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Industrial Marketing Management 36 (2007) 1046 – 1056 Marketing communication strategies in support of product launch: An empirical study of Taiwanese high-tech firms Chien-Wei Chen a,⁎, Chung-Chi Shen b , Wan-Yu Chiu c a National Chengchi University, College of Commerce, Department of International Business, No. 64, Sec. 2, ZhiNan Rd., Taipei 11605, Taiwan b Providence University, College of Management, Department of International Business, No. 200, Chung-Chi Rd., Taichung 43301, Taiwan c Bristol-Meyers Squibb Taiwan, Taiwan Received 15 November 2004; received in revised form 24 August 2005; accepted 22 August 2006 Available online 2 October 2006 Abstract To understand the mechanisms that underlie marketing communication support for product launches, the authors conduct an empirical study and propose a conceptual framework that depicts the relationships between informational/transformational or elaborational/relational messages and their effectiveness. The hypothesized message–communication and message–sales effect links are moderated by three communication process characteristics: message clarity, message uniformity, and integration of the communication. On the basis of data collected from an industrial survey of 101 high-tech firms in Taiwan, the authors find that informational and relational messages offer greater support for new products. Whereas message clarity and integration of communication expectedly demonstrate positive moderating effects on message–performance links, message uniformity only affects messages–sales effect relationships. The authors explore research insights and discuss implications for both academia and practitioners from the perspectives of new product management and integrated marketing communications. © 2006 Elsevier Inc. All rights reserved. Keywords: Communication strategy; New product launch; Integrated marketing communication 1. Introduction Product launch is perhaps the most expensive, risky, and poorly managed phase of new product development process, in the sense that firms must commit enormous time, financial, and managerial resources, and the average failure rate is as high as 40% for consumer and industrial new products (Hultink, Hart, Robben, & Griffin, 2000) and more than 60% in high-tech industries (Goldenberg, Lehmann, & Mazursky, 2001). Despite the risks inherent in commercialization, launch efforts often are decisive in securing new product success (Crawford & Di Benedetto, 2003; Guiltinan, 1999). In this challenging context, a firm that is proficient in communicating the positioning of its new products and leveraging its affiliated brands may maximize ⁎ Corresponding author. Tel.: +886 2 29393091x81135; fax: +886 2 29379071. E-mail addresses: [email protected] (C.-W. Chen), [email protected] (C.-C. Shen). 0019-8501/$ - see front matter © 2006 Elsevier Inc. All rights reserved. doi:10.1016/j.indmarman.2006.08.002 its chances of achieving profitable product acceptance in the target market (Guiltinan, 1999). Launch planning involves both strategic and tactical decisions (Biggadike, 1979). Whereas the former entails details such as product innovation, market targeting, and market leadership, the latter pertains to choosing marketing mix elements, of which marketing communications represents the central concern (Guiltinan, 1999). In the launch process, marketing communications refer to all of the information and attitude efforts expended to influence product adoption, including product attribute expressions and strong persuasion attempts (Crawford & Di Benedetto, 2003). Existing literature clearly supports the positive relationship between effective marketing communications and new product success (e.g., Cooper & Kleinschmidt, 1994; Song & Parry, 1994). However, high-tech industries are unique in the great uncertainties that derive from their market, technology, and competitive factors (Mohr, 2001; Moriarty & Kosnik, 1989). In such industries, market offerings generally are founded on significant amounts of scientific and technical know-how (John, C.-W. Chen et al. / Industrial Marketing Management 36 (2007) 1046–1056 Weiss, & Dutta, 1999). These unique industry characteristics result in different information processing patterns among buyers (Capon & Glazer, 1987; Glazer, 1991), which require adaptive marketing strategies and tools (Rangan & Bartus, 1995; Shanklin & Ryans, 1987). In response to such environmental complexity and turbulence, high-tech marketers may use marketing communications to build strong brand names (Morris, 1996) and assuage customers' fear and doubt involved in product adoption (Lee & O'Connor, 2003). From both theoretical and practical perspectives, it is worth studying what makes marketing communications that introduce new products effective, especially in high-tech industries. For example, Taiwanese high-tech firms previously based their business models on original equipment manufacturing (OEM), but OEM firms have suffered drastic profitability losses as a result of strong competition from companies located in other countries with lower labor costs. To escape this quandary, several firms, including Acer, Asus, and BenQ, began to recognize the importance of their own brands and switched their investments and endeavors toward high value-added activities such as research and development, product innovation, and brand building. Those firms that switched their business focus thus needed to engage in different marketing communications than they had used in the past. That is, unlike marketers of consumer products, which mainly rely on mass media communications (Hultink et al., 2000), firms specializing OEM businesses behave more like industrial product manufacturers, which usually communicate product-related information to buyers through personal selling or trade shows. For Taiwanese high-tech firms, the marketing communication decision has become far more complicated, because they essentially function in both business and consumer markets. Therefore, an investigation of the marketing communications used to launch products in Taiwan's high-tech industries may offer interesting and significant insights into various launch-supporting communication behaviors across product categories and markets. This research attempts to find a normative model to guide high-tech firms to effective marketing communications in support of their product launches. Specifically, we aim to achieve two related objectives: (1) determining which message content is most effective in introducing new high-tech products and (2) understanding how to manage the communication process to achieve greater effectiveness. These distinct objectives are both legitimate, in that what to say and how to say it are equally important in any type of communications. We also propose a conceptual framework, illustrated in Fig. 1, to depict the relationships among three components related to marketing communications for product launch: message content, communication process characteristics, and effectiveness. Message content consists of two dimensions: informational/transformational (Aaker & Norris, 1982; Aaker & Stayman, 1992; MacInnis & Stayman, 1993; Puto & Wells, 1984) and elaborational/relational (Bridges, Keller, & Sood, 2000). Our framework proposes that various types of message content impose different effects on the performance of launched products, which we capture with communication and sales effects. The message content–effectiveness links furthermore 1047 Fig. 1. Conceptual framework of marketing communications for product launch. are moderated by three characteristics of the marketing communication process: message clarity, message uniformity, and integration of communication. Our theoretical foundation for this model stems from exchange theory's model of interpersonal communications (Gatignon & Robertson, 1986) and integrated marketing communications (IMC), which advocates the alignment of communications to deliver a flow of consistent messages about a product or service to meet a common set of communication objectives or support a single positioning (Percy, 1997; Pickton & Broderick, 2001). Briefly, the moderation works as a result of the communication efficiency or synergy created by messages that are coordinated throughout the communication process. In examining the hypothesized relationships, we hope to shed some light on the mechanism by which IMC should provide greater message delivery capabilities. 2. Research hypotheses 2.1. Informational/transformational messages and effectiveness Messages disseminated to the market normally possess a dual nature of both rational and emotional elements (Johar & Sirgy, 1991; Liebermann & Flint-Goor, 1996; Vakratsas & Ambler, 1999). Puto and Wells (1984) similarly classify approaches to marketing messages (specifically, advertising) according to two dimensions, informational and transformational. Informational messages are factual and meaningful descriptions of the relevant product information, delivered in a logical, verifiable manner to attract customers. Transformational messages convey affectbased contents that associate the experience of owning or using a product with psychological characteristics, such as richness, warmth, excitement, enjoyment, and so on (Aaker & Stayman, 1992). For most marketing communications, messages can be conveyed in an informational or transformational form or a combination thereof (Cohen & Areni, 1991). During IMC planning, it is crucial to understand the target audience's purchase motivation, whether negative or positive, to create, maintain, modify, or change brand attitudes (Percy, 1997; Rossiter, Percy, & Donovan, 1991). Negatively originated motives, such as problem removal and avoidance, trigger customers to eliminate negative feelings or affect caused by a problem by acquiring product-related information or buying and using the chosen product. Therefore, an informational message strategy may match the needs driven by such motives. 1048 C.-W. Chen et al. / Industrial Marketing Management 36 (2007) 1046–1056 Positive motives, in contrast, correspond to a transformational message strategy, which links the use of the new product to sensory benefits or intellectually or socially rewarding states. Feeling or affect becomes positively transformed by the anticipated or actual consumption of the product (Rossiter & Percy, 1987). According to the elaboration likelihood model (ELM) of persuasion (Petty & Cacioppo, 1981), people form or change their attitudes as a result of their exposure to persuasive communications, which can be divided into two distinct routes– central and peripheral–that anchor an elaboration likelihood continuum. When attitudes form or change via the central route, the elaboration likelihood condition is high; that is, the person's motivation and ability to process issue-relevant information both are high. This person is more likely to be persuaded by product attribute-based message arguments, whereas a person who lacks the motivation or ability to process such information follows a peripheral route, and persuasion occurs through peripheral cues such as music, endorsers, country of origin, and so forth. According to the ELM, message senders should increase the strategic fit of their messages by taking into consideration the persuasion routes that message receivers are likely to use. In high-tech markets, the continuously improving and highly overlapping product generations exacerbate product obsolescence, so products of prior generations depreciate because of the launch of a new generation or model, even if they are still perfectly functional. Customers' decisions about whether or when to adopt a new generation of technology largely depend on their expectations about the pace and magnitude of product improvements (Mohr, 2001). If a new product represents a new generation or significant upgrade, potential customers' willingness to migrate to the product varies as a function of their assessment of the value derived from that change (Guiltinan, 1999; Norton & Bass, 1987). To help prospective customers manage this migration, firms may engage in product-inherent value message communications. Most high-tech products are sophisticated, technologically complex, and/or difficult to explain or understand. Their buyers speak the same language, share the same mindset, possess specialized interests, and need the same technical information. Regardless of their product knowledge, they often have rational buying motives and high levels of involvement, and their purchase decisions involve their evaluation of product performance in terms of established objective standards (Alden, Steenkamp, Jan-Benedict, & Batra, 1999). Using a variety of analytical tools, modern purchasing professionals can conduct a broad range of evaluations for any new product offerings. Therefore, rational claims may increase their perception of the value of a new product by providing information that improves their comprehension of the product. Alternatively, marketing communications about new products could be conducted in a bipolar fashion, such that the messages deliver informational cues while evoking an emotional response. Nokia offers a salient example of communications that combine state-of-theart technical performance with a humane theme, which allows users to regard their highly technical phones as means to connect with other people. Although both types of messages can be used to launch high-tech products, informational messages should be more effective in this context than transformational messages. Accordingly, we hypothesize that H1. The use of informational messages to launch a high-tech product has greater (a) communication and (b) sales effects than does the use of transformational messages. 2.2. Elaborational/relational strategy and effectiveness Marketing communications can be also classified as elaborational or relational, distinguished according to how the message contents are linked to the parent brand of a new extension product (Bridges et al., 2000). On the one hand, elaborational messages mainly address the product attributes of an innovation and therefore represent a better communication strategy if the innovation is a new brand or exhibits a low perceived fit with the parent brand (Aaker & Keller, 1990). On the other hand, relational messages emphasize the relationship between the new product and its parent brand, which, assuming a high perceived fit, helps transfer existing brand equity to the focal new product (Aaker & Keller, 1990; Bridges et al., 2000). A good example of relational messages occurs whenever IBM launches its new products under the umbrella of its corporate brand. Brand management critically differentiates a successful hightech venture from an unsuccessful one. Developing and maintaining a strong brand helps promise and deliver value to customers and establishes a differentiation foundation for all marketing activities in general and marketing messages in particular (Bendixen, Bukasa, & Abratt, 2004; Ward, Light, & Goldstine, 1999). In the high-tech context, purchases involve both business managers and end users, and business managers who make purchases for organizations are concerned about not only how the vendor's products and services will complement their company's business and technological environment but also how the purchase decision will look to others. In addition, Mohr (2001) advocates that high-tech brands must promise value to end users, not to resellers. Whereas the former are far more interested in what a technology product will do for them, the latter focus more on high margins than on reinforcing the manufacturer's promise of value. Moreover, the speed with which high-tech products are launched increases the complexity of using new products, which causes customer confusion and fears about using any new products (Beard & Easingwood, 1996; Moriarty & Kosnik, 1989). Marketers of strong brands, whose customers perceive them as trustworthy and expert, likely supply a steady stream of innovations, because customers' adoption risks and the cognitive effort associated with confusing information clutter are lessened (Keller, 1998; Mudambi, 2002). In a sense, creating strong brands is no less, if not more, important in high-tech markets than in the consumer packaged goods industry. Apparently, however, adoption resistance to new high-tech products cannot be removed simply by sending elaborational messages. Customers face uncertainty-derived risks and often become highly confused by information overload, even if they have sufficient product knowledge. The use of relational C.-W. Chen et al. / Industrial Marketing Management 36 (2007) 1046–1056 messages takes advantage of existing brand equity, because given substantial brand equity, relational messages can shape customers' attitudes toward new products. High-tech firms therefore can launch new products more successfully by sending relational messages than by sending elaborational messages. H2. The use of relational messages to launch a high-tech product has greater (a) communication and (b) sales effects than does the use of elaborational messages. 2.3. Moderation of communication process characteristics The way message contents get conveyed by the communications process is as imperative an element in marketing communications as the content. Accordingly, maintaining process quality becomes a critical issue to ensure the effectiveness of marketing communications (Phelps, Harris, & Johnson, 1996; Zahay, Peltier, Schultz, & Griffin, 2004). In the IMC era, every communication aspect must be executed in such a unified manner that information is clear and uniform and thereby achieves the maximum impact on customers (Schultz, Tannenbaum, & Lauterborn, 1993). The exchange theory model of interpersonal communications proposed by Gatignon and Robertson (1986) posits that message clarity and message uniformity represent two characteristics of the communication process that influence the uncertainty related to a message. The degree of uncertainty reflects receivers' confidence regarding the conveyed information and acts as a weight of message persuasiveness. Message clarity refers to the extent to which messages are communicated without ambiguity or noise (Gatignon & Robertson, 1991; Shannon & Weaver, 1949). In high-tech industries, market uncertainty, technological uncertainty, and competitive volatility challenge customers' cognitive capabilities, so messages with high clarity should be more readily accepted and precisely interpreted by customers, which makes the messages more persuasive (Gatignon & Robertson, 1991; Heil & Robertson, 1991). Because customers feel more comfortable and confident in making their subsequent decisions, they become more likely to react in accordance with the message sender's expectations. H3. The (a) communication and (b) sales effects of conveying informational messages increase as message clarity increases. H4. The (a) communication and (b) sales effects of conveying relational messages increase as message clarity increases. Message uniformity refers to the degree to which messages stay compatible or consistent from different sources and over time (Lilly & Walters, 1997). Higher message uniformity–that is, greater consistency among messages–increases the receivers' confidence with regard to processing and interpreting the information and enhances their coherent cognition of the product attributes (Heil & Robertson, 1991; Howell & Burnett, 1978). Consistency between new and old messages also is crucial, in the sense that previous information creates expectations, and receivers react differently when their expectations are confirmed or disconfirmed (Oliver 1997). 1049 H5. The (a) communication and (b) sales effects of conveying informational messages increase as message uniformity increases. H6. The (a) communication and (b) sales effects of conveying relational messages increase as message uniformity increases. The need for IMC increases with the size and number of activities or campaigns, which can range from discrete promotional pieces to a massive campaign involving various promotional tools and even to multiple campaigns coordinated across many countries. The integration of marketing communications occurs to different degrees that can be described in terms of a spectrum anchored by two extremes: completely detached and fully integrated. The core concept of IMC promotes synergism, which means that greater benefits accrue from greater integration. In contrast, a loose collection of unconnected activities leads to separation and dysfunction and, accordingly, imposes negative impacts on the marketing communication effort (Duncan & Everett, 2000; Pickton & Broderick, 2001; Shimp, 2000). H7. The (a) communication and (b) sales effects of conveying informational messages increase as the integration of communication increases. H8. The (a) communication and (b) sales effects of conveying relational messages increase as the integration of communication increases. 3. Research method 3.1. Measures In an attempt to test the proposed hypotheses, we designed a self-administrated questionnaire to gather information with respect to the marketing communications used by Taiwanese high-tech companies for their product launches. We provide the constructs and a sample of their corresponding measurement items in Table 1. The scales were developed on the basis of relevant studies and according to Churchill's (1979) recommendations. Seven-point Likert scales were used, for which 1 = “strongly disagree” and 7 = “strongly agree.” We developed a preliminary questionnaire from existing research, then conducted in-depth interviews with two academics and a pretest of 30 managers to refine the questionnaire, measures, and data collection methods. To analyze the pretest results, we use a series of factor analyses and eliminate items with factor loadings lower than .5 (Hair, Anderson, Tatham, & Black, 1995). The informational messages scale refers to the extent to which messages are rational, relevant, and factual, whereas the transformational messages scale captures the degree of emotional contents used in the marketing communications (Puto & Wells, 1984). To measure the level of contents associated with branding, we develop two constructs of elaborational and relational messages from Bridges et al. (2000). The first scale measures the extent to which messages focus on product-related features and customer benefits; the second scale assesses how 1050 C.-W. Chen et al. / Industrial Marketing Management 36 (2007) 1046–1056 Table 1 Summary of measures Construct Operational definition Informational messages Messages convey information about the identity of the new product logically Sample item Communicated messages emphasize the specifications of the focused product Transformational Messages convey Communicated messages experiential and messages make sentimental much of good information about experiences in using the product using the product Elaborational Messages feature Communicated messages the attributes and messages benefits of the new emphasize the product attributes or characteristics of the product Relational Messages stress Communicated messages the relationships messages between the new emphasize the product and its relationships parent brand between the new product and the brand of parent company Messages for Message clarity Disseminated launching the messages are unambiguous and new product are delivered clearly precise Messages for Message The launching the uniformity communication new product are messages for the consistent from product are beginning to end consistent throughout the launch activities The company Integration of A variety of has formulated a communication marketing well-defined communication strategy to guide activities are integrated the marketing communications strategically Communication The extent to The launched effect which the launch product enjoys great awareness activities achieve communicationrelated objectives Sales effect The extent to The sales of the which the launch launched product activities achieve are really great sales-related objectives Items Cronbach's α 9 0.9272 8 0.9073 7 0.9065 4 0.8265 5 0.8815 5 0.8908 6 0.9077 5 0.8919 5 0.8728 much the message contents relate to the parent brand of the focal product. We developed the scales of the three moderator variables as follows: Message clarity assesses the extent to which messages are conveyed in a precise and unambiguous way (Heil & Robertson, 1991; Robertson, Eliasberg, & Rymon, 1995); message uniformity measures whether communicated messages for the focal product are consistent across time and activities (Heil & Robertson, 1991; Lilly & Walters, 1997); and integration of communications captures the extent to which all marketing communications fall in line with the set objectives and complement one another (Duncan & Everett, 2000; Pickton & Broderick, 2001; Schultz et al., 1993). Finally, as is common, we assess the effectiveness of marketing communications according to communication and sales effects (Cooper & Kleinschmidt, 1987; Lavidge & Steiner, 1961; Rogers, 1962; Ruekert & Walker, 1987). Table 1 includes the Cronbach's alpha values of all scales and shows that all coefficients are greater than .80, indicating acceptable reliability and unidimensionality (Nunnally, 1978). 3.2. Sample The sampling frame of our research includes a broad spectrum of high-tech sectors in which product innovation and launch are prevalent phenomena. We obtained a combined list of high-tech firms from two sources: the database list of the Winners of the Symbol of Excellence Award held by the Taiwan External Trade Development Council (TAITRA) and a database list of the top 1000 Taiwanese enterprises from Commonwealth Magazine, one of Taiwan's leading business publications. The sample size for our research is 530 firms, which enables us to address both theoretical and practical considerations. In advance of mailing the questionnaires, preliminary telephone contacts were made to identify key informants, solicit their cooperation, and verify mailing addresses. Overall, 114 questionnaires were completed and returned, but 13 were eliminated because of missing data on key construct items. Accordingly, we have 101 usable questionnaires left for our data analysis, a response rate of 19.06%. We calculated the means of three industry-related constructs– market uncertainty, technological uncertainty, and competitive volatility (Jaworski & Kohli, 1993)–to verify the legitimacy of the samples. All three values are greater than 5, indicating a successful sample selection. To ensure that the sample is representative of the entire population, we used t-tests to examine the differences in two firm-related variables, annual sales and number of employees, between early and late respondents (Armstrong & Overton, 1977). We consider responses received within 4 weeks after the initial mailing early (n = 45) and those received after 4 weeks late (n = 56) (cf. Mishra, Heide, &Cort, 1998) and find no significant differences between the two groups on either measure. We therefore conclude that nonresponse bias is not a serious concern in this research. 3.3. Data analysis We employ a series of moderated regression analyses (Aiken, West, & Reno, 1991) to test the proposed hypotheses. The regression models include the main effects of the predictor and moderator variables, along with the predictor × moderator interaction effects. All predictor and moderator variables are meancentered to reduce multicollinearity among the product terms and their constituent terms (Cohen & Cohen, 1983; Jaccard, Wan, & Turrisi, 1990). We also calculate variance inflation factors for the C.-W. Chen et al. / Industrial Marketing Management 36 (2007) 1046–1056 1051 Table 2 Descriptive statistics and correlation matrix Variable Informational message (IM) Transformational message (TM) Elaborational message (EM) Relational message (RM) Integration of communication (IC) Message uniformity (MU) Message clarity (MC) Mean 5.77 4.98 5.71 5.88 5.12 5.43 5.64 S.D. 0.76 1.13 0.80 0.79 0.95 0.78 0.68 Coefficients of Pearson correlations IM TM EM RM IC MU MC 1.000 0.057 0.194 0.982 ⁎⁎ 0.106 0.293 ⁎⁎ 0.449 ⁎⁎ 1.000 − 0.050 0.079 0.514 ⁎⁎ 0.140 0.195 1.000 0.154 − 0.009 0.183 0.301 ⁎⁎ 1.000 0.123 0.240 0.39 1.000 0.136 0.199 ⁎ 1.000 0.582 ⁎ 1.000 ⁎ p b .05. ⁎⁎ p b .01. independent variables and find that all values are well below 10, the cutoff point for eliminating multicollinearity (Myers, 1986). To examine the effectiveness of the messages, we use a procedure suggested by Neter et al. (1990) and test whether the parameters estimated by the same regression differ. Specifically, we develop in sequence the following full model: Yi = β0 + β1Xi1 + β 2Xi2 + εi, where β1 ≠ β2, and a reduced model under the null hypothesis (β1 = β2). The F-statistics differ significantly at the .05 level, so the null hypothesis is rejected. 4. Results In Table 2, we provide the descriptive statistics and correlation matrix for all variables. We perform separate regression analyses with both categories of messages as predictor variables and the two effectiveness measures as criterion variables; thus, we report the results of four moderated regression analyses in Tables 3 and 4. 4.1. Informational/transformational messages and effectiveness As we show in Table 3, H1a is supported; informational messages are positively related to the communication aspect of effectiveness, and the effect is significantly greater than that of transformational messages (βIM = .53 N βTM = − .09; ΔF N F0.05 (1, 97)). Moreover, the regression coefficients of informational and transformational messages for sales effect differ signifi′ = .42 N β TM ′ = cantly and in the hypothesized direction (β IM − .11; ΔF N F0.05 (1, 97)), in support of H1b. To test the moderating effects, we calculate the F-statistic differences between Models 2 and 3 for communication and sales effects and find that both ΔF values are statistically significant (ΔF communication = 2.88; ΔF sales = 3.95), which indicates that variances in the criterion variables can be explained by incorporating the moderator variables into the models. Specifically, the significance of the respective product terms clearly Table 3 Informational/transformational messages and effectiveness Variables Main effects of predictor variables Informational messages (IM) Transformational messages (TM) (a) Communication effect Model 1 Model 2 Model 3 Model 1 Model 2 Model 3 .53 ⁎⁎⁎ − .09 .33 ⁎⁎ − .21 ⁎⁎ .16 ⁎ −.10 .42 ⁎⁎⁎ − .11 .22 ⁎⁎ −.23 ⁎⁎ .02 − .05 Main effects of moderator variables Message clarity (MC) Message uniformity (MU) Integration of communication (IC) Moderating effects IM × MC IM × MU IM × IC TM × MC TM × MU TM × IC F-statistic Adjusted R2 ⁎ Significant at p b .10. ⁎⁎ Significant at p b .05. ⁎⁎⁎ Significant at p b .01. (b) Sales effect 19.28 ⁎⁎⁎ .27 .35 ⁎⁎ .15 .09 .28 ⁎⁎⁎ .11 −.07 15.73 ⁎⁎⁎ .42 .24 ⁎⁎ .16 .22 ⁎⁎ .04 .01 −.11 12.85 ⁎⁎⁎ .57 11.12 ⁎⁎⁎ .17 .38 ⁎⁎ .10 .08 .29 ⁎⁎⁎ .01 − .06 13.13 ⁎⁎⁎ .31 .30 ⁎⁎ .24 ⁎⁎ .22 ⁎⁎ .02 − .02 .01 17.08 ⁎⁎⁎ .60 1052 C.-W. Chen et al. / Industrial Marketing Management 36 (2007) 1046–1056 offers support for our hypothesized moderating effects. Consistent with our expectations, both communication and sales effects of informational messages are strengthened by message clarity (βIM × MC = .24, p b .05; β′IM × MC = .30, p b .05), which confirms H3a and b. However, the moderation effect of message uniformity on the informational message–communication link is not significant (βIM × MU = .16, p N .10), so H5a is not supported. In contrast, H5b is confirmed, because the sales effect of informational messages is positively moderated by message uniformity (β′IM × MU = .24, p b .05). The hypothesized positive moderating effects of integrated communications on the relationships of informational message with communication and sales effects are both statistically significant, with βIM × IC and β′IM × IC = − .22 ( p b .05). ′ × MC = .24, specific performance (βRM × MC = .24, p b .05; βRM p b .05). Although message uniformity's moderation of the communication effect of relational messages is not significant, according to the insignificant regression coefficient of the product term βRM × MU = .13 ( p N .10), message uniformity imposes a positive moderating effect on the sales effect of relational messages (βRM ′ × MU = .32, p b .01). Thus, though H6a is not supported, H6b is confirmed. The positive moderating effects of integrated communications on the relational message– communication effect (H8a) and relational message–sales effect (H8b) links are both statistically significant, with βRM × IC = .15 ( p b .1) and βRM ′ × IC = .29 ( p b .01). 4.2. Relational/elaborational messages and effectiveness We summarize our hypothesis testing results in Table 5 and use the subsequent discussions to recapitulate the rationale behind the supported hypotheses and explore some explanations for the unsupported hypotheses. As Table 4 shows, both relational and elaborational messages have significant influences on communication objective-related performance, though the impact of relational messages is significantly greater than that of elaborational messages (βRM = .45 N βEM = .24, ΔF N F0.05 (1, 97)). Similarly, Model 1 indicates significant coefficients for both elaborational and relational messages. Relational messages have significantly greater sales effects than do elaborational messages (βRM ′ = .19 N β′EM = .18, ΔF N F0.05 (1, 97)), so both H2a and b are supported. The differences in the F-values of Models 2 and 3 (communication and sales effects) are statistically significant, which indicates that the moderator variables substantially improve the variance explanation (ΔF communication = 3.11; ΔF sales = 6.51). The moderating effects tests show that, as we hypothesized in H4, message clarity strengthens the impacts of relational messages on both communication-specific and sales- 4.3. Discussion 4.3.1. Main effects of predictor variables The ELM theory suggests that a message receiver's amount of elaboration of product-related information varies with his or her motivations and abilities (Petty & Cacioppo, 1981). The fast pace of technological change creates high uncertainty levels for high-tech customers, who must continuously search for timesensitive information, which quickly loses its value, to lessen their uncertainty (Mohr, 2001). Most customers in high-tech markets also are relatively knowledgeable and able to evaluate product-related information (Alden et al., 1999). With their greater involvement, need for cognition, and product knowledge, these customers are more inclined to follow a central processing route (Lee & O'Connor, 2003). Compared with Table 4 Elaborational/relational messages and effectiveness Variables (a) Communication effect Model 1 Main effects of predictor variables Elaborational message (EM) Relational message (RM) .24 ⁎⁎⁎ .45 ⁎⁎⁎ Main effects of moderator variables Message clarity (MC) Message uniformity (MU) Integration of communication (IC) Moderating effects EM × MC EM × MU EM × IC RM × MC RM × MU RM × IC F-statistic Adjusted R2 ⁎ Significant at p b .10. ⁎⁎ Significant at p b .05. ⁎⁎⁎ Significant at p b .01. 19.77 ⁎⁎⁎ .28 Model 2 .14 ⁎ .30 ⁎⁎⁎ (b) Sales effect Model 3 .08 .20 ⁎⁎ .32 ⁎⁎⁎ .15 − .02 .32 ⁎⁎⁎ .10 − .06 14.29 ⁎⁎⁎ .40 − .01 − .07 .07 .24 ⁎⁎ .13 .15 ⁎ 11.18 ⁎⁎⁎ .53 Model 1 .18 ⁎ .19 ⁎ 4.10 ⁎⁎ .08 Model 2 .11 .06 Model 3 .01 − .13 .31 ⁎⁎ .03 − .02 .31 ⁎⁎⁎ − .10 − .08 3.60 ⁎⁎⁎ .12 .01 .002 .07 .24 ⁎⁎ .32 ⁎⁎⁎ .29 ⁎⁎⁎ 10.11 ⁎⁎⁎ .50 C.-W. Chen et al. / Industrial Marketing Management 36 (2007) 1046–1056 1053 Table 5 Summary of results Variables Main effects Informational messages (IM) Transformational messages (TM) Relational message (RM) Elaborational message (EM) Moderating effects IM × Message clarity (MC) RM × Message clarity (MC) IM × Message uniformity (MU) RM × Message uniformity (MU) IM × Integration of Communication (IC) RM × Integration of Communication (IC) Hypothesis H1a and b H2a and b H3a and b H4a and b H5a and b H6a and b H7a and b H8a and b Expected result (sign) βIM a βTM βRM a βEM (+) (+) (+) (+) (+) (+) Coefficient Final result (a) Communication (b) Sales .53 ⁎⁎⁎ −.09 .45 ⁎⁎⁎ .24 ⁎⁎⁎ .42 ⁎⁎⁎ − .11 .19 ⁎ .18 ⁎ .24 ⁎⁎ .24 ⁎⁎ .16 .13 .22 ⁎⁎ .15 ⁎ .30 ⁎⁎ .24 ⁎⁎ .24 ⁎⁎ .32 ⁎⁎⁎ .22 ⁎⁎ .29 ⁎⁎⁎ Supported Supported Supported Supported Partially supported Partially supported Supported Supported a Expected greater impact. ⁎ Significant at p b .10. ⁎⁎ Significant at p b .05. ⁎⁎⁎ Significant at p b .01. transformational messages, informational messages, which present factual and relevant product information, therefore tend to improve communication- and sales-based launch performance. The fast-moving and volatile characteristics of high-tech industries also may result in customers' confusion and resistance to adoption (Beard & Easingwood, 1996). In the high-tech arena, a strong brand provides a distinctive identity that establishes a relevant, enduring, and credible promise of value, as well as a reassuring beacon that customers can use as a heuristic to reduce their perceived risks and anxiety (Mohr, 2000). A brand can be a powerful source of competitive advantage, in the sense that it can be understood better because it has remained the same and therefore can “buy time” in the face of new technology or serious lapses in product quality (Ward et al., 1999). In turn, brand extensions have become important launch strategies for high-tech firms like Microsoft, Intel, and Hewlett-Packard. Our findings support the use of relational messages to support product launch, because though both elaborational and relational messages enjoy positive communication and sales effects, relational messages tend to have greater impacts. Accordingly, a high-tech firm may accelerate the diffusion of its new products by associating them firmly with the family or corporate brand, in addition to conveying product attribute messages. 4.3.2. Moderating effects Overall, our findings confirm the hypotheses that suggest message clarity, message uniformity, and integration of communications moderate the relationships between messages and their effectiveness. The empirical results demonstrate the importance of communication quality for an effective message strategy. Message clarity strengthens the effects of messages, whether informational or relational, and clear, unequivocal, specific messages offer receivers a single, straightforward interpretation with which they may make causal attributions with minimal errors (Daft & Macintosh, 1981; Jervis, 1970). Thus, clearly delivered messages facilitate the message sender's intention to enhance product comprehension or increase the association with the parent brand. Uniform messages also facilitate message reception (Heil & Robertson, 1991; Howell & Burnett, 1978), but our regression analyses provide mixed results with respect to their hypothesized moderation effect. Although message uniformity fails to impose any significant moderating effect on the message– communication effect link, it demonstrates positive impacts on the message–sales effect relationship. Because message uniformity means the consistency of communications throughout launch activities and over time, it may influence the early phases of customer cognition, such as awareness, interest, and attitude (Rogers, 1962), only minimally. Instead, customers may perceive various messages as consistent only after they receive a series of communications. Hence, uniformity moderates only the influence of messages about adoption, which entail the directly sales-related aspect of cognition. Finally, the integration of communications positively affects the relationships of both informational and relational messages with communication- and sales-based performance. These findings further confirm the importance of IMC. In addition to creating and selecting the correct messages, firms must align their communication campaigns or activities with their set objectives to deliver effective and efficient marketing communications for product launches. 5. Conclusion and managerial implications Our research shows that in high-tech industries, what to say and how to say it are both essential for marketing communications designed to support a product launch. We explore the strategies for designing messages (i.e., what to say) according to informational/transformational and elaborational/relational dimensions and propose that high-tech customers, who are relatively motivated and able to process new product-related information easily, may be better swayed by informational 1054 C.-W. Chen et al. / Industrial Marketing Management 36 (2007) 1046–1056 messages, which increase their awareness of, interest in, and comprehension of new products and lead to their adoption of the product. That is, the use of informational messages is more effective for launching high-tech products than is the use of transformational messages. Moreover, it is beneficial to use relational messages, which emphasize the association of the new product with its parent brand, than elaborational messages, because the high speed of product innovation in high-tech industries increases customers' perceived adoption risks associated with product obsolescence or network externality. Marketers can overcome adoption resistance by delivering messages that link products to their parent brands, which, if they possess strong brand equity, can generate customer trust and confidence in the new products. These aforementioned findings have managerial implications for designing new product-related messages. The messages communicated to facilitate product launch should balance informational and relational elements, and the firm should make its informational and relational messages complementary, not mutually exclusive. Performance represents the price of admission in high-tech markets, so many high-tech companies promise value on the basis of cutting-edge products and superior service and support (Ward et al., 1999), which causes consumers of new high-tech products to consider them full of perceived and cognitive risks and resist their adoption (Lee & O'Connor, 2003). It is therefore critical that marketers use appropriate message strategies to reduce such risks and increase product adoption. High-tech firms also should give priority to branding and brand-building programs. Keller (1998) indicates that the short product life cycle of high-tech products places a premium on corporate or family brands with strong credibility associations. When it comes to brand strategy, a high-tech firm is less likely to brand its new products with totally new names; rapid product obsolescence would make it costly for the firm to do so and difficult for customers to develop product or brand loyalty. Corporate and product family names thus serve as naming platforms, to which modifiers are attached to name new product versions—Windows 2000, or Microsoft Word, Microsoft Works, Microsoft Explorer, and so forth (Ryder, 1994; Shipley & Howard, 1993). For example, the successful “Intel Inside” campaign has led end users to generate favorable associations with Intel's corporate brand. Likewise, Cisco Systems has leveraged its success in the behind-the-scenes business market into the growing consumer network market through its television commercials. Brand-building efforts also emerge from companies like Nokia, Qualcomm, and Oracle, which have started to use mass media to reach broader customer markets to establish and nurture their corporate or brand identities (Mohr, 2001). Managers must bear in mind that the quality of the communication process, given effective message content, is critical to new product success. Clear messages influence receivers' cognitive efficiency so they may accurately perceive and respond to the communication. The effectiveness of launch-related marketing communications, in terms of communication or sales effects, therefore can be improved. Our research reveals that the extent to which marketing communications are integrated is critical to the effectiveness of a message strategy; thus, synergy will heighten the impact of specific marketing communications. Surprisingly, message uniformity fails to impose any impact on the message–communication relationship, but it does positively moderate the sales effect—possibly because receivers perceive a series of messages as uniform only in the late stages of cognition, close to their adoption decision. High technological uncertainty, a salient characteristic of high-tech industries, may lengthen the customer's cognition process and diminish the moderating effects of consistent messages. However, marketing communications may be enhanced by accelerating customer perceptions of messages as uniform during earlier cognition stages. Overall, messages must communicate in such a clear, uniform, and integrated manner that the target audience responds or reacts just as marketers expected. For effective communication to occur, messages should fit the cognitive capability of the target audience and be delivered through coordinated, integrated marketing communications (Fill, 2001). Our findings also have important implications for high-tech firms in emerging economies like Taiwan. Most Taiwanese high-tech firms are involved in OEM, though some have been trying to change their business model into original design manufacturing or original brand manufacturing. We find that new product success hinges on the successful planning and execution of supportive marketing communications that focus messages not only on product attributes but also branding. Taiwanese high-tech firms, which possess great expertise in R&D and engineering, must start learning how to build their own brands and implement essential marketing communications to promote their brands and affiliated products if they want to increase their value for customers and themselves. 6. Directions for future research Additional research might attempt to probe the typology of message strategies, especially for product launches. Communication process represents another topic worth exploring, and the role of process quality in marketing communications needs more academic attention and efforts. For example, the frequency and strength of communications may differ across products, firms, and industries, and if we can understand the manner in which messages are carried to promote new products, we could gather normative implications. 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The role of transactional versus relational date in IMC programs: Bringing customer data together. Journal of Advertising Research, 44(1), 3−18. Chien-Wei Chen, Ph.D., is an assistant professor in the Department of International Business, College of Commerce, National Chengchi University, Taiwan. His research focuses on new product management, marketing communications, and international marketing. Chung-Chi Shen is an assistant professor in the Department of International Business at Providence University in Taiwan. His research interests include marketing strategy, e-tailing, and online consumer behavior. Wan-Yu Chiu is an MBA graduate of the Department of International Business, National Chengchi University. Currently she works for Bristol Meyers Squibb (Taiwan) Ltd.