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This chapter provides an overview of the status of applied econometric research in hospitality and tourism management and outlines the econometric toolsets available for quantitative researchers using empirical data from the field. Basic econometric models, cross-sectional models, time-series models, and panel data models are reviewed first, followed by an evaluation of relevant applications. Next, econometric modeling topics that are germane to hospitality and tourism research are discussed, including endogeneity, multi-equation modeling, causal inference modeling, and spatial econometrics. Furthermore, major feasibility issues for applied researchers are examined based on the literature. Lastly, recommendations are offered to promote applied econometric research in hospitality and tourism management.

The circular economy (CE) proposes that all materials flow in a close-looped system. Waste generated by one production stage may be useful in another. Thus, the idea of a CE is linked to the goal of zero waste (ZW) and promotes a range of sustainable economic, social and environmental benefits in each sector. When we apply this to construction waste management, waste can be managed through reducing, recycling, upcycling and reusing. However, there is an inevitable cost implication associated with this process due to the additional requirement of inventory and waste processing, and this becomes a disincentive to implementing the CE. Formal institutions, referring here to legal rules and regulations, play a critical role in motivating firms and individuals towards a CE. As different countries have different government rules and regulations, and there is limited research on their differences, we review Asia’s and Europe’s legal rules and regulations relevant to the goal of ZW and CE in the construction sector.

The aim of this chapter is to examine the role of real exchange rates in the relationship between tourist arrival and economic growth in Malaysia over the period of 2000–2018. We disaggregate Malaysian tourists into six geographical regions, namely Asia, Singapore, Europe, Pacific region, Americas, and Africa. Using a non-linear autoregressive distributed lag model, we find that the appreciation of real exchange rates with positive growth of economy plays a prominent role in influencing international tourist arrivals from Singapore, other Asian countries, Pacific region, Europe, and Americas. Our study suggests that real appreciation is important in providing some insights into the effectiveness of growth-led-tourism policies. In line with this, some implications are provided at the end of this chapter.

Spatial integration and industrial clustering have become an important feature of the culture tourism business. When the core elements in both the culture industry and tourism industry are integrated, a model based on system science is constructed that combines the resources and capacity of the two entities to envisage the ways of creating integrated products and services from the two sectors. Guided by the system science, this study proposes a culture tourism system revealing the clustering and hierarchical structure of the industrial elements. The system contains two subsystems: internal system and external system. The agglomeration model of the system includes 26 indices and the PEF methods, which involved the Parallelogram Law, Entropy-weight Method, and Fuzzy Membership Function. Finally, this study deploys an empirical study involving all provincial territories (N=31) in mainland China. It analyzes the variability and degree of balanced development of the system. In addition, through the resultant data this research adds a typology of culture tourism system along with policy recommendations.

This research analyzes the green activities implemented by banks in Indonesia following a new regulation on sustainable finance and the role of slack resources to fund the initiatives. Green practices of 35 banks in 2020–2021 were evaluated through the disclosure using green banking disclosure index (GBDI). The results show that the green practices have been disclosed adequately; however, no significant association was found for the role of financial and potential slack resources. This reflects the facts that the green activities might not have been adequately implemented and the organization’s resources might not have been allocated to support the green practices. The research periods that were still overloaded with COVID-19 issue might hinder the banks from the adequate and appropriate allocation of resources toward green practices. This research recommends a prioritization approach for the implementation of the sustainable finance regulation by banks and authorities through the increased implementation of substantive green practices, not only the increased disclosures.

American depository receipts (ADRs) listed on the New York Stock Exchange during the 1990s and 2000s are compared to determine how well they performed versus the US index and respective regional indexes utilizing three-year holding period excess returns. Results suggest that ADRs listed in the 2000s perform better than those in the 1990s. Also, seasoned equity offerings performed better than initial public offerings. Regression analysis indicated the best predictors of ADR performance are the returns of the respective regional index where the ADR-listing firm is headquartered, the date of issue (2000s vs 1990s), and whether the ADR was from an emerging economy.

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.

This chapter examines the impact of macroeconomic factors on the financial performance of Chinese companies. Using multiple regression analysis, the study finds that gross domestic product (GDP) growth rate, inflation rate, interest rate, exchange rate, and government expenditure are significant predictors of the financial performance of Chinese companies. The results show that GDP growth rate, leverage, size, liquidity, profitability, and growth in sales all have significant positive impacts on financial performance, while growth in assets has a negative impact. The study provides insights into the impact of macroeconomic factors on the financial performance of Chinese companies. Policymakers and investors should take these findings into account when making decisions about economic policies and investments, and companies operating in China should be aware of the potential impact of these factors on their financial performance and look for ways to manage them effectively. The chapter also includes a model specification test and a robustness test to validate the accuracy of the results. The findings have important guiding significance for policy makers and investors in making economic policies and investment decisions. However, the study has limitations such as the use of horizontal panel data and the limited data sources used.