Cross-cultural Methodologies for Organizational Research Using Self-Report Measures: A Best Practices Approach

Brian S. Schaffer


Christine M. Riordan


University of Georgia

Department of Management

Terry College of Business

Athens, GA  30602-6256




            There are a number of methodological issues that can be problematic in cross-cultural studies that use self-report survey instruments. This paper reviews the organizational research literature to identify the common practices being used in relation to these issues. A framework is established for this analysis that involves three stages related to the research process. These stages are 1) the development of the research question, 2) the alignment of the research contexts, and 3) the validation of the research instruments. A sample of cross-cultural studies was examined in the context of these three stages, and served as a basis for the identification of some “best-practices” that are meant to deal with cross-cultural complexities.



International perspectives are becoming more prevalent in today’s study of organizations. As business continues to take a global outlook, theoretical constructs commonly used in domestic research will need to be applied to new cross-cultural arenas. Recently, researchers have begun to take notice of some important methodological issues associated with the use of survey instruments in cross-cultural research (e.g., Cheung & Rensvold, 1999; Riordan & Vandenberg, 1994). These issues can have a strong impact on a study’s results, and on the subsequent interpretation of those results. If researchers ignore the difficulties inherent in using self-report questionnaires in cross-cultural studies, the field as a whole may be subject to misinterpreting some findings that may actually be meaningless, inconclusive, or misguiding.

The purposes of this article are threefold. First, we provide a review of these important methodological issues in cross-cultural research. It should be noted that many of these issues have previously been identified by other researchers as being threats to validity in a variety of field-research settings (e.g., Cook & Campbell, 1979; Campbell & Stanley, 1963). Our goal here is to relate these threats specifically to cross-cultural settings. Second, we review the most common practices currently being used in the administration of self-report instruments in cross-cultural research. From a sample of cross-cultural studies (see Appendix for articles included in this sample), we identified practices that were found to be most typical, and we present some problems associated with these practices. And third, we identify some “best practices” for administering these self-report instruments.

We developed a framework, consisting of three stages, for comparing and evaluating the various methodologies. These stages are 1) the development of the research question, 2) the alignment of the research contexts, and 3) the validation of the research instruments. Our comparisons and evaluations of different cross-cultural studies, in the context of these three stages, served as a basis for the identification of  “best practices”.

Stage 1: Development of Cross-Cultural Research Questions

In this stage, researchers must decide whether their study will be approached from an etic or an emic perspective, and they must establish the way in which they will define or consider culture in the context of their research. The emic approach, as it applies to cross-cultural research, focuses on studying a construct from within a specific culture, and understanding that construct as the people from within that culture understand it (Gudykunst, 1997). The etic approach, on the other hand, involves developing an understanding of a construct by comparing it across cultures using predetermined characteristics. Researchers have recognized the importance of both of these approaches.

From a measurement standpoint, criteria in an emic approach are relative to the characteristics of the particular culture being studied, and so differences or variability in one setting may not have the same significance as they would in another setting. The etic approach is more suited for broader analyses, usually involving two or more cultures. The main assumption in etic research is that there is a shared frame of reference across culturally diverse samples, and that construct measurement can be applied to all of the samples in the same way, ultimately allowing for more generalizability (Ronen & Shenkar, 1988). Since cross-cultural organizational research often involves comparative studies between two or more cultures, much of the research is conducted with an etic perspective. From a measurement standpoint, criteria in an etic approach are considered absolute or universal, with less attention being given to the internal characteristics of a particular culture (Berry, 1989). The use of an etic approach may be the most practical for organizational researchers, in terms of financial limitations and time pressures. However, if etic constructs are used to make cross-cultural comparisons, researchers risk not capturing all of the culture-specific (emic) aspects of the construct relative to a particular culture in the study. On the other hand, if an emic strategy is used, a more precise and thorough description of the construct within one culture is obtained, but the ability to make cross-cultural comparisons becomes more difficult (Church & Katibak, 1988).

When researchers fail to consider the emic aspects of the different cultures involved in their studies, and when they assume that the concepts being tested exist across all cultures, they are applying imposed etics, or pseudo etics (Barry, 1990). This problem has been recognized as being fairly common in cross-cultural research (see Ongel & Smith, 1994), and in our review we found a similar pattern. A best-practice suggestion for dealing with this problem is to use a combined emic-etic approach, or a derived etic approach. Rather than identifying emic dimensions from one culture and simply applying those dimensions to the other culture(s) in the study, a derived etic approach requires researchers to first attain emic knowledge (usually through observation, and/or participation) about all of the cultures in the study (Berry, 1990; Cheung, Conger, Hau, Lew, & Lau, 1992). This allows them to put aside their culture biases, and to become familiar with the relevant cultural differences in each setting. When this is done, it may then be possible to make cross-cultural links between the emic aspects of each culture. While some emic dimensions will emerge in all cultures, some dimensions may emerge in only one of the cultures (Cheung, et. al, 1992). Only where there are observed commonalities can cross-cultural comparisons be appropriately made. The comparisons here are considered derived etics since they are derived by first doing emic research in each of the cultures, and not just one (Berry, 1990).

In the first stage of developing the research question, researchers must also determine how the term culture will be operationalized in their study. In many of the studies we examined, “country” or “nation” was used as a proxy for culture (e.g., Kim, Park, & Suzuki, 1990). While country may in fact be a suitable and convenient indicator of culture, using it as the sole operationalization of culture has limitations. For example, in a cross-cultural study, there may be certain within-country differences that are actually greater than between-country differences along certain dimensions (Samiee & Jeong, 1994). While some countries like Japan have a relatively homogeneous culture, other countries like Canada and Switzerland may have more distinct sub-cultures within their borders (Peterson & Smith, 1997). Recognizing that there may be other delimiters of culture besides country, Peterson and Smith (1997) provided a comprehensive list of cultural determinants meant to assist researchers with this issue. These determinants include language, religion, technology, industry, national boundaries, and climate. Adding these characteristics to ‘country’ as possible delimiters of culture can enhance the integrity of cross-cultural research. A best practice in this area, then, would involve researchers establishing which characteristics are relevant to their specific research context, and then using them to more accurately assess cultural boundaries.

Stage 2: Alignment of Research Contexts

The alignment of research contexts refers to actions that researchers can take to assure congruence between the different cultures being studied. In our review, two main issues seemed to be particularly relevant to this stage. First, researchers should establish equivalency among the samples in their cross-cultural studies, and second, they should maintain consistency in the survey administration procedures used across different samples.

Because researchers sometimes have limited access to organizations, it is often difficult for them to establish the equivalency of samples. Many times, the choice of samples is arbitrary and opportunistic (Yu, Keown, & Jacobs, 1993), with convenience being the deciding factor. Samples can differ in terms of demographic characteristics, in terms of environmental characteristics, and in terms of respondents’ levels of experience related to both their work history and to their exposure to certain measurement instruments. All of these differences become a concern when they are not relevant to the research topic being studied. Demographic differences in gender, age, education, and marital status can all be sources of unwanted variation. In trying to match organizational structures for research design purposes, researchers are often forced to sacrifice demographic proportions across two or more cultures (Chikudate, 1997). Environmental characteristics become a concern in cross-cultural research when differences exist in terms of social, economic, legal, education, and/or industry structures (Janssens, Brett, & Smith, 1995). We found that cross-cultural studies sometimes fail to control for these types of factors. Finally, differences in respondents’ experience levels can be problematic. Because cross-cultural studies often involve highly dissimilar groups (Van de Vijver & & Leung, 1997), respondents from different samples are likely to have different levels of past work experience, in terms of both tenure and breadth of exposure to different functional areas (e.g., Schneider & De Meyer, 1991). In addition, differences may exist in terms of respondents’ experience levels with measurement instruments and with general testing procedures, both of which can be undesirable performance-related sources of variation (Van de Vijver & Leung, 1997).

To assure sample equivalency, researchers should try to minimize the effects of these sample differences in their cross-cultural studies. If samples cannot be matched on the basis of some predetermined variables, then the variables should be controlled for methodologically (Sekaran & Martin, 1982; Hudson, Baraket, & LaForge, 1959).

Another important issue related to contextual alignment is whether the administration of surveys is consistent across the different research settings. This involves technical equivalence, and includes establishing equivalent data collection methods, instrument formats, instrument scaling procedures, and survey-timing across the samples (Ortega & Richey, 1998; Sekaran & Martin, 1982; Yu et al., 1993). For example, if items on a written instrument were read to a sample of respondents in one culture (because of literacy levels), and administered in the standard way in another culture, the measurement reliability and validity of the study could be compromised, thus making an interpretation of the results difficult (Ortega & Richey, 1998). Similarly, when surveys are administered to each sample at different time periods, the sample of respondents receiving the later survey  might be subject to a higher attrition rate (Kok et al., 1995), and the results of the study could be distorted because of a category of respondents that were present in the first sample, but less representative in the second sample.

For the purposes of establishing contextual alignment in cross-cultural research, we identified the following best practices related to sample equivalence and technical equivalence. First, as mentioned before, efforts should be made to match samples on the basis of demographics, environmental factors, and levels of experience. However, researchers may not always be able to use a matching strategy, since resources and subjects have varying degrees of availability, and since different cultural groups may sometimes have contrasting profiles in terms of these characteristics (Van de Vijver & Leung, 1997). Therefore, researchers should statistically control for any differences that remain between the samples (e.g., Peterson et al. 1995).  Second, researchers can use insiders’ and outsiders’ perspectives together to help identify some problematic contextual issues. For example, researchers might work together with top executives from a different culture to clear up ambiguities about items on an employee survey (see Johns & Xie, 1998). This type of interaction between outsiders and insiders can be particularly helpful in alleviating some of the problems that could lead to respondents’ feelings of uneasiness with the interventions. Third, explicit instructions and examples should be included in all cross-cultural survey instruments, and these should be provided to each of the samples in a consistent manner. For example, if an instrument is translated into another language for a sample, then the instructions should also be translated. Finally, instruments can be used in pilot studies, when possible, to help identify contextual problems. These studies can help researchers identify unforeseen issues related to survey administration, such as translation problems and specific ambiguities associated with item phraseology (see Smith, Peterson, & Wang, 1996; Kanter & Corn, 1994; Gowan & Ochoa, 1998).

Stage 3: Validation of the Research Instruments

The final stage in our framework involves the validation of the research instrument. Researchers must ensure that the measures of a construct developed in one culture can be applied to another culture before they can establish a basis for theoretical comparisons. For this objective, establishing both semantic equivalence and measurement equivalence are essential. In establishing semantic equivalence, the goal for the researcher is to ensure that the multiple versions of a self-report instrument used cross-culturally fully account for linguistic differences among the samples. The main concern should be for the meaning of each item after translation to be consistent across the different respondents from each culture. This is rarely an easy task. Even in situations where researchers and linguists work together to produce a common version of an instrument for a cross-cultural study, there is still the possibility that remaining differences in meaning will have an influence on some of the study’s findings (Holtzman, 1968). For measurement equivalence  to be established, constructs and their meanings should apply equally across the different cultures being studied (conceptual equivalence), and respondents across different cultures should be consistent in their interpretations or calibrations of the scoring formats (scaling equivalence) (Riordan & Vandenberg, 1994).

We identified the following best practices for establishing semantic equivalence. First, researchers should employ back-translation when they intend to administer an instrument to respondents who speak a foreign language. In this process, bilingual experts translate the instrument from language A to language B, and then back again to language A (Ortega & Richey, 1998). The purpose of this double translation is to allow experts to examine each survey item on both versions to establish meaning conformity. If inconsistencies are found, then items can be reworded or, if necessary, eliminated. Second, researchers should avoid using certain figures of speech, terminologies, or phrases in their survey instruments that may be common in the home-base culture, but unfamiliar to other cultures. This may be particularly important when the second culture is English-speaking, and is responding to an English version of the survey. For example, respondents from non-U.S. cultures may interpret the phrase, “I put everything I have into my work”, in a number of different ways. Does the phrase refer to how much effort you put forth while doing your job, or does it mean taking all of your possessions and applying them to the work you do? Third, cross-cultural researchers need to explicitly describe the procedures they used to establish semantic equivalence. Most of the studies in our review included statements about measurement equivalence, while only some mentioned semantic equivalence. In order for cross-cultural studies to be properly evaluated and replicated, these kinds of statements become necessities.

For assessing measurement equivalence, we refer to two best-practice statistical approaches that have been previously established by researchers. These are 1) covariance structure analysis (e.g., Yang et al., 2000; Cheung & Rensvold, 1999; Ryan et al., 1999; Riordan & Vandenberg, 1994), and 2) item response theory (e.g., Butcher & Han, 1996; Hambleton & Kanjee, 1995; Ellis, Becker, & Kimmel, 1993; Hulin & Mayer, 1985). Typically, researchers have used a multiple-groups covariance structure analysis (if comparing more than two samples) to examine measurement equivalence, because such an analysis allows for direct testing of equivalency assumptions through a series of nested constraints placed upon selected parameters across the samples (Riordan & Vandenberg, 1994; Ryan et al., 1999). Measurement equivalence, including both conceptual and scaling equivalence, can be examined in a series of increasingly restrictive hypothesis tests. Cross-cultural researchers have normally determined measurement equivalence by observing the same number of constructs and items loading on a factor, along with an invariance of factor loadings (Ryan et al., 1999). Importantly, these approaches to examining measurement equivalence allow the researchers to specify constraints a priori, with some theoretical justification for proceeding with the analyses (Vandenberg & Lance, 2000). Riordan & Vandenberg’s (1994) examination of  three work-related measurement instruments across samples of Korean and American employees is an example of this covariance structure analytic approach.

Another approach for dealing with measurement equivalence, and for identifying items that do not function similarly across different cultures, is to use statistical methods based on item response theory, or IRT (Ellis et al., 1993). IRT is a theory-grounded process that models the distribution of respondents’ success at the item level (Fan, 1998). This process produces item statistics independent of respondent statistics, and person statistics independent of the survey items administered. This invariance property of the theory has made it possible to solve important measurement problems that have been difficult to address with other frameworks, and it has established the basis for theoretically justifying the use of IRT models (Fan, 1998). The models generated from this process describe the relationship between a respondent’s observable response to an item and the respondent’s standing on the unobservable trait measured by the survey instrument (Ellis et al., 1993). An item characteristic curve (ICC) can then be used to display this relationship, showing the response probability as a function of the trait measured by the instrument. When ICCs estimated separately for the same item for two samples are the same, the item is said to function equivalently for both groups, and when the ICCs differ by more than sampling error, then there exists what is called differential item functioning, or DIF (Ellis et al., 1993; Hambleton & Swaminathan, 1985; Hulin, Drasgow & Parson, 1983; Lord, 1980; Thissen, Steinberg & Wainer, 1988, 1989). DIF is an indication of a lack of measurement inequivalence for a particular item in a survey. DIF items should therefore not be used to compare samples in cross-cultural research, because such comparisons would be based on response tendencies rather than on true differences in the construct of interest.


The increased international focus in organizational research has required many researchers to apply commonly used survey instruments to new cross-cultural settings. This paper has reviewed some of the complexities involved in administering these instruments to culturally diverse samples. Specifically, we have presented three stages of the research process, and for each stage we have identified some best practices which are meant to deal with these complexities. These best practices will hopefully be employed by researchers as a checklist for verifying the validity and methodological soundness of their cross-cultural practices. 


Articles Examined for Best Practices

Aycan, Z., Kanungo, R.N. & Sinha, J.B. (1999). Organizational culture and human resource management practices: The model of culture fit. Journal of Cross-Cultural Psychology, 30(4): 501-526.

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Buda, R. & Elsayed-Elkhouly, S.M. (1998). Cultural differences between Arabs and Americans: Individualism-collectivism revisited. Journal of Cross-Cultural Psychology, 29(3): 487-492.

Cheung, P.C., Conger, A.J.,Hau, K., Lew, W.J.F., and Lau, S. (1992). Development of the multi-trait personality inventory (MTPI): Comparison among four Chinese populations. Journal of Personality Assessment, 59(3): 528-551.

Chikudate, N., (1997). Exploring the life-world of organizations by linguistic oriented phenomenology in sub-cultural analysis of organizations: A comparison between Japanese and U.S. Banks. Management International Review, 37(2): 169-183.

Chiu, R.K. & Kosinski, F.A. (1999). The role of affective dispositions in job satisfaction and work strain: Comparing collectivist and individualist societies. International Journal of Psychology, 34(1): 19-28.

Church, A.T. & Katigbak, M.S.(1988). The emic strategy in the identification and assessment of personality dimensions in a non-western culture. Journal of Cross-Cultural Psychology, 19(2): 140-163. 

Earley, P.C. (1994). Self or group? Cultural effects of training on self-efficacy and performance. Administrative Science Quarterly, 39: 89-117.

Farh, J., Dobbins, G.H., & Cheng, B. (1991). Cultural relativity in action: A comparison of self-ratings made by Chinese and U.S. workers. Personnel Psychology, 44, 129-147.

Farh, J., Earley, P.C. & Lin, S. (1997). Impetus for action: A cultural analysis of justice and organizational citizenship behavior in Chinese society. Administrative Science Quarterly, 42(3): 421-444.

Gedajlovic, E.R. & Shapiro, D.M. (1998). Management and ownership effects: Evidence from five countries. Strategic Management Journal, 19, 533-553.

Gowan, M.A. & Ochoa, C.L. (1998). Parent-country national selection for the maquiladora industry in Mexico: Results of a pilot study. Journal of Management Issues, 10, 103-118.

Gudykunst, W.B., Gao, G., Nishida, T., Nadamitsu, Y. & Sakai, J. (1992). Self-monitoring in Japan and the United States. In S. Iwawaki, Y. Kashima & K. Leung (Eds.), Innovations in Cross-Cultural Psychology: Selected Papers from the Tenth International Conference of the International Association for Cross-Cultural Psychology. Berwyn, PA: Swets & Zeitlinger.

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Janssens, M., Brett, J.M., & Smith, F.J. (1995). Confirmatory cross-cultural research: Testing the viability of a corporation-wide safety policy. Academy of Management Journal, 38, 364-382.

Johns, G. & Xie, J.L. (1998). Perceptions of absence from work: People’s Republic of China versus Canada. Journal of Applied Psychology, 83, 515-530.

Kanter, R.M. & Corn, R.I. (1994). Do cultural differences make a business difference? Contextual factors affecting cross-cultural relationship success. Journal of Management Development, 13, 5-23.

Kim, K.I., Park, H. & Suzuki, N. (1990). Reward allocations in the United States, Japan, and Korea: A comparison of individualistic and collectivistic cultures. Academy of Management Journal, 33(1): 188-198.

Love, K.G., Bishop, R.C., Heinisch, D.A. & Montei, M.S. (1994). Selection across two cultures: Adapting the selection of American assemblers to meet Japanese job performance demands. Personnel Psychology, 47: 837-846.

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Morris, M.W., Williams, K.Y., Leung, K., Larrick, R., Mendoza, M.T., Bhatnagar, D., Li, J., Kondo, M., Luo, J. Hu, J. (1998). Conflict management style: Accounting for cross-national differences. Journal of International Business Studies, 29(4): 729-748.

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Riordan, C.M. & Vandenberg, R.J. (1994). A central question in cross-cultural research: Do employees of different cultures interpret work-related measures in an equivalent manner? Journal of Management, 20, 643-671.

Ryan, A.M., Chan, D., Ployhart, R.E., & Slade, L.A. (1999). Employee attitude surveys in a multinational organization: Considering language and culture in assessing measurement equivalence. Personnel Psychology, 52: 37-58.

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Smith, P.B., Peterson, M.F., & Wang, Z.M. (1996). The manager as mediator of alternative meanings: A pilot study from China, the USA and UK. Journal of International Business Studies, 27, 115-137.

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Teagarden, M. B. & Von Glinow, M.A. (1997). Human resource management in cross-cultural contexts: Emic practices versus etic philosophies. Management International Review, 37 (1) special issue: 7-20.

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Xie, J.L. (1996). Karasek’s model in the People’s Republic of China: Effects of job demands, control, and individual differences. Academy of Management Journal, 39, 1594-1618.

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Yu, J.H., Keown, C. F., & Jacobs, L. W. (1993). Attitude scale methodology: Cross-cultural implications. Journal of International Consumer Marketing, 6(2): 47-64.



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