Computer user satisfaction

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Computer user satisfaction (and closely related concepts such as system satisfaction, user satisfaction, computer system satisfaction, end user computing satisfaction) is the attitude of a user to the computer system they employ in the context of their work environments. Doll and Torkzadeh's (1988) definition of user satisfaction is, the opinion of the user about a specific computer application, which they use. In a broader sense, the definition of user satisfaction can be extended to user satisfaction with any computer-based electronic appliance. However, scholars distinguish between user satisfaction and usability as part of Human-Computer Interaction. Successful organisations have systems in place which they believe help maximise profits and minimise overheads. It is therefore desirable that all their systems succeed and remain successful; and this includes their computer-based systems. According to key scholars such as DeLone and McLean (2002), user satisfaction is a key measure of computer system success, if not synonymous with it. However, the development of techniques for defining and measuring user satisfaction have been ad hoc and open to question. The term Computer User Satisfaction is abbreviated to user satisfaction in this article.

Contents

The CUS and the UIS

Bailey and Pearson's (1983) 39‑Factor Computer User Satisfaction (CUS) questionnaire and its derivative, the User Information Satisfaction (UIS) short-form of Baroudi, Olson and Ives are typical of instruments which one might term as 'factor-based'. They consist of lists of factors, each of which the respondent is asked to rate on one or more multiple point scales. Bailey and Pearson's CUS asked for five ratings for each of 39 factors. The first four scales were for quality ratings and the fifth was an importance rating. From the fifth rating of each factor, they found that their sample of users rated as most important: accuracy, reliability, timeliness, relevancy and confidence in the system. The factors of least importance were found to be feelings of control, volume of output, vendor support, degree of training, and organisational position of EDP (the electronic data processing, or computing department). However, the CUS requires 39 x 5 = 195 individual seven‑point scale responses. Ives, Olson and Baroudi (1983), amongst others, thought that so many responses could result in errors of attrition. This means, the respondent's failure to return the questionnaire or the increasing carelessness of the respondent as they fill in a long form. In psychometrics, such errors not only result in reduced sample sizes but can also distort the results, as those who return long questionnaires, properly completed, may have differing psychological traits from those who do not. Ives, et al. thus developed the UIS. This only requires the respondent to rate 13 factors, and so remains in significant use at the present time. Two seven‑point scales are provided per factor (each for a quality), requiring 26 individual responses in all. But in a recent article, Islam, Mervi and Käköla (2010) argued that it is difficult to measure user satisfaction in the industry settings as the response rate often remain low. Thus, a simpler version of user satisfaction measurement instrument is necessary.

The problem with the dating of factors

An early criticism of these measures was that the factors date as computer technology evolves and changes. This suggested the need for updates and led to a sequence of other factor-based instruments. Doll and Torkzadeh (1988), for example, produced a factor-based instrument for a new type of user emerging at the time, called an end-user. They identified end-users as users who tend to interact with a computer interface only, while previously users interacted with developers and operational staff as well. McKinney, Yoon and Zahedi (2002) developed a model and instruments for measuring web-customer satisfaction during the information phase. Cheung and Lee (2005) in their development of an instrument to measure user satisfaction with e-portals, based their instrument on that of McKinney, Yoon and Zahedi (2002), which in turn was based primarily on instruments from prior studies.

The problem of defining user satisfaction

As none of the instruments in common use really rigorously define their construct of user satisfaction, some scholars such as Cheyney, Mann and Amoroso (1986) have called for more research on the factors which influence the success of end-user computing. Little subsequent effort which sheds new light on the matter exists, however. All factor-based instruments run the risk of including factors irrelevant to the respondent, while omitting some that may be highly significant to him/her. Needless to say, this is further exacerbated by the ongoing changes in information technology.

In the literature there are two definitions for user satisfaction, 'User satisfaction' and 'User Information Satisfaction' are used interchangeably. According to Doll and Torkzadeh (1988) 'user satisfaction' is defined as the opinion of the user about a specific computer application, which they use. Ives et al. (1983) defined 'User Information Satisfaction' as "the extent to which users believe the information system available to them meets their information requirements." Other terms for User Information Satisfaction are "system acceptance" (Igersheim, 1976), "perceived usefulness" (Larcker and Lessig, 1980), "MIS appreciation" (Swanson, 1974) and "feelings about information system" (Maish, 1979). Ang en Koh (1997) have described user information satisfaction (UIS) as "a perceptual or subjective measure of system success". This means that user information satisfaction will differ in meaning and significance from person to person. In other words, users who are equally satisfied with the same system according to one definition and measure may not be equally satisfied according to another.

Several studies have investigated whether or not certain factors influence the UIS; for example, those by Yaverbaum (1988) and Ang and Soh (1997). Yaverbaum's (1988) study found that people who use their computer irregularly tend to be more satisfied than regular users. Ang en Soh's(1997)research, on the other hand, could find no evidence that computer background affects UIS.

Mullany, Tan and Gallupe (2006) do essay a definition of user satisfaction, claiming that it is based on memories of the past use of a system. Conversely motivation, they suggest, is based on beliefs about the future use of the system. (Mullany et al., 2006).

The large number of studies over the past few decades, as cited in this article, shows that user information satisfaction remains an important topic in research studies despite somewhat contradictory results.

A lack of theoretical underpinning

Another difficulty with most of these instruments is their lack of theoretical underpinning by psychological or managerial theory. Exceptions to this were the model of web site design success developed by Zhang and von Dran (2000), and a measure of user satisfaction with e-portals, developed by Cheung and Lee (2005). Both of these models drew upon Herzberg's two-factor theory of motivation. Consequently, their factors were designed to measure both 'satisfiers' and 'hygiene factors'. However, Herzberg's theory itself is criticized for failing to distinguish adequately between the terms motivation, job motivation, job satisfaction, and so on. Islam (2011) in a recent study found that the sources of dissatisfaction differs from the sources of satisfaction. He found that the environmental factors (e.g., system quality) were more critical to cause dissatisfaction while outcome specific factors (e.g., perceived usefulness) were more critical to cause satisfaction.

Cognitive style

A study by Mullany (2006) showed that during the life of a system, satisfaction from users will on average increase in time as the users' experiences with the system increase. Whilst the overall findings of the studies showed only a weak link between the gap in the users' and analysts' cognitive style (measured using the KAI scales) and user satisfaction, a more significant link was found in the regions of 85 and 652 days into the systems' usage. This link shows that a large absolute gap between user and analyst cognitive styles often yields a higher rate of user dissatisfaction than a smaller gap. Furthermore, an analyst with a more adaptive cognitive style than the user at the early and late stages (approximately days 85 and 652) of system usage tends to reduce user dissatisfaction.

Mullany, Tan and Gallupe (2006) devised an instrument (the System Satisfaction Schedule (SSS)), which utilizes user generated factors (that is, almost exclusively, and so avoids the problem of the dating of factors. Also aligning themselves to Herzberg, these authors argue that the perceived usefulness (or otherwise) of tools of the trade are contextually related, and so are special cases of hygiene factors. They consequently define user satisfaction as the absence of user dissatisfaction and complaint, as assessed by users who have had at least some experience of using the system. In other words, satisfaction is based on memories of the past use of a system. Motivation, conversely, is based on beliefs about the future use of the system. (Mullany et al., 2007, p. 464)

Future developments

Currently, some scholars and practitioners are experimenting with other measurement methods and further refinements of the definition for satisfaction and user satisfaction. Others are replacing structured questionnaires by unstructured ones, where the respondent is asked simply to write down or dictate all the factors about a system which either satisfies or dissatisfies them. One problem with this approach, however, is that the instruments tend not to yield quantitative results, making comparisons and statistical analysis difficult. Also, if scholars cannot agree on the precise meaning of the term satisfaction, respondents will be highly unlikely to respond consistently to such instruments. Some newer instruments contain a mix of structured and unstructured items.

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Frederick Irving Herzberg was an American psychologist who became one of the most influential names in business management. He is most famous for introducing job enrichment and the Motivator-Hygiene theory. His 1968 publication "One More Time, How Do You Motivate Employees?" had sold 1.2 million reprints by 1987 and was the most requested article from the Harvard Business Review.

<span class="mw-page-title-main">Usability</span> Capacity of a system for its users to perform tasks

Usability can be described as the capacity of a system to provide a condition for its users to perform the tasks safely, effectively, and efficiently while enjoying the experience. In software engineering, usability is the degree to which a software can be used by specified consumers to achieve quantified objectives with effectiveness, efficiency, and satisfaction in a quantified context of use.

<span class="mw-page-title-main">Technology acceptance model</span> Information systems theory

The technology acceptance model (TAM) is an information systems theory that models how users come to accept and use a technology.

<span class="mw-page-title-main">Job satisfaction</span> Attitude of a person towards work

Job satisfaction, employee satisfaction or work satisfaction is a measure of workers' contentment with their job, whether they like the job or individual aspects or facets of jobs, such as nature of work or supervision. Job satisfaction can be measured in cognitive (evaluative), affective, and behavioral components. Researchers have also noted that job satisfaction measures vary in the extent to which they measure feelings about the job. or cognitions about the job.

<span class="mw-page-title-main">Personality test</span> Method of assessing human personality constructs

A personality test is a method of assessing human personality constructs. Most personality assessment instruments are in fact introspective self-report questionnaire measures or reports from life records (L-data) such as rating scales. Attempts to construct actual performance tests of personality have been very limited even though Raymond Cattell with his colleague Frank Warburton compiled a list of over 2000 separate objective tests that could be used in constructing objective personality tests. One exception however, was the Objective-Analytic Test Battery, a performance test designed to quantitatively measure 10 factor-analytically discerned personality trait dimensions. A major problem with both L-data and Q-data methods is that because of item transparency, rating scales and self-report questionnaires are highly susceptible to motivational and response distortion ranging all the way from lack of adequate self-insight to downright dissimulation depending on the reason/motivation for the assessment being undertaken.

The two-factor theory states that there are certain factors in the workplace that cause job satisfaction while a separate set of factors cause dissatisfaction, all of which act independently of each other. It was developed by psychologist Frederick Herzberg.

<span class="mw-page-title-main">Questionnaire</span> Series of questions for gathering information

A questionnaire is a research instrument that consists of a set of questions for the purpose of gathering information from respondents through survey or statistical study. A research questionnaire is typically a mix of close-ended questions and open-ended questions. Open-ended, long-term questions offer the respondent the ability to elaborate on their thoughts. The Research questionnaire was developed by the Statistical Society of London in 1838.

The Kano model is a theory for product development and customer satisfaction developed in the 1980s by Noriaki Kano, which classifies customer preferences into five categories.

SERVQUAL is a multi-dimensional research instrument designed to capture consumer expectations and perceptions of a service along five dimensions that are believed to represent service quality. SERVQUAL is built on the expectancy–disconfirmation paradigm, which, in simple terms, means that service quality is understood as the extent to which consumers' pre-consumption expectations of quality are confirmed or disconfirmed by their actual perceptions of the service experience. When the SERVQUAL questionnaire was first published in 1985 by a team of academic researchers, A. Parasuraman, Valarie Zeithaml and Leonard L. Berry to measure quality in the service sector, it represented a breakthrough in the measurement methods used for service quality research. The diagnostic value of the instrument is supported by the model of service quality which forms the conceptual framework for the development of the scale. The instrument has been widely applied in a variety of contexts and cultural settings and found to be relatively robust. It has become the dominant measurement scale in the area of service quality. In spite of the long-standing interest in SERVQUAL and its myriad of context-specific applications, it has attracted some criticism from researchers.

The critical incident technique is a set of procedures used for collecting direct observations of human behavior that have critical significance and meet methodically defined criteria. These observations are then kept track of as incidents, which are then used to solve practical problems and develop broad psychological principles. A critical incident can be described as one that makes a contribution—either positively or negatively—to an activity or phenomenon. Critical incidents can be gathered in various ways, but typically respondents are asked to tell a story about an experience they have had.

Quality of experience (QoE) is a measure of the delight or annoyance of a customer's experiences with a service. QoE focuses on the entire service experience; it is a holistic concept, similar to the field of user experience, but with its roots in telecommunication. QoE is an emerging multidisciplinary field based on social psychology, cognitive science, economics, and engineering science, focused on understanding overall human quality requirements.

Cognitive style or thinking style is a concept used in cognitive psychology to describe the way individuals think, perceive and remember information. Cognitive style differs from cognitive ability, the latter being measured by aptitude tests or so-called intelligence tests. There is controversy over the exact meaning of the term "cognitive style" and whether it is a single or multiple dimension of human personality. However it remains a key concept in the areas of education and management. If a pupil has a cognitive style that is similar to that of his/her teacher, the chances are improved that the pupil will have a more positive learning experience. Likewise, team members with similar cognitive styles likely feel more positive about their participation with the team. While matching cognitive styles may make participants feel more comfortable when working with one another, this alone cannot guarantee the success of the outcome.

Managerial psychology is a sub-discipline of industrial and organizational psychology that focuses on the effectiveness of individuals and groups in the workplace, using behavioral science.

Quality of working life (QWL) describes a person's broader employment-related experience. Various authors and researchers have proposed models of quality of working life – also referred to as quality of worklife – which include a wide range of factors, sometimes classified as "motivator factors" which if present can make the job experience a positive one, and "hygiene factors" which if lacking are more associated with dissatisfaction. A number of rating scales have been developed aiming to measure overall quality of working life or certain aspects thereof. Some publications have drawn attention to the importance of QWL for both employees and employers, and also for national economic performance.

The Questionnaire For User Interaction Satisfaction (QUIS) is a tool developed to assess users' subjective satisfaction with specific aspects of the human-computer interface. It was developed in 1987 by a multi-disciplinary team of researchers at the University of Maryland Human–Computer Interaction Lab. The QUIS is currently at Version 7.0 with demographic questionnaire, a measure of overall system satisfaction along 6 scales, and measures of 9 specific interface factors. These 9 factors are: screen factors, terminology and system feedback, learning factors, system capabilities, technical manuals, on-line tutorials, multimedia, teleconferencing, and software installation. Currently available in: German, Italian, Portuguese, and Spanish.

<span class="mw-page-title-main">Webreep model</span>

The Webreep model is an information systems theory that explains and predicts website satisfaction, loyalty, and word-of-mouth. The model suggests that four factors directly influence website satisfaction. Website satisfaction, in turn, directly influences website visitor loyalty and likelihood of referral. Each factor is "shaped" by facets. The four dimensions and factors include:

Work motivation is a person's internal disposition toward work. To further this, an incentive is the anticipated reward or aversive event available in the environment. While motivation can often be used as a tool to help predict behavior, it varies greatly among individuals and must often be combined with ability and environmental factors to actually influence behavior and performance. Results from a 2012 study, which examined age-related differences in work motivation, suggest a "shift in people's motives" rather than a general decline in motivation with age. That is, it seemed that older employees were less motivated by extrinsically related features of a job, but more by intrinsically rewarding job features. Work motivation is strongly influenced by certain cultural characteristics. Between countries with comparable levels of economic development, collectivist countries tend to have higher levels of work motivation than do countries that tend toward individualism. Similarly measured, higher levels of work motivation can be found in countries that exhibit a long versus a short-term orientation. Also, while national income is not itself a strong predictor of work motivation, indicators that describe a nation's economic strength and stability, such as life expectancy, are. Work motivation decreases as a nation's long-term economic strength increases. Currently work motivation research has explored motivation that may not be consciously driven. This method goal setting is referred to as goal priming. Effects of primed subconscious goals in addition to goals that are consciously set related to job performance have been studied by Stajkovic, Latham, Sergent, and Peterson, who conducted research on a CEO of a for-profit business organization using goal priming to motivate job performance. Goal priming refers to the achievement of a goal by external cues given. These cues can affect information processing and behaviour the pursuit of this goal. In this study, the goal was primed by the CEO using achievement related words strategy placed in emails to employees. This seemingly small gesture alone not only cost the CEO very little money, but it increased objectively measured performance efficiency by 35% and effectiveness by 15% over the course of a 5-day work week. There has been controversy about the true efficacy of this work as to date, only four goal priming experiments have been conducted. However, the results of these studies found support for the hypothesis that primed goals do enhance performance in a for-profit business organization setting.

Employee motivation is an intrinsic and internal drive to put forth the necessary effort and action towards work-related activities. It has been broadly defined as the "psychological forces that determine the direction of a person's behavior in an organisation, a person's level of effort and a person's level of persistence". Also, "Motivation can be thought of as the willingness to expend energy to achieve a goal or a reward. Motivation at work has been defined as 'the sum of the processes that influence the arousal, direction, and maintenance of behaviors relevant to work settings'." Motivated employees are essential to the success of an organization as motivated employees are generally more productive at the work place.

Job characteristics theory is a theory of work design. It provides “a set of implementing principles for enriching jobs in organizational settings”. The original version of job characteristics theory proposed a model of five “core” job characteristics that affect five work-related outcomes through three psychological states.

Employee recognition is the timely, informal or formal acknowledgement of a person's behavior, effort, or business result that supports the organization's goals and values, and exceeds their superior's normal expectations. Recognition has been held to be a constructive response and a judgment made about a person's contribution, reflecting not just work performance but also personal dedication and engagement on a regular or ad hoc basis, and expressed formally or informally, individually or collectively, privately or publicly, and monetarily or non-monetarily.

References