; the broken line is the indirect effect (representing interconnectivity of diffusion). Assume that Innovation A is a new communication technology and that Action a is the adoption of A by an individual. This adoption subsequently facilitates the individual’s knowledge of, and desire for, Innovation B (which may or may not be a communications technology). The result is the individual’s accelerated adoption (Action b), which accelerates the rate of diffusion of Innovation B. Sequential adoptions of communication technology provide an infrastructure that is increasingly effective for the observation of new products and interaction with network members. The microlevel does not represent individuals reacting to innovations in isolation, but involves networks of individuals who observe, interpret, and reinterpret one another’s actions (Haferkamp, 1987). That is, diffusion is not simply a process of aggregation of autonomous behaviors (Munch and Smelser, 1987). The actions of one individual can and do change the actions of others, whether in the case of cohesion model or the structural equivalence model. A previous section outlined two mechanisms for unintended consequences of competitive marketing on adoption and diffusion. First is reliance on new products as a competitive strategy. This accelerates the A ! a link by making newness more familiar and acceptable. When A is a communication innovation, then the a ! b and b ! B links are subsequently accelerated. The modern social context for diffusion has implications for promotional strategy in the A ! a link, which are different from the traditional context. In traditional diffusion theory, advertising is thought to directly impact only the initial set of adopters (Bass, 1969). However, where social relevance is a substantial motivating factor in adoption, advertising plays a much more significant role in diffusion, a role which is considerably longer in duration and wider in terms of direct influence. While word-of-mouth and observation remain relevant for later adopters, advertising has an important and continuing role in positioning the innovation to potential adopters. The second type of unintended consequence is subsidization of new communication technology by sponsorship.
This also accelerates the A ! a link, with subsequent acceleration of the a ! b and b ! B links. Traditional diffusion theory does not explicitly recognize subsidization as an unintended consequence; however, the effect has parallels in the intentional subsidization of diffusion by change agents, such as governments (Brown, 1981). As noted above, the subsidization effect may produce a positive feedback loop, which significantly advances diffusion in the A ! a link. Early adopters of (real) cellular telephones offer an illustration of essential features of technological interconnectivity. On the whole, early adopters were somewhat notorious for finding a pretext to signal recipients that the call was being placed from a cell phone, usually by making casual mention of background noise, other drivers, etc. (Kellner, 1987). Consider two recipients of such a call, identical in all respects save that Recipient 1 does not own a cell phone while Recipient 2 does. Recipient 1 can reduce the status discrepancy between the caller and himself/herself by purchasing a cell phone. The adoption could be motivated by cohesion or by structural equivalence, depending upon the relationship between caller and recipient: in either case, the A ! a link is accelerated. On the other hand, Recipient 2 is likely to reciprocate by making some mention of his/her ownership of a cell phone. The establishment of a common interest in new technologies raises the likelihood of future mentions of newer technologies as they appear, accelerating the a ! b and b ! B links. The Recipient 1 call accelerates diffusion of an innovation currently on the market, while the Recipient 2 call accelerates the future diffusion of innovations not yet on the market. The case of cell phones (real and fake) illustrates the general phenomenon of willingness to embrace newness. Subsidization through sponsorship has not played a large role in cell phones but may play a role in third-generation cell phones with Internet video capabilities. Subsidization is a significant factor in adoptions of certain Internet e-mail services, such as Hotmail or Yahoo (Economist, 2000). While the individual-level motivations of status and position are important elements of diffusion, other factors pertinent to diffusion theory are omitted here for the sake of clarity. These include, but are not limited to, venturesomeness, education level, risk orientation, self-confidence, opinion leadership, and financial resources (Rogers, 1995;
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Gatignon and Robertson, 1985). For this reason, this research should be seen as applicable to the analysis of broad-scale developments in diffusion rather than to the more finely grained individual adoption decision, particularly those involving the identification and assessment of innovators or early adopters. Also omitted for clarity are certain supply side activities, which can affect the diffusion process. These activities are strategic in nature and typically affect the timing of new product availability, rate of diffusion, or viability of older technologies. Among these strategies are preemptive launch (Karakaya and Stahl, 1991), penetration pricing (Redmond, 1989), and early exit (Porter, 1980).
time delay between successive generations was relatively brief in the products they studied, and the authors note that over longer spans, the diffusion parameter may depart from equality (Norton and Bass, 1992). In the cases of TV and telephones, successive generations were more widely spaced. A higher rate of diffusion over successive generations is consistent with the interconnectivity argument, assuming that sufficient time separates the introductions of successive generations. Specifically, changes in communications infrastructure and in the social context over time can result in altered behavioral responses.
5. Conclusions 4.1. Accelerated diffusion rates A principal outcome of increasing interconnectivity is a general speeding up of diffusion rates. Two phenomena illustrate the effects of interconnectivity on the speed of diffusion. The first involves the widely noted shortening of product life cycles (PLCs) over time, while the second involves successive generations of a technology. Qualls et al. (1981) investigated the length of introductory and growth stages of household appliances and found a dramatic shortening. Specifically, they found an average of 46.3 years for innovations introduced in the 1922 –1942 period, 26.5 years for innovations introduced in the1945 – 1964 period, and 8.8 years for innovations introduced in the 1965 –1979. The authors tested, and rejected, the explanation that price differences were associated with PLC shortening. The authors concluded that the causes for shortening were uncertain and complex. Among possible explanations, they identified two that are consistent with the interconnectivity and social motivation, namely technological improvements in communications and a more favorable attitude toward innovations. Successive generations of a technology are the second phenomenon of interest. Norton and Bass (1987) propose, and find empirical support for, the thesis that successive generations of electronic components have equivalent diffusion rates (i.e., nearly identical Q parameters in the Bass, 1969 model). In a subsequent article, the authors extend this finding to other types of innovations including consumer products (Norton and Bass, 1992). Examination of still other consumer products fails to support the hypothesis of equivalent diffusion rates of successive generations. In these cases, the later generation has a diffusion rate substantially higher than the earlier. For example, color TV in the US had a diffusion rate over three times that of black and white TV (color Q = 0.836 vs. B&W Q = 0.251). Cell phones in the US have a diffusion rate more than twice that of wired telephones (cell Q = 0.386 vs. wired Q = 0.167). Norton and Bass argue that the postulated cross-generational equivalence springs from cross-generational similarities in the behavioral processes of adoption. However, the
The phenomenon of interconnectivity in the diffusion of innovations has two central elements. First, the diffusion process of an otherwise unrelated innovation is affected by the prior adoption of communication innovations. Second, the accumulating communications infrastructure has an accelerating influence on rates of diffusion. In both elements, the mechanism is a microlevel (adoption) linkage to macrolevel (diffusion) processes. The strategy of market competition via new product introductions and the subsidization of new communications technologies via advertising have impacted both the social meaning of adoption and the availability of communication innovations. In sum, the processes of adoption and diffusion in developed nations appear to have undergone a substantive change in the past century. Implications for businesses and society are outlined below. 5.1. Managerial implications of acceleration Organizational adaptations to the speeded-up technological environment may take a number of forms. For example, one widely employed method of coping with the effect of shorter PLCs is accelerated new product development processes (Millson et al., 1992). Pressures for acceleration are likely to increase in the areas of marketing research, technological development, and production planning. Widespread use of this approach is likely to have a further impact on consumers’ perceptions of the rate of product and market change, which may add to the acceleration effects. Another adaptive approach is the use of forecasting tools to anticipate the speed of diffusion of innovations. Because of its origins in diffusion theory, the Bass (1969) model is a suitable platform for incorporating new behavioral assumptions in forecasting (e.g., Mahajan et al., 1990a,b). The ramifications of complementary products for forecasting are relatively straightforward in terms of a positive cross-elasticity of demand. The interconnectivity phenomenon indicates that prior adoption of a communication innovation is complementary to the adoption of any subsequent innovation, which is likely to be communicated on or promoted via
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the first. The interconnectivity phenomenon sheds light on why forecasts for second-generation consumer innovations may be biased to the low side. It thus provides a rationale for selecting higher Q parameters for forecasting models than would otherwise be indicated by analogy with previous innovations (or with earlier generations of the same innovation). 5.2. Social implications of connectivity The accumulated impact of multiple communication innovations exerts a transformative influence on social structures and communications, generating higher degrees of connectivity. Social entrainment is the term given to the tendency toward a synchronization of temporal patterns of connected individuals (McGrath and Kelly, 1986). That is, there is a tendency for groups to move in tempo with each other, a mutual adjustment to faster patterns of information and reduced reaction times. Nowotny (1994) notes that communication technologies increasingly act to merge the space and time of workplace, free time, home, and travel. Office workers can work from home or shop from work or monitor their child’s day care from a laptop on an airplane. These are no longer separate spheres of activity with separate time patterns, but an increasingly unified fabric of time. To maintain a sense of identify, the suite of communication devices can also be used to create communication spaces that are at once private, individual, and insular (Dholakia et al., 1996). Extensive and intensive participation in communication technologies makes, simultaneity, the constant real or virtual presence of others an increasingly dominant aspect of everyday life (Nowotny, 1994). Friends, family, and coworkers are never distant, but are summoned at the touch of a button. Likewise, far-flung events, organizations, or individuals can be monitored in real time with ease. Hence, our daily experience of life is likely to become an increasingly close approximation of McLuhan’s vision of the global village. 5.3. Implications for social division While this paper deals with generalized effects of interconnectivity, participation is not universal. Unplugged individuals, or groups lacking relevant communication technologies, may lag behind. As noted above, social networks play an important role in encouraging the adoption of new technologies; however, it is also true that some networks inhibit or discourage such adoptions. Individuals strongly connected to networks whose members lack newer technology, or oppose its use, are much less likely to adopt the new themselves and this can create an ongoing pattern of negative reinforcement that inhibits future adoptions (Redmond, 1994). The unintended effects of marketing competition, which support acceleration of diffusion, are simply felt less and
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less by individuals with few contacts to newer media. Concerns about the ‘‘digital divide’’ are not about a temporary disparity, but about a permanent and possibly widening disparity, which is developing along income and ethnic lines (Hoffman and Novak, 2000). For example, lack of Internet access not only inhibits a potential adopter’s discussion about the Internet with its most knowledgeable users, it also blocks receipt of any Internet-based discussion of newer innovations. In this way, nonadopters may be increasingly isolated from the mainstream of society. Individuals on the wrong side of the digital divide may come to occupy an increasingly distanced and restricted communications space, a position increasingly out of synch with the social mainstream. Coser and Coser (1990) observe that the dominant American culture has an orientation which is future-looking and optimistic with respect to progress. In contrast, the disenfranchised are more oriented to the present and less optimistic about future possibilities. Thus, some see a real risk that society may be increasingly divided into groups with opposing orientations, in which the slower are left behind socially as well as economically (Nowotny, 1994).
References Alpert F. Innovator buying behavior over time: the innovator buying cycle and the cumulative effects of innovations. J Prod Brand Manag 1994; 3(2):50 – 62. Arthur B. Self-reinforcing mechanisms in economics. In: Anderson P, Arrow K, Pines D, editors. The economy as an evolving complex system. Reading (MA): Addison Wesley; 1988, p. 15–26. Bass F. A new product growth model for consumer durables. Manage Sci 1969;15(January):215 – 27. Belk R. Possessions and the extended self. J Consum Res 1988;15(September):139 – 68. Bourdiew P. Distinction: a social critique of the judgement of taste. London: Routledge and Kegan Paul; 1984. Brown L. Innovation diffusion: a new perspective. London: Methven; 1981. Burt R. Toward a structural theory of action: network models of social structure, perception and action. New York: Academic Press; 1982. Burt R. Social contagion and innovation: cohesion versus structural equivalence. Am J Sociol 1987;92(May):1287 – 335. Coleman J. Microfoundations and macrosocial behavior. In: Alexander J, Gieson B, Munch R, Smelser N, editors. The micro – macro link. Berkeley (CA): University of California Press; 1987, p. 153–73. Coleman J. Foundations of social theory. Cambridge (MA): Harvard Univ. Press; 1990. Coser L, Coser R. Time perspective and social structure. In: Hassard J, editor. The sociology of time. New York: St. Martin’s Press; 1990, p. 184–205. Dholakia N, Bakke J, Dholakia R. Institutional patterns of information technology diffusion. In: Belk R, Dholakia, Venkatesh, editors. Consumption and marketing: macro dimensions. Cincinnati: South-Western; 1996, p. 329–50. DiMaggio P. Culture and economy. In: Smelser N, Swedberg R, editors. The handbook of economic sociology. Princeton (NJ): Princeton Univ. Press; 1994, p. 25–57. Survey: e-entertainment. Economist 2000;October 7:5 – 26. Frenzen J, Nakamoto K. Structure, cooperation and the flow of market information. J Consum Res 1993;20(December):360 – 75.
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W.H. Redmond / Journal of Business Research 57 (2004) 1295–1302
Galbraith JK. The affluent society. Boston: Houghton Mifflin; 1958. Gatignon H, Robertson T. A propositional inventory for new diffusion research. J Consum Res 1985;11(March):849 – 67. Gatignon H, Robertson T. Innovative decision processes. In: Robertson, Kassarjian, editors. Handbook of consumer behavior. Englewood Cliffs (NJ): Prentice-Hall; 1991, p. 313–33. Giddens A. The consequences of modernity. Stanford (CA): Stanford Univ Press; 1990. Granovetter M. The strength of weak ties. Am J Sociol 1973;78(May): 1360 – 80. Haferkamp H. Complexity and behavior structure, planned associations and creation of structure. In: Alexander J, et al, editors. The micro – macro link. Berkeley (CA): University of California Press; 1987, p. 177–92. Hagerstrand T. Innovation diffusion as a spatial process. Chicago: University of Chicago Press; 1967. Hoffman D, Novak T. The growing digital divide: implications for an open research agenda. In: Brynjolfsson E, Kahin B, editors. Understanding the digital economy. Cambridge (MA): MIT Press; 2000, p. 246–67. Karakaya F, Stahl M. Entry barriers and market entry decisions. New York: Quarum Books; 1991. Kellner J. Bus Week 1987;September 21:84 – 92. Krasner J. Status without the static. Venture 1988;10(August):11 – 2. Mahajan V, Muller E, Srivastava R. Determination of adopter categories by using innovation diffusion models. J Mark Res 1990a;27(February): 37 – 50. Mahajan V, Muller E, Bass F. New product diffusion models in marketing: a review and directions for research. J Mark 1990b;54(January):1 – 26. McCracken G. Culture and consumption: a theoretical account of the structure and movement of the cultural meaning of consumer goods. J Consum Res 1986;13(June):71 – 84. McGrath J, Kelly J. Time and human interaction: toward a social psychology of time. New York: Guilford Press; 1986. Midgley D, Dowling G. A longitudinal study of product form innovation: the interaction between predispositions and social messages. J Consum Res 1988;19(March):611 – 25. Millson M, Raj SP, Wilemon D. A survey of major approaches for accelerating new product development. J Prod Innov Manag 1992;9(1):53 – 69.
Morrill R, Gaile G, Thrall G. Spatial diffusion. Newbury Park (CA): Sage Publications; 1988. Munch R, Smelser N. Relating the micro and macro. In: Alexander J, et al, editors. The micro – macro link. Berkeley (CA): University of California Press; 1987, p. 356–87. Norton JA, Bass F. A diffusion theory model of adoption and substitution for successive generations of high technology products. Manage Sci 1987;33(September):1069 – 86. Norton JA, Bass F. Evolution of technological generations: the law of capture. Sloan Manage Rev 1992;33(Winter):66 – 77. Nowotny H. Time: the modern and postmodern experience. Cambridge: Polity Press; 1994. Packard V. The waste makers. New York: McKay; 1960. Peterson R, Mahajan V. Multi-product growth models. In: Sheth J, editor. Research in marketing. Greenwich (CT): JAI Press; 1978, p. 201–31. Porter M. Competitive advantage. New York: Free Press; 1980. Qualls W, Olshavsky R, Michaels R. Shortening of the PLC—an empirical test. J Mark 1981;45(Fall):76 – 80. Redmond WH. Effects of new product pricing on the evolution of market structure. J Prod Innov Manag 1989;6(June):99 – 108. Redmond WH. When technologies compete: the role of externalities in nonlinear market response. J Prod Brand Manag 1991;8(September): 170 – 84. Redmond WH. Diffusion at sub-national levels: a regional analysis of new product growth. J Prod Innov Manag 1994;11(June):201 – 12. Rogers E. Diffusion of innovations. New York: Free Press; 1962. Rogers E. Diffusion of innovations, vol. 4E. New York: Free Press; 1995. Schor J. The overspent American. New York: Basic Books; 1998. Varadarajan PR, Jayachandran S. Marketing strategy: an assessment of the state of the field and outlook. J Acad Mark Sci 1999;27(Spring): 120 – 43. Vattimo G. The transparent society. Baltimore: Johns Hopkins Press; 1992. Veblen T. The theory of the leisure class. New York: Modem Library; 1961/ 1899. Von Hipple E. The sources of innovation. New York: Oxford Univ. Press; 1988.