1. Introduction
On 25 January 2022, the UAE government launched the “Big Data Sustainable Development” under the UN platform as part of the 2030 Agenda for Sustainable Development [
1]. The UN 2030 Agenda for Sustainable Development focuses on goals under the UN Millennium Development Goals [
2]. Big Data Sustainable Development is a part of the UAE’s national agenda for harnessing the power of Big Data to provide better quality of life and development for its residents [
3].
The UAE is, therefore, committed to sustainable development by harnessing the potential of emerging technologies such as Big Data. The role of the government as an active agent in promoting, creating, originating the Industrial 4.0 and Big Data environment and the issues that are related to the data sharing policies and human skills [
4]. Smart government initiatives on the smart grid, such as smart transportation, smart health, smart governance, and public safety and security in Dubai, spur various applications leveraging big data analytics [
5]. Even though the Big Data initiative is new, a plethora of research work has been conducted to investigate various aspects of Big Data implementation. Predominantly, research is emerging on the challenges, impact, and benefits of Big Data Implementations [
6], but very little research has been conducted on the critical success factors for continued success of Big Data in organizations. For example, Big Data Analytics has attracted research interest in analyzing public satisfaction in relation to the service quality. In a similar fashion, a study revealed that perceived usefulness, perceived ease of use, and social influence were the factors that influenced the net benefit which is used to measure the success of implementing big data analytics in the information system [
7].
Another study that involved two government agencies in Dubai [
1] indicated that the quality of Big Data has a significant impact on the quality in decision making that is based on the information system [
8]. Additionally, several other studies had been conducted to address various issues that lead to sustainability of Big Data implementation with respect to economic, environment, social performance [
9], sales growth [
10], supply chain management [
9], and improving the effectiveness of accountants [
11].
However, while there has been some research focusing on the investigation of critical factors in implementing Big Data initiatives, there is less evidence of research on the perceptions of employees from the organizations adopting Big Data. Bearing in mind the fact that the UAE government spends 17.32% of the 1.98 billion spent in the MEA [
12] on Big Data applications and implementation, it is essential that the sustainability of Big Data Implementation can be studied and evaluated. From the perspective of IT experts, more attention should be devoted to how to manage Big Data solutions after the introduction [
13]. The current study is, therefore, aimed to study the critical success factors that enable sustainability for Big Data implementation in the UAE, both in the public and private sector organizations. A recent study has already indicated that in one of the public sector organizations, RTA, the employees are positive towards the implementation of AI and Big Data initiatives [
14], and the current study intends to add to the literature in terms of exploring perceptions of the employees regarding the factors that have been considered in implementing Big Data and the sustainable implementation of the programs. By doing this, the study aims to contribute to fill the gap in literature and give insights about employee perceptions about Big Data sustainable implementation and critical success factors. More specifically, the current study aims to answer the following research questions:
- i.
What are the critical success factors for Big Data sustainable implementation in the public and private sector organizations, as perceived by their employees?
- ii.
What is the perception of employees towards Big Data sustainable implementation in their organizations?
- iii.
What is the perception of the employees towards Big Data sustainable implementation’s impact on business performance of their organizations?
The following sections present a review of the extant literature, followed by conceptual framework and the development of research hypotheses. This is followed by a section on research methodology, then findings and finally discussion and conclusion.
3. Conceptual Framework and Hypotheses
The critical success factors for Big Data success have been identified at various past research, as discussed in the literature review above. However, a comprehensive model of assessing these factors over the longer term to gauge the sustainability of Big Data Implementation is not available, though guidance can still be drawn from the theoretical models of TAM, TOE, and UTAT. However, the theoretical models are overly dependent upon the perceptions of people about the usefulness, benefits, risks, ease of use or quality of new technology available to them and maybe there is a lack of objective evaluation of the situation from the technical and organizational perspectives. Additionally, another limitation of the above models is that they predominantly guide the assessment of initial adoption of new technology, rather than provide a framework to assess the sustainability of implementation of the technology. On the other hand, some scholars have found it more useful to take the organizational maturity models as the theoretical framework. For example, Klievink et al. [
28] employ constructs such as organizational readiness, which, while focusing on organizational technological capabilities, organizational e-governance maturity levels, along with organizational IT strategy alignment with business goals. However, Klievink et al. [
28] fall short of focusing on people related factors that have been found essential in Big Data implementation by other scholars [
23,
36].
As such, the current study develops a more eclectic theoretical framework for studying the independent factors that impact on long-term sustainability of Big Data implementation. Since, most studied critical success factors that relate to success of Big Data implementation are categorized around three broad areas—technological factors, organizational factors and people factors, the current research, too, conceptualizes a model with these three broad factors as the independent influencers of Big Data sustainable implementation.
More specifically, the technological factors are derived from the work of Wamba et al. [
17], where factors such as Big Data Infrastructure quality is considered to be high if it is interoperable, scalable. Additionally, from the work of both Wamba et al. [
17] and Hung et al. [
23] where the quality of Big Data architecture is found to be linked with its being adaptable or compatible to various types of data [
17,
23]. Additionally, the work of Comuzzi and Patel [
19] and Eybers and Hattingh [
20] indicated additional factors linked to the overall construct of Big Data quality architecture and included technological factors such as storage systems and database management systems that were connected across the organizational stakeholders and suitable for handling the volume, velocity, variety and the changing dynamics of Big Data analytics systems.
We therefore suggest the following hypothesis based on the above research:
H1. Big Data Infrastructure Quality positively and significantly impacts on the long-term sustainable implementation of big data applications.
The current study evaluates the perceptions of the UAE employees toward Big Data infrastructure quality, by using the items on scalability [
43], compatibility [
25] and connectivity [
26] of Big Data architecture employed by the organization (see
Table 1).
Next, organizational readiness is a latent construct that includes factors such as organizational alignment, organizational maturity and organizational capabilities. The works of Klievink et al. [
28] and Chen et al. [
30] that present organizational readiness as a factor impacting Big Data implementation, through organizational value creation alignment with Big Data strategy, organizational e-governance maturity level, and organizational capabilities such as Big Data governance framework and Big Data expertise are used. Additionally, organizational capability is expanded through the works of Soon, Lee and Boursier [
33], Gao, Koronios and Selle [
18] and Adrian et al. [
34], who have found linkages between organizational capability of having skilled data experts with the organization as a critical success factor for Big Data Implementation. Based on this literature, the following hypothesis is suggested:
H2. Organizational readiness positively and significantly impacts on the long-term sustainable implementation of big data applications.
The current study evaluates the perceptions of employees toward their company’s readiness, which is measured by using items on organizational alignment with Big Data Strategy [
30], e-governance maturity level [
28], and organizational capabilities Klievink et al. [
28], see
Table 1.
Additionally, personal factors such as openness to novelty and an experiential style of thinking have also been found to have a positive impact on the long-term sustainable implementation of big data applications. As such, the following hypotheses are proposed:
H3. Human Cognitive factors positively and significantly impact the long-term sustainable implementation of big data applications.
The current study evaluates the perceptions of employees about their cognitive styles which is measured by using items on organizational alignment with Big Data Strategy [
30], e-governance maturity level [
28], and organizational capabilities [
28], see
Table 1.
Additionally, the research also hypothesized that the Humans’ cognitive styles may be having a moderating impact on the effectiveness of other factors such as quality of infrastructure, organizational readiness, and long-term sustainable implementation of Big Data.
H4a. Human Cognitive factors positively and significantly moderate the relationship between Quality of Big Data infrastructure and long-term sustainable implementation of big data applications.
H4b. Human Cognitive factors positively and significantly moderate the relationship between Organizational Readiness and long-term sustainable implementation of big data applications.
It is also essential to note that Big Data implementation sustainability is a construct that is reflective of consistent and expanding usage of Big Data in organizations [
39]. As such, the current study measures sustainable implementation of Big Data using the construct developed by Urbach et al. [
39], on usage of Big Data technology, (see
Table 1). This will be the dependent variable for the current study and will be used to measure the UAE employees’ perceptions toward the sustainable implementation of Big Data. In addition, the employee’s perceptions towards their company’s Business performance will also be assessed in order to test the following hypothesis:
H5. Sustainable implementation of Big Data positively and significantly impacts business performance.
Business performance is assessed through employees’ perceptions about their company’s performance on revenue enhancement, customer satisfaction and employee satisfaction, which are the performance indicators used to evaluate performance [
37,
38,
40,
41,
42], see
Table 1.
The following
Figure 1 shows the conceptual framework of the research:
Latent Variable 1 =BDAQ—Big Data Architecture Quality (IV)
Latent Variable 2 = OR—Organizational Readiness (IV)
Latent Variable 5 = HCF—Human Cognitive Factors (IV/Moderator)
Latent Variable 3 = SI—Sustainable Implementation of Big Data (DV)
Latent Variable 4 = BP—Business Performance (DV)