ضعیف، ضعیف تر و خیلی ضعیف؟ارتباط بازنگری شده عملکرد - موجودی

While firms increasingly adopt lean inventory practices, there is limited evidence that inventory leanness leads to improved firm performance. This study reexamines this relationship in an attempt to overcome some shortcomings of previous research. To that end, a theory-based measure of inventory leanness, which takes into account industry-specific inventory management characteristics, is proposed. The analysis of a large panel data set of U.S. manufacturing companies reveals that the significance and shape of the inventory–performance relationship varies substantially across industries. This relationship is significant in two-thirds of the 54 industries studied. In most of these instances, the relationship is concave, suggesting that there is an optimum level of inventory leanness beyond which firm performance deteriorates. A post-hoc analysis is conducted to identify industry-level characteristics that may determine the nature the inventory–performance relationship. Managerial implications are discussed and several opportunities for future research are outlined.

The lean production philosophy considers inventory a form of waste that should be minimized (Womack et al., 1990). In recent decades, as lean production has gained widespread adoption (IndustryWeek, 2008), lean inventory management has become synonymous with good inventory management (Hall, 1983, Zipkin, 1991, Chen et al., 2005 and Cooper and Maskell, 2008). As a result, inventories have been decreasing in many industries (Chen et al., 2005 and Chen et al., 2007). Yet evidence of improved firm performance is mixed (Rumyantsev and Netessine, 2007). The purpose of this research is to investigate the effect of inventory leanness on firm performance by analyzing empirical data from the U.S. manufacturing industry. Specifically, this study aims to contribute to existing research on three accounts: first, the effect of inventory leanness on firm performance is explored on an industry-by-industry basis. The advantage of this approach is that it controls for industry-specific characteristics that may lead to different types of relationships between inventory leanness and firm performance in various industries. When data from multiple industries are pooled, as is the case in most previous studies, the dissimilar functional forms present in these industries may mask each other and yield insignificant estimation results. Hence, the analysis of data by narrowly defined industries creates a more comprehensive understanding of the relationship between inventory leanness and firm performance. Second, the functional form of this relationship is explored. While previous empirical studies have assumed a linear relationship only, the use of a more flexible functional form affords a richer perspective on the inventory–performance relationship. For example, there may be industries in which inventory leanness increases firm performance up to a certain point beyond which the incremental effect becomes negative. Third, an alternative measure of inventory leanness, the Empirical Leanness Indicator (ELI), is proposed. The distinguishing feature of the ELI, as compared to previously used measures, is that it takes into account the nonlinear relationship between firm size and inventory holdings. Prior research has often relied on metrics such as inventory turnover (Schonberger, 2007 and Gaur et al., 2005) and average inventory levels (King and Lenox, 2001) to gauge inventory leanness. These measures ignore the effect of firm size on inventory holdings, i.e. economies of scale in inventory management, and can lead to bias in estimation results. Drawing on inventory theory, the ELI estimates a firm's inventory leanness relative to industry-specific norms and takes into account economies of scale. Subsequently, the ELI and conventional inventory leanness measures are compared in terms of their explanatory power in describing the relationship between inventory leanness and firm performance. The analyses of data from a large set of publicly traded U.S. manufacturing firms presented here provide detailed insights into the linkages between inventory leanness and firm performance, thereby contributing to both inventory theory and the theory of lean production. From a practical perspective, managers can use the methodology presented here as a new technique to benchmark their operational performance. The remainder of this paper is organized as follows: In Section 2, the relevant literature is reviewed. Research hypotheses are presented in Section 3. The definition and measurement of inventory leanness, a central concept in this study, are discussed in Section 4. Other variables of interest and data collection procedures are outlined in Section 5. The results of the empirical analysis are presented in Section 6, and a discussion of various post-hoc analyses is provided in Section 7. The paper concludes with a summary of the study's results, and a discussion of limitations and future research prospects in Section 8.

This research investigates the effect of inventory leanness on firm performance. The analysis of a large sample of U.S. manufacturing firms over a 6-year time period indicates that the significance and shape of this relationship varies greatly from one industry to another. One-third of the 54 industries studied here exhibit no significant effect of inventory leanness on firm performance. In other words, while lean inventory strategies may be economically viable in some industries, other industries may not be amenable to such approaches due to their particular product, production technology, supply or demand characteristics. The findings of this study, thus, replicate and reconcile the contradictory results of Cannon (2008) and Capkun et al. (2009). Pooling data from industries with dissimilar inventory–performance relationships can yield diluted estimation results. Hence, researchers should take this finding into account when designing future studies. Another finding of this study is that the effect of inventory leanness on firm performance is mostly positive and generally nonlinear. In most instances, the effect of inventory leanness is concave implying – in line with inventory control theory – that there is an optimal degree of inventory leanness beyond which the marginal effect of leanness on financial performance becomes negative. This provides empirical support for the “pragmatic JIT” view of Zipkin (1991) which suggests that leaner is not always better. Post-hoc analyses reveal statistically significant differences in structural industry characteristics between industries with significant and non-significant performance effects of inventory leanness. Thus, it is inferred that observed differences in inventory–performance relationships are likely due to systematic inter-industry heterogeneity, rather than random chance. Moreover, this study adds to prior lean production and inventory research by theoretically and empirically controlling for the effect of firm size on inventory leanness and presenting a size-adjusted inventory leanness measure (ELI). It is argued that this metric presents a more accurate assessment of a firm's true degree of leanness, which makes it useful and relevant both in academic research as well as in managerial practice. As with any study, this research has a number of limitations. First, certain firm-level variables and the trade-offs among them that determine the appropriateness of lean inventory strategies are not observed. In an attempt to address this concern, the data are grouped in six-digit NAICS clusters to provide some control for unobserved heterogeneity among firms in the data set. Moreover, the results rely predominantly on data from industries with a moderate to high number of publicly traded firms.3 As such, the generalizability to smaller industries or industries with relatively large numbers of privately held companies cannot be ascertained. Another limitation of this study is that it relies on U.S. data only. Many countries have expanding manufacturing industries in which industry-specific conditions may be different and differentially affect the inventory leanness–performance relationship. Thus, the results may not be generalizable beyond the U.S. From a managerial perspective, finally, the need for a comparatively large data set and basic statistical skills likely limits the usability of the ELI for at least some managers. The empirical results suggest that industry-specific characteristics may drive the nature of the relationship between inventory leanness and firm performance. In the post-hoc analysis, an initial exploration of variables that may explain differences in the shape and magnitude of the inventory leanness–performance link was presented. Further research is needed, however, to define the firm-level and industry-level factors that make lean strategies appropriate for some firms and industries but not for others. Furthermore, what might be the factors that determine the functional form (linear versus inverted U-shape) of the relationship between inventory leanness and firm performance? Also, examining aspects of leanness other than inventory leanness might be interesting. For example, asset leanness can be differentiated from employee leanness. It may be interesting to gain an understanding of how different leanness measures and their interactions affect firm performance. In short, while this research addresses some interesting questions regarding lean production and inventories, many questions worthy of further investigation still remain.