Countervailing effects of value and risk perceptions in manufacturers' adoption of expensive, discontinuous innovations

Industrial Marketing Management 41 (2012) 659–668

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Industrial Marketing Management

Countervailing effects of value and risk perceptions in manufacturers' adoption of expensive, discontinuous innovations Tao (Tony) Gao a,⁎, Gordon Leichter b, Yinghong (Susan) Wei c, 1 a b c

Marketing Group, College of Business Administration, Northeastern University, Boston, MA 02115, USA Trident University International, Cypress, CA 90630, USA Department of Marketing, William S. Spears School of Business, Oklahoma State University, Tulsa, OK 74106, USA

a r t i c l e

i n f o

Article history: Received 5 April 2007 Received in revised form 2 March 2011 Accepted 15 July 2011 Available online 26 October 2011 Keywords: Discontinuous technologies Perceived value Perceived risk Innovation adoption Industrial marketing

a b s t r a c t Both value and risk perceptions are germane to industrial firms' adoption decisions involving discontinuous innovations. Yet a surprisingly limited number of studies examine how these two considerations jointly influence the innovation adoption phenomenon. We intend to fill this gap by studying the countervailing and context-dependent effects of value and risk perceptions on industrial firms' intention to adopt discontinuous innovations. A conceptual model is proposed and tested with data collected from influential decision makers in pharmaceutical manufacturers on their decision to adopt the modular facility technology, a costly, discontinuous facility construction innovation. The findings confirm the offsetting roles of value and risk in affecting adoption and reveal the moderating effects of external market pressure in that both value and risk assume greater roles in affecting adoption as external market pressure increases. Furthermore, our results show a positive effect of external market pressure on value, and negative effects of external market pressure and internal adoption readiness on risk. Our study contributes to the innovation diffusion and industrial marketing literatures by: (1) studying the joint and countervailing effects of value and risk perceptions on adoption decisions by manufacturers, (2) considering the contextual influences on industrial adopters' value and risk perceptions, and (3) gathering data from influential decision makers for a major capital investment decision. © 2011 Elsevier Inc. All rights reserved.

1. Introduction Discontinuous innovations are complex products, processes, or concepts possessing attributes largely unfamiliar to potential adopters (Garcia & Calantone, 2002; Gatignon & Robertson, 1985). They represent major changes in basic products, services, or programs offered or markets served (DeTienne & Koberg, 2002); often alter existing patterns of production or consumption (Garcia & Calantone, 2002); and may create new patterns of consumption (Robertson & Gatignon, 1986). Souder, Sherman, and Davies-Cooper (1998) focus on the nature and amount of uncertainty to define the spectrum of innovations and note that discontinuous innovations are marked by high technical and market uncertainties. Mohr and Shooshtari (2003), among others, highlight the high failure rates in diffusion of discontinuous technology offerings and emphasize the need for better understanding of the barriers and contributing factors related to their successful adoption and implementation. ⁎ Corresponding author. Tel.: + 1 617 373 5744. E-mail addresses: [email protected] (T.(T.) Gao), [email protected] (G. Leichter), [email protected] (Y.(S.) Wei). 1 Tel.: + 1 918 594 8183. 0019-8501/$ – see front matter © 2011 Elsevier Inc. All rights reserved. doi:10.1016/j.indmarman.2011.09.014

Marketing scholars and practitioners alike highlight the central role of customer perceived value, or customers' overall assessment of the utility or worthiness of an offering, in impacting their purchase decisions (e.g., Anderson, 1995; Gao, Sirgy, & Bird, 2005b; Ulaga & Chacour, 2001; Woodruff, 1997). In the innovations diffusion literature, Rogers (2003) identifies five characteristics of innovations that help explain differences in adoption rates: relative advantages, compatibility, complexity, trialability, and observability. While discrete innovation characteristics such as relative advantages and compatibility have much to suggest about potential innovation benefits (Rogers, 2003), perceived value serves as a better summative assessment than the above, especially given its explicit coverage of adopters' perceptions of both benefits and costs of an innovation (Downs & Mohr, 1976; Moore & Benbasat, 1991; Tornatzky & Klein, 1982). The notion of factoring costs in innovation adoption decisions is particularly cogent in the case of manufacturers' adoption of complex and expensive innovations, given the large resource outlays and substantial performance outcomes mediated by the innovations. Because of the large potential benefits, stakes, and costs, many industrial purchasing decisions, especially those involving complex and expensive innovations, are hampered by elevated risks (Choffray & Johnston, 1979; Frambach, 1993; Gao, Sirgy, & Bird, 2005a; Heide &

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Weiss, 1999; Howell & Higgins, 1990; Lynn & Akgun, 1998; Moriarty & Kosnik, 1989). Perceived risk is the subjective anticipation of loss the buyer experiences when deliberating on the adoption of an innovation (cf. Bauer, 1960; Sweeney, Soutar, & Johnson, 1999). Inevitably, therefore, industrial adopters' value assessments involving expensive, discontinuous innovations may be accompanied, and even hampered, by risk perceptions. We use the term “expensive” to denote both the size of the resource investments needed to acquire and use the innovation and the magnitude of firm performance outcomes as mediated by this adoption decision (cf. Robertson & Gatignon, 1986). Take the example of innovative modular facility technology in the pharmaceutical industry. Integrating conventional construction with modular technology can save as much as 6–18 months in overall project time as opposed to building the entire facility using conventional methods (Leichter & Turstam, 2004). However, the size of the investment (hundreds of million dollars) and potential impact on a firm's market performance collectively make the purchase of this technology a risky decision for even the largest of pharmaceutical companies. While complexity, triability, and observability principally pertain to uncertainty arising from specific innovation characteristics (Rogers, 2003), risk perceptions also capture uncertainty originating from factors other than the innovation itself, such as those related to the internal and external adoption contexts. Risk perceptions further incorporate adopters' perception of the enormity of potential negative consequences should adoption failures occur. In sum, perceived risk allows for examination of how innovation characteristics join organizational and external environmental factors in presenting challenges to the adoption process. In our view, value and risk perceptions serve to capture adopters' summative assessments of both contributing factors and barriers pertaining to expensive, discontinuous innovations. It is their combination that eventually determines which innovations are adopted and which rejected. In the meantime, while value and risk perceptions are germane to industrial firms' innovation adoption decisions, a surprisingly limited number of innovation and organizational buying studies examine how these two considerations jointly influence firms' adoption decisions, especially those involving expensive, discontinuous innovations.

to adopt expensive, discontinuous innovations. We draw on the innovation diffusion, customer value, and customer risk theories to propose a conceptual mode to address the above primary research question, and also consider how external and internal environmental factors influence adopters' value and risk perceptions. We then test the model with data collected from 202 influential decision makers in pharmaceutical manufacturers on their decision to adopt an expensive, complex innovation used in drug facility construction. Our specific research questions are:

1.1. Research questions

2. Literature review and hypothesis development

In view of these gaps in prior research, we intend to contribute to innovations research by studying the simultaneous and countervailing effects of value and risk perceptions on industrial firms' intention

Even though previous research has incorporated assessments of value and risk in some diffusion models (e.g., Dickson, 1976; Jurison, 2000; Mahajan, Muller, & Bass, 1990) and innovation-related marketing

1. How do value and risk perceptions jointly influence manufacturers' intention to adopt expensive, discontinuous innovations? 2. Do external market pressure and internal adoption readiness influence adopters' value and risk perceptions for expensive, discontinuous innovations? 3. Do the effects of value and risk on manufacturers' intention to adopt expensive, discontinuous innovations change with the adoption context, specifically under different external market pressures? Our study makes two important contributions to the innovation diffusion and industrial buying literatures, by (1) theorizing and empirically confirming joint and countervailing effects of value and risk perceptions in innovation acceptance decisions, and (2) considering contextual influences on value and risk perceptions and their impacts on the adoption decision. The study further adds to the innovations literature by choosing an adoption context involving a complex, early stage innovation used for constructing drug manufacturing facilities, and by gathering data from influential decision makers for major capital investment decisions among manufacturers. In the rest of the paper, we review past research on customers' value and risk perceptions and discuss their conceptual differences. Then we develop hypotheses on the main effects of value and risk perceptions on the adoption intention, the boundary contextual conditions influencing these effects, and impacts of external pressure and internal readiness on value and risk perceptions. The conceptual model showing all hypothesized relationships is presented in Fig. 1. We follow conceptual development with descriptions of the survey methodology and analytical procedure, reporting of key findings, and discussions of the study's research and managerial implications.

H5a (EMP strengthens the PV→ ITA link)

H3 +

External Market Pressure (EMP)

Adopter Perceived Value (PV)

H1a +

H4 Intention to Adopt the Innovation (ITA)

H2 -

H6 + Internal Adoption Readiness (IR)

H7-

Adopter Perceived Risk (PR)

H1b -

H5b (EMP strengthens the PR → ITA link)

Fig. 1. The conceptual model on countervailing effects of perceived value and perceived risk on industrial firms' intentions to adopt expensive, discontinuous innovations.

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studies (e.g., Lee & Allaway, 2002; Sarin, Sego, & Chanvarasuth, 2003), few studies examine their joint influences on innovation adoption, especially involving industrial firms' adoption of expensive, discontinuous innovations. The few exceptions to this rule are all studies conducted on consumers' innovation adoption decisions featuring relatively simple innovations such as mobile phones (Snoj, Korda, & Mumel, 2004) and self-service technologies (e.g., airport selfticketing machines) (Lee & Allaway, 2002). Particularly, Lee and Allaway (2002) investigate and confirm the roles of perceived risk and perceived value in mediating the effects of personal control in inducing consumers' greater adoption intention toward self-service technologies such as airline ticketing machines, bank ATMs, and computer-based shopping services. In an effort to greatly enhance our understanding of the adoption phenomenon related to expensive, discontinuous innovations, our study captures influences of both value and risk on industrial firms' adoption decisions. 2.1. Conceptual distinctions between perceived value and perceived risk Wood and Scheer (1996) argue that a consumer's evaluation of an offering may be a function of perceived benefits, costs, and risk. In conceptualizing customer perceived value, marketing scholars largely inherit Adam Smith's rational choice theory, which holds that people and organizations weigh possible benefits of their actions against costs incurred. Eggert and Ulaga (2002), for example, view perceived value in business markets as the trade-off between multiple benefits and sacrifices of a supplier's offering as perceived by key decisionmakers in the customer organization. Accordingly, we define adopters' perceived value as potential adopters' overall assessment of the worthiness of an innovation based upon what is to be received and what is to be given up (Zeithaml, 1988). Both Kohli (1989) and Sheth (1973) view perceived risk industrial buying decisions as the magnitude of adverse consequences felt by the decision makers in the event of a wrong choice, and the level of uncertainty surrounding the decision. Accordingly, we define adopters' perceived risk as the expectation of losses associated with adopting an innovation based on perceived uncertainty about adoption outcomes and the magnitude of adverse consequences (Dowling, 1986). It is important to note that value and risk are conceptually distinct constructs subject to very different evaluation processes. Value is the customers' assessment of the total worthiness of the purchase based on a comparison of total benefits and total costs (Zeithaml, 1988). Risk, however, is related to the level of decision uncertainty and the size of negative consequences associated with a purchase failure. Negative consequences that a buyer must bear in the event of an adoption failure include the loss of all potential benefits, loss of all acquisition costs, and additional expenses related to performance recovery and damage control. In particular, we argue that low risk does not automatically translate to high value. In fact, even with low levels of purchase uncertainty and risk, many offerings are still considered to have low value, simply because the benefits are not worth the total costs. That is, even though a firm is perfectly clear about the outcomes of an innovation adoption decision, its perceived value can still be very low, if the costs far exceed the benefits. 2.2. Countervailing effects of value and risk perceptions on innovation adoption Marketing studies on perceived value consistently view it as a leading determinant of purchase decisions (Dodds, Monroe, & Grewal, 1991; Zeithaml, 1988) and innovation adoption intention (Lee & Allaway, 2002). We concur with this prior research and believe that value should predict the innovation adoption intention, especially in contexts where the decision-maker intends to make a rational choice on an important task.

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Several marketing studies further deem perceived risk as an important variable to be examined vis-a-vis perceived value (e.g., Agarwal & Teas, 2001; Chen & Dubinsky, 2003). A high level of risk prompts delays in decision-making and motivates buyers to engage in risk reduction efforts (Bourgeois, 1985; Cunningham, 1967; Urbany, Dickson, & Wilkie, 1989). Similarly, risk perception is noted as a significant barrier to the adoption of new high-tech products (e.g., Sarin et al., 2003) and other innovations (e.g., Lee & Allaway, 2002). Rogers (2003) discusses uncertainty, a dimension of risk, as relative to the newness of an innovation where limited prior knowledge causes an adopter's lack of predictability, structure, and information regarding the adoption outcomes. According to Frambach and Schillewaert (1999), potential adopters of discontinuous innovations face difficulty in determining whether the innovation will reliably function and will be compatible with their existing operating system (technical uncertainty) and will be financially attractive after implementation (financial uncertainty). In regard to the dimension of adverse consequences, various types of losses have been discussed, such as performance, social, physical, financial, psychological, psychosocial, time, and frustration (Dowling, 1986). Particularly to our study context, the loss of performance or missed market opportunity poses as a severe adverse consequence for adopters of major, expensive innovations within the pharmaceutical manufacturing industry. Based on the above discussions, we propose countervailing effects of value and risk on industrial firms' intention to adopt expensive, discontinuous innovations. Our study potentially contributes to the innovation diffusion literature by testing the following two hypotheses simultaneously: H1a. An industrial firm's perceived value of an expensive, discontinuous innovation has a positive effect on its adoption intention. H1b. An industrial firm's perceived risk of an expensive, discontinuous innovation has a negative effect on its adoption intention. 2.3. Effect of perceived risk on perceived value Several empirical studies document the role that perceived risk plays in value perceptions (Chen & Dubinsky, 2003). For example, Sweeney et al. (1999) find that in a retail environment, perceived risk has a negative effect on perceived value and mediates the relationship between product quality and perceived value. As customers' value perception in the pre-adoption stage could be negatively impacted by perceptions of risk inherent in such a situation, removing risk could be an important means of enhancing perceived value (Broydrick, 1998). Recent research in risk analysis theory also suggests a possible influence of risk on value. When risk is high, both analytical and affective sides of risk perception could come to forth (Finucane & Holup 2006). With regard to the affect effect, high risk may lead to fear which will convey a pessimistic view of the judgment situation, including an industrial firm's deliberations about an innovative offering from a supplier. This negative view may produce a halo effect on the potential adopter's assessment of the innovation, including the value perception. In view of the above rationales, we have the following hypothesis: H2. An industrial firm's perceived risk associated with adopting an expensive, discontinuous innovation has a negative influence on its perceived value of the innovation. While many organizational and external environmental factors have been studied in diffusion research (Damanpour, 1991; Gatignon & Robertson, 1989), few studies particularly examine the effects of contextual factors on value and risk perceptions in the industrial

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adoption setting. Although Chwelos, Benbasat, and Dexter (2001) identify these influences as part of their innovation adoption study, their construct of external pressure only relates to the adopter's necessity to use the technology to conduct business with partners utilizing similar technology; and their notion of internal readiness only deals with the internal ability to cope with the new technology. Similarly, Frambach (1993), and Robertson and Gatignon (1986) only identify adopters' external market pressure as competitive pressure to keep up with emerging technologies of business process automation to make organizations more competitive, and internal readiness is excluded. We seek to rectify this limitation in prior research by considering contextual influences on value and risk perceptions and their impacts on the adoption decision.

Kahneman, 1986). This discussion suggests the existence of moderating effects by external market pressure on the effects of value and risk on the adoption intention. That is: H5a. The effect of perceived value on an industrial firm's intention to adopt an expensive, discontinuous innovation increases as the external market pressure for adopting the innovation increases. H5b. The effect of perceived risk on an industrial firm's intention to adopt an expensive, discontinuous innovation increases as the external market pressure for adopting the innovation increases.

2.5. Internal adoption readiness and adopters' value and risk perceptions 2.4. External market pressure and adopters' value and risk perceptions Adopters' external market pressure is defined as the extent to which current competitive and industry conditions cause participants under oligopoly conditions to pay close attention to each other's strategic moves, including adoption of market-shaping innovations (Chwelos et al., 2001; Frambach, 1993; Gatignon & Robertson, 1989). Porter and Millar (1985) analyze the strategic rationale underlying competitive pressure as an innovation-diffusion driver. They suggest that use of major innovations may allow firms to alter the rules of competition, affect the industry structure, and leverage new ways to outperform rivals, thus changing the competitive landscape. According to past research, a high level of competition among potential innovation users stimulates innovation adoption (Frambach, 1993), because adoption of a certain innovation may help maintain one's market position in highly competitive markets (Chwelos et al., 2001; Gatignon & Robertson, 1989). This analysis can be extended to our study context (to be described in greater detail in the Methodology section). Among key benefits of the modular facility technology for pharmaceutical companies are reduction in time to market by 6–18 months and non-disruptions in existing business operations (Leichter & Turstam, 2004). The fact that adopting an innovation can provide a competitive advantage or mitigate a competitive disadvantage may enhance drug makers' perceptions of innovation benefits and strengthen their perceptions of value. In turn, if the pressure for adopting an expensive, discontinuous innovation comes from market needs and the competition, then evidence already exists to attest strategic benefits of the innovation. Such a perception will help alleviate the uncertainty surrounding the adoption decision and reduce perceived risk associated with the innovation. Hence, we have the following hypotheses: H3. The external market pressure facing an industrial firm with regard to adopting an expensive, discontinuous innovation has a positive influence on its perceived value associated with adopting the innovation. H4. The external market pressure facing an industrial firm with regard to adopting an expensive, discontinuous innovation has a negative influence on its perceived risk associated with adopting the innovation. External market pressure may give manufacturers both a sense of urgency and a need to make the right decision. These manifestations of high market pressures may propel adopter organizations to emphasize evaluations of value and risk in their decision-making as a way to enhance decision quality. For pharmaceutical companies, the avoidance of possible losses associated with an investment decision in terms of both resource outlays and strategic consequences may lead them to become “risk averse”. A high risk aversion may motivate the firms to both carefully evaluate the value and risks of the decision and rely on such evaluations in final decision-making (cf. Tversky &

Internal adoption readiness is defined as the extent to which an organization possesses the technical sophistications and financial resources necessary for adopting an innovation (cf. Chwelos et al., 2001). It can be viewed as consisting of (a) the internal ability among the management and engineering team to comprehend an innovation and (b) the availability of financial resources to support the innovation adoption (Iacovou, Benbasat, & Dexter, 1995; Parasuraman, 2000). According to the innovation diffusion theory (Moore, 1999; Rogers, 2003), early adopters are those who can envision the potential benefits of an innovation more easily than others. They can also more effectively relate the innovative idea or object to their needs, and better recognize the compatibility of an innovation than later adopters (Agarwal & Prasad, 1998; Yi, Fiedler, & Park, 2006). Greater knowledge, more experiences, stronger technical competences, and high aspirations (Moore, 1999; Rogers, 2003) may further allow early adopters to perceive the same technology to be easier and less challenging to use than late adopters. Dewar and Dutton (1986) further note that large firms, which are likely to have more technical specialists, have a greater tendency than small firms to adopt discontinuous innovations. Other researchers also note the positive association between the prevalence of “technical specialists” within an organization and receptivity to innovations (Gatignon & Robertson, 1989; Hage, 1980). We suggest that the link between internal organizational readiness and adoption is mediated by the former's positive impact on value and negative impact on risk. First, regarding potential adopters' comprehension level, the enormity of the actual end product of modular facility technology makes it difficult for them to visualize the innovation even after touring a modular pharmaceutical manufacturing facility. The tacit nature of this technology can thus reduce potential adopters' comprehension ability, a phenomenon referred to as a severity of learning by Robertson and Gatignon (1986). Therefore, companies that do have the internal ability to comprehend the innovation will have a better understanding of its benefits and a lower level of uncertainty (hence a lower level of perceived risk). Second, Frambach (1993) discusses the relationship between a potential adopter's absorption capacity and its receptivity of an innovation. A better understanding of and more support for using an innovation from both the top management and related corporate departments will help alleviate the risk of the adoption (Ettlie, Bridges, & O'Keefe, 1984; Frambach & Schillewaert, 1999; Howell & Higgins, 1990). Third, a higher availability of financial resources may increase a company's ability to afford an innovation, absorb its possible failure, bear the costs of its institution, and explore new ideas in advance of an actual need (Damanpour, 1991). Also, firms with more financial resources will likely view the same level of investment as a smaller sacrifice, thus increasing their value perception. Furthermore, a greater availability of financial resources enables the firm to better withstand negative consequences should the adoption fail to meet expectations, resulting in a lower perceived risk.

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Based on the above discussions, we posit the following hypotheses on the relationship between internal adoption readiness and perceptions of value and risk about an innovation: H6. An industrial firm's internal readiness for adopting an expensive, discontinuous innovation has a positive influence on the perceived value associated with adopting it. H7. An industrial firm's internal readiness for adopting an expensive, discontinuous innovation has a negative influence on the perceived risk associated with adopting it. 3. Methodology 3.1. Innovation context The context of our study is the pharmaceutical manufacturers' adoption decision involving a discontinuous, early stage, business service innovation, the modular facility technology for the construction and delivery of drug production facilities. In terms of the cost of the innovation, the sizes of facilities produced utilizing the modular construction concept have reached over 200,000 square feet (comparable to a Wal-Mart Supercenter or a large Home Depot store), with costs in the hundreds of million dollars. This innovation is a relatively new and complex phenomenon occurring in the pharmaceutical industry and at the time of this study, and only a small fraction of pharmaceutical manufacturing companies have utilized it. Among the adopters are industry giants Eli Lilly, Merck, Genentech, AstraZeneca, Baxter, and Pharmacia, but the number is increasing annually as the innovation diffuses (Pharmadule-Emtunga, 2004). Discontinuous innovations are complex technologies with attributes largely unfamiliar to potential adopters. They represent major changes in basic product technologies, often alter existing patterns of production or consumption, and may create new patterns of consumption (DeTienne & Koberg, 2002; Garcia & Calantone, 2002; Rice, O'Connor, Peters, & Morone, 1998; Robertson & Gatignon, 1986). The modular technology possesses all these characteristics and may thus qualify as a discontinuous innovation in drug facility construction methods. First, as a major departure from existing facility construction approaches, this technology involves manufacturing critical aspects of the facility within the innovation supplier's factory (rather than on site at the adopter firm), including structural aspects and internal finishes, complete with processing equipment, transportation of the disassembled facility in modules to the final location, and reassembling at the adopter's site. As such, modular projects must be handled differently from traditional plant construction projects, and require a “paradigm shift” in both project planning and execution (Leichter & Turstam, 2004). Second, the modular facility construction approach offers substantial advantages such as improved quality, increased versatility and adaptability to potential drug product innovations, faster completion, minimal site disruptions, and quicker validation. Third, the modular facility technology goes beyond a simple product innovation and encompasses a holistic approach to the design and construction of sophisticated manufacturing facilities for the production of pharmaceutical products. Due to the magnitude and complexity involved with funding, designing, constructing, and validating a pharmaceutical manufacturing facility, the departure from the existing ingrained project execution process is considered discontinuous in nature (cf. Gatignon & Robertson, 1989). It qualifies as a discontinuous innovation and even borders radical innovations (cf. Bower & Christensen, 1995; Garcia & Calantone, 2002) as it appeals to nonusers (e.g., companies that contract others to make their drugs) by offering a simpler solution to the conventional alternative and opens up new market opportunities.

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In sum, the newness of the construction technology, the size of the involved investment, and potential impact of the project on a pharmaceutical manufacturer's market performance collectively make a modular technology a costly and risky decision for even the largest of pharmaceutical companies. Based on the above discussions, we felt this innovation was an appropriate context for testing our conceptual model. 3.2. Sample The sample frame was membership list of the International Society of Pharmaceutical Engineering (ISPE), an international association of pharmaceutical manufacturing professionals. The surveys were directed toward a targeted group of key decision-makers for large capital investments within pharmaceutical manufacturing companies (cf. Jackson, Keith, & Burdick, 1984). They typically bear titles such as vice presidents and directors of engineering, manufacturing, industrialization, purchasing, finance, or quality assurance, as well as top management. Our email list comprised 996 members identified as those typically involved in complex and expensive capital investment decisions. Both the pre-test and final survey were conducted online via Zoomerang. Respondents were offered two incentives — the opportunity to receive the survey results and a collective contribution of $2500 to an industry related educational charity honoring their participation. In total, 210 respondents completed the survey, of which 202 contained complete data, resulting in an effective response rate of 20.24%. We assessed potential non-response bias in two ways, by comparing early and late responses and by sending a brief followup survey to a random selection of 100 email addresses from the original list. These steps showed no significant differences on means of key study constructs across concerned groups, helping minimize non-response bias as a threat for the study. 3.3. Measurement and construct validation All measures for the study constructs were drawn from previous studies in both marketing and innovation literatures but were adapted to the specific innovation of modular facility technology in the pharmaceutical industry. The measures and their sources are shown in Table 1. The intention to adopt the innovation, the extent to which key decision-makers declare their willingness to adopt the innovation, was measured with eight reflective items drawn from Chwelos et al. (2001), and Lee and Allaway (2002). Adopter perceived value, as the potential adopter's overall assessment of the worthiness or utility of an innovation based upon expected benefits and expected sacrifice (Zeithaml, 1988), was measured with six reflective items drawn from existing research (Dodds & Monroe, 1985; Gao, 1998) but adapted to the context of modular facility technology. Adopter perceived risk is defined as the expectation of losses associated with the adoption of an innovation based on perceived uncertainty about the adoption outcomes and the magnitude of adverse consequences (Dowling, 1986). Borrowing from the previous research or published industry reports (Au & Enderwick, 2000; Chwelos et al., 2001; Construction Industry Institute, 2002; Dowling, 1986; Huff, Keil, Kappelman, & Prybutok, 1997; Lee & Allaway, 2002), we developed six reflective items to measure the adopter's perceptions of uncertainty, adverse consequences, and overall risk. Adopters' external pressure is defined as the extent to which major competitors in an industry have adopted the innovation to their competitive advantages against the focal adopter. It is related to the degree to which current competitive and industry conditions cause participants under oligopoly conditions to pay close attention to each other's competitive moves. In their study on firms' EDI adoption decisions, Chwelos et al. (2001) utilize measures based on potential

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Table 1 Confirmatory factor analysis. Constructs and scale items

Loading

Intention to adopt (CR a = .81; AVE = .55; Alpha = .80) ITA1: I would consider utilizing modular facility technology in our company. ITA2: I am in favor of adopting a modular facility technology for our next manufacturing facility project. ITA3: I would recommend utilizing modular facility technology within my company. ITA4: I would be willing to use modular facility technology for my next manufacturing facility project.

.78 .75 .73 .80

Perceived value (CR = .91; AVE = .64; Alpha = .91) PV1: I believe that modular facility technology offers my organization increased value compared to the conventional process of building a facility. PV2: Modular facility technology offers greater overall value than conventional construction. PV3: Modular facility technology is a better value than available alternatives. PV4: The benefits of modular facility technology are greater than conventional alternatives. PV5: The return on investment from utilizing modular facility technology is worth the cost. PV6: The higher quality of modular facility technology would be valuable to my organization.

.85 .90 .86 .85 .71 .67

Perceived risk (CR = .82; AVE = .53; Alpha = .80) PR1: There is much uncertainty as to whether the proposed benefits of modular facility technology would materialize if we were to utilize the technology. PR2:The level of overall risk in utilizing modular facility technology for my organization is very high compared to conventional construction. PR3: Getting our product to market on time would be in jeopardy if modular facility technology were utilized on a new facility project. PR4: There is too much at stake in our business to try modular facility technology on a project.

.68 .81 .72 .73

External market pressure (EMP) (CR = .83; AVE = .61; Alpha = .85) EP1: My competitors have benefited from utilizing modular facility technology to get their products to market sooner. EP2: I feel that modular facility technology is widely utilized in my industry. EP3: I am interested in modular facility technology because my competitors are utilizing it.

.76 .81 .78

Internal readiness (IR) (CR = .80; AVE = .57; Alpha = .82) AR1: The design of a modular facility utilizes similar architectural and engineering, A&E, disciplines as a conventionally built facility. AR2: Implementing a modular facility project would not constitute a burden on my organization more than implementing a conventionally built facility AR3: If my organization were to build a new manufacturing facility, funding would not be an issue. Fit indices: χ2 = 320.08 (df = 162), p = .00, RMSEA = .06; CFI = .97, χ2/df = 1.98. Phi matrix

.77 .72 .78

b

Constructs

Mean

Standard deviation

ITA

ITA PV PR EMP IR

3.45 3.20 2.83 2.50 3.10

.74 .72 .80 .54 .51

1.00 0.76 − 0.56 0.44 0.28

PV c c c d

1.00 − 0.40 0.63 0.20

PR

c c d

1.00 − 0.29 − 0.24

EP

c d

1.00 0.21

AR

d

1.00

a

Notes: CR = composite reliability. AVE = average variances explained. Both were calculated using construct-to-item loadings. b All correlations reported in the Phi Matrix are significantly different from 1 or − 1 (the absolute value plus 2 times standard error being smaller than 1). c These correlation coefficients are significant at p = .01 level.

adopters' external pressures from their competitors and respective industries. From a different perspective, Gatignon and Robertson (1989) utilize measures that capture the degree to which potential adopters felt that the innovation of laptop computers could help them become more competitive from a sales force effectiveness position. Borrowing from these studies, we developed three reflective items for external market practice. Internal adoption readiness is defined as the levels of technical sophistication and financial capacity enabling an organization's adoption of an innovation. Frambach (1993) discusses unavailability of internal resources to properly evaluate innovations as a detriment to innovation adoption. Similarly, the Construction Industry Institute (2002) analysis identifies engineers' lack of experience with the technology a potential barrier for utilizing modular facility technology. We adapted the measures utilized by Chwelos et al. (2001) for internal ability and developed our own measures for financial capacity. Collectively, five items were used to comprise the scale for internal adopter readiness. To validate the measures of our constructs, we conducted a series of confirmatory factor analyses (CFA) using LISREL 8.8 (Jöreskog and Sörbom, 2005) to test the dimensionality, reliability, and convergent and discriminant validities of the measures (cf. Anderson & Gerbing, 1988). Certain raw indicators were removed from further analysis for the following reasons: (1) if the indicator had a large correlated error with other indicator(s), and (2) if the items had low loadings on their intended constructs (Steenkamp & Baumgartner, 1998).

Table 1 shows the results of the overall measurement model containing factors for all constructs for each sample. Aside from the factor loadings, we also report the fit indices, Cronbach's alphas, construct reliabilities, and average variances extracted (Fornell & Larcker, 1981). The fit indices collectively show adequate fit of the measurement model with the data (Hu & Bentler, 1999). Evidence for convergent validity exists in the high and significant path coefficients from latent constructs to their corresponding indicators (Anderson & Gerbing, 1988), high composite reliability coefficients (Nunnally, 1978), and the fact that average variances extracted for all the constructs were higher than the cutoff value of .50 (Fornell & Larcker, 1981). Evidence for construct discriminant validity first came from correlations between constructs being significantly different from 1.0 (the correlation coefficients plus two times of standard errors were smaller than 1) (Anderson & Gerbing, 1988). We further assessed the discriminant validity of our constructs by performing a series of two-construct CFA models for all possible pairs of constructs. In each model, the phi coefficient was constrained to unity and then freed and a chi-difference test is performed. Discriminant validity was obtained for all the constructs using this test (Δχ 2[1] N 3.84 for all pairwise comparisons). 3.4. Common method variance We assessed common method variance (CMV) with two separate tests. First, we employed Harmon's one-factor test that entails

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entering all the items for our latent variables into a single factor using CFA procedures (Podsakoff, MacKenzie, Lee, & Podsakoff, 2003). None of the factor models fit the data well, mitigating concerns of potential CMV bias. Second, we reran the final CFAs with a same-source factor added, with this extra factor having as indicators all the measures (see Belschak, Verbeke, & Bagozzi, 2006; Podsakoff et al., 2003). The impact of this additional CMV factor on factor loadings and interfactor correlations was minimal. Partialing out the effects of common method variance, hence, did not have substantial effect on the measures. 4. Results and discussion We used the structural equations modeling (SEM) approach via LISREL 8.8 (Jöreskog and Sörbom, 2005) to test the conceptual model. We followed the Ping (1995) recommendation in specifying the error variances of the two interaction terms, External Pressure ⁎ Perceived Value and External Pressure ⁎ Perceived Risk. The fit indices show adequate fit between the conceptual model and the data (Hu & Bentler, 1999) (see Table 2). The results are shown both in Table 2 and Fig. 2. The parameter estimates for hypothesized effects along with t-test results are shown in Table 2. Based on these results, hypotheses H1a, H1b, H3, H4, H5a, H5b, H6, and H7 received support, while H2 was rejected. The parameter estimates for paths from perceived value to adoption intention (PV → ITA) (β = .63, t = 6.48) and from perceived risk to adoption intention (PR → ITA) (β = −.33, t = −4.18) were both significant (at p b .01) and had expected signs, providing support for H1a and H1b. That is, manufacturers' intentions to adopt an expensive, discontinuous innovation are simultaneously influenced by both their value and risk perceptions. More specifically, intensions are enhanced by perceived value and reduced by perceived risk. Furthermore, based on the relative sizes of the absolute values of the parameter estimates, perceived value has a larger influence on industrial buyers' adoption intention than perceived risk. We further verified the above results by conducting a series of hierarchical regression analyses involving perceived value and perceived risk as sequentially introduced independent variables and adoption intention as the dependent variable. The results were similar to those from the above structural equations modeling test. Specifically, the effects on adoption intention were .67 (t = 13.51) for perceived value and −.23 (t = −4.66) for perceived risk, respectively. Both were significant at p b .01 and carried the correct signs. The results from the hierarchical regression analyses show that perceived value explained 51% (F value for changes in R 2 = 188.43, p b .01) of all variances in adoption intention alone, while perceived risk helps explain an additional 5% (F value for changes in R 2 = 21.72, p b .01) of these variances, giving an overall R 2 of .56. As Table 2 Results from testing of the structural equations model. Independent variables

Dependent variable(s) Intention to adopt (ITA)

PV

PR

Perceived value (PV) .63⁎⁎ (H1a) Perceived risk (PR) −.33⁎⁎ (H1b) − 0.07 (H2) External market pressure (EMP) .64⁎⁎ (H3) −.26⁎⁎ (H4) Internal readiness (IR) .26⁎⁎ (H6) −.20⁎⁎ (H7) External market pressure ⁎ .16⁎ (H5a) perceived value (EMP*PV) External market pressure ⁎ −.18⁎ (H5b) perceived risk (EMP*PR) R2 .64 .57 .50 Fit indices: χ2 = 356.38 (df = 196), p = .00, RMSEA = .06; CFI = .97, χ2/df = 1.82. ⁎ Significant at p = .05. ⁎⁎ Significant at p = .01.

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both incidences of R 2 increases are significant at p b .01, both perceived value and perceived risk are viewed as significant influencers of adoption intention. Regarding H2, the SEM coefficient for the path from perceived risk to perceived value, PR→ PV (β = −.07, t = −.69), was non-significant. Therefore, adopters' perceived risk does not have a negative effect on their perceived value, rejecting H2. With regard to H3 and H4, the parameter estimate for the path from external market pressure to perceived value, EMP → PV (β = .64, t = 8.34), was significant and carried the expected sign. As such, adopters' perception of external market pressure helps enhance their value perception with regard to an innovation, supporting H3. The coefficients for effect of external market pressure on perceived risk, EMP → PR (β = −.20, t = − 3.01), were also significant and carried the expected sign. Therefore, adopters' perception of external market pressures serves to reduce their risk perception, confirming H4. Next, the path coefficients for the two interaction effects, namely External Market Pressure ⁎ Perceived Value (β = .16, t = 2.25) and External Market Pressure ⁎ Perceived Risk (β = −.18, t = −2.32), were both significant at p b .01 and had the expected signs, providing support for H5a and H5b. When combined with the main effects of value and risk on adoption intention, these results suggest that the effects of value and risk on industrial firms' intention to adopt a discontinuous innovation both increase with the growth of the external market pressure favoring adoption of the innovation. The path coefficient for the influence of internal readiness on perceived value, IR → PV (β = .26, t = 3.48), was significant and carried the correct sign, leading support to H6. Therefore, adopters' readiness toward an innovation enhances their value perception. Similarly, the path coefficient for the impact of internal readiness on perceived risk, IR → PR (β = −.20, t = − 2.30), was significant and carried the expected sign. Thus, adopters' internal adoption readiness serves to reduce their risk perception, shedding light on H7. 5. Conclusion 5.1. Research implications Even though both value and risk perceptions are important considerations in innovation adoption decisions facing consumers and industrial buyers alike, limited research exists on how the two constructs work together to influence the adoption phenomenon. This limitation is especially salient in adoption contexts involving expensive, discontinuous, and technologically complex innovations, where the stakes, costs, and risks are particularly high. In such decision contexts, manufacturers' innovation value assessments naturally take place in high risk situations. By capturing the influences of both value and risk on adoption decisions related to expensive, discontinuous innovations, our study contributes to a better understanding of such innovation adoption phenomena and helps fill an important gap in both innovations and industrial marketing literatures. The merit of modeling value and risk as separate and joint antecedents of innovation adoption decision hinges on their conceptual distinctions. In a rare but important attempt in the marketing literature, we sought to identify and discuss the differences in conceptualizations about value and risk. These observations promise to bring more clarity to the conceptual dissimilarities and relationships between value and risk perceptions, and they served as the basis for our proposal of risk and value as separate and competing factors influencing buyers' innovation adoption decisions. From a survey of influential decision makers in pharmaceutical manufacturers, our findings confirm the counterbalancing roles of perceived value and perceived risk in affecting potential adopters' intention to adopt a discontinuous innovation. While our results show perceived value as a larger factor than perceived risk in influencing

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T.(T.) Gao et al. / Industrial Marketing Management 41 (2012) 659–668 H5a (.16*); Supported

External Market Pressure (EMP)

H3 (.64**) Supported

Adopter Perceived Value (PV) H1a (.63**) Supported

H4 (-.26**) Supported)

H2 (-.07) Not Supported H6 (.26**) Supported Internal Adoption Readiness (IR)

Intention to Adopt the Innovation (ITA)

H1b (-.33**) Supported

H7 (-.20**) Supported

Adopter Perceived Risk (PR)

H5b (-.18*); Supported

Notes: *: Significant at p = .05; **: Significant at p = .01 Fig. 2. Model testing results.

the adoption intention, risk is found to have a significant impact on adoption decision when the effect of value is controlled. The finding that perceived risk does not influence perceived value, while failing to lend support to hypothesis H2, gives credence to the assertion of distinct conceptualizations for these two constructs. This result was particularly significant given the high correlation between them (−.40; see Table 1) as noted in the current study and the observations and findings from other studies suggesting risk as an antecedent to value (Chen & Dubinsky, 2003; Sweeney et al., 1999). Additionally, while many organizational and external environmental factors have been studied in diffusion research (Damanpour, 1991; Gatignon & Robertson, 1989), few studies particularly examine the effects of contextual factors on value and risk perceptions in the industrial adoption setting. By considering contextual influences on value and risk perceptions and their impacts on the adoption decision, our study represents a useful contribution to innovations diffusion research. Specifically, both value and risk assume greater roles in affecting adoption as external market pressure increases. Our results further show negative effects of both external market pressure and internal adoption readiness on perceived risk and their positive effects on perceived value. In regard to the findings on the important role of external pressure on the adoption decision, our results corroborate with those of previous studies (cf. Mohr & Shooshtari, 2003). For example, Frels, Shervani, and Srivastava (2003) note that product performance alone does not determine organizational adoption decisions for hightech products; rather, the relative strength of the product's networks is more influential in shaping adoption decisions. Our finding builds on their prior findings in that it further explains how external market pressure influences adoption decision — by enhancing value perception and reducing risk perception and by increasing the roles of these two considerations in adoption decisions. 5.2. Managerial implications Marketers of high-technology products, services, and innovations in the business-to-business setting face considerable challenges in commercializing their new products (Mohr & Shooshtari, 2003; Moriarty & Kosnik, 1989). The innovation propagators are successful only if their potential customers are willing to adopt their innovations. The findings from our study have several important implications to marketers of expensive, discontinuous innovations in the industrial sector, particularly in the pharmaceutical manufacturing industry.

First, our findings highlight the importance of both value and risk perception in industrial buyers' deliberations on whether to adopt expensive, discontinuous innovations. Given the central role of customer value in buyer decision-making, many companies have undoubtedly sought to emphasize superior value creation and delivery in their innovations marketing efforts. Our findings confirm the necessity of such endeavors and particularly, revealing in regression analysis that value alone explains 51% of manufacturers' adoption intention involving expensive, discontinuous innovations. We also made an attempt to note the conceptual distinctions between value and risk perceptions and modeled risk as a separate and competing factor influencing industrial buyers' innovation adoption decisions. The results show that risk indeed has a significant influence when the effect of value is controlled. Specifically, our regression analysis shows that risk helps explain 5% of the variances in adoption intention on and above the explanatory power of value. Therefore, it is important for marketers of industrial innovations to both lower potential adopters' risk perceptions and increase their value perceptions. While risk is a factor relevant in all innovation adoption decisions facing consumers as well as industrial buyers, its importance increases with the levels of stakes, costs, and uncertainty involved in the adoption decision. Prior research has established risk as a twodimensional construct, in that it takes both importance and uncertainty to produce high risk. The level of importance has to do with purchase costs, outcomes mediated by the innovation, and additional negative consequences associated with an adoption failure. As these factors are relatively fixed, they should not become the foci of marketers' risk reduction initiatives. Rather, the attention should be directed at lowering the uncertainty facing the adopter firm. Uncertainty in innovation adoption may be attributable to factors related to the innovation, the adopter firm, the relationship between the two organizations, and market environments surrounding the adoption decision. Our study also confirms the direct effects of internal readiness on value and risk perceptions, highlighting the importance of a methodical process, which innovation marketers should follow to gradually build such readiness and support within the adopter organization and associated parties. They could work with the potential adopters to enhance their knowledge about the innovation, capacity to evaluate the innovation, and informed allocation of budgets for the innovation. In particular, considering the complexities of the buying task as a result of heightened stakes and costs, it is important for marketers to work with multiple parties both within and outside the adopter

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organization, e.g., with their consultants, as an avenue for diffusing a discontinuous innovation. The marketers could also use past relationships with the adopters to convey trustworthiness of their claims about the innovation benefits. Additionally, the findings that external market pressure may help enhance value and reduce risk suggest the possibility of using cases of existing adopters as a way to communicate on the value and need for the innovation. The significant moderating effects of external market pressure on the roles of value and risk assessments in impacting adoption intention suggest the added needs for marketers to work toward both promoting value perceptions and lowering risk perceptions among potential adopters of expensive, discontinuous innovations. 5.3. Limitations and future research directions While the study yielded some useful insights, the generalizability of certain findings could be limited by the specific type of innovation we studied. That is, the confirmed relationships among key constructs might not hold for more general innovations of low to moderate costs marketed toward industrial or consumer adopters. This is especially true to the moderating roles of external market pressure on the effects of value and risk on the adoption intention. Meantime, we believe the countervailing roles of value and risk in influencing innovation adoption could be extended to more consumer as well as business adoption contexts where an important, relatively expensive, early-state innovation is involved. Also, our study represents only a partial investigation of selected important antecedents to value and risk perceptions, namely external market pressure and internal readiness. Future efforts are encouraged to study the important topic of countervailing roles of value and risk perceptions in other innovation contexts and other important drivers of value and risk perceptions such as relationship quality and discrete innovation characteristics. Future research should also examine the extent to which value and risk serve to mediate the full effects of various innovation characteristics (relative advantages, complexity, compatibility, observability, and trialability) on the innovation adoption intention. References Agarwal, R., & Prasad, J. (1998). A conceptual and operational definition of personal innovativeness in the domain of information technology. Information Systems Research, 9(2), 204–215. Agarwal, S., & Teas, R. K. (2001). Perceived value: Mediating role of perceived risk. Journal of Marketing Theory and Practice, 9(4), 1–14. Anderson, J. C. (1995). Relationship in business markets: Exchange episodes, value creation, and their empirical assessment. Journal of the Academy of Marketing Science, 23(4), 346–350. Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411–423. Au, A. K., & Enderwick, P. (2000). A cognitive model on attitude towards technology adoption. Journal of Managerial Psychology, 15(4), 266–275. Bauer, R. A. (1960). Consumer behavior as risk taking. In R. S. Hancock (Ed.), Proceedings of the 43rd Conference of the American Marketing Association (pp. 389–398). Belschak, F., Verbeke, W., & Bagozzi, R. P. (2006). Coping with sales call anxiety: The role of sale perseverance and task concentration. Journal of the Academy of Marketing Science, 34(3), 403–418. Bourgeois, L. J., Jr. (1985). Strategic goals, perceived uncertainty, and economic performance in volatile environments. Academy of Management Journal, 28(3), 548–573. Bower, J. L., & Christensen, C. M. (1995). Disruptive technologies: Catching the wave. Harvard Business Review, 73(1), 43–53. Broydrick, S. C. (1998). Seven laws of customer value. Executive Excellence, 15, 15. Chen, Z., & Dubinsky, A. J. (2003, April). A conceptual model of perceived customer value in e-commerce: A preliminary investigation. Psychology and Marketing, 20, 323–347. Choffray, J. -M., & Johnston, P. E. (1979). Measuring perceived pre-purchase risk for a new industrial product. Industrial Marketing Management, 8(4), 333. Chwelos, P., Benbasat, I., & Dexter, A. (2001). Research report: Empirical test of an EDI adoption model. Information Systems Research, 12(3), 304–321. Construction Industry Institute (2002, July). Prefabrication, preassembly, modularization, and offsite fabrication in industrial construction: A framework for decision-making. The University of Texas at Austin. Cunningham, S. M. (1967). Dimensions of perceived risk. In Donald F. Cox (Ed.), Risk taking and information handling in consumer behavior. Boston: Harvard University 1967.

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Tao (Tony) Gao, Ph.D., is an assistant professor of marketing in the College of Business Administration, Northeastern University, Boston. He conducts research primarily on management of customer relationships, marketing innovations, and international marketing, especially marketing involving Chinese firms and consumers. He has published in Journal of Business Research, Journal of Business Ethics, Journal of Interactive Marketing, Journal of Service Research, Thunderbird International Business Review, Multinational Business Review, Industrial Marketing Management, and Journal Advertising Research, among others.

Gordon Leichter, Ph.D., is a core professor of business administration at Trident University International, Cypress, CA. He is also the East Coast sales manager for Belimed, Inc. At the time of the study, he was the Director of Business Development for Pharmadule USA, Inc. focusing on the design and delivery of pharmaceutical manufacturing facilities. He has over twenty years of experiences working in the pharmaceutical industry with extensive experience involving the design and manufacturing of sterilization and clean utility systems. Some of his previously held positions were Director of Operations for Getinge and Product Manager for AMSCO/Finn-Aqua (now Steris Corp).

Yinghong (Susan) Wei, Ph.D., is an assistant professor of marketing in the Spears School of Business at Oklahoma State University. Her research interests focus on the interface between marketing strategy and strategic management, including market orientation, innovation management, new product development, corporate entrepreneurship, business-to-business marketing, and learning theory. Her research has been published in journals and conference proceedings such as the International Journal of Research in Marketing, Industrial Marketing Management, Journal of Product and Innovation Management, and Journal Advertising Research, among others. Her dissertation research won the Kauffman Dissertation Fellowship and the ISBM Doctoral Dissertation Awards Competition.