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"SOCIOTECHNICAL SYSTEMS IN VIRTUAL ORGANIZATION:

THE CHALLENGE OF COORDINATING WORK AND KNOWLEDGE ACROSS TIME AND SPACE"1,2

Key Words: Sociotechnical, Virtual, Deliberations, Knowledge Coordination

Authors3: Pamela A. Posey, D.B.A. - pam@eyesonperformance.com; Sociotechnical Systems Roundtable Bert Painter - BertPainter@moderntimesworkplace.com; Royal Roads University

Douglas R. Austrom, Ph.D. - daustrom@tpaconsulting.com; Sociotechnical Systems Roundtable

Betty Barrett, Ph.D. - bbarrett@mit.edu; Massachusetts Institute of Technology Betsy Merck - betsy@merckconsulting.com; Sociotechnical Systems Roundtable

Ramkrishnan V. Tenkasi, Ph.D. - rtenkasi@ben.edu; Benedictine University

ABSTRACT

This study of virtual R&D projects uses Sociotechnical Systems analysis to understand the influence of virtuality on deliberations and knowledge development at various stages of an R&D continuum ranging from basic research to commercial development. It adds to our understanding of how collaborative virtual work is coordinated and learning is disseminated across time and space. Different types of coordinating mechanisms and their effect on managing knowledge development barriers across the R&D continuum are identified, and findings suggest that understanding the position of a project on the continuum can help organizations select the most appropriate coordinating mechanisms to enhance their effectiveness in a virtual work environment.

1 This material is based upon work supported by the National Science foundation under grant number NSF OCI 09-43237. Any opinions, findings and conclusions or recommendations in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. 2 This paper was developed in part from a working paper drafted by Bert Painter (a co-author and member of this research team) in September 2012 entitled “Coordination in Virtual Organization of Research and Development”. 3 Corresponding author: Pamela A. Posey, D.B.A. 4835 W Glenhaven Drive, Everett, WA 98203; Voice 425.985.6097; FAX 425.297.9087; Email pam@eyesonperformance.com

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1. INTRODUCTION Research and development (R&D) in organizations is characterized by high interaction needs and interdependencies among organizational units as well as with suppliers, customers, and competitors in today’s complex global environment. Cross-industry, cross-discipline, network-based ecosystems are emerging as a result of these increasing interdependencies. Virtual organizations that span institutional and national boundaries have become central to the emerging practice of science and engineering (Industrial Research Institute, 2011; Nobelius, 2004; Gassmann et al., 2003). As such systems proliferate, both between and within organizations, it becomes vitally important to better understand how to design work systems that are highly interdependent yet not co-located, how to lead and manage the innovation process, and how to coordinate the work across time and space, as well as across multiple organizations or organizational units.

This comparative study of ongoing R&D projects conducted in virtual, geographically dispersed organizations reinforces the importance of understanding and managing the challenge of coordinating work and knowledge across time and space. The organizations and projects studied represent different stages in an R&D process continuum that range from basic research to scale-up and commercial development. Using Sociotechnical Systems (STS) analysis as a methodological approach, the research has focused on understanding the influence of virtuality on deliberations and knowledge development at various stages of the R&D continuum. STS offers both theoretical and practical lenses through which to examine the social and technical subsystems of work, whether co-located or virtual, to determine how the design of the work and quality of fit with its goals influence the effectiveness of the outcomes. The research project sought to add to our understanding of how collaborative work is coordinated and how learning is disseminated in virtual work systems. Building on the theory of organizations as information processing and knowledge utilization systems, the research has identified different types of coordinating mechanisms used to manage and support virtual work and has investigated their effect on managing knowledge development barriers across the R&D spectrum. Findings suggest that understanding the position of an organization or project on the R&D continuum can help organizations determine and apply the most appropriate coordinating mechanisms to enhance effectiveness in a virtual work environment.

2. RESEARCH SITES AND METHODOLOGICAL APPROACH Three ongoing virtual R&D projects have been included in this study; each project is in a different industry and each deals with different challenges based on the type of virtual work being done. R&D has been characterized as an intrinsic learning system (Purser et al., 1992) with multiple stages. Each stage is defined by the degree to which participants do or do not know the “what” (objective) or the “how” (method or means) of their knowledge development and synthesizing activities. These stages form a developmental continuum that ranges from projects with high uncertainty in which participants don’t know what is the final or real objective in concrete terms and don’t know how to operationalize it – to projects with low uncertainty in which participants know what they need to achieve and also know how to achieve it operationally.

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In addition to being clearly identified as R&D projects, each of the projects in this study has been conducted in its own virtual organizational setting. In each case, the work is comprised of interdependent knowledge-based tasks conducted by participants who are dispersed across space and time and are unable to collaborate face-to-face all or most of the time. Thus, each exemplifies the primary characteristics of virtual organizations as identified in ongoing research into the nature of virtuality (Dixon and Panteli, 2010; Schweitzer and Duxbury, 2009; Gibson and Gibbs, 2006; Chudoba et al., 2005; Malhotra and Majchrzak, 2004). In addition, each project included an element of multidisciplinarity or cross–professional membership. Each project studied is located at a different stage on the continuum of the R&D process, and each displays a different level of uncertainty in the project work. The “Orchid Project” was a pure research project (R1 on the R&D continuum); The “Uniform Data Set Project” was initially studied in the early development stage (D1 on the R&D continuum); and the “Large Video Game (LVG) Project” was primarily positioned in the scale-up stage (D4 on the R&D continuum) although the engineering aspects of this project more closely aligned with the start-up stage (D3) of development (see Figure 1).

Figure 1: A Six-Stage Continuum of the R&D Process, including Location of Case Study Projects on the R&D Continuum 4

4 Carolyn Ordowich (personal communication, March 26, 2009) adapted the R&D continuum from a research portfolio model originally developed and deployed at Bell Laboratories (Mashey, 2008; Revkin, 2008).

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The degree of uncertainty within any given project is important to recognize because of the different methods organizations develop and implement to coordinate their activities at various stages. Coordination is a particularly important challenge in virtual organizations. The three cases in this study each have distinctive mechanisms that emerged or were designed to meet the challenges faced by the members of the organization as they worked in virtual environments. While some coordinating mechanisms were apparent across the continuum, different coordinating mechanisms also appeared at each different stage of the continuum. These distinctive coordinating mechanisms and the character of the structures devised to facilitate organizational function appear to be influenced by the level of uncertainty faced in the project. Hence, the relationship between the type of coordinating mechanism, the degree of uncertainty in the project, and the position on the R&D continuum are tightly coupled.

2.1 The Research Sites The “Orchid” Project represents the field of fundamental, basic research and appears at position R1 on the R&D continuum; it is a collaborative project among theoretical and experimental physicists from research universities around the world. The project, funded by the Defense Advanced Research Projects Agency (DARPA), is lead by scientists from Caltech and includes physicists from universities in the U.S., Austria, and Germany. It is a pure research study in which the researchers don’t know what they are going to find and therefore, don’t know how to design a research project that will actually be effective. The degree of virtuality is quite high in the patterns of interaction between faculty and students or post docs.

The “Uniform Data Set” Project (UDS) is a joint project among 29 Alzheimer's Disease Centers across the United States and the National Institute of Health. The project was initially located at position D1 on the R&D continuum – the parties know what their goal is but don’t know how to accomplish it. This is a mature project that is expanding its investigation based on earlier accomplishments. The chief participants have worked together for a number of years under the overall guidance of the National Alzheimer’s Coordinating Center. In addition, there are substantial professional ties within and across the centers as the membership consists of a majority of the world’s experts in Alzheimer’s Disease treatment. This project has a number of long standing practices for communicating both virtually and face-to-face.

The “Large Video Game” Project (LVG) involved some Start-Up Development (D3) and mostly Scale-Up Development (D4) activities; it incorporates art asset production, engineering, and testing activities shared among the game developer and vendors around the world. Clarity of purpose and outcome is crucial in the D4 positioning of LVG, and though uncertainty about the what and, to a somewhat lesser extent, the how of the process is low, there is a high degree of virtuality and relatively low face-to-face collaboration in this project. All three projects exhibited high virtuality, multidisciplinary activity, and varying levels of complexity and uncertainty in the work to be done and the processes required to complete the work. There was clear variation in the degree of knowledge of what were the goals of each project, how the work was to be accomplished, and how virtuality was to be managed. Over time a variety of coordinating mechanisms emerged, were used, or were designed to deal with the barriers to communication and knowledge development that arose.

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2.2 Theoretical Background and Methodological Approach In virtual organizations that involve activities such as R&D and/or new product development, work is non-linear and knowledge based. This means that much of the work itself is conducted through discussions, decision-making, and choice-making interactions that are not face-to-face; these are referred to as deliberations in sociotechnical systems theory. Deliberations are defined as “patterns of exchange and communication with ourselves or others to reduce the equivocality of a problematic issue” (Pava, 1983, p.58), where problematic issues are significant enough that they must be resolved in order to meet the goals and fulfill the mission of the organization or unit. Deliberations are particularly important in the virtual arena of R&D work; it is through deliberations that the work is moved forward. This research project focused on three main areas of inquiry related to deliberations, including the nature of optimal deliberations in virtual R&D organizations and projects, factors that differentiate successful deliberations, and the impact of structure and organization on the success of deliberations. It used Pava’s (1983) STS framework for identifying and analyzing key choice points in nonlinear work processes to understand how virtual work is coordinated across time and space in R&D settings where equivocality is often high. Other research has also demonstrated the value of deliberation analysis to identify sources of variances and delays in new product development (Shani and Sena, 2000; Tenkasi, 2000; Purser, 1992; Pasmore and Gurley, 1991). This research project was designed to extend application of this empirical method into work settings where equivocality is greater to help recognize how uncertainty shapes virtual projects and their outcomes. An extensive review of the literature in sociotechnical systems theory, virtual organization, and organizational information processing helped frame the context and focal questions for this research. Using the literature in these fields as background in developing the protocols, a series of scoping interviews were conducted with each organization to gain an understanding of the projects and the participants in the virtual work. Additional structured interview protocols were then developed and applied in the actual research process. Through a combination of structured interviews and observation, key deliberations were identified and tracked in each research site in order to gather core data about the process and outcomes of each. Finally, follow-up interviews, again relying on a structured protocol, were conducted to assess the quality and outcomes of the deliberations process.

It is important to understand the work context and collaboration demands of the work itself in order to understand the complexity of managing virtual knowledge work in R&D projects. STS provided a powerful lens through which to view the context within which knowledge generation, expansion and sharing occurs across the R&D continuum; and it highlights the importance of both social and technical systems in virtual work environments.

STS theory focuses on examining the social and technical subsystems of work (Lipnack and Stamps, 1997;Pasmore, 1988; Ackoff and Emery, 1972; Emery, 1959) to better design effective work systems. Initially, STS was developed as a design methodology in manufacturing and chemical processing industries (Davis and Cherns, 1975, Emery and Thorsrud, 1969; Rice, 1953); the design principles (Cherns, 1976) developed from this work served well as applied to routine work

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With the rapid development and expansion of the service sector in the 1980s, a greater emphasis was placed on knowledge-intensive, non-routine work. Non-routine work systems, like those found in R&D, involve nonlinear conversion flows, multiple and often concurrent tasks that are highly interdependent, and a high degree of specialized expertise and professionalism (Pava, 1983). For work in non-routine systems, 'deliberations' became the primary unit of analysis (Taylor, Gustavson, & Carter, 1986; Pava, 1983). Pava (1983) described deliberations as "equivocality reducing events" or choice points relative to knowledge generation and use that are crucial to non-routine work systems. In this study, each project provided a rich assortment of deliberations for us to analyze. For example, in the Orchid project, choices had to be made about what experiments to run, how to design those experiments, and how to make sense of the results. For the UDS, choices had to be made about what data to include, what diagnostic instruments to use, and who would have access to the data. In the LVG project, choices had to be made about what new features to develop, what contractors to use, and what the requirements would be for those contractors. Using the STS framework for analysis of the three projects highlighted the challenges of managing virtuality from both social and technical perspectives simultaneously. It has, in particular, helped increase our understanding of how knowledge is created, disseminated, and dispersed along a continuum of virtual R&D work in which the demand for “social” coordination appears to increase with higher levels of uncertainty, and the demand for “technical” coordination appears to increase as uncertainty decreases.

3. COORDINATING MECHANISMS One of the key challenges in virtual work and knowledge generation and dissemination arises from the need to manage interdependence among the work activities (Herbsleb, 2007; Gibson & Gibbs, 2006; Chudoba, et. al., 2005; Ramesh and Dennis, 2002; Malone and Crowston, 1994). Coordinating mechanisms are developed or emerge because of the need to manage this interdependence and avoid creating or exacerbating barriers that affect the capacity to reduce equivocality in virtual organizations. In the knowledge work environment of virtual organizations, several types of knowledge barriers often arise. Lack of knowledge about the work, procedures and processes, or the capabilities of virtual participants can slow or even derail progress. Even where it is available, there may be a failure to utilize knowledge by participants. A third potential set of knowledge barriers arises from a failure to share knowledge that is known to exist. Lack of a common frame of reference can also become a significant knowledge barrier in virtual organizations. A connection between coordination mechanisms and the possibility of mitigating knowledge development barriers is based on theory of organizational information processing and mutual meaning making (Malhotra & Majchrzak, 2004; Boland and Tenkasi, 1995; Weick, 1995, 1979; Daft & Lengel, 1986; Galbraith, 1974). It postulates that structural mechanisms for coordination must provide the means to handle the amount and richness of information processing required by the uncertainty and equivocality of an organization’s tasks, interdepartmental relationships, and environment in order to co-create knowledge (Boland and Tenkasi, 1995; Nonaka, 1994). Coordinating mechanisms can make a major difference in how well deliberations in non-routine work incorporate the right information and knowledge, and the right participants at the right time.

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Specific mechanisms to permit coordination have been proposed by Galbraith (1974) and others using an information processing view of organization design, starting with goal-setting, hierarchy, and rules, and extending to development of lateral relations to increase the capacity to process information. In a similar format, Mintzberg (1998, 1983, 1979) proposed a model with six broad categories of coordination: (1) mutual adjustment; (2) direct supervision; and standardization of (3) skills, (4) work processes, (5) results, and (6) norms. However, more specific to global software projects, and potentially most relevant for our study of R&D work, Sabherwal (2003) condensed many classifications identified in the information systems literature into a continuum of four main types of coordination mechanisms: (1) standards; (2) plans; (3) formal mutual adjustment; and (4) informal mutual adjustment. Coordination through “standards” and “plans” relies upon pre-specification of rules, routines, techniques, and targets. Both are mostly impersonal in nature once implemented and appear to represent elements of the technical system in virtual organizations. In contrast, both forms of “mutual adjustment” appear to be coordinated through interpersonal communication, feedback and interaction, which are more representative of the social system in organizations. In addition to defining these key modes of coordination, much research has identified the level of task uncertainty and the degree of task equivocality as key determinants of the suitability or requirement for specific coordination mechanisms (Kraut and Streeter, 1995; Daft and Weick, 1984; Argote, 1982; Weick, 1979; Van de Ven, Delbecq and Koenig, 1976; Galbraith, 1974; Thompson, 1967). According to Sabherwal (2003), the proposition has been that “more informal, communications-oriented” mechanisms (those that STS would suggest are within the social system realm) are more suitable “when uncertainty is greater: during the requirements analysis phase”. He also says that more impersonal, “more formal, control-oriented” mechanisms (those that STS would suggest are within the technical system realm) are “most suitable when uncertainty is less during the design, implementation, and testing phases of a project.” This connection between the level of task uncertainty and the prevalence of specific types of coordination mechanisms has been further validated for virtual organization. Sutanto, Kankanhalli, and Tan (2011) found a “fit” between types of task dependence (with increasing uncertainty) and optimal task coordination portfolios in global virtual teams. Lower task interdependence (pooled or sequential) was primarily coordinated by standards and plans, while higher task interdependence (reciprocal or team) required various forms of mutual adjustment. Gassman and von Zedtwita (2003) found a similar correlation between a set of determinants incorporating different levels of uncertainty and four distinct forms of virtual team organization used to execute R&D projects in various multinational companies. Extending these conclusions of prior studies to apply across the full continuum of the R&D process including pure research (R1), one could expect a pattern of different coordination mechanisms being predominant or primary for different R&D stages based on the degree of uncertainty in the process (see Figure 2).

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Figure 2: Coordination across the Continuum of the R&D Process

4. FINDINGS Initial data gathering through early interviews and secondary data sources about the nature and operating process of each of the projects studied helped place each on the R&D continuum. As has been noted, the Orchid project was a pure research effort, placing it at R1 on the continuum. The UDS project was in the developmental stage, initially placed at D1 and moving into D2 on the continuum. The LVG project included in the research had one set of activities placed clearly at the start-up phase of the developmental stage (D3), while another set of activities was clearly into the scale-up developmental stage (D4) on the continuum. Once the position on the R&D continuum was determined for each project, in-depth interviews and observation were used to gather data about the types of deliberations that occurred in each site, about the types of knowledge barriers that impeded the work, and about the coordination mechanisms the emerged or were developed to deal with those knowledge barriers. 4.1 The Orchid Project

The Orchid project was an international multi-university collaboration by a team of 20 physicists and graduate students led by faculty at the California Institute of Technology (Caltech) who partnered with scientists at other universities in Europe and North America. The research was theoretical and experimental and required high interdependence among physically dispersed teams. There were two primary teams actually designing and building the equipment needed and conducting the experimental research, and three other groups who formed a theoretical team to provide support for experimentation and for advancement of optomechanical theory. All groups were well known, yet very few had ever worked together before this project.

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Key deliberations within the Orchid project focused on the selection of experiments to run, the design of the actual experimentation, and the interpretation and refinement of the data gathered. Knowledge barriers associated with these deliberations were significant. The disciplinary roots of the various groups were related but quite different. The groups used different language to describe the same data, and each group had its own unique problem-solving approach. A significant challenge was that the wide geographic dispersion in this collaboration combined with the high degree of required reciprocal and team interdependence between their disciplines and laboratory facilities carried a constant threat of failure to utilize knowledge if the diversity of scientific perspectives could not be accessed and integrated for creative problem-solving and interpretation in the experimental process. Another major barrier to the acquisition of knowledge resulted from differences in and incompatibility in the equipment used for experimentation. Further, all scientists engaged in the Orchid project were also engaged in other demanding research projects and priorities. There was a high potential for conflict in priorities or a failure to communicate across the project, exacerbated by very tight timelines and 6-month review periods administered by DARPA.

While there was a great deal of mutual respect and strong motivation to collaborate, this project involved a tremendous challenge to invent a new methodology so the devices created at Caltech could run on different experimental equipment in Europe. This co-invention required a detailed understanding by each party of the other’s technical capabilities and limitations, a very challenging task within a virtual organization. Interestingly, the mechanism that most helped bridge these different frames of reference was the role of an embedded researcher, a European graduate student who came to Caltech for a short visit by chance and was able to see differences in approach between the experimental groups and who recognized the need to merge the approaches. Another graduate student, this one from the theoretical school, was also sent to Caltech and was able to give real-time suggestions and quickly interpret experimental data for the theorists. The liaison role that emerged served a clear purpose in helping to coordinate information and knowledge exchange. This face-to-face connection provided by several students in the project proved to be a vital coordinating mechanism.

4.2 The UDS Project This project involved the design and ongoing maintenance of the Uniform Data Set (UDS), a longitudinal database of clinical and neuropathological information on Alzheimer’s patients in the United States sponsored by the National Institute on Aging (NIA). From 1984 to 1999, Rush Presbyterian Medical Center maintained a minimum data set related to Alzheimer’s; over the years quality control of this data set suffered resulting in a missing data rate of 20-30%. By 1999, the NIA, recognizing the need for a reliable and robust data set as a key resource for Alzheimer’s research, established a National Alzheimer’s Coordinating Center (NACC) at the University of Washington-Seattle. The Center’s mandate was to encourage and support more effective collaboration among Alzheimer’s Disease Centers throughout the United States in development and utilization of a Uniform Data Set. Since then, the NACC has worked with a clinical task force of Alzheimer’s Disease Center directors and clinical core directors to develop and update the standardized content of the UDS.

Key deliberations in this project included the selection of data points to include in the data set, an important issue because it determines what longitudinal information will be available for researchers to use in their investigations of Alzheimer’s and related

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conditions. Another key deliberation revolved around how to collect the UDS data: the UDS is based on a set of standardized instruments and the cost for using these instruments has increased dramatically enough that there is now an effort to determine whether NACC should create its own instruments. In addition to how to select the data to be included and the means and frequency of data collection, another important deliberation focused on how to distribute and use the UDS data for research, as well as who should have access.

The move to the UDS from the original data set raised a number of issues: initially, many of the Alzheimer’s Disease Centers resisted the concept of a coordinating center and viewed the requirement to use standardized data collection approaches as an imposition on being able to collect data best suited to their particular research interests. This created major barriers to knowledge sharing in the early deliberations about what elements to include in the UDS. Other knowledge barriers have emerged from the different frames of reference associated with the diverse disciplines among researchers. Data are collected and analyzed by a multi-disciplinary group whose communication is further complicated by dispersion of people across separate departments and buildings, yet there is occasionally a failure to use the knowledge of one or more specific disciplines in deliberations.

The NACC itself was a purposefully designed coordinating mechanism by the NIA. It has provided an infrastructure for effective deliberations on the design and ongoing refinement of the UDS. Another important coordinating mechanism lies in the skill of specific individuals in key roles within the NACC and NIA: these individuals have built relationships and overcome barriers across organizational and disciplinary. Further, there are organizational opportunities to meet face-to-face on a bi-annual basis, promoting information sharing and knowledge dispersion. 4.3 The LVG Project

The Large Video Game project is a commercial product development process; it is based in the US and has put together a virtual organization geographically dispersed across the globe. There is limited economic viability for face-to-face interaction among members of the virtual project teams. Production includes art assets, engineering, website design, and overall quality assurance. In addition to LVG home-based staff, the virtual organization includes external art asset vendors as well as engineering and website vendors. Most of the vendors are quite familiar to LVG despite geographical distance, and the overseas vendors are large, world-class facilities serving global clients.

Key deliberations at LVG involve the core choice points that occur at the front end of the process: vendor selection is a deliberation of primary significance in all aspects of game development. Other key deliberations include defining and estimating the outsourced project work and specifying documentation and requirements. These deliberations are conducted before the production process for a particular product begins. Deliberations in virtual art production were different in nature from those for engineering and website, in part because of the type of work being outsourced and the anticipated outcomes. Key knowledge barriers were less evident in virtual art production than in all of the other development work conducted through virtual organization at LVG. For virtual engineering and web systems, significant barriers did arise. Issues included unclear expectations, unrealistic timeframes, delayed data transfer, and lack of documentation. Knowledge sharing barriers occurred in systems engineering because of intellectual property issues whereby LVG core operations could not share vital source code with vendors. Lack of planning meant that expectations about requirements often diverged and were not always

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effectively resolved between LVG and vendors. In deliberations about vendor selection, there was an initial failure to utilize knowledge that other divisions had about reliable capabilities and technical set-up in companies distributed across the vendor community. Knowledge barriers associated with different frames of reference affected quality assurance: different parts of the organization, for example, had different understandings about the pace expected for work completion.

In the relatively routine and mature work processes of virtual art production for LVG, Inc., there are clear expectations about task deliverables, and agreements on acceptable output are communicated and coordinated using screen shots, visual targets, emails, and extensive digital documentation. Uncertainty is low and the primary coordinating mechanisms are standards and rule based. For engineering and web development, however, there are a number of other coordinating mechanisms that emerged and were applied. For this group, staff often did not know the details of how the outputs were to be achieved, though they did know what was expected. The virtual nature of the work reduced the ability for the quick face-to-face feedback that is possible when co-located, making it difficult to quickly correct misunderstandings or other knowledge frame of reference issues that arose. This was particularly problematic in an environment where the delays and cost overruns that resulted had immediate performance impact.

Many of the challenges of virtual work are related to an organization’s capacity to share information and knowledge across time and space, and it is often assumed that time, geography, and language will be significant barriers to successful virtual collaboration. It was interesting to note that, for LVG in particular, the commonly accepted challenges associated with time zone, language, and cultural differences proved to be relatively insignificant barriers to sharing or using knowledge in key deliberations about expectations and requirements for art production.

5. DISCUSSION AND CONCLUSIONS To review quickly, the research project reported here was conducted in three organizations, and focused on projects within each that were conducted in complex virtual organizations. The research sites included a pure research project conducted by physicists and their students around the world, a database development project to support Alzheimer’s research, and a commercial production process that produced video games. Through interview and observation, characteristics of the virtual environments were catalogued and data were collected about the virtual work processes, the challenges facing participants in these virtual environments, and about the coordination mechanisms used to resolve those problems in order to co-create knowledge. These data were then analyzed to determine what coordinating mechanisms were used to deal with an overcome the barriers to knowledge development and dissemination that exist in virtual organizations.

Of the four main categories of coordination defined earlier (standards, plans, formal mutual adjustment, informal mutual adjustment), all were utilized to some degree within each of the three R&D projects in our study sample. Yet, the most significant mechanisms in mitigating knowledge barriers and improving R&D performance in the context of virtual organization varied across the R&D continuum. The technical, or structural approaches to coordination were applied more in those activities and projects with the lowest uncertainty: where desired outcomes had been

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clearly identified and defined, and where the methods to achieve the desired outcome were clear, coordination by standards and plans seemed most effective. The social, or mutual adjustment coordinating mechanisms were applied more in those activities and projects where there was less certainty about outcomes and process: where the end state was not well clarified and/or the methods by which to achieve them were unclear, coordination by mutual adjustment appeared to be most effective. Thus, this comparative analysis of virtual R&D projects confirms prior organizational theory and extends findings from empirical studies of global software development to include the full continuum of the R&D process. In each of these virtual R&D projects, effective coordination has involved a specific combination of elements and mechanisms. This is consistent with a knowledge-based model of coordination applied earlier to a study of global software projects (Kotlarsky, van Fenema, and Willcocks, 2008) where different types of coordination mechanisms were found to make different contributions to knowledge sharing and development: organizational/structural mechanisms facilitate knowledge flows; work-process mechanisms make knowledge and expectations explicit; technology-based mechanisms amplify knowledge; and the interpersonal skills and mechanisms associated with people build social capital.

Analysis of the findings in this project show that there is a tendency for different categories of coordination mechanisms (structural mechanisms and mutual adjustment mechanisms) to play a primary role in managing different levels of task uncertainty and equivocality related to the various stages of R&D. Structural coordinating mechanisms appear to be more appropriate where uncertainty and equivocality are low. These mechanisms in the three research sites included such practices as standardized skills training, process standardization, common data formats, and standardized error-tracking procedures. The mutual adjustment mechanisms appear most appropriate where uncertainty and/or equivocality are high; these included formal elements such as temporary co-location, site visits, informal meetings and impromptu communication as well as more formal mechanisms such as designated liaison role, formal meetings and status reviews, steering committees and task forces, and a formal facilitator role. Further, STS analysis of specific deliberations within a pure research (R1) project and an exploratory development (D2) project, when compared with deliberations in more structured start-up (D3) and scale-up (D4) development work, provides additional insight as to why the categories of key coordination mechanisms differ in different stages of R&D. In sociotechnical terms, structural coordinating mechanisms are targeted to adjustments in the technical system, and mutual adjustment coordinating mechanisms are more closely related to the social system in organizations. In general, then, our findings indicate that identifying the location of a virtual work project on the R&D continuum can help practitioners anticipate the general nature and degree of their coordination challenge and the mechanisms that are likely most important to apply. Then, STS analysis of deliberations and knowledge development barriers can provide detailed insights to inform the project-specific design of coordination for virtual R&D. Finally, as suggested by the experience of our sample of case studies, including strategic mechanisms that define common purpose for knowledge collaboration yields a framework for coordination of distributed R&D work that reflects the thinking of the National Science

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Foundation VOSS program5; namely, these virtual organizations are, and need to be coordinated as open sociotechnical systems.

5 NSF Program Title: Virtual Organizations as Sociotechnical Systems (VOSS)

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