Market-oriented new product development of functional beverages

Strategic reviews of the Irish Food and Beverage Industry have consistently emphasised the need for food and beverage firms to improve their innovation and marketing capabilities, in order to maintain competitiveness in both domestic and overseas markets. In particular, the functional food and beverages market has been singled out as an extremely important emerging market, which Irish firms could benefit from through an increased technological and market orientation. Although health and wellness have been the most significant drivers of new product development (NPD) in recent years, failure rates for new functional foods and beverages have been reportedly high. In that context, researchers in the US, UK, Denmark and Ireland have reported a marked divergence between NPD practices within food and beverage firms and normative advice for successful product development. The high reported failure rates for new functional foods and beverages suggest a failure to manage customer knowledge effectively, as well as a lack of knowledge management between functional disciplines involved in the NPD process. This research explored the concept of managing customer knowledge at the early stages of the NPD process, and applied it to the development of a range of functional beverages, through the use of advanced concept optimisation research techniques, which provided for a more market-oriented approach to new food product development. A sequential exploratory research design strategy using mixed research methods was chosen for this study. First, the qualitative element of this research investigated customers’ choice motives for orange juice and soft drinks, and explored their attitudes and perceptions towards a range of new functional beverage concepts through a combination of 15 in-depth interviews and 3 focus groups. Second, the quantitative element of this research consisted of 3 conjoint-based questionnaires administered to 400 different customers in each study in order to model their purchase preferences for chilled nutrient-enriched and probiotic orange juices, and stimulant soft drinks. The in-depth interviews identified the key product design attributes that influenced customers’ choice motives for orange juice. The focus group discussions revealed that groups of customers were negative towards the addition of certain functional ingredients to natural foods and beverages. K-means cluster analysis was used to quantitatively identify segments of customers with similar preferences for chilled nutrient-enriched and probiotic orange juices, and stimulant soft drinks. Overall, advanced concept optimisation research methods facilitate the integration of the customer at the early stages of the NPD process, which promotes a multi-disciplinary approach to new food product design. This research illustrated how advanced concept optimisation research methods could contribute towards effective and efficient knowledge management in the new food product development process.

An empirical examination of risk equalisation in a regulated community rated health insurance market

Despite universal access entitlements to the public healthcare system in Ireland, over half the population is covered by voluntary private health insurance. The market operates on the basis of community rating, open enrolment and lifetime cover. A set of minimum benefits also exists, and two risk equalisation schemes have been put in place but neither was implemented. These schemes have proved highly controversial. To date, the debate has primarily consisted of qualitative arguments. This study adds a quantitative element by analysing a number of pertinent issues. A model of a community rated insurance market is developed, which shows that community rating can only be maintained in a competitive market if all insurers in the market have the same risk profile as the market overall. This has relevance to the Irish market in the aftermath of a Supreme Court decision to set aside risk equalisation. Two reasons why insurers’ risk profiles might differ are adverse selection and risk selection. Evidence is found of the existence of both forms of selection in the Irish market. A move from single rate community rating to lifetime community rating in Australia had significant consequences for take-up rates and the age profile of the insured population. A similar move has been proposed in Ireland. It is found that, although this might improve the stability of community rating in the short term, it would not negate the need for risk equalisation. If community rating were to collapse then risk rating might result. A comparison of the Irish, Australian and UK health insurance markets suggests that community rating encourages higher take-up among older consumers than risk rating. Analysis of Irish hospital discharge figures suggests that this yields significant savings for the Irish public healthcare system. This thesis has implications for government policy towards private health insurance in Ireland.

Quantifying the value of improved wind energy forecasts in a pool-based electricity market

This work illustrates the influence of wind forecast errors on system costs, wind curtailment and generator dispatch in a system with high wind penetration. Realistic wind forecasts of different specified accuracy levels are created using an auto-regressive moving average model and these are then used in the creation of day-ahead unit commitment schedules. The schedules are generated for a model of the 2020 Irish electricity system with 33% wind penetration using both stochastic and deterministic approaches. Improvements in wind forecast accuracy are demonstrated to deliver: (i) clear savings in total system costs for deterministic and, to a lesser extent, stochastic scheduling; (ii) a decrease in the level of wind curtailment, with close agreement between stochastic and deterministic scheduling; and (iii) a decrease in the dispatch of open cycle gas turbine generation, evident with deterministic, and to a lesser extent, with stochastic scheduling.