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This study aims to understand how and when employees' pandemic fears influence their lateness attitude, with a particular focus on how this influence is mediated by emotional exhaustion and moderated by a perceived safety climate.

Survey data were collected among employees in the retail sector.

A core mechanism that explains the escalation of pandemic fears into beliefs that tardiness is acceptable is employees' sense that employees are emotionally overextended by work. The extent to which employees perceive that their organization prioritizes safety issues subdues this detrimental process though.

For human resource management (HRM) practice, the findings point to the notable danger that employees who cannot stop ruminating about an external crisis, and feel emotionally overburdened as a result, might compromise their own organizational standing by devoting less effort to punctuality. To disrupt this dynamic, HR managers can create organizational climates that emphasize safety practices.

This study adds to HRM research by revealing a pertinent source of personal adversity, pandemic fears, and how the fears affects tendencies to embrace tardiness at work. The study explicates how emotional exhaustion functions as a core conduit that connects this resource-draining condition with propensities to show up late, as well as how safety climate perceptions can buffer this translation.

This study aims to explore families that travel with children, as focuses on vulnerabilities, resource constraints and service exclusion through the lens of transformative service research (TSR). This paper investigates: how the experienced vulnerability of these families is shaped by structural, interpersonal and intrapersonal constraints, and how the constraints influence the family tourist-resource interaction in the air travel service encounter.

In total, 2,855 reviews of the family tourists with children were analyzed with text mining, t-test and multidimensional scaling using the interpretive language R to answer the research questions with analyses on unstructured (e.g. text) and structured (e.g. consumer rating) data.

The findings of the empirical investigation answered how experienced vulnerability is shaped by structural, interpersonal and intrapersonal resource constraints and the types of family tourist-resource interaction in the travel service encounter to understand the resource constraints. The findings of this paper help examine family tourism experiences from a value formation perspective to unfold how stakeholders interact to form value while increasing and decreasing their well-being by the value of co-creation and co-destruction.

This research helps advance the TSR’s service inclusion framework by enabling opportunities, offering choice, relieving suffering and fostering happiness with empirical findings in travel service encounters. These findings are particularly insightful to family tourists with children struggling with unfair access and treatment in aeromobility service encounters, which may help enhance the well-being of individuals and communities.

This study tries to examine the factors that influence the adoption of e-governance mobile applications among Indian citizens. In addition, this study aims to analyse the impact of these factors on the adoption process.

The study used convenience sampling procedure to collect the data from 431 citizens of India. Confirmatory factor analysis and structural equation modelling techniques were used to assess the validity of scale and test the hypotheses.

The finding reveals that the information quality (IQ), perceived usefulness, social influence and government appeal (GA) significantly and positively impacted the attitude of citizen towards the m-governance. In addition, perceived ease of use was not significantly and positively impacted the citizen towards the m-governance.

This study aims to contribute to the existing literature on m-governance adoption in the developing nation. The study intends to provide insightful information on the factors influencing the adoption of m-governance. Also, this study seeks to make a scholarly contribution and provide practical insights for professionals in the industry and government departments.

Mobile applications transform the government operations and enhance the efficiency of government service delivery. Although there are numerous benefits of m-government application, but still the adoption rate of m-governance is steady. The study uses technology acceptance model along with incorporated two additional constructs, i.e. IQ and GA, to make model more comprehensive and robust to understand the m-governance adoption intention.

This study examines whether US effective tax rates on foreign income of US multinationals (MNCs) vary according to the favorability of US macroeconomic conditions relative to those of non-US countries. We use the pre-Tax Cuts and Jobs Act of 2017 regime as our setting and present evidence that US effective tax rates on foreign earnings are higher (lower) in periods when macroeconomic conditions in the US are favorable (unfavorable) relative to those elsewhere in the world. These results imply that firms seek to maximize after-tax returns when making asset allocation decisions, even when faced with US repatriation tax costs. We provide further evidence indicating that our primary results vary predictably according to certain firm characteristics, namely the ability to acquire funds for investment through less expensive means than repatriation of foreign profits, high intangible asset intensity, and tax aggressiveness. Finally, we show that economic uncertainty in the US counters the positive effects of favorable US macroeconomic conditions on US effective tax rates on foreign earnings. Our findings have implications for the policy debate around the US taxation of foreign earnings and provide a (partial) explanation for the observed lower-than-expected levels of repatriation activity following the implementation of the Tax Cuts and Jobs Act of 2017.

Large-scale and complex issues tend to require a system of interconnected teams (i.e., multiteam systems) that offer more manpower, resources, and flexibility to meet more challenging demands. However, multiteam systems often work within “extreme environments” that can be very stressful, and the impact of this stress can deplete team members’ Well-Being and hinder team performance. Current research on multiteam systems does not address the need to understand how environmental stressors may impact component teams and overall team functioning and how multiteam systems in these environments can regulate stress to overcome these problems. NASA’s spaceflight multiteam system provides a unique example that organizational researchers can look at to understand how the Mission Control team helps regulate stress in the spaceflight team operating within an isolated, confined, and extreme environment. This chapter articulates how NASA’s spaceflight multiteam system stress regulation practices can inform organizational psychologists and advance our understanding of multiteam system functioning.

Visual simultaneous localization and mapping (SLAM) has limitations such as sensitivity to lighting changes and lower measurement accuracy. The effective fusion of information from multiple modalities to address these limitations has emerged as a key research focus. This study aims to provide a comprehensive review of the development of vision-based SLAM (including visual SLAM) for navigation and pose estimation, with a specific focus on techniques for integrating multiple modalities.

This paper initially introduces the mathematical models and framework development of visual SLAM. Subsequently, this paper presents various methods for improving accuracy in visual SLAM by fusing different spatial and semantic features. This paper also examines the research advancements in vision-based SLAM with respect to multi-sensor fusion in both loosely coupled and tightly coupled approaches. Finally, this paper analyzes the limitations of current vision-based SLAM and provides predictions for future advancements.

The combination of vision-based SLAM and deep learning has significant potential for development. There are advantages and disadvantages to both loosely coupled and tightly coupled approaches in multi-sensor fusion, and the most suitable algorithm should be chosen based on the specific application scenario. In the future, vision-based SLAM is evolving toward better addressing challenges such as resource-limited platforms and long-term mapping.

This review introduces the development of vision-based SLAM and focuses on the advancements in multimodal fusion. It allows readers to quickly understand the progress and current status of research in this field.

Synthetic biology begins with the underlying assumption that life and life forms can be divided into parts and reassembled or redesigned according to the whims of their creators. Therefore, synthetic biology needs to be at the centre of ethical thinking since it engages the very concept of life and radically changes it. In this paper, we will investigate the phenomenon of synthetic biology through an ethical analysis of the unfulfilled promises and potential perils surrounding this technology. The paper consists of four parts. In the first part, we will deal with the problem of defining synthetic biology since it is a field in which many scientific disciplines meet and intertwine. The second part will present a brief history of systemic biology and the groundbreaking creation of Synthia, the first synthetic organism. The third part focuses on synthetic biology's potential benefits and some prominent ethical issues. In the fourth part, we will point out the problem of synthetic biology regulation. In conclusion, we will highlight the essential ethical remarks on synthetic biology and provide the impetus for further ethical debate.

Natural disasters represent an increasing threat to businesses, putting at risk their continuity in light of sustainable performance conditions. The present chapter explores the role of organizational resilience and of human capital in manufacturing companies hit by a natural disaster, an earthquake in the current study, by considering performance in the long run. In doing so, a survey has been performed on a sample of 131 manufacturing companies hit by the Emilia earthquake (Italy) in 2012, considering both perceptual data and balance sheet data. This represents a key contribution of this chapter, as extant literature on the impact of resilience on business performance has mainly used perceptual data; conversely, our study, considering balance sheet data, enables a more comprehensive and realistic view of the phenomenon. The sample was selected from the AIDA database, as it includes revenue data that we could add to the perceptual measures obtained by administering a structured questionnaire. Partial least squares structural equation modeling (PLS-SEM) was then employed. The results show the importance of developing adaptive processes that leverage on the organization’s human capital and resilience to respond to adverse exogenous events. More specifically, it has been found that human capital and organizational resilience are profitable to post-disaster economic performance in the long run, supporting the economic sustainability of affected businesses. The implications are related to reinforcing new business solutions and adaptive strategies, looking at both organizational resilience and human capital investment to reach a stable economic business performance in the long-run after a detrimental event.