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Competitiveness Review: An International Business Journalncorporating Journal of Global Competitiveness

Emerald Article: National culture and infrastructure development: Acomparison among four cultural typologies

Jacqueline Mayfield, Milton Mayfield

Article information:

To cite this document: Jacqueline Mayfield, Milton Mayfield, (2012),"National culture and infrastructure development: Aomparison among four cultural typologies", Competitiveness Review: An International Business Journal incorporating Journal of

Global Competitiveness, Vol. 22 Iss: 5 pp. 396 - 410

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National culture andinfrastructure development

A comparison among four cultural typologies

Jacqueline Mayfield and Milton MayfieldTexas A&M International University, Laredo, Texas, USA

Abstract

Purpose The purpose of this paper is to investigate the predictive influence of national culturalmodels on national infrastructure development. The national culture models of Hofstede, GLOBE,Ronen and Shenkar, and the World and European Values Survey (WEVS), were measured andcompared to ascertain the best prediction fit for national infrastructure development.

Design/methodology/approach A literature review examined four established cultural models,most of which (with the exception of the WEVS) assert stable, holistic models of national culture forbusiness applications. The argument for cultural divergence in key moderators and mediators such asinfrastructure development was also discussed. Then each models predictability was measured withset correlation methodology, using GDP and population as co-variates. Also, the marginal influence ofthe other three cultural typologies were controlled for in each respective analysis.

Findings Each model was found to have a positive significant prediction relationship with nationalculture infrastructure growth. The most promising model is the WEVS which explains a substantialproportionof the variance in national infrastructure.Additionally, WEVS has a higher predictivelink toeach infrastructure area than the other models. These results are preliminary and cross-sectional, yet

they suggest that dynamic cultural models may be the best predictors of infrastructure development.Practical implications The study shows that increased efforts by the private sector andgovernment can rely on dynamic models to boost national GDPs, and give better strategic guidance toforeign financial investment and human resources management.

Originality/value The paper supports the hypotheses that national culture models can growGDP to a healthy level through prediction, assessment, and then taking necessary interventions.

Keywords National cultures, Economic development, National economy, Cultural typology,International management, Set correlation

Paper type Research paper

IntroductionWith the advent of an increasingly complex global business world (Friedman, 2005)new opportunities and challenges arise for investment and development priorities. Oneeffective insight into making such decisions could be based on popular national culture

typologies. Yet the key indicators of national infrastructure expenditures such aslong-term investment (national investment in capital goods and education), energyinfrastructure development (electrical, oil, and natural gas production), communicationinfrastructure (telephone main lines, number of cellular phones, and number of internethosts), and transportation infrastructure (miles of waterways, roadways, railways, andnumber of airports) are relatively unexplored in their relationships to national culturetypologies, despite much research advocacy for national level of analysis (Ashmos andHuber, 1987; Gill, 2005; Hox and Maas, 2005; Miner, 2005a, b).

Improved knowledge as to which levels of infrastructure status are linked towell-established cultural typologies would assist more effective foreign investment

The current issue and full text archive of this journal is available atwww.emeraldinsight.com/1059-5422.htm

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pp. 396-410q Emerald Group Publishing Limited1059-5422

DOI 10.1108/10595421211266285

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strategies, quality of work life projects, and ameliorate some of the dilemmas that arisefrom global decision-making, potentially boosting humanistic well-being, and nationalbudgetary and planning processes as well. Fortunately, a great deal of research oncultural typologies has been pioneered in relevant models. For example, Hofstede,Project GLOBE, Ronen and Shenkars clusters, and the World Values Survey (WVS)and its companion, the European Values Study (EVS) have identified robust models ofcultural attributes, especially for quality of life and the business world (Hofstede, 1980,2001; House et al., 2004; Inglehart and Basanez, 2000; Ronen and Shenkar, 1985).

However, all of the preceding cultural models are based on assumptions of relativenational culture stability, with the exceptions of the WVS and EVS. Therein lies the

objectives of this study. What cultural framework is most effective for predictingnational infrastructure development: the stable well-adopted models or the morechange-oriented WVS and EVS contexts? This form of research has been advocatedby numerous scholars (Diener and Diener, 1995; Gelfand et al., 2007; Inglehart et al.,2000a, b). Also, the investigation adheres to Dubins definition of the theoretical goal of:

[. . .] the analysis of a scientific model that reveals an outcome not previously apparent eitherfrom an examination of the empirical world or from the obvious consequences from anexisting theory (Dubin, 1969, p. 9).

As a result, this paper will be structured into the following sections: national cultureliterature review, national infrastructure background, methodology, and conclusionsfor discussion and recommendations.

National culture literature reviewFirst, a substantial body of research has been investigated by various scholars whohave collaborated on and extended our knowledge of national culture and its impact inorganizational behavior. For the purpose of this paper, the national culture focus willbe on the attitudes and behaviors that manifest themselves on the national level ofanalysis in organizations (Adler and Gundersen, 2008). Furthermore, national culturewill include the clarifications that values are shared, have the capacity to be flexible,and are communicated over time (Gelfand et al., 2007; Triandis, 1994). As inglehartobserved, national culture is the subjective aspect of a societys institutions: thebeliefs, values, knowledge, and skills that have been internalized by the people of agiven society (Inglehart, 1997, p. 15).

Hofstedes (1980, 2001) research is probably the most familiar and renownedcultural framework. In addition, Hofstedes model is predominant in managementtheory because of its extensive longitudinal testing and parsimony (Kirkman et al.,

2006). In Hofstedes model, a comprehensive typology was drawn from a wide range ofnational culture questions, then was collected from mainly professional personnel inworldwide IBM operations (Hofstede, 1980). Again, 20 years later, Hofstede retested hismodel and surmised that cultural characteristics remain stable over time (Hofstede,2001). Significantly, Hofstede also asserted that that the influence of national culturehad a more powerful impact on critical organizational behaviors than did suchcompeting variables such as age, profession, and job classification (Adler andGundersen, 2008).

As an overview, Hofstedes typologies initially identified four key culturaldimensions, and a fifth one has subsequently been introduced. These factors include

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power distance, individualism/collectivism, quality of life-a values orientation, anddegree of uncertainty avoidance. Later, the attributes of Confucian dynamism wereconceptualized and explored (Adler and Gundersen, 2008; Holt and Wigginton, 2002).

Power distance refers to national level workplace values regarding equality(sharing) in initiatives and decision-making. In low power distance, certain countries such as the USA, Canada, New Zealand, and The Netherlands formal organizationchain of command is more easily circumvented. Of note, those countries that reportedlow power distance scores tended to promote more social equality than their highpower distance counterparts. In comparison, high power distance nations place agreater emphasis on conforming to social and organizational formalities. For example,hierarchical commands are less likely to be challenged by lower status employees.Examples of such countries are Mexico, Japan, and India (Holt and Wigginton, 2002).

Collectivism and individualism is another basic dimension in Hofstedes framework,and this cultural aspect has been most often applied in group and organizational studies(Kirkman et al., 2006). In essence, this factor describes the pressures and rewards toconform to group norms versus individualistic behaviors. Some examples of collectivistcultures include many Latin American, Asian, and Mid-Eastern countries. Groupharmony, social norms, and family loyalty are emphasized in collectivist values. On theother hand, high country ranking in individualism can be found in Canada, Norway, theUSA, and Germany among other nations. In short, individualistic cultures reflect a highpriority on self career development and initiative.

The third Hofstede factor evaluates the nations concepts for quality of life. Qualityof life has at times been characterized by masculine (career success, wealth) or feminine

values (concern for group and social welfare, and gender equality). Sweden tends toreward feminine values by its social support system for work and family balance, alongwith progressive gender equality in organizational settings. For example, Swedishfathers can choose to take paternity leave, while women are encouraged to choose freelyamong career options. Social services such as health care and day care are alsosubsidized. In comparison, masculine quality of life values abound in countries such asthe USA and Japan, where materialism earns much social respect (Adler and Gundersen,2008; Holt and Wigginton, 2002).

The fourth central Hofstede factor is degree of uncertainty avoidance or tolerance ofambiguity in organizational behavior. In high uncertainty avoidance countries, there isan establishment of many formal rules and often long-term employment. Suchcountries in this category include Japan, Austria, and Germany. To contrast, lowuncertainty avoidance nations are correlated with shorter term employment, and lesshierarchical organizational regulations (Adler and Gundersen, 2008; Holt and

Wigginton, 2002).A fifth factor, Confucian dynamism, emerged after the initial four facets as

collaboration between Hofstede and Professor Michael Bond. This construct evaluatesthe dedication to work motivation and respect for tradition in certain Asian countries.Notably, the countries of Taiwan, Singapore, South Korea, and Hong Kong are strongin their confucian dynamism (Adler and Gundersen, 2008).

While Hofstedes work is quite prominent and coherent, there are weaknessesthat have to be acknowledged. Primarily, his research was largely limited to oneorganization (IBM), potentially reflecting a professional class of employees. Thus, somedifferentiations could be ignored and clarification of generalizability is questionable

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(Hofstede, 1980, 2001). In addition, international business scholars have questioned theHofstede models assertion of a very slow rate of nationalcultural change(Inglehartetal.,2000a, b).

Inspired by and seeking to expand Hofstedes typology was the inception andimplementation of the project, Global Leadership and Organizational BehaviourEffectiveness (GLOBE). In brief, GLOBE is an ongoing study that expanded Hofstedescultural dimensions into the following nine categories: gender differentiation,assertiveness, power distance, uncertainty avoidance, in-group collectivism-loyalty toones intimate circle of family and friends and immediate employer, future orientation,institutional collectivism-or dedication to social institutions (where the government canpotentially offer economic incentives), humane orientation-or the extent to which acountry rewards individuals for altruistic behaviors, and performance orientation theextent to which the society positively reinforces employees for work outcomes. Inaddition, GLOBE emphasized the importance of cross-cultural communications, anduniversally admired leadership attributes such as charismatic leadership (House et al.,2004; Javidan and House, 2001). Unfortunately, there has been considerable controversyaboutthe clarity of the factorsdeveloped in the study. Some of thecorrelationshave alsobeen questionable and, at present, the project is still a cross-sectional research design.Perhaps later data collection results and analysis will resolve these problems (Graen,2006; Hofstede, 2006). Moreover, the issue of national cultural stability has not been fullyaddressed and dynamic elements have not been identified (Hofstede and McCrae, 2004;

Javidan and House, 2001).Interestingly, Ronen and Shenkar (1985) also combined multiple typologies into nine

cultural clusters in an earlier project. These authors collected data for four types ofworkplace affects: job satisfaction,employment objectives, interpersonal relationships, andleadership expectations. In all, 45 countries were surveyed, with a resultant eight countryclusters-and a ninth group of outliers. This method was advantageous in that it drew fromseveral different, existing country clusters. As a result, the project was easily understood.However, most of the contributing studies to the categories were conference papers-raisingquestions about the original research rigor and creating difficulties in examining thequality of underlying data. In addition, the study runs the risk of over simplicity with amere eight clusters. And certain countries formed an independent taxonomy namelyIndia, Japan, Brazil,and Israel,which did not share enough similarities to generate a cluster(Holt and Wigginton, 2002; Ronen and Shenkar, 1985). Furthermore, as with the threepreceding typologies, the implicit assumption is one of national culture stability.

In comparison, the fourth cultural and somewhat unique-typology that will beused to predict technological infrastructure are questions in the WVS and its subset,

the EVS, that evaluate employee work attitudes such as perception of work rewards,i.e. holidays, pay, and hours, work initiative seeking, employee self-esteem about a job,and the role of work in personal talent development (The World Values Surveyweb site, 2010). Equally important, previous research on WVS surveys implies unusualemphasis on the outcomes of subjective well-being (SWB), happiness, and theirrelationships to economic development. These insights merit serious consideration(Inglehart, 1997; Inglehart et al., 2007). Also, the methodology has been conducted onan ongoing basis from 1981 until the present, with many lesser developed nationsbeing added in recent years. The sample size is quite robust with at least 112 nations(Inglehart et al., 2007, 2004).


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The WVS and EVS also are distinct from their three preceding counterparts in theiremphasis on cultural change and variance. Only these two survey sets assume thatcertainnational cultureattributes are malleable and greatly influenced by GDP. Equallyimportant, innovative cultural researchers have challenged the findings of Hofstede,GLOBE, and Ronen annd Shenkar for their stability assumptions and exclusion ofcultural moderators and mediators. These same researchers view culture asparadoxically convergent-adhering to grand models and moving to a global culture,while at the same time expressing much divergence-variance that exists in culturalvalues, dependent on the particular attribute (Gannon, 2007; Inglehart and Baker, 2000;Li and Bond, 2010; Steel and Taras, 2010; Tung and Verbeke, 2010; Wilhelms et al., 2009).

For instance, Gannon illuminated the variance between these national culturecharacteristics by noting regional, ethnic, religious, generational, industry,occupational, and corporate cultures (Gannon, 2007, p. 20).

In response and congruent with the WVS assumption of national cultural change,these scholars have raised the call to answer such critical questions as what roles donational cultural subsets such as technological investment and education play in theoutgrowth of cultural change as mediators and moderators? (Leung et al., 2005; Tungand Verbeke, 2010). These same researchers are also seeking a disentanglement fromthe grand cultural models.

The positive message sent by the WVS is that happiness can be increased on thenational level due to such factors as economic initiatives (including technologicalinfrastructure development), increased personal freedom, and social tolerance.Furthermore, the WVS data were gathered from employees (not just managers)themselves. Also pertinent, SWB had a very significant but curvilinear relationshipwith economic development levels. In fact, while augmented economic development wasa major influence on the growth of SWB in the WVS, 45 of 52 countries studied reportedrises in happiness between 1981 and 2007. Prosperity beyond certain GDP incomes wasaffected by levels of social freedom, and political democratization (Inglehart et al., 2007).Consequently, the WVS raises questions about the relationship between economicdevelopment and other social interactions.

Infrastructure backgroundThe status of national infrastructure is integral to human well-being, such as depictedin the WVS, and certainly to long-term economic health. To explain this link, we willuse the following definition of national infrastructure: a nations physical andstructural capability to meet social demands and conduct trade. For example, internetcapabilities and transportation systems are designed to serve as infrastructure. Other

important examples of national infrastructure include energy production, engineeringaccomplishments such as building construction, communication networks, andinvestment in businesses and education (Duffy-Deno and Eberts, 1991; Kessides, 1993;Roller and Waverman, 2001).

Concurrently, a debate as to whether the privatesectoror government should assumeleadership of national infrastructure development has become tenuously resolved as abalanced partnership between the two entities with the mutual goal of global economichealth. Yet, at the same time, private capitalization is lacking and infrastructuredevelopment demands are falling short on fulfillment (Anonymous, 2004). This trend isfurther pronounced by the economic crises in Europe and the USA in more recent years

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when national governments have intervened on behalf of economic welfare, includingthat of infrastructure development.

As previously stated, the characteristics of national infrastructure practices arerelated to economic and human welfare by national culture studies (Inglehart et al.,2007). Moreover, we propose that national culture models will play a significant role indetermining how infrastructure investment is allocated, with the WVS and EVSmodels being the strongest predictors. Thus, a study of which cultural model bestdescribes infrastructure development patterns could be a boon to planning andinvestment decisions. (Duffy-Deno and Eberts, 1991; Kessides, 1993; Leung et al., 2005;Miroshnik, 2002; Roller and Waverman, 2001).

Based on the preceding body of research, it appears that national culture shouldbe a good predictor of important aspects of economic development. Additionally,a preliminary hypothesis can be put forward that the more dynamic conceptualizationof national culture (embodied by the WVS/EVS) should be a stronger predictor of thesimilarly changing variables of national infrastructure. These statements arepresented formally as follows:

H1. Infrastructure f (Culturen) (where n stands for a given cultural typology).

H2. Infrastructure R2 of WVS/EVS cultural typology . stable cultural

typologies.

In brief, it is expected that all studied typologies will be useful for nationalinfrastructure development prediction, but that the dynamic cultural typologyWVS/EVS (WEVS) will be more effective and accurate than the non-dynamic models.

The details of the test will be included in the next section, methodology.

MethodPurpose, subjects, and sampling proceduresFor this study, our central purpose was to evaluate various national cultural models fortheir accuracy in predicting national level infrastructure development. Thus, we testedthe preceding hypotheses.

Cultural information was collected on 103 sovereign nations using secondary datasources (see Table I for a list of included nations). The data sources for culturalinformation were obtained from published information on Hofstedes cultural typology(Hofstede, 2001), the GLOBE typology (House et al., 2004), Ronen and Shenkars culturalclusters (Ronen and Shenkar, 1985), and the World Values cultural measures from theWVS (ASEP/JDS, 2009) and its subset the European Values Survey (EVS, 2006). Furtherinformation on national infrastructure was taken from the CIA World Factbook (CIA,

2010). The primary limitation on nation inclusion was cultural typology measurement,with each of the four typologies covering somewhat different nation sets.

Measures and covariatesThe Hofstede typology was measured using its four major variables power distance,uncertainty avoidance, individualism-collectivism, and masculinity-femininity. TheGLOBE typology was measured using all of the practices variables. The Ronen andShenkar typology used all listed clusters. Finally, the world values typology wasmeasured through the items asking what was important in a job (items C011 to C022 inthe integrated questionnaire).


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The infrastructure variablesincludeditems on long-term investment (nationalinvestmentin capital goods, and educational investment), energy infrastructure (electrical, oil, andnatural gas production), communication infrastructure (telephone main lines, number ofcellular phones, and number of Internet hosts), and transportation infrastructure (miles of

waterways, roadways, railways, and number of airports). All measures except long-terminvestment demonstratedacceptable reliability levels (Churchill, 1979), withthe long-terminvestment measures demonstrating negative correlations. As a result of this lowreliability, it was decided to use each measure separately as an infrastructure indicator.The remaining singular long-term infrastructure measures had the following reliabilities:

energy infrastructure 0.87, communication infrastructure 0.78, and transportationinfrastructure 0.96.

National GDP and population (CIA, 2010) were used as covariates for the dependentvariables. It was expected that these variables could distort the relationship betweenculture and infrastructure by adding spurious variance to the dependent variables.

Albania Algeria AndalusiaArgentina Armenia AustraliaAustria Azerbaijan BangladeshBasque Country Belarus BelgiumBosnia Bosnia Herzegovina BrazilBulgaria Canada ChileChina China ColombiaCroatia Cyprus Czech RepublicDenmark Dominican Republic East GermanyEgypt El Salvador Estonia

Finland France GaliciaGeorgia Germany Great BritainGreece Hungary IcelandIndia Indonesia IranIraq Ireland IsraelItaly Japan JordanKosovo Kyrgyzstan LatviaLatvia Lithuania LuxembourgMacedonia Malta MexicoMoldavia Moldova MontenegroMorocco The Netherlands The NetherlandsNew Zealand Nigeria NirelandNorthern Cyprus Northern Ireland NorwayPakistan Peru PhilippinesPoland Portugal Puerto RicoRomania Russia South Africa

Saudi Arabia Serbia Serbia And MontenegroSingapore South Korea SlovakiaSlovak Republic Slovenia SpainSrpska Republic Sweden SwitzerlandTaiwan Tambov TanzaniaTurkey Uganda UkraineUruguay USA ValenciaVenezuela Vietnam West GermanyZimbabwe

Table I.Nations included incultural stability analysis

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Higher GDP could allow increased infrastructure investment, and larger populationsmight create a greater need for such infrastructure. As such, this variance should bepartialled from the dependent variables.

Analysis methodSet correlation (Cohen, 1982) was used to test the proposed hypotheses. The use of setcorrelation in this study provides an appropriate analysis method due to its flexibilityand many useful properties for analyzing a wide variety of multivariatedata sets (Cohenand Cohen, 1983; Cohen et al., 2003; Kasen et al., 1996; Pauers, 2011; Sullivan and Gee,

2007; Weiner et al., 2006). In addition, set correlation offers an intermediary analyticalmethod between standard statistical methods (such as regression) that are not suitablefor examining complex models or controlling variable effects on dependent variables(Cohen, 1982), and structural equation models which require strong data assumptions tobe met and a well-developed theory underlying the model (Chin, 1998; Joreskog, 1993;

Joreskog and Sorbom, 1989; Lohmoller, 1989; Mayfield and Mayfield, 2010a, b;Schumacker and Lomax, 1996). Set correlation is appropriate for testing what can becalled moderate strength models. Strong models are those developed through extensivetesting and refinement over a period of time. Weak models are those newly developedand largely used to simply explore a relationship between variables. Moderate strengthmodels are those looking to establish particular relational strengths while controlling(either dependent or independent) variables for the influence of extraneous factors(Dubin, 1978; Lynham, 2002).

The current model falls squarely into this middle range. While national culture has

been shown to influence national characteristics (and it is known what factors mayneed to be controlled to better measure this influence), it is not known how cultureinfluences the specific aspect of national infrastructure, or what if any causal loopsexist between variables (and such understanding would be necessary to use a causalmodeling method). With a medium strength model, such methods as set correlation aremore appropriate providing means to examine complex relationships while allowingfor a more open-ended examination of data.

Set correlation provides a mechanism for analyzing relationships between sets ofindependent and dependent variables (with one or more variables in each set). It also(in contrast to canonical correlations) allows for more interpretable results that can becompared on a consistent scale (Cohen, 1982, 1988; Cohen et al., 2003). As previouslymentioned, themethod hasfewer restrictive data or theory development requirements asnecessary for the various structural equation model methods. However, set correlationstill allows for the examination of complex data sets. The technique has an additional

property of partialling covariates from either the dependent or independent variablesets, thus allowing for a more accurate assessment of the relationship between the twovariable sets.

This statistical method was also selected because it allows for analyzing multipledependent variables, partialling a set of variables from dependent variables withoutinterfering with the independent variables, and methods for comparing relativerelationship strength between different set correlation equations. For analysis, eachcultural typology was analyzed as the independent variable set, and the infrastructurevariables were used as the dependent set. From the dependent set, national GDPand population were partialled to reduce unnecessary variance. After these equations


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were run, each was evaluated for overall significance and effect size. All significantmodels effect sizes were compared to determine if one or more models displayed higheraccuracy in predicting national infrastructure development.

ResultsStatistics and data analysisSet correlation results showed that all four cultural typologies significantly predictednational infrastructure. In addition, all four typologies had f2 scores in the largecategory (Cohen, 1988). This effect size measure provides an estimate of how well theindependent variable set accounts for the variance in the dependent set. A small effectsize indicates that there are many other influences on the dependent variable set, and alarge effect size indicates thatthe independent set predicts a very substantial proportionof the variance in the dependent set. A medium effect size indicates a strong relationshipbetween the independent and dependent sets but that other (unmeasured) constructsalso influence the dependent set. Cohens guidelines for these effect sizes are as follows:small20.02 up to 0.15,medium20.15 up to 0.35,large20.35 and greater (Cohen, 1988).As can be seen in Table II, all typologies have an effect size in the large category.

Follow-up tests were used to determine if any typology was significantly better atpredicting infrastructure development than any other framework by examining theconfidence intervals around each models multivariate R2. Based on this test, theWEVS framework performed better than the GLOBE and Hofstede typologies. WEVSwas also a better predictor, though not significantly so, than was the Ronen andShenkar model. See Tables II and III for analysis results.

As a further analysis of different cultural models influences on nationalinfrastructure development, the effect strength (in terms of R2 and f2) of each modelwas examined for each individual infrastructure variable. Results provided a clearerpicture of how strongly each model was linked to the infrastructure aspects. Overall,the WEVS model continued to show the strongest linkage with infrastructure in termsof large, medium, and small effect sizes. (Cohen does not recommend differentiatingwithin these categories for his f2 measure (Cohen, 1988). WEVS had large effect sizes

Typology Multivariate R2 Cohens f2

Hofstede 0.86 0.79GLOBE 0.80 0.49Ronen and Shenkar 0.88 0.66WVS 0.92 0.71

Note: All typology models were significant at the 0.05 level

Table II.Set correlation

analysis results

Typology Multivariate R2 Lower C.I. Upper C.I. C.I. higher than C.I. lower than

Hofstede 0.86 0.78 0.93 None NoneGLOBE 0.80 0.72 0.88 None NoneRonen and Shenkar 0.88 0.83 0.93 GLOBE NoneWVS 0.92 0.88 0.95 Hofstede GLOBE None

Table III.Model comparisonresults

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for all infrastructure variables except energy, and it had a medium effect size with thisvariable. The Ronen and Shenkar model had the next strongest set of predictivelinkages with one large, two medium, and one small effect size. The GLOBE measurehad the lowest predictive strength with only three medium measures and two smallmeasures. Analysis results are presented in Table IV.

ConclusionThis paper sought to investigate the predictability of national cultural models oninfrastructure development. In general, all the research models, Hofstede, GLOBE,Ronan and Shenkar, and the WVS/EVS, significantly predicted the relationshipbetween national cultural typology and respective infrastructure development. As aresult, the first hypothesis was supported.

The second hypothesis was that the more dynamic models of the WVS and the EVSwould exceed accuracy in infrastructure development prediction than the more stabletypologies. This hypothesis was in part supported. Similarly, the WEVS showed anoverall stronger link to each individual infrastructure variable, with large linkagesbetween four out of the five factors and a medium relationship with the other factor. Assuch, the WEVS proves to be a consistently good predictor of national infrastructurefor overall comparisons and for each of the individual infrastructure measures.

However, the Ronen and Shenkar model also showed good predictive strength, andits relative relational strength was slightly higher for two infrastructure factors thanthe WEVS model. As such, there appears to be a need to further explore the relativemerits of fixed and non-fixed cultural models in analyzing some fluid national aspects.Of note, while Ronen and Shenkars forecasting power was similar to the WVS andEVS, their model was constrained by a focus on a managerial class and smaller samplesize, 45, of nations (Ronen and Shenkar, 1985).

These findings are promising, since the WVS and EVS are closely associated withInglehart et al.s assertions that national cultures change in part due to the advances ofinfrastructure development (Inglehart, 1997; Inglehart et al., 2007). Furthermore, theseresults are congruent with preceding research that has implicated cultural compatibility

Cultural typologyInfrastructure type Hofstede Globe Ronen and Shenkar WEVS

Long-term investment 0.05 0.09 0.09 0.350.05 0.10 0.10 0.54

Education 0.13 0.11 0.14 0.330.15 0.13 0.17 0.49

Energy infrastructure 0.17 0.14 0.18 0.130.20 0.17 0.22 0.15

Communication infrastructure 0.29 0.18 0.50 0.410.40 0.22 0.98 0.70

Transportation infrastructure 0.02 0.13 0.62 0.350.02 0.15 NAa 0.54

Notes: Multivariate R2 s are presented on the top row for each infrastructure factor; Cohens f2 s ispresented on the bottom row; for Cohens f2, large effect sizes are in bold, medium effect sizes areitalicized, and small effect sizes are presented in standard type face; athe f2 measure could not becalculated for this relationship due to data distribution issues

Table IV.A comparison of different

cultural typologiesstrength in predicting

individual infrastructurecharacteristics using the

multivariate R2 andCohens f2


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as a key influence in the success of global human resources strategies and tactics,foreign investment, and international acquisitions and mergers (Ang et al., 2007;Bhagat etal., 2002; Boddewyn et al., 2004; Gelfand et al., 2007; Leung et al., 2005). Finally,the insights from this study respond to recent calls from international businessscholars for more exploration of moderators and dynamism in national cultures(Leung et al., 2005).

These findings also contribute to international management practice since theysuggest useful model fits for financial investment decision-making. In addition, theresults should provide insights into acquisition/merger options. Also important,the model can offer global managers performance-oriented guidance on humanresource policies and practices, including training and development. For example, theWVS is focused on employee perceptions, not those of exclusively a management andprofessional class (Inglehart, 1997; Inglehart et al., 2000).

The weaknesses in this study can also inspire ongoing and future research. First, thestudy is not longitudinal, since only one wave of WVS and EVS questions (2000) wereexamined. However, the same surveys offer the capacity to analyze value changes indifferent timewaves beginning with 1981(Inglehart, 1997; Inglehart etal., 2000). Moreover,this study raises, but does notdefinitively prove,the hypothesis thatmore dynamic culturalmodels are better predictors of national culture infrastructure development since causalitywas not established and one of the stable models showed good levels of forecasting power,even though it had a relatively small sample size of nations. Whilethe WVS and EVScovermost nations, other models did not disclose such comprehensive samples of nationalgroups. In addition, this study is also confined to survey methods and their inherent biases.

Moreover, the lack of significance between education and infrastructure developmentmerits a deeper explanation that was not within the scope of this study.For future research, we suggest a variety of study initiatives which will more clearly

explicate our results. First, exploring the assumptions of national cultural stability is apriority to advance constructs and predictions for models of national culture. Tung andVerbake (2010) advocated improved understanding of cultural stability, convergences,and divergences especially in the context of fast technological change. Longitudinaland cross-sectional (including employee work status) are the suggested frameworks forthese initiatives. Also, the presence of causality should be explored as researchers haveraised the questions of the role of GDP and cultural change (Inglehart, 1997;Inglehart et al., 2007). Does economic growth precede cultural change or vice versa?Are the two influences mutually interactive?

Second, moderating and mediating factors in national cultural attributes arepertinent research programs, as recommended by Tung and Verbake (2010) and

Leung et al. (2005). These factorscan highlight why certain and expanded infrastructureattributes are more cohesive with cultural fit than others. For example, what roles doeseducation playin national culture infrastructure investment? Does rapid globalization ordramatic political change, such as the fall of the former Soviet Union, influence nationalcultural tendency to invest in infrastructure development? And more profoundly, do thecore values of a national culture become changed as a result? (Inglehart, 1997).

For practice, more implications for future research arise. Based on the cultural modelsemployed in this paper, foreign investment decisions and human resources policies andpractices can be assessed. For instance, which national culture infrastructures present thebest financial investment opportunities? What are optimal selection, reward,

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retention-including personnel development-adjustment, and change managementstrategies (Cascio, 2009, 2000) that will achieve congruency or even help increasenational infrastructure growth? Also, these new policies must be operationalized,implemented and evaluated. For instance, managers may want to experiment withnational culture model (such as the WEVS) driven foreign investment and merger/acquisition decisions. Also, more flexible selection and training programs for globalassignments, such as cultural intelligence frameworks that are not based on the train forstable countryprofilescan be put in place (Earley and Peterson, 2004;Templeretal., 2006;Triandis, 2006). In fact, cultural intelligence is a very limber approach that includeseducation and aptitude for cultural flexibility. Careful evaluations of the effectiveness ofthese preceding experiments will be helpful feedback into an open systems loop (Ashmosand Huber, 1987) for improved infrastructure investment and human resource policyadjustments.

In summary, this paper has added incremental knowledge to the understanding ofnational culture models relationships with national infrastructure development.Hopefully, future researchers and managers will use this information to enhance athriving global economy where employees enjoy a high quality of work life, one thatresonates with the entire human life experience.

References

Adler, N.J. and Gundersen, A. (2008), International Dimensions of Organizational Behavior,5th ed., Thomson South-Western Educational, Mason, OH.

Ang, S., Van Dyne, L., Koh, C., Ng, K.-Y., Templer, K.J., Tay-Lee, S.L.C. and Chandrasekar, N.A.(2007), Cultural intelligence: its measurement and effects on cultural judgment anddecision making, cultural adaptation and task performance, Management andOrganization Review, Vol. 3 No. 3, pp. 335-71.

Anonymous (2004), International: developing world seeks infrastructure, Oxford AnalyticaDaily Brief Service, p. 1, November 3.

ASEP/JDS (2009), World Values Survey 2000 Official Data File v. 3, World Values SurveyAssociation, Madrid, available at: www.worldvaluessurvey.org

Ashmos, D.P. and Huber, G.P. (1987), The systems paradigm in organization theory: correctingthe record and suggesting the future, The Academy of Management Review, Vol. 12 No. 4,pp. 607-21.

Bhagat, R.S., Kedia, B.L., Harveston, P.D. and Triandis, H.C. (2002), Cultural variations in thecross-border transfer of organizational knowledge: an integrative framework,The Academy of Management Review, Vol. 27 No. 2, pp. 204-21.

Boddewyn, J.J., Toyne, B. and Martinez, Z.L. (2004), The meanings of internationalmanagement, Management International Review, Vol. 44 No. 2, pp. 195-212.

Cascio, W. (2009), Managing Human Resources, 8th ed., McGraw-Hill/Irwin, New York, NY.

Cascio, W.F. (2000), Costing Human Resources: The Financial Impact of Behavior inOrganizations, 4th ed., South-Western College, Mason, OH.

Chin, W.W. (1998), The partial least squares approach for structural equation modeling,Modern Methods for Business Research, Lawrence Erlbaum Associates, London, pp. 295-336.

Churchill, G.A. Jr (1979), A paradigm for developing better measures of marketing constructs,Journal of Marketing Research, Vol. 16 No. 1, pp. 64-73.


407

7/30/2019 17054978

14/16

CIA (2010), CIA The World Factbook, Central Intelligence Agency, available at: www.cia.gov/library/publications/the-world-factbook/ (accessed December 25, 2010).

Cohen, J. (1982), Set correlation as a general multivariate data-analytic method, MultivariateBehavioral Research, Vol. 17 No. 3, pp. 301-41.

Cohen, J. (1988), Statistical Power Analysis for the Behavioral Sciences, 2nd ed., Psychology Press,New York, NY.

Cohen, J. and Cohen, P. (1983), Applied Multiple Regression/Correlation Analysis for theBehavioral Sciences, 2nd ed., Lawrence Erlbaum Associates, Hillsdale, NJ.

Cohen, J., Cohen, P., West, S.G. and Aiken, L.S. (2003), Applied Multiple Regression/Correlation

Analysis for the Behavioral Sciences, 3rd ed., Lawrence Erlbaum Associates, Mahwah, NJ.Diener, E. and Diener, C. (1995), The wealth of nations revisited: income and quality of life,

Social Indicators Research, Vol. 36 No. 3, pp. 275-86.

Dubin, R. (1969), Theory Building, The Free Press, New York, NY.

Dubin, R. (1978), Theory Building, 2nd ed., The Free Press, New York, NY.

Duffy-Deno, K.T. and Eberts, R.W. (1991), Public infrastructure and regional economicdevelopment: a simultaneous equations approach, Journal of Urban Economics, Vol. 30No. 3, pp. 329-43.

Earley, C.P. and Peterson, R.S. (2004), The elusive cultural chameleon: cultural intelligence as anew approach to intercultural training for the global manager, Academy of ManagementLearning & Education, Vol. 3 No. 1, pp. 100-15.

EVS (2006), European Values Study 2008, 4th Wave, Integrated Dataset, ZA4800 Data FileVersion 1.0.0, GESIS Data Archive, Cologne.

Friedman, T.L. (2005), The World is Flat: A Brief History of the Twenty-First Century,Douglas & McIntyre, New York, NY.

Gannon, M.J. (2007), Paradoxes of Culture and Globalization, Sage, Thousand Oaks, CA.

Gelfand, M.J., Erez, M. and Aycan, Z. (2007), Cross-cultural organizational behavior, AnnualReview of Psychology, Vol. 58 No. 1, pp. 479-514.

Gill, J. (2005), Hierarchical linear models, in Kempf-Leonard, K. (Ed.), Encyclopedia of SocialMeasurement, Elsevier, New York, NY, pp. 209-14.

Graen, G.B. (2006), In the eye of the beholder: cross-cultural lesson in leadership from projectGLOBE, The Academy of Management Perspectives, Vol. 20 No. 4, pp. 95-101.

Hofstede, G.H. (1980), Cultures Consequences: National Differences in Thinking and Organizing,Sage, Beverly Hills, CA.

Hofstede, G.H. (2001), Cultures Consequences: Comparing Values, Behaviors, Institutions,and Organizations Across Nations, Sage, Beverly Hills, CA.

Hofstede, G.H. (2006), What did GLOBE really measure? Researchers minds versus respondentsminds, Journal of International Business Studies, Vol. 37 No. 6, pp. 882-96.

Hofstede, G.H. and McCrae, R.R. (2004), Personality and culture revisited: linking traits anddimensions of culture, Cross-Cultural Research, Vol. 38 No. 1, pp. 52-88.

Holt, D.H. and Wigginton, K.W. (2002), International Management, 2nd ed., Harcourt CollegePublishers, Fort Worth, TX.

House, R.J., Hanges, P.J., Javidan, M., Dorfman, P.W. and Gupta, V. (2004), Leadership, Cultureand Organizations: The GLOBE Study of 62 Societies, Sage, Thousand Oaks, CA.

Hox, J.J. and Maas, C.J.M. (2005), Multilevel analysis, in Kempf-Leonard, K. (Ed.), Encyclopediaof Social Measurement, Elsevier, New York, NY, pp. 785-93.

CR22,5

408

7/30/2019 17054978

15/16

Inglehart, R. (1997), Modernization and Postmodernization, Princeton University Press,Princeton, NJ.

Inglehart, R. and Baker, W.E. (2000), Modernization, cultural change, and the persistence oftraditional values, American Sociological Review, Vol. 65 No. 1, pp. 19-51.

Inglehart, R. and Basanez, M. (2000), World Values Survey, University of Michigan Press,Ann Arbor, MI.

Inglehart, R., Foa, R., Peterson, C. and Welzel, C. (2007), Development, freedom, and happiness,Mimeo.

Inglehart, R. et al. (2000a), Codebook for World Values Survey, Institute for Social Research,

Ann Arbor, MI.Inglehart, R. et al. (2000b), World Values Surveys and European Values Surveys, 1981-1984,

1990-1993, and 1995-1997, No. ICPSR 2790, Institute for Social Research, Ann Arbor, MI,p. 200.

Inglehart,R. etal. (2004), WorldValues Surveys and European Values Surveys, 1999-2001: UserGuideand Codebook, Inter-university Consortium for Political and Social Research, Ann Arbor, MI.

Javidan, M. and House, R.J. (2001), Cultural acumen for the global manager-lessons from projectGLOBE, Organizational Dynamics, Vol. 29 No. 4, pp. 289-305.

Joreskog, K.G. (1993), Testing structural equation models, in Bollen, K.A. and Long, J.S. (Eds),Testing Structural Equation Models, Sage, Newbury Park, CA, pp. 294-316.

Joreskog, K.G. and Sorbom, D. (1989),LISREL 7: A Guide to the Program and Applications, SPSS,Chicago, IL.

Kasen, S., Cohen, P., Brook, J.S. and Hartmark, C. (1996), A multiple-risk interaction model:

effects of temperament and divorce on psychiatric disorders in children, Journal ofAbnormal Child Psychology, Vol. 24 No. 2, pp. 121-50.

Kessides, C. (1993), The Contributions of Infrastructure to Economic Development: A Review ofExperience and Policy Implications, World Bank, Washington, DC.

Kirkman, B.L., Lowe, K.B. and Gibson, C.B. (2006), A quarter century of cultures consequences:a review of empirical research incorporating Hofstedes cultural values framework,Journal of International Business Studies, Vol. 37 No. 3, pp. 285-320.

Leung, K., Bhagat, R.S., Buchan, N.R., Erez, M. and Gibson, C.B. (2005), Culture andinternational business: recent advances and their implications for future research, Journalof International Business Studies, Vol. 36 No. 4, pp. 357-78.

Li, L.M.W. and Bond, M.H. (2010), Value change: analyzing national change in citizensecularism across four time periods in the World Values Survey, The Social ScienceJournal, Vol. 47 No. 2, pp. 294-306.

Lohmoller, J.-B. (1989), Latent Variable Path Modeling with Partial Least Squares, 1st ed.,Physica-Verlag HD, Heidelberg.

Lynham, S.A. (2002), Quantitative research and theory building: Dubins method, Advances inDeveloping Human Resources, Vol. 4 No. 3, pp. 242-76.

Mayfield, J. and Mayfield, M. (2010a), Leader-level influence on motivating language: a two-levelmodel investigation on worker performance and job satisfaction, Competitiveness Review,Vol. 20 No. 5, pp. 407-22.

Mayfield, M. and Mayfield, J. (2010b), Developing a scale to measure the creative environmentperceptions: a questionnaire for investigating garden variety creativity, CreativityResearch Journal, Vol. 22 No. 2, pp. 162-9.


409

7/30/2019 17054978

16/16

Miner, J.B. (2005a), Organizational Behavior I: Essential Theories of Motivation and Leadership,M.E. Sharpe, Armonk, NY.

Miner, J.B. (2005b), Organizational Behavior 2: Essential Theories of Process and Structure, M.E.Sharpe, Armonk, NY.

Miroshnik, V. (2002), Culture and international management: a review, Journal of ManagementDevelopment, Vol. 21 No. 7, pp. 521-44.

Pauers, M.J. (2011), One fish, two fish, red fish, blue fish: geography, ecology, sympatry, andmale coloration in the Lake Malawi Cichlid genus Labeotropheus (Perciformes: Cichlidae),International Journal of Evolutionary Biology, Vol. 2011 No. 10, pp. 1-12.

Roller, L.H. and Waverman, L. (2001), Telecommunications infrastructure and economicdevelopment:a simultaneousapproach,AmericanEconomic Review,Vol.91No.4,pp.909-23.

Ronen, S. and Shenkar, O. (1985), Clustering countries on attitudinal dimensions: a review andsynthesis, Academy of Management Review, Vol. 10 No. 3, pp. 435-54.

Schumacker, R.E. and Lomax, R.G. (1996), A Beginners Guide to Structural Equation Modeling,Lawrence Erlbaum Associates, Mahwah, NJ.

Steel, P. and Taras, V. (2010), Culture as a consequence: a multi-level multivariate meta-analysisof the effects of individual and country characteristics on work-related cultural values,Journal of International Management, Vol. 16 No. 3, pp. 211-33.

Sullivan, P.J. and Gee, C.J. (2007), The relationship between athletic satisfaction and intrateamcommunication, Group Dynamics: Theory, Research, and Practice, Vol. 11 No. 2,pp. 107-16.

Templer, K.J., Tay, C. and Chandrasekar, N.A. (2006), Motivational cultural intelligence, realisticjob preview, realistic living conditions preview, and cross-cultural adjustment,

Group & Organization Management, Vol. 31 No. 1, pp. 154-73.Triandis, H.C. (1994), Culture and Social Behavior, McGraw-Hill, New York, NY.

Triandis, H.C. (2006), Cultural intelligence in organizations, Group & OrganizationManagement, Vol. 31 No. 1, pp. 20-6.

Tung, R. and Verbeke, A. (2010), Beyond Hofstede and GLOBE: improving the quality ofcross-cultural research, Journal of International Business Studies, Vol. 41 No. 8,pp. 1259-74.

Weiner, D.K., Rudy, T.E., Morrow, L., Slaboda, J. and Lieber, S. (2006), The relationship betweenpain, neuropsychological performance, and physical function in community dwelling olderadults with chronic low back pain, Pain Medicine, Vol. 7 No. 1, pp. 60-70.

Wilhelms, R.W., Shaki, M.K. and Hsiao, C.F. (2009), How we communicate about cultures:a review of systems for classifying cultures, and a proposed model for standardization,Competitiveness Review: An International Business Journal Incorporating Journal of GlobalCompetitiveness, Vol. 19 No. 2, pp. 96-105.

Corresponding authorJacqueline Mayfield can be contacted at: [email protected]

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