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The article by Cachon, Randall, & Schmidt (2007) addresses the strength of the bullwhip effect in various American industries. As the topic of the study is not related to the population, the authors do not mention its size and major characteristics. However, they note that the study involves six retail, 18 wholesale, and 50 manufacturing industries; all of them are nonoverlapping (Cachon et al., 2007). The authors do not describe the method of selecting the sample but note that report that all data are obtained from the U.S. Census Bureau and the Bureau of Economic Analysis (BEA). As mentioned above, the article features only nonoverlapping industries, which supports unbiased findings and helps authors to avoid possible double-counting (Cachon et al., 2007). Although no characteristics are mentioned, the authors provide a detailed description of all industries selected for the evaluation. Moreover, they note that they have purposefully included seasonally unadjusted data to avoid possible biases in measurements (Cachon et al., 2007). It is possible to say that the sample size of the industries is appropriate for the analysis.
The instruments the authors use in their article include the formulas aimed at measuring existing variables, including production in a month, production series, difference operators, amplification ratio, and amplification difference. In addition, the authors analyze the differences between logged production and demand from 1992 to 2006. Cachon et al. (2007) note that the selection of these measurements is determined by the necessity to identify the variance of the industry’s orders, which is correlated with the physical flow into the industry. It is possible to say that most of the utilized measurements are described in terms of purpose, but the language the authors use may not be easily understandable for the non-specialist audience. The measurements are appropriate for measuring the intended variables because they allow the authors to compare demand volatility at different levels of the supply chain and the amplification ratio and difference (Cachon et al., 2007). In addition, the results the study presents reveal that the selected measurements allow for identifying the prevalence of the bullwhip effect and its variation and help the authors to test all of their hypotheses.
The authors present evidence indicating that the used measurements are appropriate for the study. For instance, they discuss the reasons for using standard or nonstandard approaches to the analysis of the data they feature (Cachon et al., 2007). Moreover, in some cases, they report why some measurements are included or excluded from the evaluation. For instance, Cachon et al. (2007) note that they have included all available manufacturing series, as there is no overlapping between the codes used in different industries. The authors do not address the validity of the used instruments; however, it is evident that the implemented measurements are appropriate. Subtest reliabilities and reliability coefficients are not discussed as well. In their study, the authors utilize existing instruments, such as the models introduced by Lee and other scientists (Cachon et al., 2007). Thus, development procedures, administration, scoring, and interpretation are not addressed.
The design of the study is appropriate for testing the hypotheses of the study because the measured data corresponding to the ones presented in the hypotheses. The authors describe the evaluation procedures in detail, providing all necessary formulas and schemes in which they address how they have measured the data. The authors do not present information about a pilot study. Cachon et al. (2007) report that they have implemented several control variables, serving as control procedures for the study. For instance, they have included industry sizes without stating a hypothesis on its impact on the amplification measures. In addition, they have included indicator variables for different mean levels of amplification between the sectors of industries. The authors do not report potentially confounding variables, which means that they have been able to control for all of them (Cachon et al., 2007). The findings of the study do not show bias, which supports the conclusion made above. However, the authors report that their results may differ from the existing works (Cachon et al., 2007). The reason for it is that the studied time periods are different from those analyzed by other literature.
Reference
Cachon, G. P., Randall, T., & Schmidt, G. M. (2007). In search of the bullwhip effect. Manufacturing & Service Operations Management, 9(4), 457-479.
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