Building Smart Urban Areas: Case Study in Pleiku City, Vietnam

Comments 1: For research methods, exploratory factor analysis is generally performed first, followed by confirmatory factor analysis, which is a complete statistical analysis process. Usually we divide the data into two parts, first using one part for exploratory factor analysis, and then conducting confirmatory factor analysis. However, this article only conducted exploratory factor analysis, which is clearly not in line with research standards.

Response 1: Thank you for pointing this out. We agree with this comment. Therefore, we have revised in red letters in section 1

“Therefore, studying some factors affecting smart urban construction will help make smart urban construction projects in Vietnam more feasible. It also contributes to increased interaction between people and the government, as well as improving the quality of life for sustainable development. Pleiku City, a class I urban area and the second largest city in the Central Highlands, will host this research. The research’s findings add to the body of knowledge on smart cities. Policymakers can use it as a reference to implement smart urban construction projects in other Vietnamese cities, particularly in class I cities with significant development potential. This study is to correlate the relationship between policy mechanisms, human resources, planning and implementation organization in the context of the Central Highland which is unique are in Vietnam.”

Comments 2: The sources of the research indicators in Figure 1 are not specified in the literature. Which indicators are derived from existing research and which indicators were designed by the author themselves have not been explained. The literature does not specify the specific existing influencing factors, but rather provides general explanations. Suggest creating a table that identifies all existing influencing factors and specifies which literature each factor comes from.

Response 2: Thank you for pointing this out. We agree with this comment. Therefore, we have revised the manuscript and represented in red letters.

“Based on a limited number of studies and the research context in Vietnam, we have categorized the factors that influence the construction of smart cities into distinct groups. These include policy mechanisms, human resources, planning, and implementation organization. Figure 1 shows our research model. It was suggested that to overcome the above limitation, this study applied exploratory factor analysis (EFA) to identify the five groups of factors affecting land use planning in the Dan Phuong district, including the groups of politics (Po), economy (Ec), society (Soc), environment (En), and other (Ot) [50].

Source: Adopted from Tran Trong Phuong et al, 2023 [50].

Figure 1. Some factors affecting the construction of smart cities.

Comments 3: If all the selected influencing factor indicators come from literature, there is no need to conduct exploratory influencing factor analysis, and confirmatory factor analysis can be directly conducted. But if some of the selected influencing factor indicators come from literature and some are self-designed, then exploratory influencing factor analysis needs to be conducted first, followed by direct confirmatory factor analysis. So the choice of research method for this article depends on the indicators. However, regardless of how the indicators are selected, the research method used in this article is flawed. This indicates that this article is not in line with academic logic.

Response 3: Agree. We have modified and added the steps to emphasize this point.

“The data analysis of surveyed questionaires are followed five step (Fig 2).

Step 1. Compile and input data from 200 survey forms into Excel, filling in numbers according to each response from residents based on the specified point scale: (1 point) very little impact, (2 points) little impact, (3 points) moderate impact, (4 points) significant impact, (5 points) very significant impact.

Step 2. Reliability analysis: Use Cronbach's Alpha coefficient to test the reliability of the scale. If Cronbach's Alpha coefficient is not within [0.6 - 0.95], eliminate the variable; Next, examine the item-total correlation coefficient. If the item-total correlation coefficient ≤ 0.30, eliminate the variable.

Step 3. Exploratory factor analysis: If the KMO (Kaiser-Meyer-Olkin) coefficient is not within the range 0.5 < KMO < 1, then the factors are eliminated and considered insignificant. Check if Bartlett's test has a sig. value > 0.05, then the model is insignificant.

Step 4. Factor loading of the rotated matrix: If the extracted variance of the independent variable ≤ 50%, the variable is insignificant. This step contributes to the stratification between factors and the degree of influence of each factor.

Step 5. Linear regression analysis to determine the Standardized regression coefficient (β); Standard error (Sig.) and VIF, forming the regression equation. Use the Standardized regression coefficient (β) to evaluate the % level of influence of each factor.”

Comments 4: In addition, this study lacks innovation in methodology and lacks innovation in research content. More like a research report, it is recommended to reject the submission.

Response 4: Agree. We have revised the manuscript to emphasize this point.

“Therefore, studying some factors affecting smart urban construction will help make smart urban construction projects in Vietnam more feasible. It also contributes to increased interaction between people and the government, as well as improving the quality of life for sustainable development. Pleiku City, a class I urban area and the second largest city in the Central Highlands, will host this research. The research’s findings add to the body of knowledge on smart cities. Policymakers can use it as a reference to implement smart urban construction projects in other Vietnamese cities, particularly in class I cities with significant development potential. This study is to correlate the relationship between policy mechanisms, human resources, planning and implementation organization in the context of the Central Highland which is unique are in Vietnam.”

Comments 1: It seems that planning factor have the lowest impacts on the smart city development in this case study. These findings are very interesting to deeper understand the planning issue in this field of developing country. To some extent, it shows a different kind of ‘smart’ to disobey the planning of ‘smart city’ in its contemporary definition of ‘digitalization’. The authors may dig deeper the influencing reasons in their discussion section in this paper.

Response 1: Thank you for pointing this out. We agree with this comment. Therefore, we have revised in red letters to indicate more information about the study site.

“Therefore, studying some factors affecting smart urban construction will help make smart urban construction projects in Vietnam more feasible. It also contributes to increased interaction between people and the government, as well as improving the quality of life for sustainable development. Pleiku City, a class I urban area and the second largest city in the Central Highlands, will host this research. The research’s findings add to the body of knowledge on smart cities. Policymakers can use it as a reference to implement smart urban construction projects in other Vietnamese cities, particularly in class I cities with significant development potential. This study is to correlate the relationship between policy mechanisms, human resources, planning and implementation organization in the context of the Central Highland which is unique are in Vietnam.”

Comments 2: The conclusion line 301-303, remove the formula from the conclusion to the results.

Response 2: Thank you for pointing this out. We agree with this comment. Therefore, we have removed the formula.

Comments 3: Fig1, reformat.

Response 3: We agree. We have modified the figure.

Comments 4: ‘TVE’ adds the full name at the first time mentioned in the context.

Response 4: Agree. We have added the full name.

“Table 3 displays the evaluation results for the level of explanation of the observed variables in the model with the outcome factor. The independent variable’s Total variance explained (TVE) is 67,547”

Comments 5: in the result, should add some explanations of ‘uncertainties’ in their methodology..

Response 5: Agree. We have revised the manuscript to emphasize this point. The explainations were placed in section 4.1.

“In the process of approaching citizens to participate in the survey, there may have some uncertainties. The level of public awareness is uneven. Citizens still face many challenges in accessing and contributing opinions for the implementation of smart city development due to inconsistent understanding (smart refers to the application of digital technology in management, operation, application, and implementation. Smart city development involves developing digital data infrastructure, digital technology, and digital transformation, which are essential issues that help "smarten" other technical and socio-economic infrastructures depending on the application of technology based on the approved general urban planning of Pleiku city.

Comments 1: What does ICT stand for?

Response 1: Thank you for pointing this out. we have revised in red letters in section 1

“The phrase “smart city” initially arose in the 1990s, primarily referring to the incorporation of Information and Communication Technology (ICT) and infrastructure inside urban areas [8].”

Comments 2: Figure 1 is not clear how this categorized into CS, NL, QH, TH.

Response 2: Thank you for pointing this out. We agree with this comment. Therefore, we have revised the manuscript and represented in red letters.

“Based on a limited number of studies and the research context in Vietnam, we have categorized the factors that influence the construction of smart cities into distinct groups. These include policy mechanisms, human resources, planning, and implementation organization. Figure 1 shows our research model. It was suggested that to overcome the above limitation, this study applied exploratory factor analysis (EFA) to identify the five groups of factors affecting land use planning in the Dan Phuong district, including the groups of politics (Po), economy (Ec), society (Soc), environment (En), and other (Ot) [50].

Source: Adopted from Tran Trong Phuong et al, 2023 [50].

Figure 1. Some factors affecting the construction of smart cities.

Comments 3: In section 2, starting from line 79, I confused about the citation styles, you mentioned authers then dates then reference  numbers and those are not matched in many of them. Make sure that the reference and the style is the standard for the journal.

Response 3: Agree. We have checked and revised in the manuscript.

“The construction of smart cities is important for regional economic development [26, 27], and it is influenced by many factors [28, 29]. Numerous studies have examined various factors and their impact on the development of smart urban areas. Meijer and Boloviar's demonstrated that the construction of a smart city hinges on three key elements: smart technology, people, and governance [30]. Smart mobility, environment, economics, people, and governance are all indicators of a successful smart city [31]. It was reported similar consensus on these factors [32, 33]. Al Nuaimi also identified some similar factors in their study [34]. Recently, the research team has pointed out a number of important factors in building smart cities through the definition of smart cities, such as human and social factors, life activities, and physical infrastructure [35].

Building smart cities also involves making smarter policies for transparent governance [36], co-creating innovation [37], and encouraging citizen participation [38]. Li et al. (2022) also pointed out the importance of factors related to policy mechanisms in forming a smart city [39]. The research team also made three policy recommendations to accelerate smart city development. The implementation of smart city construction policies significantly impacts the level of urban innovation, especially in medium-sized cities [40]. However, the indirect effects of policy implementation are larger than the direct effects [41]. The effectiveness of smart urban policies will be greater in cities with excellent financial conditions and a strong digital economy [42].”

Comments 4: Research model and data analysis section, line 167, the linear regression equation is obvious but what is the use of equation related to the smart urban area?.

Response 4: The relation of equation to the smart urban area is describled as:

“The data analysis of surveyed questionaires are followed five step (Fig 2).

Step 1. Compile and input data from 200 survey forms into Excel, filling in numbers according to each response from residents based on the specified point scale: (1 point) very little impact, (2 points) little impact, (3 points) moderate impact, (4 points) significant impact, (5 points) very significant impact.

Step 2. Reliability analysis: Use Cronbach's Alpha coefficient to test the reliability of the scale. If Cronbach's Alpha coefficient is not within [0.6 - 0.95], eliminate the variable; Next, examine the item-total correlation coefficient. If the item-total correlation coefficient ≤ 0.30, eliminate the variable.

Step 3. Exploratory factor analysis: If the KMO (Kaiser-Meyer-Olkin) coefficient is not within the range 0.5 < KMO < 1, then the factors are eliminated and considered insignificant. Check if Bartlett's test has a sig. value > 0.05, then the model is insignificant.

Step 4. Factor loading of the rotated matrix: If the extracted variance of the independent variable ≤ 50%, the variable is insignificant. This step contributes to the stratification between factors and the degree of influence of each factor.

Step 5. Linear regression analysis to determine the Standardized regression coefficient (β); Standard error (Sig.) and VIF, forming the regression equation. Use the Standardized regression coefficient (β) to evaluate the % level of influence of each factor.”

Comments 5: For figure2, you mentioned many steps but they are not clear how they proceeded after each other and what are the inputs for a step and outputs for another step. Please make sure you are carefully explaining all the methods in the figure 2

Response 5: Agree. We have modified and added the steps to emphasize this point.

“The data analysis of surveyed questionaires are followed five step (Fig 2).

Step 1. Compile and input data from 200 survey forms into Excel, filling in numbers according to each response from residents based on the specified point scale: (1 point) very little impact, (2 points) little impact, (3 points) moderate impact, (4 points) significant impact, (5 points) very significant impact.

Step 2. Reliability analysis: Use Cronbach's Alpha coefficient to test the reliability of the scale. If Cronbach's Alpha coefficient is not within [0.6 - 0.95], eliminate the variable; Next, examine the item-total correlation coefficient. If the item-total correlation coefficient ≤ 0.30, eliminate the variable.

Step 3. Exploratory factor analysis: If the KMO (Kaiser-Meyer-Olkin) coefficient is not within the range 0.5 < KMO < 1, then the factors are eliminated and considered insignificant. Check if Bartlett's test has a sig. value > 0.05, then the model is insignificant.

Step 4. Factor loading of the rotated matrix: If the extracted variance of the independent variable ≤ 50%, the variable is insignificant. This step contributes to the stratification between factors and the degree of influence of each factor.

Step 5. Linear regression analysis to determine the Standardized regression coefficient (β); Standard error (Sig.) and VIF, forming the regression equation. Use the Standardized regression coefficient (β) to evaluate the % level of influence of each factor.”

Comments 6: Research results section, I could not verify the results as the detailed steps not included in the figure or within the manuscript

Response 6: Agree. We have modified the title of sections.

4.1. Reliability of factors

4.2. Factors influencing smart urban construction

4.3. Factor loading

4.4. Multivariate regression analysis determines the influence of factors on smart urban construction

Comments 7: It is better to give also small examples when explaining the methodology, for reproducing purposes to validate the results

Response 7: Agree. We have modified and added the steps to emphasize this point.

Based on a limited number of studies and the research context in Vietnam, we have categorized the factors that influence the construction of smart cities into distinct groups. These include policy mechanisms, human resources, planning, and implementation organization. Figure 1 shows our research model. It was suggested that to overcome the above limitation, this study applied exploratory factor analysis (EFA) to identify the five groups of factors affecting land use planning in the Dan Phuong district, including the groups of politics (Po), economy (Ec), society (Soc), environment (En), and other (Ot) [50].

Source: Adopted from Tran Trong Phuong et al, 2023 [50].

Comments 8: The same thing for section 4.2.

Response 8: Agree. We have modified and added the steps to emphasize this point.

4.2. Factors influencing smart urban construction

Comments 9: Section 4.3

Response 9: Agree. We would like to keep the current form.

Comments 10: The regression equation is generated by SPSS but does not reflect on the example case study clearly

Response 10: We proceed the final output of the analysis carried out by SPSS.

Comments 11: It is now the direction towards the cognitive city and how you link the work to make it ready for such cities. Please elaborate more

Response 11: I suppose this matter was indicated in the discussion.

Second, the study also highlights the relationship between human resources and smart cities. Technology is not the only factor that creates a smart city. More important is the role of human capital. In other words, human resources and education play an important role in building and developing smart cities [58]. Research reveals that Vietnam’s urban management staff lacks proper training [59]. Furthermore, awareness of urban management content is not unified, so smart urban management requires management staff to have high capacity and skills [60]. Smart cities always prioritize the human factor [61]. Smart cities are not solely shaped by advanced technology, but also by the innovative ways in which people apply this technology. It takes time to train high-quality human resources, master technology, especially leaders, and elevate the intellectual level of urban residents.

Comments 1: Introduction:

As it stands, the introduction focuses only on providing a general background of the existing literature and omits much of the necessary information that readers are looking for from the outset. The authors should re-write this section to make the literature gaps more clear. This section should also include short paragraphs about the research purpose and questions, the theoretical framework used, research methodology and methods, main findings, and the structure of the article to help readers understand what comes next.

Response 1: Thank you for pointing this out. We agree with this comment. Therefore, we have revised in red letters in section 1

“Therefore, studying some factors affecting smart urban construction will help make smart urban construction projects in Vietnam more feasible. It also contributes to increased interaction between people and the government, as well as improving the quality of life for sustainable development. Pleiku City, a class I urban area and the second largest city in the Central Highlands, will host this research. The research’s findings add to the body of knowledge on smart cities. Policymakers can use it as a reference to implement smart urban construction projects in other Vietnamese cities, particularly in class I cities with significant development potential. This study is to correlate the relationship between policy mechanisms, human resources, planning and implementation organization in the context of the Central Highland which is unique are in Vietnam.”

Comments 2: Some factors affecting the construction of smart cities: a literature review

This section is highly descriptive with a conspicuous absence of theoretical arguments that reflect the study's contributions to the literature. I recommend that authors be clear about their specific arguments throughout this section, and that they need to support these arguments with appropriate previous studies. This will help authors to clearly identify gaps in the literature both theoretically and empirically. Also, throughout the literature section, authors should present different theoretical models or frameworks and methodological approaches adopted by previous studies. This will also help authors show readers the relevance of their study and arguments for examination.

Response 2: Thank you for pointing this out. We agree with this comment. Therefore, we have revised the manuscript and represented in red letters.

“Based on a limited number of studies and the research context in Vietnam, we have categorized the factors that influence the construction of smart cities into distinct groups. These include policy mechanisms, human resources, planning, and implementation organization. Figure 1 shows our research model. It was suggested that to overcome the above limitation, this study applied exploratory factor analysis (EFA) to identify the five groups of factors affecting land use planning in the Dan Phuong district, including the groups of politics (Po), economy (Ec), society (Soc), environment (En), and other (Ot) [50].

Source: Adopted from Tran Trong Phuong et al, 2023 [50].

Figure 1. Some factors affecting the construction of smart cities.

Comments 3: Research location and methods:

3.1. Research location: This subsection should be supported by further references. Authors should also focus on why this location or city is unique and important to examine compared to other cities and studies. Furthermore, the authors should provide more background about the institutional context in which this city is located such as political forces, economic influencers, etc.

3.2. Research model and data analysis: This subsection should provide further clarification about who the questionnaire or survey was distributed to. It should also provide more information about their characteristics such as job titles, academic or professional qualifications, and field experiences that make them qualified enough to answer the survey questions. It should also provide additional descriptions of how data were coded. Additionally, authors should provide a detailed list of survey questions to evaluate the results.

Response 3: Agree. We have modified and added the steps to emphasize this point.

About the research location (3.1), we indicated more information in the revised manuscript as follow:

“Pleiku City is located in the North of the Central Highlands with a total area of 26,076.86 ha. This is the second-largest city in the Central Highlands in terms of population and urban area. Pleiku City is divided into 22 commune-level administrative units, including 14 wards: Chi Lang, Dien Hong, Dong Da, Hoa Lu, Hoi Phu, Hoi Thuong, Ia Kring, Phu Dong, Tay Son, Thang Loi, Thong Nhat, Tra Ba, Yen Do, Yen The and 8 communes: An Phu, Bien Ho, Chu A, Dien Phu, Gao, Ia Kenh, Tan Son, Tra Da.”

About the comment 3.2, we added the following statement into the revised manuscript:

Using available survey forms to randomly survey 200 households and individuals: The survey direction prioritizes selecting households living along urban streets in the urban core, urban fringe, and areas far from the urban center, households on these streets that are involved in business, trading, real estate market, civil servants, public employees...) in Pleiku City according to the level of urban development and main streets. Survey 80 forms in the urban core sub-region in Tay Son and Dien Hong wards (according to urban residential areas along the central streets passing through these 2 wards). 60 forms in the urban fringe area in Tra Ba and Thang Loi wards (according to urban residential areas along the central streets passing through these 2 wards). 60 forms in the area far from the urban center in An Phu and Dien Phu communes (according to urban residential areas along the central streets passing through these 2 communes).

Comments 4: Research results: These results are interesting but "So What?". I recommend that this section be meaningful if the authors use a specific theoretical model or framework. This will enable authors to frame their results within specific theoretical meanings or vocabulary, which reflect the theoretical concepts and contributions of this study compared to the existing literature. At present, the entire results are very descriptive and not supported by any literature. For example, “institutional theory” (e.g., Dillard et al.'s (2004) “cascading institutionalisation” model) can be used to analyse the results. Using this model, the authors can analyse and interpret their empirical results through three distinct but interrelated institutional levels. These include the "political and economic" level, the "institutional field" level, and the "micro-organisational" level. Through these interrelated levels, the authors can show us the cascading institutionalisation process of building a smart city in Vietnam. This in turn reflects the "institutional dynamics" proposed by Dillard et al. (2004) between the macro and micro levels of smart city construction. In this institutionalised sense, the reported results will be more meaningful than the current version of the manuscript.

Response 4: Agree. We indicated that Central highland is very unique study site for this research. Therefore we would like to keep our current discussion as already indicated in the discussion part.

“Thirdly, government support and governance policies serve as the foundation for the implementation of smart city initiatives [62]. To enable smart city initiatives, policy institutions need to be transparent and strategic. Smarter governments will do more than just control the products of social and economic structures [63]. For mechanisms to promote growth, innovation, and advancement, they must establish connections with enterprises, communities, and citizens [64]. It not only gives citizens access to knowledge about decisions that impact their lives, but it also helps to manage resources more effectively. In Vietnam today, smart urban policies mainly prioritize solving urgent problems without paying attention to long-term orientation [65]. This can reduce the efficiency and sustainability of smart urban projects. At the same time, it also affects residents’ quality of life and ability to adapt to climate change.”

Comments 5: Discussion: I recommend that this section be presented in a critical manner rather than the descriptive manner adopted by the authors. Authors should clearly provide what distinguishes these results from other results in other studies and contexts. What is the main theoretical message behind these results? At present, the discussion has presented only the main empirical contributions of the study with no theoretical contributions. Using the institutional theory model proposed above as an example, the critical discussion should focus more on the cascading institutionalisation process, institutional (top-down) dynamics, and contextual effects of smart city construction. This will justify the need for this study and the importance of studying this topic and context compared to its counterparts in the developing and developed literature.

Response 5: We agree. But, we indicated that Central highland is very unique study site for this research. Therefore we would like to keep our current discussion as already indicated in the discussion part.

Comments 6: Conclusions and policy implications:

This section is well-written, summarising the main ideas and findings of the study. However, to enhance this section, it would be better if the authors addressed some social implications. This demonstrates how the study results will benefit society and communities. This section should also explain the research implications/limitations, and how the study results pave the way for future research proposals. 

Response 4: We agree. We have revised the manuscript to emphasize this point.

“In addition, the government should complete the technical infrastructure system of the old urban center in an open manner, with the goal of developing new urban areas within the existing urban areas, this could contribute to a large social impact in the Central Highlands.”

Comments 7: General comments:

The entire article needs further proofreading.

Response 7: We agree. We requested an English speaking to check the manuscript.