Nowadays, information systems constitute an essential component of organizational management in order to improve efficiency and performance. However, many systems fail to achieve the expectations of its users, which negatively impact individual and organizational performance [3] [4] [5]. Therefore, the need for researches on successful operationalization of information systems emerged from these challenges and still continues to be an important subject of inquiry [6]. Thus, the evaluation of an IS being operationalized is a worthwhile undertaking to ensure its success and benefits [7]. One of the key aspects of IS success is the perceived satisfaction of its users [6].
2.1. IS user satisfaction as a measure of IS success
The IS user satisfaction reflects the degree at which a user feels an IS meets his needs and expectations [8]. The IS user satisfaction has been considered as an important element or even a surrogate of information system’s success, especially when the use of MIS is mandatory for the work [9] [7]. This assertion lies in that users are the ones who interact with an IS and know its functionality strengths and weaknesses, thus playing the role of evaluators [6] [10]. Besides that intuitive assertion, extensive researches have been conducted and found a correlation between user satisfaction and IS success [10]. Therefore, as measuring IS success is asserted to be difficult, satisfaction is usually used as a proxy measurement of IS success [11] [12].
2.2. Factors affecting user satisfaction
A variety of models have been elaborated to understand the factors that affect user satisfaction towards an IS. Among these, the most widely used are the DeLone and McLean (D&M) original and revised multi-dimensional and interdependent construct models [13] [7] [14]. According to the updated D&M model, the user satisfaction has been theorized as being associated to System quality, Information quality and Service quality [14] [15]. The model stipulates that the quality dimension of an IS has a positive effect on its use or intention to use and on its user satisfaction, which on their turn bring to IS benefits as shown in the Fig. 1 below [14].
According to D&M model, the system quality reflects the aspects of usability, availability, reliability, adaptability and response time; the information quality relates to the interface content issues, including personalization, completeness, relevance, ease of understanding and security; the service quality is concerned with support provided to the users whether coming from internally or externally to the organization; the use measures the aspects of navigation, retrieval of information and execution of operations; the user satisfaction captures user’ opinions through his experience while interacting with the system; and finally, net benefits direct to impacts realized whether positives or negatives [14] [15].
The model suggests that the results of IS quality are iteratively interrelated [14]. In fact, the system use must precede user satisfaction, but also a good experience of use (user satisfaction) would lead to the intention to and use of the system[7] [14] [15]. On the other hand, the system use and user satisfaction would result in net benefits, but the net benefits would also result in intention to use and user satisfaction [14]. A variety of empirical studies have been conducted and validated the D&M IS model. Most of these studies used quantitative design and found significant relationships between quality of IS and user satisfaction as well as a positive relationship between user satisfaction and IS benefits [16] [17] [18] [19] [20] [21] [22].
D&M IS model was criticized for its difficulties of application due to different contexts of IS researches, modelling processes with causal explanations resulting in confusing meanings, and limited coverage of dependent variables as there are many other possible categories of measures varying from users to users [23][14] [15] [10] [24] [25]. Thus, a variety of other IS success models were referred on and others surged including technology acceptance model, human-organizational-technology and fit model, technology-organization-environment model, and innovation dissemination theory [13] [7] [26].
2.3. Other main models of IS success
a. Technology Acceptance Model (TAM)
According to this model, the IS success is characterized by the extent of user acceptance measured through the actual use, while the underlying factors of that acceptance are the perceived usefulness and the perceived ease of use [27] [28]. The mode defines perceived usefulness as the extent to which users believe the information system is important in helping them for completing their job requirements, while perceived ease of use is defined as the extent to which users believe the system is used without efforts [27]. The model recognizes that these two factors are influenced by external factors which can include social, cultural and political factors [27] [29]. As illustrated in the Fig. 2 below, the model stipulates that the perceived usefulness and ease of use influence the attitudes towards the use of technology, and those attitudes influence intention to use the technology, whereas that intention leads to the actual use of technology [27].
Many studies have been conducted and validated the TAM, highlighting the significance of the relationship between perceived usefulness and perceived ease of use on technology acceptance [28] [29]. However, there have also been a high number of studies where the findings did not fit to the TAM model [30].
b. The Human-Organizational-Technology (HOT) fit model
The HOT fit model assumes that the effectiveness of an IS depends on the alignment of human factors, organizational structures and technology, with perspective of understanding IS success through a complex interplay between people, organizations and technology [31]. The human attributes reflect individual characteristics and interaction such as knowledge, skills, capabilities, motivation, position, tasks, collaboration, communication, competition and supervision; the organizational structures encompass internal and external organizational management environment and traits such as organizational size, culture, policies and strategy, practices and government regulations; while technology relates to the IS characteristics and requirements such as software, hardware, network tools, professional skills, systems quality, information quality, service quality and social presence [31].
Numerous studies have been conducted with hypothetical assumptions based on the fact that, when an information system is well aligned with the individual attributes, the organizational management practices as well as the technological equipment and tools in place, that system leads to higher user satisfaction, increased productivity, and improved system performance [32] [33]. Thus, the underlying technology adoption factors highlighted in these studies include: (i) training, perception, roles, skills, clarity of system purpose and user involvement as human attributes: (ii) leadership and support, process, participation or user involvement, internal communication and inter-organizational system as Organization factors; and (iii) ease of use, system usefulness, system flexibility, time efficiency, information accessibility and relevancy as technology factors [32] [33].
However, the literature emphases on the necessity for constant re-alignment of HOT components [31]. In fact, the alignment has to be dynamically adapted due to constant technological changes and evolving needs of the organization [31]. The literature also points out the nuances and complex interactions between HOT components and recommends further researches for exploring those interactions as well as their implications for emerging technologies and workplace dynamics [31] [34].
c. The Technology-Organization-Environment (TOE) model
The TOE model focuses on technological, organizational and environmental factors for modeling the technology adoption and innovation within organizations [35]. Technological factors capture the key characteristics of the technology under consideration, including the complexity of the technology and its compatibility with existing systems [36] [37]. The technological factors cover the internal characteristics and capabilities of an organization such as organization's absorptive capacity, leadership and innovation culture [36]. The environmental factors include the elements that are external to the organization, but crucial in shaping technology adoption in an organization such as industry regulations, pressure from competitors and market trends [36]. Studies have shown the relevance of the TOE model, highlighting specific elements that influence the technology adoption such as connectivity, IT capabilities and management support [36] [37].
d. Innovation dissemination theory (IDT)
The IDT theory explains the success of an information system in terms of gradual technology adoption. According to this theory, the extent of technology adoption pass through a diffusion process and communicated overtime throughout members of an organization [38]. In the context of an IS, an innovation is defined as a technology that is perceived as new by its users, even if it has been long on the market, and it is manifested through their knowledge, persuasion and decisions [38]. Thus, the key point of IDT model is one of achieving convergence in understanding and adopting the technology through a framework of information sharing where change agents and opinion leaders can play significant influence towards desired practices [38] [39]. This state of adoption depends on five main factors: perceived attributes of innovation, type of innovation-decision, communication channels, nature of the social system, and extent of promotion agents’ efforts [39].
2.4. User satisfaction and individual performance
The measurement of net benefits in terms of individual or organization impact, as results of system’s qualities, use and user satisfaction, has been advocated. For instance, D&M have advocated for this measurement, cautioning researchers not to limit their investigations on use and user satisfaction as measures of IS success, but also extending them towards benefits realized in terms of performance [14]. Therefore, measuring the impact of user satisfaction on individual work performance is essential and add value to the existing literature on IS success.
IS impact to individual performance is defined as the extent to which the individual perceives the level of productivity due to the use of IS [40]. While many studies found positive impact through increased quantities and quality of productivity, some studies indicated that IS use had negative or neutral impact on individual performance and social life of its users [8] [40] [18] [41].
2.5. Critical analysis and conclusion
The D&M and subsequent models intended to associate IS qualities with user satisfaction or technology adoption in terms of causal relationship of dependent and independent variables. However, the intuitive nature of the relationship is internal rather than external. When a user appreciates positively or expresses difficulties with an aspect of an IS quality or use such as ease of use or usefulness of the information generated by an IS, it is a means of expressing his satisfaction or dissatisfaction with the IS use or usefulness. Therefore, this study will focus on understanding the reasons, issues and challenges as characteristics underlying a certain level of satisfaction rather than understanding it in terms of correlation and causality.
Most of researches conducted are quantitative, exploring the relationship between user satisfaction and the IS qualities through a number of dependent and independent variables [15]. However, understanding challenges and issues with user satisfaction might not be limited to parametric models and pre-defined variables [14] [24]. In addition, there is a divergence on how IS quality variables are measured and critics on their reliability [8]. This implies that researches must give the flow to the users to express their concerns as measures of IS qualities. Thus, this study will integrate a qualitative component that will further the understanding of the issues of healthcare providers while using the system. Therefore, the D&M and other models that subsequently emerged were adapted in the conceptual framework of this study as shown in the Fig. 3 below:
D&M recommended researchers to select a small number of measurements while using their model [14] [15]. However, many of the quantitative studies conducted generally used long questionnaires and many questions had similarities, which raise confusions in distinguishing variables [13] [14] [15] [19] [20] [42]. This study used a concise questionnaire with a single question addressing user satisfaction and another one addressing its perceived impact on work performance of the users. In this study, the aspects of IS qualities and other issues characterizing user satisfaction and how they affect the individual work performance were obtained through qualitative questions. This enables discerning user judgments, avoiding a blurt in expressing their experience and letting the flow of the expression for the qualitative component of the questionnaire.
2.6. Summary and gap in the literature
The D&M model has been essential in explaining IS success through user satisfaction and quality characteristics of an IS. Following the critics on the D&M model, further researches have been conducted through a variety of other models and elaborated other factors that affect IS success including perceived ease of use and usefulness of IS, trustworthiness, top management support, design of user requirement, having been trained, computer literacy, organizational structure and management style [26] [27] [28] [29] [30]. Despite a multitude of those models, no one is claimed to exhaustively explain all the elements of an IS success. However, qualitative studies can effectively capture a wide range of IS characteristics underlying the status of IS success taking into account the specificity of organizations, but this approach remains under-explored. Thus, this study uses a mixed research approach in order to take advantage of benefits of both quantitative and qualitative approaches for analyzing the extent of an IS success as well as the underlying issues in the context of a specific hospital.