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1 – 10 of 80Rajali Maharjan and Hironori Kato
This study investigates whether logistics and supply chain resilience strategies (SCREST) can help mitigate the negative impacts of disruptions on firm performance and logistics…
Abstract
Purpose
This study investigates whether logistics and supply chain resilience strategies (SCREST) can help mitigate the negative impacts of disruptions on firm performance and logistics and supply chain (SC) activities of companies, using the COVID-19 pandemic as a case study.
Design/methodology/approach
The authors collected primary data on the implementation of different types of SCRESTs and measured the impact of COVID-19 in terms of firm performance and logistics and SC metrics through a survey of Japanese manufacturing companies in four sectors. The authors used these data to illustrate whether the companies benefitted from SCRESTs in mitigating the negative impacts of COVID-19. A questionnaire comprising structured and open-ended questions was sent to 8,000 companies all over Japan that met the selection criteria, using a combination of mail and web-based media. The respondents were logistics and SC professionals. A combination of qualitative and quantitative analysis was performed for data analysis and interpretation.
Findings
Research conducted within the case of the Japanese context revealed that findings varied depending on the methodology applied. The use of a direct analysis approach and qualitative analysis suggested that the implementation of SCRESTs is beneficial in addressing the negative impacts of COVID-19 on firm performance and logistics and SC activities, whereas the application of indirect analysis approach yielded mixed results. The analysis also indicated a shift in the preferred SCRESTs during COVID-19.
Originality/value
To the best of the authors’ knowledge, this is the first study to examine the benefits of implementing SCRESTs using primary data from the manufacturing sector of Japan. Furthermore, empirical research on this topic is generally lacking.
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Luiza Ribeiro Alves Cunha, Adriana Leiras and Paulo Goncalves
Due to the unknown location, size and timing of disasters, the rapid response required by humanitarian operations (HO) faces high uncertainty and limited time to raise funds…
Abstract
Purpose
Due to the unknown location, size and timing of disasters, the rapid response required by humanitarian operations (HO) faces high uncertainty and limited time to raise funds. These harsh realities make HO challenging. This study aims to systematically capture the complex dynamic relationships between operations in humanitarian settings.
Design/methodology/approach
To achieve this goal, the authors undertook a systematic review of the extant academic literature linking HO to system dynamics (SD) simulation.
Findings
The research reviews 88 papers to propose a taxonomy of different topics covered in the literature; a framework represented through a causal loop diagram (CLD) to summarise the taxonomy, offering a view of operational activities and their linkages before and after disasters; and a research agenda for future research avenues.
Practical implications
As the authors provide an adequate representation of reality, the findings can help decision makers understand the problems faced in HO and make more effective decisions.
Originality/value
While other reviews on the application of SD in HO have focused on specific subjects, the current research presents a broad view, summarising the main results of a comprehensive CLD.
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This study develops a computational method to investigate the predominant language styles in political discussions on Twitter and their connections with users' online…
Abstract
Purpose
This study develops a computational method to investigate the predominant language styles in political discussions on Twitter and their connections with users' online characteristics.
Design/methodology/approach
This study gathers a large Twitter dataset comprising political discussions across various topics from general users. It utilizes an unsupervised machine learning algorithm with pre-defined language features to detect language styles in political discussions on Twitter. Furthermore, it employs a multinomial model to explore the relationships between language styles and users' online characteristics.
Findings
Through the analysis of over 700,000 political tweets, this study identifies six language styles: mobilizing, self-expressive, argumentative, narrative, analytic and informational. Furthermore, by investigating the covariation between language styles and users' online characteristics, such as social connections, expressive desires and gender, this study reveals a preference for an informational style and an aversion to an argumentative style in political discussions. It also uncovers gender differences in language styles, with women being more likely to belong to the mobilizing group but less likely to belong to the analytic and informational groups.
Practical implications
This study provides insights into the psychological mechanisms and social statuses of users who adopt particular language styles. It assists political communicators in understanding their audience and tailoring their language to suit specific contexts and communication objectives.
Social implications
This study reveals gender differences in language styles, suggesting that women may have a heightened desire for social support in political discussions. It highlights that traditional gender disparities in politics might persist in online public spaces.
Originality/value
This study develops a computational methodology by combining cluster analysis with pre-defined linguistic features to categorize language styles. This approach integrates statistical algorithms with communication and linguistic theories, providing researchers with an unsupervised method for analyzing textual data. It focuses on detecting language styles rather than topics or themes in the text, complementing widely used text classification methods such as topic modeling. Additionally, this study explores the associations between language styles and the online characteristics of social media users in a political context.
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Nimesh P. Bhojak, Suresh N. Patel and Mohammadali K. Momin
Digital healthcare once again emerges due to pandemic (Covid-19). Digital healthcare can be minimising the issue of accessibility, availability, accuracy and affordability of…
Abstract
Digital healthcare once again emerges due to pandemic (Covid-19). Digital healthcare can be minimising the issue of accessibility, availability, accuracy and affordability of healthcare service during a pandemic. Digital healthcare playsa significant role to provide healthcare equity during the pandemic. This article presents the current trends and scenario of digital healthcare with a focus on health equity. The main objective of this chapter is to review the four aces of health equity in the digital healthcare literature. The scope and challenges faced by the policymakers to implementation of digital healthcare to improve health equity. This chapter considers the hybrid literature review based on the bibliometric and the systematic literature based on the various theme, sub-theme, concept and context-related health equity through digital healthcare. This study provides the previous and current research trends and preposition for the future researcher, healthcare professional, policymakers and digital healthcare innovators to invent the tool which leads the health equity through the digital healthcare in the healthcare.
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Pankaj Kumar Detwal, Rajat Agrawal, Ashutosh Samadhiya, Anil Kumar and Jose Arturo Garza-Reyes
This study aims to examine current research on the relationship between Operational Excellence and Healthcare 4.0 (H4.0) for healthcare organizations.
Abstract
Purpose
This study aims to examine current research on the relationship between Operational Excellence and Healthcare 4.0 (H4.0) for healthcare organizations.
Design/methodology/approach
The authors have performed a systematic literature review of 102 documents published between 2011 and 2022 from the Scopus database to identify the research trends on Operational Excellence and H4.0. Through a descriptive bibliometric analysis, this study has highlighted the year-wise trend in publication, top authors, prominent sources of publications, the country-wise spread of research activities and subject area analysis. Furthermore, through content analysis, this study has identified four clusters and proposed directions for future research of each identified cluster.
Findings
Results reflect overall growth in this area, with a few parts of the world being underrepresented in research related to Operational Excellence and H4.0. The content analysis focused on describing challenges pertaining to healthcare industries and the role of Operational Excellence tools and H4.0 technologies in dealing with various healthcare delivery aspects. The authors concluded their analysis by proposing a theoretical framework and providing theoretical and managerial implications of the study.
Originality/value
To the best of the authors’ knowledge, the paper is one of the first to analyze the existing literature on the healthcare sector at the interface of Operational Excellence and H4.0 technologies. The conceptual framework and cluster-wise future research prepositions are some of the unique offerings of the study.
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Sampson Asiamah, Kingsely Opoku Appiah and Ebenezer Agyemang Badu
The purpose of this paper is to examine whether board characteristics moderate the relationship between capital adequacy regulation and bank risk-taking of universal banks in…
Abstract
Purpose
The purpose of this paper is to examine whether board characteristics moderate the relationship between capital adequacy regulation and bank risk-taking of universal banks in Sub-Saharan Africa (SSA).
Design/methodology/approach
The paper uses 700 bank-year observations of universal banks in SSA between 2009 and 2019. The paper further uses the two-step generalized method of moments as the baseline estimator.
Findings
The paper finds that capital adequacy regulation is positively related to overall bank and liquidity risks. Nonetheless, capital adequacy regulation increases credit risk in the sampled banks. The paper further reports that board characteristics individually and significantly moderate the relationship between capital adequacy regulation and risk-taking.
Practical implications
The findings have implications for regulators of universal banks that board characteristics matter for capital adequacy regulation to impact risk-taking behavior.
Originality/value
The paper extends the existing literature on the effect of board characteristics on the capital adequacy regulations and risk-taking behavior nexus of universal banks.
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Lala Hajibayova, Mallory McCorkhill and Timothy D. Bowman
In this study, STEM resources reviewed in Goodreads were investigated to determine their authorship, linguistic characteristics and impact. The analysis reveals gender disparity…
Abstract
Purpose
In this study, STEM resources reviewed in Goodreads were investigated to determine their authorship, linguistic characteristics and impact. The analysis reveals gender disparity favoring titles with male authors.
Design/methodology/approach
This paper applies theoretical concepts of knowledge commons to understand how individuals leverage the affordances of the Goodreads platform to share their perceptions of STEM-related books.
Findings
The analysis reveals gender disparity favoring titles with male authors. Female-authored STEM publications represent popular science nonfiction and juvenile genres. Analysis of the scholarly impact of the reviewed titles revealed that Google Scholar provides broader and more diverse coverage than Web of Science. Linguistic analysis of the reviews revealed the relatively low aesthetic disposition of reviewers with an emphasis on embodied experiences that emerged from the reading.
Originality/value
This study contributes to the understanding of the impact of popular STEM resources as well as the influence of the language of user-generated reviews on production, consumption and discoverability of STEM titles.
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Advanced big data analysis and machine learning methods are concurrently used to unleash the value of the data generated by government hotline and help devise intelligent…
Abstract
Purpose
Advanced big data analysis and machine learning methods are concurrently used to unleash the value of the data generated by government hotline and help devise intelligent applications including automated process management, standard construction and more accurate dispatched orders to build high-quality government service platforms as more widely data-driven methods are in the process.
Design/methodology/approach
In this study, based on the influence of the record specifications of texts related to work orders generated by the government hotline, machine learning tools are implemented and compared to optimize classify dispatching tasks by performing exploratory studies on the hotline work order text, including linguistics analysis of text feature processing, new word discovery, text clustering and text classification.
Findings
The complexity of the content of the work order is reduced by applying more standardized writing specifications based on combining text grammar numerical features. So, order dispatch success prediction accuracy rate reaches 89.6 per cent after running the LSTM model.
Originality/value
The proposed method can help improve the current dispatching processes run by the government hotline, better guide staff to standardize the writing format of work orders, improve the accuracy of order dispatching and provide innovative support to the current mechanism.
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Anandika Sharma, Tarunpreet Bhatia, Rohit Kumar Singh and Anupam Sharma
The food supply chain has faced many challenges due to its complex and complicated nature. Blockchain technology is one of the mechanisms used to improve agri-food supply chain…
Abstract
Purpose
The food supply chain has faced many challenges due to its complex and complicated nature. Blockchain technology is one of the mechanisms used to improve agri-food supply chain processes by evolving organization capabilities. A study is being conducted to scrutinize the adoption of blockchain technology in the agri-food supply chain through the lens of the operational capability approach. It further makes an attempt to identify the capabilities of blockchain to improve supply chain processes.
Design/methodology/approach
The qualitative research method with semi-structured interviews was used to gather information from experts and professionals in the food supply chain and blockchain technology. The authors have adopted a systematic approach of coding using open, axial and selective methods to depict and identify the themes that represent the blockchain-enabled agri-food supply chain. The data were collected from 32 interviews of selected participants.
Findings
The result shows five critical areas where blockchain can come up to enhance the agri-food supply chain performance by providing traceability, transparency, information security, transactions, and trust and quality. Further, the study reveals that blockchain will provide safety, lower the cost of transactions and can create trust among users to communicate within the whole supply chain without the intervention of a third party. This study demonstrated that the capabilities need to be considered when introducing technology into the practice.
Research limitations/implications
The study implies thought-provoking implications for bridging the theory-practice gap by examining the empirical data to demonstrate how the operational capabilities of blockchain technology further strengthen the agri-food supply chain. Additionally, this study provides some suggestions for utilizing the results and proposes a framework to understand more about blockchain use cases in the agri-food supply chain as well as extend the application of blockchain using an operational capability approach for future academic researchers in this area.
Practical implications
This study presented some more important managerial implications which reveal that the majority of organisations were in the initial stages of adoption process of blockchain technology. Further, the positive influence of managers and IT experts can help the information technology companies (IT) and stakeholders for developing and promoting blockchain solutions in the agri-food supply chain. The important implication of blockchain enabled agri-food supply chain is to maintain information security and incresae supply chain performance.
Originality/value
The study shows the operational capabilities of agri-food supply chain using blockchain technology. Blockchain can contribute in enhancing the agri-food supply chain to increase traceability and transparency and helps to reduce the risk of disruptions.
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