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Mobile ERP Adoption Under Computer Self-Efficacy
Twenty-second Americas Conference on Information Systems, San Diego, 2016 1
Adoption of Mobile ERP in Traditional-ERP
Organizations: The Effect of Computer Self-
Efficacy
Emergent Research Forum Paper
Mousa Albashrawi
U Mass Lowell
1 University Avenue
Lowell, MA 01854
Mousa_Albashrawi@uml.edu
Luvai Motiwalla
U Mass Lowell
1 University Avenue
Lowell, MA 01854
luvai_motiwalla@uml.edu
Abstract
The objective of this research-in-progress paper is to investigate the employees’ intention to use mobile
ERP under the effect of computer self-efficacy in regular-ERP firms. Mobile ERP, business software that
integrates core business functions into a single system, has been increasingly penetrating the ERP market
but to the best of our knowledge there is no study has examined its usage intention among traditional-
ERP organizations. The updated DeLone and MacLean IS success model with its three quality factors is
employed in this study as a theoretical framework. Conclusion and potential contribution are discussed.
Keywords
Mobile ERP, adoption, IS Success model, computer self-efficacy.
Introduction
Mobile technologies have invaded the business world with promising huge benefits. Mobile technologies
can help organizations make faster and more informed decisions and allow them to capture unlimited
business opportunities (Charlton, 2014). Hence, many organizations have embraced this mobility trend
by adopting different mobile innovations, with the purpose of generating more profit and staying
competitive. One good example is mobile ERP, which refers to the use of mobile device (e.g. a smartphone
or tablet) to perform different business functions such as sales, customer relationship management and
supply chain management through a single integrated system. In other words, it is a tool used to carry out
business functions on-the-go. Mobile ERP promotes the concept of BYOD or “bring your own device” in
today enterprise domain; hence, it has been regarded as an emerging core requirement in the
contemporary business world (All, 2014). This technology shows an increasing utilization curve across
industries due to the real-time access to relevant information and to diverse functions (Schneider, 2013).
The market for mobile ERP is projected to continue to grow at a constant annual rate of 39% through
2017 (Trefis Team, 2014). This emerging phenomenon makes a close examination of the influential
factors to its wide adoption a timely and relevant research topic.
Although mobile ERP has the capability to help organizations in streamlining workflow processes,
increasing operational efficiency, deepening customer engagements and accelerating time-to-decision by
top management (Charlton, 2014), it might be still in the early adoption stage of product life cycle. This
stage provides an explanation of the current status of mobile ERP among traditional-ERP organizations,
which being described as those organizations that have implemented desktop ERP on their platform.
However, employees have become more technically savvy and their capability of handling information in
different IT contexts has been augmented in the recent years. The increase of employees’ computer self-
efficacy may increase the demand for organizations to adopt mobile ERP (Charlton, 2014). Our discussion
leads us to conclude how crucial the study of employees’ behavioral intention towards mobile ERP is to
understanding this developing market.
Mobile ERP Adoption Under Computer Self-Efficacy
Twenty-second Americas Conference on Information Systems, San Diego, 2016 2
Research in the area of mobile ERP is very scarce but a very few studies have been found addressing
different ERP topics. Kim (2013) collected data from 131 Korean manufacturing firms to determine how
internal control support of mobile ERP is related to quality and organizational performance. Felix and
Alain (2013) identified that adoption of mobile SCM can be predicted by technological factors and
organizational factors. This research gap in mobile ERP motivated us to explore this area through the
following research question: What drives usage intention towards mobile ERP considering the effect of
computer self-efficacy? Given the continued reliance on DeLone and McLean’s IS success model (2003), it
is adapted here to examine the postulated relationships in mobile ERP. This model has been validated by
multiple IS applications across different disciplines; approximately 6,575 articles adapted it as indicated
by Google Scholar. Since IS Success model focuses more on system-specific elements, computer self-
efficacy, which refers to an individual self-confidence of using a computer system is integrated to the
model to account for user- specific cognitive element and to reflect IT-specific individual differences.
The study contributes to theory and practice by 1) extending the ERP literature by considering a new
branch: mobile ERP. To the best of our knowledge, this is the first paper attempting to explore relevant IS
success factors and their impact on mobile ERP adoption among ERP-traditional organizations; 2)
providing practical insights to industry for both of the vendors and organizations. Vendors could improve
on the provided services by mobile ERP while organizations could gain a competitive advantage as first
movers to adopt.
Literature Review
To the best of our knowledge, mobile ERP adoption has not been investigated yet. Therefore we borrowed
literature from IS adoption research that implemented IS Success model as a theoretical lens and
examined various IT innovations (i.e., online learning and shopping systems, health infomediary and
mobile technologies). This research highlights the generalizability of IS Success model across different IS
artifacts. Also, some of those artifacts are similar to mobile ERP by being either enterprise system or
mobile system. Table 1 shows the significant predictors affecting behavioral intention in various IS
contexts.
Study
IS Context
Impacting factors
Song & Zahedi (2007)
Health infomediaries website
Ability, integrity, risk and benevolence
Lin (2007)
Online learning system
The three quality factors and satisfaction
Chen & Cheng (2009)
Online shopping system
The three quality factors and satisfaction
Kim et al. (2009)
Ubiquitous computing use
Accessibility, Information accuracy and
timeliness, and service quickness
Chatterjee et al. (2009)
Mobile work in healthcare
Portability, task structure, system
reliability and support
Xu et al. (2013)
E-commerce system
Usefulness and attitude
Table 1. A summary of studies conducted using IS success model
Few organizations generally get involved in the early adoption of a new technology. This adoption stage is
embedded with a chasm that reflects a recession in the market development (Moore, 1991). Once this
chasm is crossed, mobile ERP could get more exposure leading to generate a high adoption rate. We
believe that mobile ERP is still being marketed and tested across industries; thus, we are particularly
interested to explore the influential factors helping to cross this chasm and promoting mobile ERP to be
adopted on a larger scale among regular-ERP firms.
Research Model and Hypotheses Development
In order to better understand mobile ERP, this phenomenon is studied through the theoretical lens of IS
Success model (DeLone & McLean, 2003). This model has a primary goal of measuring success for any
new IS innovation; it has been widely used in IS research due to its specificity and generalizability.
Mobile ERP Adoption Under Computer Self-Efficacy
Twenty-second Americas Conference on Information Systems, San Diego, 2016 3
However, this paper examines usage intention of mobile ERP within regular-ERP organizations based on
system quality, information quality, service quality, and computer self-efficacy.
Figure 1. Research Model
System Quality
System quality encompasses the desirable characteristics that firms need to have in any IS; it can be
conceptualized in terms of ease of use, flexibility and intuitiveness (Petter et al. 2013). They suggest that
perceived system quality leads to intention to use IS. This relationship is empirically supported in online
learning course websites (Chang & Tung, 2008) and in online shopping (Chen & Cheng, 2009). According
to Kuan et al. (2008), system quality has a positive impact on usage intention of e-commerce. Therefore,
we hypothesize system quality in our research model as an independent variable:
H1: System quality is positively related to intention to use mobile ERP.
Information Quality
Information quality considers that the system outputs, such as reports, content and dashboards, are to be
characterized by relevancy, accuracy, understandability and completeness (Petter et al. 2013). They posit
that information quality relates positively to intention to use IS. This relationship has an empirical
support in online shopping (Chen & Cheng, 2009). As proposed by Kuan et al. (2008), information
quality can determine usage intention of e-commerce. Thus, we hypothesize information quality in our
research model as an independent variable:
H2: Information quality is positively related to intention to use mobile ERP.
Service Quality
Service quality refers to the degree of quality and level of support that mobile ERP can provide to firms; it
can be conceptualized in terms of responsiveness, reliability, technical competence, and empathy (Petter
et al. 2013). They theoretically propose that there is a positive relationship between service quality and
intention to use IS. This relationship is empirically corroborated in online shopping (Chen & Cheng,
2009) and as suggested by Kuan et al. (2008), service quality is an important predictor to usage intention
of e-commerce. Therefore, we hypothesize service quality in our research model as an independent
variable:
H3: Service quality is positively related to intention to use mobile ERP.
Computer Self-Efficacy
Bandura (1986) defines self-efficacy as: “People’s judgment of their capabilities to organize and execute
courses of action required to attain designated types of performance. It is not with the skills one has but
with judgments of what one can do with whatever skills one possesses (p.391).” Driven by this notion,
Compeau and Higgins (1995) develop computer self-efficacy and define it as “a judgment of one's
capability to use a computer (p.192)”. Although usage intention is mostly driven by emotional and
psychological factors, it can also be driven by cognitive factors like computer self-efficacy. This
relationship is empirically validated by Hsia et al. (2014); they indicate that computer self-efficacy affects
Mobile ERP Adoption Under Computer Self-Efficacy
Twenty-second Americas Conference on Information Systems, San Diego, 2016 4
positively the employees’ intention to use e-learning system in high-tech companies. Additionally,
different extensions of self-efficacy are found to be significant determinants, for example, web-specific
self-efficacy in adopting e-service (Hsu & Chiu, 2004) and internet efficacy in adopting online shopping
(Faqih, 2016). Thus, we conceptualize computer self-efficacy as an independent variable:
H4: Computer self-efficacy is positively related to intention to use mobile ERP.
Bandura (1986) suggests that self-efficacy generates a universal impact (direct and indirect effect) that
can be applied to various contexts. Wang et al. (2013) find that individuals’ purchase intention is
increased by ethical self-efficacy when their peceived value of online services is high. Likewise, mobile
ERP usage intention among individuals would be increased by computer self-efficacy when the levels of
easy-navigation, information relevancy and accuracy as well as service reliability and responsiveness are
high. From a practical perspective, firms usually strive to improve current services offered to their
employees. Hence, interaction variable may play a crucial role by providing valuable insights. This
interaction can help firms identify whether increasing the level of computer self-efficacy is crucial to
mobile ERP adoption through examining the relationship between the quality factors and usage intention
across employees. Thus, we conceptualize computer self-efficacy as a moderating variable:
H5(a): The higher computer self-efficacy, the greater positive relationship between system quality and
intention to use mobile ERP.
H5(b): The higher computer self-efficacy, the greater positive relationship between information quality
and intention to use mobile ERP.
H5(b): The higher computer self-efficacy, the greater positive relationship between service quality and
intention to use mobile ERP.
Research Method
Traditional-ERP organizations’ employees are considered our target population. In the process of building
our sample, we will start establishing a connection with some regional organizations that have
implemented regular ERP systems and then distributing the questionnaire electronically to survey their
employees. Structural equation modeling (SEM) technique will be employed to analyze the hypothesized
relationship between the latent variables using SmartPLS software.
The survey for this study will be developed using prior research instruments in which all factors are well-
established indicators and associated with a good reliability. These factors are adapted and modified to
reflect mobile ERP context. System quality, information quality and service quality are adapted from Zhou
(2013). Usage intention of mobile ERP is adapted from Hsu and Chiu (2004). Computer self-efficacy is
adapted from Compeau & Higgins (1995) to measure the employees’ technical capability.
Conclusion and Potential Contribution
Our study of mobile ERP would address a research gap found in literature and increase the understanding
of mobile ERP adoption in the current market. The updated DeLone and McLean IS Success framework
can be appropriately aligned with mobile ERP because it emphasizes aspects internal to the system. While
computer self-efficacy can help to determine whether regular ERP firms’ employees will embrace this
technology and use it.
The contribution of this study is twofold. First, it attempts to consider mobile ERP stream under the ERP
literature and to complement IS Success model by the cognitive factor of computer self-efficacy. Second,
the study results could identify important practical implications of mobile ERP. The results may help both
software vendors and regular-ERP firms in their decisions of whether to make the initiative and adopt
mobile ERP once understanding the surrounding circumstances of the current market. For software
vendors, they would be able to address firms’ areas of greatest concerns related to security, usability and
functionality. In addition, the vendors can increase their awareness about different regular ERP-firms by
scoping out their needs of mobile ERP and then attempting to satisfy those needs to increase the adoption
rate and accordingly their profit. For traditional-ERP firms, to be one of the first movers to adopt, it
would help to gain a competitive advantage and accumulate sufficient market share of mobile ERP
industry; this will lead to superior brand recognition and customer loyalty.
Mobile ERP Adoption Under Computer Self-Efficacy
Twenty-second Americas Conference on Information Systems, San Diego, 2016 5
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