Analyzing the role of values, beliefs and attitude in developing sustainable behavioral intentions: empirical evidence from electric power industry

Energy conservation is an economic, social, and environmental issue that offers various academic, practical, and policy implications. The growing magnitude, complexity, and relevance of energy wastage have attracted the attention of scholars and practitioners. There is a lack of consumer awareness towards electricity conservation practices of household consumers in the context of developing countries. This research utilized the theory of planned behavior to explain sustainable behavioral intentions in the context of electricity conservation. This research aims to measure the effect of beliefs, values, and attitudes on sustainable behavioral intentions in the energy conservation context. This research hypothesized awareness, compatibility, perceived value, resistance to change, and actual gain as predictors of attitude towards energy conservation and sustainable behavioral intentions. Using survey methodology, purposive sampling techniques were used to collect the data from young household consumers. Data of 246 electricity consumers of Pakistan were analyzed using confirmatory factor analysis (CFA) and structural equation modeling (SEM). Results of the study validate a significant relationship between attitude towards energy conservation and sustainable behavioral intentions. Based on results, it has been established that the amount of actual gain intentions and awareness are the main contributors to attitude towards energy conservation and sustainable behavioral intention. Compatibility and resistance to change were also significant precipitators of attitude towards energy conservation and sustainable behavioral intention. Perceived value was found a significant predictor of attitude towards energy conservation while insignificant towards sustainable behavioral intention. The study findings have a significant impact on government, policymakers, marketers, and academics interested in developing strategies to mitigate the effects of energy wastage. Prevention of resource wastage depends upon the awareness and consumption practices of the customers.

Human visual search behaviour is far from ideal

Evolutionary pressures have made foraging behaviours highly efficient in many species. Eye movements during search present a useful instance of foraging behaviour in humans. We tested the efficiency of eye movements during search using homogeneous and heterogeneous arrays of line segments. The search target is visible in the periphery on the homogeneous array, but requires central vision to be detected on the heterogeneous array. For a compound search array that is heterogeneous on one side and homogeneous on the other, eye movements should be directed only to the heterogeneous side. Instead, participants made many fixations on the homogeneous side. By comparing search of compound arrays to an estimate of search performance based on uniform arrays, we isolate two contributions to search inefficiency. First, participants make superfluous fixations, sacrificing speed for a perceived (but not actual) gain in response certainty. Second, participants fixate the homogeneous side even more frequently than predicted by inefficient search of uniform arrays, suggesting they also fail to direct fixations to locations that yield the most new information.

Nearest-neighbor-adjusted means as a selection criterion within two soybean populations

When the nearest-neighbor adjustment (NNA) reduces the magnitude of the residual mean square, plant breeders have the option of selecting genotypes on the basis of the NNA or unadjusted (UNADJ) means. The actual gain from selection for a specific set of experiments can be compared when selection is based on each criterion. Our objective was to compare the yields of lines selected with the NNA and UNADJ criteria. Three hundred soybean [Glycine max (L.) Merr.] experimental lines were evaluated in six environments. Each environment was considered a selection environment, and the actual yield advance was measured in the other five environments. In 11 out of 12 cases, the lines selected by the NNA and UNADJ criteria were equal in yield when compared in testing environments. Interlocation correlations were similar for both models. Predicted genetic gain was overestimated more often when using the NNA than the UNADJ model. Key words:Glycine max, heritability

Importance of the Characteristics of Gatekeepers in the Design of Effective Alcohol Education Programs

Community “gatekeepers” ( N = 53) participated in an alcohol education workshop designed to increase indentification, intervention, and referral of women with alcohol problems. Participants completed questionnaires before and after the workshop and, participated in a six-month follow-up. Results suggest that the higher the educational level and more salient the topic of alcoholism in women, as suggested by greater percent of women clients, the greater the actual gain in knowledge. Gatekeepers with no prior alcoholism training perceived themselves as having less knowledge about alcoholism before the workshop and showed greater pains in perceived knowledge as a result of the workshop than gatekeepers with prior training.

Uniformly best invariant stopping rules

The class of stopping rules for a sequence of i.i.d. random variables with partially known distribution is restricted by requiring invariance with respect to certain transformations. Invariant stopping rules have an intuitive appeal when the optimal stopping problem is invariant with respect to the actual gain function. Uniformly best invariant stopping rules are derived for the gamma distribution with known shape parameter and unknown scale parameter, for the uniform distribution with both endpoints unknown, and for the normal distribution with unknown mean and variance. Some comparisons with previously published results are made.

Uniformly best invariant stopping rules

The class of stopping rules for a sequence of i.i.d. random variables with partially known distribution is restricted by requiring invariance with respect to certain transformations. Invariant stopping rules have an intuitive appeal when the optimal stopping problem is invariant with respect to the actual gain function. Uniformly best invariant stopping rules are derived for the gamma distribution with known shape parameter and unknown scale parameter, for the uniform distribution with both endpoints unknown, and for the normal distribution with unknown mean and variance. Some comparisons with previously published results are made.