The contribution of resource interdependence to IT program performance: A social interdependence perspective

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International Journal of Project Management 29 (2011) 313 – 324 www.elsevier.com/locate/ijproman

The contribution of resource interdependence to IT program performance: A social interdependence perspective Neeraj Parolia a,⁎, James J. Jiang b , Gary Klein c,1 , Tsong Shin Sheu d a

eBusiness and Technology Management Department, Towson University, 8000 York Road, Towson, MD 21252, United States Research School of Business, ANU College of Business and Economics, The Australian National University, Canberra ACT 0200 Australia c College of Business and Administration, University of Colorado at Colorado Springs, P.O. Box 7150, Colorado Springs, CO 80933-7150, United States Department of Industrial Engineering and Management, Nan Kai Institute of Technology, 568, Chung Cheng Road, Tsao Tun, 542, Nan Tou County, Taiwan b

d

Received 1 July 2009; received in revised form 6 March 2010; accepted 11 March 2010

Abstract Combinations of multiple, related projects into interdependent programs are becoming common in the field of information technology. However, little work exists to study the impact of interdependence in the program environment to achieve collective success. Social interdependence theory provides a structure to examine whether collaborative efforts promote behaviors that result in higher levels of success. Using resource interdependence as an indicator of collaboration, a model of promotive behaviors is developed using the lens of social interdependence. Expectations are that resource interdependence conditions will promote more mutual support, effort, and communication. In turn, these behaviors will lead to an improvement in the business objectives and operational efficiency of the organization. A survey of program and project managers in information system vendors located in India support the model. The results provide support for the argument that programs are effective organization structures that capitalize on interdependencies and that the social interdependence theory provides a consistent model to explain the benefits of resource interdependence. © 2010 Elsevier Ltd. and IPMA. All rights reserved. Keywords: Program management; Operational effectiveness; Business objectives; Resource interdependence; Promotive interaction; Program performance

1. Introduction Programs are resource consuming organizational capabilities that have a common purpose and are typically organized as a collection of individual projects that define specific work to be accomplished (Cleland and Ireland, 2006). Program performance is related to both the completion of the individual components as well as the impact achievement of the overall purpose (Wideman, 2004). Common information system development (ISD) programs include infrastructure development segmented into components, user support for different applications, application development of ⁎ Corresponding author. E-mail addresses: [email protected] (N. Parolia), [email protected] (J.J. Jiang), [email protected] (G. Klein), [email protected] (T.S. Sheu). 1 Tel.: +1 719 255 3157.

complex systems, and management of a software product line for multiple clients (Schwalbe, 2007). Programs by their nature are very complex due to the requirement of managing inter-related projects with multiple managers in resource limited environment (Wideman, 2004). The presence of interdependencies can have beneficial or detrimental effects on the completion of a program. Interdependencies between projects can lead to different perceptions of the same situation, goal incongruence, or asymmetry of information, resulting in rework and emergence of crises and supplemental development costs due to delays (Kazanjian et al., 2000; Loch and Terwiesch, 1998).According to social interdependence theory, a team can work together cooperatively to accomplish shared goals or competitively to achieve a goal that only one or a few can attain (Johnson and Johnson, 1998). From the cooperation perspective, past literature has identified interdependence as a critical indicator of collaboration, expertise sharing, and innovation (Johnson and

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Johnson, 2005). Resource interdependence is commonly prevalent in Information system development program teams (Hendel et al., 2008). The role of resource interdependence in generating the cooperative effects suggested by social interdependence theory has not been the subject of study in the information technology program and project management literature. With these issues in mind, we consider whether the collaborative needs of resource interdependence can establish the promotive behaviors of social interdependence theory to promote program success. To this end, we develop a model of program success fostered by the presence of resource interdependence. Characteristics of collaborative social interdependence models serve as mediators to determine if ISD program success, as measured by planned performance of the combined projects and common business objectives, can be increased with the presence of resource interdependence. A survey of 92 program teams with 38 ISD vendor companies in India indicates the model holds, demonstrating that collaboration emanating due to resource interdependence promotes desired promotive interactions that can lead to success. 2. Background of programs For years, programs and projects were synonymous for many organizations. This view may have been justified since many of the management tools and techniques were the same, though the level of complexity was certainly different (Wideman, 2004). However, as projects became more ingrained in achieving the mission of organizations, grouping structures were applied to describe and control multiple projects. Related projects were grouped to be called programs, which were executed over a period of time in order to accomplish broader goals. Formally, a program is a structured grouping of interdependent projects that includes the full scope of business, process, people, technology and organizational activities that are required (both necessary and sufficient) to achieve a clearly specified business outcome (ITGI, 2007). The program life cycle comprises of formulation, organization, deployment, appraisal and dissolution phases (Thiry, 2004). Programs provide a bridge between projects and the organization's strategy (Pellegrinelli, 2002; Pellegrinelli and Bowman, 1994), take an open system view and seek change in permanent organizations (Artto et al., 2009). 2.1. Program management Program management has evolved a core set of actions, structural arrangements and approaches, which are distinct from project management, and address conceptually different issues (Pellegrinelli, 1997). Some empirical studies have developed program typologies, context typologies, and program typespecific management practices (Artto et al., 2009). Program typologies deal with the number of projects and locations (Evaristo and van Fenema, 1999), degree of change and extent to which projects exist at the time of program launch (Vereecke et al., 2003), strength of coordination (Gray, 1997) relation of strategy and projects in the program (Pellegrinelli, 1997, 2002), and scope in terms of functions involved and extent of change

(Levene and Braganza, 1996). Also, programs vary in terms of size and resource type, i.e. whether the projects included in the program have clearly stated goals and methods (Payne and Turner, 1999; Pellegrinelli et al., 2007). Program goals can be classified under business goals, efficiency goals, and effectiveness goals (Lycett et al., 2004). Business goals include coherent communication, improved project definition, alignment with business goals and strategy. Effectiveness and efficiency goals include improved coordination, improved dependency management, effective resource utilization, effective knowledge transfer and greater senior management visibility (Lycett et al., 2004). 2.2. Information technology programs Information technology (IT) companies, including software development organizations, are increasingly using program management to manage complex projects (Gierra, 2004). In the IT context, program management is used in software and application development (Caudill, 1977; Leveson and Weiss, 2004; Mäntyniemi et al., 2004), ERP implementation (Ribbers and Schoo, 2002) and IT infrastructure management (AlMashari and Zairi, 2000). For technology product and service companies, greater program and project management capabilities are required to address competence risks, especially when they become custom solution providers for their clients (Sawhney, 2004). Programs are common among IT outsourcing vendors and include application development, support, and implementation (Iyengar, 2003). An IT vendor's role has transformed from a service provider to one of strategic partner (Lindner, 2004). As such, a vendor's program management capability is responsible for the improvement of its three competencies: relationship, delivery, and transformation (Feeny et al., 2005). Outsourcing contract sizes can include hundreds of projects and sometimes run into billions of dollars (Kedia and Lahiri, 2007). Vendors no longer have to simply manage projects but manage long term relationships spanning numerous years (Mehta et al., 2006). It is important for vendors to begin planning any outsourcing initiative by facilitating a strong program management process (Mohan Babu, 2006). Lack of program management skills among IT vendors was often stated as a problem by clients (Epner, 2001). Determinants of program success and failure have varied, but often reflect the operational aspects of multiple project completion and achievement of defined business objectives. Kaufman (1992) mentions findings of case studies on process improvement, where important factors determining success in managing operational improvement programs include a non-authoritarian management style with participative management efforts, and aligning individuals' incentives with the program's goals. Top management support is critical at both the project and program level and higher level structures of rewards and management systems promote collaboration (Sharma and Yetton, 2003; Young and Jordan, 2008). Ribbers and Schoo (2002) report the following success factors in case of ERP implementation programs; 1) comprehensive program organizational role structures, 2) flexible budget policy, 3) alignment of number of parallel implementation of projects to the level of variety of program environment, and 4)

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alignment of implementation process to the degree of integration complexity. Program manager competencies and skills have been highlighted as a crucial factor in program success (Partington et al., 2005; Pellegrinelli, 2002). Shehu and Akintoye (2010) addressed the following challenges to successful implementation of program management; lack of strategy focus, cross functional working, communication, financial factors, leadership, commitment, and understanding. Little literature exists in any field to determine whether performance at the program level is affected by efforts common at the project level. It is merely assumed that the interdependent nature among projects within a program will achieve the desire levels of coordination and cooperation among projects (Wideman, 2004). Performance criteria used in programs in various industries consider aspects of both the business objectives associated with a program and the effective performance of the program itself. The business objectives of the program must be clearly established to provide expectations regarding benefits and to establish the goals sought during program execution. Business objectives may include items as overall sales impact, profitability, market performance, and success of new products (Cooper and Kleinschmidt, 1996). Effectiveness of the program is oriented toward local measures that may include project performance, product quality, time and cost. and process effectiveness (Dougherty, 1992; Pinto and Pinto, 1990). 2.3. Interdependence Program management takes into account the interconnectedness of various project objectives in order to maximize the accomplishment of combined project outcomes (Blomquist and Müller, 2004). This focus produces the view of programs as groups of projects, managed together to obtain benefits not available from managing projects individually (Maylor, 2003; PMI, 2004). Programs are organized into a core team structure and a set of individual project teams to certify that decision making and authority has a definitive source (program manager), the work of program manager is efficient, and the needs for direction and decisions are assured. Program teams comprise of program manager, constituent project managers and functional experts. The program manager is the head of the program and oversees the delivery of the business objectives and adherence to the practices (Brown, 2007). The objectives of projects within the same program are interdependent (Platje et al., 1994). Interdependence is a critical factor in the assessment of performance in teams (Guzzo and Shea, 1992; Mathieu et al., 2008). Just as in teams, programs are managed in an environment of multiple interdependencies: resource, project and goal (Engwall and Jerbrant, 2003; Lycett et al., 2004). Resource interdependence exists when each member has only a portion of the information, resources, or materials necessary for the task to be completed and members' resources have to be combined in order for the group to achieve its goal (Johnson and Johnson, 1995). Project interdependence reflects the extent to which one's project assignments require working with other groups in the organization (Katz, 1982). Goal interdependence is defined as the extent to which an individual team member believes that his or her goals can be achieved only

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when the goals of other team members are also met (Weldon and Weingart, 1993). The effective management of programs requires effective resource allocation among many projects to achieve efficient operations and achievement of the business strategies and objectives as implemented through a collection of projects (Wideman, 2004). These interdependencies between the projects result from shared attributes such as common client, potential similarity in technologies and platforms utilized, product architecture, resource sharing and common outcomes (Gerwin and Moffat, 1997a,b). Kozlowski and Bell (2003) stated that research that fails to consider interdependence has little value in developing knowledge about organizational teams. Mattessich and Monsey (1992) ascertained behaviors and attitudes that characterize interdependence as a component of collaborative practice. These include participants' thinking that they have more to gain than lose by collaboration and an ongoing flow of communication among colleagues. Soler and Shauffer (1993) also contend that interdependence is a component of collaborative efforts. A related support for collaboration is rooted in the belief that interdependence on others for certain tasks and resources allows collaborators to spend their time doing what each knows and does best (Abramson and Rosenthal, 1995). Kagan and Neville (1993) articulated how individual people and programs linked together have the opportunity to create that which they cannot create when acting independently. The cooperative interdependence enabled individual team members to exploit the benefits of diverse values, skills, and perspectives in diverse groups at work (Van der Vegt and Janssen, 2003). 2.4. Social interdependence theory Since Deutsch (1949) introduced the basic theory of cooperation and competition, social interdependence theory has evolved and provided a conceptual structure to understand cooperation in groups. The theory has been primarily applied in the context of education (student learning) and business (power, conflict, goal attainment). Different types of social interdependence that exist among group members include resource, expertise, goal and reward interdependence. When interdependence exists, such as in program teams, group members can take action in ways that relate to the actions of others (Johnson and Johnson, 1998). Social interdependence may be discerned from social dependence (i.e., the outcomes of one person are affected by the actions of a second person but not vice versa) and social independence (i.e., individuals' outcomes are unaffected by each other's actions). There are two types of social interdependence: cooperative and competitive. The basic presumption of social interdependence theory is that the type of interdependence structured in a situation determines how individuals interact with each other, which, in turn, determines results. When approached positively, interdependence tends to result in promotive interaction; while in a negative approach interdependence tends to result in oppositional interaction; and no interdependence results in an absence of interaction. Promotive interaction is the result of positive interdependence from a collaborative environment and is considered to be

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composed of three broad elements: effort to achieve, such as effort of the individual members to achieve a higher performance level; positive interpersonal relationships, such as mutual support realized in productive group relationships; and social competence, such as an ability to effectively communicate within the group. Promotive interaction is considered vital in building positive and supportive relationships among the diverse parties (Johnson and Johnson, 1998). The elements of promotive interaction have been related to a wide variety of dependent variables that measure success in their respective contexts (Johnson and Johnson, 2005). Resource sharing in program teams is implemented to exploit the synergy between client projects and complimentary resources (Hendel et al., 2008) and would also be done to fulfill any high-pressure situations and manage risk (Banerjee, 2005). Typically, program teams have high level of resource interdependence because they must share their resources to accomplish their individual project goals. Program members with high resource interdependence must work together in order to accomplish their individual project and overall program goals. Hence, resource interdependence encourages an increase in promotive behaviors to achieve these goals. Each of the promotive behaviors should, in turn, improve program performance. It is widely agreed in the literature that the flow of communication within teams influences the success of innovative projects (Griffin and Hauser, 1992). It is acknowledged in the literature that team support will improve team performance (Bishop et al., 2000; West, 2004). The effort that team members exert on their common tasks influences the success of a project (Hackman, 1987). Whether these behaviors also improve program performance, as measured by business objectives and operational effectiveness will be tested in the subsequent development of the model and hypotheses. The chain of relationships suggested by the literature provides the basis for our research model, shown in Fig. 1.

2.5. Hypotheses Positive interdependence (such as resource interdependence) promotes a situation in which participants work together in small groups to maximize the learning of all participants by sharing their resources to provide mutual support and encouragement and to celebrate their joint success (Ransley and Rogers, 1994). When group members must work together in resource interdependent situation to obtain access to important resources, this increases the amount of interaction which group members have to each other and each others' views: group members indulge in communication behaviors such as soliciting and negotiating for needed resources. These behaviors force group members to interact at a higher level than if each individual was self-sufficient in resources (Fan and Gruenfeld, 1998). Distinct insights can emerge in groups when members recognize multiple viewpoints and are able to conceptually integrate them to gain a better understanding of the situation (Gruenfeld, 1995; Nemeth, 1986). Interdependence increases beneficial tendencies such as information exchange (Johnson, 1973), helping (Spilerman, 1971) through a higher rate of task driven interactions among members, and more effective and creative problem solving (Maier, 1970). In a study conducted by Fan and Gruenfeld (1998), high resource interdependence conditions led to faster solutions which became a catalyst for collective cognition, starting into motion interactions and synergies that would not otherwise have taken place and that were beneficial for both problem solving and solution application. Without a mandate to interact, low resource interdependent teams were apparently less likely to process information collectively, and their performance suffered as a result (Fan and Gruenfeld, 1998). Additional research on resource interdependence demonstrates that when student learners are allocated only part of the resources necessary to achieve specific goals, effective information transmission, and

Fig. 1. Research model.

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positive interaction and cooperation is favored and performance enhanced (Buchs et al., 2004). .Hence we believe that,

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H2. Resource interdependence in the program team will positively improve effort expended by the program team members.

implementation failures (Enns and McFarlin, 2003). Team support has been empirically associated with an improvement in team performance (Bishop et al., 2000; Drach-Zahavy and Somech, 2001). Previous research demonstrated that behavior such as sharing ideas and information (Durham et al., 1997; Janz et al., 1997), providing instrumental assistance (Janz et al., 1997), and emotionally supporting each other (Bishop et al., 2000) raised team performance.

H3. Resource interdependence in the program team will positively improve mutual support among program members.

H7. Program members' support in the program will positively improve the operational effectiveness of the program.

The importance of communication for the successful implementation of programs and across different business functions and departments is also well documented (Cline, 2000). Substantial academic research directed on new product success emphasizes the need for efficient communication among departments, particularly between R & D and marketing (Song and Parry, 1997). In the context of IT project management, communication is the binding factor that ‘keeps everything working properly’ (Schwalbe, 2007). Fricke et al. (2000) observed that management support in the form of communication is one of the key program success factors. This support can be seen in terms of implementing the reasonable amount of projects, allocating resources suitably, setting clear goals and project priority, and assigning project manager properly. Hence,

The relationships from communication to operational effectiveness and mutual support to business objectives were not included because we did not find any explicit support in the literature. As a secondary measure, we tested these links and they were not significant.

H1. Resource interdependence in the program team will positively improve communication among program members.

H4. Communication among program members will positively improve the achievement of business objectives. Team effort has long been considered important in new product development programs (Cooper and Kleinschmidt, 1993; de Brentani, 1995; de Brentani and Cooper, 1992). The individual and collective effort that members put forth on their assignment is critical to success of cross functional teams (Trent, 1998). The difference between successful and unsuccessful project performances can be attributed to the effectiveness of the project team in terms of its team effort (Crawford, 2002). This proposition reflects the fundamental assumption that, independent of other factors such as task-relevant knowledge and skills, the level of effort brought to bear on a task influences performance (Hoegl and Gemuenden, 2001). In a study conducted by Weingart (1992), results from data of 56 student groups indicate that effort, among other variables such as planning and coordinating of tasks, has a significant influence on team performance. Hence, H5. Program members' effort will positively improve the achievement of business objectives. H6. Program members' effort in the program will positively improve the operational effectiveness of the program. Past research has shown that when implementing decisions, the support of executive peers is highly desirable (Korsgaard et al., 1995). At the executive level, the lack of peer support on key issues may lead to decision paralysis, missed opportunities, or

3. Research methodology The methodological approach will be to develop an instrument to measure the promotive interactions, resource interdependence, and both measures of program success. The instruments are applied to a sample of program and project managers to avoid single respondent biases. Analysis of the measurement and structural models is conducted with partial least squares regression. 3.1. Sample IT outsourcing vendors are project based organizations (Kodama, 2007; Tanaka, 2003) which deliver an array of IT services and products to their clients through projects. These projects integrate people with different competencies, backgrounds and experience in order to develop complex, and often innovative solutions (Prencipe and Tell, 2001; Sydow et al., 2004). Project-based organizations represent a new organizing logic with flat organizational hierarchies and emphasize interconnectedness of different units (Powell, 1990). Such IT vendors are increasingly implementing inter-related client projects in the form of programs. From an organizational perspective, programs represent mechanisms that are increasingly used to develop and implement strategic organizational changes, too complex or vague in their objectives to fit into the traditional project management frame (Dietrich, 2006). The implementation of strategic initiatives (Pellegrinelli and Bowman, 1994), the development of organizational capabilities (Pellegrinelli, 1997), and the implementation of complex information systems (Ribbers and Schoo, 2002) are examples of organizational changes introduced by programs (Pellegrinelli et al., 2007). Programs serve as temporary structures that link individual projects to a particular organizational goal (Lycett et al., 2004). To empirically validate our hypotheses, we collected data from 38 IT outsourcing vendors located in India. 50 vendors were randomly selected from the database of National Association of Software and Service Companies (NASSCOM), which is India's premier trade body and the chamber of

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commerce of the IT software and services industry to identify individuals working in program manager roles in the organization. 36 vendors agreed to provide access. Two respondents participated (out of ten contacted) who were located through a position related keyword search on social networking websites. The companies were primarily involved in conducting business in IT software, IT services, Internet, e-commerce, or IT enabled services. The vendors have proficiency in information systems development and maintenance of complex systems for their clients. Most of the vendors have headquarters in India, while a few have offshore development centers in India. The vendors have adopted program and project management practices and have been assessed at Capability Maturity Model (CMM) level 5, which assures that data within an organization is based on consistent processes. The 38 organizations identified 92 IT outsourcing programs within their organizations. For each program, questions were asked of a matching set of a program manager and a project manager to avoid common method bias. Responses were obtained by personally handing a questionnaire to the respondent and via personal and phone interviews consisting of questions from the questionnaire. After the collection of responses from the program manager, we asked the program manager to identify a project manager/leader managing a key project in the program. The project managers were later interviewed to obtain their responses. Demographic information is shown in Table 1. Overall, the pool of respondents and firms was well qualified to judge the issues related to resource interdependence and program performance. In particular, program managers are typically responsible for aligning programs and projects with business goals and objectives and analyzing and evaluating the overall performance of the program, making them good subjects to evaluate the business performance of a program (Iyengar, 2003).

Table 1 Demographics. Variables

Categories

Gender

For program manager Male Female For project managers Male Female For program managers Program managers Account managers Delivery managers Program director Senior manager Technical director For project managers Project managers Project leader N50,000 25,001–50,000 10,001–25,000 1000–10,000 b1000 b=7 8–15 16–25 N=26 Missing Up to1 year From 1 up to 2 years From 2 up to 3 years From 3 up to 5 years N5 years Missing b=7 8–15 16–25 N=26 Missing

Job position

# of employees

Average program team size

Program duration

No. of projects in the program

#

%

90 2

97.82 2.17

87 5

94.56 5.43

47 39 1 1 2 2

51.08 42.39 1.08 1.08 2.17 2.17

82 8 6 2 4 16 10 68 15 2 4 3 1 54 18 11 6 2 60 21 2 7 2

89.13 10.86 6.52 2.17 4.34 17.39 10.86 73.91 16.30 2.17 4.34 3.26 1.08 58.69 19.56 11.95 6.52 2.17 65.21 22.82 2.17 7.60 2.17

3.2. Instrument development The questionnaires consisted of items measured on a 5-point Likert-scale ranging from ‘totally disagree’ to ‘totally agree’. Negatively worded items were reverse-scaled. The items for each construct below are presented in Appendix A. Resource interdependence — in the scale for resource interdependence, items were adopted and modified from (Brown et al., 1998) to measure the interdependence of human and non-human resources such as technical expertise, administrative staff, facilities, project data and business process information. The original scale was used in the context of geographical information systems. Couples of items were replaced with resources in the context of program management. This scale had four items and respondents were asked to identify the extent of sharing of the resource among the project teams. Communication — project managers' perception of exchange of information among team members was assessed by items adapted from Hoegl and Gemuenden (2001). These items capture the quality of communication within a team in terms of the frequency, formalization, structure, and openness of the information exchange.

Effort — project managers' perception of workload sharing and prioritizing of the team's task over other obligations was assessed by four items adapted from Hoegl and Gemuenden (2001). Mutual support — project managers' perception of display of mutual respect, granting of assistance when required, and development of other team members' ideas and contributions was assessed by five items adapted from Hoegl and Gemuenden (2001) . Program performance — since there were no known measures of program performance from the vendor perspective in the context of IT programs, we modified the scale for this construct from new product development (NPD) programs. To differentiate between successful and unsuccessful programs, it was essential to first define “performance” in this context. Performance of a NPD program pertains to operational effectiveness (Chen et al., 2006; Kerssens-van Drongelen and de Weerd-Nederhof, 1999); and the realization of business objectives (Chen et al., 2006). These items were asked of the program managers.

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Control variables — several factors which might affect the formation of promotive interaction and performance parameters are controlled to purify the real effect caused by the independent variables. Program complexity (number of projects in the program), program duration and program team size are included as control variables. These controls were solicited from the program managers.

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Table 2 PLS factor loading and reliability. Factors Resource Interdependence Administrative personnel Data Technical expertise Process information

Factor loading

Composite reliability

Cronbach's alpha

0.70 0.69 0.79 0.72

0.82

0.73

0.81

0.88

0.83

0.87

0.83

0.84

0.73

0.84

0.75

0.86

0.79

3.3. PLS analysis Structured Equation Modeling (SEM) with Partial Least Squares (PLS) analysis allows empirical assessment of the measurement model used in this study (Chin, 1998). PLS is selected since it is not contingent upon data having multivariate normal distributions. Additionally, unlike LISREL which only supports reflective relationships, PLS supports both types of relationships: formative and reflective. The program performance evaluation items examined in this study are formative. Latent variables attached to formative measures are the summation of the formative observed variables associated with them (Campbell, 1960). These observed variables are not assumed to be correlated with each other or to represent the same underlying dimension (Chin, 1998). Using ordinary least squares as its estimation technique PLS performs an iterative set of factor analysis and PLS applies a bootstrap approach to estimate the significance (t-values) of the paths. In this study, PLS-Graph Version 3.01 (Chin, 1994) was used to verify the measurement and test hypotheses. In addition, PLS is a latent structural equation modeling technique that uses a componentbased approach to estimation that involves two steps. The first step is to examine the measurement model and the second step is to assess the structural model. 3.4. Measurement model Item reliability, convergent validity, and discriminant validity tests are often used to examine the measurement model in PLS. Individual item reliability can be examined by observing the factor loading of each item. A high loading implies that the shared variance between constructs and its measurement is higher than error variance (Hulland, 1999). Factor loading higher than 0.7 can be viewed as high reliability and factor loading less than 0.5 should be dropped. In Table 2, the loading of all indicators are significant at p b 0.05. Convergent validity should be assured when multiple indicators are used to measure one construct. It can be examined by reliability of questions, composite reliability of constructs, and variance extracted by constructs (AVE) (Fornell and Larcker, 1981; Kerlinger, 1986). All of these values are in Table 2. Construct reliability can be assessed with Cronbach's alpha. The Cronbach alpha of each construct was above 0.7 which indicates high internal consistency (Nunnally, 1978). To obtain composite reliability of constructs, the sum of loadings should be squared and then divided by the combination of the sum of squared loading and the sum of the error terms (Werts et al., 1974). Composite reliability of each construct was above 0.7 which is acceptable (Chin et al., 2003). AVE, in Table 2,

Support Helped and supported each other as best as they could Conflicts were easily and quickly resolved Discussions were conducted constructively Suggestions were discussed and further developed Able to each consensus regarding important issues Communication Frequent communication within the program Communicated spontaneously Project-relevant information was shared openly Conflicts regarding openness of information flow Happy with the timeliness in receiving information Happy with the precision in receiving information Happy with the usefulness in receiving information Effort Fully pushed the program Made the program their highest priority Program members put much effort into the program Conflicts regarding the effort put into the program Operational effectiveness The program was completed within budget No gridlock in the program — all the projects done on time Provided all the functionality it was supposed to provide Provided the quality service it was supposed to provide Business objectives The program was able to meet expected goals The program was able to provide expected benefits Able to meet organizational expectations The program was aligned with the business's strategy

0.75 0.83 0.76 0.71

0.77 0.78 0.51 0.65 0.73 0.69 0.78

0.82 0.81 0.86 0.51

0.87 0.59 0.77 0.78

0.84 0.66 0.79 0.83

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reflects the variance captured by indicators (Fornell and Larcker, 1981). If the AVE is less than 0.5, it means that the variance captured by the construct is less than the measurement error and the validity of a single indicator and construct is questionable (Fornell and Larcker, 1981). Discriminant validity focuses on testing whether the measures of constructs are different from each other (Messick, 1980). It can be assessed by testing whether the correlation between pairs of construct are below the threshold value of 0.90 (Bagozzi et al., 1991) and whether the square root of AVE is larger than correlation coefficients (Chin, 1998; Fornell and Larcker, 1981). Bivariate correlation can be calculated as the Pearson correlation coefficient. These are shown in Table 3. Another way to determine discriminant validity is to verify the factor loading of indicators (Chin, 1998). To have discriminant validity, indicators should have higher loading in the construct of interest than other constructs. Because PLS graph (Chin, 1994) only provides factor loading on one construct, procedures suggested by Smith et al. (2001) were used to generate crossloading values. Examination of cross-loadings indicated no problems. 3.5. Direct model Basic information about each variable is given in Table 3, including means, standard deviation, skewness, and kurtosis. For each variable the skewness was less than 2 and the kurtosis less than 5, indicating no significant violation of normal distribution (Ghiselli et al., 1981). The test of the structural model includes estimating the path coefficients, which indicate the strengths of the relationships between the dependent and independent variables, and the R2 value, which indicates the amount of variance explained by the independent variables. R2 represents the predictive power of the model and interprets the same as a multiple regression. A bootstrap resampling procedure was used to generate t-statistics and standard errors (Chin, 1998). The bootstrap procedure utilizes a confidence estimation procedure other than the normal approximation. In this study, resamples of 100 are chosen. The power of each test exceeded 0.80. Fig. 2 shows the results of the structural analysis. Significant relationships are shown with a solid line and insignificant relationships with a dashed line. All hypotheses were supported

except H2. The result suggests that resource interdependence plays an important role in increasing promotive interaction behaviors. The insignificant result of H2 may indicate that a larger role is played by other kinds of interdependence, such as reward interdependence, in explaining the effort put forth by members in the program. The control variables; team size, program size and duration were included as input to both dependent variables (shown grouped in Fig. 2 by a dashed box). None of the control variables showed to be significant to either dependent variable. In order to further explore the data set, we examined the direct effect of resource interdependence on both program outcome variables; no significant effect was found for either direct effect. From these results we can conclude that the promotive interaction variables fully mediate the effects of resource interdependence on the two dimensions of program performance. 4. Conclusions Programs serve as temporary structures that link individual projects to a particular organizational goal (Lycett et al., 2004). It is believed that through coordinating individual deliveries produced by projects, programs are able to leverage the real business benefits beyond the direct outcomes (Lycett et al., 2004; Maylor et al., 2006). By nature, the projects within the same program are interdependent (Platje et al., 1994). These interdependencies between the projects comprising a program result from shared attributes and shared resources (Gerwin and Moffat, 1997a,b). Given the importance and popularity of information system projects, it is crucial to examine the impact of mechanisms designed to promote improved performance. Based upon social interdependence theory, we proposed that active resource interdependency among projects will facilitate promotive interaction behaviors and lead to improved program performance. The promotive interaction behaviors examined include mutual support, communication, and effort (Johnson and Johnson, 1998). The program performance was measured as business objectives and operational effectiveness. Furthermore, given the potential conflicts among projects as evidenced in the ISD literature, resource sharing serves as an active interdependency device to facilitate the promotive interaction behaviors among project team members within a program. Based upon a survey of 92 programs of ISD vendors in India,

Table 3 Basic information and correlation table. Basic information

1 RESINT 2 SUPPORT 3 COMM 4 EFFORT 5 OP EFFEC 6 BUS OBJ

Correlation matrix Mean

Std. dev.

M3

M4

1

2

3

4

5

6

3.63 3.85 3.72 3.59 3.94 4.12

0.82 0.61 0.64 0.70 0.58 0.57

−0.38 −0.51 −1.13 −0.18 −0.79 −0.31

−0.43 0.93 2.89 0.07 1.04 −0.44

0.73 0.33 0.34 0.22 0.24 0.61

0.78 0.70 0.47 0.58 0.38

0.71 0.58 0.50 0.47

0.77 0.49 0.49

0.76 0.61

0.79

M3: skewness; M4: kurtosis. The diagonal line of correlation matrix (in bold) presents the square root of AVE.

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Fig. 2. Data analysis results.

the results supported our proposed hypotheses that resource interdependence was observed to enhance the levels of communication, effort, and mutual support among program members. As suggested by social interdependency theory, the promotive interaction behaviors were positively associated with final program performance. These results indicate that a critical factor of influence of the levels of ISD program performance is the level of promotive interaction behavior among program team members. There are several implications of this study for ISD researchers. First, this study is the first empirical evidence to document the effect of program management practice. The results indicate that program performance is at least partly determined by promotive interaction behaviors. In other words, the result of this study has strongly encouraged ISD researchers to further examine various management interventions for effective program management. The result of this study acknowledged the need for structuration of interdependence as an intervention to promote collaborative behaviors. Based upon social interdependence theory, promotive interaction behaviors will be observed as the outcomes of active resource interdependence, the result of this study found a positive relationship between promotive interaction behaviors and final program performance. Future studies attempting to examine the effectiveness of program performance should consider the nature of interdependence among projects. This study also provides further empirical evidence of the relationship between promotive interaction behaviors and performance. To our best knowledge, it is the first evidence to exhibit the effects of promotive interaction behaviors and ISD program performance. This result suggests that future studies may need to examine other types of behaviors and their impacts on final program outcomes. Finally, this study also suggests that resource sharing may be a critical management intervention in program management practices. Resource interdependence was signifi-

cantly and positively associated with promotive interaction behaviors. Although social interdependence theory indicates that any positive interaction results in promotive interaction behaviors, the levels of resource interdependence in an ISD vendor program were highly correlated with the levels of promotive interaction behavior (i.e., communication, effort, and mutual support). This result suggests that researchers adopting social interdependence theory as a foundation for examining a phenomenon should consider the levels of resource interdependence in their proposed research models, at least as a control, especially in the ISD context. The result of this study also has several important implications to IT management. First, it suggests that IT management must understand that interdependence among ISD projects within a program team may facilitate positive coordination among program members. However, interdependence can also lead to complexity and conflict. It is advisable to encourage resource sharing to achieve a higher level of promotive interaction behaviors. Second, communication, effort, and mutual support were highly associated with final program performance. More specifically, communication was highly associated with business objective achievement and mutual support was highly correlated with operational effectiveness. On the other hand, effort has a positive relation with both business objectives and operational effectiveness. This indicated that different types of outcomes may need different types of promotive interaction behaviors among program members. IT management must facilitate such behaviors according to the organizational objective priorities. Third, the result of this study also suggests that IT management must actively both “enhance” and “monitor” the levels of promotive interaction behaviors among program members. Without positive promotive interaction behaviors, the desired outcomes for an IT program may be difficult to achieve. Although the exact management intervention mechanisms are beyond the scope of this study, findings from the literature

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may provide some guidelines. In order to emphasize common program goal and encourage cooperation, the reasons for enhancing interdependence needs to emphasized and program members must want to belong and believe in vision. One such is that resource interdependence is a key factor to consider in the design of program teams. An appropriate level of resource interdependence imposed on a group can force a level of interaction that will encourage promotive interaction appropriate to the program. Promotive interaction can be improved by requiring certain levels of cross-project training. Program managers could assign projects to project managers who possess the requisite skills, attributes, and behaviors that facilitate effective promotive interaction. It is also important that program managers consider, develop and communicate the criteria used for performance evaluation at the program level. Program members may be uncertain about how they are evaluated at the program level; program managers need to convey clear performance parameters. Finally, the result of this study provides a confirmation to IT managers that program management practices could provide benefits beyond using isolated project management to achieve business objectives. The present study, like any other, has inherent limitations. First, the types of services provided by the examined vendors may be different from other vendors. The results may not be applicable to all ISD outsourcing programs. Secondly, the data are strictly from software outsourcing vendors in India. The limitations set by a single industry class and nation limit generalizations to the IT industry in general. Single culture studies are also limiting in that relationships might be dependent on traits inherent in the culture under study. Finally, business objectives and operational effectiveness were examined in this study. Other program performance measures such as business process efficiency and stakeholder management were not examined. Future studies that adopt different sample frames and different performance measures are strongly encouraged to further generalize this study. Appendix A

COMM4 In our program, there were conflicts regarding the openness of the information flow. COMM5 The program members were happy with the timeliness in which they received information from other program members. COMM6 The program members were happy with the precision of the information received from other program members. COMM7 The program members were happy with the usefulness of the information received from other program members. Effort EFF1 EFF2 EFF3 EFF4

Mutual support SUPP1 Program members helped and supported each other as best as they could. SUPP2 If conflicts came up in the program, they were easily and quickly resolved. SUPP3 Discussions and controversies were conducted constructively. SUPP4 Suggestions and contributions of program members were discussed and further developed. SUPP5 Program members were able to reach a consensus regarding important issues. Business objectives BO1 BO2 BO3

Survey items BO4 Resource interdependence For each resource listed below, identify the extent of sharing among all project teams in the program RI1 RI2 RI3 RI4

Administrative personnel (non-technical) Data Technical expertise Process information

COMM1 There was frequent communication within the program. COMM2 The program members communicated often in spontaneous meetings, phone conversations, etc. COMM3 Project-relevant information was shared openly by all program members.

The program was able to meet expected goals. The program was able to provide expected benefits. The program was able to meet organizational expectations. The program was aligned with the business's strategy.

Operational effectiveness OPE1 OPE2 OPE3 OPE4

Communication

Every program member fully pushed the program. Every program member made the program their highest priority. Program members put much effort into the program. There were conflicts regarding the effort that program members put into the program.

The program was completed within budget. No gridlock in the program — all the projects done on time. The program provided all the functionality that it was supposed to provide. The program provided quality service that it was supposed to provide.

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