ASIS Midyear '98 Proceedings

Collaboration Across Boundaries:
Theories, Strategies, and Technology

Measuring the Impact of Information
on Work Performance of
Collaborative Engineering Teams

Kim, Seung-Lye

School of Information and Library Science
University of North Carolina at Chapel Hill
Chapel Hill, North Carolina



Information has played a central role to achieve a successful team project in engineering field. Many researchers have reported engineers' information needs, information seeking behavior, and the relationship between information use and their work performance. By reviewing the types of information, the factors affecting information seeking of engineers and the role of boundary spanners, this paper is concerned with constructing an integrated perspective model of engineers' information use and their work performance, and propose a model that provides a framework for measuring the impact of information on work performance of collaborative engineering teams. A proposed model provides the insight into the process of information and its impact on task completion or work performance. The model should be more explored and tested to see its validity, and some of controllable factors are identified for further research.



Over the decades, research literature on information and work performance of engineers has noted that information plays a central role in the development of a successful team project (Allen & Cohen, 1969; Allen, 1977; Aloni, 1985; Chakrabarti, etc., 1983; Mondshein, 1990; Rosenberg, 1967; Tushman, 1978, 1979). A number of studies (Allen, 1977; Pinelli, 1991; Tushman, 1978) have documented engineers' information needs, information seeking behavior, and the relationship between information use and their work performance. These studies included electrical, chemical, design and computer engineers.

The research on information seeking, use, and transfer among engineers and scientists was begun during the 1960s by engineering management scientists. Allen (1968) at MIT, for instance, conducted a series of investigations on the information need of technologists, and the relationship between various ways of fulfilling information needs and their performance. Most studies, however, focused on some particular aspects such as communication channel, accessibility of information and work characteristics (Chakrabarti, & etc., 1983; Gertsberger & Allen, 1968; Morrow, 1981) rather than a comprehensive integrated aspect.

In contrast, I have attempted to construct an integrated perspective of engineers' information use and their work performance by reviewing the literature. In reality, to fit into a rapidly changing industrial environment, engineers interact with a variety of information, and the factors that affect information seeking are getting more complex and dynamic. For example, industry has been shifting from a sequential to concurrent engineering process to reduce the product development time. In a concurrent engineering environment, which is defined as "the earliest possible integration of the overall company's knowledge, resources and experience in design, development, marketing, manufacturing, and sales into creating successful new products" (Shina, 1991, p.1), engineers from different functional areas perform a variety of activities in parallel. To perform these activities in parallel, they must interact and exchange information with colleagues from different work functions and environments. However, we lack the clear understanding of the dynamics of interactions between information and various work functions or environments. One concern is how much information gives the impact on engineers' work performance. We know information is a critical factor in achieving a successful team project, but how critical is it? This question leads us to a point that without resolving methodology issues surrounding the measurement of information and work performance, the research progress would be hindered. Also the lack of understanding of the dynamics of interaction between information and work performance could lead to an improper development of information systems for engineers.

Thus, by reviewing 1) the types of information, 2) the factors affecting information seeking of engineers, 3) the role of boundary spanners, this paper proposes a model that provides an integrated framework for measuring the information impact on work performance of collaborative engineering teams based on analysis of the research literature on this topic.



Many researchers have defined various concepts of information (Buckland, 1991; Derr, 1985; Yovits, de Korvin, & Mascarenhas, 1987) and types of information (Allen, 1968). Others have explained the significance of information role in management, psychology, communication as well as library and information science (Allen, 1968; Belkin, 1978; Hayes, 1993; Johnson & etc., 1995; Rouse and Rouse, 1984). Although the definition of information, however, has long been a central issue in library and information science and other disciplines, there is no single agreement on it so far. One approach has considered the value or importance of information. For example, Yovits, & etc. (1987) defined information in terms of relationship between information and decision making. In their view, information should be considered by its value when it is actually used in decision making. This paper also approached information as value added one. In this paper, three general types of information which are applicable to engineers' information need and use are reviewed; oral communication, written information, and online database information.

Oral Communication

Communication is the process by which two or more parties exchange information and share the meaning (O'Reilly & Pondy, 1979) and it can be conducted by several forms such as written, oral, electronic means. One of the difficulties in the review study of information and engineers is that previous research, especially those conducted by engineering management scholars, did not specify the types of communication. Rather, they simplified that communication means face to face oral communication. Thus, in this paper oral communication is considered as one type of information and others are defined as written and online.

In the engineering field, most projects to develop a new product or process are expected to involve a certain level of communication with a variety of individuals and groups who share their knowledge and experiences, because complex processes require a great deal of information. Substantial research indicates that oral communication is a particularly effective method for sharing information (Allen, 1977; Chakrabarti and et al, 1983; Kraut and Lynn, 1995; Tushman, 1979b). Most of their findings indicate that R & D (Research and Development) engineers tend to prefer to have information through personal communication within their organization to solve their problems because of easier access and fast feedback.

Research on engineers' information use consistent with the fact that communication is the most important medium for R & D engineers to solve their problems. In a study by Allen (1970), he selected 8 pairs of individuals working on the same problems in different organizations. When he had technical evaluators compare their performance on solutions with respect to the number of contact times with organizational colleagues to solve problems, it was found that high performers consulted with colleagues a lot more than low performers.

Tushman (1978, 1979a, 1979b, 1979c, 1980) also conducted numerous researches on communication patterns of R & D engineers. From all of his studies, he concluded that high performers on research projects had extensive communication with project team members. He argued that communication patterns are an important information process in R & D settings, and although there is no one best communication pattern these processes can be properly managed. His research (1979c) provided an evident that high performing research projects had a characteristic of decentralized patterns of communication within the project.

These findings of preference for oral communication support one hypothesis; information accessibility is the most important factor in selecting information source. From Gertsberger and Allen's work (1968) of identifying the criteria used by R & D engineers in their selection of an information source, they found the accessibility to be the most important determinant of an information channel used. There is, however, an important indication to the effectiveness of oral communication as an information medium. Tushman (1978) proposed that oral communication is effective only where information "actors" share common language with similar background or viewpoint (p.625). He further suggested that in routine tasks, considerable communication would be unnecessary and high-priced but contrary to routine tasks, complex tasks need a great deal of communication between interdependent areas.

Written Information

Researchers found that most engineers spend less time to get information through the written or formal information as compared to the personal communication (Allen, 1969, 1977; Tushman, 1979). It can be explained by such as difficulty of professional journals (Allen, 1969), slow feedback, less ease of access. However, Allen (1969 ) found the very weak tendency for the oral channels to show higher performance when he examined relative importance of the oral channels and written channels of information.

One distinguishing point from the view of engineering management, which considers library or information systems the least used sources, the authors from library and information science tend to focus on the value of having information when library or information systems provide the service in light of how much high performers use these systems compared to low performers.

Online Database Information

Why have information retrieval systems not been successful tools in searching information in the engineering field? Griffith and King (1993) reported that online database of engineers is surprisingly low. Couple of reasons was suggested. One reason could be the information sources that engineers consult mostly. Engineers were found to heavily use textbooks and internal reports to solve problems. This information is difficult to put online and some of information is protected by its organization. Gerstberger & Allen (1968) assert that technology is difficult to document. Allen (1970) states that the failure of information retrieval of scientific and technical information is due to the nature and complexity of the information itself, and to the uncertainty and a user's very personal nature of information needs. He implies that human beings are still the most effective source of information.

However, given that many research on online information for engineers is concerned with the retrieval system itself rather than overall effectiveness of using a system in engineers' work context, several recent research (Hart and Rice, 1991; Bishop, 1994) revealed interesting findings that using online database information influence the work outcomes. Through open-ended interviews and questionnaires, Hart and Rice (1991) tested several hypotheses including users of online information will experience improvements in their work performance. Although they indicated one concern that a great amount of information from the database search might increase the time to process information, their results showed that use of online database information has association with perceived improvements in work performance. Bishop (1994) explored the use of computer networks in aerospace engineering through the mail survey and found that most engineers judged the network access highly valuable since it enables them to access a variety of resources.

Those findings are consistent with as of Bayer and Jahoda (1981)'s study. They tested the hypothesis that the exposure to and use of online bibliographic searching, with the assistance of information specialists, will significantly alter selected aspects of scientists and engineers' activities pertaining to their information style and information habits. They found that from the survey among engineers, the more frequent users of online searching decreased their amount of discussion with colleagues. Thus, they suggested that it is possible that use of online searching allows more available time for writing or problem solving as opposed to literature searching.



Understanding of users' information seeking behaviors has also been a main concern of information science because this understanding is central to serve users better and design the proper information systems. One definition of information seeking behavior is proposed by Krikelas (1983) as "activity of an individual that is undertaken to identify a message that satisfies a perceived need" (p.6). In Belkin's words (1980), information seeking begins with user's perception of uncertainty of current knowledge. This uncertainty needs to be somehow resolved. In an attempt to draw a comprehensive model of information seeking, Johnson, Donohue, Atkin, & Johnson (1995) contest that the critical determinant of the success of organization depends on the individual information seeking. They pose that due to the changing organizational environment (downsizing of organizations and the decline of the numbers of layers in hierarchy), individuals tend to increase responsibility of information for decision making and problem solving.

Particularly in the engineering field, those who seek and identify relevant information are essential in making a team project successful. As indicated earlier it has been noticed that engineers prefer to get information through communication with their colleagues to solve their problems. Thus, in this context this chapter reviews what factors influence engineers' information seeking behavior, particularly communication behavior. Three types of factors are identified for this purpose; organizational factors, work task factors, and personal characteristic factors.

Organizational Factors

Several studies (Allen, 1970; Tushman, 1979) have shown that the status of hierarchies will affect the flow of information. Furthermore, they revealed that organizational factors are the most critical barriers to effective communication. Tushman and Nadler conceptualized the R & D Laboratories as an information processing system, both internally and externally. They argued, given that the importance of technical communications in R & D settings, managers should manage their laboratory's communication network in appropriate way. Allen & Cohen (1969), in a study of the structure of the technical communication network of the laboratory, also inform us informal organization has a strong influence over communication structure.

Tushman (1979b) indicated that certain organizational factors are often the most critical barriers to effective innovation. In his field study conducted in the corporate R & D setting of a large corporation, he found that in essence different projects have systematically different communication patterns. The research indicated that high performing research project had less controlled communication pattern while high performing technical service projects had more controlled communication pattern. Based on his study, he suggested that communication patterns could be managed.

Another investigation of Tushman (1979c) is that matching information processing requirements and information processing capacity. This approach suggests that the performance is related with subunit structure. He suggests based on his findings high performing project with non-routine tasks need more "decentralized pattern of intra-project communication" (p.89). He also revealed that high performing projects with a large amount of departmental inter-dependence were significantly more decentralized than high performing projects with a small amount of departmental inter-dependence and those high performing projects with a great amount of organizational inter-dependence were significantly more hierarchical.

Task Factors: Uncertainty related with work tasks

A number of authors have explored the relationship of information use and uncertainty or complexity of work tasks (Tushman & Nadler, 1978; Tushman, 1979; O'Reilly, 1982; Bystrom, 1995; Auster & Choo, 1993). Their empirical studies show that task characteristics constitute important determinants of information processing. Tushman (1978), for example, by investigating communication patterns and the work characteristics, developed a framework, information processing approach (p.624), According to him, projects must match their information processing capabilities (communication patterns) to their information processing requirements (characteristics of their work). Based on this assumption, he proposed that the more effectively managed projects would develop appropriate communication patterns to their work. Further, he considered task characteristics and task interdependence as the most critical factors of technical communication.

Ducan (1972) provides several concepts of uncertainty, which generally have several components such as insufficient information regarding the work or environment and inability of predicting the outcome of a specific decision. He studied the characteristics of the environment that contribute to decision makers experiencing uncertainty in manufacturing and R & D organizations. He indicated the degree of uncertainty is related to the organizational environment, and decision makers who experiencing the greatest amount of uncertainty in decision making were in dynamic and complex environment.

O'Reilly (1982) addressed in the investigation of decision makers' selection of information sources that uncertainty in the task is highly related to the frequency of information use. However, he also pointed out that when comparing the other factors which impact on information use such as quality, accessibility, the perceived uncertainty and complexity of the work were not critical factors of information source used.

Another research in decision environment, Auster and Choo found the level of perceived uncertainty is highly related with the amount of "environmental scanning" (p. 200). The interesting finding of their study is that perceived source quality is the most important factor in source use, which is contrast to most of Allen's work, Tushman, Ducan, and Rosenberger and some other authors with the exception of Culnan's work (1983b). Auster and Choo explained that the present business environment, which is highly complex and dynamic, could be the main reason why perceived source quality is more important than perceived source accessibility.

Zeffane and Gul (1993) conducted research in a telecommunication industry to address how task characteristics impact on amounts and timeliness of information. Three measures of task characteristics; "task variety, task analyzability, and task inter-dependence" (p. 709) were identified for the analysis. Their findings suggest that task variety is related to the amount of information processing to reduce the uncertainty on the task while task analyzability is related with the timeliness to obtain information solving. Those findings support the idea of Tushman's information processing approach in that task variety and sub-unit structure affect requisite for information processing.

The recent study of Bystrom and Jarvlin (1995) also indicated that the task complexity affects on information seeking and use. Based on qualitative analysis including questionnaires and diaries, they identified the relationship of task types and information types. They categorized 5 task types from simple to complex type and viewed how different work tasks use different information types, channels, and sources. What they found was that as work tasks increase complexity, then information need also increase complexity, general information sharing increase, and the number of sources consulted also increase.

Individual Characteristic Factors

Individual characteristics could be counted as various forms such as gender, age, personal experience, state of the present knowledge, and cognitive stage of understanding, etc. Compared to the other areas of study which influence information seeking, individual characteristic factors understudied significantly. But some studies show (Bayer & Jahoda, 1979) gender and age are important factors for online bibliographic services. Allen's work (1977) indicates that more experienced individuals tend to be aware of specialized information sources than less experienced person. This finding is also supported by the work of O'Reilly (1982). O'Reilly reported that decision makers who have more tenure, education and motivation tend to seek and use more updated information. However, there is not clear explanation how the author collected data for this work.

For the online searching, admitting that technical gatekeepers use information systems a lot more than other engineers, Culnan (1983a) studied whether direct users, who were assumed having similar personal characteristics with gatekeepers, of online information systems are more likely to better educated , belong to more professional organizations and read more professional literature than mediated users who have someone does a online search. The findings indicated that there was only partial support that individuals with gatekeeper characteristics search online databases directly, and there were no significant difference in reading journals among direct users and indirect users. This study, however, showed that direct users are more educated and young.

One study Palmer (1991) did was an exploring personal factor by the psychometric test on the information behavior of a group of agricultural research scientists. Based on the test methods, The Kirton Adaption-Innovation Inventory (KAI) and the Learning Styles Questionnaire (LSQ), she identified "cognitive style, problem solving style, creative style, and learning style" (pp. 256-260). Although she assumed individual difference is a main attribute in information seeking, her analysis showed that discipline or subject area was more important than personal differences. Despite the controversy of psychometric test, it is quite unique study in that it actually identified and analyzed personality with regard to information seeking behavior.

The interesting study of Wang and White (1995) shows that users' psychological, cognitive, and situational relevance criteria play a central role in selecting, reading, and citing. They studied participants of a research project to examine why documents were used or not used when originally selected as relevant. They identified criteria affecting relevance judgments in the early stage (selecting) and later stage of information seeking (reading, citing). They found users applied different criteria at different stages and concluded that information use is an individual user's cognitive behavior that is constantly changing, situational and affected by multiple factors. For the cognitive models of information need, seeking and use behavior, Allen (1991) and Ingwersen (1996) give general and broad review for the history, its implications and applications of cognitive research in information science.



One of the common findings of this area is that in organization there exist small numbers of individuals who gain and disseminate external information through active interaction with engineers of other organization. These individuals are identified as "gatekeepers" (Allen, 1969, 1977; Tushman, 1980) or "environmental scanners, interorganizational stars, and inter disciplinary stars" (Sonnenwald, 1995.1996, 1997). In general, these boundary spanners differ from their colleagues in their orientation toward outside information sources. They read, search online, present, and publish papers more than average engineers. They role as a bridge to connect with outside information and their organization.

In a study of communication network of large aerospace firm's R & D division, Allen identified gatekeepers according to the degree of interconnectivity with other colleagues in other organizations. Based on his finding which gatekeepers brought new information into the organization, he suggested that bringing new information to the project from outside would be effective if an organization supports and uses technical gatekeepers effectively.

Kraut and Streeter (1995) studied the problems of coordination activities in software development. They argued that the most important problem in developing large software systems is the difficulty of coordination among development team members. They surveyed the intergroup collaboration across 65 projects in one large software company to see coordination practice that influenced the sharing of information and goals (p.71). Their findings demonstrate that both informal and formal interpersonal communication mechanisms are valuable to share information and achieve coordination in software development.

Well explained and further explored works on the role of boundary spanners can be found Sonnenwald's works (1995, 1996; Sonnenwald and Lievrouw,1997). She characterized design as process of "contested collaboration" (1995, pp. 872-874) and specified the types of boundary spanning roles in engineering teams: "organizational boundaries, task boundaries, discipline boundaries, personal boundaries, and multiple boundaries"(1996, pp. 179-204). Based on her study, she introduced the concept that boundary spanning must occur across boundaries within a project as well. The study of Sonnenwald and Lievrouw (1997) was conducted in a high technology firm to examine the applicability of those boundary roles. From the questionnaires and extensive interviews, they found that there exist certain types of communication roles, or multiple roles in the design team and individual work performance is strongly related to the communication among team members.



The basic hypothesis of my model is that engineering work tasks give rise to particular information needs, and according to existing literature on engineers' information seeking behavior, engineers' perception on accessibility and quality of information influence the way in which information is sought. Important factors including search tasks, organizational structure and personal characteristics are identified which influence information search process. Certain types of information such as face to face informal communication, formal communication (e.g. meetings, conferences), written information (e.g. text books, manuals, internal reports, journals) and online database information are consulted as an important factor which influence search tasks. Empirical studies demonstrate that organizational structure also influence information search process. Different work tasks need different organizational structure. For instance, more research oriented team project as compared to routine and technical works needs an informal and less hierarchical organizational structure. Although little research has been done on personal characteristics, which influence information search process, existing research shows that the differences of individuals ultimately affect on information search process.

The model shows how information uses impact on work performance of engineers' team project. For the evaluation of task performance or completion, several factors could be considered such as the quality of task performance, meeting to deadline, budget, technical progress, commercial success (Barczak, 1991) or efficient design and development process (Ancona, 1990). This model also allows us to observe the patterns of information needs based on completion of team project. For example, how high performed team members deal task- related uncertainty or how they differently or similarly use the channels of information as compared to others. To test this model, several approaches could be conducted by controlling or examining search tasks, organizational structure and personal characteristics.



This paper started with the concern of how much information gives the impact on work performance of engineers by reviewing types of information that engineers use, factors affecting their information needs, seeking, and use behavior. The previous research informs us that individual difference, organizational difference, and task differences influence the performance and information seeking of individuals and team projects. And those differences are also related to the use of different information sources and types.

Based on these, I proposed the model that provides the process of information impact on work performance of engineering team projects. Given that most previous research is confined to a particular team project or organization, with a proposed model by cumulative observations and experiments in a long term we could comprehend the dynamics of information behavior and its impact. Thus, the problems of measuring work performance in terms of using information should be more explored since information related activities are getting more complex. Once we understand those nature, we could probably provide a more generalizable model. Another point is, although I did not include in my proposed model, boundary spanning roles should not be ignored in their importance because by clear understanding those roles and patterns of interacting with information and colleagues, we can verify what facilitates high quality collaboration between team project members.

ACKNOWLEDGMENT: I gratefully acknowledge the help of Professor Diane H. Sonnenwald. I sincerely thank her guidance and advice in conducting this study.



Allen, Bryce L. (1991). Cognitive research in information science: implications for design. Martha E. Williams, Ed.: Annual review of Information Science and Technology, 26, 3-37.

Allen, Thomas. (1968). Organizational aspects of information flow in technology, Aslib Proceedings, 20(10), 433-454.

Allen, Thomas J., & Cohen, Stephen I. (1969). Information flow in research and development laboratories. Administrative Science Quarterly, 4, 12-19.

Allen, Thomas J. (1970). Communication networks in R & D laboratories. R & D Management, 1(1), 14-21.

Allen, Thomas. (1977). Managing the Flow of Technology. The MIT Press, Cambridge.

Ancona, D.G. (1990). Outward bound: strategies for team survival in an organization. Academy of Management Journal, 33, 334-365.

Aloni, Michaela. (1985). Patterns of information transfer among engineers and applied scientists in complex organizations. Scientometrics, 8(5-6), 279-300.

Auster, Ethel & Choo, Chun Wei. (1993). Environmental scanning by CEO in two Canadian industries. Journal of the Association for Information Science, 44(4), 194-203.

Barczak, Gloria, & Wilemon, David. (1991). Communications Patterns of new product development team leaders. IEEE Transactions on Engineering Management, 38 (2), 101-109.

Bayer, Alan E., & Jahoda, Gerald. (1979). Background characteristics of industrial and academic users and nonusers of online bibliographic search services. Online Review, 3 (1), 95-105.

Bayer, Alan E., & Jahoda, Gerald. (1981). Effects of online bibliographic searching on scientists' information style. Online Review, 5(4), 323-333.

Belkin, N.J. (1978). Information concepts for information science. Journal of Documentation, 34(1), 55-85.

Belkin, N.J. (1980). Anomalous state of knowledge as a basis for information retrieval. Canadian Journal of Information Science, 5, 133-143.

Buckland, Michael K. (1991). Information as thing. Journal of the Association for Information Science, 42(5), 351-360.

Bishop, Ann Peterson. (1994). The role of computer networks in aerospace engineering. Library Trends, 42(4), 694-729.

Bystrom, Katrina & Jarvelin, Kalervo. (1995). Task complexity affects information seeking and use. Information Processing and Management, 31(2), 191-213.

Chakrabarti, Alok K., Feineman, Stephen., & Fuentevilla, William. (1983). Characteristics of sources, channels, and contents for scientific and technical information systems in industrial R and D. . IEEE Transactions on Engineering Management, 30(2), 83-88.

Culnan, Mary J. (1983a). Chauffeured versus end user access to commercial databases: the effects of task and individual differences. MIS Quarterly, 7(1), 55-67.

Culnan, Mary J. (1983b). Environmental scanning: the effects of task complexity and source accessibility on information gathering behavior. Decision Science, 14, 194-206.

Derr, Richard. (1985). The concept of information in ordinary discourse. Information Processing and Management, 21(6), 489-499.

Duncan, Robert B. (1972). Characteristics of organizational environments and perceived environmental uncertainty. Administrative Science Quarterly, 17, 313-327.

Gerstberger, Peter G., & Allen, Thomas J. (1968). Criteria used by research and development engineers in the selection of an information source. Journal of Applied Psychology, 52(4), 272-279.

Griffiths, Jose-Marie, & King, Donald W. (1993). Special libraries : increasing the information edge. Washington, D.C. : Special Libraries Association.

Hart, Paul & Rice, Ronald. (1991). Using information from external databases: contextual relationships of use, access method, task, database type, organizational differences, and outcomes. Information Processing and Management, 27(5), 461-479.

Hayes, Robert M. (1993). Measurement of information. Information Processing and Management, 29(1), 1-11.

Ingwersen, Peter. (1996). Cognitive perspectives of information retrieval interaction elements of a cognitive IR theory. Journal of Documentation, 52(1), 3-50.

Johnson, J. David, Donohue, William A., Atkin, Charles K., & Johnson, Sally. (1995). A comprehensive model of information seeking. Science Communication, 16(3), 274-303.

Krikelas, James. (1983). Information seeking behavior: patterns and concepts. Drexel Library Quarterly, 19, 5-20.

Kraut, Robert E & Streeter, Lynn A. (1995). Coordination in Software Development. Communications of the ACM, 38(3), 69-81.

Mondschein, Lawrence G. (1990). Selective dissemination of information (SDI): relationship to productivity in the corporate R & D environment. Journal of Documentation, 46(2), 137-145.

Morrow, Paula C. (1981). Work related communication, environmental uncertainty, and subunit effectiveness: a second look at the information processing approach to subunit communication. Academy of Management Journal, 24(4), 851-858.

O'Reilly, Charles A. (1982). Variations in decision makers' use of information sources: the impact of quality and accessibility of information. Academy of Management Journal, 25(4), 756-771.

Palmer, Judith. (1991). Scientists and information: II. Personal factors in information behavior. Journal of documentation, 47(3), 254-275.

Pinelli, Thomas E. (1991). The information-seeking habits and practices of engineers. Science and Technology Libraries, 11(3), 5-25.

Rosenberg, Victor. ( 1967). Factors affecting the preferences of industrial personnel for information gathering Methods. Information Storage and Retrieval, 3, 119-127.

Rouse, William B. & Rouse, Sandra H. (1984). Human information seeking and design of information systems. Information Processing and Management, 20(1-2), 129-138.

Shina, Sammy G. (1991). Concurrent engineering and design for manufacture of electronics products. New York, New York: Van Nostrand Reinhold.

Sonnenwald, Diane H. (1995). Contested collaboration: a descriptive model of intergroup communication in information system design. Information Processing and Management, 31(6), 859-877.

Sonnenwald, Diane H. (1996). Communication roles that support collaboration during the design process. Design Studies, 17, 277-301.

Sonnenwald, Diane H. & Lievrouw, Leah. (1997). Collaboration during the design process: a case study of communication, information behavior, and project performance. In Reijo Savolainen, Graham Taylor, & Brenda Dervin (Eds.), Information Seeking in Context, 179-204.

Swanson, E. Burton. (1987). Information channel disposition and use. Decision Science, 18, 131-145.

Tushman, Machael L. & Katz, Ralph. (1980). External communication and project performance: an investigation into the role of gatekeepers. Management Science, 26, 1071-1085.

Tushman, Michael L. (1978). Technical communication in R & D laboratories: the impact of project work characteristics. Academy of Management Journal, 21(4), 624-645.

Tushman, Michael. (1979a). Impacts of perceived environmental variability on patterns of work related communication. Academy of Management Journal, 22(3), 482-500.

Tushman, Michael L. (1979b). Managing communication networks in R & D laboratories. Sloan Management Review, 20(Winter), 37-49.

Tushman, Michael L. (1979c). Work characteristics and subunit communication structure: a contingency analysis. Administrative Science Quarterly, 24, 82-98.

Wang, Peiling, White, Marilyn Domas. (1995). Document use during a research project: a longitudinal study. Proceedings of the 58th ASIS annual meeting, Chicago, IL, October 9-12, 1995 (pp. 181-188). Medford, NJ: Learned Information, Inc.

Yovits, M C., de Korvin, A., Kleyle, R., & Mascarehas, M. (1987). External documentation and its quantitative relationship to the internal information state of a decision maker: the information profile. Journal of the Association for Information Science, 38(6), 405-419.

Zeffane, Rachid M. & Gul, Ferdinand. (1993). The effects of task characteristics and sub-unit structure on dimensions of information processing. Information Processing and Management, 29(6), 703-719.

Paper presented at the 1998 midyear meeting of the Association for Information Science, May 17-20, 1998, Orlando, Florida.

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