Understanding what drives the purchase decision in pension and investment products

The aims of this paper are to first seek an understanding of consumer decision-making when purchasing pension and investment products, and second to ascertain how this decision-making affects the consumer's choice of distribution route. The study employed both focus groups and postal questionnaire survey methods based on the framework of a classical decision-making model that investigated problem recognition, information search, evaluation tools used and post-purchase. The findings show that the decision-making process experience differed to a lesser or greater degree depending on the distribution route. The majority of respondents had recognised the need to make a purchase decision long before seeking information. Younger respondents on all incomes believed that they must make some pension provision for themselves as opposed to relying on the government's retirement provision. Many changed channels for information searches, but tended to settle with the Independent Financial Adviser (IFA). The two main evaluation tools for pension and investment were found to be the ‘charges’ and ‘historic fund performance’. The vast majority of respondents reiterated their worry that the outcomes would not be known until retirement. In terms of analysis by the level of ‘financial literacy’, respondents who scored in the upper quartile were more inclined to be on a higher income, less inclined to evaluate on charges and more proactive in discussing the investment strategy of their pension fund. Respondents who scored in the lower quartile had opposite results. One of the implications of these findings is that the younger respondents’ recognition of pension savings favours the government's intention to reverse the existing balance of pension distribution. The other main implication is that the findings will be of help to managers in appreciating the dominance of the IFA channel by providing an explanation of why consumers choose this route, and, additionally, can assist direct marketing managers in identifying customers who will be more likely to use multichannel or single-channel shoppers. It can also help the marketing manager increase the usage of different channels by addressing the factors driving the purchase decision and distribution choice.

Identification of meat spoilage by FTIR spectroscopy and neural networks

Freshness and safety of muscle foods are generally considered as the most important parameters for the food industry. To address the rapid determination of meat spoilage, Fourier transform infrared (FTIR) spectroscopy technique, with the help of advanced learning-based methods, was attempted in this work. FTIR spectra were obtained from the surface of beef samples during aerobic storage at various temperatures, while a microbiological analysis had identified the population of Total viable counts. A fuzzy principal component algorithm has been also developed to reduce the dimensionality of the spectral data. The results confirmed the superiority of the adopted scheme compared to the partial least squares technique, currently used in food microbiology.

Managing sales people strategically when promoting new products: Incorporating market orientation into a sales management control framework

Salespeople play a pivotal role in promoting new products. Therefore, managers need to know what control mechanism (i.e., output-based control, behavior-based control, or knowledge-based control) can improve their salespeople's new product sales performance. Furthermore, managers may be able to assist salespeople in performing better by having a strong market orientation. The literature has been inconsistent regarding the effects of sales management control mechanisms and has not yet incorporated market orientation into a sales management control framework. The current study surveyed 315 Taiwanese salespeople from publicly traded electronics companies with the aim of contributing to the sales management literature. The results show that sales management controls can directly affect salespeople's innovativeness, which, in turn, affects new product sales performance. However, sales management controls cannot affect performance directly. Furthermore, market orientation can positively moderate the relationship between salespeople's innovativeness and new product sales performance.

Intake of dairy products in relation to periodontitis in older Danish adults

This cross-sectional study investigates whether calcium intakes from dairy and non-dairy sources, and absolute intakes of various dairy products, are associated with periodontitis. The calcium intake (mg/day) of 135 older Danish adults was estimated by a diet history interview and divided into dairy and non-dairy calcium. Dairy food intake (g/day) was classified into four groups: milk, cheese, fermented foods and other foods. Periodontitis was defined as the number of teeth with attachment loss ≥3 mm. Intakes of total dairy calcium (Incidence-rate ratio (IRR) = 0.97; p = 0.021), calcium from milk (IRR = 0.97; p = 0.025) and fermented foods (IRR = 0.96; p = 0.03) were inversely and significantly associated with periodontitis after adjustment for age, gender, education, sucrose intake, alcohol consumption, smoking, physical activity, vitamin D intake, heart disease, visits to the dentist, use of dental floss and bleeding on probing, but non-dairy calcium, calcium from cheese and other types of dairy food intakes were not. Total dairy foods (IRR = 0.96; p = 0.003), milk (IRR = 0.96; p = 0.028) and fermented foods intakes (IRR = 0.97; p = 0.029) were associated with reduced risk of periodontitis, but cheese and other dairy foods intakes were not. These results suggest that dairy calcium, particularly from milk and fermented products, may protect against periodontitis. Prospective studies are required to confirm these findings.

A Fuzzy-Wavelet Neural Network Model for the Detection of Meat Spoilage using an Electronic Nose

Food product safety is one of the most promising areas for the application of electronic noses. The performance of a portable electronic nose has been evaluated in monitoring the spoilage of beef fillet stored aerobically at different storage temperatures (0, 4, 8, 12, 16 and 20°C). This paper proposes a fuzzy-wavelet neural network model which incorporates a clustering pre-processing stage for the definition of fuzzy rules. The dual purpose of the proposed modeling approach is not only to classify beef samples in the respective quality class (i.e. fresh, semi-fresh and spoiled), but also to predict their associated microbiological population directly from volatile compounds fingerprints. Comparison results indicated that the proposed modeling scheme could be considered as a valuable detection methodology in food microbiology

A Rapid Detection of Meat Spoilage using an Electronic Nose and Fuzzy-Wavelet systems

Freshness and safety of muscle foods are generally considered as the most important parameters for the food industry. To address the rapid detection of meat spoilage microorganisms during aerobic or modified atmosphere storage, an electronic nose with the aid of fuzzy wavelet network has been considered in this research. The proposed model incorporates a clustering pre-processing stage for the definition of fuzzy rules. The dual purpose of the proposed modelling approach is not only to classify beef samples in the respective quality class (i.e. fresh, semi-fresh and spoiled), but also to predict their associated microbiological population directly from volatile compounds fingerprints. Comparison results against neural networks and neurofuzzy systems indicated that the proposed modelling scheme could be considered as a valuable detection methodology in food microbiology

Neuro-Fuzzy based Identification of Meat Spoilage using an Electronic Nose

Freshness and safety of muscle foods are generally considered as the most important parameters for the food industry. The performance of a portable electronic nose has been evaluated in monitoring the spoilage of beef fillet stored aerobically at different storage temperatures (0, 4, 8, 12, 16 and 20°C). An adaptive fuzzy logic system model that utilizes a prototype defuzzification scheme has been developed to classify beef samples in their respective quality class and to predict their associated microbiological population directly from volatile compounds fingerprints. Results confirmed the superiority of the adopted methodology and indicated that volatile information in combination with an efficient choice of a modeling scheme could be considered as an alternative methodology for the accurate evaluation of meat spoilage