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1 – 10 of 210Mehmet Kursat Oksuz and Sule Itir Satoglu
Disaster management and humanitarian logistics (HT) play crucial roles in large-scale events such as earthquakes, floods, hurricanes and tsunamis. Well-organized disaster response…
Abstract
Purpose
Disaster management and humanitarian logistics (HT) play crucial roles in large-scale events such as earthquakes, floods, hurricanes and tsunamis. Well-organized disaster response is crucial for effectively managing medical centres, staff allocation and casualty distribution during emergencies. To address this issue, this study aims to introduce a multi-objective stochastic programming model to enhance disaster preparedness and response, focusing on the critical first 72 h after earthquakes. The purpose is to optimize the allocation of resources, temporary medical centres and medical staff to save lives effectively.
Design/methodology/approach
This study uses stochastic programming-based dynamic modelling and a discrete-time Markov Chain to address uncertainty. The model considers potential road and hospital damage and distance limits and introduces an a-reliability level for untreated casualties. It divides the initial 72 h into four periods to capture earthquake dynamics.
Findings
Using a real case study in Istanbul’s Kartal district, the model’s effectiveness is demonstrated for earthquake scenarios. Key insights include optimal medical centre locations, required capacities, necessary medical staff and casualty allocation strategies, all vital for efficient disaster response within the critical first 72 h.
Originality/value
This study innovates by integrating stochastic programming and dynamic modelling to tackle post-disaster medical response. The use of a Markov Chain for uncertain health conditions and focus on the immediate aftermath of earthquakes offer practical value. By optimizing resource allocation amid uncertainties, the study contributes significantly to disaster management and HT research.
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Juan Zhang, Xi Gao, Xi Hong and Hamish Coates
Although doctoral education has experienced substantial development in recent decades, it remains an elite, hence fragile, dimension of university policy and practice. This study…
Abstract
Purpose
Although doctoral education has experienced substantial development in recent decades, it remains an elite, hence fragile, dimension of university policy and practice. This study aims to articulate perspectives to guide the next phase of strengthening and growth.
Design/methodology/approach
Working from theoretical and empirical research conducted in China, including scholarship on workforce ecosystems, education design and the student experience, this study contributes a framework with qualitative insights which clarify the goals and experiences of doctoral education in ways that will render it more relevant, effective and contributing.
Findings
The paper identifies areas for doctoral reform to ensure career readiness, including three distinctive outcomes and four indispensable experiences.
Originality/value
This study advances a doctoral design framework which can render transparent the substance of programs and prompt program coordinators to develop and ensure career relevance.
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Florian Follert and Werner Gleißner
From the buying club’s perspective, the transfer of a player can be interpreted as an investment from which the club expects uncertain future benefits. This paper aims to develop…
Abstract
Purpose
From the buying club’s perspective, the transfer of a player can be interpreted as an investment from which the club expects uncertain future benefits. This paper aims to develop a decision-oriented approach for the valuation of football players that could theoretically help clubs determine the subjective value of investing in a player to assess its potential economic advantage.
Design/methodology/approach
We build on a semi-investment-theoretical risk-value model and elaborate an approach that can be applied in imperfect markets under uncertainty. Furthermore, we illustrate the valuation process with a numerical example based on fictitious data. Due to this explicitly intended decision support, our approach differs fundamentally from a large part of the literature, which is empirically based and attempts to explain observable figures through various influencing factors.
Findings
We propose a semi-investment-theoretical valuation approach that is based on a two-step model, namely, a first valuation at the club level and a final calculation to determine the decision value for an individual player. In contrast to the previous literature, we do not rely on an econometric framework that attempts to explain observable past variables but rather present a general, forward-looking decision model that can support managers in their investment decisions.
Originality/value
This approach is the first to show managers how to make an economically rational investment decision by determining the maximum payable price. Nevertheless, there is no normative requirement for the decision-maker. The club will obviously have to supplement the calculus with nonfinancial objectives. Overall, our paper can constitute a first step toward decision-oriented player valuation and for theoretical comparison with practical investment decisions in football clubs, which obviously take into account other specific sports team decisions.
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Anti-racism has been practiced in various ways, with varying degrees of effectiveness. This chapter engages with the body of scholarship that focuses on approaches aimed at…
Abstract
Anti-racism has been practiced in various ways, with varying degrees of effectiveness. This chapter engages with the body of scholarship that focuses on approaches aimed at promoting anti-racist actions, policies and social change. It discusses some of the main anti-racism strategies that have been deployed across different countries and examines anti-racism practices in interpersonal, intergroup and community settings. These approaches encompass civil rights campaigns, legislative and policy interventions, affirmative action, diversity and inclusion training, prejudice reduction, intergroup contact, organisational development and holistic anti-racism approaches. Some anti-racism practices and policies, such as awareness campaigns, social marketing and diversity training, also extend to digital platforms, with social media and multimedia networks deployed to broaden the reach and impact of anti-racist endeavours. This chapter specifically engages with local anti-racism movements and draws principles for broader implementation of anti-racism policy and practice. It concludes with a brief discussion of the effectiveness of contemporary anti-racism approaches.
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Keith D. Walker and Benjamin Kutsyuruba
In this concluding chapter of the handbook, the authors first revisit the conceptual focus of this handbook with a brief overview of research literature on wellbeing, using a…
Abstract
In this concluding chapter of the handbook, the authors first revisit the conceptual focus of this handbook with a brief overview of research literature on wellbeing, using a common conceptual approach that identifies the dimensions of wellbeing and then provide an overview of literature that both addresses and imagines the wellbeing with students, faculty, staff, leadership, and institutional levels in mind. Finally, the authors will proffer that there is a need for agentic moral imagination to sustain and progress the cause of wellbeing in higher education.
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Ülker Çolakoğlu, Esra Anış, Özlem Esen and Can Serkan Tuncay
This study explores tourists' virtual reality experiences during the transition to the Metaverse.
Abstract
Purpose
This study explores tourists' virtual reality experiences during the transition to the Metaverse.
Design/methodology/approach
Qualitative approach was employed to capture tourists' virtual reality experiences and knowledge of the Metaverse at two five-star hotels in Kusadasi (Republic of Turkey). The data were collected from Kusadasi using a purposive sampling technique. The research design focused on data collection with the structured interview technique. The interview form consisted of 7 questions in total, and a voice recorder was used to record the answers of the participants. After the first 4 questions were asked, the participants were presented a virtual reality experience with the virtual reality (VR) glasses. The interview was held face-to-face with thirty-five participants consisting of domestic and foreign tourists in two five-star hotels in the summer season of 2022. The collected data were analyzed with the content analysis technique and themes were created.
Findings
This study's findings enhance the conceptual capital in this emerging field and provide insights into many of the participants who have and have never experienced virtual reality applications and who are familiar and unfamiliar with the Metaverse as a concept.
Research limitations/implications
This study generates empirical data that informs contemporary debates about virtual reality and the Metaverse.
Practical implications
The findings show that most participants have never experienced a virtual reality application. Hotels and travel agencies should be aware of this new futuristic technology before the Metaverse transition. Metaverse is for generation Y and Z instead of Baby Boomers and generation X.
Originality/value
This study is unique in terms of depth and fills the gap as it provides useful insights regarding the evaluation of tourists' virtual reality experiences in the transition process to the Metaverse.
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Unlike other types of corporate disclosure, corporate political disclosure (CPD), which is the disclosure of corporate political contributions and the related governing policies…
Abstract
Purpose
Unlike other types of corporate disclosure, corporate political disclosure (CPD), which is the disclosure of corporate political contributions and the related governing policies and oversight mechanisms, does not provide completely new information to stakeholders. Some of the information disclosed in CPD is available from other public records (e.g. the Federal Election Committee website or OpenSecrets website). Given this unique feature of CPD, it is interesting to investigate the cost and benefit tradeoff for firms of altering their CPD practice in response to policy and political uncertainty.
Design/methodology/approach
This study employs recently developed indexes of aggregate economic policy uncertainty (EPU) and a novel dataset of CPD transparency to examine the impact of EPU on CPD transparency and how the proprietary cost of corporate political activities moderates this association. The sample consists of S&P 500 companies from the 2012 to 2019 period.
Findings
The authors document that firms mitigate the heightened information asymmetry associated with higher aggregate EPU by increasing CPD transparency. The positive association between EPU and CPD is less pronounced for firms that are more sensitive to EPU, for firms that more actively manage EPU through corporate political contributions or lobbying activities and for firms that are followed by more analysts. The authors also find that more transparent CPD helps to mitigate the information asymmetry caused by heightened EPU. This study’s results hold when the authors control for other types of voluntary corporate disclosure.
Originality/value
This study contributes to the emerging literature on the determinants of CPD transparency by identifying EPU's positive impact on CPD transparency. This study also provides empirical evidence that the proprietary costs arising from the controversial nature of corporate political activities dampen firms' incentives to provide transparent CPD in response to heightened EPU, and that information on corporate political activities gathered and processed by financial analysts seems to lower the marginal benefit to companies of publicizing CPD on their own website.
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Vimala Balakrishnan, Aainaa Nadia Mohammed Hashim, Voon Chung Lee, Voon Hee Lee and Ying Qiu Lee
This study aims to develop a machine learning model to detect structure fire fatalities using a dataset comprising 11,341 cases from 2011 to 2019.
Abstract
Purpose
This study aims to develop a machine learning model to detect structure fire fatalities using a dataset comprising 11,341 cases from 2011 to 2019.
Design/methodology/approach
Exploratory data analysis (EDA) was conducted prior to modelling, in which ten machine learning models were experimented with.
Findings
The main fatal structure fire risk factors were fires originating from bedrooms, living areas and the cooking/dining areas. The highest fatality rate (20.69%) was reported for fires ignited due to bedding (23.43%), despite a low fire incident rate (3.50%). Using 21 structure fire features, Random Forest (RF) yielded the best detection performance with 86% accuracy, followed by Decision Tree (DT) with bagging (accuracy = 84.7%).
Research limitations/practical implications
Limitations of the study are pertaining to data quality and grouping of categories in the data pre-processing stage, which could affect the performance of the models.
Originality/value
The study is the first of its kind to manipulate risk factors to detect fatal structure classification, particularly focussing on structure fire fatalities. Most of the previous studies examined the importance of fire risk factors and their relationship to the fire risk level.
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