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Experimental economics has been treated with skepticism by some Austrian economists. We argue that experimental methods are consistent with strong versions of praxeology, and are therefore not methodologically problematic for Austrians. We further argue that experimental research methods have illustrated many uniquely Austrian themes and provide a fruitful method for future Austrian-inspired research.

John and Storr (this volume) make the case that quantitative methods help establish whether culture matters, but do not tell us how culture matters. To better understand how culture matters, social scientists must use qualitative methods like interviews, in-depth case studies, and archival research. Currently, experimental economists engage qualitative methods through the coding of “chat” transcripts and informal talks with subjects while payments are arranged. Experimental economists do this because they know that it is a good idea to talk to the people they seek to understand and learn from their thought process. The goal of this chapter is to build on the insights from John and Storr about the importance of qualitative work and to provide experimental economists with some concrete ideas about qualitative methods that can improve their research.

Experimental design has long been used by psychology and consumer behavior researchers to examine causal effects of interventions on human responses. However, it remains underutilized in hospitality and tourism research. Furthermore, problems in design, implementation, and report of results were identified in previous hospitality and tourism publications. It is imperative to equip hospitality and tourism experimenters with sophisticated and state-of-the-art knowledge about experimental design, and to draw their attention to some crucial, but easily neglected, issues in designing the experiment and writing the experimental research paper. Given these reasons, this book chapter discusses some key issues in experimental design and provides corresponding insights related to the sections of introduction, literature review, hypothesis, method, analysis, and results in an experimental research paper, while the uniqueness of hospitality and tourism is considered. It is expected that the chapter will be useful for hospitality and tourism researchers to plan, conduct, and report their experimental studies in the future.

Education researchers have been urged to utilize causal inference methods to estimate the policy effect more rigorously. While randomized controlled trials (RCTs) are the gold standard for assessing causality, RCTs are infeasible in some educational settings, particularly when ethical concerns or high cost are involved. Quasi-experimental research designs are the best alternative approach to study educational topics not amenable to RCTs, as they mimic experimental conditions and use statistical techniques to reduce bias from variables omitted in the empirical models. In this chapter, we introduce and discuss the core concepts, applicability, and limitations of three quasi-experimental methods in higher education research (i.e., difference-in-differences, instrumental variables, and regression discontinuity). By introducing each of these techniques, we aim to expand the higher education researcher's toolbox and encourage the use of these quasi-experimental methods to evaluate educational interventions.

This chapter considers whether and how race/ethnicity can be examined using experimental methods.

We begin by discussing the highly contextual nature of race/ethnicity and reviewing the properties of experiments. After examining existing experimental literature that focuses on race/ethnicity, we turn to our current study that uses the incompatible complexity condition to examine the multilevel interactions of diverse racial/ethnic groups composed of Mexican American and White participants in Texas and Black and White participants in Ohio.

We argue that experiments, when guided by formal theoretical approaches that allow for general inquiries of theoretical principles, are especially suitable for studying interactional characteristics such as race/ethnicity.

We suggest a particular approach that emphasizes interactional aspects of race/ethnicity and how these aspects can be utilized to diminish inequality in group processes.

Measuring behavior requires research methods that can capture observed outcomes and expose underlying processes and mechanisms. In this chapter, we present a toolbox of instruments and techniques we designed experimental tasks to simulate decision environments and capture behavior. We deployed protocol analysis and text analysis to examine the underlying cognitive processes. In combination, these can simultaneously grasp antecedents, outcomes, processes, and mechanisms. We applied them to collect rich behavioral data on two key topics in strategic management: the exploration–exploitation trade-off and strategic risk-taking. This mix of methods is particularly useful in describing actual behavior as it is, not as it should be, replacing assumptions with data and offering a finer-grained perspective of strategic decision-making.

Online retailers often lack nexus within a purchaser’s home state and do not collect sales tax at the point of sale. Consumers exacerbate the loss of tax revenue by typically not remitting the use tax on these purchases. To date, very little research addresses the effectiveness of methods to increase use tax compliance, and the need for more work is well documented in the literature.

This study examines, in a controlled economics-based experiment, the effectiveness of current approaches to close the use tax gap. Participants are randomly assigned to one of three treatments to determine the extent to which they would voluntarily pay use tax on a purchase transaction. The experiment mimics the natural environment and measures the participants’ actual compliance with cash payouts.

We find individuals are significantly more likely to pay the use tax when given detailed information about their online purchases and the use tax obligation compared to only receiving a description of the use tax. We also find compliance is significantly higher when individuals have a separate state income tax line on which to report use tax liability.

Unlike personal income tax compliance, consumers are more likely to evade use tax payments because taxing authorities are usually unable or unwilling to audit consumer purchases. This makes an examination of the effectiveness of reporting and collection methods worthwhile. This study measures use tax compliance based on actual consumer behavior with real economic consequences rather than taxpayer intentions, as reported in prior work. This is important because intentions and behavior are often different, especially in an economic setting. Finally, policymakers will benefit from an effectiveness-assessment of actual methods, rather than hypothetical and potentially unfeasible approaches, to try and increase use tax compliance.

A heated debate surrounds the significance of reproducibility as an indicator for research quality and reliability, with many commentators linking a “crisis of reproducibility” to the rise of fraudulent, careless, and unreliable practices of knowledge production. Through the analysis of discourse and practices across research fields, I point out that reproducibility is not only interpreted in different ways, but also serves a variety of epistemic functions depending on the research at hand. Given such variation, I argue that the uncritical pursuit of reproducibility as an overarching epistemic value is misleading and potentially damaging to scientific advancement. Requirements for reproducibility, however they are interpreted, are one of many available means to secure reliable research outcomes. Furthermore, there are cases where the focus on enhancing reproducibility turns out not to foster high-quality research. Scientific communities and Open Science advocates should learn from inferential reasoning from irreproducible data, and promote incentives for all researchers to explicitly and publicly discuss (1) their methodological commitments, (2) the ways in which they learn from mistakes and problems in everyday practice, and (3) the strategies they use to choose which research components of any project need to be preserved in the long term, and how.