Chinese Journal of Urban and Environmental Studies

Application of big data analytics (BDA) is seen in various disciplines within an organization to predict trends, explore opportunities and monitor performance. Among all the industries, BDA presents immense value in sustainable manufacturing (SM) given that it is an industry that consumes a high amount of energy, emits high amounts of waste and carbon emissions and requires a large amount of manpower. This paper aims at illustrating the effects of BDA in supporting SM by studying the Indian manufacturing firms which have unfavorable labor laws compared to other developing countries. With an extensive literature review, this paper discusses the relationship between BDA and sustainability, the capabilities of BDA, the concept of SM, the BDA framework for SM, the relationship between Industry 4.0 and SM and the challenges of implementing BDA. Using qualitative meta-analysis research methodology, the paper examines the nine common critical success factors that enable SM through BDA implementation by comparing 15 primary studies. Finally, the paper concludes the research findings and outlines future research directions. The study provides theoretical and practical contributions to BDA implementation in achieving effective SM practices in emerging economies.

This study attempts to investigate the climatic variability in the southwestern area of Bangladesh focusing on temperature and precipitation extremes. Long-term daily records of temperature and precipitation from six weather stations spread over the study area were analyzed. A total of 20 yearly indices were calculated and testified for the trends with the Mann–Kendal test and Sen’s estimator of slope at a 95% confidence interval. Moreover, one-way ANOVA and Tukey–Kramer post-hoc tests were applied to verify the spatial heterogeneity of the climatic indices among the meteorological stations. Findings revealed that Khulna is the worst affected area with significant changes in 12 climatic indices. Jessore and Faridpur followed Khulna with significant changes in 10 and 9 indices, respectively. Among the indices, significant changes in TN10p (frequencies of daily minimum temperature event that falls below the 10th percentile value), TX10p (frequencies of daily maximum temperature event that falls beyond the 10th percentile value), CSDI (cold spell duration indicator), and CDD (consecutive dry day) are the most common phenomenon in the studied region. Five out of six stations have been experiencing significant increasing trends for TN10p. That indicates an overall increase of extreme cold day frequencies in the area. Khulna station showed shreds of evidence of extreme cold temperature instances with a statistically significant fall in the minimum value of the yearly minimum temperatures (TNn). Besides, Khulna also experienced a statistically significant fall in the minimum value of the yearly maximum temperatures. Consistently, the area showed a significant trend of wider cold spells. Similarly, the extremely warm day frequencies have also been increasing significantly for the Khulna, Jessore, and Faridpur areas. Therefore, it is evident that the studied area has been experiencing temperature extremes. On the other hand, precipitation extremes are apparent for only Khulna and Jessore. Both these stations showed increasing trends in heavy precipitation events and wet spells (consecutive precipitation days). ANOVA outcome suggests that the study area has significant spatial heterogeneity in climatic indices. Precipitation indices show high spatial heterogeneity than those of temperature. Among the meteorological stations, Mongla and Ishwardi show the maximum departure than those of others. This study may help policy-makers, researchers, and academicians to take proper initiatives to reduce the impacts of changing climatic parameters in the coastal areas of Bangladesh.

In recent years, the tourism economy of Guangxi Zhuang Autonomous Region (hereinafter referred to as “Guangxi”), China, has been caught in the contradiction between infrastructure construction and natural environmental protection. By combing Guangxi’s tourism economy with its development path of smart long-term rental housing, this paper finds that the long-term rental market in Guangxi based on artificial intelligence (AI) technology can solve the development contradiction through accurate construction planning to improve efficiency. The long-term rental housing market in Guangxi has entered a low-carbon economy period since pilot programs were launched for the policy of managing public rental housing with AI and information technologies. From the perspective of AI, facts have proved that AI has the ability to re-adjust the competition order of an industry, which not only realizes the low-carbon development of the rental market, but also promotes the industrial upgrading of the tourist industry.

In recent decades, the unbalanced development of Iranian cities and the advent of many problems in various social, cultural, economic, physical and environmental dimensions have resulted inevitably in the need to use urban development plans to advance the spatio-physical condition of cities. In this regard, about five decades have passed since the start of the preparation of urban development plans in Iran; but despite gaining a lot of experience by producers and executors of urban affairs, in practice, urban projects have not been able to take a positive step in the direction of programmed development. Therefore, by detecting the causes of unachievability and failure of these plans, it is possible to prepare realistic and executive plans. Hence, this study seeks to investigate the shortcomings of the master plan approved in 2016 in Tabriz and identify the factors affecting its unrealizability by using the qualitative methods (Delphi and case study methods). Among the most significant reasons for the impracticability of this plan, the following should be mentioned: (1) the inadequacy of the design model (positivism, belief system, obligation, inductive reasoning, centrism and being government-centered); (2) inadequacy in the content of the plan (being governmental and non-participatory, inadequate subjectology and collection of irrelevant data, lack of segregation of interventions in different contexts, lack of an organized monitoring system, mere physical emphases, lack of definition of executive financial possibilities, perfectionism, lack of attention to relativism and inflexibility and lack of connection between the elements and components of the plan); and (3) inadequacy of the plan proposals and strategies (emphasis on quantity, incomplete inference, inefficiency and not including all levels and strata).

Colombo is the commercial capital of Sri Lanka, with a high population, buildings, and vehicles. Therefore, it is vital to observe the spatial distribution of vegetation types and changes in the green cover of Colombo city to identify priority areas to improve green cover. This study was carried out to estimate the changes in green cover in Colombo Municipal Area (CMA) and its postal zones over 10 years using remote sensing techniques. The green cover was categorized into trees, shrubs, Playgrounds (PG)/Grasslands, wetlands, rooftops, and Ipomoea cover. Accordingly, total green cover increased up to 26.17% from 22.36% during the period of 2012–2022. During the past decade, except for the PG/Grasslands, all other vegetation types have been reduced. Five of the 15 postal zones in the CMA’s green cover have decreased during the past 10 years, including Colombo 04, 05, 06, 09, and 13. The highest green cover was recorded in Colombo 07, while the lowest green cover was present in Colombo 11. The outcome of the study emphasizes that CMA is moving towards greening and sustainability even with the expansion of built-up areas and urban populations.

The government’s vision is oriented towards reforming the urban map and increasing the urban communities’ ability to face current and future urban development challenges. However, it is becoming increasingly aware that it cannot achieve this by acting alone. This in turn poses an important question about good urban governance, and appropriate management mechanisms that may enable the achievement of the strategic goals. In this context, the government adopted a “National Housing Strategy”, which aims to transfer the current situation of the housing sector in Egypt and encourage the private sector to provide more diversity of patterns of holdings in this sector. However, to what extent the government can develop this approach into an effective public–private partnership framework that ensures a strong private sector response in the delivery of affordable housing is still unclear. Accordingly, this research aims to develop a conceptual framework to guide decision-makers on how the state can apply urban development partnership as an integrated approach to better development of affordable housing in Egypt.

A majority of Chinese high-tech firms were founded in development zones established by the Chinese government. It is necessary to identify the impacts of development zones on firms’ innovation (hereinafter referred to as “innovation effects”) as well as the possible knowledge spillover of development zones. Different types of zones, due to their different administrative levels and original purposes of establishment, may have different innovation effects. In this paper, the innovation effects of the Shanghai development zones are identified by using the geographic range of Shanghai development zones as well as geographic coordinates, patents, and research and development (R&D) data of manufacturing firms. The research results robustly show that there are significant and positive innovation effects of development zones. Through the use of regression analysis and by using firm data on both sides of zone boundaries, we observe knowledge spillovers. We also test a possible mechanism for the innovation effects of development zones.