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1 – 10 of over 2000
Article
Publication date: 30 May 2018

Anna Visvizi and Miltiadis D. Lytras

The purpose of this paper is to rethink the focus of the smart cities debate and to open it to policymaking and strategy considerations. To this end, the origins of what is termed…

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Abstract

Purpose

The purpose of this paper is to rethink the focus of the smart cities debate and to open it to policymaking and strategy considerations. To this end, the origins of what is termed normative bias in smart cities research are identified and a case made for a holistic, scalable and human-centred smart cities research agenda. Applicable across the micro, mezzo and macro levels of the context in which smart cities develop, this research agenda remains sensitive to the limitations and enablers inherent in these contexts. Policymaking and strategy consideration are incorporated in the agenda this paper advances, thus creating the prospect of bridging the normative and the empirical in smart cities research.

Design/methodology/approach

This paper queries the smart cities debate and, by reference to megacities research, argues that the smart city remains an overly normatively laden concept frequently discussed in separation from the broader socio-political and economic contexts in which it is embedded. By focusing on what is termed the normative bias of smart cities research, this paper introduces the nested clusters model. By advocating the inclusion of policymaking and strategy considerations in the smart cities debate, a case is made for a holistic, scalable and human-centred smart cities agenda focused, on the one hand, on individuals and citizens inhabiting smart cities and, on the other hand, on interdependencies that unfold between a given smart city and the context in which it is embedded.

Findings

This paper delineates the research focus and scope of the megacities and smart cities debates respectively. It locates the origins of normative bias inherent in smart cities research and, by making a case for holistic, scalable and human-centred smart cities research, suggests ways of bypassing that bias. It is argued that smart cities research has the potential of contributing to research on megacities (smart megacities and clusters), cities (smart cities) and villages (smart villages). The notions of policymaking and strategy, and ultimately of governance, are brought into the spotlight. Against this backdrop, it is argued that smart cities research needs to be based on real tangible experiences of individuals inhabiting rural and urban space and that it also needs to mirror and feed into policy-design and policymaking processes.

Research limitations/implications

The paper stresses the need to explore the question of how the specific contexts in which cities/urban areas are located influence those cities/urban areas’ growth and development strategies. It also postulates new avenues of inter and multidisciplinary research geared toward building bridges between the normative and the empirical in the smart cities debate. More research is needed to advance these imperatives at the micro, mezzo and macro levels.

Practical implications

By highlighting the connection, relatively under-represented in the literature, between the normative and the empirical in smart cities research, this paper encourages a more structured debate between academia and policymakers focused on the sustainable development of cities/urban areas. In doing so, it also advocates policies and strategies conducive to strengthening individuals’/citizens’ ability to benefit from and contribute to smart cities development, thereby making them sustainable.

Social implications

This paper makes a case for pragmatic and demand-driven smart cities research, i.e. based on the frequently very basic needs of individuals and citizens inhabiting not only urban but also rural areas. It highlights the role of basic infrastructure as the key enabler/inhibitor of information and communication technology-enhanced services. The nested clusters model introduced in this paper suggests that an intimate connection exists between individuals’ well-being, their active civic engagement and smart cities sustainability.

Originality/value

This paper delineates the relationship between megacities and smart cities research. It identifies the sources of what is termed normative bias in smart cities research. To address the implications of that bias, a nested clusters model for smart cities is introduced, i.e. a conceptual framework that allows us to redraw the debate on smart cities and establish a functional connection between the array of normatively laden ideas of what a smart city could be and what is feasible, and under which conditions at the policymaking level.

Details

Journal of Science and Technology Policy Management, vol. 9 no. 2
Type: Research Article
ISSN: 2053-4620

Keywords

Abstract

Details

Journal of Science and Technology Policy Management, vol. 9 no. 2
Type: Research Article
ISSN: 2053-4620

Open Access
Article
Publication date: 30 September 2019

Joseph F. Hair Jr. and Luiz Paulo Fávero

This paper aims to discuss multilevel modeling for longitudinal data, clarifying the circumstances in which they can be used.

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Abstract

Purpose

This paper aims to discuss multilevel modeling for longitudinal data, clarifying the circumstances in which they can be used.

Design/methodology/approach

The authors estimate three-level models with repeated measures, offering conditions for their correct interpretation.

Findings

From the concepts and techniques presented, the authors can propose models, in which it is possible to identify the fixed and random effects on the dependent variable, understand the variance decomposition of multilevel random effects, test alternative covariance structures to account for heteroskedasticity and calculate and interpret the intraclass correlations of each analysis level.

Originality/value

Understanding how nested data structures and data with repeated measures work enables researchers and managers to define several types of constructs from which multilevel models can be used.

Details

RAUSP Management Journal, vol. 54 no. 4
Type: Research Article
ISSN: 2531-0488

Keywords

Article
Publication date: 5 May 2021

Samrat Gupta and Swanand Deodhar

Communities representing groups of agents with similar interests or functions are one of the essential features of complex networks. Finding communities in real-world networks is…

Abstract

Purpose

Communities representing groups of agents with similar interests or functions are one of the essential features of complex networks. Finding communities in real-world networks is critical for analyzing complex systems in various areas ranging from collaborative information to political systems. Given the different characteristics of networks and the capability of community detection in handling a plethora of societal problems, community detection methods represent an emerging area of research. Contributing to this field, the authors propose a new community detection algorithm based on the hybridization of node and link granulation.

Design/methodology/approach

The proposed algorithm utilizes a rough set-theoretic concept called closure on networks. Initial sets are constructed by using neighborhood topology around the nodes as well as links and represented as two different categories of granules. Subsequently, the authors iteratively obtain the constrained closure of these sets. The authors use node mutuality and link mutuality as merging criteria for node and link granules, respectively, during the iterations. Finally, the constrained closure subsets of nodes and links are combined and refined using the Jaccard similarity coefficient and a local density function to obtain communities in a binary network.

Findings

Extensive experiments conducted on twelve real-world networks followed by a comparison with state-of-the-art methods demonstrate the viability and effectiveness of the proposed algorithm.

Research limitations/implications

The study also contributes to the ongoing effort related to the application of soft computing techniques to model complex systems. The extant literature has integrated a rough set-theoretic approach with a fuzzy granular model (Kundu and Pal, 2015) and spectral clustering (Huang and Xiao, 2012) for node-centric community detection in complex networks. In contributing to this stream of work, the proposed algorithm leverages the unexplored synergy between rough set theory, node granulation and link granulation in the context of complex networks. Combined with experiments of network datasets from various domains, the results indicate that the proposed algorithm can effectively reveal co-occurring disjoint, overlapping and nested communities without necessarily assigning each node to a community.

Practical implications

This study carries important practical implications for complex adaptive systems in business and management sciences, in which entities are increasingly getting organized into communities (Jacucci et al., 2006). The proposed community detection method can be used for network-based fraud detection by enabling experts to understand the formation and development of fraudulent setups with an active exchange of information and resources between the firms (Van Vlasselaer et al., 2017). Products and services are getting connected and mapped in every walk of life due to the emergence of a variety of interconnected devices, social networks and software applications.

Social implications

The proposed algorithm could be extended for community detection on customer trajectory patterns and design recommendation systems for online products and services (Ghose et al., 2019; Liu and Wang, 2017). In line with prior research, the proposed algorithm can aid companies in investigating the characteristics of implicit communities of bloggers or social media users for their services and products so as to identify peer influencers and conduct targeted marketing (Chau and Xu, 2012; De Matos et al., 2014; Zhang et al., 2016). The proposed algorithm can be used to understand the behavior of each group and the appropriate communication strategy for that group. For instance, a group using a specific language or following a specific account might benefit more from a particular piece of content than another group. The proposed algorithm can thus help in exploring the factors defining communities and confronting many real-life challenges.

Originality/value

This work is based on a theoretical argument that communities in networks are not only based on compatibility among nodes but also on the compatibility among links. Building up on the aforementioned argument, the authors propose a community detection method that considers the relationship among both the entities in a network (nodes and links) as opposed to traditional methods, which are predominantly based on relationships among nodes only.

Details

Information Technology & People, vol. 37 no. 2
Type: Research Article
ISSN: 0959-3845

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Abstract

Details

Handbook of Transport Modelling
Type: Book
ISBN: 978-0-08-045376-7

Book part
Publication date: 10 April 2019

Iraj Rahmani and Jeffrey M. Wooldridge

We extend Vuong’s (1989) model-selection statistic to allow for complex survey samples. As a further extension, we use an M-estimation setting so that the tests apply to general…

Abstract

We extend Vuong’s (1989) model-selection statistic to allow for complex survey samples. As a further extension, we use an M-estimation setting so that the tests apply to general estimation problems – such as linear and nonlinear least squares, Poisson regression and fractional response models, to name just a few – and not only to maximum likelihood settings. With stratified sampling, we show how the difference in objective functions should be weighted in order to obtain a suitable test statistic. Interestingly, the weights are needed in computing the model-selection statistic even in cases where stratification is appropriately exogenous, in which case the usual unweighted estimators for the parameters are consistent. With cluster samples and panel data, we show how to combine the weighted objective function with a cluster-robust variance estimator in order to expand the scope of the model-selection tests. A small simulation study shows that the weighted test is promising.

Details

The Econometrics of Complex Survey Data
Type: Book
ISBN: 978-1-78756-726-9

Keywords

Abstract

Details

Review of Marketing Research
Type: Book
ISBN: 978-0-7656-1305-9

Book part
Publication date: 5 November 2021

Joseph A. Bonito

Multilevel approaches are generally well suited to group communication because what people say and do in groups is a function of intra- and trans-individual mechanisms. This…

Abstract

Multilevel approaches are generally well suited to group communication because what people say and do in groups is a function of intra- and trans-individual mechanisms. This chapter first provides a brief overview of group research as a multilevel problem and then describes more modern approaches to modeling nested data using latent variable models, including multilevel structural equation modeling and latent class analysis. The chapter concludes by addressing conceptual opportunities provided by multilevel latent modeling approaches to group communication.

Details

The Emerald Handbook of Group and Team Communication Research
Type: Book
ISBN: 978-1-80043-501-8

Keywords

Article
Publication date: 11 December 2009

Diddy Antai, Sara Wedrén, Rino Bellocco and Tahereh Moradi

Each ethnic group has its own peculiar cultural practices that may widen inequalities in child health and survival among ethnic groups. This study estimated ethnic disparities in…

Abstract

Each ethnic group has its own peculiar cultural practices that may widen inequalities in child health and survival among ethnic groups. This study estimated ethnic disparities in mortality of under‐five‐year‐olds, controlling for individual and community level characteristics. Using multilevel multivariable regression analysis on a nationally representative sample drawn from 7,864 households in the 2003 Nigeria Demographic and Health Survey, we estimated the risks of deaths under‐five‐year‐olds for 6,029 children nested within 2,735 mothers aged 15‐49 years old, who were in turn nested within 365 communities. Results were expressed as odds ratios with 95% confidence intervals. The observed risk of under‐five death was highest among children of Hausa/Fulani/Kanuri mothers and lowest among children of Yoruba mothers. The mother's affiliation to the Yoruba ethnic group, compared to Hausa/Fulani/Kanuri, was still significantly associated with decreased under‐five mortality (OR = 0.66, 95% CI = 0.45 ‐ 0.96) after adjustment for individual and community level factors. Under‐five mortality was significantly related to socio‐economic and demographic factors (birth order/birth interval, mother's age, and mother's education), which explained much but not all of the ethnic disparities. Findings underscore the need for measures aimed at improving female education and the socio‐economic standard of women, changing short birth spacing norms and reducing inequitable distribution of maternal and child health services.

Details

Ethnicity and Inequalities in Health and Social Care, vol. 2 no. 4
Type: Research Article
ISSN: 1757-0980

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Article
Publication date: 1 March 2013

Marko Kryvobokov

The purpose of the paper is to verify whether the version of neighbourhoods created from the lowest geographical level improve a predictive accuracy of hedonic model in comparison…

Abstract

Purpose

The purpose of the paper is to verify whether the version of neighbourhoods created from the lowest geographical level improve a predictive accuracy of hedonic model in comparison with those based on upper geographical levels.

Design/methodology/approach

The paper proposes a method for defining neighbourhoods using Thiessen polygons. The clustering technique is based on fuzzy equality. Clustering is started at different geographical levels: municipalities, traffic analysis zones, and apartment blocks' Thiessen polygons. Delineated neighbourhoods are incorporated into hedonic model of apartment prices, the applied methodologies are ordinary least squares and spatial error.

Findings

With ordinary least squares regression, the slight superiority of Thiessen polygons is found in both in‐sample analysis and ex‐sample prediction. With spatial error technique, the clusters of Thiessen polygons do not always provide the best outcome, and their superiority is contested by the highest geographical level of municipalities.

Research limitations/implications

This paper is the first attempt to apply the proposed method, which not always demonstrates clear superiority. In future study, the method of neighbourhood delineation could be used in combination with market segmentation.

Practical implications

The proposal to use Thiessen polygons as a transition from points to continuous space can outline a base for the use of different clustering techniques, which are applicable to delineate neighbourhoods in housing market studies, in particular for the assessment purpose. The fuzzy equality clustering algorithm itself can be applied to polygonal data.

Originality/value

The originality of the proposed method is that it defines neighbourhoods starting from individual observations applying fuzzy equality. Its advantages are an increased independence from existing boundaries, self‐determination of a number of clusters, and total coverage of an area.

Details

International Journal of Housing Markets and Analysis, vol. 6 no. 1
Type: Research Article
ISSN: 1753-8270

Keywords

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