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Under the background of low consumer financial knowledge and accumulated credit card liabilities, this study investigates the relationship between financial knowledge and responsible credit card behavior using data from the 2019 China Household Finance Survey (CHFS). From the perspective of consumer economic well-being, this study defines accruing credit card debt to buy houses and cars when loans with lower interest rates are available as irresponsible credit card behavior.

This study uses probit regressions to examine the association between financial knowledge and responsible credit card behavior because the dependent variable is a dummy variable. To alleviate endogeneity problems, this study uses instrument variables and Heckman’s two-step estimation. Furthermore, to explore the potential mediators in this process, this study follows the stepwise regression method. Finally, this study introduces interaction terms to examine whether this association differs in different groups.

The results indicate that financial knowledge is conducive to increasing the probability of responsible credit card behavior. Mediating analyses reveal that the roles of financial knowledge occur by increasing the degree of concern for financial and economic information and the propensity to plan. Moderating analyses show that the effects of financial knowledge on responsible credit card behavior are stronger among risk-averse consumers and in regions with favorable digital access.

This study measures responsible credit card behavior from the perspective of the consumer’s well-being, which enriches practical implications for consumer finance. Furthermore, this study explores the potential mediators influencing the process of financial knowledge that affects responsible credit card behavior and identifies moderators to conduct heterogeneous analyses, which helps comprehensively understand the nexus between financial knowledge and credit card behavior. By achieving these contributions, this study helps to curb the adverse effects of irresponsible credit card behavior on consumers’ well-being and the economic system and helps policymakers promote financial knowledge to fully prevent irresponsible credit card behavior.

This chapter explores middle leadership identity through the real-world accounts of how two middle leaders construct and develop their leadership identity and how this impacts the way their middle leadership is practiced. Leadership identity, an internal narrative of oneself as a leader which is practised professionally in context, represents a concept that is best understood as being unique to an individual, enduring over time, and a consequence of human experiences. Middle leadership is often the first promotion for teachers from teacher to leader and, as such, how middle leaders perceive themselves as a leader and how this formative process of leadership identity underpins middle leaders’ practices can make a significant impact on a leader’s decision making, professional relationships, behaviours, and actions. This chapter is co-authored by two researchers and two middle leaders with the intention of understanding middle leader identity development and its influence on middle leadership practices. Using interviews, middle leaders’ stories of identity were co-composed and re-storied to construct each middle leader’s narrative. This chapter concludes with a discussion on the influences of identity for middle leaders and considerations for leadership development.

Autonomous mobile robots (AMRs) play a crucial role in industrial and service fields. The paper aims to build a LiDAR-based simultaneous localization and mapping (SLAM) system used by AMRs to overcome challenges in dynamic and changing environments.

This research introduces SLAM-RAMU, a lifelong SLAM system that addresses these challenges by providing precise and consistent relocalization and autonomous map updating (RAMU). During the mapping process, local odometry is obtained using iterative error state Kalman filtering, while back-end loop detection and global pose graph optimization are used for accurate trajectory correction. In addition, a fast point cloud segmentation module is incorporated to robustly distinguish between floor, walls and roof in the environment. The segmented point clouds are then used to generate a 2.5D grid map, with particular emphasis on floor detection to filter the prior map and eliminate dynamic artifacts. In the positioning process, an initial pose alignment method is designed, which combines 2D branch-and-bound search with 3D iterative closest point registration. This method ensures high accuracy even in scenes with similar characteristics. Subsequently, scan-to-map registration is performed using the segmented point cloud on the prior map. The system also includes a map updating module that takes into account historical point cloud segmentation results. It selectively incorporates or excludes new point cloud data to ensure consistent reflection of the real environment in the map.

The performance of the SLAM-RAMU system was evaluated in real-world environments and compared against state-of-the-art (SOTA) methods. The results demonstrate that SLAM-RAMU achieves higher mapping quality and relocalization accuracy and exhibits robustness against dynamic obstacles and environmental changes.

Compared to other SOTA methods in simulation and real environments, SLAM-RAMU showed higher mapping quality, faster initial aligning speed and higher repeated localization accuracy.

Due to the impact of the pandemic that enforced mass closures and lock downs, galleries, libraries, archives, and museums [GLAM] institutions around the world were required to re-think how they interacted with the public. As a result of the measures that enforced isolation, distancing, and increased hygiene requirements, the usefulness of virtual technologies as a storytelling medium has come into sharper focus. This chapter will explore the emergence of augmented reality as a viable post-COVID-19 solution to meaningful digital narrative creation and user interaction in the museum environment. This chapter will concentrate on the development of a project between the University of South Australia [UniSA] and the South Australian Museum [SAM] to explore how it might be possible to create sustainable immersive stories within this environment.

The purpose of this paper is to conceptualize the notion of thin crossing points from a social network perspective and to outline the concrete networking strategies that enable salespeople to foster mutually valuable resource exchange (i.e. to thin crossing points) across a selling ecosystem.

The authors integrate extant theoretical perspectives to advance a conceptual framework of sales-related networking across three key actors in a selling ecosystem: intraorganizational selling actors and actors in customers and external partner organizations.

Thin crossing points are defined as figurative transaction points at the boundary between organizations or organizational subunits at which actors engage in mutually valuable resource exchange in the process of value cocreation. To thin crossing points with key ecosystem actors, salespeople must adapt networking strategies considering the time and trust constraints inherent in a network relationship. Such constraints inform the most advantageous network centralities (degree, eigenvector and betweenness) and actions to impact key network properties (tie strength, contact diversity) that enable salespeople to efficiently develop social capital and thus to optimally thin crossing points across a selling ecosystem.

To the best of the authors’ knowledge, this study is the first social network-based exploration of salespeople’s role in thinning crossing points with key ecosystem actors. It advances a novel conceptual framework of sales-related networking strategies that foster social capital development and optimally thin crossing points across a selling ecosystem.

Three scenario-based experiments were conducted to explore the influence of the base option’s price format (just-at vs just-below) on tourists’ upgrade intention. The findings of this research indicated that tourists are more inclined to upgrade the option when the base option’s price is presented in a just-at condition due to the mediating role of tourists’ price perceptions of the upgrade option. This study discovered that the just-at (vs just-below) pricing strategy can lower tourists’ price perceptions of the upgrade choice. This research further explored the moderating of tourists’ mindsets. It was found the threshold-crossing effect will disappear for tourists with fixed mindsets. This study also provides practical implications for travel service providers to set up appropriate pricing strategies to attract tourists to make upgrade decisions.

Research has focused primarily on the antecedents that influence the risk taking of CEOs themselves. This study examines how an important event experienced by a CEO at a direct rival firm influences a CEO's risk-taking. It also examines how prior firm performance relative to aspirations moderates the relationship.

In order to test the hypothesis, the authors perform an a difference-in-differences methodology.

Using a difference-in-differences methodology, we find that when a CEO wins a prestigious CEO award, competitor CEOs increase their firm risk-taking in the post-award period. The proclivity becomes stronger when their prior firm performance relative to aspirations is better. These findings suggest that a CEO winning a prominent CEO award influences competitor CEOs' risk-taking.

This study contributes to the literature on managerial risk-taking by highlighting that a star CEO winning a prominent award may serve as a striving aspiration and induce competitor CEOs to take risks, and that two different types of aspirations – striving and competitive aspirations – interact to influence the competitor CEOs' risk-taking.

This study aims to contribute novel insights into understanding and mitigating the harmful consequences of abusive supervision (AS) by examining the association between AS experiences, revenge, forgiveness, and the moderating role of emotional intelligence (EI). The key argument is that employees' EI can influence the AS experience through affective processes, countering supervisors' abusive behaviors.

A between-person scenario-based experiment was conducted with 366 participants divided into AS and control groups. The study explored the association between AS experience and revenge/forgiveness, mediated by core affect (valence and activation). EI abilities were measured as a moderator. Data analysis examined the relationships and interactions among AS, revenge/forgiveness, EI, and affective experiences.

The study reveals significant findings indicating that AS experiences were positively associated with revenge and negatively associated with forgiveness. The mediation analysis confirmed the role of core affect in these relationships. EI emerged as a moderator, shaping the association between AS experiences and revenge/forgiveness. Importantly, participants with higher EI exhibited lower revenge intentions, demonstrating the potential of EI to mitigate the adverse effects of AS. Unexpectedly, individuals with high EI also expressed fewer forgiveness intentions.

This study provides a comprehensive understanding of how employees can effectively counterbalance the impact of AS through higher levels of strategic EI. Examining core affect as a mediator offers novel insights into coping mechanisms in response to AS experiences and their consequences.

The study acknowledges several limitations, as the scenarios may only partially capture the complexities of real-life AS situations. The focus on a specific context and the sample characteristics limit the generalizability of the findings. Future research should explore diverse organizational contexts and employ longitudinal designs.

The findings have practical implications for organizations as enhancing employees' EI skills through training programs interventions and integrating EI into organizational culture and leadership conduct.

Cultural heritage archiving is experiencing an increase in digitalisations of artefacts in the last 15 years. The reason behind this trend is a demand for providing information about the artefact in a more accessible way to the audience, for example, through online delivery or virtual reality. Other reasons might be to simplify and automate the management of artefacts. Having a ‘digital copy’ of artefacts, allows one to search an archive and plan its storage and dissemination in a comprehensive manner. With the increased digitalisation comes an increased use of artificial intelligence [AI] applications. AI can be very beneficial in classifying artefacts automatically through machine learning [ML] and natural language processing [NLP]. For example, an algorithm can identify the source and age of artefacts based on an image and can do this much faster for a large collection of photos than a human. Although AI provides many benefits, it also presents challenges: Sophisticated AI techniques require certain insights on how they work, need specialists to customise a solution, and require an existing large dataset to train an algorithm. Another challenge is that typical AI techniques are regarded as black boxes, which means they decide, but it is not obvious why a decision has been made. This chapter describes a project in collaboration with the South Australian Museum [SAM] on the application of AI to extract material lists from a description of artefacts. A large dataset to train an algorithm did not exist, and hence, a customised approach was required. The outcome of the project was the application of NLP in combination with easy-to-customise rules that can be applied by non-IT specialists. The resulting prototype achieved the extraction of materials from a large list of artefacts within seconds and a flexible solution that can be applied on other collections in the future.

The use of insects as food is a proposed solution for the increased demand for food worldwide, but it lacks acceptance because of restrictive emotional factors. This article aims to understand better customers' emotions’ role in considering and consuming insect-based food.

To assess their acceptance, an experiment was developed with 38 participants living in Portugal to identify how people feel when consuming processed insect bars compared to cereal bars (of equal flavour). A video was recorded “before”, “during” and “after” the consumption of such foods, and the triggered emotions and affective states were identified using the Facial Action Coding System (FACS) and the circumplex model of affect, respectively. After consumption, the Self-Assessment Manikin (SAM) was asked to be completed.

It was observed that the valence and arousal of the emotions and affective states triggered during consumption were higher in the insect bar than in the cereal bar. Its consumption resulted in surprise and a positive evaluation. Processed insect-based foods may result in a potentially increased acceptance of this new food alternative in the market.

Prior studies briefly identified disgust as a primary emotion activated by insect-based food. The current research deeply studied emotional responses to insect-based processed foods in the Western world using the dimensional emotional models. This study offers arguments for the insect-based food industry to invest in processed food justified by its potential for acceptance. In addition, it motivates further research focused on other insect-based products (e.g. non-processed ones).