Computer user satisfaction: Difference between revisions

Revision as of 13:24, 7 January 2025

Revision as of 15:28, 7 January 2025

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Using findings, [[Product design|product designers]], [[Business analysis|business analysts]], and [[Software engineering|software engineers]] anticipate change, and prevent user loss by identifying missing features, shifts in requirements, general improvements, or corrections. ''[[end user|End user]] computing satisfaction'' is also [[Psychology|psychological]], in that the findings can sometimes represent objective views, rather than subjective truths. For example, previous success or failure impact next generation products. [[Organization|Organizations]] emphasize value in how products and opinions thereof manifest, preserving what is valued and caring how this is perceived.

This often creates a [[Positive feedback|positive feedback loop]] and creating a sense of agency for the user. These surveys assist to steer the system towards stable product sector positions. This is important, because the effects of satisfied or dissatisfied users could be difficult to change as time goes on. Real world examples are [[End user|end-user]] loyalty in the premium [[mobile device]] segment, opinion and perception of dependable [[Automotive industry|automotive]] brands, or lower quality products originate from certain nationalities based on [[Stereotype|stereotypes]]. In such cases, the [[Corrective and preventive action|corrective action]] is not made on a product level, rather it is handled in another business process via [[change management]], which aims to educate, inform and promote the system with the users, swaying opinions which could not be other altered amending product.

The satisfaction measurements are often used in industry, [[manufacturing]], or other large organizations for obtain internal user satisfaction. This could be used to motivate internal changes to improve or correct existing business processes. This could be by discontinuing use of systems, or prompt adopting to more applicable solutions. It could also be based on [[Job satisfaction|employee satisfaction]] which is important to promote productive work environments.

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==The CUS and the UIS==

Bailey and Pearson's (1983) 39‑Factor ''Computer'' ''User Satisfaction (CUS) questionnaire and its de''rivative, 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 [[Sampling (statistics)|sample]] of users rated as most important: ''[[Accuracy and precision|accuracy]]'', ''[[Reliability (statistics)|reliability]]'', ''timeliness'', ''[[Relevance|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 ''organizational position of EDP'' (the electronic data processing, or computing department). However, the CUS requires 39 x 5 = 195 individual seven‑point scale responses.<ref>{{cite journal |last1=Bailey |first1=James E. |last2=Pearson |first2=Sammy W. |title=Development of a Tool for Measuring and Analyzing Computer User Satisfaction |journal=Management Science |date=May 1983 |volume=29 |issue=5 |pages=530–545 |doi=10.1287/mnsc.29.5.530 }}</ref> Ives, Olson and Baroudi (1983), amongst others, thought that so many responses could result in errors of [[Attrition (research)|attrition]].<ref>{{cite journal |last1=Ives |first1=Blake |last2=Olson |first2=Margrethe H. |last3=Baroudi |first3=Jack J. |title=The measurement of user information satisfaction |journal=Commun. ACM |date=1 October 1983 |volume=26 |issue=10 |pages=785–793 |doi=10.1145/358413.358430 }}</ref> 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 [[Trait theory|psychological traits]] from those who do not. Ives, et al. thus developed the UIS. This only requires the respondent to rate 13 factors that remain in significant use. Two seven‑point scales are provided per factor (each for a quality), requiring 26 individual responses. However, in a recent article, Islam, Mervi, and Käköla (2010) argued that measuring user satisfaction in industry settings is difficult as the response rate often remains low. Thus, a simpler version of the user satisfaction measurement instrument is necessary.

==The problem with the dating of factors==