The inverse hockey stick effect: an empirical investigation of the fiscal calendar’s impact on firm inventories

Hoberg, Kai; Badorf, Florian; Lapp, Lars

doi:10.1080/00207543.2016.1269969

Cited by 12 publications

(16 citation statements)

References 64 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…They applied their methodology for technology selection. Using a sample of 4877 U.S. manufacturing companies, Hoberg, Badorf, and Lapp (2017) found that the fiscal calendar impact the inventory level, which the authors termed 'the inverse hockey stick effect'. Dotoli, Epicoco, and Falagario (2017) maximised the supply chain network efficiency under uncertainty.…”

Section: Tactical Levelmentioning

confidence: 99%

From data to big data in production research: the past and future trends

Kuo

Kusiak

2018

International Journal of Production Research

157

View full text Add to dashboard Cite

Data have been utilised in production research in meaningful ways for decades. Recent years have offered data in larger volumes and improved quality collected from diverse sources. The state-of-the-art data research in production and the emerging methodologies are discussed. The review of the literature suggests that production research enabled by data has shifted from that based on analytical models to data-driven. Manufacturing and data envelopment analysis have been the most popular application areas of data-driven methodologies. The research published to date indicates that data mining is becoming a dominant methodology in production research. Future trends and opportunities for data-driven production research are presented.

show abstract

Section: Tactical Levelmentioning

confidence: 99%

From data to big data in production research: the past and future trends

Kuo

Kusiak

2018

International Journal of Production Research

157

View full text Add to dashboard Cite

show abstract

“…Additionally, a number of papers identify relationships between inventory investment and the underlying driving factors. Examples of such relationships include production flexibility and the number of dealerships in the case of the automotive industry (Cachon and Olivares, 2010); the time relative to the fiscal year end in publicly traded firms (Lai, 2008; Hoberg et al, 2017); and sales characteristics, gross margins, and capital intensity in the retail industry (Gaur et al, 2005). We refer the reader to Eroglu and Hofer (2011), Steinker et al (2016), and Bendig et al (2018) for recent reviews of different aspects of the empirical inventory literature and focus on the studies that are most immediately relevant to our topic.…”

Section: Literature Reviewmentioning

confidence: 99%

Inventory agility upon demand shocks: Empirical evidence from the financial crisis

Udenio

Hoberg

Fransoo

2018

J of Ops Management

Self Cite

View full text Add to dashboard Cite

The objective of this paper is to identify antecedents of inventory agility (i.e., the capability to quickly adapt inventories to changes in demand) upon demand shocks based on the awareness‐motivation‐capability (AMC) framework and to explore the link between inventory agility and financial performance. We introduce an empirical measure of inventory agility based on the deviation of relative inventories (i.e., inventory days) from their forecasted values. We hypothesize that firms with higher awareness, motivation, and capabilities are associated with higher inventory agility in the presence of demand shocks. We define two empirical measures for each of the three dimensions of the AMC framework in the context of inventory agility: awareness (i.e., market orientation and technology orientation), motivation (i.e., gross margin and liquidity), and capabilities (i.e., inventory management capability and resource availability). In addition, we incorporate the constraining factor model (CFM) into the AMC framework, thus allowing for complementarity among the different measures. In this view, the influence of each of the measures on inventory agility varies according to which of the measures is the constraining factor for a given firm. The 2008 financial crisis may have tested firms' inventory agility more than any other crisis since the Great Depression, as an unprecedented collapse of demand coincided with a reduction in credit availability. Therefore, for our analysis, we use firm‐level empirical data from 1263 public U.S. manufacturing firms for the 2005–2011 period. We find that firms' motivation and capabilities are key factors associated with inventory agility. Through the CFM, we show that identifying the constraining factors leads to a more refined understanding of the moderating effects of the antecedents of inventory agility. In a separate analysis, we find that inventory agility is positively associated with a number of financial performance metrics during crisis periods. We distinguish between inventory underages and overages and find that, during the crisis, they are both associated with lower financial performance. Furthermore, we find evidence that higher underages (overages) magnify the effect of overages (underages). Among other managerial insights, our findings suggest that the use of inventory reductions as a quick way to increase liquidity must be gauged against their potential impact on other aspects of financial performance.

show abstract

“…In an inventoryspecific context, Lai (2008) found that retailers reduce inventories on average by 10% in the fourth fiscal quarter, even after correcting for sales timing. Hoberg et al (2017) extended this analysis to manufacturing firms, which reduce inventories on average by 6% at the end of the fiscal year. These strong inventory reductions could serve as signals of efficiency.…”

Section: Introductionmentioning

confidence: 99%

Multiperiod Inventory Management with Budget Cycles: Rational and Behavioral Decision‐Making

Becker‐Peth

Hoberg

Protopappa‐Sieke

2020

Production and Operations Management

Self Cite

View full text Add to dashboard Cite

We examine inventory decisions in a multiperiod newsvendor model. In particular, we analyze the impact of budget cycles in a behavioral setting. We derive optimal rational decisions and characterize the behavioral decision‐making process using a short‐sightedness factor. We test the aforementioned effect in a laboratory environment. We find that subjects reduce order‐up‐to levels significantly at the end of the current budget cycle, which results in a cyclic pattern during the budget cycle. This indicates that the subjects are short‐sighted with respect to future budget cycles. To control for inventory that is carried over from one period to the next, we introduce a starting‐inventory factor and find that order‐up‐to levels increase in the starting inventory.

show abstract

The inverse hockey stick effect: an empirical investigation of the fiscal calendar’s impact on firm inventories

Cited by 12 publications

References 64 publications

From data to big data in production research: the past and future trends

From data to big data in production research: the past and future trends

Inventory agility upon demand shocks: Empirical evidence from the financial crisis

Multiperiod Inventory Management with Budget Cycles: Rational and Behavioral Decision‐Making

Contact Info

Product

Resources

About