Purpose – The aim is to understand customers' willingness, or unwillingness, to pay a price premium in the market for consumer packaged food and what kind of images brands can use in order to achieve a price premium. Design/methodology/approach – The study is based on a quantitative survey of brand images found in food and branding literature and their impact on loyalty as well as customers' willingness to pay a price premium for consumer packaged food. Findings – The survey shows that quality is a significant determinant of price premium, but adding other image dimensions doubles the predictability and understanding about price premium. The strongest determinants of price premium are social image, uniqueness and home country origin. Other significant determinants are corporate social responsibility (CSR) and awareness. Practical implications – The results help brand managers to recognise the importance of incorporating price premium and to develop a better understanding of what drives price premium in addition to more traditional dimensions as quality and loyalty. Originality/value – In grocery retailing, the competition for customers, margins and price premiums between manufacturer and private labels is fierce. Traditionally, the literature on this competition has focused on quality and product improvements as the main tool for creating distance to low priced competition. This study looks into other more branding related dimensions to distance from price competition.

No abstract

Summary• Here, species composition and biomass production of actively growing ectomycorrhizal (EM) mycelia were studied over the rotation period of managed Norway spruce (Picea abies) stands in south-western Sweden.• The EM mycelia were collected using ingrowth mesh bags incubated in the forest soil during one growing season. Fungal biomass was estimated by ergosterol analysis and the EM species were identified by 454 sequencing of internal transcribed spacer (ITS) amplicons. Nutrient availability and the fungal biomass in soil samples were also estimated.• Biomass production peaked in young stands (10-30 yr old) before the first thinning phase. Tylospora fibrillosa dominated the EM community, especially in these young stands, where it constituted 80% of the EM amplicons derived from the mesh bags. Species richness increased in older stands.• The establishment of EM mycelial networks in young Norway spruce stands requires large amounts of carbon, while much less is needed to sustain the EM community in older stands. The variation in EM biomass production over the rotation period has implications for carbon sequestration rates in forest soils.

Purpose -This paper seeks to develop a framework for understanding what drives customer-based brand equity and price premium for grocery products. Design/methodology/approach -The paper reviews empirical studies made within the area of brand equity and studies of grocery products. It compares and analyses the results from an explorative and qualitative field study with previous research on brand equity and food quality. Findings -The study finds that brand equity and price premium focusing on the grocery sector specifically highlights the role of uniqueness, together with the four traditionally basic dimensions of brand equity proposed: awareness, qualities, associations and loyalty. Relevant brand associations (origin, health, environment/animal friendliness, organisational associations and social image), and quality attributes (taste, odour, consistency/texture, appearance, function, packaging and ingredients) specific to groceries are identified and proposed for future measurement scales and model validating research. Practical implications -The development of a customer-based brand equity model, that adds awareness, associations and loyalty to previous discussions on price and quality, brings to the table a more nuanced and multi-faced tool for marketing of consumer packaged food. Originality/value -The paper provides a framework for understanding, evaluating, measuring and managing brand equity for grocery products. As this paper presents the first conceptual brand equity framework for groceries, there is a contribution to research on food branding. Also, there is a contribution to the general field of brand equity as previous models have been very general.

The purpose of this research was to investigate e‐business and e‐supply strategies in Scottish small‐ and medium‐sized enterprises (SMEs). The paper reviews academic literature and recent survey reports on the degree of e‐business adoption in the UK and Republic of Ireland. The qualitative methodology undertaken is described, findings are discussed and implications from this study for e‐business strategies outlined. This was an exploratory study using a small sample with possible geographic biases. Nevertheless, the data so far are in line with findings from larger studies. The role of support agencies is examined, as well as how government could better serve the SMEs. Finally conclusions and future research plans are presented.

Globalisation and technology effects appear to have spurred smaller firms around the world to embrace e-business practices. However, there is considerable variability in adoption and usage from country to country. Drawing on existing research on e-business and conventional business and marketing in the smaller firm, this paper formulates a conceptual framework of reasons behind adoption and non-adoption in the smaller firm. Macro dimensions, industry sector and firm-level factors are analysed, together with owner/manager motivations and attitudes towards e-business adoption. A conceptual framework is constructed and research propositions are then developed in order to focus attention on sets of internal and external factors which impact on smaller firm e-business usage. Recommendations for future theory development are presented, together with implications for industry bodies involved in supporting the SME sector.

No abstract

Regression conformal prediction produces prediction intervals that are valid, i.e., the probability of excluding the correct target value is bounded by a predefined confidence level. The most important criterion when comparing conformal regressors is efficiency; the prediction intervals should be as tight (informative) as possible. In this study, the use of random forests as the underlying model for regression conformal prediction is investigated and compared to existing state-of-the-art techniques, which are based on neural networks and k-nearest neighbors. In addition to their robust predictive performance, random forests allow for determining the size of the prediction intervals by using out-of-bag estimates instead of requiring a separate calibration set. An extensive empirical investigation, using 33 publicly available data sets, was undertaken to compare the use of random forests to existing stateof-the-art conformal predictors. The results show that the suggested approach, on almost all confidence levels and using both standard and normalized nonconformity functions, produced significantly more efficient conformal predictors than the existing alternatives.