Skip to main content
SpringerLink
Log in

Developing a multidimensional instrument to measure psychic distance stimuli

  • Article
  • Published:
Journal of International Business Studies Aims and scope Submit manuscript

Abstract

This paper develops and tests a range of potential psychic distance stimuli including differences in culture, language, religion, education, and political systems. Using trade flows among a set of 38 nations as the dependent variable, it is shown that, whereas the majority of the proposed indicators prove to be statistically significant predictors of trade flows, the most common psychic distance surrogate – a composite measure of Hofstede's cultural dimensions – is not significant.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

Notes

  1. Some researchers, such as Gomes and Ramaswamy (1999) and Lee (1998), treat these two constructs as isomorphic. However, the authors of this article favour the interpretation that views them as related but distinct constructs, with cultural distance being only one dimension of psychic distance.

  2. This approach parallels a framework proposed by Hallen and Wiedersheim-Paul (1984) and more recently by Conway and Swift (2000). It also has strong parallels with Child et al.'s (2002) schema of distance-creating and distance-bridging factors.

  3. The analyses reported in this paper were also performed using an alternative dependent variable: the trade intensity index (Srivastava and Green, 1986). These results are available in a working paper from the primary author. Although some of the specific results differ between the two approaches, the same overall conclusions are quite similar. The most relevant difference is that Hofstede's composite index proved to be a significant predictor when the trade intensity index was used. However, Hofstede's index still only represented <25% of the variance explained by the complete set of psychic distance stimuli.

  4. The means of some of the education, industrial development, and democracy difference scores, as reported in Table 2, differ from zero because of missing data; however, these deviations are small and statistically non-significant.

  5. The omitted dummy variables were for Ethiopia, Finland, Italy, and Sierra Leone as exporting nations, and India and Tanzania as importing nations. These variables were identified by their high variance proportion loadings in the multicollinearity diagnostics. The multicollinearity predominantly concerned the baseline gravity model, and not the main variables under examination.

  6. These comments exclude models, such as Regression 3, where collinearity has already been identified as a problem. Regression results confirming the significance of the Ind DevF (abs), DemF (abs) and Colony variables in the confirmation sample are not reported here, but are available on request.

  7. See note 3.

References

  • Anderson, J.E. and Wincoop, E. (2003) ‘Gravity with gravitas: a solution to the border puzzle’, American Economic Review 93(1): 170–192.

    Article  Google Scholar 

  • Arora, A. and Fosfuri, A. (2000) ‘Wholly owned subsidiary versus technology licensing in the worldwide chemical industry’, Journal of International Business Studies 31(4): 555–572.

    Article  Google Scholar 

  • Barkema, H.G. and Vermeulen, F. (1997) ‘What differences in cultural backgrounds of partners are detrimental for International Joint ventures?’ Journal of International Business Studies 28(4): 845–864.

    Article  Google Scholar 

  • Barraclough, G. (ed.) (1988) Concise Atlas of World History, Times Books: London.

    Google Scholar 

  • Barrett, D.B. (ed.) (1982) World Christian Encyclopedia, Oxford University Press: Nairobi.

    Google Scholar 

  • Beck, T., Clarke, G., Groff, A, Keefer, P and Walsh, P (2001) ‘New tools in comparative political economy: the database of political institutions’, World Bank Economic Review 15(1): 165–176.

    Article  Google Scholar 

  • Beckerman, W. (1956) ‘Distance and the pattern of Intra-European trade’, Review of Economics and Statistics 38(1): 31–40.

    Article  Google Scholar 

  • Bergstrand, J.H. (1989) ‘The generalized gravity equation, monopolistic competition and the factor proportions theory in International trade’, Review of Economics and Statistics 71(1): 143–153.

    Article  Google Scholar 

  • Bollen, K.A. and Lennox, R. (1991) ‘Conventional wisdom on measurement: a structural equation perspective’, Psychological Bulletin 110(2): 305–314.

    Article  Google Scholar 

  • Boyacigiller, N. (1990) ‘The role of expatriates in the management of interdependence, complexity and risk in multinational corporations’, Journal of International Business Studies 21(3): 357–381.

    Article  Google Scholar 

  • Carlson, S. (1974) ‘International transmission of information and the business firm’, Annals of the American Academy of Political and Social Science 412(March): 55–63.

    Article  Google Scholar 

  • Cavusgil, S.T. (1980) ‘On the internationalization process of firms’, European Research 8(November): 273–281.

    Google Scholar 

  • Child, J., Ng, S.H. and Wong, C. (2002) ‘Psychic distance and internationalization’, International Studies of Management and Organizations 32(1): 36–56.

    Google Scholar 

  • Conlon, R.M. (1985) Distance and Duties: Determinants of Manufacturing in Australia and Canada, Carlton University Press: Ottawa.

    Google Scholar 

  • Conway, A. and Swift, J.S. (2000) ‘International relationship marketing: the importance of psychic distance’, European Journal of Marketing 34(11/12): 1391–1413.

    Article  Google Scholar 

  • Davidson, W. (1980) ‘The location of foreign direct investment activity: country characteristics and experience effects’, Journal of International Business Studies 11(2): 9–22.

    Article  Google Scholar 

  • Davidson, W.H. and McFetridge, D.G. (1985) ‘Key characteristics of the choice of international technology transfer mode’, Journal of International Business Studies 16(2): 5–22.

    Article  Google Scholar 

  • Dichtl, E., Koeglmayr, H.-G. and Mueller, S. (1990) ‘International orientation as a precondition for export success’, Journal of International Business Studies 21(1): 23–40.

    Article  Google Scholar 

  • Dichtl, E., Leibold, M., Koeglmayr, H.-G. and Mueller, S. (1984) ‘The export decision of small and medium-sized firms: a review’, Management International Review 24(2): 49–60.

    Google Scholar 

  • Dow, D. (2000) ‘A note on psychological distance and export market selection’, Journal of International Marketing 8(1): 51–64.

    Article  Google Scholar 

  • Evans, J. and Mavondo, F.T. (2002) ‘Psychic distance and organizational performance: an empirical examination of international retailing operations’, Journal of International Business Studies 33(3): 515–532.

    Article  Google Scholar 

  • Evans, J., Treadgold, A. and Mavondo, F. (2000) ‘Explaining export development through psychic distance’, International Marketing Review 17(2): 164–168.

    Article  Google Scholar 

  • Freedom House (2000) ‘Freedom in the World’, [www document] http://www.freedomhouse.com/uploads/FIWrank7502.xls. (accessed 17 December 2003).

  • Geraci, V.J. and Prewo, W. (1977) ‘Bilateral trade flows and transport costs’, The Review of Economics and Statistics 59(1): 64–74.

    Article  Google Scholar 

  • Gleditsch, K.S. (2003) ‘Modified Polity P4 and P4D Data’, [www document] http://weber.ucsd.edu/~kgledits/Polity.html. (accessed 17 December 2003).

  • Goerzen, A. and Beamish, P. (2003) ‘Geographic scope and multinational enterprise performance’, Strategic Management Journal 24(13): 1289–1306.

    Article  Google Scholar 

  • Gomes, L. and Ramaswamy, K. (1999) ‘An empirical examination of the form of the relationship between multinationality and performance’, Journal of International Business Studies 30(1): 173–188.

    Article  Google Scholar 

  • Grimes, J.E. and Grimes, B.F. (eds.) (1996) Ethnologue Language Family Index, Summer Institute of Linguistics: Dallas, TX.

    Google Scholar 

  • Gruber, W.H., Mehta, S. and Vernon, R. (1970) ‘The R&D factor in international trade and international investment of US industries’, Journal of Political Economy 75(1): 20–37.

    Article  Google Scholar 

  • Hallen, L. and Wiedersheim-Paul, F. (1984) ‘The Evolution of Psychic Distance in International Business Relationships’, in I. Hagg and F. Wiedersheim-Paul, Between Market and Heirarchy. University of Uppsala, Uppsala, Sweden, 15–27.

    Google Scholar 

  • Harris, I., Mews, S., Morris, P. and Shepherd, J. (1992) Contemporary Religions: A World Guide, Longman: Harlow.

    Google Scholar 

  • Henisz, W.J. (2000) ‘The institutional environment for economic growth’, Economics and Politics 12(1): 1–31.

    Article  Google Scholar 

  • Hofstede, G. (1980) Cultural Consequences: International Differences in Work Related Values, Sage: Beverly Hills, CA.

    Google Scholar 

  • Hofstede, G. and Bond, M.H. (1988) ‘The Confucius connection: from cultural roots to economic growth’, Organizational Dynamics 16(4): 4–21.

    Article  Google Scholar 

  • Holzmuller, H.H. and Kasper, H. (1990) ‘The decision-maker and export activity: a cross-national comparison of the foreign orientation of Austrian Managers’, Management International Review 30(3): 217–230.

    Google Scholar 

  • Holzmuller, H.H. and Kasper, H. (1991) ‘On a theory of export performance: personal and organisational determinants of export trade activities observed in small and medium-sized firms’, Management International Review 31(Special Issue): 45–70.

    Google Scholar 

  • Johanson, J. and Vahlne, J.-E. (1977) ‘The internationalization process of the firm: a model of knowledge development and increasing foreign market commitments’, Journal of International Business Studies 8(1): 23–32.

    Article  Google Scholar 

  • Johanson, J. and Wiedersheim-Paul, F. (1975) ‘The internationalization of the firm: four Swedish cases’, Journal of Management Studies 12(October): 305–322.

    Article  Google Scholar 

  • Kim, W.C. and Hwang, P. (1992) ‘Global strategy and multinationals’ entry mode choice’, Journal of International Business Studies 23(1): 29–53.

    Article  Google Scholar 

  • Klein, S. and Roth, V.J. (1990) ‘Determinants of export channel structure: the effects of experience and psychic distance’, International Marketing Review 7(5): 27–38.

    Article  Google Scholar 

  • Kobrin, S.J. (1976) ‘The environmental determinants of foreign direct manufacturing investment: an ex-post empirical analysis’, Journal of International Business Studies 7(2): 29–42.

    Article  Google Scholar 

  • Kogut, B. and Singh, H. (1988) ‘The effect of national culture on the choice of entry mode’, Journal of International Business Studies 19(3): 411–432.

    Article  Google Scholar 

  • Leamer, E.E. and Storper, M. (2001) ‘The economic geography of the internet age’, Journal of International Business Studies 32(4): 641–665.

    Article  Google Scholar 

  • Lee, D.-J. (1998) ‘The effect of cultural distance on the relational exchange between exporters and importers: the case of Australian exporters’, Journal of Global Marketing 11(4): 7–22.

    Article  Google Scholar 

  • Linder, S.B. (1961) An Essay on Trade and Transformation, John Wiley & Sons: New York.

    Google Scholar 

  • Linnemann, H. (1966) An Econometric Study of International Trade Flows, North-Holland: Amsterdam.

    Google Scholar 

  • Luo, Y., Shenkar, O. and Nyaw, M.-K. (2001) ‘A dual parent perspective in international joint ventures: lessons from a developing economy’, Journal of International Business Studies 32(1): 41–58.

    Article  Google Scholar 

  • Nordstrom, K.A. and Vahlne, J.-E. (1994) ‘Is the Globe Shrinking? Psychic Distance and the Establishment of Swedish Subsidiaries During the Last 100 Years’, in M. Landeck (ed.) International Trade: Regional and Global Issues, St Martin's Press: New York, pp 41–56.

    Google Scholar 

  • O’Brien, J. and Palmer, M. (eds.) (1993) The State of Religion Atlas, Simon & Schuster: New York.

    Google Scholar 

  • Rauch, J.E. (1999) ‘Networks versus markets in international trade’, Journal of International Economics 48(1): 7–35.

    Article  Google Scholar 

  • Rauch, J.E. and Trindade, V. (2002) ‘Ethnic Chinese networks in international trade’, Review of Economics and Statistics 84(1): 116–130.

    Article  Google Scholar 

  • Ronen, S. and Shenkar, O. (1985) ‘Clustering countries on attitudinal dimensions: a review and synthesis’, Academy of Management Review 10(3): 435–454.

    Google Scholar 

  • Schwartz, S.H. (1994) ‘Beyond Individualism/Collectivism: New Cultural Dimensions of Values’, in U. Kim, H.C. Triandis, C. Kagitcibasi, S.-C. Choi and G. Yoon (eds.), Individualism and Collectivism: Theory, Method, and Applications, Sage: Thousand Oaks, CA, 18 pp: 85–119.

    Google Scholar 

  • Shenkar, O. (2001) ‘Cultural distance revisited: towards a more rigorous conceptualization and measurement of cultural differences’, Journal of International Business Studies 32(3): 519–536.

    Article  Google Scholar 

  • Simonin, B.L. (1999) ‘Transfer of marketing know-how in international strategic alliances: an empirical investigation of the role and antecedents of knowledge ambiguity’, Journal of International Business Studies 30(3): 463–490.

    Article  Google Scholar 

  • Sivakumar, K. and Nakata, C. (2001) ‘The stampede toward Hofstede's framework: avoiding the sample design pit in cross-cultural research’, Journal of International Business Studies 32(3): 555–575.

    Article  Google Scholar 

  • Srivastava, R.K. and Green, R.T. (1986) ‘Determinants of bilateral trade flows’, Journal of Business 59(4): 623–640.

    Article  Google Scholar 

  • Stottinger, B. and Schlegelmilch, B.B. (1998) ‘Explaining export development through psychic distance: enlightening or elusive?’ International Marketing Review 15(5): 357–372.

    Article  Google Scholar 

  • Subramanian, A. and Wei, S.-J. (2003) ‘The WTO Promotes Trade Strongly But Unevenly’, NBER working paper series, NBER: Cambridge, MA, Paper 10024.

  • Tihanya, L., Griffith, D.A. and Russell, C.J. (2005) ‘The effect of cultural distance on entry mode choice, international diversification, and MNE performance: a meta-analysis’, Journal of International Business Studies 36(3): 270–283.

    Article  Google Scholar 

  • Triandis, H.C. (2000) ‘Culture and conflict’, International Journal of Psychology 35(2): 145–152.

    Article  Google Scholar 

  • Tushman, M.L. (1978) ‘Technical communication in R&D laboratories: the impact of project work characteristics’, Academy of Management Journal 21(4): 624–644.

    Article  Google Scholar 

  • United Nations (1995a) Statistical Yearbook, United Nations Statistical Division: New York.

  • United Nations (1995b) ‘Social Indicator Data’, [www document] http://www.un.org/depts/unsd/social/. (accessed 16 June 1998).

  • Vahlne, J.-E. and Wiedersheim-Paul, F. (1977) ‘Psychic distance: an inhibiting factor in international trade’, Centre for International Business Studies, Department of Business Administration, University of Uppsala, working paper no. 2.

  • Welch, D.E., Welch, L.S. and Marschan-Piekkari, R. (2001) ‘The persistent impact of language on global operations’, Prometheus 19(3): 193–209.

    Article  Google Scholar 

  • Whaling, F. (ed.) (1987) Religion in Today's World: The Religious Situation of the World from 1945 to the Present Day, T & T Clark: Edinburgh.

    Google Scholar 

  • Winer, B.J. (1971) Statistical Principles in Experimental Design, McGraw-Hill: New York.

    Google Scholar 

  • Zhao, H., Luo, Y. and Suh, T. (2004) ‘Transaction cost determinants and ownership-based entry mode choice: A meta-analytical review’, Journal of International Business Studies 35(6): 524–544.

    Article  Google Scholar 

Download references

Acknowledgements

We thank JIBS Departmental Editor Professor J Myles Shaver and the two anonymous JIBS reviewers for their comments, insights, and suggestions.

Author information

Authors and Affiliations

  1. Centre for the Practice of International Trade, Melbourne Business School, University of Melbourne, Carlton, Victoria, Australia

    Douglas Dow

  2. School of Commerce, The University of Adelaide, South Australia

    Amal Karunaratna

Authors
  1. Douglas Dow
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Amal Karunaratna
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Douglas Dow.

Additional information

Accepted by J Myles Shaver, Departmental Editor, 20 April 2006. This paper has been with the authors for two revisions.

Appendices

Appendix A. Coding

Languages

A major language for a given country is defined as any language that can be spoken by more than 20% of the population (i.e., widely used second languages qualify), or a language that holds a special official status within the country (e.g., English in India and several African nations). (For Nigeria and Zambia no single language exceeded the 20% threshold. For these countries, languages above 10% were deemed major.) For the countries used in our analyses, 34 languages qualified as a major language for at least one of the 38 countries. These languages have been grouped into a hierarchy of families, branches, first level sub-branches and second level sub-branches based on Grimes and Grimes’ (1996) more substantial classification of 6809 languages. An abridged version of the Grimes’ language classification is provided in Appendix B

Distance between major languages (L1)

The distance between the two closest major languages for each pair of countries is based on that classification system and is coded as follows:

5:

Different families

4:

Same family but different branches

3:

Same branch but different at the first sub-branch level

2:

Same sub-branch at the first level but different at the second level

1:

Same language

Incidence of one country's major language(s) in other countries (L2 and L3)

The second and third language indicators measure the proportion of the population in one country who are able to speak the major languages of another country. L2 concerns the incidence of country i's major language(s) in country j, and L3 concerns the incidence of country j's major language(s) in country i. The indicators are coded as follows:

5:

Less than 1%

4:

Greater than or equal to 1% but less than 5%

3:

Greater than or equal to 5% but less than 50%

2:

Greater than or equal to 50% but less than 90%

1:

Greater than or equal to 90%

Languages within the same lowest level sub-branch of language families are counted as the same language for this item (e.g., variations of German such as High German, Bavarian, and Schwyzerdutsch are grouped together). Where a country has more than one major language, a weighted average is calculated.

Religions

A major religion is defined as any religion to which more than 20% of the population claim an affiliation. Within a religion that is deemed ‘major’, only the divisions that represent at least one quarter of that religion's adherents are deemed relevant for this analysis. For example, Sunni Muslims must represent at least 25% of a county's Muslims to be considered a ‘major’ group. Similarly, only denominations and sects that represent at least one quarter of that religion's division are considered ‘major’. For example, Baptists must represent at least 25% of a country's Protestants to be considered in the analyses. If no divisions or denominations/sects reach that threshold, the largest division and denomination/sect will be used. For the countries used in our analyses, 8 religions, 9 corresponding divisions, and 12 denominations/sects qualified as ‘major’ for at least one of the 38 countries. These religions have been grouped into a hierarchy of families, religions, divisions of religions and denominations/sects based on a range of sources (Barrett, 1982; Whaling, 1987; Harris et al., 1992; O’Brien and Palmer, 1993). The classification of religions is provided in Appendix B.

Distance between major religions (R1)

The distance between the two closest major religions for each pair of countries is based on that classification system and is coded as follows:

5:

Different families of religion

4:

Same family but different religions

3:

Same religion but different division

2:

Same division but different denomination or sect

1:

Same denomination or sect

Incidence of one country's major religion(s) in other countries (R2 and R3)

The second and third religion indicators measure the proportion of the population in one country who belong to the same religion as a significant proportion of another country. R2 concerns the incidence of country i's major religion(s) in country j, and R3 concerns the incidence of country j's major religion(s) in country i. The indicators are coded as follows:

5:

Less than 1%

4:

Greater than or equal to 1% but less than 5%

3:

Greater than or equal to 5% but less than 50%

2:

Greater than or equal to 50% but less than 90%

1:

Greater than or equal to 90%

Where a country has more than one major religion, a weighted average is calculated.

Appendix B. Classification schemes

Languages

Table A1

Table 9 Table a1
Full size table

Religions

Table A2

Table 10 Table a2
Full size table

Appendix C. Formulae for psychic distance stimuli

Language

LangF is the single-factor solution, using principal component analysis, for L1, L2, and L3.

  • L1 is the score for the distance between the major languages, as per Appendices A and B

  • L2 is the score for the incidence of country i's major language in country j, as per Appendices A and B

  • L3 is the score for the incidence of country j's major language in country i, as per Appendices A and B

Religion

ReligF is the single-factor solution, using principal component analysis, for R1, R2, and R3.

  • R1 is the score for the distance between the major religions, as per Appendices A and B

  • R2 is the score for the incidence of country i's major religion in country j, as per Appendices A and B

  • R3 is the score for the incidence of country j's major religion in country i, as per Appendices A and B

Education

EduF (abs)=absolute value of EduF.

  • EduF is the single-factor solution, using principal component analysis, for E1ij, E2ij and E3ij.

where E1i=100 minus percentage of illiterate adults (15+, male and female) for the exporting country (i) and E1j=100 minus percentage of illiterate adults (15+, male and female) for the importing country (j).

where E2i and E2j are the number of students in second-level education/estimated population under the age of 15 for the exporting country (i) and the importing country (j) respectively.

where E3i and E3j are the number of students in third-level education/estimated population under the age of 15 for the exporting country (i) and the importing country (j) respectively.

Industrial development

Ind DevF (abs)=absolute value of Ind DevF.

  • Ind DevF is the single-factor solution, using principal component analysis, for I1ij, I2ij, I3ij, I4ij, I6ij, I7ij, I8ij, I9ij and I10ij.

where I1i and I1j are the GDP per capita ($US) for the exporting country (i) and the importing country (j) respectively.

where I2i and I2j are the energy consumption per capita (kg of coal equivalent) for the exporting country (i) and the importing country (j) respectively.

where I3i and I3j are passenger cars per 1000 people for the exporting country (i) and the importing country (j) respectively.

where I4i and I4j=100−percentage of labour force in agriculture for the exporting country (i) and the importing country (j) respectively.

where I5i and I5j are manufacturing as a percentage of GDP for the exporting country (i) and the importing country (j) respectively.

where I6i and I6j are the percentages of population living in urban areas for the exporting country (i) and the importing country (j), respectively.

where I7i and I7j are daily newspaper circulation per 1000 people for the exporting country (i) and the importing country (j) respectively.

where I8i and I8j are radios per 1000 people for the exporting country (i) and the importing country (j) respectively.

where I9i and I9j are telephones per 1000 people for the exporting country (i) and the importing country (j) respectively.

where I10i and I10j are televisions per 1000 people for the exporting country (i) and the importing country (j), respectively.

Democracy

DemF (abs)=absolute value of DemF.

  • DemF is the single-factor solution, using principal component analysis, for D1ij, D2ij, D3ij and D4ij.

where D1i and D1j are Henisz's (2000) POLCON measure (0–1, average score for 1990 to 1994) for the exporting country (i) and the importing country (j), respectively.

where D2i and D2j are Bollen's Polity IV – Polity measure (−10 to +10 scale, average score for 1993 to 1998) for the exporting country (i) and the importing country (j), respectively.

where D3i and D3j are the Freedom House political rights scale (1–7; reverse-coded, average score for 1993–1998) for the exporting country (i) and the importing country (j) respectively.

where D4i and D4j are the Freedom House civil liberties scale (1–7; reverse-coded, average score for 1993 to 1998) for the exporting country (i) and the importing country (j) respectively.

Socialism

where Social i and Social j are the average of Beck et al.'s (2001) Right–Centre–Left scale for the chief executive's political party and the largest political party (0–1, average score for 1993–1998) for the exporting country (i) and the importing country (j), respectively.

Hofstede's dimensions of culture

where PDI i and PDI j are Hofstede's power distance score for the exporting country (i) and the importing country (j) respectively.

where UAI i and UAI j are Hofstede's uncertainty avoidance scores for the exporting country (i) and the importing country (j) respectively.

where IDV i and IDV j are Hofstede's individuality scores for the exporting country (i) and the importing country (j) respectively.

where MAS i and MAS j are Hofstede's masculinity scores for the exporting country (i) and the importing country (j) respectively.

where LTO i and LTO j are Hofstede's long term orientation scores for the exporting country (i) and the importing country (j) respectively.

where VarPDI is the variance of Hofstede's power distance scale, PDI i ; VarUAI is the variance of Hofstede's UAI scale, UAI i ; VarIDV is the variance of Hofstede's individuality scale, IDV i ; and VarMAS is the variance of Hofstede's masculinity scale, MAS i .

Rights and permissions

Reprints and permissions

About this article

Cite this article

Dow, D., Karunaratna, A. Developing a multidimensional instrument to measure psychic distance stimuli. J Int Bus Stud 37, 578–602 (2006). https://doi.org/10.1057/palgrave.jibs.8400221

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1057/palgrave.jibs.8400221

Keywords

Search

Navigation