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Effects of process and outcome controls on business process outsourcing performance: Moderating roles of vendor and client capability risks
Accepted Manuscript
Effects of process and outcome controls on business process outsourcing performance: Moderating roles of vendor and client capability risks Shan Liu , Lin Wang , Wei Huang (Wayne) PII: DOI: Reference:
S0377-2217(17)30055-3 10.1016/j.ejor.2017.01.020 EOR 14201
To appear in:
European Journal of Operational Research
Received date: Revised date: Accepted date:
18 February 2016 6 January 2017 10 January 2017
Please cite this article as: Shan Liu , Lin Wang , Wei Huang (Wayne) , Effects of process and outcome controls on business process outsourcing performance: Moderating roles of vendor and client capability risks, European Journal of Operational Research (2017), doi: 10.1016/j.ejor.2017.01.020
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Highlights Process and outcome controls positively influence project performance.
Outcome control is more effective than process control.
Vendor and client capability risks differentially moderate control effectiveness.
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Effects of process and outcome controls on business process outsourcing performance: Moderating roles of vendor and client capability risks
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Shan Liu1, Lin Wang2*, Wei Huang (Wayne) 1 1. School of Management, Xi’an Jiaotong University, Xi’an 710049, China
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2. School of Management, Huazhong University of Science and Technology, Wuhan 430074 China
Abstract
Control over outsourced projects is a significant concern for both clients and vendors. Although the effect of control on performance has been studied previously, vendor and client capability risks have rarely been merged into the control–performance relationship. Using paired quantitative data
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collected from 234 business process outsourcing projects, we empirically determine that outcome control is more effective than process control, although both positively influence the performance of outsourced projects. Vendor and client capability risks play miscellaneous moderating roles on the effects of process and outcome controls on performance. In the presence of high vendor capability risk, the effect of process control on performance is high, but the effectiveness of outcome control is
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low. By contrast, high client capability risk results in low effectiveness of process control but high effectiveness of outcome control. Different control modes have various attributes and generate different levels of performance. Either vendor or client capability risk serves as a double-edged
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sword with regard to control. Therefore, the risky situation of both vendors and clients should be considered in the selection and enforcement of control in managing outsourced projects.
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Keywords: (B) Project management; risk management; business process outsourcing; control
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mechanism; vendor
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* Corresponding author. Email addresses: [email protected]; [email protected];
[email protected].
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1. Introduction Business process outsourcing (BPO) has become a transformational and prevalent business practice of organizations in realizing their strategic goals and managing their operations (Handley and Benton, 2009; Narayanan et al., 2011; Mani et al., 2012). In BPO, an organization enters into contract with an external firm to manage and to deliver one or more business functions or processes
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(Gartner, 2013). In 2011, the global BPO market reached 176 billion dollars and was estimated to reach more than 200 billion dollars in 2017 at a compounded annual growth rate of 5.7% (APCEO, 2012; Donovan, 2013). The rapid growth of BPO is recognized by researchers and practitioners, but a large number of organizations fail to obtain the benefit and value of BPO, as seen in their negative experiences with BPO projects. In a survey of 189 firm clients of BPO across various industries (e.g., finance and accounting, retailing, and health administration), 50% declared that BPO failed to
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reduce costs as prescribed in the contract, produce knowledge of specific processes, and provide extra value beyond standard operations (Fersht, 2014). Meanwhile, approximately 75% of the vendors indicated that client firms lacked adequate preparations for outsourcing, systematic strategies, and understanding of outsourcing working processes; this result is based on the survey of 300 executives from firms with more than $30 million annual deals worldwide across diverse
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industries (e.g., manufacturing, retail, services, and education) (Robinson et al., 2008). These results show that BPO projects exhibited unsatisfactory performance. Poor risk management and control
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strategies may be exercised by both clients and vendors in outsourced projects. In recent years, two research streams emerged to foster outsourcing performance. One stream draws upon control-based theory and emphasizes the significant role of formal control practices
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(Choudhury and Sabherwal, 2003; Rustagi et al., 2008). The other stream builds on the risk-based view and highlights the importance of managing key risks (Li et al., 2013; Liu and Wang, 2014a).
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These two streams have recently been integrated based on the influence of the interplay of control and risk on performance (Tiwana and Keil et al., 2010; Rustagi, 2004; Azimian et al., 2016). However, vendor and client capability risks have not been examined in the integration of control
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and risk. Prior studies on the control of outsourced projects have exhibited at least four gaps. First, although the correlation between formal control and the performance of outsourced
projects has been examined, the question of whether specific modes of formal control significantly facilitate outsourced project performance has not been addressed. Two modes of formal control were studied in prior research, namely, process control and outcome control. Process control refers to the mechanism utilized by a controller to evaluate the performance of the controlee based on how the latter follows the prescribed procedures and methods (Tiwana and Keil, 2007; Choudhury and
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Sabherwal, 2003). Outcome control is the mechanism employed by a controller to assess the performance of the controlee based on how the latter follows the prescriptions of desired outputs (Kirsch, 1997; Tiwana and Keil, 2010). Previous studies have provided evidence that formal control can enhance the performance of outsourced projects (Tiwana, 2008; Keil et al., 2013). However, the relationship between two formal control modes (i.e., process and outcome controls) and has
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relatively
little
attention.
Previous
studies
regarding
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performance
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control–performance relationship have also displayed contradictory findings. For example, Gopal and Gosain (2010) found that process control positively and significantly affected the performance of outsourced projects, whereas Tiwana and Keil (2010) showed that increased use of process control had insignificant association with performance. The same situation also occurs for the correlation between outcome control and performance (Gopal and Gosain, 2010; Tiwana and Keil,
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2010). Therefore, additional empirical research is needed to study this issue.
Second, although both process and outcome controls are exercised extensively to manage outsourced projects, little evidence has been provided as to which mode of formal control exhibits greater influence on performance. In a multiple-case study, Choudhury and Sabherwal (2003) observed that outcome control dominated the portfolios of control in outsourced projects, but
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process control was often used in the late phase of outsourced projects. This finding suggests that the choice and presumably the effectiveness of process and outcome controls may differ in the
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context of outsourcing. Different control modes also exhibit various characteristics: process control is mechanistic and emphasizes predictability and regularity (Das and Teng, 1998; Ouchi, 1980), whereas outcome control is organic and emphasizes the balance of emergence and control (Harris et
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al., 2009). Different features of process and outcome controls may result in varied levels of performance in outsourced projects. Therefore, investigations on the relative importance of process
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and outcome controls are complicated and significant. Understanding this issue enables the proper selection of effective formal modes and optimization of control strategies in managing outsourced projects.
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Third, researchers have argued that risk and control collectively affect the performance of
outsourced projects. However, they focused primarily on the technical aspect of risk (e.g., technology uncertainty and technological modularity risk) (e.g., Tiwana, 2008; Harris et al., 2009) while neglecting the importance of capability risks in outsourcing performance and relationship management. Capability risks, which denote the uncertainty and issues associated with the ability, knowledge, and skills to manage outsourced projects, are among the top ten risks in domestic and offshore outsourcing projects (Nakatsu and Iacovou, 2009). The effective management of such risks
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is fundamental to the success of outsourcing (Handley, 2012). Nevertheless, capability risks have never been integrated into control–performance relationship before. Previous studies have presented diverse results on the interactions between risk and the same formal control mode. For instance, Tiwana and Keil (2010) empirically determined that requirement volatility (i.e., “the extent to which project requirements unpredictably change over the course of the systems development life
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cycle” (Tiwana and Keil, 2010, p. 21) lowered the effect of outcome control on performance. In spite of this intuitive result, other studies found that the effectiveness of outcome control can be enhanced in the environment of technology risk (Harris et al., 2009). Therefore, how critical risks, capability risks in particular, affect the effects of process and outcome controls on performance in outsourced projects should be examined. Explorations of this issue may enable managers to deal with capability risks correctly and thus optimize control portfolios in the presence of such risks.
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Fourth, previous research seldom distinguished the source of risk. Little is known about the influence of vendor and client capability risks on the relationship of formal control modes with performance. Vendor capability risk refers to the issues associated with the ability, knowledge, and skills of a vendor to accomplish project goals that can increase the uncertainty of project outcomes, whereas client capability risk refers to the issues associated with the ability, knowledge, and skills
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of a client to manage the outsourcing process and vendors (Nakatsu and Iacovou, 2009; Han et al., 2013). Vendor and client capability risks display significant differences because these two risks
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originate from two independent parties (i.e., client and vendor). Prior research highlights the significance of understanding both stakeholders to achieve high outsourcing performance (Nyaga et al., 2010; Oosterhuis et al., 2013), but vendor and client capability risks have never been
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investigated simultaneously. Given that the input from different parties has different influences on control effectiveness (Kirsch, 1997; Choudhury and Sabherwal, 2003), understanding how vendor
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and client capability risks may moderate the correlations between two formal control modes and performance in outsourced projects is necessary and important. Further examinations of the roles of vendor and client capability risks in control effectiveness may assist the understanding of effective
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management of such risks and the client–vendor control relationship. These issues are noteworthy in practice because managers may select control modes that are
ineffective in a risky environment but may work effectively in others. Explorations of these issues will probably help client managers to manage the control relationship with vendors productively based on the risks associated with both clients and vendors, minimize unnecessary resources and costs associated with the exercise of control, and avoid unsatisfactory outcomes. This study focuses on BPO projects because BPO involves diverse operational objectives (e.g., business transformation,
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innovation, and cost reduction) and may generate various levels of control and risk (Mani et al., 2010; Rai et al., 2012). In sum, we address the following research questions based on the above discussions: (1) How do process control and outcome control influence the performance of BPO projects? (2) How do vendor and client capability risks alter control–performance relationship in BPO
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projects?
We present a theoretical model based on the control-based theory and risk-based views. We also analyze survey data obtained from 234 BPO projects in China and provide insights on the integration of control with vendor and client capability risks in BPO projects. The rest of the paper is organized as follows. The relevant theory and literature are introduced in Section 2. The conceptual model and hypotheses are presented in Section 3. Data collection, scale, and
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measurement validation are described in Section 4. Results of data analysis are given in Section 5. Finally, the theoretical and managerial implications of the research findings are discussed in Section 6. 2. Theoretical foundation 2.1. Control in outsourcing relationships
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Control in outsourcing relationships refers to the mechanism that an outsourcer (controller) uses to regulate the actions of outsourcees (controlees) to achieve desired goals (Tiwana and Keil,
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2010; Choudhury and Sabherwal, 2003). Control is performed by the client firm (controller) through various control mechanisms to ensure that the vendor firm (controlee) behaves in a manner that will help realize the outsourcing objectives (Kirsch et al., 2002; Tiwana, 2008). This study
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focuses on formal control mechanisms, which are exercised intensively in managing outsourcing relationships. In formal control, controlee behavior is influenced by adherence to prescribed
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processes and outcome-based evaluations (Tiwana and Keil, 2007; Choudhury and Sabherwal, 2003). Two modes of formal control are described in previous studies: process control and outcome control. Process control (or behavior control) is implemented by the client to evaluate vendor
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performance based on how prescribed procedures and methods are adopted by the vendor (Tiwana, 2008). Outcome control is practiced by the client to assess vendor performance according to the extent to which desired final targets and outputs are achieved regardless of the process (Henderson and Lee, 1992; Tiwana and Keil, 2010). Process control describes how desired outcomes are achieved, whereas outcome control describes what should be accomplished in outsourced projects (Kirsch et al., 2002). Previous research in the control of outsourcing context has focused on the following areas: (1)
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exploration and formation of specific control mechanisms (Das and Teng, 1998; Choudhury and Sabherwal, 2003), (2) investigation of factors that can predict and decide the choice of specific control modes (Rustagi et al., 2008; Goodale et al., 2008), (3) control configuration and optimization in the process of outsourcing (Daityari et al., 2008; Gregory et al., 2013; Schildbach, and Morari, 2016), (4) documentation of internal functions between a pair of control modes
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(Tiwana, 2010; Rijsdijk and Ende, 2011), and (5) examination of the correlation between control and performance (Tiwana and Keil, 2010; Stouthuysen et al., 2012). 2.2. Control and performance in outsourced projects
The positive relationship between formal control and performance is well documented and recognized in previous research (Rustagi, 2004; Keil et al., 2013). However, contradictory findings have been obtained with respect to the effectiveness of process and outcome controls in outsourced
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projects (Tiwana, 2008; Gopal and Gosain, 2010; Tiwana and Keil, 2010). Thus, further empirical evidence is required to understand how process and outcome controls affect outsourcing performance. In accordance with our general understanding of the positive effectiveness of formal control (Keil et al., 2013), effective exercise of process and outcome controls may enable the client to acquire satisfactory outputs and expected project values realized by the vendors.
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Although both process and outcome controls are practiced in managing outsourced projects, previous studies suggest that the effectiveness of these two control modes may differ. For instance,
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Tiwana and Keil (2010) argued that the performance of outsourced projects was positively influenced by outcome control but insignificantly influenced by process control because of the difficulty in implementing process control in outsourced projects. As a result, the effect of outcome
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control on performance may be stronger than that of process control in outsourced projects. 2.3. Vendor and client capability risks, control, and performance
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In prior literature, risk is viewed as a condition that seriously influences outsourcing success (Gewald and Dibbern, 2009; Powell et al., 2016). Lehtiranta (2014) argued that risk can generate unanticipated results and exert either negative or positive influence because of its high uncertainty.
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Management approaches and activities (e.g., control) will adapt (weaken or strengthen) toward project risks to achieve success from the complexity view (Lehtiranta, 2011; Liu, 2015). This research focuses on two significant risk factors, namely, vendor and client capability risks, which may change the effects of process and outcome controls on performance. These two risks are associated with two different parties (i.e., client and vendor) and display significant differences. They were selected from various types of risks (e.g., contract management and technological risks) related to outsourcing projects for three reasons. First, vendor and client capability risks are broadly
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acknowledged to be critical. They are situated in the top ten risks in offshore and domestic outsourcing projects (Nakatsu and Iacovou, 2009). Effective management of such risks is vital to the success of outsourcing (Handley, 2012). Second, compared with technology-related risks, the moderating roles played by vendor and client capability risks in the relationship between control and performance are poorly understood. Third, vendor and client capability risks have never been
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investigated simultaneously; however, many studies argue that inputs from either client or vendor significantly could influence outsourcing performance (Li et al., 2008; Narayanan et al., 2011).
Previous evidence implies that vendor and client capability risks may change control effectiveness. For instance, boundary spanning, which is an organizational capability of vendors, significantly moderates the effectiveness of process and outcome controls in outsourced projects (Gopal and Gosain, 2010). Client peripheral knowledge (specialized knowledge in the domain of
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outsourced activities), a type of capability of clients, also exerts a significant moderating effect on the relationship between control and performance (Tiwana and Keil, 2007). Given that vendor and client capability risks refer to issues or uncertainty associated with capability, these two risks together may moderate the effects of process and outcome controls on the performance of outsourced projects.
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2.4. BPO satisfaction as a dependent variable
According to the literature (Dibbern et al., 2004; Rai et al., 2012), outsourcing performance
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can be defined from three perspectives, namely, the performance of outsourced processes and operations, the accomplishment of objectives (e.g., cost reduction), and satisfaction. BPO satisfaction is used as a critical performance metric in this study because it is simple, significant,
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and well-defined in the literature. It also represents perceived performance of business partnerships (Poppo and Zenger 2002; Mani et al., 2010). Consistent with previous studies (Rai et al., 2012;
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Mani et al., 2010), we define BPO satisfaction as the extent to which satisfactory service and outcomes of BPO project are delivered. 3. Research model and hypothesis development
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Figure 1 displays our research model. We contend that process and outcome controls would
positively affect BPO performance. However, the effect of outcome control on BPO performance may be greater than that of process control. The moderating effects of vendor and client capability risks on the relationships between process/outcome controls and performance may differ. The relationship between process control and BPO performance could be positively moderated by vendor capability risk, but negatively moderated by client capability risk. In contrast, the effectiveness of outcome control may be negatively moderated by vendor capability risk but
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positively moderated by client capability risk.
Process control
H5-
H1+
H3: The relationship between outcome control and BPO performance is stronger than that between process control and BPO performance
H7+
BPO performance
H4+ Outcome control
H2+
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Client capability risk
H6-
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Vendor capability risk
Figure 1. Research model. 3.1. Effects of process and outcome controls on performance
Control works effectively in enhancing the performance of outsourced projects (Tiwana, 2008;
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Daityari et al., 2008). A number of studies provide empirical evidence that formal control mechanisms have positive effects on performance in either domestic or international outsourcing projects (Li et al., 2008; Srivastava and Teo, 2012). Therefore, we posit that process and outcome
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controls would positively influence the performance of BPO projects. In process control, clients (controllers) focus on the suitability and significance of process
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execution. Their practice of process control ensures that vendors (controlees) adopt appropriate steps and procedures to minimize errors and meaningless modifications and thus increase working
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performance (Gopal and Gosain, 2010; Liu and Wang, 2014b). Process control also offers a systematic and structured method of developing business processes to avoid uncertainty and generate outcomes according to client expectations. By evaluating the extent to which prescribed
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procedures and rules are adopted upon the accomplishment of project objectives, vendors can work effectively on completing project tasks; clients are also able to monitor project progress conveniently (Henderson and Lee, 1992). Therefore, we present the following hypothesis: H1. Process control exerts a positive effect on the performance of BPO projects. Outcome control emphasizes the significance of accomplishing desired goals of outsourced projects. In outcome control, clients can provide feedback efficiently for corrections by evaluating accomplished outcomes (Love and Josephson, 2004). Vendors are also motivated to take
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appropriate action if project objectives and requirements are not satisfied, thereby resulting in high output efficiency and reliability (Gopal and Gosain, 2010). Outcome control enables vendors to follow explicit scopes and goals, hence producing outcomes with client expectations (Barnes and Targett, 1999). Outcome control considerably increases the working efficiency of vendors in completing tasks, thereby enhancing the performance of outsourced projects (Bello and Gilliland,
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1997). The stipulated evaluation criteria also generate proper vendor actions that lead to delivery of satisfied outcomes (Gopal and Gosain, 2010). Thus, we present the following hypothesis. H2. Outcome control exerts a positive effect on the performance of BPO projects. 3.2. Relative significance of process and outcome controls to performance
Although both process and outcome controls positively influence the performance of BPO projects, we posit that outcome control would be more effective than process control. Process
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control and outcome control display different characteristics. Process control is mechanistic and emphasizes predictability and regularity (Das and Teng, 1998; Ouchi, 1980). By contrast, outcome control is organic and balances emergence and control (Harris et al., 2009; Tiwana and Keil, 2010). Given that the management of outsourcing relationships with both emergence and control outperforms that with either predictability or emergence (Choi et al., 2001), outcome control
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influences performance to a greater degree than process control.
In process control, the direct observation and monitoring of vendor actions and behavior are
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difficult in outsourced projects (Tiwana and Keil, 2010). Process control is also more costly than outcome control because considerable time and work are required to monitor and evaluate the outsourcing processes (Choudhury and Sabberwal, 2003). These factors may negatively influence
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the effectiveness of process control. Compared with process control, outcome control explicitly specifies desired goals and is associated more directly with project performance (Daityari et al.,
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2008). Evaluations and rewards based on outcome control also inspire vendors more directly to deliver satisfactory outcomes (Liu and Wang, 2014b). Outcome control exhibits high levels of flexibility in accomplishing project goals and places little weight on implementation processes
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(Tiwana and Keil, 2007), hence working effective in such situations. Therefore, we present the following hypothesis. H3.
The relationship between outcome control and performance is stronger than the
relationship between process control and performance in BPO projects. 3.3. Moderating effects of vendor and client capability risks We argue that vendor and client capability risks could change the effectiveness of each mode of formal control differently. Drawn upon the control theory, an effective exercise of control
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depends on the knowledge and capability of the controller and controlee (Eisenhardt, 1985; Kirsch et al., 2002). A competent controller is confident and capable of specifying accurate rules, processes, and methods that a controlee should follow to facilitate performance (Kirsch, 1997). However, controlees with high levels of capability tend to focus on their own processes (Kirsch, 1996; Silbermayr and Minner, 2016), causing the process control exercised by the controller to become
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ineffective. These prior findings indicate that the effectiveness of process control may be enhanced in the presence of low client capability risk but weakened in the presence of low vendor capability risk. By contrast, while competent controlees are capable of managing their own processes, they could enable the controller to perform outcome control more effectively. Logically, a competent controller is likely to place much control on process, thereby impairing the flexibility of outcome control. The above analysis implies that the effectiveness of outcome control may be enhanced in
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the presence of low vendor capability risk but weakened in the presence of low client capability risk. Hence, the effects of process and outcome controls exercised by the client are expected to differ in the presence of high levels of vendor and client capability risks.
In process control, clients prescribe rules and procedures and expect vendors to follow these predefined processes and steps (Tiwana and Keil, 2010). If high vendor capability risk is present,
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clients will articulate and predefine rules and processes clearly and precisely. They will also check the project progress frequently and evaluate the conditions of outsourced projects carefully to
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monitor and manage the outsourcing process (Sabherwal and King, 1995). These control activities intensify the performance of outsourced projects. Furthermore, given that vendors with low capability experience great difficulty in using their own methods and processes to accomplish tasks
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(Choudhury and Sabberwal, 2003), high vendor capability risk may lead vendors focus carefully and accurately on adopting and executing the processes and procedures prescribed by clients,
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thereby leading to satisfactory outcomes. Therefore, we present the following hypothesis. H4. The effect of process control on the performance of BPO projects is strong when vendor capability risk is high.
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High client capability risk increases the difficulty of prescribing accurate and executable
procedures and steps that guide vendors to accomplish project goals (Chua et al., 2012). Clients with high capability risk may also design incorrect rules and processes, which impair the performance of outsourced project if adopted. Moreover, such clients cannot monitor the behavior of vendors appropriately and evaluate project status because of insufficient skills and knowledge to manage outsourcing processes (Choudhury and Sabherwal, 2003). Conflicts between clients and vendors are also very likely to arise because vendors may not agree with and adopt the processes
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designed by clients with high capability risk. Thus, we present the following hypothesis. H5. The effect of process control on the performance of BPO projects is low when client capability risk is high. Outcome control enables clients to prescribe desired goals and allows vendors to accomplish these goals by using their own processes and methods (Tiwana, 2008). However, vendors with high
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capability risk lack systematic methods and adequate expertise to complete tasks and achieve project objectives (Tang and Rai, 2012). Thus, the influence of outcome control on performance is lessened. Vendor capability risk also leads to the uncertainty of processes and tasks (Wallace et al., 2004). Such situations results in frequent changes in targets and goals, thereby increasing the difficulty of assessing vendor performance based on predefined evaluation criteria. Therefore, the effectiveness of outcome control is diminished. Vendor capability risk also reduces the efficiency of
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outcome control (Kortmann et al., 2014), which minimizes the effect of outcome control on BPO performance.
H6. The effect of outcome control on the performance of BPO projects is low when vendor capability risk is high.
Clients with high capability risk focus heavily on specifying the goals and requirements of
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outsourced projects but minimize their focus on the outsourcing process (Choudhury and Sabherwal, 2003). They also evaluate the accomplishment of project objectives carefully; thus, the effectiveness
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of outcome control is enhanced in such situations. Client capability risk increases the flexibility of outcome control (Harris et al., 2009), which motivates and encourages vendors to take on their responsibility, satisfy client needs, and realize project goals. Clients with low capability are also
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likely to develop a trusting relationship with vendors (Tiwana and Keil, 2007). Such a relationship may enable vendors to accomplish project goals effectively. Thus, we present the following
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hypothesis.
H7. The effect of outcome control on the performance of BPO projects is strong when client capability risk is high.
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4. Research methodology 4.1. Research design A survey on 234 BPO projects was conducted to gather quantitative data, which were used
empirically to test hypotheses. Consistent with previous studies of outsourcing or project management (e.g., Tiwana and Keil, 2010; Arumugam et al., 2016), we employed a multi-informant approach to gather data from both clients and vendors at the project level, thereby avoiding common method bias. The project manager in the Chinese vendor firm, to which the project was
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outsourced, and the manager who oversaw and supervised the project in the client firm answered a pair-wise survey questionnaire. A sample of 600 service organizations with BPO experience was drawn from the directory of corporate project managers provided by the Service Outsourcing Association of China. These service organizations, which are located in both Eastern and Western China, have provided BPO
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service for more than 30000 firms. The vendor-side project managers of these firms, who possessed extensive experience in managing BPO projects, were contacted to nominate an appropriate BPO project and a client-side manager who participated in and supervised the same project. To achieve high levels of project diversity, project managers from various BPO business functions were contacted. Thus, main types of BPO projects (e.g., customer service, finance and accounting, human resource, training, and procurement) were included in the project sample. To avoid recall issues, the
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selected project should have been completed within the previous year. Moreover, at least one deliverable function should be accomplished to guarantee that significant control activities have occurred in the project. After the BPO projects were determined, we collected and reviewed information (e.g., project duration and contract type) on the selected projects to ensure their diversity and representativeness. All selected projects were required to pair off both the vendor- and
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client-side project managers for the survey. The client-side manager should demonstrate an extensive understanding of the nominated projects. Before distributing the questionnaires, the
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client-side managers were contacted to ensure their eligibility as respondents. On the basis of existing measures, a survey instrument was developed to obtain data. A pilot study on 30 managers with rich experience in BPO projects was first conducted. Then, we sent
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coded questionnaires through mail and e-mail to the requested vendor- and client-side managers who were eligible to participate. Both vendor- and client-side managers were asked to respond
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retrospectively to the designated questions in the questionnaire. Next, we conducted a number of tests on our sample to examine method and non-response bias, and obtain useful responses during survey administration. Subsequently, we developed and validated a set of measurement models to
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test hypotheses through hierarchical regression analysis. The effect of process and outcome control was assessed and compared to test H1 to H3. Moderating effects of client and vendor capability risks were evaluated to test H4 to H7. Specific procedures are stated below. 4.2. Construct operationalizations and instrument development We used multi-item scales to operationalize each variable. Previous instruments related to control, risk, complexity, and performance were adapted primarily for the variables. A seven-point reflective Likert scale that ranged from “strongly disagree” to “strongly agree” was used to measure
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each item. Paired questionnaires were designed for vendor- and client-side managers. Process control, outcome control, and client capability risk were evaluated by vendor-side managers, whereas vendor capability risk, project complexity, and performance were assessed by client-side managers. We first developed the English version questionnaire, translated it into Chinese, and back-translated it into English. The original and back-translated English questionnaires were
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compared to check for consistency.
Following previous studies (e.g., Tang and Rai, 2014), we acquired several measures to improve the initial instrument. First, the two-stage Q-sorting method was applied for face and content validities (Moore and Benbasat, 1991). Second, a panel of 10 American and Chinese Ph.D. students, and five professors with expertise in business process management and outsourcing was formed to provide suggestions for the survey design and evaluate the questionnaire design, format,
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expressions, and content. Based on their feedback, revisions on the survey instrument were performed. This process lasted for two months. Third, we conducted a pilot test with 30 randomly selected vendor- and client-side managers to ensure comprehensibility and reliability, and evaluate the variances of constructs explained by the measures. These managers have intensive experience in managing BPO projects. They provided effective suggestions on the expression of each item. The
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questionnaire was modified to strengthen its reliability based on the feedback we received. This process lasted for one month. Final construct measurements are shown in Table 1.
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Process control was measured by three items based on the studies by Tiwana (2008) and Keil et al. (2013). Four scale items to measure outcome control were adapted from Kirsch et al. (2002) and Tiwana (2008). Vendor capability and client capability risks were measured using four items
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adopted from Nakatsu and Iacovou (2009) and Han et al. (2013). Project complexity, which was used as a control variable in this study, refers to the inherent difficulty that a project experiences.
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This variable was measured by four indicators, which were adapted from Abdullah and Verner (2012) and Liu (2015). The scales and items to measure performance, which reflect reliability, responsiveness, systematization, and innovation of the service, was adopted from the work of Mani
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et al. (2010).
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Table 1 Constructs and measures.
VCR1 VCR2 VCR3 VCR4
CCR1 CCR2 CCR3 CCR4
PCP1 PCP2 PCP3 PCP4
PFM1 PFM2 PFM3
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PFM4
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OCT1 OCT2 OCT3 OCT4
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PCT3
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PCT2
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PCT1
Construct and Measure Process control (Vendor-side manager) In this BPO project The client expected the vendor to follow an understandable written sequence of steps specified by the client toward the accomplishment of project goals The client expected the vendor to follow articulated rules and procedures specified by the client toward the accomplishment of project goals The client assessed the extent to which existing written procedures and practices were followed during the outsourcing process Outcome control (Vendor-side manager) In this BPO project The client placed significant weight upon the timely completion of project tasks The client placed significant weight upon project completion within budget The client placed significant weight upon project completion to the satisfaction of the client The client evaluated the performance of the vendor by the extent to which project goals were accomplished Vendor capability risk (Client-side manager) In this BPO project The vendor lacked adequate technical knowledge necessary for the project The vendor lacked adequate business knowledge necessary for the project The vendor lacked specialized skills required by the project Vendor employees were inexperienced Client capability risk (Vendor-side manager) In this BPO project The client lacked outsourcing experience The client lacked essential skills and knowledge to manage the outsourcing process The client lacked the ability for contract management The client lacked the ability for vendor management Project complexity (Client-side manager) In this BPO project Business process required complex integration and customization There was high level of technical complexity The task was highly complex There were many business and technical difficulties Performance (Client-side manager) In this BPO project The vendor performed contracted services dependably and accurately The vendor provided prompt service The processes, procedures, systems, and technology provided by the vendor made the service a seamless one The vendor leveraged process knowledge to deliver a range of process enhancements that go beyond performance expectations of the client
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No.
4.3. Data collection All the projects in the sample were conducted in China. China represents an emerging and fast-growing market, and it is also the second largest country undertaking offshore outsourcing. The total amount of offshore outsourcing contracts accounted for approximately 30% of the global
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offshore outsourcing market in 2013 (CSORC, 2014). Such a large market enables us to collect data from different types of BPO projects across various industries. In addition, the mixture of domestic and offshore projects in China can exhibit various levels of vendor and client capability risks. Managers in China are likely to experience different forms of control because complicated control
for analyzing the interaction between risks and control.
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combinations are required in offshore BPO projects. Therefore, a rich context is provided in China
With the assistance from the Service Outsourcing Association of China, we obtained a list of 600 nationwide service firms under the BPO industry. The final English and Chinese questionnaires were mailed and emailed to the managers who worked as vendor-side project managers in these firms. These managers were asked for the nomination of BPO projects and designation of relevant client-side managers, who then received coded questionnaires through mail and e-mail after the
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evaluation of their eligibility. Both vendor- and client-side managers were asked to respond retrospectively to the designated questions in the questionnaire. The vendor-side project managers evaluated the situation of process control, outcome control, and client capability risk, and provided the basic information of the project; whereas client-side managers responded to questions associated with vendor capability risk, project complexity, and performance. During the survey process, we
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asked the respondents whether any issues existed in the question response and whether they can favorably respond to each question. All respondents felt comfortable to assess the performance,
nominated BPO projects.
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control, and risks considering extensive understanding of the process and outcomes of the
The formal survey started in March 2014. With three months and two rounds of reminders, 234
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valid pair-wise questionnaires were received, yielding a response rate of 39%. Given the difficult reality of obtaining pair-wise data, the sample size was acceptable. The sample size is larger than
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previous project outsourcing studies where pair-wise design was employed (Kirsch et al., 2002; Tiwana and Keil, 2010). The ratio of sample size to the number of variables is also higher than the recommended ratio of 30:1 (Van Voorhis and Morgan, 2007). Vendor-side managers reported an
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average experience of 8.3 years (standard deviation = 5.4 years) in managing BPO projects, whereas client-side managers indicated an average experience of 7.1 years (standard deviation = 4.9 years) in participating in BPO projects. The respondents indicated working experience in the present firms for an average of 6.1 years (standard deviation = 4.6 years) for vendor-side managers and 7.4 years (standard deviation = 5.5 years) for client-side managers. We asked informants to evaluate the extent to which they were knowledgeable about the project to ensure that the respondents possessed sufficient knowledge to respond to the questionnaires. The mean was 6.67
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(standard deviation = 0.47) and 6.31 (standard deviation = 0.46) with seven-point scale for vendor-side managers and client-side managers, respectively. The project characteristics are presented in Table 2. Table 2 BPO project characteristics.
Contract length
1 2 3 4 5 6 7
Contract type
1 2
Number 36 22 46 22 20 16 72
Percentage 15.4% 9.4% 19.7% 9.4% 8.5% 6.8% 30.7%
122 112
52.1% 47.9%
60 52 20 22 8 12 60
25.6% 22.2% 8.5% 9.4% 3.4% 5.1% 25.6%
118 116
50.4% 49.6%
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1 2
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Outsourcing arrangement
Range Customer service Finance and accounting Human resource Training Procurement Back office Others Mean=4.30; standard deviation=2.24 Onshore Offshore Mean=1.48; standard deviation=0.50 1 month to 6 months 7 to 12 months 13 to 18 months 19 to 24 months 25 to 30 months 31 to 36 months > 36 months Mean=3.61; standard deviation=2.39 Fixed-price Time and materials Mean=1.50; standard deviation=0.50
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1 2 3 4 5 6 7
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Business function
Table 2 shows that our sample of BPO projects is diverse in terms of business function,
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outsourcing arrangement, contract length, and contract type. The majority of BPO projects is associated with customer service (15.4%), human resource (19.7%), and other emerging business
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functions (30.7%). This situation conforms that China is characterized as a sufficient human resource with low labor cost and huge demand market (BPO. net, 2016). BPO has also been applied in many emerging areas, such as the Internet, information service, and healthcare industries
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(Ministry of Commerce of China, 2016). Thus, we can reasonably expect that the BPO projects investigated in this study are related to these three domains. Nearly half of the sample was offshore BPO projects. This is expected because China is the second largest country that commences outsourcing projects, and the percentage of offshore BPO projects is increasing every year (Ministry of Commerce of China, 2016). This characteristic also conforms with the demographic in the research of Hardley and Benton (2009), where the percentages of onshore and offshore BPO projects are similar. The contract length of the investigated BPO projects ranges from 1 month to
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over 36 months, reflecting various project sizes. The mean value and standard deviation of contract length are 3.61 and 2.39, respectively (with a total scale of 7), which indicates that these projects are diverse in sizes (because of the high standard deviation) but have minimum negative influences on the data analysis (because of the medium mean value). Similar to outsourcing arrangement, almost half of the projects has fixed-price contract and the other half has time and materials contract.
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The mean value and standard deviation of contract type are 1.50 and 0.50, respectively (with a total scale of 2), suggesting that this feature also has a minimum negative effect to our subsequent analysis results. In summary, these BPO project characteristics indicate that our sample is diverse and includes representative projects in the BPO market of China. The duration and type of projects can also guarantee an effective analysis on the research model.
Common method bias can be reduced significantly through a pair-wise survey from vendor and
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client managers. We also followed the procedures recommended by Podsakoff et al. (2003) for the evaluation of common method bias by conducting exploratory factor analysis. Any single factor fails to account for the majority of covariance for all variables (< 20%). Thus, common method bias is minimal in our sample. Non-response bias was evaluated to examine external validity. We compared the questionnaires received during the early and late stages. The t-tests on process control,
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outcome control, vendor capability risk, client capability risk, performance, and all project characteristics demonstrate that significance levels of these variables are greater than 0.05.
4.4. Control variables
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Therefore, significant difference is not found and non-response bias does not threaten the sample.
Five control variables were incorporated in this study, namely, business function, outsourcing
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arrangement, contract length, contract type (see Table 1), and project complexity. Outsourcing different business functions may result in varied performance. Thus, we examine the effect of
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business function on BPO performance. Given that offshore outsourcing projects are across two countries and display high environmental and communication uncertainty (Nakatsu and Iacovou, 2009), outsourcing performance may differ between domestic and offshore projects. Contract length
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reflects the size of the BPO project, which is regarded as a type of risk that threatens the project success (Mani et al., 2010). Therefore, the effect of contract length on performance should be investigated. Fixed-price contracts and time and materials contracts have different levels of uncertainty (Mani et al., 2012). Hence, examining the influence of contract type is desirable. Project complexity is related to both risk and resilience (Lehtiranta, 2011; Thomé et al., 2016; Mishra et al., 2016), which influence project performance. Therefore, we examined the relationships among complexity, risks, and performance.
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4.5. Measurement assessment Reliability and validity of the constructs were first evaluated by conducting several tests. We performed exploratory factor analysis. All items exhibited high loadings on the expected variables and low loadings on the other variables. Factor loadings of all items exceeded 0.7. Cronbach’s α and composite reliability of each variable were higher than 0.7. Average variance extracted (AVE)
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values were greater than 0.5. The above results, which are shown in Table 3, collectively indicate good internal consistency. Table 3 Reliability and validity of constructs.
Client capability risk
Project complexity
AVE 0.79
0.95
0.94
0.83
0.94
0.94
0.78
0.91
0.93
0.71
0.94
0.94
0.81
0.91
0.93
0.73
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Performance
Construct reliability 0.92
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Vendor capability risk
Cronbach’s α 0.91
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Outcome control
Measure PCT1 PCT2 PCT3 OCT1 OCT2 OCT3 OCT4 VCR1 VCR2 VCR3 VCR4 CCR1 CCR2 CCR3 CCR4 PCP1 PCP2 PCP3 PCP4 PFM1 PFM2 PFM3 PFM4
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Construct Process control
Factor Loading 0.84 0.93 0.89 0.86 0.97 0.82 0.98 0.87 0.91 0.90 0.85 0.83 0.86 0.85 0.83 0.86 0.93 0.90 0.90 0.88 0.85 0.83 0.85
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We also conducted confirmatory factor analysis with AMOS 17.0. The results indicate that χ2 = 509.29 (p = 0.000), df = 215, χ2/df = 2.37 (< 3.00), RMSEA = 0.077 (< 0.08), 90% confidence
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interval for RMSEA is (0.068, 0.085), p of close fit is 0.000, SRMR = 0.05, NFI = 0.90, TLI = 0.93, CFI = 0.94, and IFI = 0.94. Although the relatively small sample size may influence the measurement model, the fit indices were acceptable (Kenny et al., 2014). Thus, the data and the model exhibited a reasonable fit (Hulland et al., 1996). Finally, discriminant validity was examined. We compared χ2 difference between two models for each of the 15 pairs among six latent variables. The first model allowed the correlation between all variable pairs to vary freely, whereas the second model allowed the correlation to be 1.0. All 15
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pairs are significant (p < 0.001), thereby indicating good discriminant validity (Kroes and Ghosh, 2010). We also followed the procedure suggested by Fornell and Larcker (1981). The squared correlation between each pair of latent variables was lower than the AVE for each construct. This result provides additional evidence for good discriminant validity. 5. Results
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The descriptive statistics and correlations between each variable are presented in Table 4. The hypotheses were tested by conducting hierarchical regression analysis with ordinary least squares. SPSS 17.0 was used for descriptive and hierarchical regression analyses. Theorized variables were incorporated stepwise to examine the amount of variance that explained for the dependent variable. Additional evidence of the significance level can be obtained by calculating the incremental explained variance and the value of F hierarchical (Carte and Russell, 2003). Four models were
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formed, as shown in Table 5. The first model investigated the relationship between control variables and the dependent variable. The second model analyzed the main effect of independent variables on the dependent variable, in which H1 and H2 can be tested. Model 2 was also used as basis for testing H3. The third model added the moderators based on the second model. This model works as a basis of comparison with other models to compute the incremental explained variance and value
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of F hierarchical. The fourth model examined the effects of the interaction between moderators and independent variables. H4, H5, H6, and H7 can be tested with Model 4. We mean-centered each
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variable before the formation of interaction terms to avert potential multi-collinearity. The variance inflated factor scores were also computed in all models. The resulting values were all less than 2.1, thereby indicating that multi-collinearity is insignificant in this study.
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Table 4 Descriptive statistics and correlations.
Standard 1 2 3 4 deviation 1. Process control 5.43 0.95 1.00 2. Outcome control 5.10 0.98 0.65** 1.00 3. Vendor capability risk 4.08 1.23 0.06 0.04 1.00 4. Client capability risk 3.75 1.37 -0.02 -0.08 0.23** 1.00 5. Project complexity 4.46 1.31 0.11 0.19** -0.10 -0.05 6. Performance 4.59 0.96 0.42** 0.47** -0.12* -0.17** Two-tail t-test was performed. * Significant at α=0.05, ** Significant at α=0.01. Mean
5
6
1.00 0.08
1.00
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Variable
Table 5 shows the explained construct variances and standardized path coefficients. By
comparing the changes in R2 between each two models, the values of F hierarchical were calculated and also shown in Table 5. Model 1 in Table 5 reveals that four control variables (i.e., business function, outsourcing arrangement, contract length, and project complexity) are insignificantly
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associated with performance. However, one control variable (i.e., contract type) significantly influences BPO performance. These results indicate that the performance of BPO projects is similar across different business functions, regardless of whether they are onshore or offshore. Moreover, BPO projects with long duration and high levels of complexity do not necessarily exhibit poor performance. Nevertheless, significant performance difference was found between BPO projects
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with time and materials and fixed-price contracts. Therefore, managers should carefully select the proper contract type to manage the outsourcing process. In addition, we examined the relationship of contract length with project complexity as well as the relationships of project complexity with client capability and vendor capability risks. The result shows that contract length is positively associated with project complexity (β = 0.19 and p < 0.01), which affects the two capability risks insignificantly (β = -0.05, p > 0.05; β = -0.10; p > 0.05). Thus, BPO projects of long duration
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exhibit high levels of complexity. Table 5 Hierarchical regression results.
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Model 3 Variable Model 1 Model 2 Model 4 Block 1: Control variable Business function 0.03 (0.03) 0.03 (0.02) -0.02 (0.02) -0.04 (0.02) Outsourcing arrangement -0.07 (0.13) -0.06 (0.11) -0.08 (0.11) -0.07 (0.10) Contract length 0.10 (0.03) 0.02 (0.02) -0.002 (0.02) -0.01 (0.02) Contract type 0.15* (0.12) 0.12* (0.11) 0.12* (0.11) 0.12* (0.11) Project complexity 0.07 (0.05) -0.003 (0.04) -0.01 (0.04) 0.03 (0.04) Block 2: Main effect Process control 0.20* (0.08) 0.22* (0.08) 0.18* (0.07) Outcome control 0.33*** (0.08) 0.31*** (0.07) 0.32*** (0.07) Vendor capability risk -0.15* (0.05) -0.15** (0.04) Client capability risk -0.11 (0.04) -0.07 (0.04) Block 3: Moderating effect Process control × Vendor capability risk 0.16* (0.06) Process control × Client capability risk -0.16* (0.06) Outcome control × Vendor capability risk -0.34*** (0.06) Outcome control × Client capability risk 0.23** (0.05) ΔR2 (Performance) 0.213 0.038 0.104 f2 (Effect size) 0.286 0.054 0.173 R2 (Performance) 0.043 0.256 0.294 0.398 F Hierarchical 64.702*** 12.057*** 38.007*** Number of observations (n) is 234. All path coefficients are standardized. The value in each parenthesis is the standard error. * p < 0.05; ** p < 0.01; *** p < 0.001.
Significant variances are explained for the dependent variable in model 2 (Table 5). The path
coefficients between all two independent variables and the dependent variable are significant. Process and outcome controls both influence outsourcing performance positively, thus supporting H1 and H2. The path coefficient between outcome control and performance is higher and more
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significant (β = 0.33; p< 0.001) than that between process control and performance (β = 0.20; p < 0.05). Thus, the effect of outcome control on performance is greater than that of process control. We also performed a t-test between the two path coefficients, as proposed by Cohen et al. (2003), to conduct statistical comparison of the two effects. The comparison was computed on the basis of the
1 R Y *(r ii r jj 2r ij ) n k 1 2
, where RY2 is the R2 of the dependent variable,
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j
following equation: t
rij are the factors of the inverted correlation metrics, k is the number of independent variable, n is the sample size, ßi is the path coefficient of independent variable i (i.e., outcome control in this study), and ßj is the path coefficient of independent variable j (i.e., process control in this study). The two-tail t-test result revealed that the effectiveness of outcome control was statistically higher
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than the effectiveness of behavior control (t=2.08). Therefore, H3 is supported.
Model 4 shows that vendor and client capability risks differentially and significantly moderate the effects of process and outcome controls on performance. The interaction term between vendor capability risk and process control is positive and significant, whereas the interaction term between client capability risk and process control is negative and significant. Therefore, the relationship
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between process control and performance is positively moderated by vendor capability risk but negatively moderated by client capability risk. Conversely, the interaction term between vendor
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capability risk and outcome control is negative and significant, whereas the interaction term between client capability risk and outcome control is positive and significant. Thus, the correlation between outcome control and performance is negatively moderated by vendor capability risk but
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positively moderated by client capability risk. The significance level of F hierarchical value further validates the significant moderating effects. Therefore, H4, H5, H6, and H7 are supported.
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The statement and result of each hypothesis are summarized in Table 6. Each hypothesis is supported.
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Table 6 Hypothesis testing results. Hypothesis H1 H2 H3 H4 H5 H6 H7
Path Process control → Performance Outcome control → Performance Outcome control → Performance > Process control → Performance Process control × Vendor capability risk → Performance Process control × Client capability risk → Performance Outcome control × Vendor capability risk → Performance Outcome control × Client capability risk → Performance
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Proposed effect Positive Positive Stronger Positive Negative Negative Positive
Result Support Support Support Support Support Support Support
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Both vendor and client capability risks moderate the effects of behavior and outcome control on performance differentially (H4–H7). Appendix A shows the two-way interaction graph for each of the four significant interaction effects (Aiken and West, 1991). In the presence of high vendor capability risk, high levels of process control yield high performance, whereas high levels of outcome control yield low performance. By contrast, high levels of process control result in low
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performance but high levels of outcome control result in high performance at high levels of client capability risk.
In each interaction graph, the highest performance can be obtained when process control is high and vendor capability risk is high or client capability risk is low. The highest performance can also be achieved when outcome control is high and vendor capability risk is low or client capability risk is high. Therefore, process control should be enhanced to achieve high performance in the
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presence of high vendor capability risk. In the presence of high client capability risk, outcome control should be enhanced to improve performance. Moreover, process control is recommended when the client has strong capability (low client capability risk) to facilitate high performance. Outcome control is recommended when the vendor has strong capability (low vendor capability risk)
6. Discussions and implications
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to facilitate high performance.
This research explored how vendor and client capability risks affected the effects of process
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and outcome controls on performance in BPO projects on the basis of risk- and control-based theories. We postulate that the correlation between each formal control mode and performance is moderated differentially by vendor and client capability risks. Empirical analysis of the dataset
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obtained from 234 BPO projects in China shows that the influence of outcome control on BPO project performance is greater than that of process control, although both formal control modes
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influence performance positively. Moreover, vendor and client capability risks play different and mixed roles in moderating the effects of process and outcome controls on performance. BPO performance is positively influenced by high levels of vendor capability risk and process control but
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is negatively affected by high levels of client capability risk and process control. By contrast, high levels of vendor capability risk and outcome control are associated with high performance, whereas high levels of client capability risk and outcome control are associated with low performance. The results of this study may not only contribute some novel knowledge to the BPO literature, but also provide some managerial implications for vendor-side and client-side managers in the effective enforcement of control and management of critical risks. 6.1. Theoretical implications
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First, our study may contribute to BPO literature by conducting an empirical investigation of the effects of process and outcome controls on performance. We provide solid evidence that process and outcome controls positively influence the performance of BPO projects. This result supports the previous argument that the enforcement of control effectively enhances performance and conforms to previous findings that process and outcome controls are positively associated with the
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performance of outsourced projects (Tiwana, 2008; Keil et al., 2013). Understanding both “what” and “how” goals of outsourced projects are accomplished is significant to outsourcing success. However, the simultaneous exercise of the two formal control modes is not required. The achievement of adequate control levels requires time, resources, and effort and transforms into “hidden costs” with outsourcing (Handley and Benton, 2013). Therefore, clients should also compare the cost and value associated with the applications of specific control modes to determine
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the appropriate control strategy.
Second, our research could contribute to control theory by highlighting the different attributes and effectiveness of process and outcome controls. Our findings reveal that the influence of outcome control on the performance of BPO projects is stronger than that of process control. Both formal control modes ensure predictability. However, process control is mechanistic and outcome
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control is flexible. Thus, outcome control can better balance emergence and predictability to provide satisfactory deliveries. The enforcement of process control is also more expensive than that
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of outcome control because process control requires high process observability of the client and frequent monitoring activities (Choudhury and Sabherwal, 2003; Tiwana and Keil, 2010). Although outcome control is more effective than process control, this condition does not mean that process
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control is unnecessary or insignificant in the management of outsourced projects. For example, clients rely heavily on process control in outsourcing professional service because frequent
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exchanges of information and processes are required in such types of outsourced projects (Stouthuysen et al., 2012). Third, our results indicate that either vendor or client capability risk plays a mixed role in
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moderating the relationship between process and outcome controls and performance in BPO projects. We present some new knowledge by demonstrating that capability risk related to vendors and clients serves as a two-edged sword with respect to control. In the presence of high vendor capability risk, the effect of process control on performance is high but the effectiveness of outcome control is low. Process control has low effectiveness in the presence of high client capability risk, whereas the effect of outcome control on performance is high. These observations contradict the general understanding in risk management literature that risk impairs project success (Mitra et al.,
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2016). The results support the existing argument that risks can be managed appropriately to produce high levels of operational performance (Liu, 2016; Aven, 2016). The current research also bridges an existing gap on whether the correlation between control and performance is negatively or positively moderated by risks (Tiwana and Keil, 2010; Harris et al., 2009). In addition, our findings address the existing gap resulting from same formal control mode being detected as either
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significantly or not significantly influencing performance in various studies (Tiwana, 2008; Tiwana and Keil, 2010). We find that each type of capability risk moderates the effects of process and outcome controls on performance differently.
Fourth, the results of the current research indicate that vendor and client capability risks exert opposing moderating effects on the correlation between each formal control mode and performance. This finding addresses the existing gap in previous studies that integrate risk and control but fail to
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distinguish the source of risk. The study also extends control literature by presenting empirical facts on the capability and knowledge of the controller and controlee to influence control effectiveness (Choudhury and Sabherwal, 2003). This observation supports the previous argument that the inputs from controllers and controlees generate different control results (Kirsch, 1997). Thus, before the enforcement of control, clients should not only evaluate the capability risk of vendors but also
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appraise their own capability risk. The occurrence of both high vendor and client capability risks should be avoided. Given that vendor capability risk decreases the effectiveness of outcome control
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and client capability risk diminishes the effectiveness of process control, formal control mechanisms cannot work effectively in such situations. 6.2. Managerial implications
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Our research has several important implications for practice. First, despite both process and outcome controls working effectively in reinforcing the performance of BPO projects, the inherent
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attributes of each formal control mode should be recognized. Outcome control is recommended in managing outsourced projects because such a control mode can balance the degree of emergence and regularity and is more effective than process control. Outcome control is particularly important
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in managing offshore outsourcing projects because it simplifies coordination processes and avoids considerable cultural conflicts. Although process control tends to be mechanistic, it can serve as an effective control portfolio by integrating other informal control modes, such as self-control (i.e., a mechanism that allows controlees to self-manage their tasks and achievements), which emphasizes emergence and autonomy. The enforcement of process control also requires frequent information exchange and communication between clients and vendors (Stouthuysen et al., 2012), thereby promoting mutual understanding and the development of long-term relationships (Ross et al., 2016).
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Second, client-side managers should discern the effective approach to exercise process and outcome controls in managing BPO projects when high vendor capability risk or client capability risk occurs. Clients with high capability risk should prioritize performing outcome control, whereas process control is suggested when high levels of vendor capability risk exist. However, when both vendor and client capability risks are present, the exercise of any formal control mode would not be
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effective in enhancing performance. In such situations, clients and vendors should either attempt to mitigate these two risks or change the practice of formal control mechanisms to alternative control mechanisms (e.g., informal control). Conversely, when both clients and vendors have high capability (i.e., low capability risk), the exercise of outcome control should be prioritized because the client can take full advantage of vendor capabilities while avoid high control costs. Process control can be modestly applied in the late stage of the outsourcing process.
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Clients should evaluate the capability risk of vendors and themselves regularly when they perform control because the capabilities of vendor or client may change during the outsourcing process. In such situations, the control strategy should also change accordingly. For example, vendor capability risk may be high at the beginning of outsourcing but largely decreases because of the accumulation of knowledge and experience. Thus, clients can implement process control first
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and outcome control at later stages. The control portfolio of process and outcome controls also enables clients to effectively manage multiple vendors with both high and low levels of capability
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risk. Client-side managers can perform process control effectively for those vendors with high capability risk, but exercise outcome control for vendors with low capability risk. Third, the miscellaneous moderating roles of vendor and capability risks give rise to the issues
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of treatment and management of such risks. Blindly minimizing vendor and client capability risks may produce additional unnecessary costs and unexpected results. On one hand, client executives
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should exploit the positive side of the two capability risks because of their capability to enforce process control with high vendor capability risk and to perform outcome control with high client capability risk. On the other hand, both client and vendor-side managers should design strategies to
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mitigate the negative aspects of vendor and client capability risks. Employees of either clients or vendors should receive adequate technical and business training to improve their capabilities. They can also adopt experienced managers to participate in the project (Liu and Wang, 2016). Clients and vendors should assist each other in addressing the challenge. Clients can offer knowledge-transfer training for vendors with high capability risk to enable vendors to gain an appropriate knowledge base to accomplish the project (Mehta and Mehta, 2009). Clients can also share their resources (e.g., human resource and personal management expertise) with vendors. Vendors can exchange
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employees with clients to enable each party to obtain new skills (Liu et al., 2010). 7. Limitations and directions for future research This research has three limitations in terms of theory, methodology, and geography. Theoretically, this study emphasized the roles of formal control mechanisms in managing BPO projects, but did not investigate the effectiveness of informal control mechanisms, which was not
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the focus of this research. Previous studies have suggested that informal control modes are weakly relied on and do not positively influence performance in outsourced projects because their practice requires extra significant formal controls (Chourhury and Sabherwal, 2003; Tiwana and Keil, 2010). Therefore, the inclusion of informal control mechanisms in this study may not be appropriate and necessary. However, future research can still examine the interactive effects between informal control mechanisms and capability risks because vendor and client capability risks may also
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enhance the effectiveness of informal control.
Methodologically, our measure of performance is based on subjective scales (i.e., satisfaction). The employment of objective scales appears to be more reliable than the application of subjective measures because social desirability concerns can be reduced considerably. Future research can use objective data associated with time, budget and quality of the accomplishment to reflect
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performance. Moreover, the sample size is relatively small for structural equation modelling, which may affect the fit of the model to the data. Future research can use a larger sample size to further
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validate our model.
Geographically, our study was performed in China, and that our results can be directly applied to other countries is not guaranteed. Different countries possess varied institutional and business
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culture contexts that might influence the decision-making of managers in performing control and their perceptions on vendor and client capability risks. Future research can extend our model to
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other cultural settings and introduce country-level elements, such as social value and legal environment, into the analysis to gain a more comprehensive understanding. The findings also provide four possible directions for future research. First, given that the
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control–performance relationship is differentially changed by vendor and client capability risks, the moderating effects of other risks derived from clients and vendors (e.g., client’s lack of cooperation and vendor’s lack of responsibility) are worth exploring. Second, this study focuses on the overall satisfaction of selected outsourced projects. The inclusion of the social aspect of performance (e.g., client-vendor long term relationship) in our model would be interesting because the influence of formal control mechanisms on social performance is still poorly understood. Third, the control relationship that we examined was between client and vendor. Future studies can apply our model
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into other control relationships in outsourcing (e.g., vendor-side project manager and employees) and investigate whether similar results can be obtained. Finally, formal control mechanisms and their corresponding effectiveness in managing multiple vendors can be studied. Given that both high and low levels of capability risks may be involved in different vendors, examinations of control effectiveness in such situations would be interesting.
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8. Conclusions
This study is one of the few attempts to investigate the interplay of risk and control and contributes to literature by indicating that vendor and client capability risks differentially moderate the effects of process and outcome controls on the performance of BPO projects. One significant finding of our study is that outcome control is more effective than process control in the context of outsourcing, although both formal control modes positively affect the performance of BPO projects.
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These results suggest that different formal control modes have various attributes and generate different levels of performance. Another important contribution may be the miscellaneous roles of vendor and client capability risks in moderating the correlation between control and performance. Under high vendor capability risk, process control has a significant effect on performance but the effectiveness of outcome control is low. By contrast, high client capability risk results in low
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effectiveness of process control but high effectiveness of outcome control. These results indicate that either vendor or client capability risk works as a double-edged sword with regard to control.
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The findings also highlight the significant difference between vendor and client capability risks in their moderating roles. Therefore, the risky situation of both vendors and clients should be
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Appendix A. Interaction graphs
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All constructs are mean-centered and there is no constant. Low vendor or client capability risk is one standard deviation below the mean and high vendor or client capability risk is one standard deviation above the mean.
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Effects of process and outcome controls on business process outsourcing performance: Moderating roles of vendor and client capability risks Shan Liu , Lin Wang , Wei Huang (Wayne) PII: DOI: Reference:
S0377-2217(17)30055-3 10.1016/j.ejor.2017.01.020 EOR 14201
To appear in:
European Journal of Operational Research
Received date: Revised date: Accepted date:
18 February 2016 6 January 2017 10 January 2017
Please cite this article as: Shan Liu , Lin Wang , Wei Huang (Wayne) , Effects of process and outcome controls on business process outsourcing performance: Moderating roles of vendor and client capability risks, European Journal of Operational Research (2017), doi: 10.1016/j.ejor.2017.01.020
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Highlights Process and outcome controls positively influence project performance.
Outcome control is more effective than process control.
Vendor and client capability risks differentially moderate control effectiveness.
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Effects of process and outcome controls on business process outsourcing performance: Moderating roles of vendor and client capability risks
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Shan Liu1, Lin Wang2*, Wei Huang (Wayne) 1 1. School of Management, Xi’an Jiaotong University, Xi’an 710049, China
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2. School of Management, Huazhong University of Science and Technology, Wuhan 430074 China
Abstract
Control over outsourced projects is a significant concern for both clients and vendors. Although the effect of control on performance has been studied previously, vendor and client capability risks have rarely been merged into the control–performance relationship. Using paired quantitative data
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collected from 234 business process outsourcing projects, we empirically determine that outcome control is more effective than process control, although both positively influence the performance of outsourced projects. Vendor and client capability risks play miscellaneous moderating roles on the effects of process and outcome controls on performance. In the presence of high vendor capability risk, the effect of process control on performance is high, but the effectiveness of outcome control is
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low. By contrast, high client capability risk results in low effectiveness of process control but high effectiveness of outcome control. Different control modes have various attributes and generate different levels of performance. Either vendor or client capability risk serves as a double-edged
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sword with regard to control. Therefore, the risky situation of both vendors and clients should be considered in the selection and enforcement of control in managing outsourced projects.
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Keywords: (B) Project management; risk management; business process outsourcing; control
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mechanism; vendor
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* Corresponding author. Email addresses: [email protected]; [email protected];
[email protected].
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1. Introduction Business process outsourcing (BPO) has become a transformational and prevalent business practice of organizations in realizing their strategic goals and managing their operations (Handley and Benton, 2009; Narayanan et al., 2011; Mani et al., 2012). In BPO, an organization enters into contract with an external firm to manage and to deliver one or more business functions or processes
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(Gartner, 2013). In 2011, the global BPO market reached 176 billion dollars and was estimated to reach more than 200 billion dollars in 2017 at a compounded annual growth rate of 5.7% (APCEO, 2012; Donovan, 2013). The rapid growth of BPO is recognized by researchers and practitioners, but a large number of organizations fail to obtain the benefit and value of BPO, as seen in their negative experiences with BPO projects. In a survey of 189 firm clients of BPO across various industries (e.g., finance and accounting, retailing, and health administration), 50% declared that BPO failed to
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reduce costs as prescribed in the contract, produce knowledge of specific processes, and provide extra value beyond standard operations (Fersht, 2014). Meanwhile, approximately 75% of the vendors indicated that client firms lacked adequate preparations for outsourcing, systematic strategies, and understanding of outsourcing working processes; this result is based on the survey of 300 executives from firms with more than $30 million annual deals worldwide across diverse
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industries (e.g., manufacturing, retail, services, and education) (Robinson et al., 2008). These results show that BPO projects exhibited unsatisfactory performance. Poor risk management and control
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strategies may be exercised by both clients and vendors in outsourced projects. In recent years, two research streams emerged to foster outsourcing performance. One stream draws upon control-based theory and emphasizes the significant role of formal control practices
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(Choudhury and Sabherwal, 2003; Rustagi et al., 2008). The other stream builds on the risk-based view and highlights the importance of managing key risks (Li et al., 2013; Liu and Wang, 2014a).
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These two streams have recently been integrated based on the influence of the interplay of control and risk on performance (Tiwana and Keil et al., 2010; Rustagi, 2004; Azimian et al., 2016). However, vendor and client capability risks have not been examined in the integration of control
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and risk. Prior studies on the control of outsourced projects have exhibited at least four gaps. First, although the correlation between formal control and the performance of outsourced
projects has been examined, the question of whether specific modes of formal control significantly facilitate outsourced project performance has not been addressed. Two modes of formal control were studied in prior research, namely, process control and outcome control. Process control refers to the mechanism utilized by a controller to evaluate the performance of the controlee based on how the latter follows the prescribed procedures and methods (Tiwana and Keil, 2007; Choudhury and
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Sabherwal, 2003). Outcome control is the mechanism employed by a controller to assess the performance of the controlee based on how the latter follows the prescriptions of desired outputs (Kirsch, 1997; Tiwana and Keil, 2010). Previous studies have provided evidence that formal control can enhance the performance of outsourced projects (Tiwana, 2008; Keil et al., 2013). However, the relationship between two formal control modes (i.e., process and outcome controls) and has
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relatively
little
attention.
Previous
studies
regarding
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performance
the
control–performance relationship have also displayed contradictory findings. For example, Gopal and Gosain (2010) found that process control positively and significantly affected the performance of outsourced projects, whereas Tiwana and Keil (2010) showed that increased use of process control had insignificant association with performance. The same situation also occurs for the correlation between outcome control and performance (Gopal and Gosain, 2010; Tiwana and Keil,
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2010). Therefore, additional empirical research is needed to study this issue.
Second, although both process and outcome controls are exercised extensively to manage outsourced projects, little evidence has been provided as to which mode of formal control exhibits greater influence on performance. In a multiple-case study, Choudhury and Sabherwal (2003) observed that outcome control dominated the portfolios of control in outsourced projects, but
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process control was often used in the late phase of outsourced projects. This finding suggests that the choice and presumably the effectiveness of process and outcome controls may differ in the
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context of outsourcing. Different control modes also exhibit various characteristics: process control is mechanistic and emphasizes predictability and regularity (Das and Teng, 1998; Ouchi, 1980), whereas outcome control is organic and emphasizes the balance of emergence and control (Harris et
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al., 2009). Different features of process and outcome controls may result in varied levels of performance in outsourced projects. Therefore, investigations on the relative importance of process
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and outcome controls are complicated and significant. Understanding this issue enables the proper selection of effective formal modes and optimization of control strategies in managing outsourced projects.
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Third, researchers have argued that risk and control collectively affect the performance of
outsourced projects. However, they focused primarily on the technical aspect of risk (e.g., technology uncertainty and technological modularity risk) (e.g., Tiwana, 2008; Harris et al., 2009) while neglecting the importance of capability risks in outsourcing performance and relationship management. Capability risks, which denote the uncertainty and issues associated with the ability, knowledge, and skills to manage outsourced projects, are among the top ten risks in domestic and offshore outsourcing projects (Nakatsu and Iacovou, 2009). The effective management of such risks
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is fundamental to the success of outsourcing (Handley, 2012). Nevertheless, capability risks have never been integrated into control–performance relationship before. Previous studies have presented diverse results on the interactions between risk and the same formal control mode. For instance, Tiwana and Keil (2010) empirically determined that requirement volatility (i.e., “the extent to which project requirements unpredictably change over the course of the systems development life
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cycle” (Tiwana and Keil, 2010, p. 21) lowered the effect of outcome control on performance. In spite of this intuitive result, other studies found that the effectiveness of outcome control can be enhanced in the environment of technology risk (Harris et al., 2009). Therefore, how critical risks, capability risks in particular, affect the effects of process and outcome controls on performance in outsourced projects should be examined. Explorations of this issue may enable managers to deal with capability risks correctly and thus optimize control portfolios in the presence of such risks.
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Fourth, previous research seldom distinguished the source of risk. Little is known about the influence of vendor and client capability risks on the relationship of formal control modes with performance. Vendor capability risk refers to the issues associated with the ability, knowledge, and skills of a vendor to accomplish project goals that can increase the uncertainty of project outcomes, whereas client capability risk refers to the issues associated with the ability, knowledge, and skills
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of a client to manage the outsourcing process and vendors (Nakatsu and Iacovou, 2009; Han et al., 2013). Vendor and client capability risks display significant differences because these two risks
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originate from two independent parties (i.e., client and vendor). Prior research highlights the significance of understanding both stakeholders to achieve high outsourcing performance (Nyaga et al., 2010; Oosterhuis et al., 2013), but vendor and client capability risks have never been
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investigated simultaneously. Given that the input from different parties has different influences on control effectiveness (Kirsch, 1997; Choudhury and Sabherwal, 2003), understanding how vendor
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and client capability risks may moderate the correlations between two formal control modes and performance in outsourced projects is necessary and important. Further examinations of the roles of vendor and client capability risks in control effectiveness may assist the understanding of effective
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management of such risks and the client–vendor control relationship. These issues are noteworthy in practice because managers may select control modes that are
ineffective in a risky environment but may work effectively in others. Explorations of these issues will probably help client managers to manage the control relationship with vendors productively based on the risks associated with both clients and vendors, minimize unnecessary resources and costs associated with the exercise of control, and avoid unsatisfactory outcomes. This study focuses on BPO projects because BPO involves diverse operational objectives (e.g., business transformation,
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innovation, and cost reduction) and may generate various levels of control and risk (Mani et al., 2010; Rai et al., 2012). In sum, we address the following research questions based on the above discussions: (1) How do process control and outcome control influence the performance of BPO projects? (2) How do vendor and client capability risks alter control–performance relationship in BPO
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projects?
We present a theoretical model based on the control-based theory and risk-based views. We also analyze survey data obtained from 234 BPO projects in China and provide insights on the integration of control with vendor and client capability risks in BPO projects. The rest of the paper is organized as follows. The relevant theory and literature are introduced in Section 2. The conceptual model and hypotheses are presented in Section 3. Data collection, scale, and
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measurement validation are described in Section 4. Results of data analysis are given in Section 5. Finally, the theoretical and managerial implications of the research findings are discussed in Section 6. 2. Theoretical foundation 2.1. Control in outsourcing relationships
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Control in outsourcing relationships refers to the mechanism that an outsourcer (controller) uses to regulate the actions of outsourcees (controlees) to achieve desired goals (Tiwana and Keil,
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2010; Choudhury and Sabherwal, 2003). Control is performed by the client firm (controller) through various control mechanisms to ensure that the vendor firm (controlee) behaves in a manner that will help realize the outsourcing objectives (Kirsch et al., 2002; Tiwana, 2008). This study
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focuses on formal control mechanisms, which are exercised intensively in managing outsourcing relationships. In formal control, controlee behavior is influenced by adherence to prescribed
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processes and outcome-based evaluations (Tiwana and Keil, 2007; Choudhury and Sabherwal, 2003). Two modes of formal control are described in previous studies: process control and outcome control. Process control (or behavior control) is implemented by the client to evaluate vendor
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performance based on how prescribed procedures and methods are adopted by the vendor (Tiwana, 2008). Outcome control is practiced by the client to assess vendor performance according to the extent to which desired final targets and outputs are achieved regardless of the process (Henderson and Lee, 1992; Tiwana and Keil, 2010). Process control describes how desired outcomes are achieved, whereas outcome control describes what should be accomplished in outsourced projects (Kirsch et al., 2002). Previous research in the control of outsourcing context has focused on the following areas: (1)
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exploration and formation of specific control mechanisms (Das and Teng, 1998; Choudhury and Sabherwal, 2003), (2) investigation of factors that can predict and decide the choice of specific control modes (Rustagi et al., 2008; Goodale et al., 2008), (3) control configuration and optimization in the process of outsourcing (Daityari et al., 2008; Gregory et al., 2013; Schildbach, and Morari, 2016), (4) documentation of internal functions between a pair of control modes
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(Tiwana, 2010; Rijsdijk and Ende, 2011), and (5) examination of the correlation between control and performance (Tiwana and Keil, 2010; Stouthuysen et al., 2012). 2.2. Control and performance in outsourced projects
The positive relationship between formal control and performance is well documented and recognized in previous research (Rustagi, 2004; Keil et al., 2013). However, contradictory findings have been obtained with respect to the effectiveness of process and outcome controls in outsourced
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projects (Tiwana, 2008; Gopal and Gosain, 2010; Tiwana and Keil, 2010). Thus, further empirical evidence is required to understand how process and outcome controls affect outsourcing performance. In accordance with our general understanding of the positive effectiveness of formal control (Keil et al., 2013), effective exercise of process and outcome controls may enable the client to acquire satisfactory outputs and expected project values realized by the vendors.
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Although both process and outcome controls are practiced in managing outsourced projects, previous studies suggest that the effectiveness of these two control modes may differ. For instance,
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Tiwana and Keil (2010) argued that the performance of outsourced projects was positively influenced by outcome control but insignificantly influenced by process control because of the difficulty in implementing process control in outsourced projects. As a result, the effect of outcome
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control on performance may be stronger than that of process control in outsourced projects. 2.3. Vendor and client capability risks, control, and performance
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In prior literature, risk is viewed as a condition that seriously influences outsourcing success (Gewald and Dibbern, 2009; Powell et al., 2016). Lehtiranta (2014) argued that risk can generate unanticipated results and exert either negative or positive influence because of its high uncertainty.
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Management approaches and activities (e.g., control) will adapt (weaken or strengthen) toward project risks to achieve success from the complexity view (Lehtiranta, 2011; Liu, 2015). This research focuses on two significant risk factors, namely, vendor and client capability risks, which may change the effects of process and outcome controls on performance. These two risks are associated with two different parties (i.e., client and vendor) and display significant differences. They were selected from various types of risks (e.g., contract management and technological risks) related to outsourcing projects for three reasons. First, vendor and client capability risks are broadly
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acknowledged to be critical. They are situated in the top ten risks in offshore and domestic outsourcing projects (Nakatsu and Iacovou, 2009). Effective management of such risks is vital to the success of outsourcing (Handley, 2012). Second, compared with technology-related risks, the moderating roles played by vendor and client capability risks in the relationship between control and performance are poorly understood. Third, vendor and client capability risks have never been
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investigated simultaneously; however, many studies argue that inputs from either client or vendor significantly could influence outsourcing performance (Li et al., 2008; Narayanan et al., 2011).
Previous evidence implies that vendor and client capability risks may change control effectiveness. For instance, boundary spanning, which is an organizational capability of vendors, significantly moderates the effectiveness of process and outcome controls in outsourced projects (Gopal and Gosain, 2010). Client peripheral knowledge (specialized knowledge in the domain of
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outsourced activities), a type of capability of clients, also exerts a significant moderating effect on the relationship between control and performance (Tiwana and Keil, 2007). Given that vendor and client capability risks refer to issues or uncertainty associated with capability, these two risks together may moderate the effects of process and outcome controls on the performance of outsourced projects.
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2.4. BPO satisfaction as a dependent variable
According to the literature (Dibbern et al., 2004; Rai et al., 2012), outsourcing performance
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can be defined from three perspectives, namely, the performance of outsourced processes and operations, the accomplishment of objectives (e.g., cost reduction), and satisfaction. BPO satisfaction is used as a critical performance metric in this study because it is simple, significant,
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and well-defined in the literature. It also represents perceived performance of business partnerships (Poppo and Zenger 2002; Mani et al., 2010). Consistent with previous studies (Rai et al., 2012;
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Mani et al., 2010), we define BPO satisfaction as the extent to which satisfactory service and outcomes of BPO project are delivered. 3. Research model and hypothesis development
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Figure 1 displays our research model. We contend that process and outcome controls would
positively affect BPO performance. However, the effect of outcome control on BPO performance may be greater than that of process control. The moderating effects of vendor and client capability risks on the relationships between process/outcome controls and performance may differ. The relationship between process control and BPO performance could be positively moderated by vendor capability risk, but negatively moderated by client capability risk. In contrast, the effectiveness of outcome control may be negatively moderated by vendor capability risk but
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positively moderated by client capability risk.
Process control
H5-
H1+
H3: The relationship between outcome control and BPO performance is stronger than that between process control and BPO performance
H7+
BPO performance
H4+ Outcome control
H2+
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Client capability risk
H6-
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Vendor capability risk
Figure 1. Research model. 3.1. Effects of process and outcome controls on performance
Control works effectively in enhancing the performance of outsourced projects (Tiwana, 2008;
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Daityari et al., 2008). A number of studies provide empirical evidence that formal control mechanisms have positive effects on performance in either domestic or international outsourcing projects (Li et al., 2008; Srivastava and Teo, 2012). Therefore, we posit that process and outcome
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controls would positively influence the performance of BPO projects. In process control, clients (controllers) focus on the suitability and significance of process
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execution. Their practice of process control ensures that vendors (controlees) adopt appropriate steps and procedures to minimize errors and meaningless modifications and thus increase working
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performance (Gopal and Gosain, 2010; Liu and Wang, 2014b). Process control also offers a systematic and structured method of developing business processes to avoid uncertainty and generate outcomes according to client expectations. By evaluating the extent to which prescribed
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procedures and rules are adopted upon the accomplishment of project objectives, vendors can work effectively on completing project tasks; clients are also able to monitor project progress conveniently (Henderson and Lee, 1992). Therefore, we present the following hypothesis: H1. Process control exerts a positive effect on the performance of BPO projects. Outcome control emphasizes the significance of accomplishing desired goals of outsourced projects. In outcome control, clients can provide feedback efficiently for corrections by evaluating accomplished outcomes (Love and Josephson, 2004). Vendors are also motivated to take
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appropriate action if project objectives and requirements are not satisfied, thereby resulting in high output efficiency and reliability (Gopal and Gosain, 2010). Outcome control enables vendors to follow explicit scopes and goals, hence producing outcomes with client expectations (Barnes and Targett, 1999). Outcome control considerably increases the working efficiency of vendors in completing tasks, thereby enhancing the performance of outsourced projects (Bello and Gilliland,
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1997). The stipulated evaluation criteria also generate proper vendor actions that lead to delivery of satisfied outcomes (Gopal and Gosain, 2010). Thus, we present the following hypothesis. H2. Outcome control exerts a positive effect on the performance of BPO projects. 3.2. Relative significance of process and outcome controls to performance
Although both process and outcome controls positively influence the performance of BPO projects, we posit that outcome control would be more effective than process control. Process
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control and outcome control display different characteristics. Process control is mechanistic and emphasizes predictability and regularity (Das and Teng, 1998; Ouchi, 1980). By contrast, outcome control is organic and balances emergence and control (Harris et al., 2009; Tiwana and Keil, 2010). Given that the management of outsourcing relationships with both emergence and control outperforms that with either predictability or emergence (Choi et al., 2001), outcome control
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influences performance to a greater degree than process control.
In process control, the direct observation and monitoring of vendor actions and behavior are
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difficult in outsourced projects (Tiwana and Keil, 2010). Process control is also more costly than outcome control because considerable time and work are required to monitor and evaluate the outsourcing processes (Choudhury and Sabberwal, 2003). These factors may negatively influence
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the effectiveness of process control. Compared with process control, outcome control explicitly specifies desired goals and is associated more directly with project performance (Daityari et al.,
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2008). Evaluations and rewards based on outcome control also inspire vendors more directly to deliver satisfactory outcomes (Liu and Wang, 2014b). Outcome control exhibits high levels of flexibility in accomplishing project goals and places little weight on implementation processes
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(Tiwana and Keil, 2007), hence working effective in such situations. Therefore, we present the following hypothesis. H3.
The relationship between outcome control and performance is stronger than the
relationship between process control and performance in BPO projects. 3.3. Moderating effects of vendor and client capability risks We argue that vendor and client capability risks could change the effectiveness of each mode of formal control differently. Drawn upon the control theory, an effective exercise of control
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depends on the knowledge and capability of the controller and controlee (Eisenhardt, 1985; Kirsch et al., 2002). A competent controller is confident and capable of specifying accurate rules, processes, and methods that a controlee should follow to facilitate performance (Kirsch, 1997). However, controlees with high levels of capability tend to focus on their own processes (Kirsch, 1996; Silbermayr and Minner, 2016), causing the process control exercised by the controller to become
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ineffective. These prior findings indicate that the effectiveness of process control may be enhanced in the presence of low client capability risk but weakened in the presence of low vendor capability risk. By contrast, while competent controlees are capable of managing their own processes, they could enable the controller to perform outcome control more effectively. Logically, a competent controller is likely to place much control on process, thereby impairing the flexibility of outcome control. The above analysis implies that the effectiveness of outcome control may be enhanced in
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the presence of low vendor capability risk but weakened in the presence of low client capability risk. Hence, the effects of process and outcome controls exercised by the client are expected to differ in the presence of high levels of vendor and client capability risks.
In process control, clients prescribe rules and procedures and expect vendors to follow these predefined processes and steps (Tiwana and Keil, 2010). If high vendor capability risk is present,
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clients will articulate and predefine rules and processes clearly and precisely. They will also check the project progress frequently and evaluate the conditions of outsourced projects carefully to
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monitor and manage the outsourcing process (Sabherwal and King, 1995). These control activities intensify the performance of outsourced projects. Furthermore, given that vendors with low capability experience great difficulty in using their own methods and processes to accomplish tasks
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(Choudhury and Sabberwal, 2003), high vendor capability risk may lead vendors focus carefully and accurately on adopting and executing the processes and procedures prescribed by clients,
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thereby leading to satisfactory outcomes. Therefore, we present the following hypothesis. H4. The effect of process control on the performance of BPO projects is strong when vendor capability risk is high.
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High client capability risk increases the difficulty of prescribing accurate and executable
procedures and steps that guide vendors to accomplish project goals (Chua et al., 2012). Clients with high capability risk may also design incorrect rules and processes, which impair the performance of outsourced project if adopted. Moreover, such clients cannot monitor the behavior of vendors appropriately and evaluate project status because of insufficient skills and knowledge to manage outsourcing processes (Choudhury and Sabherwal, 2003). Conflicts between clients and vendors are also very likely to arise because vendors may not agree with and adopt the processes
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designed by clients with high capability risk. Thus, we present the following hypothesis. H5. The effect of process control on the performance of BPO projects is low when client capability risk is high. Outcome control enables clients to prescribe desired goals and allows vendors to accomplish these goals by using their own processes and methods (Tiwana, 2008). However, vendors with high
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capability risk lack systematic methods and adequate expertise to complete tasks and achieve project objectives (Tang and Rai, 2012). Thus, the influence of outcome control on performance is lessened. Vendor capability risk also leads to the uncertainty of processes and tasks (Wallace et al., 2004). Such situations results in frequent changes in targets and goals, thereby increasing the difficulty of assessing vendor performance based on predefined evaluation criteria. Therefore, the effectiveness of outcome control is diminished. Vendor capability risk also reduces the efficiency of
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outcome control (Kortmann et al., 2014), which minimizes the effect of outcome control on BPO performance.
H6. The effect of outcome control on the performance of BPO projects is low when vendor capability risk is high.
Clients with high capability risk focus heavily on specifying the goals and requirements of
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outsourced projects but minimize their focus on the outsourcing process (Choudhury and Sabherwal, 2003). They also evaluate the accomplishment of project objectives carefully; thus, the effectiveness
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of outcome control is enhanced in such situations. Client capability risk increases the flexibility of outcome control (Harris et al., 2009), which motivates and encourages vendors to take on their responsibility, satisfy client needs, and realize project goals. Clients with low capability are also
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likely to develop a trusting relationship with vendors (Tiwana and Keil, 2007). Such a relationship may enable vendors to accomplish project goals effectively. Thus, we present the following
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hypothesis.
H7. The effect of outcome control on the performance of BPO projects is strong when client capability risk is high.
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4. Research methodology 4.1. Research design A survey on 234 BPO projects was conducted to gather quantitative data, which were used
empirically to test hypotheses. Consistent with previous studies of outsourcing or project management (e.g., Tiwana and Keil, 2010; Arumugam et al., 2016), we employed a multi-informant approach to gather data from both clients and vendors at the project level, thereby avoiding common method bias. The project manager in the Chinese vendor firm, to which the project was
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outsourced, and the manager who oversaw and supervised the project in the client firm answered a pair-wise survey questionnaire. A sample of 600 service organizations with BPO experience was drawn from the directory of corporate project managers provided by the Service Outsourcing Association of China. These service organizations, which are located in both Eastern and Western China, have provided BPO
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service for more than 30000 firms. The vendor-side project managers of these firms, who possessed extensive experience in managing BPO projects, were contacted to nominate an appropriate BPO project and a client-side manager who participated in and supervised the same project. To achieve high levels of project diversity, project managers from various BPO business functions were contacted. Thus, main types of BPO projects (e.g., customer service, finance and accounting, human resource, training, and procurement) were included in the project sample. To avoid recall issues, the
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selected project should have been completed within the previous year. Moreover, at least one deliverable function should be accomplished to guarantee that significant control activities have occurred in the project. After the BPO projects were determined, we collected and reviewed information (e.g., project duration and contract type) on the selected projects to ensure their diversity and representativeness. All selected projects were required to pair off both the vendor- and
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client-side project managers for the survey. The client-side manager should demonstrate an extensive understanding of the nominated projects. Before distributing the questionnaires, the
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client-side managers were contacted to ensure their eligibility as respondents. On the basis of existing measures, a survey instrument was developed to obtain data. A pilot study on 30 managers with rich experience in BPO projects was first conducted. Then, we sent
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coded questionnaires through mail and e-mail to the requested vendor- and client-side managers who were eligible to participate. Both vendor- and client-side managers were asked to respond
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retrospectively to the designated questions in the questionnaire. Next, we conducted a number of tests on our sample to examine method and non-response bias, and obtain useful responses during survey administration. Subsequently, we developed and validated a set of measurement models to
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test hypotheses through hierarchical regression analysis. The effect of process and outcome control was assessed and compared to test H1 to H3. Moderating effects of client and vendor capability risks were evaluated to test H4 to H7. Specific procedures are stated below. 4.2. Construct operationalizations and instrument development We used multi-item scales to operationalize each variable. Previous instruments related to control, risk, complexity, and performance were adapted primarily for the variables. A seven-point reflective Likert scale that ranged from “strongly disagree” to “strongly agree” was used to measure
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each item. Paired questionnaires were designed for vendor- and client-side managers. Process control, outcome control, and client capability risk were evaluated by vendor-side managers, whereas vendor capability risk, project complexity, and performance were assessed by client-side managers. We first developed the English version questionnaire, translated it into Chinese, and back-translated it into English. The original and back-translated English questionnaires were
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compared to check for consistency.
Following previous studies (e.g., Tang and Rai, 2014), we acquired several measures to improve the initial instrument. First, the two-stage Q-sorting method was applied for face and content validities (Moore and Benbasat, 1991). Second, a panel of 10 American and Chinese Ph.D. students, and five professors with expertise in business process management and outsourcing was formed to provide suggestions for the survey design and evaluate the questionnaire design, format,
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expressions, and content. Based on their feedback, revisions on the survey instrument were performed. This process lasted for two months. Third, we conducted a pilot test with 30 randomly selected vendor- and client-side managers to ensure comprehensibility and reliability, and evaluate the variances of constructs explained by the measures. These managers have intensive experience in managing BPO projects. They provided effective suggestions on the expression of each item. The
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questionnaire was modified to strengthen its reliability based on the feedback we received. This process lasted for one month. Final construct measurements are shown in Table 1.
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Process control was measured by three items based on the studies by Tiwana (2008) and Keil et al. (2013). Four scale items to measure outcome control were adapted from Kirsch et al. (2002) and Tiwana (2008). Vendor capability and client capability risks were measured using four items
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adopted from Nakatsu and Iacovou (2009) and Han et al. (2013). Project complexity, which was used as a control variable in this study, refers to the inherent difficulty that a project experiences.
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This variable was measured by four indicators, which were adapted from Abdullah and Verner (2012) and Liu (2015). The scales and items to measure performance, which reflect reliability, responsiveness, systematization, and innovation of the service, was adopted from the work of Mani
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et al. (2010).
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Table 1 Constructs and measures.
VCR1 VCR2 VCR3 VCR4
CCR1 CCR2 CCR3 CCR4
PCP1 PCP2 PCP3 PCP4
PFM1 PFM2 PFM3
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PFM4
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OCT1 OCT2 OCT3 OCT4
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PCT3
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PCT2
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PCT1
Construct and Measure Process control (Vendor-side manager) In this BPO project The client expected the vendor to follow an understandable written sequence of steps specified by the client toward the accomplishment of project goals The client expected the vendor to follow articulated rules and procedures specified by the client toward the accomplishment of project goals The client assessed the extent to which existing written procedures and practices were followed during the outsourcing process Outcome control (Vendor-side manager) In this BPO project The client placed significant weight upon the timely completion of project tasks The client placed significant weight upon project completion within budget The client placed significant weight upon project completion to the satisfaction of the client The client evaluated the performance of the vendor by the extent to which project goals were accomplished Vendor capability risk (Client-side manager) In this BPO project The vendor lacked adequate technical knowledge necessary for the project The vendor lacked adequate business knowledge necessary for the project The vendor lacked specialized skills required by the project Vendor employees were inexperienced Client capability risk (Vendor-side manager) In this BPO project The client lacked outsourcing experience The client lacked essential skills and knowledge to manage the outsourcing process The client lacked the ability for contract management The client lacked the ability for vendor management Project complexity (Client-side manager) In this BPO project Business process required complex integration and customization There was high level of technical complexity The task was highly complex There were many business and technical difficulties Performance (Client-side manager) In this BPO project The vendor performed contracted services dependably and accurately The vendor provided prompt service The processes, procedures, systems, and technology provided by the vendor made the service a seamless one The vendor leveraged process knowledge to deliver a range of process enhancements that go beyond performance expectations of the client
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No.
4.3. Data collection All the projects in the sample were conducted in China. China represents an emerging and fast-growing market, and it is also the second largest country undertaking offshore outsourcing. The total amount of offshore outsourcing contracts accounted for approximately 30% of the global
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offshore outsourcing market in 2013 (CSORC, 2014). Such a large market enables us to collect data from different types of BPO projects across various industries. In addition, the mixture of domestic and offshore projects in China can exhibit various levels of vendor and client capability risks. Managers in China are likely to experience different forms of control because complicated control
for analyzing the interaction between risks and control.
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combinations are required in offshore BPO projects. Therefore, a rich context is provided in China
With the assistance from the Service Outsourcing Association of China, we obtained a list of 600 nationwide service firms under the BPO industry. The final English and Chinese questionnaires were mailed and emailed to the managers who worked as vendor-side project managers in these firms. These managers were asked for the nomination of BPO projects and designation of relevant client-side managers, who then received coded questionnaires through mail and e-mail after the
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evaluation of their eligibility. Both vendor- and client-side managers were asked to respond retrospectively to the designated questions in the questionnaire. The vendor-side project managers evaluated the situation of process control, outcome control, and client capability risk, and provided the basic information of the project; whereas client-side managers responded to questions associated with vendor capability risk, project complexity, and performance. During the survey process, we
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asked the respondents whether any issues existed in the question response and whether they can favorably respond to each question. All respondents felt comfortable to assess the performance,
nominated BPO projects.
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control, and risks considering extensive understanding of the process and outcomes of the
The formal survey started in March 2014. With three months and two rounds of reminders, 234
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valid pair-wise questionnaires were received, yielding a response rate of 39%. Given the difficult reality of obtaining pair-wise data, the sample size was acceptable. The sample size is larger than
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previous project outsourcing studies where pair-wise design was employed (Kirsch et al., 2002; Tiwana and Keil, 2010). The ratio of sample size to the number of variables is also higher than the recommended ratio of 30:1 (Van Voorhis and Morgan, 2007). Vendor-side managers reported an
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average experience of 8.3 years (standard deviation = 5.4 years) in managing BPO projects, whereas client-side managers indicated an average experience of 7.1 years (standard deviation = 4.9 years) in participating in BPO projects. The respondents indicated working experience in the present firms for an average of 6.1 years (standard deviation = 4.6 years) for vendor-side managers and 7.4 years (standard deviation = 5.5 years) for client-side managers. We asked informants to evaluate the extent to which they were knowledgeable about the project to ensure that the respondents possessed sufficient knowledge to respond to the questionnaires. The mean was 6.67
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(standard deviation = 0.47) and 6.31 (standard deviation = 0.46) with seven-point scale for vendor-side managers and client-side managers, respectively. The project characteristics are presented in Table 2. Table 2 BPO project characteristics.
Contract length
1 2 3 4 5 6 7
Contract type
1 2
Number 36 22 46 22 20 16 72
Percentage 15.4% 9.4% 19.7% 9.4% 8.5% 6.8% 30.7%
122 112
52.1% 47.9%
60 52 20 22 8 12 60
25.6% 22.2% 8.5% 9.4% 3.4% 5.1% 25.6%
118 116
50.4% 49.6%
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1 2
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Outsourcing arrangement
Range Customer service Finance and accounting Human resource Training Procurement Back office Others Mean=4.30; standard deviation=2.24 Onshore Offshore Mean=1.48; standard deviation=0.50 1 month to 6 months 7 to 12 months 13 to 18 months 19 to 24 months 25 to 30 months 31 to 36 months > 36 months Mean=3.61; standard deviation=2.39 Fixed-price Time and materials Mean=1.50; standard deviation=0.50
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1 2 3 4 5 6 7
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Business function
Table 2 shows that our sample of BPO projects is diverse in terms of business function,
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outsourcing arrangement, contract length, and contract type. The majority of BPO projects is associated with customer service (15.4%), human resource (19.7%), and other emerging business
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functions (30.7%). This situation conforms that China is characterized as a sufficient human resource with low labor cost and huge demand market (BPO. net, 2016). BPO has also been applied in many emerging areas, such as the Internet, information service, and healthcare industries
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(Ministry of Commerce of China, 2016). Thus, we can reasonably expect that the BPO projects investigated in this study are related to these three domains. Nearly half of the sample was offshore BPO projects. This is expected because China is the second largest country that commences outsourcing projects, and the percentage of offshore BPO projects is increasing every year (Ministry of Commerce of China, 2016). This characteristic also conforms with the demographic in the research of Hardley and Benton (2009), where the percentages of onshore and offshore BPO projects are similar. The contract length of the investigated BPO projects ranges from 1 month to
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over 36 months, reflecting various project sizes. The mean value and standard deviation of contract length are 3.61 and 2.39, respectively (with a total scale of 7), which indicates that these projects are diverse in sizes (because of the high standard deviation) but have minimum negative influences on the data analysis (because of the medium mean value). Similar to outsourcing arrangement, almost half of the projects has fixed-price contract and the other half has time and materials contract.
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The mean value and standard deviation of contract type are 1.50 and 0.50, respectively (with a total scale of 2), suggesting that this feature also has a minimum negative effect to our subsequent analysis results. In summary, these BPO project characteristics indicate that our sample is diverse and includes representative projects in the BPO market of China. The duration and type of projects can also guarantee an effective analysis on the research model.
Common method bias can be reduced significantly through a pair-wise survey from vendor and
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client managers. We also followed the procedures recommended by Podsakoff et al. (2003) for the evaluation of common method bias by conducting exploratory factor analysis. Any single factor fails to account for the majority of covariance for all variables (< 20%). Thus, common method bias is minimal in our sample. Non-response bias was evaluated to examine external validity. We compared the questionnaires received during the early and late stages. The t-tests on process control,
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outcome control, vendor capability risk, client capability risk, performance, and all project characteristics demonstrate that significance levels of these variables are greater than 0.05.
4.4. Control variables
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Therefore, significant difference is not found and non-response bias does not threaten the sample.
Five control variables were incorporated in this study, namely, business function, outsourcing
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arrangement, contract length, contract type (see Table 1), and project complexity. Outsourcing different business functions may result in varied performance. Thus, we examine the effect of
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business function on BPO performance. Given that offshore outsourcing projects are across two countries and display high environmental and communication uncertainty (Nakatsu and Iacovou, 2009), outsourcing performance may differ between domestic and offshore projects. Contract length
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reflects the size of the BPO project, which is regarded as a type of risk that threatens the project success (Mani et al., 2010). Therefore, the effect of contract length on performance should be investigated. Fixed-price contracts and time and materials contracts have different levels of uncertainty (Mani et al., 2012). Hence, examining the influence of contract type is desirable. Project complexity is related to both risk and resilience (Lehtiranta, 2011; Thomé et al., 2016; Mishra et al., 2016), which influence project performance. Therefore, we examined the relationships among complexity, risks, and performance.
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4.5. Measurement assessment Reliability and validity of the constructs were first evaluated by conducting several tests. We performed exploratory factor analysis. All items exhibited high loadings on the expected variables and low loadings on the other variables. Factor loadings of all items exceeded 0.7. Cronbach’s α and composite reliability of each variable were higher than 0.7. Average variance extracted (AVE)
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values were greater than 0.5. The above results, which are shown in Table 3, collectively indicate good internal consistency. Table 3 Reliability and validity of constructs.
Client capability risk
Project complexity
AVE 0.79
0.95
0.94
0.83
0.94
0.94
0.78
0.91
0.93
0.71
0.94
0.94
0.81
0.91
0.93
0.73
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Performance
Construct reliability 0.92
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Vendor capability risk
Cronbach’s α 0.91
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Outcome control
Measure PCT1 PCT2 PCT3 OCT1 OCT2 OCT3 OCT4 VCR1 VCR2 VCR3 VCR4 CCR1 CCR2 CCR3 CCR4 PCP1 PCP2 PCP3 PCP4 PFM1 PFM2 PFM3 PFM4
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Construct Process control
Factor Loading 0.84 0.93 0.89 0.86 0.97 0.82 0.98 0.87 0.91 0.90 0.85 0.83 0.86 0.85 0.83 0.86 0.93 0.90 0.90 0.88 0.85 0.83 0.85
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We also conducted confirmatory factor analysis with AMOS 17.0. The results indicate that χ2 = 509.29 (p = 0.000), df = 215, χ2/df = 2.37 (< 3.00), RMSEA = 0.077 (< 0.08), 90% confidence
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interval for RMSEA is (0.068, 0.085), p of close fit is 0.000, SRMR = 0.05, NFI = 0.90, TLI = 0.93, CFI = 0.94, and IFI = 0.94. Although the relatively small sample size may influence the measurement model, the fit indices were acceptable (Kenny et al., 2014). Thus, the data and the model exhibited a reasonable fit (Hulland et al., 1996). Finally, discriminant validity was examined. We compared χ2 difference between two models for each of the 15 pairs among six latent variables. The first model allowed the correlation between all variable pairs to vary freely, whereas the second model allowed the correlation to be 1.0. All 15
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pairs are significant (p < 0.001), thereby indicating good discriminant validity (Kroes and Ghosh, 2010). We also followed the procedure suggested by Fornell and Larcker (1981). The squared correlation between each pair of latent variables was lower than the AVE for each construct. This result provides additional evidence for good discriminant validity. 5. Results
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The descriptive statistics and correlations between each variable are presented in Table 4. The hypotheses were tested by conducting hierarchical regression analysis with ordinary least squares. SPSS 17.0 was used for descriptive and hierarchical regression analyses. Theorized variables were incorporated stepwise to examine the amount of variance that explained for the dependent variable. Additional evidence of the significance level can be obtained by calculating the incremental explained variance and the value of F hierarchical (Carte and Russell, 2003). Four models were
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formed, as shown in Table 5. The first model investigated the relationship between control variables and the dependent variable. The second model analyzed the main effect of independent variables on the dependent variable, in which H1 and H2 can be tested. Model 2 was also used as basis for testing H3. The third model added the moderators based on the second model. This model works as a basis of comparison with other models to compute the incremental explained variance and value
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of F hierarchical. The fourth model examined the effects of the interaction between moderators and independent variables. H4, H5, H6, and H7 can be tested with Model 4. We mean-centered each
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variable before the formation of interaction terms to avert potential multi-collinearity. The variance inflated factor scores were also computed in all models. The resulting values were all less than 2.1, thereby indicating that multi-collinearity is insignificant in this study.
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Table 4 Descriptive statistics and correlations.
Standard 1 2 3 4 deviation 1. Process control 5.43 0.95 1.00 2. Outcome control 5.10 0.98 0.65** 1.00 3. Vendor capability risk 4.08 1.23 0.06 0.04 1.00 4. Client capability risk 3.75 1.37 -0.02 -0.08 0.23** 1.00 5. Project complexity 4.46 1.31 0.11 0.19** -0.10 -0.05 6. Performance 4.59 0.96 0.42** 0.47** -0.12* -0.17** Two-tail t-test was performed. * Significant at α=0.05, ** Significant at α=0.01. Mean
5
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1.00 0.08
1.00
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Variable
Table 5 shows the explained construct variances and standardized path coefficients. By
comparing the changes in R2 between each two models, the values of F hierarchical were calculated and also shown in Table 5. Model 1 in Table 5 reveals that four control variables (i.e., business function, outsourcing arrangement, contract length, and project complexity) are insignificantly
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associated with performance. However, one control variable (i.e., contract type) significantly influences BPO performance. These results indicate that the performance of BPO projects is similar across different business functions, regardless of whether they are onshore or offshore. Moreover, BPO projects with long duration and high levels of complexity do not necessarily exhibit poor performance. Nevertheless, significant performance difference was found between BPO projects
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with time and materials and fixed-price contracts. Therefore, managers should carefully select the proper contract type to manage the outsourcing process. In addition, we examined the relationship of contract length with project complexity as well as the relationships of project complexity with client capability and vendor capability risks. The result shows that contract length is positively associated with project complexity (β = 0.19 and p < 0.01), which affects the two capability risks insignificantly (β = -0.05, p > 0.05; β = -0.10; p > 0.05). Thus, BPO projects of long duration
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exhibit high levels of complexity. Table 5 Hierarchical regression results.
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Model 3 Variable Model 1 Model 2 Model 4 Block 1: Control variable Business function 0.03 (0.03) 0.03 (0.02) -0.02 (0.02) -0.04 (0.02) Outsourcing arrangement -0.07 (0.13) -0.06 (0.11) -0.08 (0.11) -0.07 (0.10) Contract length 0.10 (0.03) 0.02 (0.02) -0.002 (0.02) -0.01 (0.02) Contract type 0.15* (0.12) 0.12* (0.11) 0.12* (0.11) 0.12* (0.11) Project complexity 0.07 (0.05) -0.003 (0.04) -0.01 (0.04) 0.03 (0.04) Block 2: Main effect Process control 0.20* (0.08) 0.22* (0.08) 0.18* (0.07) Outcome control 0.33*** (0.08) 0.31*** (0.07) 0.32*** (0.07) Vendor capability risk -0.15* (0.05) -0.15** (0.04) Client capability risk -0.11 (0.04) -0.07 (0.04) Block 3: Moderating effect Process control × Vendor capability risk 0.16* (0.06) Process control × Client capability risk -0.16* (0.06) Outcome control × Vendor capability risk -0.34*** (0.06) Outcome control × Client capability risk 0.23** (0.05) ΔR2 (Performance) 0.213 0.038 0.104 f2 (Effect size) 0.286 0.054 0.173 R2 (Performance) 0.043 0.256 0.294 0.398 F Hierarchical 64.702*** 12.057*** 38.007*** Number of observations (n) is 234. All path coefficients are standardized. The value in each parenthesis is the standard error. * p < 0.05; ** p < 0.01; *** p < 0.001.
Significant variances are explained for the dependent variable in model 2 (Table 5). The path
coefficients between all two independent variables and the dependent variable are significant. Process and outcome controls both influence outsourcing performance positively, thus supporting H1 and H2. The path coefficient between outcome control and performance is higher and more
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significant (β = 0.33; p< 0.001) than that between process control and performance (β = 0.20; p < 0.05). Thus, the effect of outcome control on performance is greater than that of process control. We also performed a t-test between the two path coefficients, as proposed by Cohen et al. (2003), to conduct statistical comparison of the two effects. The comparison was computed on the basis of the
1 R Y *(r ii r jj 2r ij ) n k 1 2
, where RY2 is the R2 of the dependent variable,
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j
following equation: t
rij are the factors of the inverted correlation metrics, k is the number of independent variable, n is the sample size, ßi is the path coefficient of independent variable i (i.e., outcome control in this study), and ßj is the path coefficient of independent variable j (i.e., process control in this study). The two-tail t-test result revealed that the effectiveness of outcome control was statistically higher
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than the effectiveness of behavior control (t=2.08). Therefore, H3 is supported.
Model 4 shows that vendor and client capability risks differentially and significantly moderate the effects of process and outcome controls on performance. The interaction term between vendor capability risk and process control is positive and significant, whereas the interaction term between client capability risk and process control is negative and significant. Therefore, the relationship
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between process control and performance is positively moderated by vendor capability risk but negatively moderated by client capability risk. Conversely, the interaction term between vendor
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capability risk and outcome control is negative and significant, whereas the interaction term between client capability risk and outcome control is positive and significant. Thus, the correlation between outcome control and performance is negatively moderated by vendor capability risk but
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positively moderated by client capability risk. The significance level of F hierarchical value further validates the significant moderating effects. Therefore, H4, H5, H6, and H7 are supported.
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The statement and result of each hypothesis are summarized in Table 6. Each hypothesis is supported.
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Table 6 Hypothesis testing results. Hypothesis H1 H2 H3 H4 H5 H6 H7
Path Process control → Performance Outcome control → Performance Outcome control → Performance > Process control → Performance Process control × Vendor capability risk → Performance Process control × Client capability risk → Performance Outcome control × Vendor capability risk → Performance Outcome control × Client capability risk → Performance
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Proposed effect Positive Positive Stronger Positive Negative Negative Positive
Result Support Support Support Support Support Support Support
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Both vendor and client capability risks moderate the effects of behavior and outcome control on performance differentially (H4–H7). Appendix A shows the two-way interaction graph for each of the four significant interaction effects (Aiken and West, 1991). In the presence of high vendor capability risk, high levels of process control yield high performance, whereas high levels of outcome control yield low performance. By contrast, high levels of process control result in low
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performance but high levels of outcome control result in high performance at high levels of client capability risk.
In each interaction graph, the highest performance can be obtained when process control is high and vendor capability risk is high or client capability risk is low. The highest performance can also be achieved when outcome control is high and vendor capability risk is low or client capability risk is high. Therefore, process control should be enhanced to achieve high performance in the
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presence of high vendor capability risk. In the presence of high client capability risk, outcome control should be enhanced to improve performance. Moreover, process control is recommended when the client has strong capability (low client capability risk) to facilitate high performance. Outcome control is recommended when the vendor has strong capability (low vendor capability risk)
6. Discussions and implications
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to facilitate high performance.
This research explored how vendor and client capability risks affected the effects of process
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and outcome controls on performance in BPO projects on the basis of risk- and control-based theories. We postulate that the correlation between each formal control mode and performance is moderated differentially by vendor and client capability risks. Empirical analysis of the dataset
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obtained from 234 BPO projects in China shows that the influence of outcome control on BPO project performance is greater than that of process control, although both formal control modes
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influence performance positively. Moreover, vendor and client capability risks play different and mixed roles in moderating the effects of process and outcome controls on performance. BPO performance is positively influenced by high levels of vendor capability risk and process control but
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is negatively affected by high levels of client capability risk and process control. By contrast, high levels of vendor capability risk and outcome control are associated with high performance, whereas high levels of client capability risk and outcome control are associated with low performance. The results of this study may not only contribute some novel knowledge to the BPO literature, but also provide some managerial implications for vendor-side and client-side managers in the effective enforcement of control and management of critical risks. 6.1. Theoretical implications
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First, our study may contribute to BPO literature by conducting an empirical investigation of the effects of process and outcome controls on performance. We provide solid evidence that process and outcome controls positively influence the performance of BPO projects. This result supports the previous argument that the enforcement of control effectively enhances performance and conforms to previous findings that process and outcome controls are positively associated with the
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performance of outsourced projects (Tiwana, 2008; Keil et al., 2013). Understanding both “what” and “how” goals of outsourced projects are accomplished is significant to outsourcing success. However, the simultaneous exercise of the two formal control modes is not required. The achievement of adequate control levels requires time, resources, and effort and transforms into “hidden costs” with outsourcing (Handley and Benton, 2013). Therefore, clients should also compare the cost and value associated with the applications of specific control modes to determine
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the appropriate control strategy.
Second, our research could contribute to control theory by highlighting the different attributes and effectiveness of process and outcome controls. Our findings reveal that the influence of outcome control on the performance of BPO projects is stronger than that of process control. Both formal control modes ensure predictability. However, process control is mechanistic and outcome
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control is flexible. Thus, outcome control can better balance emergence and predictability to provide satisfactory deliveries. The enforcement of process control is also more expensive than that
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of outcome control because process control requires high process observability of the client and frequent monitoring activities (Choudhury and Sabherwal, 2003; Tiwana and Keil, 2010). Although outcome control is more effective than process control, this condition does not mean that process
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control is unnecessary or insignificant in the management of outsourced projects. For example, clients rely heavily on process control in outsourcing professional service because frequent
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exchanges of information and processes are required in such types of outsourced projects (Stouthuysen et al., 2012). Third, our results indicate that either vendor or client capability risk plays a mixed role in
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moderating the relationship between process and outcome controls and performance in BPO projects. We present some new knowledge by demonstrating that capability risk related to vendors and clients serves as a two-edged sword with respect to control. In the presence of high vendor capability risk, the effect of process control on performance is high but the effectiveness of outcome control is low. Process control has low effectiveness in the presence of high client capability risk, whereas the effect of outcome control on performance is high. These observations contradict the general understanding in risk management literature that risk impairs project success (Mitra et al.,
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2016). The results support the existing argument that risks can be managed appropriately to produce high levels of operational performance (Liu, 2016; Aven, 2016). The current research also bridges an existing gap on whether the correlation between control and performance is negatively or positively moderated by risks (Tiwana and Keil, 2010; Harris et al., 2009). In addition, our findings address the existing gap resulting from same formal control mode being detected as either
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significantly or not significantly influencing performance in various studies (Tiwana, 2008; Tiwana and Keil, 2010). We find that each type of capability risk moderates the effects of process and outcome controls on performance differently.
Fourth, the results of the current research indicate that vendor and client capability risks exert opposing moderating effects on the correlation between each formal control mode and performance. This finding addresses the existing gap in previous studies that integrate risk and control but fail to
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distinguish the source of risk. The study also extends control literature by presenting empirical facts on the capability and knowledge of the controller and controlee to influence control effectiveness (Choudhury and Sabherwal, 2003). This observation supports the previous argument that the inputs from controllers and controlees generate different control results (Kirsch, 1997). Thus, before the enforcement of control, clients should not only evaluate the capability risk of vendors but also
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appraise their own capability risk. The occurrence of both high vendor and client capability risks should be avoided. Given that vendor capability risk decreases the effectiveness of outcome control
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and client capability risk diminishes the effectiveness of process control, formal control mechanisms cannot work effectively in such situations. 6.2. Managerial implications
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Our research has several important implications for practice. First, despite both process and outcome controls working effectively in reinforcing the performance of BPO projects, the inherent
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attributes of each formal control mode should be recognized. Outcome control is recommended in managing outsourced projects because such a control mode can balance the degree of emergence and regularity and is more effective than process control. Outcome control is particularly important
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in managing offshore outsourcing projects because it simplifies coordination processes and avoids considerable cultural conflicts. Although process control tends to be mechanistic, it can serve as an effective control portfolio by integrating other informal control modes, such as self-control (i.e., a mechanism that allows controlees to self-manage their tasks and achievements), which emphasizes emergence and autonomy. The enforcement of process control also requires frequent information exchange and communication between clients and vendors (Stouthuysen et al., 2012), thereby promoting mutual understanding and the development of long-term relationships (Ross et al., 2016).
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Second, client-side managers should discern the effective approach to exercise process and outcome controls in managing BPO projects when high vendor capability risk or client capability risk occurs. Clients with high capability risk should prioritize performing outcome control, whereas process control is suggested when high levels of vendor capability risk exist. However, when both vendor and client capability risks are present, the exercise of any formal control mode would not be
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effective in enhancing performance. In such situations, clients and vendors should either attempt to mitigate these two risks or change the practice of formal control mechanisms to alternative control mechanisms (e.g., informal control). Conversely, when both clients and vendors have high capability (i.e., low capability risk), the exercise of outcome control should be prioritized because the client can take full advantage of vendor capabilities while avoid high control costs. Process control can be modestly applied in the late stage of the outsourcing process.
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Clients should evaluate the capability risk of vendors and themselves regularly when they perform control because the capabilities of vendor or client may change during the outsourcing process. In such situations, the control strategy should also change accordingly. For example, vendor capability risk may be high at the beginning of outsourcing but largely decreases because of the accumulation of knowledge and experience. Thus, clients can implement process control first
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and outcome control at later stages. The control portfolio of process and outcome controls also enables clients to effectively manage multiple vendors with both high and low levels of capability
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risk. Client-side managers can perform process control effectively for those vendors with high capability risk, but exercise outcome control for vendors with low capability risk. Third, the miscellaneous moderating roles of vendor and capability risks give rise to the issues
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of treatment and management of such risks. Blindly minimizing vendor and client capability risks may produce additional unnecessary costs and unexpected results. On one hand, client executives
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should exploit the positive side of the two capability risks because of their capability to enforce process control with high vendor capability risk and to perform outcome control with high client capability risk. On the other hand, both client and vendor-side managers should design strategies to
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mitigate the negative aspects of vendor and client capability risks. Employees of either clients or vendors should receive adequate technical and business training to improve their capabilities. They can also adopt experienced managers to participate in the project (Liu and Wang, 2016). Clients and vendors should assist each other in addressing the challenge. Clients can offer knowledge-transfer training for vendors with high capability risk to enable vendors to gain an appropriate knowledge base to accomplish the project (Mehta and Mehta, 2009). Clients can also share their resources (e.g., human resource and personal management expertise) with vendors. Vendors can exchange
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employees with clients to enable each party to obtain new skills (Liu et al., 2010). 7. Limitations and directions for future research This research has three limitations in terms of theory, methodology, and geography. Theoretically, this study emphasized the roles of formal control mechanisms in managing BPO projects, but did not investigate the effectiveness of informal control mechanisms, which was not
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the focus of this research. Previous studies have suggested that informal control modes are weakly relied on and do not positively influence performance in outsourced projects because their practice requires extra significant formal controls (Chourhury and Sabherwal, 2003; Tiwana and Keil, 2010). Therefore, the inclusion of informal control mechanisms in this study may not be appropriate and necessary. However, future research can still examine the interactive effects between informal control mechanisms and capability risks because vendor and client capability risks may also
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enhance the effectiveness of informal control.
Methodologically, our measure of performance is based on subjective scales (i.e., satisfaction). The employment of objective scales appears to be more reliable than the application of subjective measures because social desirability concerns can be reduced considerably. Future research can use objective data associated with time, budget and quality of the accomplishment to reflect
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performance. Moreover, the sample size is relatively small for structural equation modelling, which may affect the fit of the model to the data. Future research can use a larger sample size to further
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validate our model.
Geographically, our study was performed in China, and that our results can be directly applied to other countries is not guaranteed. Different countries possess varied institutional and business
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culture contexts that might influence the decision-making of managers in performing control and their perceptions on vendor and client capability risks. Future research can extend our model to
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other cultural settings and introduce country-level elements, such as social value and legal environment, into the analysis to gain a more comprehensive understanding. The findings also provide four possible directions for future research. First, given that the
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control–performance relationship is differentially changed by vendor and client capability risks, the moderating effects of other risks derived from clients and vendors (e.g., client’s lack of cooperation and vendor’s lack of responsibility) are worth exploring. Second, this study focuses on the overall satisfaction of selected outsourced projects. The inclusion of the social aspect of performance (e.g., client-vendor long term relationship) in our model would be interesting because the influence of formal control mechanisms on social performance is still poorly understood. Third, the control relationship that we examined was between client and vendor. Future studies can apply our model
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into other control relationships in outsourcing (e.g., vendor-side project manager and employees) and investigate whether similar results can be obtained. Finally, formal control mechanisms and their corresponding effectiveness in managing multiple vendors can be studied. Given that both high and low levels of capability risks may be involved in different vendors, examinations of control effectiveness in such situations would be interesting.
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8. Conclusions
This study is one of the few attempts to investigate the interplay of risk and control and contributes to literature by indicating that vendor and client capability risks differentially moderate the effects of process and outcome controls on the performance of BPO projects. One significant finding of our study is that outcome control is more effective than process control in the context of outsourcing, although both formal control modes positively affect the performance of BPO projects.
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These results suggest that different formal control modes have various attributes and generate different levels of performance. Another important contribution may be the miscellaneous roles of vendor and client capability risks in moderating the correlation between control and performance. Under high vendor capability risk, process control has a significant effect on performance but the effectiveness of outcome control is low. By contrast, high client capability risk results in low
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effectiveness of process control but high effectiveness of outcome control. These results indicate that either vendor or client capability risk works as a double-edged sword with regard to control.
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The findings also highlight the significant difference between vendor and client capability risks in their moderating roles. Therefore, the risky situation of both vendors and clients should be
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Appendix A. Interaction graphs
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All constructs are mean-centered and there is no constant. Low vendor or client capability risk is one standard deviation below the mean and high vendor or client capability risk is one standard deviation above the mean.
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