Consumers' perceptions of speciality foods and therural mail-order business

Many rural-based farm and food businesses are relatively small but successful companies. They face severe constraints in terms of finance, marketing and distribution. However, marketing food by mail order presents the opportunity for these firms to gain access to national or even international markets. The achievement of commercial success requires that these companies become marketing oriented. Thus, the critical issue for these firms is to identify the needs of existing or potential customers. The objectives of the paper are to establish a profile of the characteristics, behaviour and attitudes of mail order customers.

A review of dynamic Bayesian network techniques with applications in healthcare risk modelling

Coping with an ageing population is a major concern for healthcare organisations around the world. The average cost of hospital care is higher than social care for older and terminally ill patients. Moreover, the average cost of social care increases with the age of the patient. Therefore, it is important to make efficient and fair capacity planning which also incorporates patient centred outcomes. Predictive models can provide predictions which their accuracy can be understood and quantified. Predictive modelling can help patients and carers to get the appropriate support services, and allow clinical decision-makers to improve care quality and reduce the cost of inappropriate hospital and Accident and Emergency admissions. The aim of this study is to provide a review of modelling techniques and frameworks for predictive risk modelling of patients in hospital, based on routinely collected data such as the Hospital Episode Statistics database. A number of sub-problems can be considered such as Length-of-Stay and End-of-Life predictive modelling. The methodologies in the literature are mainly focused on addressing the problems using regression methods and Markov models, and the majority lack generalisability. In some cases, the robustness, accuracy and re-usability of predictive risk models have been shown to be improved using Machine Learning methods. Dynamic Bayesian Network techniques can represent complex correlations models and include small probabilities into the solution. The main focus of this study is to provide a review of major time-varying Dynamic Bayesian Network techniques with applications in healthcare predictive risk modelling.

Consumers' willingness to pay for ethical attributes

Purpose: In recent years, there has been a big increase in the use of ethical attributes as marketing appeals. This paper examines consumers’ willingness to pay for three selected ethical attributes, namely ‘Organic’, ‘Recyclable Packaging’ and ‘Fairtrade’ in monetary terms. Design/Methodology/Approach: A modified choice-based experimental design with manipulation of the key constructs was used to estimate the mean value of how much consumers are willing to pay for the selected attributes attached to a box of premium chocolates. The results are based on the responses of a total of 208 consumers. Findings: Of the three attributes, ‘Recyclable Packaging’ has the strongest influence on the purchase decision, although this attribute generates the least additional value. The aggregated result shows that although consumers are willing to pay more for the product with ethical attributes than the one that is without, still around a half of them are not willing to pay more. In terms of demographics, the results show no significant differences between the two genders or different age groups in their willingness to pay for ethical attributes. As might be expected, willingness to pay was correlated with the level of consciousness of the ethical attributes. Originality/Value: The findings of this study help management to think practically about the value consumers willing to pay for the selected attributes. The results show a significant synergy in a combination of ethical attributes in products.

Rethinking gossip and scandal in healthcare organizations

Purpose – The purpose of this viewpoint paper is to argue that gossip is a neglected aspect of organizational communication and knowledge, and an under-used management resource. Design/methodology/approach – The paper challenges mainstream managerial assumptions that gossip is trivial or tainted talk which should be discouraged in the workplace. Instead, gossip is re-framed at an organizational level of analysis, which provides the opportunity for relational knowledge about systemic failure and poor practice in healthcare to surface. Findings – Rather than simply viewing gossip as an individual behaviour and interpersonal process, it is claimed that organizational gossip is also a valuable early warning indicator of risk and failure in healthcare systems. There is potentially significant value in re-framing gossip as an aspect of organizational communication and knowledge. If attended to (rather than neglected or silenced) gossip can provide fresh insights into professional practice, decision-making and relational leadership. Originality/value – This paper offers a provocative challenge to mainstream health organization and management thinking about gossip in the workplace. It offers new ways of thinking to promote patient safety, and prevent the scandals that have plagued healthcare organizations in recent years.