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Idaho State University and University of Idaho Introduction to Nuclear Engineering UI: NE 450 Principles of Nuclear Engineering ISU: NE 402 Fundamentals of Nuclear Science & Engineering Fall Semester 2009 August 25 – December 17 LECTURE  _1 Introduction Course Description A Few Basics / Chapter 1
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Task−Technology Fit for Mobile Information Systems
Judith Gebauer
University of Illinois at Urbana−Champaign
Michael J. Shaw Michele L. Gribbins
University of Illinois at Urbana−Champaign University of Illinois at Urbana−Champaign
Abstract
Mobile information systems (IS) hold great promise to support organizational processes.
Clear guidelines, however, of how to design effective mobile IS in support of organizational
processes have not been developed. Based on earlier research that emphasizes the importance
of fit between organizational tasks and technology and that develops fit profiles for specific
task−technology combinations, this paper develops a task−technology fit (TTF) profile for
mobile IS to support managerial tasks. We suggest a three−way match between dimensions
of managerial tasks, mobile IS, and the mobile use context. We find that use situations
characterized by high distraction and poor quality of network connection are particularly
challenging for the design of mobile IS, and that the user interface requires particular
attention. The proposed conceptual model of task−technology fit provides guidelines for the
design of effective mobile IS and for future research studies.
This working paper replaces 2005 Working Paper #05−0119
Published: 6/26/2006
URL: http://www.business.uiuc.edu/Working_Papers/papers/06−0107.pdfTask−Technology Fit for Mobile Information Systems
Judith Gebauer
University of Illinois at Urbana−Champaign
Michael J. Shaw Michele L. Gribbins
University of Illinois at Urbana−Champaign University of Illinois at Urbana−Champaign
Abstract
Mobile information systems (IS) hold great promise to support organizational processes.
Clear guidelines, however, of how to design effective mobile IS in support of organizational
processes have not been developed. Based on earlier research that emphasizes the importance
of fit between organizational tasks and technology and that develops fit profiles for specific
task−technology combinations, this paper develops a task−technology fit (TTF) profile for
mobile IS to support managerial tasks. We suggest a three−way match between dimensions
of managerial tasks, mobile IS, and the mobile use context. We find that use situations
characterized by high distraction and poor quality of network connection are particularly
challenging for the design of mobile IS, and that the user interface requires particular
attention. The proposed conceptual model of task−technology fit provides guidelines for the
design of effective mobile IS and for future research studies.
Published: 6/26/2006
Entered: June 26, 2006.Task-Technology Fit for Mobile Information Systems

Judith Gebauer, Michael J. Shaw, Michele L. Gribbins
{gebauer|mjshaw|mgribbin}@uiuc.edu

University of Illinois at Urbana-Champaign
College of Business
Department of Business Administration

350 Wohlers Hall
1206 South Sixth Street
Champaign, IL 61820

Last updated: June 21, 2006

Abstract
Mobile information systems (IS) hold great promise to support organizational processes. Clear guidelines,
however, of how to design effective mobile IS in support of organizational processes have not been
developed. Based on earlier research that emphasizes the importance of fit between organizational tasks
and technology and that develops fit profiles for specific task-technology combinations, this paper
develops a task-technology fit (TTF) profile for mobile IS to support managerial tasks. We suggest a
three-way match between dimensions of managerial tasks, mobile IS, and the mobile use context. We find
that use situations characterized by high distraction and poor quality of network connection are
particularly challenging for the design of mobile IS, and that the user interface requires particular
attention. The proposed conceptual model of task-technology fit provides guidelines for the design of
effective mobile IS and for future research studies.
Keywords: Mobile information systems, managerial tasks, task-technology fit
1Motivation
The relationships among technology, organizational processes, and performance are of great
interest to organizational researchers (Orlikowski 2000). Technologies now exist that enable employees
to “stay close to their local situations while engaging in global activities critical to their company’s
sustainability (Malhotra and Majchrazk 2005).” One such technology is mobile information systems (IS).
The ubiquitous nature of mobile IS provide new opportunities, issues and challenges (Lyytinnen and Yoo
2002a, 2002b) to organizations as they adopt these new technologies into their processes with the hopes
of enhancing performance. While mobile IS that are deployed to support an increasingly mobile
workforce promise to improve organizational processes (Balasubramaniam, Peterson, and Jarvenpaa
2002; Computerworld 2003), many questions remain concerning technology development, applications
and business models (Agrawal, Chari, and Sankar 2003; Smith, Kulatilaka, and Venkatraman 2002;
Tarasewich, Nickerson, and Warkentin 2002; Zhang, Yuan, and Archer 2003). In particular, the
requirements of mobile IS to adequately support mobile professionals have not been identified
systematically.
This paper integrates earlier research in the areas of organizational tasks, mobile technology, and
task-technology fit in order to develop a profile of task-technology fit (TTF) for mobile IS, with the intent
to contribute to the effectiveness and success of mobile IS in organizational settings. More specifically,
we hope to identify areas where the deployment of mobile IS can be considered particularly promising or
difficult to achieve due to the use context. Our results help assess and explain the success of mobile IS
applications within organizations, while providing conceptual guidelines for system development. In
addition, our systematically derived propositions comprise a research framework that can guide future
research studies. In the following, we first discuss our conceptual bases of earlier research publications of
task-technology fit, managerial tasks and mobile IS. We then develop a profile of task-technology fit for
mobile IS, discuss the implications of our propositions, draw a number of conclusions, and point out
avenues for future research.
2Two Theories of Task-Technology Fit
Two largely independent theories of TTF have emerged. The first, initiated by Goodhue and
Thompson (1995), established TTF as an important concept in assessing and explaining IS success. The
second, initiated by Zigurs and Buckland (1998), developed a systematic profile for the task-technology
combination of group tasks and group support systems (GSS). While Goodhue and Thompson (1995)
focused on individuals’ use of IS and presented a primarily positivistic research approach applicable to IS
in general, Zigurs and Buckland (1998) focused on groups’ use of IS and formulated fit profile applicable
specifically to GSS. Both streams are reviewed next.
Task-Technology Fit to Explain IS Success
Goodhue and Thompson (1995) proposed a comprehensive technology-to-performance model
that included characteristics of information technology, tasks, and of the individual user as explanatory
variables for technology use and for individual performance. A simpler version of the technology-to-
performance model, referred to as the TTF model, found moderate empirical support for the direct links
between task and technology characteristics and user-perceived TTF. Results confirmed that TTF and
usage together better explained the impact of information technology on individual performance (i.e.,
user-perceived accomplishment of individual tasks) than usage alone.
Related studies broadly confirmed the relevance of the TTF construct to assess the value of an IS
(Goodhue 1995) and to assess and predict system usage (Dishaw and Strong 1998) and individual
performance (Goodhue et al. 2000). Staples and Seddon (2004) confirmed that the technology-to-
performance model can explain performance for both mandatory and voluntary use settings. Different
aspects of TTF have been confirmed relevant for IS in general (Ferratt and Vlahos 1998, Goodhue 1995,
Goodhue 1998, Goodhue et al. 1997, and Goodhue and Thompson 1995), as well as for specific
technologies (Dishaw and Strong 1998, 1999; Goodhue et al. 2000), and for a variety of tasks (Dishaw
and Strong 1998, 1999; Ferrat and Vlahos 1998; Goodhue 1995, 1998; Goodhue and Thompson 1995;
Goodhue et al. 1997, 2000; Majchrzak, Malhotra and John 2005; Staples and Seddon 2004).
3In summary, we note that this stream of research corroborated the relevance of the TTF concept
in explaining and predicting IS success for individual performance. Since no systematic bias has been
identified regarding the relevance of TTF for different types of IS, we assume that TTF is a valid
construct to explain the success of mobile IS, yet we also take note of the need to include into the analysis
the particularities of mobile technology as compared to non-mobile technology, such as the individual use
context. The basic idea of TTF has been considered in mobile IS research studies (Gebauer and Shaw
2004, Junglas and Watson 2003, Liang and Wei 2004), but has not been integrated systematically. A
limiting aspect to our research objective is the fact that Goodhue and Thompson (1995) focused more on
the relevance of the TTF concept to explain individual performance. The systematic analysis of
requirements to achieve fit for particular combinations of tasks and technology, however, achieved less
attention, an aspect that is addressed by the second stream of research.
Task-Technology Fit for Group Support Systems
Building on earlier research work on organization and group processes, Zigurs and Buckland
(1998) developed a theory of TTF to support the development and deployment of GSS to support group
tasks. Assuming that a good fit between tasks and technology would result in good group performance,
the authors defined fit as “ideal profiles composed of an internally consistent set of task contingencies and
GSS elements that affect group performance (p. 323).” Performance was viewed generically as the
accomplishment of group goals to be operationalized for individual task situations. Five categories of
group tasks were identified (simple, problem, decision, judgment, and fuzzy) as well as three technology
support dimensions (communication, process structuring, information processing support). Finally, a set
of fit profiles was developed (e.g., “Simple tasks should result in the best group performance … when
done using a GSS configuration that emphasizes communication support”), which was later tested and
largely confirmed by Zigurs et al. (1999).
Research studies building on Zigurs and Buckland’s (1998) theory of TTF generally sought to
improve the support of collaborative and group tasks to be conducted in various circumstances, with a
variety of group support technologies (Barkhi 2001-2002, Dennis, Wixom and Vandenberg 2001,
4Massey, Montoya-Weiss, Hung and Ramesh 2001, Murty and Kerr 2004, Sussman, Gray, Perry and Blair
2003). Jahng, Jain and Ramamurthy (2000) applied a similar concept in the area of electronic commerce,
but overall, Zigurs and Buckland’s (1998) theory of TTF has mostly been applied to collaborative
technologies. Research has found that not all tasks that a group might undertake are best supported by
collaborative technologies (see Malhotra and Majchrzak 2004; Wittenbaum, Hollingshead and Botero
2004).
Towards a Profile of TTF for Mobile IS
To develop a profile of TTF for mobile IS, we apply the concept of task-technology fit to
managerial tasks, supported by IS in a mobile use context, using task performance as a proxy of system
success. Similar to Zigurs and Buckland (1998), we consider TTF as pre-defined profiles, which we
develop in a three step process. Profiles have the benefit of being specific about the suggested areas of
application and the identification of potential problems while outlining a research agenda. We first look at
the main constructs and then describe the steps to derive TTF for mobile IS.
Managerial tasks
As managers are among the most mobile employees in organizations and many current
applications of mobile technology do in fact target managers (Computerworld 2003), a focus on
managerial tasks is warranted for the analysis of mobile IS. Managerial research studies have frequently
used two dimensions to describe managerial tasks: task non-routineness (ranging from low to high) and
task interdependence (ranging from low to high). In the context of mobile IS, a third dimension, time-
criticality (ranging from low to high), appears to be relevant.
Task Non-Routineness
The concept of task non-routineness has a long history in management research. Anthony (1965)
categorized managerial activities based on the degree of (non-)routineness (operational control,
managerial control, strategic planning), followed by Gorry and Scott Morton (1971) who linked the
degree of structure with different organizational levels of managerial decision making and stated that
lower degrees of structure (routineness) are associated with higher levels of management. In an analysis
5of how humans solve problems, Simon (1960) found the level of structure (routineness) of a task to be
manifested in characteristics such as repetitiveness and novelty, and to determine the ease with which
managerial decision making can be programmed (automated) or requires judgment and intelligent,
adaptive, problem-oriented action. Perrow (1967) described organizational technologies according to the
number of exceptions to be handled and the degree to which a search procedure is analyzable (i.e., relying
on past experiences and previously developed concepts and routines) or unanalyzable (i.e., not logical or
unanalytic, often reverting to intuition, chance, and guesswork). According to Perrow (1967), non-routine
technology is best applied to situations with large numbers of exceptions and unanalyzable search results,
while routine technology is best applied to situations with few exceptions and analyzable search results.
Van de Ven and Ferry (1980) distinguished between two dimensions of task structure: task variability
(e.g., number of exceptions), and task difficulty (e.g., analyzability and predictability). Ahuja and Carley
(1999) classify tasks by their analyzability and variety, defining task analyzability as “the extent to which
a task can be broken down into small, well-defined components” and task variety as “the extent to which
there is variation in the task over time.” Since in practice, task variety and difficulty (analyzability) were
correlated and difficult to distinguish, some researchers have combined the two variables into a single
dimension, termed task-non-routineness (Daft and Macintosh 1981, Karimi et al. 2004), a concept that we
follow in the current paper.
Based on previous research studies of management, we view task non-routineness as the level of
structuredness, analyzability, difficulty and predictability of a task. Tasks of low non-routineness (high
routineness) include the processing of travel expenses or the procurement of standard items, whereas
tasks of high non-routineness are typically more difficult to accomplish (e.g., strategic planning, solving
of unique problems, and managerial decision-making). The completion of non-routine tasks are a
common challenge for distributed teams (Majchrzak, Malhotra and John 2005).
Task Interdependence
Identified as a second dimension of managerial tasks (Goodhue and Thompson 1995, Karimi et
al. 2004), task interdependence has been defined as the exchange of output between segments within a
6subunit and with other organizational units (Fry and Slocum 1984). Interdependence requires
coordination between activities (Malone and Crowston 1994) and, thus, lends itself well to technological
support. Research on task interdependence dates back to Thompson (1967) who was concerned with
different mechanisms to achieve organizational coordination. Thompson (1967) proposed that different
types of interdependence (e.g., pooled, sequential, reciprocal) existed that required different coordination
mechanisms (e.g., standardization, plan, and mutual adjustment) depending on the technologies applied in
an organization. For example, when interdependence increased from pooled to sequential to reciprocal,
coordination mechanisms should change from rules to standardization to mutual adjustment, as the later
required a greater amount of communication as a means for coordination (Thompson 1967). Thompson’s
(1967) three interdependency types are thought to contain “increasing degrees of contingency,
coordination difficulty, and cost” (Barki and Pinsonneault 2005).
We include task interdependence into our analysis as the degree to which a task is related to other
tasks and organizational units, and as a result the extent to which coordination with other organizational
units is required (Thompson 1967). The level of interdependence determines the user’s need to obtain
access to an IS to perform a task as part of a larger whole, which has a direct impact on users’
performance and an indirect impact on the performance of others (Gebauer and Shaw 2004). Highly
interdependent tasks, such as the development of an advertising campaign, require process actors to
interact extensively to generate the desired outcome, while a task having no interdependence, such as
telemarketing, can be executed entirely by one person (Wageman and Gordon 2005). Interdependence
can be operationalized with the number of regular communication channels and partners that a user
interacts with, the pattern of interaction between tasks and resources that are consumed and produced
jointly or individually (Crowston 2003), or the level of connectedness (e.g., Gantt-diagram).
Time Criticality
Time criticality, defined as the importance with which a task needs to be performed promptly
(urgency) depicts the dynamics of managers’ work environments and tasks. Even though time criticality
has generally received limited attention by scholars of organization science, the ability of organizations to
7respond quickly to changing market requirements has been discussed in management and strategy
research (D’Aveni 1994, Bradley and Nolan 1998). For example, Straub and Karahanna (1998) found that
the urgency (time-criticality) of communication tasks influence communicators’ preferred type of media
(synchronous vs. asynchronous) selected to support the task.
The concept of time-criticality has also captured the attention of scholars of mobile IS. Junglas
and Watson (2003) described time-dependency as relevant to mobile commerce, while Balasubramaniam,
Peterson and Jarvenpaa (2001) mentioned time criticality as an important dimension of mobile systems.
Liang and Wei (2004) suggested that mobile commerce was well suited for emergency and time-critical
services (similar: Yuan and Zhang 2003), while Siau, Lim and Shen (2001) stated that mobile
technologies provide immediacy. Jarvenpaa, Lang, Takeda, and Tuunainen (2003) found that users’ value
of mobile devices and services revealed their desire to obtain rapid feedback. Venkatesh, Ramesh and
Massey (2003) concluded that time-criticality as a trigger for use might be more important in wireless
than in wired environments, which could explain why time-criticality has not found more consideration in
organization literature. In practice, support for urgent tasks (e.g., notification of emergency situations) has
been among the earliest applications of mobile technologies (Ammenwerth, Buchauer, Bludau and Haux
2000).
Mobile IS
Research on mobile IS has evolved in recent years. Scholars have provided conceptual overviews
of the industry value chain (Barnes 2002), identified development and research issues (Tarasewich,
Nickerson and Warkentin 2002, Varshney, Malloy, Jain and Ahluwalia. 2002, Varshney and Vetter
2001), conceptualized business models for telecommunication services providers, devices and
applications (Haaker et al. 2004, Varshney and Vetter 2001), identified strategies for system development
(Kemper and Wolf 2003, Krogstie et al. 2004), and detailed development cost and infrastructure standards
(Balasubramaniam et al. 2001). To develop a profile of TTF for mobile IS, we focus on studies that
emphasize the user perspective, and characterize mobile IS along three dimensions: functionality, user
interface, and adaptability (similar: Siau and Shen 2003). Functionality is conceptualized to be applicable
8