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Understanding the relationship between uncertainty and international information technology sourcing strategy: a conceptual framework.


The inherent economic advantages of international offshore sourcing (offshoring) work to cheaper offshore locations have made offshoring a business necessity for many enterprises. More and more organizations are relying on offshoring to provide critical information technology (IT) products and services and this phenomenon is likely to continue into the future (Davis, Ein-Dor, King & Torkzadeh, 2006). Significant cost savings are not the only or major objective for IT offshoring. Many companies are forced to offshore due to the lack of available technical talent in their home country (Ernst, 2006). However, the decision to offshore involves a certain degree of uncertainty for the firm (client) entering the offshoring arena. The question is not always about whether it is better for a company to insource or outsource. Rather, the question is increasingly becoming--how can companies reduce the uncertainties associated with IT offshoring and fit their IT offshoring strategies to the uncertainties encountered? To date, there has been little research investigating how IT managers address and match uncertainty with their IT offshoring strategy.

Much has been written about the management of and the decision to adopt IT outsourcing and offshoring (i.e., Lacity & Willcocks, 1996; Wang, 2002). Generally, when examining the IT outsourcing decision, the literature has focused on costs and control structures (Kern & Willcocks, 2000; Kim & Kim, 2008). Relatively few studies have investigated the uncertainties that surround the IT offshoring decision (i.e., Saunders, Gebelt & Hu, 1997). This is somewhat surprising given that nearly all international investments, including IT offshoring, are impacted by uncertainty and dealing with this uncertainty is crucial for success. Recent research by Hahn, Doh and Bunyaratevej (2009) suggests a significant need to examine the determinants of firm IT offshoring behavior with respect to offshoring location risk.

Given the predicted growth of the offshoring phenomenon, and the significant role of risk with a firm's performance, there is ample opportunity and an essential need for academics and practitioners to understand the impact of uncertainties in regards to the IT offshoring decision. Previous research has failed to fully capture and explain the role of uncertainties involved in IT offshoring. A framework that would synthesize the role of uncertainty in the context of the IT offshoring decision has yet to fully emerge. Moreover, much of the existing research on offshoring has assumed that the different forms of uncertainties (i.e., political uncertainty, cultural uncertainty, macroeconomic uncertainty, etc.) have the same (or similar) effect on a client firm's offshoring decision (i.e., Aspray, Mayadas & Vardi, 2006; Hahn et al., 2009; Kleim, 2004). We argue that this not true as some uncertainties can only be resolved through learning (i.e., a client firm's activities) and other uncertainties evolve independent of a client firm's activities. Drawing on the real options and organization learning theories we develop a framework that incorporates uncertainty in explaining the IT offshoring model decision. To parsimoniously assess the uncertainty inherent to IT offshoring our proposed framework distinguishes between endogenous and exogenous uncertainties in relation to the IT offshoring decision. Specifically, we argue the level of endogenous and exogenous uncertainty surrounding IT offshoring determines whether a client firm adopts a captive offshoring, joint-venture, third-party or onsite IT offshoring model. In doing so, we seek to fill an important gap in the IT offshoring literature.

The remainder of the paper is organized as follows. The next section reviews the extant IT offshoring literature in regards to uncertainty. Next, we develop a theoretical framework used to examine uncertainty in the IT offshoring environment. The third section discusses the propositions regarding the role of uncertainty and the IT offshoring decision. We then present an illustrative case example demonstrating how our framework captures the evolution of a client firm's IT offshoring strategy to fit the uncertainties faced by the client firm. We conclude with sections presenting the research limitations, suggest implications for both academics and practitioners and provide recommendations for future IT offshoring uncertainty research.


Organizations today follow a variety of approaches when entering into an IT offshoring arrangement. These approaches include: the use of foreign subsidiaries, foreign acquisitions, offshore development centers, joint ventures or alliances, and foreign contracting (Carmel & Agarwal, 2002). The ambiguity in the definition and many forms of IT offshoring complicate an already challenging decision for organizations. An expanded definition by Davis et al. (2006) indicates offshoring to be accomplished in one of two ways. First, the organization may outsource some of its activities to service providers in other countries who hire, train, supervise and manage its (i.e., the client's) personnel. Second, the client organization may set up service operations in other countries where the operations are managed by its own staff located in those countries rather than by the outside service provider. Barthelemy and Geyer (2005) also define outsourcing as either (1) a contract with an outsourcing vendor or (2) a client setting up their own IT subsidiary offshore (i.e., captive-outsourcing). For the purpose of this paper, we apply a general definition to offshoring where we focus on the IT offshoring decision to include the client firm utilizing a selected IT offshoring model.

Specifically, in this paper we focus on the following offshoring models: joint ventures, captive offshoring, third party offshoring, and an offshoring arrangement located onsite (i.e., onsite captive offshoring model). The offshoring models differ based on the amount of equity or investment that is made by the client firm and also on the degree of learning occurring as a result of the investment. In an offshore captive model the client firm invests, owns and operates a subsidiary in an offshore location. The client firm is in charge of hiring and operating the offshore facility utilizing the offshore resources. In an onsite captive offshoring model, the client firm brings offshore resources to work at the onsite location by collaborating with a third party. That is, the third party offshore vendor will provide the human capital resources by relocating the vendor employees to the client's location to perform the IT activities. The vendor resources will be managed by and report to the client's project leaders. In a joint-venture model, the client and vendor firm share the investments needed to operate offshore. Client firms may also choose to hire a third party offshore vendor to supply the IT activities to the client firm. The vendor is located offshore and performs the IT activities outside of the home country of the client firm. Hiring a third party vendor requires less equity or upfront investment when compared to the equity-based offshore models.


In this paper uncertainty in the offshoring setting refers to the prospect of unanticipated developments in the technological, business, or political environments of the offshore vendor country which are of particular concern in the offshoring decision, given the global nature of IT offshoring (Mirani, 2006). Studies often cite a wide variety of uncertainty definitions. For example, Miliken (1987) defines uncertainty as a "perceived inability to predict accurately" due to a lack of "sufficient information." Uncertainty can also be defined as a condition in which one cannot ascertain the probability of an event and therefore cannot insure against its occurrence (Miller & Shamsie, 1999; North, 1990). In order to develop a parsimonious theoretical framework to effectively capture the various uncertainties involved in the IT offshoring decision, we introduce and rely on the distinction between endogenous and exogenous uncertainty (Dixit & Pindyck, 1994; Folta, 1998). Uncertainty is endogenous when a client is able to reduce or dispel the uncertainty through its own actions. For example, uncertainty associated with operating in a very culturally different environment diminishes as a firm gains experience about cultural norms and business practices (i.e., customer preferences, partner relationships, supplier network etc.). That is, the reduction of endogenous uncertainty is dependent on the client firm's learning process (Folta, 1998; Roberts & Weitzman, 1981). In contrast, exogenous uncertainty arises externally to the firm and is mostly independent of the firm's actions; it includes factors such as unforeseen actions by external entities (i.e., regulatory bodies, governments etc.) (Folta, 1998). Firms have little or no control over the evolution of exogenous uncertainty. Client firms have to deal with a variety of exogenous uncertainties while operating in a host country (Hill, Hwang & Kim, 1990). These include political uncertainty (Kobrin, 1982; Miller, 1992), legal and regulatory uncertainty (Teece, 1986; Teisberg, 1993), and macroeconomic uncertainty (Hassett and Metcalf, 1999; Miller, 1992). For example, a client firm's actions have marginal or no effect on reducing exogenous uncertainty (i.e., political regime change). However, it can be reduced by a passive observation and a general learning of the host country's environment.

As seen from the above discussion, a client firm may face both endogenous and exogenous uncertainties when examining its own IT offshoring decision. Viewing IT offshoring models as a special kind of real options, we draw on the real options and organizational learning literature to develop a theoretical framework that allows for effective differentiation and understanding of uncertain environments and its effects on the IT offshoring decision.


Traditionally, offshoring has been viewed as a unique form of foreign market entry; one that is focused on access to labor markets. There are several theoretical perspectives in this body of literature that provide valuable insights into the offshoring model choice. For example, the transaction cost theory (TCT) (Williamson, 1975) has been widely applied to analyze the IT outsourcing decision from an economic perspective (i.e., Lacity & Willcocks, 1996; Wang, 2002). It suggests that when asset specificity is low, and transactions are relatively frequent, the transactions will tend to be governed by markets and the offshoring decision will move towards utilizing an offshore third party. On the other hand, high asset specificity and uncertainty will lead to transactional difficulties and transactions will be held internally within the firm, or vertically integrated through a client sponsored offshore subsidiary (captive offshoring).

The proponents of the internalization theory (Buckley & Casson, 1976) posit that multinational enterprises (MNEs) internalize their operations when faced with uncertainty surrounding a transfer of their proprietary knowledge. In the context of offshoring, a client might choose to open and operate their own offshoring subsidiary instead of partnering with a host country vendor when the risk of opportunism by the partner is high. This view draws on the organizational learning literature and suggests that cumulative international experiences enable MNEs to reduce uncertainty. Likewise, a stage model of offshoring elaborated by Carmel and Agarwal (2002) suggests that client firms manage uncertainty by choosing offshoring models based on their learned experiences. Specifically, their field work identified four IT offshoring stages adopted by US firms: Stage 1-Offshore Bystanders are firms that do not offshore at all, but may have a few advocates pushing the idea, Stage 2-Offshore Experimenters are pilot testing sourcing of non-core IT processes offshore., Stage 3--Proactive Cost Focus are companies that take a proactive cost focus and seek broad, corporate-wide leverage of cost efficiencies through offshore work, and Stage 4--Proactive Strategic Focus--are companies that take a proactive strategic focus and view offshore sourcing as a strategic imperative. While the IT offshoring research has grown into a large body of work, the existing literature has not sufficiently explained the relationship between the degree and type of uncertainty and offshoring model choice. Specifically, each of the previously mentioned theoretical approaches tends to focus on only one kind of uncertainty and its impact on the choice of the IT offshoring model.

The real options theory provides a framework that overcomes such limitation. The theory can be used to explain IT offshoring choices and help managers to account for the uncertainties that arise in such evolving environments (Trigeorgis, 1996). The strength in the real options theory is in recognizing the impact of uncertainties on investment decisions and the flexibility it provides to managers in making strategic decisions. Researchers have conceptualized real options as a theoretical framework in various environments such as equity joint ventures (Kogut, 1991), investments in emerging markets (Kogut & Kulatilaka, 1994), R&D projects (Mitchell & Hamilton, 1988) and IT infrastructure (Balasubramanian, Kulatilaka, & Storck, 2000; Fichman, 2004). One of the primary reasons for the growing interest in real options theory is the practical concern that strategic investment decisions are often made under uncertainty (Dixit & Pindyck, 1994). The primary advantage of holding a real option is that it offers flexibility to its holders by conferring them the option to defer (McDonald & Siegel, 1986), or an option to abandon (Myers & Majd, 1990). In order for real options to be viable, two conditions must be met. First, the decision must be characterized by uncertainty and second, the investment should not be easily irreversible. That is, once the decision is made, it cannot be reversed without incurring cost. IT offshoring can be viewed as a real option as it meets both criteria. The decision to offshore is surrounded by uncertainty (i.e., uncertainty dealing with foreign vendors, uncertainties arising from local environment) that is typically not associated with traditional domestic IT outsourcing or internal sourcing. In addition, the decision of a client to back-source (i.e. bring IT back in-house) or switch vendors (Lacity & Willcocks, 2000) can have serious financial implications. Thus, the offshoring decision is not easily reversible. Under conditions of uncertainty and irreversibility, holding an option represents the right to postpone the decision in order to resolve some of the uncertainty. In our case, this can be uncertainty surrounding the client's offshore vendors or the subsidiary's offshore host country environment. Once the IT offshoring model decision has been made (i.e., the option has been exercised by making an investment in a subsidiary to be operated in another country), the resources spent to implement the strategy cannot be easily recovered if the IT offshoring decision is often revealed to be suboptimal.

IT offshoring usually involves higher complexity and risks when compared to insourcing or domestic outsourcing because of the need to control the project remotely and to interact cross-culturally (Carmel & Agarwal, 2002). In addition, the client firm is also exposed to additional levels of uncertainty in regards to managing security across country and organizational boundaries. IT offshoring often entails IT assets and information to be in possession of an offshore vendor in another country and thus making the client's assets much more difficult to protect. Firms engaging in offshoring may also face uncertain political and economic instabilities of the offshore locations. One example is India (a leading provider of IT offshoring) and their unstable political relationship with Pakistan, where the two have been on the brink of war on a number of occasions. Economic uncertainties can also be substantial. An example is the Philippines' government's pressure to eliminate the generous tax incentives, which could eventually push up prices in the region (Carmel & Nicholson, 2005).

We should note that uncertainty is only one of many factors that influence a client's choice of offshoring model. Factors such as strategic alignment, cost, technology etc. all can have an impact on the clients' choice of offshoring model (i.e., Carmel & Agarwal, 2002; Kakabadse & Kakabadse, 2000; King & Malhotra, 2000). These factors, however, are beyond the scope of this paper whose primary focus is to gain a better understanding of the effects of uncertainty on IT offshoring model choice.


The impact of uncertainty on the IT offshoring decision has been suggested to be critical to organizational performance (Hahn et al., 2009). Companies whose offshoring initiatives fail to meet their expectations typically make one of the following mistakes (Aron & Singh, 2005). First, companies do not spend enough time evaluating which aspects (i.e., processes, application development, and customer service) they should offshore and those that they shouldn't. Second, firms do not take into account all of the risks that are inherent within the offshoring context. Client firms often fail to realize that once they transfer their processes, their vendors could gain the upper hand as the power in the relationship shifts from the clients to the vendors. There is no guarantee that offshored projects will be any more successful given the time delay, cultural, financial, technical and legal issues. The complications of IT offshoring can make it very easy for firms to underestimate the difficulty of the offshoring engagement and eventually terminate the offshoring relationship. Offshoring usually involves higher complexity and risks because of the need to control the project remotely and to interact cross-culturally (Carmel & Agarwal, 2002). As a result, a framework is necessary to support client firms in managing the uncertainties inherent to IT offshoring.


The suggested framework (Figure 1) considers uncertainty to consist of two dimensions endogenous and exogenous--which are independent and capture wholly different types of uncertainty. Although the occurrence of uncertainty is a continuous phenomenon, we use a dichotomous categorization for the sake of simplicity. A firm can be perceived to be experiencing either high or low levels of endogenous uncertainty or high or low levels of exogenous uncertainty. An illustrative exercise to introduce the relationship between the uncertainties is to consider moving along various paths from any given point in a hypothetical two-dimensional space as depicted in Figure 1. Consider first moving eastward along line A, increasing exogenous uncertainty while holding endogenous uncertainty constant at a relatively low level. Firms experience constant endogenous uncertainty along this path and correspondingly increased levels of exogenous uncertainty. Likewise, when moving northward along line B from the midpoint of the exogenous uncertainty axis and, increasing endogenous uncertainty while holding exogenous uncertainty constant a firm could also simultaneously experience an increase in both endogenous and exogenous uncertainties (i.e., moving in the northeast direction along line C). Advancing along both the dimensions of uncertainty increases the challenges a client faces when compared to the previous two scenarios. In the following sections, we discuss the unique problems encountered by client firms within each quadrant in making strategic decisions regarding IT offshoring. We identify examples of offshoring models for each scenario that could provide effective means to manage these uncertainties. These examples are not a comprehensive list of possible IT offshoring models, but to an extent represent a selection of those that are prominently discussed in the existing literature.


From the client firm's perspective, Quadrant I (Figure 1) represents the most desirable uncertainty case. In this situation, the client firm has a good understanding of the host country culture, technology and the outsourced activity. Moreover, it also has a good understanding of the host country macroeconomic environment (i.e., legal, political, etc.). An example of this scenario would be a US located client firm offshoring its quality management task (i.e., application testing) to an IT firm located in Canada. In such a case, because of relatively low levels of endogenous and exogenous uncertainties, client firms have all the information needed to make a decision regarding their offshoring model. To the extent that the client firm is already familiar with the partner firm, host country culture and institutional framework, there is no need for the client firm to delay its decision to invest. Viewing the offshoring decision from the real options perspective, under conditions of both low endogenous and low exogenous uncertainty, client firms do not have to take an option to defer the action to offshore (McDonald & Siegel, 1986). That is, the client firms do not have to delay or postpone the offshoring decision to another time period as both endogenous and exogenous uncertainties are low. In addition, given the low need to proactively manage uncertainty, they are likely to choose a "captive offshoring model" that is an offshoring subsidiary owned and operated by the client firm that is located in a foreign location. When both endogenous and exogenous uncertainties are low, the client firm tends to have accurate information about the host country's culture and institutional framework. This enables the client firm to pursue captive offshoring which tends to have the lowest coordination and production costs (Cha, Pingry & Thatcher, 2008). Achieving effective collaboration is difficult in global offshoring projects as there are often multiple boundaries that must be bridged simultaneously (Espinosa, Cummings, Wilson & Pearce, 2003; Hinds & Bailey, 2003).

Captive offshoring models avoid the need for a partner and costs including search costs associated with looking for and screening of potential local vendors and costs associated with contract monitoring and enforcement. Offshore captive operations also tend to have low operating costs. Rao (2004) also suggests that captive offshoring models provide firms with the benefits of tax incentives offered by the local offshore governments and access to skilled labor force all contribute to the growth in the captive offshore model. Thus, when there is little need to manage either exogenous or endogenous uncertainty, a captive offshoring model is the most desirable option.

In sum, the scenario represented in Quadrant I represents the most favorable situation for the client firm. Ceteris paribus, client firms are likely to pursue captive offshoring model based in a foreign location when endogenous and exogenous uncertainty is low. Thus we suggest:

P1. A captive offshoring model will be favored over other offshoring models (i.e., joint venture offshoring) by client firms when operating in host countries with low endogenous and low exogenous uncertainty environments.


Quadrant II (Figure 1) depicts a more challenging situation for client firms than Quadrant I. In this scenario client firms face many endogenous uncertainties that could influence their IT offshoring model selection. Endogenous uncertainties as defined earlier include uncertainties that the firm has the ability to take action to reduce or dispel through their learning and development of capabilities. The proprietary knowledge and capabilities developed as a result of coping with endogenous uncertainties can then be used by the firm to manage the endogenous uncertainty in other host countries (Luo, 2002).

One endogenous uncertainty faced by offshore client firms includes the offshore location's cultural uncertainty. Cultural uncertainty is related to the difficulty of operating in a host country due to lack of understanding of the foreign location's values, beliefs, and customs. Cultural incompatibility has been cited as a major stumbling block and concern in international sourcing (Carmel & Nicholson, 2005), but the effects can be mitigated by the intercultural competence of the client and vendor firms (Haried & Ramamurthy, 2009). Research indicates that the lack of cultural readiness could have serious negative effects (Barkema, Bell & Pennings, 1996; Delmonte & McCarthy, 2003). The rate at which the client can learn about the host country culture depends on the "distance" of this culture to the client. The more distant the culture of host country, the harder it is for the local firm to quickly learn that culture as it lacks the absorptive capacity to assimilate this new knowledge (Cohen & Levinthal, 1990). Under such conditions, it is prudent for the local firm to undertake sequential learning so that it could develop the requisite absorptive capacity to develop knowledge about the host country culture (Folta, 1998). Indeed, in order to understand "distant" cultures, firms generally form collaborative ventures with host country partners to help navigate and understand the ways of doing business in these countries (Kogut & Singh, 1988).

Using local partners to overcome cultural uncertainty presents a firm with another type of endogenous uncertainty--the partner uncertainty. This is typically because of the possibility of opportunistic and self-seeking behavior on the part of the host country partners (Hennart & Zeng, 2002; Williamson, 1975). The uncertainty surrounding partner opportunism is further heightened due to information asymmetry and difficulty in evaluating potential partners (Balakrishna & Koza, 1993; Woodcok, Beamish & Makino, 1994). However, over time, firms become better at assessing their local partners and as they develop alliance management capability (Ireland, Hitt & Vaidyanath, 2002), the information asymmetry gradually decreases.

The real options literature posits that in order to resolve endogenous uncertainty firms must undertake projects in stages so that learning can occur incrementally (Chang 1995; Folta, 1998). Research on real options and related work on organizational learning suggests that joint ventures are especially suited for learning about new markets and building capabilities (Kogut & Kulatilaka, 1994; Luo, 2002). In the context of foreign market, joint ventures represent a real option (Kogut, 1991). They help client firms to proactively manage uncertainties by giving them the strategic flexibility to increase commitment if their understanding of the host country market improves and, correspondingly, increasing their ability to exit the market quickly without incurring substantial loss should the host country market situation worsen.

From the point of view of the IT offshoring literature, the client firm's investment in a joint venture (JV) represents an important mechanism by which a client can leverage and acquire new competencies and learn to handle the inherent endogenous uncertainties. Thus, based on the above discussion we argue that clients will undertake a joint venture when utilizing host countries with high endogenous uncertainty and low exogenous uncertainty because the initial costs (due to loss of control) will be more than offset by the gains in learning and strategic flexibility. By opting for equity joint venture offshoring model, clients can manage and limit the effects of the endogenous uncertainties by relying on the partners' resources, including their knowledge of the host country culture, market, and suppliers (Inkpen & Beamish, 1997). Thus, ceteris paribus, we state:

P2: A joint venture offshoring model will be favored over other offshoring models (i.e., third party offshoring model) by client firms when operating in host countries with high endogenous and low exogenous uncertainty environments.


In Quadrant III (Figure 1), the client firms experience high exogenous uncertainty and relatively low endogenous uncertainty. This situation is more ambiguous than the previous situation because in contrast to endogenous uncertainty, client firms have little or no control over the evolution of exogenous uncertainty. Client firms have to deal with a variety of exogenous uncertainties as introduced earlier: political, legal, regulatory, and macroeconomic uncertainty. Client firms engaging in IT offshoring face uncertainties through the threat of major disruptions arising from political upheaval or war in an offshore host country. Typically, businesses prefer to operate in offshore location countries that are politically stable. However, wage rates tend to be lower in less stable countries, thus organizations are often tempted to operate in relatively unstable environments (Davis et al., 2006). Firms also face increased intellectual property issues when offshoring sensitive software development and maintenance to unstable offshore locations. When their resources are not well protected due to weak intellectual property rights regime, firms are more likely to undertake a wait-and-see approach rather than committing large equity upfront (despite the desire to increase control over the venture).

Another important exogenous uncertainty that could impact the client is the macroeconomic uncertainty of the host country. Miller (1992) defines macroeconomic uncertainty as the unpredictability of fluctuations in economic activities and prices in a host country. For example, the global economic crisis and the 2008 terrorist attack in Mumbai, India produced significant uncertainties for the client firms who have offshored IT activities to India and for those considering offshoring to India (Srivastava, Lakshman & Hamm, 2008). These uncertainties are prompting the client firms to consider limiting or discontinuing their offshore investments in India.

A number of studies have supported the view that firms can reduce their exposure to exogenous uncertainties by limiting their levels of direct ownership (Brouthers, 2002; Kobrin, 1983). In the IT outsourcing literature, when contractual hazards are perceived to be high, meaning that the formal contract cannot cover or address the uncertainties involved in the relationship, client firms tend to prefer a client-vendor relationship (Barthelemy, 2003). When the exogenous uncertainties are high, it is prudent for firms to limit their vulnerability by lowering their resource commitment and making sure that they can exit the market quickly without incurring substantial loss should the conditions worsen. Under conditions of high ownership levels, such as in an offshore captive offshore subsidiary, the large investments are not as desirable as they would lead to a commitment level that is difficult to reverse. Previous research indicates firms entering countries with high macroeconomic volatility are less likely to undertake large commitments (Goldberg & Kolstadt, 1995) as flexibility becomes paramount in mitigating this type of uncertainty (Sutcliffe & Zaheer, 1998). Similarly, when political uncertainty is high, firms tend to make lower commitments (Delios & Henisz, 2000). Rather than be constrained by a high ownership offshoring model a firm should engage in an IT offshoring model that allows it to respond to the exogenous uncertainties. The more adaptive mode of entry is the third party offshoring model when compared to other offshoring models. Although the third party offshoring model is associated with less control, the model offers increased flexibility to adapt to changing environments. Furthermore, while a joint venture offshoring model is important when learning and developing new capabilities for dispelling endogenous uncertainty under conditions of exogenous uncertainty; firms have minimal control over the reduction of exogenous uncertainty. In other words, exogenous uncertainty evolves independent of the client firm's actions. Moreover, as the endogenous uncertainty is relatively low in this situation, firms do not have to take any actions to reduce endogenous uncertainty. This suggests that, ceteris paribus:

P3: A third party offshoring model will be favored over other offshoring models (i.e., captive offshoring model) by client firms when operating in host countries with low endogenous and high exogenous uncertainty environments.


At times client firms experience the situation depicted in Quadrant IV (Figure 1). Here endogenous and exogenous uncertainties jointly describe the state that offshore client firms experience during the offshore model selection. We have already discussed that while building capabilities that minimize endogenous uncertainties is possible, it is extremely difficult, if not a significant challenge to accomplish the same as in case of exogenous uncertainty. We argue that learning in environments with high levels of exogenous uncertainty is less manageable and transferable as the decision makers are ignorant of the underlying causes of the uncertainty and the ex post environment is unclear. The ability to build new capabilities is hindered when the firms cannot predict the outcome or assign a probability to it. Indeed, Luo (2002) observed that capability building is negatively related to environmental complexity (which contained macroeconomic, political/legal and socio-cultural dimensions).

Our contention is that client firms that experience high exogenous uncertainty and high endogenous simultaneously will first choose the onsite offshoring model. By bringing resources onsite client firms can reduce some of endogenous uncertainty (i.e., cultural uncertainty) and lower the level of endogenous uncertainty experienced. That is, the firm can learn about partner, host country culture, etc., by interacting with the third party resources onsite. This arrangement also allows the client firms to mitigate the influence of exogenous uncertainty as the job tasks are being performed in the client's location. In other words, this allows the client firms to learn and resolve endogenous uncertainty without being distracted by exogenous uncertainty. After they have developed the necessary capabilities to lower endogenous uncertainty (i.e., reduce the endogenous uncertainty through experience), client firms will pursue one of three offshoring models that we discussed earlier (i.e., captive offshoring, third party offshoring or joint venture offshoring) depending on the exogenous uncertainty in the host county at that time. Ceteris paribus, when dealing with both high endogenous and exogenous uncertainties simultaneously, offshore client firms will first choose onsite offshoring arrangement with a third party vendor.

P4: When dealing with both high endogenous and high exogenous uncertainty environments client firms will first prefer to enter offshoring relationship with an onsite captive offshoring model. After developing capabilities to deal with the endogenous uncertainty, client firms will choose another offshoring model (i.e., captive offshoring) depending on the exogenous uncertainty in the host country at that time.


To further illustrate the relationship between IT offshoring strategy and endogenous and exogenous levels of uncertainty we present a case that demonstrates a shift in offshoring strategy as classified in our offshoring uncertainty framework. The case example is taken from a series of interviews conducted during December 2006 through June 2007 with a client firm who shifted their offshore strategy from Quadrant IV to Quadrant I due to the realization of endogenous and exogenous uncertainties. For each case, we included interviewees from business and technology functions along with both managerial (i.e., senior business and technology managers) and operational (i.e., business analysts, system engineers) level stakeholders. For the purpose of this paper, the selected case example demonstrates an offshore model strategy shift from Quadrant IV to Quadrant I (i.e., the most dissimilar types in terms of their uncertainty combinations of low to high) allows us to highlight the role of uncertainty and IT offshoring strategy. Upon the request of the client firm involved, the client name has been changed to maintain anonymity.


HealthCenter is a diversified industrial corporation, operating in a number of segments: from infrastructure, finance, healthcare, and industrial manufacturing. In 2004, HealthCenter started to investigate different offshore strategies to provide technical and network support utilizing resources in India. The offshore initiative provides initial network and technical support, 24 hours a day, 7 days a week. Examples of the support provided include: network security, infrastructure issues, connectivity, database, applications and general security issues. The goal was to offload the troubleshooting and support issues to India and reduce the turnaround time for issue resolution. The utilization of India resources for support would allow the US based employees to concentrate on design and major projects originating from the U.S.A based HealthCenter. Over the lifetime of the offshore initiative, HealthCenter underwent a shift in their offshore strategy. They initially selected the onsite captive offshoring strategy (Quadrant IV) and evolved into the captive offshore strategy located offsite (Quadrant I) to better fit the uncertainties present in their offshore relationship. Early on in the project, the plan was to bring offshore personnel provided by an offshore vendor firm to the US location to work side by side with the US HealthCenter personnel. The goal was to learn about the Indian culture, test the waters and leverage the intellectual capital of India. However, as HealthCenter matured in their offshore operations and learned to deal with the endogenous and exogenous uncertainties involved, they were able to shift their offshoring strategy to better fit the uncertainties present in the relationship.

Early on from an uncertainty perspective, HealthCenter viewed both the exogenous and endogenous uncertainties to be extremely high. Since this was one of the first offshore experiences of HealthCenter, endogenous uncertainty at this point was seen as high and uncontrollable. They had little understanding and experience in working in the Indian cultural context. From an exogenous standpoint in Quadrant IV, a major uncertainty from the client's perspective was the macro-economic situation of India. Offshore workers were jumping jobs frequently, resulting in loss of productivity and performance due to all of the retraining that was necessary. The senior business manager pointed out that "there was a lot of job hopping... turnover was very high in the IT area.... what people would do is they would ramp their skills up, boom jump a job and get another 30% increase, then boom, go to another job, get another 30%, you can't blame them for trying to increase their standard of living. But we would have to keep retraining, and that became an issue for us." Overtime, HealthCenter determined that opening and operating their own captive offshore center (Quadrant I) would be a strategy to help minimize the exogenous macroeconomic uncertainty.

In addition, cultural issues appeared to play a key role in the initial concerns HealthCenter had in regards to their selected offshore model strategy. However, as HealthCenter garnered experiences in working with the offshore resources, alternatives were uncovered that could limit the effects of cultural issues. The systems engineer noted "one thing that I learned early on was that they don't like to confront us at all. Even though they disagree with us, they nod, say yes, so later on we found out that we basically have to tell them that it is ok to tell us that you don't agree. in their culture you don't go against your boss or manager, you don't argue back with them, whatever they say is right, were not always right and we know that, but sometimes it is good to disagree with the boss." Onsite HealthCenter personnel indicated concerns over the passive nature of the offshore resources. The senior business manager noted that a challenge was "taking a passive culture and making the people a little bit more aggressive to fit the HealthCenter style." The senior business manager noted "people are more passive, because everything is very polite and that is just to me the Indian culture... they need to be aggressive, when they grab that problem, take it and solve it." HealthCenter was able to control some of the endogenous uncertainties by confronting the offshore personnel and explaining to the expectations of open communication in the relationship that appeared to be drastically different due to the offshore culture.

Communication challenges also arose due to cultural issues. HealthCenter had to play an active role in managing and reducing this endogenous uncertainty. The senior IT manager noted "understanding them was a chat was used. it was better if they were typing rather than speaking." Non-verbal communication challenges also emerged due to the cultural differences. During our discussions, the client's business staff noted that "I had them saying yes to me, but they were shaking their heads to me in the American way as no, and then another group of them were saying no to me and shaking their heads to me in an American way of yes." As the offshore experiences of HealthCenter matured they were better able to address and manage these differences by directly addressing the communication challenges that were not understood early on during their offshore relationship.

Economics was another driving force behind the offshore model shift. Early on, bringing Indian personnel onsite to the US location was a cheaper economic strategy than staffing the IT troubleshooting department with US based employees, due to the labor arbitrage that existed among the two countries. The senior business manager pointed out that "the deal was where we would have people come here initially, and then as they did the knowledge transfer they would go back to India and do the work. But what really ended up happening was because there were different rates. If you work onshore at HealthCenter the vendor was charging a certain rate, if the personnel were located and worked offshore the rate went way down. It actually worked for a good couple years, and then the contract kind of went sour, due to the fact that we had way too many people being onshore instead of offshore." At this point in time HealthCenter reevaluated their offshore strategy to better fit the uncertainties that were learned over their initial offshore experiences.

After a few years of experience and an increased understanding of the uncertainties involved, they reevaluated their perceptions of the endogenous and exogenous uncertainties involved to better fit their offshoring strategy to their specific environment. They determined that the early concerns over the cultural issues were not as extreme as initially believed. They also determined that they could influence some of the wage rate issues and job hopping/turnover issues that were rampant in India. As a result, HealthCenter shifted their offshore model into Quadrant I, thus running their own offshore captive center. HealthCenter invested and constructed a dedicated building just for technology and network support that employed around 300 people who were considered full HealthCenter employees. Factors driving the shift according to the senior business manager "we were actually able to reduce our costs a lot. the big difference was that early on we were spending a million dollars on contracting costs, and we were in the 80-20 model. So we would be 20% HealthCenter and 80% contracted. as we learned more about the opportunities in India we thought we were spending way too much on contractor costs. So what we would do is leverage the intellectual talent on India, by opening our own location in India and make the resources that were contractors HealthCenter employees, which really helped lower our turnover and job hopping." Overall, HealthCenter according to its business manager indicated that "I just think it has proved out to be a cost effective way to lower cost of ownership as well as running operations." As a result, it appears that HealthCenter was able to select an offshore model that best fit the uncertainties that were present in their offshoring relationship.

The case of HealthCenter provides a valuable early investigation and demonstration of the role uncertainty plays in a firm's offshore strategy selection. The case also illustrates how a firm's IT offshoring strategy may shift after exogenous and endogenous uncertainties are learned. Further case investigations and empirical work are highly recommended to illustrate the use of our framework to guide firms in matching their selected offshoring model to the endogenous and exogenous uncertainties faced by a client firm.


In this paper, we sought to develop a theoretical framework that would help explain IT offshoring model choices. In doing so, we sought to contribute to the literature on international IT sourcing, commonly referred to as IT offshoring, by highlighting how uncertainty affects a client's IT offshoring decision. In addition, in our theoretical approach (drawing on the real options theory) we overcame some of the limitations with current theoretical approaches that relied on a one-dimensional view of uncertainty. We suggest that the nature of uncertainty is a combination of two different dimensions: endogenous and exogenous. Using the two-dimensional framework to describe the client host country environments allows us to meaningfully and parsimoniously understand the challenges faced by clients while operating in uncertain host country environments. Our illustrative example demonstrates the importance of incorporating uncertainty into the offshore strategy decision and the importance of fit in regards to offshore strategy and the uncertainties present in offshoring. This framework allows for a more precise, theoretically grounded description of uncertainties facing IT offshoring clients in their IT offshoring strategy selections. In particular we suggest that endogenous uncertainty can be influenced by the actions of clients (i.e., by forming joint venture offshoring relationship a client can develop capabilities to mitigate the effects of endogenous uncertainty on the firms operations and performance). In addition, we argue that client actions have little influence on exogenous uncertainty as the environments are too ambiguous for capability development to take place.

Prior research findings on uncertainty and offshoring client firm behavior support our theory. Client firms desiring greater control (i.e., decreasing uncertainty) prefer a subsidiary IT offshore entry mode (Jagersma & van Gorp, 2007). Fitzgerald and Willcocks (1994) suggest that more strategic partnerships are ideal when business and technical uncertainty are high and loose contracts are written. Lee, Miranda, and Kim (2004) observed that firms desiring cost efficiency in their outsourcing relationships would be best served by arm's length relationships whereas those wishing to derive strategic competence or technology catalysis needed to develop network type relationships with their providers. In practice all contracts contain both complete and incomplete sections wherein the governance mechanisms can be viewed as a range of alternatives from a very tight and lengthy contract to no contract with a true partnership relationship. The limitations of contract can be avoided with the use of the subsidiary offshoring model since the client firm is operating the offshore venture. In other offshoring models, a complete contract specifies all of the actions that each party is responsible for in the relationship. Such a contract might reduce the uncertainty faced by organizational decision makers and the risk of opportunism created in the offshoring agreement. However, situations will develop during the course of a multi-year outsourcing contract (i.e., technological obsolescence, political turbulence) that the contract might not cover. . Thus, it is important to incorporate flexibility into an outsourcing contract (Fitzgerald & Willcocks, 1994; Willcocks and Kern, 1998). Flexibility includes the option for the client to change service requirements and for the vendor to change the means by which service requirements are met (Clark, Zmud & McCray, 1995). Often it is the "unwritten contract" between the vendor and client that strengthens the relationship to the point that it becomes an invaluable partnership and relationship (Webb & Laborde, 2005).

Previous outsourcing research has also explored the relationship between success and uncertainty. Research has hypothesized a negative relationship between the level of environmental uncertainty and the outcome of outsourcing (i.e., less successful outsourcing in volatile environments). However, the findings are inconclusive (Dibbern, Goles, Hirschheim & Jayatilaka, 2004). Wang (2002), following transaction cost theory, finds a negative relationship between uncertainty and outsourcing success, whereas Poppo and Zenger (1998) contradict this. One reason for this could be the erroneous assumption in much of the existing offshoring literature that different types of uncertainties (i.e., political, cultural etc.) have similar effect on offshoring decision. Thus, our framework provides valuable insight and extensions to the offshoring literature examining the role of uncertainty and IT offshoring success.

Additionally, the management literature also supports our framework. Earlier studies have found that the greater the host country uncertainty the greater the likelihood that firms will opt for licensing rather than wholly-owned subsidiaries (Kim & Hwang, 1992), and joint ventures rather than wholly-owned subsidiaries (Bell, 1996). This suggests that clients are reluctant to commit resources and prefer to maintain some degree of strategic flexibility when uncertainty is high. Thus, as we posit throughout this study, uncertainty (both endogenous and exogenous) plays a critical role in the IT offshoring decision and should not be ignored.


We anticipate that the insights offered by this study will prove useful to scholars interested in studying success and international IT sourcing strategies. On a practical front, this study shows that attention needs to be given to the role and types of uncertainty inherent to the IT offshoring decision. Often the level and type of uncertainty appears to have been ignored or, alternatively, studies focused on only one of many types of uncertainties. Scholars need to recognize that uncertainty needs to be accounted for and action may need to be taken to support a successful offshoring initiative.

By integrating the organizational learning and real options theory, our paper provides a significant contribution to the IT offshoring arena. The extant management literature suggests that under uncertainty firms must take collaborative ventures rather than investing in a wholly owned subsidiary. The literature also stresses the importance of developing "complete" contracts, which is unrealistic in most offshoring circumstances. However, the same literature is less clear regarding the "type" of offshoring model a firm must undertake in a particular type of uncertainty (endogenous vs. exogenous). Moreover, it understates the relationship between learning and uncertainty. Our paper highlights the notion that firms can dispel endogenous uncertainty through learning whereas they have no control over exogenous uncertainty. It also provides not only a fuller, more holistic explanation of the offshoring model choice but offers normative recommendations to IT offshoring client managers.


Our theory is particularly relevant to practitioners given the exponential growth of IT offshoring investments made by client firms in emerging global markets. As Luo (2001) observed, while uncertainty is present in most markets, it is typically widespread in emerging and under developed economies. Thus, our two-dimensional framework of uncertainty has several implications for client managers making strategic IT offshoring decisions. First, the framework highlights the importance of distinguishing the uncertainty in a particular country from those that are present in other countries. Second, it emphasizes learning as a way of reducing or dispelling endogenous uncertainty and underscores the difficulty that client firms face in developing capabilities to counter exogenous uncertainty.

Clarifying the role and type of uncertainty inherent to the IT offshoring decision should help client firms determine a fit between their IT offshoring strategy and the associated uncertainties to help ensure success. Client firms may start by clarifying the type of uncertainty that they are experiencing or may experience due to context of the offshoring relationship. Client firms who are able to predict and address any uncertainties and fit their IT offshoring strategy to the uncertainties that may be encountered will be in an improved position of success probability when compared to firms who lack a preparation and understanding of the uncertainties inherent to IT offshoring.


Several additional directions for future research present themselves as a result of this analysis. Future research can empirically examine the impact of different uncertainties on the IT offshoring model decision in various regions. IT offshoring practices tend to be more mature in the USA when compared to other locations and could lead to potential differences in the desired client outcomes (Koh, Ang & Straub, 2004). Future research may want to focus on the various offshore vendor locations (i.e., India, China, and Brazil). In addition, research may want to include various client locations that are purchasing the IT offshoring (i.e., USA, Canada, and UK). By incorporating diverse client and vendor locations, we may gain unique insight in regard to how uncertainty is managed.

Our illustrative case example provides some indication that client firms perceptions of endogenous uncertainty are resolved through learning. An interesting venue for future research is the issue of client's evaluation of uncertainty (endogenous and exogenous) and how it manages the uncertainty. Such research might explicitly examine the differences across various client stakeholder groups and trace their evolution. As the relationship and experiences mature, client firms/stakeholders may refine/redefine their assessment of uncertainty. This suggests that longitudinal studies may be needed to consider the uncertainty dimensions at different stages of the relationship. Future research may also seek to explain why these evaluations change. For example, is the change due to learning or is it due to institutional effects (i.e., imitative behavior). In sum, our framework provides rich avenues for future researchers to pursue.


The international sourcing of IT products/services is clearly a phenomenon that will not disappear in the foreseeable future having evolved from being a cost saving initiative to more of a survival strategy for an increasing number of organizations in today's economic climate. The study's expanded view of the uncertainties involved in the IT offshoring decision offers some unique insights into how client firms need to evaluate the various levels of uncertainty and fit their IT offshoring strategy to both endogenous and exogenous uncertainties. Our illustrative case study lends some support to our conceptual uncertainty framework. We hope our this work will fuel further research on the influence of uncertainty in international sourcing decisions to help ensure organizations realize the most effective fit for their IT sourcing needs.


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Mujtaba Ahsan, Pittsburg State University

Peter Haried, University of Wisconsin--La Crosse

Martina Musteen, San Diego State University
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Author:Ahsan, Mujtaba; Haried, Peter; Musteen, Martina
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Date:Jul 1, 2010
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