An Overview of the Diffusion of Advanced Techniques

Electronic copy available at: http://ssrn.com/abstract=1373209

Electronic copy available at: http://ssrn.com/abstract=1373209

An Overview of the Diffusion of Advanced Techniques 309

Copyright © 2003, Idea Group Inc. Copying or distributing in print or electronic forms without writtenpermission of Idea Group Inc. is prohibited.

Chapter XVI

An Overview of theDiffusion of

Advanced TechniquesDavood Askarany

University of South Australia, Australia

ABSTRACTThis chapter addresses a variety of factors influencing the diffusion of advanced techniquesin organizations with particular reference to advanced cost and management accountingpractices. Having identified almost all of influencing factors addressed in the literature,this chapter also develops a model for the diffusion of advanced techniques and clarifiesthe most significant group of influencing factors responsible for such a diffusion processfrom users’ point of view.

Addressing diffusion of advanced techniques in the global environment as apractical issue requires global evidence, which is almost impossible to provide in a singlestudy. However, to address such an issue and to explore significant factors influencing thediffusion of advanced techniques in the organizations, this chapter relies on the results ofrecent surveys on the diffusion of advanced cost and management accounting techniquesas an example. The diffusion model developed in this chapter is more likely to be applicableto any diffusion study, investigating the diffusion process of either accounting or non-accounting advanced techniques in the global environment, with minor modification.

310 Askarany


INTRODUCTIONThe nature of global competition faced by organizations in different aspects of their

operation (such as manufacturing process, operation technologies, and information sys-tems) has changed significantly during the last two decades (Shields, 1997). This has placeda greater emphasis on developing and implementing advanced techniques including manu-facturing practices and management accounting innovations (Perera, Harrison, & Poole,1997). Consistent with systems approach theory, a common theme for the diffusion ofadvanced techniques in the global environment is that changes in an organization’soperating environment, such as changes in communication, information systems, competi-tion, and manufacturing processes, may lead to the consideration of the subsequent changesnecessary in other parts of the organization, such as administration systems, cost andmanagement accounting techniques, etc. (Kellett & Sweeting, 1991).

Given the extent of recent advanced technological changes, the growing level of globalcompetition has intensified the challenge for managers to consider more effective ways ofachieving competitive advantage and improved organizational performance for the survivalof their organization. Any attempt to facilitate diffusion of advanced techniques in any sectorof organizations, such as communication, information systems, manufacturing processes,and administration systems, can be considered a means of achieving such a competitiveadvantage in the global environment. With regard to the current ever-changing nature ofglobal environment, it is not an exaggeration to suggest that an organization’s ability tofunction successfully and survive in the current intensified global competition dependshighly on the availability of accurate, detailed and up-to-date information that can be usedby decision makers in the organization. This highlights the important role of advanced costand management accounting techniques in providing such information and emphasizes thesignificant contribution of any effort to facilitate the implementation of new managementaccounting techniques in practice. However, a progressing major concern is that why theadoption rate of these new advanced cost and management accounting techniques is low andwhich factor(s) influence diffusion of such techniques.

Addressing the diffusion issue of advanced techniques, several studies suggestedsome elements as hindering or facilitating factors in diffusion and investigated their roles indiffusion processes of management accounting and accounting information systems (e.g.,Askarany & Smith, 2000a; Bjornenak, 1997; Booth & Giacobbe, 1998; Chenhall & Langfield-Smith, 1998; Damanpour, 1988; Damanpour & Gopalakrishnan, 1998; Gosselin, 1997; Hartnett& Lowry, 1994). Most of these studies reported some kind of relationship between diffusionof cost and management accounting innovation and some influencing factors such asorganizational, structural, or cultural factors. However, no significant influencing factorexplaining the majority of variance in diffusion processes has been reported.

Shedding light on the diffusion of advanced techniques, this chapter explains thediffusion process, identifies influencing factors addressed in the diffusion literature anddevelops a diffusion model by classifying all influencing factors into three main categories:characteristics of innovations, characteristics of innovators, and other influencing factorsthat can not be categorized therein (notably factors related to social system, environment,and so on). Reporting on the results of recent surveys on diffusion of advanced techniques,this chapter also tries to identify the significant group of influencing factors that might beresponsible for the great majority of the variance in the diffusion process of advancedtechniques.



DIFFUSION OF ADVANCED TECHNIQUESWe may refer to an “advanced technique” as an innovation in this chapter. Rogers

(1995) defines an innovation as “an idea, practice, or object that is perceived as new by anindividual or other unit of adoption.” Further, he suggests that if the individual has noperceived knowledge about an idea and sees it as new, it is an innovation. Likewise,Damanpour and Gopalakrishnan (1998) define innovation as “the adoption of an idea orbehavior new to the organization.” The common criterion in any definition of innovation isnewness. According to Rogers (1995), newness in an innovation might be expressed not onlyin terms of new knowledge, but also in terms of first persuasion or a decision to adopt. Thesecond element that needs some clarification is diffusion. Wolfe (1994) explains diffusion ofan innovation as a way the new ideas are accepted (or not) by those to whom they are relevant.Rogers (1995) extends this definition to consider diffusion as a process by which aninnovation is communicated through certain channels over time among the members of asocial system.

A clear understanding of the complexities of the innovation process and of alternativediffusion methods is central to any innovation diffusion study. Depending on the source ofinnovation, the diffusion of the innovation might follow different stages, so that alternativeapproaches and perspectives might be applicable under different innovation diffusionprocesses.

According to Damanpour and Gopalakrishnan (1998), diffusion of innovations inorganizations takes place in two ways: generation and adoption. In the case of generation,innovations are generated by organizations for their own use or for export to otherorganizations. In the case of adoption, innovations are imported into the organization foradoption. The process of adoption of an innovation is a very long and difficult process,especially because many innovations need a long period of time to become widely adopted(Rogers, 1995). Rogers further emphasizes that increasing the diffusion rate of an innovationis a common problem for potential adopters of that innovation.

The process of innovation diffusion is different when the innovation is generated bythe organization; in that case, the main stages include: the stages of idea generation, projectdefinition, design, development, and marketing and commercialization (Cooper & Kleinchmidt,1990). In the case of adoption of an innovation which has been developed outside theorganization the stages will be: awareness of innovation, attitude formation, evaluation,decision to adopt, trial implementation, and sustained implementation (Zaltman et al., 1973).Furthermore, Wolfe (1994, p. 411) added that when innovation is generated in the organizationthe stages “tend to be mulled and overlapping,” while in the case of adoption the stages “tendto occur in the expected order.” Depending on whether the innovation is generated withinor adopted by an organization, two alternative general models can be formulated to describethe diffusion process.

An important contribution is made by Rogers (1995), who suggests there are six phasesfor the diffusion of an innovation, including: recognition of a problem or need, basic andapplied research, development, commercialization, diffusion and adoption, and conse-quences. However, he emphasizes that these six phases are somewhat arbitrary, as they mightnot always occur in order and some of them might be skipped in the case of particularinnovations. An innovation development consists of all decisions and activities and theirimpacts that occur during these phases. These suggested stages for innovation developmentare largely consistent with the generation approach of Damanpour and Gopalakrishnan(1998).

312 Askarany


Zahra and Covin (1994) adopt a different perspective suggesting that there are threemajor sources of innovation: imitative, acquisitive, and incubative. They define these threemajor sources of innovation as follows. Imitative sources are those innovations that are firstintroduced by other firms and then copied by organizations. Acquisitive sources also includethose innovations that have been developed by other firms but are acquired throughpurchase, licensing, acquisition, or merger. Finally, incubative sources are those innovationsthat have been developed in organizations for their own use. This categorization is compatiblewith the generation and adoption approach of Damanpour and Gopalakrishnan (1998) in that“imitative innovations” and “acquisitive innovations” can be classified as “adopted”innovations and “incubative innovations” as “generated” ones.

From a process point of view, Rogers (1995) divides the innovation process inorganizations into two sub-processes: an initiation process and an implementation process.The initiation process itself includes two stages: agenda-setting and matching. These twostages involve all activities, such as information gathering, conceptualizing, and planningfor the adoption of an innovation. The implementation process includes three stages:redefining/restructuring, clarifying, and routinizing. These three stages contain all of theactions, events, and decisions involved in implementing an innovation. This classificationis again consistent with the adoption method explained by Damanpour and Gopalakrishnan(1998).

Given the compatibility of the alternative diffusion methods suggested by Zahra andCovin (1994), Rogers (1995), and Damanpour and Gopalakrishnan (1998), innovation diffu-sion will be categorized into two separate groups of generation approach and diffusionapproach, illustrated as Figures 1 and 2, respectively.

Given this classification, the diffusion of an advanced technique as an innovation(either as a generation or an adoption approach) in an organization is influenced by a varietyof factors. The next section identifies a variety of influencing factors addressed in theliterature.

INFLUENCING FACTORSAn advanced technique as an innovation may not simply emerge and develop full-

blown. Some groups of people, some places, or some organizations have immediate accessto the advanced techniques, some access them later, and some never do. As Schumpeter(1934) remarked, an innovation and its diffusion are part of a larger pattern of social, political,and economic activity. So, it is expected that the diffusion of an innovation is influenced bya variety of factors. It is also noticeable that the characteristics of an innovation and factorsinfluencing its diffusion change over time, rather than remaining static. The following areamong the most important influencing factors that have been addressed in the literature.

The Overall Benefits and UncertaintyIt has been suggested that the rate of diffusion of an innovation is a function of the

degree of uncertainty associated with the innovation, the amount of investment required toadopt the innovation, and the extent of economic advantage of the innovation (Askarany &Smith, 2000b; Mansfield, 1961; Moore, 1991; Rogers, 1995). Askarany and Smith (2000b)found that the degree of uncertainty associated with the innovation was one of the hinderingfactors in the diffusion of cost and management accounting techniques in Australia.



Supply and Demand RationaleSome researchers, like Brown (1981), Griliches (1957), and Robinson and Lakhani (1975),

proposed a supply and demand rationale as an explanation of diffusion rate. Brown (1981)explained that the market and infrastructure factors exist in the supply side of diffusion andshape its course. He further emphasized that the central element of supply framework is thediffusion agency.

Clark (1984) believes that the demand approach in the diffusion process is more diverseand more extensive. It focuses on the adoption of innovations that are available to everyone.He thinks the supply approach is dealing with cases where the innovation is not universallyavailable due to the fact the supply is under control. In other words, when every potentialadopter of an innovation does not have equal access to an innovation, supply factor mightbe considered as an important influencing factor in the diffusion process of that innovation.

Learning Perspective and Information TransferExplanation

The learning perspective has been introduced as another factor affecting the diffusionrate of an innovation by Casetti and Semple (1969) and Sahal (1981). Expanding the scope ofinfluencing factors, Hagerstrand (1967) and Bernhard and MacKenzie (1972) proposed aninformation transfer explanation as being a factor that influences the diffusion rate. Someother researchers like Blackman (1972) and Sharif and Kabir (1976) considered the diffusionof an innovation as a replacement process and claimed that the dynamics of this replacementprocess account for the diffusion rate during the diffusion period. However, in some cases,

Idea generation

Project definition

Design

Development

Marketing and commercialisation

Figure 1: Generation of Innovation

Figure 2: Adoption of Innovation

Awareness ofinnovation

Attitude formation

Evaluation

Decision to adopt

Trial implementation

Sustained implementation

314 Askarany


an innovation might be an addition to an employed technique or an ongoing capacity andnot a complete replacement.

Continuity of the Innovation ProgressSurprisingly, continuity of the innovation progress as an influential factor is suggested

to have a negative impact on the diffusion of an innovation. Brown (1981, p. 158) confirmsthat “deliberation and slowness in the adoption decision is encouraged by the continuity ofthe innovation process which results in many improvements during the course of diffusion.”Rosenberg (1976) also confirms that there is often a delay in adoption because of theexpectation of future improvements in the innovation. He emphasizes that the expectationof continued improvement might lead to a slowing down in the rate of diffusion of aninnovation.

In line with the above suggestion, it can be argued that the slow initial rate of thediffusion is likely to reflect the time needed to improve the innovation and supply it to thepotential users. In this case, delays and caution can be justified because such improvementsare anticipated, in much the same way as computer purchases might be postponed in theexpectation of imminent product improvements. It can be concluded that one of the factorsinfluencing the diffusion rate of an innovation is the outcome of a rational decision-makingprocess that expects that tomorrow’s innovation is likely to have more advantages thantoday’s.

However, the idea of negative impact of continuity of improvement on the diffusion ofan innovation is not consistent (Brown, 1981; Innes & Mitchell, 1995; Rosenberg, 1976).Brown (1981) argues that an innovation is generally crude and inefficient when it is firstdeveloped, and it might offer few or no advantages over the existing ones. He concludes thatthe continued improvements during the diffusion process are very important and might leadto an increase in the adopters or the rate of diffusion. So, continuity in the improvement ofan innovation might have both a negative and a positive influence on the diffusion of thatinnovation. It seems very difficult to measure such influences and give a preference to thenegative or positive influence of such impact. For example, the continuity of the improvementof a technique might encourage those who are not usually seen as adopters of that specialtechnique to implement it. Meanwhile, such improvement might lead potential adopters topostpone implementation of the technique based upon having the knowledge that tomorrow’stechnique is likely to be considerably better than today’s.

Resistance to ChangeAttitudes of employees and their resistance to change has been introduced as another

factor that might result in lags in the use of innovation or a slow rate of diffusion (Askarany& Smith, 2000b; Brown, 1981; Foster & Gupta, 1990; McGowan & Klammer, 1997; Shields,1995). The development of technical skills and learning perspective among users has beensuggested to reduce employees’ resistance and to facilitate the diffusion of an innovation(Bernhard & MacKenzie, 1972; Blackman, 1972; Brown, 1981); Casetti & Semple, 1969;Hagerstrand, 1967; Sahal, 1981; Sharif & Kabir, 1976).

ProfitabilityAnother factor influencing the diffusion of an innovation is said to be profitability.

Linstone and Sahal (1976) propose that the more profitable the innovation and the smaller



the required investment, the greater the rate of the diffusion. Profitability of an innovationcan be interpreted as cost saving, relative advantage, or cost effectiveness of that innovation.Considering conventional investment theory, Brown (1981) suggests that the rate ofdiffusion for an additional innovation is expected to be greater than the rate of diffusion fora replacement innovation, because in the case of replacement, industry already has a sunkcost to be amortized or written off. Therefore, it can be concluded that since new firms do nothave such a sunk cost, they are more likely to implement a new technique (innovation) thanthe older firms, which have already implemented an old technique.

Technological FactorsAccording to Brown (1981), technological factors are other elements that influence

diffusion of innovations. He explains these technological factors as the continuity ofinventive activity, the development of technical skills among users, the development of skillsin machine making, complementarities and improvements in old technologies.

CompetitionCompetition is said to be another factor influencing the diffusion rate of an innovation

(Anderson, 1995; Booth & Giacobbe, 1998; Innes & Mitchell, 1995; Krumwiede, 1998; Libby& Watherhouse, 1996; Parker, 1974). Parker (1974) states that some of the early adoption takesplace because certain firms wish to gain an advantage over their competitors. Then, lateradopters follow the adoption either to remain competitive or to take advantage of theinnovation.

Characteristics of InnovationDiffusion of an innovation is also expected to be affected by its characteristics

(Anderson, 1995; Chenhall & Langfield-Smith, 1998; Innes & Mitchell, 1995; Moore, 1991;Rogers, 1995; Shields, 1995; Tornatzky & Klein, 1982). Rogers (1995) has identified fiveaspects of an innovation that affect its rate of diffusion in a population to whom the innovationis relevant. He argues that the high rate of diffusion of an innovation would be a feature ofits “relative advantage” over the current practice, its “compatibility” with other aspects ofthe culture, its “complexity” to understand, and its “trialability” to experience its “observability”to see the results.

Among these five aspects, relative advantage is the most difficult concept to describe.From the profitability point of view, relative advantage may refer to the profitability of aninnovation over various periods of time, such as short-term and long-term profitability, whichmay not be the same. Relative advantage may also refer to a necessary investment for aninnovation’s capital cost in comparison with the required investment of other techniques orits effects on the current cost of the system. Relative advantage of an innovation can alsoextend to aspects other than profitability, such as time reduction, being easily accessible,being comfortably useable, achieving popularity for an organization, attracting the population’strust, and many more. So, it seems difficult to measure all these relative advantages of aninnovation in all aspects over various periods of time (Rogers, 1995).

Flexibility or capability of modification of an innovation, which can be classified asanother characteristic of innovations, is said to be an important factor influencing thediffusion of an innovation. Kimberly and de Pouvoirville (1993) suggest the capability of

316 Askarany


modification of an innovation increases the chance of its widespread diffusion amongpotential adopters. They further emphasize that the different context and society will createdifferent needs, so the more an innovation can be adapted to meet these changed circum-stances, the higher the diffusion rate will be.

It can be argued that type of innovation is another element that might influence itsdiffusion speed. An innovation can be cost effective in a special society or for firms ororganizations for a certain size. It can be concluded that although the size of the firms couldinfluence the diffusion rate of an innovation, the type of innovation might also play animportant role in that influence.

AwarenessIt can be argued that awareness of an innovation as a possible solution for a problem

or as an available technique for progress can also impact on the diffusion rate of an innovation(Askarany & Smith, 2000b; Booth & Giacobbe, 1998; Brown, 1981). Sometimes, potentialadopters of an innovation might be aware of existence of an innovation but have little or noknowledge about its capabilities and characteristics to see it as a possible solution for theirneeds. By providing such information, it seems likely that the number of adopters wouldincrease, and innovation would gain a higher rate of diffusion. This argument is compatiblewith the supply approach of analysis of diffusion provided by Brown (1981), who suggestedthat the more widespread a marketing strategy, the faster build-up of sales and the fasterdiffusion rate.

Structural, Process, and Cultural ComponentsClark (1984) classified diffusion studies into three categories: structural, process, and

cultural components of innovation diffusion. He suggested that under process components,the slow adoption of an innovation might be the result of a few factors. Examples of thesefactors follow: weak communication system, low relative advantages of the innovation, highprice of an innovation, high expectations of immediate improvement to the system. Understructural and cultural components of innovation diffusion, innovation is defined in itsbroadest context as both a product of and an influence on a particular structure or cultureof a society. So, the diffusion rates of an innovation under these approaches are not limitedto the characteristics of innovations. It can be influenced by conditions of a society oreconomy. Groups and individuals in a society bring forward innovations and createconditions to increase the diffusion rate of the innovations. In return, innovations alter social-economic conditions.

Regarding the influence of structural and cultural factors on the diffusion of innovation,Goss (1979) and Gotsch (1972) argued that there should be less emphasis on the role of theinnovation itself and more on the spatially variable character of the society into which theinnovation is introduced. They believed that the diffusion rate of an innovation depends lesson the nature of innovation than on the type of society before the innovation. On the contrary,Rogers (1995) believes that the diffusion rate of an innovation depends more on itscharacteristics than any other influencing factors.

Aggressiveness and InnovativenessAggressiveness and innovativeness of management are mentioned as other influenc-

ing factors in the diffusion process. Brown (1981) suggested that aggressiveness and



innovativeness of the management of an organization or firm influences the diffusion rate ofan innovation. He further introduced the availability or provided level of information aboutthe innovation as another factor influencing the diffusion rate of an innovation. Thisinformation generally creates an awareness of the innovation, reduces uncertainty, and helpsfirms to appraise the costs and relative advantages of the innovation.

Availability and Distribution of ResourcesSeveral studies have indicated that availability of an innovation influences its diffusion

(Askarany & Smith, 2000b; Innes & Mitchell, 1995; Shields, 1995). Askarany and Smith(2000b) found that from organizations’ point of view, availability of innovation received thefirst priority among the hindering factors responsible for the diffusion of innovation.However, Clark (1984) places more emphasis on the effect of the cost of an innovation(required funding or investment for an innovation) on its diffusion rate. He explains that onlya few innovations out of all that are devised and tested will get the public or private fundingneeded to take the idea to market. Further, he concludes that innovations that are developedto the market and gain a high rate of spread are those that are interesting to people who controlthe disbursement of public and private funds.

Confirming the above suggestion, Yapa (1976) indicated that the availability anddistribution of resources or individual access to the means of production and public goodsaffect the diffusion of an innovation. Examples of resources in this context would includecapital, information, public goods or services such as electricity, transportation, watersystem, network communication, and education.

CommunicationCommunication is another influencing factor that could facilitate or hinder the diffusion

of an innovation (Anderson, 1995; Brown, 1981; Kimberly & de Pouvoirville, 1993; Rogers,1995; Shields, 1995). Emphasizing the role of communication in the diffusion of innovation,Kimberly and Associates (1993) explain that strong communication informs more potentialadopters of the existence of an innovation immediately, and this could increase the overallrate of the adoption of the innovation.

Social Development of SocietyThe level of development of a society might influence the diffusion rate of an innovation

(Anderson, 1995; Chenhall & Langfield-Smith, 1998; Gosselin, 1997; Innes & Mitchell, 1995;Malmi, 1997; Tornatzky & Klein, 1982). Brown (1981) argued that the speed with which aninnovation diffuses through a population depends upon its correspondence with thedevelopment level, personal characteristics, and social norms associated with that popula-tion. He further emphasized that, as personal characteristics and social norms relevant toinnovation diffusion are themselves related to the level of development, the critical factorinfluencing the speed of an innovation might be the level of development of the society. So,in general, it might be suggested that the higher the level of development in the society, thefaster the diffusions spread.

Size of OrganizationsSize is one of the most controversial influencing factors in the literature. Some

authors argue that large firms have several advantages over smaller firms in the

318 Askarany


adoption of an innovation (Brown, 1981), while some other authors argue thatdiffusion of innovation in small firms is quicker than large firms because of theadvantages of small size (Acs & Auderetsch, 1988; Julien, 1993; Lefebvre &Lefebvre, 1993; Riding, 1993). However, the controversy on the impact of size onthe diffusion of innovation has been increased by the mixed results of the studiesinvestigating the relationship between size as an influential factor and the diffusionof innovation (Aiken, Bacharach, & French, 1980; Blau & McKinley, 1979; Booth& Giacobbe, 1998; Damanpour, 1992; Dewar & Dutton, 1986; Hage, 1980;Krumwiede, 1998; Libby & Watherhouse, 1996). This demands further researchon the relationship between size and diffusion of innovation.

CATEGORIZATION OF INFLUENCINGFACTORS IN DIFFUSION PROCESS

A variety of potential factors that might influence the diffusion of an innovation wereaddressed in the previous section. Although ignoring the impact of any of those influencingfactors on the diffusion of an innovation process in any diffusion research might reduce theability of such research to offer an appropriate model or suggestion for the current or futurestatus of the innovation, it is more appropriate to categorize the influencing factors intosmaller groups, based on some common characteristics or criteria.

Wolfe (1994) defined the diffusion of an innovation as a process in which an innovationspreads through a population of potential adopters. Two main elements in this definition are:innovation and adopters.

It is possible to categorize most of the influencing factors (explained in the previoussection) into these two categories. However, there are some factors, such as the level ofdevelopment of society, communication channels and change agents, that are more relatedto the social system than these two categories. Given that, this chapter categorizes allinfluential factors into three main categories: factors related to the characteristics ofinnovation (attributes of innovations), factors related to the adopters of innovation (at-tributes of adopters), and factors related to the social system (attributes of social systems)in which diffusion is taking place. It would be appropriate, therefore, to classify theinfluencing factors based on their probable relationship with these three main elements:innovations, the adopters of innovations, and the social system.

(a) Attributes of InnovationsUnder this classification, the primary influential factors in a diffusion process that might

be categorized under factors related to the innovation are characteristics of innovations suchas: relative advantage, compatibility, complexity, trialability, and observability. Other influ-encing factors that could be closer to the innovation category than other categories mightinclude factors such as:• the degree of uncertainty associated with the innovation,• the amount of investment required to adopt the innovation,



• the extent of economic advantage of an innovation,• continuity of the innovation progress,• overall benefit of an innovation (including economic and non-economic advantage of

an innovation),• reinventing and dynamics aspects of innovations,• profitability,• flexibility and capability of modification of an innovation,• availability of an innovation and the information about it for potential adopters, and

the type of innovation.

Categorizing all of the attributes of an innovation as a separate group influencing itsdiffusion is consistent with Rogers’ classification of influencing factors. However, researchon the impact of attributes of innovations on their diffusion has received scant attention inthe literature. According to Rogers (1995), an accumulated body of literature on diffusionindicates that much effort has been devoted to studying the innovativeness and determiningthe characteristics of adopters, while relatively little effort has been spent in investigatinghow the “properties” of innovations affect their rate of adoption. He further emphasizes thatthis second type of research can be of great value in predicting potential adopters’ reactionsto an innovation. He confirms that diffusion researchers in the past have oversimplifiedinnovation units by considering them as equivalent units from the viewpoint of theiranalyses.

Although, characteristics of innovations include more than five factors, Rogers (1995)suggests that the main attributes of innovations can be described by five characteristics. Inorder to see whether these five factors can explain the main attributes of innovations, it seemsuseful to understand how they are defined by Rogers. Relative advantage, as one attributeof innovations, is explained as the degree to which an innovation seems to be better than theidea that is replacing. Subdimensions of relative advantages include social prestige, savingsin time and efforts, low initial cost, the degree of economic profitability, increase in comfortor decrease in discomfort, and the immediacy of the output. However, it is difficult todemonstrate all potential relative advantages of an innovation as some of them might not beapparent prior to implementation. CLOSE UP SPACE……………

Compatibility, as another characteristic of innovations, refers to the degree of consis-tency of an innovation with the needs, expected values, and the norms of potential adoptersand their social systems. Complexity can be explained as the degree to which an innovationseems difficult to understand and use. Trialability as the fourth characteristic of aninnovation is defined as the degree to which an innovation can be tried on a limited basisbefore full implementation. The fifth characteristic of an innovation, observability, refers tothe degree to which the results of an innovation can be observed by potential adopters.

Among these five characteristics of innovation, four (complexity being the exception)are expected to be positively related with the diffusion of an innovation. The diffusion of aninnovation in a particular population is usually measured by its rate of implementation.According to Brown (1981), diffusion rates are often measured in terms of the proportion offirms using a new technique (an innovation) as compared with those using the old ones.Rogers (1995) reviewed and classified most of the diffusion studies prior to 1995, andconcluded that the diffusion rate of innovations can be explained by these five characteristicsof innovations. He defined the rate of adoption as the relative speed of adoption of aninnovation by its potential adopters. He explained the rate of adoption as a numerical indicator

320 Askarany


that is generally measured by the number of adopters who adopt an innovation during aspecified period of time. However, he emphasized that scant diffusion research has beenundertaken to identify the influence of characteristics of innovations on their diffusion Thissupports further research into the impact of influencing factors (especially attributes ofinnovations) on the diffusion of innovation.

It might be concluded from this section that attributes of innovations as a group ofinfluencing factors are claimed to be of significant importance to the diffusion of innovations.It was also suggested that relatively little effort has been spent in investigating how theproperties of innovations affect their rate of adoption (Rogers, 1995). So, consistent withRogers, this chapter emphasizes that research on the influence of “characteristics ofinnovations” can be of great value in predicting potential adopters’ reactions to aninnovation and providing appropriate suggestions for a better diffusion.

(b) Characteristics of AdoptersWith regard to the influencing factors that have been addressed in the literature and

research studies undertaken on diffusion of innovation in organizations, a number ofinfluencing factors can be related to the adopters of innovations. Factors related to theadopters of innovations in a broad definition could be included in three main characteristicsof organizations: organizational strategy, organizational structure and organizational culture.In other words, most of characteristics of organizations can be explained by these threecategories. These categories might include factors such as: the size of organizations, theaggressiveness and innovativeness of their managers, level of information about theinnovation, the learning perspective of organizations, information transfer explanation byorganizations, resistance to change, technical skills of the users of an innovation inorganizations, competition, and awareness of an innovation as a possible solution or as anavailable technique for progress.

Although Rogers (1995) did not categorize time as an influencing factor on the diffusionof innovation process, he introduced it as one of the main elements in the diffusion process.He suggested that the time dimension relates to three aspects of a diffusion process: theinnovation decision process, the innovativeness of adopters, and the rate of adoption in asystem. Rogers emphasized that time factors are central to the five main steps in an innovationdecision process: knowledge, persuasion, decision, implementation, and confirmation. Heclassified innovation-decisions into three main types: optional, collective, and authorityinnovation decisions and believes that time is involved in each type. He further explained thattime also plays a major role in innovativeness, which is the degree to which an individual orother unit of adoption is relatively earlier in adopting new ideas than the other members ofthe system. He classified the members of a social system on the basis of innovativeness, intofive categories: innovators, early adopters, early majority, late majority, and laggards. Thediffusion of an innovation is the third particular aspect of a diffusion process in which timeis involved.

Classifying all characteristics of adopters as an influencing group is consistent with thesecond category of Rogers’ classification (the type of innovation-decision). However,factors associated with this category are far more than the type of innovation-decision factor.For example, most of the recent research on the impact of contextual factors on the diffusionof innovation confirms the significance of the influence of adopters’ attributes (such asorganizational structure, organizational culture, and organizational strategy) on the diffusion



of innovations (Bjornenak, 1997; Damanpour & Gopalakrishnan, 1998; Gosselin, 1997;Hoffman, 1999; Smith, 1998).

Besides attributes of both innovations and innovators, Rogers’ classification ofinfluencing factors includes three more categories. In general, he categorizes all factorsinfluencing the diffusion of innovations into five categories: (1) attributes of innovations;(2) the type of innovation decision; (3) the nature of communication channels; (4) the natureof social system; and (5) the extent of change agents’ promotion efforts. However, he claimsthat 49% to 87% of the variance in adoption rate of innovations can be explained by theirattributes (relative advantage, compatibility, complexity, trialability, and observability). Hebelieves that the rest of the variance (13% to 51%) in diffusion of an innovation can beexplained by the other four influencing factors. In other words, despite paying less attentionto the adopters’ attributes, Rogers does pay full attention to the role of innovation attributesin a diffusion process. He not only gives the most weight to the influencing factors associatedwith the innovation category, but also argues that the attributes of innovations are the mostimportant factors among these influencing factors that are able to explain the diffusion ofinnovations. Furthermore, Rogers (1995) suggests that the considerable amount of researchalready devoted to the characteristics of “adopters” has failed to explain the diffusionprocess. He suggests that future research should focus more on the innovation decisionprocess and the nature of the innovations itself.

(c) Attributes of Social Social SystemsThe level of development of a society, communication channels in a society, social

concerns, change agents, opinion leaders, and social norms might be classified into the socialsystem factors. It might be possible to categorize all of the influential factors that could notbe either related to the innovation category or the adopters category under a social systemcategory. This section explains the rest of the four main elements of the diffusion process(the innovation, communication channels, time, and the social system) as presented byRogers (1995) that have not been classified under the two other groups of influencing factors.

Rogers (1995) classified communication channels, change agents, and social system asseparate influential factors in a diffusion process approach. He explained communicationchannel as the process of providing and sharing information by and between participantsfor better understanding. In other words, a communication channel is the means throughwhich new ideas are exchanged between one individual and another. Rogers emphasizes thatdiffusion is a particular type of communication that deals with the exchange of new ideas. Hefurther explained that a diffusion process involves four factors: an innovation, an adopterwho already knew about the innovation or adopted it, another potential adopter who has notyet experienced the innovation, and a communication channel that is able to connect thesetwo adopters.

Another main element of the diffusion process in Rogers’ definition of diffusion is socialsystem. Rogers defined a social system as a group of individuals that are interconnected andwork together to achieve a common goal. He further explained the main factors in a socialsystem that might influence the diffusion process of innovations. These factors include:social structure, system norms, opinion leaders, and change agents. However, classifyingone influencing factor into one category does not deny the existence of any relationshipbetween that factor and the other influencing factors in other categories. It should beremembered that an innovation and its diffusion are part of a larger interrelated pattern of

322 Askarany


social, political, and economic activity. So, some influencing factors might be influenced byor influence other factors.

Given the above classification, the general diffusion model in Figure 3 can be developed.Adopting the general diffusion model, Table 1 illustrates the majority of influencing

factors addressed in the literature as hindering or facilitating factors and classifies them intothree categories as shown on the following page.

Taking into account different type of innovations and different stages of the diffusionprocess, the previous basic model can be refined and developed to the general modelillustrated on page 324 through 328.

Under this model, in general, what makes one diffusion research different from anotherdiffusion research is the type or group of influencing factors and the kind or the number ofadvanced techniques. So, depending on the type of influencing factors and kind of advancedtechniques, a more detailed model can be adopted from the above general model and modifiedto tailor a specific diffusion research. Also, depending on the research approaches (genera-tion of innovation or adoption of innovation), the central focus of the research might change.

AN EXAMPLE OF DIFFUSION OFADVANCED TECHNIQUES

Recent studies on the diffusion of advanced management accounting techniques maybe considered as an example to fit the general diffusion model developed in this chapter. Anoverview of these studies is also expected to provide further evidence to identify the mostsignificant influencing factors responsible for the diffusion of advanced techniques inorganizations.

Intensified global competition, along with advanced manufacturing practices such asflexible manufacturing systems (FMS), computer-integrated manufacturing (CIM), andcomputer-aided design (CAD), has led many authors and practitioners to criticize theefficiency and capability of traditional cost and management accounting practices in copingwith the requirements of the current, ever-changing nature of global environment (Beng,Schoch, & Yap, 1994; Bork & Morgan, 1993; Gosselin, 1997; Hartnett & Lowry, 1994;Horngern, Foster, & Datar, 1994 Lefebvre & Lefebvre, 1993; Spicer, 1992). In reply to thesecriticisms, several advanced management accounting techniques, such as activity-basedcosting; target costing, and the balanced scorecard, have been introduced during this period.However, a progressing major concern regarding the diffusion of these innovations has ledmany authors to establish different investigations into the diffusion of recently developedcost and management accounting practices (e.g., Anderson & Young, 1999; Askarany &Smith, 2000a; Bjornenak, 1997; Booth & Giacobbe, 1998; Chenhall & Langfield-Smith, 1998;Cooper & Kaplan, 1991; Damanpour, 1987, 1988; Damanpour & Gopalakrishnan, 1998;Gosselin, 1997; Hartnett & Lowry, 1994; Malmi, 1999). Yet, the results of these studies haveat best been equivocal and, at worst, contradictory, with no study able to provide plausiblereason(s) to justify the majority of variance in diffusion process of cost and managementaccounting techniques.

Most of the studies on diffusion of cost and management accounting innovationsreported some kind of relationship between diffusion of cost and management accountinginnovation and some influencing factors such as organizational, structural, and cultural



factors. However, no significant influencing factor explaining the majority of variance indiffusion processes has been reported. For example, Booth and Giacobbe (1998) found nosupport for the impact of a variety of influencing factors classified as “demand and supplyfactors” on the diffusion of accounting innovations. In their study, Booth and Giacobbe(1998) investigated the impact of cost structure, product diversity, and competition (termed“demand factors”) and rhetoric, firm size and information source (termed “supply factors”)on the diffusion process of activity-based costing (ABC). Although they found one demandfactor—the current level of overhead—and one supply factor—firm size—to influence theinitiation of interest in ABC adoption, no demand or supply factors were found to influencethe adoption of ABC as a practice.

Some studies on diffusion of cost and management accounting innovation eitherproduced a mixed result or suggested further investigation regarding the impact of thoselimited number of influencing factors that have been under investigation. For example, studiesinvestigating the relationship between size as an influential factor and innovation haveproduced mixed results. Hage (1980) found a negative relationship between size andinnovation, while Aiken, Bacharach and French (1980) reported a non-significant relation-ship. In contrast, Blau and McKinley (1979), Dewar and Dutton (1986), and Damanpour (1992)found a positive relationship between size and innovation. Interestingly enough, Gosselin(1997) reported a different relationship between size and innovation process during thedifferent stages of innovation of activity management (AM) (which includes activityanalysis, activity cost analysis, and ABC). In other words, he found a significant indirectassociation between size and innovation at the state of adoption of AM in general, while atthe stage of adoption of ABC, he found no significant relationship between size andinnovation. According to these results, the impact of organizational size on the diffusion ofaccounting innovation seems to be ambiguous.

The identification of a number of hindering and facilitating factors in the diffusionprocess of cost and management accounting innovations was expected to speed up diffusionof recently developed cost and management accounting innovations. However, despiteintroducing several recently developed cost and management accounting techniques duringthe last two decades, the application rates of these techniques are still lower than those oftraditional techniques (Askarany & Smith, 2000c; Chenhall & Langfield-Smith, 1998). Forexample, it has been estimated that only around 10% of organizations that adopt some kindsof cost and management accounting innovations such as activity-based costing continueto use it (Anderson & Young, 1999; Ness & Cucuzza, 1995). This is while many users oftraditional cost and management accounting techniques are not satisfied with their current

INOVATORS INOVATIONS SOCIAL SYSTEM

DIFFUSION OF ADVANCED TECHNIQUES

Figure 3: Basic Diffusion Model

324 Askarany


Table 1: Influencing Factors in Diffusion Process

Characteristics of innovations Reference(s) Availability of innovation Askarany and Smith, 2000b; Innes and Mitchell,

1995; Shields, 1995 Average years needed Foster and Swenson, 1997 Compatibility with existing systems

Anderson, 1995; Chenhall and Langfield-Smith, 1998; Innes and Mitchell, 1995; Moore, 1991; Rogers, 1995; Shields, 1995; Tornatzky and Klein, 1982

Complexity to understand Anderson, 1995; Innes and Mitchell, 1995; Rogers, 1995; Tornatzky and Klein, 1982

Cost saving Brown, 1981; Rogers, 1995; Sahal, 1981 Divisibility

Davis, 1986; Moore, 1991; Rogers, 1995; Tornatzky and Klein, 1982

Image Moore, 1991 Maintaining cost of innovation Askarany and Smith, 2000b Observability to see the results Rogers, 1995; Tornatzky and Klein, 1982 Perceived ease of use Davis, 1986; Moore, 1991; Rogers, 1995 Perceived usefulness Davis, 1986; Booth and Giacobbe, 1998; Moore,

1991; Rogers, 1995 Quality of innovation information McGowan and Klammer, 1997 Relative advantage over the current practice

Anderson, 1995; Brown, 1981; Innes and Mitchell, 1995; Krumwiede, 1998; Sahal, 1981; Rogers, 1995; Tornatzky and Klein, 1982

Relevance to manager’s decisions Anderson, 1995; Chenhall and Langfield-Smith, 1998; Foster and Swenson, 1997; Innes and Mitchell, 1995; Krumwiede, 1998; Moore, 1991; Rogers, 1995; Shields, 1995

Sales revenue Innes and Mitchell, 1995 The amount of investment required to adopt the innovation

Anderson, 1995; Askarany and Smith, 2000b; Innes and Mitchell, 1995; Mansfield, 1961; Moore, 1991; Shields, 1995

The continuity of the innovation progress

Brown, 1981; Innes and Mitchell, 1995; Rosenberg, 1976

The degree of uncertainty associated with the innovation

Askarany and Smith, 2000b; Mansfield, 1961; Moore, 1991

The extent of economic advantage and profitability of the innovation

Brown, 1981; Mansfield, 1961; Moore, 1991; Rogers, 1995; Sahal, 1981; Tornatzky and Klein, 1982



The overall benefits of an innovation

Askarany and Smith, 2000b; Mansfield, 1961; Moore, 1991; Rogers, 1995

Trialability to experience Rogers, 1995; Tornatzky and Klein, 1982 Characteristics of innovators Reference s Adequacy of current system/ technique

Askarany and Smith, 2000b

Aggressiveness and innovativeness

Brown, 1981

Attitudes of employers, worker responsibility/risk

Anderson, 1995; Foster and Gupta, 1990

Attitudes of manager Askarany and Smith, 2000b; Foster and Gupta, 1990

Availability and distribution of resources

Clark, 1984; Yapa, 1976

Awareness Askarany and Smith, 2000b; Booth and Giacobbe, 1998; Brown, 1981

Behavioral factors McGowan and Klammer, 1997; Shields, 1995 Capacity to learn Libby and Watherhouse, 1996 Centralized decision making Anderson, 1995; Gosselin, 1997 Commitment Anderson, 1995; Foster and Swenson, 1997 Competition Anderson, 1995; Booth and Giacobbe, 1998; Innes

and Mitchell, 1995; Krumwiede, 1998; Libby and Watherhouse, 1996; Parker, 1974

Cross-functional support Foster and Swenson, 1997; Innes and Mitchell, 1995; Shields, 1995

Decentralisation Libby and Watherhouse, 1996 Degree of decision usefulness of cost information

Krumwiede, 1998

Degree of lean production system implementation

Krumwiede, 1998

Degree of potential for cost distortions

Krumwiede, 1998

Degree of total quality management implementation

Krumwiede, 1998

Development of technical skills among users

Brown, 1981

Dissatisfaction with current system

Booth and Giacobbe, 1998

Education Askarany and Smith, 2000b; Argyris and Kaplan, 1994

Table 1: Influencing Factors in Diffusion Process (Continued)

326 Askarany


Formalized job procedure Anderson, 1995; Gosselin, 1997; Krumwiede, 1998

Functional specialization Anderson, 1995; Shields, 1995 Heterogeneity of demands Anderson, 1995; Chenhall and Langfield-Smith,

1998; Gosselin, 1997; Innes and Mitchell, 1995; Krumwiede, 1998

Implementation involvement Anderson, 1995; Foster and Swenson, 1997; McGowan and Klammer, 1997

Information system quality Anderson and Young, 1999; Krumwiede, 1998 Institutional pressures for innovation


Internal communication Anderson, 1995 Job uncertainty Anderson, 1995; Foster and Swenson, 1997;

Krumwiede, 1998; Shields, 1995 Level of clarity and consensus for innovation objectives

Krumwiede, 1998

Linkage to evaluation Shields, 1995 Linkage to quality initiative Shields, 1995 Need for change Anderson and Young, 1999; Askarany and Smith,

2000b; Booth and Giacobbe, 1998 Number of purposes identified for innovation

Krumwiede, 1998

Organizational culture Clark, 1984; Foster and Swenson, 1997; Goss, 1979; Gotsch, 1972; Hoffman, 1999; Rogers, 1995; Smith, 1998

Organizational factors Anderson, 1995; Chenhall and Langfield-Smith, 1998; Clark, 1984; Foster and Swenson, 1997; Goss, 1979; Gotsch, 1972; Malmi, 1997; Rogers, 1995; Shields, 1995

Organizational strategy Bjornenak, 1997 Organizational structure Clark, 1984; Damanpour and Gopalakrishnan,

1998; Goss, 1979; Gotsch, 1972; Rogers, 1995; Smith, 1998

Presence of an internal champion Booth and Giacobbe, 1998 Pressure from consultants for innovation


Product diversity Booth and Giacobbe, 1998 Production process knowledge Anderson, 1995 Prospector strategy Gosselin, 1997





Resistance to change Anderson, 1995; Askarany and Smith, 2000b; Brown, 1981; Foster and Swenson, 1997; Innes and Mitchell, 1995; Malmi, 1997

Resource adequacy Anderson and Young, 1999; Booth and Giacobbe, 1998; Foster and Swenson, 1997; Innes and Mitchell, 1995; Shields, 1995

Reward Anderson, 1995; Anderson and Young, 1999; Foster and Swenson, 1997; McGowan and Klammer, 1997; Shields, 1995

Situational variables McGowan and Klammer, 1997 Size Booth and Giacobbe, 1998; Brown, 1981;

Krumwiede, 1998; Libby and Watherhouse, 1996 Sponsorship Argyris and Kaplan, 1994 Technical Factors Anderson, 1995; Brown, 1981; Chenhall and

Langfield-Smith, 1998; Malmi, 1997; McGowan and Klammer, 1997

The information transfer explanation

Bernhard and MacKenzie, 1972; Blackman, 1972, Casetti and Semple, 1969; Hagerstrand, 1967; Sahal, 1981; Sharif and Kabir, 1976

The learning perspective

Bernhard and MacKenzie, 1972; Blackman, 1972, Casetti and Semple, 1969; Hagerstrand, 1967; Sahal, 1981; Sharif and Kabir, 1976

Time Krumwiede, 1998 Top management support Innes and Mitchell, 1995; Krumwiede, 1998;

Shields, 1995 Training Krumwiede, 1998; McGowan and Klammer,

1997; Shields, 1995 Training investments Anderson, 1995; Foster and Swenson, 1997;

Krumwiede, 1998; McGowan and Klammer, 1997; Shields, 1995

Users preparation McGowan and Klammer, 1997 Vertical organizational structure Gosselin, 1997 Voluntariness of use Moore, 1991

Other Influencing Factors References Compensation Foster and Swenson, 1997; Competition Anderson, 1995; Innes and Mitchell, 1995;

Krumwiede, 1998; Libby and Watherhouse, 1996; Parker, 1974

Diffusion agency Brown, 1981; Clark, 1984; Griliches, 1957; Robinson and Lakhani, 1975

328 Askarany



Environmental uncertainty Anderson, 1995; Chenhall and Langfield-Smith, 1998; Gosselin, 1997; Innes and Mitchell, 1995; Malmi, 1997

External communication factors Anderson, 1995; Brown, 1981; Kimberly and Associates, 1993; Rogers, 1995; Shields, 1995

External financial or cost accounting standards or practices

Askarany and Smith, 2000b

Heterogeneity of demands Anderson, 1995; Chenhall and Langfield-Smith, 1998; Gosselin, 1997; Innes and Mitchell, 1995; Krumwiede, 1998

Institutional pressures for innovation


Market and infrastructure factors Brown, 1981; Clark, 1984; Griliches, 1957; Robinson and Lakhani, 1975

Number of primary applications Foster and Swenson, 1997 Pressure from consultants for innovation


Reward Anderson, 1995; Anderson and Young, 1999; Foster and Swenson, 1997; McGowan and Klammer, 1997; Shields, 1995

Social approval Tornatzky and Klein , 1982 Social development of society Brown, 1981 Social norms associated with that population

Brown, 1981

Sponsorship Argyris and Kaplan, 1994 Union support Anderson and Young, 1999

techniques (Beng et al., 1994; Bork & Morgan, 1993; Gosselin, 1997; Hartnett & Lowry, 1994;Horngern, Foster, & Datar, 1994; Lefebvre & Lefebvre, 1993; Spicer, 1992). This situationraises the question: What are the main influencing factors from users’ points of view thatmight be able to explain the great majority of the variance in the diffusion process and adoptionrate of cost and management accounting innovations?

To answer this question, Askarany and Smith (2000a) report on an exploratory studyin Australia that identifies characteristics of innovations as the most significant influencingfactors from the users’ points of view. Consistent with this view, Rogers (1995), reviewingthe literature on characteristics of innovations, believes that characteristics of innovationshave the most significant impact on their diffusions and the main attributes of innovationscan be described by five characteristics.



Figure 4: A General Model of Influencing Factors and Diffusion Process

Diffusion of innovation

Attributes of innovation

Attributes of adopters

Relative advantage Easy of use Trialability Observability Compatibility

Organizational Structure

Organizational Culture

Organizational Strategy

Level of development of society and social environment Communication channels change agents Opinion leaders Social norms Social concerns

Other Factors (Social system)

Generation of innovation Adoption of

innovation

Idea generation

Project definition

Design

Development

Marketing and commercialization

Awareness of innovation

Attitude formation

Evaluation

Decision toadopt

Trial implementation

Sustained implementation

FURTHER RESEARCHWhile the literature review presented in this chapter suggests the significant role of

characteristics of innovations on their diffusion, little research on relatively few character-istics of innovations has been reported in the literature (Anderson, 1995); Chenhall &Langfield-Smith, 1998; Foster & Swenson, 1997; Innes & Mitchell, 1995); Krumwiede, 1998;Shields, 1995). Furthermore, these studies neither included all characteristics of innovationsnor produced similar results. For example, Anderson (1995), in a case study at General Motors,

330 Askarany


investigated the influence of a small number of characteristics of an innovation (ABC) on itsimplementation. These factors, which Anderson classified as technical factors, include:complexity for users, compatibility with existing system, relative improvement over existingsystem, and relevance to manager decisions. Anderson found a positive relationshipbetween three characteristics of ABC including: (a) compatibility with existing system; (b)relative improvement over current system; and (c) relevance to manager decisions andimplementation. While Shields (1995) found no relationship between implementation of ABCand its compatibility with the existing system. Also, Krumwiede (1998) found no relationshipbetween implementation of ABC and its relative improvement over the current system.

Implications to AdoptersThe literature review on the impact of influencing factors on diffusion of advanced

techniques presented in this chapter reveals that there are a variety of factors influencing thediffusion processes of innovations. However, recent surveys on diffusion of advancedtechniques (e.g., Askarany & Smith, 2000a; Chenhall & Lanfield-Smith, 1998) suggest thatfactors related to the characteristics of innovations are among the first influencing factorsthat determine whether there is a need for change, innovation, and diffusion of innovation.If an advanced technique is expected to replace an applied technique, the first question inconsidering such a technique for implementation by an organization would be: What are theadvantages or disadvantages of the new technique compared to the existing technique?Indeed, before thinking about other influencing factors such as organizational culture,strategy, structures and so on, potential adopters of an advanced technique would ask aboutthe benefits that such a advanced technique is going to offer, and which might not beachievable with their current techniques. Even when no replacement is involved, thecharacteristics of that advanced technique are still among the first factors that potentialadopters would consider in adopting such an innovation. The findings indicate thatcharacteristics of innovations are important factors to organizations, managers, consultants,and other decision-makers in making decision regarding implementing such innovations.

CONCLUSIONThis chapter identified the majority of influencing factors addressed in the literature as

hindering or facilitating factors in diffusion processes of advanced techniques and devel-oped a diffusion model for further studies. The theoretical model developed in this chapterclassified all influencing factors responsible for diffusion of advanced techniques into threemain categories: characteristics of innovations, characteristics of innovators, and otherinfluencing factors that can not be categorized therein (notably factors related to socialsystem, environment, etc.).

Reviewing the results of the recent surveys on diffusion of advanced techniques (e.g.,Askarany & Smith, 2000a; Chenhall & Langfield-Smith, 1998), this chapter suggests thatcharacteristics of innovations (as a group) are the most important influencing factors in thediffusion process of advanced techniques. Further research is recommended to examine theextent of the impact of the characteristics of innovations on diffusion of advanced tech-niques.



REFERENCESAcs, Z. J. & Auderetsch, D. B. (1988). Innovation and firm size in manufacturing. Technovation,

7: 197-210.Aiken, M., Bacharach, S. B., & French, J. L. (1980). Organizational structure, work process

and proposal making in administrative bureaucracies. Academy of ManagementJournal, 23: 631-652.

Anderson, S. W. (1995). A framework of assessing cost management system changes: Thecase of activity based costing implementation at General Motors, 1986-1993. Journalof Management Accounting Research, 7: 1-51.

Anderson, S. W. & Young, S. M. (1999). The impact of contextual and process factors on theevaluation of activity-based costing systems. Accounting, Organizations and Soci-ety, 24: 525-559.

Argyris, C. & Kaplan, R. S. (1994). Implementing new knowledge: The case of activity basedcosting. Accounting Horizons, 8(3): 83-105.

Askarany, D. & Smith, M. (2000a). A critical evaluation of the diffusion of cost andmanagement accounting innovations. The International Conference on Managementof Innovation and Technology (ICMIT), (July 9-12, 2000), Orchard Hotel, Singapore,The 2000 IEEE.

Askarany, D. & Smith. M. (2000b). The impact of contextual factors on the diffusion ofaccounting innovation: Australian evidence. In Proceedings of the Sixth Interdisci-plinary Perspective’s on Accounting Conference (IPA), (November 12-15, pp. 59-64),Manchester, UK.

Askarany, D. & Smith, M. (2000c). The reality of cost and management accounting lag.Second Conference on New Directions in Management Accounting: Innovation inPractice and Research, Brussels, Belgium, European Institute for Advanced Studies inManagement (December 14-16, 2000).

Beng, A. K., Schoch, H. & Yap, T. (1994). Activity based costing in the electronic industry:The Singapore experience. Small Business and Entrepreneurship (J.S.B.E.), 11(2): 28-37.

Bernhard, I. & MacKenzie, K. (1972). Some problems in using diffusion models for newproducts. Management Science, 19(2): 187-200.

Bjornenak, T. (1997). Diffusion and accounting: The case of ABC in Norway. ManagementAccounting Research, 8: 3-17.

Blackman, A. W. J. (1972). A mathematical model for trend forecasts. TechnologicalForecasting and Social Change, 3: 441-452.

Blau, J. R. & McKinley, W. (1979). Idea, complexity, and innovation. Administrative ScienceQuarterly, 24: 165-176.

Booth, P. & Giacobbe, F. (1998). The impact of demand and supply factors in the diffusionof accounting innovations: the adoption of Activity-Based Costing in AustralianManufacturing Firms. Management Accounting Conference, Sydney, EAA AnnualConference (September).

Bork, H. P. & Morgan, M. J. (1993). Is ABC really a need not an option? ManagementAccounting London (MAC), 71(8): 26-27.

Brown, L. A. (1981). Innovation diffusion: A new perspective. New York: Methuen.Casetti, E. & Semple, R. K. (1969). Concerning and testing of spatial diffusion hypotheses.

Geographical Analysis, 1: 254-259.

332 Askarany


Chenhall, R. H. & Langfield-Smith, K. (1998). Adoption and benefits of managementaccounting practices: An Australian study. Management Accounting Research, 9: 1-19.

Clark, G. (1984). Innovation diffusion: Contemporary geographical approaches. Norwich,CT: Geo Books.

Cooper, R. Kaplan, R. S. (1991). Profit priorities from activity based costing. Harvard BusinessReview, 69(3): 130-135.

Cooper, R.G. & Kleinchmidt, E.J. (1990). New product success factors: A comparison of “kills”versus success and failures. R & D Management, 20: 47-63. Damanpour, F. (1987). Theadoption of technological, administrative and ancillary innovations: Impact of organi-zational factors. Journal of Management, 13(3): 555-590.

Damanpour, F. (1988). Innovation type, radicalness, and the adoption process. Communi-cation Research, 15: 545-67.

Damanpour, F. (1992). Organizational size and innovation. Organizational Studies, 13(3):375-402.

Damanpour, F. & Gopalakrishnan, S. (1998). Theories of organizational structure andinnovation adoption: The role of environmental change. Journal of Engineering andTechnology Management, JET-M, 15: 1-24.

Davis, F. D. (1986). A technology acceptance model for empirically testing new end-userinformation system: Theory and results. Unpublished Doctoral Dissertation, Massa-chusetts Institute of Technology, Boston, MA.

Dewar, R. D. & Dutton, J. E. (1986). The adoption of radical and incremental innovations: anempirical analysis. Management Science, 32(11): 1422-1433.

Foster, G. & Gupta, M. (1990). Activity accounting: An electronics industry implementation.Measures for Manufacturing Excellence, 225-268.

Foster, G. & Swenson, D. W. (1997). Measuring the success of activity-based cost manage-ment and its determinants. Journal of Management Accounting Research, 9: 107-139.

Goss, K. F. (1979). Consequences of diffusion innovation. Transactions of the Institute ofBritish Geographers, 59: 77-79.

Gosselin, M. (1997). The effect of strategy and organizational structure on the adoption andimplementation of activity based costing. Accounting, Organizations and Society,22(2): 105-122.

Gotsch, C. H. (1972). Technical change and the distribution of income in rural area. AmericanJournal of Agricultural Economics, 54: 326-341.

Griliches, Z. (1957). Hybrid corn: An exploration in the economics of technological change.Economics, 25: 501-522.

Hage, J. (1980). Theories of organizations. New York: Wiley.Hagerstrand, T. (1967). Innovation diffusion as a spatial process. Chicago, IL: University

of Chicago Press.Hartnett, N. & Lowry, J. (1994). From ABC to ABM. Australian Accountant (AAA), 28-33,

Melbourne, March.Hoffman, R. C. (1999). Organizational innovation: Management influence across culture.

Multinational Business Review, 7(1): 37-49.Horngern, T., Foster, C.G., & Datar, S.M. (1994). Cost accounting: A managerial emphasis.

Englewood Cliffs, NJ: Prentice-Hall.Innes, J. & Mitchell, F. (1995, June). A survey of activity-based costing in the U.K.’s largest

companies. Management Accounting Research, 137-153.



Julien, P. A. (1993). Small business as a research subject: Some reflections on knowledge ofsmall business and effects on economic theory. Small Business Economics, 5(2): 157-166.

Kellett, B. M. & Sweeting, R. C. (1991). Accounting innovation and adoptions: A U.K. case.Management Accounting Research, 2(1): 15-26.

Kimberly, J. R. & de Pouvoirville, G. (eds.)(1993). The migration of managerial innovation.San Francisco, CA: Jossey-Bass Publishers.

Krumwiede, K. R. (1998). The implementation stages of activity-based costing and the impactof contextual and organizational factors. Journal of Management Accounting Re-search, 10: 239-277.

Lefebvre, E. & Lefebvre, L. (1993). Competitive position and innovative efforts in SMEs.Small Business Economics, 5(4): 297-306.

Libby, T. & Watherhouse, J. H. (1996). Predicting change in management accountingsystems. Journal of Management Accounting Research, 8: 137-150.

Linstone, H. A. & Sahal, D. (1976). Technological substitution: Forecasting techniques andapplications. New York: Elsevier.

Malmi, T. (1997). Towards explaining activity-based costing failure: Accounting and controlin a decentralized organization. Management Accounting Research, 8: 459-480.

Malmi, T. (1999). Activity-based costing diffusion across organizations: An exploratoryempirical analysis of Finnish firms. Accounting, Organizations and Society, 24: 649-672.

Mansfield, E. (1961). Technical change and the rate of imitation. Econometrica, 29: 741-766.McGowan, A. & Klammer, T. (1997). Satisfaction with activity-based cost management

implementation. Journal of Management Accounting Research, 9: 217-237.Moore, G. C. & Benbasat, I. (1991). Development of an instrument to measure the perceptions

of adopting an information technology innovation. Information Systems Research,2(3): 193-222.

Ness, J. A. & Cucuzza, T. G. (1995). Tapping the full potential of ABC. Harvard BusinessReview, 95: 130-138.

Parker, J. E. S. (1974). The economics of innovation. London: Longman.Perera, S., Harrison, G., & Poole, M. (1997). Customer-focused manufacturing strategy and

the use of operations-based non-financial performance measures: A research note.Accounting, Organizations and Society, 22(6): 557-572.

Riding, A. (1993). Banking on technology: The environment for bank borrowing by smallCanadian technology-based firms. Journal of Small Business and Entrepreneurship(JSBE), 10(2): 13-24.

Robinson, B. & Lakhani, C. (1975, June). Dynamic price models for new product planning.Management Science, 21: 1113-1122.

Rogers, E. M. (1995). Diffusion of innovation. New York: The Free Press.Rosenberg, N. (1976). On technological expectations. Economic Journal, 86: 523-35.Sahal, D. (1981). Patterns of technological innovation. Reading MA: Addison’s Weekly.Schumpeter, J. A. (1934). –The Theory of Economic Development. Cambridge: Harvard

University Press.Sharif, M. N. & Kabir, C. (1976). A generalized model for forecasting technological

substitution. Technological Forecasting and Social Change, 21: 301-323.Shields, M. D. (1995). An empirical analysis of firms’ implementation experiences with

activity-based costing. Journal of Management Accounting Research, 7: 148-166.

334 Askarany


Shields, M. D. (1997). Research in management accounting by North Americans in the 1990s.Journal of Management Accounting Research, 9: 3-61.

Smith, M. (1998). Culture and organizational change. Management Accounting (London),76(7): 60-62.

Spicer, B. H. (1992). The resurgence of cost and management accounting: A review of somerecent development in practice, theories and case research methods. ManagementAccounting Research, 3(1): 1-38.

Tornatzky, L. G. & Klein, K. (1982, February). Innovation characteristics and innovationadoption-implementation: A meta-analysis of findings. IEEE Transactions on Engi-neering Management, EM-29, 28-45.

Wolfe, R. A. (1994). Organisational Innovation: Review, Critique and Suggested ResearchDirections. Journal of Management Studies, 31(3): 405-431.

Yapa, L. S. (1976). Innovation diffusion and economic involution: An essay. Department ofGeography. Columbus, Ohio State University.

Zahra, S. A. & Covin, J. G. (1994). The financial implications of fit between competitivestrategy and innovation types and sources. Journal of High Technology and Man-agement, 5: 183-211.

Zaltman, G., Duncan, R. & Holbek J. (1973). Innovations and Organizations. New York:Wiley.

An Overview of the Diffusion of Advanced Techniques

Documents

Transcript of An Overview of the Diffusion of Advanced Techniques