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This paper aims to study the value of informal care (IC) time from the perspective of caregivers using two alternative contingent valuation tools – willingness to pay (WTP) and willingness to accept (WTA) – and to identify the variables that affect the stated values.

The authors used data from a multi-centre study of 610 adult caregivers conducted in two Spanish regions in 2013. The existence of “protest zeros” and “economic zeros” because of the severe budgetary constraints of the households was also considered. Two-part multivariate models were used to analyse the main factors that explained the declared values of WTA and WTP.

The average WTP and WTA were €3.12 and €5.98 per hour of care, respectively (€3.2 and €6.3 when estimated values for “protest zeros” and “economic zeros” were considered). Some explanatory variables of WTA and WTP are coincident (place of residence and intensity of care time), whereas other variables only help to explain WTP values (household and negative coping with caregiving) or WTA values (age and burden of care). Some nuances are also identified when comparing the results obtained without protest and economic zeros with the estimated values of these special zeros.

Studies analysing the determinants of WTP and WTA in IC settings are very scarce. This paper seeks to provide information to fill this gap. The results indicate that the variables that explain the value of IC from one perspective may differ from the variables that explain it from an alternative perspective. Given the relevance of contextual factors, studies on the topic should be expanded, and care should be taken with the extrapolation of results across countries and settings.

The topics of gender and sustainability are firmly anchored within a social discourse. Based on both factors, customers are placing demands on companies and have specific ideas on how they should be represented in advertising. The case study presented herein combines these two topics and examines the portrayal of gender in the external marketing communication of the fair fashion label ARMEDANGELS. By analysing individual Instagram publications, the case study identifies how the topic is generally portrayed on the company’s channel. Furthermore, the perspectives of customers are determined through conducted interviews. When comparing the two sides, it becomes apparent that customers mostly approve of the attempt to break with conservative gender roles as well as an equal representation of the male and female personas. In addition to expanding the theoretical considerations of the triple bottom line as well as the S-O-R model, we derive recommendations for ARMEDANGELS and for other companies in the fashion industry. For customer retention purposes, companies should therefore focus on aligning the sexes, breaking with the general gender binary and integrating LGBTQ+ communities in future marketing measures.

Digital twin (DT) is an emerging technology that enables sophisticated interaction between physical objects and their virtual replicas. Although DT has recently gained significant attraction in both industry and academia, there is no systematic understanding of DT from its development history to its different concepts and applications in disparate disciplines. The majority of DT literature focuses on the conceptual development of DT frameworks for a specific implementation area. Hence, this paper provides a state-of-the-art review of DT history, different definitions and models, and six types of key enabling technologies. The review also provides a comprehensive survey of DT applications from two perspectives: (1) applications in four product-lifecycle phases, i.e. product design, manufacturing, operation and maintenance, and recycling and (2) applications in four categorized engineering fields, including aerospace engineering, tunneling and underground engineering, wind engineering and Internet of things (IoT) applications. DT frameworks, characteristic components, key technologies and specific applications are extracted for each DT category in this paper. A comprehensive survey of the DT references reveals the following findings: (1) The majority of existing DT models only involve one-way data transfer from physical entities to virtual models and (2) There is a lack of consideration of the environmental coupling, which results in the inaccurate representation of the virtual components in existing DT models. Thus, this paper highlights the role of environmental factor in DT enabling technologies and in categorized engineering applications. In addition, the review discusses the key challenges and provides future work for constructing DTs of complex engineering systems.

This paper claims to identify the behavioral and cultural features that push to use, or not, cryptocurrencies for electronic commerce. Indeed, despite the use of cryptocurrencies for electronic commerce spreading worldwide at a fast and growing pace, there are supporters and detractors among their users. The analysis of what distinguish these two groups of users is fundamental for understanding their different intention to use cryptocurrencies for electronic commerce.

A survey has been administered to 2,532 cryptocurrencies’ users across the USA and China, collecting data on their behavioral predispositions and cultural features. Results were then analyzed through structured equation modeling.

Results showed that while attitude, subjective norms, perceived behavioral control and herding behavior have a positive impact on the intention to use cryptocurrencies for electronic commerce, financial literacy has no influence. Cultural dimensions amplified or reduced the discovered relationships and caused different effects: positive for the USA and negative for China when considering illegal attitude and perceived risk.

Theory of planned behavior, financial behavior and cultural factors can, all together, represent a useful framework for envisioning the behavior of users in adopting cryptocurrencies for electronic commerce purposes through a test of all its elements. To the best of the authors’ knowledge, this is the first study considering behavior and cultural variables on the intention to use cryptocurrencies for electronic commerce as well as being the largest carried out, in terms of sample, on the cryptocurrency topic.

The aim of this study is to examine the behavioral intention (BI) to adopt the Coinbase Wallet by Spanish users.

A survey was administered to individuals residing in Spain between March and April 2021. There were 301 questionnaires analyzed. This research applies a new predictive model based on technology acceptance model (TAM) 2, the unified theory of acceptance and use of technology (UTAUT) model, the theory of perceived risk and the commitment trust theory. A mixed partial least squares structural equation modeling (PLS-SEM)/fuzzy-set qualitative comparative analysis (fsQCA) methodology was employed for the modeling and data analysis.

The results showed that all the variables proposed have a direct and positive influence on the intention to use a Coinbase Wallet. The findings present clear directions for traders, investors and academics focused on improving their understanding of the characteristics of these markets.

First, this study addresses important concerns relating to the adoption of crypto-wallets during the global pandemic. Second, this research contributes to the existing literature by adding electronic word of mouth (e-WOM), trust, web quality and perceived risk as new drivers of the intention to use the Coinbase Wallet, providing unique and innovative insights. Finally, the study offers a solid methodological contribution by integrating linear (PLS) and nonlinear (fsQCA) techniques, showing that both methodologies provide a better understanding of the problem and a more detailed awareness of the patterns of antecedent factors.

The purpose of this paper is to examine the association between consumers’ emotions towards emerging e-banking technology, perceived risk and subsequent intention to adopt emerging e-banking technology.

An online questionnaire was used to collect data, which were analysed in a quantitative study. The final sample of 224 educated young consumers, familiar with emerging e-banking technology, allowed testing of the research hypotheses by applying confirmatory factor analysis and structural equation modelling (SEM).

The empirical results indicate that deterrence emotions and hedonic motivation are associated with consumers’ perceived risk and, subsequently, their intention to adopt emerging e-banking technology. Additionally, analysing the moderating role of hedonic motivation in the association between consumers’ deterrence emotions towards emerging e-banking technology and their perceived risk highlights the significant association of deterrence emotions with perceived risk, regardless of the presence of hedonic motivation.

This study demonstrates the association between consumers’ emotions, perceived risk and subsequent intention to adopt emerging e-banking technology whilst underscoring the importance of distinguishing between different types of emotions and their corresponding appraisals.

The purpose of this study is to target utilizing Human resources (HRs) data analytics that may enhance strategic business, but little study has examined how it affects components. Data analytics, HRM and strategic business require empirical investigations and how to over come HR data analytics implementation issues.

A semi-systematic methodology for its evaluation allows for a more complete examination of the literature that emerges theoretical framework and a structured survey questionnaire for quantitative data collection from IT sector personnel. SPSS analyses data.

Future research is essential for organisations to exploit HR data analytics’ performance-enhancing potential. Data analytics should complement human judgment, not replace it. This paper details these transitions, the important contributions to theory and practice and future research.

Data analytics has grown rapidly and might make HRM practices faster, more efficient and data-driven. HR data analytics may improve strategic business. HR data analytics on employee retention, engagement and organisational success is insufficient. HR data analytics may boost performance, but there is limited proof. The authors do not know how HRM data analytics influences firms and employees.

Data analytics offers HRM new opportunities, along with technical and ethical challenges. This study makes a significant contribution to HR data analytics, evidence-based practice and strategic business literature. In addition to estimating turnover risk, identifying engagement factors and planning interventions to increase retention and engagement, HR data analytics can also estimate the risk of employee attrition.