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Article
Publication date: 16 November 2022

Claudio Nigro, Enrica Iannuzzi, Naomi di Santo and Roberta Sisto

This paper aims to investigate the phenomenon of online food purchasing in Italy and, specifically, Italian consumers' future intentions to use these services even after the end…

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Abstract

Purpose

This paper aims to investigate the phenomenon of online food purchasing in Italy and, specifically, Italian consumers' future intentions to use these services even after the end of the COVID-19 emergency. To this purpose, to understand if these phenomena are robust enough to represent irreversible and well-established trends, in the present study, consumers’ Behavioural Intention was investigated.

Design/methodology/approach

A theoretical framework based on a preliminary literature analysis on the use of delivery services was developed. Then, an online survey was carried out in Italy during 2021. The data were then elaborated through an exploratory factor analysis (EFA), followed by confirmatory factor analysis (CFA). Following the verification of constructs reliability, a structural equation modelling (SEM) using the statistical tools, SPSS and R (Lavaan) was performed.

Findings

The results suggest that Behavioural Intention is influenced by items such as convenience, variety of food and time savings. Moreover, the relevant role of social networks and interpersonal relationships in influencing consumers' purchasing intentions has highlighted the importance of focussing on advertising campaigns and good “word of mouth.”

Originality/value

The present research represents the first attempt to investigate the food delivery and ghost kitchens’ phenomena, recently accepted thanks to the delivery applications use in Italy, a Country with strong gastronomic tradition and with an important digital gap. In this scenario, the research focused on the attention on the consumers' future intentions to use these services even after the end of the COVID-19 emergency.

Details

British Food Journal, vol. 125 no. 6
Type: Research Article
ISSN: 0007-070X

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Article
Publication date: 21 February 2025

Simona Curiello, Enrica Iannuzzi, Dirk Meissner and Claudio Nigro

This work provides an overview of academic articles on the application of artificial intelligence (AI) in healthcare. It delves into the innovation process, encompassing a…

1

Abstract

Purpose

This work provides an overview of academic articles on the application of artificial intelligence (AI) in healthcare. It delves into the innovation process, encompassing a two-stage trajectory of exploration and development followed by dissemination and adoption. To illuminate the transition from the first to the second stage, we use prospect theory (PT) to offer insights into the effects of risk and uncertainty on individual decision-making, which potentially lead to partially irrational choices. The primary objective is to discern whether clinical decision support systems (CDSSs) can serve as effective means of “cognitive debiasing”, thus countering the perceived risks.

Design/methodology/approach

This study presents a comprehensive systematic literature review (SLR) of the adoption of clinical decision support systems (CDSSs) in healthcare. We selected English articles dated 2013–2023 from Scopus, Web of Science and PubMed, found using keywords such as “Artificial Intelligence,” “Healthcare” and “CDSS.” A bibliometric analysis was conducted to evaluate literature productivity and its impact on this topic.

Findings

Of 322 articles, 113 met the eligibility criteria. These pointed to a widespread reluctance among physicians to adopt AI systems, primarily due to trust-related issues. Although our systematic literature review underscores the positive effects of AI in healthcare, it barely addresses the associated risks.

Research limitations/implications

This study has certain limitations, including potential concerns regarding generalizability, biases in the literature review and reliance on theoretical frameworks that lack empirical evidence.

Originality/value

The uniqueness of this study lies in its examination of healthcare professionals’ perceptions of the risks associated with implementing AI systems. Moreover, it addresses liability issues involving a range of stakeholders, including algorithm developers, Internet of Things (IoT) manufacturers, communication systems and cybersecurity providers.

Details

European Journal of Innovation Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1460-1060

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