Public Partnership and Performance of Smart Cities in Malaysia

Main Article Content

Khairul Azizan Suda
Nazatul Shima Abdul Rani
K. Sarojani Devi Krishnan
ibtessam Boubekeur

Abstract

This study was conducted to explore the relationship between the public partnership with the performance of smart cities in Malaysia. About two hundred (200) respondents identified via LinkedIn and a link to the survey were shared via LinkedIn. About eighty-seven (87) responded to the survey. The questionnaires divided into two parts which are part A is on the respondent profiles, and part B is on government institutions (local level) (10 items), government agencies (14 items), and smart city performance (34 items). A reliability analysis was performed using the SPSS software, and the Cronbach’s Alpha scores for the three (3) variables are high with a score of more than 0.900. The results of the correlation analysis indicated that there are positive and significant relationships between GIL, GA, and SP. The relationship between GIL with SP is a weak correlation (r=0.290**; p=0.006), GA with SP is a moderate correlation (r=0.517**; p=0.000), and the relationship between GIL and GA is a strong relationship (r=0.695**; p=0.000). Hence, it can be assumed that the residents at smart city in Malaysia agreed that the government at the local level and government agencies have an influence on the performance of the smart city.

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Author Biographies

Khairul Azizan Suda, UniKL Malaysia Italy Design Institute (UniKL MIDI), Universiti Kuala Lumpur, Taman Shamelin Perkasa, Kuala Lumpur, Malaysia

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Nazatul Shima Abdul Rani, Centre for Women Advancement and Leadership (CWAL), Management and Entrepreneurship Section, UniKL Business School, Universiti Kuala Lumpur, Jalan Sultan Ismail, Malaysia

This study was conducted to explore the relationship between the public partnership with the performance of smart cities in Malaysia. About two hundred (200) respondents identified via LinkedIn and a link to the survey were shared via LinkedIn. About eighty-seven (87) responded to the survey. The questionnaires divided into two parts which are part A is on the respondent profiles, and part B is on government institutions (local level) (10 items), government agencies (14 items), and smart city performance (34 items). A reliability analysis was performed using the SPSS software, and the Cronbach’s Alpha scores for the three (3) variables are high with a score of more than 0.900. The results of the correlation analysis indicated that there are positive and significant relationships between GIL, GA, and SP. The relationship between GIL with SP is a weak correlation (r=0.290**; p=0.006), GA with SP is a moderate correlation (r=0.517**; p=0.000), and the relationship between GIL and GA is a strong relationship (r=0.695**; p=0.000). Hence, it can be assumed that the residents at smart city in Malaysia agreed that the government at the local level and government agencies have an influence on the performance of the smart city.

K. Sarojani Devi Krishnan, General Studies Section, UniKL Business School, Universiti Kuala Lumpur, Jalan Sultan Ismail, Kuala Lumpur, Malaysia

This study was conducted to explore the relationship between the public partnership with the performance of smart cities in Malaysia. About two hundred (200) respondents identified via LinkedIn and a link to the survey were shared via LinkedIn. About eighty-seven (87) responded to the survey. The questionnaires divided into two parts which are part A is on the respondent profiles, and part B is on government institutions (local level) (10 items), government agencies (14 items), and smart city performance (34 items). A reliability analysis was performed using the SPSS software, and the Cronbach’s Alpha scores for the three (3) variables are high with a score of more than 0.900. The results of the correlation analysis indicated that there are positive and significant relationships between GIL, GA, and SP. The relationship between GIL with SP is a weak correlation (r=0.290**; p=0.006), GA with SP is a moderate correlation (r=0.517**; p=0.000), and the relationship between GIL and GA is a strong relationship (r=0.695**; p=0.000). Hence, it can be assumed that the residents at smart city in Malaysia agreed that the government at the local level and government agencies have an influence on the performance of the smart city.

ibtessam Boubekeur, UniKL Business School, Universiti Kuala Lumpur, Malaysia

This study was conducted to explore the relationship between the public partnership with the performance of smart cities in Malaysia. About two hundred (200) respondents identified via LinkedIn and a link to the survey were shared via LinkedIn. About eighty-seven (87) responded to the survey. The questionnaires divided into two parts which are part A is on the respondent profiles, and part B is on government institutions (local level) (10 items), government agencies (14 items), and smart city performance (34 items). A reliability analysis was performed using the SPSS software, and the Cronbach’s Alpha scores for the three (3) variables are high with a score of more than 0.900. The results of the correlation analysis indicated that there are positive and significant relationships between GIL, GA, and SP. The relationship between GIL with SP is a weak correlation (r=0.290**; p=0.006), GA with SP is a moderate correlation (r=0.517**; p=0.000), and the relationship between GIL and GA is a strong relationship (r=0.695**; p=0.000). Hence, it can be assumed that the residents at smart city in Malaysia agreed that the government at the local level and government agencies have an influence on the performance of the smart city.

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