Sustainable warehouse evaluation with AHPSort traffic light visualisation and post-optimal analysis method

Sustainable warehousing is essential for organisations to achieve overall supply chain sustainability. Warehousing facilities have the greatest potential for reducing socio-environmental impact. Yet, both research and practice have given relatively less attention to considering all aspects of sustainability in warehouses. In order to address this gap, this study proposes combining both input from professionals and from a literature survey of triple-bottom-line theory in order to develop a sustainable warehouse criteria framework, thus contributing to sustainable organisational warehouse evaluation. The method supporting the evaluation of this framework is based on the integration of a multicriteria AHPSort traffic light visualisation technique and novel post-optimal analysis. Furthermore, the authors deployed this framework and integrated methodology in an Indian manufacturing company to evaluate and classify seven of their warehouses for decision making. The traffic light visualisation technique presents and conveys the results better than numbers. Finally, the new post-optimal analysis provides recommendations for cost efficient improvements. The findings of this study present valuable insights and guidelines for industrial managers and practitioners, especially those from the Indian manufacturing industry, for sustainable warehouse decision-making, and for improving their overall corporate sustainability performance

A best-worst-method-based performance evaluation framework for manufacturing industry

Purpose: The purpose of paper is to develop a performance evaluation framework for manufacturing industry to evaluate overall manufacturing performance. Design/methodology/approach: The Best Worst Method (BWM) is used to aid in developing a performance evaluation framework for manufacturing industry to evaluate their overall performance. Findings: The proposed BWM-based manufacturing performance evaluation framework is implemented in an Indian steel manufacturing company to evaluate their overall manufacturing performance. Operational performance of the organization is very consistent and range between 60% to 70% throughout the year. Management performance can be seen high in percentage in the first two quarter of the financial year ranging from 70% to 80% whereas a slight decrease in the management performance is observed in the 3rd and 4th quarter ranging from 60% to 70%. The social stakeholder performance has a peak in first quarter ranging from 80% to 100% as at start of financial year. Originality/value: This paper utilized BWM, a MCDM method in developing a performance evaluation index that integrates several categories of manufacturing and evaluates overall manufacturing performance. This is a novel contribution to BWM decision-making application.Output Status: Forthcoming/Available Onlin

Mental Health Prevention and Promotion in General Practice Settings: A Protocol for a Feasibility Study

Background A reactive approach is typically taken when addressing and intervening with mental health problems rather than a proactive or preventative one, yet preventative approaches can also reduce mental ill-health. This study protocol aims to evaluate the feasibility of recruiting general practice patients into a randomised feasibility study where they will receive either mental health treatment as usual or a brief psychological intervention for preventing the deterioration of mental health and promoting emotional wellbeing. Methods This is a two-arm RCT, where participants will be randomised to either: treatment-as-usual within GP; or treatment-as-usual within GP plus a mental health prevention and promotion intervention. Sixty patients, aged 16+ from GP surgeries, with mild to moderate mental health difficulties as indicated by the PHQ9 and GAD7 will be recruited. Data on engagement with the intervention will be summarised using descriptive statistics. Regression models will be fitted, using the 12-week post-intervention follow-up data as the outcome variable and age, gender, trial arm and the corresponding baseline data as covariates. Cost-effectiveness will be investigated in an explorative way. Descriptive statistics will be used to analyse participant's resource use and HRQoL. Qualitative data will understand factors that facilitate or challenge the successful implementation of interventions and a process evaluation will provide insight into the intervention's mechanisms of action. Discussion The research team will progress from a feasibility RCT to a larger definitive RCT and disseminate widely across stakeholders (clinical, academic, service users, caregivers, Integrated Care Board (ICB) colleagues), ensuring accessibility in collaboration with the PPI committee

Convalescent plasma in patients admitted to hospital with COVID-19 (RECOVERY): a randomised controlled, open-label, platform trial

SummaryBackground Azithromycin has been proposed as a treatment for COVID-19 on the basis of its immunomodulatoryactions. We aimed to evaluate the safety and efficacy of azithromycin in patients admitted to hospital with COVID-19.Methods In this randomised, controlled, open-label, adaptive platform trial (Randomised Evaluation of COVID-19Therapy [RECOVERY]), several possible treatments were compared with usual care in patients admitted to hospitalwith COVID-19 in the UK. The trial is underway at 176 hospitals in the UK. Eligible and consenting patients wererandomly allocated to either usual standard of care alone or usual standard of care plus azithromycin 500 mg once perday by mouth or intravenously for 10 days or until discharge (or allocation to one of the other RECOVERY treatmentgroups). Patients were assigned via web-based simple (unstratified) randomisation with allocation concealment andwere twice as likely to be randomly assigned to usual care than to any of the active treatment groups. Participants andlocal study staff were not masked to the allocated treatment, but all others involved in the trial were masked to theoutcome data during the trial. The primary outcome was 28-day all-cause mortality, assessed in the intention-to-treatpopulation. The trial is registered with ISRCTN, 50189673, and ClinicalTrials.gov, NCT04381936.Findings Between April 7 and Nov 27, 2020, of 16 442 patients enrolled in the RECOVERY trial, 9433 (57%) wereeligible and 7763 were included in the assessment of azithromycin. The mean age of these study participants was65·3 years (SD 15·7) and approximately a third were women (2944 [38%] of 7763). 2582 patients were randomlyallocated to receive azithromycin and 5181 patients were randomly allocated to usual care alone. Overall,561 (22%) patients allocated to azithromycin and 1162 (22%) patients allocated to usual care died within 28 days(rate ratio 0·97, 95% CI 0·87–1·07; p=0·50). No significant difference was seen in duration of hospital stay (median10 days [IQR 5 to >28] vs 11 days [5 to >28]) or the proportion of patients discharged from hospital alive within 28 days(rate ratio 1·04, 95% CI 0·98–1·10; p=0·19). Among those not on invasive mechanical ventilation at baseline, nosignificant difference was seen in the proportion meeting the composite endpoint of invasive mechanical ventilationor death (risk ratio 0·95, 95% CI 0·87–1·03; p=0·24).Interpretation In patients admitted to hospital with COVID-19, azithromycin did not improve survival or otherprespecified clinical outcomes. Azithromycin use in patients admitted to hospital with COVID-19 should be restrictedto patients in whom there is a clear antimicrobial indication

Sustainable warehouse evaluation with AHPSort traffic light visualization and post-optimal analysis method

Sustainable warehousing is essential for organizations to achieve overall supply chain sustainability. Warehousing facilities have the greatest potential for reducing socio-environmental impact. Yet, both research and practice have given relatively less attention to considering all aspects of sustainability in warehouses. In order to address this gap, this study proposes combining both input from professionals and from a literature survey of triple-bottom-line theory in order to develop a sustainable warehouse criteria framework, thus contributing to sustainable organizational warehouse evaluation. The method supporting the evaluation of this framework is based on the integration of a multicriteria AHPSort-traffic light visualization technique and novel post-optimal analysis. Furthermore, the authors deployed this framework and integrated methodology in an Indian manufacturing company to evaluate and classify seven of their warehouses for decision making. The traffic light visualization technique presents and conveys the results better than numbers. Finally, the new post-optimal analysis provides recommendations for cost efficient improvements. The findings of this study present valuable insights and guidelines for industrial managers and practitioners, especially those from the Indian manufacturing industry, for sustainable warehouse decision-making, and for improving their overall corporate sustainability performance

A best-worst-method-based performance evaluation framework for manufacturing industry

Purpose: the purpose of paper is to develop a performance evaluation framework for manufacturing industry to evaluate overall manufacturing performance.Design/methodology/approach: the Best Worst Method (BWM) is used to aid in developing a performance evaluation framework for manufacturing industry to evaluate their overall performance. Findings: the proposed BWM-based manufacturing performance evaluation framework is implemented in an Indian steel manufacturing company to evaluate their overall manufacturing performance. Operational performance of the organization is very consistent and range between 60% to 70% throughout the year. Management performance can be seen high in percentage in the first two quarter of the financial year ranging from 70% to 80% whereas a slight decrease in the management performance is observed in the 3rd and 4th quarter ranging from 60% to 70%. The social stakeholder performance has a peak in first quarter ranging from 80% to 100% as at start of financial year.Originality/value: this paper utilized BWM, a MCDM method in developing a performance evaluation index that integrates several categories of manufacturing and evaluates overall manufacturing performance. This is a novel contribution to BWM decision-making application

A knowledge-based experts’ system for evaluating digital supply chain readiness

The digitalization of the supply chain (SC) enables companies to address customers' new requirements, the challenges of managing the SC and the expectations, and efficiency improvement. Although digital supply chain (DSC) is a buzzword, very few organizations and decision-makers understand the challenges of transforming from a traditional supply chain to a DSC. Therefore, the purpose of this paper is to develop and implement an integrated knowledge-based system (KBS) and evaluate the overall DSC readiness value (score) of an organization. DSC readiness factors are identified from an extensive literature review and validated by experts from academia and industry. The proposed KBS is based on Fuzzy – AHP that establishes a link between DSC readiness factors and their impact on performance and evaluates overall DSC readiness value (score). The proposed KBS has been validated in an Indian manufacturing company, and results show that the overall DSC readiness value (score) of the case company is 0.267. This paper will help organizations evaluate their current position in transforming from traditional supply chain to DSC and make a plan to achieve digitalization completely in their SC operations. Managers, practitioners, and decision-makers who are involved in digitalization can use our study’s findings as a starting point for aiding the transformation