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1 – 10 of over 1000
Open Access
Article
Publication date: 15 August 2023

Doreen Nkirote Bundi

The purpose of this study is to examine the state of research into adoption of machine learning systems within the health sector, to identify themes that have been studied and…

Abstract

Purpose

The purpose of this study is to examine the state of research into adoption of machine learning systems within the health sector, to identify themes that have been studied and observe the important gaps in the literature that can inform a research agenda going forward.

Design/methodology/approach

A systematic literature strategy was utilized to identify and analyze scientific papers between 2012 and 2022. A total of 28 articles were identified and reviewed.

Findings

The outcomes reveal that while advances in machine learning have the potential to improve service access and delivery, there have been sporadic growth of literature in this area which is perhaps surprising given the immense potential of machine learning within the health sector. The findings further reveal that themes such as recordkeeping, drugs development and streamlining of treatment have primarily been focused on by the majority of authors in this area.

Research limitations/implications

The search was limited to journal articles published in English, resulting in the exclusion of studies disseminated through alternative channels, such as conferences, and those published in languages other than English. Considering that scholars in developing nations may encounter less difficulty in disseminating their work through alternative channels and that numerous emerging nations employ languages other than English, it is plausible that certain research has been overlooked in the present investigation.

Originality/value

This review provides insights into future research avenues for theory, content and context on adoption of machine learning within the health sector.

Details

Digital Transformation and Society, vol. 3 no. 1
Type: Research Article
ISSN: 2755-0761

Keywords

Open Access
Article
Publication date: 28 November 2022

Elena Stefana, Paola Cocca, Federico Fantori, Filippo Marciano and Alessandro Marini

This paper aims to overcome the inability of both comparing loss costs and accounting for production resource losses of Overall Equipment Effectiveness (OEE)-related approaches.

1401

Abstract

Purpose

This paper aims to overcome the inability of both comparing loss costs and accounting for production resource losses of Overall Equipment Effectiveness (OEE)-related approaches.

Design/methodology/approach

The authors conducted a literature review about the studies focusing on approaches combining OEE with monetary units and/or resource issues. The authors developed an approach based on Overall Equipment Cost Loss (OECL), introducing a component for the production resource consumption of a machine. A real case study about a smart multicenter three-spindle machine is used to test the applicability of the approach.

Findings

The paper proposes Resource Overall Equipment Cost Loss (ROECL), i.e. a new KPI expressed in monetary units that represents the total cost of losses (including production resource ones) caused by inefficiencies and deviations of the machine or equipment from its optimal operating status occurring over a specific time period. ROECL enables to quantify the variation of the product cost occurring when a machine or equipment changes its health status and to determine the actual product cost for a given production order. In the analysed case study, the most critical production orders showed an actual production cost about 60% higher than the minimal cost possible under the most efficient operating conditions.

Originality/value

The proposed approach may support both production and cost accounting managers during the identification of areas requiring attention and representing opportunities for improvement in terms of availability, performance, quality, and resource losses.

Details

International Journal of Productivity and Performance Management, vol. 73 no. 11
Type: Research Article
ISSN: 1741-0401

Keywords

Open Access
Article
Publication date: 29 April 2021

Roberto Sala, Marco Bertoni, Fabiana Pirola and Giuditta Pezzotta

This paper aims to present a dual-perspective framework for maintenance service delivery that should be used by manufacturing companies to structure and manage their maintenance…

2050

Abstract

Purpose

This paper aims to present a dual-perspective framework for maintenance service delivery that should be used by manufacturing companies to structure and manage their maintenance service delivery process, using aggregated historical and real-time data to improve operational decision-making. The framework, built for continuous improvement, allows the exploitation of maintenance data to improve the knowledge of service processes and machines.

Design/methodology/approach

The Dual-perspective, data-based decision-making process for maintenance delivery (D3M) framework development and test followed a qualitative approach based on literature reviews and semi-structured interviews. The pool of companies interviewed was expanded from the development to the test stage to increase its applicability and present additional perspectives.

Findings

The interviews confirmed that manufacturing companies are interested in exploiting the data generated in the use phase to improve operational decision-making in maintenance service delivery. Feedback to improve the framework methods and tools was collected, as well as suggestions for the introduction of new ones according to the companies' necessities.

Originality/value

The paper presents a novel framework addressing the data-based decision-making process for maintenance service delivery. The D3M framework can be used by manufacturing companies to structure their maintenance service delivery process and improve their knowledge of machines and service processes.

Details

Journal of Manufacturing Technology Management, vol. 32 no. 9
Type: Research Article
ISSN: 1741-038X

Keywords

Abstract

Purpose

Mental illness presents a huge individual, societal and economic challenges, currently accounting for 20% of the worldwide burden of disease. There is a gap between the need for and access to services. Digital technology has been proven effective in e-mental health for preventing and treating mental health problems. However, there is a need for cross-disciplinary efforts to increase the impact of e-mental health services. This paper aims to report key challenges and possible solutions for cross-disciplinary and cross-sectorial research teams within the domain of e-mental health.

Design/methodology/approach

The key challenges and possible solutions will be discussed in light of the literature on effective cross-disciplinary research teams.

Findings

Six topics have been key challenges in our cross-disciplinary and cross-sectorial research team: to develop a shared understanding of the domain; to establish a common understanding of key concepts among the project participants; to involve the end-users in the research and development process; to collaborate across sectors; to ensure privacy and security of health data; and to obtain the right timing of activities according to project dependencies.

Research limitations/implications

This study focuses to increase knowledge and training in cross-disciplinary and cross-sectorial research, as this is often referred to as an important tool when developing sustainable solutions for major societal challenges.

Practical implications

This study needs to include theory and skills training in cross-disciplinary research in research training.

Social implications

Cross-disciplinary teams have the potential to address major societal challenges, including more perspectives and more stakeholders than single disciplinary research teams.

Originality/value

Major societal challenges require complex and sustainable solutions. However, there is a lack of knowledge about how cross-disciplinary and cross-sectorial research teams may work productively to solve these challenges. This paper shares experiences regarding the challenges and possible solutions for productive collaboration in cross-disciplinary and cross-sectorial research teams within the domain of e-mental health services.

Details

Journal of Enabling Technologies, vol. 15 no. 4
Type: Research Article
ISSN: 2398-6263

Keywords

Open Access
Article
Publication date: 7 June 2021

Adriana Soares Ito, Torbjörn Ylipää, Per Gullander, Jon Bokrantz and Anders Skoogh

Manufacturing companies struggle to manage production disturbances. One step of such management deals with prioritising those disturbances which should undergo root cause…

1722

Abstract

Purpose

Manufacturing companies struggle to manage production disturbances. One step of such management deals with prioritising those disturbances which should undergo root cause analysis. The focus of this work is on two areas. First, investigating current challenges faced by manufacturing companies when prioritising root cause analysis of production disturbances. Second, identifying the stakeholders and factors impacted by production disturbances. Understanding the current challenges and identifying impacted stakeholders and factors allows the development of more efficient prioritisation strategies and, thus, contributes to the reduction of frequency and impact of disturbances.

Design/methodology/approach

To achieve the intended purpose of this research, a qualitative approach was chosen. A series of interviews was conducted with practitioners, to identify current challenges. A series of focus groups was also held, to identify the impacted stakeholders and factors by disturbances.

Findings

Various challenges were identified. These are faced by manufacturing companies in their prioritisation of production disturbances and relate to the time needed, criteria used, centralisation of the process, perspective considered and data support. It was also found that a wide range of stakeholders is impacted by production disturbances, surpassing the limits of production and maintenance departments. Furthermore, the most critical factors impacted are quality, work environment, safety, time, company results, customer satisfaction, productivity, deliverability, resource utilisation, profit, process flow, plannability, machine health and reputation.

Originality/value

The current situation regarding root cause analysis prioritisation has not been identified in previous works. Moreover, there has been no prior systematic identification of the various stakeholders and factors impacted by production disturbances.

Details

International Journal of Quality & Reliability Management, vol. 39 no. 5
Type: Research Article
ISSN: 0265-671X

Keywords

Open Access
Article
Publication date: 25 May 2023

Suchismita Swain, Kamalakanta Muduli, Anil Kumar and Sunil Luthra

The goal of this research is to analyse the obstacles to the implementation of mobile health (mHealth) in India and to gain an understanding of the contextual inter-relationships…

Abstract

Purpose

The goal of this research is to analyse the obstacles to the implementation of mobile health (mHealth) in India and to gain an understanding of the contextual inter-relationships that exist amongst those obstacles.

Design/methodology/approach

Potential barriers and their interrelationships in their respective contexts have been uncovered. Using MICMAC analysis, the categorization of these barriers was done based on their degree of reliance and driving power (DP). Furthermore, an interpretive structural modeling (ISM) framework for the barriers to mHealth activities in India has been proposed.

Findings

The study explores a total of 15 factors that reduce the efficiency of mHealth adoption in India. The findings of the Matrix Cross-Reference Multiplication Applied to a Classification (MICMAC) investigation show that the economic situation of the government, concerns regarding the safety of intellectual technologies and privacy issues are the primary obstacles because of the significant driving power they have in mHealth applications.

Practical implications

Promoters of mHealth practices may be able to make better plans if they understand the social barriers and how they affect each other; this leads to easier adoption of these practices. The findings of this study might be helpful for governments of developing nations to produce standards relating to the deployment of mHealth; this will increase the efficiency with which it is adopted.

Originality/value

At this time, there is no comprehensive analysis of the factors that influence the adoption of mobile health care with social cognitive theory in developing nations like India. In addition, there is a lack of research in investigating how each of these elements affects the success of mHealth activities and how the others interact with them. Because developed nations learnt the value of mHealth practices during the recent pandemic, this study, by investigating the obstacles to the adoption of mHealth and their inter-relationships, makes an important addition to both theory and practice.

Details

International Journal of Industrial Engineering and Operations Management, vol. 6 no. 2
Type: Research Article
ISSN: 2690-6090

Keywords

Open Access
Article
Publication date: 31 October 2022

Sunday Adewale Olaleye, Emmanuel Mogaji, Friday Joseph Agbo, Dandison Ukpabi and Akwasi Gyamerah Adusei

The data economy mainly relies on the surveillance capitalism business model, enabling companies to monetize their data. The surveillance allows for transforming private human…

2012

Abstract

Purpose

The data economy mainly relies on the surveillance capitalism business model, enabling companies to monetize their data. The surveillance allows for transforming private human experiences into behavioral data that can be harnessed in the marketing sphere. This study aims to focus on investigating the domain of data economy with the methodological lens of quantitative bibliometric analysis of published literature.

Design/methodology/approach

The bibliometric analysis seeks to unravel trends and timelines for the emergence of the data economy, its conceptualization, scientific progression and thematic synergy that could predict the future of the field. A total of 591 data between 2008 and June 2021 were used in the analysis with the Biblioshiny app on the web interfaced and VOSviewer version 1.6.16 to analyze data from Web of Science and Scopus.

Findings

This study combined findable, accessible, interoperable and reusable (FAIR) data and data economy and contributed to the literature on big data, information discovery and delivery by shedding light on the conceptual, intellectual and social structure of data economy and demonstrating data relevance as a key strategic asset for companies and academia now and in the future.

Research limitations/implications

Findings from this study provide a steppingstone for researchers who may engage in further empirical and longitudinal studies by employing, for example, a quantitative and systematic review approach. In addition, future research could expand the scope of this study beyond FAIR data and data economy to examine aspects such as theories and show a plausible explanation of several phenomena in the emerging field.

Practical implications

The researchers can use the results of this study as a steppingstone for further empirical and longitudinal studies.

Originality/value

This study confirmed the relevance of data to society and revealed some gaps to be undertaken for the future.

Details

Information Discovery and Delivery, vol. 51 no. 2
Type: Research Article
ISSN: 2398-6247

Keywords

Open Access
Article
Publication date: 28 June 2021

Humphrey Ngala Ndi, Roland Akoh Ndi, Henry Ngenyam Bang, Marcellus Forh Mbah and Judwin Alieh Ndzo

This paper aims to explore the responses of households in the informal economic sector to the Cameroon Government strategy against Covid-19 in Yaounde, Cameroon between March and…

1351

Abstract

Purpose

This paper aims to explore the responses of households in the informal economic sector to the Cameroon Government strategy against Covid-19 in Yaounde, Cameroon between March and May 2020.

Design/methodology/approach

Given the recency of Covid-19, the exploratory design was used to collect and analyse information for the study. Empirical data was obtained through personal observations and questionnaires, whereas grey data were sourced from official sources in government and international agencies in Yaounde. The mode of the ordinal data generated from the questionnaire was used to characterise the attitudes of respondents to quarantine measures and bar charts were used to illustrate the distribution of responses.

Findings

The government’s strategy against Covid-19 was largely ignored in Yaounde between March and May 2020 because of the influence of the predominantly informal economy on household’s ability to allocate scarce resources between the competing needs of protecting their health on the one hand, and their livelihoods on the other hand. Poor households had to walk a difficult line between shutting down their businesses to protect their health or risking Covid-19 infections to protect their livelihoods. Over 53.1% of respondents thought quarantine measures were unsuccessful as over 63% ignored them. Quarantining and Social distancing were also difficult in informal settlements because of structural congestion.

Research limitations/implications

Perhaps, the greatest limitation of this study was the use of non-probability sampling. As such, sampling error could not be estimated, blurring the ability to ascertain the degree of similarity between the sample and the study population. This made sample generalisability difficult.

Practical implications

There are short-term and long-term policy implications of these findings. Basic comprehensive measures including food and water distribution, as well as rent holidays, must be implemented in informal neighbourhoods to ensure more successful quarantines in future pandemics. In the long run, investments in urban social housing must be carried out to reduce slums, an ever-present risk factor in the rapid propagation of infections.

Originality/value

The originality of this study is first, in its level of analysis which is the household. By measuring household responses to quarantine measures within defined neighbourhoods, the study deviates from most that have adopted a theoretical approach and conducted analysis at country or regional levels. Few studies have attempted to investigate the failure of quarantine measures against Covid-19 from the viewpoint of the occupational characteristics of the populations involved.

Details

Journal of Humanities and Applied Social Sciences, vol. 3 no. 5
Type: Research Article
ISSN:

Keywords

Open Access
Article
Publication date: 14 June 2021

Narinderjeet Kaur Dadar Singh, Jiann Lin Loo, Azlan Ming Naing Ko, Syed Shajee Husain, Jiloris Frederick Dony and Syed Sharizman Syed Abdul Rahim

This study aims to determine the prevalence of obesity and its relationship with mental health issues among healthcare workers in Kota Kinabalu District Health Office, Sabah…

3261

Abstract

Purpose

This study aims to determine the prevalence of obesity and its relationship with mental health issues among healthcare workers in Kota Kinabalu District Health Office, Sabah Borneo and its associating factors.

Design/methodology/approach

This cross-sectional study was conducted among 387 healthcare workers working in the Kota Kinabalu District Health Office, Sabah. Sociodemographic data and anthropometric measurements were collected and DASS 21 questionnaire was used to assess mental health status.

Findings

The prevalence of obesity among healthcare workers was 29%, which is significantly associated with years of service (p = 0.016) and abnormal depression subscale scores (p = 0.012) at univariate analysis. The percentage of abnormal subscale score for depression, anxiety and stress was 16, 26 and 12%, respectively. Multivariable logistic regression revealed that more than five years of service years (OR 2.23, 95%CI 1.16–4.28) and high depressive subscale score (OR 2.09, 95%CI 1.18–3.71) were both significantly associated with obesity.

Originality/value

This study has affirmed the link between physical and mental health. Policies that tackle both issues should be put in place to promote wellness among healthcare workers.

Details

Journal of Health Research, vol. 36 no. 5
Type: Research Article
ISSN: 0857-4421

Keywords

Open Access
Article
Publication date: 27 September 2023

Myrthe Blösser and Andrea Weihrauch

In spite of the merits of artificial intelligence (AI) in marketing and social media, harm to consumers has prompted calls for AI auditing/certification. Understanding consumers’…

1917

Abstract

Purpose

In spite of the merits of artificial intelligence (AI) in marketing and social media, harm to consumers has prompted calls for AI auditing/certification. Understanding consumers’ approval of AI certification entities is vital for its effectiveness and companies’ choice of certification. This study aims to generate important insights into the consumer perspective of AI certifications and stimulate future research.

Design/methodology/approach

A literature and status-quo-driven search of the AI certification landscape identifies entities and related concepts. This study empirically explores consumer approval of the most discussed entities in four AI decision domains using an online experiment and outline a research agenda for AI certification in marketing/social media.

Findings

Trust in AI certification is complex. The empirical findings show that consumers seem to approve more of non-profit entities than for-profit entities, with the government approving the most.

Research limitations/implications

The introduction of AI certification to marketing/social media contributes to work on consumer trust and AI acceptance and structures AI certification research from outside marketing to facilitate future research on AI certification for marketing/social media scholars.

Practical implications

For businesses, the authors provide a first insight into consumer preferences for AI-certifying entities, guiding the choice of which entity to use. For policymakers, this work guides their ongoing discussion on “who should certify AI” from a consumer perspective.

Originality/value

To the best of the authors’ knowledge, this work is the first to introduce the topic of AI certification to the marketing/social media literature, provide a novel guideline to scholars and offer the first set of empirical studies examining consumer approval of AI certifications.

Details

European Journal of Marketing, vol. 58 no. 2
Type: Research Article
ISSN: 0309-0566

Keywords

1 – 10 of over 1000