Research Article: 2021 Vol: 25 Issue: 1S
Halah Muneer Mahmood Yousfi, Universiti Utara Malaysia
Badariah Haji Din, Universiti Utara Malaysia
Rusdi Bin Omar, Universiti Utara Malaysia
Smart City, Strategic Leadership
Since the beginning of the twenty-first century and the beginning of the fourth industrial revolution and due to the rapid and advanced changes of the work system, sweeping the winds of change in the world, where the phenomenon of smart government has become more urgent with the increasing applications and artificial intelligence around the world. The main challenges of this study are to show the prominent role of strategic leaders to build an integrated smart city capable of responding to the changing needs of various government sectors and private sectors, managed by flexible strategic leaders, able to make investment decisions for the city, and to face global and regional challenges and changes. In addition to providing insight into the industries in various sectors, representing a massive revolution in the art of government and private sector management and intelligent building automated system to make sure the flow of data in real time easily and smoothly. And work to build an ideal platform of high quality concerned with the applications of "data principles and standards." of smart data to respond to the changing needs of the system of large cities to build an integrated automated system, based on open data sharing standards, to increase the efficiency and effectiveness of crisis and disaster management and risk management represented in identifying risks and disasters according to classification." Risk file. This mission can only be achieved under conscious leadership based on an advanced strategy that supports the culture of innovation and new practices, managed by leaders capable of making investment decisions for the city. According to previous literature and hundreds of research studies to study this phenomenon in accelerated areas of life, the new technological development has not been comprehensively kept pace with the building of a smart city based on its structure on a vision and the big data system (Chen et al., 2012), in line with creative thinking and strategic leadership for the quality of investment decisions and innovative expectations that have become a vital and indispensable component. For the continuation and prosperity of the organization's activity. Therefore, the United Arab Emirates attaches great importance to concerted efforts in ensuring a better life for future generations, directly affecting people's lives, such as health, education and the economy.
Throughout history, the Fourth Industrial Revolution has represented an important and influential turning point in the future of countries. Since the emergence of the revolution, its first wave has brought about unprecedented changes in human history, as the practice of building smart cities has become an increasing standard in all parts of the world and one of the most important technological transformations the world is witnessing, (Laney & Jain, 2017).
This practice has led to many challenges that the world's governments must prepare for and prepare to benefit from them optimally, and one of the most important challenges is the creation of environmentally friendly civilized cities, technically integrated and carefully planned urban cities by strategic leaders capable of making investment decisions (Chen & Zhang, 2014).
Within the framework of the five-year plan of the United Arab Emirates developed for the year 2016 to 2021, Figure (1). In addition, its centenary 2071, the United Arab Emirates realized the importance of keeping pace with the technological revolution through the participation of the world in creating the future and transforming future challenges into opportunities and achievements. This will lead to the development of its smart cities as a global laboratory for the future industry .
The government of the United Arab Emirates continued to emphasize the adoption of the smart city strategy, through (UAE Strategy, 2016), noting that this strategy does not only mean that the country is on the right path to developing smart cities, but that there is a need for strategic leaders, (Gao et al., 2015), Leadership skills manage the city efficiently and effectively through strategic leaders by engaging citizens in development processes and innovations (Struis et al., 2014).
Likewise, the Global Competitiveness Report for the year 2019 issued by the World Economic Forum confirms the findings of the International Institute for Administrative Development. Within the classification, the UAE is the most competitive in the Arab region (25th in the general classification) (Figure 2).
The main study problem is; In the role of strategic leadership, and how to choose the appropriate leadership styles, to transform cities into smart and digital cities, and to seek solutions and best practices, and to work on attracting a huge number of investments, and how to develop and develop the skills of administrative leaderships, and expand the horizons of strategic thinking, to face a data.
Moreover, perhaps most importantly, leaders should initiate the development of a culture of security and protection among smart city management employees and develop technical measures with their safe positions (Chen et al., 2012), and provide a platform for cooperation between many stakeholders in the field of smart cities (Ahmed et al., 2017).
1. Does the strategic leadership direction (planning and creative development policy, creative intelligence, and strategic visions), affect building cities smart sustainable?
2. What is the level of strategic directions of the leaderships in building smart sustainable cites?
3. What are the obstacles facing the development of the strategic leadership direction in building a sustainable smart city?
The Following Study Objectives Aim to Answer the Above Study Questions
• Identifying the reality of strategic leadership and identifying leadership practices through (creative planning and development policy, creative intelligence, strategic visions) to build sustainable smart cities.
• Determining the level of strategic directions for leaderships for the purpose of building sustainable smart cities.
• highlighting on the obstacles facing the development of the strategic leadership direction, big in building a sustainable smart city.
Significance of Studying
The importance of the study is that it is the pioneering study in the context of the topic it will address, which are the open challenges and future direction in the increasingly complex work environment, (Aaltonen & Tempini, 2014), which is represented in the role of strategic leadership, of making investment decisions in smart cities (Tan et al., 2015).
Concept of Smart Cities
An integrated city operating in an innovative way, covering all areas of the economy, governance, society and health, (Moir et al., 2014), with a focus on support and effective participation, of the government sector and the role of strategic leaders and decision makers who make investment decisions to big data analysis (U4SSC, 2016).
A smart city provides a variety of applications and smart services (Van den Broek & Van, 2015) in these four regions, thus promoting coordinated developments in smart applications, (Tiefenbacher & Olbrich, 2015) that a smart city provides within the dimensions of reproduction, economic development and social interaction.
In addition to identifying the dynamic nature of representing the diversity of strategic elements to become the first in the world, (ubran Rainmaking Program) .Models of viable smart cities should be "multi-dimensional, encompassing different aspects of intelligence, (Ekbia et al., 2015) and emphasizing the importance of integration and interaction across multiple domains".(Figure 3)
The complexity of smart city deployment is twofold, on the one hand, the scarcity of resources to stimulate investments in infrastructure, (Stein et al.,2013) and on the other hand, upgrading the model and making it self-sustainable, so that citizens become the main users and consumers, sharing In developing business systems (Lycett, 2013), and utilizing data that improve work quality through a dynamic service delivery system, (Tamm et al., 2013) and for the purposes of smart city development, (Zegras et al., 2015).
Strategic Leadership Concept
The history of research on leadership goes back more than a thousand years, as the topic of leadership was a continuous discussion for several decades, especially on the topic of strategy, organization and development (Yunus, 2002).
Later on, the need for the concept of strategic leadership emerged instead of traditional leadership, especially with the rapid changes and surrounding situations facing the organization and the need to have a strategic vision for the future to increase motivation and encourage creativity and innovation (Al-Murabba, 2008).
Robert Levingson defined leadership as reaching the goal by the best means and at the lowest costs, i.e. within the limits of the available resources (Al-Wahaibi, 2005). In addition, (Crow, 1993) defined strategic leadership. Those actions focus on the strategic vision to achieve it.
Strategic leadership is characterized by clarity of the future vision and seeks to achieve effectiveness and efficiency among the goals, available opportunities and capabilities acquired through experiences (Woerner & Wixom, 2015), and the knowledge that distinguishes the leadership personality and how to develop it through specialized programs in leadership skills in order to create future Leaders to put the organization at the forefront (Yunus, 2002).(Figure 4)
The aforementioned discussion also concluded that the strategic leadership orientation is a strong indicator of building smart cities. Therefore, the first hypothesis of this study was formulated as follows:
H1: There is a positive impact relationship between the dimensions of the strategic leadership direction and building smart sustainable cities.
Artificial Intelligence Strategy
Artificial intelligence technology, as an important tributary to building a competitive, high-productivity knowledge economy based on innovation, scientific research and modern technology, by 2021 (Laney & Jain, 2017).
The aforementioned discussion also concluded that the policy of artificial intelligence is a strong indicator of building smart cities. Therefore, the following hypotheses for this study were formulated as follows:
H1a: Policy affects positively and significantly on the direction of strategic leadership in building smart cities.
Policy of Creative Competencies and Capabilities
Those human resources represent a capital resource that needs investment, while maintaining the effective organizational culture, and focusing on the essential and behavioral dimensions (Hill & Jones, 1998).
The aforementioned discussion also concluded that the policy of the policy of creative competencies and capabilities is a strong indication of the direction of the strategic leadership in building smart sustainable cities. Therefore, the following hypotheses for this study were formulated as follows:
H1b: Policy influences creative competencies and capabilities positively and significantly on the direction of strategic leadership in building smart sustainable cities.
Creative Planning and Development Policy
“Henry Fawel” defined the planning process (Awad, 2012), as predicting what the future will be like while preparing for this future.
The planning and development of creative policy, it is a positive plan to develop and improve the performance of the organization, to fit the changing environment (Hawari, 1992), a systematic process dedicated to achieving the priorities of (Hill & Jones, 1998).
According to previous literature, the policy of creative planning and development is considered a strong indicator of the direction of strategic leaders. In addition, many previous studies have reported that the policy of creative planning and development has a positive importance on the direction of strategic leaders in building smart cities.
The following hypothesis was reached:
H1c: Planning and development policy affects positively and significantly on the strategic leadership direction in building smart sustainable cities.
Future visions for building smart cities target infrastructure, for massive data sets, (Policy Exchange, 2016), to study large amounts of data, to uncover patterns (Bilal et al., 2016), and to obtain insights to extract valuable information in various Sectors.
The following hypothesis was reached:
H1d: Strategic visions positively and significantly affect the direction of the strategic leadership in building smart sustainable cities.
According to the previous literature, Creative Intelligence is considered a strong indicator of the strategic leadership orientation. In addition, many previous studies have reported that Creative Intelligence has a positive importance on the strategic leadership orientation in building smart sustainable cities.
The following hypothesis was reached:
H1e: Creative Intelligence affects positively and significantly on the direction of strategic leaders in building smart sustainable cities.
In Figure (5), the network theory assumes that obtaining positive results through the influence of data on preparing a global strategy and setting global standards for smart cities.
Development of the Model of Situational Management Leadership Theory
Researchers have worked explicitly on the use of the theory of situational leadership in the technological literature. The figure (6) is a model that contains changes and developments, models based on the original model of the theory, that obtaining positive results through the influence of the Directs strategic leadership on preparing a global strategy and setting global standards for smart cities, and for the purposes of creating the relationship between directs strategic leadership and strategy investment decisions, the strategic leadership must be able to think strategically, to deal with rapid variables and high risk environments, (Sosik et al., 2005).
The framework of the study population was defined as it included 10 government departments that relate to the economy and trade in the United Arab Emirates. The study focuses on collecting data on the demographic characteristics of the respondents from statistical departments and information technology departments such as the Ministry of Interior, the Ministry of Economy, Federal Customs Authorities and the Ministry of Health throughout the UAE United Arab Emirates, so that the number of employees in this study includes (300) employees.
The concerned managers were counted in the Dubai Customs Department, and the total number of directors and experts in the economic field was (87) leading employees, while the remaining departments, which numbered (9), approximately (223) employees, to cover the different axes of the questionnaire, highlighting the main improvements and assessing weaknesses. The quantitative study method was used to conduct the questionnaire, where a database was provided containing the names of employees in the departments to be contacted for the purposes of the study. Table 1
The Sample Size of The Study
|No||Departments||Total number of target population||The minimum of study||Number of questionnaires retrieved|
|2||Ministry of Interior||40||25||1|
|3||General Command of Dubai Police||40||25||15|
|4||Ministry of Health and Prevention||40||20||10|
|6||Dubai Electricity and Water Authority||20||5||1|
|7||the National Council||10||3||1|
|8||Ministry of Foreign Affairs||20||10||2|
|9||The Ministry of Economy||40||40||16|
The population of the United Arab Emirates is (9,771) million, there are basically (7) million employees in all sectors of the state, as the number of employees in the private sector has reached 5 million, while the number of employees in the government sector has reached 2 million.
The number of national employees working in the federal government within the leadership category reached 2,421 employees, of which 27.1% were in Abu Dhabi, 51.5% in Dubai, and 21.4% in the northern regions of the country.
Firstly, the number of employees cannot be studied in full, whether in government departments or the private sector. Second that the current line of study is to target government departments to build a smart city in the United Arab Emirates to make the results more generalizable. The technique of random probability sampling was used, where a link was sent by phone and then the data collection process was conducted through quantitative methods via the link, case studies and focus groups.
A random sample consisted of (300) people was selected, where (232) questionnaires were retrieved, and (68) questionnaires were excluded due to lack of answers, and therefore the response rate is (77%). From the questionnaires completed two months after the survey was sent, some numbers were included for communication in case the employees need further clarification and information related to the study and use the data for academic purposes only and in full confidentiality.
Spatial Boundaries: United Arab Emirates
Composite Reliability Values
In this predominant study, convergent validity was verified by values of mean contrast extracted (AVE) above the threshold of 0.50 as recommended by previous researchers.(Table 2 and Figure 7)
Composite Reliability Values
|0.61||0.851||0.785||CPDP1||Creative planning and development policy|
|0.588||0.77||0.769||C I1||Creative intelligence|
|0.769||C I2||(C I)|
|0.559||0.78||0.752||ROP1||Regulatory oversight policy|
|0.679||0.878||0.847||AIP1||Artificial Intelligence Policy|
|0.631||0.866||0.801||PCCC1||policy of creative competencies and capabilities|
Evaluating the Good Fit of the Structural Model
Finally, the effect size (f2) determines the effect of the external variable on the Q2 predictive relevance of the endogenous variable.(Table 3)
Evaluating The Good Fit of The Structural Model
|Subject of Evaluation||Actions||Threshold Values|
|Specified coefficient||R2||0.19 (weak), 0.33(modrernate ), 0.67 (substantial)|
|Path parameter||t-value||1.28 (P>0.10), 0.65 (P>0.05), 2.33 (P>0.01)|
|Effect size||F2||0.02(small), 0.15 (medium), 0.35(large)|
|Predictive relevancy||Q2||0.02(small), 0.15 (medium), 0.35(large)|
Conclusively, (Table) represents the cut-off values of all parameters' such as coefficient of determination (R2), path parameter estimation (t-VALUE), effect sizes (f2) and predictive relationship (Q2)
According to the endorsement of (Hair et al., 2014) these threshold values are also applied in this study to test the inside model PLS-SEM, the collinearity test is imperative in evaluating the internal model of the study.
Therefore, to ensure that there is no collinearity problem, the VIF values for both combinations were also reported in (Table 4), the values confirmed the absence of a collinearity problem in the current study.
Evaluate the Coefficient of Determination (R2) Value
The main goal of PLS-SEM is to explain the internal latent variable and to assess R2 as the most vital criteria in the structural model. (Table 5)
Coefficient of Determination R2
|Variable Underlying Internal||Square Value of R _|
|Building smart sustainable cities.||0.519|
Test Hypotheses of the Study: Structural Model Results (SEM Result and Hypothesis Testing): (Table 6)
Structural Model Results
|Hypothesis||Relationship||Path Coefficient||Std.Error||t -value||p -value||Supported|
|H1d||SL< -C I||0.232||0.052||3.439||0||yes|
Effect size (f2):
Under the suggestions of Heineller & Vassot (2010), the effect size (f2) of the exogenous variables is determined for further analysis in addition to the influence of the particular external factors.
In addition, the small size of the effect (Chen et al., 2003), which can be meaningful, should not be neglected. (Table 7)
Effect Size (f2)
|Self-Constructed||Outdoor Installations||Impact Size||Notes|
|Creative Planning And Development Policy (CPDP)||0.14||Medium effect value|
|Strategic leadership||Creative Intelligence (CI)||0.267||Large effect value|
|SL||Strategic Visions (SV)||0.088||Small effect value|
|Making investment decisions||Regulatory Oversight policy (ROP)||0.071||small effect value|
|MID||Governance Skill,(GS)||0.232||Medium effect value|
|Big data strategy||Risk Policy (RP)||0.074||small effect value|
|Data quality(DQ)||0.187||Large effect value|
|Building smart sustainable cities.||Artificial Intelligence Policy (AIP)||0.057||small effect value|
|BSSC||policy of creative competencies and capabilities (PCCC)||0.161||Medium effect value|
Mediation Effect Test
In the PLS model, the mediation effect is determined by a bootstrap analysis (with 100 re-samples) structured with a detailed hypothesis, the significant result shown during a primer analysis of the indirect effect (β=0.773) along with a t-test of 3.696.
Thus, the study results revealed the mediating effect of the position between the relationship between big data and smart cities and statistical significance (β=0.733, t=3.696, p<0.01). Results of Path Coefficient (Mediation Results).(Table 8)
Mediation Effect Test
|H||Strategic leadership< Making investment decisions< Big data analysis<< Building smart sustainable cities.||0.733||3.696||Supported|
Note: p<0.05 (t>1.645); ** p<0.01 (t>2.33)
Limitations and Future Recommendations
In the future, a comprehensive study, observations, proposals and in-depth interviews are proposed in order to gain an understanding of the smart ecosystem's operating environment and its sustainability. In the future, research may be looking at other variables that affect the building of smart cities and cooperating with regional and international bodies to attract experts in the field of smart city in order to obtain their knowledge ideas, and prepare a smart integrated project that analyzes all data so that it is linked to all systems in the relevant Dubai government departments. And global security systems and depends on the concept of risk analysis and does its own in real-time and direct analysis to help reduce smuggling operations and increase the security efficiency of the state community.
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