Quality & Quantity

Journal Information
ISSN / EISSN: 00335177 / 15737845
Published by: Springer Nature
Total articles ≅ 3,723

Latest articles in this journal

Published: 5 February 2023
Quality & Quantity pp 1-12; https://doi.org/10.1007/s11135-023-01616-9

We study a fixed duration pursuit-evasion differential game problem of one pursuer and one evader with Grönwall-type constraints (recently introduced in the work of Samatov et al. (Ural Math J 6:95–107, 2020b)) imposed on all players’ control functions. The players’ dynamics are governed by a generalized dynamic equation. The payoff is the greatest lower bound of the distances between the evader and the pursuers when the game is terminated. The pursuers’ goal, which contradicts that of the evader, is to minimize the payoff. We obtained sufficient conditions for completion of pursuit and evasion as well. To this end, players’ attainability domain and optimal strategies are constructed.
Published: 30 January 2023
Quality & Quantity pp 1-19; https://doi.org/10.1007/s11135-023-01612-z

The COVID-19 pandemic manifested around the World since February 2020, leading to disruptive effects on many aspects of people social life. The suspension of face-to-face teaching activities in schools and universities was the first containment measure adopted by the Governments to deal with the spread of the virus. Remote teaching has been the emergency solution implemented by schools and universities to limit the damages of schools and universities closure to students’ learning. In this contribution we intend to suggest to policy makers and researchers how to assess the impact of emergency policies on remote learning in academia by analysing students’ careers. In particular, we exploit the quasi-experimental setting arising from the sudden implementation of remote teaching in the second semester of academic year 2019/2020: we compare the performance of the cohort 2019/2020, which represents the treatment group, with the performance of the cohort 2018/2019, which represents the control group. We distinguish the impact of remote teaching at two levels: degree program and single courses within a degree program. We suggest to use Difference-In-Differences approach in the former case and multilevel modeling in the latter one. The proposal is illustrated analysing administrative data referred to freshmen of cohorts 2018/2019 and 2019/2020 for a sample of degree programs of the University of Florence (Italy).
Published: 27 January 2023
Quality & Quantity pp 1-41; https://doi.org/10.1007/s11135-023-01615-w

All social media platforms can be used to conduct social science research, but Twitter is the most popular as it provides its data via several Application Programming Interfaces, which allows qualitative and quantitative research to be conducted with its members. As Twitter is a huge universe, both in number of users and amount of data, sampling is generally required when using it for research purposes. Researchers only recently began to question whether tweet-level sampling—in which the tweet is the sampling unit—should be replaced by user-level sampling—in which the user is the sampling unit. The major rationale for this shift is that tweet-level sampling does not consider the fact that some core discussants on Twitter are much more active tweeters than other less active users, thus causing a sample biased towards the more active users. The knowledge on how to select representative samples of users in the Twitterverse is still insufficient despite its relevance for reliable and valid research outcomes. This paper contributes to this topic by presenting a systematic quantitative literature review of sampling plans designed and executed in the context of social science research in Twitter, including: (1) the definition of the target populations, (2) the sampling frames used to support sample selection, (3) the sampling methods used to obtain samples of Twitter users, (4) how data is collected from Twitter users, (5) the size of the samples, and (6) how research validity is addressed. This review can be a methodological guide for professionals and academics who want to conduct social science research involving Twitter users and the Twitterverse.
Published: 27 January 2023
Quality & Quantity pp 1-20; https://doi.org/10.1007/s11135-023-01613-y

A key point to assess the applications of machine learning models in Artificial Intelligence (AI) is the evaluation of their predictive accuracy. This because the “automatic” choice of an action crucially depends on the made prediction. While the best model in terms of fit to the observed data can be chosen using a “universal” - and therefore automatable - criterion, based on the models’ likelihood, such as AIC and BIC, this is not the case for the best model in terms of predictive accuracy. To fill the gap, we propose a Rank Graduation Accuracy (RGA) measure which evaluates the concordance between the ranks of the predicted values and the ranks of the actual values of a series of observations to be predicted. We apply the RGA to a use-case that concerns the measurement of the financial risks that arise from crypto assets. The RGA appears as a “universal” alternative predictive model selection criterion that, differently from standard measures, such as the Root Mean Squared Error, is robust to the presence of outlying observations.
Published: 23 January 2023
Quality & Quantity pp 1-17; https://doi.org/10.1007/s11135-022-01594-4

This experimental study aims to check and improve the quality of 16 established survey measures of political solidarities and related concepts, such as redistribution and social trust. Political solidarities are defined as one’s willingness to share the costs that result from public redistribution that favours people other than oneself and thus constitute a subset of welfare state attitudes. The pre-registered study plan included suggestions for the development of improved rating scales, which we defined as five-point, end verbalized rating scales without non-substantive answer options. The overall results from an experimental online survey in Germany indicate differences in response effort in terms of response times but almost no differences in data quality in terms of criterion validity. Thus, the 16 survey measures show solid instrument validity as well as minor improvements in respondents’ response times. Indeed, the measures are (at least) in the online survey world of Germany of high-quality and warrant inclusion in future surveys with small efficiency gains still attainable.
Published: 17 January 2023
Quality & Quantity pp 1-27; https://doi.org/10.1007/s11135-022-01574-8

Construction projects are complex endeavors where achieving higher quality standards is challenging due to the intrinsic difficulties and dynamic quality management processes. Several quality management techniques exist to overcome quality concerns, such as the cost of quality (COQ). However, implementing COQ in building construction is challenging due to the absence of a comprehensive quality cost-capturing system. Several studies have tried to quantify different quality costs but are mainly focused on visible failure cost—the tip of the iceberg while the base of the iceberg has rarely been explored. This study develops and quantifies each component of the visible and hidden quality costs—the base of the iceberg. Accordingly, a modified prevention, appraisal, and failure model is developed and applied to the primary data of 25 building projects. The findings highlight the unfamiliarity and passive attitude of the involved construction firms towards quality, thus, incurring higher failure costs amounting to over 12% of the total project cost. Most of this cost remains hidden as traditional accounting systems cannot capture it. Such costs must be eliminated by implementing COQ systems as utilized in the current study. Further, a quality costing framework is established for building projects and applied to the local construction industry to reduce construction failures and improve the quality performance of building projects.
Published: 16 January 2023
Quality & Quantity pp 1-22; https://doi.org/10.1007/s11135-022-01609-0

This paper employs bibliometric analysis to determine the scientific landscape of the influence of social transfers on female labor supply. We determine the scale and scope of the subject, as well as interconnections between various research fields, utilizing the Scopus database. The most significant areas of the research landscape are (i) labor, (ii) socioeconomics, and (iii) maternity, with multiple and complex connections between and among them. However, these areas are specific within given countries, and there is little collaboration between countries and researchers. This implies that the current state of research may not be sufficient to explain how, in fact, cash transfers affect human behavior in case of women’s labor. It is important for policymakers, particularly those governing non-homogeneous structures, such as the European Union, to avoid generalizing conclusions on the success or failure of a given policy in a given country. Research results demonstrate that the large scientific landscape investigated is divided into clusters which encompass ideas that are strongly interconnected outside their clusters. Nevertheless, the degree of collaboration between authors from different countries is low. A map of keywords reveals that certain aspects of the landscape may be associated only with a specific country or group of countries.
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