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The changes that are constantly occurring in the labour sector have led organisations and companies to move towards digital transformation. This process was accelerated by the COVID-19 pandemic and conducted to a massive recourse to the practice of remote working, which in this study is understood as the term for the way of performing work outside the usual workplace and with the support of ICT. Currently, there are no flexible scales in the literature that allow measuring the benefits and disadvantages of remote working with a single instrument. Thus, the distinction between the positive and negative consequences of working remotely, substantiated by a solid literature, provides a framework for a systematical understanding of the issue. The aim of the present study is to develop and validate a scale on remote working benefits and disadvantages (RW-B&D scale). For this end, a preliminary Exploratory Factor Analysis (EFA) with 304 participants, a tailored EFA with a sample of 301 workers and a Confirmatory Factor Analysis (CFA) with 677 workers were conducted. Participants were all Italian employees who worked remotely during the period of the COVID-19 health emergency. Data were collected between October 2020 and April 2021. The psychometric robustness of the model was assessed through bootstrap validation (5000 resamples), fit indices testing and measurement of factorial invariance. The statistical analyses demonstrated the bifactorial nature of the scale, supporting the research hypothesis. The model showed good fit indices, bootstrap validation reported statistically significant saturations, good reliability indices, and convergent and discriminant validity. Measurement invariance was tested for gender and organisational sector. The results suggested that the novel scale facilitates the quantitative measurement of the benefits and disadvantages associated with remote working in empirical terms. For this reason, it could be a streamlined and psychometrically valid instrument to identify the potential difficulties arising from remote working and, at the same time, the positive aspects that can be implemented to improve organisational well-being.

The topic of community resilience attracts as much academic research as it does social media. Understanding the drivers of change and community adaptation in the face of critical events is a key clue to governance actions and local measures. However, both academia and the media often provide partial definitions of community resilience. Beginning with an integration of theory-driven and data-driven knowledge, the study aims to uncover and operationalize the building blocks of community resilience potential within a measurement tool. An assessment study, conducted on 1278 participants from diverse communities statistically supported a broad, inclusive model: Community Resilience Potential is composed of four main constituents (social capital, community competence, structural-functional potential, socio-economic potential). The Confirmatory Composite Analysis formalized for Partial Least-Squares Structural Equation Modeling revealed its good psychometric properties and measurement invariance. Although the study has limitations, it provides researchers with a valuable, theoretically grounded, widely-applicable tool for the investigation of the community resilience potential.

This study examined the factor structure and model specifications of the Interaction Anxiousness Scale (IAS) with confirmatory composite analysis (CCA) using partial least squares-structural equation modeling (PLS-SEM) with a sample of Italian adolescents ($$n = 764$$ n = 764 ). The CCA and PLS-SEM results identified the reflective nature of the IAS sub-scale scores, supporting an alternative measurement model of the IAS scores as a second-order reflective–reflective model.

Background According to more recent approaches on problematic internet use (PIU), using the internet can be seen as a way of compensating for psychosocial malaise. Taking semiotic cultural psychology theory as its theoretical framework, this study examines the role of affect-laden assumptions concerning the world, known as latent dimensions of sense (LDSs), in promoting (or not) adaptive responses, including internet use as a maladaptive strategy against problems and difficulties. Aims To test a theoretical model in which PIU is predicted by LDSs through the mediation of high levels of psychosocial malaise. Method We measured PIU (using the Generalized Problematic Internet Use Scale 2), LDSs (View of Context questionnaire), negative affect (Positive and Negative Affect Schedule), social anxiety (Interaction Anxiousness Scale) and loneliness (Italian Loneliness Scale) in 764 Italian adolescents (mean age 15.05 years, s.d. = 1.152 years). LDSs were detected using a multiple correspondence analysis; after confirmatory composite analysis, partial least squares structural equation modelling with higher-order components was performed to test the mediation model. Results The results show a relationship between LDSs corresponding to an extreme negative evaluation of the sociocultural context, experienced as absolutely unreliable, and PIU through the mediation of psychosocial malaise (95% CI 0.101– 0.171; P = 0.000). Conclusions Overall, the findings suggest that PIU might be a way of compensating for unpleasant states in a context perceived in an extremely negative and homogenising way, i.e. as totally lacking resources and trustworthy people.

The structure of knowledge about Structural Equation Modelling (SEM) based on the Partial Least Squares (PLS) estimator has been analysed by systematic and reproducible bibliometric citation analysis. This contribution aims to create a dynamic picture of the PLS-SEM research activity to support scholars with an enhanced understanding of the history, the present and the future directions of this fascinating modelling approach. Analysis was conducted using the Bibliometrix packageR with documents extracted (n = 3,854) from the Web of Science (WoS) database by Clarivate. Hence, we find seminal papers in the context of PLS-SEM as well as the diffusion and use in different research domains, suggesting new directions of applications. We also identify the collaboration networks involving authors and countries to highlight the new potential for cooperation from a co-authorship and international project standpoint. Furthermore, the dynamics of the sources indicate the interest of journals in this field in a dissemination role, which can assist authors in selecting a suitable publisher. Finally, the historiographic overview shows the dominant topics and the possible evolution in the citation analysis from the theoretical and application angles.

A single acceptance sampling plan for the three-parameter Lindley distribution under a truncated life test is developed. For various consumer’s confidence levels, acceptance numbers, and values of the ratio of the experimental time to the specified average lifetime, the minimum sample size important to assert a certain average lifetime are calculated. The operating characteristic (OC) function values as well as the associated producer’s risks are also provided. A numerical example is presented to illustrate the suggested acceptance sampling plans.

Applications of partial least squares structural equation modelling (PLS-SEM) often draw on survey data. While researchers go to great lengths to document reliability and validity statistics that support the generalisability of their findings, they often overlook or ignore a more fundamental issue related to data analysis—the representativeness of their sample. Addressing this concern, the present paper offers guidelines for using the weighted PLS-SEM (WPLS-SEM) algorithm to apply sampling weights in the model estimation. The results of the WPLS algorithm and the traditional PLS algorithm are then compared using a marketing research model. The findings show that researchers should routinely consider the procedure of the WPLS algorithm when using the PLS technique for assessment. The WPLS algorithm is a useful and practical approach for achieving better average population estimates in situations where researchers have a set of appropriate weights. This paper substantiates the use of the WPLS algorithm and provides business researchers and practitioners with the proper guidelines to assess, report, and interpret PLS-SEM results. It also illustrates that the use of the WPLS algorithm produces different inference test results in the structural model and different predictive relevance results. Thus, the study contributes to the advancement of PLS-SEM applications.

Many data science competitions occur in the context of soccer match prediction. The Kaggle European Soccer (KES) database, one of the biggest soccer datasets available on Kaggle, includes information about soccer players and matches from season 2009 to 2015 in 10 different European countries. For what concerns players’ performance indicators, sofifa experts’ of Electronic Arts Sports are considered the leading authority: they state that specific abilities make up broader dimensions, each of which reflects a more general performance ability. In other words, players’ performance attibutes (variables) of the KES database can be summarized into fewer performance composite indicators, useful for predictive modeling. Assuming experts’ classifications solidity, Carpita et al. (Stat Model 19(1):74–101, 2019c) recently underlined the importance of variables transformation and information about players’ role in building these indicators. However, previous works focused on clustering matches rather than players’ attributes (e.g., investigating the role of seasonality in successful vs dropping performance; Wibowo in Commun Sci Technol 1(1), 2016), thus leaving the statistical examination of experts’ groupings a still unexplored territory. The present work aims at shedding light on this aspect through the Cluster of variables around Latent Variables approach: this clustering method makes latent components simultaneously shine from variable groupings. This procedure might finetune the recently developed role-based players’ performance indicators and improve predictive modeling of match outcomes.

We propose a new method to combine adaptive processes with a class of entropy estimators for the case of streams of data. Starting from a first estimation obtained from a batch of initial data, model parameters are estimated at each step by combining the prior knowledge with the new observation (or a block of observations). This allows to extend the maximum entropy technique to a dynamical setting, also distinguishing between entropic contributions of the signal and the error. Furthermore, it provides a suitable approximation of standard GME problems when the exacted solutions are hard to evaluate. We test this method by performing numerical simulations at various sample sizes and batch dimensions. Moreover, we extend this analysis exploring intermediate cases between streaming GCE and standard GCE, i.e. considering blocks of observations of different sizes to update the estimates, and incorporating collinearity effects as well. The role of time in the balance between entropic contributions of signal and errors is further explored considering a variation of the Streaming GCE algorithm, namely, Weighted Streaming GCE. Finally, we discuss the results: in particular, we highlight the main characteristics of this method, the range of application, and future perspectives., Comment: 22 pages, 11 figures

This work focuses on consumer evaluation of bluefish products in terms of three distinguished investigation macro-dimensions: Consumer habits, Bluefish Perception, New Product Propensity. We analyse data to extract the contributions of variables in these macro-dimensions and discuss the phenomena of uncertainty and factor indeterminacy in their relevance as drivers of consumers' decisions.

Excessive daytime sleepiness is a frequent condition among children and adolescents that may lead to several and significant daytime consequences, including impaired neurocognitive skills and scholastic performance. Here, we evaluated in one hundred and ninety-one unselected primary school children, the relationship between sleepiness and a wide range of cognitive and academic skills through a standardized neuropsychological test battery. In order to assess the statistical relationship, we performed a partial least squares path modelling, a non-parametrical approach which combined a model of paths between latent variables and the coefficients between indicators and dimensions. Results were validated through the bootstrap approach and suggest that sleepiness is not associated with all cognitive and scholastic abilities, but only with those relying on verbal abilities and complex cognitive functions (i.e., reading comprehension, oral/syntactic comprehension, spelling, and mathematic skills). Our data suggest the idea that sleepiness in children is associated mostly with "higher" (mainly verbal) cognitive function(s), while the visuospatial domain was not affected.

In this paper, data concerning MILANO EXPO2015 is collected from the official twitter page of the event before and after its opening. In order to extract a semi-supervised ontology and to evaluate the global sentiment around the event, a variety of language processing techniques has been applied on the collected “tweets”: Latent Semantic Analysis, sentiment polarity tracking, along with gap analysis has allowed the semantic evaluation of users’ opinions. Moreover, the generalized cross entropy approach has been applied for the first time on web data, adding prior information on the effect of semantic classes on the global sentiment, improving accuracy and adding detail to the analysis.

Purpose Lifetime data are used in many different applied sciences, like biomedicine, engineering, insurance and finance and others. The purpose of this paper is to develop a new acceptance sampling plans for Rama distribution when the mean lifetime test is truncated at a pre-determined time. The minimum sample sizes required to assert the specified life mean is obtained for a given customer’s risk. The operating characteristic function values of the sampling plans and producer’s risk are calculated. Design/methodology/approach The results are illustrated using numerical examples and a real data set is considered to illustrate the performance of the suggested acceptance sampling plans and how it can be used for the industry applications. Findings This paper shows a new acceptance sampling plans based on Rama distribution in the particular case when the mean life time test is truncated. Originality/value The results calculated in this paper demonstrate the differences between OC values for different distributions taken into account. In particular, OC values of Rama distribution are found to be less than the proposed distribution counterparts.

Three main methodological practices have been employed in psychotherapy science: the empirical-quantitative, empirical-qualitative, and theoretical one. Some scholars have argued for a monopoly of the empirical-quantitative methodological practice, sustained by scientific monism. This systematic review aims at exploring the contribution of each methodological practice to the field. Fifteen journals were searched from 2003 to 2013. A total of 9796 publications and 9915 studies met inclusion criteria and were coded for the methodological practice employed. Empirical-quantitative studies were the most published overall, over time, and in most of the journals considered. This overwhelming prevalence increased when considering the citation rates of the publications. We argue that these results are indicative of a quantitative monopoly, which in turn is due to a lack of critical thinking sustaining scientific monism. We call for disciplinary critical thinking and the consequent scientific pluralism valuing the plurality, diversity, and multiplicity of all the existing methodological practices.

Although exponential technologies promise to bring unprecedented value at the socio-economic and policy levels, the social acceptability and preparedness for the technological “singularity” should be carefully considered. In particular, whereas digital innovation is able to drive an extraordinary development of entrepreneurial ventures, a number of challenging issues and the ongoing pandemic crisis have increased the need to investigate how technological breakthrough and human capital can be effectively combined in order to build resilient socio-technical and entrepreneurial ecosystems. This paper offers a synopsis of the major investigation areas and a reflection on the themes associated with the emergence of a digital society and the affirmation of digital entrepreneurship ecosystems. The research process follows a systematic literature review and a conceptual development approach aimed to introduce both the concept and a model of the digital society “incubator”. The proposed model identifies the actors, values, flows, and processes that are required to support the construction of a resilient entrepreneurial ecosystem. In this perspective, the study proposes a new focus by hybridizing and integrating both entrepreneurial and technology-related dimensions into a single unifying model. The study also lays the groundwork for further studies aimed at identifying the environmental and institutional factors required to support a smooth and effective transition towards a resilient entrepreneurial and technology-driven society.

This study aims to compare polygraphic data in patients with OSA treated with Barbed Reposition Pharyn-goplasty (BRP) performed with a simplified technique compared to the standard method. Variations of tech-nique were performed and tested with the purpose of promoting tolerability and diffusion of this simplified technique. To evaluate the efficacy of the simplified BRP method, a sample of 99 patients was divided into two groups: Group A was treated with BRP (BRP group) and Group B was treated with simplified BRP (sBRP group). The results obtained on the two groups were compared with the two sample Bootstrap t-tests method, showing a substantial overlap in polygraphic results recorded 6 months after surgery.

Excessive daytime sleepiness is a frequent condition among children and adolescents that may lead to several and significant daytime consequences, including impaired neurocognitive skills and scholastic performance. Here, we evaluated in one hundred and ninety-one unselected primary school children, the relationship between sleepiness and a wide range of cognitive and academic skills through a standardized neuropsychological test battery. In order to assess the statistical relationship, we performed a partial least squares path modelling, a non-parametrical approach which combined a model of paths between latent variables and the coefficients between indicators and dimensions. Results were validated through the bootstrap approach and suggest that sleepiness is not associated with all cognitive and scholastic abilities, but only with those relying on verbal abilities and complex cognitive functions (i.e., reading comprehension, oral/syntactic comprehension, spelling, and mathematic skills). Our data suggest the idea that sleepiness in children is associated mostly with &ldquo, higher&rdquo, (mainly verbal) cognitive function(s), while the visuospatial domain was not affected.

To illustrate a new technological advance in the standard drug-induced sleep endoscopy (DISE) model, a new machine was used, the Experimental 5 Video Stream System (5VsEs), which is capable of simultaneously visualizing all the decisional parameters on a single monitor, and recording and storing them in a single uneditable video. The DISE procedure was performed on 48 obstructive sleep apnea (OSA) or snoring patients. The parameters simultaneously recorded on a single monitor are (1) the pharmacokinetics and pharmacodynamics of propofol (through the target controlled infusion (TCI) pump monitor), (2) the endoscopic upper airway view, (3) the polygraphic pattern, and (4) the level of sedation (through the bispectral index (BIS) value). In parallel to the BIS recording, the middle latency auditory evoked potential (MLAEP) was also recorded and provided. Recorded videos from the 5VsEs machine were re-evaluated six months later by the same clinician and a second clinician to evaluate the concordance of the therapeutic indications between the two. After the six-month period, the same operator confirmed all their clinical decisions for 45 out of 48 videos. Three videos were no longer evaluable for technical reasons, so were excluded from further analysis. The comparison between the two operators showed a complete adherence in 98% of cases. The 5VsEs machine provides a multiparametric evaluation setting, defined as an &ldquo, all in one glance&rdquo, strategy, which allows a faster and more effective interpretation of all the simultaneous parameters during the DISE procedure, improving the diagnostic accuracy, and providing a more accurate post-analysis, as well as legal and research advantages.

In this paper, we proposed a new ranked data control chart using repetitive sampling criterion to increase the performance of detecting any shift in mean process. For the comparisons target, the average run length (ARL) of the proposed control chart based on repetitive extreme ranked set sampling computed using exact and estimated parameters. The results showed that the ARL affected negatively by the parameter estimation. Moreover, the performances of the proposed control chart is evaluated and compared with similar control chart that obtained by using different sampling schemes such as the simple random sampling, ranked set sampling, extreme ranked set sampling and repetitive ranked set sampling.. The results showed that the ranked data based control chart outperform the classical control chart in terms of the ARL.

This paper aims to represent that levels of customer satisfaction of tourist accommodation are an important prerequisite when the goal is building a loyal relationship with this type of facility. The research involved 239 participants (% 50 women) who have used tourist facilities during the last 2 years. The data used in the research were collected through the administration of a questionnaire: Prosumership Service Quality Model (PROSERV-Q). The methodology utilized to analyse data is the multi-group analysis based on Partial Least Squares Path Modelling (PLS-PM) with high order constructs. The results show that in the PROSERV model the level of global satisfaction affect the attitude of customer loyalty towards the tourism services.

The purpose of this chapter is to provide a framework that could be of valid support to firms to align big data analysis with their innovation objectives. A vast amount of data, information, and knowledge spread all over the web has emerged today, denoting the age of the Big Data Revolution. While there are different researches that evidence the role and the outcomes that big data could bring to firms in terms of innovation, efficiency, productivity, quality, and customer satisfaction, most of the big data analytics are unfocused and inefficient as they lack alignment with business innovation strategy. A literature review of the main issues characterizing the Big Data Revolution is conducted. Then, based on main emerging challenges and drawbacks an operational framework has been constructed as a response to close off some of the inefficiencies encountered. Finally, the framework has been applied and validated in the context of tourism destinations being that tourism is a sector where knowledge is considered essential for competitiveness and innovation. The findings demonstrate the validity of the framework as well as a series of relevant pieces of knowledge that derive from big data analysis; useful and valid for innovating customers’ experience.

The present paper offers a new extension to the Ishita distribution called Size-Biased Ishia distribution (SBID). Various structural statistical properties of this distribution are derived such as the jth moment, moment generating function, the coefficients of variation, skewness and kurtosis. Also, the distribution of order statistics, harmonic mean, mode, reliability analysis, maximum likelihood estimation are provided, as well as the Fisher’s information, generalized and Renyi entropies are derived. The main advantage of using sized-based distributions appears when the sample are recorded with unequal probabilities. Accordingly, the superiority of the SBI distribution is illustrated to ball bearings data. It is shown that the SBID is the most appropriate model for this data set as compared to Rama distribution, Ishita distribution and Marshall–Olkin Esscher Transformed Laplace distribution. We believe that the SBID is an alternative distribution to lifetime data analysis.

Research on the determinants of the psychological sense of community (PSoC) is of particular importance to community interventions. A cross-sectional study involving 778 residents in an Italian local community explored through a mediation model the effects on PSoC of an individual cultural variable that has been scarcely investigated in PSoC research, that is, values-specifically, universalism-, and a perceived contextual variable, that is, the assessment of community services (a component of residential satisfaction). Results showed that universalism increased PSoC both directly and indirectly, having an effect also on the evaluation of community services, which, in comparison to values, showed a greater direct impact on PSoC. Limitations and implications for community interventions are discussed.

This chapter is an extended version of the paper: Salvatore et al. (2018a). Symbolic universes between present and future of Europe. First results of the map of European societies’ cultural milieu. PLoS ONE 13(1): e0189885. With respect to that work, the current chapter presents an extension of the levels of analysis (i.e. the detection of the lines of semiotic force) and a more comprehensive sample (i.e. the inclusion of Dutch and Danish subsamples).; International audience; The chapter reports the main findings of an analysis of cultural milieus of a sample of 11 European countries (Cyprus, Denmark, Estonia, France, Germany, Greece, Italy, Malta, Netherlands, Spain, United Kingdom). The analysis is based on a questionnaire (View of Context—VOC) applied to a sample built through a two-step procedure of post-hoc random selection from a broader dataset based on an online survey. According to the methodological framework outlined in the previous chapter, responses to the questionnaire were subjected to multidimensional analysis—a combination of Multiple Correspondence Analysis and Cluster Analysis. We identified three fundamental dimensions of meanings, interpreted as lines of semiotic forces comprising the semiotic field of European societies: Affective connotation of the world—foe versus friend; Direction of desire—passivity versus engagement; Form of demand—demand for systemic resources versus demand for community bond. Moreover, 5 symbolic universes were mapped. Each symbolic universe corresponds to a basic, embodied, affect-laden, generalized worldview: People in this study see the world as either (a) an ordered universe; (b) a matter of interpersonal bond; (c) a caring society; (d) consisting of a niche of belongingness; (e) a hostile place (others’ world).