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Research in International Business and Finance 23 (2009) 181–192

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Research in International Businessand Finance

journal homepage: www.elsevier.com/locate/r ibaf

A cultural perspective on innovation ininternational manufacturing

Alessandra Vecchi ∗, Louis BrennanTrinity College, School of Business, Dublin 2, Ireland

a r t i c l e i n f o

Article history:Received 31 January 2007Received in revised form 19 January 2008Accepted 10 March 2008Available online 25 April 2008

JEL classification:L60 (general manufacturing)O57 (comparative studies of countries)

Keywords:InnovationCultureGlobal manufacturingIMSS survey

a b s t r a c t

This paper presents the results of a survey administered across24 countries that examines innovation in manufacturing firms byadopting Hofstede’s national cultural framework. The purpose ofthis study is to test the validity of the “culture-specific” argumentas an explanatory construct for innovation performance in inter-national manufacturing. Data was collected in 2006 as part of theInternational Manufacturing Strategy Survey IV (IMSS) by relying ona questionnaire addressed to firms classified by ISIC codes (rev.3.1)Divisions 28–35. From the findings it emerges that the “culture-specific argument” is a useful explanatory construct for innovationperformance.

© 2008 Elsevier B.V. All rights reserved.

1. Introduction

A significant strand of the literature seeks to assess the diversity of performance across countries.In the field of comparative management research, there have been three main approaches. The empir-ical work has been aimed towards testing the “culture-free” hypothesis (Child and Kieser, 1979), the“convergence” hypothesis (Form, 1979) and the “culture-specific” hypothesis (Hofstede, 1980). Thelatter two are of most interest to the authors of this paper in an international comparison of innova-tion performance across manufacturing firms. The “convergence” hypothesis (Form, 1979) asserts thatlearning will lead managers from different cultures to adopt the same efficient management practices.Competitive pressures will eliminate those who resist convergence; consequently with the increased

∗ Corresponding author. Tel.: +353 1 8963202; fax: +353 1 8963939.E-mail address: vecchia@tcd.ie (A. Vecchi).

0275-5319/$ – see front matter © 2008 Elsevier B.V. All rights reserved.doi:10.1016/j.ribaf.2008.03.008

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dissemination about best practices around the world, one would expect each country’s respondent toembrace the same approach of their overseas counterparts. The “culture-specific” argument (Hofstede,1980) contends that even if managers located in different societies face similar imperatives for change;deep-embedded cultural factors will still affect the way managers approach innovation and react tothe need for change.

Both these hypothesis find equivocal support in empirical studies of innovation. To fill this gap,the purpose of this study is to test the validity of the “culture-specific” argument as an explanatoryconstruct for innovation performance.

2. Cultural studies of innovation: an overview

The “convergence” hypothesis is supported by several empirical studies. Historically, the “technol-ogy gap” theory (Gershenkron, 1962; Fagerberg, 1994) first stipulated that the potential for knowledgeimitation was positively linked to the development gap (often measured in terms of GDP per capita)between countries. According to this theory, a less developed a firm or a country, the smaller is itsknowledge stock and therefore the bigger its potential to increase through learning from the leadingcountries. However, the theory failed to explain the huge amount of knowledge exchanges among sim-ilar countries such as those based in the Triads (USA, Europe and Japan). Other empirical studies laterargued that the intensity of knowledge flows among developed countries could be explained by theirtechnological proximity. In this sense, countries sharing the same industrial structure benefit fromfaster and larger knowledge flows among them, since they are able to master the same scientific andtechnological knowledge (Smith, 1995). Orlando (2000), for instance investigates the importance oftechnological proximity for R&D spillovers and his findings indicate that although technological prox-imity is positively correlated with innovation performance, knowledge spillovers are not necessarilygeographically bound.

On the other hand, there is a critical mass of empirical research that supports the “culture-specific”argument according to which culture has profound influence on the innovative capacity of a soci-ety. Barnett (1953) postulates a positive correlation between the individualism of a society and itsinnovative potential: the greater the freedom of the individual to explore and express opinions, thegreater the likelihood of new ideas coming into being. Hofstede (1980) indicated that societies whichscore high on individualism and low on power distance tend to display higher growth and innovationrates. Similarly, Shane using Hofstede’s definition of culture (Shane, 1993) shows that specific culturaldimensions provide crucial support for innovation performance: in particular he finds that individual-istic societies which accept uncertainty and which exhibit a low level of power distance are those whoattain better innovation performance. Hussler (2004) by looking at European patent citations showshow culture – if compared to other drivers such as geographical proximity, technological proximity andeconomic proximity – strongly affects the geography of knowledge flows and innovation performance.Hussler in particular introduces a culture-based taxonomy of innovation performance, according towhich societies which accept uncertainty and which exhibit a low level of power distance are thosewho attain better innovation performance. These societies are those that succeed by innovating ontheir own as they possess a “culture of endogenous innovation”. Vice versa, those countries with highuncertainty avoidance and high power distance can be defined as “cultures of imitation”. Finally, Hus-sler defines those societies displaying high uncertainty avoidance regardless of their level of powerdistance as possessing a “less innovative culture”.

Overall, the importance of innovation to firms, nations and regions is reflected in the myriad ofpolicies and strategies which strive to nurture it and reap its benefits. Competitiveness is related totechnological change and the capacity to innovate and to adopt new innovations (Best, 2001; CEC,2000; Deardoff, 1984; Fites et al., 1999; NESC, 1993; O’Donnell, 1992; Solow, 1957). Innovation itselfmay be defined as the process of making changes, introducing or adopting new ideas, methods orbehaviours, etc. (Damanpour and Gopalakrishnan, 1998; Hornby, 1995) and may include a product’sor service’s design, production, marketing and support (Porter and Van der Linde, 1995). The literaturedistinguishes innovation types and sources in various ways. For example: 1-internal versus external(where external innovations are adopted and assimilated) sources of innovation; 2-inputs (such asR&D and management processes) versus outputs (such as commercial exploitation, new products

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and patents); 3-process versus product innovations; 4-technical (technologies which may be productor process related) versus administrative/organisational; 5-radical versus incremental (Chiesa et al.,1996; Damanpour, 1991; Hagedoorn and Cloodt, 2003; McDermott and O’Connor, 2002; Neely et al.,2001).

The literature has identified a number of resources that are critical for innovation. For exam-ple, Hii and Neely (2000) conclude that a broad range of factors, including culture, technologicalresources and competence influence innovation. There is a comparatively small body of research thathas examined innovation across cultures. This research stream has focussed primarily on the diffusionrate across borders (Ghoshal and Barlett, 1988) or differences in innovative activities (Carlsson andHansen, 1982). In terms of innovation performance, complementarity and fit between strategies areimportant drivers for sustained innovation and performance, as in the case of internal and externalinnovation strategies (Cassiman and Veugelers, 2002) and of manufacturing and business/marketingstrategies (Milling and Hasenpusch, 2000). Formalization of manufacturing strategies and standard-ization of work processes in manufacturing also positively influence firm performance (Barney, 1995;Damanpour, 1991; Demeter, 2000). Collaboration and networking have also been identified as keyelements in fostering innovation (Kiston and Michie, 1998; Roper, 2000). Customer and supplier rela-tionships (Oliver et al., 2002) and use of external collaboration for design (co-design) (Zotteri etal., 2000) have a considerable impact on innovation performance improvement and the wider thespectrum of integration the stronger the association with improvement (Frohlich and Westbrook,2001). Other indicators of innovation performance of manufacturing firms include R&D intensity(Tsai, 2001), investment in IT and engineering equipment, such as the use of ERP (Kostopoulus etal., 2002), the ability to exploit existing technological and customer competencies and to developnew ones (Danneels, 2002), implementation of Total Quality Management (Kaynak, 2003), investmentin human and knowledge capabilities (Kostopoulus et al., 2002), proportion of specialists employed(Damanpour, 1991) and size—sales and number of employees (Tsai, 2001). Miller (1988) developeda taxonomy of technological settings and found that different configurations of technology did notresult in different profitability and suggests that strategic position was more important. A proactivestrategic posture leads to a flexible organizational structure and a more innovative firm (Ozsomer etal., 1997).

Since both the “convergence” and “culture-specific” hypotheses find equivocal support in empir-ical studies of innovation, the purpose of this study is to test the validity of the “culture-specific”argument as an explanatory construct for explaining innovation performance. This paper specificallyexamines similarities and differences by comparing innovation performance across Hofstede’s fourcultural dimensions in 24 countries. To this end, we assess innovation performance by looking at inno-vation inputs (e.g. technology adoption, R&D investment and management processes) and processinnovations (e.g. product development procedures) of both technical and administrative nature in thecontext of global manufacturing.

3. Research design and methodology

We take a broad definition of innovativeness as a firm’s tendency to engage in or adopt new ideasmethods or behaviours that may result in new products, services, or technological processes (Lumpkinand Dess, 1996).

In particular we endorse the idea that innovation is likely to be affected by national cultures(Hofstede, 1980; Shane, 1993; Hussler, 2004). In this sense we argue that existing research on inno-vation that had an international focus has primarily focussed on different corporate and professionalcultures (Ulijn et al., 2001; Pivoda, 2001), as well as organisational culture (Feldman, 1988) while gen-erally overlooking the importance of national culture as a means to explain and predict innovationperformance in a global context (Herbig and Dunphy, 1998). Although it appears that no real sub-stantial effort has been made to study whether innovation is, or should be, managed differently indifferent national cultures (Hofstede, 1980; Shane, 1993; Hussler, 2004) we argue that national cul-ture is equally a relevant lens through which the systematic comparison of similarities and differenceswould considerably improve our understanding of innovation performance in a global manufacturingcontext.

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To this end, Hofstede’s four dimensions of national cultures (1980, 2001) seem particularly rele-vant to address this issue. First, although Hofstede’s cultural dimensions are far from being perfect(Sondergaard, 1994; Au, 2000; Pizman et al., 1997; Fernandez et al., 1997) the construct validity ofnational culture has been reconfirmed by an impressive number of successful replications (for anoverview see Pagell et al., 2005). Second, Hofstede’s work is widely used as a theoretical frameworkfor guiding cross-cultural comparisons (Flynn and Saladin, 2006).

The universality of theories and management practices across countries has been long questionedby researchers. The existence of systematic differences between nations has been well establishedand there are a number of studies that show that national cultures affect managerial behaviour. Inparticular Hofstede (1980, 2001) identifies four relevant dimensions of national cultures:

(a) Power distance is the extent to which less powerful members of organisations expect that power isdistributed equally (Hofstede, 1980). In low power distance countries there is limited dependenceof subordinates on their bosses. Hierarchy is established for convenience among equal employeesand a consultative style often takes place. Power is very decentralised as well as decision-making. Incontrast, in high power distance countries, the hierarchy is the fundamental principle on which allrelationships are based. Power is centralised as well as decision-making, leading to more emphasison formal methods for gathering and analysing external information (Flynn and Saladin, 2006).

(b) Individualism describes the degree to which people are oriented toward acting as individualsas opposed as a group (collectivism) (Hofstede, 1980). In individualist countries people tend toact according to their own interest. These countries value individual success and achievement.Members of individualist countries are autonomous and confident, tending to rely primarily ontheir own ideas (Snell and Hui, 2000). In contrast, in collectivist countries people are bound ingroups such as the extended family, the tribe or the village. Members of collectivist countries aremore likely to rely on information provided by others in formulating their opinions (Snell and Hui,2000).

(c) Masculinity describes the extent to which aggressiveness and success are valued, as opposed tothe concern for relationships (femininity) (Hofstede, 1980). In high masculinity countries highearnings, advancement through opportunities and challenging work are mostly emphasised. Com-petition is the main driver. The use of information to support decision-making is dependent on itsexpected effectiveness in gaining advantage over competitors (Flynn and Saladin, 2006). In con-trast, in high femininity countries, relationships, concern for the others, inclusiveness and society’sbest interest are valued. Cooperation often is a visible feature. The use of information to supportdecision-making is very typical of a feminine national culture (Wacker and Sprague, 1998).

(d) Uncertainty avoidance is the degree to which people feel confident about the future (Hofstede,2001). National cultures that score high in uncertainty avoidance have an emotional need forrules. Vice versa, national cultures that score low in uncertainty avoidance dislike formal rules,setting them only when it is necessary (Flynn and Saladin, 2006).

Since we endorse the argument that these different dimensions of national cultures are likely to bearimportant implications for the broader issue of innovation in a global context, we therefore examinethe following three questions:

(1) Could the “culture-specific” argument be used as an explanatory construct for explaining innova-tion performance?

(2) Is there a variety in innovation performance across national cultures?(3) What are the managerial implications?

4. Data collection

Primary data from the IV iteration of the International Manufacturing Strategy Survey 2006 (IMSS)are employed in this paper. The IMSS addresses firm strategy, competitive priorities, capabilities, oper-ations and performance. To date four surveys have been administered (1992, 1996, 2001 and 2003).The survey covers firms in the ISIC codes (rev.3.1) Divisions 28–35: 28, manufacture of fabricated

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metal products, except machinery and equipment; 29, machinery and equipment, not elsewhere clas-sified; 30, office, accounting and computing machinery; 31, electrical equipment and apparatus; 32,radio, television and communication equipment and apparatus; 33, medical, precision and opticalinstruments; 34, motor vehicles, trailers and semi-trailers; 35, other transport equipment.

The survey was conducted using a self-administered questionnaire completed by the director/headof operations/manufacturing and the unit of analysis is the plant/business unit with sampling biasedtowards best practice and best performing firms. Data from each country were gathered by localinstitutions participating in the IMSS network which, in some cases, translated and/or assistedrespondents in completing the questionnaire. Data from 24 countries are employed comprising 711respondents.

Previous work on this data by the authors has included analyses of innovation and performanceparticularly of Irish-based manufacturing (Crowe et al., 2007; Crowe and Brennan, 2007; Brennan etal., 2002, 2003) as well as work on quality practices, priorities and performance between indigenousand foreign firms (Vecchi and Brennan, 2006; Brennan et al., 2005). This paper specifically examinesinnovation performance across the 24 IMSS countries, classified according to Hofstede’s four culturaldimensions. In order to benchmark innovation performance on a global scale, a complete list of theIMSS countries as well as their classification between ‘low’ and ‘high’ according the four types of scores(power distance, individualism, masculinity, uncertainty avoidance) is provided in Tables 1 and 2 inthe appendix.

5. Data analysis

In the questionnaire, eight indicators of innovation in manufacturing firms are examined separatelyand compiled into an innovation index assessing the overall innovation performance. The innova-tion indicators are: use of technology for operations; use of Enterprise Resource Planning (ERP); R&Dinvestment (% unit’s revenues); process equipment (% unit’s revenues); training (% unit’s revenues);manufacturing overheads (% manufacturing costs on salaries within design, planning and mainte-nance, and on indirect personnel in production but excluding costs such as administration and sales);co-ordination of design and manufacturing; and management of product development cycle.

Table 3 (see appendix) illustrates the indicators of innovation performance according to the lit-erature as well as their respective IMSS variables. After the removal of outliers, the figures for R&Dinvestment (% unit’s revenues), process equipment (% unit’s revenues), training (% unit’s revenues) andmanufacturing overheads (% manufacturing costs) were employed directly.

Under manufacturing practices we look at individual technologies employed in operations and useof ERP in different functions. Here we include these as indicators of innovation where their overalluses are measured in two composite variables. Use of the technologies for operational activities wasevaluated using a multi-item question comprising of 13 items.1 The extent of use (1–5) for each tech-nology was summed to give a composite variable for technology use (maximum = 50). The inter-itemconsistency was high (Cronbach’s alpha = 0.7728). The extent of the use (1–5) of software, namely,Enterprise Resource Planning (ERP) to support various management areas2 also had a high inter-itemconsistency (Cronbach’s alpha = 0.8798). These items were summed to create a composite ERP variable(maximum = 45).

Factor analysis was conducted on the variables relating to product development. Co-ordination ofdesign and manufacturing was assessed using three variables based on 5-point scale (use of rules andstandards; use of cross-functional teams; and use of job rotation between design and manufacturing).These three variables loaded onto one factor. Likewise, management of the product development cyclewas assessed using three 5-point scale variables which loaded onto one factor (early involvement of

1 e.g. Stand-alone/NC machines, machining centres, CNC-DNC, automated tool change, robots, AGVs, automatedstorage-retrieval systems, flexible manufacturing/assembly systems/cells, computer-aided inspection/testing/tracking, CAD,LAN–WAN/Intranet/shared databases/Internet.

2 Material management, production planning and control, sales and distribution, accounting and finance, human resourcemanagement, project management.

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the manufacturing function; use of concurrent engineering; and use of tests and prototypes). Thesetwo factor scores were saved as variables and used as indicators of innovation.

A measure of innovation in the form of an index was generated based on the eight indicators ofinnovation identified in Table 3 and described above. The actual figures for R&D, process equipment,training and manufacturing overheads were used as well as the composite variables for technologyand ERP, and the two factor scores for product development. If a response was in the top quartilefor any indicator an index score of 1.0 was awarded and a score of 0.5 for a position in the secondquartile. A response below the median was awarded no score on the index. A maximum score of eight ispossible.

6. Main findings

Table 4 provides the main indicators of innovation and the scores for the innovation index accordingto the different dimensions of culture. Panel A illustrates the indicators and the scores for nationalcultures characterised by different levels of power distance. The findings indicate that power distanceper se has a positive impact on innovation with high power distance countries employing technologyfor operational activities as well as ERP more extensively than those firms located in low power distancecountries. Furthermore, firms based in high power distance countries tend to spend more resources onR&D, process equipment as well as training and education (expressed as the average% of total sales).The findings suggest that firms based in high power distance countries spend considerably more oninnovation inputs; process innovations and they also display a higher score for coordination of designand manufacturing.

Panel B provides the main findings in relation to individualism. The findings indicate that low levelsof individualism are generally associated with higher levels of innovation inputs—not only do firmsbased in collectivistic countries display a more intensive use of technology for operational activity andERP, they also invest more resources into R&D, process equipment and training and education. Con-versely, firms based in individualistic countries spend more on manufacturing overheads, as averagepercentage of manufacturing costs. As for process innovations, firms based in collectivistic countriesdisplay a higher score of co-ordination between design and manufacturing as well as a higher overallinnovation performance (i.e. a higher innovation index) than those based in individualist countries.

Panel C provides the main findings in relation to masculinity. From the findings it emerges thatmasculinity per se only marginally affects innovation performance. As for innovation inputs, firmsbased in feminine countries employ ERP more extensively. There are not any significant differencesin terms of process innovation, however feminine countries also display a higher overall innovationindex when compared with firms based in masculine countries.

Panel D provides the main findings in relation to uncertainty avoidance. The findings suggestthat uncertainty avoidance mainly affects innovation inputs with firms based in low uncertaintyavoidance countries spending more on process equipment and training and education. There areno significant differences neither in terms on process innovations or as for the overall innovationperformance.

7. Conclusions and directions for further research

7.1. Could the “culture-specific” argument be used as an explanatory construct for explaininginnovation performance?

The findings prove the validity of the “culture-specific” argument as an exploratory construct forinnovation in two ways. By adopting Hofstede’s model of national cultures several significant statisticaldifferences tend to emerge: first, all the four dimensions of culture affect innovation inputs; second,both process innovations as well as the overall innovation performance measured by the innovationindex are affected by three cultural dimensions out of four (power distance, individualism and mas-culinity). In this context, uncertainty avoidance does not seem to play any major role in determininginnovation performance.

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7.2. Is there a variety in innovation performance across national cultures?

Although the findings prove the general validity of the “culture-specific” argument as an explana-tory construct for innovation performance (Hofstede, 1984; Shane, 1993; Hussler, 2004), our findingsalso present several major discrepancies with the literature. Some of these unexpected findings beara little discussion.

As for power distance, our findings contradict Hofstede’s (1984) as well as Shane’s (1993) findingsindicating that low power distance cultures tend to display better innovation performance. Similarlyour findings seem to defy Hussler’s argument (2004) (according to which the heavy hierarchical struc-ture of high power distance countries might reduce creative thinking by imposing a “top-down” rigidcontrol) by showing that the very same cultural dimension might also foster a creative environmentwhere innovative solutions need to be adopted “bottom-up” (i.e. through innovation inputs and pro-cess innovations) perhaps to overcome the obstacles that a rigid bureaucratic structure inevitablyentails. As a matter of fact, firms based in high power distance countries display a statistically signifi-cant higher innovation index than those firms based in low power distance countries. Our discrepantfindings also raise an interesting question—if we adopt Hussler’s taxonomy for instance, might thehigher innovation performance of high power distance countries be attributed to their so-called “cul-ture of imitation”? Given that globalisation increasingly enables transfer of knowledge and criticalinformation by inevitably leading to unintended leakages and spillovers (e.g. counterfeiting), a deeperunderstanding of the cultural variables underpinning “culture of imitation” would be desirable to shedsome light on the global nature of innovation.

As for individualism, our findings contradict Barnett’s (1953) findings according to which the greaterthe freedom of the individual to explore and express opinion, the greater the likelihood of new ideascoming into being. Conversely our findings tend to support Herbig and Miller’s (1991) argumentaccording to which collectivistic countries tend to perform better in process innovations while col-lectivism might inhibit more radical product innovation. Similarly while Hegarty and Hoffman (1990)show how process innovations differ among national cultures, national cultures are differently inclinedtoward distinctive strategic management activities. As a matter of fact, our findings clearly indicatethat firms based in collectivistic countries spend significantly more on innovation inputs, performbetter in process innovations and display a statistically significant higher innovation index than thosebased in individualist countries.

As for masculinity, the more extensive use of innovation inputs and in particular the more extensiveuse of ERP by feminine countries confirms Hofstede’s argument (1980, 2001), according to whichfeminine countries tend to rely on more rigorous systems and more formal planning activities as ameans for running their organisation. In line with previous studies (Hussler, 2004), our findings showthat firms based in feminine countries also display a higher innovation performance if compared withfirms based in masculine countries.

As for uncertainty avoidance, whereas previous studies indicated that national cultures charac-terised by low uncertainty avoidance display better innovation performance (Hofstede, 1980, 2001;Shane, 1993), our findings suggest that it only affects innovation inputs. In particular, our findingsindicate that high-risk tolerance countries tend to invest more on process equipment as well as intraining and education.

7.3. What are the managerial implications?

The growth of global markets has renewed interest in innovation as a means to improve the compet-itive positions of many global manufacturing firms. By confirming the validity of the “culture-specific”argument as an explanatory construct for innovation performance our findings raise some considera-tions about two main issues: the current validity of Hostede’s four cultural dimensions as well as thechanging nature of innovation.

As for the current validity of Hofstede’s cultural dimensions, all the criticisms addressed to theconstruct of national culture as a suitable variable for differentiation, apply to all four dimensions aswell. Today in many IMSS countries such us Canada, Israel and Belgium different ethnic or nationalcultures co-exist (Au, 2000). This process is likely to be further exacerbated as the result of increased

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people mobility that inevitably globalisation entails. In particular, within the same country differentsub-cultures might persist, but they might also still stand apart for religious reasons (e.g. Ireland),because of their language (e.g. Belgium) or their ethnicity (US, France, Turkey). In this sense, the fourdimensions of national cultures could be far from being reliable proxies for cultural homogeneity fora given national culture.

Furthermore, one can reasonably believe that different corporate, organisational, industrial and/orsectoral cultures may co-exist within the same firm and might as well conflict and counterbalancethe national one. Specifically regarding Hofstede’s results, it is worth pointing out that although theauthor proves the reliability of his findings, they are clearly empirically biased since they are based onthe analysis of only one US firm (i.e. IBM).

Conversely, if we assume the validity of Hofstede’s four cultural dimensions our findings illustratethe ever fast changing nature of innovation—whereas previous studies emphasised the innovativenessof national cultures characterised by low power distance, our findings show that the very same culturaldimension might also foster a creative environment where innovative solutions are adopted “bottom-up” (i.e. through innovation inputs and process innovations) perhaps to overcome the obstacles that arigid bureaucratic structure inevitably entails. In a similar way, where previous studies also showed thatindividualism fosters innovation performance, our findings support the argument according to whichcollectivistic countries tend to perform better in process innovations. This trend is particularly visibleif we consider the emblematic experience of many successful industrial clusters whose innovationperformance strongly relies on a pool of resources and capabilities that clustered firms deploy througha collective effort. As for uncertainty avoidance, our findings indicate that it does not play any majorrole in determining innovation performance, although it affects innovation inputs.

Finally our findings illustrate the relevance of national cultures to process innovation within thecontext of global manufacturing. By adopting Hofstede’s model of national cultures it emerges thatall the four dimensions of culture affect innovation inputs; and both process innovations as well asthe overall innovation performance measured by the innovation index are affected by three culturaldimensions out of four (power distance, individualism and masculinity). In this sense, the paper laysthe ground for another interesting question of whether and how the same cultural dimensions mightrather differently affect product innovation.

Appendix A. Appendix

See Tables 1–4.

Table 1Hofstede’s measures of national culture

IMSS IV country Power Individualism Masculinity Uncertainty

Argentina 46 46 56 86Australia 39 90 61 51Belgium 65 75 54 94Brazil 69 38 49 76Canada 39 80 52 48China 80 20 66 30Denmark 18 74 16 23Estonia 40 60 30 60Germany 35 67 66 65Greece 60 35 57 112Hungary 46 80 88 82Ireland 28 70 68 35Israel 13 54 47 81Italy 50 76 70 75New Zealand 22 79 58 49The Netherlands 38 80 14 53Norway 31 69 8 50Portugal 63 27 31 104

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Table 1 (Continued )

IMSS IV country Power Individualism Masculinity Uncertainty

Spain 57 51 42 86Sweden 31 71 5 29Turkey 66 37 45 85UK 35 89 66 35US 40 91 62 46Venezuela 81 12 73 76

Source: Hofstede’s cultural dimensions, 2006.

Table 2IMSS countries classification

IMSS IV country Power Individualism Masculinity Uncertainty

Argentina L L H HAustralia L H H HBelgium H H H HBrazil H L L HCanada L H H LChina H L H LDenmark L H L LEstonia L H L HGermany L H H HGreece H L H HHungary L H H HIreland L H H LIsrael L H L HItaly L H H HNew Zealand L H H LThe Netherlands L H L HNorway L H L LPortugal H L L HSpain H H L HSweden L H L LTurkey H L L HUK L H H LUS L H H LVenezuela H L H H

L, low = index score ≤50; H, high = index score >50.

Table 3Indicators of innovation performance in the literature and in the IMSS survey data

Indicators of innovation IMSS variables

IT, engineering equipment (Kostopoulus et al., 2002) Use of technology for operationalactivities

Technological competencies (Danneels, 2002) Use of ERPAdopting external technology, ERP (Cassiman and

Veugelers, 2002, Waarts et al., 2002)R&D investment (% unit revenues past3 years)

R&D investment (Tsai, 2001) Process equipment investment (% unitrevenues past 3 years)

Internal/external funds (Kostopoulus et al., 2002) Training and education (% unitrevenues past 3 years)

Knowledge/human (Kostopoulus et al., 2002) Manufacturing overheadsProportion of specialists and professionals employed

(Damanpour, 1991)Co-ordination of design andmanufacturing (e.g. cross-functionalteams)

Manufacturing and human resource practices (Floridaand Davison, 2001)

Management of product developmentcycle (e.g. concurrent engineering)

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Table 4Indicators of innovation and innovation index—breakdown by countries characterised by national cultures with a different levelof power distance, individualism, masculinity and uncertainty

Low (n = 537) High (n = 174) Total Significance(kw)

Panel A: Indicators of innovation and innovation index—breakdown by countries characterisedby national cultures with a different level of power distance (n = 711)

Indicators of innovationUse of technology for operational activities (maximum50) 23 27 24 ***Use of ERP (maximum 45) 27 30 28 ***R&D investment (% total sales) 7 11 8 ***Process equipment (% total sales) 2 4 3 **Training and education (% total sales) 2 4 3 **Manufacturing overheads (% manufacturing costs) 21 20 21Co-ordination of design and manufacturing (factor score) −0.06 0.18 0.00 ***Management of product development cycle (factor score) −0.03 0.10 0.00

Innovation index 2.5 3.0 2.7 ***

Panel B: Indicators of innovation and innovation index—breakdown by countries characterisedby national cultures with a different level of individualism (n = 711)

Indicators of innovation Low (n = 187) High (n = 525) Total Significance(kw)

Use of technology for operational activities (maximum 50) 26 23 24 ***Use of ERP (maximum 45) 30 27 28 *R&D investment (% total sales) 11 7 8 ***Process equipment (% total sales) 4 2 3 *Training and education (% total sales) 4 2 3 *Manufacturing overheads (% manufacturing costs) 19 22 21 **Co-ordination of design and manufacturing (factor score) 0.18 −0.06 0.00 ***Management of product development cycle (factor score) 0.07 −0.02 0.00

Innovation index 3.0 2.5 2.7 ***

Panel C: Indicators of innovation and innovation index—breakdown by countries characterisedby national cultures with a different level of masculinity (n = 711)

Indicators of innovation Low (n = 300) High (n = 411) Total Significance(kw)

Use of technology for operational activities (maximum 50) 25 23 24Use of ERP (maximum 45) 30 27 28 ***R&D investment (% total sales) 7 9 8Process equipment (% total sales) 2 3 3Training and education (% total sales) 2 3 3Manufacturing overheads (% manufacturing costs) 21 21 21Co-ordination of design and manufacturing (factor score) 0.06 −0.04 0.00Management of product development cycle (factor score) 0.04 −0.03 0.00

Innovation index 2.8 2.5 2.7 *

Panel D: Indicators of innovation and innovation index—breakdown by countries characterisedby national cultures with a different level of uncertainty (n = 711)

Indicators of innovation Low (n = 296) High (n = 415) Total Significance(kw)

Use of technology for operational activities (maximum 50) 24 24 24Use of ERP (maximum 45) 28 28 28R&D investment (% total sales) 7 8 8Process equipment (% total sales) 3 2 3 ***Training and education (% total sales) 3 2 3 ***Manufacturing overheads (% manufacturing costs) 21 21 21Co-ordination of design and manufacturing (factor score) −0.04 0.03 0.00Management of product development cycle (factor score) 0.02 −0.01 0.00

Innovation index 2.7 2.6 2.7

Significance: *p < 0.05; **p < 0.01; ***p < 0.001 and kw: Kruskall–Wallis test.

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