Self-construals, Symbolic and Hedonic Preferences, and Actual Purchase Behavior

The study explores the influence of the independent and interdependent self-construals on actual purchase behavior and the mediating role of consumer preferences for symbolic and hedonic meanings. Data were collected through a survey of about 1,000 respondents. Results indicate that independent consumers draw on the self/hedonic- and status-symbolic resources of clothing in the construction and expression of their identities. Regarding the interdependent consumers, they show no interest in clothing affiliation and status symbolism. The degree of preference for status-symbolic meaning mediates all effects of the independent and interdependent self-construals on actual purchase behavior; self-expressive/hedonic preferences mediate two of the three effects of the independent self on actual purchase behavior when accounting for suppression effects, whereas the expected mediation of preference for affiliation meaning is not supported.

Physiological and behavioral patterns of corruption

We study the behavior and emotional arousal of the participants in an experimental auction, leading to an asymmetric social dilemma involving an auctioneer and two bidders. An antisocial transfer (bribe) which is beneficial for the auctioneer (official) is paid, if promised, by the winner of the auction. Some pro-social behavior on both the auctioneers' and the bidders' sides is observed even in the absence of any punishment mechanism (Baseline, Treatment 0). However, pro-social behavior is adopted by the vast majority of subjects when the loser of the auction can inspect the transaction between the winner and the auctioneer (Inspection, Treatment 1). The inspection and punishment mechanism is such that, if a bribe is (not) revealed, both corrupt agents (the denouncing bidder) lose(s) this period's payoffs. This renders the inspection option unprofitable for the loser and is rarely used, especially towards the end of the session, when pro-social behavior becomes pervasive. Subjects' emotional arousal was obtained through skin conductance responses. Generally speaking, our findings suggest that stronger emotions are associated with decisions deviating from pure monetary reward maximization, rather than with (un)ethical behavior per se. In fact, using response times as a measure of the subject's reflection during the decision-making process, we can associate emotional arousal with the conflict between primary or instinctive and secondary or contemplative motivations and, more specifically, with deviations from the subject's pure monetary interest.

Exploring farmer preferences for contagious bovine pleuropneumonia vaccination: a case study of Narok District, Kenya

Contagious bovine pleuropneumonia (CBPP) is an economically important disease in most of sub-Saharan Africa. A conjoint analysis and ordered probit regression models were used to measure the preferences of farmers for CBPP vaccine and vaccination attributes. This was with regard to inclusion or not of an indicator in the vaccine, vaccine safety, vaccine stability as well as frequency of vaccination, vaccine administration and the nature of vaccination. The analysis was carried out in 190 households in Narok District of Kenya between October and December 2006 using structured questionnaires, 16 attribute profiles and a five-point Likert scale. The factors affecting attribute valuation were shown through a two-way location interaction model. The study also demonstrated the relative importance (RI) of attributes and the compensation value of attribute levels. The attribute coefficient estimates showed that farmers prefer a vaccine that has an indicator, is 100% safe and is administered by the government (p<0.0001). The preferences for the vaccine attributes were consistent with expectations. Preferences for stability, frequency of vaccination and nature of vaccination differed amongst farmers (p>0.05). While inclusion of an indicator in the vaccine was the most important attribute (RI=43.6%), price was the least important (RI=0.5%). Of the 22 household factors considered, 15 affected attribute valuation. The compensation values for a change from non inclusion to inclusion of an indicator, 95-100% safety, 2h to greater than 2h stability and from compulsory to elective vaccination were positive while those for a change from annual to biannual vaccination and from government to private administration were negative. The study concluded that the farmers in Narok District had preferences for specific vaccine and vaccination attributes. These preferences were conditioned by various household characteristics and disease risk factors. On average the farmers would need to be compensated or persuaded to accept biannual and private vaccination against CBPP. There is need for consideration of farmer preferences for vaccine attribute levels during vaccine formulations and farmer preferences for vaccination attribute levels when designing delivery of vaccines.

Investigating preferences for dynamic electricity tariffs: the effect of environmental and system benefit disclosure

Dynamic electricity pricing can produce efficiency gains in the electricity sector and help achieve energy policy goals such as increasing electric system reliability and supporting renewable energy deployment. Retail electric companies can offer dynamic pricing to residential electricity customers via smart meter-enabled tariffs that proxy the cost to procure electricity on the wholesale market. Current investments in the smart metering necessary to implement dynamic tariffs show policy makers’ resolve for enabling responsive demand and realizing its benefits. However, despite these benefits and the potential bill savings these tariffs can offer, adoption among residential customers remains at low levels. Using a choice experiment approach, this paper seeks to determine whether disclosing the environmental and system benefits of dynamic tariffs to residential customers can increase adoption. Although sampling and design issues preclude wide generalization, we found that our environmentally conscious respondents reduced their required discount to switch to dynamic tariffs around 10% in response to higher awareness of environmental and system benefits. The perception that shifting usage is easy to do also had a significant impact, indicating the potential importance of enabling technology. Perhaps the targeted communication strategy employed by this study is one way to increase adoption and achieve policy goals.

Analysis of the courtship behavior of the Navel Orangeworm, Amyelois transitella (Walker) (Lepidoptera: Pyralidae), with a commentary on methods for the analysis of sequences of behavioral transitions

The courtship behavior of the navel orangeworm, Amyelois transitella, was examined in a wind tunnel. Sixty nine courtship sequences were analyzed and successful sequences divided into two categories: rapid courtship sequences, which involved few breaks in contact, short or no periods of male/female chasing and lasted <10 s between initial contact and mating; and prolonged courtship sequences, which involved many breaks in contact, extended periods of male/female chasing and lasted >10 s. Fifty six (81%) courtships were successful (50.7% rapid courtship and 30.4% prolonged courtship); the remaining 13 (18.8%) sequences were failed courtships. Of failed courtships, 9 (13.0%) were due to males losing contact with females during courtship chases and 4 (5.8%) due to females flying away immediately after male contact. Of all courtship sequences involving a break in contact during a chase, 38.5% resulted in an unsuccessful mating attempt. These findings contrast with previous studies of the courtship behavior of the navel orangeworm, potentially indicating that the type of bioassay used to study courtship may have a large effect on the behavioral sequences displayed. We evaluate several diagnostic techniques for the analysis of sequences of behavioral transitions.

Utilizing insect behavior in chemical detection by a behavioral biosensor

Traditionally, biosensors have been defined as consisting of two parts; a biological part, which is used to detect chemical or physical changes in the environment, and a corresponding electronic component, which tranduces the signal into an electronically readable format. Biosensors are used for detection of volatile compounds often at a level of sensitivity unattainable by traditional analytical techniques. Classical biosensors and traditional analytical techniques do not allow an ecological context to be imparted to the volatile compound/s under investigation. Therefore, we propose the use of behavioral biosensors, in which a whole organism is utilized for the analysis of chemical stimuli. In this case, the organism detects a chemical or physical change and demonstrates this detection through modifications of its behavior; it is the organism's behavior itself that defines the biosensor. In this review, we evaluate the use and future prospects of behavioral biosensors, with a particular focus on parasitic wasps.

Strategy Method (and payment cards)

Payment cards are a useful device to measure subjects’ preferences for a good and especially their willingness to pay for it. Together with some other similar elicitation methods, payment cards are especially appropriate for both hypothetical and incentive-compatible valuations of a good; a property which has prompted many researchers to use them in studies comparing stated and revealed valuations. The Strategy Method (hereafter SM) is a method based on a similar principle as that of payment cards, but is aimed at eliciting a subject’s full profile of responses to each of the strategies available to the rival(s).

Temperament and self-based correlates of cooperative, competitive and individualistic learning preferences

People vary in the extent to which they prefer cooperative, competitive or individualistic achievement tasks. In the present research, we conducted two studies designed to investigate correlates and possible roots of these social interdependence orientations, namely approach and avoidance temperament, general self-efficacy, implicit theories of intelligence, and contingencies of self-worth based in others’ approval, competition, and academic competence. The results indicated that approach temperament, general self-efficacy, and incremental theory were positively, and entity theory was negatively related to cooperative preferences (|r| range from .11 to .41); approach temperament, general self-efficacy, competition contingencies, and academic competence contingencies were positively related to competitive preferences (|r| range from .16 to .46); and avoidance temperament, entity theory, competitive contingencies, and academic competence contingencies were positively related, and incremental theory was negatively related to individualistic preferences (|r| range from .09 to .15). The findings are discussed with regard to the meaning of each of the three social interdependence orientations, cultural differences among the observed relations, and implications for practicioners.

Analysis and clustering of residential customers energy behavioral demand using smart meter data

Clustering methods are increasingly being applied to residential smart meter data, providing a number of important opportunities for distribution network operators (DNOs) to manage and plan the low voltage networks. Clustering has a number of potential advantages for DNOs including, identifying suitable candidates for demand response and improving energy profile modelling. However, due to the high stochasticity and irregularity of household level demand, detailed analytics are required to define appropriate attributes to cluster. In this paper we present in-depth analysis of customer smart meter data to better understand peak demand and major sources of variability in their behaviour. We find four key time periods in which the data should be analysed and use this to form relevant attributes for our clustering. We present a finite mixture model based clustering where we discover 10 distinct behaviour groups describing customers based on their demand and their variability. Finally, using an existing bootstrapping technique we show that the clustering is reliable. To the authors knowledge this is the first time in the power systems literature that the sample robustness of the clustering has been tested.

Ungulate behavioral responses to the heterogeneous road-network of a touristic protected area in Africa

Understanding how wildlife responds to road and traffic is essential for effective conservation. Yet, not many studies have evaluated how roads influence wildlife in protected areas, particularly within the large iconic African National Parks where tourism is mainly based on sightings from motorized vehicles with the consequent development and intense use of roads. To reduce this knowledge gap, we studied the behavioral response and local spatial distribution of impala Aepyceros melampus along the heterogeneous (with variation in road surface type and traffic intensity) road-network of Kruger National Park (KNP, South Africa). We surveyed different types of roads (paved and unpaved) recording the occurrence of flight responses among sighted impala and describing their local spatial distribution (in relation to the roads). We observed relatively few flight responses (19.5% of 118 observations), suggesting impalas could be partly habituated to vehicles in KNP. In addition, impala local distribution is apparently unaffected by unpaved roads, yet animals seem to avoid the close proximity of paved roads. Overall, our results suggest a negative, albeit small, effect of traffic intensity, and of presence of pavement on roads on the behavior of impala at KNP. Future studies would be necessary to understand how roads influence other species, but our results show that even within a protected area that has been well-visited for a long time, wildlife can still be affected by roads and traffic. This result has ecological (e.g., changes in spatial distribution of fauna) and management implications (e.g., challenges of facilitating wildlife sightings while minimizing disturbance) for protected areas where touristic activities are largely based on driving.

Is behavioral ecology important for understanding and predicting population dynamics?

Population ecology is a discipline that studies changes in the number and composition (age, sex) of the individuals that form a population. Many of the mechanisms that generate these changes are associated with individual behavior, for example how individuals defend their territories, find mates or disperse. Therefore, it is important to model population dynamics considering the potential influence of behavior on the modeled dynamics. This study illustrates the diversity of behaviors that influence population dynamics describing several methods that allow integrating behavior into population models and range from simpler models that only consider the number of individuals to complex individual-based models that capture great levels of detail. A series of examples shows the importance of explicitly considering behavior in population modeling to avoid reaching erroneous conclusions. This integration is particularly relevant for conservation, as incorrect predictions regarding the dynamics of populations of conservation interest can lead to inadequate assessment and management. Improved predictions can favor effective protection of species and better use of the limited financial and human conservation resources.

Behavioral economics, wearable devices, and cooperative games: results from a population-based intervention to increase physical activity

Background: Health care literature supports the development of accessible interventions that integrate behavioral economics, wearable devices, principles of evidence-based behavior change, and community support. However, there are limited real-world examples of large scale, population-based, member-driven reward platforms. Subsequently, a paucity of outcome data exists and health economic effects remain largely theoretical. To complicate matters, an emerging area of research is defining the role of Superusers, the small percentage of unusually engaged digital health participants who may influence other members. Objective: The objective of this preliminary study is to analyze descriptive data from GOODcoins, a self-guided, free-to-consumer engagement and rewards platform incentivizing walking, running and cycling. Registered members accessed the GOODcoins platform through PCs, tablets or mobile devices, and had the opportunity to sync wearables to track activity. Following registration, members were encouraged to join gamified group challenges and compare their progress with that of others. As members met challenge targets, they were rewarded with GOODcoins, which could be redeemed for planet- or people-friendly products. Methods: Outcome data were obtained from the GOODcoins custom SQL database. The reporting period was December 1, 2014 to May 1, 2015. Descriptive self-report data were analyzed using MySQL and MS Excel. Results: The study period includes data from 1298 users who were connected to an exercise tracking device. Females consisted of 52.6% (n=683) of the study population, 33.7% (n=438) were between the ages of 20-29, and 24.8% (n=322) were between the ages of 30-39. 77.5% (n=1006) of connected and active members met daily-recommended physical activity guidelines of 30 minutes, with a total daily average activity of 107 minutes (95% CI 90, 124). Of all connected and active users, 96.1% (n=1248) listed walking as their primary activity. For members who exchanged GOODcoins, the mean balance was 4,000 (95% CI 3850, 4150) at time of redemption, and 50.4% (n=61) of exchanges were for fitness or outdoor products, while 4.1% (n=5) were for food-related items. Participants were most likely to complete challenges when rewards were between 201-300 GOODcoins. Conclusions: The purpose of this study is to form a baseline for future research. Overall, results indicate that challenges and incentives may be effective for connected and active members, and may play a role in achieving daily-recommended activity guidelines. Registrants were typically younger, walking was the primary activity, and rewards were mainly exchanged for fitness or outdoor products. Remaining to be determined is whether members were already physically active at time of registration and are representative of healthy adherers, or were previously inactive and were incentivized to change their behavior. As challenges are gamified, there is an opportunity to investigate the role of superusers and healthy adherers, impacts on behavioral norms, and how cooperative games and incentives can be leveraged across stratified populations. Study limitations and future research agendas are discussed.

Distinct behavioral phenotypes in male mice lacking the thyroid hormone receptor alpha1 or beta isoforms

Thyroid hormones influence both neuronal development and anxiety via the thyroid hormone receptors (TRs). The TRs are encoded by two different genes, TRalpha and TRbeta. The loss of TRalpha1 is implicated in increased anxiety in males, possibly via a hippocampal increase in GABAergic activity. We compared both social behaviors and two underlying and related non-social behaviors, state anxiety and responses to acoustic and tactile startle in the gonadally intact TRalpha1 knockout (alpha1KO) and TRbeta (betaKO) male mice to their wild-type counterparts. For the first time, we show an opposing effect of the two TR isoforms, TRalpha1 and TRbeta, in the regulation of state anxiety, with alpha1 knockout animals (alpha1KO) showing higher levels of anxiety and betaKO males showing less anxiety compared to respective wild-type mice. At odds with the increased anxiety in non-social environments, alpha1KO males also show lower levels of responsiveness to acoustic and tactile startle stimuli. Consistent with the data that T4 is inhibitory to lordosis in female mice, we show subtly increased sex behavior in alpha1KO male mice. These behaviors support the idea that TRalpha1 could be inhibitory to ERalpha driven transcription that ultimately impacts ERalpha driven behaviors such as lordosis. The behavioral phenotypes point to novel roles for the TRs, particularly in non-social behaviors such as state anxiety and startle.