Flexible‐Duration Extended Warranties with Dynamic Reliability Learning

Frequent technological innovations and price declines adversely affect sales of extended warranties (EWs) as product replacement upon failure becomes an increasingly attractive alternative. To increase sales and profitability, we propose offering flexible‐duration EWs. These warranties can appeal to customers who are uncertain about how long they will keep the product as well as to customers who are uncertain about the product's reliability. Flexibility may be added to existing services in the form of monthly billing with month‐by‐month commitments or by making existing warranties easier to cancel with pro‐rated refunds. This paper studies flexible warranties from perspectives of both customers and the provider under customers' reliability learning. We present a model of customers' optimal coverage decisions and show that customers' optimal coverage policy has a threshold structure under some mild conditions. We further show that flexible warranties can result in higher profits and higher attach rates in a homogeneous market as well as in a heterogeneous market with multiple segments differing in various dimensions.     

Joint regression modeling for missing categorical covariates in generalized linear models

Missing covariates data is a common issue in generalized linear models (GLMs). A model-based procedure arising from properly specifying joint models for both the partially observed covariates and the corresponding missing indicator variables represents a sound and flexible methodology, which lends itself to maximum likelihood estimation as the likelihood function is available in computable form. In this paper, a novel model-based methodology is proposed for the regression analysis of GLMs when the partially observed covariates are categorical. Pair-copula constructions are used as graphical tools in order to facilitate the specification of the high-dimensional probability distributions of the underlying missingness components. The model parameters are estimated by maximizing the weighted log-likelihood function by using an EM algorithm. In order to compare the performance of the proposed methodology with other well-established approaches, which include complete-cases and multiple imputation, several simulation experiments of Binomial, Poisson and Normal regressions are carried out under both missing at random and non-missing at random mechanisms scenarios. The methods are illustrated by modeling data from a stage III melanoma clinical trial. The results show that the methodology is rather robust and flexible, representing a competitive alternative to traditional techniques.     

A beta-inflated mean regression model with mixed effects for fractional response variables

Abstract

In this article we propose a new mixed-effects regression model for fractional bounded response variables. Our model allows us to incorporate covariates directly to the expected value, so we can quantify exactly the influence of these covariates in the mean of the variable of interest rather than to the conditional mean. Estimation is carried out from a Bayesian perspective. Due to the complexity of the augmented posterior distribution, we use a Hamiltonian Monte Carlo algorithm, the No-U-Turn sampler, implemented using the Stan software. A simulation study was performed showing that our model has a better performance than other traditional longitudinal models for bounded variables. Finally, we applied our beta-inflated mean mixed-effects regression model to real data which consists of utilization of credit lines in the peruvian financial system.     

Business intelligence and analytics value creation in Industry 4.0: a multiple case study in manufacturing medium enterprises

Abstract

Medium enterprises (MEs) form a majority of enterprises in several regions, yet they are underrepresented in the literature. The digital transformation known as Industry 4.0 (I4.0) brings new data streams into enterprises. MEs and large enterprises will both leverage business intelligence and analytics (BI&A) to improve their business performance, so the study of the conditions favouring value creation of BI&A is of interest. However, there are few studies focusing on the impact of business intelligence and analytics (BI&A) on value creation in I4.0 and none focusing on MEs. Using a multiple case-study design, this paper explores factors linked to BI&A business value creation in manufacturing MEs that are undergoing an I4.0 transformation. Findings suggest enterprises resources and capabilities are not sufficient to predict business value: organizational learning and organizational culture have a non-negligible influence for MEs.     

Profit Sharing in Portugal: Why Higher Productivity?

The paper studies some characteristics of Portuguese profit‐sharing (PS) firms based on a sample of 192 manufacturing firms. Some issues are examined that could help explain observed productivity differences such as the performance contingency of PS payments and the complementary or substitution nature of these payments regarding wages. The higher productivity found for PS firms seems to be more related to higher total remuneration in these firms than to the specific PS pay formula. The issues of why, how and by whom PS payments are determined could clarify the exact nature of our findings.     

The effect of artificial light on bat richness and nocturnal soundscapes along an urbanization gradient in an arid landscape of central Peru

Urbanization usually reduces bat richness; however, the presence of green areas within cities and peripheral rural areas in arid ecosystems may provide microhabitats for some species. Light pollution is a major feature of urbanization, but its impact on bat behavior appears to be species-specific and previous studies have documented contrasting responses. Moreover, the effect of urbanization on bat species has been poorly studied in arid regions. We assessed the effect of artificial night light intensity (as a proxy of urbanization) on both bat occupancy and the acoustic space used (ASU) in an urbanization gradient in Peruvian central coast, based on passive acoustic recorders. We collected 26,169 recordings from 19 sites which resulted in 579 independent detections of 15 bat species. Variation in both ASU and species richness was best explained by artificial night light intensity. Species-specific effects of the artificial night light intensity based on a multi-species occupancy modeling showed that this covariate had a negative effect on occupancy for most of the bat species (12 species). ASU and both observed and posterior bat species richness were positively correlated, suggesting that ASU can be used as a proxy of bat richness. This study provides evidence that both bat richness and occupancy decrease with artificial light intensity; nevertheless, eight species used urban areas, similar to results found in other cities around the world.

     

Managerial entrenchment and corporate social responsibility engagement: the role of economic policy uncertainty

Journal of Management and Governance - The behavioral theory of corporate governance is employed to investigate the relationship between managerial entrenchment and corporate social responsibility...