When Residential Energy Labeling Becomes Irrelevant: Sustainability vs. Profitability in the Liberalized Chilean Property Market

The study of the relevance of energy efficiency attributes on residential choices is usually based on stated preferences, using performance indicators. However, this issue has not been researched in developing countries, where energy certification schemes have a low adoption rate. This article paper uses a methodology based on a Kansei Engineering and Kano Model to identify home buyers’ energy performance perceptions in three real estate developments in Santiago de Chile. Surprisingly, energy ratings negatively affected the survey respondents’ willingness to buy. On the other hand, the ratings indicated that the most relevant attribute for influencing the purchasing is the perception of the home as a good investment. This finding contradicts most of the studies on energy certification and shows the relevance given to the profit of purchasing new housing units. Therefore, the analyses suggest that this situation represents a decoupling of consumer perception from both the items measured by energy labels and their contribution to consumer choices.

Sustainable HRM as a Pathway to Sustainability—HRMS Relevance on Affective Commitment through Organizational Trust

Human resource management system (HRMS) is an organizational instrument that sends organizational messages to employees. If we consider that HRMS can be an indicator of organization’s involvement towards employees’ it is relevant to understand its impact in employees’ organizational commitment and study indicators that can help unravel the black box between HRMS and positive results, associating an emerging approach, sustainable HRMS that relates HRMS with sustainability, having as common features the association with positive results for employees. Recent literature has tested organizational trust (OT) as a relevant indicator in the understanding of this process. There have been studies that have debated and tested OT in managers as a mediator or moderator of HRMS on affective commitment (AOC) and support for both have been found. In this study, we attempt to contribute to the development of the field, by considering the terminological, conceptual and statistical distinction between moderator and mediator, testing two alternative models that may elucidate the relationship between these variables. 1328 valid responses with employees and managers from 21 Portuguese organizations were collected. A factor analysis, a cluster analysis, moderation tests using hierarchical linear regression, pos hoc tests and mediation tests with sequential regressions were performed. HRMS dimensions are mediated (partially or totally) by OT in manager towards AOC. HRMS dimensions (HR relationship with employees, comprehensibility, utility, visibility and distributive justice) influences OT in manager, which, in turn, influences AOC. Regarding moderation, the interaction between distributive justice and OT, pos-hoc tests showed that when distributive justice increases and levels of OT in manager is high, OAC increases rapidly. It seems that the importance of the distributive justice of HRMS only becomes relevant on OAC, if OT in manager is present. This empirical test of the HRMS model also suggests its reframing in two meta-dimensions: A. the agents of HR system, the HR relationship with employees based on their competence, consistent behavior, ability to solve problems and listening to people; and B. the effects of the system itself, possibly Visibility is the most relevant attribute. We suggest that these interactions between HR agents and employees are relevant and may lead to generalizations about the HRMS.

Activity Recognition on Subject Independent Using Machine Learning

Recent Activity Daily Living (ADL) not only tackles simple activities, but also caters to a wide range of complex activities. Although the same activity has been carried out under the same environmental conditions, the acceleration signal obtained from each subject considerably differs. This happens due to the pattern of action generated for each subject is diverse based on several aspects such as subject age, gender, emotion and personality. This project therefore compares the accuracy of various machine learning models for ADL classification. On top of that, this research work also scrutinizes the effectiveness of various feature selection methods to identify the most relevant attribute for ADL classification. As a result, Random Forest was able to achieve the highest accuracy of 83.3% on subject independent matter in ADL classification. Meanwhile, CFS Subset Evaluator is considered to be a good feature selector as it successfully selected the 8 most relevant features compared with Correlation and Information Gain Evaluator.

Is Biodiversity a Relevant Attribute for Assessing Natural Parks? Evidence from Cornalvo Natural Park in Spain

The economic valuation of goods that do not have a market, like services offered by natural parks, provide a lot of information for the purpose of policy making on the conservation and protection of the natural environment, as well as for establishing park use strategies for potential park visitors. In this respect, this paper aims to analyse visitor preferences for Cornalvo Natural Park, which has been classed, since 1992, as a Site of Community Importance. To do this, we conducted an analysis adopting the choice experiment methodology to determine visitor preferences for a set of attributes. Additionally, we included a visitor preference heterogeneity analysis based on a mixed logit model in order to calculate individual willingness to pay with respect to a set of previously specified attributes. Finally, we also implemented the latent class methodology to define groups of individuals with similar characteristics. The information was gathered from visitor surveys conducted during 2019. The main results show that tourists had a high preference and willingness to pay for higher biodiversity levels and lower numbers of visitors, whereas the other attributes were less relevant. Additionally, we detected some degree of heterogeneity in willingness to pay by sex, age and income. Finally, Latent class analysis identified two visitor classes, determined primarily by age and income.

Do not despair about severity—yet

In a recent extended essay, philosopher Daniel Hausman goes a long way towards dismissing severity as a morally relevant attribute in the context of priority setting in healthcare. In this response, we argue that although Hausman certainly points to real problems with how severity is often interpreted and operationalised within the priority setting context, the conclusion that severity does not contain plausible ethical content is too hasty. Rather than abandonment, our proposal is to take severity seriously by carefully mapping the possibly multiple underlying accounts to well-established ethical theories, in a way that is both morally defensible and aligned with the term’s colloquial uses.

The Role of Explicit Categorization in the Implicit Association Test

The present study investigated how task-irrelevant attributes of a stimulus affected responses in a multi-attribute version of the Implicit Association Test (IAT). In Experiment 1, participants categorized images of Black and White male and female individuals on the basis of either race or gender. Both the race and gender of the individuals affected task performance regardless of which attribute was currently relevant to performing the task, yielding the IAT effects on both attributes. However, the influences of a task-irrelevant attribute depended on whether the task-relevant attribute was categorized compatibly or incompatibly with the underlying implicit biases. These results suggest that individuals are still categorized implicitly based on task-irrelevant social attributes and that the explicit categorization required in the standard IAT has a considerable impact on implicit social biases. Experiment 2 considered a third, non-social attribute (the color of the picture frame) and reproduced task-irrelevant IAT effects and their dependence on explicit categorization. However, Experiments 3 and 4 suggested that the task-irrelevant IAT effects based on social attributes are determined by whether the task-relevant attribute is a social or non-social attribute. The results raise fundamental questions about the basic assumptions underpinning the interpretations of the results from the IAT.

Specific Features of Descriptive Statistics with Fuzzy Random Variables

The aim of the paper is to examine procedures of descriptive statistics in the case when the values of relevant attribute in a sample are set in the form of fuzzy categories. The paper provides alternative definitions of a fuzzy random variable, and describes corresponding procedures for calculating the analogues of location and spread parameters. The paper also presents some illustrative examples and analyses the results obtained. Based on the result analysis, practical recommendations are given on how to use procedures of fuzzy statistics.