Technical developments in electronic communication, computing, and decision support, coupled with new interest on the part of organizations to improve meeting effectiveness, are spurring research in the area of group decision support systems GDSS. A GDSS combines communication, computing, and decision support technologies to facilitate formulation and solution of unstructured problems by a group of people. This paper presents a conceptual overview of GDSS based on an information-exchange perspective of decision making, Three levels of systems are described, representing varying degrees of intervention into the decision process. Research on GDSS is conceived as evolving over time from the study of simple "shell" systems, consisting of menus of features available for selection by a group, to consideration of sophisticated rule-based systems that enable a group to pursue highly structured and novel decision paths. A multi-dimensional taxonomy of systems is proposed as an organizing framework for research in the area. Three environmental contingencies are identified as critical to GDSS design: group size, member proximity, and the task confronting the group. Potential impacts of GDSS on group processes and outcomes are discussed, and important constructs in need of study are identified.

A foundation for the study of group decision support systems

Research in organizational learning has demonstrated processes and occasionally performance implications of acquisition of declarative (know-what) and procedural (know-how) knowledge. However, considerably less attention has been paid to learned characteristics of relationships that affect the decision to seek information from other people. Based on a review of the social network, information processing, and organizational learning literatures, along with the results of a previous qualitative study, we propose a formal model of information seeking in which the probability of seeking information from another person is a function of (1) knowing what that person knows; (2) valuing what that person knows; (3) being able to gain timely access to that person's thinking; and (4) perceiving that seeking information from that person would not be too costly. We also hypothesize that the knowing, access, and cost variables mediate the relationship between physical proximity and information seeking. The model is tested using two separate research sites to provide replication. The results indicate strong support for the model and the mediation hypothesis (with the exception of the cost variable). Implications are drawn for the study of both transactive memory and organizational learning, as well as for management practice.

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A Relational View of Information Seeking and Learning in Social Networks

What are the positive and negative consequences of telecommuting? How do these consequences come about? When are these consequences more or less potent? The authors answer these questions through construction of a theoretical framework and meta-analysis of 46 studies in natural settings involving 12,883 employees. Telecommuting had small but mainly beneficial effects on proximal outcomes, such as perceived autonomy and (lower) work–family conflict. Importantly, telecommuting had no generally detrimental effects on the quality of workplace relationships. Telecommuting also had beneficial effects on more distal outcomes, such as job satisfaction, performance, turnover intent, and role stress. These beneficial consequences appeared to be at least partially mediated by perceived autonomy. Also, high-intensity telecommuting (more than 2.5 days a week) accentuated telecommuting’s beneficial effects on work–family conflict but harmed relationships with coworkers. Results provide building blocks for a more complete theoretical and practical treatment of telecommuting.

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The good, the bad, and the unknown about telecommuting: meta-analysis of psychological mediators and individual consequences.

Effective work groups engage in external knowledge sharing-the exchange of information, know-how, and feedback with customers, organizational experts, and others outside of the group. This paper argues that the value of external knowledge sharing increases when work groups are more structurally diverse. A structurally diverse work group is one in which the members, by virtue of their different organizational affiliations, roles, or positions, can expose the group to unique sources of knowledge. It is hypothesized that if members of structurally diverse work groups engage in external knowledge sharing, their performance will improve because of this active exchange of knowledge through unique external sources. A field study of 182 work groups in a Fortune 500 telecommunications firm operationalizes structural diversity as member differences in geographic locations, functional assignments, reporting managers, and business units, as indicated by corporate database records. External knowledge sharing was measured with group member surveys and performance was assessed using senior executive ratings. Ordered logit analyses showed that external knowledge sharing was more strongly associated with performance when work groups were more structurally diverse. Implications for theory and practice around the integration of work groups and social networks are addressed.

Work Groups, Structural Diversity, and Knowledge Sharing in a Global Organization

People use weak ties---relationships with acquaintances or strangers---to seek help unavailable from friends or colleagues. Yet in the absence of personal relationships or the expectation of direct reciprocity, help from weak ties might not be forthcoming or could be of low quality. We examined the practice of distant employees (strangers) exchanging technical advice through a large organizational computer network. A survey of advice seekers and those who replied was conducted to test hypotheses about the viability and usefulness of such electronic weak tie exchanges.Theories of organizational motivation suggest that positive regard for the larger organization can substitute for direct incentives or personal relationships in motivating people to help others. Theories of weak ties suggest that the usefulness of this help may depend on the number of ties, the diversity of ties, or the resources of help providers. We hypothesized that, in an organizational context, the firm-specific resources and organizational motivation of people who provide advice will predict the usefulness of advice.We investigated these theories in a study of employees of a global computer manufacturer. We collected survey and observational data on the relationships between information seekers and information providers; the number, diversity, resources, and motivations of information providers, and subjective ratings of the usefulness of the advice (from both parties in the exchange) and whether or not the advice solved information seekers' problems.We found that information providers gave useful advice and solved the problems of information seekers, despite their lack of a personal connection with the seekers. The data support the main hypotheses and provide some support for resource and diversity explanations of weak tie influence. We discuss how this organization's culture sustained useful intormation exchange through weak ties.

The kindness of strangers : on the usefullness of electronic weak ties for technical advice

The proximity among people in an organization is known to exert considerable influence on a variety of organizational outcomes such as performance, stress, and job satisfaction. Early research on p...

The Dynamics of Organizational Proximity

Traditional measures of proximity all share three common weaknesses when applied to the study of human organizations: (a) they are based on linear physical distance rather than functional distance, (b) they measure distance as afixed rather than afluctuating quantity, and (c) they treat people as proximate to a single other person rather than to multiple others. A measure of proximity which attempts to deal with these problems for research in large organizations is developed in this paper. Proximity is defined as the probability of people being in the same location during the same period of time, i.e., as an opportunity for face-to-face communication made possible by people sharing a communication space and time. It is operationalized as a mean joint probability among all people in the organization. A computer program (PROXVAL) developed to calculate the required quantities is described. Data which demonstrate the usefulness of the procedure are reported.

Measuring Proximity in Human Organization

Research findings from the literatures of administrative science, communication network analysis, industrial and personnel psychology, sociometry, social psychology, and sociology were combined in ...

The Determinants of Communication and Communication Structure in Large Organizations: A Review of Research

This article reports the results of research efforts to develop and test two structural equation models of the antecedents of involvement in communication networks in large organizations, one for c

Determinants of Communication Network Involvement: Connectedness and Integration

Psychologists have long been interested in the role that proximity plays in determining various aspects of human behavior, such as communication and interaction (Festinger, Schacter, & Back, 1950; Newcomb, 1961), attraction (Kahn & McGaughey, 1977), and impression formation (Tesch, 1979). During the past decade, organizational psychologists have begun to explore the relationship of proximity to a variety of variables important to the work place, such as performance (Conrath, 1973), job satisfaction (Quinn, 1977), and organizational commitment (Conrath, 1973; Monge & Kirste, 1980). Monge and Kirste (1980) developed a definition and operationalization of proximity that is more appropriate for research in organizational contexts than are earlier methods developed from interpersonal studies. The definition contains three elements that distinguish proximity in organizations from the same construct in interpersonal settings: (1) that a person's proximity is usefully conceptualized in terms of meaningful work spaces that facilitate or inhibit the opportunity for faceto-face communication, (2) that each person in an organization is proximate to multiple others, and (3) that a person's proximity to these multiple others is dynamic and changes over time. The index developed for this definition provides the conditional probability of an individual's spending time in the same physical locations with each other person in the organization. It varies from 0, representing complete isolation from all other individuals, to 1, representing continuously sharing the same work space with all other individuals. A second index, indicating the proximity of each person to all others in the organization, can also be computed. Recently, Monge, White, Eisenberg, Miller, and Kirste (Note 1) reported research on the dynamics of "organizational proximity," an aggregate-level measure for an entire organization, which is defined as the degree to which people within an organization share the same physical locations during the same periods of time; there is assumed to be both the opportunity and psychological obligation to engage in face-to-face communication. Data were gathered in IS-min intervals for 1 workweek on the amount of time that employees spent in the different "locations" that constituted the entire organization. A single measure of organizational proximity indicating the "density" of people across all locations was computed for each of the 205 time periods for the week and subjected to time-series analysis. The results indicated both a significant daily variation in the congregation and isolation of people and a systematic day-to-day pattern. Since more than 50,000 data points are required to represent 2S0 people in different locations during a workweek, it is extremely helpful to have access to a computer program that computes the values of organizational proximity. Data collection typically requires that all individuals in the organization record the locations where they spend their time for predetermined intervals (e.g., each 15 min) over some period of time (e.g., a day, week). PROXTIME, the computer program described in this report, can be used to compute organizational proximity values for each (user-defined) time interval, as well as individual proximity values for each person. These values may be utilized in other analyses to test relevant theories and hypotheses.

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Kenneth K. Kirste

Papers

The Dynamics of Organizational Proximity

Measuring Proximity in Human Organization

The Determinants of Communication and Communication Structure in Large Organizations: A Review of Research

Determinants of Communication Network Involvement: Connectedness and Integration

Computing dynamic organizational proximity: The PROXTIME computer program