IT Work

IT capabilities, interfirm performance, and the state of economic development

Buraj Patrakosol Faculty of Commerce and Accountancy, Chulalongkorn University,

Bangkok, Thailand, and

Sang M. Lee Department of Management, University of Nebraska,

Lincoln, Nebraska, USA

Abstract

Purpose – Prior studies have found that productivity gains associated with information technology (IT) adoption, measured at either the firm- or aggregate-economy levels, differ between developed and developing countries. The purpose of this paper is to extend prior cross-country research to the interfirm IT capabilities and relationship-level.

Design/methodology/approach – A two-country comparative study is conducted: the USA, a developed country; and Thailand, a developing country. The measurement constructs for the interfirm IT capabilities and performance are derived from the existing literature. Data are collected from IT managers who oversee interfirm relationships as follows: 68 from the US firms; 107 from Thai firms. Several statistical tools are used to test the developed hypotheses, including correlation, regression, and t-test analysis.

Findings – The important results of the paper indicate the following: IT technical capabilities are positively associated with interfirm performance across two countries. However, IT personnel IT capabilities had a positive relationship with interfirm performance only in Thai firms. Also, Thai firms realize higher innovation performance as a result of IT adoption than the US firms.

Research limitations/implications – This is an exploratory study as it is based on data from only two countries. Thus, a new causal theory about interfirm relationship-level performance is not sought. The future research needs include data collection from more countries and longitudinal analyses of trends based on advances in IT capabilities in different countries.

Originality/value – In today’s networked global economy, many organizations have value chains that involve interfirm relationships. This paper is the first attempt to explore productivity gains associated with IT adoption, measured at interfirm relationship-level, based on cross-country comparative analysis.

Keywords Business performance, Communication technologies, Cross-cultural studies, Thailand, United States of America

Paper type Research paper

Introduction By definition, developed countries dominate the world economy. They hold recognized leadership positions over the developing and underdeveloped countries with respect to critical competitive resources such as scientists, engineers, infrastructure, and legal and financial institutions. Similarly, their information technology (IT) infrastructures are extensive, complex and highly sophisticated. Research and development (R&D)

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Received 8 May 2009 Revised 9 July 2009

Accepted 20 July 2009

Industrial Management & Data Systems

Vol. 109 No. 9, 2009 pp. 1231-1247

q Emerald Group Publishing Limited 0263-5577

DOI 10.1108/02635570911002298

activities keep them at the cutting edge and IT adoption is prevalent throughout the society. The majority of firms and citizens are comfortable with IT in enhancing their work efficiency and quality of life (Anandarajan et al., 2002).

By contrast, IT is not as widely available and utilized in most developing countries (Dewan and Kraemer, 2000). One fundamental issue is a disparity in the level of investment in IT (Shih et al., 2008). However, not only are there differences between developed and developing countries in how extensively IT has been deployed, but also various cross-country studies indicate that firms in the developed countries actually extract more benefits from IT utilization than their counterparts in less-developed countries. These prior studies typically investigated the impact of IT at either the firm -level, examining the effects on individual firm performance, or the aggregate effect on an entire industry or country economy. The primary performance variable of interest in these cross-country comparisons has been productivity growth attributed to IT investment, following the reasoning that automation due to IT adoption increases labor productivity or that organizational process improvements increase multi-factor productivity (MFP).

A recent review, in summarizing several empirical studies, reported consistent positive correlations between IT investment and growth in both labor productivity and MFP in developed countries but insignificant or inconsistent correlations in developing countries (Dedrick et al., 2003). Although an increase in profitability is also an objective in IT investment, this outcome has proven elusive due to competitive forces (Hitt and Brynjolfsson, 1996). In developed economies, firms in highly competitive environments lack pricing power. Hence, gains in efficiency and quality may be passed on to the consumer through price reductions, rather than contributing to higher profit margins for the firm. This effect is not as extensively studied in developing economies.

However, there are other potential benefits of IT adoption that were not included in these prior comparisons between developed and developing countries. These benefits are derived from the inter-organizational usage of IT to link customers and supply-chain partners (Johnston and Vitale, 1988; Subramani, 2004). The current study addresses this gap by extending previous comparisons between developed and developing countries to include inter-organizational IT capabilities. The context of interfirm relationships is essential in the current global business environment. Firms strive to collaborate with others to realize benefits from alliances and the global value chain.

The cross-country interfirm IT study is still at a very early stage of development. While organizations in developed countries have been familiar with interfirm relationships and exploiting benefits from such relationships, organizations in developing countries are just beginning to realize the importance of such relationships. When cross-country context is not at focus, a number of within-country studies have made progress (Johnston and Vitale, 1988; Subramani, 2004). These studies suggested that firms with advanced IT capabilities generally have a positive relationship with interfirm firm-level performance. In other words, firms attain higher performance as a result of their IT-based interfirm relationships. The primary reason is because IT brings improvements to the relationship quality. As the quality improves, insightful and useful information is exchanged and various transaction costs are reduced. Taken this suggestion with the general cross-country IT literature earlier, a generalization can be made that firms in developed countries attain higher interfirm performance than their peers in less-developed countries do in the context of IT-based interfirm relationships.

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This generalization maintains cross-country context of the earlier literature and extends it with the interfirm IT literature. The thread to validity of this generalization is minimal because interfirm firm-level performance is a subset of aggregated firm performance. However, this generalization at firm-level may lead to misunderstandings at the relationship-level. That is because the firm-level performance does not always correlate positively with the relationship-level performance (Balakrishnan et al., 1996). Good firm-level performance does not mean good relationship-level performance and vice versa. There are many factors such as firm strategy and economy influencing firm performance. Therefore, this presents an opportunity to further our understanding of cross-country interfirm IT adoption.

This paper intends to advance cross-country interfirm IT study in two ways. First, it aims to generate new insights and understanding about the impact of IT capabilities in the cross-country context within the interfirm IT literature. Second, it refines the investigation from firm-level performance to relationship-level performance. Particularly, it aims to discover differences and similarities in IT-related elements between interfirm relationship-level performance in developed and developing countries. Two research questions are posed:

RQ1. Is there any difference in terms of the relationship-level interfirm performance between firms in the two types of countries?

This question sets a baseline for the next question. The second question deals with the explanation of first question:

RQ2. Does IT utilization contribute similarly or differently in the performance?

By posing these two questions, we hope to capture a more comprehensive picture of the context in focus, which is cross-country interfirm performance at the relationship-level.

In the next section, we present a literature review in the area of interfirm performance and IT capabilities in the context of country development levels. This review will lead to the development of hypotheses. Then, research methodology is discussed, including measurement and data collection. Next, the collected data are analyzed through statistical methods to test the hypotheses and ultimately answer research questions. The last section presents the conclusion of the study and its implications.

Review of relevant literature and hypotheses development Using the Solow residual as an indicator of total factor productivity, Lee et al. (2005) reported that aggregate IT investment does not contribute to economic growth as much in the developing countries as it does in the developed countries. This confirmed earlier results from Dewan and Kraemer (2000) who studied productivity differences using an inter-country production function relating gross domestic product to IT capital stocks. Differences in the effect of IT on productivity and economic growth were attributed to the prevalence of IT complementary factors such as specialized information infrastructure, human resources, R&D, low tariffs on computer imports, telecommunication liberalization, adaptive business models, and reorganization of manual processes. These fundamental factors must, to a large extent, be established by government policies and development strategies, which vary from country to country. The authors concluded that countries that have invested in information and

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communication technology (ICT) over a long period of time and accumulated a substantial installed base and complementary investments in telecommunications and human resources are better able to achieve positive and significant returns to IT.

Studies at the firm level, using a technology-organization-environment framework found that organizations in the developed countries enjoyed more benefits from advanced IT capability than their counterparts in the developing countries (Zhu et al., 2004; Zhu and Kraemer, 2005). The primary reason given was that organizations in the developed countries have successfully integrated IT into their organizational capabilities. Dedrick et al. (2003) also documented that the relationship between organizational performance and IT capability is very strong in developed countries but not strong in developing countries. They reasoned that low-labor costs discourage developing IT capability to substitute for human resources in developing countries. Hence, IT capability in organizations was not potent in the relationship.

Interfirm relationships and performance Interfirm relationships manifest themselves when two or more organizations enter into business collaborations for mutual benefits. The relationships range from simple buy-and-sell to strategic alliance and joint ventures. Information exchanged in these relationships is very diverse depending on the type of relationships. It varies from simple buy-sell transaction to highly complex collaboration information such as those in R&D activities.

Dyer and Singh (1998) suggest four sources of benefits from interfirm relationships. The first is relationship-specific investments between partners. These investments are made only for the relationship and partners enjoy the shared benefits. The second source is knowledge-sharing routines within the relationship. These routines encourage knowledge exchange and bring about new shared knowledge through a strong relationship between partners. The third source is complementary resources and capabilities. Values of some unique resources and capabilities of both partners are enhanced when they are jointly utilized. The last is governance mechanism. This mechanism can be classified into formal and informal and both of them are mutually beneficial to the interfirm partners. Formal mechanisms such as contracts can be well-crafted and enforced for the greater good of both partners. Informal mechanisms such as trust and reputation help lower interfirm management costs and enhance partnership uniqueness. These sources are also recognized under such umbrella concepts as social capital and network resources (Gulati et al., 2000).

Interfirm performance is broadly recognized as performance resulted from interfirm relationships. Straub et al. (2005) elaborates that the interfirm performance can be classified into four levels. The first and the finest is individual-level. Performance at this level is resulted from an individual who performs the interfirm task. Park et al. (2007) unveil that this performance is directly and indirectly affected by individuals’ absorptive capability. The second is group-level. Output of the performing team in the relationship is the performance indicator at this second level. This performance is largely affected by both IT capabilities and characteristics of the partnership (Majchrzak et al., 2005). The third is firm-level. This level concerns with aggregated performance indices of the firm. Rai et al. (2006) uncovered that interfirm IT capability enables the firm to efficiently extract its interfirm information and effectively utilize this information with its partners. The fourth and the broadest is network-level.

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The entire configuration of firms within the network contributes to this type of interfirm performance. This level is recently recognized. Straub et al. (2005) explored a possibility to measure this level of performance in a dyadic network. The firm-level performance has received the most attention out of all levels. This study intends to refine interfirm IT study from largely firm to rarely relationship-level oriented. The relationship-level conceptualizes an interfirm relationship as a unit of analysis and focuses on performance of the relationship, not individuals in the relationship (Phan et al. 2005). According to the classification system by Straub et al. (2005), this study fails into the group-level.

Regardless of the four levels, literature divides the interfirm performance into economic and innovation aspects. These aspects are important because they indicate a firm’s competitiveness and its survivability (Salomon, 2006; Wang et al., 2008). Traditionally, studies have focused on only one aspect of performance. For example, Goerzen (2007) focused on the economic performance and Laursen and Salter (2006) dealt with the innovation performance. However, no organization in the global age could effectively compete if it focused on only one aspect of performance (Christensen et al., 2008). These two types of performance are not mutually exclusive and can be simultaneously achieved (Malhotra et al., 2005). This study argues that more comprehensive insights could be obtained if both aspects of performance are investigated simultaneously.

Interfirm performance in different country-development levels The interfirm IT literature suggests that interfirm performance between firms in the two types of country-development levels may differ. However, which country type attains higher performance is unclear. A plausible line of arguments suggests that interfirm performance of firms in developed countries would be higher than that of firms in developing countries. IT is a flexible artifact. This artifact is so flexible that it can be tailored to accommodate different settings (Kumar, 2004; Corea, 2007). Superior performance from IT capabilities is conditioned on appropriate infrastructures. It is well known that firms in developing countries lack the infrastructures (Jarvenpaa and Leidner, 1998). Thus, superior interfirm performance falls on the firms in developed countries. The primary underlying assumption according to this line of argument is that interfirm performance largely depends on IT capabilities.

However, interfirm performance is the result of many factors and IT capability is just one factor. Muthusamy and White (2006) and Medlin et al. (2003), for example, discovered that the performance is influenced by the ways of coordination (i.e. trust, commitment, and power sharing) between firms. Gulati et al. (2005) reported the importance of adaptability to each other of both parties.

This study argues that firms in developed and developing countries may actually have different ways to achieve desired interfirm performance and, as a result, they are indifferent in performance levels. Supporting this argument, Guillen (2000) found unique characteristics of alliances in “emerging economies” during the 1990s. Plant and Willcocks (2007) documented that firms in developing and developed countries have different ways of handling IT projects. Furthermore, interfirm relationships are largely by choice to realize potential benefits (Dyer and Singh, 1998). Firms have a range of options to tailor relationships to meet their performance goals. When everything is free to vary, the current study expects equal interfirm performance is

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expected in both types of countries. H1 is thus proposed in a null form. The result of this hypothesis should shed light on RQ1:

H1. There is no difference in interfirm performance between the developed and developing countries.

IT capabilities and interfirm performance Studies in IT capabilities and business performance have a long tradition. Researchers, however, have less agreement on what IT capabilities actually are. Nonetheless, they generally agree on one principal definition. The IT capabilities are coherent IT-related components that are integrated to fulfill business objectives (King, 2002; Morris and Strickland, 2009). Melville et al. (2004) and Byrd and Turner (2000) suggest that the IT capabilities operate on two basic components: technical (i.e. IT artifacts) and personnel.

Melville et al. (2004) and Wheeler (2002) point out that IT capabilities are the source of efficiency and innovation. The capabilities deliver mechanisms for the better interfirm performance. Various types of interfirm relationships are supported by IT capabilities. For instance, IT capabilities bring about information sharing and process optimization in the supply chain (Rai et al., 2006). Furthermore, IT capabilities originate value-added activities and support interfirm collaborations in the strategic alliance (Lee and Lim, 2005).

When the context of developed and developing countries is taken into account, Walsham and Sahay (2006) argue that this context does not change the effects of IT capabilities. Jennex (2003) reported that utility firms in Eastern European countries realized similar benefits as their counterparts in Western Europe and North America. Bruce and Daniel (2007) showed similar results in electronic banking in United Arab Emirates and Western European countries. Mejias et al. (1996) revealed that group support systems had similar effects on subjects from the USA and Mexico. In light of the literature, H2 is proposed as follows:

H2. IT capabilities are positively associated with interfirm performance in both developed and developing countries.

The context of developed and developing countries may change the potency of IT capabilities. Many studies have argued that the potency would be less in developing countries. Jennex (2003) attributed such result to the fact that firms in developing countries possess less IT capabilities. Bruce and Daniel (2007) reported that managers in developing countries were conservative and slow in building IT capabilities in their organizations. Abdul-Gader and Kozar (1995) documented that managers in these countries felt alienated by the technology. Additionally, Caselli and Coleman (2001) unveiled that the lack of quality human capital was a major hurdle in developing countries.

On the contrary, many believe that the potency of IT capabilities is actually stronger in developing countries than in developed countries because of the greater room for improvement. Firms in developing countries are generally operating within the “old economy” model. These firms are on average less than a half-way into e-business development (Evans, 2001). Firms in less-developed countries have more room for improvement and IT capabilities offer great potential to help support this need (Piatkowski, 2006). Furthermore, regulatory systems in developing countries might indirectly promote the potency of IT capabilities (Zhu and Kraemer, 2005).

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The reviewed studies in the literature do not persuasively suggest the IT capabilities either increase or decrease their potency. However, both streams agree that there are differences in the potency of IT capabilities between firms in developed and developing countries. As a result, the current study propose H3:

H3. IT capabilities differently affect interfirm performance in developing and developed countries.

The testing of H2 and H3 would answer RQ2. H2 would confirm the importance of IT capabilities in the interfirm performance, while H3 would clarify the importance of IT capabilities is in interfirm relationships across the two country-development levels.

Research methodology We conducted a two-country research in the USA, a developed country, and Thailand, a developing country. Thailand was selected because it is an average developing country. According to the World Bank’s classification of economies, Thailand has been consistently ranked in the middle of developing economies. Table I illustrates basic economic and IT infrastructure indicators of the two countries in late 2006. The data on the number of telephone subscribers, cell-phone subscribers, internet users, and broadband subscribers were collected from the ICT Statistics Database of the International Telecommunication Union (ITU) and are reported in the unit of per-100 inhabitants. The income per capita was collected from the World Bank in US dollars.

IT infrastructure data indicate that Thailand lags behind the US significantly in IT infrastructures. Relatively, small gaps exist in voice-oriented communications and much larger gaps present in data-oriented communications. These gaps hint that voice communications are much more ubiquitous than data communications across the two countries.

Control variable Task variety is included as a control variable. The variety of tasks is an important dimension of interfirm task characteristics. Studies showed the influence of the task characteristics over the interfirm performance (Sobrero and Schrader, 1998; Malhotra et al., 2005). Task characteristics are particularly relevant in interfirm IT studies because they are the source of uncertainties in the needed information and processes in the interfirm relationships (Bensaou et al., 1999). Including this variable would account for other potential effects over the performance.

Measures Measuring constructs in the context of interfirm studies is full of challenges. Most constructs are complex, not-fully observable, and context dependent. When these challenges are present, perceptual measures are more suitable than objective measures

Income per capita ($)

Telephone subscribers

Cell-phone subscribers

Internet users

Broadband subscribers

Thailand 2,990 73.80 62.88 13.07 0.16 USA 44,970 134.55 77.40 69.83 19.31

Table I. Basic economic and

IT infrastructure indicators in 2006

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(Homburg et al., 1999). This study creates a perceptual instrument based on existing literature by selecting items from reputable previous studies to rely on their established validity. Interfirm performance items were from the literature concerning two dimensions of performance (Arias, 1995; Poppo and Zenger, 1998; Repenning and Sterman, 2002). These dimensions include economics and innovation. Economic performance is concerned with return on investment. Innovation performance is concerned with improvements of products or processes. IT capabilities items were selected from items of Byrd and Turner (2000). These items capture flexible capability of IT which is a very important aspect of interfirm information systems in sustaining strategic goals. The IT flexibility is the degree to which IT infrastructure can cope with uncertainties stemming from interfirm relationships. This flexibility is further refined into technical IT resources (i.e. hardware and software) and IT personnel. Lastly, items of Daft and Macintosh (1981) were the basis for task variety items. Task variety represents problem and uncertainty in the interfirm tasks.

In all, each construct had four to five items. All items were scaled on a seven-point Likert scale (1 – strongly disagree to 7 – strongly agree) and were compiled with some demography items in the instrument. The survey packet included the instrument, along with a cover letter explaining the goal of study and an optional prepaid self-return envelope. The data analysis indicated that all measures satisfied the Cronbach’s alpha reliability test. No Cronbach’s alpha was less than 0.70 for each construct in each country. The average value of the items in each construct was used as variables for the analysis. The complete list of measurement items is given in the Appendix.

Data collection Data were collected from IT managers who oversee interfirm relationships. Each manager was asked to provide information on only one relationship that he/she was most familiar with. Focusing on an informant for a relationship is common in relationship-level investigations (Olk and Young, 1997; Bercovitz et al., 2006). In total, 2,400 IT managers were randomly selected from directories of IT managers in the two countries. Two methods were used to deliver the survey packets. The US managers were sent the survey packet with a prepaid self-return envelope via the US mail. On the other hand, Thai managers were personally delivered the packets, without a self-return envelope, by helpers in Thailand. The reason for this in-person delivery will be discussed below.

A total of 175 managers participated in the study. About 68 were US managers and 107 were Thai managers. Personal delivery could well be the reason for the higher response rate among Thai managers. The data showed that IT managers who participated came from diverse backgrounds. More managers were from the service than manufacturing industry. Their positions ranged from the IT director to chief information officer. On average, US managers had been with their firms for 12 years and held current positions for nine years. Their Thai counterparts were with their firms for 13 years on average and had been in their positions about five years.

As this is a cross-country study, only one version of instrument was used in the data collection. This version was in English language. The instrument version posed a concern because majority of Thai managers did not use English as their first language. Participants might not have fully understood the survey items. A cross-country study

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normally creates two versions of the instrument with the double-translation protocol to address this concern.

However, the result of double-translation is oftentimes not perfect (Mitchell et al., 2000). This imperfection was a concern for validity of this study. A number of Thai managers were consulted to learn more about their English proficiency. These managers informed us that a majority of Thai managers in well established global firms command a relatively high level of English proficiency. Understanding questionnaire items was not their problem. A decision was made in light of this fact to have only one version of the instrument. Nonetheless, we wanted to make sure that the participants were absolutely comfortable with the English instrument. The solution was to bring in helpers to deliver survey packets. These helpers were instructed to ask the managers about their comfort levels in English language but not to discuss any aspect of the questionnaire with the managers. If the managers were not comfortable in any way, the helpers would not deliver the packet.

Results Descriptive statistics Tables II and III provide descriptive statistics of all variables of Thai and US firms, respectively.

Test of hypotheses H1. In testing H1, independent-samples t-test was utilized to discern centrality differences between the two countries. A normality check was conducted before the t-test procedure. Skewness and Kurtosis of each variable were examined in Tables II and III. No skewness and kurtosis fell out of the recommended range, ^2 for skewness and ^7 for kurtosis (Douglas et al., 2007). Hence, the data satisfied normality assumption. The t-test routine in SPSS software version 15 was utilized for the statistical testing. Table IV presents the results.

Construct Mean Skewness Kurtosis 1 2 3 4

1. Economics 5.05 20.28 20.31 – 2. Innovation 5.11 20.53 20.93 0.47 * – 3. IT technical 4.54 20.40 20.51 0.40 * 0.41 * – 4. IT personnel 4.59 20.44 20.05 0.35 * 0.36 * 0.44 * – 5. Task variety 4.42 20.17 20.47 0.13 0.30 * 0.22 * 0.09

Note: *p # 0.05

Table II. Thai firms descriptive

statistics and correlation coefficients

Construct Mean Skewness Kurtosis 1 2 3 4

1. Economics 5.29 20.29 20.33 – 2. Innovation 4.75 20.49 20.44 20.35 * – 3. IT technical 4.92 20.37 20.08 20.35 * 0.15 – 4. IT personnel 5.51 20.14 20.88 20.12 * 0.22 20.46 * – 5. Task variety 3.63 20.10 20.31 20.13 * 0.12 20.07 * 20.9

Note: *p # 0.05

Table III. US firms descriptive

statistics and correlation coefficients

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The statistical analysis revealed similarities and differences between firms in the two countries. With regard to the performance, the t-statistics did not indicate differences in terms of economics performance ( p-value ¼ 0.111) but indicated differences in innovation performance ( p-value ¼ 0.026). These results imply that firms in both countries realize economic return at a similar level. However, Thai firms realize more innovation than their US counterparts from interfirm relationships.

On the issue of IT capabilities, statistical values indicated differences between the two countries. US firms possessed higher IT capability than Thai firms in both IT technical ( p-value ¼ 0.011) and IT personnel ( p-value ¼ 0.000) areas. This comes as no surprise because US IT infrastructures are more advanced than that of Thailand. The data from ITU also supported this finding. Regarding the task characteristics, the statistic indicator suggests that there are differences in task variety ( p-value ¼ 0.000). Interfirm tasks involved more varieties in Thai firms than in US firms.

These results point to the following conclusions. US firms had higher IT capabilities in conducting their interfirm relationships and Thai firms implemented interfirm tasks with more varieties than their counterparts in the US did. Firms in both countries evenly achieved interfirm economic performance but Thai firms realized higher interfirm innovation performance. Thus, H1 is confirmed in the dimension of economic but not innovation performance.

H2 and H3. The current study addresses H2 and H3 by investigating any association of IT capabilities with the interfirm performance while controlling for the task characteristics. Two ordinary least square (OLS) regression models were developed for each country. The first model estimated parameters associated with the economic performance and the second model estimated parameters associated with the innovation performance. This study used the OLS regression routine in SPSS software version 15 for the parameter estimation. Statistical results are shown in Table V.

USA Thailand t-statistic p-value

Economics 5.29 5.05 1.60 0.111 Innovation 4.75 5.11 22.24 0.026 *

IT technical 4.92 4.54 2.59 0.011 *

IT personnel 5.51 4.59 6.02 0.000 * *

Task variety 3.63 4.42 25.23 0.000 * *

Note: *p # 0.05; * *p # 0.01 Table IV. t-Test results

Model 1 Model 2 Predictors US econ. perf. Thailand econ. perf. US inno. perf. Thailand inno. perf.

IT technical 0.325 * 0.295 * 0.069 0.266 *

IT personnel 0.038 0.220 * 0.203 0.223 *

Task variety 20.099 0.043 0.140 0.224 *

R 2

0.133 * 0.201 * 0.072 0.258 *

Note: *p # 0.05 Table V. OLS results

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All variables satisfy the normality requirement as examined above. Parameter estimations were carried out in light of the normality. After the parameter estimation, possibility of multicollinearity was inspected. Variance inflation factors (VIF) were used for this inspection. All VIF values were well below the recommended threshold of ten (Chatterjee et al., 2000). The inspection showed no sign of multicollinearity. The estimated parameters were reliable.

The first model showed that only IT technical capability was positively related to the interfirm economic benefits of US firms. On the contrary, Thai firms realized economic benefits from both IT technical and IT personnel capabilities. The R 2-values of this model on the two countries indicate that the model successfully explain a portion of the economic performance. About 13 percent of variance was accounted for in US firms and about 20 percent in Thai firms. The second model illustrated quite an interesting contrast. US firms did not attain any innovation benefits from the three predictors. This result is confirmed by the statistical insignificance of the model (R 2 ¼ 0.072). On the other hand, all three predictors were positively associated with innovation performance in Thai firms. This model accounted for about 26 percent of innovation performance variance.

The results of these two models together partially confirm both H2 and H3. H2 is fully confirmed for Thai firms but not for the US firms. IT capabilities were positively related to both dimensions of interfirm performance for Thai firms. On the other hand, only technical IT capabilities were positively associated with economics interfirm performance for US firms. General observations reveal that the effects of IT capabilities on performance are more potent in Thai firms. However, a t-test for coefficient differences between the two regression models reveals that the effects of 0.325 and 0.295 at technical IT capabilities on economic performance between US and Thai firms are not significantly different ( p . 0.05). As a result, H3 is partially confirmed.

Discussion and conclusion This study refines cross-country IT study from the firm-level to relationship-level. It aims to investigate differences and similarities between the interfirm relationships in a developed and a developing country in association with IT adoption. Two research questions and three hypotheses guided this investigation. Statistical analyses revealed the following findings:

(1) both Thai and US firms attained similar economic performance;

(2) Thai firms realized higher innovation performance;

(3) IT technical capabilities are positively associated with both aspects of interfirm performance across two countries;

(4) IT personnel capabilities had a positive relationship with both aspects of interfirm performance in Thai firms;

(5) US firms had higher levels of both IT technical and personnel capabilities than Thai firms did; and

(6) Thai firms implemented less routine interfirm tasks than their US counterparts did.

The first and second findings answer RQ1. This study documents that economic performance was similar but innovation performance was different between the two

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countries at the relationship-level. The third and fourth findings answer RQ2. IT capabilities benefited interfirm relationships in the developing country more than in the developed country. Both types of IT capability are consistently and positively associated with the two types of interfirm performance in Thai firms. However, only one type of IT capabilities (i.e. technical) and one type of interfirm performance (i.e. economic) were positively linked in the US firms. The earlier literature review at firm-level suggested a result that firms in the developing countries were less successful in harvesting benefits from IT capabilities. The current result at relationship-level contradicted with this result at the firm-level. This study showed that the firm-level findings did not hold at the relationship-level. The fifth finding confirms previous literature on the level of IT capabilities in developed countries. The sixth finding highlights a nature of Thai interfirm task characteristics.

This study recognizes that there is a possibility that Thai managers might have misinterpreted the questionnaire. To assess whether this possibility presents a significant threat to this study’s findings, the reliability of questionnaire is examined. All Cronbach’s alpha (a reliability indicator) values show good reliability. Hence, the reliability of this study was not compromised given the possibility of misinterpretation.

Furthermore, data from only two countries present a challenge in generalizing the findings. The nature of this study is exploratory. We do not seek to develop a new causal theory about interfirm relationship-level performance. Nonetheless, these findings shed many insights. First, technical IT capability was not a dominant factor in interfirm economic performance within the cross-country context. The impact of the capability was alike across the two countries. US firms had higher IT capabilities but achieved about a same level of performance as Thai firms did. If technical IT capability was a dominant factor, interfirm economic performance would have been higher among the US firms. In other words, technical IT alone does not lead to superior performance at the relationship-level. Second, a reason that Thai firms attained higher innovation performance was the positive impact of IT capabilities and task variety. Insight regarding innovation performance is in line with the result of many studies (Karimi, 2004; Majchrzak et al., 2005). IT capabilities facilitate information sharing (Apostolou et al., 2009) and task variety encourages collaborations between parties (Wong, 2004). Information flow between parties enhances innovation.

The third insight is based on the sixth finding. This finding highlights a dynamic nature of Thai interfirm task and environment uncertainty. In other words, this finding may suggest that the US firms implement more routine tasks as the environment is more stable. Majchrzak et al. (2005) point out that high-task variety is associated with low-task routineness. Low-routine tasks are more dynamic and complex (Kirsch, 2004). Karimi (2004) uncovered that nonroutine tasks were often the result of environment uncertainty.

The last insight, the lower innovation performance among the US firms might have stemmed from their defocus (either intentionally or unintentionally) on innovation. Levina (2005) observed that firms that focus heavily on economic efficiencies might unintentionally hurt their innovation. A cross-cultural study between the USA and Japan managers reported a similar insight (Tiwana and Bush, 2007). US managers placed importance on the economic aspect but not on the knowledge aspect of interfirm relationships. Japanese managers, unlike their US counterparts, placed

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importance on both aspects. Since knowledge is the source of creativity, the US firms’ innovation suffered.

Discussions up to this point lead to some meaningful managerial implications. An implication is that managers in developing countries should not be discouraged by their handicap in IT capabilities. This study showed that the handicap did not equate to lower performance. Another implication is that opportunities to enhance interfirm performance are open for managers in both developed and developing countries. Managers in the developed countries may look to improvements of task characteristics as a means to increase the interfirm performance. Managers in the developing counties, on the other hand, may look into IT infrastructure as a means to improve performance. The final implication is rather a reminder. Many studies showed that advanced IT capabilities in the developed country helped firm performance. However, managers must not confuse relationship- with firm-level performance. This study agrees with Balakrishnan et al. (1996) that good relationship-level performance does not automatically translate to good firm-level performance.

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Appendix

Corresponding author Sang M. Lee can be contacted at: [email protected]

Economic benefits (Thailand, a ¼ 0.81; USA, a ¼ 0.84)

1. The relationship has saved us money 2. The relationship has speeded up transactions or shortened

cycle-time 3. The relationship has increased return on financial

investments 4. The relationship has enhanced our employees productivity or

business efficiency IT technical (Thailand, a ¼ 0.73; USA, a ¼ 0.76)

1. Flexible electronic links exist in the relationship 2. The IT infrastructure of the relationship can quickly adapt to

new tasks 3. There are very few identifiable IT bottlenecks between our

organization and the partner organization 4. Various forms of electronic data received from the partner are

assimilated and utilized quickly in our organization 5. Information is shared seamlessly between our organization

and the partner, regardless of locations Task variety (Thailand, a ¼ 0.71; USA a ¼ 0.75)

1. A variety of unanticipated events regularly occur to tasks in the relationship

2. The tasks in the relationship are mostly non-routines 3. Decisions in the tasks are dissimilar from one day to the next 4. It takes a lot of experience and training to know what to do

when a problem arises in the tasks 5. Any problem in the activities requires an extensive and

demanding search for a solution Innovation (Thailand, a ¼ 0.82; USA, a ¼ 0.82)

1. The relationship enables our organization to become more agile in launching new products or solving problems

2. The relationship encourages us to invest more in R&D activities

3. The relationship has led our organization to new ways to compete with competitors

4. The relationship has led our organization to better business processes

IT personnel (Thailand, a ¼ 0.90; USA, a ¼ 0.85)

1. Our IT personnel provide unique capabilities to the relationship

2. Our IT personnel are self-directed and proactive 3. Our IT personnel are able to interpret business requirements

and develop appropriate technical solutions 4. Our IT personnel are knowledgeable about business tasks

related to the relationship 5. Our IT personnel are skillful in suggesting plausible IT-

business solutions

Table AI. Measurement instrument

items

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