Technological change and technology monitoring process: Evidence from four Italian case studies

Technology monitoring (TM) may take on different meanings in a company’s day-to-day activities. In some cases it can be interpreted as a technology intelligence methodology, while in others it is understood as technology forecasting or even as technology assessment. These different interpretations are confirmed by an analysis of the literature. This case study examines the technology monitoring process in four Italian companies.For each of the cases considered, first we analysed the way technology monitoring is carried out and then we tried to understand what factors influence the company approach to technology monitoring. Four factors that can be expected to influence a company’s technology monitoring approach came out of this empirical research study: the industry a company operates in, the business model it uses, the importance of technology in the corporate culture, and the level of its R&D resources.     

University Quality and Labour Market Outcomes in Italy

Abstract. This paper uses proxies for university quality derived from Performance Indicators to evaluate the impact of university quality on the early labour market outcome of a cohort of recent Italian graduates. Institutional research quality is found to have a negative effect on the probability that both male and female graduates will be overeducated. Additionally, research inputs are positively related to men's wages. In contrast, teaching quality does not appear to enhance students’ economic success.     

The need to improve communication about scope changes: frustration as an indicator of operational inefficiencies

Early and timely sharing of information can provide a sustainable competitive advantage. However, even if lean information management aims to improve this information flow, it has mainly been investigated in ‘operations-based’ companies. This paper fills this gap, drawing upon the experience of the authors working within a large project-based company engaged in the ‘engineer and manufacture to order’ of a complex piece of equipment costing millions of dollars, for its strategic long-term client, both working in the same industrial field, i.e. nuclear decommissioning. This research investigates the information flow regarding scope changes between the project-based company and the long-term client adapting and applying a five-step framework to highlight operational inefficiencies, reduce the corresponding transaction costs and increase the overall company’s competitiveness. This is exemplified through a particular case, but can be applied to other project-based companies dealing with strategic clients involved in long-term relationships.     

What fuels the fire: Job- or task-specific motivation (or both)? On the hierarchical and multidimensional nature of teacher motivation in relation to job burnout

Drawing on a hierarchical (job and task level) and multidimensional conceptualisation of work motivation (intrinsic, identified, introjected, and external regulations), this study examines relationships between motivational regulations and burnout. Participants were 806 French-Canadian teachers working in public elementary and high schools. Results reveal different associations between burnout and the regulations that drive teachers to engage in their overall job or in specific tasks: autonomous regulations (intrinsic and identified) are negatively associated with burnout but more negatively at the job than task level, whereas controlled regulations (introjected and external) are positively associated with burnout but more positively at the task than job level. This study provides valuable insights into how teachers’ motivations towards both the job and tasks can foster or prevent burnout symptoms. Implications for theory and research on burnout and work motivation are discussed.     

A multi-user tool for enhancing the daily replanning and control of visits in home care services

The uncertainty associated with patients’ demands and operators’ availabilities is the main complexity factor in planning health care activities. Thus, activity replanning is required to react to the variations and to guarantee a good service quality. A particularly complex replanning activity is required in Home Care (HC) services, where any variation to the plans involves several decisions related, e.g. to nurses’ travels. Such complexity makes impossible for planners to integrate and to effectively handle all of the information in real time with the classical HC management tools. In this work, we design, implement and validate a new visualisation tool to support HC planners in handling the data, to better perform their replanning activities. The tool consists of a desk equipped with an interactive map, where up to four planners can manage the information together in a multilayer configuration. This solution allows to manage the high amount of data in a more effective and natural way than the tabular form of the current commercial tools, due to both the horizontal map visualisation and the multilayer information provisioning. The prototype has been tested with real HC planners and expert users; outcomes show the capability to meet the gap between planners and information complexity, and to provide adequate support for replanning HC activities.     

E-Coaching: Prozess- und Ergebnisevaluation des„Virtuellen Zielerreichungscoachings“

The authors present the design and first results of an ongoing research project. The main emphasis of the research lies on observable and mental processes of the coach and the coachee in and between coaching sessions as well as for the coachee after the coaching. The research is based on a particular e-coaching format named “virtual goal attainment coaching”, consisting of telephone-based coaching sessions combined with by internet mediated questions that the coachee answers with support of the coach. The ambition of this particular type of coaching, since based on empirical findings of coaching success factors and combined with modern media, is to generate excellent results within a short amount of time. Preliminary findings confirm the efficiency and effectiveness of this blended coaching program.     

Factors Motivating Individuals to Take Precautionary Action for an Expected Earthquake in Istanbul

Istanbul is expected to experience an earthquake in the near future, but individuals show limited interest in preparing for it. This study aims to identify the factors associated with taking action to prepare for an earthquake and mitigate its effects at the individual level. A field survey was carried out in 2007 in two districts of Istanbul with different levels of earthquake risk. Within these districts, three socioeconomic levels were considered. A total of 1,123 people were interviewed face to face. Analysis indicated that the educational level of the respondents was the leading factor associated with taking at least three measures, followed by living in a higher earthquake risk area, having participated in rescue and solidarity activities in previous earthquakes, a higher level of knowledge about earthquakes, home ownership, a higher score for action‐stimulating attitudes, being younger, and a higher general safety score, in that order. The findings pointed to the role of knowledge about earthquakes and possible mitigation/preparedness measures, and thus the importance of developing effective awareness programs. Such programs should also consider the characteristics of different groups in the population. Motivated individuals, such as those who have participated in rescue and solidarity activities in previous earthquakes, could be involved in reaching other people.     

From Linear to Semidefinite Programming: An Algorithm to Obtain Semidefinite Relaxations for Bivalent Quadratic Problems

In this paper, we present a simple algorithm to obtain mechanically SDP relaxations for any quadratic or linear program with bivalent variables, starting from an existing linear relaxation of the considered combinatorial problem. A significant advantage of our approach is that we obtain an improvement on the linear relaxation we start from. Moreover, we can take into account all the existing theoretical and practical experience accumulated in the linear approach. After presenting the rules to treat each type of constraint, we describe our algorithm, and then apply it to obtain semidefinite relaxations for three classical combinatorial problems: the K-CLUSTER problem, the Quadratic Assignment Problem, and the Constrained-Memory Allocation Problem. We show that we obtain better SDP relaxations than the previous ones, and we report computational experiments for the three problems.     

Quantitative Risk Assessment of Haemolytic and Uremic Syndrome Linked to O157:H7 and Non‐O157:H7 Shiga‐Toxin Producing Escherichia coli Strains in Raw Milk Soft Cheeses

Shiga‐toxin producing Escherichia coli (STEC) strains may cause human infections ranging from simple diarrhea to Haemolytic Uremic Syndrome (HUS). The five main pathogenic serotypes of STEC (MPS‐STEC) identified thus far in Europe are O157:H7, O26:H11, O103:H2, O111:H8, and O145:H28. Because STEC strains can survive or grow during cheese making, particularly in soft cheeses, a stochastic quantitative microbial risk assessment model was developed to assess the risk of HUS associated with the five MPS‐STEC in raw milk soft cheeses. A baseline scenario represents a theoretical worst‐case scenario where no intervention was considered throughout the farm‐to‐fork continuum. The risk level assessed with this baseline scenario is the risk‐based level. The impact of seven preharvest scenarios (vaccines, probiotic, milk farm sorting) on the risk‐based level was expressed in terms of risk reduction. Impact of the preharvest intervention ranges from 76% to 98% of risk reduction with highest values predicted with scenarios combining a decrease of the number of cow shedding STEC and of the STEC concentration in feces. The impact of postharvest interventions on the risk‐based level was also tested by applying five microbiological criteria (MC) at the end of ripening. The five MCs differ in terms of sample size, the number of samples that may yield a value larger than the microbiological limit, and the analysis methods. The risk reduction predicted varies from 25% to 96% by applying MCs without preharvest interventions and from 1% to 96% with combination of pre‐ and postharvest interventions.