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The protection of industrial heritage emerged as a major concern when those buildings and installations representative of the industry, became at risk. North Africa, considered the geographical gateway to European countries, experienced enormous industrial activity during the French colonial era. Industrial buildings such as the flour mills, were built during this era of colonial rule. Today, a lack of legislation concerning industrial heritage has left this type of buildings with no protection, leading this paper to a preservation process. The aim of this paper is to locate and identify the flour mills of the 19th and 20th centuries in Algeria.

This research consists of cross-referencing data from archived documents against the geographical location.

The results obtained are the first step in the process of preservation. The success of this research can be summarized as follows: identification of 88.46% of the flour mills in Algeria by means of the inventory data collected, and their location, with the use of a crisp logic, the remaining 9.62% with the use of fuzzy logic by the attribution of a “fuzzy radius” with a total localization and identification of 98.08%.

The use of both crisp (Boolean) and fuzzy logic as part of the geographical localization method.

Technology has revolutionized the delivery of health-care services, with e-consultations becoming popular mode of service delivery, especially during the pandemic. Extant research has examined the adoption of e-health consultation services, with little attention paid to examine the switching behavior. This study aims to identify factors affecting patients’ intentions to switch from conventional mode i.e. visiting hospitals/clinics to e-health consultations.

To understand this we use the push–pull–mooring (PPM) framework and integrate variables from status quo bias framework to the model. A cross-section research design was used, which rendered 413 valid responses which were obtained from the patients visiting a traditional hospital setup. The data was analyzed using partial least square – structural equation modeling using SmartPLS 3.0.

Findings suggest that push effects (inconvenience and perceived risk), pull effects (opportunity for alternatives and ubiquitous care), mooring effects (trust) and inertia significantly influence patients’ switching intentions from visiting hospitals/clinics to e-health consultations. Further, habit and switching cost positively influence inertia.

This study shall enable online health-care service providers and practitioners to understand patients’ intentions to switch to online health platforms and accordingly develop related marketing strategies, services and policies to encourage them to switch to the new offerings.

The current study enriches the previous research on e-health services by applying and extending PPM framework as the base model and showing its efficiency in predicting individuals switching intentions in the context of emerging economies. This study bridges the gap by focusing on switching behavior in context of health services.