Journal Articles (Peer-Reviewed)
Hoberg, Kai, Florian Badorf and Lars Lapp (In press):The Inverse Hockey Stick Effect: An Empirical Investigation of the Fiscal Calendar's Impact on Firm Inventories, International Journal of Production Research.
Flöthmann, Christoph and Kai Hoberg (In press):Career Patterns of Supply Chain Executives: An Optimal Matching Analysis, Journal of Business Logistics.
Steinker, Sebastian, Mario Pesch and Kai Hoberg (2016):Inventory Management under Financial Distress: An Empirical Analysis, International Journal of Production Research, 54(17): 5182-5207.
Abstract: This study analyses inventory reductions as a means of short-term financing of firms under financial distress. We use quarterly panel data of U.S. manufacturing firms for the period from 1995 to 2007. We identify a sample of 198 distressed firms for which we analyse changes in relative inventory. Approximately 70% of distressed firms reduce their inventories until the end of their individual distress periods. This decrease corresponds to a mean reduction of 18.7 inventory days or 9.4%. Additional regression analyses show that differences in inventory adjustments depend on pre-distress inventory performance, firm size, and turnaround strategy. We also compile a sample of 142 firms that defaulted to analyse inventory actions of unsuccessful turnarounds. Our findings indicate that defaulting firms also reduce their inventories but that the reductions are lower than those of firms that resolve their financial distress. We conclude that distressed firms use short-term inventory adjustments to free up cash and to achieve long-term efficiency gains from inventory optimisation. Our findings suggest that inventory optimisation is an essential part of a complete and successful turnaround strategy and financially distressed firms should always consider this action as a means to prevent bankruptcy.
Hoberg, Kai and Ulrich W. Thonemann (2015):Analyzing Variability, Cost, and Responsiveness of Base-Stock Inventory Policies with Linear Control Theory, IIE Transactions, 47(8): 865-879.
Abstract: The effect of inventory policies on order variability has been analyzed extensively. Two popular means of reducing order variability are demand smoothing and order smoothing. If the objective is minimizing demand variability, demands and orders can be heavily smoothed, resulting in an inventory policy that orders equal amounts in each time period. Such a policy obviously minimizes order variability, but it leads to high cost and low responsiveness of the inventory system. To optimize the overall performance of an inventory system, the effect of the inventory policy on all relevant dimensions of operational performance must be analyzed. We address this issue and analyze the effect of the parameter values of an inventory policy on three main dimensions of operational performance: Order variability, expected cost, and responsiveness. The inventory policy we use is the partial correction policy, a policy that can be used to smooth demand and to smooth orders. To analyze this policy, we use linear control theory. We derive the transfer function of the policy and prove the stability of the inventory system under this policy. Then, we determine the effect of the policy parameters on order variability, cost, and responsiveness and discuss how good parameter values can be chosen.
Hoberg, Kai and Ulrich W. Thonemann (2014):Modeling and analyzing information delays in supply chains using transfer functions, International Journal of Production Economics, 156: 132-145.
Abstract: Advanced inventory policies require timely system-wide information on inventories and customer demand to accurately control the entire supply chain. However, the presence of unsynchronized processes, processing lags or inadequate communication structures hinder the widespread availability of real-time information. Therefore, inventory systems often have to deal with obsolete data which can seriously harm the overall supply chain performance. In this paper, we apply transfer function methods to analyze the effect of information delays on the performance of supply chains. We expose the common echelon-stock policy to information delays and determine to what extent a delay in inventory information and point-of-sale data deteriorates the inventory policies׳ performance. We compare the performance of this policy with the performance of an installation-stock policy that is independent of information delays since it only requires local information. We find that this simple policy should be preferred in certain settings compared to relying on a complex policy with outdated system-wide information. We derive an echelon-stock policy that compensates for information delays and show that its performance improves significantly in their presence. We note potential applications of the approach in service parts supply chains, the hardwood supply chain, and in fast moving consumer goods settings.
Steinker, Sebastian and Kai Hoberg (2013):The impact of inventory dynamics on long-term stock returns – An empirical investigation of U.S. manufacturing companies, Journal of Operations Management, 31(5): 250-261.
Abstract: This paper investigates the relationship between the inventory dynamics and long-term stock returns of a large panel of U.S. manufacturing firms over the time period from 1991 to 2010. We propose two measures of inventory dynamics: one metric to assess the fluctuations of quarterly inventories within the year and a second metric to quantify relative year-over-year inventory growth. Our results indicate that within-year inventory volatility (IV) and abnormal year-over-year inventory growth (ABI) are associated with abnormal stock returns. Both metrics cannot be entirely explained by common risk factors. We find that firms with high IV and low ABI have the best long-term stock returns, and that stock performance decreases monotonically with higher ABI values. Our results are robust to various control variables including size, book-to-market value, industry and prior performance. We therefore conclude that changes in inventory levels provide valuable insights into the risks and opportunities faced by a company.
Bock, Stefan and Kai Hoberg (2007):Detailed layout planning for irregularly-shaped machines with transportation path design, European Journal of Operational Research, 177(2): 693-718.
Hoberg, Kai, Ulrich W. Thonemann and James R. Bradley (2007):Analyzing the effect of inventory policies on the nonstationary performance with transfer functions, IIE Transactions, 39(9): 911-924.
Hoberg, Kai, James R. Bradley and Ulrich W. Thonemann (2007):Analyzing the effect of the inventory policy on order and inventory variability with linear control theory, European Journal of Operational Research, 176(3): 1620-1642.
Journal Articles (Professional)
Alicke, Knut, Christoph Glatzel, Kai Hoberg and Per-Magnus Karlsson (2016): Big data and the supply chain: The big supply chain analytics landscape Part 1 (of 2), McKinsey&Company Operations Extranet, February.
Alicke, Knut, Christoph Glatzel, Kai Hoberg and Per-Magnus Karlsson (2016): Big data and the supply chain: Capturing the benefits (Part 2), McKinsey&Company Operations Extranet, March.
Abstract: In the first part of this series, we described the many ways Big Data and Advanced Analytics can be used to improve supply chain performance. Now we look at an approach companies can use to make big supply chain analytics work for them.
Hoberg, Kai, Christoph Flöthmann and Knut Alicke (2015): Karriere: Tipps für den Weg nach oben, Logistik heute, 1-2: 22-23.
Hoberg, Kai, Knut Alicke and Markus Leopoldseder (2015): Time to Get Supply Chain Management to the Board, Supply Chain Management Review, July/August.
Abstract: Supply chain leaders frequently deal with an executive team that lacks both knowledge and interest in supply chain management. Yet, the supply chain community all too often struggles to communicate the value it provides. To get the required executive support, SCM needs to be better positioned in the firm. Here is a framework that provides guidance on how to bring supply chain management to the Board agenda.
Hoberg, Kai, Knut Alicke, Christoph Flöthmann and Johan Lundin (2014): The DNA of Supply Chain Executives, Supply Chain Management Review: 36-43.
Abstract: Who are the professionals who make supply chain management the engine of the firm? We find that many roads lead to Rome: The diversity of supply chain talent resembles the extraordinary, cross-functional nature of the supply chain profession. Here is an overview of the education, career paths, and success factors of supply chain executives.
Hoberg, Kai, Christoph Flöthmann and Knut Alicke (2014): Karriere: Quereinsteiger für das Supply Chain Management, Logistik heute, 12: 20-21.
Hoberg, Kai and Knut Alicke (2013): 5 Lessons for Supply Chains from the Financial Crisis, Supply Chain Management Review, September/October.
Abstract: For many supply chain executives, the Financial Crisis has been one of the toughest challenges in their careers. Firms across industries were required to deal with huge demand-supply mismatches caused by collapsing demand. However, the supply chain community found innovative ways to deal with the challenges of these tough times. Here are five action areas supply chain managers should be aware of—before the next crisis.