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Based on appraisal theory and social response theory, this study aims to explore the mechanism of AI failure types on consumer recovery expectation from the perspective of service failure assessment and validate the moderate role of anthropomorphism level.

Three scenario-based experiments were conducted to validate the research model. First, to test the effect of robot service failure types on customer recovery expectation; second, to further test the mediating role of perceived controllability, perceived stability and perceived severity; finally, to verify the moderating effect of anthropomorphic level.

Non-functional failures reduce consumer recovery expectation compared to functional failures; perceived controllability and perceived severity play a mediating role in the impact of service failure types on recovery expectation; the influence of service failure types on perceived controllability and perceived severity is moderated by the anthropomorphism level.

The findings enrich the influence mechanism and boundary conditions of service failure types, and have implications for online enterprise follow-up service recovery and improvement of anthropomorphic design.

The purpose of this paper was to investigate the relationships among the intellectual ability of artificial intelligence (AI), cognitive emotional processes and the positive and negative reactions of human members. The authors also examined the moderating role of AI status in teams.

The authors designed an experiment and recruited 120 subjects who were randomly distributed into one of three groups classified by the upper, middle and lower organization levels of AI in the team. The findings in this study were derived from subjects’ self-reports and their performance in the experiment.

Regardless of the position held by AI, human members believed that its intelligence level is positively correlated with dependence behavior. However, when the AI and human members are at the same level, the higher the intelligence of AI, the more likely it is that its direct interaction with team members will lead to conflicts.

This paper only focuses on human–AI harmony in transactional work in hybrid teams in enterprises. As AI applications permeate, it should be considered whether the findings can be extended to a broader range of AI usage scenarios.

These results are helpful for understanding how to improve team performance in light of the fact that team members have introduced AI into their enterprises in large quantities.

This study contributes to the literature on how the intelligence level of AI affects the positive and negative behaviors of human members in hybrid teams. The study also innovatively introduces “status” into hybrid organizations.

Customers' co-design behavior is an important source of knowledge for product innovation. Firms can regulate the focus of information interaction with customers to set goals and motivate their co-design behavior. Drawing on regulatory fit theory and construal level theory, the authors build a research model to study whether the fit between the regulatory focus of firms' task invitations (promotion focus vs prevention focus) and their feedback focus (self-focused vs other-focused) can enhance co-design behavior by improving customers' experiences (perceived meaning, active discovery and perceived empowerment).

The authors conducted two online between-subjects experiments to validate the proposed research model.

The two online experiments reveal that customers' experiences are enhanced when the feedback focus is congruent with the regulatory focus of the firm's task invitations. Specifically, self-focused feedback has a stronger positive effect on customers' experiences in the prevention focus context. Other-focused feedback has a stronger positive effect on customers' experiences in the promotion focus context. Moreover, customers' experience significantly and positively affects co-design behavior (i.e. co-design effort and knowledge contribution).

This work provides theoretical and practical implications for firms to improve the effectiveness of information interaction with their customers and eventually ensure the sustainability of co-design.

Despite corporate communications having an immense impact on corporate success, there is a lack of dedicated techniques for their management and visualization. A potential strategy is to apply business process management (BPM) approach with business process model and notation (BPMN) modeling techniques.

The goal of this study was to gain empirical insights into the cognitive effectiveness of BPMN-based corporate communications modeling. To this end, experimental research was performed in which subjects tested two modeling notations – standardized BPMN conversation diagrams and a BPMN extension with corporate communications-specific concepts.

Standard conversation diagrams were demonstrated to be more time-efficient for designing and interpreting diagrams. However, the subjects made significantly fewer mistakes when interpreting the diagrams modeled in the BPMN extension. Subjects also evolved positive perceptions toward the proposed extension.

BPMN-based corporate communications modeling may be applied to organizations to depict how formal communications are or should be performed consistently, effectively and transparently by following and integrating with BPM approaches and modeling techniques.

The paper provides empirical insights into the cognitive effectiveness of corporate communications modeling based on BPMN and positions the corresponding models into typical process architecture.

Service robots are expected to become increasingly common, but the ways in which they can move around in an environment with humans, collect and store data about humans and share such data produce a potential for privacy violations. In human-to-human contexts, such violations are transgression of norms to which humans typically react negatively. This study examines if similar reactions occur when the transgressor is a robot. The main dependent variable was the overall evaluation of the robot.

Service robot privacy violations were manipulated in a between-subjects experiment in which a human user interacted with an embodied humanoid robot in an office environment.

The results show that the robot's violations of human privacy attenuated the overall evaluation of the robot and that this effect was sequentially mediated by perceived robot morality and perceived robot humanness. Given that a similar reaction pattern would be expected when humans violate other humans' privacy, the present study offers evidence in support of the notion that humanlike non-humans can elicit responses similar to those elicited by real humans.

The results imply that designers of service robots and managers in firms using such robots for providing service to employees should be concerned with restricting the potential for robots' privacy violation activities if the goal is to increase the acceptance of service robots in the habitat of humans.

To date, few empirical studies have examined reactions to service robots that violate privacy norms.

A humanoid intelligent robot (HIR) possessing a human-like appearance can undertake human jobs, interact, communicate and even transmit emotions to human beings. Such robots have gradually been integrated into people's daily life and production scenarios. However, it is unclear whether and by what mechanism HIRs can stimulate people’s risk perception and its impact on consumption attitudes. Based on the risk decision theory, this study aims to take the social value substitution attribute of a HIR as the incentive and analyzes the influence of social value substitution and risk perception on the customers’ consumption attitudes.

Three experiments were conducted to investigate the related questions about the social value substitution attribute of a HIR, its impact on risk perception and the customers’ consumption attitudes.

The results reveal that physical labor, intellectual labor, friendship, kinship and the ego constitute the hierarchical elements of social value substitution. Among them, physical labor and intellectual labor pertain to the dimension of social function value substitution, while friendship, kinship and ego pertain to the dimension of social presence value substitution; social function value substitution and social presence value substitution affect the subjects’ risk perception positively, but the latter arouses a stronger risk perception; the 2 (risk perception of social function value: security/danger) × 2 (risk perception of social presence value: security/danger) condition corresponds to diverse consumption attitudes.

The results enrich the theories of the “cha-xu pattern” and “uncanny valley” and provide reference for the healthy development of the HIR industry.

The purpose of this study was to investigate trust within human-AI teams. Trust is an essential mechanism for team success and effective human-AI collaboration.

In an online experiment, the authors investigated whether trust perceptions and behaviours are different when introducing a new AI teammate than when introducing a new human teammate. A between-subjects design was used. A total of 127 subjects were presented with a hypothetical team scenario and randomly assigned to one of two conditions: new AI or new human teammate.

As expected, perceived trustworthiness of the new team member and affective interpersonal trust were lower for an AI teammate than for a human teammate. No differences were found in cognitive interpersonal trust and trust behaviours. The findings suggest that humans can rationally trust an AI teammate when its competence and reliability are presumed, but the emotional aspect seems to be more difficult to develop.

This study contributes to human–AI teamwork research by connecting trust research in human-only teams with trust insights in human–AI collaborations through an integration of the existing literature on teamwork and on trust in intelligent technologies with the first empirical findings on trust towards AI teammates.

Preservice English teachers are expected to use literary theories and criticism to read and respond to literary texts. Over the past century, two of the most common approaches to literary encounters in secondary schools have been New Criticism – particularly the practice of close reading – and Rosenblatt's transactional theory, both of which have been expanded through critical theorizing along the way. Elucidated by data produced in iterative experiments with Frost's “The Road Not Taken,” the authors reconceptualize the reader, the text, and close reading through the critical posthuman theory of reading with love as a generative way of thinking outside of the habitual practices of European humanisms.

In “thinking with” (Jackson and Mazzei, 2023) desiring-machines, affect, Man and critical posthuman theory, this post qualitative inquiry maps how the “The Road Not Taken” worked when students plugged into it iteratively in processes of reading with love, an affirmative and creative series of experiments with literature.

This study mapped how respect for authority, the battle of good v evil, individualism and meritocracy operated as desiring-machines that channeled most participants’ initial readings of “The Road Not Taken.” In subsequent experiments with the poem, the authors demonstrate that reading with love as a critical posthuman process of reading invites participants to exceed the logics of recognition and representation, add or invent additional ways of being and relating to the world and thereby produce the possibility to transform a world toward greater inclusivity and equity.

The authors reconceptualize the categories of “the reader” and “the text” from Rosenblatt’s transactional theory within practices of reading with love, which they situate within a critical posthuman theory. They eschew separating efferent and aesthetic reading stances while also recuperating practices of “close reading,” historically associated with the New Critics, by demonstrating the generativity of critically valenced “close reading” within a Deleuzian process of reading with love.

In order to estimate the value of semi-automated subject indexing in operative library catalogues, the study aimed to investigate five different automated implementations of an open source software package on a large set of Swedish union catalogue metadata records, with Dewey Decimal Classification (DDC) as the target classification system. It also aimed to contribute to the body of research on aboutness and related challenges in automated subject indexing and evaluation.

On a sample of over 230,000 records with close to 12,000 distinct DDC classes, an open source tool Annif, developed by the National Library of Finland, was applied in the following implementations: lexical algorithm, support vector classifier, fastText, Omikuji Bonsai and an ensemble approach combing the former four. A qualitative study involving two senior catalogue librarians and three students of library and information studies was also conducted to investigate the value and inter-rater agreement of automatically assigned classes, on a sample of 60 records.

The best results were achieved using the ensemble approach that achieved 66.82% accuracy on the three-digit DDC classification task. The qualitative study confirmed earlier studies reporting low inter-rater agreement but also pointed to the potential value of automatically assigned classes as additional access points in information retrieval.

The paper presents an extensive study of automated classification in an operative library catalogue, accompanied by a qualitative study of automated classes. It demonstrates the value of applying semi-automated indexing in operative information retrieval systems.

Advances in technology and the popularity of social media influencers have sparked a rise of “virtual influencers (VIs).” This study examines consumer attitudes toward VIs in social networking services and explores factors that enhance or dampen these attitudes. In three experiments, it was explored how contextual factors (background and companion) interact with human (HIs) and VIs, influencing attitudes through trustworthiness.

Three experiments were conducted using an online panel (N = 894). All experiments were based on the comparison between HIs and VI with mediating role of trustworthiness. In Studies 2 and 3, moderated mediation analyses were conducted to test hypotheses.

The results revealed that human-like VI was less trusted than animi-like VI or HIs. However, the perceived trustworthiness toward VI was enhanced when the VI was in a virtual (vs. real) environment (Study 2) or accompanied by a virtual (vs. human) companion (Study 3), leading to positive attitudes.

This research not only enriches relevant literature (avatars and SMIs) but also provides actionable insight for practitioners who design and utilize VIs. This paper proposes novel and handy tactics to enhance consumers' trustworthiness in and attitudes toward VIs.