Task-Technology Fit (TTF)

In IS research, the concept of Task-Technology Fit (TTF) has assumed various definitions. The numerous TTF definitions that have been used in TTF research are summarized in Table 4.1.

Table 4.1. Definitions of Task-Technology Fit (TTF)

Definition Source

The degree to which available technology is useful in supporting the unique needs of a given task.

Nance (1992, p. 50)

The degree to which technology assists an individual in performing his or her portfolio of tasks.

Goodhue and Thompson (1995, p. 216)

The degree to which a technology does or could meet user needs. Goodhue, Littlefield and Straub (1997, p. 458)

The matching of the functional capability of available information technology with the activity demands of the task at hand.

Dishaw (1994, p. 36), Dishaw and Strong (1998, p.

154)

The extent to which tasks can be performed effectively and efficiently using particular technologies.

Mathieson and Keil (1998, p. 222)

User perceptions of the fit of systems and services used based on personal task needs.

Pendharkar, Khosrowpour and Rodger (2001, p. 84)

The match or congruence between an information system and its

The perception that system capabilities match user task requirements. Jarupathirun and Zahedi (2007, p. 945) The degree to which an organization’s information systems functionality and

services meet information needs of the task.

Wu, Shin and Heng (2007, p. 168)

Ioiomo and Aronson (2003) observed that as the gap between task requirements and technological support capacity increases, ‘Fit’ significantly decreases (p. 197). This gap signifies an ‘under-fit’ or ‘over-fit’. An ‘under-fit’ represents minimal capacity because the technology used does not sufficiently meet task requirements and is rendered ineffective. Conversely, an ‘over-fit’ represents excessive technological support capacity because the technology provides excessive resources, thereby causing IT ‘slack’ (Gupta, 2003). Thus ‘fit’ technology represents sufficient supporting capacity to meet user needs (Nance and Straub, 1996). Since the inception of TTF theory, a clear distinction between research at the individual and group levels has been observed. At the individual level, survey methods have often been used. For example, to assess impacts of TTF on utilization and performance outcomes, Goodhue (1998) surveyed 357 technology users across ten companies. However, at the group level, experimental studies have often been conducted. For example, Fuller and Dennis (2004) conducted a longitudinal experiment to assess TTF effects on group performance. As such, TTF can be used to link observed occurrences at the individual and group level, to utilization and performance outcomes.

TTF models comprise the task and technology, and the ‘fit’ between task and technology characteristics, which in turn affects technology use and/or task performance outcomes (Goodhue, 1995; Goodhue and Thompson, 1995; Dishaw and Strong, 1998a; Dishaw and Strong, 2003; Dishaw, Strong, and Bandy, 2002; Strong, Dishaw and Bandy, 2006). TTF influences use because an IT will be used if its functions ‘fit’ user needs (Dishaw and Strong, 1998a, p. 153). Similarly, TTF influences user performance because a task will be performed if functions of the IT used ‘fit’ user needs (Goodhue, 1995, p. 1829).

The task performed by the technology user is the first Task-Technology Fit (TTF) component. A task is an action a performer needs to perform in order to accomplish a goal or influence an outcome (Hackman, 1969; Hackos and Redish, 1998; Hansen, 1999;

Shepherd, 1998). In prior works, four task types have been identified and used to performer. Task characteristics are objective “real world”

properties such as the physical nature of either the stimuli e.g.

input rate, or stimulus material e.g. instructions.

Roby and Lanzetta, characteristics are specific behavioural requirements, needs, or

‘critical demands’, i.e. required or needed for adequate processes e.g. recording, or human behaviours e.g. decision-making that the performer would typically exhibit when performing the task. successful task completion based on physical, psychological and background characteristics.

Ferguson, 1956;

Fleishman and Hogan, 1978;

In the domain of TTF research, tasks have often been characterized as behaviour

‘requirements’ (Miller, 1962; Gagne, 1964), or ‘description’ (McCormick, 1965;

Dunnette, 1966). For the most part, the task has been defined as an action to be performed by a technology user (Nance, 1992). This performed task has been described as the

‘behavioural requirements’ that are necessary for accomplishing a stated goal through a process, given the information available (Zigurs and Buckland, 1998, p. 316). The

‘behaviour requirement’ task-type is considered a relatively stable attribute of any task, and can be described independently of the characteristics of the task performer (Wood, 1986). Moreover, since tasks are activities performers need to perform, required behaviours are influenced by the nature of the task, not the characteristics of the performer. This task type therefore represents a sound basis for task description (Hackman, 1969). As such, it is has been considered the most applicable approach to IS research (Junglas, Abraham and Watson, 2008). The task performed can therefore comprise characteristics that reflect the performer’s behavioural requirements, needs, or critical job demands (Hackman, 1969, p. 104). Tasks can be characterized along dimensions such as routineness versus non-routineness (Perrow, 1967), interdependence (Wageman and Gordon, 2005), variety (Karimi, Somers and Gupta, 2004), time criticality (Ballard and Siebold, 2004), user mobility (Gebauer et al., 2010), and location structuredness, difficulty, and predictability in performing the task.

Gebauer, Shaw and Gribbins (2010)

Interdependence The need of the task performer to co-operate with others in preforming the task.

Wageman and Gordon, 2005;

Hsiao and Chen (2012) Time criticality The need of the task performer to urgently

perform the task.

Location Dependency The need of the task performer to know his or her location and the location or

The technology used by the task performer is the second component of Task-Technology Fit (TTF). Technology is the system or tool (hardware, software, or data) used by a user to perform a task (Goodhue, 1995). This system or tool can be computerized or

paper-based³¹, and encompasses procedures, equipment, and knowledge or information transfer (Randolph, 1986; Ammenwerth et al., 2006, p. 4). The technology is described as providing a set of features that influences how the user chooses to perform a particular task (DeSanctis and Poole, 1994). In the Operations Management discipline, three types of technology have been identified in previous research. Technology has been classified as operations, materials, or knowledge (Hickson, Pugh, Pheysey, 1969, p. 380), as summarized in Table 4.4.

Table 4.4. Technology Types

Technology Type Description Source(s)

Operations Technology Technology is defined as the techniques used in sequencing workflow activities to produce and distribute output i.e. desired goods or services.

Thompson and Bates, 1957; Pugh, Hickson Hinings, Macdonald, Turner and Lupton, 1963

Materials Technology Technology is defined as the characteristics of particular objects or raw materials or used by users in workflow activities.

Perrow, 1967; Thompson, 1967

Knowledge Technology Technology is defined as the characteristics of particular knowledge or information attributes useful to users in workflow activities.

Hickson, Pugh and Pheysey (1969)

In more recent research, two basic groups of Information Technologies (ITs) have been identified (Huber, 1990). The first group, described as ‘basic characteristics’, relates to data storage, transmission, and processing capacities. Advanced ITs could enable higher levels of these characteristics. Notably, no clear distinction has been made between data (stimuli and symbols), and information (data that conveys meaning as a result of reducing uncertainty) (p. 49). The second group, described as ‘properties’, relates to the multi-faceted configuration of levels that characterize those technologies most relevant to particular tasks. These may cause the use of advanced ITs to have effects on users (p. 50).

In prior IS research, ITs have been characterized along attributes related to communication and decision aiding, information codification, and information diffusion (Huber, 1990; Simons, 1995; Wickramasinghe, 1999). These technology characteristics are described in Table 4.5.

31 Please refer Chapter 3 for empirical comparisons of mHealth tool and paper-based system user performance impacts.

Table 4.5. Typical Technology Characteristics

Technology Characteristic Description Source(s)

Communication IT enables easier, more reliable, and less costly, means of communication, and recording and indexing of content.

Huber, 1990

Decision Aiding IT enables the storing and retrieval of large amounts of data, the rapid and selective access to, and accurate combination and reconfiguration of, information.

Huber, 1990

Information Codification IT enables the structuring of information through the categorization (codifying) and compression of raw data.

Boisot, 1986; Simons, 1995

Information Diffusion IT enables easy information sharing by providing efficiently and effectively codified channels for diffusing data.

Simons, 1995

In related IS research, technology has been assessed along information characteristics such as accuracy, timeliness, relevance, aggregation, formatting, uniqueness, conciseness, clarity, and readability (Swanson, 1974; Ahituv, 1980; DeLone and McLean, 1992).

Technology has similarly been characterised as system and information quality (DeLone and McLean, 2003). System quality refers to desired processing characteristics of technology such as usability, reliability, and response time, whereas information quality refers to desired content characteristics such as completeness, accuracy, format, and currency (p. 25). In TTF-related research, technology features evaluated have closely resembled so-called IT ‘properties’ (Huber, 1990), typically consistent with characteristics such as communication and decision aiding (p. 50). For instance, for communication, these properties have included facilitating the ITs used in (1) transmitting precise information easily, cost-effectively, rapidly, and across time and geographic location (Rice and Bair, 1984), and (2) recording and indexing information content more reliably (Culnan and Markus, 1987). For decision aiding, these properties have included facilitating the users of ITs in (1) quickly and cost-effectively storing and retrieving large amounts of information, (2) more rapidly and selectively accessing the most recent information generated, and (3) more accurately combining, re-configuring, and transmitting information for interpretation and use (Zmud, 1983; Sprague and McNurlin, 1986; Sprague and Watson, 1986). In prior works, the ‘fit’ variable in TTF models has been theorized to influence outcomes of use (e.g. Dishaw and Strong, 1998a;

Dishaw and Strong, 2003, Strong et al., 2006), user performance (e.g. Goodhue, 1995,

Goodhue et al., 2000), or a combination thereof (e.g. Goodhue and Thompson, 1995). In TTF research, the use of technologies has involved hardware such as Electronic Performance Support Systems (Tjahono, Fakun, Greenough and Kay, 2001), software such as UML (Grossman, Aronson and McCarthy, 2005) data such as web travel information (D’Ambra and Wilson, 2004a, 2004b), and user-support services such as voice recognition (Goette, 2000). The performance of tasks involves but is not restricted to user activities such as intellective tasks such as solving problems with correct responses (Murthy and Kerr, 2004), decision-making such as evaluating criteria (Fuller and Dennis, 2009), and software maintenance such as de-bugging administrative systems and applications (Dishaw and Strong, 1998a). The TTF theoretical model, and its variations and extensions, are identified and discussed in Section 4.3.