Different rates of defense evolution and niche preferences in clonal and nonclonal milkweeds (Asclepias spp.).

Given the dual role of many plant traits to tolerate both herbivore attack and abiotic stress, the climatic niche of a species should be integrated into the study of plant defense strategies. Here we investigate the impact of plant reproductive strategy and components of species' climatic niche on the rate of chemical defense evolution in the milkweeds using a common garden experiment of 49 species. We found that across Asclepias species, clonal reproduction repeatedly evolved in lower temperature conditions, in species generally producing low concentrations of a toxic defense (cardenolides). Additionally, we found that rates of cardenolide evolution were lower for clonal than for nonclonal species. We thus conclude that because the clonal strategy is based on survival, long generation times, and is associated with tolerance of herbivory, it may be an alternative to toxicity in colder ecosystems. Taken together, these results indicate that the rate of chemical defense evolution is influenced by the intersection of life-history strategy and climatic niches into which plants radiate.

Playing cat and mouse : consumer empowerment and marketing interaction on the net

Peer-reviewed

Social Preferences and Transport Policy: The case of US speed limits

This article, in reviewing the longrunning US debate on speed limits, illustrates how a different valuation of the trade-off between private mobility needs and safety concerns can shape transport policies. It is argued that the regulatory decentralization debate, together with the speed limit in force in each state, obey the social preferences and valuation given to this tradeoff. Such a view is consistent with evidence that higher speed limits are to be found in states with greater private mobility needs, even though their fatality rates might be among the highest in the country. By contrast, lower speed limits and supporters of a low national speed limit are to be found in states that show a greater concern for safety outcomes and which are less dependent on private mobility. By reviewing these events and examining the role played by the main actors and analyzing their motivations, the article identifies important lessons for similar future discussions on transport policy.

Drivers and Barriers of Collaboration in the Value Chain of Paperboard-Packed Consumer Goods

Value chain collaboration has been a prevailing topic for research, and there is a constantly growing interest in developing collaborative models for improved efficiency in logistics. One area of collaboration is demand information management, which enables improved visibility and decrease of inventories in the value chain. Outsourcing of non-core competencies has changed the nature of collaboration from intra-enterprise to cross-enterprise activity, and this together with increasing competition in the globalizing markets have created a need for methods and tools for collaborative work. The retailer part in the value chain of consumer packaged goods (CPG) has been studied relatively widely, proven models have been defined, and there exist several best practice collaboration cases. The information and communications technology has developed rapidly, offering efficient solutions and applications to exchange information between value chain partners. However, the majority of CPG industry still works with traditional business models and practices. This concerns especially companies operating in the upstream of the CPG value chain. Demand information for consumer packaged goods originates at retailers' counters, based on consumers' buying decisions. As this information does not get transferred along the value chain towards the upstream parties, each player needs to optimize their part, causing safety margins for inventories and speculation in purchasing decisions. The safety margins increase with each player, resulting in a phenomenon known as the bullwhip effect. The further the company is from the original demand information source, the more distorted the information is. This thesis concentrates on the upstream parts of the value chain of consumer packaged goods, and more precisely the packaging value chain. Packaging is becoming a part of the product with informative and interactive features, and therefore is not just a cost item needed to protect the product. The upstream part of the CPG value chain is distinctive, as the product changes after each involved party, and therefore the original demand information from the retailers cannot be utilized as such – even if it were transferred seamlessly. The objective of this thesis is to examine the main drivers for collaboration, and barriers causing the moderate adaptation level of collaborative models. Another objective is to define a collaborative demand information management model and test it in a pilot business situation in order to see if the barriers can be eliminated. The empirical part of this thesis contains three parts, all related to the research objective, but involving different target groups, viewpoints and research approaches. The study shows evidence that the main barriers for collaboration are very similar to the barriers in the lower part of the same value chain; lack of trust, lack of business case and lack of senior management commitment. Eliminating one of them – the lack of business case – is not enough to eliminate the two other barriers, as the operational model in this thesis shows. The uncertainty of the future, fear of losing an independent position in purchasing decision making and lack of commitment remain strong enough barriers to prevent the implementation of the proposed collaborative business model. The study proposes a new way of defining the value chain processes: it divides the contracting and planning process into two processes, one managing the commercial parts and the other managing the quantity and specification related issues. This model can reduce the resistance to collaboration, as the commercial part of the contracting process would remain the same as in the traditional model. The quantity/specification-related issues would be managed by the parties with the best capabilities and resources, as well as access to the original demand information. The parties in between would be involved in the planning process as well, as their impact for the next party upstream is significant. The study also highlights the future challenges for companies operating in the CPG value chain. The markets are becoming global, with toughening competition. Also, the technology development will most likely continue with a speed exceeding the adaptation capabilities of the industry. Value chains are also becoming increasingly dynamic, which means shorter and more agile business relationships, and at the same time the predictability of consumer demand is getting more difficult due to shorter product life cycles and trends. These changes will certainly have an effect on companies' operational models, but it is very difficult to estimate when and how the proven methods will gain wide enough adaptation to become standards.

Learning Preferences with Kernel-Based Methods

Learning of preference relations has recently received significant attention in machine learning community. It is closely related to the classification and regression analysis and can be reduced to these tasks. However, preference learning involves prediction of ordering of the data points rather than prediction of a single numerical value as in case of regression or a class label as in case of classification. Therefore, studying preference relations within a separate framework facilitates not only better theoretical understanding of the problem, but also motivates development of the efficient algorithms for the task. Preference learning has many applications in domains such as information retrieval, bioinformatics, natural language processing, etc. For example, algorithms that learn to rank are frequently used in search engines for ordering documents retrieved by the query. Preference learning methods have been also applied to collaborative filtering problems for predicting individual customer choices from the vast amount of user generated feedback. In this thesis we propose several algorithms for learning preference relations. These algorithms stem from well founded and robust class of regularized least-squares methods and have many attractive computational properties. In order to improve the performance of our methods, we introduce several non-linear kernel functions. Thus, contribution of this thesis is twofold: kernel functions for structured data that are used to take advantage of various non-vectorial data representations and the preference learning algorithms that are suitable for different tasks, namely efficient learning of preference relations, learning with large amount of training data, and semi-supervised preference learning. Proposed kernel-based algorithms and kernels are applied to the parse ranking task in natural language processing, document ranking in information retrieval, and remote homology detection in bioinformatics domain. Training of kernel-based ranking algorithms can be infeasible when the size of the training set is large. This problem is addressed by proposing a preference learning algorithm whose computation complexity scales linearly with the number of training data points. We also introduce sparse approximation of the algorithm that can be efficiently trained with large amount of data. For situations when small amount of labeled data but a large amount of unlabeled data is available, we propose a co-regularized preference learning algorithm. To conclude, the methods presented in this thesis address not only the problem of the efficient training of the algorithms but also fast regularization parameter selection, multiple output prediction, and cross-validation. Furthermore, proposed algorithms lead to notably better performance in many preference learning tasks considered.

The use of non-animal alternatives in the safety evaluations of cosmetics ingredients by the Scientific Committee on Consumer Safety (SCCS)

In Europe, the safety evaluation of cosmetics is based on the safety evaluation of each individual ingredient. Article 3 of the Cosmetics Regulation specifies that a cosmetic product made available on the market is to be safe for human health when used normally or under reasonably foreseeable conditions. For substances that cause some concern with respect to human health (e.g. colorants, preservatives, UV-filters), safety is evaluated at the Commission level by a scientific committee, presently called the Scientific Committee on Consumer Safety (SCCS). According to the Cosmetics Regulations, in the EU, the marketing of cosmetics products and their ingredients that have been tested on animals for most of their human health effects, including acute toxicity, is prohibited. Nevertheless, any study dating from before this prohibition took effect is accepted for the safety assessment of cosmetics ingredients. The in vitro methods reported in the dossiers summited to the SCCS are here evaluated from the published reports issued by the scientific committee of the Directorate General of Health and Consumers (DG SANCO); responsible for the safety of cosmetics ingredients. The number of studies submitted to the SCCS that do not involve animals is still low and in general the safety of cosmetics ingredients is based on in vivo studies performed before the prohibition.

Synthesis and NMR characterization of aliphatic-aromatic copolyesters by reaction of poly(ethylene terephthalate) post-consumer and poly(ethylene adipate)

An aliphatic-aromatic copolyester of poly(ethylene terephthalate), PET, and poly(ethylene adipate), PEA, PET-co-PEA, was synthesized by the high temperature melt reaction of post-consumer PET and PEA. As observed by NMR spectroscopy, the reaction yielded random copolyesters in a few minutes through ester-interchange reactions, even without added catalyst. The copolyesters obtained in the presence of a catalyst presented higher intrinsic viscosity than that obtained without the addition of catalyst, due to simultaneous polycondensation and ester-interchange reactions. The structure of the aliphatic-aromatic copolyesters obtained in different PET/PEA ratio is random as observed by NMR analysis.

Informed recommender: basing recommendations on consumer product reviews

Recommender systems attempt to predict items in which a user might be interested, given some information about the user's and items' profiles. Most existing recommender systems use content-based or collaborative filtering methods or hybrid methods that combine both techniques (see the sidebar for more details). We created Informed Recommender to address the problem of using consumer opinion about products, expressed online in free-form text, to generate product recommendations. Informed recommender uses prioritized consumer product reviews to make recommendations. Using text-mining techniques, it maps each piece of each review comment automatically into an ontology

Reliable entertainment: Spanish consumers' preferences regarding a film's country of origin

This article contributes to the study of cinema audiences in Europe by analyzing theactual behavior of Spanish moviegoers and their level of satisfaction. We modeledmoviegoers’ choice of film by country of origin (U.S.A., Spain, and other countries)according to a set of determinants: (1) consumers’ interpretation of several sources of information, (2) motivations and (3) choice rules. We found three clear consumerstereotypes related to each type of film: (1) U.S.A. films were preferred by almost everyone (especially families and younger audiences); (2) Spanish films had audiences composed of middle-age and middle-class moviegoers; and (3) European productions were preferred by a social or intellectual elite. U.S.A. films dominate the Spanish market for the reason that they provide most of what moviegoers prefer, namely, familiar, reliable entertainment in Spanish; three characteristics that are not satisfied by Spanish and European films. Additionally, we discuss the implications for the European cultural policy

Empirical welfare analysis: when preferences matter

Fleurbaey and Maniquet have proposed the criteria of conditional equality and of egalitarian equivalence to assess the equity among individuals in an ordinal setting. Empirical applications are rare and only partially consistent with their framework. We propose a new empirical approach that relies on individual preferences, is consistent with the ordinal criteria and enables to compare them with the cardinal criteria. We estimate a utility function that incorporates individual heterogeneous preferences, obtain ordinal measures of well-being and apply conditional equality and egalitarian equivalence. We then propose two cardinal measures of well-being, that are comparable with the ordinal model, to compute Roemer’s and Van de gaer’s criteria. Finally we compare the characteristics of the worst-off displayed by each criterion. We apply this model to a sample of US micro data and obtain that about 18% of the worst-off are not common to all criteria.

Consumer valuation of energy-saving features of residential air conditioners with hedonic and choice models

The promotion of energy-efficient appliances is necessary to reduce the energetic and environmental burden of the household sector. However, many studies have reported that a typical consumer underestimates the benefits of energy-saving investment on the purchase of household electric appliances. To analyze this energy-efficiency gap problem, many scholars have estimated implicit discount rates that consumers use for energy-consuming durables. Although both hedonic and choice models have been used in previous studies, a comparison between two models has not yet been done. This study uses point of sale data about Japanese residential air conditioners and estimates implicit discounts rates with both hedonic and choice models. Both models demonstrate that a typical consumer underinvests in energy efficiency. Although choice models estimate a lower implicit discount rate than hedonic models, the latter models estimate the values of other product characteristics more consistently than choice models.

Sensory and Non-sensory Factors Behind the Liking and Choice of Healthy Food Products

A healthy and balanced diet can reduce health problems, such as overweight and metabolic syndrome. In general, people have a considerably good knowledge of what constitutes a healthy diet and how they could achieve it with their food choices. Besides, people argue that health is among their top five food choice motives. Nevertheless, the prevalence of overweight is increasing and other food choice motives, such as taste, seem to conflict with the health. Liking for food does not necessarily determine acceptance alone, thus several non-sensory factors, such as brand, country of origin and nutrition claim, can also influence. Moreover, consumers are individuals in how they prioritize sensory and nonsensory factors of foods, but e.g. increasing age, female gender and health concern have been connected to a more health-oriented dietary behaviour. To sum up, identifying different factors that can increase the liking and consumption of healthy food is essential in order to develop more attractive healthful food products. Adding vitamins, minerals, fibre or other ingredients to a food product can be used to enrich the nutritional quality of the products. However, this may be difficult in practice as regards the sensory quality and pleasantness of the foods. Generally, consumers are not willing to compromise on taste in food. On the other hand, consumers are very heterogeneous in their likings, and their personal values and attitudes may interact with preferences for specific sensory characteristics. The aims of this study were to investigate the effects of intrinsic product characteristics on sensory properties and hedonic responses; to determine the impact of few non-sensory factors; and to examine the interaction between sensory and non-sensory factors with consumers’ demographics, values and attitudes in liking of healthy model foods. The results showed that product composition influenced sensory quality and had an effect on hedonic responses. Adding flaxseed to bakery products showed a significant improvement in the nutritional quality without negative effects on sensory properties. On the other hand, the fortification of wellness beverages with vitamins and minerals may impart off-flavours. In general, sweetness of yoghurts, freshness of wellness beverages and low intensity of rye bread flavour appealed to consumers. Information about the domestic origin of yoghurts and claiming a specific function for wellness beverages enhanced liking. However, consumers who were more concerned about their health and considered natural content as an important food choice motive, rated sourer and less sweet yoghurts and wellness beverages as more pleasant. In addition, interest in health increased the consumption of rye breads and other whole grain breads among adolescents. The results showed that the optimal product quality in terms of intrinsic and extrinsic factors differs between individual consumers, and personal values and food choice motives can be connected to preferences for specific sensory characteristics of foods. This indicates that each food product needs to be considered in relation to its specific market niche, and to which segment of consumer will respond most positively to its characteristics.