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This paper aims to identify the key factors to design efficient, healthy and potentially economical neighbourhood places in the surroundings of smart cities to reduce the urban polarization for the sustainable urban development.

A two-stage methodology is followed. First, the key factors for neighbourhood are identified from literature studies. The selected factors are validated by sample t-tests. Second, the total interpretive structural modeling is used to interpret the complexity of relationships among various factors. Further, cross-impact matrix multiplication is applied for classification analysis to find the most driving factors for neighbourhood design.

The contribution of this research is to show hierarchical relationships among the various factors to design the neighbourhood places as smart from the perspectives of city planners and decision makers.

The applicability of the research findings is limited to developing countries mainly where population is large and most of cities have high pressure on its infrastructure to fulfil the citizens’ demands.

This paper will aid policymakers, city planners and government officials to design a sustainable smart city model in which smart neighbourhood would also be the potential solution to decrease pressure on a city’s critical infrastructure especially in developing countries.

A smart city could be considered as the centre point of smart initiatives to develop a place smart, and it should continue beyond the city boundaries to enhance the facilities, services, resources utilization and working environment in neighbourhood places also.

The study explores the various literature on neighbourhood planning and then link with smart city development as current need of urban development scenario. The authors propose a hierarchical relation framework to develop the neighbourhood places as smart places to meet the future demand of urbanization in developing countries like India.

With the ever-growing population in the urban areas, the concept of smart cities started to be more present in the literature. Smart cities are seen as a solution that will respond to the needs of providing a sustainable place for living, and at the same time improving residents’ lives. To achieve this, various information and communication technologies (ICTs) are exploited, making the digitalization in the modern world of an immense importance. Advanced digital technologies enable the transformation of existing and the creation of new business models, the development of new products and services, increase the efficiency and competitiveness of the economy, and contribute to wider socio-economic development. Digitization of society and the economy through innovative and intensive use of ICTs has great potential for growth and is the basis for further development and competitiveness. This all generates an enormous amounts of data sets from which useful information are generated and used again the decision support systems. This chapter presents two examples from Slovenia where big data is used for improving residents’ lives, as part of the strategies for smart cities.

Smart cities require data governance to articulate data sharing and use among relevant stakeholders. Given the lack of a comprehensive examination of this research topic, this study aims to review data governance publications to detect and categorize endeavors backing up data sharing in smart cities.

A systematic literature review was conducted, and 568 academic and professional sources were identified, but finally, only 10 relevant papers were selected.

Results reveal that data governance must be based on well-defined mechanisms, procedures and roles to achieve accountability and responsibility in a multi-actor environment. Moreover, data governance should be adapted to address power imbalances among all interested parties.

The main limitation is the list of sources considered for the literature review. However, this study provides a holistic overview for researchers and professionals willing to know more about smart city data sharing.

This review identifies the data governance approaches supporting data sharing in smart cities, analyzes their data dimension, enhances the state-of-the-art literature on this topic and suggests possible areas for future research.

Due to technological improvement and development of the vehicle-to-home (V2H) concept, electric vehicle (EV) can be considered as an active component of net-zero energy buildings (NZEBs). However, to achieve more dependable results, proper energy analysis is needed to take into consideration the stochastic behavior of renewable energy, energy consumption in the building and vehicle use pattern. This study aims to stochastically model a building integrating photovoltaic panels as a microgeneration technology and EVs to meet NZEB requirements.

First, a multiobjective nondominated sorting genetic algorithm (NSGA-II) was developed to optimize the building energy performance considering panels installed on the façade. Next, a dynamic solution is implemented in MATLAB to stochastically model electricity generation using solar panels as well as building and EV energy consumption. Besides, the Monte Carlo simulation method is used for quantifying the uncertainty of NZEB performance. To investigate the impact of weather on both energy consumption and generation, the model is tested in five different climatic zones in Iran.

The results show that the stochastic simulation provides building designers with a variety of convenient options to select the best design based on level of confidence and desired budget. Furthermore, economic evaluation signifies that investing in all studied cities is profitable.

Considering the uncertainty in building energy demand and PV power generation as well as EV mobility and the charging–discharging power profile for evaluating building energy performance is the main contribution of this study.

Purpose: This chapter presents criticisms of financial inclusion.

Methodology: This chapter uses critical discourse analysis to critique the modern financial inclusion agenda.

Findings: The findings reveal that (i) financial inclusion is an invitation to live by finance and leads to the financialization of poverty; (ii) some of the benefits of financial inclusion disappear after a few years; (iii) financial inclusion ignores how poverty affects financial decision-making; (iv) it promotes digital money which is difficult to understand; (v) financial inclusion promotes the use of transaction accounts; (vi) digital money is difficult to understand; and that (vii) some financial inclusion efforts bear a resemblance to a campaign against having cash-in-hand.

Implication: This study will help policymakers in their assessment of the economic, social, political, and cultural factors that hinder financial inclusion as well as the consequence of financial inclusion for society. For academics, this study will provide a critical perspective to on-going financial inclusion debates in the large positivist literature on financial inclusion.

Originality: Currently, there are no studies that use critical discourse analysis to analyze the broader concept of financial inclusion. This chapter is the first study that uses critical discourse analysis to critique some aspects of the modern financial inclusion agenda.