Sustainability starts from within: A critical analysis of internal marketing in supporting sustainable value co-creation in B2B organisations

Data availability: The data used is confidential.Copyright © 2023 The Authors. The role of value co-creation in embedding sustainability within B2B marketing is well-documented. However, little is known about how employees enact this value co-creation, or how they can be supported to do so by their organisations. This article addresses this theoretical gap by analysing the role of employees and Internal Marketing in B2B organisations' efforts to co-create sustainable value. We propose that, since employees are tasked with delivering their organisation's ‘promise’, they can also purposely generate value for a broader range of stakeholders. As such, Internal Marketing can be a key enabler (or inhibitor) in these efforts. Adopting a Service-Dominant Logic and Service Gap lens, the research utilises Template Analysis of 17 semi-structured interviews with employees from a range of B2B organisations, which have adopted ‘sustainability-oriented’ practices. The findings highlight the contribution of Internal Marketing in supporting sustainable value, and demonstrate that, whilst employees can play a key role in the co-creation of sustainable value, value co-destruction can occur due to a ‘Sustainability gap’ within their organisations. This study contributes significantly to extant knowledge by offering a taxonomized analysis of the ‘sustainability gap’ and identifying how B2B organisations can address these at the awareness, design, internal communication, and implementation stages

Stratification of asthma phenotypes by airway proteomic signatures

© 2019 Background: Stratification by eosinophil and neutrophil counts increases our understanding of asthma and helps target therapy, but there is room for improvement in our accuracy in prediction of treatment responses and a need for better understanding of the underlying mechanisms. Objective: We sought to identify molecular subphenotypes of asthma defined by proteomic signatures for improved stratification. Methods: Unbiased label-free quantitative mass spectrometry and topological data analysis were used to analyze the proteomes of sputum supernatants from 246 participants (206 asthmatic patients) as a novel means of asthma stratification. Microarray analysis of sputum cells provided transcriptomics data additionally to inform on underlying mechanisms. Results: Analysis of the sputum proteome resulted in 10 clusters (ie, proteotypes) based on similarity in proteomic features, representing discrete molecular subphenotypes of asthma. Overlaying granulocyte counts onto the 10 clusters as metadata further defined 3 of these as highly eosinophilic, 3 as highly neutrophilic, and 2 as highly atopic with relatively low granulocytic inflammation. For each of these 3 phenotypes, logistic regression analysis identified candidate protein biomarkers, and matched transcriptomic data pointed to differentially activated underlying mechanisms. Conclusion: This study provides further stratification of asthma currently classified based on quantification of granulocytic inflammation and provided additional insight into their underlying mechanisms, which could become targets for novel therapies

Basic science232. Certolizumab pegol prevents pro-inflammatory alterations in endothelial cell function

Background: Cardiovascular disease is a major comorbidity of rheumatoid arthritis (RA) and a leading cause of death. Chronic systemic inflammation involving tumour necrosis factor alpha (TNF) could contribute to endothelial activation and atherogenesis. A number of anti-TNF therapies are in current use for the treatment of RA, including certolizumab pegol (CZP), (Cimzia ®; UCB, Belgium). Anti-TNF therapy has been associated with reduced clinical cardiovascular disease risk and ameliorated vascular function in RA patients. However, the specific effects of TNF inhibitors on endothelial cell function are largely unknown. Our aim was to investigate the mechanisms underpinning CZP effects on TNF-activated human endothelial cells. Methods: Human aortic endothelial cells (HAoECs) were cultured in vitro and exposed to a) TNF alone, b) TNF plus CZP, or c) neither agent. Microarray analysis was used to examine the transcriptional profile of cells treated for 6 hrs and quantitative polymerase chain reaction (qPCR) analysed gene expression at 1, 3, 6 and 24 hrs. NF-κB localization and IκB degradation were investigated using immunocytochemistry, high content analysis and western blotting. Flow cytometry was conducted to detect microparticle release from HAoECs. Results: Transcriptional profiling revealed that while TNF alone had strong effects on endothelial gene expression, TNF and CZP in combination produced a global gene expression pattern similar to untreated control. The two most highly up-regulated genes in response to TNF treatment were adhesion molecules E-selectin and VCAM-1 (q 0.2 compared to control; p > 0.05 compared to TNF alone). The NF-κB pathway was confirmed as a downstream target of TNF-induced HAoEC activation, via nuclear translocation of NF-κB and degradation of IκB, effects which were abolished by treatment with CZP. In addition, flow cytometry detected an increased production of endothelial microparticles in TNF-activated HAoECs, which was prevented by treatment with CZP. Conclusions: We have found at a cellular level that a clinically available TNF inhibitor, CZP reduces the expression of adhesion molecule expression, and prevents TNF-induced activation of the NF-κB pathway. Furthermore, CZP prevents the production of microparticles by activated endothelial cells. This could be central to the prevention of inflammatory environments underlying these conditions and measurement of microparticles has potential as a novel prognostic marker for future cardiovascular events in this patient group. Disclosure statement: Y.A. received a research grant from UCB. I.B. received a research grant from UCB. S.H. received a research grant from UCB. All other authors have declared no conflicts of interes

FDI in hot labour markets: The implications of the war for talent

This paper highlights an inherent contradiction that exists within investment promotion activities in rich countries. Since the financial crisis, many inward investment agencies have shifted their activities from job creation per se to seeking to attract investment in high-tech activities. Such knowledge-intensive sectors are engaged in what has become referred to as “the war for talent”, so locations need to understand their value proposition to firms, especially where labour is tight. This paper explores the implications of this, in terms of the impact on employment and earnings of high skilled labour. We show that, because skill shortages already exist in many of these sectors, seeking to attract inward investment in these sectors simply causes the earnings of such workers to be bid up, and employment in the incumbent sector to fall. We highlight the over-riding importance that firms place on the availability of skilled labour when determining locations, and how policies which promote labour market flexibility, particularly through investment in skills to address skill shortages, can significantly mitigate the adverse effects, which tend to be more keenly felt in poorer regions of Europe where skilled labour is in even shorter supply

A computational framework for complex disease stratification from multiple large-scale datasets.

BACKGROUND: Multilevel data integration is becoming a major area of research in systems biology. Within this area, multi-'omics datasets on complex diseases are becoming more readily available and there is a need to set standards and good practices for integrated analysis of biological, clinical and environmental data. We present a framework to plan and generate single and multi-'omics signatures of disease states. METHODS: The framework is divided into four major steps: dataset subsetting, feature filtering, 'omics-based clustering and biomarker identification. RESULTS: We illustrate the usefulness of this framework by identifying potential patient clusters based on integrated multi-'omics signatures in a publicly available ovarian cystadenocarcinoma dataset. The analysis generated a higher number of stable and clinically relevant clusters than previously reported, and enabled the generation of predictive models of patient outcomes. CONCLUSIONS: This framework will help health researchers plan and perform multi-'omics big data analyses to generate hypotheses and make sense of their rich, diverse and ever growing datasets, to enable implementation of translational P4 medicine