Outsourcing risk management in offshore software development Projects

Abstract

This study is related to outsourcing risk management in information technology generally and in offshore software development projects particularly. An increase in project profits matter a lot to the software vendor. Therefore, this study finds out the effect of different factors including the selection of contract on the growth of project profits. The data for this study is collected from an Indian software vendor that handles offshore projects. With the help of this data, the researcher becomes able to explain how a vendor selects a contract. The selection of a contract is based on several characteristics. These characteristics include the shortage of resources, uncertainty about the requirements and unsure team size of project.  It is found that there is a direct relationship between the selection of a contract and the profits associated with that project. Project profits also have direct relationship with the size of project and duration of project.

Chapter One: Introduction

Outsourcing different kinds of projects including software development has  been increased greatly in the last few years. Outsourcing the projects to other countries results in a decrease in expenses. More and more projects are being outsourced from Europe and United States to countries where labor is cheap and development

costs are less as compared to the costs for the same projects in the parent country. As globalization is increasing, businesses are giving attention to outsourcing. Indian software industry has undergone great growth in the last few years as this industry receives huge software development projects from all over the world. Outsourcing has several advantages but there are some disadvantages too like a client cannot monitor the development phases of software closely. (Lacity and Willcocks 84-93)

The researcher investigates the determinants of offshore contractual arrangements, and the manner in which contract choice affects project performance. The research site is a leading Indian software developer with an extensive network of clients in Asia, Europe, and North America. The size of the Indian software industry was $ 8.1 billion in 2002. Most of the revenue comes from turnkey development and maintenance projects under different contractual arrangements, ranging from individual contracts for individual projects to long-term (10-year) contracts for dedicated offshore centers. The size of the Indian industry, the offshore setting, and the availability of relevant data provide a unique opportunity to study contracts in this market.

In a world of complete information, it does not matter which type of contract is chose; parameters of different types of contracts can always be chosen to make them ex ante welfare equivalent. However, most real-world settings are characterized by incomplete information (Hart and Moore p. 21-28), and the software context is no exception. It seems unreasonable to assume that contracting parties can foresee all future contingencies at the time of contracting. All else being the same, a risk-averse agent prefers a contract that protects him from risk ex post to a contract that does not adequately compensate for risk ex ante because of incomplete information. Analyzing how contracts are formed, and the extent to which contracts account for risks and uncertainties, is therefore important in understanding the dynamics behind what drives success. Since offshore development involves contracting between parties from different economies in differing political and cultural climates, it provides a unique opportunity in this regard.

Based on this motivation, the researcher examines the adoption of the two prevalent forms of contracting in the software industry-fixed-price contracts and time-and-materials contracts. The major portion of the development risk is borne by the vendor under a fixed-price contract, and the client under a time-and-materials contract. While a risk-neutral vendor would be indifferent between these contractual forms, a risk-averse vendor (client) would prefer a time-and-materials (fixed-price) contract, all else equal. A testable implication of this premise is that with a risk-averse vendor, the preference for a time-and-materials contract is increasing in task uncertainty. The researcher tests this implication using a data set containing details of a single software vendor’s contractual arrangements with 93 offshore clients. The researcher identifies a set of vendor-, client-, and project-related characteristics to explain the choice of the contractual form.

The researcher’s contributions are threefold. First, this study is one of the first attempts to empirically study the determinants of contract choice in the software industry. Although there is some discussion of the importance of outsourcing contracts in the trade press (King and Hoffman 56-75, Binstock 133-140), extant literature offers little by way of when a particular contractual form would prevail. Second, this study builds on the growing body of research on the Indian offshore software industry (Banerjee and Duflo 989-1017). Although this literature focuses on industry wide practices and business issues, little work has been conducted at the project or organization level.

Finally, the researcher addresses the linkage between contract choice and project profits, and identifies other variables that determine project profits in offshore software projects. Although project performance has been measured in terms of costs, schedules, and quality metrics in past research (Krishnan et al. 745-759, Gopal et al. 193-200), this is the first time absolute project profits has been used to characterize project performance.

Chapter Two: Review of Related Literature

“Outsourcing is a phenomenon in which a user organization (client) transfers property or decision rights over information technology (IT) infrastructure to an external (vendor) organization” (Loh and Venkatraman p. 334-378). The history of information technology has seen both successes and failures. Eastman Kodak was the first to outsource its IT services (Applegate and Montealegre p. 43-52). Since then the outsourcing industry is expanding with at the rate of 20 percent per annul. (Caldwell and McGee p. 734-98). Thirty percent of budget regarding information technology was spent on outsourcing in 2000 where as $ 64 billion were spent on services related to outsourcing of information technology throughout the world in 2001 (Mason p. 19). Although IT outsourcing is growing rapidly, software vendors and clients are still conscious to find whether outsourcing is beneficial enough, regarding management and economic both, that it can balance the costs and risks related to IT outsourcing.

IT outsourcing helps in reducing and controlling the costs that the vendor has to pay for conducting the information technology operations (Ang and Cummings p. 235-256; Ang and Straub p. 535-552). Another reason to outsource IT projects is to find the required talent if it is not available in-house. It is found that the expected benefits are not gained sometimes (Hirschheim and Lacity p.  99-107) and failures in IT outsourcing are also reported (Aubert et al. p. 685-693, p. 7068-7079). It is found from a Gartner Dataquest Report that two-third of the contracts, in which IT outsourcing was done to reduce the cost, have been successful where as one-third of those contracts were badly failed as the requirements were not met.  (Caldwell p. 54-64, p.  84-94). It is also found that some companies are planning to cancel their outsourcing contracts as their requirements were not met and they will be concentrating on bringing the new technical talent, though at a greater cost, to their in-house. (Buxbaum p.  38). As there are mixed experiences of IT outsourcing, the concept of outsourcing is still alive.

As outsourcing is increasing, it is obvious that firms of all sizes are in the market and these firms believe that their IT outsourcing is providing them value. The rate of success in IT outsourcing is increasing because vendors are learning from their past mistakes and thus providing value for money. (Willcocks and Lacity p. 355-384). As success and failure both are observed in IT outsourcing, there is a need to find out the factors that are essential to deliver value for money.

Definitions of Outsourcing

There seems to be confusion in the management literature about what is meant by the term “outsourcing.” In their study of information technology (IT) outsourcing, Lob and Venkatraman defined outsourcing as “the significant contribution by external vendors in the physical and/or human resources associated with the entire or specific components of the IT infrastructure in the user organization” (p. 9). Kotabe has defined outsourcing as “products supplied to the multinational firm by independent suppliers from around the world” and “the extent of components and finished products supplied to the firm by independent suppliers” (Kotabe, 103). Lee and Hitt have defined outsourcing as “the reliance on external sources for manufacturing components and other value-adding activities” (Lei & Hitt, 836). Generally, the definition of outsourcing used in studies of the subject is so broad that it includes virtually any good or service that an organization procures from outside firms.

However, defining outsourcing simply in terms of procurement activities does not capture the true strategic nature of the issue. Outsourcing is not simply a purchasing decision; all firms purchase elements of their operations. On the contrary, we suggest that outsourcing is less common and represents the fundamental decision to reject the internalization of an activity. In this way, outsourcing is a highly strategic decision that has the potential to cause ripple effects throughout the entire organization. Further, we propose that outsourcing may arise in two ways. First, growth in outsourcing may result if internal activities are substituted with the help of external purchases. In this way, it can be viewed as a discontinuation of internal production (whether it be production of goods or services) and an initiation of procurement from outside suppliers. To the extent that this type of outsourcing reduces a firm’s involvement in successive stages of production, substitution based outsourcing may be viewed as vertical disintegration. This seems to be the most commonly understood type of outsourcing.

However, outsourcing may also occur through abstention. Outsourcing need not be limited to those activities that are shifted to external suppliers. Outsourcing also takes place when some goods are not produced in-house or when some services are not provided in-house in the past. However, we believe that abstention-based outsourcing is unique from basic procurement, because the former only occurs when the internalization of the good or service outsourced was within the acquiring firm’s managerial and/or financial capabilities. In other words, as with substitution-based outsourcing, abstention-based outsourcing also reflects a decision to reject internalization. Therefore, we suggest that organizations having no choice but to acquire a particular good or service from an external source (because of a lack of capital or expertise, for example) are not outsourcing, because the internalization of the activity in question is not an option. In other words, rejecting the internalization of the focal activity was never a choice, and the firm is simply engaging in procurement. Whether virtual or network organizations, as well as other types of firms founded with the intention of performing only a narrow range of activities in-house from inception, are considered to be outsourcing must. be determined on a firm-by-firm (or even activity-by-activity) basis. Indeed, this definition of outsourcing may exclude many types of activities that have been considered outsourced in prior research. Previous definitions of outsourcing have not made the substitution/abstention distinction and, therefore, have not allowed researchers to approach the subject of outsourcing from a common starting point.

Read also about Threshold Capabilities

The Advantages of Outsourcing

Although the definition of outsourcing has been somewhat uncertain, many potential benefits of outsourcing have been identified in the literature. Those most often discussed are improved financial performance (attributable, in part, to almost immediate cost improvements) and various nonfinancial performance effects, such as a heightened focus on core competencies. These and other proposed advantages of outsourcing are discussed below.

Outsourcing firms often achieve cost advantages relative to vertically integrated firms (Bettis, Bradley, & Hamel, 7-22; D’Aveni & Ravenscraft, 1167-1206; Kotabe, 1-15; Lei & Hitt, 835-859; Quinn, 976-1123). Through outsourcing, manufacturing costs decline and investment in plant and equipment can be reduced (Bettis et al., 7-22). This reduced investment in manufacturing capacity lowers fixed costs and leads to a lower break-even point. The short-run cost improvement swiftly reinforces the outsourcing decision. Thus, outsourcing may be an attractive method of improving a firm’s financial performance, especially in the short run.

Outsourcing may contribute to other advantages as well. In-house production increases organizational commitment to a specific type of technology and may constrain flexibility in the long run (Harrigan, 686-697). However, firms focusing on outsourcing can switch suppliers as new, more cost effective technologies become available. In addition, outsourcing allows for quick response to changes in the environment (Dess, Rasheed, McLaughlin, & Priem, 7-20) in ways that do not increase costs associated with bureaucracy (D’Aveni & Ravenscraft, 1167-1206). Thus, firms that outsource may achieve long-run advantages compared to firms relying on internal production. As noted by Quinn, “virtually all staff and value chain activities are activities that an outside entity, by concentrating specialists and technologies in the area, can perform better than all but a few companies for whom that activity is only one of many” (37).

An increased focus on an organization’s core competencies is another important benefit associated with outsourcing (Dess et al., 7-20; Kotabe & Murray, 383-408; Quinn, 76-84). Outsourcing noncore activities allows the firm to increase managerial attention and resource allocation to those tasks that it does best and to rely on management teams in other organizations to oversee tasks at which the outsourcing firm is at a relative disadvantage.

The importance of defining and developing the core competence of the firm has attained great popularity among management researchers and practitioners (Prahalad & Hamel, 79-93). This has increasingly led to a move away from market-based definitions of businesses toward more competence-based definitions. For example Honda’s core competence is in small engine production and, therefore, the domain of Honda’s activities can be seen as any business in which this core competence finds an application. Nike’s core competencies are in the design and marketing of shoes rather than in their manufacture. Therefore, Nike has focused on these aspects of the athletic shoe industry and has relied on outside firms for virtually all manufacturing activities. Quinn, Doorley, and Paquette (79-87) and Quinn (97-121) also make a strong case for outsourcing activities in which a firm cannot excel to provide the firm with heightened focus on its core competencies.

Other non-financial benefits of outsourcing have received less attention in research. One additional advantage is that it tends to promote competition among outside suppliers, thereby ensuring availability of higher-quality goods and services in the future (Kotabe & Murray, 383-408). Quality improvements may also be realized by outsourcers, because they can oftentimes choose suppliers whose products or services are considered to be among the best in the world (Dess et al., 7-20; Quinn, 65-87). Outsourcing also spreads risk (Quinn, 65-87). By using outside suppliers for products or services, an outsourcer is able to take advantage of emerging technology without investing significant amounts of capital in that technology. Thus, the outsourcer is able to switch suppliers when market conditions demand.

The Disadvantages of Outsourcing

Although outsourcing’s potential benefits are many, some argue that reliance on outside suppliers is likely to lead to a loss of overall market performance (Bettis et al., 7-22; Kotabe, 65-84). One of the most serious threats resulting from a reliance on outsourcing is declining innovation by the outsourcer. Outsourcing can lead to a loss of long-run research and development (R&D) competitiveness (Teece, 65-95) because it is often used as a substitute for innovation. As a result, firms that outsource are likely to lose touch with new technological breakthroughs that offer opportunities for product and process innovations (Kotabe, 65-84).

In addition, as suppliers gain knowledge of the product being manufactured, they may use that knowledge to begin marketing the product on their own (Prahalad & Hamel, 79-93). In fact, firms from the Pacific Rim have a well-established pattern of market entry based on outsourcing partnerships. Many Asian firms have made their initial entrance into U.S. markets by first entering supplier arrangements with U.S. manufacturers, and subsequently marketing their own brands aggressively. In this way, many Asian firms have achieved market dominance.

There are several other dangers associated with outsourcing. First, the cost savings associated with outsourcing may not be as great as they seem, especially with respect to foreign suppliers. The transaction costs associated with repeated market-based transactions, especially overseas, can be significant. In addition, as long as foreign wages remain relatively low and the dollar remains relatively strong, foreign outsourcing is attractive (Markides & Berg, 113-120). However, success attributable to low foreign wages and a strong dollar is fleeting advantage. Also, outsourcing requires a shift in overhead allocation to those products or activities that remain in-house. This reallocation of overhead degrades the apparent financial performance of the remaining products or activities and raises their vulnerability to subsequent outsourcing (Bettis et al., 7-22), perhaps leading to an outsourcing spiral. Thus, those remaining products or activities that were performing satisfactorily before the onset of outsourcing may erroneously be targets for future outsourcing. In addition, longer lead times resulting from spatial dispersion cause several problems, such as larger inventories, communication and coordination difficulties, lower demand fulfillment, and unexpected transportation and expediting costs (Levy, 343-360). Tariffs are another danger associated with outsourcing, as are increases in the difficulty of bringing back into the firm activities that may now add value because of market shifts (Dess et al., 7-20).

The preceding discussion of the benefits and dangers of outsourcing make it clear that reliance on outsourcing is not necessarily a viable competitive strategy. On the contrary, continuously switching from one supplier to another may merely postpone the “day of reckoning” when firms must fix what is wrong with their organizations (Markides & Berg, 113-120).

Drivers of Outsourcing

While the IT outsourcing literature identifies many reasons why firms outsource IT, a few themes emerge. According to Smith, Mitra and Narasimhan (61-93) the drivers of IT outsourcing are classified into five categories. These five categories are: cost reduction, focus on core competence, liquidity needs, IT capability factors, and environmental factors. These categories are not exhaustive but identify the major drivers of IT outsourcing.

Cost Reduction
Cost reduction and control are often given as reasons for outsourcing IT (Alpar & Saharia 197-217). “It is commonly believed that an outside vendor can provide the same level of service at a lower cost than the internal IT department. The often-cited rationale is that the vendor typically has better economies of scale, tighter control over fringe benefits, better access to lower-cost labor pools, and more focused expertise in managing IT” (Smith, Mitra and Narasimhan, p64). It must be acknowledged, however, that cost reduction through IT outsourcing is controversial, especially because the vendor often maintains the identical infrastructure in terms of equipment and personnel and has to make a profit through the arrangement (Lacity & Hirschheim 73-86).

Focus on Core Competence
Companies may outsource their IT to simplify the management agenda and focus on the firm’s core business (Cross 94-103). “Senior executives often consider the IT function a commodity service, best managed by a large supplier. Effective IT management requires senior management commitment and expertise. If managers do not see a strategic role for IT, then IT outsourcing is often viewed as a means of conserving managerial effort and focusing on areas with greater strategic potential” (Smith, Mitra and Narasimhan, p64) . Also, firms can outsource a significant portion of the IT infrastructure, while still retaining those aspects (such as critical applications development) that are viewed as strategic.

Cash Needs
Companies often outsource IT to generate cash (McFarlan & Nolan 9-23). “An important part of many IT outsourcing agreements is an introductory cash payment by the vendor for the tangible and intangible IT assets of the client. The vendor then uses this infrastructure (and may also hire the IT staff of the client) to provide contract services to the client and others” (Smith, Mitra and Narasimhan, p64). This initial payment would be particularly attractive to firms burdened with short-term liabilities and higher debt. For a firm considering divestiture, outsourcing can liquefy an asset that is unlikely to be recognized in the deal (McFarlan & Nolan 9-23). Firms considering acquisitions may consider outsourcing as a means of generating capital to partially fund the acquisition.

IS Capability Factors
IT capability factors may also motivate outsourcing (Grover et al. 33-44). Outsourcing can also be used to create or retool an IT infrastructure without substantial capital investments. “Sometimes outsourcing follows the failure of a major system or a breakdown in IT performance, resulting in financial losses for the company. For example, Massachusetts Blue Cross and Blue Shield’s decision to outsource was motivated by the failure of major systems development projects and severe financial losses” (Smith, Mitra and Narasimhan, p64). Internal politics, dissatisfaction with the IS department, lack of trust in the CIO, and inadequate service from the IT department are a few of the other reasons why firms outsource IT.

Environmental Factors
Environmental factors often play a role in the outsourcing decision (Hu et al 288-301). These include factors that are not specific to the firm, but exist in its industry or in the economy at the time of outsourcing. “The decision to outsource IT may be driven by imitative behavior among firms or by a mix of external media, vendor pressure, and internal communications at the personal level among managers”  (Smith, Mitra and Narasimhan, p65). After the Kodak outsourcing decision, many large firms began to view IT outsourcing as a viable alternative. The availability of qualified vendors willing to provide the service, pressure from vendors, positive stock market reaction to the phenomenon (Loh &Venkatraman 334-358), and extensive coverage in the popular press are other factors that also influence the decision.

Propositions
Firms that outsource IT do so in spite of the significant risks associated with the practice. Prominent risks associated with IT outsourcing include the loss of in-house IT capability, loss of power with respect to the vendor, hidden costs, technological obsolescence, loss of innovative ability, and the loss of key IT employees (Earl 26-32). The fast pace of technological change makes it difficult to design contracts that cover all future aspects of the arrangement. Even large companies may enter into IT outsourcing agreements that are contrary to their own interests (Caldwell 86-87). The trade literature cites several examples of companies that have painstakingly reversed their IT outsourcing decisions (Caldwell 86-87). In short, large-scale IT outsourcing can have a major impact on a firm’s long-term profitability, cost structure, and ability to use IT as a strategic resource.

Why do some firms outsource their IT while others in their industries retain the function in-house? The propositions examined in this paper share a common assumption: that firms that outsource a large part of their IT infrastructure in spite of the risks associated with the arrangement do so because they differ from other firms in their industries with respect to the key drivers discussed earlier.

Cost reduction is an often-cited motivation for outsourcing. Thus, firms that choose to outsource IT in spite of the associated risks must be more cost-conscious than other firms in their industries. A greater need to reduce costs may arise from lower growth opportunities, higher debt, or falling profitability. In such cases, IT outsourcing is part of a larger cost-cutting effort for the entire company.

Firms are more likely to accept the risks associated with IT outsourcing if the event is part of an organization-wide effort to focus on their core competence and sell non-core assets. For such firms, IT outsourcing is not performed in isolation, but as part of a larger effort (McFarlan, & Nolan 9-23). For example, in the well-known Kodak example, IT outsourcing was initiated as part of an organization-wide effort to focus on the core (Alpar & Saharia 197-217). The criteria used to evaluate IT outsourcing are similar to those used to consider outsourcing other non-core areas.

There are several important parts involved in the arrangement of IT sourcing. The most important among them is the initial payment that a vendor pays for the management of IT assets of that firm (McFarlan, & Nolan 9-23). Firms that find this payment attractive is more likely to outsource IT in spite of the risks. Such firms would have a greater need to generate cash than others in their industries, such as when having low cash reserves, higher debt, and consequently higher debt service payments.

It has been asserted that IT outsourcing is a “game for losers” and that firms that outsource IT are often plagued by low profitability and performance (Strassman 75). Empirical evidence also suggests that the stock market reacts favorably to IT outsourcing announcements. Therefore, firms with low profitability may outsource IT for short-term reductions in cost or to send a positive message to their shareholders.

These propositions are not intended to be exhaustive and are naturally restricted to those that can be directly or indirectly tested through publicly available financial data. Nevertheless, they have wide support in the academic and trade literature, and illustrate the major determinants of IT outsourcing as stated in that literature.

Characteristics of Outsourcing Strategies

Two generic types of outsourcing are proposed here: peripheral outsourcing and core outsourcing. The first type occurs when firms acquire less strategically relevant, peripheral activities from external suppliers. The second type occurs when firms acquire activities that are considered highly important to long-run success. What constitutes a core or peripheral activity is essentially a judgment by each individual firm, based on what it considers as its core competency and the strategy it intends to pursue. Thus, although it is possible that some similarities may exist within the industry, there is considerable scope for variation among firms within the industry.

In addition, it is proposed here that each of these outsourcing strategies is not a unidimensional concept. Instead, outsourcing strategies can be conceptualized as having two fundamental properties, breadth and depth. Breadth is defined here as the number of activities (i.e., accounting, maintenance, machining) outsourced as a percentage of the total number of activities in which the firm could be engaged. This is similar to Harrigan’s (638 -652) conceptualization of breadth of vertical integration.

Outsourcing strategies vary greatly in their breadth. On the one hand, many firms choose to maintain internalization of most of their activities and, therefore, have relatively narrow outsourcing strategies. Such firms may decide to outsource only a few activities while maintaining tight control over most others. In contrast, other firms choose to take a much broader approach to their outsourcing strategies by farming-out many peripheral activities, and even some activities much closer to their core capabilities.

The second dimension of outsourcing strategies is “depth.” Whereas firms outsourcing some portion of many activities are considered to have higher levels of breadth, those firms farming-out a higher portion of the value of each outsourced activity are considered to have deeper outsourcing strategies. Thus, given that an activity is outsourced, depth is the extent to which a firm outsources a higher portion of that activity on average, For example, all else being equal, a firm farming-out an average of, say, 80% of each outsourced activity is considered to have a deeper outsourcing strategy than an identical firm farming-out an average of only 10% of each outsourced activity.

It is proposed here that the breadth and depth dimensions combine to form an organization’s overall outsourcing strategy. Attempting to determine a firm’s reliance on outsourcing strategies by examining breadth or depth in isolation is much less meaningful than examining them in tandem. A firm’s dependence on outsourcing cannot be measured simply by the number of activities that the firm (partially) outsources. Examining a firm’s level of outsourcing, only in terms of breadth misses an important aspect of the phenomenon: the extent to which each activity is provided by an outside supplier. Only when a firm’s breadth and depth of outsourcing are combined does an accurate picture of the firm’s reliance on outsourcing emerge. In the current study, breadth and depth are multiplied together to form a single indicator of the level of outsourcing. This combined construct is called “outsourcing intensity,” and reflects the firm’s overall reliance on outsourcing.

Performance Implications of Outsourcing Intensity

The current level of understanding of making outsourcing decisions and their effects on organizations is based primarily on anecdotal evidence. Potential performance enhancements that may result from a carefully formulated outsourcing strategy are suggested by the competency-based and resource-based perspectives on strategic management. “As mentioned previously, the competency-based view suggests that a firm should continuously invest in those activities that constitute its core competence while outsourcing the rest” (Prahalad & Hamel, 79). The core competencies provide both the basis and the direction for the growth of the firm (Peteraf, 179-191). Similarly, the resource-based view suggests that sustained competitive advantage is possible only through developing resources and capabilities that are valuable, rare, imperfectly imitable, and nonsubstitutable (Barney, 99-120; Grant, 114-135). Thus, the resource-based view suggests that inputs that are traded should be procured from the market, because investments in their creation are unlikely to lead to any sustainable competitive advantage.

Potential benefits of outsourcing, such as cost improvements and a more narrow focus on core competencies, make outsourcing an attractive option. On the other hand, potential disadvantages, such as declining innovation by outsourcing firms and eventual competition from suppliers, make the benefits of outsourcing suspect. Thus, the performance implications of varying levels of outsourcing intensity appear uncertain. To clarify some of-the misunderstandings that underlie this debate, and to proceed toward resolving the issue of performance consequences of outsourcing, we propose firm performance to be influenced by the two types of outsourcing (peripheral and core) in unique ways.

Peripheral Outsourcing. By peeling off layers of peripheral tasks and shifting their production to highly focused, specialist organizations, firms can see enhanced performance (Bettis et al., 7-22; D’Aveni & Ravenscraft, 1167-1206; Kotabe, 1-15; Lei & Hitt, 835-859; Quinn, 76-95). This performance improvement relative to nonoutsourcing firms manifests itself in three ways. First, reducing peripheral activities allows firms to focus on those activities they do best. This heightened focus on core competencies may greatly enhance firm performance by allowing the firm to become more innovative and agile in its core domain. Second, outsourcing peripheral activities may greatly improve the quality of those activities (Dess et al., 7-20). Specialist organizations, by focusing their attention on a very narrow set of functions, perform them much more successfully than could the outsourcing firm, to which a given peripheral activity is only one of many (Quinn, 76-94). Finally, outsourcing peripheral activities to the lowest-cost suppliers may lead to incremental improvements in a firm’s overall cost position. Therefore, it is proposed that, by pursuing intense peripheral outsourcing strategies, firms can achieve higher levels of performance relative to firms that do not outsource their peripheral activities.

Core Outsourcing. Firm performance may also be influenced by the intensity with which a firm outsources its near-core, strategically relevant activities. Several authors have noted that this “core outsourcing” may lead to declining innovation (Kotabe, 623-638; Teece, 65-95) and eventual competition from suppliers (Bettis et al., 7-22; Prahalad & Hamel, 79-93; Quinn, 76-95), resulting in reduced firm performance. In addition, the transfer of specialized knowledge necessary when firms outsource near-core activities may also place the firm’s future performance in jeopardy. The decline of industries such as televisions, bicycles, and automobiles in the U.S. has consistently been used as examples of the dangers of outsourcing near-core activities (Bettis et al., 7-22). Therefore, it is proposed that firms outsourcing activities very near their strategic core will achieve lower levels of performance relative to firms that retain tight control over these activities.

Moderating Relationships. The relationships between the two types of outsourcing and firm performance may be more complex than they first appear. When certain conditions exist, the positive effects of peripheral outsourcing and the negative effects of core outsourcing may be increased or reduced. Below, the potential moderating effects of firm strategy and environmental dynamism are discussed.

Generic Firm Strategy. The relationship between outsourcing intensity and firm performance may be contingent on a firm’s generic strategy. By using peripheral outsourcing, cost leaders may not only heighten their focus on their core competencies and improve the quality of their non-strategic activities (Dess et al., 7-20), but they may also incrementally lower their total costs. This improved cost position may greatly enhance their competitiveness relative to industry rivals, thereby leading to superior performance. Therefore, it is proposed that a cost leadership strategy strengthens the positive effect (or reduces any negative effect of peripheral outsourcing on firm performance.

On the contrary, firms pursuing a differentiation strategy, while also benefiting from a heightened focus on core competencies and improved peripheral activity quality, stand to gain less (relative to cost leaders) by outsourcing peripheral activities. The incremental cost improvements that may be achieved through peripheral outsourcing are less significant to differentiators, because these cost improvements may have little direct effect on the differentiation, of their outputs. Although there may be an indirect effect of cost reductions for differentiators (i.e., they may have more resources with which to pursue differentiation-enhancing activities), we believe that differentiators have less to gain relative to cost leaders. Thus, a differentiation strategy is proposed to weaken the positive effect (or strengthen the negative effect) of peripheral outsourcing on firm performance.

With respect to core outsourcing, the situation is different. Although firms outsourcing activities near their core skills are proposed to have lower levels of performance, the negative performance effects are likely to be different for cost leaders than they are for differentiators. For cost leaders, the drawbacks of near-core outsourcing may be partially offset by the improvement in their cost competitiveness that results from their actively seeking out the lowest-cost provider of each near-core activity. In this way, a cost leadership strategy is proposed to reduce the negative effect (or increase the positive effect) of core outsourcing on performance.

The opposite relationship may occur for differentiators. Harrigan (638 -652) noted that it is critical for differentiators to determine which activities drive their differentiation (i.e., their core activities) and keep them in-house. Differentiators that outsource higher levels of their unique, differentiation-enhancing internal transfers (Barney, 45-63) will likely find that their control over these activities has been sacrificed. This, in turn, may lead to erosion of the differentiator’s competitive position. Thus, any negative effect of core outsourcing on firm performance is likely increased for firms pursuing a differentiation strategy.

In summary, any benefits of outsourcing are more likely to be realized by cost leaders than by differentiators, and any costs are more likely to be borne by differentiators than by cost leaders.

Environmental Dynamism. Dynamism of the organization’s external environment may also moderate the relationships between the two types of outsourcing intensity and firm performance. Because environments represent one of the major sources of contingency faced by firms, outsourcing intensity may not affect the performance of firms in different environments equally. Rather, the influence of outsourcing on firm performance may be contingent on the level of environmental dynamism.

The effect of outsourcing may increase with increasing levels of environmental dynamism. By relying on outsiders for peripheral and near-core activities in more dynamic environments, firms are able to take advantage of emerging technologies without investing large amounts of capital in them (Quinn, 74-95). Furthermore, when new technologies emerge, outsourcing firms may switch suppliers, when contractually allowable, to exploit any cost or quality improvements that may then be available (Dess et al., 7-20). Therefore, environmental dynamism increases an important benefit of outsourcing (technology-related flexibility), thereby increasing the positive effects of outsourcing on firm performance and partially offsetting the negative effects..

On the contrary, the performance effects of outsourcing intensity may decline in stable environments. There are two reasons for this. First, an important advantage of outsourcing is that it allows firms to switch suppliers as technological considerations demand. In more stable environments, the outsourcing-related benefits associated with changes in technology are much less pronounced than they are in more dynamic environments, because production and service technologies are changing much less rapidly. Thus, environmental stability reduces an important benefit of outsourcing. Second, firms in more stable environments may find it more difficult to avoid the transfer of knowledge associated with shifting activities to external, organizations. A firm’s competitive advantage is largely based on its ability to obscure the connection between its resources and skills and its success in the industry. This causal ambiguity (Dierickx & Cool, 1504-1511) may be much less pronounced in stable environments, leading outsourcing firms to inadvertently divulge their source of competitive advantage to their suppliers. Thus, environmental stability likely increases the negative effect of outsourcing on firm performance.

What Risks Need To Be Managed?
Most IT firms are involved with some element of outsourcing. To achieve the benefits of outsourcing, financial institutions must ask the following questions:

Are Performance Metrics Being Actively Monitored To Ensure the IT firm Is Getting the Service It Deserves?
This not only helps the IT firm in receiving the services specified in the contract but also helps to resolve problems with the service provider early before they escalate into much larger problems.

Is The IT firm Actively Reevaluating And Updating Its List Of Performance Metrics On Its IT Outsourcing Contract?
Some of the IT firm’s initial metric requirements may no longer need to be as tight or may no longer even be needed. Identifying both unnecessary measures and any new metrics that are needed will reduce unnecessary costs and keep the outsourced area aligned with evolving business needs. This will also cut down on the common syndrome where users feel that they are not being provided with what they contracted for, even though their current needs had never been specified in the contract. (Huber 114)

Does The IT firm Link Compensation to Performance in Its Contract Agreements?
Compensation can be tied with specific performance metrics; it can also be linked with the profits gained or saved based on the IT firm’s previous service experiences. There are many ways of imposing both rewards and penalties based on the service provider’s performance. As with the performance metrics, compensation and penalties should be actively reevaluated to get the most out of the outsourcing partnership.

Does The IT firm Have Processes in Place to Document the Service Provider’s Understanding And Adherence To The IT firm’s Internal Standards, Policies, And Regulatory Requirements?
IT firms that outsource work cannot outsource their legal or customer obligations. As discussed below, recent regulatory guidance reinforces a IT firm’s obligation to properly manage its service providers. Consider whether your outsourcer shares your IT firm’s respect for and compliance with FDIC Improvement Act (FDICIA) and regulatory requirements. This is especially relevant to a number of the new Internet Service Providers that currently serve the financial services community.

Does The IT firm View The Outsourcing As A Business Partnership Or As A Quick Fix Or Low-Cost Solution?
Terminating one outsourcer and entering into a new arrangement with another can be very costly, both monetarily and in terms of service disruptions during the transition to the new outsourcer. The more the two entities work together and adapt to each other as business strategies and technologies change, the further ahead both will be. Therefore, many businesses now consider their service providers to be outsourcing or alliance partners.

Does The IT firm’s Contract Take into Consideration Evolving Technologies or the Potential Regulatory Requirements That May Develop?
In the new economy, technology is developing at a rapid pace. The current services, skills, and technologies provided by the IT firm’s best-fit provider of today will probably not keep the IT firm at the head of the pack two years from now–or even one year from now. As the IT firm’s business plans mold to the evolving market and as new technologies appear to enhance its ability, the IT firm’s outsourcing provider also must adapt. If the appropriate contractual plans don’t exist already, ensure they are included during the IT firm’s next contract negotiation. If not, the service provider will continue to provide what the IT firm initially contracted for and at a very nominal rate to the provider. The cost to your IT firm in missed opportunities, however, will not be so nominal. In addition, as regulatory expectations change to reflect new issues in the economy and in technology, the IT firm’s outsourcer needs to demonstrate its ability and willingness to adapt accordingly.

Best Practices for Mitigating Outsourcing Risk
We have found that IT firms with solid outsourcing track records begin with a clear sense of the competencies that make them unique and give them strength in the market; these are their core competencies. Outsourcing these core competencies would bring excessive risk–a loss of the expertise and skills that characterize the IT firm and that shape its products and services. The following are critical best practices.

Develop an IT outsourcing strategy that reflects the IT firm’s strengths and its vision. Deciding to outsource an IT-related process or service usually results in considerable change: Employees will be affected, overhead costs will change, management focus will shift, and cycle times will shrink. Without a cohesive strategy that recognizes the potential for change, fragmented IT outsourcing activities can lead to problems that snowball into customer dissatisfaction. In developing strategy, IT firms should consider their sensitivity to this risk.

Developing a strategy with realistic financial goals is crucial. Outsourcing may reduce costs, including wages, salaries, and benefits, but these savings are generally short term at best. The real financial advantages lie with allowing IT management to focus time and resources on what the IT firm does best and where it earns most. The need to invest in new capital equipment also often leads a IT firm to consider outsourcing.

Outsource IT processes in which the IT firm lacks expertise or where it is difficult to achieve efficiency. Processes and services that do not make the IT firm unique and are not necessary to the continued success of the IT firm are candidates for outsourcing. The IT firm is apt to be less than competent in many of these areas. The first and most obvious candidates for outsourcing are generally functions such as network management and help desk administration.

Work with trusted outsourcers, yet clearly communicate expectations in the contract. The success of outsourcing depends a great deal on the outsourcer selection process. For some activities, one or two people may be able to select the outsourcer and transfer the process. This is typical of commodity services with a deep, experienced outsourcer market, such as photocopy services or garbage removal. For other activities, people from several areas of the company may need to shape the overall expectations for an outsourcer, identify the best outsourcer available, and transfer the process to the outsourcer.

Best-practices companies put together an outsourcer selection team that includes representation by all potential users. Members of this team will help write the request for proposal (RFP), review proposals from candidates, and interview final candidates. The RFP should be thorough enough to allow all candidates to develop a realistic solution with accurate prices. Withholding information needed to determine the level and scope of work will lead to outsourcer failure, frustration, and lack of incentives to perform.

Visits to the outsourcer’s place of business help verify proposal information, confirm the outsourcer’s ability to handle the proposed volume of work, and provide a preliminary check of the outsourcer’s ability to perform as expected. In addition, reference checks can provide invaluable insights into an outsourcer’s loyalty, integrity, and willingness to satisfy its customers or trading partners.

Many outsourcers offer a standard contract to expedite the approval process. Outsourcing contracts can be full of loopholes; with a standard contract, the outsourcing company is apt to be the victim. Even a IT firm that outsources a number of processes will not have the experience of an outsourcer. An experienced lawyer should help with negotiations and contract preparation.

In addition, companies should create a replacement plan in case they have to switch outsourcers. Most companies do not have the expertise or staff needed to bring a process quickly and smoothly in-house; a well-thought-out transition plan can minimize the potential for costly delays and customer dissatisfaction.

Create an integrated team of company and outsourcer staff to manage the transition or start-up process and oversee ongoing performance. Many companies fail in their attempts at outsourcing because they neglect the one group that has the greatest power to make it successful: employees. Transition planning should begin when the IT firm first considers outsourcing. Ideally, both the IT firm and the outsourcer should involve their human resource experts early in this planning process. The plan should describe the business process transfer activities, IT firm and outsourcer roles and responsibilities, and any changes in employee salary, wages, and benefits.

Best-practices companies choose an outsourcer that is prepared to address human resource issues before the contract is awarded. A potential outsourcer who does not explore these issues early in the bidding process will fail to consider not only cultural issues that will affect employee performance but also factors that could lead to costly legal disputes.

IT firms must also minimize the impact of the outsourcing decision-making process on employee productivity and morale. The uncertainty that employees face during the transition will directly affect work output. Keeping the transition process short and communicating openly and often will help minimize doubts. The more information a IT firm can provide to its employees once they know their work will be outsourced, the less acute their uncertainty.

IT firms should closely monitor the transition process, including progress, service levels, employee morale, and cost savings. The interfaces between internal processes and outsourced processes should also be monitored.

Link outsourcer compensation to outsourcer performance. The first step in tying outsourcer compensation to performance is to identify performance measures. The next step involves collecting baseline measures before the outsourcer takes over.

Outsourcer performance requirements should specify 100% of the outcomes. If an outsourcer must meet 90% of all service requests within three days, the other 10% may never be met. Holding the outsourcer fully accountable would mean specifying performance levels for this 10%. In this case, full accountability might mean meeting 90% of all service requests within three days and the balance within five days.

Best-practices companies provide incentives that encourage peak performance from outsourcers and include penalties for substandard performance. Cash penalties may fall short of compensating a company for the full extent of its losses in the case of extreme nonperformance. But by including a cash penalty in the contract, the company will be able to get the full attention of the outsourcer’s top management if performance starts to slip.

The contract should distinguish between critical measures that the outsourcer will be penalized for failing to meet and noncritical measures. For noncritical measures, the outsourcer may face significantly smaller penalties or the thresholds for nonperformance may be lower.

In addition, financial measures should be adjusted for inflation. Without this, faltering performance may appear to be consistent performance, and average performance may actually be superior performance.

 

 

Chapter Three: Research Hypotheses

Contracts found in the offshore software development area can be broadly classified into tow categories—fixed-price contracts and time-and-material contracts (Figure 1) Banerjee and Duflo (989-1017) show that in a market characterized by highly uncertain reputations of clients and vendors, these two contractual types strictly dominate other mixed or hybrid contract types. Other arrangements that exist are variations of these two broad types. Fixed-price contracts include a fixed fee for the software negotiated before the start of the project. The vendor bears the major part of the risk in this case. In a time-and-materials contract, the vendor contracts out his services at a certain rate. The client is responsible for monitoring progress on the project and thus bears the cost of over-runs.

In developing testable implications regarding contract choice, the researcher assumes that the decision makers for the client and the vendor are risk averse. Most Indian vendors are financially smaller than their European or North American clients. Therefore, the financial burden of a terminated contract to the vendor is considerable. In addition, the decision makers for both the vendor and the client are aware of a loss of personal reputation in the case of terminated or unsuccessful projects. From the client side, non-delivery of the required software could result in loss of revenues and time. The researcher categorizes the factors of interest in the following manner to facilitate discussion and clarity.

Software Development Risks

Software development is an inherently uncertain process. Barki et al (203-225) identify requirements uncertainty and project size as significant variables that characterize risk in a software project. Thus, projects that are large and projects with greater requirements uncertainty pose greater risks and task uncertainty. As a result, the researcher could expect a risk-averse vendor to prefer time and material contracts in such cases.

Hypothesis 1: Increased perceived requirements uncertainty is associated with a higher probability of a time-and-materials contract.

Hypothesis 2: Larger projects are associated with a higher probability of a time-and-materials contract.

The importance of people in software development activities has also been stressed in past research (Gopal et al. 193-200). The lack of trained software engineers is a major problem in most software companies, and this is particularly so in the Indian context (Nidomolu and Goodman 15-22). Attrition in the software industry remains high as the market for software engineers continues to present attractive prospects for trained personnel. Projects requiring specific training impose even greater risk because training costs are often not recovered. The availability of trained personnel to work on a project is therefore a risk that adversely affects task uncertainty, leading the researcher to the following hypothesis.

Hypothesis 3: Higher perceived risk of availability of trained personnel is associated with a higher probability of a time-and-materials contract.

Client Knowledge Set

In an outsourcing arrangement, the role of the client cannot be overlooked. The researcher tries to capture certain aspects of the client’s knowledge and evaluates their impact on chosen contract type. In the transaction costs literature, it is accepted that the ability to foresee future contingencies reduces transactions costs and improves contracting efficiencies (Williamson 233-261). Clients with greater experience in handling offshore outsourcing contracts can be expected to have greater ability to specify contractual terms more precisely, which mitigates task uncertainty from the vendor’s point of view. Also, system specifications tend to be more precise and well defined, and monitoring the vendor would be more efficient and less expensive. Anecdotal evidence of the importance of client knowledge and competence in managing the software development activity exists (Lacity and Hirschheim 23-25). Consequently, the vendor may be more inclined to accept a fixed-price contract since the overall risk of the project is reduced. Additionally, more experienced clients are, all else being equal, potential repeat customers. Therefore, there are incentives for the vendor to accept a fixed-price contract for the current project.

Hypothesis 4: Perceptions of higher client MIS experience and associated with higher probabilities of a fixed-price contract.

Hypothesis 5: Perceptions of higher client experience with outsourcing are associated with higher probabilities of a fixed-price contract.

Bargaining Power

The contract choice depends on the relative bargaining power of the two parties. Given the earlier premise that both the client and the vendor are risk averse on the margin, each party would prefer a contract form that would shield them from the risks inherent in the contractual arrangement, all else being equal. In this context, the client would prefer a fixed-price contract that transfers the risk to the vendor, and the vendor would prefer a time-and-materials contract. Bargaining power weakens the association between task uncertainty and contract choice. A vendor (client) with considerable bargaining power would be able to negotiate a time-and-materials (fixed-price) contract independent of task uncertainty. Studying bargaining power variables in this setting will improve our understanding of how these affect contract choice.

Some common indicators of bargaining power in the context include the reputation of the parties, future business potential and the relative size of the parties (Banerjee and Duflo 989-1017). The reputation of the client increases the bargaining power and can be leveraged by the client during the contracting process. Similarly, the possibility of future business with the client can also increase the client’s bargaining power. Size of the client relative to the vendor is an important variable that has been studies in other outsourcing contexts and strongly increases client’s bargaining power (Mjoen and Tallman 257-274).

A variable that can arguably reduce the client’s bargaining power is the importance of the project to the client. The more important the project is to the client, the less the client will be using her bargaining power. Clearly, vendor reputation and size are also important; however, the researcher has data from only one vendor. Based on these arguments, the researcher proposes the following.

Hypothesis 6: Perceptions of higher client reputation are associated with higher probabilities of a fixed-price contract.

Hypothesis 7: Perceptions of higher future business potential are associated with higher probabilities of a fixed-price contract.

Hypothesis 8: Larger clients are associated with higher probabilities of a fixed-price contract.

Hypothesis 9: Perceptions of greater project importance to the client are associated with higher probabilities of a time-and-materials contract.

Market Conditions

Competition in the offshore software industry provides the client with an alternative, thereby preventing the vendor from locking in the customer (Lacity and Hirschheim 23-27). Williamson (233-261) discusses the effects of having alternative suppliers on the contracts formed and the transaction costs. Thus, the presence of competition reduces the vendor’s bargaining power. On the other hand, if the vendor has already completed several projects for the client and has an established relationship, then the transactions costs of switching to an alternative vendor can be an issue for the client.

Hypothesis 10: Perceptions of greater competition will be associated with higher probabilities of a fixed-price contract.

Hypothesis 11: A higher number of projects completed by the vendor for the client will be associated with higher probabilities of a time-and-materials contract.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Chapter Four: Methodology and Data Collection

Research Site: The data for this research were collected on 93 projects completed between 1995 and 1998 by a leading offshore developer in India. The firm employs around 5,000 people with its primary area of expertise being software development and maintenance of business systems. It has five primary development centers in India and offices in Europe, the United States, and Japan. The researcher developed a questionnaire after discussions with the senior management at the research site and tested it before administrating to project personnel.

In some cases, the project was in development during questionnaire administration and in others, the project was close to completion. To minimize recall bias, data for different aspects of the project was sought from different persons, and in certain cases, two or more people answered the same questionnaire items for the same project independently. If there was a clear gap between the two responses, the project was dropped from the analysis. The respective project managers provided the project-specific details and marketing or business unit manager provided the client-and contract-specific information. The perceptual information was gathered through the questionnaire and the project information was extracted from the company database. The sample consists of 55 time-and-materials and 38 fixed-price contracts. The projects in the sample were completed for 32 clients, with the highest number of projects per client being 4, 10 projects were maintenance; 34 were development; and 49 were re-engineering projects.

Variable Descriptions: The data for this study were tested for reliability and principal component analysis was used to identify patterns within the individual questionnaire items. To ensure validity, wherever possible, the researcher created several questionnaire items for each of the perceptual variables. Using multiple items for a variable increases the validity of the variable, and it also becomes possible to assess the reliability of the measurement. The variable descriptions are given in Table 1. To assess reliability of the multiple-item factors, the researcher calculated Cronbach’s alpha for each of these factors. In general, the items had good reliability scores, as shown in Table 2.

Most of the variables using multiple questionnaire items were taken from previous work in software outsourcing and software development (Barki et al 203-225, Nidomolu 191-219). Therefore, confirmatory factor analysis (principal components) was performed on these questionnaire items prior to subsequent use. The principal components were calculated and used in subsequent analysis rather than the individual items to conserve the degrees of freedom. The principal components used were thus a smaller set of factors capturing the maximum possible variance in the original set of questionnaire items.

Among the variables studied, new measures were created for two variables (client experience and client MIS experience) based on Lacity and Hirschheim (23-29) and discussions with project managers. These two multiple-item variables showed good validity and reliability measures. The human resources variables were adapted from previous researcher (Gopal et al 193-200). No factor analysis was performed on single-item variables or binary variables. Some of our measures are single item and are therefore potentially susceptible to measurement problems. The summary statistics are shown in Table 2.

Data Analysis: The researcher hypothesized that the contract choice is a function of information available to the parties during eh contracting stage. The researcher uses regression analysis to test the hypotheses. Since the dependent variable contract is binary, the researcher cannot use ordinary least squares as OLS estimates are inefficient and cannot be restricted to the [0,1] interval. Therefore, the researcher uses a probit regression specification to test the hypotheses.

Where C equals zero if the contract is a time-and-materials contract and one if it is a fixed-price contract. The exogenous variables are listed in Table 3.

Since effort and client size are interval variables and are large compared to other variables, the researcher standardizes these variables. The probit specification was estimated using maximum likelihood and the results are shown in Table 4. Note that since project type is used as a control variable. The researcher does not specify any expectation for the sign of this coefficient.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Chapter Five: Results and Discussion

Referring to the estimation results in Table 3, the overall model fit is good with a statistically significant chi-square of 57.46 (p value < 0.01). The correlation between the predicted contract type and the actual chosen contract type is around 0.90, indicating a good fit.

The researcher receives support for the hypotheses of task uncertainty on contract choice. The analysis indicates that projects with more uncertain requirements are associated with time-and-materials contracts since the vendor faces considerable risk from changing requirements. Similarly, larger projects in terms of effort are associated with time-and-materials contracts. As mentioned before, project size is a strong variable in software engineering and therefore is an important part of the contracting parties’ decision-making process. Moreover, cost and schedule models show that estimation error is higher in larger projects. This is because the complexity of size increases the degree of task uncertainty, thus making the outcomes of the project riskier (Jones 54-62). The results also indicate that projects involving considerable risk of getting and retaining trained personnel are associated with a time-and-materials contract.

The two hypotheses regarding the client knowledge set receive mixed support. Hypothesis 4 regarding the client MIS department experience receives strong support while Hypothesis 5 is not supported. The presence of a strong client MIS department reduces the risk for the vendor in the outsourcing relationship as indicated by Lacity et al. (84-93). Therefore, the vendor is more amenable to accepting a fixed-price contract. An experienced client MIS department also increases the bargaining power of the client by providing her with an alternative-to keep the software development in-house. The discussions with the project managers at the researcher site support this reasoning, indicating that a capable MIS department would rather keep the project in-house than outsourcing offshore, and incur the costs of managing the project remotely.

Hypothesis 5 that relates client experience with outsourcing is not supported in the results. The insignificance of the coefficient can be attributed to low variance in the independent variable. Managers at the research site confirmed that clients in the client set did not have much prior experience in offshore outsourcing.

Turning the attention to the impact of bargaining power on contract choice, Hypotheses 6 and 7 are not supported. Hypothesis 6 pertains to client reputation and Hypothesis 7 pertains to future business. Although discussions with project managers indicated that these variables were influential in their decision making, the researcher does not see a significant result. It is possible that since both variables were single-item measures, there is significant measurement error in these constructs. In addition, these two questions may also be measuring the same underlying phenomenon.

Hypothesis 8 is supported and pertains to the client size variable. The results show that larger clients are associated with a higher probability of a fixed-price contract. The size of the firm increases the client’s bargaining power and also indicates to the vendor a strong possibility of future business. Therefore, the vendor can be induced into accept a fixed-price contract. Hypothesis 9, which refers to the importance of the project to the client, is also supported. The researcher had hypothesized that the importance of the project to the client organization would reduce the client’s bargaining power. Therefore, an increase in this variable would be associated with an increasing probability of a time-and-materials contract. The client might also prefer a time-and-materials contract since it can control the development process of important projects.

Hypothesis 10, pertaining to the presence of competition, receives mixed support in the analysis. The coefficient for client-country competition is in the expected direction. Thus, the presence of alternative developers in the client country, by reducing the bargaining power of the vendor, is associated with an increase the probability of a fixed-price contract. The coefficient for vendor-country competition is opposite to the researcher’s expectation and is significant. The presence of other vendors in India increases the probability of time-and-materials contracts.

The researcher proposes the following reason for this finding. All software vendors in India operate at approximately the same margins and costs. This reduces the influence of costs alone as the deciding factor between different Indian firms. Therefore, the choice between different vendors falls on past performance or reputation. The firm with the highest reputation and quality is able to leverage this factor and in effect, increase its bargaining power. Banerjee and Duflo (989-1017) confirm the influence of reputation in the Indian software industry. Thus, an increase in vendor-country competition indirectly increases the bargaining power of the vendor. This could be particularly true in the sample since the research site is a market leader in the Indian industry. Additionally, the fact that two single item measures were used to characterize competition in this setting could lead to the ambiguous results. More research is required in creating valid measures for competition in the offshore market.

The final hypothesis pertains to the number of prior projects completed by the vendor for the same client, and receives strong support. An increase in the number of prior projects tends to increase the bargaining power of the vendor since this leads to a lock-in effect. The client would prefer to contract again with the same vendor rather than incur transaction costs of finding another vendor. In the Indian context in 1995, trust was a vital factor in the client’s decision making since the offshore market was perceived as being risky. Therefore, the client would be more amenable to a time-and-materials contract in repeat projects since the trust factor is higher.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Chapter Six: Tests of Contract Efficiency—Framework

The results of the previous section established that a set of vendor-specific task uncertainty factors and client-specific characteristics help explain contract choice. These results underscore the incompleteness in the contracting environment. The sample also presents a unique opportunity to test the efficiency of offshore contracts, which the researcher presents in this section

It is important to recognize that an incomplete contract need not be inefficient with respect to available information at the time of contracting. If the parameters of the contract are chosen efficiently, any deviation of the actual performance under the contract from expected performance should only be a function of contingencies that were unanticipated; there should be no systematic and predictable association between realized performance under the contract and information upon which the contract is based. To formalize these arguments, let C be the type of contract chosen. Let

EP = f (C, Ic)

Where EP = expected profit, C = contract type and Ic = information available during the contracting period.

Contract efficiency implies that the contract choice incorporates all available information known at the time of contracting. If the contracts were chosen efficiently with respect to the information variables Ic, then any deviation of the realized profit from the expected profit should be random. Let

RP = EP + e                                                              (2)

Where RP = realized profit and e = random error term. Substituting for EP, we get

RP = f (C, Ic) + e                                                       (3)

Expanding this equation and assuming a linear specification, we get the following.

where RP is the realized profit, C is the contract choice, and Ic represents the information set at the time of contracting. The results of the previous section suggest that ?1 will be nonzero. In particular, if the vendor’s profits were to be higher under the preferred time-and-material contracts, we expect ?1 < 0. Since the contract is formed using the information variables known then, the effects of these variables should be limited to the contracting stage, and should have no effect on realized profits once the contract type is controlled for. In other words, once the contract type is controlled for, the information variables should be uncorrelated with the deviation of the realized profit from expected profit. Therefore, in Equation (4), the coefficient vector ?2 should be zero. Even if one of the coefficients in ?2 is not zero, then that variable influences the realized profits after controlling for the contract type, indicating that the contract was inefficient with respect to that variable.

Finally, to add power to these tests, the researcher includes some ex post “performance” variables in Equation (4) that would explain some of the deviation of the realized profit from expected profit (i.e., variables correlated with the error term e). A typical example of a development factor is the actual duration of the project (cycle time). Although the contracting parties may have expectations of the schedule of the project, the actual duration is susceptible to unforeseen circumstances such as rework that may have arisen during the development of the software. Therefore, this variable should be able to explain some of the variance in the profits that is part of the error term e. Thus, we argument Equation (4) with these variables called D in the following manner.

where D = development factors (known ex post). The researcher includes three development factors-duration, core team size, and the level of employee turnover during the project.

All the three development variables are important variables from a software engineering perspective. The duration of a software project is an important aspect of a software project and has been used in the literature as a performance metric for a software project (Gopal et al. 193-200, Harter et al. 451-467).

Core team size refers to the core number of programmers that were assigned to the development team during the development of the project. Note that actual number of people working on a project changes over time but the core team personnel remain on the project. The quality of programmers or project personnel also has been shown to have a positive effect on project performance. Krishnan et al. (745-759) and Guinan et al. (101-125) study the effects of programmer experience and quality on the performance in software projects. In our context, rather than use people skills, we use the core team size since our dependent variable is project profit rather than effort or quality.

The third variable is the effect of employee turnover in the project team during the project life cycle. Although the trade press has addressed this phenomenon in some detail (Mandell 20, McGee 46), there has been little empirical work in analyzing the effects of employee attrition in development projects. High attrition rates in software development firms are common in the Indian software industry as well (Nidomolu and Goodman 15-22, Miller and Kaye 130-137). Thus, the effects of employee attrition will significantly impact the profits of the vendor. Given the nature of attrition, it is difficult to capture an exact figure since people occupy different levels of importance in a project team. The loss of a project manager will be more keenly felt that the loss of a programmer.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Chapter Seven: Analysis and Results of Profit Model

To estimate Equation (5), the independent variables the researcher uses are the Ic variables, which the researcher described in previous sections of this paper, the development factors, and the contract type (fixed-price or time-and-materials). The dependent variable is project profit measured in Indian rupees. Project profits are the net profits attributed to each project, and is calculated by subtracting all travel- and project-related costs from the total revenues attributable to the project. The profit was not converted into dollars to avoid confounding the analysis with currency exchange risks and other currency fluctuations that occurred in the market during the project.

In estimating Equation (5), it is important to keep in mind that one of the independent variables, C, is an endogenous variable. The vendor has an expectation of profits from a given contract type, which drives his preference for a certain contract type. This creates an endogeneity problem in the estimation of Equation (5). It is well known that in the presence of endogeneity problem, OLS estimates are biased and inconsistent (Maddala 67-83). The researcher uses the Heckman two-stage model to control for this endogeneity problem (Heckman 475-492). In particular, the researcher uses the treatments effect model described in Barnow et al. (43-59) to estimate Equation (5). In Stage 1 of this method, a probit regression is estimated of the reduced form contract choice equation, and inverse Mills ratios, referred to as ?i, are calculated for each of the data points.

Stage two of the procedure entails introducing the ?i as an additional explanatory variable in Equation (5). This two-step procedure produces consistent and unbiased estimates of Equation (5). In particular, the researcher estimates the following equation:

where eH is the Heckman-corrected error term.

Equation (6) can now be estimated using OLS, and the resulting coefficients are consistent and unbiased. Least square estimates of the standard errors are, however, biased and corrected errors are calculated using the estimator proposed in Heckman (475-492). The coefficient ?3 of the ?S is used to control for endogeneity, and is indicative of the presence or absence of the effects of endogeneity or sample selection in the specification. Before estimating Equation (6) using OLS, the researcher tested for the presence of multi-collinearity (Belsley et al. 56-64), outliers and normality of errors (Shapiro and Wilks 591-612), and no assumptions of the OLS model were rejected. The estimates from Heckman’s two stage model are heteroskedastic in nature and the analysis automatically corrects the errors (Maddala 96-108). The results of the estimation of Equation (6) are shown in Table 4. Note that the earlier probit results remain the same since the first stage of the Heckman procedure involves estimating a probit contract choice model.

Recall that one of the maintained hypotheses specified that the vendor prefers a time-and-materials contract. The researcher sees support for that hypothesis in this analysis. The analysis indicates that after controlling for all other factors, time-and-materials projects are associated with higher profits. The coefficient ?3 is significant in this model, indicating the presence of endogeneity. The contract variable is significant even after controlling for endogeneity and the presence of the lambdas. The contract variable indicates that vendor profits are Rs 748,000 (roughly $ 20,000) less in a fixed-price contract, all else being equal. Thus, the null hypothesis of contract equivalence can be dismissed. This finding is significant because it indicates that even in the presence of a risk premium that might have been charged for fixed-price projects, the vendor might still incur some losses due to unforeseen circumstances in fixed-price contracts.

The researcher hypothesized that if the contract were efficient with respect to the Ic variables, there should be no significant effect of these variables on realized profits once the contract type was controlled for. The hypothesis of efficiency is rejected in the sample since several of the Ic variables are significant at the p = 0.05 level. Therefore, the analysis indicates that the contract is inefficient with respect to Ic variables. This result is also consistent with earlier empirical work in rational expectations that finds limited support for the rational expectations hypothesis (Lovell 110-124). In the context, since the researcher does not have expected profit information, the researcher cannot conclusively reject the contract efficiency hypothesis. Although the results provide evidence in support of contract inefficiency, this result should be interpreted with a caveat. Note that in this sample, contracts are of only two types. The significance of Ic variables in the profit model may also be due to this restriction of contract types.

Project effort is significant and is associated with increases of the project profits. This result is not surprising since effort is an integral part of the software engineering process, and is a strong driver of most performance measures in software development. Requirements uncertainty also affects project profits and this result is intuitive. Shaky requirements are the bane of most software development projects. A more surprising result from our analysis is the association between number of prior projects executed for the same client and project profits. Past research on software contracting in custom software development has shown vendors adopting a “low-baling” strategy, i.e., bid low at first and then hike rates once the client is locked in (Whang 1343-1357). Hence it is argued that profits to the vendor will increase over time with more projects executed with the same client. The underlying reasoning behind this argument is the vendor’s learning about the client’s business domain, thereby leading to more efficient execution of later projects and, consequently, greater profits. However, in the present setting, the researcher finds the opposite effect, i.e., profits reduce in subsequent projects for the same client.

The researcher discussed the above results with senior managers at the researcher site and identified several possible reasons for this finding. First, it was established that the vendor had signed long-term contracts on fixed billing rates with nominal adjustments for annual increments with large clients. The projects in the sample spanned from 1994 to 1998—a period of high growth in both global software and the Indian offshore market. Due to the strong demand for software services, the market rate for software services had increased much faster than the annual increments worked into long-term contracts with clients. This situation could have driven a decrease in profits in repeat projects for the vendor. In addition, the researcher learned that in these long-term multiproject contractual arrangements, the vendor typically retained the same experienced staff in repeat projects with clients. This was to leverage the learning that had already taken place. The vendor was, however, forced to pay his experienced staff market-level compensation, thereby squeezing the vendor’s margins further. Thus, the vendor finds itself locked into a long-term contractual agreement with the client on one hand and an increasing cost of development on the other, leading to lower margins on such profits.

The decrease in profits with repeat projects may also be explained due to the intense competition among software vendors in the Indian software industry. It is possible that large clients may be benefiting from this competition and hence gaining more of the surplus in projects over time. The association of offshore competition variable with lower profits in the analysis further supports this argument.

The two competition variables are significant but with opposite signs. Offshore competition is associated with lower profits for the vendor. This result is intuitive since the presence of competition in the offshore market limits the price that the vendor can charge to a client and therefore, would have a negative effect on the vendor profit. The presence of onshore competition tends to increase the profit from a project. Project importance to the client reduces the profits from a project for the vendor, and this result is explained by the high level of interaction required in such projects between the client and vendor teams. Managers at the research site indicated that critical projects had a higher level of travel requirements, larger onsite teams for requirements and testing stages and increased costs of monitoring and reporting progress on the project. Since these activities are usually not specified in the contract but emerge during the development phase of the projects, their costs tend to drive down vendor profits on average. The intangible benefits gained from successful implementation of a critical project are, however, immerse and accrue over a longer time period.

The other variable that is significant is the client MIS experience variable that tends to increase the profit of the vendor. As discussed in Lacity and Willcocks (363-408), the presence of an experienced MIS department at the client side makes the outsourcing arrangement more efficient. Requirement ambiguity is reduced and open issues arising during the development phase are sorted out more quickly. This is true for both contract types since the experienced MIS department provides quicker feedback and useful information that is uniformity beneficial for both parties. Discussions with project managers at the research site indicated that this is particularly true in the offshore context where the cultural and linguistic differences add to the technical complexity already present in the outsourcing process.

The researcher had hypothesized that the three development factors would be significant. Team size and duration of the project are significant, but employee turnover is significant in the analysis. It is possible that the subjective nature of the turnover measure did not capture the whole impact of attrition on the project team. The core team size variable is significant and indicates that the vendor’s profit increases from an additional team member. Larger core teams tend to be more self-contained units with fewer interactions with noncore team members on average. Therefore, coordination time and effort with noncore team members are reduced. Additionally, larger-core teams are generally able to manage attrition from the team better since there are other members within the team who might be able to pick up the slack.

The result with respect to the last development factor, project duration, is ambiguous because of the sign of the coefficient. The variable is statistically significant, indicating that longer projects are associated with greater vendor profits. This is usually true for time-and-materials projects since longer projects involve larger billings, which translate to larger profit. However, in fixed-price contracts, this result is contrary to what is expected. In a fixed-price project, the vendor has an incentive to shorten the duration of a project since the price is fixed. This result could again be driven by the sample where time-and-materials projects are larger than fixed-price projects. In addition a t-test on effort between the two contract types indicates that time-and-materials projects are statistically larger than fixed-price projects (t = 2.861, p < 0.005).

 

 

 

 

 

 

 

 

Chapter Eight: Conclusions and Future Research

In this paper, the researcher has empirically studied how contracts are chosen in offshore software development projects contracts, and bargaining power to determine the influence of information known to the contracting parties during contracting on the chosen contract type. The results support both the underlying assumptions regarding the different contract preferences the two contracting parties have and the hypotheses made on the actual contract chosen.

In subsequent analysis, the research studies the efficiency of the contract by examining the effect of the information known during contracting on project profits. The researcher also introduces three development factors to improve the fit of the regression analysis. The researcher also interprets these results in the context of prior contributions in the software engineering literature. Although the researcher is hampered by the lack of some data, the results indicate that the vendor does make higher profits from time-and-materials contracts, controlling for project specific variables such as project type and effort. Moreover, the researcher sees evidence suggesting that the contract is not efficient with respect to the information variables known during contracting. These information variables have a residual impact on project profit and the researcher interprets these results accordingly.

The analysis is subject to a few limitations and caveats. First, the researcher does not have first-hand data from the individual clients and data on contract prices due to confidentiality reasons. The researcher was not allowed to directly contact clients and elicit responses to the questionnaires. Second, some of the data is susceptible to recall bias and results must be interpreted accordingly. Third, as noted earlier, this research is limited to two contract choices. However, two contracts may not be always optimal. Further research is required to understand other incentive-based contracts such as agreements with a fixed price and a reward or penalty for the vendor based on the project outcome in terms of project schedule and product quality.. The researcher uses prior theory in task uncertainty, incomplete

Although the context here is offshore software outsourcing, some broad results can be applied to domestic outsourcing as well. Many of the task uncertainty and risk factors studied apply to domestic outsourcing as well and the efficiency of contracts needs to be analyzed in this context. Additionally, it is possible that reputation of vendors and clients are more easily verifiable and disputes more easily resolved in domestic outsourcing, therefore leading to the occurrence of more hybrid contractual types. At present, there is a lack of empirical analysis of contracts in domestic outsourcing. This is an area for future research and it would also be beneficial to conduct a comparison of contract types between these types of outsourcing and their effects on project performance. Cost is often the primary reason to move offshore but it would be useful to analyze the determinants of this cost advantage and how they accrue over different contract types at the end of a project.

 

 

 

 

 

 

 

 

 

Figure 1: Project timeline

 

 

 

 

 

 

 

 

 

 

 

 

Description and measurement
Size (effort)
Person-hours. The correlation between effort and size is very high (Boehm 1983) and therefore the use of effort is acceptable.
Requirements uncertainty
Measured using four questionnaire items adapted from Barki et al. (1993)
Project type
Categorical variable: development, re-engineering and maintenance
Human resources (training)
Measured the availability of trained personnel for the project using three questionnaire items adapted from Barki et al. (1993)
Client MIS experience
Measured using four questionnaire itemws adapted from discussion in Lacity and Hirschheim (1993)
Client experience with outsourcing
Measured the client’s past experience with outsourcing using two questionnaire items adapted from  Lacity and Hirschheim (1993)
Project importance
Measured using one questionnaire item on a 5-point scale
Client reputation
Measured using one questionnaire item on a 5-point scale
Future business
Measured using one questionnaire item on a 5-point scale
Client size
Measured as the number of employees in the whole organization
Competition (client)
Presence of alternative development firms in the client country
Competition (vendor)
Presence of other competing development firms in India
No. of prior projects
Number of projects completed by the vendor for the same client
Contract type
Contract type in binary-fixed-price and time-and-materials
Table 1: Variable descriptions

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 2: Summary statistics

 

 

Variable
Unit/scale
Mean
Std dev
C.A.
Var (1)
MIS experience
5-point scale
3.121
0.85
0.77
0.61
Client experience
5-point scale
3.101
0.989
0.56
0.68
Effort
Person-days
995.21
1,345.74
NA
NA
Requirements uncertainty
5-point scale
2.192
1.023
0.90
0.77
HRR training risk
5-point scale
2.559
0.967
0.76
0.68
Project importance
5-point scale
4.070
0.864
NA
NA
Client reputation
5-point scale
2.694
1.272
NA
NA
Future business
5-point scale
1.777
0.942
NA
NA
Client size
No. of employees
65,779
85, 712
NA
NA
Competition (vendor)
5-point scale
2.530
1.264
NA
NA
Competition (client)
5-point scale
2.542
1.046
NA
NA
Prior projects
No. of projects
7.858
13.147
NA
NA
Project type
Categorical (1-3)
1.24
0.62
NA
NA
Contract
Binary
0.40
0.49
NA
NA
Project duration
Calendar days
358.48
290.73
NA
NA
Employee turnover
5-point scale
1.902
0.804
0.73
0.78
Team size
# of people
9.102
8.269
NA
NA
Project profit
‘000s, Indian Rs.
191.41
528.34
NA
NA
 

 

 

Table 3: Probit Analysis Results

 

Variable
Coefficient
Std Error
Pr(?Z?>)
supported
Requirements uncertainty
-0.90
0.33
0.006
Yes
Effort
-0.42
0.21
0.50
Yes
Human resources (training)
-0.90
0.28
0.001
Yes
MIS experience
0.80
0.29
0.006
Yes
Client experience
0.22
0.21
0.27
Ns
Client reputation
0.05
0.16
0.73
Ns
Future business
0.30
0.19
0.10
Ns
Client size
0.59
0.26
0.02
Yes
Project importance
-0.58
0.27
0.03
Yes
Competition (vendor)
-1.37
0.34
0.0001
Yes
Competition (client)
0.83
0.32
0.01
No
No. of prior projects
-0.08
0.02
0.001
Yes
Project type
-0.80
0.36
0.02
NA
Notes. -2 Log L = 62.90. Model fit = 57.46 with 12 df. Significant at p < 0.01. Association of predicted probabilities and observed responses = 90.2%.

ns: Not significant

NA: Not applicable

 

Contract: 0 – time-and-materials, 1-fixed-price, N = 93.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 4: Regression of Realized Profit (N = 93)

 

Variable
Parameter
Std Error
p-value
Intercept
1243.96
562.04
0.02
Effort
321.10
43.25
0.0001
Project type
-127.67
72.27
0.07
Requirements uncertainty
-155.08
51.10
0.002
Human resources (training)
70.02
57.20
0.22
Prior projects for client
-19.33
5.15
0.0002
Competition (offshore)
-351.23
76.03
0.0001
Competition (onshore)
162.23
61.06
0.007
Project importance
-132.67
53.05
0.01
Client reputation
-30.99
35.41
0.39
Future business
27.07
43.37
0.53
Client size
90.01
54.41
0.09
Client experience
-0.658
58.38
0.99
MIS experience
184.89
78.77
0.01
Contract
-748.14
237.74
0.001
Employee turnover
-38.97
50.67
0.44
Team size
12.57
4.65
0.006
Project duration
0.355
0.14
0.01
Lambda
313.71
142.35
0.027
Notes. Model F = 10.83, 18 df. Significant at p < 0.01. R2  = 0.72. Adjusted R2 = 0.65.

 

 

 

 

 

 

 

 

 

 

Works Cited

 

 

Alpar, P., and Saharia, A.N. 1995. Outsourcing information system functions: an organization economics perspective. Journal of Organizational Computing, 5, 3, 197-217

Ang, S., and Cummings, L. L. “Strategic Response to Institutional Influences on Information Systems Outsourcing,” Organization Science (8:3), May-June 1997, pp. 235-256.

Ang, S., and Straub, D. “Production and Transaction Economies and IS Outsourcing: A Study of the U.S. Banking Industry,” MIS Quarterly (22:4), December 1998, pp. 535-552.

Applegate, L. M., and Montealegre, R. 1991. “Eastman Kodak Co.: Managing Information Systems Through Strategic Alliances,” Harvard Business School Case 192-030, Boston, MA.

Aubert, B. A., Dussault, S., Patry, M., and Rivard, M. “Managing the Risk of IT Outsourcing,” in Proceedings of the Thirty-Second Hawaii International Conference on System Sciences , IEEE Computer Society Press, Los Alamitos, CA, 1999, pp. 7068-7079.

Aubert, B. A., Patry, M., and Rivard, M. “Assessing the Risk of IT Outsourcing,” in Proceedings of the Thirty-First Hawaii International Conference on System Sciences , IEEE Computer Society Press, Los Alamitos, CA, 1998, pp. 685-693.

Bajari, P., S. Tadelis. 2001. Incentives vs. transaction costs: A theory of procurement contracts. RAND J. Econom. 32 (3) 387-408.

 

Banerjee, A. V., E. Duflo. 2000. Reputation effects and the limits of contracting: A study of the Indian software industry. Quart. J. Econom. 115 (3) 989-1017.

 

Barki, H., Rivard, J. Talbotl. 1993. Toward an assessment of software development risk. J. Management Inform. Systems 10 (2) 203-225.

Barney, J.B. 1991. Firm resources and sustained competitive advantage. Journal of Management, 17: 99-120.

Barney, J.B. 1997. Gaining and sustaining competitive advantage. New York: Addison-Wesley.

Barnow, B. S., G. S. Cain, A. S. Goldberger. 1981. Issues in the analysis of selectivity bias. Eval. Stud. Rev. Annual 5 43-59.

 

Belsley, D. A., E. Kuh, R. E. Welsch. 1980. Regression Diagnostics Identifying Influential Data and Sources of Collinearity. Wiley and Sons, New York.

Bettis, R., Bradley, S., 8: Hamel, G. 1992. Outsourcing and industrial decline. Academy of Management Executive, 6 (1): 7-22.

Binstock, A. 1999. Outside development partners. Information Week (Oct 18) 133-140.

Boddewyn, J.J., Halbrich, M.B., & Perry, A.C. 1986. Service multinationals: Conceptualization, measurement, and theory. Journal of International Business Studies, Fall: 41-57.

Buxbaum, P. “Bringing IT Back Home,” Computerworld (36:31, July 29, 2002, p. 38.

Caldwell, B. “2001 Trends in IT Outsourcing Delivery, Solution Development, Marketing, Sales and Alliances,” Gartner Dataquest Report, Stamford, CT, January 22, 2002a.

Caldwell, B. “Outsourcing Cost Reduction Creates Paradox: How to Still Make a Profit,” Gartner Dataquest Report, Stamford, CT, April 12, 2002b.

Caldwell, B. 1997. Transquest finds it can fly solo. Information Week, 613 (January 13, 1997), 86-87.

Caldwell, B., and McGee, M. K. “Outsourcing Backlash,” Information Week (650), September 29, 1997.

Cameron, K. 1978. Measuring organizational effectiveness in institutions of higher education. Administrative Science Quarterly, 23: 604-632.

Chakravarthy, B. 1986. Measuring strategic performance. Strategic Management Journal, 6: 437-458.

Cohen, J. 1988. Statistical power analysis for the behavioral sciences. Hillsdale: Lawrence Erlbaum Associates.

Crocker, K. J., K. J. Reynolds. 1993. The efficiency of incomplete contracts: An empirical analysis of Air Force engine procurement. RAND J. Econom. 24 (2) 126-147.

Cronbach, L.J. 1951. Coefficient alpha and the internal structure of tests. Psychometrika, 16: 297-334.

Cross, J. 1995. IT outsourcing: British Petroleum’s competitive approach. Harvard Business Review, 73, 3 (May-June 1995), 94-103.

D’Aveni, R., & Ravenscraft, D. 1994. Economies of integration versus bureaucracy costs: Does vertical integration improve performance? Academy of Management Journal, 37 (5): 1167-1206.

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

Dess, G.G., Ireland, R.D., & Hitt, M.A. 1990. Industry effects and strategic management research. Journal of Management, 16: 7-27.

Dess, G.G., Rasheed, A., McLanghlin, K., & Priem, R. 1995. The new corporate architecture. Academy of Management Executive, 9 (3): 7-20.

Dieriekx, I., & Cool, K. 1989. Asset stock accumulation and sustainability of competitive advantage. Management Science, 35: 1504-1511.

Dillman, D.A. 1978. Mail and telephone surveys: The total design method. New York: Wiley.

Earl, M. 1996. The risks of outsourcing IS. Sloan Management Review, 37 (Spring 1996), 26-32.

Fitzgerald, G., L. Willcocks. 1994. Contracts and partnerships in the outsourcing of IT. Internet, Conf. Inform. Systems. Vancourver, B. C., 91-98.

Ford, J.K., MacCallum, R.C., & Tait, M. 1986. The application of exploratory factor analysis in applied psychology: A critical review and analysis. Personnel Psychology, 39: 291-314.

Gopal, A., T. Mukhopadhyay, M. S. Krishnan. 2002. The role of software processes and communication in offshore software development. Comm. ACM 45 (4ve) 193-200.

Grant, R.M. 1991. The resource-based theory of competitive advantage: Implications for strategy formulation. California Management Review, 33 (3): 114-135.

Greer, C.R., & Ireland, T.C. 1992. Organizational and financial correlates of a “contrarian” human resource investment strategy. Academy of Management Journal, 35: 956-984.

Grover, V.; Cheon, M.J.; and Teng, J.T.C. 1994. A descriptive study on the outsourcing of the information systems functions. Information and Management, 27 (July 1994), 33-44.

Guinan, P. J., J. G. Cooperider, S. Faraj. 1998. Enabling software development team performance during requirements definition: A behavioural versus technical approach. Inform. Systems Res. 9 (2) 101-125.

Harrigan, K.R. 1984. Formulating vertical integration strategies. Academy of Management Review, 9(4): 638 -652.

Harrigan, K.R. 1985. Exit barriers and vertical integration. Academy of Management Journal, 28(3): 686-697.

Hart, O., J. Moore. 1988. Incomplete contracts and renegotiation. Econometrica 56 (4) 755-785.

Harter, D. E., M. S. Krishnan, S. A. Slaughter. 2000. Effects of process maturity on quality, cycle time, and effort in software product development. Management Sci. 46 (4) 451-467.

Hatten, K.J., Schendel, D.E., & Cooper, A.C. 1978. A strategic model of the U.S. brewing industry. Academy of Management Journal, 21: 592-610.

Heckman, J.1976. The common structure of statistical models of truncation, sample selection and limited dependent variables and a simple estimator for such models. Ann. Econom. Social Measurement 5 475-492.

Hill, C.W.L., & Jones, G.R. 1995. Strategic management: An integrated approach. Boston: Houghton Mifflin.

Hirschheim, R. A., and Lacity, M. C. “The Myths and Realities of Information Technology Insourcing,” Communications of the ACM (43:2), February 2000, pp. 99-107.

Hu, Q.; Saunders, C.; and Gebelt, M. 1997. Research report: diffusion of information systems outsourcing: a reevaluation of influence sources. Information Systems Research, 8, 3 (September 1997), 288-301.

Huber, Richard L “How Continental Bank Outsourced its ‘Crown Jewels.'” Harvard Business Review 71, 1 (January/February 1993): p. 114.

 

Jenson, M., W. Meckling. 1976. Theory of the firms: Managerial behaviour, agency costs and ownership structure. J. Financial Econom. 3 305-360.

 

Jones, C. 1994. Assessment and Control of Software Risks. Yourdon Press, Prentice Hall, Englewood Cliffs, NJ.

 

Keane, M. P., D. E. Runkle. 1990. Testing the rationality of price forecasts: New evidence from panel data. Amer. Econom. Rev. 80 (4) 714-735.

 

King, J., T. Hoffman. 1998. Outsourcing gotchas. Computerworld 32 (26).

Kotabe, M. 1989. “Hollowing-out” of U.S. multinationals and their global competitiveness: An intrafirm perspective. Journal of Business Research, 19: 1-15.

Kotabe, M. 1990. The relationship between offshore sourcing and innovativeness of U.S. multinational firms: An empirical investigation. Journal of International Business Studies, 3: 623-638.

Kotabe, M. 1992. Global sourcing strategy: R&D, manufacturing, and marketing interfaces. New York: Quorum.

Kotabe, M., & Murray, J. 1990. Linking product and process innovations and modes of international sourcing in global competition: A case of foreign multinational firms. Journal of International Business Studies, 3: 383-408.

Krishnan, M. S., C. H. Kriebel, S. Kekre, T. Mukhopadhyay. 2000. An empirical analysis of productivity and quality in software products. Management Sci. 46 (6) 745-759.

Kumar, N., Stern, W., & Anderson, J.C. 1993. Conducting interorganizational research using key informants. Academy of Management Journal, 36: 1633-1651.

Lacity, M. C., L. P. Willcocks, D. F. Feeny. 1995. IT outsourcing: Maximize flexibility and control .Harvard Bus. Rev. 73 84-93.

 

Lacity, M. C., L. P. Willcocks. 1998. An empirical investigation of information technology sourcing practices: Lessons from experience. MIS Quart. 22 363-408.

 

Lacity, M. C., R. A. Hirschheim. 1993. Information Systems Outsourcing: Myths, Metaphors and Realties. John Wiley and Sons, New York.
Lacity, M.C., and Hirschheim, R. 1993. The information systems outsourcing bandwagon. Sloan Management Review, 35, 1 (Fall 1993), 73-86.

 

Lafontaine, F., M. E. slade. 2001. Incentive contracting and the franchise decision. K. Chatterjee, W. Samuelson, eds. Adv. Bus. Appl. Game Theory. Kluwer Academic Press, Amsterdam, The Netherlands.

Lei, D., & Hitt, M. 1995. Strategic restructuring and outsourcing: The effect of mergers and acquisitions and LBOs on building firm skills and capabilities. Journal of Management, 21(5): 835-859.

Levy, D.L. 1995. International sourcing and supply chain stability. Journal of International Business Studies, 26(2): 343-360.

Loh, L., & Venkatraman, N. 1992. Determinants of information technology outsourcing: A cross-sectional analysis. Journal of Management Information Systems, 9(1): 7-24.

Loh, L., and Venkatraman, N. 1992.  Diffusion of information technology outsourcing: influence sources and the Kodak effect. Information Systems Research, 3, 4 (December 1992), 334-358.

Loh, L., and Venkatraman, N. 1992b. “Diffusion of Information Technology Outsourcing: Influence Sources and the Kodak Effect,” Information Systems Research (3:4), December 1992b, pp. 334-378.

Lovell, M. C. 1986. Tests of the rational expectations hypothesis. Amer. Econom. Rev. 76 (1) 110-124.

Maddala, G. S. 1983. Limited-Dependent and Qualitative Variables in Econometrics. Cambridge University Press, Cambridge, U. K.

 

Mandell. J. 1998. Retaining IT talent. Software Magazine 18 (13) 20.

Markides, C., & Berg, N. 1988. Manufacturing offshore is bad business. Harvard Business Review, September-October: 113-120.

Mason, P. “Report Shows ‘Two Nations’ of it Spend Health Services Lag Behind General Growth,” Computer Weekly , March 2, 2000, p. 19.

McDougall, P., & Robinson, R.B., Jr. 1990. New venture strategies: An empirical identification of eight ‘archetypes’ of competitive strategies for entry. Strategic Management Journal, 11: 447-467.

McFarlan, F.W., and Nolan, R.L. 1995. How to manage an IS outsourcing alliance. Sloan Management Review, 36, 2 (Winter 1995), 9-23.

McGee, M. K. 1998. Boot camp for CIOs. Informationweek (Sept. 28) 46.

Miller, D. 1988. Relating Porter’s business strategies to environment and structure: Analysis and performance implications. Academy of Management Journal, 31: 280-308.

Miller, D., & Friesen, P. 1982. Innovation in conservative and entrepreneurial firms: Two models of strategic momentum. Strategic Management Journal, 3: 1-25.

Miller, M., L. Kaye. 1999. Climbing the value ladder. Inst. Investor 33 (9) 130-137.

 

Mjoen, H., S. Tallman. 1997. Control and performance in international joint ventures. Organ. Sci. 8 (3) 257-274.

Moorman, R.H., Blakely, G.L., & Niehoff, B.P. 1998. Does perceived organizational support mediate the relationship between procedural justice and organizational citizenship behavior? Academy of Management Journal, 41: 351-357.

Nayyar, P.R. 1993. On the measurement of competitive strategy: Evidence from a large multiproduct U.S. firm. Academy of Management Journal, 36: 1652-1669.

Nidomolu, S. 1995. The effect of coordination and uncertainty on software project performance: Residual performance risk as an intervening variable. Inform, Systems. Res 6 (3) 191-219.

 

Nidomolu, S. R., S. E. Goodman. !993. Computing in India: An Asian elephant learning to dance. Comm. ACM 36 (4) 15-22.

Pearce, J.A., Jr, Robbins, D.K., & Robinson, R.B., Jr. 1987. The impact of grand strategy and planning formality on financial performance. Strategic Management Journal, 8: 125-134.

Peteraf, M.A. 1993. The cornerstones of competitive advantage: A resource-based view. Strategic Management Journal 14: 179-191.

Porter, M.E. 1985. Competitive advantage: Creating and sustaining superior performance. New York: Free Press.

Prahalad, C.K., & Hamel, G. 1990. The core competence of the corporation. Harvard Business Review, 68(3): 79-93.

Priem, R.A., Rasheed, A., & Kotulic, A.G. 1995. Rationality in strategic decision processes, environmental dynamism, and firm performance. Journal of Management, 5: 913-929.

Quinn, J.B. 1992. Intelligent enterprise: A knowledge and service based paradigm for industry. New York: Free Press.

Quinn, J.B., Doorley, T.L., & Paquette, P.C. 1990. Technology in services: Rethinking strategic focus. Sloan Management Review, 31(2): 79-87.

Richmond, W. B., A. Seidmann. A. B. Whinston. 1992. Incomplete contracting issues in information systems development outsourcing. Decision Support Systems 8 (5) 459-478.

Roth, J.C 1992. International configuration and coordination archetypes for medium-sized firms in global industries. Journal of International Business Studies, 23(3): 533-549.

Rumelt, R. 1974. Strategy, structure, and economic performance. Cambridge, MA: Harvard University Press.

Rumelt, R. 1982. Diversification strategy and profitability. Strategic Management Journal, 3: 359-370.

Shapiro, S., M. Wilk. 1965. An analysis of variance test for normality. Biometrika 52 591-612.

Shehata, M. 1991. Self-selection bias and the economic consequences of accounting regulation: An application of two-stage switching regression to SFAS. No. 2. Accounting Rev. 66 (4) 768-787.

 

Smith, M.A., Mitra, S. and Narasimhan, S. 1998. Information Systems Outsourcing: A Study of Pre-event Firm Characteristics: Journal of Management Information Systems, 15(2): pp. 61–93.

 

Strassman, P. 1995. Outsourcing, a game for losers. Computerworld, 29 (August 21, 1995), 75.

Teece, D. 1987. Capturing value from technological innovation: Integration, strategic partnering, and licensing decisions. In B. Guile & H. Brooks (Eds.), Technology and global industry: 65-95. Washington: National Academy Press.

Whang, S. 1992. contracting for software development. Management Sci. 38 (3) 307-325.

 

Whang., S. 1995. Market provision of custom software: Learning effects and low balling. Management Sci. 41 (8) 1343-1357.

Willcocks, L., and Lacity, M. C. “Relationships in IT Outsourcing: A Stakholder Perspective,” in Framing the Domains of IT Management, R. Zmud (ed.), Pinnaflex Inc., Cincinnati, OH, 2000, pp. 355-384.

Williamson, O. E. 1979. Transaction-cost Economic: The governance of contractual relations J. Law Econom. 22 (2) 233-261.