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Vector Autoregression (VAR) has been a standard empirical tool used in macroeconomics and finance. In this paper we discuss how to compare alternative VAR models after they are estimated by Bayesian MCMC methods. In particular we apply a robust version of deviance information criterion (RDIC) recently developed in Li, Zeng, and Yu (2014b) to determine the best candidate model. RDIC is a better information criterion than the widely used deviance information criterion (DIC) when latent variables are involved in candidate models. Empirical analysis using US data shows that the optimal model selected by RDIC can be different from that by DIC.

This chapter outlines a dynamic model of compositional strategic advantage for resource-poor firms where the attractiveness of the product offering in terms of scope and perceived value-to-price ratio identifies a number of elementary compositional strategies. A resource-poor firm can establish a compositional strategy composed of one or more of these elementary compositional strategies. It is argued that how the compositional strategic advantage is formed by three indispensable factors of aspiration (asymmetry between ambition and position), attitude (be “ALERT” to change), and action (use the asymmetry to create advantage). It is explained how the underlying theoretical rationales are particularly useful to understand the successful expansion of multinational Chinese firms and coinciding with basic cultural values.

The disparities of COVID-19 vaccination rates between the rural and urban areas have become apparent during this pandemic. There is a need to understand the root causes of vaccine hesitancy demonstrated by the rural population to increase coverage and to contain the disease spread throughout the United States. This study aimed to explore other factors influencing vaccine hesitancy among rural dwellers besides the geography-related barriers such as poor health care access and individuals having no or suboptimal insurance coverage.

By reviewing existing data and literature about vaccination, health literacy, and behaviors, and prevailing ideologies, we discuss the potential causes of vaccine hesitancy in rural areas that could create barriers for successful public health efforts related to vaccine coverage and provide suggestions to ameliorate the situation.

Geography-related barriers, health literacy, and preconceived notions are key determinants of adopting healthy behaviors and complying with public health authorities' recommendations among rural individuals during a public-health crisis. We argue that ideology, which is much deeper than preconception or misconception on vaccination, should be incorporated as a key factor to redefine the term “vulnerable populations” in public health research.

The limitation of our study is that we have not found an effective way to encourage the populations who hold conservative religious and political ideologies to join the efforts for public health. Even though geography-related barriers may strongly impact the rural dwellers in achieving optimal health, the various forms of ideologies they have toward certain health behaviors cannot be discounted to understand and address vaccine-related disparities in rural areas. There is a need to redefine the term “vulnerable population” particularly as it relates to rural areas in the United States. During large-scale public health disasters, scholars and public health authorities should consider the ideologies of individuals, in addition to other factors such as race/ethnicity, area of residence (rural vs. urban), and socioeconomic factors influencing the existing vulnerabilities and health disparities.

In a pandemic framework (COVID-19), this chapter explores the impact of the global economy and socio-cultures concerning three axes: recreational, tourism, and hospitality. Although we slowly see an economic revival, it is well known that this sector of study is very susceptible to being affected by the context of nations. Following restrictions and measures taken by governments around the world to reduce the number of cases of coronavirus infections, many nations closed their borders, affecting international travel and by 2020 tourism had been reduced to the near cessation of operations due to the imminent fear of this poorly studied disease, and the service sector was negatively affected. It should be added that, according to the World Tourism Organization's projections, a decrease of between 20 and 30% is forecast for 2020 compared to the previous year.

A zero-day vulnerability is a complimentary ticket to the attackers for gaining entry into the network. Thus, there is necessity to device appropriate threat detection systems and establish an innovative and safe solution that prevents unauthorised intrusions for defending various components of cybersecurity. We present a survey of recent Intrusion Detection Systems (IDS) in detecting zero-day vulnerabilities based on the following dimensions: types of cyber-attacks, datasets used and kinds of network detection systems.

Purpose: The study focuses on presenting an exhaustive review on the effectiveness of the recent IDS with respect to zero-day vulnerabilities.

Methodology: Systematic exploration was done at the IEEE, Elsevier, Springer, RAID, ESCORICS, Google Scholar, and other relevant platforms of studies published in English between 2015 and 2021 using keywords and combinations of relevant terms.

Findings: It is possible to train IDS for zero-day attacks. The existing IDS have strengths that make them capable of effective detection against zero-day attacks. However, they display certain limitations that reduce their credibility. Novel strategies like deep learning, machine learning, fuzzing technique, runtime verification technique, and Hidden Markov Models can be used to design IDS to detect malicious traffic.

Implication: This paper explored and highlighted the advantages and limitations of existing IDS enabling the selection of best possible IDS to protect the system. Moreover, the comparison between signature-based and anomaly-based IDS exemplifies that one viable approach to accurately detect the zero-day vulnerabilities would be the integration of hybrid mechanism.