Bayesian parameter inference for stochastic SIR epidemic model with hyperbolic diffusion

This paper is concerned with the Bayesian estimation parameters of the stochastic SIR (Susceptible-Infective-Removed) epidemic model from the trajectory data. Specifically, the data from the count of both infectives and susceptibles is assumed to be available on some time grid as the epidemic progresses. The diffusion approximation of the appropriate jump process is then used to estimate missing data between every pair of observation times. If the time step of imputations is small enough, we derive the posterior distributions of the infection and recovery rates using the Milstein scheme. The paper also presents Markov-chain Monte Carlo (MCMC) simulation that demonstrates that the method provides accurate estimates, as illustrated by the synthetic data from SIR epidemic model and the real data.     

The Impact of Lean Management Practices and Sustainably‐Oriented Innovation on Sustainability Performance of Small and Medium‐Sized Enterprises: Empirical Evidence from the UK

While lean management practices (LMP) help small and medium‐sized enterprises (SMEs) to be efficient, sustainability‐oriented innovation (SOI) facilitates adopting environmental and social practices. Although prior research looks into the effect of LMP on the economic performance (EP) of SMEs, less is known about the effect of LMP on sustainability (economic, environmental and social) performance. Studies on the effect of SOI on sustainability and economic performance are also scant. Additionally, examining the mediating effect of corporate social responsibility (CSR) practices (environmental and social practices) on both LMP and SOI achieving sustainability performance (SP) is rare. This research bridges these knowledge gaps by answering the question of how LMP, SOI, CSR practices, sustainability and economic performance are correlated. Through hypothesis testing using structural equation modelling, this study reveals the impact of LMP, SOI, CSR (environmental and social) practices on sustainability and economic performance. The study uses data from 119 SMEs within manufacturing industries in the Midlands, UK. The analysis reveals that LMP and SOI facilitate achieving both sustainability and economic performance, and SOI mediates LMP to achieve sustainability performance. Additionally, although CSR practices mediate LMP to achieve sustainability performance, they only borderline mediate SOI to achieve sustainability performance.     

Dominance and Efficiency in Multicriteria Decision under Uncertainty

This paper proposes several concepts of efficient solutions for multicriteria decision problems under uncertainty. We show how alternative notions of efficiency may be grounded on different decision contexts, depending on what is known about the Decision Maker's (DM) preference structure and probabilistic anticipations. We define efficient sets arising naturally from polar decision contexts. We investigate these sets from the points of view of their relative inclusions and point out some particular subsets which may be especially relevant to some decision situations.     

Consistency of information criteria for model selection with missing data

ABSTRACT

In this paper, we investigate the consistency of the Expectation Maximization (EM) algorithm-based information criteria for model selection with missing data. The criteria correspond to a penalization of the conditional expectation of the complete data log-likelihood given the observed data and with respect to the missing data conditional density. We present asymptotic properties related to maximum likelihood estimation in the presence of incomplete data and we provide sufficient conditions for the consistency of model selection by minimizing the information criteria. Their finite sample performance is illustrated through simulation and real data studies.     

Decentralised bilevel model for shared inventory management

In this study, we consider the case of a large corporation that owns a warehouse and two concurrent chains. The company opted for shared inventory policy. The warehouse is looking into minimising its inventory cost and at the same time reducing the fluctuation of the personnel. The chains, independently, are trying to minimise their inventory costs. The warehouse plays the role of a leader in optimising its objectives and, as followers, the two chains try to satisfy their objectives. The problem is formulated into a decentralised nonlinear bilevel programming problem. We also consider the fuzziness of some parameters due to the imprecise available information. We propose the mathematical model and we solve it for our specific case.     

Liberalization,crisis and growth in MENA region: Do institutions matter?

The main purpose of this study is to investigate the interaction between financial liberalization, banking crisis and economic growth by taking into consideration the role of institutions. Our sample covers 15 Middle East and North African observed during the period 2000–2013. Using a dynamic panel data framework, our findings reveal that financial liberalization contributed to improve economic growth in MENA countries while banking crisis had harmful effects on MENA economies. The quality of institutions did not have a clear impact except for rule and order and democratic institution. These results have important policy implications. To grow output and avoid the occurrence of banking crisis, MENA countries should reinforce their institutions quality by adopting good practice of governance and regulation.     

Resampling for Order Estimation of Autoregressive Models with Missing Data

In this article, we consider the order estimation of autoregressive models with incomplete data using the expectation–maximization (EM) algorithm-based information criteria. The criteria take the form of a penalization of the conditional expectation of the log-likelihood. The evaluation of the penalization term generally involves numerical differentiation and matrix inversion. We introduce a simplification of the penalization term for autoregressive model selection and we propose a penalty factor based on a resampling procedure in the criteria formula. The simulation results show the improvements yielded by the proposed method when compared with the classical information criteria for model selection with incomplete data.