The Usability of Mobile Enterprise Resource Planning Systems

Thomas Wüllerich and Alexander Dobhan

Department of Business and Engineering, University of Applied Sciences Schweinfurt, Schweinfurt, Germany

Keywords: Usability, Usability Evaluation, User-oriented, Mobile Enterprise Resource Planning Systems.

Abstract: This paper presents a model for end-user-based evaluation of the usability of mobile ERP systems. Recent

studies show that the mobile use of ERP software is both, crucial for user satisfaction and still improvable for

many ERP systems. Therefore, ERP-specific usability models are necessary to meet the requirements of ERP

systems in comparison to e.g., apps for private use. The research objective is therefore to develop a model

that enables software providers to measure and benchmark the usability of their software products. Therefore,

we introduce after a literature research a usability model for the mobile application of ERP systems (mobile

ERP). Our usability model is based on the widely used PACMAD model. We modify the PACMAD model

for the context of ERP systems. This results in a new end-user-based model, that differs from existing models,

because of its focus on end-users and the ERP context. Subsequently, the model will be tested in an initial

study with 19 test persons. The results of the study indicate two main findings. Firstly, the model allows the

measurement of the usability of mobile ERP systems. Secondly, some key factors substantially affect the

usability of mobile ERP systems.

1 INTRODUCTION

The proliferation of smartphones and tablets has

released a discussion on mobile flexibility of business

applications, and in particular of enterprise resource

planning (ERP) systems (Bahssas et al., 2015; Omar

& Gomez, 2016; Tai et al., 2016) Today mobile ERP

applications are now part of the ERP standard.

Providers of ERP systems are responding to user

feedback by increasing the suitability of their

software for mobile devices. This enables, for

example, sales representatives to access internal data

(Bahssas et al., 2015). At the same time, users still see

a need for improvement in this area among software

providers (Trovarit AG, 2019).

Regardless of whether mobile use is realized as a

native application, web application, or hybrid

application (Gronau & Fohrholz, 2016), recent

research outcomes show that users, who complain

about the usability of ERP systems, often reduce

overall user satisfaction. The reason for the negative

usability perception is the complex and static way of

operation (Omar, 2015; Trovarit AG, 2019) caused by

a large amount of data and complex functionalities.

(Omar et al., 2016).

On the other hand, usability challenges refer to the

mobile use of ERP systems, such as limited screen

size, the reduced reliability of the mobile data

connection, and other aspects. The complexity of

ERP systems, which in the past required specific

usability approaches for desktop applications (Singh

& Wesson, 2009), makes a specific usability model

necessary for mobile ERP systems as well (Omar &

Gomez, 2017).

Therefore, researchers have already developed

usability models for mobile ERP systems. However,

these are mostly expert based, while no studies have

been conducted from the perspective of end-users

(Omar et al., 2016). Therefore, the intention of our

research in this paper is to develop an end-user-based

model for evaluating the usability of mobile ERP

applications.

Thus, the next paragraph contains an overview of

recent research outcomes. Subsequently, we

introduce a new usability model based on PACMAD.

The applicability of the new model is then tested

based on an initial study with 19 participants for two

ERP systems. The results of the study are described.

The results include some indications for inter-

dependencies between the components of our model.

2 LITERATURE REVIEW

The common use of mobile devices leads to usability

challenges such as limited screen size, different

Wüllerich, T. and Dobhan, A.

The Usability of Mobile Enterprise Resource Planning Systems.

DOI: 10.5220/0010445005170524

In Proceedings of the 23rd International Conference on Enterprise Information Systems (ICEIS 2021) - Volume 2, pages 517-524

ISBN: 978-989-758-509-8

517

screen resolutions, limited processing, and

performance capabilities, limited data entry methods,

the diversity of mobile operating systems and security

in the mobile ERP context (Omar, 2015; Zhang &

Adipat, 2005). Another factor is the mobile

environment, as interaction with environmental

elements causes distraction (Zhang and Adipat,

2005). Mobile connectivity is often a critical feature

(Muccini et al., 2012). Furthermore, different levels

of end-user knowledge should not be neglected

(Nayebi et al., 2012). Another usability challenge

refers directly to the back-end ERP system.

Compared to other mobile applications, mobile ERP

systems process a large amount of data (Omar et al.,

2016).

The PACMAD model of Harrison et al.(2013) is

one of the most applied usability models for mobile

applications. It considers the specific requirements of

mobile devices and offers sufficient leeway for

adaptations. PACMAD means "People At the Center

of Mobile Application Development” and is based on

the approaches of Nielsen and ISO 9241-11. The

model identifies the three factors user, task, and

context that influence the usability of an application.

Furthermore, the model has the following seven

dimensions (Harrison et al., 2013):

Effectiveness examines the ability of a user to

complete a certain task. It is measured by successful

task completion (Harrison et al., 2013; Alturki and

Gay, 2017). It has been applied similarly several

times in a similar way (Alturki & Gay, 2017; Frokjaer

et al., 2000)

Efficiency measures the ability of a user to

perform tasks with the desired speed and accuracy

(Harrison et al., 2013). One of the measurable

indicators is the time of completion (Alturki & Gay,

2017; Cooprider et al., 2010). To calculate Efficiency,

time is put in relation to Effectiveness.

Satisfaction examines the perceived level of

comfort and friendliness of the system (Harrison et

al., 2013; Frokjaer et al., 2000; Omar, 2015). This is

measured using a questionnaire or other qualitative

techniques such as emoji cards (Harrison et al., 2013).

The Errors dimension is used to determine the

error rate during use (Nielsen, 1994). In practice, it is

measured with the number of errors (Hussain et al.,

2018). According to PACMAD, Memorability is the

ability of a user to maintain the effective use of an

application and avoid repeated learning (Harrison et

al., 2013). This can be determined by repeated

sessions after a period of inactivity (Zali, 2016) or by

using a questionnaire (Hussain et al., 2018). This

dimension is like Learnability, which is defined as an

experience that the user can gain.

The Cognitive Load refers to the amount of

cognitive processing the user can perform (Harrison

et al., 2013). This is measured with the use of eye-

tracking technology or a NASA TLX test (Alturki and

Gay, 2017).

The analysis of usability studies on mobile ERP

systems showed that no end-user-oriented approach

to usability evaluation exists yet.

3 USABILITY MODEL MERP-U

Our model aims to adapt the PACMAD model to

mobile ERP systems. In the first step, the dimensions

of the basic PACMAD model are partially

summarised and operationalized for the mobile ERP

context. After that supplementing, we add further

dimensions that are required for the end-user-oriented

assessment of mobile ERP systems.

To calculate the Effectiveness (1), the share of

successfully completed tasks is quantified. The

outcome of the following formula indicates the level

of Effectiveness:

(1)

In the context of ERP systems, the correctness of data

maintenance or data extraction is easy to quantify for

simple tasks. The number of errors is a measure for

the Errors dimension. For the present model, the

Effectiveness and the Errors are put into a ratio.

(2)

To determine the Efficiency (2) of mobile ERP

systems, the time, it takes to complete the test, is

recorded. Then we take the proportion of correct tasks

in relation to the time spent to get the Efficiency as an

outcome.

Previous studies on user Satisfaction use a

questionnaire with a 5-point Likert scale to measure

it (Hussain et al., 2018; Alturki and Gay, 2017; Omar

2018).

For the model, Learnability is combined with

Memorability. The measurement requires the record

of the time to reach and maintain a given level of

competence (Harrison et al., 2013). It is integrated

𝐸𝑓𝑓𝑒𝑐𝑡𝑖𝑣𝑒𝑛𝑒𝑠𝑠 =

𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑡𝑎𝑠𝑘𝑠 𝑐𝑜𝑚𝑝𝑙𝑒𝑡𝑒𝑑 𝑠𝑢𝑐𝑐𝑒𝑠𝑓𝑢𝑙𝑙𝑦

𝑡𝑜𝑡𝑎𝑙 𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑡𝑎𝑠𝑘𝑠 𝑢𝑛𝑑𝑒𝑟𝑡𝑎𝑘𝑒𝑛

×100%

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into the questionnaire and estimated by the users

themselves.

In the context of the study, the NASA TLX test is

an indicator for the Cognitive Load (Harrison et al.,

2013; Alturki and Gay, 2017). It relies on a

multidimensional construct to derive an overall

workload score based on a weighted average of

ratings on six subscales: mental demand, physical

demand, temporal demand, performance, effort, and

frustration level (Cao et al., 2009).

According to Singh and Wesson, the criteria for

the usability of ERP systems are limited due to the

small number of corresponding studies. However,

they distinguish between six specific basic criteria for

assessing usability (Singh and Wesson, 2009):

• Navigation: navigational functions of the ERP

system

• Learnability: the degree of learnability of the ERP

system

• Task support: the ability of the ERP system to

provide effective task support

• Presentation: presentation capabilities of the ERP

system

• Customization: the ability of the ERP system to

adapt to a specific organization and individual

user

From these heuristics defined by Singh and

Wesson, we select two dimensions to expand the

operationalized PACMAD model. Learnability is not

included because it is already considered in

combination with Memorability. Furthermore, the

heuristic Task Support is included in Effectiveness

and Efficiency. The evaluation of Customization does

not take place within the scope of the study. Instead,

the dimension Presentation considers the main

problems of ERP systems: The complex screen

display and outputs that are often difficult to

understand (Singh and Wesson, 2009). Mobile

applications are particularly affected by this due to

the smaller display (Omar et al., 2016). The

dimension aims to ensure that the layout of menus,

dialogue boxes, controls, and information on the

screen is appropriate and clear (Singh & Wesson,

2009). Another important dimension for the mobile

ERP context is Navigation, as this is a design issue

for ERP systems. This examines the application's

ability to access appropriate information, menus,

reports, options, and elements (Singh and Wesson,

2009). Both, Presentation and Navigation are

subjective criteria of the questionnaire. Along with

Satisfaction participants estimate these dimensions

by using a 5-point Likert scale.

Figure 1: Extended model MERP-U.

The modified PACMAD model, MERP-U, is an

evaluation model that is especially suitable for mobile

ERP systems. It combines the best of both, ERP

usability models (Singh and Wesson) and usability

models for mobile apps (PACMAD). In summary, the

new model includes seven dimensions (see Fig. 1).

4 USABILITY STUDY

For testing the applicability of our model, we applied

it for two ERP systems in an initial study.

4.1 Research Design

The study was about two ERP software products

available on the European market. System A is a

relatively new ERP product, still unknown on most

European markets, but established on the eastern

European market with growing sales figures. It

specializes in production-oriented small or medium-

sized businesses. In contrast, System B is a mature

ERP software for SMEs that is established on the

worldwide market. Both systems are web-based. For

System B an app for mobile devices with Android and

iOS is available. System A works with all common

browsers.

The Participants of the study were 19 research

assistants, student assistants as well as Bachelor and

Master Students with professional and academic ERP

experience. All participants were able to operate in an

ERP software system before and to understand its

basics. Thus, according to Hofer et. al. (2007) the

crucial prerequisite for realistic end-users is fulfilled

Nevertheless, it must be considered that the

participants have a different level of knowledge

regarding the systems.

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519

To record usability-related information, the study

includes the application of various methods, which

are:

• The (digital) test sheet (SurveyMonkey) contains

simple tasks in the mobile ERP system (e.g.,

changes in the article master). For usability

recording, answers on the test sheet and the

modified data records in the system were

evaluated for correctness and number of errors.

The results represent the indicators for the

PACMAD dimensions Effectiveness, Errors, and

Efficiency. During processing the tasks, a study

coordinator observed the behaviour of the

participants. He logged the comments of the users

and the user’s reactions. The gained observations

mainly refer to Satisfaction, Cognitive Load

Navigation, and Presentation.

• After the users completed the test sheet tasks, they

were asked to fill out some questions on

Navigation, Presentation, and Satisfaction with a

5-point Likert scale. In addition, the participants

assessed the Memorability and Learnability

Furthermore, they had the opportunity to express

further comments. The questionnaire also

contains an extended NASA TLX test.

For organizational reasons, participants were

assigned to two groups: In the case of the first group,

an online meeting took place via Zoom. The study

coordinator was available to the subjects during this

time for questions and acted as an observer. Group 1

mainly consisted of experienced users.

The members of the second group received their

credentials and access to their tenant (each user has

their client in both systems). The users also received

all instructions and links required for the test by e-

mail. The second group primarily included users with

less experience.

At the beginning of the individual online

meetings, the participants received a short

introduction to the study. Any questions were

clarified in advance so that the first digital test sheet

could be used. The participants worked through the

tasks of the test sheet on their smartphones.

Additionally, they answered the questions on the test

sheet. The study coordinator was available for any

questions and recorded comments, reactions, and

other conspicuous features.

After completion (about 10 minutes), the

participants received a feedback sheet on the ERP

system in the chat. As soon as this was completed, the

participants turned to the second system in the same

way. In the end, a summary feedback discussion took

place.

Participants of group 2 received a more detailed

introduction and worked through the process steps

according to the above structure except for

observation and feedback discussion.

4.2 Results

A total number of 19 participants completed the

study. 8 of these worked through the questions in a

live meeting and 11 completed the tasks outside of an

online session. A total of 18 feedback questionnaires

were filled out completely.

For Effectiveness and Errors, we have achieved

the following results:

Table 1: Results of the Effectiveness and Errors.

System A System B

Effectiveness 77% 63%

Errors 23% 37%

System A seems to have a higher Effectiveness and a

lower Error rate than System B. According to the

results, users completed on average one task more

correctly in System A than ins System B. It turned out

that incorrect spelling, forgotten data, or a lack of

available (in ERP system) information mostly caused

the errors.

Table 2: Results of the Efficiency.

System A System B

Efficiency 62% 39%

The results regarding the Efficiency show a better

Efficiency for System A. This is related to the fact

that the processing time for System A was on average

1.72 minutes shorter than for System B (even though

the effectiveness was better).

To capture the Satisfaction of the users with the

system, participants were supposed to rate the

following statement on a Likert scale: "The

application is satisfactory overall".

The outcome on that is given below:

Table 3: Results of the Satisfaction.

System A System B

Disagree at all 0,00% 0,00%

Disagree 16,67% 22,22%

Part/part 16,67% 27,78%

Agree 50,00% 44,44%

Clearly agree 16,67% 5,56%

When comparing the results regarding the two ERP

applications, it is obvious that users are more satisfied

with System A than with System B.

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The answers regarding the statement about Learn-

ability and Memorability give the following picture:

“The functions and steps of the application are

memorable and easy to learn”.

Table 4: Results of the Memorability and Learnability.

System A System B

Disagree at all 11,11% 5,56%

Disagree 0,00% 11,11%

Part/part 0,00% 22,22%

Agree 38,89% 38,89%

Clearly agree 50,00% 22,22%

The distribution of results between the two systems is

slightly similar. With System B, most users consider

the software as easy to learn and memorable.

However, compared to System A, the application

scores lower. 89% of respondents found System A to

be good to very good. 11%, on the other hand, were

very dissatisfied.

For measuring the Cognitive Load, we applied the

NASA TLX test. The table below contains the test

results:

Table 5: Results of the Cognitive Load.

System A System B

Mental effort Not at all (1,47) Little (2,29)

Physical effort Not at all (1,06) Not at all (1,37)

Time pressure Little (1,71) Little (2,35)

Satisfaction of

performance

Satisfied (4,11) Neither (3,27)

Performance

level

Less hard (1,65) Less hard (2,16)

Stress level Little (1,82) Little (2,37)

Most of the test persons feel a lower strain

accompanied by a higher self-satisfaction for System

A compared to System B. The greatest difference

arises in the mental strain and satisfaction

experienced by the participants during the processing.

To record Navigation in the questionnaire, we let

the participants rate the following statement:

"I like the menu navigation and menu structure of the

application".

The table below shows the result on Navigation:

Table 6: Results of the Navigation.

System A System B

Disagree at all 16,67% 11,11%

Disagree 5,56% 33,33%

Part/part 27,78% 27,78%

Agree 27,78% 22,22%

Clearly agree 22,22% 5,56%

System A performs better overall because the

users rate the menu navigation and the menu structure

better than for System B. The conversations and

comments of the test persons confirm that result. The

structure of System A is less extensive and the menu

navigation with its subdivision is logically arranged.

However, some users do not find their way around the

menu navigation. This is due to the poor quality of the

translation. The poorer tendency for the menu

structure of System B is mainly due to the extensive

design of the application and the ease of finding

functions. This has a negative impact on the search

for information.

From the observation and the interviews as well

as the comments in the questionnaire, factors for the

Navigation were also identified:

Table 7: Factors for the Navigation.

System A System B

+ drop-down menu + successful design

+ simple structure + good scaling

+ confirmation of

transactions

+ mature system

- not mature, many errors - overloaded input fields

- poor translation - no transaction

confirmation

- poor scaling on a

smartphone

- modules difficult to

find

The statement for Presentation is as follows: "The

application is designed clearly".

The users of both systems gave the following

feedback on this:

Table 8: Results of the Presentation.

System A System B

Disagree at all 0,00% 5,56%

Disagree 22,22% 50,00%

Part/part 27,78% 16,67%

Agree 27,78% 16,67%

Clearly agree 22,22% 11,11%

Users prefer the clarity of System A to System B. The

negative user ratings are justified by the fact that the

format of System A as a web application is not

scalable to smartphones. Nevertheless, some users

praise the clear presentation of the individual areas

and submenus. In contrast, the scaling of System B is

adapted to the smartphone. On the other hand, it is a

challenge for most users to obtain an overview to find

the desired data.

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521

5 INTERPRETATION OF THE

RESULTS

The results of the study show that System A performs

better in all usability dimensions. This may be an

indicator of how the individual dimensions effect on

each other. This means that the positive or negative

result of one usability attribute has a corresponding

effect on another attribute. For this purpose, the

relationships of the dimension are presented taking

into account the external influences identified by

Omar (2015).

Here, the user forms an opinion about the menu

navigation and the presentation of the content. If users

perceive these aspects as positive, they feel low

Cognitive Load. Because of the low Cognitive Load,

there is a high level of self-satisfaction and satisfaction

in general. Furthermore, Memorability and Learn-

ability benefit from this, so that data can be learned and

memorized more easily. This in turn promotes

Effectiveness and Efficiency in the decision (Akiki et

al., 2016). The starting points of the effect chain seems

to be the newly introduced usability attributes

Navigation and Presentation (Babaian et al., 2016).

The reasons for the evaluation of the two new

dimensions are the interaction between the software

architecture and the personal attitude of the user

towards the architecture (Dabkowski & Jankowska,

2003). Therefore, users mostly justify their satisfaction

with arguments that evaluate Navigation and

Presentation. In between, is the Cognitive Load, which

has been shown to influence Satisfaction (Schmutz et

al., 2009). Nevertheless, it should be noted that the

external challenges identified by Omar (2015) also

affect the dimensions within the back-end ERP system.

In the present study, for example, the clarity of

System B was criticized by the test persons due to the

high depth of functions and the numerous options in

the input menus. This had a negative impact on user

satisfaction and usability (Singh and Wesson, 2009;

Omar, 2015). In a Trovarit study, a similar correlation

was found between the range of functions and

satisfaction, which reinforces the research conducted.

It was found out that ERP solutions with fewer

features and applications from smaller vendors scored

best in user satisfaction (Trovarit AG, 2019).

However, despite the higher usability of small

ERP systems, the decision factor for companies to

purchase them is not only usability. These would be,

for example, the desire for a high level of functional

depth. This is especially true for larger companies,

with a large amount of information (Omar and

Gomez, 2016).

6 LIMITATIONS OF RESEARCH

For this study, we designed two different settings.

The advantages of the online meeting were the direct

feedback from the users during the conversation. This

was not possible for participants outside of the online

session. However, the time flexibility was an

important factor for these users to participate in the

study. Originally, live conduction with the support of

eye-tracking was planned for the research design.

This plan was discarded due to the COVID 19 crisis,

so an alternative design without the physical presence

of the participants was intended. With the new

concept, it was consequently no longer possible to use

the eye-tracking system to test the Cognitive Load.

Figure 2: Dimensions of MERP-U.

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Due to the use of digital media, the new approach

represents a modern alternative to the classic study

with the presence of the participants (Gray et al.,

2020).

Nevertheless, this approach brings challenges

compared to live execution. On the one hand, it

happened that tasks were not fully completed by the

users. Furthermore, there is the risk that participants

cheat by giving false information when completing

the test sheets. The absence of errors was not directly

observed.

Another point of criticism is that test persons in

the study were partly familiar with one of the systems.

Of the 19 users, 15 had practical experience in System

B, while one person was familiar with System A.

Three subjects only had experience in other ERP

systems before the study. Previous knowledge on

performing tasks on a particular system can

significantly influence the results. It is to be expected

that due to experience effects, the known system B

performs better. In this study, no positive tendency

towards the familiar system was noticeable. This

strengthens the result that the usability of system A is

higher than that of B.

Likewise, the system sequence during the study

should be considered, as the learning effect of the first

application probably had a positive effect on the

result of the second system. Of the 19 participants,

eleven started first with System A and eight with

System B. Although System B was mostly used

second, it performed worse in Effectiveness and

Efficiency. Thus, no clear correlation can be

discerned here.

Compared to other studies, the number of

participants in this study is lower, at 19 users

(Frokjaer et al., 2000; Raptis et al., 2013). This is

because this first study was a test of applicability

which already gives us interesting insights.

Furthermore, the results motivate us to plan a study

with by far more participants. This study will be

designed to examine our hypothesis that the

dimensions Navigation and Presentation affect all

other usability dimensions.

7 CONCLUSION

In summary, this research aimed to develop an end-

user-oriented model for the usability evaluation of

mobile ERP systems. This was achieved with the

MERP-U model. The interpretation of the study

results indicates that there are correlations between

the dimensions within the model and that a high

functional depth has a negative effect on usability.

Furthermore, the results allow us to suppose that the

dimensions Navigation and Presentation are of high

importance for mobile ERP systems.

As we emphasized in the paragraph regarding

limitations, the sample size was small compared to

other studies. Therefore, for future research, we are

planning to apply the model to further mobile ERP

applications with a higher number of participants.

The use of techniques such as eye-tracking or web

augmentation is also recommended for analysing

aspects like Navigation, Presentation or Cognitive

Load. This would allow us to automate the process

partly, with the possibility of expanding the analysis

to a higher audience. For that study, it makes sense to

slightly modify the research design to examine the

interdependencies between the dimensions.

REFERENCES

Akiki, P. A., Bandara, A. K., & Yu, Y. (2016). Engineering

Adaptive Model-Driven User Interfaces. IEEE

Transactions on Software Engineering, 42(12), 1118–

1147. https://doi.org/10.1109/TSE.2016.2553035

Alturki, R., & Gay, V. (2017). Usability Testing of Fitness

Mobile Application: Methodology and Quantitative

Results. In N. Meghanathan (Ed.), Computer Science &

Information Technology (CS & IT) (pp. 97–114).

Academy & Industry Research Collaboration Center

(AIRCC). https://doi.org/10.5121/csit.2017.71108

Babaian, T., Lucas, W., Chircu, A., & Power, N. (2016).

Evaluating Interactive Visualizations for Supporting

Navigation and Exploration in Enterprise Systems. In

S. Hammoudi, L. Maciaszek, M. M. Missikoff, O.

Camp, & J. Cordeiro (Eds.), Iceis 2016: Proceedings of

the 18th International Conference on Enterprise

Information Systems : Rome, Italy, April 25-28, 2016.

SCITEPRESS - Science and Technology Publications

Lda. https://doi.org/10.5220/0005770203680377

Bahssas, D. M., Al Bar, A. M., & Hoque, M. R. (2015).

Enterprise resource planning (ERP) systems: design,

trends and deployment. The International Technology

Management Review, 5(2), 72–81. https://www.

atlantis-press.com/journals/itmr/24089

Cao, A., Chintamani, K. K., Pandya, A. K., & Ellis, R. D.

(2009). Nasa TLX: Software for assessing subjective

mental workload. Behavior Research Methods, 41(1),

113–117. https://doi.org/10.3758/BRM.41.1.113

Cooprider, J., Topi, H., Xu, J., Dias, M., Babaian, T., &

Lucas, W. (2010). A Collaboration Model for ERP

User-System Interaction. In R. H. Sprague (Ed.), 43rd

Hawaii International Conference on System Sciences

(HICSS) (pp. 1–9). IEEE. https://doi.org/10.1109/

HICSS.2010.5

Dabkowski, A., & Jankowska, A. M. (2003).

Comprehensive framework for mobile ERP system. In

I. C. S. Staff (Ed.), 14th International Conference on

Database and Expert Systems Applications (pp. 890–

The Usability of Mobile Enterprise Resource Planning Systems

523

894). IEEE. https://doi.org/10.1109/DEXA.2003.123

2134

Frokjaer, E., Hertzum, M., & Hornbæk, K. (2000).

Measuring usability: are effectiveness, efficiency, and

satisfaction really correlated? In T. Turner & S.

Pemberton (Eds.), CHI 2000: The future is here: CHI

2000 conference proceedings : conference on human

factors in computing systems (pp. 345–352). ACM

Press. https://doi.org/10.1145/332040.332455

Gray, L. M., Wong-Wylie, G., Rempel, G. R., & Cook, K.

(2020). Expanding qualitative research interviewing

strategies: Zoom video communications. The

Qualitative Report, 25(5), 1292–1301. http://search.

proquest.com/openview/c264828516f288b941ad22c63

c576706/1?pq-origsite=gscholar&cbl=55152

Gronau, N., & Fohrholz, C. (2016). Mobiles Business mit

ERP. In M. Knoll & S. Meinhardt (Eds.), Edition HMD.

Mobile Computing: Grundlagen - Prozesse und

Plattformen - Branchen und Anwendungsszenarien

(pp. 53–64). Springer. https://doi.org/10.1007/978-3-

658-12029-0_4

Harrison, R., Flood, D., & Duce, D. (2013). Usability of

mobile applications: literature review and rationale for

a new usability model. Journal of Interaction Science,

1(1), 2–16. https://doi.org/10.1186/2194-0827-1-1

Hofer, S., Wende, S., Will, A., & Züllighoven, H. (2007).

End User Development für Leitstand-Arbeitsplätze:

Beschreibung einer Systemarchitektur. In W. Bleek, J.

Raasch, & H. Züllighoven (Eds.), Software

Engineering 2007 (pp. 131–143). Gesellschaft für

Informatik e. V. https://dl.gi.de/handle/20.500.1211

6/22756

Hussain, A., Mkpojiogu, E. O. C., Fadzil, N., Hassan, N.,

& Zaaba, Z. F. (2018). A Mobile Usability Evaluation

of a Pregnancy App. Journal of Telecommunication,

Electronic and Computer Engineering (JTEC), 10(1-

11), 13–18. http://journal.utem.edu.my/index.php/jtec/

article/view/3843

Muccini, H., Di Francesco, A., & Esposito, P. (2012).

Software testing of mobile applications: Challenges and

future research directions. In D. Hoffman (Ed.),

Proceedings of the 7th International Workshop on

Automation of Software Test (pp. 29–35). IEEE.

https://doi.org/10.1109/IWAST.2012.6228987

Nayebi, F., Desharnais, J.-M., & Abran, A. (2012). The

state of the art of mobile application usability

evaluation. In A. G. Aghdam (Ed.), 25th IEEE

Canadian Conference on Electrical and Computer

Engineering (CCECE) (pp. 1–4). IEEE. https://doi.org/

10.1109/CCECE.2012.6334930

Nielsen, J. (1994). Usability engineering. Elsevier.

https://books.google.de/books?hl=de&lr=&id=DBOo

wF7LqIQC&oi=fnd&pg=PP1&dq=usability+engineer

ing+nielsen&ots=Bl75TNFWzT&sig=XTl3WVzyV8x

V_mLuOgxBPYEj1WU

Omar, K. (2015). Towards improving the usability of

mobile ERP. A model for devising adaptive mobile us

to improve the usability of mobile ERP. In D. W.

Cunningham, K. Meer, & I. Schmitt (Eds.), Informatik

2015 (pp. 1783–1794). Gesellschaft für Informatik e.

V. https://dl.gi.de/handle/20.500.12116/2165

Omar, K., & Gomez, J. M. (2016). A selection model of

ERP system in mobile ERP design science research:

Case study: mobile ERP usability. In Proceedings of the

13th International Conference of Computer Systems

and Applications (AICCSA) (pp. 1–8). IEEE.

https://doi.org/10.1109/AICCSA.2016.7945791

Omar, K., & Gomez, J. M. (2017). An adaptive system

architecture for devising adaptive user interfaces for

mobile ERP apps. In G. Issa (Ed.), Proceedings of the

2nd International Conference on the Applications of

Information Technology in Developing Renewable

Energy Processes and Systems (IT-DREPS 2017)

(pp. 1–6). IEEE. https://doi.org/10.1109/IT-

DREPS.2017.8277812

Omar, K., Rapp, B., & Gómez, J. M. (2016). Heuristic

evaluation checklist for mobile ERP user interfaces. In

7th International Conference on Information and

Communication Systems (ICICS). IEEE.

https://doi.org/10.1109/IACS.2016.7476107

Raptis, D., Tselios, N., Kjeldskov, J., & Skov, M. B. (2013).

Does size matter? In M. Rohs & A. Schmidt (Eds.),

MobileHCI'13: Proceedings of the 15th International

Conference on Human-Computer Interaction with

Mobile Devices and Services: Association for

Computing Machinery. https://doi.org/10.1145/24931

90.2493204

Schmutz, P., Heinz, S., Métrailler, Y., & Opwis, K. (2009).

Cognitive Load in eCommerce Applications—

Measurement and Effects on User Satisfaction.

Advances in Human-Computer Interaction, 2009, 1–9.

https://doi.org/10.1155/2009/121494

Singh, A., & Wesson, J. (2009). Evaluation criteria for

assessing the usability of ERP systems. In B.

Dwolatzky, J. Cohen, & S. Hazelhurst (Eds.), ACM

Digital Library, Proceedings of the 2009 Annual

Research Conference of the South African Institute of

Computer Scientists and Information Technologists

(pp. 87–95). ACM. https://doi.org/10.1145/1632149.16

32162

Tai, Y.-T., Huang, C.-H., & Chuang, S.-C. (2016). The

construction of a mobile business application system

for ERP. Kybernetes, 45(1), 141–157.

https://doi.org/10.1108/K-02-2015-0041

Trovarit AG. (2019). ERP in der Praxis – Trovarit – the IT-

Matchmaker. https://www.trovarit.com/erp-praxis/

Zali, Z. (2016). An initial theoretical usability evaluation

model for assessing defence mobile e-based application

system. In ICICTM '16: Proceedings of the

International Conference on Information and

Communication Technology (pp. 198–202). IEEE.

https://doi.org/10.1109/ICICTM.2016.7890800

Zhang, D., & Adipat, B. (2005). Challenges,

Methodologies, and Issues in the Usability Testing of

Mobile Applications. International Journal of Human-

Computer Interaction, 18(3), 293–308. https://doi.org/

10.1207/s15327590ijhc1803_3

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