Selecting Forecasting Methods

I examined six ways of selecting forecasting methods: Convenience, “what’s easy,” is inexpensive, but risky. Market popularity, “what others do,” sounds appealing but is unlikely to be of value because popularity and success may not be related and because it overlooks some methods. Structured judgment, “what experts advise,” which is to rate methods against prespecified criteria, is promising. Statistical criteria, “what should work,” are widely used and valuable, but risky if applied narrowly. Relative track records, “what has worked in this situation,” are expensive because they depend on conducting evaluation studies. Guidelines from prior research, “what works in this type of situation,” relies on published research and offers a low-cost, effective approach to selection. Using a systematic review of prior research, I developed a flow chart to guide forecasters in selecting among ten forecasting methods. Some key findings: Given enough data, quantitative methods are more accurate than judgmental methods. When large changes are expected, causal methods are more accurate than naive methods. Simple methods are preferable to complex methods; they are easier to understand, less expensive, and seldom less accurate. To select a judgmental method, determine whether there are large changes, frequent forecasts, conflicts among decision makers, and policy considerations. To select a quantitative method, consider the level of knowledge about relationships, the amount of change involved, the type of data, the need for policy analysis, and the extent of domain knowledge. When selection is difficult, combine forecasts from different methods

Supply Chain Intelligence

This chapter provides on overall picture of business intelligence (BI) and supply chain analytics (SCA) as a means to support supply chain management (SCM) and decision-making. Based on the literature review, we clarify the needs of BI and performance measurement in the SCM sphere, and discuss its potential to enhance decision-making in strategic, tactical and operational levels. We also make a closer look in to SCA in different areas and functions of SCM. Our findings indicate that the main challenge for harnessing the full potential of SCA is the lack of holistic and integrated BI approaches that originates from the fact that each functional area is using its own IT applications without necessary integration in to the company’s overall BI system. Following this examination, we construct a holistic framework that illustrates how an integrated, managerially planned BI system can be developed. Finally, we discuss the main competency requirements, as well as the challenges still prohibiting the great majority of firms from building smart and comprehensive BI systems for SCM.fi=vertaisarvioitu|en=peerReviewed

Internationalisation speed and MNE performance: A study of the market-seeking expansion of retail MNEs

Existing research is divided on whether firms that rapidly expand their overseas operations perform better than firms that internationalize slowly. Drawing on Penrose’s theory of the growth of the firm we argue that the positive effects of rapid internationalization give way to negative effects with increasing internationalization speed, leading to an inverted U-shaped association between internationalization speed and firm performance. We analyse the market-seeking expansion of 110 retailers over a 10-year period (2003–2012) and find support for a curvilinear relationship between internationalization speed and firm performance that is moderated by the geographic scope of firms’ internationalization path and firms’ international experience. Our study contributes to resolving conflicting views on the link between internationalization speed and firm performance

A Customer Perspective on Product Eliminations: How the Removal of Products Affects Customers and Business Relationships

Regardless of the apparent need for product eliminations, many managers hesitate to act as they fear deleterious effects on customer satisfaction and loyalty. Other managers do carry out product eliminations, but often fail to consider the consequences for customers and business relationships. Given the relevance and problems of product eliminations, research on this topic in general and on the consequences for customers and business relationships in particular is surprisingly scarce. Therefore, this empirical study explores how and to what extent the elimination of a product negatively affects customers and business relationships. Results indicate that eliminating a product may result in severe economic and psychological costs to customers, thereby seriously decreasing customer satisfaction and loyalty. This paper also shows that these costs are not exogenous in nature. Instead, depending on the characteristics of the eliminated product these costs are found to be more or less strongly driven by a company’s behavior when implementing the elimination at the customer interface

Evaluating Forecasting Methods

Ideally, forecasting methods should be evaluated in the situations for which they will be used. Underlying the evaluation procedure is the need to test methods against reasonable alternatives. Evaluation consists of four steps: testing assumptions, testing data and methods, replicating outputs, and assessing outputs. Most principles for testing forecasting methods are based on commonly accepted methodological procedures, such as to prespecify criteria or to obtain a large sample of forecast errors. However, forecasters often violate such principles, even in academic studies. Some principles might be surprising, such as do not use R-square, do not use Mean Square Error, and do not use the within-sample fit of the model to select the most accurate time-series model. A checklist of 32 principles is provided to help in systematically evaluating forecasting methods

Alternative pathway dysregulation in tissues drives sustained complement activation and predicts outcome across the disease course in COVID-19

Complement, a critical defence against pathogens, has been implicated as a driver of pathology in COVID-19. Complement activation products are detected in plasma and tissues and complement blockade considered for therapy. To delineate roles of complement in immunopathogenesis, we undertook the largest comprehensive study of complement in an COVID-19 to date, a comprehensive profiling of 16 complement biomarkers, including key components, regulators and activation products, in 966 plasma samples from 682 hospitalised COVID-19 patients collected across the hospitalisation period as part of the UK ISARIC4C study. Unsupervised clustering of complement biomarkers mapped to disease severity and supervised machine learning identified marker sets in early samples that predicted peak severity. Compared to heathy controls, complement proteins and activation products (Ba, iC3b, terminal complement complex) were significantly altered in COVID-19 admission samples in all severity groups. Elevated alternative pathway activation markers (Ba and iC3b) and decreased alternative pathway regulator (properdin) in admission samples associated with more severe disease and risk of death. Levels of most complement biomarkers were reduced in severe disease, consistent with consumption and tissue deposition. Latent class mixed modelling and cumulative incidence analysis identified the trajectory of increase of Ba to be a strong predictor of peak COVID-19 disease severity and death. The data demonstrate that early-onset, uncontrolled activation of complement, driven by sustained and progressive amplification through the alternative pathway amplification loop is a ubiquitous feature of COVID-19, further exacerbated in severe disease. These findings provide novel insights into COVID-19 immunopathogenesis and inform strategies for therapeutic intervention

Para-infectious brain injury in COVID-19 persists at follow-up despite attenuated cytokine and autoantibody responses

Data Availability Statement: The individual-level data from these studies is not publicly available to main confidentiality. Data generated by the ISARIC4C consortium is available for collaborative analysis projects through an independent data and materials access committee at isaric4c.net/sample_access. Data and samples from the COVID-Clinical Neuroscience Study are available through collaborative research by application through the NIHR bioresource at https://bioresource.nihr.ac.uk/using-our-bioresource/apply-for-bioresource-data-access/. Brain injury marker and immune mediator data are present in the paper and in the source data file. Source data are provided with this paper.To understand neurological complications of COVID-19 better both acutely and for recovery, we measured markers of brain injury, inflammatory mediators, and autoantibodies in 203 hospitalised participants; 111 with acute sera (1–11 days post-admission) and 92 convalescent sera (56 with COVID-19-associated neurological diagnoses). Here we show that compared to 60 uninfected controls, tTau, GFAP, NfL, and UCH-L1 are increased with COVID-19 infection at acute timepoints and NfL and GFAP are significantly higher in participants with neurological complications. Inflammatory mediators (IL-6, IL-12p40, HGF, M-CSF, CCL2, and IL-1RA) are associated with both altered consciousness and markers of brain injury. Autoantibodies are more common in COVID-19 than controls and some (including against MYL7, UCH-L1, and GRIN3B) are more frequent with altered consciousness. Additionally, convalescent participants with neurological complications show elevated GFAP and NfL, unrelated to attenuated systemic inflammatory mediators and to autoantibody responses. Overall, neurological complications of COVID-19 are associated with evidence of neuroglial injury in both acute and late disease and these correlate with dysregulated innate and adaptive immune responses acutely.National Institute for Health and Care Research (NIHR) (CO-CIN-01) and jointly by NIHR and UK Research and Innovation (CV220-169, MC_PC_19059). B.D.M. is supported by the UKRI/MRC (MR/V03605X/1), the MRC/UKRI (MR/V007181/1), MRC (MR/T028750/1) and Wellcome (ISSF201902/3). C.D. is supported by MRC (MC_PC_19044). We would like to thank the University of Liverpool GCP laboratory facility team for Luminex assistance and the Liverpool University Biobank team for all their help, especially Dr. Victoria Shaw, Lara Lavelle-Langham, and Sue Holden. We would like to acknowledge the Liverpool Experimental Cancer Medicine Centre for providing infrastructure support for this research (Grant Reference: C18616/A25153). We acknowledge the Liverpool Centre for Cell Imaging (CCI) for provision of imaging equipment (Dragonfly confocal microscope) and excellent technical assistance (BBSRC grant number BB/R01390X/1). Tom Solomon is supported by The Pandemic Institute and the NIHR Health Protection Research Unit (HPRU) in Emerging and Zoonotic Infections at University of Liverpool. D.K.M. and E.N. are supported by the NIHR Cambridge Biomedical Centre and by NIHR funding to the NIHR BioResource (RG94028 and RG85445), and by funding from Brain Research UK 201819-20. We thank NIHR BioResource volunteers for their participation, and gratefully acknowledge NIHR BioResource centres, NHS Trusts and staff for their contribution. We thank the National Institute for Health and Care Research, NHS Blood and Transplant, and Health Data Research UK as part of the Digital Innovation Hub Programme. Support for title page creation and format was provided by AuthorArranger, a tool developed at the National Cancer Institute. The authors would like to acknowledge the eDRIS team (Public Health Scotland) for their support in obtaining approvals, the provisioning and linking of data and facilitating access to the National Safe Haven. The views expressed are those of the author(s) and not necessarily those of the UKRI, NHS, the NIHR or the Department of Health and Social Care

Implementation of corticosteroids in treatment of COVID-19 in the ISARIC WHO Clinical Characterisation Protocol UK: prospective, cohort study

Background: Dexamethasone was the first intervention proven to reduce mortality in patients with COVID-19 being treated in hospital. We aimed to evaluate the adoption of corticosteroids in the treatment of COVID-19 in the UK after the RECOVERY trial publication on June 16, 2020, and to identify discrepancies in care. Methods: We did an audit of clinical implementation of corticosteroids in a prospective, observational, cohort study in 237 UK acute care hospitals between March 16, 2020, and April 14, 2021, restricted to patients aged 18 years or older with proven or high likelihood of COVID-19, who received supplementary oxygen. The primary outcome was administration of dexamethasone, prednisolone, hydrocortisone, or methylprednisolone. This study is registered with ISRCTN, ISRCTN66726260. Findings: Between June 17, 2020, and April 14, 2021, 47 795 (75·2%) of 63 525 of patients on supplementary oxygen received corticosteroids, higher among patients requiring critical care than in those who received ward care (11 185 [86·6%] of 12 909 vs 36 415 [72·4%] of 50 278). Patients 50 years or older were significantly less likely to receive corticosteroids than those younger than 50 years (adjusted odds ratio 0·79 [95% CI 0·70–0·89], p=0·0001, for 70–79 years; 0·52 [0·46–0·58], p80 years), independent of patient demographics and illness severity. 84 (54·2%) of 155 pregnant women received corticosteroids. Rates of corticosteroid administration increased from 27·5% in the week before June 16, 2020, to 75–80% in January, 2021. Interpretation: Implementation of corticosteroids into clinical practice in the UK for patients with COVID-19 has been successful, but not universal. Patients older than 70 years, independent of illness severity, chronic neurological disease, and dementia, were less likely to receive corticosteroids than those who were younger, as were pregnant women. This could reflect appropriate clinical decision making, but the possibility of inequitable access to life-saving care should be considered. Funding: UK National Institute for Health Research and UK Medical Research Council