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1 – 10 of 12Kaira Zoe Alburo-Cañete, Nnenia Campbell, Shefali Juneja Lakhina, Loïc Le Dé and María N. Rodríguez Alarcón
This conversation presents the reflections from four inspirational early career disaster scholars on the opportunities and challenges associated with post-disaster research and…
Abstract
Purpose
This conversation presents the reflections from four inspirational early career disaster scholars on the opportunities and challenges associated with post-disaster research and disaster studies in general.
Design/methodology/approach
This paper is based on the conversations that took place on Disasters: Deconstructed Podcast livestream on the 15th September 2021.
Findings
The prominent themes in this conversation include representation, power imbalances and research extractivism and reciprocity.
Originality/value
The conversation contributes to the ongoing discussions around how research is conducted immediately following disasters.
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Labor migration poses a risk to the family as a social institution. Dissolution of marriages among couples caused by infidelity and labor migration is considered to be one of the…
Abstract
Labor migration poses a risk to the family as a social institution. Dissolution of marriages among couples caused by infidelity and labor migration is considered to be one of the social costs of migration, where children of migrants are greatly affected. This study examines the response of children when they found out about their parent’s infidelity and the ways of coping employed in dealing with the changed family situation. Nine participants aged 16–25 who are children of overseas Filipino workers (OFW) were interviewed. Thematic analysis was used to draw out recurring themes to answer the research questions. The results showed that there are negative feelings felt upon knowing the infidelity of their parent, either by their parent-left or the parent abroad. The relationship between the child and the parent who committed infidelity has been significantly interrupted. Additionally, friends were considered to be an essential source of support. The study contributed to the understanding that labor migration is one of the factors that contributed to strained relationships between husband and wife, and the children were the most affected.
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Khaled Hamed Alyoubi, Fahd Saleh Alotaibi, Akhil Kumar, Vishal Gupta and Akashdeep Sharma
The purpose of this paper is to describe a new approach to sentence representation learning leading to text classification using Bidirectional Encoder Representations from…
Abstract
Purpose
The purpose of this paper is to describe a new approach to sentence representation learning leading to text classification using Bidirectional Encoder Representations from Transformers (BERT) embeddings. This work proposes a novel BERT-convolutional neural network (CNN)-based model for sentence representation learning and text classification. The proposed model can be used by industries that work in the area of classification of similarity scores between the texts and sentiments and opinion analysis.
Design/methodology/approach
The approach developed is based on the use of the BERT model to provide distinct features from its transformer encoder layers to the CNNs to achieve multi-layer feature fusion. To achieve multi-layer feature fusion, the distinct feature vectors of the last three layers of the BERT are passed to three separate CNN layers to generate a rich feature representation that can be used for extracting the keywords in the sentences. For sentence representation learning and text classification, the proposed model is trained and tested on the Stanford Sentiment Treebank-2 (SST-2) data set for sentiment analysis and the Quora Question Pair (QQP) data set for sentence classification. To obtain benchmark results, a selective training approach has been applied with the proposed model.
Findings
On the SST-2 data set, the proposed model achieved an accuracy of 92.90%, whereas, on the QQP data set, it achieved an accuracy of 91.51%. For other evaluation metrics such as precision, recall and F1 Score, the results obtained are overwhelming. The results with the proposed model are 1.17%–1.2% better as compared to the original BERT model on the SST-2 and QQP data sets.
Originality/value
The novelty of the proposed model lies in the multi-layer feature fusion between the last three layers of the BERT model with CNN layers and the selective training approach based on gated pruning to achieve benchmark results.
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Ksenia Chmutina, Gonzalo Lizarralde, Jason von Meding and Lee Bosher
Driven by the New Urban Agenda and the Sustainable Development Goals, decision makers have been striving to reorientate policy debates towards the aspiration of achieving urban…
Abstract
Purpose
Driven by the New Urban Agenda and the Sustainable Development Goals, decision makers have been striving to reorientate policy debates towards the aspiration of achieving urban resilience and monitoring the effectiveness of adaptive measures through the implementation of standardised indicators. Consequently, there has been a rise of indicator systems measuring resilience. This paper aims to argue that the ambition of making cities resilient does not always make them less vulnerable, more habitable, equitable and just.
Design/methodology/approach
Using an inductive policy analysis of ISO standard 37123:2019 “Sustainable cities and communities — Indicators for resilient cities”, the authors examine the extent to which the root causes of risks are being addressed by the urban resilience agenda.
Findings
The authors show that the current standardisation of resilience fails to adequately address the political dimension of disaster risk reduction, reducing resilience to a management tool and missing the opportunity to address the socio-political sources of risks.
Originality/value
Such critical analysis of the Standard is important as it moves away from a hazard-centric approach and, instead, permits to shed light on the socio-political processes of risk creation and to adopt a more nuanced and sensitive understanding of urban characteristics and governance mechanisms.
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Jason von Meding and Ksenia Chmutina
Vulnerability is a label and a concept that is widely used in disaster studies. To date the meaning has been quite limited and implied “weakness”, with criticisms arising…
Abstract
Purpose
Vulnerability is a label and a concept that is widely used in disaster studies. To date the meaning has been quite limited and implied “weakness”, with criticisms arising periodically but not halting vulnerability's reproduction. In this paper, the authors offer a new theory of vulnerability for the field, suggesting that complicating the concept can create space for liberatory discourse and organising.
Design/methodology/approach
The authors draw from diverse understandings of vulnerability to generate new conceptual ground for disaster scholars. The authors explore the relationships between power and agency and autonomy and social hierarchy with regards to how vulnerability is considered within neoliberal democracies. The authors also outline ideological responses and the political actions that follow.
Findings
This exploration is underpinned by dissatisfaction with the way that vulnerability has thus far been theorised in disaster studies. Using the analytical framings provided, the authors hope that others will build on the idea that so-called “vulnerable” people, working in solidarity and using intersecting frameworks of anti-racism, anti-colonialism and anti-capitalism, can undermine the risk-creating norms of the neoliberal state.
Originality/value
The authors argue that the dominant framing of vulnerability in disaster studies – and usage of the vulnerability paradigm – provides political traction for neoliberal social projects, based on notions of humanitarianism. The authors make this claim as a challenge to the authors and the authors' peers to maintain reflexive scholarship and search for liberatory potential, not only in vulnerability but in other concepts that have become normative.
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Isaac Chairez, Israel Alejandro Guarneros-Sandoval, Vlad Prud, Olga Andrianova, Sleptsov Ernest, Viktor Chertopolokhov, Grigory Bugriy and Arthur Mukhamedov
There are common problems in the identification of uncertain nonlinear systems, nonparametric approximation, state estimation, and automatic control. Dynamic neural network (DNN…
Abstract
Purpose
There are common problems in the identification of uncertain nonlinear systems, nonparametric approximation, state estimation, and automatic control. Dynamic neural network (DNN) approximation can simplify the development of all the aforementioned problems in either continuous or discrete systems. A DNN is represented by a system of differential or recurrent equations defined in the space of vector activation functions with weights and offsets that are functionally associated with the input data.
Design/methodology/approach
This study describes the version of the toolbox, that can be used to identify the dynamics of the black box and restore the laws underlying the system using known inputs and outputs. Depending on the completeness of the information, the toolbox allows users to change the DNN structure to suit specific tasks.
Findings
The toolbox consists of three main components: user layer, network manager, and network instance. The user layer provides high-level control and monitoring of system performance. The network manager serves as an intermediary between the user layer and the network instance, and allows the user layer to start and stop learning, providing an interface to indirectly access the internal data of the DNN.
Research limitations/implications
Control capability is limited to adjusting a small number of numerical parameters and selecting functional parameters from a predefined list.
Originality/value
The key feature of the toolbox is the possibility of developing an algorithmic semi-automatic selection of activation function parameters based on optimization problem solutions.
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Ismail Olaleke Fasanya, Oluwasegun Babatunde Adekoya and Felix Odunayo Ajayi
This paper aims to model the relationship between oil price and stock returns for selected sectors in Nigeria using monthly data from January 2007 to December 2016.
Abstract
Purpose
This paper aims to model the relationship between oil price and stock returns for selected sectors in Nigeria using monthly data from January 2007 to December 2016.
Design/methodology/approach
The authors use both the linear (symmetric) autoregressive distributed lag (ARDL) by Pesaran et al. (2001) and non-linear (asymmetric) ARDL by Shin et al. (2014), and they also account for structural breaks using the Bai and Perron (2003) test that allows for multiple structural changes in regression models.
Findings
The results indicate that the strength of this relationship varies across sectors, albeit asymmetric and breaks. The authors identify two structural breaks that occur in 2008 and 2010/2011, which coincidentally correspond to the global financial crisis and the Arab spring (Libyan shutdowns), respectively. Moreover, the authors observe strong support for asymmetry and structural breaks for some sectors in the reaction of sector returns to movement in oil prices. These findings are robust and insensitive when considering different oil proxies. While further extensions can be pursued, the consideration of asymmetric effects as well as structural breaks should not be jettisoned when modelling this nexus.
Originality/value
This study is one of the very few studies that have investigated the sectoral behaviour of stocks to oil price shocks, particularly in Nigeria. This paper contributes to the oil stock literature using the recent technique of asymmetry and also considering the role structural breaks play in the relationship between oil price and stock returns.
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Ting Cui, Shenlong Tang and Siti Hasnah Hassan
Despite the enormous benefits, smart homes (SHs) are still not widely adopted by residents in China. Furthermore, research on the intention to use SHs has overlooked the role of…
Abstract
Purpose
Despite the enormous benefits, smart homes (SHs) are still not widely adopted by residents in China. Furthermore, research on the intention to use SHs has overlooked the role of family factors. Thus, this study aims to propose a new research model to examine the impact of family factors on the usage intention (UI) of SHs.
Design/methodology/approach
This study collected 265 valid data from potential users of SHs in China using a convenience sampling method. The PLS-SEM method was applied to test the research model and related hypotheses.
Findings
The empirical results confirm the mediating role of optimism (OP) in perceived family support (PFS)/perceived family trust (PFT) and attitude (AT). Unsurprisingly, the results validated the relationship between perceived usefulness (PU), attitude (AT) and UI of SHs through TAM theory. Besides, this study also identified the moderating effect of perceived risk (PR) between AT and UI.
Practical implications
To improve SH adoption, practitioners should focus on family factors and utilize family influence to promote the spread of smart home reputation. Besides, SH practitioners should enhance user trust and reduce perceived risks through technological upgrades and security measures.
Originality/value
Based on the Social Impact Theory and Technology Acceptance Model (TAM), this study is an empirical attempt to explore the impact of family factors on the intention to use SHs, expanding the research on smart home adoption.
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Line Schmeltz and Matilde Nisbeth Brøgger
The aim of this study is to investigate the prevalence of corporate health initiatives as part of CSR, and how and to what extent these initiatives are communicated in CSR reports.
Abstract
Purpose
The aim of this study is to investigate the prevalence of corporate health initiatives as part of CSR, and how and to what extent these initiatives are communicated in CSR reports.
Design/methodology/approach
The study comprises two strands. First, a mapping of the extent and nature of health-related CSR initiatives among 11 selected Danish companies is developed, based on a qualitative email questionnaire. Next, the mapping serves as the framework for coding and analyzing CSR reports from 2018 to 2020 from 15 companies (45 in total).
Findings
The study provides a typology of the extent and nature of such CSR initiatives consisting of more than 50 types of health-related initiatives. Analysis of the CSR reports illustrates an increase in the explicit communication of employee health initiatives as well as the number of different categories applied over the three years.
Practical implications
The study provides CSR managers with awareness about the extent and usage of employee health as part of corporate communication on CSR, including how such initiatives can be communicated in the CSR report. It also gives rise to carefully considering the potential negative implications for employees when planning health initiatives.
Originality/value
The study is the first of its kind to combine the perspectives of CSR and workplace health promotion to discuss the potential institutionalization of employee health as part of the corporate CSR program.
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