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The purpose of this paper is to investigate the effects of personality dimensions (conscientiousness, neuroticism, extraversion, agreeableness, openness to experience, locus of control) on the efficacy of judgmental adjustments of statistical forecasts.

This paper uses a two-level hierarchical linear model to analyze a large data set obtained from an organizational setting (a quick service restaurant chain) that includes 3,812 judgmental adjustments of sales forecasts made by 112 store managers.

The results indicate that the average forecast accuracy improves as a result of judgmental adjustments, but performance of individual forecasters varies considerably based on their personality. Specifically, the trait of openness to experience tends to improve forecast accuracy while extraversion and external locus of control have negative effects.

Integration of human judgment with analytics algorithms is a major challenge for organizations. Documenting the impact of these traits on forecast accuracy opens the door for forecasting support system design, training, personnel selection and correction strategies that can be applied to judgmental adjustments.

Whereas inventory theory traditionally assumes the periodic review inventory model (R, T), with an order‐up‐to level R, has a random demand and lead time coupled with a deterministic review interval T, firms often deviate from a strict adherence to a fixed review interval when they attempt to capture transportation scale efficiencies. Employing this policy introduces additional supply chain variability. This paper aims to provide an expression for the standard deviation of demand during the protection period, important in setting safety stock, as well as an expression for the amount of order variance amplification induced by a stochastic review interval.

Analytical modeling is used to develop the expression for the standard deviation of demand during the protection period as well as the calculation for the amount of order variance amplification induced by a stochastic review interval.

In terms of the variance of demand over the protection period, a stochastic review interval has a similar effect to that of a stochastic lead time, but its impact on demand variance amplification within the supply chain differs fundamentally. Specifically, a stochastic review interval creates an order batching bullwhip effect not identified in existing literature.

This study offers an expression for the standard deviation of demand during the protection period when stochastic review intervals are employed. The expression can be used to more effectively set safety stock. The paper also offers an expression for the order variance amplification induced by a stochastic review interval.

The study offers suggestions for retailers and suppliers regarding when the use of a stochastic review interval is effective in terms of cost efficiencies.

While the existence and effect of lead time variability is well‐established in the literature, traditional approaches the periodic review inventory model ignore the stochastic nature of review interval. This paper highlights the use of stochastic review intervals as a contributing factor to the bullwhip effect.

The purpose of this paper is to investigate the direct and interaction effects of shelf space, case pack quantity, and consumer demand on shelf stockouts, i.e. stockouts at the shelf level when inventory is available in the backroom of a retail store.

This study uses discrete‐event simulation based on data collected from the ready‐to‐eat breakfast cereal category with multiple stockkeeping units (SKUs) to model a retail supply chain consisting of a supplier, a retailer, and consumers.

The results indicate that shelf space and case pack quantity have direct effects on shelf stockouts. Furthermore, evidence is found for interactions among shelf space, case pack quantity and consumer demand. Though many retailers adopt simple heuristics for shelf space allocation, such as a multiple of case pack quantity, this study suggests that such heuristics tend to over‐ or underestimate shelf space requirements when consumer demand is ignored.

This study suggests that managers should allocate shelf space for SKUs on the basis of not only case pack quantity but also consumer demand.

This paper aims to present the development of a scale, off‐site customer service (OCS), which assesses the factors that are important in consumer evaluation of an off‐site customer service contact method (e.g. website or telephone).

A scale is developed and tested. A discrete choice model provides supporting evidence of the practical applications of the scale.

The resultant scale is developed with consumer evaluation delineated on usability and experiential dimensions. The usability dimension consists of items capturing ease of use, error recovery, security, and customization constructs. The experiential dimension consists of items capturing satisfaction, socialization, empathy, and privacy sensitivity constructs. A discrete choice model shows that the scale performs equally well for both website and telephone contact methods. The paper concludes with managerial implications and avenues for additional research.

Unlike existing scales that focus on a particular type of contact method or a particular customer service encounter or transaction, OCS scale is versatile enough to be used for different contact methods and under different customer service encounter scenarios.

The purpose of this paper is to assess the current state of implementation of lean production practices in China as compared to the USA. Moreover, an institutional‐theoretic framework is developed that explores the interplay among economic, socio‐cultural and regulative forces that may shape the adoption process of lean production practices in China.

The paper draws its conclusions from an analysis of survey data from samples of Chinese and US manufacturing executives. Lean production implementation is measured via a survey instrument, and the data are analyzed via regression analysis.

The results suggest that the degree of implementation of lean production in China is equal to, if not greater than lean production implementation in the USA. While the results are fairly consistent across industries, they vary across different lean production practice bundles. In light of these findings, an institutional theory perspective is adopted to develop further insight into the potential drivers of and barriers to lean production implementation in China. It is argued that, while several economic factors function as enablers for the implementation of these practices, various social processes and cultural traits in China still hinder the full adoption of lean production.

Larger‐scale empirical studies are required for further hypothesis testing and enhanced validity. In particular, the explicit measurement of institutional forces and the statistical analysis of their effects on lean production adoption are recommended for future research.

This is the first study to systematically compare the adoption of lean practices in China and the USA. The analyses and discussions provide a basis for further theory building and hypothesis testing research. In addition, the insights offered in this study may help firms gain a better understanding of the unique opportunities and challenges associated with adoption of lean production in China.