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As the size of the population is growing and the capacity of the planet Earth is limited, human beings are searching for sustainable and technology-enabled solutions to support society, ecology and economy. One of the solutions has been developing smart sustainable cities. Smart sustainable cities are cities as systems, where their infrastructure, different subsystems and different functional domains are virtually connected to the information and communication technologies (ICT) and internet via sensors and devices and the Internet of Things (IoT), to collect and process real-time Big Data and make efficient, effective and sustainable solutions for a democratic and liveable city for its various stakeholders. This chapter explores the concepts and practices of sustainable smart cities across the globe and explores the use of technologies such as IoT, Blockchain technology and Cloud computing, etc. their challenges and then presents a view on business models for sustainable smart cities.

It’s a global challenge to make cities and communities become an age-friendly society. This paper aims to discuss how to develop good concepts for senior residences in Norway and aim to study what the challenges are in the early planning phase, searching the answer to the following research questions: (1) What makes a senior housing attractive? (2) What are the challenges that hinder future concept development? (3) Suggest actions in order to obtain a sustainable development.

This research uses a descriptive and explorative approach describing the phenomena by (I) a short literature review describing existing concepts and challenges, (II) “Walk-through”-methodology with informal dialogue on site and (II) semi-structured interviews of property developers, architects or contractors, politicians, care providers or planners in the municipality involved in seven pilot projects in Kristiansand and Stavanger.

The authors find that new and diverse concepts need to be developed to meet the demand of the seniors. The new concepts should be developed in collaboration with both public and private actors as well as developing a communication platform to meet the needs of the seniors in terms understanding the possibilities of alternative housings, incentives to move and how to influence and get involved in the planning.

There is a limited no. of informants among the public stakeholders. Only three of the seven pilot projects are accomplished. There is an advantage if the rest of the projects are evaluated when accomplished.

Develop participation models and PPP models at the local level.

The value lies in the evaluation of the seven pilot projects.

This study aims to identify clusters amongst the county housing markets in Poland, taking into account the criteria of size and quality of the housing stock, as well as price level. In addition, this work is intended to detect the socio-economic factors driving the cluster formation.

To group the studied housing markets into homogeneous clusters, this analysis uses a proprietary algorithm based on taxonomic and k-means++ methods. In turn, the generalised ordered logit (gologit) model was used to explore factors influencing the cluster formation.

The results obtained revealed that Polish county housing markets can be classified into three or four homogeneous clusters in terms of the size and quality of the housing stock and price level. Furthermore, the results of the estimation of the gologit models indicated that population density, number of business entities and the level of crime mainly determine the membership of a given housing market in a given cluster.

In contrast to previous studies, this is the first to examine the existence of homogeneous clusters amongst the county housing markets in Poland, taking into account the criteria of size and quality of the housing stock, as well as price level simultaneously. Moreover, this work is the first to identify the driving forces behind the formation of clusters amongst the surveyed housing markets.

This paper aims to analyze how nearby property prices are affected by new construction projects in Stockholm. If there is an impact on property prices, the authors endeavor to investigate whether the effects vary among different areas within the municipality, for different groups of inhabitants and for different types of housing (i.e. public versus private housing).

The authors use a difference-in-difference specification in a hedonic model, and the sample consists of more than 90,000 observations over the period 2005-2013.

The results are robust and indicate that house prices in nearby areas increase following the completion of infill development. The results also indicate that infill development has a positive spillover effect on nearby dwelling prices only in areas with lower incomes, more public housing units and more inhabitants born abroad.

It provides an analysis on how nearby property prices are affected by new construction projects by creating a restricted control area, so as to make the treatment group and the control group more homogeneous. Thus, it mitigates any potential problems with spatial dependency, which can cause biased standard errors.

Digitalization accelerates the need of tourism and hospitality ecosystems to reframe business models in line with a data-driven orientation that can foster value creation and innovation. Since the question of data-driven business models (DDBMs) in hospitality remains underexplored, this paper aims at (1) revealing the key dimensions of the data-driven redefinition of business models in smart hospitality ecosystems and (2) conceptualizing the key drivers underlying the emergence of innovation in these ecosystems.

The empirical research is based on semi-structured interviews collected from a sample of hospitality managers, employed in three different accommodation services, i.e. hotels, bed and breakfast (B&Bs) and guesthouses, to explore data-driven strategies and practices employed on site.

The findings allow to devise a conceptual framework that classifies the enabling dimensions of DDBMs in smart hospitality ecosystems. Here, the centrality of strategy conducive to the development of data-driven innovation is stressed.

The study thus developed a conceptual framework that will serve as a tool to examine the impact of digitalization in other service industries. This study will also be useful for small and medium-sized enterprises (SMEs) managers, who seek to understand the possibilities data-driven management strategies offer in view of stimulating innovation in the managers' companies.

The paper reinterprets value creation practices in business models through the lens of data-driven approaches. In this way, this paper offers a new (conceptual and empirical) perspective to investigate how the hospitality sector at large can use the massive amounts of data available to foster innovation in the sector.

This paper aims to draw on community risk assessment (CRA) for assessing vulnerability to climate change in north-western Ghana, focusing on sunshine, temperature and wind, elements of climate which are seldom explored in vulnerability assessments to climate change.

The paper draws on data collected from a qualitative research design that used participatory rural appraisal methods, particularly, in-depth interviews, focus group discussions and seasonal calendar analysis in three selected rural communities of the Sissala East District. Furthermore, an inter-generational framework was adopted for comparative assessment of vulnerability and changes in vulnerability to climate change.

The results show that the current generation of smallholder farmers is more vulnerable to climate change than the past generation, the era of grandparents. Thus, farmers are exposed to higher-intensity sunshine, temperature and wind in contemporary times than was the case in the past. Consequently, their livelihoods are affected the most by the damaging effects of these climatic hazards. The CRA process revealed the relevance of indigenous knowledge systems for vulnerability assessments and at the same time, underpins the need for adaptation of such knowledge if it is to sustain smallholder farmer efforts at climate change adaptation at community levels.

The paper recommends an endogenous development approach to climate change adaptation planning (CCAP), one that will build on indigenous knowledge systems for effective community education, mobilization and participatory response to climate change. Policy interventions should aim at enhancing climate change adaptation through innovations in soil and water conservation, access to water for irrigation and domestic use, climate smart-housing architecture and agro-forestry within the framework of decentralization and district development planning.

This paper will contribute to climate change research in two ways: first, by drawing attention to the usefulness of CRA in vulnerability assessment; and second, by focusing on climate elements which are critical for CCAP but rarely given sufficient attention in vulnerability assessments.

The Cloud of Things (IoT) that refers to the integration of the Cloud Computing (CC) and the Internet of Things (IoT), has dramatically changed the way treatments are done in the ubiquitous computing world. This integration has become imperative because the important amount of data generated by IoT devices needs the CC as a storage and processing infrastructure. Unfortunately, security issues in CoT remain more critical since users and IoT devices continue to share computing as well as networking resources remotely. Moreover, preserving data privacy in such an environment is also a critical concern. Therefore, the CoT is continuously growing up security and privacy issues. This paper focused on security and privacy considerations by analyzing some potential challenges and risks that need to be resolved. To achieve that, the CoT architecture and existing applications have been investigated. Furthermore, a number of security as well as privacy concerns and issues as well as open challenges, are discussed in this work.