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A large number of potential sites are given and we have to choose k sites in order to set up information centres, where each centre is able to serve a limited number of clients. The price a client pays for accessing a centre is proportional to the distance between the client and the centre. This problem belongs to a class of problems for which most theoretical computer scientists believe that there is no fast algorithm for finding an optimal solution. We therefore look for algorithms that produce an approximate solution. In this paper we present a fast algorithm that chooses k sites and assigns the clients to the centres in such a way that the maximum price a client pays is at most nine times the maximum price in an optimal solution. This algorithm works under the assumption that the number of chosen sites is small in comparison to the number of possible sites.

This study adopted the functional, expressive and aesthetic (FEA) consumer needs model, aimed to examine the influence of consumers' FEA perceptions of three-dimensional printing (3DP) integrated apparel products on their product satisfaction and purchase intention.

An online survey was employed with a sample of 332 participants (165 female and 167 male) aged 19 to 76, mean age of 35 years. A gender-neutral, 3DP integrated hooded sweatshirt was developed for this study featuring flexible, white 3D printed insets fabricated with an FDM 3D printer and white TPU filament sewn with traditional gray knit fleece.

The findings of this study suggest that the FEA model is appropriate in predicting consumers' satisfaction with 3DP integrated apparel products. Specifically, aesthetic (perceived beauty) and expressive (perceived coolness) dimensions are more influential than functional factors, except for the positive influence of perceived fit, in predicting consumers' satisfaction and purchase intentions for 3DP integrated apparel products.

Future studies could consider data collection from participants' physical fit testing or try on evaluation to determine the importance of the functional dimension in consumer response to 3DP integrated apparel product. Future studies could also examine full 3D printed apparel, or other 3DP integrated wearable products to expand the understanding of consumer perception of the application of 3DP technology.

Despite the increasing exploration of 3DP integrated apparel products and industry attempts to make this innovation in apparel more mainstream, research on how mainstream consumers perceive such 3DP integrated apparel products is limited. This study addresses this gap, providing critical implications for future research and design.

An electronic health record (EHR) enables clinicians to access and share patient information electronically and has the ultimate goal of improving the delivery of healthcare. However, this can create security and privacy risks to patient information. This paper aims to present a model for securing the EHR based on role-based access control (RBAC), attribute-based access control (ABAC) and the Clark-Wilson model.

A systematic literature review was conducted which resulted in the collection of secondary data that was used as the content analysis sample. Using the MAXQDA software program, the secondary data was analysed quantitatively using content analysis, resulting in 2,856 tags, which informed the discussion. An expert review was conducted to evaluate the proposed model using an evaluation framework.

The study found that a combination of RBAC, ABAC and the Clark-Wilson model may be used to secure the EHR. While RBAC is applicable to healthcare, as roles are linked to an organisation’s structure, its lack of dynamic authorisation is addressed by ABAC. Additionally, key concepts of the Clark-Wilson model such as well-formed transactions, authentication, separation of duties and auditing can be used to secure the EHR.

Although previous studies have been based on a combination of RBAC and ABAC, this study also uses key concepts of the Clark-Wilson model for securing the EHR. Countries implementing the EHR can use the model proposed by this study to help secure the EHR while also providing EHR access in a medical emergency.

Drawing on social network and information diffusion theories, the authors study the impact of the structural characteristics of a seller’s local social network on her promotion effectiveness in social commerce.

The authors define a local social network as one formed by a focal seller, her directly connected users and all links among these users. Using data from a large social commerce website in China, the authors build econometric models to investigate how the density, grouping and centralization of local social networks affect the number of likes received by products posted by sellers.

Local social networks with low density, grouping and centralization are associated with more likes on sellers’ posted products. The negative effects of grouping and centralization are reduced when density is high.

The paper deepens the understanding of the determinants of social commerce success from a network structure perspective. In particular, it draws attention to the role of sellers’ local social networks, forming a foundation for future research on social commerce.

Evidence suggests that, in the presence of imperfect market institutions, individuals devote resources to the establishment of reliable connections to attenuate the frictions that reduce trading and insurance opportunities. In this chapter, the author surveys the relevant literature on strategic formation of networks and use it to study this particular economic situation. A simple model is built to show that the investment in strong ties often, though not always, produces stable configurations that manage to improve upon the imperfections of market institutions.