Assignment II This assignment requires the creation of an at least 5-page APA compliant multiple source essay citing at most five peer reviewed full text journal articles fetched from ProQuest, BE & T, InfoTrac, and Academic OneFile. The essay should demo

An assessment of the measurement

of performance in international

business research

G Tomas M Hult1, David J Ketchen Jr2, David A Griffith1, Brian R Chabowski3, Mary K Hamman1, Bernadine Johnson Dykes1, Wesley A Pollitte1 and S Tamer Cavusgil1

1Eli Broad Graduate School of Management,

Michigan State University, East Lansing, MI,

USA; 2Auburn University, Auburn, USA; 3University of Tulsa, Tulsa, USA

Correspondence: GTM Hult, Eli Broad Graduate School of Management, Michigan State University, East Lansing, MI 48824-1121, USA. Tel: þ1 517 353 4336; Fax: þ1 517 432 1009; E-mail: [email protected]

Received: 21 May 2005 Revised: 29 July 2007 Accepted: 24 September 2007 Online publication date: 22 May 2008

Abstract A sizeable body of international business (IB) research is devoted to building

knowledge about the determinants of organizational performance. A key precursor to accurately diagnosing why some organizations succeed in the

international marketplace while others struggle is operationalizing performance

appropriately. Yet, to date, no systematic investigation has considered how well IB research measures performance. We examine the measurement of perfor-

mance in 96 articles published in the Academy of Management Journal,

Administrative Science Quarterly, Journal of Marketing, Journal of Marketing Research, Journal of International Business Studies, Management Science, Organiza-

tion Science, and the Strategic Management Journal between 1995 and 2005. The

findings reveal that most studies do not measure performance in a manner that captures the multifaceted nature of the construct. We describe the implications

of these results, and offer suggestions for improving future practice.

Journal of International Business Studies (2008) 39, 1064– 1080. doi:10.1057/palgrave.jibs.8400398

Keywords: performance measurement; financial performance; operational performance; overall effectiveness performance

INTRODUCTION Why some firms outperform others in the global arena is a primary research question within the field of international business (IB) (e.g., Hitt, Hoskisson, & Kim, 1997; Tallman & Li, 1996). As a result, performance is a key dependent variable of interest to IB scholars (e.g., Brouthers, 2002; Glaister & Buckley, 1999). However, although a great deal of research has focused on performance, IB researchers lament that the field has ‘‘yielded little by way of conclusive results’’ (Gomes & Ramaswamy, 1999: 173), often drawing ‘‘seemingly conflicting findings’’ (Kotabe, Srinivasan, & Aulakh, 2002) regarding the determinants of performance. Fre- quently, when a body of findings is equivocal, methodological problems are at issue (e.g., Ferguson & Ketchen, 1999; Lewin & Minton, 1986; Short, Ketchen, & Palmer, 2002). One possible contributor to this lack of performance findings in the IB literature derives from the diverse and complex operationalization of the performance construct (Ariño, 2003; March & Sutton, 1997; Venkatraman & Ramanujam, 1986). While all business disciplines must grapple with performance’s multidimensional and multilevel

Journal of International Business Studies (2008) 39, 1064 –1080 & 2008 Academy of International Business All rights reserved 0047-2506

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nature, operationalizing performance in the IB context is particularly difficult (e.g., Ariño, 2003) owing to cross-border variations in accounting standards, the nature of firm boundaries, and the geographic scope of operations (e.g., Fahy, Hooley, Cox, Beracs, Fonfara, & Snoj, 2000).

For example, an investigation by Hult, Ketchen and Slater (2004) of a multinational enterprise’s supply chains revealed that the extent to which these chains focus on acquiring knowledge was positively related to subjectively measured cycle time performance, but was not related to objec- tively measured cycle time performance. In other words, supply chain participants believe that acquiring more knowledge reduces cycle time, but company records suggest that it does not. Had these authors used only the subjective measure of performance from primary data sources, they would have concluded that knowledge acquisition is a key lever for reducing cycle time in global supply chains. Had they relied only on the objective measure of performance from secondary data sources, they likely would have contended that knowledge acquisition matters little in the cycle time context. These results highlight the value of measuring performance via multiple indicators and multiple data sources to enhance the understand- ing of antecedents of the performance construct (cf. Ariño, 2003; Venkatraman & Ramanujam, 1986).

In this study, we extend Venkatraman and Ramanujam’s (1986) performance-measurement framework, which focuses on multiple indicators and multiple data sources, for the international arena by incorporating level of analysis as a third dimension. Level of analysis is included, given:

(1) the increased development of unique strategies used by firms operating in the global market- place at various operating levels;

(2) the movement of academic researchers toward deconglomeration of strategy in the assessment of performance (e.g., Ariño, 2003; Hult et al., 2004; Robinson & Pearce, 1988); and

(3) the growing importance within IB inquiry of heterarchical organizational structures (Hedlund, 1994).

The specific purpose of our paper is twofold. First, we assess the measurement of performance in IB research relative to three dimensions: type of data sources (primary and secondary1), type of measure (financial, operational, and overall effectiveness), and level of analysis (firm, strategic business unit (SBU), and inter-organizational). Next, based on the

assessment of the literature related to performance, we offer guidelines for future research that are intended to assist the field in maximizing its potential for building knowledge regarding why some firms outperform others in the global arena. This study therefore follows Hitt, Boyd, and Li (2004), who argue that scholarly endeavors are needed to identify methodological dilemmas and propose remedies in order for fields to advance. The next section outlines the methodology used, fol- lowed by the findings, a discussion of the implica- tions that can be drawn, and our conclusions.

METHODOLOGY To assess performance research in the IB literature, a series of study parameters were established to set the boundaries for the research undertaken in this paper. These study parameters are established to identify clearly what was undertaken, and to bring out possible limitations in a transparent manner. First, for the purpose of this study, IB was defined as a firm-level phenomenon occurring across national borders (Morrison & Inkpen, 1991; Nehrt, Truitt, & Wright, 1970; Ricks, 1985; Ricks, Toyne, & Martinez, 1990; Werner & Brouthers, 2002; Wright and Ricks, 1994). Second, studies examining performance – be it at the level of the firm, the SBU, or the inter- organizational unit – were examined. Third, a time period of examination was established. Given that the ‘‘citation half-life’’ of premier journal articles is approximately 10 years (cf. Cabell, 2004), a con- servative approach was undertaken, and an 11-year window (i.e., 1995–2005) was used.2 This approach follows the argument that the incremental gain of analyzing articles beyond 11 years after publication provides considerably less benefit to the advance- ment of knowledge (Bergh, Perry, & Hanke, 2006; Chung, Cox, & Mitchell, 2001). This ensures that the majority of research that remains influential is covered in the study.

To select the journals to be included in the study, we followed the following process. First, we reviewed the journals associated with the core disciplines of IB (i.e., finance, marketing, manage- ment and economics) (Chandy & Williams, 1994). Among this set of journals, we chose only those journals that were considered the top-rated journals in their respective disciplines (e.g., DuBois & Reeb, 2000; Gómez-Mejia & Balkin, 1992; Hult, Neese, & Bashaw, 1997; Tahai & Meyer, 1999; Trieschmann, Dennis, Northcraft, & Niemi, 2000; Werner & Brouthers, 2002).3 Next, we considered only those journals that had a focus on IB research (Werner &

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Brouthers, 2002). Not surprisingly, the final list of journals contained primarily marketing and man- agement journals, given the increasing influence of these two disciplines in the field of IB (Chandy & Williams, 1994). Given these criteria, the journals in our sample were Academy of Management Journal, Administrative Science Quarterly, Journal of Marketing, Journal of Marketing Research, Journal of International Business Studies, Management Science, Organization Science, and Strategic Management Journal. Lastly, to be included in the study, articles had to measure performance as a dependent variable in an international context at either the firm, SBU, or inter-organizational level of analysis. Using these parameters, 96 articles were identified for inclusion (see Table 1), with JIBS as the largest contributor, with 56 articles (58% of our sample).

The data collection proceeded in accordance with content analysis guidelines (cf. Kolbe and Burnet, 1991; Marshall & Rossman, 1989; Patton, 1990). Four scholars participated in coding the articles. The list of articles was divided into two halves, and two scholars independently coded each article within each half. Differences were resolved through discussion (cf. Kolbe & Burnet, 1991). As an additional check, 20 articles were randomly selected (10 from each half) and coded by alternate scholars. Inter-rater reliability (as measured by percentage of agreement) was 92.5%, which is above accepted standards (e.g., Kolbe & Burnet, 1991), and also compares favorably with similar studies (e.g., 93% in Shook, Ketchen, Hult, & Kacmar, 2004).

Each article was categorized by performance type (i.e., financial, operational, overall effectiveness). Financial performance centers on outcome-based indicators assumed to reflect economic goals, inclusive of accounting-based and market-based metrics (cf. Venkatraman & Ramanujam, 1986). In this study, financial performance includes overall profitability (indicated by ratios such as return on investment, return on sales, return on assets, and return on equity), profit margin, earnings per share, stock price, sales growth, growth of foreign sales, and Tobin’s Q. Operational performance refers to non-financial dimensions, and focuses on opera- tional success factors that might lead to financial performance (cf. Venkatraman & Ramanujam, 1986). Operational performance includes both product–market outcomes (including market share, efficiency, new product introduction and innova- tion, and product/service quality) and internal process outcomes (productivity, employee retention

and satisfaction, and cycle time). Measurement of overall effectiveness reflects a wider conceptualiza- tion of performance, and includes reputation, survival, perceived overall performance, achieve- ment of goals, and perceived overall performance relative to competitors (cf. Lewin & Minton, 1986; Venkatraman & Ramanujam, 1986).

Articles were also coded based on data source (i.e., primary vs secondary) (cf. Venkatraman & Ramanujam, 1986), with full documentation on how performance was measured (i.e., cross-sectionally, lagged, or longitudinally). In addition, the level(s) of analysis (firm, SBU, inter-organizational unit) at which performance was measured were assessed. Studies measuring performance using multiple performance types, multiple data sources, or at multiple levels of analysis were coded accordingly.

RESULTS

Types of Data Source Table 2 presents the results for types of data source used (i.e., primary or secondary, where, following Venkatraman and Ramanujam’s (1986) terminol- ogy, primary refers to subjective data and secondary data refers to objective data). Of the 96 studies examined, only two studies used both types of data source (i.e., Daily, Certo, & Dalton, 2000; Song, Xie, & Dyer, 2000). Each of the remaining studies used either primary measures (55 studies) or secondary measures (39 studies).

To further assess the data sources used in IB research, the data were examined across time periods. Splitting the sample based upon time resulted in 38.5% of the studies (37/96) being included in the 1995–1999 time period and 61.5% of the studies (59/96) in the 2000–2005 time period.4 The findings of the time segmentation analysis indicate that the proportion of studies in the overall sample that used primary data to measure performance was 62.1% (23/37) during 1995–1999 and 54.2% (32/59) during 2000–2005.

Types of Measure Findings related to the types of measure used (i.e., financial, operational and overall effectiveness) are presented in Tables 2–5. Our findings indicate that only seven studies (7.3% of the 96 studies assessed) used all three types of performance measurement. The use of two types of performance measure in a given study was more common, but studies of this sort constituted only 32.3% (31/96) of performance research over the 11-year period (with

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Table 1 Studies included in the assessment

Academy of Management Journal (n¼10) Tallman and Li (1996) Zahra, Ireland, and Hitt (2000) Wan and Hoskisson (2003) Hitt, Hoskisson, and Kim (1997) Delios and Beamish (2001) Lu and Beamish (2004) Autio, Sapienza, and Almeida (2000) Shrader (2001) Aulakh, Kotabe, and Teegen (2000) Tihanyi, Johnson, Hoskisson, and Hitt (2003)

Administrative Science Quarterly (n¼1) Luo (2001)

Journal of International Business Studies (n¼56) *Bird and Beechler (1995) Morosini, Shane, and Singh (1998) Cadogan, Diamantopolous, and Siguaw (2002) Birkinshaw and Morrison (1995) Gomes and Ramaswamy (1999) Evans and Mavondo (2002) Dussauge and Garrette (1995) Luo and Peng (1999) Kotabe, Srinivasan, and Aulakh (2002) Gencturk and Aulakh (1995) Money and Graham (1999) Nobeoka, Dyer, and Madhok (2002) Johnson (1995) Myers (1999) Pothukuchi, Damanpour, Choi, Chen, and Park (2002) Lee and Beamish (1995) Pan, Li, and Tse (1999) Skarmeas, Katsikeas, and Schlegelmilch (2002) Murray, Kotabe, and Wildt (1995) Brouthers, Werner, and Matulich (2000) Ariño (2003) *Lyles and Salk (1996) Fahy, Hooley, Cox, Beracs, Fonfara, and Snoj (2000) Buck, Filatotchev, Demina, and Wright (2003) Aulakh, Kotabe, and Sahay (1996) Reuer (2000) Capar and Kotabe (2003) Holm, Eriksson, and Johanson (1996) *Luo, Shenkar, and Nyaw (2001) Child, Chung, and Davies (2003) Hooley, Cox, Shipley, Fahy, Beracs, and Kolos (1996) Fey and Björkman (2001) Contractor, Kundu, and Hsu (2003) Makino and Delios (1996) Lau and Ngo (2001) Doukas and Lang (2003) Anand and Delios (1997) Lenartowicz and Roth (2001) Hewett, Roth, and Roth (2003) Dyer and Song (1997) Li, Lam, and Qian (2001) Zhang, Cavusgil, and Roath (2003) Gómez-Mejia and Palich (1997) Pantzalis (2001) Choi and Beamish (2004) Katrishen and Scordis (1998) Peng and York (2001) Dhanaraj, Lyles, Steensma, and Tihanyi (2004) Luo (1998) *Brouthers (2002) Knight and Cavusgil (2004) Makino and Beamish (1998) *Brouthers and Xu (2002) Venaik, Midgley, and Devinney (2005) Mishra and Gobeli (1998) Buckley, Clegg, and Wang (2002) Cadogan et al. (2002)

Journal of Marketing (n¼9) Bello and Gilliland (1997) Capron and Hulland (1999) Homburg, Workman, and Jensen (2002) Dekimpe, Francois, Gopalakrishna, Lilien, and Van den Bulte (1997) Song, Xie, and Dyer (2000) Zou and Cavusgil (2002) Samiee and Anckar (1998) Hewett and Bearden (2001) *Morgan, Kaleka, and Katsikeas (2004)

Journal of Marketing Research (n¼2) Kumar, Scheer, and Steenkamp (1995) Simester, Hauser, Wernerfelt, and Rust (2000)

Management Science (n¼2) MacDuffie, Sethuraman, and Fisher (1996) Ettlie (1998)

Organization Science (n¼1) Dyer and Chu (2003)

Strategic Management Journal (n¼15) Arora and Gambardella (1997) Lu and Beamish (2001) Carpenter, Pollock, and Leary (2003) Fiegenbaum, Shaver, and Yeung (1997) *Robins, Tallman, and Fladmoe-Lindquist (2002) Goerzen and Beamish (2003) Delios and Beamish (1999) Seth, Song, and Pettit (2002) Dhanaraj and Beamish (2004) Daily, Certo, and Dalton (2000) Vermeulen and Barkema (2002) Kim, Hoskisson, and Wan (2004) Geringer, Tallman, and Olsen (2000) Brouthers, Brouthers, and Werner (2003) Makino, Isobe, and Chan (2004)

Note: The use of measures of all three types – financial, operational, and overall effectiveness – was rare; only 7.92% of the studies assessed these three forms of performance. The studies that did so are marked with an asterisk.

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It is important to note that although the mea- sures listed under financial performance may appear to be secondary measures often found on financial statements, not all studies measured these items using secondary data. Indeed, 33 of the 69 studies using financial measures of performance used primary data. Of those, over 50% used sales- based measures of performance, such as sales growth and return on sales, and approximately 25% used return on investment.

Level of Analysis Given the interrelated nature of the three perfor- mance dimensions investigated, level of analysis issues were examined in relation both to types of data source and to types of measure (see Tables 2 and 5). The data indicate that studies focusing on IB issues have relied to a greater degree on primary rather than secondary measures (93 vs 53 operatio- nalizations). Primary measures of performance at the level of inter-organizational units were most often measured by respondents’ perceived overall performance (80% of studies). Four of the five studies of interorganizational unit performance using secondary data employed financial measures, although the actual measures varied across studies. Both for studies using primary data and for studies using secondary data, the most common SBU performance measures were sales based: 66% of SBU performance studies using primary data and 75% of those using secondary data employed sales- based measures. Examining the data longitudinally, studies of firm and financial performance were 38.5% (5/13) during 1995–1999 and 30.0% (9/30) during 2000–2005, whereas studies of SBU and financial performance were 75.0% (6/8) during 1995–1999 and 63.6% (7/11) during 2000–2005.T

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Performance measurement in IB research G Tomas M Hult et al 1068

Journal of International Business Studies

The results for types of measure used across levels of analysis are reported in Tables 2–5. Table 2 indicates that the largest body of studies (44.8% or 43/96) focused on the firm level of analysis and used financial measures of performance. As shown in Table 3, the only studies to combine operational performance and overall effectiveness measures were studies of inter-organizational unit perfor- mance. As presented in Table 4, only one study measured performance at all three levels (i.e., Shrader, 2001), six studies (6.3%) measured perfor- mance at two levels, and 92.7% (89/96) of studies measured performance at one level. These results

suggest a lack of breadth in relation to performance measurement across units of analysis. Table 5 indicates the most frequently used measures by level of analysis and measurement type. The measures most often used for financial perfor- mance, regardless of level of analysis, were sales based. Finally, the dominance of measuring finan- cial performance at the firm level was consistent throughout the 11-year period covered in our study. The proportion of studies using financial measures was 70.3% (26/37) during the first period and 72.9% (43/59) in the second period. Additionally, the proportion of studies using firm performance

Table 4 Use of multiple measures: firm, SBU, and inter-organizational unit

Financial

performance

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Overall effectiveness

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aShrader (2001). Note: Rows do not necessarily sum to total because some studies used multiple measures across financial, operational, and overall effectiveness performance types.

Table 5 Commonly used measures by performance type

Financial performancea Operational performance Overall effectiveness performance

Firm Sales based: 44%

Return on assets: 40%

Market share: 47% Reputation: 30%

Strategic business unit Sales based: 68%

Return on investment: 47%

Market share: 46% Performance relative to competitors: 50%

Perceived overall performance: 33%

Inter-organization unit Sales based: 62%

Profitability: 31%

Productivity: 44%

Market share: 33%

Product/service quality: 33%

Perceived overall performance: 71%

Total Sales based: 52%

Return on assets: 29%

Profitability: 26%

Market share: 44%

Productivity: 20%

Perceived overall performance: 47%

Performance relative to competitors: 20%

a‘‘Sales based’’ includes sales volume, foreign sales/total sales, sales growth, and growth in foreign sales.

Table 3 Use of multiple measures: financial, operational and overall effectiveness

Firm Strategic business unit (SBU) Inter-organizational unit Total

Financial and operational performance 9 10 2 21

Financial and overall effectiveness performance 4 3 3 7

Operational and overall effectiveness performance 0 0 3 3

All three 3a 1b 3c 7

aBrouthers (2002), Brouthers and Xu (2002), Morgan et al. (2004). bBird and Beechler (1995). cLuo et al. (2001), Lyles and Salk (1996), Robins et al. (2002). Note: Rows do not necessarily sum to total because some studies used multiple measures across firm, SBU, and inter-organizational performance types.

Performance measurement in IB research G Tomas M Hult et al 1069

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measures was 48.6% (18/37) in the first period and 61.0% (36/59) in the second period.

IMPLICATIONS Our findings indicate that five broad issues related to IB performance measurement should be consid- ered in future IB research. Clearly, adhering to all aspects of what Table 6 summarizes in terms of the implications of the findings is unlikely in every IB research project. However, we view the issues in Table 6, which are discussed in this section of the paper, as an ‘‘action plan’’ for improving the measurement of performance within the IB field in the same spirit as the main thrust in the work by

Venkatraman and Ramanujam (1986). IB research- ers should therefore attempt to incorporate as many of the action items as possible into their research while balancing research rigor with prac- tical relevance.

Overcome Reliability Issues with Primary and Secondary Data Sources Some researchers may be suspicious of the validity of primary data sources, and concerned about bias introduced with subjectivity, but performance research in international contexts indicates that primary data measuring performance can be more reliable than secondary data in certain contexts –

Table 6 Action plan for performance research in international business

Overcome reliability issues with primary and secondary data sources

Use primary data sources in the following conditions:

K When financial measures are likely to be unreliable or are unavailable

K When privately held firms are studied, and secondary data cannot be accessed

K When comparability of different types of firm is difficult to achieve owing to heterogeneous attributes

(e.g., firm objectives, culture, context)

K Data concerning specific units of analysis (e.g., SBU) cannot be obtained from secondary sources

K Managers are reluctant to provide secondary data due to competitive or proprietary concerns

Consider these factors when using cross-national financial and accounting data:

K Earnings capitalization, book value, and residual income valuation models

K Accruals and cash accounting structures (e.g., common accounting standards)

Improve international business research by measuring multiple types of performance

To measure performance as a multidimensional/multilevel construct:

K Use measures that capture objective financial, operational, overall effectiveness performance whenever possible

K Measure performance using different units of analysis – firm, SBU, and inter-organizational – as demanded by the research

setting studied

Make valid causal inferences with proper longitudinal measures of performance

Use longitudinal data under the following conditions:

K Whenever possible, use performance data taken from a period of t + n, where t is the time period when the (primary and/or

secondary) antecedent variables were collected, and n equals any time later than the collection of the (primary and/or

secondary) antecedent variables (additionally, for each step in a multi-step model, use data taken from a period later than the

previous variables for each step, if possible)

K Collect performance data across organizations and over (multiple) time periods whenever possible

K When panel data are unavailable, collect primary performance data at a time later than the data on explanatory variables (t + n)

Improve inferential specificity in relation to level of analysis

Utilization of the extant literature

K Empirical findings being drawn for comparison are at similar level of analysis

K Theoretical development based upon arguments established in the extant literature are at the same level of analysis

Resolve concerns with endogeneity and selection

Use two-stage least squares (2SLS):

K When the dependent variable is correlated with the error term in the regression equation

K When criterion variable is nonrandom and level effect impacts only on intercept term

Use ‘‘Heckit’’:

K When the dependent variable is observed for portion of sample. and is nonrandom

K When dependent variable and explanatory variables (intercept as well as independent variables) are nonrandom

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such as emerging markets as China (e.g., Lukas, Tan, & Hult, 2001) – where objective measures are often unreliable. Further, the use of primary data for measuring performance in IB is particularly appropriate when the researcher is aiming to identify not only the goals associated with a specific strategy but also the understanding and interpretation of an organization’s performance goals by managers (Brouthers, 2002). In situations where firms (and managers) are hesitant to provide secondary financial, operational, or overall effec- tiveness performance data, collecting primary data provides IB researchers with a better ability to understand the values that a manager may place on specific financial, operational, or overall effective- ness performance measures. In fact, some research- ers contend that, given the different goals inherent across firms, secondary measures can be misleading as to the firms’ focus on the performance measures analyzed, thus potentially making primary mea- sures more realistic than secondary ones in certain cases (Robinson & Pearce, 1988; Zhang, Cavusgil, & Roath, 2003).

Grounded in the notion that managerial percep- tions and actions may influence a firm’s res- ponses to its environment (cf. Child, 1972), the premise that perceptions among managers differ across countries was introduced early in the IB literature (e.g., Vogel, 1976). Generally, culture (e.g., national, organizational, professional, group) and national wealth have been found to explain many perceptual differences among managers, across countries, across firms, and across functional areas (Hofstede, Deusen, Mueller, & Charles, 2002; Leung, Bhagat, Buchan, Erez, & Gibson, 2005; Neelankavil, Mathur, & Zhang, 2000). Further, whether analyzing managerial perceptions of short-term financial plan- ning (Gentry, Mehta, Bhattacharyya, Cobbaut, & Scaringella, 1979), influences on a firm’s capital structure (Wald, 1999) or external conditions influ- encing firm operations (Miller, 1993), the institu- tional environment in which managers function has a fundamental and systematic role in influencing managerial perceptions of risk (Makhija & Stewart, 2002). The sole use of primary measures of perfor- mance may therefore not capture the full dimen- sions of performance (it may also result in single- source bias and common method variance con- cerns). This leads to the need for secondary (objective) measures of performance in IB research to supplement the limitations that measures of performance based on managerial perceptions may exert in cross-country measurement.

While overcoming some of the limitations of primary measures of performance, the use of secondary measures of performance is not without limitations. Specifically, the influence of differing, and at times competing, accounting standards has been noted to shape how performance is perceived and measured within the IB context (Ashbaugh & Olsson, 2002; Ball, Kothari, & Robin, 2000; Buck, Filatotchev, Demina, & Wright, 2003; Hung, 2000; Kachelmeier & Shehata, 1997). International firms are often subject to multiple institutional contexts, and therefore typically operate under heteroge- neous accounting standards (exceptions to this may include exporters who operate from a single country). For example, differences in disclosure standards exist among domestic and foreign firms listed on the New York Stock Exchange and the Securities and Exchange Commission (Huddart, Hughes, & Brunnermeier, 1999). Similarly, in a study spanning 21 countries, Hung (2000) found that accrual accounting negatively affected the value of financial statements in countries with little shareholder protection, but did not have an influence in countries with strong shareholder protections in place. The complications associated with accounting measures in a variety of countries leave some researchers to posit that secondary measures of performance are incomparable (and sometimes misleading) (Brouthers, 2002; Brouthers, Brouthers, & Werner, 1999; Buck et al., 2003; Chandler & Hanks, 1993; Fey & Björkman, 2001).

However, the movement toward harmonized standards, such as those offered by the Interna- tional Accounting Standards Board, have dimin- ished differences considerably (Hope 2003). One way to overcome accounting differences in the measurement of performance with secondary data is to restrict samples to firms adopting harmonized standards (although changing exchange rates will still make cross-country comparisons difficult). It is important to note while restricting the sample to firms adopting harmonized standards may intro- duce selection bias issues: for example, if the population of firms that adopt harmonized stan- dards is fundamentally different from those who do not, researchers must interpret the implications of their findings conservatively. Dropping observa- tions from firms or organizational forms that do not operate under harmonized accounting stan- dards is analogous to dropping country contexts from the sample. The researcher must then decide whether or not the research question is still interesting and meaningful in the absence of

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observations from these countries. For example, if the researcher is concerned primarily with entry mode or international expansion, confining analy- sis to firms with a common parent country and, in turn, the same accounting regime is unlikely to jeopardize the integrity of findings unless the goal is to generalize beyond companies listed in that country. In some cases, country-level fixed effects to control for the differences in accounting stan- dards across countries and allow for a ceteris paribus interpretation may work. Thus opting for percep- tual or overall measures of performance, as argued by Pothukuchi, Damanpour, Choi, Chen, and Park (2002), may be the most reasonable option. In short, the extent to which differences in account- ing standards are a problem depends on the research question, but considering the potential impact of these differences when formulating research questions and study design should be a universal step in the process of IB research.

Overall, using primary or secondary sources of data alone to measure performance does not necessarily capture the entire domain of the construct. It can introduce the possible dilemma of single data source bias and/or lead to inaccurate inferences (as evidenced by the earlier example of Hult et al., 2004). As only two studies in our sample used both types of data, one could conclude that the extant IB research may reveal less about why some firms outperform others than it could if research designs were used that assessed perfor- mance via the use of both primary and secondary measures. Thus, to draw conclusions about perfor- mance in IB research more effectively, building on prior measurement concerns in the literature (e.g., Dess & Robinson, 1984; Glaister & Buckley, 1999; Harris, 2001), we suggest that IB researchers con- sider using both primary and secondary sources of data whenever possible in the measurement of firm performance.

Improve IB Research by Measuring Multiple Types of Performance Our findings indicate that few of the IB studies examined meet the most rigorous standards of specification for performance measurement (cf. Lewin & Minton, 1986; Venkatraman & Ramanujam, 1986). To advance knowledge of how performance is generated in international contexts, and to generate normative conclusions for practitioner use, research should be based on clearly specified measures of type of performance to minimize

misleading results. For instance, Gomes and Ramaswamy (1999), by clearly specifying perfor- mance types, found the influence of multination- ality to be positive with respect to financial performance and negative with respect to an operational performance measure.

Further, although some studies use multiple measures of performance (e.g., Luo, Shenkar, & Nyaw, 2001), these studies often use multiple measures sampled from the same conceptual performance domain (e.g., multiple financial performance mea- sures such as return on assets and return on sales). Thus, rather than examining measures from across the three performance categories (financial, opera- tional and overall effectiveness) to create a multi- dimensional approach, or to test hypotheses at multiple levels of performance, these studies, much like single-metric studies, provide a narrow per- spective of antecedents to performance elements. Such analyses can lead to inappropriate inferences when generalized, as well as not providing the robustness necessary for fully understanding the relationships between antecedents of specified aspects of performance.

The use of a single performance metric (or multiple measures sampled from the same con- ceptual domain) may help determine the drivers of a specific aspect of performance (Fahy et al., 2000) in relation to a specified research question. These ‘‘unidimensional’’ performance studies are impor- tant first steps in understanding certain perfor- mance-based relationships. However, as knowledge in the IB field deepens, it is important to use multiple types of performance measures to gain a more complete view of the nature of performance (e.g., Gomes & Ramaswamy, 1999). Alternatively, multiple studies testing the same relationships but using different types of performance measure should become a natural ingredient in IB research to advance knowledge. At the same time, it is appropriate to suggest that researchers should consider using measures of multiple types of performance to comprehend more fully the rela- tionships studied. Research can also benefit from devising measures that are more closely tailored to the particular theory being tested (e.g., Reuer & Tong, 2007; Tong & Reuer, 2007).

Make Valid Causal Inferences with Proper Longitudinal Measures of Performance Our findings indicate that the IB literature is dominated by studies that measure performance cross-sectionally as opposed to longitudinally or

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with time lags. Conclusions regarding causality require an inferential leap of faith when using cross-sectional data (cf. March & Sutton, 1997). These inferences of causality can be considerably strengthened when key variables are measured over time (Kotabe et al., 2002). For example, researchers indicate that past profitability is a better predictor of current profitability than country or industry effects (Haar, 1989; Whittington, 1971). These studies generally regressed average performance over the most recent set of years (e.g., 5 years) on a series of country and industry dummy variables and an average of performance for the time period (e.g., 5 years) immediately following. As an inter- esting example of studying performance over time, Brouthers (1998) used pooled cross-sectional times- series analysis that regressed profitability at time t on a series of country and industry dummies with interaction and profitability at time t�1 for 167 firms over 15 years. With this study design, Brouthers (1998) found the effect of past profit- ability to be insignificant, indicating that in prior cross-sectional studies averaging of the ‘‘lagged’’ profitability variable picked up differences across firms rather than across time.

Ideally, longitudinal data should be used to assess the influence of a predictor variable on the criterion variable. The appropriate time lag is of particular importance when using longitudinal research (e.g., 1 year, 3 years, multiple year average). In the case of a time lag, it is critical that researchers match the duration of the lag appro- priately with the specified research question and the theoretical nature of the intended effect. For example, Geringer, Tallman, and Olsen (2000), when examining the performance effects of product and international diversification, argue for a 1-year time lag as it is indicative of the typical planning cycle in their sample (i.e., they theo- retically tied the lag period to the intended antecedent effect). We suggest that researchers should carefully determine (and report) the theo- retical rationale for the selected lag period in relation to the research question (and antecedents) under investigation (cf. March & Sutton, 1997). However, it is important to note that, even with theoretically justified lag effects, causality is often difficult to establish. For example, Cool and Schendel (1987) find that although strategic groups are stable across time periods, perfor- mance across time periods related to these groups is not suggestive of the importance of contextual effects.

Unfortunately, although longitudinal data are strongly preferred for establishing causality, limited data availability and the expense and difficulty of data collection make longitudinal studies rare in IB research. To overcome these limitations, researchers can use various methodological solutions. First, when panel data are not available, researchers could estimate ‘‘seemingly unrelated regression’’ (SUR) models with an unequal number of observa- tions, or analyze the data within ‘‘structural equation models’’ (SEM) to draw causal inferences (assuming that solid theory guides the research). Alternatively, researchers could use dynamic regres- sion models, or models with lagged variables. Further, under circumstances of data limitations, IB research might also benefit from attention to the Granger causality test (cf. Greene, 2003; Gujarati, 2003). While this type of causality is by no means the same as theoretical causality, evidence that changes in explanatory variables do consistently precede changes in the dependent variable makes a stronger case for inferring theoretical causality.

In summary, cross-sectional measurement of performance is often insufficient to support the causal inferences that researchers desire to make in performance studies. Ideally, performance and its antecedents should be measured longitudinally. By gathering data across time periods, IB researchers can better infer that findings are not unique to the contextual conditions associated with one specific moment in time. However, when longitudinal data are not available, researchers should consider using SUR models, SEM models, dynamic regression models, or Granger causality testing to enhance causal inferences.

Improve Inferential Specificity in Relation to Level of Analysis The findings indicate that IB research varies widely in the level of analysis (i.e., SBU, firm, inter- organizational) in which performance is measured. The variability in the unit of analysis of extant IB performance research creates both empirical and theoretical concerns for the advancement of the field.

Empirically, inconsistencies in levels of analysis across studies could partially explain the contra- dictory findings in the IB literature. For example, a positive influence of antecedent X on performance in study 1 and a lack of effect of antecedent X on performance in study 2 could be attributed to the fact that study 1 focused on the firm level whereas study 2 focused on the inter-organizational level

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(when the same type of performance was measured across studies). Examination of the unit of analysis, when comparing empirical findings across studies, therefore becomes an important concern for draw- ing appropriate inferences.

Arguments made at one level of analysis are not automatically generalizable to other levels of analysis (Klein, Dansereau, & Hall, 1994). An examination of the literature studied indicates that antecedents of performance at one level of analysis are often used to establish similar theore- tical linkages at other units of analysis. Issues of theoretical generalizability abound when extrapo- lating the theoretical arguments from one unit of analysis to another (Klein et al., 1994). The issue of mixed units of analysis in the operationalization of a model is widely criticized, but mixing theore- tical levels of analysis in drawing inferences between antecedents and consequences from one study to another is often overlooked. For example, although a specified antecedent may be positively related to operational performance at an SBU level, the generalization of that relationship to the inter- organizational level may be inappropriate, given differences in the boundary parameters of the initial study.

We therefore argue that scholars, reviewers, and editors carefully examine the level of analysis used in the theoretical development of hypotheses and empirical generalization in relation to IB research focused on performance. This is not to say that all constructs have to be at the same level in a research study; it is very plausible that SBU antecedents can have an effect on firm-level performance (especially if the SBU is of significant size within the firm). However, critically, through diligence in theoretical development and application of extant empirical findings, the alternative explanation embodied by mixed levels of analysis in relation to performance antecedents can be overcome.

Resolve Concerns with Endogeneity and Selection Endogeneity and selection are important problems for IB performance researchers; however, these issues have received limited attention in the IB performance literature (Brouthers, Brouthers, & Werner, 2003; Heckman, 1979; Shaver, 1998). Following Shaver (1998), who demonstrated the importance of appropriately applying selection correction models to account for self-selection in entry mode research, IB research has recently begun to address endogeneity problems formally (e.g., Brouthers et al., 2003). While issues of endogeneity

and selection are not directly related to the measurement of performance in isolation, they are issues that IB researchers universally face in the course of modeling performance, and therefore are deemed relevant to this discussion.

An explanatory variable is endogenous when it is correlated with the error term in the regression equation. Perhaps the most common form of endogeneity that arises in performance research occurs when an individual or organization’s choice of behavior or strategy is nonrandom (or ‘‘self- selected’’). For example, strategic choice may depend in part on a firm’s corporate culture, orga- nizational capabilities, or some other factors that are difficult to measure and cannot be included in the model. Thus the strategic choice construct will be correlated with the error term, and OLS esti- mation will produce biased parameter estimates. The usual econometric response to this problem is two-stage least squares (2SLS) estimation. Alterna- tively, selection occurs when there is incidental truncation, that is, where the dependent variable is observed for a portion of the sample only, and is nonrandom. The usual econometric response to this problem is a selection correction technique similar to that used in Shaver (1998), which was adapted from Heckman (1979) and is now increas- ingly referred to as the ‘‘Heckit’’.5

It is easy to confuse the issues of endogeneity and selection when there is an endogenous binary (dummy) variable. As is the case in the entry mode literature, Shaver (1998) and subsequent papers (e.g., Brouthers et al., 2003) argue that choice of entry mode is nonrandom. In this situation, the researcher must decide whether there is an endogeneity problem, a selection problem, or both. One may conclude that this is an endogeneity problem only because performance is observed, regardless of the choice of entry mode. Yet the issue is not quite as clear as the definitions of endogeneity and selection might imply. When acquisition is chosen, acquisition performance is observed but the performance of a greenfield project may not be observed. The situation could be reversed as well, when a new factory constructed in a greenfield venture is chosen as the unit of analysis instead. In other words, incidental trunca- tion may exist.

Practically, if the researcher believes that entry mode choice is nonrandom but that the choice of entry mode has a level effect only (i.e., influences the intercept term in the performance model only and not the coefficients on other key explanatory

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variables), then a 2SLS estimation strategy for entry mode choice is appropriate. However, if the researcher believes that choice of entry mode should influence both level of performance and other explanatory variables on performance (differ- ent intercept and difference slopes), a selection correction model such as Heckit is appropriate.

Performance research in the IB literature often seeks to explain a phenomenon that is part of a rich system of causal linkages that is sometimes less than clear. Identification for any model related to this stream of IB research is indeed formidable. However, IB by definition examines business phe- nomena in an international context. This implies that the phenomena of interest often occur under differing policy regimes and macroeconomic conditions. If the researcher can identify a ‘‘treat- ment’’ group of organizations (for which a policy change or macroeconomic occurrence can be argued to be a source of exogenous variation in key explanatory variables) and a ‘‘control’’ group (which did not experience the same change, and has at least two periods of data for these two groups, one before and one after the change), divergence in differences estimation is possible (cf. Snyder & Evans, 2006).

In summary, we argue that although IB research may be limited by data availability, statistical tools can often be used to address complications related to endogeneity and selection. As a value-added element, IB researchers should consider and report issues of endogeneity and selection in their studies to allow future research the possibility to more fully explore such issues.

LIMITATIONS AND CONCLUSION Although our research provides a number of new insights, it is not without its limitations. First, in this study we used the data categorization scheme put forth by Venkatraman and Ramanujam (1986), where primary data are considered subjective and secondary data are considered objective. Although this categorization was used to maintain consis- tency with the framework driving our study, it is important to recognize that this approach is limited by the fact that both primary and secondary data can be both subjective and objective. It is therefore important that IB scholars carefully consider the subjective and objective nature of both primary and secondary research when examining performance. Second, we were unable to discern whether there are country-specific patterns in the use of data sources. It would be interesting, for example, to

discover whether studies focused on US-based firms rely more on secondary data than studies focused on firms from other countries.

Third, although our findings offer a general assessment of the measurement of performance in IB research, it is important to recognize that the assessment is limited by the complexity of the phenomena under study. This means that the guidelines we provided in Table 6 and discussed in the implications section must be necessarily flex- ible to allow for the most appropriate study design for the research questions posed. For example, while we recommend multiple types of perfor- mance measurement to comprehend more fully the implications of antecedent factors, we also believe that is important that researchers: (1) measure performance in line with their theoretical model, which is driven by the primary research question under investigation; and (2) build parsimonious models. The former may restrict the necessary types of performance to be measured, and the latter may restrict both antecedents and performance con- structs included for the sake of obtaining, for example, high-quality data. We therefore recom- mend that IB scholars carefully consider the appropriateness of each type of performance measure for their specified research question as well as clearly specify their type of performance measure and its appropriateness.

In conclusion, improving the effective measure- ment of performance is central to advancing the IB literature. This study sought to contribute to this advancement by examining the current status of IB performance measurement. Although limited by its scope (e.g., we did not examine mediators and levels that run between individual decisions and performance), our study provides an assessment of types of data, types of measure and level of analysis of performance measurement in the IB literature. The assessment revealed that performance has been studied in a manner that often overlooks its multidimensional and multilevel nature. While these issues are often mentioned as limitations within the extant literature, we suggest that researchers move toward more effective measure- ment of performance and greater specification and justification of its measurement. To this aim, we offer a set of guidelines for the advancement of effective performance measurement (Table 6). However, it is also important to note that the primary driver of the measurement of performance is the basic research question posed, and so our prescriptions for strengthening IB research

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should be viewed as foundational guidelines, and not as the specified standards to be applied to all IB studies.

ACKNOWLEDGEMENTS We appreciate the guidance provided by Editor-in- Chief Arie Y Lewin and the anonymous reviewers, as well as research funding from the Center for Interna- tional Business Education and Research at Michigan State University (MSU-CIBER).

NOTES 1In this study, to be consistent with the extant

literature, we use Venkatraman and Ramanujam’s (1986) terminology, where ‘‘primary’’ refers to sub- jective data and ‘‘secondary’’ refers to objective data.

2This time period was also selected based upon the initial discussions of measurement invariance in the IB literature initiated by Mullen (1995) and Singh (1995).

3Although the Journal of Consumer Research is considered influential in the marketing field (Werner & Brouthers, 2002), its primary unit of analysis is the consumer, not the firm. Also, no articles in Marketing Science, another important marketing journal, were found to be within the domain of our analysis.

4Based on a reviewer’s comment, we also examined the data using two 5-year periods. The findings were substantively the same: thus we report findings that draw on all 11 years of data.

5See Heckman (1979) for a full explanation of the selection correction procedure, or Shaver (1998) for the adaptation to entry mode research.

REFERENCES Anand, J., & Delios, A. 1997. Location specificity and the

transferability of downstream assets to foreign subsidiaries. Journal of International Business Studies, 28(3): 579–603.

Ariño, A. 2003. Measures of strategic alliance performance: An analysis of construct validity. Journal of International Business Studies, 34(1): 66–79.

Arora, A., & Gambardella, A. 1997. Domestic markets and international competitiveness: Generic and product-specific competencies in the engineering sector. Strategic Manage- ment Journal, 18(6): 53–74.

Ashbaugh, H., & Olsson, P. 2002. An exploratory study of the valuation properties of cross-listed firms’ IAS and US GAAP earnings and book values. The Accounting Review, 77(1): 107–126.

Aulakh, P. S., Kotabe, M., & Sahay, A. 1996. Trust and performance in cross-border marketing partnerships: A beha- vioral approach. Journal of International Business Studies, 27(5): 1005–1032.

Aulakh, P. S., Kotabe, M., & Teegen, H. 2000. Export strategies and performance of firms from emerging economies: Evidence from Brazil, Chile, and Mexico. Academy of Management Journal, 43(3): 342–361.

Autio, E., Sapienza, H. J., & Almeida, J. G. 2000. Effects of age at entry, knowledge intensity, and imitability on international growth. Academy of Management Journal, 43(5): 909–924.

Ball, R., Kothari, S. P., & Robin, A. 2000. The effect of international institutional factors on properties of accounting earnings. Journal of Accounting and Economics, 29(1): 1–51.

Bello, D. C., & Gilliland, D. I. 1997. The effect of output controls, process controls, and flexibility on export channel perfor- mance. Journal of Marketing, 61(1): 22–38.

Bergh, D. D., Perry, J., & Hanke, R. 2006. Some predictors of SMJ article impact. Strategic Management Journal, 27(1): 81–100.

Bird, A., & Beechler, S. 1995. Links between business strategy and human resource management strategy in US-based Japanese subsidiaries: An empirical investigation. Academy of Management Journal, 26(1): 23–46.

Birkinshaw, J. M., & Morrison, A. J. 1995. Configurations of strategy and structure in subsidiaries of multinational corpora- tions. Journal of International Business Studies, 26(4): 729–753.

Brouthers, K. D. 2002. Institutional, cultural and transaction cost influences on entry mode choice and performance. Journal of International Business Studies, 33(2): 203–221.

Brouthers, K. D., Brouthers, L. E., & Werner, S. 2003. Trans- action cost-enhanced entry mode choices and firm perfor- mance. Strategic Management Journal, 24(12): 1239–1248.

Brouthers, L. E. 1998. Explaining MNC profitability: Country- specific, industry-specific and country-industry interactive influences. Management International Review, 38(4): 345–361.

Brouthers, L. E., & Xu, K. 2002. Product stereotypes, strategy and performance satisfaction: The case of Chinese exporters. Journal of International Business Studies, 33(4): 657–677.

Brouthers, L. E., Brouthers, K. D., & Werner, S. 1999. Is Dunning’s eclectic framework descriptive or normative? Journal of International Business Studies, 30(4): 831–844.

Brouthers, L. E., Werner, S., & Matulich, E. 2000. The influence of triad nations’ environments on price-quality product strategies and MNC performance. Journal of International Business Studies, 31(1): 39–62.

Buck, T., Filatotchev, I., Demina, N., & Wright, M. 2003. Insider ownership, human resource strategies and performance in a transition economy. Journal of International Business Studies, 34(6): 530–549.

Buckley, P. J., Clegg, J., & Wang, C. 2002. The impact of inward FDI on the performance of Chinese manufacturing firms. Journal of International Business Studies, 33(4): 637–655.

Cabell, D. W. E. 2004. Cabell’s directory of publishing opportunities in management research. Beaumont, TX: Cabell Publishing.

Cadogan, J. W., Diamantopoulos, A., & Siguaw, J. A. 2002. Export market-oriented activities: Their antecedents and performance consequences. Journal of International Business Studies, 33(3): 615–626.

Capar, N., & Kotabe, M. 2003. The relationship between international diversification and performance in service firms. Journal of International Business Studies, 34(4): 345–355.

Capron, L., & Hulland, J. 1999. Redeployment of brands, sales forces, and general marketing management expertise follow- ing horizontal acquisitions: A resource-based view. Journal of Marketing, 63(2): 41–54.

Carpenter, M. A., Pollock, T. G., & Leary, M. M. 2003. Testing a model of reasoned risk-taking: Governance, the experience

Performance measurement in IB research G Tomas M Hult et al 1076

Journal of International Business Studies

of principals and agents, and global strategy in high- technology IPO firms. Strategic Management Journal, 24(9): 803–820.

Chandler, G. N., & Hanks, S. H. 1993. Measuring the performance of emerging businesses: A validation study. Journal of Business Venturing, 8(5): 391–408.

Chandy, P. R., & Williams, T. 1994. The impact of journals and authors on international business research: A citation analysis of JIBS articles. Journal of International Business Studies, 25(4): 715–728.

Child, J. 1972. Organizational structure, environment and per- formance: The role of strategic choice. Sociology, 6(1): 1–22.

Child, J., Chung, L., & Davies, H. 2003. The performance of cross-border units in China: A test of natural selection, strategic choice and contingency theories. Journal of Interna- tional Business Studies, 34(3): 579–603.

Choi, C.-B., & Beamish, P. W. 2004. Split management control and international joint venture performance. Journal of International Business Studies, 35(3): 201–215.

Chung, K. H., Cox, R. A. K., & Mitchell, J. B. 2001. Citation patterns in the finance literature. Financial Management, 30(3): 99–118.

Contractor, F. J., Kundu, S. K., & Hsu, C.-C. 2003. A three-stage theory of international expansion: The link between multi- nationality and performance in the service sector. Journal of International Business Studies, 34(1): 5–18.

Cool, K. O., & Schendel, D. 1987. Strategic group formation and performance: The case of the US Pharmaceutical industry, 1963–1982. Management Science, 33(9): 1102–1124.

Daily, C., Certo, S., & Dalton, D. 2000. International experience in the executive suite: The path to prosperity? Strategic Management Journal, 21(4): 515–523.

Dekimpe, M. G., Francois, P., Gopalakrishna, S., Lilien, G. L., & Van den Bulte, C. 1997. Generalizing about trade show effectiveness: A cross-national comparison. Journal of Market- ing, 61(4): 55–64.

Delios, A., & Beamish, P. W. 1999. Geographic scope, product diversification, and the corporate performance of Japanese firms. Strategic Management Journal, 20(8): 711–727.

Delios, A., & Beamish, P. W. 2001. Survival and profitability: The roles of experience and intangible assets in foreign subsidiary performance. Academy of Management Journal, 44(5): 1028–1038.

Dess, G. G., & Robinson, R. B. J. 1984. Measuring organizational performance in the absence of objective measures: The case of the privately-held firm and conglomerate business unit. Strategic Management Journal, 5(3): 265–273.

Dhanaraj, C., & Beamish, P. W. 2004. Effect of equity ownership on the survival of international joint ventures. Strategic Management Journal, 25(3): 295–305.

Dhanaraj, C., Lyles, M. A., Steensma, H. K., & Tihanyi, L. 2004. Managing tacit and explicit knowledge transfer in IJVs: The role of relational embeddedness and the impact on performance. Journal of International Business Studies, 35(5): 428–442.

Doukas, J. A., & Lang, L. H. P. 2003. Foreign direct investment, diversification and firm performance. Journal of International Business Studies, 34(2): 153–172.

DuBois, F. L., & Reeb, D. 2000. Ranking the international business journals. Journal of International Business Studies, 31(4): 689–704.

Dussauge, P., & Garrette, B. 1995. Determinants of success in international strategic alliances: Evidence from the global aerospace industry. Journal of International Business Studies, 26(3): 505–530.

Dyer, B., & Song, X. M. 1997. The impact of strategy on conflict: A cross-national comparative study of US and Japanese firms. Journal of International Business Studies, 28(3): 467–493.

Dyer, J. H., & Chu, W. 2003. The role of trustworthiness in reducing transaction costs and improving performance:

Empirical evidence from the United States, Japan, and Korea. Organization Science, 14(1): 57–68.

Ettlie, J. E. 1998. R&D and global manufacturing performance. Management Science, 44(1): 1–11.

Evans, J., & 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.

Fahy, J., Hooley, G., Cox, T., Beracs, J., Fonfara, K., & Snoj, B. 2000. The development and impact of marketing capabilities in Central Europe. Journal of International Business Studies, 31(1): 63–81.

Ferguson, T. D., & Ketchen Jr, D. J. 1999. Organizational configurations and performance: The role of statistical power in extant research. Strategic Management Journal, 20(4): 385–395.

Fey, C. F., & Björkman, I. 2001. The effect of human resource management practices on MNC subsidiary performance in Russia. Journal of International Business Studies, 32(1): 59–75.

Fiegenbaum, A., Shaver, J. M., & Yeung, B. 1997. Which firms expand to the Middle East: The experience of US multi- nationals. Strategic Management Journal, 18(2): 141–148.

Gencturk, E. F., & Aulakh, P. S. 1995. The use of process and output controls in foreign markets. Journal of International Business Studies, 26(4): 755–782.

Gentry, J. A., Mehta, D. R., Bhattacharyya, S. K., Cobbaut, R., & Scaringella, J. 1979. An international study of management perceptions of the working capital process. Journal of Interna- tional Business Studies, 10(1): 28–38.

Geringer, J. M., Tallman, S., & Olsen, D. M. 2000. Product and international diversification among Japanese multinational firms. Strategic Management Journal, 21(1): 51–80.

Glaister, K. W., & Buckley, P. J. 1999. Performance relationships in UK international alliances. Management International Review, 39(2): 123–147.

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

Gomes, L., & Ramaswamy, K. 1999. An empirical examination of the form of the relationship between multinationality and performance. Journal of International Business Studies, 30(1): 173–187.

Gómez-Mejia, L. R., & Balkin, D. 1992. Determinants of faculty pay: An agency theory perspective. Academy of Management Journal, 35(5): 921–955.

Gómez-Mejia, L. R., & Palich, L. E. 1997. Cultural diversity and the performance of multinational firms. Journal of International Business Studies, 28(2): 309–335.

Greene, W. H. 2003. Econometric analysis. Upper Saddle River, NY: Prentice-Hall.

Gujarati, D. N. 2003. Basic econometrics. New York: McGraw-Hill. Haar, J. 1989. A comparative analysis of the profitability

performance of the largest US, European and Japanese multinational enterprises. Management International Review, 29(3): 5–18.

Harris, L. C. 2001. Market orientation and performance: Objective and subjective empirical evidence from UK compa- nies. Journal of Management Studies, 38(1): 17–43.

Heckman, J. J. 1979. Sample selection bias as a specification error. Econometrica, 47(1): 153–162.

Hedlund, G. 1994. A model of knowledge management and the N-form corporation. Strategic Management Journal, 15(Sum- mer Special Issue): 73–90.

Hewett, K., & Bearden, W. O. 2001. Dependence, trust, and relational behavior on the part of foreign subsidiary marketing operations: Implications for managing global marketing operations. Journal of Marketing, 65(4): 51–66.

Hewett, K., Roth, M. S., & Roth, K. 2003. Conditions influencing headquarters and foreign subsidiary roles in marketing activities and their effects on performance. Journal of Interna- tional Business Studies, 34(6): 567–585.

Performance measurement in IB research G Tomas M Hult et al 1077

Journal of International Business Studies

Hitt, M., Boyd, B., & Li, D. 2004. The state of strategic management research and a vision of the future. In D. Ketchen & D. Bergh (Eds), Research methodology in strategy and management: 1–32. New York: Elsevier.

Hitt, M. A., Hoskisson, R. E., & Kim, H. 1997. International diversification: Effects on innovation and firm performance in product-diversified firms. Academy of Management Journal, 40(4): 767–798.

Hofstede, G., Deusen, C. A. V., Mueller, C. B., & Charles, T. A. 2002. What goals do business leaders pursue? A study in fifteen countries. Journal of International Business Studies, 33(4): 785–803.

Holm, D. B., Eriksson, K., & Johanson, J. 1996. Business networks and cooperation in international business relationships. Journal of International Business Studies, 27(5): 1033–1053.

Homburg, C., Workman Jr, J. P., & Jensen, O. 2002. A configurational perspective on key account management. Journal of Marketing, 66(2): 38–60.

Hooley, G., Cox, T., Shipley, D., Fahy, J., Beracs, J., & Kolos, K. 1996. Foreign direct investment in Hungary: Resource acquisition and domestic competitive advantage. Journal of International Business Studies, 27(4): 683–695.

Hope, O. K. 2003. Disclosure practices, enforcement of accounting standards, and analysts’ forecast accuracy: An international study. Journal of Accounting Research, 41(2): 235–272.

Huddart, S., Hughes, J. S., & Brunnermeier, M. 1999. Disclosure requirements and stock exchange listing choice in an international context. Journal of Accounting and Economics, 26(1–3): 237–269.

Hult, G. T. M., Neese, W. T., & Bashaw, R. E. 1997. Faculty perceptions of marketing journals. Journal of Marketing Education, 19(1): 37–52.

Hult, G. T. M., Ketchen Jr, D. J., & Slater, S. F. 2004. Information processing, knowledge development, and strategic supply chain performance. Academy of Management Journal, 47(2): 241–253.

Hung, M. 2000. Accounting standards and value relevance of financial statements: An international analysis. Journal of Accounting & Economics, 30(3): 401–420.

Johnson Jr, J. H. 1995. An empirical analysis of the integration- responsiveness framework: US construction equipment indus- try firms in global competition. Journal of International Business Studies, 26(3): 621–635.

Kachelmeier, S. J., & Shehata, M. 1997. Internal auditing and voluntary cooperation in firms: A cross-cultural experiment. The Accounting Review, 72(3): 407–431.

Katrishen, F. A., & Scordis, N. A. 1998. Economies of scale in services: A study of multinational insurers. Journal of Interna- tional Business Studies, 29(2): 305–324.

Kim, H., Hoskisson, R. E., & Wan, W. P. 2004. Power dependence, diversification strategy, and performance in keiretsu member firms. Strategic Management Journal, 25(7): 613–636.

Klein, K. J., Dansereau, F., & Hall, R. J. 1994. Levels issues in theory development, data collection, and analysis. Academy of Management Review, 19(2): 195–229.

Knight, G. A., & Cavusgil, S. T. 2004. Innovation, organizational capabilities, and the born-global firm. Journal of International Business Studies, 35(4): 124–141.

Kolbe, R. H., & Burnet, M. S. 1991. Content-analysis research: An examination of applications with directions for improving research reliability and objectivity. Journal of Consumer Research, 18(2): 243–250.

Kotabe, M., Srinivasan, S. S., & Aulakh, P. S. 2002. Multi- nationality and firm performance: The moderating role of R&D and marketing capabilities. Journal of International Business Studies, 33(1): 79–97.

Kumar, N., Scheer, L. K., & Steenkamp, J.-B. E. M. 1995. The effects of supplier fairness on vulnerable resellers. Journal of Marketing, 32(1): 54–65.

Lau, C.-M., & Ngo, H.-Y. 2001. Organization development and firm performance: A comparison of multinational and local firms. Journal of International Business Studies, 32(1): 95–114.

Lee, C., & Beamish, P. W. 1995. The characteristics and performance of Korean joint ventures in LDCs. Journal of International Business Studies, 26(3): 637–654.

Lenartowicz, T., & Roth, K. 2001. Does subculture within a country matter? A cross-cultural study of motivational domains and business performance in Brazil. Journal of International Business Studies, 32(2): 305–325.

Leung, K., Bhagat, R. S., Buchan, N. R., Erez, M., & Gibson, C. B. 2005. Culture and international business: Recent advances and their implications for future research. Journal of Interna- tional Business Studies, 36(4): 357–378.

Lewin, A. Y., & Minton, J. W. 1986. Determining organizational effectiveness: Another look, and an agenda for research. Management Science, 32(5): 514–538.

Li, J., Lam, K., & Qian, G. 2001. Does culture affect behavior and performance of firms? The case of joint ventures in China. Journal of International Business Studies, 32(1): 115–131.

Lu, J. W., & Beamish, P. W. 2001. The internationalization and performance of SMEs. Strategic Management Journal, 22(6/7): 565–586.

Lu, J. W., & Beamish, P. W. 2004. International diversification and firm performance: The S-curve hypothesis. Academy of Management Journal, 47(4): 598–609.

Lukas, B., Tan, J. J., & Hult, G. T. 2001. Strategic fit in transitional economies: The case of China’s electronics industry. Journal of Management, 27(4): 409–429.

Luo, Y. 1998. Timing of investment and international expansion performance in China. Journal of International Business Studies, 29(2): 391–408.

Luo, Y. 2001. Antecedents and consequences of personal attachment in cross-cultural cooperative ventures. Adminis- trative Science Quarterly, 46(2): 177–201.

Luo, Y., & Peng, M. W. 1999. Learning to compete in a transition economy: Experience, environment, and performance. Journal of International Business Studies, 30(2): 269–295.

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

Lyles, M. A., & Salk, J. E. 1996. Knowledge acquisition from foreign parents in international joint ventures: An empirical examination in the Hungarian context. Journal of International Business Studies, 27(5): 877–903.

MacDuffie, J. P., Sethuraman, K., & Fisher, M. L. 1996. Product variety and manufacturing performance: Evidence from the international automotive assembly plant study. Management Science, 42(3): 350–369.

Makhija, M. V., & Stewart, A. C. 2002. The effect of national context on perceptions of risk: A comparison of planned versus free-market managers. Journal of International Business Studies, 33(4): 737–756.

Makino, S., & Beamish, P. W. 1998. Performance and survival of joint ventures with non-conventional ownership structures. Journal of International Business Studies, 29(4): 797–818.

Makino, S., & Delios, A. 1996. Local knowledge transfer and performance: Implications for alliance formation in Asia. Journal of International Business Studies, 27(5): 905–927.

Makino, S., Isobe, T., & Chan, C. M. 2004. Does country matter? Strategic Management Journal, 25(10): 1027–1043.

March, J. G., & Sutton, R. I. 1997. Organizational performance as a dependent variable. Organization Science, 8(6): 698–706.

Marshall, C., & Rossman, B. B. 1989. Designing qualitative research. Newbury Park, CA: Sage.

Miller, K. D. 1993. Industry and country effects on managers’ perceptions of environmental uncertainties. Journal of Interna- tional Business Studies, 24(4): 693–714.

Performance measurement in IB research G Tomas M Hult et al 1078

Journal of International Business Studies

Mishra, C. S., & Gobeli, D. H. 1998. Managerial incentives, internalization, and market valuation of multinational firms. Journal of International Business Studies, 29(3): 563–598.

Money, R. B., & Graham, J. L. 1999. Salesperson performance, pay, and job satisfaction: Tests of a model using data collected in the United States and Japan. Journal of International Business Studies, 30(1): 149–172.

Morgan, N. A., Kaleka, A., & Katsikeas, C. S. 2004. Antecedents of export venture performance: A theoretical model and empirical assessment. Journal of Marketing, 68(1): 90–108.

Morosini, P., Shane, S., & Singh, H. 1998. National cultural distance and cross-border acquisition performance. Journal of International Business Studies, 29(1): 137–158.

Morrison, A. J., & Inkpen, A. C. 1991. An analysis of significant contributions to the international business literature. Journal of International Business Studies, 22(1): 143–153.

Mullen, M. R. 1995. Diagnosing measurement equivalence in cross-national research. Journal of International Business Stu- dies, 26(3): 573–596.

Murray, J. Y., Kotabe, M., & Wildt, A. R. 1995. Strategic and financial performance implications of global sourcing strategy: A contingency analysis. Journal of International Business Studies, 26(1): 181–202.

Myers, M. B. 1999. Incidents of gray market activity among US exporters: Occurrences, characteristics, and consequences. Journal of International Business Studies, 30(1): 105–126.

Neelankavil, J. P., Mathur, A., & Zhang, Y. 2000. Determinants of managerial performance: A cross-cultural comparison of the perceptions of middle-level managers in four countries. Journal of International Business Studies, 31(1): 121–140.

Nehrt, L., Truitt, J. F., & Wright, R. 1970. International business research: Past, present, and future. Bloomington, IN: Indiana University Graduate School of Business.

Nobeoka, K., Dyer, J. H., & Madhok, A. 2002. The influence of customer scope on supplier learning and performance in the Japanese automobile industry. Journal of International Business Studies, 33(4): 717–736.

Pan, Y., Li, S., & Tse, D. 1999. The impact of order and mode of market entry on profitability and market share. Journal of International Business Studies, 30(1): 81–104.

Pantzalis, C. 2001. Does location matter? An empirical analysis of geographic scope and MNC market valuation. Journal of International Business Studies, 32(1): 133–155.

Patton, M.Q 1990. Qualitative evaluation and research methods (2nd ed.). Newbury Park, CA: Sage.

Peng, M. W., & York, A. S. 2001. Behind intermediary per- formance in export trade: Transactions, agents, and resources. Journal of International Business Studies, 32(2): 327–346.

Pothukuchi, V., Damanpour, F., Choi, J., Chen, C. C., & Park, S. H. 2002. National and organizational culture differences and international joint venture performance. Journal of Interna- tional Business Studies, 33(2): 243–265.

Reuer, J. J. 2000. Parent firm performance across international joint venture life-cycle stages. Journal of International Business Studies, 31(1): 1–20.

Reuer, J. J., & Tong, T. W. 2007. How do real options matter? Empirical research on strategic investments and firm perfor- mance. Advances in Strategic Management, 24: 145–173.

Ricks, D. A. 1985. International business research: Past, present, and future. Journal of International Business Studies, 16(2): 1–4.

Ricks, D. A., Toyne, B., & Martinez, Z. 1990. Recent develop- ments in international management research. Journal of Management, 16(2): 219–253.

Robins, J. A., Tallman, S., & Fladmoe-Lindquist, K. 2002. Autonomy and dependence of international cooperative ventures: An exploration of the strategic performance of US ventures in Mexico. Strategic Management Journal, 23(10): 881–901.

Robinson, R. B. J., & Pearce, J. A. I. 1988. Planned patterns of strategic behavior and their relationship to business-unit performance. Strategic Management Journal, 9(1): 43–60.

Samiee, S., & Anckar, P. 1998. Currency choice in industrial pricing: A cross-national evaluation. Journal of Marketing, 62(3): 112–127.

Seth, A., Song, K. P., & Pettit, R. R. 2002. Value creation and destruction in cross-border acquisitions: An empirical analysis of foreign acquisitions of US firms. Strategic Management Journal, 23(10): 921–940.

Shaver, J. M. 1998. Accounting for endogeneity when assessing strategy performance: Does entry mode choice affect FDI survival? Management Science, 44(4): 571–585.

Shook, C. L., Ketchen Jr, D. J., Hult, G. T. M., & Kacmar, K. M. 2004. An assessment of the use of structural equation modeling in strategic management research. Strategic Man- agement Journal, 25(4): 397–404.

Short, J. C., Ketchen Jr, D. J., & Palmer, T. B. 2002. The role of sampling in strategic management research on performance: A two-study analysis. Journal of Management, 28(3): 363–385.

Shrader, R. 2001. Collaboration and performance in foreign markets: The case of young high-technology manufacturing firms. Academy of Management Journal, 44(1): 45–61.

Simester, D. I., Hauser, J. R., Wernerfelt, B., & Rust, R. T. 2000. Implementing quality improvement programs designed to enhance customer satisfaction: Quasi-experiments in the United States and Spain. Journal of Marketing Research, 37(1): 102–112.

Singh, J. 1995. Measurement issues in cross-national research. Journal of International Business Studies, 26(3): 597–620.

Skarmeas, D., Katsikeas, C. S., & Schlegelmilch, B. B. 2002. Drivers of commitment and its impact on performance in cross-cultural buyer–seller relationships: The importer’s perspec- tive. Journal of International Business Studies, 33(4): 757–783.

Snyder, S. E., & Evans, W. N. 2006. The impact of income on mortality: Evidence from the social security notch. Review of Economics and Statistics, 88(3): 482–495.

Song, X. M., Xie, J., & Dyer, B. 2000. Antecedents and consequences of marketing managers’ conflict-handling behaviors. Journal of Marketing, 64(1): 50–66.

Tahai, A., & Meyer, M. J. 1999. A revealed preference study of management journals’ direct influences. Strategic Manage- ment Journal, 20(3): 279–296.

Tallman, S., & Li, J. 1996. Effects of international diversity and product diversity on the performance of multinational firms. Academy of Management Journal, 39(1): 179–196.

Tihanyi, L., Johnson, R. A., Hoskisson, R. E., & Hitt, M. A. 2003. Institutional ownership differences and international diversifi- cation: The effects of boards of directors and technological opportunity. Academy of Management Journal, 46(2): 195–211.

Tong, T. W., & Reuer, J. J. 2007. Real options in multinational corporations: Organizational challenges and risk implications. Journal of International Business Studies, 38(2): 215–230.

Trieschmann, J. S., Dennis, A. R., Northcraft, G. B., & Niemi Jr, A.W 2000. Serving multiple constituencies in business schools: MBA program versus research performance. Academy of Management Journal, 43(6): 1130–1141.

Venaik, S., Midgley, D. F., & Devinney, T. M. 2005. Dual paths to performance: The impact of global pressures on MNC subsidiary conduct and performance. Journal of International Business Studies, 36(6): 655–675.

Venkatraman, N., & Ramanujam, V. 1986. Measurement of business performance in strategy research: A comparison of approaches. Academy of Management Review, 11(4): 801–814.

Vermeulen, F., & Barkema, H. 2002. Pace, rhythm, and scope: Process dependence in building a profitable multi- national corporation. Strategic Management Journal, 23(7): 637–653.

Vogel, R. H. 1976. Uses of managerial perceptions in clustering countries. Journal of International Business Studies, 7(1): 91–99.

Wald, J. K. 1999. How firm characteristics affect capital structure: An international comparison. Journal of Financial Research, 22(2): 161–187.

Performance measurement in IB research G Tomas M Hult et al 1079

Journal of International Business Studies

Wan, W. P., & Hoskisson, R. E. 2003. Home country environ- ments, corporate diversification strategies, and firm perfor- mance. Academy of Management Journal, 46(1): 27–45.

Werner, S., & Brouthers, L. E. 2002. How international is manage- ment? Journal of International Business Studies, 33(3): 583–591.

Whittington, G. 1971. The prediction of profitability. Cambridge: Cambridge University Press.

Wright, R. W., & Ricks, D. A. 1994. Trends in international business research: Twenty-five years later. Journal of Interna- tional Business Studies, 25(4): 687–701.

Zahra, S. A., Ireland, R. D., & Hitt, M. A. 2000. International expansion by new venture firms: International diversity, mode of market entry, technological learning, and performance. Academy of Management Journal, 43(5): 925–950.

Zhang, C., Cavusgil, S. T., & Roath, A. S. 2003. Manufacturer governance of foreign distributor relationships: Do relational norms enhance competitiveness in the export market? Journal of International Business Studies, 34(6): 550–566.

Zou, S., & Cavusgil, S. T. 2002. The GMS: A broad conceptua- lization of global marketing strategy and its effect on firm performance. Journal of Marketing, 66(4): 40–56.

ABOUT THE AUTHORS G Tomas M Hult (PhD, University of Memphis) is Professor of Marketing and International Business and Director of the Center for International Busi- ness Education and Research (MSU-CIBER) in the Eli Broad Graduate School of Management at Michigan State University. He is Executive Director of the Academy of International Business, and has held roles as Associate Editor-in-Chief and Depart- ment Editor of the Journal of International Business Studies. He is a native of Sweden. E-mail: hult@ msu.edu.

David J Ketchen Jr (PhD, Penn State University) is the Lowder Eminent Scholar and Professor of Management at Auburn University. He is a former Department Editor of the Journal of International Business Studies and currently serves as an associate editor for the Academy of Management Journal. His research focuses on strategy, entrepreneurship, and research methods. He is a native of the US. E-mail: [email protected].

David A Griffith (PhD, Kent State University) is Associate Professor of Marketing in the Eli Broad Graduate School of Management at Michigan State University. His research interests include interna- tional marketing strategy and the employment of firm resources for strategic marketing effectiveness. He has published in the Journal of Marketing, Journal of International Business Studies, Journal of Operations Management, etc. He is a native of the US. E-mail: [email protected].

Brian R Chabowski (PhD, Michigan State Univer- sity) is Assistant Professor of Marketing at the University of Tulsa. He is originally from Chicago in the US. His research interests include interna- tional marketing strategy, marketing and financial performance metrics, and the allocation and utili- zation of resources and capabilities in the firm. E-mail: [email protected].

Mary K Hamman is a doctoral candidate in the School of Labor and Industrial Relations at Michigan State University. Her research interests include the economics of work, family and fertility, and comparative health and work–life policy. Her dissertation research examines the impact of work- place policies on the health and well-being of women and children. She is a native of the US. E-mail: [email protected].

Bernadine Johnson Dykes, CPA, is a PhD candi- date in Strategic Management with a minor in International Business and Sociology in the Eli Broad Graduate School of Management at Michi- gan State University, and a native of Virginia in the US. Her research interests include competitive dynamics and firm behavior in emerging markets. She has published in the Academy of Management Journal and the Journal of Management Studies. E-mail: [email protected].

Wesley A Pollitte is a PhD candidate in Marketing and International Business in the Eli Broad Gradu- ate School of Management at Michigan State University. His research interests include network organization of supply channel relationships and e- commerce. He has a forthcoming article in the Journal of Product Innovation Management. He is a native of the US. E-mail: [email protected].

S Tamer Cavusgil (PhD, University of Wisconsin) is University Distinguished Faculty and the John W Byington Endowed Chair in Global Marketing in the Eli Broad Graduate School of Management at Michigan State University. His areas of interest include international marketing strategy, early internationalization, and emerging markets. He served as the inaugural Editor of Journal of Interna- tional Marketing, and edits Advances in International Marketing. He is a native of Turkey. E-mail: cavusgil@ msu.edu.

Accepted by Arie Y Lewin, Editor-in-Chief, 24 September 2007. This paper has been with the authors for two revisions.

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