The dark and bright side of remote work: social isolation, concentration, and performance of remote workers

This dissertation, comprised of three separate studies, focuses on the relationship between remote work adoption and employee job performance, analyzing employee social isolation and job concentration as the main mediators of this relationship. It also examines the impact of concern about COVID-19 and emotional stability as moderators of these relationships. Using a survey-based method in an emergency homeworking context, the first study found that social isolation had a negative effect on remote work productivity and satisfaction, and that COVID-19 concerns affected this relationship differently for individuals with high and low levels of concern. The second study, a diary study analyzing hybrid workers, found a positive correlation between work from home (WFH) adoption and job performance through social isolation and job concentration, with emotional stability serving respectively as a buffer and booster in the relationships between WFH and the mediators. The third study, even in this case a diary study of hybrid workers, confirmed the benefits of work from home on job performance and the importance of job concentration as a mediator, while suggesting that social isolation may not be significant when studying employee job performance, but it is relevant for employee well-being. Although each study provides autonomously a discussion and research and practical implications, this dissertation also presents a general discussion on remote work and its psychological implications, highlighting areas for future research

Criteri di valutazione medico-legale della narcolessia

Impairment due to narcolepsy strongly limits job performance, but there are no standard criteria to assess disability in people with narcolepsy and a scale of disease severity is still lacking. We explored: 1. the interobserver reliability among Italian Medical Commissions making disability and handicap benefit decisions for people with narcolepsy, searching for correlations between the recognized disability degree and patients’ features; 2. the willingness to report patients to the driving licence authority; 3. possible sources of variance in judgement. Fifteen narcoleptic patients were examined by four Medical Commissions in simulated sessions. Raw agreement and interobserver reliability among Commissions were calculated for disability and handicap benefit decisions and for driving licence decisions. Levels of judgement differed on percentage of disability (p<0.001), severity of handicap (p=0.0007) and the need to inform the driving licence authority (p=0.032). Interobserver reliability ranged from Kappa = - 0.10 to Kappa = 0.35 for disability benefit decision and from Kappa = - 0.26 to Kappa = 0.36 for handicap benefit decision. The raw agreement on driving licence decision ranged from 73% to 100% (Kappa not calculable). Spearman’s correlation between percentages of disability and patients’ features showed correlations with age, daytime naps, sleepiness, cataplexy and quality of life. This first interobserver reliability study on social benefit decisions for narcolepsy shows the difficulty of reaching an agreement in this field, mainly due to variance in interpretation of the assessment criteria. The minimum set of indicators of disease severity correlating with patients’ self assessments encourages a disability classification of narcolepsy.

Essays in Behavioral Personnel Economics

The thesis contemplates 4 papers and its main goal is to provide evidence on the prominent impact that behavioral analysis can play into the personnel economics domain.The research tool prevalently used in the thesis is the experimental analysis.The first paper provide laboratory evidence on how the standard screening model–based on the assumption that the pecuniary dimension represents the main workers’choice variable–fails when intrinsic motivation is introduced into the analysis.The second paper explores workers’ behavioral reactions when dealing with supervisors that may incur in errors in the assessment of their job performance.In particular,deserving agents that have exerted high effort may not be rewarded(Type-I errors)and undeserving agents that have exerted low effort may be rewarded(Type-II errors).Although a standard neoclassical model predicts both errors to be equally detrimental for effort provision,this prediction fails when tested through a laboratory experiment.Findings from this study suggest how failing to reward deserving agents is significantly more detrimental than rewarding undeserving agents.The third paper investigates the performance of two antithetic non-monetary incentive schemes on schooling achievement.The study is conducted through a field experiment.Students randomized to the main treatments have been incentivized to cooperate or to compete in order to earn additional exam points.Consistently with the theoretical model proposed in the paper,the level of effort in the competitive scheme proved to be higher than in the cooperative setting.Interestingly however,this result is characterized by a strong gender effect.The fourth paper exploits a natural experiment setting generated by the credit crunch occurred in the UK in the2007.The economic turmoil has negatively influenced the private sector,while public sector employees have not been directly hit by the crisis.This shock–through the rise of the unemployment rate and the increasing labor market uncertainty–has generated an exogenous variation in the opportunity cost of maternity leave in private sector labor force.This paper identifies the different responses.

Integrating the age factor in designing industrial environments and workstations in the workforce ageing era

As people spend a third of their lives at work and, in most cases, indoors, the work environment assumes crucial importance. The continuous and dynamic interaction between people and the working environment surrounding them produces physiological and psychological effects on operators. Recognizing the substantial impact of comfort and well-being on employee satisfaction and job performance, the literature underscores the need for industries to implement indoor environment control strategies to ensure long-term success and profitability. However, managing physical risks (i.e., ergonomic and microclimate) in industrial environments is often constrained by production and energy requirements. In the food processing industry, for example, the safety of perishable products dictates storage temperatures that do not allow for operator comfort. Conversely, warehouses dedicated to non-perishable products often lack cooling systems to limit energy expenditure, reaching high temperatures in the summer period. Moreover, exceptional events, like the COVID-19 pandemic, introduce new constraints, with recommendations impacting thermal stress and respiratory health. Furthermore, the thesis highlights how workers' variables, particularly the aging process, reduce tolerance to environmental stresses. Consequently, prolonged exposure to environmental stress conditions at work results in cardiovascular disease and musculoskeletal disorders. In response to the global trend of an aging workforce, the thesis bridges a literature gap by proposing methods and models that integrate the age factor into comfort assessment. It aims to present technical and technological solutions to mitigate microclimate risks in industrial environments, ultimately seeking innovative ways to enhance the aging workforce's comfort, performance, experience, and skills. The research outlines a logical-conceptual scheme with three main areas of focus: analyzing factors influencing the work environment, recognizing constraints to worker comfort, and designing solutions. The results significantly contribute to science by laying the foundation for new research in worker health and safety in an ageing working population's extremely current industrial context.

Constraint Programming-based Job Dispatching for Modern HPC Applications

A High-Performance Computing job dispatcher is a critical software that assigns the finite computing resources to submitted jobs. This resource assignment over time is known as the on-line job dispatching problem in HPC systems. The fact the problem is on-line means that solutions must be computed in real-time, and their required time cannot exceed some threshold to do not affect the normal system functioning. In addition, a job dispatcher must deal with a lot of uncertainty: submission times, the number of requested resources, and duration of jobs. Heuristic-based techniques have been broadly used in HPC systems, at the cost of achieving (sub-)optimal solutions in a short time. However, the scheduling and resource allocation components are separated, thus generates a decoupled decision that may cause a performance loss. Optimization-based techniques are less used for this problem, although they can significantly improve the performance of HPC systems at the expense of higher computation time. Nowadays, HPC systems are being used for modern applications, such as big data analytics and predictive model building, that employ, in general, many short jobs. However, this information is unknown at dispatching time, and job dispatchers need to process large numbers of them quickly while ensuring high Quality-of-Service (QoS) levels. Constraint Programming (CP) has been shown to be an effective approach to tackle job dispatching problems. However, state-of-the-art CP-based job dispatchers are unable to satisfy the challenges of on-line dispatching, such as generate dispatching decisions in a brief period and integrate current and past information of the housing system. Given the previous reasons, we propose CP-based dispatchers that are more suitable for HPC systems running modern applications, generating on-line dispatching decisions in a proper time and are able to make effective use of job duration predictions to improve QoS levels, especially for workloads dominated by short jobs.