The impact of public research expenditure on agricultural productivity: evidence from developed European countries

The objective of this paper is to assess the impact of public research expenditure on agricultural productivity in developed European countries. Our research provides original evidence, making possible a comparison with existing studies focused on United States of America (USA). We apply a fixed effects Gamma distributed-lag model to yearly data in 1970-2016 sourced from the United States Department of Agriculture (USDA), the Organisation for Economic Cooperation and Development (OECD), and the Food and Agriculture Organization (FAO). In our results, public research expenditure has a significant impact on agricultural productivity up to 35 years, with peak at 17 years and long-term elasticity equal to 0.172. Based on our model, the countries with the highest internal rate of return of agricultural research expenditure resulted Germany, Spain, France and Italy (24.5-25.2%), followed by Netherlands, United Kingdom, Denmark, Greece, Belgium and Luxembourg (20.5-21.8%). However, only Germany, Denmark and Greece increased agricultural research expenditure in recent years. The estimated internal rates of return are in line with the ones reported by existing studies on USA, and they suggest that developed European countries, just like USA, could benefit from research investments in Agriculture to a much greater extent than they currently do.

Decomposing tourists’ sentiment from raw NL text to assess customer satisfaction

The importance of the Word of Mouth is growing day by day in many topics. This phenomenon is evident in everyday life, e.g., the rise of influencers and social media managers. If more people positively debate specific products, then even more people are encouraged to buy them and vice versa. This effect is directly affected by the relationship between the potential customer and the reviewer. Moreover, considering the negative reporting bias is evident in how the Word of Mouth analysis is of absolute interest in many fields. We propose an algorithm to extract the sentiment from a natural language text corpus. The combined approach of Neural Networks, with high predictive power but more challenging interpretation, with more simple but informative models, allows us to quantify a sentiment with a numeric value and to predict if a sentence has a positive (negative) sentiment. The assessment of an objective quantity improves the interpretation of the results in many fields. For example, it is possible to identify crucial specific sectors that require intervention, improving the company's services whilst finding the strengths of the company himself (useful for advertising campaigns). Moreover, considering that the time information is usually available in textual data with a web origin, to analyze trends on macro/micro topics. After showing how to properly reduce the dimensionality of the textual data with a data-cleaning phase, we show how to combine: WordEmbedding, K-Means clustering, SentiWordNet, and the Threshold-based Naïve Bayes classifier. We apply this method to Booking.com and TripAdvisor.com data, analyzing the sentiment of people who discuss a particular issue, providing an example of customer satisfaction.

Multipoint vs slider: a protocol for experiments

Since the broad diffusion of Computer-Assisted survey tools (i.e. web surveys), a lively debate about innovative scales of measure arose among social scientists and practitioners. Implications are relevant for applied Statistics and evaluation research since while traditional scales collect ordinal observations, data from sliders can be interpreted as continuous. Literature, however, report excessive times of completion of the task from sliders in web surveys. This experimental protocol is aimed at testing hypotheses on the accuracy in prediction and dispersion of estimates from anonymous participants who are recruited online and randomly assigned into tasks in recognition of shades of colour. The treatment variable is two scales: a traditional multipoint 0-10 multipoint vs a slider 0-100. Shades have a unique parametrisation (true value) and participants have to guess the true value through the scale. These tasks are designed to recreate situations of uncertainty among participants while minimizing the subjective component of a perceptual assessment and maximizing information about scale-driven differences and biases. We propose to test statistical differences in the treatment variable: (i) mean absolute error from the true value (ii), time of completion of the task. To correct biases due to the variance in the number of completed tasks among participants, data about participants can be collected through both pre-tasks acceptance of web cookies and post-tasks explicit questions.

A bibliometric study of global research activity in relation to the use of partial least squares for policy evaluation

Structural equation modeling (SEM), especially partial least squares path modeling (PLS-PM) has become a mainstream method in many fields of research. In the last years it has been increasingly disseminated in a variety of disciplines. The researchers have been promoting this new statistical methods for the evaluation of policies. Generally, policy evaluation applies evaluation principles and methods to examine the content, implementation or impact of a policy. To better understand and characterize this trend, a bibliometric study of international papers on this subject has been developed in order to describe the use of SEM and PLS-PM approaches in the policy evaluation in the almost last 20 years. A total of 450 articles from 2000 to 2020 have been selected and analyzed in order to discover the research trends in this field and the main dimensions and words related to the terms “decision making” and “SEM-PLS” approach, that are most commonly employed in the scientific literature. The research has been conducted in theWeb of Science from ISI Web of Knowledge database and Scopus database, with the aim of identifying the major themes, authors, areas, types of the sources, titles, years of publication and countries of these publications, as well as the main themes related to the two topic analyzed

Thematic atlas of Italian oncological research: the analysis of public IRCCS

This paper has been developed in the frame of the research project “V:ALERE 2019” focused on Italian public-owned Academic Medical Centers. The main aim of the project is to provide evidence, advice, and remarks to help the agents of the public health system to address the many challenges that they face. In recent years, there is an increasing recognition of the potential value of research evidence as one of the many factors considered by policymakers and practitioners. Even more, in the case of medical science, the analysis of research and its impact is indispensable, in light of its implications for public health. The starting point for mapping a research area is to review the related scientific literature because by synthesizing past research findings, it is possible to effectively use the existing knowledge base and advance lines of future researches. In this sense, bibliometrics becomes useful, by providing a structured analysis to a large body of information, to infer trends over time, themes researched, and to show the “big picture” of extant research. In particular, in this work, we focus our attention on the scientific production of the last 20 years of the Scientific Institutes for Research, Hospitalization, and Healthcare (IRCCS “Istituto di Ricovero e Cura a Carattere Scientifico”) specialized in the oncology research. IRCCS are biomedical institutions of relevant national interest that drive clinical assistance in strong relation to research activities. They are committed to being a benchmark for the whole public health system for both the quality of patient care and the innovation skills in the field of the organization. All the analyses were carried out by using the Bibliometrix, an open-source tool for quantitative research in scientometrics and bibliometrics that includes all the main bibliometric methods of analysis.

Frameworks and inequalities in healthcare: some applications

Background Social determinants of health (SDOH) have increasingly entered health policy conversations as a growing body of researches, reveal the direct relationship between social determinants and health outcome. In fact, the recent literature is moving from the traditional model that focus on how health affects economic status, to a new view that economic status affects health. Objectives To investigate the principal conceptual frameworks for action on social determinants of health. Another aim is to contribute on the ongoing discourse on feasible measures which could be used to alert regions to inequalities in the distribution of health. Methodology, Italian data are used as a demonstration. Quadrant charts illustrate associations between how much regions spend on health and how effectively health system functions. The relevant inequality measures are used to rank health inequalities. Main results Frameworks have been presented to help communities, health professionals and others begin to better understand and address a variety of factors that affects health. Quadrant analysis technique shows the extent to which spending more on health, translates into better health outcomes, higher quality of care and improve access to care across the Italian regions, whilst also recognition the importance of major risk factors. Conclusions The social inequalities in health and what this means for how we understand and reduce them, as not to date been compressively examined empirically. There is an urgent need to expand our knowledge with comparable data on health determinants and more refined health outcomes. Furthermore, there is a need for feasible inequality measures in the health information systems. The measures used in this study, provide a step to inform and guide the uptake of equity-sensitive policies.

Wine preferences based on intrinsic attributes: A tasting experiment in Alto Adige/Südtirol province

Different methods have been developed by researchers in modelling wine consumers purchase behaviour. The quality of a food product is described by a set of characteristics ascribable to the intrinsic and extrinsic product attributes (Olson and Jacoby, 1972). Price, brand, region of origin, grapes and gained awards are the key extrinsic attributes and physical characteristics of the wine such as taste and flavour are intrinsic attributes. This paper addresses the problem of measuring the intrinsic attributes that characterise the wine, based on specific characteristics and the impact on consumers in terms of preferences. To this end, a fractional factorial experiment held on a selection of white wines of the Alto Adige/Südtirol province in Italy. The sensorial experiment involved a voluntary sample of 33 mild wine consumers and concerned 6 grape varieties typical of that territory. For each variety, two producing cellars were selected for a total of 12 evaluated wines. The experiment followed a double-blind administration procedure to the sample and a paper questionnaire was used to elicit the consumers’ opinions on the tasted wines. The results show that intrinsic attributes, such as taste-olfactory intensity, harmony and olfactory complexity, are the drivers used in combination by consumers to rank wines in order of preference.

Measuring logical competences and soft skills when enrolling in a university degree course

Logical abilities are a ubiquitous ingredient in all those contexts that take into account soft skills, argumentative skills or critical thinking. However, the relationship between logical models and the enhancement of these abilities is rarely explicitly considered. Two aspects of the issue are particularly critical in our opinion, namely: (i) the lack of statistically relevant data concerning these competences; (ii) the absence of reliable indices that might be used to measure and detect the possession of abilities underlying the above-mentioned soft skills. This paper aims to address both aspects of this topic by presenting the results of a research we conducted in the period October – December 2020 on students enrolled in various degree courses at the University of Florence. To the best of our knowledge, to date this is the largest available database on the subject in the Italian University System. It has been obtained by a three-stage initiative. We started from an “entrance” examination for assessing the students' initial abilities. This test comprised ten questions, each of which was centered on a specific reasoning construct. The results we have collected show that there is a widespread lack of understanding of basic patterns that are common in the everyday way of arguing. Students then underwent a short training course, using formal logic techniques in order to strengthen their abilities, and afterwards took an “exit” examination, replicating the structure and the questions difficulty of the entrance one in order to evaluate the effectiveness of the course. Results show that the training was beneficial.

Short-term and long-term international scientific mobility of Italian PhDs: An analysis by gender

In the last years, there has been a large increase in high-educated and high-skilled people’s mobility as a consequence of the internationalization and globalization, the weakening of research and university systems of sending countries (the “brain drain” process), the increase in skilled demand and improvements in higher education of host countries (the “brain gain” process). At the micro-level, academic mobility has positive consequences on occupational prospects and careers of researchers, both in the short- and long- run. Nevertheless, numerous research studies have demonstrated the challenges of engaging in international academic mobility for people with caring responsibilities, particularly women. Using Italian data on occupational conditions of PhDs collected in 2018 by Istat and modelling multinomial logistic regression analyses, we intend to verify if female researchers are associated with a lower international mobility irrespective their field of study, and the extent to which gender interacts differently in the various fields of study in affecting the probability of moving abroad after PhD qualification. Also, the distinction between long-term and short-term mobility, which has been mainly neglected in the literature concentrating on longer stays, has taken into account. In this respect, short-term mobility is a potentially high-value investment that may be pursued also by those researchers and scientists who cannot move for longer periods, such as women with caring responsibilities. In the literature, it is acknowledged that an experience abroad during early career may have positive effects on future occupational prospects. With our work, we intend to shed light on potential disparities on moving abroad that may exist among researchers in their early career by gender, and which could contribute to leave behind women in academia.

Innovation and sustainability: the Italian scenario

Society and policy makers demand innovation systems oriented towards several goals of sustainable development. Therefore, recent literature has dedicated a growing interest to both innovation and sustainability in the pursuit of environmental, economic and social development; in addition, the emerging topic of ‘sustainable innovation’ (and ‘eco-innovation’) seems to combine the main features of them. The definition of these concepts has been significantly changed during the last decades, and a broad discussion continues today about which indicators should be used to measure innovation, sustainability and their combination. The current paper investigates this relationship, and - in the authors’ opinion - the research question connected to the impact of the innovative product (and service and process) solutions on sustainability can be addressed by means of a stable theoretical framework. To study the interaction between innovation and sustainability, the usage of specific territorial features might represent a useful perspective to manage short-and long-term environmental and economic issues. As for the theoretical model, the present article considers a specific technique suitable for investigating the entire set of characteristics involved in the model. From a public makers and managerial point of view, the possibility of improving the firm’ efficiencies in terms of several dimensions of sustainable innovation represents a relevant topic that must be encouraged.