Factors Influencing User’s Satisfaction with Information Systems

Laila Zeroual and Ouafae Zerouali Ouariti

Ibn Zohr University, ENCG-A Rue Hachtouka Hay Salam, BP: 37/S Agadir- Morocco

Keywords: User Satisfaction, Information System, Partial Least Squares Structural Equation Modeling (PLS-SEM)

Abstract: User satisfaction is considered to be one of the most important main dependent variables used to measure

the success of the information system, this vision initiated Cyert and March in 1963 since they propose that

if an information system meets the needs of the user, the satisfaction of that user will be enhanced while if

not, the user will be dissatisfied and look for another source or another system. This is also confirmed by

several authors indicating that user satisfaction is directly linked to the use of the system. Also the most

frequent measures of success in the literature are user satisfaction, use of the information system and their

influence on performance. In this article we have first presented the main models of user satisfaction as well

as some definitions. Secondly the methodology adopted. And finally we will present the results of the

empirical study using the partial least square structural equation modeling (SEM).

1 INTRODUCTION

User satisfaction is one of the mechanisms to be

taken into account in setting up an information

system. User satisfaction is defined as the extent to

which users believe that the information system

available to them meets their information needs. For

its part, Bailey and Pearson (1983) defined it as the

set of feelings and attitudes of users of a technology

in relation to the characteristics of information and

user involvement.

For Raymond (1995) user satisfactions is “a

multidimensional attitude towards various aspects of

IS management, such as the quality of results, the

man-machine interface, personnel and IT services,

and various related constructs to the user, such as

feelings of participation and understanding”. Yet for

Spreng and MacKoy (1996), it is “an affective state

reflecting an emotional reaction to a product or

service”. In addition, user satisfaction is an overall

emotional and cognitive assessment of the user of the

level of achievement related to their experience with

the IS.

In this sense, user satisfaction is one of the key

factors for the success of information systems. Note

that a good system perceived by its users as being

poor is a poor system (Thong and Yap, 1996). This

concept was also present in the work of Shao, Z. and

al, (2020) who suggest that an information system

that perfectly meets the needs of the user will

strengthen their satisfaction with this system, and if it

does not provide the necessary the user will become

dissatisfied. These authors were the first to propose

the concept of user satisfaction as a proxy measure

for IS success, so several other studies have shown

this direct link between satisfaction and usage

behavior.

We can therefore understand that user satisfaction

is a subjective measure; it measures how users

perceive the information system they are using, either

through a feeling of pleasure and satisfaction or a

feeling of dissatisfaction. Usually, the systems that

best meet user information requirements are used the

most. The main models for measuring employee

satisfaction users, namely the Bailey and Pearson

(1983) model which was reassessed by Ives et al,

(1983) and the Doll and Torkzadeh (1988) model and

the Delone and Mclean information system access

model (2003). These models are considered the most

important and form the basis of any study aimed at

measuring user satisfaction.

2 LITERATURE REVIEW

2.1 User Satisfaction Measurement

Models

2.1.1 Bailey and Pearson Model (1983)

Bailey and Pearson (1983) consider user satisfaction

as a basic criterion for measuring the success or

552

Zeroual, L. and Zerouali Ouariti, O.

Factors Inﬂuencing User’s Satisfaction with Information Systems.

DOI: 10.5220/0010743500003101

In Proceedings of the 2nd International Conference on Big Data, Modelling and Machine Learning (BML 2021), pages 552-557

ISBN: 978-989-758-559-3

failure of information systems. The researchers put

in a tool to measure user satisfaction with 39 items.

This analysis included many factors such as the

quality of information, the performance of systems,

personal relationships and management

involvement. However this study presents a set of

limitations namely the sample which was small, 29

responses which were retrieved with difficulty in

applying and testing the questionnaire in different

contexts.

Ives et al, (1983) re-evaluated the model of

Bailey and Pearson and proposed a more developed

version focusing on the satisfaction of information

users (UIS), it is therefore a question of measuring

the general satisfaction of users vis- with respect to

the information provided. The goal of the

researchers was to strengthen the validity and

reliability of the Bailey and Pearson instrument

through a larger sample of about 200 users.

2.1.2 Ives and al, Model (1983)

Ives, and al, (1983) confirmed the validity of the

user satisfaction measurement tool developed by

Bailey and Pearson (1983). Indeed, the services

offered and the relationship with the personnel are

reflected in the relationships with the personnel of

the IT department; the quality of the information

produced is reflected, for example, by the reliability

and precision of the information; and the knowledge

and the implication are also translated for example

by the training carried out to the users on the use of

the SI ... let us know that the results of the work of

Ives, and al, (1983) inspired Doll and Torkzadeh

(1988) in the implementation of another model to

measure the satisfaction of users of information

systems.

2.1.3 Doll and Torkzadeh Model (1988)

Doll and Torkzadeh (1988) proposed another model

which takes into account the environment of the use

of the information system, and propose to integrate

variables linked to the conditions of interaction

between users and information systems. . A model

considered as complete since they went through a

review of previous work on user satisfaction,

moreover they presented in the bibliography of their

study an exhaustive list of articles dealing with this

link.

Indeed, a new instrument has been put in place

by these authors to measure user satisfaction with

specific applications, and was carried out using a

survey of 340 end users on their satisfaction /

dissatisfaction with regard to web portals.

2.1.4 Mahmoud and al, Model (2000)

The researchers produced a synthesis of the

literature on the main variables that affect user

satisfaction. The work of Mahmood and al, (2000) is

based on the results of empirical research between

the year 1986 and 1998, their model is composed of

three main factors (perceived benefits, user training

and organizational support), and each factor is

linked to three variables.

2.1.5 DeLone and Mclean Model (2003)

Management Information Systems researchers

DeLone and McLean have developed a model for

evaluating information systems and its effect on

performance. Their model is generally referred to as

the Information Systems Success Model. The

researchers identified five main dimensions of the

success of an information system namely: the quality

of the information, the quality of the system, the

quality of the service, the use, the satisfaction of the

users and the net benefits.

2.2 User Satisfaction

User satisfaction is determined by positive attitudes

towards the information system and by the response

of the user to the use of the output, thus constituting

the level of satisfaction of the user when he uses an

IS (Y.K. Dwivedi et al, 2012). Also it reflects the

user's feeling about the overall system experience,

i.e. the system itself, the end result, then to the

services provided by the system (Petter, Set al,

2008).

Indeed, several researchers have suggested

models to measure user satisfaction mainly we cite

(Bailey and Pearson, Ives et al, Doll and Torkzadeh

and Delone and Mclean their models are considered

the most important to measure user satisfaction. Two

other authors Seddon and Kiewont worked on a

satisfaction model rather than an evaluation of the

success of the IS covering a technological dimension

rather than an organizational one, the authors

proposed to use the user satisfaction variable as a

measure of perception of the success of the system.

User satisfaction is supposed to be a substitute

for the contribution of information systems to

performance, better performance will automatically

follow if the system meets users' information needs

Petter and al (2013). We keep this principle with the

definition of satisfaction as the degree of

correspondence between the characteristics of the

task and the functionality of the information system.

In addition, the quality of the information system, in

Factors Inﬂuencing User’s Satisfaction with Information Systems

553

terms of response time and availability of

information is the variable that most affects user

satisfaction.

3 HYPOTHESIS OF STUDY

H1: The quality of training is positively

associated with user satisfaction;

H2: The quality of service is positively

associated with user satisfaction;

H3: The quality of the information system is

positively associated with user satisfaction;

H4: The quality of information is positively

associated with user satisfaction;

4 METHODOLOGY

Our method of investigation is based on a

questionnaire made up of closed logical questions,

and with a Likert attitude scale evaluating the

different aspects questioned. The idea is to help the

interviewee to answer as well as possible the

different questions answered.

We have adopted convenience sampling for

practical reasons of accessibility, the population we

want to study is all IS users with different profiles.

We were able to distribute our questionnaire online

and face-to-face to 480 people with the

questionnaire link (www.) And with a message

inviting respondents to give it some time. Only

volunteers responded with 256 responses.

To test and confirm the causal relationships, we

used Partial least square structural equation

modeling (SEM), using the SmartPLS3 software,

this procedure consists of two main parts which are

the measurement and the structure model.

5 RESULTS

5.1 Measurement Model

This model is made up of all the relationships

between the indicators (Id) and the latent variables

or constructs that they help to measure (V).

Table 1: Results of Evaluation the Measurement Model

Latent variable

indicators

Factor Loading

Composite

Reliability

AVE

Cronbach’ s

alpha

User

Satisfaction

US1 0.868

0.895

0.77

0.903

US2 0.840

US3 0.886

US4 0.926

Training

Quality

TQ1 0.838

0.869

0.68

0.771

TQ2 0.812

TQ3 0.838

Service

Quality

SQ1 0.782

0.881

0.65

0.821

SQ2 0.772

SQ3 0.874

SQ4 0.794

Information

System Quality

ISQ1 0.840

0.920

0.69

0.891

ISQ2 0.875

ISQ3 0.716

ISQ4 0.879

ISQ5 0.857

Information

Quality

INQ1 0.864

0.887

0.61

0. 840

INQ2 0.808

INQ3 0.788

INQ4 0.719

INQ5 0.722

This table lists the survey scales and their internal

consistency reliability, for the responses provided all

of the composite reliability measures were well

above the recommended level of 0.70. The C.Rs

found vary between (0.8 and 0.9) values greater than

the suggested threshold, indicating good internal

consistency (Nunnally, J.C, 1978).

In addition, convergent validity is adequate when

constructs have an extracted mean variance (AVE)

of at least 0.5 (Fornell, C. et al, 1981), and as shown

in the table all AVE values are greater than at the

limit value of 0.5 varies between (0.5 and 0.7).

Finally for the scales, the loading of the items is

greater than or equal to (0.7).

5.2 Structural Model

This system of structural relations refers to the

determination of the causal relations between the

latent variables (V), which makes it possible to trace

the direction of the hypotheses to be tested by taking

into account the measurement errors of the estimate.

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5.2.1 R-squard

The validity of the structural model is assessed using

the coefficient of determination (R²).

Table 2: Result of the R² test

Variable R²

User

Satisfaction

0.658

We obtained a coefficient R² = 0.658> 0.30, this

value of 66% corresponds to a good coefficient of

determination, that is to say a good prediction.

5.2.2 F-squard

Effect size f² allows analyzing the contribution of

each independent variable on the dependent variable.

Table 3: Result of the f² test

User Satisfaction

Training Qualit

0.212

Service Qualit

0.051

Information S

stem Qualit

0.210

Information Qualit

0.552

For the size effect f² of the quality of information on

the dependent variable "user satisfaction", the value

obtained from our calculations shows a very high

size effect f². This effect can be interpreted by the

role that information plays in the success of any

organization, and its importance in this changing

field. Other than the quality of the information, the

training and the quality of the information system

have an effect considered to be moderate, playing a

role as well in the satisfaction of the actors. Finally

service quality with low effect.

5.2.3 Hypothesis Testing

The result of hypothesizes testing showed significant

support for all of hypothesis in this study.

Table 4: Summary of Hypothesis Testing

value

Suppo

H1: Training

Quality User

satisfaction

0,377 6,780 0,000 Yes

H2:Service

Quality user

satisfaction

0,174 3,060 0,002 Yes

H3:Information

System Quality

user satisfaction

0,237 4,273 0,000 Yes

H4:Information

Quality user

satisfaction

0,377 6,780 0,000 Yes

6 DISCUSSION

It emerges from these causal coefficients that:

The quality of information has a positive and

significant effect on user satisfaction. For the safety

of organizations, information becomes a strategic

stake, it is considered in several works as the raw

material of the economic world allowing being

efficient. Any organization will be better than its

competitors especially if it has precise and correct

information, making it easier to control unexpected

variations. In other words, it makes it possible to

control the present and to foresee the future, by

meeting the requirements which all rely on

information.

The quality of information seems to be the

quality most expected of users, determining their

satisfaction. ((In terms of information that meets

their needs, allowing them to make better

decisions)).

Factors Inﬂuencing User’s Satisfaction with Information Systems

555

The quality of the information system has a

significant effect on user satisfaction; it is a variable

that represents the user's perception of the

interaction with the functionalities of the

information system used. Indeed, this is where the

dimension "speed of the information system used"

takes place given the constraints of the economic

environment which is characterized by volatile

demand. Users consider that the better the quality of

the IS, the higher their satisfaction.

The quality of training has a positive and

significant effect on the quality of service, user

satisfaction, quality of logistics and user information

system, which shows that training or precisely its

perceived quality plays an important role in the

acceptance of new technologies leading to a certain

satisfaction with the service and the IS used.

Training therefore provides the tools necessary to

apply practical solutions to problems encountered in

the workplace. IS users consider that the better the

quality of the training they receive, the higher their

satisfaction, by offering them functional ease.

Finally, the quality of service has also a positive

and significant effect on the quality of the logistics

information system and on user satisfaction. This

result reflects the effort that IT staff must provide to

meet user expectations and listen to them. . So that

this significance was confirmed through the

assurance, empathy, reliability and responsiveness of

the service to respond to the problems encountered.

These results are similar to those obtained by J.

Floropoulos et al, (2010); Nunes (2012); Demian

Abrego-Almazán (2017); Solano et al, (2014);

Seddon P, et al, (1996). Although the context of the

studies is different, there is support for our result.

7 CONCLUSION

The results of our study show that the quality of

information is the main determinant of user

satisfaction. The presence of quality qualified

information is an important prerequisite for

management decision making, especially when the

decisions taken can have serious consequences

leading to the loss of customers. Through Therefore,

scrutinizing the information obtained and requiring

that it meet certain characteristics is essential.

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