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Service experiences and waiting lines are often – unfortunately – seen to go hand in hand. This chapter explains why this is the case. Beginning with an exploration of capacity and operating constraints, discussion then delves into both the mathematical origins and psychological implications of waiting lines. The final section offers hope to managers and guests alike, with a survey of different operations strategies and tactics that can eliminate or abate the need to wait.

The COVID-19 pandemic has disrupted the ‘real’ world and substantially impacted the virtual world and thus the Internet ecosystem. It has caused a significant exogenous shock that offers a wealth of natural experiments and produced new data about broadband, clouds, and the Internet in times of crisis. In this chapter, we characterise and evaluate the evolving impact of the global COVID-19 crisis on traffic patterns and loads and the impact of those on Internet performance from multiple perspectives. While we place a particular focus on deriving insights into how we can better respond to crises and better plan for the post-COVID-19 ‘new normal’, we analyse the impact on and the responses by different actors of the Internet ecosystem across different jurisdictions. With a focus on the USA and Europe, we examine the responses of both public and private actors, with the latter including content and cloud providers, content delivery networks, and Internet service providers (ISPs). This chapter makes two contributions: first, we derive lessons learned for a future post-COVID-19 world to inform non-networking spheres and policy-making; second, the insights gained assist the networking community in better planning for the future.

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.

Purpose – The purpose of this study is to estimate the own- and cross-price elasticity of brand-name outpatient prescription drug cost-sharing for maintenance medications and to estimate the effects of changes in the price differential between generic and brand-name prescription drugs.

Methodology/approach – We first review the literature on the effects of an increase in brand-name drug patient cost-sharing. In addition, we analyze two examples of utilization patterns in filling behavior associated with an increase in brand-name cost-sharing for patients in employer-sponsored health plans with chronic illness.

Findings – We found that the own-price elasticity of demand for brand-name prescription drugs was inelastic. However, the cross-price elasticity was not consistent in sign, and utilization patterns for generic prescription fills did not always increase after a rise in brand-name cost-sharing.

Research limitations – The empirical examples are limited to the experience of patients with employer-sponsored health insurance.

Practical implications – The common practice of increasing brand-name prescription drug patient cost-sharing to increase consumption of generic drugs may not always result in higher generic medication use. Higher brand-name drug cost-sharing levels may result in discontinuation of chronic therapies, instead of therapeutic switching.

Originality/value of chapter – The value of this chapter is its singular focus on the effects of higher brand-name drug cost-sharing through a synthesis of the literature examining the own- and cross-price elasticity of demand for brand-name medications and two empirical examples of the effects of changes in brand-name cost-sharing.

This paper proposes to rethink the concepts of relevance and usefulness and their relation to the theory–practice gap in management research.

On the basis of the cognitive-linguistic relevance theory or inferential pragmatics, supplemented by insights from information science, we define relevance as a general conceptual category, while reserving usefulness for the instrumental application in a particular case.

There is no reason to hold onto the difference between theoretical and practical relevance, nor to distinguish between instrumental and conceptual relevance.

This novel approach will help to clarify the confusion in the field and contribute to a better understanding of the added value of management research.

The objective of the research, and paper, is to determine first whether or not the accounting abstraction appears to dominate the manager’s perceptions of the physical reality of the firm’s utilization of its physical assets, and second, whether changes in the accounting abstraction (e.g. the addition of Capacity cost management reports and measurements) lead to changes in how managers perceive, and use, their physical assets. Using a cognitive decision-making structure developed by Wagenaar et al. (1995), this study explores the interplay between the structure and nature of capacity reporting (the surface structure of the decision) and the subsequent analysis and choice of managers within the firm (the deep structure of the decision). A five-site field research methodology was used to gather data from companies across a multitude of industry contexts and situations. Results suggest that the nature of capacity measurement and reporting does shape manager’s perceptions of current and potential future performance (the cognitive surface structure), with major implications for the nature and type of decisions and trade-offs made (the deep structure). Specifically, managers appear to make decisions that are illogical when considered in light of the physical reality of their operations based on the representations of this reality (e.g. the capacity measures and reports). Analysis and interpretation of these results suggest that what accounting makes visible appears to drive decision-making and performance in organization.