Strategic monitoring of port authorities activities: Proposal of a multi-dimensional digital dashboard

Abstract

The consequence of port evolution is that port authorities (PA) around the world are modifying their nature and their role, acquiring more and more an active role in the governance of logistic systems and are often adopting managerial and entrepreneurial behaviours. This new role of PA requires the adoption of a complex approach to monitoring the performance of the single stakeholders and of the whole port. Existing studies on port performance consider only specific indicators of port performance such as operational and financial efficiency neglecting aspects like customer satisfaction, port security and port sustainability. This paper tries to fill this literature gap: (i) outlining an integrated multi-dimensional dashboard to monitor port performance in a strategic perspective; (ii) analysing the role of digital technology to support the PA in the implementation of the monitoring dashboard; (iii) defining the evolutionary stages of tools implementation in the strategic monitoring of PAs.     

Sleepiness,choice consistency,and risk preferences

We investigate the consistency and stability of individual risk preferences by manipulating cognitive resources. Participants are randomly assigned to an experiment session at a preferred time of day relative to their diurnal preference (circadian matched) or at a non-preferred time (circadian mismatched) and choose allocations between two risky assets [using the Choi et al. (Am Econ Rev 27(5):1921–1938, 2007), design]. We find that choices of circadian matched and mismatched subject are statistically similar in terms of satisfying basic requirements for preference consistency. However, mismatched subjects tend to choose riskier asset bundles.     

The relationship of maternal work characteristics to childcare type and quality in rural communities

Drawing on data from the Family Life Project collected in North Carolina and Pennsylvania, this paper examines the relationship between maternal work characteristics and childcare type and quality in rural communities. Research is limited on the childcare experiences of rural families. Rural areas have less access to formal childcare and families often commute long distances for work, restricting childcare options. Employed mothers using childcare were selected (n=441). Logistic and OLS regression was used to examine which characteristics, including workplace support, objective occupational measures, hours, wage, and shift, predicted care type and quality. Results indicated that most families were using informal care. Those with more hazardous work conditions and working night shifts were less likely to use centers. Higher quality care was related to more workplace support, center use, and higher wages. Implications for social policy and practice are discussed.     

An Integrated Approach to Managing Change

Complex systems often involve a huge number of variables whose interdependence must be taken into account. This makes the adoption of an integrated approach essential for the proper management of a wide range of aspects related to human life, from social matters to the environment. In particular, this paper takes into consideration three different experiences in which the use of an integrated approach represented the most effective response for managing the evolving realities we took into consideration. We focused on the issue of land management, with particular attention to the problem of monoculture in Brazil. Then we analyzed the attempted cooperation between the States of the Aral Sea area for efficient water management of the basin and, finally, we dealt with the matter of energy efficiency and how the production of home integrated systems could lead to a better rationalization of energy consumption in the near future.      

On boosting kernel regression

In this paper we propose a simple multistep regression smoother which is constructed in an iterative manner, by learning the Nadaraya–Watson estimator with _L2$L_2$ boosting. We find, in both theoretical analysis and simulation experiments, that the bias converges exponentially fast, and the variance diverges exponentially slow. The first boosting step is analysed in more detail, giving asymptotic expressions as functions of the smoothing parameter, and relationships with previous work are explored. Practical performance is illustrated by both simulated and real data.     

Metabolic impact of shift work

In developing countries, shift work represents a considerable contingent workforce. Recently, studies have shown that overweight and obesity are more prevalent in shift workers than day workers. In addition, shift work has been associated with a higher propensity for the development of many metabolic disorders, such as insulin resistance, diabetes, dislipidemias and metabolic syndrome. Recent data have pointed that decrease of the sleep time, desynchronization of circadian rhythm and alteration of environmental aspects are the main factors related to such problems. Shortened or disturbed sleep is among the most common health-related effects of shift work. The plausible physiological and biological mechanisms are related to the activation of the autonomic nervous system, inflammation, changes in lipid and glucose metabolism, and related changes in the risk for atherosclerosis, metabolic syndrome, and type II diabetes. The present review will discuss the impact of shift work on obesity and metabolic disorders and how disruption of sleep and circadian misalignment may contribute to these metabolic dysfunctions.     

Finding disturbances in on-farm biogas production

When implementing innovations, disturbances are very likely to take place. Disturbances are undesirable because they can lead to unwanted outcomes, such as economic losses and work overload to workers. However, they can be powerful opportunities for learning and re-designing innovations. Here, we will present activity theoretical tools for analyzing disturbances in a way that they could be used as learning opportunities. We illustrate the proposed tools by analyzing a disturbance that took place during the implementation of a project of biogas production. By interpreting the disturbance process with a network of activity systems, we found that on-farm disturbances were formed as ruptures, innovations and asynchronies originated in other activity systems. This finding suggests that disturbances are outcomes of the functioning of networks, rather than simple results of failure of individuals or technical devices. The proposed tools could be used in interventions to help practitioners and ergonomists to recognize the systemic and networked nature of problems, and therefore, realize that they may require the collaboration of actors from different activities. In this sense, disturbances may be turned into opportunities for learning and developing innovations. We conclude by discussing how the method could be used in ergonomic design and intervention.     

Random coefficient models for binary longitudinal responses with attrition

We extend the approach introduced by Aitkin and Alfò (1998, Statistics and Computing, 4, pp. 289–307) to the general framework of random coefficient models and propose a class of conditional models to deal with binary longitudinal responses, including unknown sources of heterogeneity in the regression parameters as well as serial dependence of Markovian form.Furthermore, we discuss the extension of the proposed approach to the analysis of informative drop-outs, which represent a central problem in longitudinal studies, and define, as suggested by Follmann and Wu (1995, Biometrics, 51, pp. 151–168), a conditional specification of the full shared parameter model for the primary response and the missingness indicator. The model is applied to a dataset from a methadone maintenance treatment programme held in Sydney in 1986 and previously analysed by Chan et al. (1998, Australian & New Zealand Journal of Statistics, 40, pp. 1–10).All of the proposed models are estimated by means of an EM algorithm for nonparametric maximum likelihood, without assuming any specific parametric distribution for the random coefficients and for the drop-out process.A small scale simulation work is described to explore the behaviour of the extended approach in a number of different situations where informative drop-outs are present.     

Finding an unknown number of multivariate outliers

Summary.  We use the forward search to provide robust Mahalanobis distances to detect the presence of outliers in a sample of multivariate normal data. Theoretical results on order statistics and on estimation in truncated samples provide the distribution of our test statistic. We also introduce several new robust distances with associated distributional results. Comparisons of our procedure with tests using other robust Mahalanobis distances show the good size and high power of our procedure. We also provide a unification of results on correction factors for estimation from truncated samples.     

Association of Problem Gambling with Type of Gambling Among Italian General Population

The origin of gambling disorders is uncertain; however, research has shown a tendency to focus on specific types of games as a potential important risk factor. The principal aim of this study is to examine the relationships between types of gambling practices and gambling disorder. The data were extracted from IPSAD-Italia^® 2010–2011 (Italian Population Survey on Alcohol and other Drugs), a survey among the Italian general population which collects socio-cultural information, information about the use of drugs, legal substances and gambling habits. In order to identify the “problem gambler” we used the Problem Gambling Severity Index. Three groups are considered in this analysis: no-risk gamblers, low-risk gamblers, moderate-risk/problem gamblers. Type of gambling practice was considered among two types of gambler: one-game players and multi-games players. 1.9 % of multi-game players were considered problem gamblers, only 0.6 % of one-game players were problem gamblers (p < 0.001). The percentage of players who were low and moderate-risk gamblers was approximately double among multi-game players, with 14.4 % low-risk and 5.8 % moderate-risk; compared with 7.7 % low-risk and 2.5 % moderate risk among one-game players. Results of ordinal logistic regression analysis confirmed that higher level of gambling severity was associated with multi-game players (OR = 2.23, p < 0.0001). Video-poker/slot-machines show the highest association with gambling severity among both one-game players and multi-game players, with scores of OR equal to 4.3 and 4.5 respectively. These findings suggest a popular perception of risk associated with this type of gambling for the development of gambling problems.