Managerial disposition and front-end innovation success

JBR-09233; No of Pages 9 Journal of Business Research xxx (2016) xxx–xxx

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Journal of Business Research

Managerial disposition and front-end innovation success Mayoor Mohan Ph.D. a,⁎, Kevin E. Voss Ph.D. b, Fernando R. Jiménez Ph.D. c a b c

VCU School of Business, Virginia Commonwealth University, Richmond, VA 23284, USA Spears School of Business, Oklahoma State University, Stillwater, OK 74078, USA College of Business Administration, The University of Texas at El Paso, El Paso, TX 79968, USA

a r t i c l e

i n f o

Article history: Received 2 April 2016 Received in revised form 4 August 2016 Accepted 8 August 2016 Available online xxxx Keywords: Managerial disposition Front-end innovation Innovation culture Manager activation theory Decision-making comprehensiveness

a b s t r a c t The link between innovation culture and firm performance is well established. However, the specific mechanism via which innovation culture facilitates better managerial decision-making in front-end innovation remains unknown. Based on manager activation theory, the authors propose that innovation culture enables decisionmaking comprehensiveness—the full exploration of new ideas—by inhibiting the deleterious effects of the fear of negative evaluation and allowing managers to apply themselves to those areas in which they feel most competent. In turn, decision-making comprehensiveness is positively related to front-end innovation success. The model was tested with survey data collected from a sample of 172 innovation decision-makers. Implications are that top management should incentivize the quantity of new ideas, not penalize product failures, and encourage decision-making comprehensiveness. With an innovation culture, the risk of making suboptimal decisions in the front end of innovation is limited. © 2016 Elsevier Inc. All rights reserved.

1. Introduction In 1995, in the U.S. professional baseball leagues, Seattle Mariners' star batsman Edgar Martinez had 511 chances at bat and hit the ball 182 times (a 0.356 batting average, which was the best that year). Martinez was walked 116 times, hit 29 home runs, and struck out 87 times that season. In baseball, great hitters need the freedom to swing. However, that freedom comprises the freedom to not swing (i.e., to walk), to swing for the fences (i.e., hit home runs), and to swing and miss (i.e., strike out). In business, managers have long recognized that an innovation culture in which employees feel free to swing and miss at new product ideas is a key predictor of innovation success (Ali & Park, 2016; Büschgens, Bausch, & Balkin, 2013; Tellis, 2012). Moreover, the extant research supports the link between innovation culture and firm performance (Chen, Bu, Wu, & Liang, 2015; Hurley & Hult, 1998; Rubera & Kirca, 2012; Tellis, Prabhu, & Chandy, 2009). However, the specific mechanism explaining how an innovation culture affects employees' decisions to swing or not to swing remains unclear. Thus, this study attempts to fill that void. The authors propose that innovation culture facilitates front-end innovation success by enhancing decision-making comprehensiveness—conducting an exhaustive consideration of multiple ⁎ Corresponding author. E-mail addresses: [email protected] (M. Mohan), [email protected] (K.E. Voss), [email protected] (F.R. Jiménez).

approaches (Slotegraaf & Atuahene-Gima, 2011). Based on Triandis' (1989) framework, the authors introduce manager activation theory and develop a conceptual model in which an innovation culture inhibits the deleterious effects of the fear of negative evaluation and allows managers to apply themselves to those areas in which they feel most competent. This improves decision-making comprehensiveness, which, in turn, improves front-end innovation performance. The model is supported by survey data collected from a sample of 172 innovation managers. To the best of our knowledge, this is the first study to test the combined role of two managerial dispositions: (i) fear of negative evaluation and (ii) perceived competence in innovation decision-making. The mechanism via which innovation culture affects managerial decision-making, as well as assists managers in designing more efficient innovation processes, implementing appropriate policies, and developing effective reward systems, is highlighted. In particular, upper-level management should nurture a culture of innovation in the organization by incentivizing the development of new ideas, minimizing the penalty associated with unsuccessful ideas or “failures,” and encouraging decision-making comprehensiveness. Unless the firm's innovation culture is strong, the risk of making sub-optimal decisions in the front-end of innovation, in which concepts with merit may be prematurely expunged, will increase. In the rest of the paper, we provide a review of the relevant literature, introduce the theoretical framework, and develop testable hypotheses. Then, we discuss our methodology and results, which is

http://dx.doi.org/10.1016/j.jbusres.2016.08.019 0148-2963/© 2016 Elsevier Inc. All rights reserved.

Please cite this article as: Mohan, M., et al., Managerial disposition and front-end innovation success, Journal of Business Research (2016), http:// dx.doi.org/10.1016/j.jbusres.2016.08.019

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subsequently followed by a discussion focusing on the managerial and theoretical implications. 2. Theoretical background and hypotheses Innovation culture is an organizational culture in which organizational members share the belief that openness to new products, processes, or ideas are distinctive organizational values (Hurley & Hult, 1998; Rubera & Kirca, 2012). These values provide norms for behavior that result in the development and launch of new products (Damanpour, 1991; Deshpandé, Farley, & Webster, 1993). Firms that nurture an innovation culture emphasize creativity, risk-taking, flexibility, and spontaneity, while de-prioritizing control, rigidity, tradition, and stability (Burns & Stalker, 1966; Chatman & Jehn, 1994; Deshpandé et al., 1993; Hurley & Hult, 1998; Jassawalla & Sashittal, 2003). Further, the idea that innovation culture enables better firmlevel performance outcomes has received substantial support (Hurley & Hult, 1998; Rubera & Kirca, 2012; Tellis, 2012; Tellis et al., 2009). At the managerial-level, a culture of innovation is associated with managers' attitudes and behaviors deemed conducive to innovation. For instance, innovation culture is related to willingness to cannibalize (Chandy & Tellis, 1998), tolerance for risk (Cooper, Edgett, & Kleinschmidt, 2004), and readiness to deal with and accept uncertainty (Büschgens et al., 2013). Thus, an innovation culture helps managers mitigate the negative associations that stem from innovation failures (Tellis, 2012) and empowers them to consider alternatives that they otherwise may not (Gumusluoğlu & Ilsev, 2009). Indeed, a conclusion reached from this literature is that innovation culture is related to managerial decision-making, but the specific mechanism of how innovation culture enables a manager's decisions in front-end innovation remains unknown. Followed by formal development and commercialization, front-end innovation is the first and most important stage of the innovation process (cf. Brown & Eisenhardt, 1995; Griffin, 1997; Montoya-Weiss & Calantone, 1994; Reid & De Brentani, 2004). The most critical decisions associated with new product success occur during the front-end stage of innovation (Reid & De Brentani, 2004), which entails activities such as idea generation, concept definition, opportunity recognition, and idea evaluation. The front-end stage culminates with the decision of whether to invest more resources in a new product idea (Moenaert, Meyer, Souder, & Deschoolmeester, 1995; Reid & De Brentani, 2004; Smith & Reinertsen, 1998)—to swing or not to swing. At this stage, managers decide whether to be inclusive or exclusive in the number of new product ideas to put forth for formal development. An inclusive approach is referred to as decision-making comprehensiveness (Simons, Pelled, & Smith, 1999). Formally, decision-making comprehensiveness is defined as the “degree to which the innovation team is exhaustive as it considers multiple approaches, courses of action, and decision criteria in its strategic decision making” (Slotegraaf & Atuahene-Gima, 2011, p. 97). This activity aims to rigorously examine the feasibility, profitability, potential variants, competitive market advantage, and probability of the success or failure of new product ideas and concepts. This process may decrease the speed of new product development and tax additional resources; however, empirical research is inconclusive about the relationship between development speed and performance (Cankurtaran, Langerak, & Griffin, 2013). Nevertheless, the more rigorous the exploration of the multiple ideas entailed in decision-making comprehensiveness, the higher the likelihood of striking new product success (Slotegraaf & Atuahene-Gima, 2011). However, due to financial, informational, and time constraints, managers often must make “go-kill” decisions without certainty regarding the respective probabilities of product success or failure (Girotra, Terwiesch, & Ulrich, 2010; Van de Ven, 1986). Unfortunately, contrary to normative recommendations, decision-making biases under uncertainty influence managers to embrace a relatively exclusive approach by expunging uncertain ideas, often times prematurely (Droge, Calantone, & Harmancioğlu, 2008; García-Granero, Llopis,

Fernández-Mesa, & Alegre, 2015; Henard & Szymanski, 2001). Notably, in the published literature, theorists have not reconciled the role of innovation culture with regard to these managerial decision-making phenomena. This article contends that innovation culture increases decisionmaking comprehensiveness via managerial activation. Triandis (1989) proposed that a cultural context can influence an individual's behavior by activating or suppressing behavioral dispositions. Moreover, the link between national culture, disposition, and behavior has been empirically validated across several contexts, such as communication (Singelis & Brown, 1995), motivation (Markus & Kitayama, 1991), emotions (Singelis & Sharkey, 1995), personality (Mowen, 2000; Triandis & Suh, 2002), and consumer behavior (Cleveland, Rojas-Méndez, Laroche, & Papadopoulos, 2016; Kacen & Lee, 2002). In the same way that national culture influences individuals' behavioral dispositions, theorists suggest that organizational culture can activate a manager's dispositions (Chatman & Barsade, 1995; Chatman & Spataro, 2005; Hofstede, 1994). Hence, the authors introduce manager activation theory, which rests on the notion that all managers have within themselves latent dispositions that manifest in specific organizational contexts. These managerial dispositions can be suppressed or activated by organizational contexts such as culture (Bamberger, 2008; Johns, 2006). In turn, these dispositions are correlated with context-specific behaviors (Mowen, 2000). In the context of front-end innovation, two managerial dispositions are most prevalent: fear of negative evaluation and perceived competence. These dispositions manifest when managers act in the face of uncertainty (Klein, Cerully, Monin, & Moore, 2010; Trautmann, Vieider, & Wakker, 2008)—an idiosyncratic aspect of front-end innovation. Based on this notion, a model is presented in Fig. 1 in which a strong innovation culture leads to innovation success by enhancing decisionmaking comprehensiveness. A key proposition is that the firm's standing on innovation culture activates or suppresses managers' dispositions with respect to fear of negative evaluation and perceived competence—which, in turn, affect decision-making comprehensiveness. Thus, the model puts forth a mechanism by which innovation culture enables managerial decision-making. Fear of negative evaluation is a managerial disposition that inhibits decision-making comprehensiveness, and is defined as the “apprehension and distress arising from concerns about being judged disparagingly or hostilely by others” (Carleton, McCreary, Norton, & Asmundson, 2006, p. 297). In the front end, managers have little guarantee that the probabilities associated with future product success or failure can or will be identified. According to Danneels (2008), “the fear of failure in a punitive climate can dampen exploration” (p. 523). When fear of negative evaluation is activated, the fear of being perceived as wasting the firm's resources on unsuccessful ideas leads managers to steer new product decisions toward options for which the probabilities are known. In such cases, the deep consideration and investigation of alternatives—typical of high levels of decision-making comprehensiveness—are unlikely to change the decision. Thus, when fear of negative evaluation is activated, managers tend to shun ambiguous options without deep consideration and focus on more certain prospects (Curley, Yates, & Abrams, 1986; Fox & Tversky, 1998; Fox & Weber, 2002; Trautmann et al., 2008). Accordingly, managerial fear of negative evaluation suppresses decision-making comprehensiveness. Hence, we propose the following hypothesis. H1. Fear of negative evaluation is negatively related to decision-making comprehensiveness. Perceived competence refers to a manager's own sense of skill, knowledge, and understanding over a given decision context (Bandura, 1981; Heath & Tversky, 1991; Klein et al., 2010). Moreover, Bandura (1981) suggests that this disposition is important in “prospective situations that contain many ambiguous, unpredictable, and often stressful elements” (p. 200). Managers who perceive themselves as

Please cite this article as: Mohan, M., et al., Managerial disposition and front-end innovation success, Journal of Business Research (2016), http:// dx.doi.org/10.1016/j.jbusres.2016.08.019

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Innovation Culture

H3a β = .22 p < .01 Fear of Negative Evaluation

H5 β = .52 p < .01 H3b β = .21 p < .01

H1 β = −.18 p < .01 Decision-Making Comprehensiveness

Perceived Competence

3

H4 β = .34 p < .01

Front-end Innovation Performance

H2 β = .25 p < .01 2

Notes: system-weighted R = .46; standardized beta coefficients reported. Fig. 1. Conceptual model.

competent over a domain tend to perceive that, with their expertise in the area as well as proper research and consideration, they can arrive at better decisions than those reached by other managers (Camerer & Weber, 1992; Heath & Tversky, 1991). Hence, when perceived competence is high, managers pursue opportunities and use deep investigation to identify and manage aspects of the opportunity that can prevent loss (Klein et al., 2010). Thus, innovation managers that possess a high degree of perceived competence will push their teams to engage in an in-depth analysis of alternatives, use multiple criteria and metrics, and be more thorough in examining the available options and their respective merits to maximize the probability of success. Thus, we propose the following hypothesis. H2. Perceived competence is positively related to decision-making comprehensiveness. Manager activation theory states that innovation culture activates a manager's behavioral dispositions (Mowen, 2000; Singelis & Brown, 1995; Triandis, 1989). As discussed above, a strong innovation culture emphasizes the norms, values, and beliefs related to a firm's openness to new ideas (Hurley & Hult, 1998). At the same time, innovation culture serves to ruthlessly remove obstacles to successful innovation in firms. This cultural context makes employees feel supported to use resources to explore new ideas (Gumusluoğlu & Ilsev, 2009) and mitigates the negative associations that stem from failure (Tellis, 2012). A recent ad campaign by a national pizza restaurant chain illustrates this perspective when they brag that failure is an option (CPB Group, 2016). In such an environment, a manager's dispositions will be biased toward perceived competence and away from fear of negative evaluation. Specifically, fear of negative evaluation is less likely to become activated because the firm's innovation culture acts as a safety net (Danneels, 2008; Levinthal & March, 1993). Because a strong innovation culture supports the opportunity to both swing for the fences and swing and miss, concepts that might be ambiguous do not need to be automatically dismissed. Rather, such ideas and concepts can be pursued on an equal basis with less concern devoted to criticism. On the other hand, when innovation culture is weak, a project leader would experience fear of negative evaluation and, thus, engage in behavior to shield themselves from any potential blame (Trautmann et al., 2008); therefore, the originally hypothesized negative main effect would remain. Hence, we propose the following hypothesis.

H3a. When innovation culture is high, no obvious relationship between fear of negative evaluation and decision-making comprehensiveness will be observed; however, when innovation culture is low, the relationship between fear of negative evaluation and decision-making comprehensiveness is negative. In organizations with a weak innovation culture, managers are routinely expected to follow accepted norms regardless of their selfperceived areas of competence (Büschgens et al., 2013). In this type of decision-making context, managers are forced to allot resources in ways that are subject to the firm's directives, rather than at their discretion. Such contexts discourage creativity, reduce flexibility, and minimize empowerment (Hurley & Hult, 1998; Moorman, 1995; Moorman & Miner, 1997). Returning to the baseball metaphor, a firm's relatively formal procedures and structural rigidity takes the bat out of the hitter's hands. In contrast, firms with strong innovation cultures are thought to be less formalized and structurally rigid, thus opening up degrees of freedom for independent managerial action (Büschgens et al., 2013). As suggested by Poskela and Martinsuo (2009), with this relatively generous level of decision-making autonomy, managers can influence decision-making in the front end in ways in which they feel are positive. Accordingly, the organization's innovation culture empowers managers to pursue decision choices that they perceive as lucrative (Taylor, 1995). Therefore, the effects of high perceived competence on decision-making comprehensiveness are suppressed in weak innovation cultures. On the other hand, in strong innovation cultures, the positive effects of perceived competence on decision-making comprehensiveness are enhanced. Thus, the following hypothesis is proposed. H3b. When innovation culture is high, the relationship between perceived competence and decision-making comprehensiveness is positive; however, when innovation culture is low, no obvious relationship between perceived competence and decision-making comprehensiveness will be observed. In the published research, theorists have drawn strong empirical conclusions regarding the relationship between decision-making comprehensiveness and firm performance (Atuahene-Gima & Li, 2004; Menon, Bharadwaj, Adidam, & Edison, 1999). This positive relationship has also been demonstrated in research that has examined new product

Please cite this article as: Mohan, M., et al., Managerial disposition and front-end innovation success, Journal of Business Research (2016), http:// dx.doi.org/10.1016/j.jbusres.2016.08.019

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advantage and firm innovation performance (Slotegraaf & AtuaheneGima, 2011). However, rather than focusing directly on overall firm innovation performance, the focus herein is on the effect of decisionmaking comprehensiveness on front-end innovation performance. This is because the organizational context created by the firm's innovation culture is thought to have its greatest impact in the earliest stages of the innovation process, in which key “go-kill” decisions are made. Front-end innovation performance is defined in terms of the overall evaluation of the quality of the product concepts produced by the front end of the innovation process, which entails activities like idea generation, concept definition, and opportunity recognition. This involves numerous other sub-activities that require extensive research, collaborative work, and the evaluation and justification of various prospects. Consequently, to be successful at the front end of innovation, a high degree of decision-making comprehensiveness is necessary. If innovation teams do not engage in this key activity, systemic failures at the front end of innovation could result, which would inevitably be passed on to the subsequent stages of the innovation process. As a result, we propose the following hypothesis. H4. The relationship between decision-making comprehensiveness and front-end innovation performance is positive. Indeed, past research is consistent with the idea that innovation culture supports the structural processes associated with overall firm performance. For example, Hurley and Hult (1998) suggest that innovation culture influences overall firm performance by enabling the firm's capacity to innovate. As such, a firm that values innovation and develops norms that encourage the behaviors that support innovation, and/or sanction behaviors that interfere with innovation, will be highly likely to build skills and abilities that enable innovation success. The front end of innovation activities and skills are especially primed to benefit from a strong cultural focus on innovation (Büschgens et al., 2013; Reid & De Brentani, 2004). According to De Brentani and Kleinschmidt (2004), this is especially the case for the managers and key decision-makers who benefit from the motivational aspects of such a culture. Therefore, when examining the front end of innovation as a key stage for generating new ideas and concepts, be they radical or incremental in scope, cultural mechanisms play a vital role (O'Connor & Rice, 2013). For this and reasons stated previously, we propose the following hypothesis. H5. The relationship between innovation culture and front-end innovation performance is positive.

3. Research methodology 3.1. Data collection overview and sample A survey was developed and administered to a panel of key informants with significant expertise in innovation-related decisionmaking. The questionnaire was developed and pre-tested using a group of marketing scholars (n = 3), convenience sample of MBA students (n = 8), and small group of industry professionals (n = 3). Relevant feedback was employed to refine and improve the survey. Respondents, who were solicited by professional panel provider Research Now, were presented with the questionnaire online. The sampling frame consisted of U.S. based managers responsible for making key innovation-related decisions. Potential study participants that fit the sampling frame were invited by the panel provider to take the survey. To ensure quality, key informant qualification questions were employed to assess respondents' level of involvement in innovation-related decision-making (Kumar, Stern, & Anderson, 1993). The screening questions identified whether respondents made final decisions regarding innovation/new product development and led those respective teams. Based on these screening criteria, only

those respondents that passed the qualification hurdle were presented the survey instrument. Of 372 invitees, 178 respondents (47.7%) qualified to take the survey based on the screening questions. Moreover, six incomplete cases were dropped, leaving a sample of 172 respondents in the dataset. To further evaluate the quality of those participants that qualified based on the screening questions, an additional nine seven-point Likert-type items were included, which were intended to assess informants' managerial role and expertise with respect to innovation activities. The mean for each of the nine items was N5.75. Based on both the screening question and the nine-item measure to assess overall informant quality, study respondents have high levels of expertise, knowledge, and experience of their firm's innovation activities as well as overall objectives and goals (Kumar et al., 1993). 3.2. Key informant characteristics The respondents in the current study come from a broad representation of U.S. firms in a wide variety of industries. They reported employment in manufacturing, transportation services, electrical power generation, information services, entertainment, biotechnology, construction, and financial services and banking, among other sectors. When compared with the total number of U.S. companies—done by testing against the data from the 2012 U.S. Economic Census (the most recent economic census data available)—this sample contains a larger proportion of firms (χ2 = 65.11(1), p b 0.001) with higher overall annual sales. Similarly, based on the number of employees, a greater proportion of large firms (χ2 = 3320.19(1), p b 0.001) are included in this study. On average, informants reported 14 years of work experience in innovation-related job roles, and the average number of new-product projects in which participants had been involved was 53. To alleviate potential concerns regarding the use of self-reported questionnaires, a series of diagnostic tests was conducted to assess common method bias. First, a Harman (1976) one-factor test was performed; an exploratory factor analysis (EFA) extracted a five-factor unrotated solution with no one factor explaining a majority of the variance. In addition, a forced one-factor solution was only able to explain 37.62% of the variance in the data. Furthermore, Harman's single-factor test was performed using a confirmatory factor analysis (CFA) approach (Malhotra, Kim, & Patil, 2006). On running the singlefactor CFA model, three items failed the measurement criterion (t N ±1.96, p b 0.05), and the resultant fit indices were suggestive of a poor fitting model (χ2 = 1939.65, p b 0.001, df = 209; CFI = 0.704, NFI = 0.680, RMSEA = 0.219, SRMR = 0.175). Third, following the recommendations of Podsakoff, MacKenzie, Lee, and Podsakoff (2003), a measurement model that included a “same-source” factor (i.e., a single common method factor) was examined using a CFA approach. A model comparison was performed between the original measurement model and measurement model with the addition of the unmeasured latent method factor to ascertain the effects, if any, of common method bias. The results indicate a 0.006 change in the comparative fit index (CFI) between the two models, clearly below the 0.01 threshold established by Cheung and Rensvold (2002). These tests suggest that common method bias was not a threat to the validity of the results. 3.3. Measures and psychometrics The study variables were measured using seven-point Likert-type multiple-item scales. Fear of negative evaluation was measured by adapting a four-item scale developed by Rodebaugh et al. (2004), innovation culture was measured with a four-item scale adopted from Dobni (2008), and decision-making comprehensiveness was measured with a four-item measure borrowed from Slotegraaf and AtuaheneGima (2011). Table 1 provides the summary statistics for all study variables.

Please cite this article as: Mohan, M., et al., Managerial disposition and front-end innovation success, Journal of Business Research (2016), http:// dx.doi.org/10.1016/j.jbusres.2016.08.019

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Table 1 Correlations, means, and standard deviations. Construct

Mean

SD

PCOMP

Perceived competence (PCOMP) Fear of negative evaluation (FNE) Innovation culture (ICL) Decision-making comprehensiveness (DMC) Front-end innovation performance (FPS)

5.50 2.56 4.94 5.17 4.87

1.16 1.39 1.19 .90 1.02

.94 −.18⁎ .38⁎⁎ .37⁎⁎ .39⁎⁎

FNE .92 −.06 −.21⁎⁎ −.10

ICL

DMC

FPS

.89 .46⁎⁎ .67⁎⁎

.80 .52⁎⁎

.93

Notes: Numbers on the diagonal are Cronbach's alphas; SD = standard deviation; ** correlation is significant at the 0.01 level (two-tailed); * correlation is significant at the 0.05 level (two-tailed).

The scales for decision-maker's perceived competence and frontend innovation performance were developed based on the established procedures recommended in the extant literature (Churchill, 1979; Gerbing & Anderson, 1988; Mowen & Voss, 2008). The constructs were defined and a pool of potential items was generated. The initial pool was refined based on feedback from experts in the field, which resulted in a five-item scale to measure decision-maker's perceived competence in new-product development decisions, and a five-item measure to capture front-end innovation performance (FPS). Then, the unidimensionality, reliability, and validity of the scales were assessed. An EFA for the perceived competence scale extracted a single factor that explained 84.22% of the total variance; Cronbach's alpha was 0.95. Further, an EFA on the FPS scale produced a one-factor solution explaining 78.6% of the variance; Cronbach's alpha was 0.93. These results support the unidimensionality and reliability of the new scales. The convergent and discriminant validity of the scales were assessed via CFA. Appendix A contains the measurement model including scale items, factor loadings, construct reliabilities, and average variance extracted (AVE). All measures were subjected to a CFA in LISREL 9.1 (Jöreskog & Sörbom, 1996). When sample sizes are relatively small, the chi-square fit statistic may not be a strong indicator of model fit due to sampling error (Bentler, 1990). Accordingly, we rely on fit statistics that are more appropriate including Root Mean Square Error of Approximation (RMSEA) and CFI (Bentler, 1990). A sound measurement model was obtained (χ2 = 409.29, p b 0.001, df = 199; CFI = 0.96; RMSEA = 0.078; SRMR = 0.055), and a number of analyses were performed to determine convergent and discriminant validity. All standardized factor loadings were above 0.62 and statistically significant (p b 0.01). Moreover, construct reliabilities were above 0.80 and the AVE for each construct was above the 0.50 minimum recommended cut-off. As prescribed by Voorhees, Brady, Calantone, and Ramirez (2016), in all cases, evidence of discriminant validity is present, since AVE is larger than the squared multiple correlations between the paired constructs (Fornell & Larcker, 1981). Appendices A and B present the summaries

of this analysis. These results support the unidimensionality, reliability, and validity of all scales. 4. Results 4.1. Model estimation Hypothesis testing was performed by the simultaneous fitting of hierarchically arranged multiple-regression equations in SAS 9.3. A three-stage least squares model was used to test the hypothesized relationships presented in Fig. 1. This approach allows the use of cross-product terms for moderation, while permitting the simultaneous estimation of the regression equations for mediation tests. A main effects model was fit first followed by a second model that included the hypothesized interaction effects; all variables were mean centered. The full model's system weighted R-squared was 0.466 and all parameter estimates were statistically significant and in the expected direction. Table 2 provides the results from the main effects and full model estimation. H1 posited a negative relationship between a manager's fear of negative evaluation and decision-making comprehensiveness. The parameter between these two constructs was negative and statistically significant (β = −0.18, p = 0.006; note: all β reported in the paper are standardized). Thus, H1 is supported. This finding supports the idea that the activation of the fear of negative evaluation suppresses a manager's tendency to engage in an extensive evaluation of ambiguous ideas. Moreover, H2 proposed a positive association between a manager's perceived competence and decision-making comprehensiveness, and the results support it (β = 0.25, p b 0.001). When managers feel competent about the decision at hand, they more deeply consider the issues surrounding the idea. H4 and H5 suggested that front-end innovation performance is positively associated with decision-making comprehensiveness and innovation culture, respectively. Both of these hypotheses are supported (H4: β = 0.34, p b 0.001; H5: β = 0.52, p b 0.001). Further,

Table 2 Three-stage least squares simultaneous estimation results. Main effects model Equation Dependent variable: DMC Intercept FNE PCOMP ICL FNE × ICL PCOMP × ICL Dependent variable: FPS Intercept DMC ICL

Full model with interaction terms

β

Std. Coef.

t-value

p value

β

Std. Coef.

t-value

p value

3.18 −.10 .16 .28

– −.15 .20 .37

8.77 −2.28 2.81 5.19

.001 .024 .006 .001

−.05 −.12 .19 .29 .12 .13

– −.18 .25 .39 .22 .21

84.68 −2.80 3.46 5.49 3.24 3.18

.001 .006 .001 .001 .001 .002

4.87 .38 .44

– .34 .52

88.16 5.56 8.48

.001 .001 .001

.90 .33 .46

– .29 .54

System-weighted MSE = .999 Degrees of freedom = 337 System-weighted R2 = .42

2.69 4.84 8.79

.008 .001 .001

Hypothesis

H1 H2 H3a H3b

H4 H5

System-weighted MSE = .996 Degrees of freedom = 335 System-weighted R2 = .47

Notes: Front-end innovation performance (FPS), decision-making comprehensiveness (DMC), innovation culture (ICL), perceived competence (PCOMP), fear of negative evaluation (FNE); mean squared error (MSE).

Please cite this article as: Mohan, M., et al., Managerial disposition and front-end innovation success, Journal of Business Research (2016), http:// dx.doi.org/10.1016/j.jbusres.2016.08.019

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decision-making comprehensiveness had a statistically significant and positive impact on front-end innovation performance, and innovation culture had a statistically significant and positive direct effect on such performance.

4.2. Examination of moderation and mediation effects H3a stated that the negative effect of the fear of negative evaluation on decision-making comprehensiveness is more pronounced when innovation culture is low, rather than high. Conversely, H3b argued that the link between perceived competence and decision-making comprehensiveness was stronger when innovation culture was high, rather than low. The results of the three-stage model show that the interactions between innovation culture and fear of negative evaluation (β = 0.22, p = 0.001) and innovation culture and perceived competence (β = 0.21, p = 0.002) were significant. Thus, H3a and H3b are partially supported. To further explore the magnitude and direction of the moderation effects, simple slopes analysis was employed (Cohen & Cohen, 1983). Figs. 2 and 3 provide a visual representation of the results. The coordinates for the high and low values for each construct were estimated by using a ± 1 standard deviation from the mean cut-off. Fig. 2 shows the slope analysis for the effect of the fear of negative evaluation on decision-making comprehensiveness at both high and low levels of innovation culture. Specifically, when innovation culture was low (value = 3.75), the relationship between fear of negative evaluation and decision-making comprehensiveness was negative (slope = − 0.40). However, when innovation culture was high (value = 6.13) no relationship between fear of negative evaluation and decision-making comprehensiveness was observed (slope = 0). Fig. 3 shows that when innovation culture was low, no relationship between perceived competence and decision-making comprehensiveness was observed (slope = 0). However, when innovation culture was high, a strong positive relationship between perceived competence and decision-making comprehensiveness was present (slope = 0.49). A further test of the interactions was performed by individually submitting the two moderated relationships to a Preacher and Hayes (Hayes, 2013; Model 1) test, which employs a conditional process modeling technique, and the results confirmed the previous interpretation of the significant interaction effect.

Fig. 3. Positive relationship between perceived competence and decision-making comprehensiveness when innovation culture is high.

Furthermore, to strengthen the validity of the hypothesized model, and also given the indirect mediated relationships in the conceptual model, a number of analyses were performed to test for mediation. Post-hoc mediation tests followed the recommendations of Zhao, Lynch, and Chen (2010). The tests, which used PROCESS (Hayes, 2013; Model 4), provided strong support for the mediated paths in the model (Table 3). The results suggest that the effects of the fear of negative evaluation and perceived competence on front-end innovation performance are mediated by decision-making comprehensiveness. Thus, we conclude that both H3a and H3b are supported. In summary, every hypothesis is supported. 5. Discussion Innovation culture creates a context that enables better firm performance (Hurley & Hult, 1998; Rubera & Kirca, 2012; Tellis et al., 2009). However, the exact workings that explain how innovation culture effects managers' decisions, with respect to front-end innovation decisions, have received less attention. As such, the introduction of manager activation theory—which posits that a firm's culture activates context-specific managerial dispositions—has shed light on this topic. Specifically, innovation culture suppresses managers' fear of negative evaluation and enhances perceived competence. As a result, in firms with a strong innovation culture, managers tend to promote higher levels of decision-making comprehensiveness. That is, these managers tend to allow innovation teams to be more inclusive and exhaustive in their evaluation of new product ideas. In turn, decision-making comprehensiveness is positively related to front-end innovation performance. Therefore, as theorized, the prevalent organizational culture effects which managerial dispositions are activated in the given context. 5.1. Theoretical and managerial contributions

Fig. 2. Negative relationship between fear of negative evaluation and decision-making comprehensiveness when innovation culture is low.

This study explains why and how innovation culture enables frontend innovation performance. The data are consistent with the hypotheses drawn from manager activation theory that innovation culture is an organizational force that inhibits and facilitates managerial dispositions vis-a-vis decision-making in the front end of innovation. This context theory adds to our understanding on how organizational characteristics provide constraints and opportunities for managerial behavior (Bamberger, 2008; Johns, 2006). Specifically, this study illuminates how innovation culture facilitates managerial dispositions, in the

Please cite this article as: Mohan, M., et al., Managerial disposition and front-end innovation success, Journal of Business Research (2016), http:// dx.doi.org/10.1016/j.jbusres.2016.08.019

M. Mohan et al. / Journal of Business Research xxx (2016) xxx–xxx

7

Table 3 Mediation tests. Baron and Kenny path coefficients

95% Bootstrap confidence interval

Mediated relationship

a

b

c′

Lower bound

Upper bound

Zhao et al. (2010) Classification

PCOMP → DMC → FPS FNE → DMC → FPS

.29⁎⁎ −.14⁎⁎

.49⁎⁎ .59⁎⁎

.20⁎⁎ .01

.07 −.15

.23 −.02

Complementary, mediation Indirect-only, mediation

Notes: All estimates were obtained using PROCESS (Model 4) in SPSS 22; front-end innovation performance (FPS), decision-making comprehensiveness (DMC), perceived competence (PCOMP); ** coefficient is significant at the 0.01 level (two-tailed); * coefficient is significant at the 0.05 level (two-tailed).

context of front-end innovation, which is an important contribution because understanding how the organizational context can overcome the psychological limitations of individuals, with respect to adopting new ideas, is a central problem in innovation management (GarcíaGranero et al., 2015; Van de Ven, 1986). Actionable managerial recommendations to improve frontend innovation performance result from the findings set out herein. Specifically, a weak innovation culture increases the probability of making sub-optimal decisions in the front end of innovation, where concepts with merit may be prematurely expunged. To avoid this, top management has to recognize the value of failure. Managers should encourage rather than penalize employees for trial and failure. In addition, innovation managers should be free to select the number and type of new product ideas to pursue. Innovation leaders that have degrees of freedom to engage in the development of ideas in their area of competence produce more qualified ideas in the front end of innovation. Furthermore, innovation culture and front-end innovation performance are directly linked. Hence, managers should continually nurture a strong innovation culture, which means inducing a mindset and related supportive decision-making environment that recognizes the value in failures and, more importantly, the value in endowing managers the freedom to swing for the fences or to swing and miss.

5.2. Limitations and directions for future research Managerial decisions in the front-end stage of innovation were examined in this study. Accordingly, the sample consists of managers involved in decision-making at this particular stage. As such, a larger sample of managers in other innovation stages is needed to generalize the findings across the entire innovation process. Moreover, this study used single-respondent data from highly qualified respondents. Yet, despite their expertise, knowledge, and experience, key informants' responses to constructs, like decision-making comprehensiveness and innovation culture, may not accurately represent the responses of their coworkers. Future research that examines the proposed model using multiple-informant measures is needed to validate the subjective evaluations provided by these respondents. Further, a comprehensive number of control variables were incorporated in earlier estimations of the conceptual model; these included variables like firm size and age, number of new products launched, market, technology, and environmental turbulence. However, a lack of increase in predictive power (i.e., change in R-squared) and the preference for a more parsimonious model eventually aided the decision to omit them from the results presented. Although the measure used for decision-making comprehensives captures a manager's general disposition to engage in an exhaustive and inclusive decision-making exercise, the scale lacks specificity as to the type and number of elements being considered in the decision. Future research could examine how specific elements in the decision-making process, such as the number of ideas being considered, number of ideas screened out, size of the innovation team, and number of departments involved, affect front-end innovation success.

In addition, the issue of how decision-making comprehensiveness affects the speed of the new product development process is still an open question (Cankurtaran et al., 2013). Future research that focuses on how decision-making comprehensiveness and the speed to market affect ultimate new product performance would be greatly valued. Another promising area of future inquiry is exploring how other organizational contexts activate managerial dispositions. Gaining a better understanding of how organizational characteristics constrain or facilitate managers' tendencies and heuristics can increase our understanding of managerial decisionmaking (Bamberger, 2008; Johns, 2006). Further, more context theories are needed to help organizations develop organizational interventions to effectively influence employees' dispositions and behavior. Finally, the reader must be wary of the statistical limitations of this study; therefore, more research on this topic needs to accumulate to arrive at conclusive results.

6. Conclusion By introducing manager activation theory, this article explains the positive association between organizational innovation culture and front-end innovation performance. In an organizational context that fosters trial and failure, front-end innovation managers are less susceptible to the fear of negative evaluation and more confident about their self-competence. Thus, they tend to perform an exhaustive and inclusive consideration of alternatives before making front-end innovation decisions. This extended decision-making process, in turn, is related to front-end innovation performance. Moreover, this theory offers a promising framework to examine how the organizational context can activate context-specific managerial dispositions and influence managerial behavior. Further, invoking the baseball metaphor one last time, firms should promote an organizational culture in which innovation managers feel the liberty to swing freely. Thus, innovation culture should encourage innovator autonomy, praise innovation attempts, and accept failure as part of the process. By doing so, the likelihood of hitting a homerun could significantly increase. After all, nobody hits a home run by just holding the bat.

Acknowledgements The authors are grateful to the associate editor Domingo Ribeiro Soriano and three anonymous reviewers for their constructive comments on this study. The authors also thank Gerard Tellis, Eric Boyd, Gloria Barczak, Alex Zablah, Brian Brown, Kenneth Kahn, Marina Candi, and Suzanne Makarem for their valuable comments on previous versions of this manuscript. This article is based on the first author's dissertation, which received the 2012 Phillips Doctoral Dissertation Fellowship Award while at Oklahoma State University. The financial support from this award was instrumental in the completion of this study and is gratefully acknowledged. As such, this research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

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M. Mohan et al. / Journal of Business Research xxx (2016) xxx–xxx

Appendix A

Table A1 Measurement model. Construct

Standardized Loading

Perceived competence (PCOMP) - Newly developed scale For the following questions, please select your level of expertise, knowledge, or experience. 1. I have many years of experience in innovation. 2. I am very knowledgeable about new product development. 3. I consider innovation an area in which I know what I am doing. 4. I have developed expertise in managing innovation. 5. I have developed expertise in managing product development. Fear of negative evaluation (FNE) - Adapted from Rodebaugh et al. (2004) When I make decisions on new product ideas: 1. I am afraid that others will criticize decisions I have made. 2. I worry a lot about what my supervisors would think of my decision. 3. I worry a lot about what my coworkers would think of my decision. 4. These decisions are open to criticism by others. Innovation culture (ICL) - Adopted from Dobni (2008) In my company: 1. Innovation is an underlying culture and not just a word. 2. Our senior managers are able to effectively cascade the innovation message throughout the organization. 3. Innovation is a core value. 4. We have an innovation vision that is aligned with projects, platforms, or initiatives. Decision-making comprehensiveness (DMC) - Adopted from Slotegraaf and Atuahene-Gima (2011) When I have been the decision-maker of a new-product development team, we: 1. Develop many alternative courses of action. 2. Use multiple criteria for eliminating possible courses of action. 3. Engage in extensive and in-depth analysis of all available strategic options. 4. Thoroughly examine multiple explanations for problems and opportunities. Front-end innovation performance (FPS) - Newly developed scale Please select the appropriate response in the context of your innovation activities, especially its early stages (also referred to as the front-end of innovation). 1. The front-end results of new product projects I have led have been really good. 2. Front-end idea screening is considered a strength here. 3. Front-end concept development processes are considered a strength here. 4. When I think about our new-product development processes, the front-end activities are excellent. 5. In our front-end process, we excel at producing solid product concepts for future development. Model fit: χ2 = 409.29; df = 199; p b 0.01; NFI = 0.93; CFI = 0.96; RMSEA =0.078; SRMR =0.055.

0.86 0.92 0.85 0.88 0.87

0.85 0.95 0.94 0.73

0.76 0.75 0.90 0.89

0.62 0.68 0.75 0.80

0.78 0.84 0.84 0.91 0.85

t-value*

CR

AVE

0.943

0.768

0.928

0.765

0.897

0.688

0.804

0.508

0.927

0.720

14.14 15.66 13.73 14.62 14.22

13.73 16.71 16.47 11.11

11.47 11.21 14.91 14.69

18.29 19.31 10.72 11.56

12.11 13.54 13.48 15.36 16.68

Notes: * All values significant at 0.01 level; CR = composite reliability; AVE = average variance extracted.

Appendix B

Table B1 Discriminant validity tests. Test 1

Test 2

Construct pairs

AVE

SMC

rxy b 1

Perceived competence (PCOMP) Fear of negative evaluation (FNE) Innovation culture (ICL) Front-end innovation performance (FPS) Decision-making comprehensiveness (DMC) Innovation culture (ICL)

0.768 0.765 0.688 0.720 0.508 0.688

0.035

χ2 = 583.08; df = 1; p b 0.001

0.498

χ2 = 181.48; df = 1; p b 0.001

0.289

χ2 = 131.25; df = 1; p b 0.001

Notes: Test 1 is a comparison of average variance extracted (AVE) and squared multiple correlations (SMC); Test 2 is a correlation b1 test; results from a chi-square difference test between the constrained and unconstrained models are reported.

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