The economic dimension encompasses various aspects of economic functioning and development. It includes subdimensions such as:

1. Labour Market, Efficient Labour Allocation, and Skills Improvement. This involves managing supply and demand for labor, optimizing labor resources for productivity, and improving workforce skills through education and training programs.

The technical dimension encompasses technological aspects within a system or organization, including hardware, software, networks, and procedures. It involves the development, implementation, maintenance, and optimization of specific goals or objectives. The technical dimension consists of the following subdimensions:

1. Administrative processes, which include simplifying and enhancing administrative processes, including improving workflow and document management.

Competitive advantage is the ability to produce services of good quality, and it is considered a strong motivator that pushes to exert more effort, to continuously improve performance at all levels within organizations, and to reach development (Hadj et al., 2020).

In this study, the researchers define it as the totality of capabilities and modalities that the Kingdom of Saudi Arabia seeks through economic and technological dimensions to achieve a global competitive advantage through the 2030 vision.

The 2030 vision of the Kingdom of Saudi Arabia is a document based on a set of pillars and relies on three axes: a vibrant society, a thriving economy, and an ambitious nation. It is also a post-oil plan announced on 25 April 2016 (Vision, 2030, 2016).

In this study, the researchers define it as a set of measures that the researchers will take to benefit from it to know the effectiveness of applying the economic and technological dimensions of the 2030 Kingdom of Saudi Arabia vision to achieve competitive advantage (Khashan, 2017).

Tracking the relationship between leaders’ mastery of tacit knowledge management skills and the achievement of competitive advantage, Aldosari (2023) explored the relationship between leaders’ mastery of tacit knowledge management skills and the achievement of competitive advantage at universities. The study was conducted using qualitative research methods and interviews with university leaders. The findings indicate that the mastery of tacit knowledge management skills by leaders is important for achieving competitive advantage at universities. The study also found that leaders’ mastery of tacit knowledge management skills is associated with increased innovation, improved collaboration, and better decision making. This study provides valuable information on how universities can leverage the skills of their leaders to achieve a competitive advantage.

In the context of understanding the effectiveness of the Saudi Arabian government’s Vision 2030 plan in creating a knowledge-based economy, a study by Amirat and Zaidi. (2020) examined the effectiveness of the Saudi Arabian government’s Vision 2030 plan in creating a knowledge-based economy and how it will impact the country’s GDP growth (Triki et al., 2023). It uses a combination of quantitative and qualitative methods to analyze the potential impact of the plan, including an analysis of the existing economic environment and the potential effects of the plan on the labour market, infrastructure and the overall economy. The results suggest that the Vision 2030 plan could significantly increase GDP growth in Saudi Arabia, but more analysis and research is needed to confirm this.

Similarly, another study by Alharbi (2018) looks at the readiness of the Saudi healthcare system to change in the context of the Saudi National Healthcare Plan in Vision 2030. This study includes a review of the literature on the current evidence on the readiness of the Saudi healthcare system for change and an analysis of factors that may impede or facilitate the adoption of innovation in the Saudi healthcare system. The research also uses a qualitative method to analyze the perceptions of experts in the field who were asked to provide their opinions on the readiness of the healthcare system to change. The results of the study suggest that the Saudi healthcare system is not fully prepared to change, and several challenges must be addressed to adapt to the changes proposed by the National Healthcare Plan in Vision 2030.

In the framework of analytical studies and exploratory studies about green marketing dimensions positively impacted environmental preservation, the study by AL-Ghaswyneh (2021) examined how applying green marketing dimensions, such as product design, pricing, and promotion, can help preserve the environment according to the objectives of Vision 2030 in Saudi Arabia. The study focused on the Northern Region Cement Company (NRC). The research methodology used was a survey of NRC customers, followed by stakeholder interviews. The results showed that the dimensions of green marketing positively impacted environmental preservation, with customers and stakeholders showing a preference for sustainable products (Vision, 2030, 2016). The study concluded that green marketing should be used to help achieve Vision 2030 objectives in the region.

In the context of understanding the use of governance to gain competitive advantages, Ahmadani. (2020) examined the impact of governance on achieving competitive advantages in firms (Triki et al., 2023). The authors used a qualitative approach, conducting semi-structured interviews with 10 top-level managers in companies in three countries. The findings suggest that governance plays an important role in providing firms with competitive advantages, particularly in terms of strategic decision making, organizational efficiency, and risk management. The study also found that firms with better governance practices tend to be more successful in the long run. The results of this study provide valuable information on how companies can use governance to gain competitive advantages.

To explore the relationship between proactive environmental innovation and firm financial performance, a study by Johl and Toha. (2021) examined the relationship between proactive eco-innovation and financial performance in the context of a circular economy. The authors analyze data from more than 3,000 publicly traded companies in the United States, Europe, and Asia-Pacific regions to explore the relationship between proactive ecoinnovation and firm financial performance. The authors hypothesize that proactive eco-innovation is positively associated with firm financial performance and that the relationship is stronger when considering the circular economy perspective. The authors then conduct a multilevel regression analysis to test their hypothesis. The study results indicate that proactive eco-innovation is positively associated with firm financial performance and that the strength of the relationship increases when considering the circular economy perspective. The study provides evidence for the importance of eco-innovation in the context of a circular economy and the potential for firms to benefit financially from proactive eco-innovation.

Lastly, to focus on developing 21st-century skills, Allmnakrah and Evers. (2020) study examined the need for a fundamental shift in the Saudi Arabian education system to implement the Saudi Arabian Economic Vision 2030. The authors review existing literature on the current state of the Saudi education system and the challenges and opportunities that accompany implementing a shift toward Vision 2030. The authors suggest that the Saudi education system should focus on developing 21st century skills, such as critical thinking and creativity, while highlighting the importance of technology and innovation. The authors also discuss the need for increased collaboration between the government, the private sector, and educational institutions in order to ensure successful implementation. Finally, the study provides recommendations on how the Saudi education system can be reformed to meet the goals of Vision 2030.

The competitive advantage of the Hail region in Saudi Arabia’s Vision 2030 can be seen in the application of both economic and technological dimensions. This research will discuss the region’s potential for economic and technological development to create a competitive edge. To explore this potential, it is important to analyze the theory of technological innovation and evolutionary economics.

The study was limited to identifying the effectiveness of applying the economic and technological dimensions of the Kingdom’s 2030 vision in achieving competitive advantage. The study consists of two dimensions: the economic dimension and the technological dimension. Dimensions will be essential in the field study. The study sample consisted of faculty members from Hail University in the Kingdom of Saudi Arabia. The study was carried out in the academic year 2022.

After identifying the study problem, questions and objectives, the data collection stage related to determining the perceptions of faculty members at Hail University in the Kingdom of Saudi Arabia was carried out according to a set of steps, which are as follows.

The study population is described as “all the lexicon of the phenomena examined by the researcher, and thus all the people or objects that are the topic of the issue” (Obeidat et al., 2014, p. 11). Therefore, the study population includes all faculty from Hail University. In the next step, the researcher chose a sample of (60) faculty members. The sample size from the original population was determined on the basis of the Khashan (2017) table. The following table and chart show the distribution of sample members according to the educational qualification variable as a percentage.

It is evident from Table 1 and the chart that the research sample was distributed according to the professor category to (11) representing (18.33%) (23) from the associate professor category with (38.33%) and (26) from the assistant professor category with a percentage (% 43.34). The faculty members of Hail University were an appropriate population and sample for this study due to the university’s unique access to both economic and technological resources. Furthermore, Hail University is a leading university of higher education in Saudi Arabia and its faculty are well versed in the economic and technological aspects of KSA Vision 2030.

Researchers used the questionnaire as an instrument to collect information from study sample members to reveal the perceptions of faculty members at Hail University about the effectiveness of applying the economic and technological dimensions of the Kingdom’s Vision 2030 in achieving competitive advantage and its repercussions on the Saudi society-Hail region. The questionnaire was developed by the research team of Hail University, Saudi Arabia, drawing on the theoretical background, previous studies, and revolutionary economic theory, using this theory to identify how technological development can create a competitive advantage in the region and that leads to increased productivity, improved economic growth, and increased regional economic competitiveness. The reliability and validity of the questionnaire were verified by conducting a pilot test. The pilot study was conducted among a sample of faculty members of Hail University to check its reliability and validity. The results of the pilot study were used to refine the questionnaire. The questionnaire was also finalized in consultation with experts in the field of economics and technology. The questionnaire consisted of two key parts. The first part included the basic data of the study sample according to the educational qualification variable. On the contrary, the second part included the dimensions of the questionnaire (economic, technological). Accordingly, the study instruments include (42) items for the two dimensions. A five-point Likert scale (very high, high, medium, low, and very low) was chosen to measure the responses of the samples. The questionnaire was written in English and was not translated into Arabic. Standard translation and back-translation methods were not adopted.

The validity of the research instrument was shown to be correct after its internal consistency was checked, which is the consistency of the elements of the study dimensions and their interrelationship with each other. It is measured by calculating the correlation coefficient of each dimension with the total degree of the questionnaire through the data from a pilot sample (Obeidat et al., 2014). To ensure the internal consistency of the questionnaire, it was administered to a pilot sample of (22) faculty members at Hail University, and their responses were entered into the software (SPSS 23). The significance levels of the correlation coefficient values were then used to construct the correlation coefficients between the overall score for each research dimension and the correlation coefficient values. The methodologies to determine the validity of internal consistency are presented in Table 2.

It is clear from Table 2 that the correlation coefficients of the study dimensions related to faculty perceptions and their significance value ranged between (0.9019) and (0.9846) degrees, which are high correlation coefficients and are statistically significant at the significance level (0.01). This indicates that the dimensions of the study are valid for internal consistency.

To verify the reliability of the study instrument, the reliability coefficient of the study instrument was extracted through the (Cronbach’s Alpha) coefficient, and Table 3 shows this.

It is seen from Table 3 that the values of Cronbach’s alpha reliability coefficients for the dimensions of the study instrument (questionnaire) are high values; this shows that the questionnaire has a high grade of reliability and was suitable for scientific research purposes. To allow the elucidation of the results of the study questions, the researcher used the method of determining the level of answer to the items in the study instruments, where weight was given to the alternatives: (very high = 5, high = 4, medium = 3, low = 2, very low = 1). The answers were then categorized into five levels of the same range by the following equation: Range = (largest value - smallest value), range = 5–1 = 4. Determining the length of the confidence limits is done by the following equation: Length of confidence limits = range of the number of questionnaire responses (length of confidence limits = 4 ÷ 5 = 0.8). Thus, we have the following classification according to Table 4 and Figure 1.

After the study tool (the questionnaire) in its final form was ready for application, the necessary measures were taken to implement it, as the questionnaire was distributed to the study sample members electronically through Google Drive; after this stage, the questionnaires were collected, by referring to Google Drive. The data were then transferred to an Excel file, and in another step, the data was transferred to the Statistical Package for Social Sciences (SPSS). Finally, the researchers reviewed each questionnaire separately to ensure its suitability for use in the study and to ensure that respondents followed the instructions for filling out the questionnaire. These instructions require taking into account honesty and objectivity in answering the questionnaire items and that the respondent places only one sign in front of each item.

Consequently, SPSS used statistical treatment methods, in addition to frequencies and percentages, to describe the study sample. Pearson’s correlation coefficient was used to verify the internal consistency of the study instrument, and Cronbach’s Alpha coefficient to calculate the reliability of the study instrument. Arithmetic means, and standard deviations were also used, as well as the “One Way Anova” test Table 5, to identify statistically significant differences in the responses of the study sample about their perceptions of the effectiveness of applying the economic and technological dimensions of the Kingdom’s Vision 2030 in achieving competitive advantage and its repercussions on Saudi society-Hail region.

While the study offers meaningful insights into the effectiveness of applying the economic and technological dimensions of Saudi Arabia’s Vision 2030 to achieve a competitive advantage in the Hail region, several limitations need to be acknowledged, particularly regarding the population sample.

Limited Population Sample: One of the primary limitations of this study is the restricted size and scope of the population sample. The data was gathered from a relatively small and region-specific demographic, focusing mainly on faculty from Hail University within the Hail region. This restriction could potentially skew the findings, making them less generalizable to other regions within the Kingdom of Saudi Arabia.

To mitigate this limitation, future research should aim to include a more diverse and extensive sample size that covers multiple regions of Saudi Arabia. A broader sample would provide a more comprehensive understanding of the nationwide effectiveness of Vision 2030s economic and technological dimensions.

Potential Effects on Findings: The limited population sample presents several potential effects on the study’s outcomes. First, the specific contextual factors unique to the Hail region (such as its current economic status, technological infrastructure, and local cultural attitudes) could influence the perceived effectiveness of Vision 2030 initiatives. These nuanced variables might not be present or as influential in other regions, thereby affecting the generalizability of the findings.

Moreover, the size of the sample might not capture the full spectrum of opinions and experiences regarding the implementation of Vision 2030. This could lead to an overrepresentation or underrepresentation of certain views, impacting the robustness and reliability of the study’s conclusions.

Additionally, the limited sample may restrict the study’s ability to identify broader trends and patterns that could emerge from a more varied demographic. For instance, urban areas with different economic and technological baselines might exhibit different levels of progress and face distinct challenges.

Future research should prioritize incorporating methodological approaches that can help mitigate these limitations. Utilizing stratified sampling techniques to ensure that various subgroups within the population are adequately represented would provide a more balanced and accurate representation. Furthermore, employing longitudinal studies could offer deeper insights into how the impacts of Vision 2030 evolve over time across different regions.

Engaging with a broader array of stakeholders, including policymakers, business leaders, and ordinary citizens from various parts of Saudi Arabia, would also enrich the data pool, leading to more holistic and generalizable findings. This expanded approach would assist in identifying wider national trends, thereby enhancing the study’s relevance and applicability.

To address the first question, arithmetic means, and standard deviations of the research sample’s answers were computed from the economic dimension and its subdimensions represented in: (labour market, efficient labour allocation and skills improvement) (business environment and regulation: support for emerging businesses) (enabling entrepreneurship opportunities and attractive competitiveness).

The arithmetic means and standard deviations of the replies from the research sample were determined from the technical dimension to answer the first question and its subdimensions represented in: (administrative operations) (human resources) (electronic regulation), and (technical infrastructure).

The study found that the arithmetic means for the dimension (labour market, efficient labour allocation, and skill improvement) was (3.92) which is a high arithmetic mean with a percentage between (68%) and (84%). This is consistent with the findings of similar previous studies, which have also found that the labour market, efficient labour allocation, and skill improvement are highly effective strategies for improving labour productivity (Aldosari, 2023; Allmnakrah and Evers, 2020). A study conducted by the World Bank found that effective labour market policies can improve labour productivity by up to 20%. Furthermore, research conducted by the International Monetary Fund has also found that improving the skills and knowledge of workers through training and education can lead to significant improvements in labour productivity. Thus, the study’s results align with the findings of this research, which suggest that the labour market, efficient labour allocation, and skills improvement are key strategies to improve labour productivity.

Additionally, the study found that the arithmetic means for the dimension (business environment and regulation support for emerging businesses) was (4.00), which is a high arithmetic mean with a percentage between (68%) and (84%). This result is consistent with the findings of Shahrani et al. (2021), who looked at the effect of government regulation and support on emerging businesses. These studies have shown that when governments provide support and regulation for emerging businesses, it positively affects their growth and development. In addition, governments have been found to play a critical role in promoting economic stability, reducing uncertainty, and encouraging investment in small and medium-sized enterprises. The results of this study further confirm the importance of government support and regulation in creating an enabling environment for emerging companies.

It was also evident that the arithmetic means for the dimension (enabling entrepreneurial opportunities) was (3.65), which is a high arithmetic mean with a percentage between (68%) and (84%). This result is similar to previous studies’ findings that people generally have a positive attitude towards enabling entrepreneurship opportunities. For example, Al-Mamary’s (2022) study found that people had a strong willingness to take risks and be entrepreneurial, and this attitude was higher in countries with higher GDP (Al-Mamary, 2022). This suggests that the level of economic development can be an important factor in influencing people’s attitudes toward entrepreneurship. Additionally, Arora’s 2022 study found that people with higher levels of education were more likely to be positive toward entrepreneurship, and this is reflected in the study’s results as well. Overall, these findings suggest that individuals generally support enabling entrepreneurship opportunities and that this attitude is likely influenced by factors such as economic development and educational attainment (Arora and Sarker, 2022).

Lastly, the study found that the arithmetic mean for the dimension (attractive competitiveness) was (3.71), which is a high arithmetic mean with a percentage between (68%) and (84%). This result is in line with the study by Zheng and Wang. (2022), which found that attractive competitiveness is an important factor in determining the success of a business (Wonglimpiyarat, 2010). According to these studies, companies that have a high level of attractive competitiveness tend to have higher profits and increased customer loyalty. In addition, these companies are more likely to attract and retain new customers.

Based on the results, the arithmetic means for the dimension (administrative operations) was (3.49), which is a high arithmetic mean with a percentage between (68%) and (84%). This result is similar to the study by Amirat and Zaidi. (2020), which found that effective administrative operations are associated with higher performance in organizations. Therefore, this result suggests that o Moreover, this result is also in line with Allmnakrah (2020), which found that organizations with effective administrative operations tend to have higher levels of job satisfaction, increased productivity, and improved customer service. Overall, the findings of this study indicate that administrative operations are essential for organizations to achieve success.

The study also found that the arithmetic means for the dimension (human resources) was (3.36), which is a high arithmetic mean with a percentage ranging between (68%) and (84%) and the arithmetic means for the dimension (electronic regulation) was (3.48) which is a high arithmetic mean with a percentage between (68%) and (84%). This result is consistent with the study by Johl and Toha. (2021) that looked at the same two dimensions. These studies have found that HR and electronic regulation have a high arithmetic mean with a percentage ranging between 68% and 84%. This suggests that HR and electronic regulation are both important factors that organizations must consider when implementing digital transformation. In addition, these studies have highlighted the need for organizations to ensure that they have the necessary resources and technology to enable a successful digital transformation.

The study also revealed that the arithmetic means for the dimension (technical infrastructure) was (3.47), which is a high arithmetic mean with a percentage ranging between (68%) and (84%) and the level of competitive advantage came to a high degree through the values of the arithmetic means of the economic dimension and the technological dimension of the 2030 vision of the Kingdom of Saudi Arabia. This result is consistent with Nurunnabi’s study (2017), which found that the 2030 Vision of the Kingdom of Saudi Arabia has the potential to provide a high level of competitive advantage. This is due to the emphasis placed on the development of a strong technical infrastructure, as well as technological and economic advancements. The study also found that the economic dimension of the 2030 vision was the highest of the three dimensions, indicating that the Kingdom of Saudi Arabia is focusing more on economic development. This is in line with the goal of the 2030 vision to achieve long-term economic growth and diversification.

The theoretical implications of this study include the idea that the KSA Vision 2030 competitive advantage of the Hail region can be enhanced through the application of economic and technological dimensions. This suggests that economic and technological factors are integral to the realization of the KSA Vision 2030 goals and objectives. Furthermore, the region must also invest in and promote the development of its technological infrastructure, including the development of new technology, the diversification of existing technology, and the modernization of existing technology. Finally, the region must prioritize the development of new and innovative products and services that are able to provide a competitive advantage over other regions in the region and beyond.

The researchers recommend decision-makers, planners, and leaders of the private sector in Hail regions _KSA to:

1. Based on the results related to the technological dimension and achieving effectiveness for institutions, the researchers recommend developing administrative processes to activate technology requirements in line with Vision 2030 and adopting practical procedures that facilitate the application of technology in all institutions of the Kingdom of Saudi Arabia.

One major limitation of this study is the limited population sample. If the sample is too small or if it does not accurately represent the population of interest, it can limit the generalizability of the study’s findings. The study only focused on faculty from Hail University within the Hail region, the findings may not be applicable to other industries or groups in the region. This could lead to a biased representation of the effectiveness of applying the economic and technological dimensions of the Vision 2030 initiative in achieving competitive advantage. Other limitations included the lack of comprehensive data on the economic and technological dimensions of the Hail Region, and its competitive advantage presents a limitation to this research and the lack of resources available to conduct a comprehensive study on the economic and technological dimensions of the competitive advantages of the Hail Region. Future research can focus on conducting a comparative analysis of Hail Region’s competitive advantages over other regions. This will help to identify the strengths and weaknesses of Hail Region’s competitive advantages and provide insights into potential areas of improvement.