Organizational models for collaboration in the new economy.

Technology Drivers and Collaboration

The new economy is a knowledge-based economy without borders, where the race is between companies and locales over how to learn faster and organize more flexibly to take advantage of technology-enabled market opportunities (Kelly, 1998; Best, 2001). Within this new economy, the World Wide Web is ubiquitous. It has transformed geographically separated locales into a "global village" for information sharing, social interaction, and economic exchange. Technology, in particular, ever-expanding digital bandwidth, has resulted in the creation of new-economy forms of intangible, knowledge-based capital, the value of which now exceeds that of the physical capital that once dominated old economies (Castells, 2000; Tapscott, et al., 2000). Whereas old-economy business models emphasized organizationally defined tasks and roles, new-economy business models value self-organizing teams, companies, and industry-based clusters or communities of networked firms and institutions to meet the changing requirements of innovative projects, the boundaries of which transcend the rigidities of old-economy hierarchies. The perspective taken in this article asserts that the careers and work experiences of new-economy workers are interdependent with their involvement in Web-enabled teams, companies, and social and industry communities through which project work is accomplished (see Exhibit 1).

We evidenced a shift from immobile-wired infrastructures to mobile, miniature, and wireless modes of communication, computing, and transacting. Customers demand "any time, any place" solutions of their problems. Such demands have led companies to invest in creating online business processes and services as either substitutes or supplements to brick-and-mortar service offerings (Gulati & Garino, 2000). Moreover, by compressing the time cycles for satisfying customer requirements, companies now face unprecedented organizational challenges in adapting their human resources and organizational practices to the fast-moving business environment. Rigid organizational routines will destroy economic value when market and technological requirements advance (Leonard-Barton, 1995).

Innovative enterprises that employ technology to facilitate independent, project-based collaborations are the hallmark of the new economy (Quinn, et al., 1997). Such collaborations can range from arms-length information sharing to highly interdependent joint cooperation in the creation of new products and services (Best, 2001). Information technology now makes possible a variety of collaborative workspaces for project teams, companies, and industry clusters or networks. In the sections to follow, we examine each of these modes of collaboration and assess the opportunities and challenges for HR managers and their new economy knowledge workers.

Technology, Teams, and Trust

The new economy's performance demands and its technology tools are affecting the way in which project teams are organized. First, in the old economy, companies facing predictably long-term and stable demands for products and services could create work teams of relatively long duration. But new-economy companies face much shorter demand cycles and less-predictable customer requirements. As a result, new-economy companies must be able to create and dissolve teams rapidly in response to rapidly changing requirements. Team members must be prepared to change their team affiliations frequently and effectively and efficiently to collaborate with new team members on new projects. Such short-lived teams challenge more orthodox notions of building group cohesion and commitment over time (Mullen & Copper, 1994).

Second, old-economy companies were typically staffed through stable, long-standing organizational units, so that marketing departments had marketing teams, engineering departments had engineering teams, and project boundaries largely reflected internal organizational arrangements. New-economy companies face complex demands for knowledge creation and knowledge sharing that span traditional organizational boundaries (Sapsed, et al., 2002). Project teams of the new economy can arise anywhere within the company, and project members can be drawn from many separate organizational units and business functions. These inter-department teams are necessary in order to provide the needed depth and breadth of skill and experience for meeting complex business requirements. Indeed, a primary contribution of these team members to project performance may be as gatekeepers of external knowledge sources (Keller, 2001).

Third, old-economy companies typically created teams by co-locating members for face-to-face project work. New-economy companies often must confront project tasks where the requisite skills and expertise are geographically dispersed within far-flung organizational units. Thus, new-economy project teams are often virtual teams whose members collaborate at a distance from each other using groupware software and other virtual collaborative tools. These include shared databases, email, organization intranets, computer conferencing software, and video-mediated communications systems, such as video telephony or video conferencing (Symon, 2000).

Fourth, old-economy companies typically staffed their project teams exclusively with their full-time employees and thus maintained uniform control over team member performance evaluation and compensation arrangements. New-economy companies frequently need to create project teams whose membership includes representatives from supplier companies, customer organizations, and independent contracting third parties. As a result, the project team spans both organizational and physical boundaries. Such inter-firm collaborative teams raise important challenges in aligning disparate performance incentives, work processes, and project priorities (Tapscott, et al., 2000).

Fifth, old-economy companies effectively accomplished their project work through autonomous and independent project teams, which periodically needed to communicate and coordinate their project work with other project teams. This was often accomplished by meetings of project team leaders and supported by the exchange of project progress reports. By contrast, today's new-economy project work requires up-to-the minute ("real time") coordination and collaboration among widely scattered members of interdependent but physically separate project teams. Recent developments in real time collaborative software now allow separate project teams and their members to link a spread sheet cell to any data source, input that source, and make the resulting findings instantly available to everyone connected to the real time, event-driven database (Economist, 2002).

Finally, electronic communications need to complement rather than replace face-to-face communications. Evidence is now accumulating that electronic communications may lack the social cues needed to foster a deeply shared personal understanding of work-relevant values and attitudes among team members (Garton & Wellman, 1995; Nohria & Eccles, 1992). A team collaborating to develop a new product or service may require rich, intense forms of face-to-face communications at the beginning of a project in order to lay the groundwork for subsequent virtual project work (Davenport, 1997). Moreover project teams must develop shared mental models of their task domain and the specific behaviors expected of them in working with other team members (Cooke, et al., 2000) The need for shared understanding among virtually connected team members stretches traditional ideas not only about team performance but also about organizational culture and employee participation. New collaborative software is by itself far from enough.

In sum, the challenges to team-based collaboration are not only technological, but also managerial. Effective collaboration generally requires a greater degree of trust among project participants when their work is computer-mediated, insofar as workers cannot directly observe the actions of their team members and develop team cohesion through normal team-building processes of face-to-face interaction (Zuboff, 1982). The problem is exacerbated within project teams whose members have not previously worked together, insofar as trust must be created swiftly at the onset of the project (Meyerson, et al., 1996). Without trust between team members and their project supervisors, companies and their HR managers are constrained to implement potentially intrusive and time-consuming work monitoring and behavioral control practices that may reduce the self-organizing flexibility and speed of response of project teams (Soderlund, 2000). Moreover, the larger organization structures within which project work occurs is a stra tegic HR challenge, to which we now turn.

Organizational Models for Project Work

The new economy exerts competitive and market pressures on companies to organize themselves flexibly, in order to maximize the advantage of their human capital. Companies need the capacity for rapid self-organization into new combinations of human capital, as well as the protection from falling back into rigid, self-perpetuating structures. Project-based organization (PBO) refers to a variety of organizational models that address both of these needs (DeFillippi & Arthur, 1998; Hobday, 2000; Turner & Keegan, 2001). PBOs involve the creation of temporary organizations or sub-units for the performance of project-based tasks. Upon completion of the project, the temporary organization or sub-unit is dissolved and its participants move on to new projects, involving new human capital arrangements. The project-based organization is seen by some as promoting highly mobile talent that can self-organize in response to project opportunities and requirements: "The ultimate innovative organization is a free floating pool o f talent that moves into any project at any time, based on market-like interactions" (Quinn et al., 1997, p. 132).

Project-based organizing of company operations is found in a wide range of industries. Typical industry settings for such enterprises include consulting and professional services (e.g., management consulting, accounting, law, architectural design, public relations), cultural industries (e.g., fashion, film making, theater, publishing) high technology (e.g., software, multimedia), and complex products and systems (e.g., construction, transportation, communications, infrastructure). Evidence is, however, accumulating that firms in more traditional manufacturing industries are also catching on. For example, Oticon Holding A/S, the Danish manufacturer of hearing aids, has since the early 1990s been organized as a collection of over 100 projects, in which each employee may be simultaneously working on several projects. The top management team works as project owners, and offers project advice and consultation if requested by company project teams (Larsen, 2002, in this issue).

Project-based organizational models first achieved notoriety in the 1960s with the rise of matrix forms of management for aerospace (i.e., NASA space projects) and other high-technology innovative projects (Galbraith, 1973). Matrix management involved the creation of an authority structure for the management of project resources that complemented the functional authority structure for the management of departmental resources. Larson and Gobeli (1987) later discerned three types of matrix organization: the functional matrix, which subordinated project resource management activities within the authority of one or more functional managers, the balanced matrix, where responsibilities and authority for each project were shared between functional and project managers, and the project matrix, where the project manager was the undisputed manager of all project resources.

Project-based organizational models of more recent vintage (DeFillippi & Arthur, 1998; Hobday, 2000) tend to relegate functional management (including human resource management) to the support of projects and project managers and thus tend toward the project matrix end of the organizational continuum. Such models create both new capabilities (flexibility in resource use for creative, innovative task performance) but also new challenges for project managers and the human resource function. Several contemporary examples follow.

DeFillippi and Arthur (1998) describe the project-based enterprise organizational form in which all the functions of a product organization are internally located within a temporary project structure. Such temporary organizations are found within cultural industries (film-making, theater) and sometimes within professional services (e.g., public relations, conference management). Generally, such enterprises are relatively small in size (less than 150 people), and the entire organization functions as an interdependent network of project teams (sometimes referred to as crews). Within such organizational settings, human resource management functions are decentralized through a cascading set of appointments of team leaders, each of whom in turn selects his or her team members based upon past experience or referral networks. Participants in such project-enterprise-based organizations and industries tend to have careers that involve mobility across employing organizations in search of more significant project opport unities associated with greater status, visibility, and economic returns (Jones & DeFillippi, 1996). Human resource management as a functional discipline tends not to evolve for such small-scale, adhocracy organizational forms (Mintzberg, 1979)

By contrast, Hobday (2000) describes project-based organization structures used by large corporations in which the project is the primary business mechanism for coordinating and integrating all the main business functions of the firm (including human resource management). Thus, it is similar to the project-based enterprise form (DeFillippi & Arthur, 1998). These PBOs are temporary creations, either as a temporary unit within a larger corporation, or as a temporary coalition of companies, typically led by a firm acting as a system integrator or prime contractor (Gann & Salter, 2000). In both forms of PBO, the project sponsoring company has in place its own human resource management capabilities and the project participants in PBOs are thus subject to the HR practices of their sponsoring organization as well as the demands of their project organization. Such organizations must thus cope with the HR challenge of divided loyalties to project and functional units that HR managers have long faced in matrix manageme nt organizations (Galbraith, 1973). Such loyalty challenges become exacerbated when project participants hold loyalties to disparate sponsoring companies and have personalized loyalties to client organizations (Grabher, 2002).

For all these project-organization forms, two additional HR challenges involve the management of knowledge and careers. Although project organizations offer the flexibility of uniquely combining human resources for innovative projects, such organizations report a common challenge in their attempts to retain the knowledge and lessons learned from past projects for re-use in future projects (Gann & Salter, 2000; Prencipe & Tell, 2001). Much of the knowledge created within projects is embodied in the tacit experiences of project members and such knowledge is imperfectly codified for wide-spread dissemination and re-use (Davenport & Prusak, 1998).

Moreover, the placement of project participants in subsequent projects is a staffing challenge for HR managers in large-scale companies, where hundreds of projects may be occurring simultaneously. Younger and newer recruits in one project-based company reported concerns over career development and professional advancement because of the dispersion of technical leadership across projects (Hobday, 2000). Related to this concern was the perceived lack of incentives within the project-based organization for HR development. Senior technical managers reported fewer incentives to groom and mentor junior engineers after the firm reorganized from a functionally based matrix to a project-based organization (Hobday, 2000).

In summary, project organizations may fail to provide an effective focal point for the accumulation and transfer of either project wisdom or career guidance. Increasingly, the regionally based industry community of fellow project workers and organizational partners becomes a context and repository for project and career relevant knowledge (Sydow & Staber, 2002). We next review the regionally based industry community as a context for project collaboration in the new economy and the regional implications for HR development by regional institutions.

Regional Collaboration and Industry Communities

Despite the opportunity for virtual communication, much successful project collaboration in the new economy occurs within geographically concentrated industry clusters or communities (Castells, 2000; Best, 2001). Such industry clusters or communities economize on the transaction costs of searching and selecting collaborative partners. Also, the geographic proximity of collaborative partners facilitates continuous monitoring of partner contributions and makes possible face-to-face interactions when needed (Grabber, 2001).

Regional agglomeration of potential project collaborators also makes possible the creation of informal communities of practice (Wenger, 1998) that not only disseminate knowledge of technical practices but also maintain a code of conduct. Such community-based shared beliefs and standards of practice facilitate project-based collaboration by reducing the uncertainty surrounding the swift formation of new project teams and organizations (Meyerson, et al., 1996).

Hence, project collaboration within a regional industry community (e.g., San Jose's Silicon Valley, Boston's Route 128, or London's Soho media cluster) is facilitated by the existence of dense networks of cooperative relations among knowledge-creating companies and institutions (such as universities and government research laboratories). This cooperation includes not only project collaboration but also knowledge about technological advances within industries and occupations relevant to each company. Some of this external learning is absorbed into companies that recruit workers from within the region. Other times, this external learning is acquired through the process of collaboration with partner companies and institutions (Hendry, et al., 2000a, 2000b).

Best (2001) suggests that a new model of regional collaboration is providing significant competitive advantages to those companies and regions that embrace it. This new model includes the following elements. First, there is an integration of diverse systems of technology from specialist suppliers as the driver of new product development. Second, networked groups of firms are linked by open systems product architecture. Third, basic research is integrated into a regional model of innovation and technical skill formation in which regional companies, universities, and government institutions cooperate. American examples of this regional collaborative model include Silicon Valley and Route 128. European and Asian examples of innovative milieus of regional collaboration include London (the M4 corridor), Milan, Paris Sud, Taipeo-Hsinchu in Taiwan, and Singapore (Castells, 2000).

In order for such regional communities of innovation to flourish, Best (2001) recommends that regionally based companies, educational and governmental institutions cooperate in fostering the development of a skilled workforce whose capabilities are on par with competing regional industry centers. Skill formation must include a wide range of capabilities, from entry-level industry technicians to university-level and post-graduate technology specialists. Finally, skill formation must also include internships and school-to-work programs that can foster a closer dialogue between regional educational institutions and regional employers.

Although regional clusters and industry communities have a relatively long and distinguished history in high technology, the most celebrated and discredited face of the new economy has been the rise and fall of dot.coms and related online business models. It is to these forms of business Web collaboration we now turn.

Business Webs and Dot.coms: New Economy Chaos?

The World Wide Web and the advent of e-commerce and e-business have fostered more extended webs of collaboration through electronic links among companies, independent contractors, and other stakeholders. These business webs incorporate project-based organizing principles within a larger constellation of inter-company collaborations (Tapscott, et al., 2000). A variety of Web-enabled organizational models have evolved to provide a means for companies and people to participate in creating value. These Web-enabled organizational models all involve the substitution of physical assets and co-location with the use of digital assets and Web-based coordination. During the late 1990s, venture capital markets, notably in the United States, provided lavish funding for a wide variety of such Web-based business models. Although some of the entrants were established companies with substantial physical assets and capabilities, (e.g., Cisco, Dell), the overwhelming majority of business entrants were start-up ventures fueled o n imaginative business models (largely untested) and championed by charismatic entrepreneurs (tending to be young and technically skilled). These Web business entrepreneurs frequently made bold promotional and marketing claims (lacking in historical evidence), backed by their financiers, that old-economy rules of business were obsolete and that new rules applied to the Web-based new economy (Martin, 2001).

Since approximately March 2000, the Internet-based sector of the new economy has suffered a significant loss of market value. The initial cause of market downturn appeared to be the irrational exuberance of investors in so-called dot.com companies (see Verkinderen and Altman in this issue). This burst of the new-economy bubble has been followed more recently by the catastrophic bankruptcies of such leading new-economy firms as energy and commodities business web conglomerate Enron and telecommunications giant World Com, and countless smaller dot.com start-ups.

Many of the dot.com failures can be criticized for their flawed financial management and subsequent miscommunication of financial and market performance to interested stakeholders, including the investment community. The opaque financial and marketing activities of some dot.com companies provided poor benchmarks for assessing past performance or predicting future performance. By the time market indicators were available to company observers, these companies suffered significant financial losses, followed by even more catastrophic losses in reputations with putative resource suppliers, investors, and customers (Martin, 2001; Verkinderen & Altman, this issue).

From a human resource management perspective, the dot.coms of the late 1990s featured relatively young and inexperienced venture founders presiding over rapidly growing companies that were required to respond in so-called "Internet time" to unprecedented demands for rapid organizational change and transformation. Business models and business processes were created and abandoned with dizzying speed.

The impact of such rapid growth and change posed enormous challenges for HR planning, recruiting, and training of staff. Moreover, the reliance upon stock options as a major component of employee compensation and benefits created incentive problems when the Internet bubble burst and option values became almost worthless (Verkinderen & Altman, this issue).

Yet, successful companies that have adopted Web-based models of organization still exist. The most successful of these companies (e.g., Dell, Cisco) appear to have blended both old-economy virtues of tangible asset accumulation and coordination, with new-economy leveraging of the reach and richness of Web-based services and Web-based processes (Gulati & Garino, 2000). The successful management of human resources within these next-generation business web companies may well require an artful blending of old-economy and new-economy management practice.

Community Webs: Open Source Software and Linux

There are also examples of more durable forms of Web-based organizing whose relative success, in comparison to the more celebrated failures of their dot.com cousins, may offer some instruction. A particular example involves open source software (OSS). OSS projects allow interested parties to participate in the development, application, and testing of new software by making the source code for the software and its application software freely available. Such projects usually begin with someone posting on the Web a software kernel and inviting people to write hacks (software program instructions) to add to the kernel's functionality and to post these hacks back to the originator, typically on an open Web site. Others are invited to test the software for defects or errors (bugs) and to offer solutions (patches) back to the online Web site, which serves as a central clearinghouse for all volunteer software development activity.

OSS software projects, such as the series of projects behind the development of the Linux operating system, have become increasingly significant contributors to the software industry and the practice of open source software development. They stand in contrast to more traditional in-house proprietary software development, and are now employed by a growing number of major software providers like Netscape, and computer suppliers like IBM (Economist, 2001). Insofar as these projects are created by a community of volunteer participants, we denote such organizations as community webs in contrast to the strictly commercial business webs discussed previously.

Gallivan (2001) suggests that the relative success of community-web-organized OSS projects results in large part from the operation of implicit control mechanisms. These serve to increase confidence that community participants will behave cooperatively and subsequently produce trust in Web-based exchange and cooperation. A prominent example involves the OSS community behind the previously mentioned Linux operating system. How does this community gain control over partner contributions, and in turn create trust in virtual collaboration? To begin, Linux and other longstanding open source communities tended to evolve explicitly defined roles for certain community members to perform within the business web. These roles included: (1) project leaders responsible for an overall open source project; (2) developers responsible for creating software codes for a project; and (3) bug detectors and testers of code who submitted problem reports (Gallivan, 2001). These roles correspond to equivalent roles in internal compan y software development projects, but the primary distinction is that these roles are typically voluntary and not subject to either corporate compensation or internal organizational control.

Thus, in place of corporate control there exists a reputation-based control system. Contributors to the success of early open source projects have their contributions attached to the resulting software project documentation. Coincident with explicit documentation is the creation of a market for reputation, in which past contributors to successful open source projects are recognized explicitly within electronic bulletin boards and their services solicited for future open source projects. This process is akin to job posting at a project-based company, such as Oticon (Larsen, this issue), with the important difference that job seekers for these projects are not employees of the project organization but unpaid volunteers.

Open source software projects appear chaotic, but there is an underlying order within their web of interactions. For example, Linux utilizes a work flow governed by the Linux kernel mailing list, which determines which developers receive messages regarding Linux projects. To help neophyte Linux community members participate appropriately, a FAQ document specifies rules of open source conduct and process and also reiterates the norms and values of the Linux community (Moon & Sproull, 2000).

Markus, et al. (2000) suggest that open source projects depend upon both self-control by participants (to preserve one's reputation) and social controls by peers, who can easily monitor member contributions and sanction inappropriate conduct. As a result of these diverse mechanisms of institutional rules, membership roles, self-controls and social controls, open source projects typically outperform conventional in-house software development projects in producing robust and reliable software (Raymond, 1998)

Moreover, open source projects are iterative and each project's performance generates knowledge about what worked and what did not. This is captured both in the project documentation and in the electronically facilitated e-mail conversations occurring within the community of open source project participants. As a result, a community of practice evolves in which open source project members share their project experiences, and these stories provide a narrative that promotes further community-level learning (DeFillippi & Arthur, 2002).

Commercial companies wishing to benefit from membership within open source communities face a daunting HR challenge. One company that has succeeded in aligning its HR practices with the open source community is Red Hat, a distributor of Linux operating system software and provider of Linux software technical support and consulting services. Red Hat maintains continuing external relations with key Linux software developers throughout the world. In a few cases, Red Hat employs key Linux software developers on a contract basis; however, these relations are more akin to a loose advisory relationship than a contract employment relationship. As described by Red Hat's engineering group director: "Our relationship with the (Linux) kernel developers is not so much one of active management direction, though we do tell them the kinds of things Red Hat cares about more than others" (MacCormack & Herman, 1999, 9).

In summary, Red Hat illustrates how commercial companies cultivate and maintain alliance-type relationships with open source communities in order to access the voluntary as well as paid contributions of the community's members. Indeed, the good will fostered by demonstrations of sympathy with open source community leaders may be viewed as more vital than the specific employment contracts with individuals within the community. Enlightened new-economy companies such as Red Hat strive to become embedded within such community webs as a trusted member. According to Red Hat's chief operating officer, Tim Buckley:

The last thing we want to do is start getting isolated from the [Linux] community, which we are accused of a bit, but only because we are getting bigger and have a reputation.... [It] makes us want to double our efforts. We...give everything back to the community. [We] have three or four of the top [Linux] kernel developers on our payroll and they're not developing Red Hat stuff --that's just another sign that we're trying to make sure the community and the kernel development remains solid. (MacCormack & Herman, 1999, 11)

New-Economy Workers and Human Resource Practices

In sum, the emergence of new-economy models of project-based and Web-based organizing is a mixed blessing for the HR function. These new-economy models call for just-in-time recruitment of outsourced workers and e-lancing contractors who may not necessarily be on the company's permanent payroll and are often not on the company's premises. Issues of loyalty and commitment are redefined in these more fluid, project-based employment relations. Adding to the challenge of the new economy is the generational divide between the "net generation" of young workers who have grown up in an electronic, virtual universe and the "baby boom" generation of managers and HR professionals who are transitioning from old-economy to new-economy organizational models and management practices. In many instances, the newest members of the new economy are more attuned to project-based and Web-based organizing than the very managers and HR professionals responsible for their performance.

The organization of work in the new economy is also creating opportunities for HR managers. A recent study examining the impact of new-economy "boundaryless" modes of organizing human resources found that offering workers the option of "going boundaryless" was a successful way of attracting and retaining qualified workers (Ceridian, 1999). The study found that more than half of the people surveyed said boundaryless work arrangements -- involving one or more of telecommuting, virtual teams, flexible time and pay plans, and temporary, project-based professionals -- are highly successful for attracting qualified workers, and 60 percent said the practices are successful in retaining employees.

Project-based and Web-based models of organizing will further affect how HR managers carry out their traditional roles of recruiting, staffing, training, compensation, and employee communications. Each of these processes will take full advantage of both the Web-based technology of the new economy and the changing nature of new-economy labor markets and employment relations (Snell, 1994; Cortada & Hargraves, 1999).

Recruiting for the new economy will involve accessing local, national, and even international databases in which both employers and employees post their requirements. Web-based job posting services provided by new-economy companies such as Monster.com have now become an important venue for temporary work job postings, and such labor market intermediaries will play a greater role in providing just-in-time employees for temporary projects and outsourced project assignments (Tapscott, et al., 2000). Even during the recent economic downturn, the Web has served as an electronic self-help network for unemployed dot.com workers (Corcoran, 2002).

Staffing in new economy companies will be based less on seniority or job description and more upon the fit between a project's skill and experience requirements and the project portfolio history of the applicant. Job posting will occur with greater regularity, and employees will compete for assignments on high status, high visibility projects. Moreover, new-economy employees will take much greater responsibility for managing their project-based careers and will seek out those projects that can help them achieve their subjectively defined career goals (Arthur, et al., 1995; Jones & DeFillippi, 1996).

Training emphasis will be placed on participating in temporary project teams. Moreover, new and old employees alike will need to be trained and retrained in using the latest electronic communications and collaborative tools such as groupware software to facilitate virtual project work. Indeed, the largest of the new-economy companies will be involved in global projects and thus global virtual team training will become a necessity (Lipnack & Stamps, 1997).

Compensation will increasingly focus on the ability of people to develop new skills required for their project assignments. Self-improvement in skill development will be rewarded both directly and by future assignment to higher priority projects. Compensation will also emphasize more pay for performance, with careful attention to team-based as well as individual contributions to project success (Gross, 1995).

Benefits will include a greater emphasis on cafeteria benefit plans in which people choose the set of benefits best suited to their personal needs and prerogatives within an established monetary limit for the total value of their compensation package. Such cafeteria plans will require employees to take much greater personal responsibility for their retirement futures. In the United States it is now possible for employees at many companies to self-monitor their benefit plans in real-time through Web-based access to their individual pension accumulations and related benefits. These Web-based benefit programs offer the ultimate in self-monitoring and self-management of employee benefits and are likely to become more attractive to younger knowledge workers and Web-savvy participants in the new economy (Tropman, et al., 2001).

Communications to employees will be less in print form and more often digital. Moreover, the content of these communications will be less standardized and more customized to particular requirements of the worker. Cookies linked to personnel Web sites will trigger specific forms of employee information that are high priorities for that individual. Hence, information technology will improve both the reach and customization of employee communications (Evans & Wurster, 2000).

Through these adaptations to new technology, HR managers have the opportunity to provide their work force with Web-enabled tools for them to self-manage their careers, training, compensation, and benefit packages; however, there is a distinction between applying new technology to established HRM practices on the one hand, and adapting HRM to new organizational models on the other hand. Some of the most technically capable workers model themselves after free-agent workers (Pink, 2001), linked to a broad network of project-relevant colleagues, coaches, sponsors, and global partners. Human resource managers would do well to facilitate and encourage such network linkages (as in the Red Hat example) rather than view such linkages as threats to company loyalty and retention.

Conclusion

The technology driving the new economy is constrained by neither company nor national borders, over which the ubiquitous World Wide Web is overlord. Compressed cycle times and the demand for flexibility mean that rigid organizational routines -- the hallmark of Fordist success -- now destroy rather than create organizational value. Project-based organizing provides a means for companies to avoid the pitfalls of the past. But project-based organizing has profound implications for company learning, which becomes at once more critical to company success. Regional collaboration may continue to provide a degree of face-to-face communication that Web-based communications lack; however, this form of collaboration shifts the focus from the individual company to the region as a whole as the source of relevant skills and knowledge.

The mixed success of business webs and dot.coms raises questions about the further direction of e-business activities. Yet the parallel development of community webs, forged independently of their members' company affiliations, suggests a more enduring model for people's occupational learning. New-economy work is collaborative and such collaboration encompasses the multiple work contexts of individuals, teams, companies, and industry and Web-based communities. Human resource management for such new economy work and workers must similarly expand its horizons to incorporate these dynamic multiple contexts.

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Biographical Sketch

Robert DeFillippi is a professor of management and the academic director for entrepreneurial studies at the Sawyer School of Management, Suffolk University, Boston, and associate research fellow, Innovation Center for Complex Products and Systems, Science Policy Research Unit, Sussex University, Brighton, England. He specializes in understanding how the new economy is creating opportunities for organizing innovative and creative careers, companies, and industry-based clusters. His research includes studies of global industry practices in optoelectronics, software, filmmaking, and business and financial services. He is widely published in leading journals and books in management. Additionally, he is the book series editor for Research in Management Education and Development and is past chair of the Academy of Management's Management Education and Development division.