The belief that National Healthcare Systems, particularly in the most industrialised countries, require innovation processes has grown in recent years (Marmor 2013). The focus of such an innovation is mainly on healthcare services (Haggerty, 2017; Perelman, 2017). This issue may be caused by demographic changes, technological advancements, an increasingly volatile digital environment, and, more broadly, the increased demand for health care (Kodama 2015).
In this context, a role of great relief for National Healthcare Systems can be played by companies and health professionals that operate in a privatised regime and that have the potential to provide proximity services by decentralising their provision compared to more traditionally public and centralised organisations, such as hospitals.
This research was grounded on the Transformative Service Research theory (TSR), an emerging movement aiming to analyse the impacts of services on individual and collective well-being (Rosenbaum et al., 2011; Anderson et al., 2013). TSR distinguishes itself from traditional service research in relation to the investigated outcomes (Alkire et al., 2019). As a matter of fact, the healthcare sector has received great attention from the service communities because it was identified as a research priority (Ostrom et al., 2015).
The professional figure who, among others, stood out in the pandemic period is that of the pharmacist. Pharmacists were recently recognised as the role they had lost in the past, namely that of “consultant” for the citizens on the front line in providing health services. Some studies (White et al., 2012; Carter et al., 2012) have already highlighted how the role of the pharmacist is vital in the social context of a community, and today new technologies allow this professional to provide beneficial services (DeRemer et al. 2021; Bahlol & Dewey, 2021; Cobelli & Chiarini, 2020). These are often confined virtuous examples, which fail to have a national or supranational value.
This study adopted a systematic literature review based on the Tranfield et al. (2003) approach (planning the review, conducting the review, reporting and dissemination). The literature search was conducted using the Scopus database (Parè et al., 2015). Seventy documents were extracted. The authors analysed the bibliometric characteristics and classified the works into the main themes and sub-themes related to the investigated phenomenon.
In addition, to address the study purpose, quantitative research was developed to detect factors that motivate pharmacists to participate in eHealth management programs. A questionnaire was developed, inspired by acceptance technologies models. It was administered online by involving Italian pharmacies’ owners. Data were analysed by using SEM.
The expected results of the survey provide valuable insights for developing policies and strategies to promote e-health programmes in Italian pharmacies by creating a network closer to citizens’ needs.

In recent years, the rapid development of smartphone, mobile Internet and information communication technology fostered a new way of mobility service. Smart mobility service (SMS) platforms include several functions, such as travel planning, booking, contacting drivers, or arrival reminders. This paper is one of the first to explore urban consumer travelling and their decision-making. It extends theoretical and exemplary models with real world behavioral data. Three studies introduce several relevant factors, such as punctuality, predictability, or convenience in the decision-making process.

In the qualitative first study we interviewed a variety of consumers and identified their drivers for decision making.

The quantitative study 2 included 2,000 consumers and confirmed the importance of these drivers.

To observe real customer behavior in Study 3, we launched three shuttles and a smart mobility service app. We divided this experiment in three phases, controlling for the service environment and population density. Following previous studies’ results, phase I aimed for acquiring customers for the newly programmed app that guided customers through the whole service experience. In this phase we provided the service for free. Phase II fixed the price and varied the routing, and phase III tested different pricing and promotion strategies. While phase I ended with 950 registered users, our app captured app. 40,000 orders of which we analyzed 29,000 in phase II, and 35,000 valid cases in phase III.

Our findings indicate that convenience is the main driver behind consumers’ purchase, especially in peak hours. The different routing strategies impact consumer purchase rates such that fixed-routing produces higher purchase rates compared to dynamic routing. Punctuality risks and time predictions strongly influence consumers’ buying behavior. Unsurprisingly, higher prices result in reduced purchase rates and price promotions increase consumers' purchase rate.
The studies provide a comprehensive picture of urban residents' mobility behavior patterns. From a managerial perspective, this study underlines consumers’ changing mobility behavior. It emphasizes the dusk of buying and owning cars and describes the dawn of providing and adopting SMS. Our study also answers the long-debated question in the smart mobility industry: Can we provide a smart mobility service (such as smart shuttle service), which can meet both the consumers’ convenience (on-call service) and their low-cost needs at the same time? This paper confirms that the dynamic route strategy offers much lower purchase rates than the fixed-route strategy, and provides solid evidence that service convenience and low price cannot be obtained at the same time. Our findings guide SMS providers to focus on designing such offerings with accentuated service convenience and accurate prediction times. In low-price settings, adopting a fixed-route strategy appears fruitful. Such strategies can help smart mobility operators to achieve higher consumer purchase rates, improve customer experience and reduce operating costs.

WHO predicts that up to 5 billion people will be unable to access healthcare services in 2030. Health technology is seen as one solution to this inequality in healthcare access, tackling geographical challenges and offering a low-cost alternative to traditional services. However, despite already having the access, there are several sociodemographic subgroups, such as mental health consumers, elderly people and people in developing countries, that continue to show slow health technology uptake. Much attention has been paid to the reasons for this lack of adoption. However, yet most of technology adoption literature (e.g., TAM, UTAUT) focuses on technology attributes and individual user characteristics. Less attention has been paid to the social setting in which technology is adopted. That is despite recent research suggests that cultural expectations regarding technology are a major contributor to adoption. Indeed, consumers’ socio-cultural setting– including perceived norms and values in a society – shapes their interpretations of and reactions to social situations, including encounters with health technology. Drawing on services literature and the theory of validation in higher education research, we examine how consumers’ socio-cultural repertoires – such as the perceived roles of the consumer and service providers - affects their expectations towards service technology. The empirical context of our study is online mental healthcare service provided by a major hospital in northern Europe. With the users of the platform, we conducted 38 in-depth interviews. Emerging from a phenomenological interpretational analysis, our findings show that consumers can experience health technology as invalidating of their socio-cultural backgrounds and lived experiences. We find that health technology privileges customers who share cultural expectations regarding the use of technology as a form of treatment and have internalized the role of consumer as co-producer. Patients whose cultural repertoires do not align with these expectations experience referral to online therapy as an invalidation of their role as patient. These users feel that they are not listened to or taken seriously, and that they are being asked to perform tasks that are incommensurate with their capabilities, which leads to frustrations, doubt, and non-compliance with medical recommendations. Crucially, we also find that in some cases, healthcare providers offered their patients validation that mitigated these negative outcomes. We identify three forms of validation: valorization, empowerment, and realignment, that the service users can use to enhance the cultural repertoires of patients to the point where online healthcare technology is no longer perceived as an inadequate mode of treatment and the patients are able to conceive themselves as active participant in healthcare co-creation. In conclusion, our study shows that to reduce uneven access to healthcare the role of consumers’ broader socio-cultural context on technology adoption must be taken into account. Our study contributes to ongoing research on barriers to service innovation adoption, as we highlight the importance of designing and deploying information technology in a way that validates consumers’ diverse socio-cultural backgrounds. We further identify three practices of validation, that the service users can use to enhance the cultural repertoires of consumers.

​​The intelligent operating room (IOR) (Wachs 2010)), where digital technology inputs can assist human team members is becoming a reality (Hashimoto et al. 2018). The key issue for patients is that the IOR involves the collection and use of patient data through devices such as video recording, robotics, medical team worn sensors (i.e., sabermetrics) and artificial intelligence (AI). As this technology is adopted, it is important to understand how patients feel about this data. This exploratory study aims to establish patient perceptions of the data collected in intelligent operating rooms across four technology types (robotics, sabermetrics, video, AI). A structured survey with four vignettes including visual and text descriptions, alongside closed and open ended questions was administered. A sample (n=462) of UK participants from PROLIFIC answered three questions on a 1-5 scale for each technology: I don’t really think about this as my data; I would be willing to consent to the data being collected and used in this way, I would like to have access to this data. Concluding with an open question: “Do you have any comments about your data in this scenario?” Inductive thematic analysis and repeated measures ANOVAs were conducted.

Ownership of the data: variation depending on the type of technology (F(3, 1188) = 163.72, p = .001). Specifically, video data was considered the most personal (M = 2.73) followed by AI (M =3.66), robotic (M = 3.91), and sabermetrics (M = 4.10). All conditions differed from one another at p < .001.

Consent to data donation: differed by technology (F(3, 1182) = 33.40, p = .001). Participants are more willing to consent to their data being collected and used for sabermetrics (M = 4.47) compared to robotic data (M = 4.39, p = .03), AI (M = 4.10, p = .01), and video (M = 4.05, p = .01). Willingness to consent was higher for robotic data than AI (p = .01) and video (p = .01). There was no difference in consent for AI and video (p = .44)

Desire for data access: differed by technology (F(3, 1164) = 20.98, p = .001). Access to video data (M = 3.80) was more desirable than access to sabermetrics (M = 3.32, p = .00), robotics (M =3.57, p =.00), and AI (M = 3.52, p =.00). Participants wanted access to robotics data more than sabermetrics (p = .00). Finally, participants wanted access to their AI data more than sabermetrics (p =.00). No difference found between robotics and AI.

Thematic analysis of the open ended questions reveals positive themes of: altruism and evidence potential while negative perceptions were based on need for control (via data consent and access), need for anonymity and potential violation of privacy.

To summarize, participant willingness to share data across all four technologies was high. However for successful future implementation and adoption of this technology concerns around consent data misuse and trust must be addressed. A follow-up experiment to optimize communication examining trust and the role of data end-user is currently underway.