FINANCIAL TECHNOLOGY AND OTHER RELATING ISSUES
2. Literature review and research model
2.1.1. Quality of Information System
According to DeLone & McLean, 2016, system quality is associated with success and they use a scale of quality of information system consistent with the developed model, including: ease of use, system functions, reliability, flexibility, data quality, portability, integration, and materiality. In the successful information systems model, DeLone & McLean (2003) proposed that the success of the information system is considered through six factors, namely: (1) system quality, (2) quality of information, (3) quality of service, (4) use of the system, (5) user satisfaction and (6) net benefit. Information system quality is concerned with measuring the desirable system characteristics: availability, validity, reliability, adaptability, and response time. In the study of Peter et al (2008) on measuring the success of information systems in relation to models, aspects, building scales and relationships, the author said that the quality of information systems shows desirable system properties such as ease of use, flexibility, reliability, ease of understanding, system sophistication and response time.
2.1.2. Top management support
Top management support is defined as the ability of companies to grow and to have the support and commitment of managers to create and build knowledge within the organization (Akgun et al, 2007). Senior managers play an important role in developing and committing to a working environment within the organization. Through commitment and support, managers create a work environment that provides guidance, feedback, constructive criticism, and empowers employees to work and make decisions, become to part of IS usage (Goh, 2003). In addition, top management support meaned those managers are willing to provide additional resources, acquire new options, and make the necessary changes to promote employee use of the system. In this way, management can effectively build and support a work environment that helps their organization survive and sustain itself.
2.1.3. Facilitating condition
Facilitating condition refers to the personal belief that the technical environment and infrastructure exist to support the use of IS (Chan et al, 2010), a concept that influences using the technology identified by Venkatesh et al (2003). In this study, Venkatesh argues facilitating conditions do not affect behavioral intention but affect usage behavior. Facilitating involves the availability of sufficient resources and support for individuals to use technology (Neslin & Shankar, 2009). Lack of timely support, inadequate information and limited resources can prevent individuals from accepting the use of technology.
2.1.4. Usage of information system
The behavior of usage IS according to the TAM model is influenced by the perceived usefulness of IS (Davis, 1989). According to these theories, using IS is the behavior of the user to manipulate IS during the operation on a regular basis, repeating and expected to continue in the future. The view of usage IS has been inherited and used in many studies on choosing and using an ERP system (Nwankpa, 2019). Using ERP refers to how users use ERP features to perform tasks and run jobs (Nwankpa & Roumani, 2014). If the process of usage IS fails or the user does not use it correctly, the system will develop serious problems, usage IS is understood as a user using IS components and tools including using using software in processing, participating in using prodedures and processes in the system and under the supervision of system security control procedures. Usage Information system increased performances and operations efficiency especially in large companies and as well good management of resources and better control of expenditure, budgeting, and forecasting.
Information systems also provide information on both actual and budgeted data which would help companies to establish, plan and control operations (Tilahun, 2019). Studying the usage IS in this topic and the factor affecting the usage IS to explain the actual usage IS in Vietnamese enterprises.
2.1.5. User satisfaction
System user satisfaction describes the user's feeling after interacting with the system, which is the degree to which users believe that a system available to them meets their expectations (Ives & Olson, 1984). This element describes an individual's attitude and perception towards the system they are using to perform a task. Besides, user satisfaction is the most common success measure to evaluate the success of IS (DeLone & McLean, 2016).
Furthermore, empirical research showed a significant influence on user satisfaction on individual impact (Iivari, 2005; Petter & McLean, 2009; Urbach et al, 2010). Since user satisfaction is considered one of the main indicators when assessing the success of new system adoption, it has been widely used as a metric in the IS field (DeLone & McLean, 2016; Montesdioca & Macada, 2015). According to Xinli (2015), user satisfaction refered to the extent to which users perceive a system as useful and want to use it again. While Lin &
Wang (2012) defined it as the satisfaction of system users in terms of speed, quantity of
functions, quality and format of the system. Several studies have shown that user satisfaction affects performance in many IT contexts and applications.
2.2. Theoretical basis
2.2.1. Unified Theory of Acceptance and Use of Technology (UTAUT)
Models in the theory of technology acceptance are useful for the assessment of technology acceptance and use. These models provide an explanation of the factors that predict adoption and usage (Sun & Zhang, 2006; Venkatesh et al, 2012). The Technology Acceptance Model (TAM) is one of the most widely used in technology acceptance researches (Davis, 1989; Ajzen & Fishbein, 1975). TAM and its citations have been frequently used in researches to investigate technology adoption (Sun & Zhang, 2006;
Venkatesh & Bala, 2008; Venkatesh & Davis, 2000). However, TAM only predicts acceptance in less than 50% of cases related technology adoption (Venkatesh & Davis, 2000).
To tackle the drawbacks of TAM, Venkatesh et al (2003) proposed the UTAUT model based on in-depth analysis of the literature on technology acceptance. UTAUT is a popular choice in papers so it is a unified model that integrates the different variables from many different prominent theories. This model includes four basic determinants of technology adoption:
performance expectancy, effort expectancy, social influence, and facilitating conditions.
Facilitating conditions is the degree to which people believe that an organization and technical infrastructure exists within the organization to support training in the usage of IS, and according to this theory, facilitating conditions are assumed as a determinant of usage IS.
2.2.2. Information system success model
Although user acceptance of the system is a prerequisite for IS success, this factor is not equivalent to IS success (Petter et al, 2008). Thus, DeLone & McLean developed a model that can deal with the complexity, interdependence, and multidimensional nature of IS and can assess the success of IS implementation. Aspects of success were identified as user satisfaction, intention to use, use, individual and organizational impact. Thereafter, individual, and organizational effects have shaped another aspect of success, that of net benefit (Delone
& McLean, 2003). In the model DeLone & McLean (2016) identify six interdependent aspects of IS success: information quality; quality System; service quality; use the system;
user satisfaction; net benefits. In which, the use of IS has a strong impact on the system user’s satisfaction.
2.3. Reasearch model and Hypothesis
2.3.1. The relationship between Top management support and Usage of IS
In this study, top management support refers to the extent to which top management understands the importance of IS and the extent to which senior management is involved in system implementation. Drawing from previous research on IT implementation (Pijers et al, 2001; Ragu-Nathan et al, 2004), this study argues that the support of top leadership is crucial in enhancing the integration of technology into the business strategy, facilitating the
implementation of the system in different ways. First, the most difficult and challenging system implementation involves the major changes that need to be made in organizational and business processes (Davenport, 1998). These changes can be met with resistance from various interest groups in the organization unless there is absolute commitment from the top management (Grover et al, 1995). Second, system implementation involves a program of large-scale organizational preference-changing initiatives, not software installation efforts (Hong & Kim, 2002). Senior manager responsible for resolving deviations between the needs of the organization and the IS function. Third, given the widespread influence of system implementation on business processes and practices, senior management intervention is required to facilitate the allocation of necessary resources in the implementation IS.
Ultimately, senior management cannot force organizational members to be satisfied with the use of new technology. User acceptance of an ERP system is critical to an organization performance. Top management support can be found to encourage positive user attitudes towards ERP system (Hirt & Swanson, 2001; Wang & Chen, 2006). Therefore, the level of senior management support can promote more successful usage of the system. From that result, the author gives the hypothesis:
H1: Top management support has a positive effect on usage of IS.
2.3.2. The relationship between system quality and usage of IS
System quality refers to the quality of the performance of the information system and its functionality (DeLone & McLean, 2016). System quality can be defined as the desirable characteristics provided by an information system (Petter et al, 2008). System quality is the key factor for the success of the information systems (Delone & McLean, 2016). From a different viewpoint, Hassanzadeh et al (2012) noted that the system quality affects learners’
satisfaction and intention to use, leading to enhanced learner usage of the elearning system.
Mohammadi (2015) found that system quality is the key predictor of satisfaction and intention to use. This leads to the following hypothesis:
H2: System quality has a positive effect on the usage of IS 2.3.3. The relationship between facilitating condidtions and usage of IS
UTAUT is an integrated model that acts as a valuable tool for researchers to assess the likelihood of a new technology being successful (Venkatesh et al, 2003). The proposed UTAUT model has been appropriately validated to provide a unified theoretical basis for advancing information systems (IS) research or IT adoption and dissemination. The four core parameters suggested by this model to directly determine IT behavioral intentions and usage include performance expectations, effort expectations, social influence and facilitating conditions. Several researchers have confirmed that IS usage is influenced and determined by facilitating conditions (Nistor et al, 2013; Tosuntas et al, 2015). Thus, the hypotheses offer:
H3: Facilitating conditions has a positive effect on the usage of IS
2.3.4. The relationship between usage of IS and user satisfaction.
According to DeLone & McLean (2016), actual usage is the extent to which an individual uses the capabilities of an information system in terms of frequency, nature, and duration of use. In an IS, actual use also reflects the frequency and duration of use (Kim et al, 2007). DeLone & McLean (2016) also point out that one of the most important directions in the use of technology is the need to assess the impact of system usage on IS success factors such as performance. Several studies have examined the effect of actual usage on performance and satisfaction (Hou, 2012; Son et al, 2012). Despite mixed results, it was determined that there is a significant relationship between actual usage and employee satisfaction levels (D'Ambra et al, 2013; Isaac et al, 2017; Makokha & Ochieng, 2014;
Ramirez-Correa et al, 2017). This study examines the effect of actual usage on employee satisfaction. Therefore, the following hypothesis is proposed:
H4: Usage of IS has a positive effect on user satisfaction.
Figure 1. Research model
3. Research methodology 3.1. The instrument
In this study, the author carried out quantitative research method. The important content in quantitative research is a detailed questionnaire with information about the scales related to the measurement of facilitating conditions (FC) according to the scale of Chauhan
& Jaiswal (2016) specifically, the FC scale includes 4 observed variables (FC1 to FC4), the top management support (TMS) scale includes 4 observed variables (TMS1 to TMS4) from the scale of Lin (2010), the usage of information system (UIS) scale includes 3 observed variables (UIS1 to UIS3) from the scale of Chang et al (2008); Schwarz (2003), the user satisfaction (US) scale includes 4 observed variables (US1 to US4) from the scale of Costa et al (2016). The scale system quality (SQ) variable is a result scale, including 6 observed variables (SQ1 to SQ6), measuring the quality of IS, selected by the author from the study of DeLone & McLean (2016). These observed variables are measured on a 5-point Likert scale (1: Strongly disagree; 5: Strongly agree).
3.2. Sampling
The data collection tool in the study is a questionnaire, the author conducts direct and indirect survey of individuals who using directly IS and individuals participating in using IS in the ERP environment. The research is mainly conducted in enterprises in Ho Chi Minh City and some other provinces from March to May 2021. Sample 110 was chosen according to the non-probability method, with this approach, the author has collected the necessary sample size for the study.
The sample of 110 surveyed individuals included: 72 employees (65.4%) and 38 managers who have used IS (34.6%), 54 male (49%) and 56 women (51%). Number of respondents aged from 30 to 40 accounts for the highest proportion of 68 people (61.8%).
Professional qualifications accounting for the highest proportion are university (69.2%), followed by postgraduate (20.2%) and college 10.6%. Work experience of employees accounts for the highest rate from 5 to 10 years (43.3%), work experience of less than 5 years accounts for 29.4% and work experience over 10 years has the rate 27.3%.