The Input Evaluation of Generalized Bernoulli Processes for Salary Lines Construction by Means of Continuous Time Generalized Non-Homogeneous Semi-Markov Processes

Salary line forecasting assumes a relevant role in manpower and in pension funds Previously, the authors presented a generalized Bernoulli process, useful for forecasting the evolution of salary lines, taking into account the salary costs, the number of workers at each rank and the probability transitions between the ranks. The problem with applying this model is constructing the probability of transition between the grades. In this article, we will present a model that allows obtaining these probabilities by means of the solution of the evolution equation of a generalization of continuous time non-homogeneous semi-Markov processes.     

A non-linear time series approach to modelling asymmetry in stock market indexes

In this paper we analyse the performances of a novel approach to modelling non-linear conditionally heteroscedastic time series characterised by asymmetries in both the conditional mean and variance. This is based on the combination of a TAR model for the conditional mean with a Constrained Changing Parameters Volatility (CPV-C) model for the conditional variance. Empirical results are given for the daily returns of the S&P 500, NASDAQ composite and FTSE 100 stock market indexes.     

Simulation analysis of cold chain performance based on time–temperature data

Perishable goods are a fundamental source of revenue for the retail sector; their management, however, constitutes a severe challenge for retailers and supply chain partners. A significant cost in particular is the fraction of products perished through the supply chain, which also constitutes an ethical and environmental concern. Supply chain organisation and operative characteristics have a significant influence on this matter, as in fact ensuring suitable temperature conditions for the stock-keeping units throughout the supply chain is mandatory for perishable products. Recent developments in sensing and communication technologies allow detailed monitoring and control of cold chain; however, depending on the characteristics of the supply chain, an inherent risk of perished products is often inevitable, even in the hypothesis of perfect control. This article proposes a methodology to evaluate the performance of a cold chain in terms of expected product quality at the retail store, and to estimate the expected fraction of perished products, according to the supply chain configuration. The approach is based on Monte Carlo simulation, and implements referenced shelf-life models. A real application is also presented, involving a preliminary analysis and mapping of the supply chain activities based on time–temperature data, in order to demonstrate the practicability of the approach proposed.     

Unit Root Tests under Time-Varying Variances

The paper provides a general framework for investigating the effects of permanent changes in the variance of the errors of an autoregressive process on unit root tests. Such a framework - which is based on a novel asymptotic theory for integrated and near integrated processes with heteroskedastic errors - allows to evaluate how the variance dynamics affect the size and the power function of unit root tests. Contrary to previous studies, it is shown that non-constant variances can both inflate and deflate the rejection frequency of the commonly used unit root tests, both under the null and under the alternative, with early negative and late positive variance changes having the strongest impact on size and power. It is also shown that shifts smoothed across the sample have smaller impacts than shifts occurring as a single abrupt jump, while periodic variances have a negligible effect even when a small number of cycles take place over a given sample. Finally, it is proved that the locally best invariant (LBI) test of a unit root against level stationarity is robust to heteroskedasticity of any form under the null hypothesis.     

Correlates of internal audit function involvement in sustainability audits

Journal of Management and Governance - While an increasing number of organizations are engaging in sustainability activities, assurance of these activities is relatively new. We investigate the...     

The management of firms’ alliance network positioning: Implications for innovation

In spite of the frequent calls for a much more integrated approach, the field of management still faces the ever continuing challenges in attempting to bridge the gap between academic research and managerial actions and practices. The field of strategic alliances and firms’ networks are those among which research and practice are more diverging. Trying to cover this separation, the article presents an empirical research on automotive industry that investigates the effects on innovation performance of the position that firms occupy in the network of alliances. The hypothesis that guides this research is that innovation is generated not only from the resources that a company is able to develop internally, but also through access to resources and capabilities owned by the external companies and organizations that the firm itself is tied to through alliances and cooperation agreements. Beyond this broad argument, the paper links tightly research and practice showing way and how the quality of access to resources owned by partners is influenced by the position occupied in the network of alliances and not only by the existence of single collaborative ties. Assuming a managerial approach which relies on the milestones of network research, different types of positioning in the network of alliances are discussed and tested on their impact on innovation.