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Around 60 per cent of people with dementia in the UK live at home. The experience of caring for a family member with dementia can be rewarding and positive, but it can also be significantly stressful. Current healthcare policy is encouraging greater provision to support family carers. Along with respite-care, day-care and support group-based initiatives, there has also been a focus on developing dementia-specific communication training. The paper discusses this issue.

The authors outline a new initiative “Empowered Carers” which is being piloted in the North of England. Empowered Carers is an online support and communication training service for family carers who are caring for someone with dementia at home. It utilises online video conference-calling technology to connect carers with support workers, and also allows for simultaneous interactions involving other family members. A central tenet of the approach is a theoretically grounded support model, based on the concept of mentalisation.

The authors describe the background to Empowered Carers, and how a conventional evaluation strategy for the initiative is being used alongside a socio-linguistic approach (Conversation Analysis – CA). This aims to provide empirical evidence about how the assimilation of mentalisation is reflected in the structuring of speech patterns in carers during support sessions.

The authors explain the CA method, how it has been applied to similar talk-based therapeutic settings, and why its ability to explore sequential linguistic patterns across extremely large data-sets is particularly suited to studying interaction in emerging online arenas.

Several high street retail banks are extending their brands into digital banking through fully digital, app-only neobanks, which have been described as traditionally-driven neobanks (TDNBs). These TDNBs are considered a form of brand extension, representing the increased complexity of branding banks and financial institutions. This study explicitly addresses the branding strategies employed by TDNBs.

This study has adopted a case study research design, using a multi-stage data collection strategy. Initially, interviews were conducted with bank managers, followed by interviews with customers. Later, user-generated content was extracted through verified reviews from the app store. Subsequently, these three strands of data were thematically analysed and triangulated, in order to gain a holistic understanding of the branding strategies used by TDNBs.

Three key themes emerged regarding the branding strategies of the TDNBs: aligning with the parent brand, reinforcing the digital experience, and enhancing the brand image.

This study contributed to the growing body of research on marketing, branding, and digital transformation of bank services. As more traditional banks are exploring opportunities to pivot and explore other fintech options, this study offers significant insights that will help in managing brand experience and promotion across customer journeys in the banking sector.

This study contributes to the growing body of research on marketing, branding, and digital transformation of bank services. Even as more traditional banks explore opportunities to pivot as well as other fintech options, this study offers significant insights to help manage brand experience and promotion across customer journeys in the banking sector.

While previous studies on banking and financial services have concentrated on traditional retail and high street banks, there is a need for a greater understanding of the brand positioning of digital banks, especially those created by traditional banks.

The boom in livestreaming commerce (LSC) has brought significant changes to social interaction methods. Understanding customer engagement in LSC is critical for online sellers who try to enhance the social influence and improve marketing effectiveness of LSC. Based on the stimulus–organism–response (S–O–R) paradigm, this study aims to develop a model to investigate the effects of perceived attributes of LSC (real-time interaction, perceived proximity and perceived authenticity) on social support (informational and emotional support) and subsequent engagement.

An online survey is conducted to collect data from LSC customers, and data are analyzed using SPSS and SmartPLS.

The results indicate that informational and emotional support are positively affected by real-time interaction, perceived proximity and perceived authenticity. In turn, informational and emotional support enable and mediate the prediction of customer engagement intention in LSC.

Prior LSC studies tend to focus on the motivation influencing LSC engagement from the perspective of perceived value. This study confirms the importance of perceived attributes of LSC in driving customer engagement from the perspective of social support.

This study proposes targeted modernization of the Department of Defense (DoD's) Joint Forces Ammunition Logistics information system by implementing the optimized innovative information technology open architecture design and integrating Radio Frequency Identification Device data technologies and real-time optimization and control mechanisms as the critical technology components of the solution. The innovative information technology, which pursues the focused logistics, will be deployed in 36 months at the estimated cost of $568 million in constant dollars. We estimate that the Systems, Applications, Products (SAP)-based enterprise integration solution that the Army currently pursues will cost another $1.5 billion through the year 2014; however, it is unlikely to deliver the intended technical capabilities.

The purpose of this paper is to propose customer behavior analysis based on real-time data processing and association rule for digital signage-based online store (DSOS). The real-time data processing based on big data technology (such as NoSQL MongoDB and Apache Kafka) is utilized to handle the vast amount of customer behavior data.

In order to extract customer behavior patterns, customers’ browsing history and transactional data from digital signage (DS) could be used as the input for decision making. First, the authors developed a DSOS and installed it in different locations, so that customers could have the experience of browsing and buying a product. Second, the real-time data processing system gathered customers’ browsing history and transaction data as it occurred. In addition, the authors utilized the association rule to extract useful information from customer behavior, so it may be used by the managers to efficiently enhance the service quality.

First, as the number of customers and DS increases, the proposed system was capable of processing a gigantic amount of input data conveniently. Second, the data set showed that as the number of visit and shopping duration increases, the chance of products being purchased also increased. Third, by combining purchasing and browsing data from customers, the association rules from the frequent transaction pattern were achieved. Thus, the products will have a high possibility to be purchased if they are used as recommendations.

This research empirically supports the theory of association rule that frequent patterns, correlations or causal relationship found in various kinds of databases. The scope of the present study is limited to DSOS, although the findings can be interpreted and generalized in a global business scenario.

The proposed system is expected to help management in taking decisions such as improving the layout of the DS and providing better product suggestions to the customer.

The proposed system may be utilized to promote green products to the customer, having a positive impact on sustainability.

The key novelty of the present study lies in system development based on big data technology to handle the enormous amounts of data as well as analyzing the customer behavior in real time in the DSOS. The real-time data processing based on big data technology (such as NoSQL MongoDB and Apache Kafka) is used to handle the vast amount of customer behavior data. In addition, the present study proposed association rule to extract useful information from customer behavior. These results can be used for promotion as well as relevant product recommendations to DSOS customers. Besides in today’s changing retail environment, analyzing the customer behavior in real time in DSOS helps to attract and retain customers more efficiently and effectively, and retailers can get a competitive advantage over their competitors.

Rapid innovation and globalization have generated tremendous opportunities and choices in the marketplace for firms and customers. Competitive pressures have led to sourcing and manufacturing on a global scale resulting in a significant increase in products. The paper tries to identify the need for real time business intelligence (BI) in supply chain analytics.

The paper provides argument and analysis of the advantages and hurdles in BI.

The paper focuses on the necessity to revisit the traditional BI concept that integrates and consolidates information in an organization in order to support firms that are service oriented and seeking customer loyalty and retention. Enhancing effectiveness and efficiency of supply chain analytics using a BI approach is a critical component in a company's ability to achieve its competitive advantage.

This paper furthers understanding of the issues surrounding the use of BI systems in supply chains.

Electric mobility as a service (eMaaS) is suggested as a possible solution to ease transportation and lessen environmental issues by providing a collaborative transport sharing infrastructure that is based on electric vehicles (EVs) such as electric cars, electric bicycles and so on. Accordingly, this study aims to propose a multi-tier architecture to support the collection, processing, analytics and usage of mobility data in providing eMaaS within smart cities. The architecture uses application programming interfaces to enable interoperability between different infrastructures required for eMaaS and allow multiple partners to exchange and share data for making decision regarding electric mobility services.

Design science methodology based on a case study by interview was used to collect data from an infrastructure company in Norway to verify the applicability of the proposed multi-tier architecture.

Findings suggest that the architecture offers an approach for collecting, aggregating, processing and provisioning of data originating from sources to improve electric mobility in smart cities. More importantly, findings from this study provide guidance for municipalities and policymakers in improving electric mobility services. Moreover, the author’s findings provide a practical data-driven mobility use case that can be used by transport companies in deploying eMaaS in smart cities.

Data was collected from a single company in Norway, hence, it is required to further verify the architecture with data collected from other companies.

eMaaS operates on heterogeneous data, which are generated from EVs and used by citizens and stakeholders such as city administration, municipality transport providers, charging station providers and so on. Therefore, the proposed architecture enables the sharing and usage of generated data as openly available data to be used in creating value-added services to improve citizen’s quality of life and viability of businesses.

This study proposes the deployment of electric mobility to address increased usage of vehicles, which contributes to pollution of the environment that has a serious effect on citizen’s quality of life.

This study proposes a multi-tier architecture that stores, processes, analyze and provides data and related services to improve electric mobility within smart cities. The multi-tier architecture aims to support and increase eMaaS operation of EVs toward improving transportation services for city transport operators and citizens for sustainable transport and mobility system.

The paper examines the circumstances of success in telematic use and strategic effects resulting from the implementation and use of such technologies from SMEs in the Greek Market.

The analysis is based on a three‐phased triangulated research methodology; that is literature review, interviews from 15 logistics directors and a questionnaire survey of 73 logistics SMEs in Greece.

The basic finding that has been derived from both phases 2 and 3 (survey and interviews) is that although the penetration of telematics is still low in Greece, logistics operators understand the importance of mobile services and they already know which they plan to their customers.

An inherent limitation of this survey is the fact that it address, like all surveys, the requirements of its respondents only, without taking into account.

This paper explores customer perceptions and requirements for the implementation of mobile real‐time support services for city logistics. The requirements, elicited by the results of the survey, are used to propose a systemic representation of a real‐time vehicle management mechanism for urban transportation.

The COVID-19 pandemic has disrupted the ‘real’ world and substantially impacted the virtual world and thus the Internet ecosystem. It has caused a significant exogenous shock that offers a wealth of natural experiments and produced new data about broadband, clouds, and the Internet in times of crisis. In this chapter, we characterise and evaluate the evolving impact of the global COVID-19 crisis on traffic patterns and loads and the impact of those on Internet performance from multiple perspectives. While we place a particular focus on deriving insights into how we can better respond to crises and better plan for the post-COVID-19 ‘new normal’, we analyse the impact on and the responses by different actors of the Internet ecosystem across different jurisdictions. With a focus on the USA and Europe, we examine the responses of both public and private actors, with the latter including content and cloud providers, content delivery networks, and Internet service providers (ISPs). This chapter makes two contributions: first, we derive lessons learned for a future post-COVID-19 world to inform non-networking spheres and policy-making; second, the insights gained assist the networking community in better planning for the future.