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Many jurisdictions fine illegal cartels using penalty guidelines that presume an arbitrary 10% overcharge. This article surveys more than 700 published economic studies and judicial decisions that contain 2,041 quantitative estimates of overcharges of hard-core cartels. The primary findings are: (1) the median average long-run overcharge for all types of cartels over all time periods is 23.0%; (2) the mean average is at least 49%; (3) overcharges reached their zenith in 1891–1945 and have trended downward ever since; (4) 6% of the cartel episodes are zero; (5) median overcharges of international-membership cartels are 38% higher than those of domestic cartels; (6) convicted cartels are on average 19% more effective at raising prices as unpunished cartels; (7) bid-rigging conduct displays 25% lower markups than price-fixing cartels; (8) contemporary cartels targeted by class actions have higher overcharges; and (9) when cartels operate at peak effectiveness, price changes are 60–80% higher than the whole episode. Historical penalty guidelines aimed at optimally deterring cartels are likely to be too low.

There has been a growing call from within the operations management (OM) academic community for research of more managerial relevance. This has implied a greater emphasis on empirical research: surveys, cases, and action research. But in fact these types are quite different. However, the great majority of empirical OM work published is based on postal surveys and/or interviewing executives, where research method selection is made for reasons of practical convenience and academic expectation. Given the level of complexity involved in understanding the OM perspective of business issues then the emphasis should be placed on plant‐based research. Conducting research on‐site and investigation through the analysis of relevant data, issues, developments and events ensures relevance and a validity essential to making an impact on business practice. There are obstacles to increasing the amount of plant‐based research which is carried out, such as practical and personal difficulties, a mistaken concern over research rigour, and academic institutional inertia. Each of these needs to be overcome if OM research is to influence business practice more in the future than it has in the past.

This chapter presents the results of the comprehensive literature survey and supportive empirical assessment of the potential impacts of the Financial Transactions Tax (FTT) recently adopted by the European Commission in response to the significant financial sector misallocations arising from the Global Financial Crisis.

A survey of 50 academic articles relating to both Financial Transaction Taxes and Tobin Taxes shows that although a reduction in liquidity can be expected from such taxes, the impacts this will have on volatility and efficiency in a market are less obvious. A regression model quantifying what the possible effect of an introduction of a 0.1% tax on financial transactions would be on trading volumes and levels of volatility in the European equity market confirms the survey results in broader terms.

The results suggest that, in the current economic climate, such a tax would likely increase volatility levels but may not have much effect on trading volumes.

As a result the proposed tax can be viewed as an exercise in revenue generation but not as a macro-prudential tool for addressing potential future shocks and imbalances within the European financial system. In other words, contrary to political and media statements, the FTT does not appear to be an effective tool for addressing past, present and future risks associated with systemic malfunctioning in the banking and financial systems.

The study presents an extensive and systematic survey of academic literature on FTT and links this survey to empirical model estimation. This twin approach to the analysis is novel to the academic and policy literature on Financial Transactions Tax. Whilst popular belief is that introduction of FTT will aid the objective of achieving greater financial and economic sustainability across the European financial systems, evidence presented in this chapter suggests that such a conclusion is at the very best naive.

The aim of any research is to create knowledge and to generate new insights. For insights from empirical research to be valid, the data from which insights are derived must be valid. Empirical data in tourism and hospitality research is predominantly collected by means of surveys. The chapter discusses a range of dangers to data validity associated with survey research; explains under which circumstances surveys represent a suitable or unsuitable method of data collection; and offers practical recommendations that can easily be adopted by survey researchers to ensure maximum validity of their data.

This paper provides guidelines for the design and execution of survey research in operations management (OM). The specific requirements of survey research aimed at gathering and analysing data for theory testing are contrasted with other types of survey research. The focus is motivated by the need to tackle the various issues which arise in the process of survey research. The paper does not intend to be exhaustive: its aim is to guide the researcher, presenting a systematic picture which synthesises suitable survey practices for research in an OM context. The fundamental aim is to contribute to an increase in the quality of OM research and, as a consequence, to the status of the OM discipline among the scientific community.

To achieve changing customer demands, organizations are striving hard to embrace cutting-edge technologies facilitating a high level of customization. Industry 4.0 (I4.0) implementation aids in handling big data that could help generate customized products. Lean six sigma (LSS) depends on data analysis to execute complex problems. Hence, the present study aims to empirically examine the key operational characteristics of LSS and I4.0 integration such as principles, workforce skills, critical success factors, challenges, LSS tools, I4.0 technologies and performance measures.

To stay competitive in the market and quickly respond to market demands, industries need to go ahead with digital transformation. I4.0 enables building intelligent factories by creating smart manufacturing systems comprising machines, operators and information and communication technologies through the complete value chain. This study utilizes an online survey on Operational Excellence professionals (Lean/Six Sigma), Managers/Consultants, Managing Directors/Executive Directors, Specialists/Analysts/Engineers, CEO/COO/CIO, SVP/VP/AVP, Industry 4.0 professionals and others working in the field of I4.0 and LSS. In total, 83 respondents participated in the study.

Based on the responses received, reliability, exploratory factor analysis and non-response bias analysis were carried out to understand the biasness of the responses. Further, the top five operational characteristics were reported for LSS and I4.0 integration.

One of the limitations of the study is the sample size. Since I4.0 is a new concept and its integration with LSS is not yet explored; it was difficult to achieve a large sample size.

Organizations can utilize the study findings to realize the top principles, workforce skills, critical success factors, challenges, LSS tools, I4.0 tools and performance measures with respect to LSS and I4.0 integration. Moreover, these operational characteristics will help to assess the organization's readiness before and after the implementation of this integration.

The authors' original contribution is the empirical investigation of operational characteristics responsible for I4.0 and LSS integration.

Survey research has developed to become the default empirical approach to answering research questions in the field of hospitality (and many other fields of research within the social sciences). This paper aims to reflect on the use of survey research in hospitality and offers recommendations for improvement.

First, known dangers to validity associated with survey research are discussed. Next, a sample of studies recently published in leading hospitality journals is assessed in view of these known dangers. Finally, recommendations are offered for editors, reviewers, readers and authors to mitigate the risk of drawing invalid conclusions based on survey research.

Survey research is very common in hospitality research and is used to investigate a wide range of research questions and constructs under study. The nature of constructs studied, the answer scales used and the nature of the samples point to a substantial risk to the validity of conclusions drawn.

A number of risk mitigation measures are proposed that can help authors minimise the risks to validity arising from known dangers associated with survey research. These same risk mitigation measures can be used by editors and reviewers in the assessment of manuscripts and by readers to evaluate the validity of conclusions drawn in already published work.

The value of this study lies in reflecting from a distance on how the survey research is conducted in the social sciences in general and in hospitality research in specific. The paper reveals that some routine approaches particularly prone to undermining the validity of conclusions may have been adopted and offers a few suggestions how this risk can be mitigated.

Accounting comparability has been the subject of significant interest in empirical financial accounting research. Recent literature, particularly that following De Franco et al.’s (2011) influential study, has focused on utilizing the output of the financial reporting process to measure accounting comparability. In this paper, we conduct an early survey of studies using output-based measures of comparability. We provide two distinct contributions to the literature. First, we describe and comment on four important measurement concepts as well as the studies that introduced them. With this methodological contribution, we aim to facilitate the measurement choice for empirical accounting researchers engaged in comparability research. Second, we classify the sub-streams of literature and related studies. In providing this content-related contribution, we sum up what has already been achieved in output-based accounting comparability research and highlight potential areas for prospective research. As a whole, our study attempts to guide empirical researchers who (plan to) undertake studies on accounting comparability in selecting relevant topics and choosing adequate approaches to measurement.

The sustainable success of infrastructures is becoming a driving force for advancing urbanization globally. However, to achieve infrastructure sustainable success (ISS), how project management practices (PMPs) play their role remains unexplored in current literature. To this end, an empirical study on whether PMPs play significant impacts on the accomplishment of ISS was conducted.

This research is based on an empirical survey of domestic and overseas infrastructure projects managed by Chinese companies. 162 data samples were collected and further analyzed deploying structural equation modeling (SEM) on the basis of goal-setting theory. PMP factors derived from the plan-do-check-act (PDCA) ideology, i.e. culture, strategy, implementation and reflection were hypothesized and validated to have direct and indirect relationships with ISS.

The results of this study indicate that both culture and reflection can directly drive the PMPs toward ISS. Furthermore, it is revealed that by affecting mediator factors of strategy, implementation and reflection, culture is found to present an indirect influence on ISS; by affecting mediator factors of implementation and reflection, Strategy is found to present an indirect influence on ISS and by affecting the mediator factor of reflection, implementation is found to present an indirect influence on ISS.

These findings contribute to the body of knowledge in measuring sustainability success of project management performances by clarifying critical relationships of how PMPs lead to ISS. Prospectively, the outputs of this research will generate informative insights for practitioners to improve their PMPs in the process of pursuing ISS in future infrastructure management practices.

Past studies have paid extensive attention to investigate learning issues in individual, organizational and team contexts. Learning activities in the workplace, however, often occur in the interdisciplinary dyadic context. Hence, the purpose of this paper is to clarify what factors make interdisciplinary dyads lead to better learning effects. The authors attempted to clarify two major agendas: What knowledge factors (intellectual capitals) owned by the parties of the dyads can induce better learning effects? What contextual factors (learning tasks) can make better learning effects during the dyadic learning process?

To examine the previous agendas, the authors first conducted in-depth interviews and an exploratory survey so that a four-element dyadic intellectual capital (DIC) architecture was circumscribed: knowledge interdependency, expertise similarity, collaborative routines and mutual trust. Dyadic learning tasks were classified as exploitative and exploratory learning. The authors then sampled 248 respondents for the formal empirical survey to examine the relationship between DIC, dyadic learning tasks and knowledge sharing.

The statistical evidences confirmed the positive relationships between DIC and knowledge sharing, and the results also signified the previous relationships with a mediating effect from exploratory learning, while the effect of exploitative learning was not supported. Thus, only dyads (the two heads) with knowledge interdependency and mutual trust can make the exploratory task better than that of one individual (the one head).

This study provides a new insight into the learning issue with an interdisciplinary dyadic perspective to supplement the existing gap between academic efforts and learning practices in the workplace.