organizational innovation capability: a driver for competitive superiority in marketing channels
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Organizational Innovation Capability:A Driver for Competitive Superiority inMarketing ChannelsMatti Tuominen a & Saara Hyvönen ba Department of Marketing , Helsinki School of Economics ,Helsinki, Finlandb Department of Economics & Management , University ofHelsinki , Helsinki, Finlandc Department of Marketing , Helsinki School of Economics , POB1210, Fin-00101, Helsinki, Finland Phone: + 358 9 43138 735 Fax: +358 9 43138 735 E-mail:Published online: 17 Feb 2007.
To cite this article: Matti Tuominen & Saara Hyvönen (2004) Organizational Innovation Capability:A Driver for Competitive Superiority in Marketing Channels, The International Review of Retail,Distribution and Consumer Research, 14:3, 277-293, DOI: 10.1080/09593960410001678417
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Organizational Innovation Capability:A Driver for Competitive Superiorityin Marketing Channels
MATTI TUOMINEN* & SAARA HYVONEN**
*Department of Marketing, Helsinki School of Economics, Helsinki, Finland, **Department of
Economics & Management, University of Helsinki, Helsinki, Finland
ABSTRACT This paper investigates the interplay between innovation and competitive superiorityin the context of channel management by adopting a capabilities view. The relevance for channelmarketing and management scholars is that we developed an environment-strategy-value contin-gency model to address the focal phenomenon. Our empirical results clearly support the key ar-gument that managerial and technological innovations play an essential role in understanding ofhow competitive superiority is achieved in constantly evolving marketing channels. As such, ourcontingency factors involved have a significant intermediate role in each of the research contextsexamined, indicating that the innovation capability has a channel specific profile.
KEY WORDS: Channel dynamism, competitive superiority, innovation capability, marketingchannels
Introduction
Since the seminal contribution provided by Chandler (1962), the mutual relation-ships between a firm’s strategy, structure and competitive conduct havecommanded substantial attention. However, research in this field has overlookedan essential feature in the preceding interplay, i.e. innovation (Sanchez 1995;Krinsky & Jenkins 1997; Durand 1997; Varadarajan & Jayachandran 1999; Schle-gelmilch, Diamantopoulos & Kreutz 2003). Strategy is concerned with creatingand appropriating value and sustained competitive advantage, which, in turn,leads to competitive superiority (Day & Wensley 1988). Two processes are funda-mental to achieve this outcome. The first process especially emphasizes capabilitiesin technological innovations, the other interacts with capabilities in managerialinnovations (Han, Kim & Srivastava 1998). The former involves the creation ofvalue (customer value) by new or modified product or service offerings, while thelatter focuses on appropriating value (firm value) by restricting competitive forcesand on extracting profits in the marketplace (Mizik & Jacobson 2003). Conse-quently, firms that are unable to restrict competitive forces by their managerial
Correspondence Address: Matti Tuominen, Helsinki School of Economics, Department of Marketing,
POB 1210, Fin-00101 Helsinki, Finland. Fax: + 358 9 43138 660; Tel.: + 358 9 43138 735; Email:
Int. Rev. of Retail, Distribution and Consumer Research,Vol. 14, No. 3, 277–293, July 2004
ISSN 0959-3969 Print/1466-4402 Online/04/030277-17 # 2004 Taylor & Francis Ltd
DOI: 10.1080/09593960410001678417
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innovations are also not able to appropriate the value they have created bycapabilities in technological innovations.
Research in marketing and strategic management has extensively explored howfirm resources and capabilities affect business performance by adopting varioustypes of strategic trade-offs that firms realize (e.g. archetypes provided by Miles &Snow 1978). Although, the trade-off between value creation and value appropria-tion capabilities has been acknowledged (March 1991), research to date has notexplicitly explored the value adding effects of innovation capability on firmcompetitive superiority (Mizik & Jacobson 2003). Extant channel managementliterature has devoted only scant attention to strategic issues, while putting mostinterest on inter-firm links in marketing channels, and on such notions like power,commitment and trust (Heide 1994; Johnson 1999). Moreover, there have beeninadequacies in the conceptualization and operationalization of organizationalinnovation and competitive superiority constructs (Durand 1997; Weerawardena2003; Schlegelmilch, Diamantopoulos & Kreutz 2003; Gatignon et al. 2002). Ourstudy addresses these gaps by examining the innovation–performance interplaywithin different channel environment contexts. To this end, we explore the extentof consequences of organizational innovation capability on the level of a firm’scompetitive superiority, and, further, whether the external contingencies involvedaffect this association.
Theoretical Frame of Reference: A Contingency Approach
Innovation is a key managerial process because it is linked to business performance(Sanchez 1995) and to means of survival in the face of competition and environ-mental uncertainty (Gronhaug & Kaufmann 1988). Organizational innovation hasbeen described as the fundamental reconceptualization of business models and thereshaping of existing markets by breaking the rules and changing the nature ofrivalry (Schlegelmilch, Diamantopoulos & Kreutz 2003). Indeed, innovation hasbeen posited as providing a firm with an indirect approach to avoid competitionand thereby achieve a differential advantage over its competitors (Varadarajan &Jayachandran 1999). Innovation is also at the core of dynamic organizationalcapabilities (Teece, Pisano & Shuen 1997; Durand 1997), and, thus, innovators notonly focus on rivals and their own competitive position within the marketing chan-nel, but they also look across substitute channels (Kim & Mauborgne 1999; Rigby& Zook 2002). Nevertheless, after 30 years of research on innovation and businessperformance, fundamental concepts and measures are often ambiguous, and, thus,there is substantial empirical confusion on the effects of different kinds of innova-tion on firm performance and competitive superiority (Gatignon et al. 2002).Moreover, a careful examination of the literature on innovation reveals, implicitly,that marketing channel is simply an antecedent or a phase of a value deliveringprocess (e.g. Durand 1997; Sudharshan & Sanchez 1998; Rigby & Zook 2002) thatcould be labelled channel driven innovation. In this context, we provide an appliedenvironment-strategy-value contingency model derived from the vast literature onthe characteristics of organizational innovations. We argue that this new capabil-ities view, visualized in Figure 1, integrates contextual, structural, processual, andoutcome perspectives into the focal phenomenon under study.
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In our contingency model, relationships between the contextual factors (antece-dents) and the key input constructs are visualized with broken rules, while thelinkages between the input factors (determinants) and output factors (conse-quences) are demonstrated with constant lines. The arrows involved indicate theassumed direction of influence.
If organizational innovation is to be tested as a key determinant in our concep-tual model, a precise redescription of the innovation capability construct isrequired. Review of the extant marketing and organizational innovation literatureprovides such a conceptual foundation. In marketing, the conventional meaningof the term innovation largely refers to ‘a process of turning opportunities intonew ideas and of putting these into widely used practice’ (Tidd, Bessant & Pavitt1997). Hence, the innovation focus in the marketing literature has been predomi-nately technology intensive (Han, Kim & Srivastava 1998), whereas empiricalevidence reinforces the claim that firms pursue both technological and managerialinnovations and both types of innovation lead to competitive superiority (Weera-wardena 2003; Schlegelmilch, Diamantopoulos & Kreutz 2003). Moreover, a largenumber of factors affect the process of innovation, and, thus, there is a clear needfor a better understanding of antecedents and consequences of innovation, as thesame factors can explain both success and failure (Sanchez 1995). This requiresstudying innovation with a broader scope.
Several attempts have been made to enhance firm capabilities to acceleratethe innovation process, for example, by introducing systematic ways of screen-ing ideas (Lynn & Heintz 1992) followed by a stage-gate model ofoverhauling the innovation process (Cooper & Kleinschmidt 1993). A numberof studies have also pointed out that interfunctional co-ordination is a prere-quisite for a successful innovation process (Mukhopadhyay & Gupta 1998).Therefore, we suggest that the notion of organizational innovation capabilityshould be split into two separate aspects or entities: managerial innovation andtechnological innovation. The distinction is one of the most meaningfuldichotomies in the field of innovation research. This can be shown by the factthat technological capabilities have been consistently highlighted in priorresearch as central to the value creation (value to customer) process, andmanagerial capabilities to the value appropriation (value to firm itself) process(Mizik & Jacobson 2003).
Innovation capability
� Managerial innovation� Technological innovation
Competitive superiority
Financial performance� Value adding performance
Marketing channel� B-to-C� B-to-B
Channel dynamism� Turbulent� Stable
�
Figure 1. Contingency model: environment-strategy-value conduct
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Managerial innovation involves new strategies and new organizational forms,which are indirectly related to basic business activities within an organization,whereas technological innovation pertains to product, service and process technol-ogy interrelated with these business activities (Damanpour 1991). The managerialvs technological dichotomy has been shown to relate differently to the same ante-cedents, as well as in its impact on organizational performance and competitivesuperiority (Sanchez 1995). Therefore, we hypothesize that:
H1: The type and level of organizational innovation capability differ betweenhigh and low performers in competitive superiority.
Han, Kim and Srivastava (1998) have endorsed that the rationale behind orga-nizational innovativeness showing a strong, positive influence on businessperformance is ascribed to innovations that serve to accommodate the uncertain-ties a firm faces in its competitive environment. Given the speed with whichinnovations can be copied by rivals, it is reasonable to presume that some innova-tions, either managerial or technological, may be necessary to improve a firm’srelative market posture, and, particularly, to achieve competitive superiority interms of financial and value-adding performance. However, firm performance andcompetitive superiority may depend more on the congruency between innovationsof different types than each type alone (Damanpour 1991). More recently, whenseveral technologies are needed to get access to key resources and capabilities,innovation processes have been carried out in a network employing both suppliers,customers, and other channel partners (Day 2000).
Collaboration and closeness to the channel partners capitalize on the notion ofmarketing channels as vertical value-adding chains that create innovations andcompetitive advantage (Stern, El-Ansary & Coughlan 1996; Sethi, Smith & Park2001). In this respect, the efficiency of internal business processes is useless if thecompany is not taking into account channel partners’ views and customers’ expec-tations (Sudharshan & Sanchez 1998). As Chandler (1962) stated, firms andmarkets coevolve: the activities of firms and their innovations shape markets, asmuch as markets shape firms and their innovations (Teece, Pisano & Shuen 1997).Indeed, innovation demands an outside-in approach so that a wide range of cred-ible, external channel views (suppliers and intermediaries) can be integrated intothe internal process, challenging previous assumptions and filling critical knowl-edge gaps (Tushman & Anderson 1997). Additionally, several other microenvironmental contingencies affect the innovation-competition-value chain inmarketing channels (Schlegelmilch, Diamantopoulos & Kreutz 2003). For firms,innovations usually represent a means to deal with the evolving market structuresand dynamics of the channel environment (Durand 1997), and, in turbulent chan-nel environments, innovators create and appropriate value proactively by meansof new technological solutions (Varadarajan & Jayachandran 1999). Prior researchhas acknowledged that these micro-environmental factors especially affect theextent of the effects of organizational innovations on business performance andcompetitive superiority (Han, Kim & Srivastava 1998; Kim & Mauborgne 1999),even though the propensity of open-market (market driven) innovation variesacross industries and marketing channels adopted (Rigby & Zook 2002).
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In channel management literature, however, these issues are like a ‘black box’,and channel members’ strategic postures have been traditionally consideredthrough a surrogate B-to-C (consumer products) vs B-to-B (business products)taxonomy (Frazier & Antia 1995). Therefore, investigating how the type ofmarketing channel and channel dynamism affect the innovation dichotomy is ofparticular pertinence to our conceptual model. Formally, it is hypothesized that:
H2: Turbulent channel environments and B-to-B channels emphasize technologicalinnovation capability, which, in turn, affects the level of firm competitive superior-ity.H3: Stable channel environments and B-to-B channels emphasize managerial inno-vation capability, which, in turn, affects the level of firm competitive superiority.H4: Turbulent channel environments and B-to-C channels emphasize technologicalinnovation capability, which, in turn, affects the level of firm competitive superior-ity.H5: Stable channel environments and B-to-C channels emphasize managerial inno-vation capability, which, in turn, affects the level of firm competitive superiority.
To recapitulate and summarize the hypothesized relationships outlined in Figure1, managerial and technological innovation capabilities affect the level of thefirm’s competitive superiority in terms of excellent financial and value-addingperformance. Furthermore, both the rate of the dynamism in channel environmentand the type of the marketing channel committed influence the level of competitivesuperiority.
Research Design
In view of relatively limited a priori knowledge about the relationships betweenour key constructs, we are deploying exploratory techniques instead of confirma-tory approaches. As with all empirical investigations at an early stage ofdevelopment, analyses are first explorative in nature and there is then an opportu-nity in future research to broaden the discovery with more rigorous multivariatemethods (Greenley & Foxall 1998).
Based on our theoretical foundations and research setting, we are assessing theextent to which the type and level of organizational innovation capability distin-guish between firms characterized by high and low levels of competitivesuperiority. This requires a combination of analysis of variance and multiple two-group discriminant analysis to test our hypotheses and to generate a body ofempirical evidence for the existence of significant differences in organizationalinnovation capability across the firms examined.
Research Context and Data Collection
Our survey was carried out in early summer 2002 (co-ordinated by Aston BusinessSchool/Aston University, UK). Given that we are bedded in the etic tradition inour study, and to enable meaningful cross-national comparison to be made infuture, we also took into account the issue of equivalence following the instruc-
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tions of Steenkamp and Baumgartner (1998). The sampling frame, however, wassupplied by national research institutes in each country involved (in our case:TOY-Research Ltd, Finland). Following the frame (Dunn and Bradstreet) oursample covered small, medium and large firms representing consumer products,business products, business services, and consumer services. The final question-naire was mailed to 1,400 firms in Finland and in total 327 usable responses wasreceived yielding a response rate of 24%. No significant differences in means werefound between early and late respondents on the scales studied indicating thatnon-response bias is unlikely to be a problem. Similar studies are underway (andat various stages of completion) in other countries, including the UK, Ireland,Australia, New Zealand, Austria, Greece, Hungary, Poland, Slovenia and China,to allow multi-country comparisons to be made and the international robustnessof the scales to be gauged.
Measures
While organizational innovation has been extensively studied in recent years(see e.g. Gatignon et al. 2002), capabilities in creating and appropriating valueby innovations have not been systematically explored. Following extensivereview of the literature to specify the domains of the innovation capability andthe competitive superiority constructs, and in-depth interviews with marketingmanagers in the UK, a number of innovation capability and performance itemswere generated. The item pool was refined through expert opinion of marketingscholars in a number of European countries and following the analysis of thepilot data (in the UK and Austria) the seminal questionnaire was furtherrefined.
Subsequently, the final questionnaire was developed deploying 12 innovationcapability items generated as above, hypothesized as two separate factorsfollowing the two proposed by several scholars (e.g. Damanpour 1991;Gatignon et al. 2002). Besides the above, the questionnaire consisted of 11competitive superiority items—hypothesized as two separate factors based on thecategorization by Day and Wensley (1988)—one set (5 items) for financialperformance, the other set (6 items) for value-adding performance. All itemswere measured on a five-point advantage scale, relative to major rivals. More-over, we deployed two sets of dichotomous variables: one for the channelenvironment dynamism (turbulent vs stable)—based on the scale provided byMiller (1987)—the other for the type of marketing channel (B-to-B vs B-to-C)derived from the identification codes (business products vs consumer products)involved in our survey.
Analysis and Results
Before submitting the data to the main analyses, basic psychometric tests wereemployed to provide evidence of the internal validity and reliability of the keyscales adopted. Evidence of construct validity is present when the patterns ofcorrelations among scales and variables conform to what is predicted by theory(Cronbach 1970).
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Scale Construction and Validation
Our purpose here is to develop and refine scales for assessing organizational inno-vation capability and competitive superiority. These were developed following theparadigm endorsed by Churchill (1979). First, initial purification of the items wasundertaken employing exploratory factor analyses (EFA). In the case of innova-tion capability, two ‘noisy’ items were deleted due to low levels of communalities,and the EFA, using Kaiser criterion for factor extraction and Varimax rotationfor factor interpretation, resulted in two distinct factors accounting for 53.4% ofthe variance in the original items. These two factors were readily interpretable inline with the theory as: managerial innovation capability and technological innova-tion capability. Cronbach alphas were computed for both scales and were 0.87 and0.69, respectively. As these responses are from a new type of exploration deploy-ing new research instruments, the range of coefficients is acceptable (Nunnally1967), and consistent with those reported in leading marketing journals (Greenley& Foxall 1998). An in-depth analysis of the EFA results is reported in Table 1.
In the case of the competitive superiority construct, the EFA resulted in twodiverse factors accounting for 62.3% of the variance in the original 11 items (EFA
Table 1. Exploratory factor analysis (EFA)—innovation capability
Rotated factor loadings
Innovation capability itemsFactor 1
managerialFactor 2
technological
We are more innovative than our rivals in deciding whatmethods to use in achieving our targets and objectives
.91
We are more innovative than our rivals in initiating newprocedures or information systems
.88
We are more innovative than our rivals in developing new waysof accomplishing our targets and objectives
.84
We are more innovative than our rivals in initiating changes inthe job contents and work methods of our staff
.72
We are more innovative than our rivals in product technologyand in developing new and qualitative products
.74
We are more innovative than our rivals in process technologyand in developing new production processes
.66
We are more innovative than our rivals in deploying newtechnological modes in our business
.65
We are more innovative than our rivals in corporealizing andcommercializing new product innovations
.61
We are more innovative than our rivals in exploiting informa-tion technology in our business
.53
We are more innovative than our rivals in deploying effectivelya high standard R&D function
.46
Construct reliability (Cronbach alpha) .87 .69Percent of variance extracted 34 19VAF for by 2 factor solution=53.4%
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results are not analysed here in-depth, but the items of performance advantagesare presented in Table 2). The factors were interpreted analogously with the theo-ry as financial performance and value-adding performance. Alphas were computedfor these scales respectively of 0.80 and 0.88. In this inquiry, however, theseconstructs are deployed unidimensionally to keep the fundamental analysesinvolved within reasonable dimensions. Indeed, our interest is predominantly puton the performance advantages at the expense of positional advantages (marketposture), i.e., value creating and value appropriating initiatives, even though somemeaningful information and findings are probably hidden in this way. Neverthe-less, the alpha for the new scale labelled competitive superiority was 0.88 indicatingan acceptable level of reliability and internal validity (Nunnally 1967; Churchill1979) as reported in Table 2.
Our questionnaire was piloted prior to data collection, and, thus, modifica-tions were made to address the issue of content validity. Moreover, a single-factor test was performed on the data, in order to test discriminant validity(Podsakoff & Organ 1986). The original items involved (21) were factor analysedtogether and the EFA produced 3 factors with eigenvalues greater than unityand accounting 50.4% of the variance in the original items. A very clean solu-tion resulted as the managerial innovation capability, technological innovationcapability, and competitive superiority items loaded onto different factors, andas virtually unique significant factor loadings (.40 or higher). Therefore, theresults indicate discriminant validity among the scales (results are not reportedhere in detail). The oblique nature of our factor model, however, showed thatthese three measurement proxies are intercorrelated as formerly postulated byseveral scholars (e.g. Damanpour 1991; Gatignon et al. 2002). Subsequently,convergent validity of the adopted scales (3) was tested through pairwise correla-tions between the measures: two were significant at p5 0.01 level (.24 and .29),while the correlation between technological innovation capability and competitivesuperiority was significant at p5 0.05 level (.12). Indeed, the results demonstrateevidence of convergence within each scale. Briefly, we find evidence of reliability,discriminant validity, convergent validity, and concurrent validity, all providingsupport for the construct validity and robustness of the scales developed.
Innovation Capability–Performance Superiority Linkages: Evaluation of Hypotheses
To recapitulate, we argued that a strong positive association exists betweenorganizational innovation capability and competitive superiority. A multivariateanalysis of variance (MANOVA) and one-way analysis of variance (ANOVA)were used to investigate the existence of links between the two components ofinnovation capability and the level of competitive superiority. To this end,firms were classified, as discussed previously, into two categories (high vslow). First, MANOVA was employed to examine the equality of covariancematrices (overall association) between the components of innovation capability(MANAGER vs TECHNO). Thereafter, ANOVA was utilized to analysedifferences in dimensional means of MANAGER and TECHNO between thelow and high performing firm groups (SUPER). The results, displayed inTable 3 (see also MANOVA summary) indicate that both dimensions of inno-
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Table 2. Internal validity and reliability of the competitive superiority (SUPER) scale
Item-to-total correlations
Scale No of items Mean Standard deviation Cronbach alpha (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)
SUPERa,b 11 41.84 13.92 0.88 0.59 0.62 0.65 0.46 0.30 0.64 0.61 0.66 0.62 0.64 0.67
Notesafinancial performance: (1) profit level, (2) profit margin, (3) ROI, (4) sales volume, and (5) market share.bvalue-adding performance: (6) customer satisfaction, (7) customer loyalty, (8) employee satisfaction, (9) employee retention, (10) socialresponsibility, and (11) shareholder satisfaction.
Organiza
tionalInnovatio
nCapability
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vation capability are significantly different between the groups of low vs highperforming firms.
The ANOVA analysis was supplemented by examining the dimensionalimpact of innovation capability on group differences in competitive superioritythrough a two-group discriminant analysis. The discriminant loadings, depictedin Table 3, and the group centroids of low- and high-performing firms,displayed in Table 4, provide a summary of the results clearly supporting ourhypothesis 1, i.e. innovation capability has a positive association with competi-tive superiority.
The discriminant model satisfied the independence assumption as theMANAGER and TECHNO scales were constructed by a factor analysis (EFA)with orthogonal rotation, and, thus, there is no multicollinearity between thesescales. Although the model did not meet the assumption of equality of covariancematrices (MANOVA) between the two groups (Box’s M=15.189; F with (3;15003) df=5,0244; p 5 0,002), the discriminant function is robust to this viola-tion as the ratio between larger and smaller groups (155/141=1.099) is less than1.5 (Hair, Anderson & Tatham 1995).
Consistent with the findings of one-way ANOVA, the results of the two-group discriminant analysis confirm that both components of innovationcapability are collectively and significantly distinguishing between the groups oflow- vs high-performing firms. Finally, the directions of the discriminant load-ings are all positive, and the group centroid is negative for low-performingfirms, and positive for high-performing firms. This is consistent with our maineffects hypothesis 1.
Table 4. Statistics of the capability – superiority discriminant function
Group centroids
Scale Low High EigenvalueCanonicalcorrelation
Wilkslambda*
SUPER (competitive superiority) 7 0.31 0.34 0.11 0.31 0.90
Note*Significant at (5 0.001)
Table 3. Results of MANOVA, ANOVA, and multiple discriminant analysis
SUPER means DiscriminantInnovation capability scales Low High F-ratio p-value loadings*
MANAGER (managerial innovation) 3.23 3.76 14.75 0.000 0.69TECHNO (technological innovation) 3.14 3.60 23.71 0.000 0.87
MANOVA summary: there are only two levels and the results of MANOVA are identical tothe results of univariate tests of significance
*Pooled within-groups correlations between discriminating variables and standardizeddiscriminant functions.
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Contingency influence on innovation–performance interplay. As previously discussed,we hypothesized that the effectiveness of the type of innovation capability is depen-dent on the type of the marketing channel involved, and on the rate of the currentdynamism in the channel environment. Simply put, there should be a matchbetween the types of marketing channel, channel dynamics and innovation. Theinfluence of the marketing channel and channel dynamism was examined byemploying a two-group discriminant analysis simultaneously in two diverse contex-tual split-groups: marketing channel (B-to-C vs B-to-B) and channel dynamism(turbulent vs stable). We designed a classical 2 6 2 matrix of the split-group resultswithout violating the rules of a valid discriminant analysis.
The direction and magnitude of the impact of the two innovation capabilitycomponents on overall group differences were assessed by employing a multiplediscriminant analysis within each of those split groups. Derived discriminant load-ings, eigenvalues, canonical correlations, and group centroids for low- and high-performing firms are displayed in Table 5. We developed the MANAGER andTECHNO scales through EFA with orthogonal rotation, and, thus, there is nomulticollinearity between the scales satisfying the independence assumption of adiscriminant analysis. Furthermore, each model also exceeds the threshold (Hair,Anderson & Tatham 1995) regarding the assumption of equality of covariancematrices between the two SUPER groups. The derived discriminant functions arerobust.
Relationships between the components of innovation capability (MANAGERand TECHNO) and competitive superiority (SUPER) were then assessed byemploying a one-way ANOVA procedure. The univariate F-ratios indicate severalsignificant differences between the SUPER groups across the MANAGER andTECHNO components within each split group. These findings are reported inTable 5 and discussed below in a more detailed manner.
When considering simultaneously the discriminant loadings and the ANOVAsummary, a few remarks can be given. In the case of the B-to-C channel, techno-logical innovation capability (TECHNO) differentiates significantly between thehigh and low SUPER groups if the current channel environment is turbulent, whilemanagerial innovation capability (MANAGER) distinguishes between the twogroups if the prevailing channel environment is stable. Surprisingly, in the case ofthe B-to-B channel, managerial innovation capability (MANAGER) is the oneand only discriminator between the two firm groups regardless of the current rateof dynamism in channel environment. Contrary to our argument, technologicalinnovation capability was not significantly distinguishable between the two firmgroups, indicating that, in a B-to-B context, new technological product, process orservice solutions are not directly associated with our performance advantagesmeasures. Briefly, our findings confirm the claim that the type of marketing chan-nel and the rate of the dynamism in channel environment influence the type andlevel of organizational innovation capability, and, further, the interplay betweeninnovation capability and competitive superiority. These relationships have to betaken into account when trying to create organizational innovations, especiallymanagerial ones that are most conducive to performance advantages underprevailing channel conditions. Formally, these results provide strong empiricalevidence for our hypotheses 3, 4 and 5, while hypothesis 2 is rejected.
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Table 5. Results of ANOVA, and split-group effects discriminant analysis
Split-group factors: Marketing channel: B-to-C B-to-BChannel dynamism: Turbulent Stable Turbulent Stable
Discriminant loadings*:MANAGER (managerial innovation) 0.42a 1.00 1.00 1.00TECHNO (technological innovation) 1.00 0.15 0.28 0.44 a
Statistics of the discriminant functions: Low High Low High Low High Low HighGroup centroids (low vs high SUPER) 70.28 0.36 70.27 0.36 7 0.33 0.29 7 0.42 0.34Eigenvalue 0.10 0.10 0.10 0.15Canonical correlation 0.31 0.30 0.30 0.36Wilks lambda 0.90 0.91 0.91 0.87n (low vs high SUPER) 28 22 25 19 43 49 44 55ANOVA summary F-ratio p-value F-ratio p-value F-ratio p-value F-ratio p-valueMANAGER 0.10 0.757 4.22 0.046 8.62 0.004 14.11 0.000TECHNO 5.03 0.030 1.62 0.210 0.40 0.529 3.15 0.079
Notes*Pooled within-groups correlations between discriminating variables and standardized discriminant functions.aThis variable is not included in the discriminant function but exceeds the conservative interpretation (threshold +/70.30) for an acceptablediscriminant loading (Hair, Anderson & Tatham 1995).
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Nevertheless, we went further and looked beyond the summary statistics byexamining the original 11 competitive superiority measures across the stable-turbu-lent and B-to-B vs B-to-C split groups. This analysis suggests that within theinvolved split groups there exist certain characteristics to describe the performanceadvantages’ profile concerned. Accordingly, in the case of turbulent B-to-C, thegroup emphasizes shareholder satisfaction, customer loyalty and employee reten-tion as ends of stakeholder value creation, whereas profit margin is the only keyinitiative in appropriating firm value. Actually, a value creation enthusiasm domi-nates this group. In stable B-to-C group, the performance advantage profile isseemingly different: both customer and employee satisfaction in conjunction withsocial responsibility are the key outcomes in value creation, and, respectively,profit level and ROI in appropriating value to the firm itself. As far as the two B-to-B split-groups are concerned, members of the group in the turbulent channelprefer employee retention and social responsibility as the way to create stake-holder value, while ROI, yet not so pronounced, play a central role in firm valueappropriation. Similarly, members of the stable B-to-B group put the emphasis onshareholder satisfaction in value creation, whereas in appropriating firm value,besides ROI, also profit margin and profit level are the most highlighted initia-tives.
In brief, our micro-level analysis provides more empirical evidence of thecomplexity of competitive superiority in marketing channels. It supports our claimof the relevance of examining jointly the strategic market postures, innovations,and performance advantages.
Classification Results
In our final analysis we used the established discriminant functions to examinehow well the components of innovation capability can predict the group member-ship of low- vs high-performing firms involved. However, due to the limitednumber of cases in each of our split groups, we did not follow the conventionalsplit-sample approach. Instead, the U-method proposed by Lachenbruch (1975)was employed as a technique to validate externally the results of our discriminantanalysis. The technique concerned focuses on assessing unbiased classificationaccuracy within discriminant analysis.
The classification results—reported in Table 6—show that the proportion oforiginal cases correctly classified by our main effects model was 66.9%, and in thecase as an estimator (cross-validated) 66.6%. Respectively, when considering oursplit-group discriminant models, the classification results of the original cases varybetween 58.8–68.3%, and, in the case as an estimator, it classifies correctly newobservations in the range of 58.6–68.1%. Due to the limited space the split-groupclassification results are not reported in detail here.
As far as the proportional change and maximum change criteria are concerned(see Table 6), our main discriminant model exceeds the thresholds computed forthis study. In the case of our split-group discriminant models the computed thresh-olds are also exceeded (proportional change criteria respectively of 50.7%, 50.5%,46.6% and 50.7%, and maximum change criteria in the range of 44.0%, 53.3%,41.3% and 55.6%). Hence, it can be argued that the main and the split-group
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discriminant functions are valid instruments in the sense of the accuracy with whichthey can be used to classify firms with a low and high level of competitive superior-ity in terms of differences in their type and level of innovation capability.
Discussion and Conclusions
This study contributes to our understanding of the interplay between innovationcapability and superior business performance in the context of distributive trades.Our results clearly support the basic argument: innovation capability is a keyprerequisite for success in business performance. In this process, the marketingchannel adopted and the prevailing channel dynamism influence the key processesof value creation and value appropriation.
We provide strong empirical evidence for prior demonstrations (Gronhaug &Kaufmann 1988; Durand 1997; Han, Kim & Srivastava 1998; Schlegelmilch,Diamantopoulos & Kreutz 2003) that innovation capability positively influencesfirm competitive superiority and survival under uncertain conditions in channelenvironment. We also reaffirmed that innovation capability, as a vital requisite forsuperior performance, warrants firm attention for successful implementation ofboth managerial and technological kinds as formerly forwarded by several scho-lars (e.g. Gatignon et al. 2002; Weerawardena 2003). Our results for theinnovation–performance link not only underscore the separate contributions ofmanagerial and technological innovations to firm competitiveness but also lendsupport to synergies between the two types of capabilities enhancing firm superiorperformance (Sanchez 1995). These findings reinforce Damanpour’s (1991) recom-mendation that a firm must take a balanced approach to innovations for optimalresults. Our study also shows that the emphasis a firm places on managerial inno-vation capability relative to a technological one indicates its value appropriationdominance relative to value creation. This is in line with the arguments endorsedby Mizik and Jacobson (2003). Moreover, our results reinforce the claim (Han,Kim & Srivastava 1998; Kim & Mauborgne 1999) that external contingenciesstrongly affect the innovation–performance interplay.
Table 6. Classification results
Predicted group*SUPER (whole sample) Low High Actual total**
Original group Low 102 (65.8%) 53 (34.2%) 155High 45 (31.9%) 96 (68.1%) 141
Cross-validated1 Low 101 (65.2%) 54 (34.8%) 155High 45 (31.9%) 96 (68.1%) 141
Notes1In cross-validation, each case is classified by the function derived from all cases other thanthat case.*66.9% of originally grouped cases correctly classified, and 66.6% of cross-validated groupedcases correctly classified.**Proportional change criterion (155/296)2+ (141/296)2=50.1%, and maximum changecriterion (141/296)=47.6%.
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Empirical evidence has been obtained from a small open economy, where bothmarket and technology uncertainties have been the hallmark within distributivetrades. In this respect, small, medium, and large firms representing either consu-mer products (B-to-C) or business products (B-to-B) were chosen as the unit ofanalysis and vehicle for examining the innovation–performance interplay. Weargued that there is a strong positive association between the key constructs.Moreover, the influence of our contingency factors was examined within two splitgroups simultaneously. The procedure provided a classical 2 6 2 matrix of thesplit-group results revealing that the focal phenomenon is channel specific.Accordingly, in B-to-B context, firms tend to rely on managerial innovationcapability in conjunction with value appropriation regardless of the prevailingcompetition and environmental uncertainties. On the contrary, in B-to-C context,and in turbulent channel conditions, firms rest on technological innovationcapability to sustain their value creation ability, while in stable channel conditionsfirms realize a value appropriation strategy through managerial innovationcapability. The point is of an environment–strategy–value conduct as visualized inFigure 2.
Indeed, our study has contributed to bridging the gap between the researchtraditions in this particular field. Furthermore, it provides a promising metaphorand taxonomy for channel management scholars to address the competitive super-iority of the firm through value creation and value appropriation processes inorganizational innovation.
We crystallize the implication recipe for management as follows: ‘To surviveand remain vital in turbulent channel environment, companies—committed, espe-cially, to B-to-C channel—need to focus on consumers and on creating value
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Figure 2. Effective means of organizational innovation capability in competitive superiority
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through technological capabilities, i.e. corporealising and commercialising product,service, or process innovations.’ Following Kim and Mauborgne (1999), these arereal managerial challenges within our rapidly evolving information era. Therefore,future research should facilitate this endeavour by delving into the management’s‘black box’ and by discovering the role of the marketing channel and channelstrategy as the key drivers for a superior organizational innovation, and, further,for competitive superiority in distributive trade. However, as Rigby and Zook(2002) stated: opening your borders is not necessarily easy; some firms that deploythe tools of open-market innovation without a strategy and a system can wind upgetting burned.
As a consequence of this study, we note some limitations, which in turn offeropportunities for additional work. First, the results are based on a sample drawnfrom one nation, and, thus, our multi-country comparisons in the near future areneeded to ensure the generalizability of the associations examined. Second, themultivariate methods adopted do not allow, on one hand, the determination ofcausality, and, on the other, the assessments of lagged effects of causes on conse-quences. Therefore, more rigorous techniques (confirmatory analyses inconjunction with structural equation models) are needed to verify our conceptualmodel developed and causal links identified. Last but not least, the data utilized inthis study may be biased in terms of managerial attitudes measured by Likert-typescales reflecting a single informant’s perceptions rather than actual organizationalbehaviour, which can reduce the reliability and validity of the data.
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