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While the importance of human touch for maintaining a tech–touch balance has been stressed, little knowledge exists regarding how such human elements should be incorporated in service settings dominated by technologies. This study aims to examine the outcomes of human touch levels across different travel stages in a hotel stay context.

Data were collected through a survey on 900 participants. Latent class analysis was first conducted to categorize the sample into groups based on human touch levels. Hypotheses were then tested using regression-based moderation analysis with the PROCESS macro for SPSS.

Human touch level negatively predicts perceived risk, which is negatively associated with satisfaction. These effects are particularly significant at check-in and check-out stages. Informational privacy significantly moderates the effect of human touch level on perceived risk. Such interaction effects were spotted at the booking and check-out stages.

This study contributes to theory by revealing the role of human touch elements in technology-driven service scenarios and provides practical guidelines for hotels on sharpening service experience by integrating human touch and technology elements.

Through integrating the service encounter framework and concept of customer touchpoints, this study takes a different approach that integrates both “tech” and “touch” by investigating the effects of customer-owned touchpoints in each core stage of a hotel stay journey.

The impact of frontline robots (FLRs) on customer orientation perceptions remains unclear. This is remarkable because customers may associate FLRs with standardization and cost-cutting, such that they may not fit firms that aim to be customer oriented.

In four experiments, data are collected from customers interacting with frontline employees (FLEs) and FLRs in different settings.

FLEs are perceived as more customer-oriented than FLRs due to higher competence and warmth evaluations. A relational interaction style attenuates the difference in perceived competence between FLRs and FLEs. These agents are also perceived as more similar in competence and warmth when FLRs participate in the customer journey's information and negotiation stages. Switching from FLE to FLR in the journey harms FLR evaluations.

The authors recommend firms to place FLRs only in the negotiation stage or in both the information and negotiation stages of the customer journey. Still then customers should not transition from employees to robots (vice versa does no harm). Firms should ensure that FLRs utilize a relational style when interacting with customers for optimal effects.

The authors bridge the FLR and sales/marketing literature by drawing on social cognition theory. The authors also identify the product categories for which customers are willing to negotiate with an FLR. Broadly speaking, this study’s findings underline that customers perceive robots as having agency (i.e. the mental capacity for acting with intentionality) and, just as humans, can be customer-oriented.

The authors' research examines how negative electronic word-of-mouth (e-WOM) alters focal customers' post-recovery justice perceptions and attitudes to determine their future behavior with the service provider. Specifically, this paper develops and tests a conceptual model to investigate how negative e-WOM alters focal customers' perceptual and attitudinal outcomes after the service recovery experience. It also examines the post-recovery effect of negative e-WOM on focal customers’ willingness to patronize the service after their recovery experience.

To test the hypotheses, two pretests and two experimental studies with created scenarios in the retail context were conducted.

The authors' findings reveal that services are judged during and well beyond failure and recovery occurrences. To maintain a loyal customer base, service managers should develop processes that address service complaints both within and beyond the service consumption stage. The authors also find that despite a favorable recovery, focal customers gravitate toward the failure experience and develop unfavorable attitudes toward the service provider, leading to likely defections.

The authors' research demonstrates the persuasive power of negative e-WOM at the post-service recovery stage, making a unique contribution to the service recovery literature. This research also contributes to the persuasive effect of negative e-WOM, demonstrating message context as a boundary condition of negative e-WOM effects. In general, the authors' work highlights the importance of understanding the psychological processes involved in eliciting the persuasive influence of negative e-WOM in the post-service recovery stage that may lead to the defection of “so-called” successfully recovered customers.

By introducing the mass customization service mode into the cloud logistics environment, this paper studies the joint optimization of service provider selection and customer order decoupling point (CODP) positioning based on the mass customization service mode to provide customers with more diversified and personalized service content with lower total logistics service cost.

This paper addresses the general process of service composition optimization based on the mass customization mode in a cloud logistics service environment and constructs a joint decision model for service provider selection and CODP positioning. In the model, the two objective functions of minimum service cost and most satisfactory delivery time are considered, and the Pareto optimal solution of the model is obtained via the NSGA-II algorithm. Then, a numerical case is used to verify the superiority of the service composition scheme based on the mass customization mode over the general scheme and to verify the significant impact of the scale effect coefficient on the optimal CODP location.

(1) Under the cloud logistics mode, the implementation of the logistics service mode based on mass customization can not only reduce the total cost of logistics services by means of the scale effect of massive orders on the cloud platform but also make more efficient use of a large number of logistics service providers gathered on the cloud platform to provide customers with more customized and diversified service content. (2) The scale effect coefficient directly affects the total cost of logistics services and significantly affects the location of the CODP. Therefore, before implementing the mass customization logistics service mode, the most reasonable clustering of orders on the cloud logistics platform is very important for the follow-up service combination.

The originality of this paper includes two aspects. One is to introduce the mass customization mode in the cloud logistics service environment for the first time and summarize the operation process of implementing the mass customization mode in the cloud logistics environment. Second, in order to solve the joint decision optimization model of provider selection and CODP positioning, this paper designs a method for solving a mixed-integer nonlinear programming model using a multi-layer coding genetic algorithm.

In today's global and competitive corporate environment characterised by rapidly changing information, knowledge and technology (IKT), researchers must be upskilled in all aspects of research data management (RDM). This study investigates a set of capabilities and competencies required by researchers at selected South African public universities, using the community capability model framework (CCMF) in conjunction with the digital curation centre (DCC) lifecycle model.

The post-positivist paradigm was used in the study, which used both qualitative and quantitative methodologies. Case studies, both qualitative and quantitative, were used as research methods. Because of the COVID-19 pandemic rules and regulations, semi-structured interviews with 23 study participants were conducted online via Microsoft Teams to collect qualitative data, and questionnaires were converted into Google Forms and emailed to 30 National Research Foundation (NRF)-rated researchers to collect quantitative data.

Participating institutions are still in the initial stages of providing RDM services. Most researchers are unaware of how long their institutions retain research data, and they store and backup their research data on personal computers, emails and external storage devices. Data management, research methodology, data curation, metadata skills and technical skills are critically important RDM competency requirements for both staff and researchers. Adequate infrastructure, as well as human resources and capital, are in short supply. There are no specific capacity-building programmes or strategies for developing RDM skills at the moment, and a lack of data curation skills is a major challenge in providing RDM.

The findings of the study can be applied widely in research, teaching and learning. Furthermore, the research could help shape RDM strategy and policy in South Africa and elsewhere.

The scope, subject matter and application of this study contribute to its originality and novelty.

This paper aims to assess whether the current eResearch Knowledge Centre’s (eRKC) research support practices align with researchers’ requirements for achieving their research objectives. The study’s objectives were to assess the current eRKC research support services and to determine which are adequate and which are not in supporting the Human Sciences Research Council (HSRC) researchers.

This study uses interviews as part of the qualitative approach. The researcher chose to use interviews, as some aspects warranted further explanation during the interview. The interviews were scheduled using Zoom’s scheduling assistant. The interviews were semi-structured, guided by a flexible interview procedure and supplemented by follow-up questions, probes and comments. The research life cycle questions guided the interviews. The data obtained were coded and transcribed using MS Excel. The interview data were analysed, using NVivo, according to the themes identified in the research questions and aligned with the theory behind the study. Pre-determined codes were created in line with the six stages of the research life cycle and applied to group the data and extract meaning from each category. Interviewee responses were assigned to groups in line with the stages of the research life cycle.

The current eRKC research support services are aligned with the needs of HSRC researchers and highlight services that could be expanded or promoted more effectively to HSRC researchers. It proposes a new service, data analysis, and suggests that the eRKC could play a more prominent role in research impact, research data management and fostering collaboration with HSRC research divisions.

This study is limited to assessing the eRKC’s support practices at the HSRC in Pretoria, South Africa. A more comprehensive study is needed for HSRC research services, capabilities and capacity.

Assessment of eRKC followed a comprehensive interviewee schedule that followed Raju and Schoombee’s research life cycle model.

Zoom’s scheduling assistant may have generated Zoom fatigue and reduced productivity. Technical issues, losing time, communication gaps and distant time zones may have affected face-to-face interaction.

eRKC research support practices are rare in South Africa and most parts of the world. This study bridges the gap between theory and practice in assessing eRKC research support practices.

Smart services have gained attention both among academics and practitioners, but manufacturing firms struggle in getting their new smart services extensively adopted by customers, employees and distributors. The purpose of this paper is to identify and analyse the requirements of different actors and the interconnectedness between their requirements in introducing smart services.

An embedded single-case study was conducted with a manufacturing firm and its network, including its sales and service personnel, customers and external salespeople. Data were collected via 30 in-depth interviews.

The paper advances the multi-actor perspective by identifying the requirements of key actors for introducing smart services. These requirements were divided into eight categories: value of smart services, reliability of smart services, competence for smart services, data security and management, attitude towards services, reliance, knowledge of installed base of equipment and services and service reputation. The findings reveal the interconnectedness of different actors’ requirements for introducing new smart services and how discussion and relationships between actors affected their requirements.

The findings represent a comprehensive template of requirements, as well as mapping the interconnectedness of actors’ requirements, serving as a practical guideline for managers.

This study characterises the introduction of smart services as a multi-dimensional, interconnected effort by manufacturing firms and their networks. It shows that service introduction cannot be viewed as manufacturer’s development task or customers’ adoption decision only. Propositions are offered on how multiple actors’ viewpoints can be combined to achieve success in introducing smart services.

Drawing on person–environment fit theory, this study aims to investigate how the relationships between service task types (i.e. utilitarian and hedonic service tasks) and perceived authenticity (i.e. service and brand authenticity) differ under different conditions of service providers (human employee vs service robot). This study further examines whether customers’ stereotypes toward service robots (competence vs warmth) moderate the relationship between service types and perceived authenticity.

Using a 2 × 2 between-subjects experimental design, Study 1 examines a casual restaurant, whereas Study 2 assesses a theme park restaurant. Analysis of covariance and PROCESS are used to analyze the data.

Both studies reveal that human service providers in hedonic services positively affect service and brand authenticity more than robotic employees. Additionally, the robot competence stereotype moderates the relationship between hedonic services, service and brand authenticity, whereas the robot warmth stereotype moderates the relationship between hedonic services and brand authenticity in Study 2.

Restaurant managers need to understand which functions and types of service outlets are best suited for service robots in different service contexts. Robot–environment fit should be considered when developers design and managers select robots for their restaurants.

This study blazes a new theoretical trail of service robot research to systematically propose customer experiences with different service types by drawing upon person–environment fit theory and examining the moderating role of customers’ stereotypes toward service robots.

The use of recycled coarse aggregate in concrete structures promotes environmental sustainability; however, performance of these structures might be negatively impacted when it is used as a replacement to traditional aggregate. This paper aims to simulate recycled concrete beams strengthened with carbon fiber-reinforced polymer (CFRP), to advance the modeling and use of recycled concrete structures.

To investigate the performance of beams with recycled coarse aggregate concrete (RCAC), finite element models (FEMs) were developed to simulate 12 preloaded RCAC beams, strengthened with two CFRP strengthening schemes. Details of the modeling are provided including the material models, boundary conditions, applied loads, analysis solver, mesh analysis and computational efficiency.

Using FEM, a parametric study was carried out to assess the influence of CFRP thickness on the strengthening efficiency. The FEM provided results in good agreement with those from the experiments with differences and standard deviation not exceeding 11.1% and 3.1%, respectively. It was found that increasing the CFRP laminate thickness improved the load-carrying capacity of the strengthened beams.

The developed models simulate the preloading and loading up to failure with/without CFRP strengthening for the investigated beams. Moreover, the models were validated against the experimental results of 12 beams in terms of crack pattern as well as load, deflection and strain.

This study aims to highlight the importance of developing academic research in tourism and hospitality management into a more responsible approach, applying a multistakeholder model. This multistakeholder approach forces the tourist community to be considered when identifying the gaps and impacts of academic research.

This study suggests action research as one of the appropriate methodological approaches for conducting responsible research, as action research allows challenges to be overcome through the interaction of researchers and stakeholders. Principles of responsible research are indicated and exemplar studies that use action research are described.

Proposals and recommendations for responsible research are identified, such as demand-driven research, action research as a methodological approach and a way to address societal challenges, and the importance of considering the research ecosystem. In addition, some advantages (funding, reputation and legitimacy) and barriers (resources and publication) of responsible research are explained.

Practical implications are described. Conducting responsible research is oriented toward identifying real practical implications proposed and validated by the tourist community instead of being proposed solely by the researchers.

This paper emphasizes the need to work together with the tourist community and their stakeholders to enhance the real societal impact of academic research in tourism and hospitality management.

The authors would like to raise a self-critical debate for the future enrichment of research in the tourism industry. Research in this industry can contribute to solving significant societal problems. Responsible research can help scholars to be part of the solution to these challenges, working together with different tourism stakeholders.