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Article
Publication date: 21 December 2023

Ann-Marie Bright, Agnes Higgins and Annmarie Grealish

There has been a move towards the implementation of digital/e-health interventions for some time. Digital/e-health interventions have demonstrable efficacy in increasing…

Abstract

Purpose

There has been a move towards the implementation of digital/e-health interventions for some time. Digital/e-health interventions have demonstrable efficacy in increasing individual empowerment, providing timely access to psychological interventions for those experiencing mental ill-health and improving outcomes for those using them. This study aims to determine the efficacy of digital/e-health interventions for individuals detained in prison who experience mental ill-health.

Design/methodology/approach

A systematic search of five academic databases – CINAHL, ASSIA, PsycINFO, Embase and Medline – was completed in December 2020 and updated in February 2022. The review was guided by the Whittemore and Knafl (2005) framework for integrative reviews. A total of 6,255 studies were returned and screened by title and abstract. A full-text screening of nine (n = 9) studies was conducted.

Findings

No study met the inclusion criteria for the clinical efficacy of digital/e-health interventions in a prison setting. Subsequently, a review of the literature that made it to the full-text review stage was conducted, and gaps in the literature were identified to inform policy, practice and future research.

Originality/value

To the best of the authors’ knowledge, this is the first integrative review conducted on the efficacy of digital/e-health interventions for mental ill-health in prison settings.

Details

International Journal of Prison Health, vol. 20 no. 1
Type: Research Article
ISSN: 2977-0254

Keywords

Article
Publication date: 20 March 2024

Anni Rahimah, Ben-Roy Do, Angelina Nhat Hanh Le and Julian Ming Sung Cheng

This study aims to investigate specific green-brand affect in terms of commitment and connection through the morality–mortality determinants of consumer social responsibility and…

Abstract

Purpose

This study aims to investigate specific green-brand affect in terms of commitment and connection through the morality–mortality determinants of consumer social responsibility and the assumptions of terror management theory in the proposed three-layered framework. Religiosity serves as a moderator within the framework.

Design/methodology/approach

Data are collected in Taipei, Taiwan, while quota sampling is applied, and 420 valid questionnaires are collected. The partial least squares technique is applied for data analysis.

Findings

With the contingent role of religiosity, consumer social responsibility influences socially conscious consumption, which in turn drives the commitment and connection of green-brand affect. The death anxiety and self-esteem outlined in terror management theory influence materialism, which then drives green-brand commitment; however, contrary to expectations, they do not drive green-brand connection.

Originality/value

By considering green brands beyond their cognitive aspects and into their affective counterparts, morality–mortality drivers of green-brand commitment and green-grand connection are explored to provide unique contributions so as to better understand socially responsible consumption.

Details

Journal of Product & Brand Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1061-0421

Keywords

Open Access
Article
Publication date: 22 December 2023

Hai-Anh Dang, Toan L.D. Huynh and Manh-Hung Nguyen

The COVID-19 pandemic has wrought havoc on economies around the world. The purpose of this study is to learn about the distributional impacts of the pandemic.

Abstract

Purpose

The COVID-19 pandemic has wrought havoc on economies around the world. The purpose of this study is to learn about the distributional impacts of the pandemic.

Design/methodology/approach

The authors contribute new theoretical and empirical evidence on the distributional impacts of the pandemic on different income groups in a multicountry setting. The authors analyze rich individual-level survey data covering 6,082 respondents from China, Italy, Japan, South Korea, the United Kingdom and the United States. The results are robust to various econometric models, including ordinary least squares (OLS), Tobit and ordered probit models with country-fixed effects.

Findings

The authors find that while the outbreak has no impact on household income losses, it results in a 63% reduction in the expected own labor income for the second-poorest income quintile. The pandemic impacts are most noticeable for savings, with all the four poorer income quintiles suffering reduced savings ranging between 5 and 7% compared to the richest income quintile. The poor are also less likely to change their behaviors regarding immediate prevention measures against COVID-19 and healthy activities. The authors also found countries to exhibit heterogeneous impacts.

Social implications

Designing tailor-made social protection and health policies to support the poorer income groups in richer and poorer countries can generate multiple positive impacts that help minimize the negative and inequality-enhancing pandemic consequences. These findings are relevant not only for COVID-19 but also for future pandemics.

Originality/value

The authors theoretically and empirically investigate the impacts of the pandemic on poorer income groups, while previous studies mostly offer empirical analyses and focus on other sociodemographic factors. The authors offer a new multicountry analysis of several prevention measures against COVID-19 and specific health activities.

Details

Journal of Economics and Development, vol. 26 no. 1
Type: Research Article
ISSN: 1859-0020

Keywords

Article
Publication date: 7 February 2024

Dwi Suhartanto, David Dean and Iklima Farhani

This study aims to evaluate the loyalty formation model on e-grocery service incorporating food quality, e-grocery quality and relationship quality as determinants of loyalty.

Abstract

Purpose

This study aims to evaluate the loyalty formation model on e-grocery service incorporating food quality, e-grocery quality and relationship quality as determinants of loyalty.

Design/methodology/approach

The quantitative approach was used by using 353 data from young Indonesian customers with purchasing experience of local food through e-grocery service. The hypothesized relationships between variables were tested using partial least squares structural equation modeling.

Findings

The results confirm that local food quality, e-grocery service quality and the relationship quality elements of a sense of community and attitudinal attachment, are all loyalty drivers. Next, mediation tests reveal that local food quality and e-grocery service quality influence customer loyalty through customers’ attitudinal attachment and a sense of community.

Practical implications

This study recommends that managers of e-grocery services of local food businesses could benefit from the development of attachment and a sense of community among their young clients. Furthermore, to develop loyalty among young customers, offering high-quality local food as well as e-grocery services is suggested.

Originality/value

To the best of the author’s knowledge, this is the first examination of the e-grocery service loyalty in the context of local food.

Details

International Journal of Quality and Service Sciences, vol. 16 no. 1
Type: Research Article
ISSN: 1756-669X

Keywords

Article
Publication date: 28 February 2024

Nastaran Hajiheydari and Mohammad Soltani Delgosha

Digital labor platforms (DLPs) are transforming the nature of the work for an increasing number of workers, especially through extensively employing automated algorithms for…

Abstract

Purpose

Digital labor platforms (DLPs) are transforming the nature of the work for an increasing number of workers, especially through extensively employing automated algorithms for performing managerial functions. In this novel working setting – characterized by algorithmic governance, and automatic matching, rewarding and punishing mechanisms – gig-workers play an essential role in providing on-demand services for final customers. Since gig-workers’ continued participation is crucial for sustainable service delivery in platform contexts, this study aims to identify and examine the antecedents of their working outcomes, including burnout and engagement.

Design/methodology/approach

We suggested a theoretical framework, grounded in the job demands-resources heuristic model to investigate how the interplay of job demands and resources, resulting from working in DLPs, explains gig-workers’ engagement and burnout. We further empirically tested the proposed model to understand how DLPs' working conditions, in particular their algorithmic management, impact gig-working outcomes.

Findings

Our findings indicate that job resources – algorithmic compensation, work autonomy and information sharing– have significant positive effects on gig-workers’ engagement. Furthermore, our results demonstrate that job insecurity, unsupportive algorithmic interaction (UAI) and algorithmic injustice significantly contribute to gig-workers’ burnout. Notably, we found that job resources substantially, but differently, moderate the relationship between job demands and gig-workers’ burnout.

Originality/value

This study contributes a theoretically accurate and empirically grounded understanding of two clusters of conditions – job demands and resources– as a result of algorithmic management practice in DLPs. We developed nuanced insights into how such conditions are evaluated by gig-workers and shape their engagement or burnout in DLP emerging work settings. We further uncovered that in gig-working context, resources do not similarly buffer against the negative effects of job demands.

Details

Information Technology & People, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0959-3845

Keywords

Book part
Publication date: 5 April 2024

Zhichao Wang and Valentin Zelenyuk

Estimation of (in)efficiency became a popular practice that witnessed applications in virtually any sector of the economy over the last few decades. Many different models were…

Abstract

Estimation of (in)efficiency became a popular practice that witnessed applications in virtually any sector of the economy over the last few decades. Many different models were deployed for such endeavors, with Stochastic Frontier Analysis (SFA) models dominating the econometric literature. Among the most popular variants of SFA are Aigner, Lovell, and Schmidt (1977), which launched the literature, and Kumbhakar, Ghosh, and McGuckin (1991), which pioneered the branch taking account of the (in)efficiency term via the so-called environmental variables or determinants of inefficiency. Focusing on these two prominent approaches in SFA, the goal of this chapter is to try to understand the production inefficiency of public hospitals in Queensland. While doing so, a recognized yet often overlooked phenomenon emerges where possible dramatic differences (and consequently very different policy implications) can be derived from different models, even within one paradigm of SFA models. This emphasizes the importance of exploring many alternative models, and scrutinizing their assumptions, before drawing policy implications, especially when such implications may substantially affect people’s lives, as is the case in the hospital sector.

Book part
Publication date: 5 April 2024

Mike G. Tsionas

In this chapter, we consider the possibility that a firm may use costly resources to improve its technical efficiency. Results from static analyses imply that technical efficiency…

Abstract

In this chapter, we consider the possibility that a firm may use costly resources to improve its technical efficiency. Results from static analyses imply that technical efficiency is determined by the configuration of factor prices. A dynamic model of the firm is developed under the assumption that managerial skill contributes to technical efficiency. Dynamic analysis shows that the firm can never be technically efficient if it maximizes profits, the steady state is always inefficient, and it is locally stable. In terms of empirical analysis, we show how likelihood-based methods can be used to uncover, in a semi-non-parametric manner, important features of the inefficiency-management relationship using a flexible functional form accounting for the endogeneity of inputs in a production function. Managerial compensation can also be identified and estimated using the new techniques. The new empirical methodology is applied in a data set previously analyzed by Bloom and van Reenen (2007) on managerial practices of manufacturing firms in the UK, US, France and Germany.

Article
Publication date: 4 December 2023

Ahmed M. Attia, Ahmad O. Alatwi, Ahmad Al Hanbali and Omar G. Alsawafy

This research integrates maintenance planning and production scheduling from a green perspective to reduce the carbon footprint.

Abstract

Purpose

This research integrates maintenance planning and production scheduling from a green perspective to reduce the carbon footprint.

Design/methodology/approach

A mixed-integer nonlinear programming (MINLP) model is developed to study the relation between production makespan, energy consumption, maintenance actions and footprint, i.e. service level and sustainability measures. The speed scaling technique is used to control energy consumption, the capping policy is used to control CO2 footprint and preventive maintenance (PM) is used to keep the machine working in healthy conditions.

Findings

It was found that ignoring maintenance activities increases the schedule makespan by more than 21.80%, the total maintenance time required to keep the machine healthy by up to 75.33% and the CO2 footprint by 15%.

Research limitations/implications

The proposed optimization model can simultaneously be used for maintenance planning, job scheduling and footprint minimization. Furthermore, it can be extended to consider other maintenance activities and production configurations, e.g. flow shop or job shop scheduling.

Practical implications

Maintenance planning, production scheduling and greenhouse gas (GHG) emissions are intertwined in the industry. The proposed model enhances the performance of the maintenance and production systems. Furthermore, it shows the value of conducting maintenance activities on the machine's availability and CO2 footprint.

Originality/value

This work contributes to the literature by combining maintenance planning, single-machine scheduling and environmental aspects in an integrated MINLP model. In addition, the model considers several practical features, such as machine-aging rate, speed scaling technique to control emissions, minimal repair (MR) and PM.

Details

Journal of Quality in Maintenance Engineering, vol. 30 no. 1
Type: Research Article
ISSN: 1355-2511

Keywords

Article
Publication date: 2 November 2022

Moses Elaigwu, Salau Olarinoye Abdulmalik and Hassnain Raghib Talab

This paper aims to examine the effect of corporate integrity and external assurance on Sustainability Reporting Quality (SRQ) of Malaysian public listed companies.

Abstract

Purpose

This paper aims to examine the effect of corporate integrity and external assurance on Sustainability Reporting Quality (SRQ) of Malaysian public listed companies.

Design/methodology/approach

The study uses a longitudinal sample of 2,463 firm-year observations of non-financial firms listed on the main board of Bursa Malaysia from 2015 to 2019. The study employed panel regression that is, Fixed Effect (FE) Robust Standard Error estimation technique to test its hypotheses.

Findings

The panel regression results reveal that corporate integrity and external assurance positively and significantly influence the quality of sustainability reporting. Though the positive association shows an improvement in the SRQ of the sampled firms, it needs an improvement as the disclosure is more general and qualitative than quantitative. The present improvement in SRQ might result from some regulatory changes like the Sustainability Practice Note 9 Updates of Bursa Malaysia 2017 and the Revised MCCG Principle A to C within the same period.

Research limitations/implications

The study adopts a purely quantitative approach and call for a qualitative investigation in the area in the future.

Practical implications

The study has policy implication for the government and regulators to strengthen compliance with the sustainability reporting guide and the Practice Note 9 Updates. It also has implication for corporate integrity and external assurance for companies, to enhance SRQ and achieve sustainable development.

Originality/value

The study bridged literature gaps by offering new insights and empirical evidence on the role of corporate integrity in SRQ, which has received no empirical attention in the Malaysian context.

Details

Asia-Pacific Journal of Business Administration, vol. 16 no. 2
Type: Research Article
ISSN: 1757-4323

Keywords

Article
Publication date: 18 September 2023

Jianxiang Qiu, Jialiang Xie, Dongxiao Zhang and Ruping Zhang

Twin support vector machine (TSVM) is an effective machine learning technique. However, the TSVM model does not consider the influence of different data samples on the optimal…

Abstract

Purpose

Twin support vector machine (TSVM) is an effective machine learning technique. However, the TSVM model does not consider the influence of different data samples on the optimal hyperplane, which results in its sensitivity to noise. To solve this problem, this study proposes a twin support vector machine model based on fuzzy systems (FSTSVM).

Design/methodology/approach

This study designs an effective fuzzy membership assignment strategy based on fuzzy systems. It describes the relationship between the three inputs and the fuzzy membership of the sample by defining fuzzy inference rules and then exports the fuzzy membership of the sample. Combining this strategy with TSVM, the FSTSVM is proposed. Moreover, to speed up the model training, this study employs a coordinate descent strategy with shrinking by active set. To evaluate the performance of FSTSVM, this study conducts experiments designed on artificial data sets and UCI data sets.

Findings

The experimental results affirm the effectiveness of FSTSVM in addressing binary classification problems with noise, demonstrating its superior robustness and generalization performance compared to existing learning models. This can be attributed to the proposed fuzzy membership assignment strategy based on fuzzy systems, which effectively mitigates the adverse effects of noise.

Originality/value

This study designs a fuzzy membership assignment strategy based on fuzzy systems that effectively reduces the negative impact caused by noise and then proposes the noise-robust FSTSVM model. Moreover, the model employs a coordinate descent strategy with shrinking by active set to accelerate the training speed of the model.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 17 no. 1
Type: Research Article
ISSN: 1756-378X

Keywords

1 – 10 of 55