The aim of this study was to evaluate the incidence and outcome of isolated moderate renal pelvis dilatation (RPD) [anterior-posterior diameter (APD) 10-15 mm] in an unselected population of 2-month-old infants prospectively followed for up to 12-14 months of life. Isolated moderate renal pelvis dilatation was detected in 282 of the 11,801 (2.4%), infants screened; 240 infants with normal renal ultrasound were enrolled as the control group. Resolution of RPD was considered when an APD
The aim of this study was to evaluate the incidence and outcome of isolated severe renal pelvis dilatation (RPD; APD>15
Our data demonstrate that meconium passage does not induce ET-1 secretion.
The world we live in today is pervaded by digital, the net is increasingly present and mixes the dimensions of the physical and the virtual, changing the way we understand, decide and evaluate things and also the way we do business. Artificial intelligence (AI) and related technologies are transforming the way we think and do marketing and the way companies relate to consumers and society.Internet has assumed a key role in nurturing innovation within business ecosystems. AI, big data and Internet of things (IoT) are key drivers of the current revolution in the way of communicating and relating among both individuals and products. This change is mainly due to the impact of algorithms’ mediations on the creation of value and customer engagement.Recent years, growing attention has been devoted to consumer brand engagement through emerging technological platforms (e.g., social media/artificial intelligence-based). However, despite important knowledge advancement, much remains unknown regarding the effect of Consumers’ Technology-Facilitated Brand Engagement (CTFBE) on individuals’ wellbeing, thus determining an important research gap (Hollebeek and Belk, 2021). CTFBE comprises a vital social facet. Hollebeek and Belk (2021) define CTFBE as a consumer’s bloodedly volitional resource investment in technology-mediated brand interactions (Kumar et al., 2019; Hollebeek et al, 2020). Online behavioral customer engagement occurs because of the rise of the new media and the advancement of technology, which have changed the way customers connect and interact with firms (Jahn and Kunz, 2012). One of the most active channels for such an aim are social media (Gummerus et al, 2012) where customers share their own experiences, information, review brands and manifest enthusiasm, delight, or disgust about a brand with others (Hollebeek and Chen, 2014).Digital transformation has totally transformed the value creation process (Reinartz et al., 2019) revolutionizing the way of doing business using the large mass of available data and information, through sophisticated service platforms that increase both effectiveness and efficiency in the value creation processes. AI has been a key component of digital transformation, substantially affecting consumer decision-making (Duan et al., 2021).AI, big data and the IoT are supporting and / or automating many decision-making processes: product, price, channel, supply chain, communication, etc. The customer experience is also redesigned starting from new value creation objectives and can become a stimulus for the creation of new business models. This, in turn, can provide a customized experience that is highly valued by consumers (Lemon and Verhoef, 2016). While new technologies have brought more ways for customers to interact with brands and companies, digital technologies have similarly enabled the automation of company’s interactions with customers (Kunz et al., 2017).According to Kumar et al (2010), AI represents the enabling technology for the transformation of marketing theory and practices: the enormous availability of data, the explosion of the possibilities to reach and interact on the markets and an increased speed of transactions. AI-enabled digital platform helps organizations to attract their customers (Bag et al, 2021; Chawla and Goyal, 2021).An increasing number of marketing decisions already use artificial intelligence in some way, and with the rise of big data is becoming easier to incorporate AI into business practices. Marketers may develop a more effective and personalized communication approach (Mogaji et al., 2020). For this reason, today AI is adopted in all activities where classification, forecasts and clustering are useful or necessary to solve problems and support decisions (management of anomalies in processes, logistics and optimization planning, customer service and customization).In the contemporary world the ubiquity of digital has made fluid the distinctions between channels and has integrated two dimensions of reality (physical and virtual one in phygital), the management of complex processes has become agile and adaptive, the advantages of integration and dynamic use of resources condition the operation of entire businesses. Well, what influence all this changes, new technologies and brand algorithms will have on social engagement?Prior studies on artificial intelligence in service and marketing research have not addressed customer engagement (Kaartemo & Helkkula, 2018). Perhaps, even Kaartemo & Helkkula (2018) specifically called for more research to answer the question: “How can we improve customer engagement through AI?”The article proposal is theoretical/conceptual in nature and starts from an updated review of academic literature on the aforementioned topics, mainly within marketing and business management disciplines, to achieve an interpretative attempt of Brand algorithm and social engagement (role) in digital era. References on request.
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