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Terrorist events are unforeseen and have the potential to shake and rattle markets and investors. The purpose of this study is to examine whether major terrorist incidents have affected the Economic Sentiment Indicator (ESI) in four European countries.

An index is constructed that weights the severity of each event and then used to evaluate through the use of vector autoregressive and impulse response analysis estimation techniques whether or not and to what extent the ESI has been affected.

Effects were more pronounced and evident in the case of France and Germany while the ESI in Spain and Great Britain did not appear to be particularly affected by terrorist incidents.

The effects of terrorism on economic sentiment in other countries will provide additional evidence that will allow more robust and conclusive statistical inferences.

The impact of terrorist activity on the ESI for the four European countries studied here has not been examined before using VAR and impulse response analysis.

Purpose: In recent times, ‘artificial intelligence (AI)’ has been pervasive even in organisations or at home. AI is defined as programming computers or other technological devices to act, react, respond, or assist the same way humans do. AI has undeniably made people’s lives easier. In organisations, the impact of AI is even more visible. The main aim of this chapter is to examine the significant role of future work skill’s (FWS) each component in the field of on-growing automation. The focus will be especially on emotional and social intelligence (ESI) (a key component of FWS) while adopting AI.

Need of the Study: In terms of human resource management (HRM), AI is useful for people management, payroll services, staff monitoring and improving the recruiting network, among other things. Even managers put their organisation’s job openings on the web and get applicant resumes electronically. People and employees in the organisation have become more advanced and innovative due to AI. A device obtains employee attendance, and human resource (HR) can track their employees and their organisation’s workforce data. HR has now been awarded more authority to manage and fix their employee’s problems because of AI. In a rapidly changing world, AI is affecting all aspects. AI is yearning to automate all of the jobs.

Methodology: Now a question arises how we can stay relevant in AI economic development? As humans, we learned that every issue is a problem of optimisation because we simply require human skills to develop, create and innovate new things. Therefore, researchers recognised that adopting sustainable growth skills encourages people to continue learning throughout their lives. Moreover, AI has enabled machines the ability to learn over time. Still, they will never be able to develop new ideas like human intelligence. A machine can use only one fixed data algorithm. Now humans have made significant progress in various fields with the help of FWS; without integrated computer sciences, brain science would not make such an outstanding achievement. On the other hand, human minds are masters of their intelligence, such as creativity, complex problem-solving, cognitive thinking, ESI and communication. Breakthrough human mind are masters of algorithms represented people have to understand new trends of technology around us, and the best way to move forward is to be aware, adapt and update skills.

Practical Implications: However, AI is required because, regardless of technological advancements, AI is leading Industry 4.0. The industry’s transformation is in 4.0, and hopefully, 5.0 will jump on board soon. Undoubtedly, AI should streamline the process and eliminate redundancy or administrative tasks.

Finding: AI can be more effective in organisations if they incorporate other FWS, particularly the soft human ESI skills, whereas AI is present everywhere, we can still not neglect FWS, especially ESI. So, this chapter highlights the important role of soft skills, that is, ESI and FWS, while adapting AI for an effective HRM.

The chapter aims to evaluate the efficacy of stakeholder participation in the solid waste management system of Mauritius in view of providing a possible mechanism to attain the goals of a sustainable waste management framework.

The study employs qualitative indicators, namely, User Inclusivity and Producer Inclusivity of the Wasteaware Benchmark Indicators. Secondary data are used to conduct a critical and comprehensive analysis of the sub-indicators falling under each of the two main indicators to determine the overall compliance level with respect to stakeholder engagement of the waste management sector of Mauritius.

The results of the study show a LOW/MEDIUM compliance level for both User Inclusivity and Provider Inclusivity indicators, which indicates that improvement is required in the stakeholder engagement mechanism in Mauritius. The main weaknesses identified comprise of lack of an adequate legal framework with clear definition of waste types with regards to segregation, especially for non-hazardous wastes, low efficiency of sustainable waste management awareness campaigns and lack of inclusion of the informal sector. The main strengths identified consist of a proper bidding mechanism in place and a good level of equity in the provision of waste management services with respect to comingled waste collection. Suggested improvement areas include a revamping of the existing legal framework related to waste management to cater for higher inclusivity of all stakeholders together with including sustainable waste management topics in the formal education curriculum.

The User Inclusivity and Producer Inclusivity indicators were previously applied only to cities to measure the level of stakeholder participation, but this study has demonstrated that these indicators can also be adopted on a nation-wide level to evaluate stakeholder engagement. The use of these indicators together with secondary data presents a less time-consuming method to assess stakeholder participation in the waste sector, which can be particularly useful for Small Island Developing States.

The purpose of this study is twofold. First, the author posits and finds a significant positive relation between environmental performance (i.e., environmental efficiency) and firm performance (i.e., firm efficiency) by using a large panel sample from 1987 to 2015. The results are consistent with the notion in prior research (e.g., Porter, 1991; Porter & van der Linde, 1995) that pollution indicates a form of resource inefficiency and reducing pollution can increase firm performance. Second, managerial ability has recently received tremendous research attention. The author investigates the impact of managerial ability on the relation between environmental efficiency and firm efficiency and finds that the results are mainly driven by firms with low managerial ability.

This chapter investigates the predictability of the European monetary policy through the eyes of the professional forecasters from a large investment bank. The analysis is based on forward-looking Actual and Perceived Taylor Rules for the European Central Bank which are estimated in real-time using a newly constructed database for the period April 2000–November 2009. The former policy rule is based on the actual refi rate set by the Governing Council, while the latter is estimated for the bank’s economists using their main point forecast for the upcoming refi rate decision as a dependent variable. The empirical evidence shows that the pattern of the refi rate is broadly well predicted by the professional forecasters even though the latter have foreseen more accurately the increases rather than the policy rate cuts. Second, the results point to an increasing responsiveness of the ECB to macroeconomic fundamentals along the forecast horizon. Third, the rolling window regressions suggest that the estimated coefficients have changed after the bankruptcy of Lehman Brothers in October 2008; the ECB has responded less strongly to macroeconomic fundamentals and the degree of policy inertia has decreased. A sensitivity analysis shows that the baseline results are robust to applying a recursive window methodology and some of the findings are qualitatively unaltered from using Consensus Economics forecasts in the regressions.

This chapter focuses on the importance of social media for pop culture fans. A web survey for fans of the Twilight Saga is implemented, using the concepts of cognitive, affective, and evaluative social identity and personal, product, and situational involvement. The purpose is to examine to what degree social identity and involvement can explain pop culture fans’ future intention to travel, make recommendations to others, and use social media. Findings show that pop culture fans use social media to a large extent and that these means are important for making decisions about traveling and event participation. Moreover, the chapter shows that involvement dimensions are more important than social identity dimensions to explain future intention to travel, to recommend to others, and to use social media.

This chapter estimates a regime switching Taylor Rule for the European Central Bank (ECB) in order to investigate some potential nonlinearities in the forward-looking policy reaction function within a real-time framework. In order to compare observed and predicted policy behavior, the chapter estimates Actual and Perceived regime switching Taylor Rules for the ECB. The former is based on the refi rate set by the Governing Council while the latter relies on the professional point forecasts of the refi rate performed by a large investment bank before the upcoming policy rate decision. The empirical evidence shows that the Central Bank’s main policy rate has switched between two regimes: in the first one the Taylor Principle is satisfied and the ECB stabilizes the economic outlook, while in the second regime the Central Bank cuts rates more aggressively and puts a higher emphasis on stabilizing real output growth expectations. Second, the results point out that the professional forecasters have broadly well predicted the actual policy regimes. The estimation results are also robust to using consensus forecasts of inflation and real output growth. The empirical evidence from the augmented Taylor Rules shows that the Central Bank has most likely not responded to the growth rates of M3 and the nominal effective exchange rate and the estimated regimes are robust to including these additional variables in the regressions. Finally, after the bankruptcy of Lehman Brothers the policy rate has switched to a crisis regime as the ECB has focused on preventing a further decline in economic activity and on securing the stability of the financial system.

Nonresident fathers have the task of negotiating childrearing responsibilities while residing away from their children. Parenting stress arises when nonresident fathers perceive childrearing power differentials as maternal gatekeeping behaviors. In this pilot study, a mediation model was tested with a sample of Black fathers who reported coparenting a nonresident child or children with only one mother (n = 80). The proposed mediation model tested two hypotheses: (1) coparenting relationship and coparenting support, respectively, each have a direct effect on paternal stressors and (2) the effects of coparenting relationship and coparenting support on fathers’ paternal stressors are mediated through maternal gatekeeping behaviors. Findings indicate that cooperative coparenting lessens parental stressors such as concerns about role functions and concerns about their child’s behavior in the presence of controlling maternal gatekeeping behaviors.

This chapter studies the effects of the COVID-19 pandemic on the economic structure of the US and EU economies by measuring its impact on some reference macro-economic variables. We use a factor model approach on a set of variables available at different frequencies (daily, weekly, monthly, and quarterly) and provide evidence of instability in the primary factors driving the economy. A sequential analysis of the factors allows us to evaluate the model's forecasting performance and extract some instability measures based on the factor model's eigenvalues. Finally, we show how to use COVID-related variables, such as policy, economic, and health indicators, to compute conditional forecasts with factor models, and perform a scenario analysis on the variables of interest to understand economic instability.

In recent years, research on children's tourism experiences has gained prominence, as children are becoming an increasingly vital market for the tourism industry. While events are a main sector of the industry and host millions of children every year, there is a lack of research specifically focussed on children's experiences in events. This chapter focusses on children's entertainment events which can provide children with a satisfying, memorable and educational experience. This study has developed a framework to facilitate deeper mixed studies on children's experiences in event tourism. The framework is composed of four pillars based on various social, tourism and event theories and models, including the Cognition–Affect–Behaviour (CAB) theoretical framework, the Orchestra Model of Experience, the Event Experience Scales (EES), the Theory of Child Well-being and the Transtheoretical Model of Behaviour Change (TTM). The framework can be used by future researchers as an analytical evaluation tool to study children's experiences in different types of events and understand the mechanisms of behaviour change in this context.