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The broad objective of this the chapter is to investigate corporate brand identity and social media in the transportation industry. To do so, considering that passenger transportation includes similar structures regardless of the means used, we chose to analyze air transportation precisely because it is considered the most competitive in the transportation industry.

According to the national balance sheets of the most advanced economies, despite a recent sharp decline in per capita net wealth, Italian private households present a higher rate among the wealthiest and least indebted in Europe. Recently, the COVID-19 outbreak caused a new leap in households' savings worldwide, particularly in advanced economies and Italy. This study underlines that using advanced analytics tools, household saving behaviour information, and big data analytics may support data-driven decision approaches addressing the management of complex relationships in the financial arena. More specifically, using exploratory and predictive analyses based on big data analytics and machine learning, this study aims to provide extensive customer profiling in the household saving sector in Italy, supporting a data-driven decision-making approach. A profiling of household savings has been defined using the information provided by big data analysis. To proceed in this direction, the hardware and software requirements necessary to perform data processing were considered in the first phase of the study. Data collection was performed according to the so-called extract, transform, load (ETL) process. The contribution of this study lies in the results obtained in terms of data analytics over a dataset that accounts for the purchasing behaviour of almost 20 million postal savers. The clustering algorithm is highly efficient and scales well for large datasets. K-means clustering can be implemented within the MapReduce computational framework. Therefore, the overall procedure proposed here can be easily extended to big data using parallel computing and software implementing MapReduce, such as Hadoop and Spark.

he recent outbreak of novel coronavirus (Covid-19) has led to a global panic due to its fatal nature which has harshly impacted the tourist sector and on the place reputation in general. This study aims to compare the factors that develop tourist preferences in terms of (i) what drives the favorability of tourist preferences? (ii) what relationship exists between tourist expectations, proximity, and favorable reputation? and (iii) what are the main influences of tourist preferences on hospitality system competitiveness pre and post Covid-19? By employing structural equation modeling, this study advances knowledge into the research variables’ relationships and advances reputation and marketing performance and practices in the hospitality industry.

The lockdowns of several countries due to COVID-19 outbreak resulted in severe economic consequences, among which was the immediate general disruption of the international supply chain, with few exceptions. This article aims to investigate whether some supply chains were resilient or not and why, using a knowledge-based approach and specifically focusing on the role played by supply chain innovation in building resilience to disruptions, thanks to knowledge preparedness. The study is motivated by two main rationales: the unique situation of a global pandemic and the absence of studies providing grounded evidences of supply chain resilience in a worst-case scenario. The research is based on the assumption that knowledge preparedness introduces logistics/supply chain innovations and enables companies to prevent, detect, and respond to unpredictable negative events. By using a large-scale sample of European firms' data from the Eurostat and a multivariate regression analysis, the authors cross-study the effects of supply chain knowledge preparedness – based on innovation type and expenditures – on the international trade of goods from January to June 2020. The results confirm that the most resilient supply chains were those that had previously introduced innovations, a factor that strengthens the knowledge preparedness of firms when faced with unforeseeable supply chain disruptions.

Technology is advancing at an exponential rate; the desire of many organizations is to improve a brand’s reputation by following the progress of emerging trends. Augmented reality and virtual and mixed reality solutions are becoming strategic trends capable of offering customers unique experiences on their brands.

Food represents one of the most discussed topics on social networks, arriving at giving voice to real virtual communities, vertically specific or transversally generic, with reference to peculiar food behaviors and / or food preferences. This study aims to understand if and how social networks can contribute to bringing out subcultures, food subcultures in this specific case, from underground situations to mainstream levels. The survey was carried out on Instagram, with a focus on the vegan subculture and with an emphasis on the period of the COVID-19 pandemic, analyzing Instagram posts from mid-October 2020 to mid-November 2020. The results show that the Instagram users associated with posts that can be classified as "#vegan food porn" show traits of content and sentiment in line with an emerging subculture, finding a sense of identity and affirmation in their posts and in those linked by consistent hashtags. Despite the limitations that are pointed out in the research, the study is specifically intended for enterprises in the food sector that seek to develop consumer marketing actions on social networks with a predominantly cultural and subcultural slant.

he recent outbreak of novel coronavirus (Covid-19) has led to a global panic due to its fatal nature which has harshly impacted the tourist sector and on the place reputation in general. This study aims to compare the factors that develop tourist preferences in terms of (i) what drives the favorability of tourist preferences? (ii) what relationship exists between tourist expectations, proximity, and favorable reputation? and (iii) what are the main influences of tourist preferences on hospitality system competitiveness pre and post Covid-19? By employing structural equation modeling, this study advances knowledge into the research variables’ relationships and advances reputation and marketing performance and practices in the hospitality industry.

Taking into account the increasing importance of digitalization to characterize companies’ competitive advantages, and the contextual growing research interest in digital transformation, this paper focuses on dynamic capabilities affecting firms’ digital innovation in terms of creation of new offerings, processes or solutions by using a wide range of digital technologies. By means of quantitative research on a sample of managers of 210 firms in Italy, the study performs an ordinary least squares regression to investigate whether and how different knowledge-based capabilities support the process to develop digital innovation, taking into consideration the moderating effect of social media. Despite some limitations, essentially due to the geographical focus of the analysis, the paper contributes to better understand the effect of digitalization in the distinguishing context of the Italian companies, providing useful insights to rethink firms’ innovation models.

Digital transformation has completely changed the demand/offering interaction in the travel industry, as well as largely affecting the customer journey. In this direction, “big social data” and user-generated content have become key sources of well-timed and rich knowledge supporting data driven decision approaches addressed the managing of complex relationships. Based on this theoretical framework, the paper suggests how to apply “big social data” in the tourist experience co-design, providing an increased value for the visitors and a better decision making approach for managers. In this respect, the field analysis concentrated specifically on user-generated content regarding the Pompeii Archaeological Site (P.A.S.), to trace valuable insights for the tourist experience. Based on double stage of research – netnographic analysis and a supplementary online survey – the study aimed to detect: (a) tourist perception on the P.A.S.; (b) random chat on the part of internet users (tourists and other browsers, not necessarily visitors) on the topic of the P.A.S.; (c) the main characteristics of the P.A.S. that attract internet user attention; (d) the main topics debated by influencers/opinion leaders managing online discussions on the P.A.S. managerial and theoretical implications were investigated highlighting the main limitations of the study as well.

This chapter sets the scene for discussions on the relevance of climate change and its impact on corporate and brand strategies, especially in terms of environmental tools to mitigate climate risks (i.e., environmental auditing). In particular, this chapter identifies the main challenges and recommendations linked with this framework.

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Temporal lobe epilepsy, a common drug-resistant epilepsy in adults, is primarily a limbic network disorder associated with predominant unilateral hippocampal pathology. Structural MRI has provided an in vivo window into whole-brain grey matter structural alterations in temporal lobe epilepsy relative to controls, by either mapping (i) atypical inter-hemispheric asymmetry; or (ii) regional atrophy. However, similarities and differences of both atypical asymmetry and regional atrophy measures have not been systematically investigated. Here, we addressed this gap using the multisite ENIGMA-Epilepsy dataset comprising MRI brain morphological measures in 732 temporal lobe epilepsy patients and 1418 healthy controls. We compared spatial distributions of grey matter asymmetry and atrophy in temporal lobe epilepsy, contextualized their topographies relative to spatial gradients in cortical microstructure and functional connectivity calculated using 207 healthy controls obtained from Human Connectome Project and an independent dataset containing 23 temporal lobe epilepsy patients and 53 healthy controls and examined clinical associations using machine learning. We identified a marked divergence in the spatial distribution of atypical inter-hemispheric asymmetry and regional atrophy mapping. The former revealed a temporo-limbic disease signature while the latter showed diffuse and bilateral patterns. Our findings were robust across individual sites and patients. Cortical atrophy was significantly correlated with disease duration and age at seizure onset, while degrees of asymmetry did not show a significant relationship to these clinical variables. Our findings highlight that the mapping of atypical inter-hemispheric asymmetry and regional atrophy tap into two complementary aspects of temporal lobe epilepsy-related pathology, with the former revealing primary substrates in ipsilateral limbic circuits and the latter capturing bilateral disease effects. These findings refine ou

AIMS: The causes of distinct patterns of reduced cortical thickness in the common human epilepsies, detectable on neuroimaging and with important clinical consequences, are unknown. We investigated the underlying mechanisms of cortical thinning using a systems-level analysis. METHODS: Imaging-based cortical structural maps from a large-scale epilepsy neuroimaging study were overlaid with highly spatially resolved human brain gene expression data from the Allen Human Brain Atlas. Cell-type deconvolution, differential expression analysis and cell-type enrichment analyses were used to identify differences in cell-type distribution. These differences were followed up in post-mortem brain tissue from humans with epilepsy using Iba1 immunolabelling. Furthermore, to investigate a causal effect in cortical thinning, cell-type-specific depletion was used in a murine model of acquired epilepsy. RESULTS: We identified elevated fractions of microglia and endothelial cells in regions of reduced cortical thickness. Differentially expressed genes showed enrichment for microglial markers and, in particular, activated microglial states. Analysis of post-mortem brain tissue from humans with epilepsy confirmed excess activated microglia. In the murine model, transient depletion of activated microglia during the early phase of the disease development prevented cortical thinning and neuronal cell loss in the temporal cortex. Although the development of chronic seizures was unaffected, the epileptic mice with early depletion of activated microglia did not develop deficits in a non-spatial memory test seen in epileptic mice not depleted of microglia. CONCLUSIONS: These convergent data strongly implicate activated microglia in cortical thinning, representing a new dimension for concern and disease modification in the epilepsies, potentially distinct from seizure control.

OBJECTIVE: Drug-resistant focal epilepsy is often caused by focal cortical dysplasias (FCDs). The distribution of these lesions across the cerebral cortex and the impact of lesion location on clinical presentation and surgical outcome are largely unknown. We created a neuroimaging cohort of patients with individually mapped FCDs to determine factors associated with lesion location and predictors of postsurgical outcome. METHODS: The MELD (Multi-centre Epilepsy Lesion Detection) project collated a retrospective cohort of 580 patients with epilepsy attributed to FCD from 20 epilepsy centers worldwide. Magnetic resonance imaging-based maps of individual FCDs with accompanying demographic, clinical, and surgical information were collected. We mapped the distribution of FCDs, examined for associations between clinical factors and lesion location, and developed a predictive model of postsurgical seizure freedom. RESULTS: FCDs were nonuniformly distributed, concentrating in the superior frontal sulcus, frontal pole, and temporal pole. Epilepsy onset was typically before the age of 10 years. Earlier epilepsy onset was associated with lesions in primary sensory areas, whereas later epilepsy onset was associated with lesions in association cortices. Lesions in temporal and occipital lobes tended to be larger than frontal lobe lesions. Seizure freedom rates varied with FCD location, from around 30% in visual, motor, and premotor areas to 75% in superior temporal and frontal gyri. The predictive model of postsurgical seizure freedom had a positive predictive value of 70% and negative predictive value of 61%. SIGNIFICANCE: FCD location is an important determinant of its size, the age at epilepsy onset, and the likelihood of seizure freedom postsurgery. Our atlas of lesion locations can be used to guide the radiological search for subtle lesions in individual patients. Our atlas of regional seizure freedom rates and associated predictive model can be used to estimate individual l

Epilepsy is associated with genetic risk factors and cortico-subcortical network alterations, but associations between neurobiological mechanisms and macroscale connectomics remain unclear. This multisite ENIGMA-Epilepsy study examined whole-brain structural covariance networks in patients with epilepsy and related findings to postmortem epilepsy risk gene expression patterns. Brain network analysis included 578 adults with temporal lobe epilepsy (TLE), 288 adults with idiopathic generalized epilepsy (IGE), and 1328 healthy controls from 18 centres worldwide. Graph theoretical analysis of structural covariance networks revealed increased clustering and path length in orbitofrontal and temporal regions in TLE, suggesting a shift towards network regularization. Conversely, people with IGE showed decreased clustering and path length in fronto-temporo-parietal cortices, indicating a random network configuration. Syndrome-specific topological alterations reflected expression patterns of risk genes for hippocampal sclerosis in TLE and for generalized epilepsy in IGE. These imaging-transcriptomic signatures could potentially guide diagnosis or tailor therapeutic approaches to specific epilepsy syndromes.

One outstanding challenge for machine learning in diagnostic biomedical imaging is algorithm interpretability. A key application is the identification of subtle epileptogenic focal cortical dysplasias (FCDs) from structural MRI. FCDs are difficult to visualize on structural MRI but are often amenable to surgical resection. We aimed to develop an open-source, interpretable, surface-based machine-learning algorithm to automatically identify FCDs on heterogeneous structural MRI data from epilepsy surgery centres worldwide. The Multi-centre Epilepsy Lesion Detection (MELD) Project collated and harmonized a retrospective MRI cohort of 1015 participants, 618 patients with focal FCD-related epilepsy and 397 controls, from 22 epilepsy centres worldwide. We created a neural network for FCD detection based on 33 surface-based features. The network was trained and cross-validated on 50% of the total cohort and tested on the remaining 50% as well as on 2 independent test sites. Multidimensional feature analysis and integrated gradient saliencies were used to interrogate network performance. Our pipeline outputs individual patient reports, which identify the location of predicted lesions, alongside their imaging features and relative saliency to the classifier. On a restricted 'gold-standard' subcohort of seizure-free patients with FCD type IIB who had T1 and fluid-attenuated inversion recovery MRI data, the MELD FCD surface-based algorithm had a sensitivity of 85%. Across the entire withheld test cohort the sensitivity was 59% and specificity was 54%. After including a border zone around lesions, to account for uncertainty around the borders of manually delineated lesion masks, the sensitivity was 67%. This multicentre, multinational study with open access protocols and code has developed a robust and interpretable machine-learning algorithm for automated detection of focal cortical dysplasias, giving physicians greater confidence in the identification of subtle MRI lesions in

Despite a recent sharp decline in per-capita net wealth, according to the national balance sheets of the most advanced economies, Italian private households present higher rate among the wealthiest and least indebted in Europe (Acciari and Morelli, 2021). Italian personal precautionary saving bent represents a cultural trait of individual financial behaviour at a national level (Fuchs‐Schündeln et al., 2020). Nevertheless, recent demographic changes (i.e., households with multiple earners, increase in longevity, decline in fertility and so on) had a deep effect on household saving and its dynamic over time. Recently, the COVID-19 outbreak gave a new jump to the households’ savings worldwide, especially in the advanced economies (Romei, 2021) and also in Italy (Ercolani et al., 2021). This circumstance might depend on the unstable economic situation that leads consumers to adopt a more precautionary behaviour, which evolve in a high saving rate (Statista, 2021). Therefore, the research on this topic is crucial to predict future behaviours and finds a new, very relevant fellow in the support provided by digital transformation (Reis et al., 2018). On this stream, this study underlines as by virtue of advanced analytics tools, household saving behaviours information and big data analytics may support data-driven decision approaches addressed the managing of complex relationships in the financial arena. More punctually, by means of an exploratory and predictive analysis based on big data analytics and the use of machine learning, the aim of this study is to provide an extensive customer profiling in the household saving sector in Italy, supporting a data-driven decision-making approach.

One of the sectors most affected by the COVID-19 health emergency has been tourism and culture. The aim of the present work is to answer the research question of if and how the pandemic crisis has affected the expectations of young cultural tourists, impacting on the behavior of choice of cultural destination, will be exposed and analyzed the variables that influenced and that will influence the archaeological belief and the choice of cultural destination of young visitors. This qualitative-quantitative study, starting from the Theory of Planned Behaviour, TPB, integrated with context variables, focuses on the identification of the tourist with the place of visit and results in the intention of visiting at the base of the processes of choice of the cultural destination. In this way, new segments that are more attractive and of interest are determined. For the analysis and validation of the conceptual model, structural equations (SEM) were used with AMOS, on a sample of 998 young people (i.e. Millennials and Generation Z) passionate about cultural tourism, with a control sample composed of 40 experts in the field. The study has important theoretical and managerial implications. The limits of the study are outlined and the directions for future research have been considered

Nowadays organizations are increasingly engaged in talent management, because it allows firms to grow rapidly by leveraging on human capital. Most antecedent studies focused on expectations and motivations of talents living in developed countries. Though, a little is known about career expectations of talents in emerging economies, and whether they diverge from those of developed countries or not. However, this information might be of use for several motives. First, emerging countries have a high growth rate. Second, these talents may be effectively harnessed from domestic and non-domestic firms, depending on whether their expectations are met or not. Consistently, this study aims at exploring the career expectations of individuals in emerging countries, by capturing the heterogeneity of expectations between emerging and developed countries due to cultural, politic, economic, and religious differences. As a matter of fact, emerging countries are frequently characterized by low levels of both income and employment, differently from many developed countries. For such motives and because of the absence of valid employment alternatives, talents might be more willing to engage in entrepreneurial initiatives rather than attempting to be employed in an organization. Thus, the primary intent of this explorative study is to understand what are the factors that affect career expectations of talents in emerging countries. Consistently, a cross-sectional principal component analysis (PCA) was used for hypotheses testing. The sample refers to a set of African countries, based on data availability for 2019. Data used for the analysis are drawn from the Global Entrepreneurship Monitor (GEM) and they refer to individual entrepreneurial behaviours and attitudes. Notably, findings show that career expectations of talents are driven by motivation and opportunity, especially in the male groups. However, the study also originally shows that the need for achievement and the willingness t

In recent years, food wastage become a top-priority issue in western countries, calling for collective efforts for the waste reduction. In this scenario, food sharing platforms emerge as digital solutions to quickly reallocate food surpluses among society engaging players at different level of the chain and reconfiguring the consumption-production system. A multiple case study was carried out interviewing four Italian food sharing platforms’ founders in order to analyze the business model adopted and the reasons why food sharing is not a widespread phenomenon in Italy. Findings suggest that Italian food sharing platforms have different business model and they pursue different aim. Moreover, the study highlights the existence of three difficulties to spread the food sharing platforms in the Italian market, namely cultural barriers, economic problems, and legislative obstacles. From a managerial point of view, this research provides some recommendations for who wants to launch a food sharing platforms in Italy, describing successful business models and showing the challenges to face in order to develop an effective food sharing platform

Data on fetal MRI in L1 syndrome are scarce with relevant implications for parental counseling and surgical planning. We identified two fetal MR imaging patterns in 10 fetuses harboring L1CAM mutations: the first, observed in 9 fetuses was characterized by callosal anomalies, diencephalosynapsis, and a distinct brainstem malformation with diencephalic-mesencephalic junction dysplasia and brainstem kinking. Cerebellar vermis hypoplasia, aqueductal stenosis, obstructive hydrocephalus, and pontine hypoplasia were variably associated. The second pattern observed in one fetus was characterized by callosal dysgenesis, reduced white matter, and pontine hypoplasia. The identification of these features should alert clinicians to offer a prenatal L1CAM testing.Copyright © 2021 The Authors. Annals of Clinical and Translational Neurology published by Wiley Periodicals LLC on behalf of American Neurological Association

Data on fetal MRI in L1 syndrome are scarce with relevant implications for parental counseling and surgical planning. We identified two fetal MR imaging patterns in 10 fetuses harboring L1CAM mutations: the first, observed in 9 fetuses was characterized by callosal anomalies, diencephalosynapsis, and a distinct brainstem malformation with diencephalic-mesencephalic junction dysplasia and brainstem kinking. Cerebellar vermis hypoplasia, aqueductal stenosis, obstructive hydrocephalus, and pontine hypoplasia were variably associated. The second pattern observed in one fetus was characterized by callosal dysgenesis, reduced white matter, and pontine hypoplasia. The identification of these features should alert clinicians to offer a prenatal L1CAM testing.

The internationalization of R&D activities has become crucial for small and medium-sized enterprises (SMEs) to create sources of competitive advantage. This research aims to analyze the role of social capital and information technology (IT) in enhancing knowledge sharing and innovation capabilities in the particular context of SMEs with geographically dispersed R&D teams. The study uses structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (FsQCA) to investigate data from an online survey of 265 R&D managers in Italian manufacturing SMEs with responsibility for at least one international R&D team. The results reveal the critical role of structural social capital and IT in enhancing knowledge sharing and innovation capabilities. The research contributes to existing knowledge and provides useful insights for marketers by highlighting how social capital, also in combination with IT, strengthens SMEs' competitiveness even when they operate in a mature industry.

Over the last two decades academic literature has addressed much attention to the relationship between corporate ethical practices and financial performance. Results however remain contradictory, especially in terms of direction and effectiveness of their connection. Broadly speaking, most theorizing on the link between social and economic indicators assumes that the evidence is insufficient or too contrasting to draw any generalizable conclusions. In this perspective, this study aims to better explain the connection between corporate ethical practices and corporate financial performance, verifying that it is impacted by a large number of key variables. The empirical research is based on a longitudinal study on Italian listed companies operating in the banking sector. The adoption of the code of ethics is considered to measure their ethical practices, while regarding financial performance several accounting indicators are taken into consideration, including some control variables. To process the dataset a panel regression with fixed effect is applied. The paper aims at strengthening recent studies that consider bi-directional causality in the theory that “corporate social responsibility is both a predictor and consequence of firm financial performance”. Thus, the interest of the study lies in the identification of a reverse causality between positive financial performance and ethical orientation of Italian banking services companies

Malformations of cortical development are a group of rare disorders commonly manifesting with developmental delay, cerebral palsy or seizures. The neurological outcome is extremely variable depending on the type, extent and severity of the malformation and the involved genetic pathways of brain development. Neuroimaging plays an essential role in the diagnosis of these malformations, but several issues regarding malformations of cortical development definitions and classification remain unclear. The purpose of this consensus statement is to provide standardized malformations of cortical development terminology and classification for neuroradiological pattern interpretation. A committee of international experts in paediatric neuroradiology prepared systematic literature reviews and formulated neuroimaging recommendations in collaboration with geneticists, paediatric neurologists and pathologists during consensus meetings in the context of the European Network Neuro-MIG initiative on Brain Malformations (https://www.neuro-mig.org/). Malformations of cortical development neuroimaging features and practical recommendations are provided to aid both expert and non-expert radiologists and neurologists who may encounter patients with malformations of cortical development in their practice, with the aim of improving malformations of cortical development diagnosis and imaging interpretation worldwide.