Search results for "Timo"
showing 10 items of 2111 documents
How Does Stakeholder Engagement Affect Business Model Sustainability?
2019
This chapter develops insight for the management of businesses, in various sectors of economic activity, that take, or wish to adopt, a proactive or reactive approach to the triple dimensions of sustainability, suggesting itself to support both academics and practitioners in the wide area of business management. More in detail, this book analyzes, from different points of view, how SE and proper relationship management can contribute to achieving corporate sustainability goals by creating value for the business and particularly ethical and environmental values for the entire community.
Innovation strategies geared toward the circular economy: A case study of the organic olive-oil industry
2018
Circular Economy (CE) focuses on the (re)design of processes and products aiming to minimize negative environmental impact, by reducing the use of non-renewable resources, increasing products durability, improving waste management and enhancing the market for secondary raw materials. In the management field very few contributions deal with the topic of CE as a model that firms can implement from a business model perspective. The aim of the present study is to describe, by using a case study in olive oil industry, how firms in practice adapt their business model towards CE paradigm and the influence of personal drivers and stakeholders in this adaptation. The findings reveal that circular ec…
Mercato immobiliare. Gli standard valutativi internazionali.
2009
L'applicazione degli standard valutativi internazionali nelle valutazioni mirano all'efficienza e alla trasparenza del mercato immobiliare.
Stime catastali e standard internazionali
2008
Il metodo per classi e tariffe del Catasto italiano è esaminato alla luce degli standard valutativi e catastali internazionali.
Fast and universal estimation of latent variable models using extended variational approximations
2022
AbstractGeneralized linear latent variable models (GLLVMs) are a class of methods for analyzing multi-response data which has gained considerable popularity in recent years, e.g., in the analysis of multivariate abundance data in ecology. One of the main features of GLLVMs is their capacity to handle a variety of responses types, such as (overdispersed) counts, binomial and (semi-)continuous responses, and proportions data. On the other hand, the inclusion of unobserved latent variables poses a major computational challenge, as the resulting marginal likelihood function involves an intractable integral for non-normally distributed responses. This has spurred research into a number of approx…
Importance sampling correction versus standard averages of reversible MCMCs in terms of the asymptotic variance
2017
We establish an ordering criterion for the asymptotic variances of two consistent Markov chain Monte Carlo (MCMC) estimators: an importance sampling (IS) estimator, based on an approximate reversible chain and subsequent IS weighting, and a standard MCMC estimator, based on an exact reversible chain. Essentially, we relax the criterion of the Peskun type covariance ordering by considering two different invariant probabilities, and obtain, in place of a strict ordering of asymptotic variances, a bound of the asymptotic variance of IS by that of the direct MCMC. Simple examples show that IS can have arbitrarily better or worse asymptotic variance than Metropolis-Hastings and delayed-acceptanc…
Estimating the causal effect of timing on the reach of social media posts
2022
AbstractModern companies regularly use social media to communicate with their customers. In addition to the content, the reach of a social media post may depend on the season, the day of the week, and the time of the day. We consider optimizing the timing of Facebook posts by a large Finnish consumers’ cooperative using historical data on previous posts and their reach. The content and the timing of the posts reflect the marketing strategy of the cooperative. These choices affect the reach of a post via a dynamic process where the reactions of users make the post more visible to others. We describe the causal relations of the social media publishing in the form of a directed acyclic graph, …
Efficient spatial designs using Hausdorff distances and Bayesian optimization
2021
An iterative Bayesian optimisation technique is presented to find spatial designs of data that carry much information. We use the decision theoretic notion of value of information as the design criterion. Gaussian process surrogate models enable fast calculations of expected improvement for a large number of designs, while the full-scale value of information evaluations are only done for the most promising designs. The Hausdorff distance is used to model the similarity between designs in the surrogate Gaussian process covariance representation, and this allows the suggested algorithm to learn across different designs. We study properties of the Bayesian optimisation design algorithm in a sy…
Estimating Mean Lifetime from Partially Observed Events in Nuclear Physics
2022
Abstract The mean lifetime is an important characteristic of particles to be identified in nuclear physics. State-of-the-art particle detectors can identify the arrivals of single radioactive nuclei as well as their subsequent radioactive decays (departures). Challenges arise when the arrivals and departures are unmatched and the departures are only partially observed. An inefficient solution is to run experiments where the arrival rate is set very low to allow for the matching of arrivals and departures. We propose an estimation method that works for a wide range of arrival rates. The method combines an initial estimator and a numerical bias correction technique. Simulations and examples b…
Large-sample properties of unsupervised estimation of the linear discriminant using projection pursuit
2021
We study the estimation of the linear discriminant with projection pursuit, a method that is unsupervised in the sense that it does not use the class labels in the estimation. Our viewpoint is asymptotic and, as our main contribution, we derive central limit theorems for estimators based on three different projection indices, skewness, kurtosis, and their convex combination. The results show that in each case the limiting covariance matrix is proportional to that of linear discriminant analysis (LDA), a supervised estimator of the discriminant. An extensive comparative study between the asymptotic variances reveals that projection pursuit gets arbitrarily close in efficiency to LDA when the…