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Although additive manufacturing (AM; 3D printing/3DP) is presently in its infancy, once it becomes economically viable for mass production, it would revolutionize the operation and supply chain network of traditional businesses and manufacturing industries. To this end, approaches for ensuring a smooth transition of the economy, businesses, manufacturing centers and related services are being investigated. This review paper assesses the existing literature on the impact of AM on the maritime transportation sector.

This paper provides a systematic literature review through three methodological phases: (1) a comprehensive review of the number of English language literature studies published on the topics of AM or 3DP (1970–2021); (2) a bibliometric analysis of selected keyword combinations and (3) a detailed review on the impact of AM on different sectors.

The key findings are that existing studies do not attempt to forecast shipping volume and ton-miles that can be affected by the mainstreaming of the technology. Additionally, existing literature that focuses on the impact of the technology on different shipping categories is limited to studies on container ships.

The review identifies some potential areas of research that since maritime transportation will be affected by mainstreaming AM, it will have economic, social and environmental impacts on global trade that require future assessment.

Building on the conservation of resources (COR) theory, this study aims to investigate employee empowerment’s moderation effect on the relationship of situational (job satisfaction, affective commitment) and dispositional (positive affectivity, emotional intelligence) variables toward the emotional exhaustion of service employees amidst the pandemic.

In total, 288 service employees from various sectors in Indonesia participate as the study’s respondents. This study applies a two-stage structural equation modeling approach to test the hypotheses.

The results show that employee empowerment moderates situational and dispositional variables differently. While employee empowerment significantly influences situational variables, a different situation is found on dispositional variables, that employee empowerment does not significantly influence these variables. This study’s findings portray the COR theory in practice and clarify the importance of employee empowerment for employees with particular attributions.

The present study bears four limitations: the cross-sectional design; no exploration of dispositional and situational variables’ antecedents; the findings are limited to the service workers; and lastly, this study only takes Indonesian samples.

From a practical perspective, this study reveals which type of service employees are responsive to empowerment policy and which are prone to experience emotional exhaustion, particularly during a crisis.

By understanding what factors determine employee empowerment’s effectiveness, managers could maximize the impacts of their empowerment policies. Subsequently, it will create better service deliveries which might benefit the broader societal scope.

This study contributes to both theoretical and practical understanding. Theoretically, this study adds and promotes using a categorical lens to examine the pattern of interactions between organizations and employees.

The authors investigate how COVID-19 has influenced the amount, type or topics of abuse that UK politicians receive when engaging with the public.

This work covers the first year of COVID-19 in the UK, from March 2020 to March 2021 and analyses Twitter abuse in replies to UK MPs. The authors collected and analysed 17.9 million reply tweets to the MPs. The authors present overall abuse levels during different key moments of the pandemic, analysing reactions to MPs by gender and the relationship between online abuse and topics such as Brexit, the government’s COVID-19 response and policies, and social issues.

The authors have found that abuse levels towards UK MPs were at an all-time high in December 2020. Women (particularly those from non-White backgrounds) receive unusual amounts of abuse, targeting their credibility and capacity to do their jobs. Similar to other large events like general elections and Brexit, COVID-19 has elevated abuse levels, at least temporarily.

Previous studies analysed abuse levels towards MPs in the run-up to the 2017 and 2019 UK General Elections and during the first four months of the COVID-19 pandemic in the UK. The authors compare previous findings with those of the first year of COVID-19, as the pandemic persisted, and Brexit was forthcoming. This research not only contributes to the longitudinal comparison of abuse trends against UK politicians but also presents new findings, corroborates, further clarifies and raises questions about the previous findings.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-07-2022-0392

Recommendation systems are a fundamental tool for hotels to adopt a differentiating competitive strategy. The main purpose of this work is to use machine learning techniques to treat imbalanced data sets, not applied until now in the tourism field. These techniques have allowed the authors to analyse the influence of imbalance data on hotel recommendation models and how this phenomenon affects client dissatisfaction.

An opinion survey was conducted among hotel customers of different categories in 120 different countries. A total of 135.102 surveys were collected over eleven quarters. A longitudinal design was conducted during this period. A binary logistic model was applied using the function generalized lineal model (GLM).

Through the analysis of a representative amount of data, the authors empirically demonstrate that the imbalance phenomenon is systematically present in hotel recommendation surveys. In addition, the authors show that the imbalance exists independently of the period in which the survey is done, which means that it is intrinsic to recommendation surveys on this topic. The authors demonstrate the improvement of recommendation systems highlighting the presence of imbalance data and consequences for marketing strategies.

The main contribution of the current work is to apply to the tourism sector the framework for imbalanced data, typically used in the machine learning, improving predictive models.

The purpose of this study is to explore the paranormal tourist experience on ghost tours, taking into account the participants’ perceptions and their prior knowledge of the paranormal, in order to determine the principal components of the future of paranormal tourist experience.

The study is divided into two phases. The first phase is based on participant observation during a ghost tour. The second phase is based on a previously published framework for paranormal tourism. It introduces a qualitative adaptation of the orchestra model to look in-depth at how experiences with paranormal tours might shape the future of tourism as a major subtype.

Paranormal tourism has external (situational-enchantment, historical, mystical, ghostly and unsolved mysteries) and internal (affective, cognitive, sensory, behavior and relationship) components that are inter-linked. Future paranormal tourist experiences (FPTEs) must be focused on enhancing these aspects in order to offer an immersive experience.

Consequently, this paper proposes the FPTE model.

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.