Arvind Karunakaran

Toward a model of collaborative information behavior in organizations

There is increasing interest in topics at the nexus of collaboration and information behavior. A variety of studies conducted in organizational settings have provided us with key insights about the collaborative aspects of seeking, retrieving, and using information. Researchers have used a range of terms, including collaborative information seeking (CIS), collaborative information retrieval (CIR), collaborative search, collaborative sensemaking, and others to describe various pertinent activities. Consequently, we lack conceptual clarity concerning these activities, leading to a tendency to use terms interchangeably when in fact they may be referring to different issues. Here, we offer collaborative information behavior (CIB) as an umbrella term to connote the collaborative aspects of information seeking, retrieval, and use. We provide the contours of a model of CIB synthesized from findings of past studies conducted by our research team as well as other researchers. By reanalyzing and synthesizing the data from those studies, we conceptualize CIB as comprised of a set of constitutive activities, organized into three broad phases—problem formulation, collaborative information seeking, and information use. Some of the activities are specific to a particular phase, whereas others are common to all phases. We explain how those constitutive activities are related to one another. Finally, we discuss the limitations of our model as well as its potential usefulness in advancing CIB research.

Barriers to collaborative information seeking in organizations

There has been a growing interest within the information sciences and HCI communities to understand the role of collaboration in facilitating information seeking. This focus had led to the emergence of the research area of collaborative information seeking (CIS). Although researchers are starting to identify various activities and mechanisms that underlie CIS, we know very little about the barriers to CIS. In this study, we used Mechanical Turk (MTurk) to gather data from 307 participants to understand the barriers to CIS in organizations. Through our data analysis, we identified a variety of barriers that hinder CIS. These barriers fell under four broad categories – organizational, technical, individual, and team. These barriers also had a strong temporal component which we highlight in the discussion. From these findings, we discuss some design implications for information retrieval systems.

Process-based ideology of participative experimentation to foster identity-challenging innovations: The case of Gmail and AdSense:

Prior research has examined how organizational identity can enable and constrain innovations. A complementary literature has examined organizational ideology as the basis for actions driving identity-enhancing innovations. We examine how organizational ideology can serve as the basis for identity-challenging innovations through an in-depth study of the emergence of two innovations at Google—Gmail and AdSense. Findings from this study highlight a process-based ideology of participative experimentation. We explicate the constituent elements of this process-based ideology, and discuss its implications for research on innovation and identity.

A Platform for Recombining Process Knowledge Chunks

We describe ReKon, a platform that contains fine-granular templates, each describing a process knowledge chunk, which may be combined, as needed, to support ad hoc processes needed in large projects. The platform allows user-lead (re)-construction of a process to deal with the unique and emergent needs of a project by leveraging prior knowledge encoded in process chunks. We have populated ReKon with process chunks created from more than 1200 real-world project templates contributed by four consulting organizations. The fine-granularity of process chunks contained in ReKon represents a direct response to the emergent nature of large projects that defies high-volume production processes. The paper develops the underlying meta-model and operations for ReKon that adapt and extend the combination quadrant in Nonaka and Takeuchi’s knowledge creation framework. A two-phase evaluation illustrates the need for ReKon and points to its potential usefulness.