O riginally adopted by the automotive manufacturers, lean management practices have since been applied to many other manufacturing industries. This study reviews the different theoretical perspectives on the leanness-performance relationship in the context of the motor carriage industry. Drawing on both the lean management in logistics and organizational slack literatures, we develop hypotheses addressing the link between asset leanness and financial performance. These hypotheses are empirically tested using a comprehensive panel data set of 1,172 firm-quarter observations from the U.S. publicly traded truckload motor carriers. Initially expecting an inverted U-shaped relationship between asset leanness and performance, findings indicated a U-shaped relationship, both for carriers' total assets and the subset of trailer assets.
Multiround business simulation games have been gaining popularity in higher education. However, certain aspects of experiential learning of individual students in the game remain unaddressed in research literature. Team assessments, such as team papers, appear a common, “natural” choice given the team‐based nature of the games but may potentially mask individual learning outcomes. In this study we use a qualitative method to glean from individual students’ papers a deeper understanding of the process of learning of individual students in a team‐based, multiround business simulation game. Our findings indicate that individual and timely assessments are necessary to identify cases of not meeting the expected individual learning outcomes for the instructor's corrective intervention. This study contributes to the understanding of the process and outcomes of student learning in a multiround business simulation game, methods of teaching a supply chain and operations class with a simulation, and methods for better aligning course goals and assessments.
Purpose The purpose of this paper is to provide a comprehensive review of the respondents’ fraud phenomenon in online panel surveys, delineate data quality issues from surveys of broad and narrow populations, alert fellow researchers about higher incidence of respondents’ fraud in online panel surveys of narrow populations, such as logistics professionals and recommend ways to protect the quality of data received from such surveys. Design/methodology/approach This general review paper has two parts, namely, descriptive and instructional. The current state of online survey and panel data use in supply chain research is examined first through a survey method literature review. Then, a more focused understanding of the phenomenon of fraud in surveys is provided through an analysis of online panel industry literature and psychological academic literature. Common survey design and data cleaning recommendations are critically assessed for their applicability to narrow populations. A survey of warehouse professionals is used to illustrate fraud detection techniques and glean additional, supply chain specific data protection recommendations. Findings Surveys of narrow populations, such as those typically targeted by supply chain researchers, are much more prone to respondents’ fraud. To protect and clean survey data, supply chain researchers need to use many measures that are different from those commonly recommended in methodological survey literature. Research limitations/implications For the first time, the need to distinguish between narrow and broad population surveys has been stated when it comes to data quality issues. The confusion and previously reported “mixed results” from literature reviews on the subject have been explained and a clear direction for future research is suggested: the two categories should be considered separately. Practical implications Specific fraud protection advice is provided to supply chain researchers on the strategic choices and specific aspects for all phases of surveying narrow populations, namely, survey preparation, administration and data cleaning. Originality/value This paper can greatly benefit researchers in several ways. It provides a comprehensive review and analysis of respondents’ fraud in online surveys, an issue poorly understood and rarely addressed in academic research. Drawing from literature from several fields, this paper, for the first time in literature, offers a systematic set of recommendations for narrow population surveys by clearly contrasting them with general population surveys.
As the supply chain revolution continues, small and medium-sized enterprises and smaller facilities of large companies experience an increased pressure from their adjacent supply chain partners and their own senior management to improve their performance. This places higher demands on the accuracy of their performance measurement, particularly labor productivity in warehouses. Smaller facilities cannot afford to implement engineered labor standards (ELS) and rely on traditional metrics of output, such as piece count, which do not provide the reliable level of accuracy demanded today. Changing the traditional view of the inputs-outputs paradigm, this study suggests a unique labor productivity metric for non-ELS facilities based on warehouse lift-truck utilization data. Empirical tests using a longitudinal data set from an automotive parts distribution center provide evidence that the new metric is more accurate than the traditional output metrics because it is not affected by the assignment contribution error due to workload smoothing. The new metric offers managers an opportunity to fine-tune labor productivity measurement in warehouses and other environments with extensive lift-truck utilization without investing in ELS projects.
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