The STRATADAPT scale: a measure of marketing strategy adaptation to international business markets

Purpose – The development of marketing strategies optimally adjusted to export markets has been a vitally important topic for both managers and academics for about five decades. However, there is no agreement in the literature about which elements integrate marketing strategy and which components of domestic strategies should be adapted to export markets. The purpose of this paper is to develop a new scale – STRATADAPT. Design/methodology/approach – Results from a sample of small and medium-sized industrial exporting firms support a four-dimensional scale – product, promotion, price, and distribution strategies – of 30 items. The scale presents evidence of composite reliability as well as discriminant and nomological validity. Findings – Findings reveal that all four dimensions of marketing strategy adaptation are positively associated with the amount of the firm's financial resources allocated to export activity. Practical implications – The STRATADAPT scale may assist managers in developing better international marketing strategies as well as in planning more accurate and efficient marketing programs across markets. Originality/value – This study develops a new scale, the STRATADAPT scale, which is a broad measure of export marketing strategy adaptation.

Hypersensitivity and growth adaptation of oestrogen-deprived MCF-7 human breast cancer cells

Background: Efficacy of endocrine therapy is compromised when human breast cancer cells circumvent imposed growth inhibition. The model of long-term oestrogen-deprived MCF-7 human breast cancer cells has suggested the mechanism results from hypersensitivity to low levels of residual oestrogen. Materials and methods: MCF-7 cells were maintained for up to 30 weeks in phenol-red-free medium and charcoal-stripped serum with 10-8 M 17-oestradiol and 10 g/ml insulin (stock 1), 10-8 M 17-oestradiol (stock 2), 10 g/ml insulin (stock 3) or no addition (stock 4). Results: Loss of growth response to oestrogen was observed only in stock 4 cells. Long-term maintenance with insulin in the absence of oestradiol (stock 3) resulted in raised oestrogen receptor alpha (ERlevels (measured by western immunoblotting) and development of hypersensitivity (assayed by oestrogen-responsive reporter gene induction and dose response to oestradiol for proliferation under serum-free conditions), but with no loss of growth response to oestrogen. Conclusion: Hypersensitivity can develop without any growth adaptation and therefore is not a prerequisite for loss of growth response in MCF-7 cells.

Strong armies, slow adaptation: civil-military relations and diffusion of military power

Why are some states more willing to adopt military innovations than others? Why, for example, were the great powers of Europe able to successfully reform their military practices to better adapt to and participate in the so-called military revolution of the sixteenth and seventeenth centuries while their most important extra-European competitor, the Ottoman Empire, failed to do so? This puzzle is best explained by two factors: civil-military relations and historical timing. In the Ottoman Empire, the emergence of an institutionally strong and internally cohesive army during the early stages of state formation—in the late fourteenth century—equipped the military with substantial bargaining powers. In contrast, the great powers of Europe drew heavily on private providers of military power during the military revolution and developed similar armies only by the second half of the seventeenth century, limiting the bargaining leverage of European militaries over their rulers. In essence, the Ottoman standing army was able to block reform efforts that it believed challenged its parochial interests. Absent a similar institutional challenge, European rulers initiated military reforms and motivated officers and military entrepreneurs to participate in the ongoing military revolution.

Metaproteomics analysis reveals the adaptation process for the chicken gut microbiota

The animal gastrointestinal tract houses a large microbial community, the gut microbiota, that confers many benefits to its host, such as protection from pathogens and provision of essential metabolites. Metagenomic approaches have defined the chicken fecal microbiota in other studies, but here, we wished to assess the correlation between the metagenome and the bacterial proteome in order to better understand the healthy chicken gut microbiota. Here, we performed high-throughput sequencing of 16S rRNA gene amplicons and metaproteomics analysis of fecal samples to determine microbial gut composition and protein expression. 16 rRNA gene sequencing analysis identified Clostridiales, Bacteroidaceae, and Lactobacillaceae species as the most abundant species in the gut. For metaproteomics analysis, peptides were generated by using the Fasp method and subsequently fractionated by strong anion exchanges. Metaproteomics analysis identified 3,673 proteins. Among the most frequently identified proteins, 380 proteins belonged to Lactobacillus spp., 155 belonged to Clostridium spp., and 66 belonged to Streptococcus spp. The most frequently identified proteins were heat shock chaperones, including 349 GroEL proteins, from many bacterial species, whereas the most abundant enzymes were pyruvate kinases, as judged by the number of peptides identified per protein (spectral counting). Gene ontology and KEGG pathway analyses revealed the functions and locations of the identified proteins. The findings of both metaproteomics and 16S rRNA sequencing analyses are discussed.

Enabling sharing and reuse of scientific data

The purpose of this study was to develop an understanding of the current state of scientific data sharing that stakeholders could use to develop and implement effective data sharing strategies and policies. The study developed a conceptual model to describe the process of data sharing, and the drivers, barriers, and enablers that determine stakeholder engagement. The conceptual model was used as a framework to structure discussions and interviews with key members of all stakeholder groups. Analysis of data obtained from interviewees identified a number of themes that highlight key requirements for the development of a mature data sharing culture.

Workaround motivation model (WAMM): an adaptation of the Theory of Interpersonal Behaviour

The study of workarounds (WA) has increased in importance due to their impact on patient safety and efficiency. However, there are no adequate theories to explain the motivation to create and use a workaround in a healthcare sitting. Although theories of technology acceptance help to understand the reasons to accept or reject technology, they fail to explain drivers for alternatives. Also workarounds involve creators and performers that have different motivations. Models such as Theory of Planned Behaviour (TPB) or Theory of Reasoned Action (TRA) can help to explain the role of workaround users, but lack explanation of workaround creators’ dynamics. Our aim is to develop a theoretical foundation to explain workaround motivation behaviour models with norms that relate to sanctions to provide an integrated Workaround Motivation Model; WAMM. The development of WAMM model is explained in this paper based on workaround cases as part of further research to establish the model.

Towards cost-sensitive adaptation: when is it worth updating your predictive model?

Our digital universe is rapidly expanding,more and more daily activities are digitally recorded, data arrives in streams, it needs to be analyzed in real time and may evolve over time. In the last decade many adaptive learning algorithms and prediction systems, which can automatically update themselves with the new incoming data, have been developed. The majority of those algorithms focus on improving the predictive performance and assume that model update is always desired as soon as possible and as frequently as possible. In this study we consider potential model update as an investment decision, which, as in the financial markets, should be taken only if a certain return on investment is expected. We introduce and motivate a new research problem for data streams ? cost-sensitive adaptation. We propose a reference framework for analyzing adaptation strategies in terms of costs and benefits. Our framework allows to characterize and decompose the costs of model updates, and to asses and interpret the gains in performance due to model adaptation for a given learning algorithm on a given prediction task. Our proof-of-concept experiment demonstrates how the framework can aid in analyzing and managing adaptation decisions in the chemical industry.

High-level face adaptation without awareness

When a visual stimulus is suppressed from awareness, processing of the suppressed image is necessarily reduced. Although adaptation to simple image properties such as orientation still occurs, adaptation to high-level properties such as face identity is eliminated. Here we show that emotional facial expression continues to be processed even under complete suppression, as indexed by substantial facial expression aftereffects.

Researching farmer behaviour in climate change adaptation and sustainable agriculture: lessons learned from five case studies

Understanding farmer behaviour is needed for local agricultural systems to produce food sustainably while facing multiple pressures. We synthesize existing literature to identify three fundamental questions that correspond to three distinct areas of knowledge necessary to understand farmer behaviour: 1) decision-making model; 2) cross-scale and cross-level pressures; and 3) temporal dynamics. We use this framework to compare five interdisciplinary case studies of agricultural systems in distinct geographical contexts across the globe. We find that these three areas of knowledge are important to understanding farmer behaviour, and can be used to guide the interdisciplinary design and interpretation of studies in the future. Most importantly, we find that these three areas need to be addressed simultaneously in order to understand farmer behaviour. We also identify three methodological challenges hindering this understanding: the suitability of theoretical frameworks, the trade-offs among methods and the limited timeframe of typical research projects. We propose that a triangulation research strategy that makes use of mixed methods, or collaborations between researchers across mixed disciplines, can be used to successfully address all three areas simultaneously and show how this has been achieved in the case studies. The framework facilitates interdisciplinary research on farmer behaviour by opening up spaces of structured dialogue on assumptions, research questions and methods employed in investigation.