Prof. Dr.
Kai Hoberg

Publications

Professor of Supply Chain and Operations Strategy

 

Prof. Dr.
Kai Hoberg

Publications

Professor of Supply Chain and Operations Strategy

 

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Journal Articles (Peer-Reviewed)

DOI: https://doi.org/10.1002/joom.1271 

Abstract: The emergence of digital technologies across all aspects of operations management has enabled shifts in decision making, shaping new operational dynamics and business opportunities. The associated scholarly discussions in information systems and operations management span digital manufacturing, the digitalization of operations management and supply chain management, platform outcomes, and economies of collaboration. For such changes to be successful, however, there is a need for organizations to go beyond the mere adoption of digital technologies. Instead, successful changes are transformational, delving into digital transformation endeavors, which in turn can enable operational improvements in organizational performance, lead to structural changes in operations processes, and may result in new business models being deployed. Our aim here, thus, is to provide an epistemic platform to advance our understanding of how such endeavors, including the adoption of digital technologies, business model innovations, and innovations in collaboration mechanisms and methods of operations improvement, can affect various aspects of operations management.

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DOI: https://doi.org/10.1016/j.tre.2023.103178 

Abstract: Complete and accurate data is an important enabler of effective supply chain decision making. Despite the increasing efforts to fully automate data collection processes using advanced sensors and scanners, human operators are still in charge of data entry tasks in most industries. Unfortunately, operators do not often comply with the standard operating procedures (SOPs) and do not always exhibit the consistency and commitment required to collect high-quality data. In fact, data collection is often perceived as a non-value-adding activity that increases workloads and lowers productivity. We aim to empirically study the extent to which compliance with SOPs for data collection is affected by some of the key factors. Using a large dataset obtained from a leading postal service provider in Australia, we find that an operator’s workload, fatigue, and related work experience directly impact the compliance levels. We also find that a company’s compliance reinforcement intervention to improve compliance behavior can moderate these impacts.

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DOI: https://doi.org/10.2139/ssrn.4408404 

Abstract: Purpose - Disruptions and shortages of drugs have become severe problems in recent years, which has triggered strong media and public interest in the topic. However, little is known about the factors that can be associated with the increased frequency of shortages. In this paper, we analyze the drivers of drug shortages using empirical data for Germany, the fourth largest pharmaceutical market. Design/methodology/approach - We use a dataset provided by the German Federal Institute for Drugs and Medical Devices (Bundesinstitut für Arzneimittel und Medizinprodukte [BfArM]) with 425 reported shortages for drug substances (DSs) in the 24-month period between May 2017 and April 2019 and enrich the data with information from additional sources. Using logistic and negative binomial regression models, we analyze the impact of (1) market characteristics, (2) drug substance characteristics and (3) regulatory characteristics on the likelihood of a shortage. Findings - We find that factors like market concentration, patent situation, manufacturing processes or dosage form are significantly associated with the odds of a shortage. We discuss the implications of these findings to reduce the frequency and severity of shortages. Originality/value – We contribute to the empirical research on drug shortages by analyzing the impact of market characteristics, DS characteristics and regulatory characteristics on the reported shortages. Our analysis provides a starting point for better prioritizing efforts to strengthen drug supply as it is currently intensely discussed by healthcare authorities.

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DOI: https://doi.org/10.1002/joom.1210 

Abstract: When the COVID-19 pandemic began in 2020, the medical product industry faced an unusual demand shock for personal protective equipment (PPE), including face masks, face shields, disinfectants, and gowns. Companies from various industries responded to the urgent need for these potentially life-saving products by adopting ad hoc supply chains in an exceptionally short time: They found new suppliers, developed the products, ramped-up production, and distributed to new customers within weeks or even days. We define these supply chains as ad hoc supply chains that are built for a specific need, an immediate need, and a time-limited need. By leveraging a unique sampling, we examined how companies realize supply chain agility when building ad hoc supply chains. We develop an emergent theoretical model that proposes dynamic capabilities to enable companies building ad hoc supply chains in response to a specific need, moderated by an entrepreneurial orientation allowing firms to leverage dynamic capabilities at short notice and a temporary orientation that increases a company's focus on exploiting the short-term opportunity of ad hoc supply chains.

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DOI: https://doi.org/10.1016/j.ejor.2023.10.038 

Abstract: Slow-moving goods are common in many retail settings and occupy a vast part of retail shelves. Since stores sell these products irregularly and in small quantities, the replenishing distribution center may only place batched orders with manufacturers every few weeks. While order quantities are often fixed, the challenge for manufacturers facing such intermittent demand is to forecast the order timing. In this paper, we explore the value of Point-of-Sales (PoS) data to improve a food manufacturer’s order timing forecast for slow-moving goods. We propose an inventory modeling approach that uses the last order, PoS data from retail stores, and the expected lead time demand to estimate the retailer’s channel inventory. With this dynamic estimate, we can ‘nowcast’ the retailer’s inventory and predict his next order. To illustrate our methodology, we first conduct an experimental simulation and compare our results to a Croston variant and a moving average model. Next, we validate our approach with empirical data from a small German food manufacturer that serves a grocery retailer with a central distribution center and 53 hypermarkets. We find that, on average, our approach improves the accuracy of order-timing predictions by 10–20 percent points. We overcome a shrinkage-induced bias by incorporating an inventory correction factor. Our approach describes a new way of utilizing PoS data in multi-layered distribution networks and can complement established forecasting methods such as Croston. Particular applications arise when the order history is short (e.g., product launch) or represents a bad predictor for future demand (e.g., during COVID-19).

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DOI: https://doi.org/10.1002/joom.1185 

Abstract: Numerous studies have examined the relationship between inventory management and financial performance. However, the focus of such empirical work has primarily been on how a firm's own inventory characteristics affect its performance. Our objective is to extend this body of literature beyond the firm-level. We draw on inventory theory and resource-based theories to hypothesize about the effect of supplier inventory leanness on a focal firm's financial performance and how supplier and focal firm inventory leanness interact to affect such outcomes. We test our hypotheses using a large panel dataset of supplier-focal firm relationships obtained from Compustat's Customer Segment database and aggregated to the focal firm-quarter level, as well as firm financial information from Compustat's Fundamentals Quarterly database. The econometric analyses provide evidence that supplier inventory leanness influences focal firm financial performance indirectly through the interaction with the firm's own inventory leanness. In particular, our estimation results detail how supplier inventory leanness affects the non-linearity of the focal firm's inventory leanness-financial performance relationship and its optimal inventory leanness level. The findings broaden the scope of empirical inventory literature and highlight supplier inventory leanness as an important consideration in firm-level inventory decision making.

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DOI: https://doi.org/10.1016/j.ejor.2022.03.017 

Abstract: Various advanced systems deploy artificial intelligence (AI) and machine learning (ML) to improve demand forecasting. Supply chain planners need to become familiar with these systems and trust them, considering real-world complexities and challenges the systems are exposed to. However, planners have the opportunity to intervene based on their experience or information that the systems may not capture. In this context, we study planners’ adjustments to AI-generated demand forecasts. We collect a large amount of data from a leading AI provider and a large European retailer. Our dataset contains 30 million forecasts at the SKU-store-day level for 2019, plus variables related to products, weather, and holidays. In our two-phase analysis, we aim to understand the adjustments made by planners and the quality of these adjustments. Within each phase, we first identify the drivers of adjustments and their quality using random forest, a well-known ML algorithm. Next, we investigate the collective effects of the different drivers on the occurrence and the quality of the adjustments using a decision tree approach. We find that product characteristics such as price, freshness, and discounts are important factors when making adjustments. Large positive adjustments occur more frequently but are often inaccurate, while large negative adjustments are generally more accurate but fewer in number. Thus, planners do not contribute to accuracy on average. Our findings provide insights for the better use of human knowledge in judgmental forecasting.

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DOI: https://doi.org/10.1016/j.ijpe.2021.108258 

Abstract: Digital technologies, such as advanced analytics, autonomous vehicles or the Internet of Things, are often touted as means to substantially improve operations. While this potential has been frequently highlighted and evidenced from single case applications, we still lack a deeper theoretical understanding of the underlying mechanisms how digital technologies can support process improvement in general, and lean practices more specifically. In this paper, we use a qualitative study based on focus group design to understand how manufacturing and supply chain management professionals perceive the potential of digital technologies in support of lean practices. We identify eight digital waste reduction mechanisms that illustrate how digital technologies can support lean practices. These include a cluster of mechanisms that augment operational execution in terms of speed and precision of execution, as well as flexibility in space and time. Furthermore, we identify a second cluster of mechanisms that augment decision-making through visibility, feedback, engagement, and prevention. In terms of managerial implications, our findings provide firms with a structured approach how to identify those digital technologies that can most effectively support their respective process improvement activities.

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DOI: file:///Z:/Citavi_DB_KLU_Publikationen/Upload KLU publications current/KLU publications current/doi.org/10.1080/00207543.2020.1821116 

Abstract: While many supply chain decisions could take advantage of big data, firms struggle with investments into supply chain analytics since they are not able to assess the application areas and benefits of these initiatives. In this paper, we provide a multi-level perspective to assess the value of supply chain data. We develop a framework that highlights the connections between data characteristics and supply chain decisions with different time horizons (i.e. short- or long-term) as well as different supply chain levels (i.e. individual-firm level or supply-chain level). As data gets more complex in one or more of the 4 V dimensions (i.e. volume, variety, velocity, veracity), firms must assess how to best take advantage of the opportunities offered. We use the Dutch floriculture sector as a case study for our framework in which we highlight four data analytics applications to improve logistics processes. In the applications, we demonstrate how the data is used to support the decisions at different time horizons and supply-chain levels. We find that each of the big data’s Vs is required differently according to the decisions’ characteristics. Based on the findings, applications in other industries and promising directions for future research are discussed.

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DOI: file:///Z:/Citavi_DB_KLU_Publikationen/Upload KLU publications current/KLU publications current/doi.org/10.1016/j.ejor.2021.03.042 

Abstract: Motivated by recent advances in Internet-of-Things (IoT) technology for household appliances, we analyze a Smart Replenishment system that leverages point-of-consumption (POC) information at end consumers to decide on deliveries of consumables. As such, we extend the classic Vendor-Managed Inventory (VMI) concept to end consumers. We model the system for a single manufacturer who directly serves end consumers with uncertain demand. End consumers partially adopt the new Smart Replenishment mode, which results in a mix of VMI and non-VMI customers. We assume that unfulfilled demand is lost and that the manufacturer’s dispatch capacity is constrained. Customers compete for the same capacity while featuring different out-of-stock risks and service-level expectations, both of which are costly to the manufacturer. Considering various adoption levels, we decide on the design of such a system and focus on (i) inventory control, (ii) customer prioritization, and (iii) degree of smart, integrated decision-making. Using discrete-event simulation and a full-factorial experiment, we show that replenishment decisions can be significantly enhanced with POC information. It leads to substantial improvements in service levels and capacity utilization without loading customers with inventories. This improvement potential is highest for a low demand coverage of the replenishment quantity, a high gap in the ordering behavior of manufacturer and end consumers, and a long lead time. To realize this improvement potential, we propose a flexible reorder corridor to manage inventories at VMI customers that balances the trade-off between out-of-stock risk and service-level expectation inherent in the system.

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DOI: https://doi.org/10.1016/j.jretconser.2019.101921 

Abstract: In this study, we examine the influence of weather on daily sales in brick-and-mortar retailing using empirical data for 673 stores. We develop a random coefficient model that considers non-linear effects and seasonal differences using different weather parameters. In the ex-post analysis using historic weather data, we quantify the explanatory power of weather information on daily sales, identify store-specific effects and analyze the influence of specific sales themes. We find that the weather has generally a complex effect on daily sales while the magnitude and the direction of the weather effect depend on the store location and the sales theme. The effect on daily sales can be as high as 23.1% based on the store location and as high as 40.7% based on the sales theme. We also find that the impact of extreme bad and good weather occurrences can be misestimated by traditional models that do not consider non-linear effects. In the ex-ante analysis, we analyze if weather forecasts can be used to improve the daily sales forecast. We show that including weather forecast information improves sales forecast accuracy up to seven days ahead. However, the improvement of the forecast accuracy diminishes with a higher forecast horizon. 

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DOI: https://doi.org/10.1111/poms.13123 

Abstract: 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.

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Abstract: Supply chain management (SCM) is an intricate part of the business world at present. As organizations serve the global consumer or user, supply chains must reach a wide range of markets. Markets range from dense megacities to sparsely populated rural communities. Despite this range, supply chain employees must determine how to efficiently, effectively and sustainably deliver products and services to all their customers. The complexities that exist within these various supply chains create a myriad of difficulties for supply chain decision-makers. Furthermore, the introduction of omnichannel retail and the belief that consumers expect delivery within two days or less have further increased complexity. Hence, additional pressure has been added to the ever fast-paced supply chain networks. Consequently, organizations' supply chains are becoming more multifaceted and increasingly challenging to manage. Remaining competitive while addressing increasing requirements on the supply chain forces decision-makers to seek a variety of options. When assessing these options, supply chain decision-makers are faced with critically evaluating the boundaries of their knowledge and the supply chain workforce. The exploration of expanding the limitations of the workforce is illustrated by the growing interest in artificial intelligence, process automation and autonomous machines. Perhaps the limitations of the workforce may be addressed through new technologies. For example, LeMay and Keller (2019) in their article for the special issue explore the history of truck drivers. They report on an industry that is heavily regulated, has long hours and suffers from a shortage of manpower. Within their article, they acknowledge that with the increased demands due to omnichannel, e-commerce and new regulations, trucking is investing in more innovative technologies to help truck drivers focus, get more rest and deal with the demands of the job. There is a constant exploration of how to enhance the abilities of the supply chain workforce to service the dynamic environment businesses must operate within. However, before truly pursuing more technologically advanced options, organizations need to understand the individual competencies of supply chain employees as well as the limits of their capabilities. More specifically, what are the competencies, skills and abilities that are necessary for supply chain employees to be successful in this complex environment? Once these areas are identified, how can organizations complement their employees' individual competencies using technological advances? Furthermore, how much should organizations augment their workforce with varying technological advancements, and is there a point of diminishing returns? Finally, what is the best approach to the introduction of technology and innovation to the labor force? This thought piece seeks to call for research on understanding the challenges faced by the human factor within SCM. Furthermore, we call for additional exploration into how supply chains can expand the capabilities of supply chain decision-makers and supply chain employees through technological advancements, which can help organizations look to the future. Organizations that are successful in integrating the institutional knowledge of supply chain decision-makers and employees with the technological advances within the industry will achieve a competitive advantage. A way to move forward might be to (1) understand the individual competencies and supply chain employees' ability to handle the demands of the field; (2) acknowledge the imperfect human decision-maker by understanding where it is unrealistic and impractical to depend solely on a human decision-maker; and (3) augment the human decision-maker by integrating technological advancements into supply chain processes, providing additional actionable insights to supply chain decision-makers.

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DOI: https://doi.org/10.1111/jscm.12203 

Abstract: Supplier selections are complex but nonetheless strategically important decisions that are influenced by numerous factors. Drawing on the resource-based and relational view of the firm, we investigate how suppliers’ economies of scale influence the buyer’s selection decision, and we illustrate how the influence of scale is contingent upon important economic, buyer, and relationship characteristics. We test the model with a large secondary dataset of actual supplier selection decisions from the automotive industry and show that economies of scale have a strongly positive but diminishing effect on the buying firm’s supplier selection decision. These effects are reinforced or extenuated by economic, buyer, and relationship characteristics, with characteristics that are more specific to the buyer-supplier situation (e.g., relationship duration and power balance) having a stronger moderating effect than do characteristics that are more global (e.g., economic cycle). Our research helps suppliers to better understand how to manage selection probabilities with buyers and provides buying firms with a better understanding of how contextual factors affect the benefit of supplier-provided economies of scale.

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DOI: https://doi.org/10.1108/IJPDLM-09-2017-0275 

Abstract: The purpose of this paper is to derive monetary benchmarks and managerial implications for omni-channel retailers’ B2C e-fulfillment strategies by investigating the trade-offs between lead time, delivery convenience and total price including shipment in the context of online electronics retailing. Based on a choice-based conjoint analysis among 550 US online shoppers, the monetary values of lead time and convenience were calculated in a log-log regression model. In addition, latent class segmentation was applied to identify consumer segments according to their differing e-fulfillment preferences. From a consumer perspective, the analysis suggests that price is the most important criteria in omni-channel retailer selection, followed by lead time and convenience. The value of time is, on average, $3.61 per day. Regarding convenience, the results indicate that delivery to the home is highly preferred over pick-up options. The value of the consumer’s travel time was estimated at $10.62 per hour. The latent class segmentation identified four segment groups with different preferences.

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Abstract: Spare parts are a particularly interesting application for switching production from traditional manufacturing (TM) to additive manufacturing (AM). Research assessing AM has primarily addressed cost models centering on the production process or the operations management of separate spare parts. By combining case study, modelling, and design science elements, we adopt a holistic perspective and develop a design to examine the systematic leverage of AM in spare parts operations. Contextually grounded in problems faced by a leading material handling equipment manufacturer that is challenged by common characteristics of after-sales operations, we engage with practice to propose a portfolio level analysis examining the switchover share from TM to AM. Using a dataset of 53,457 spare parts over nine years, we find that up to 8% of stock keeping units (SKUs) and 2% of total units supplied could be produced using AM, even if unit production costs are four times those of TM. This result is driven by low demand, high fixed costs, and minimum order quantities in TM. Finally, we present the evaluation by the case company's management and highlight five areas of opportunity and challenge.

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DOI: https://doi.org/10.1016/j.ejor.2017.05.010 

Abstract: Firms are increasingly interested in transport policies that enable a shift in cargo volumes from road (truck) transport to less expensive, more sustainable, but slower and less flexible transport modes like railway or inland waterway transport. The lack of flexibility in terms of shipment quantity and delivery frequency may cause unnecessary inventories and lost sales, which may outweigh the savings in transportation costs. To guide the strategic volume allocation, we examine a modal split transport (MST) policy of two modes that integrates inventory controls.We develop a single-product–single-corridor stochastic MST model with two transport modes considering a hybrid push–pull inventory control policy. The objective is to minimize the long-run expected total costs of transport, inventory holding, and backlogging. The MST model is a generalization of the classical tailored base-surge (TBS) policy known from the dual sourcing literature with non-identical delivery frequencies of the two transport modes. We analytically solve approximate problems and provide closed-form solutions of the modal split. The solution provides an easy-to-implement solution tool for practitioners. The results provide structural insights regarding the tradeoff between transport cost savings and holding cost spending and reveal a high utilization of the slow mode. A numerical performance study shows that our approximation is reasonably accurate, with an error of less than 3% compared to the optimal results. The results also indicate that as much as 85% of the expected volume should be split into the slow mode.

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DOI: https://doi.org/10.1108/IJPDLM-02-2017-0120 

Abstract: Abstract Purpose The purpose of this paper is to extend the understanding of supply chain management (SCM) competencies by splitting them into individual and organizational components and measuring their impact on SCM performance. Design/methodology/approach Hypothesized relationships are tested using structural equation modeling and bootstrapping mediation analysis based on a multi-national survey with 273 managers while drawing on the theory of knowledge management and literature streams of individual competencies in the fields of SCM and human resource management (HRM), respectively. Findings The analysis reveals that individual SCM competencies and organizational SCM knowledge positively influence SCM performance to a similar magnitude. Moreover, organizational learning enhances individual competencies and organizational knowledge significantly and equally while corporate training programs fall surprisingly short of expectations. The disentanglement of SCM competencies renders HRM’s contribution to SCM visible by revealing the impact of HRM and learning practices on competencies, knowledge, and performance. Research limitations/implications To validate the findings, future research could apply different research methods such as case studies and focus on more countries to reduce potential methodological and regional biases. Practical implications The results suggest that corporate training programs need further development. Organizational learning’s strong direct and indirect effects have two main implications: first, it should serve as motivation for organizations to constantly improve their learning capabilities. Second, these only tap its true potential for enhancing SCM performance if they first elevate individual competencies and organizational knowledge.

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DOI: https://doi.org/10.1108/SCM-03-2018-0101 

Abstract: Abstract Purpose This study aims to enhance the understanding of competency requirements of supply chain planners and analysts (SCP&As) and identify different personal preferences of hiring managers toward job candidates’ competency profiles. Design/methodology/approach A total of 243 supply chain managers with hiring experience participated in an adaptive choice-based conjoint experiment to uncover the relative importance of six competency attributes, namely, analytical and problem-solving ability, interpersonal skills, general management skills, computer/IT skills, supply chain management (SCM) knowledge and industry experience. Findings SCM knowledge and analytical and problem-solving ability were identified as the most important competencies and were considered three times more important than general management skills. Based on convergent cluster and ensemble analysis, two types of hiring managers were identified. The first group is characterized by a pronounced preference for job candidates with extensive SCM knowledge. In contrast, the second group’s members prefer candidates with a more balanced competency profile.

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DOI: https://doi.org/10.1111/jbl.12150 

Abstract: This exploratory study analyzes the careers of 307 supply chain executives (SCEs). Motivated by career theory, our findings create new knowledge about the educational backgrounds and career paths that lead to SCE positions. Based on an optimal matching analysis, we are able to distinguish among six career patterns for SCEs. They differ in terms of the individuals’ previous professional experience, educational background, and the time they needed to arrive in an executive position. By characterizing the backgrounds and career paths of SCEs, we show that supply chain management (SCM) is truly a cross-functional profession. Our findings suggest that previous staff responsibility appears to be a more important hiring criterion than extensive SCM experience. While 56% of the executives had prior staff responsibility, only 12% of the cumulated careers were actually spent inside the SCM function.

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DOI: https://doi.org/10.1108/IJPDLM-05-2016-0142 

Abstract: Purpose The purpose of this paper is to identify the interplay between a firm’s financial situation and its inventory ownership in a single-firm and a two-firm perspective. Design/methodology/approach The analysis uses different secondary data sources to quantify the effect of both financial constraints and cost of capital on inventory holdings of public US firms. The authors first adopt a single-firm perspective and analyze whether financial constraints and cost of capital do generally affect the amount of inventory held. Next, the authors adopt a two-firm perspective and analyze the inventory ownership in customer-supplier relationships. Findings Inventory levels are affected by financial constraints and cost of capital. Results indicate that higher costs of capital are weakly associated with lower inventories. However, contrary to the authors’ expectations, firms that are less financially constrained hold less inventories than firms that are more financially constrained. Finally, the authors find that customers hold the larger fraction of supply chain inventory in supplier-customer dyads. Practical implications The authors’ results indicate that financial considerations generally play a role in inventory management. However, inventory holdings seem to be influenced only slightly by financing costs and inventory holdings between supplier and customer seem to be less than optimal from a financial perspective. Considering those financial aspects can lead to relevant financial advantages. Originality/value In contrast to other recent research, the authors study how the financial situation of a firm affects its inventory levels (not vice versa) and also consider inventories from a two-firm perspective.

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DOI: https://doi.org/10.1111/poms.12721 

Abstract: To be efficient, logistics operations in e-commerce require warehousing and transportation resources to be aligned with sales. Customer orders must be fulfilled with short lead times to ensure high customer satisfaction, and the costly under-utilization of workers must be avoided. To approach this ideal, forecasting order quantities with high accuracy is essential. Many drivers of online sales, including seasonality, special promotions and public holidays, are well known, and they have been frequently incorporated into forecasting approaches. However, the impact of weather on e-commerce operations has not been rigorously analyzed. In this study, we integrate weather data into the sales forecasting of the largest European online fashion retailer. We find that sunshine, temperature, and rain have a significant impact on daily sales, particularly in the summer, on weekends, and on days with extreme weather. Using weather forecasts, we have significantly improved sales forecast accuracy. We find that including weather data in the sales forecast model can lead to fewer sales forecast errors, reducing them by, on average, 8.6% to 12.2% and up to 50.6% on summer weekends. In turn, the improvement in sales forecast accuracy has a measurable impact on logistics and warehousing operations. We quantify the value of incorporating weather forecasts in the planning process for the order fulfillment center workforce and show how their incorporation can be leveraged to reduce costs and increase performance. With a perfect information planning scenario, excess costs can be reduced by 11.6% compared with the cost reduction attainable with a baseline model that ignores weather information in workforce planning.

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DOI: https://doi.org/10.1080/00207543.2016.1157273 

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.

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DOI: https://doi.org/10.1080/0740817X.2014.999897 

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.

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DOI: https://doi.org/10.1016/j.ijpe.2014.05.019 

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.

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DOI: https://doi.org/10.1016/j.jom.2013.05.002 

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.

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DOI: https://doi.org/10.1016/j.ejor.2005.11.011 

Abstract: In order to obtain a competitive level of productivity in a manufacturing system, efficient machine or department arrangements and appropriate transportation path structures are of considerable importance. By defining a production system’s basic structure and material flows, the layout determines its operational performance over the long term. However, most approaches proposed in the literature provide only a block layout, which neglects important operational details. By contrast, in this paper, we introduce approaches to planning layouts at a more detailed level. Hence, this present paper introduces an integrated approach which allows a more detailed layout planning by simultaneously determining machine arrangement and transportation paths. Facilities to be arranged as well as the entire layout may have irregular shapes and sizes. By assigning specific attributes to certain layout subareas, application-dependent barriers within the layout, like existing walls or columns, can be incorporated. We introduce a new mathematical layout model and develop several improvement procedures. An analysis of the computational experiments shows that more elaborate heuristics using variable neighborhoods can generate promising layout configurations.

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DOI: https://doi.org/10.1016/j.ejor.2005.10.040 

Abstract: In this paper we apply linear control theory to study the effect of various inventory policies on order and inventory variability, which are key drivers of supply chain performance. In particular, we study a two-echelon supply chain with a stationary demand pattern under the influence of three inventory policies: an inventory-on-hand policy that bases orders on the visible inventory at an installation, an installation-stock policy that bases orders on the inventory position (on-hand plus on-order inventory) at an installation, and an echelon-stock policy that bases orders on the inventory position at that installation and all downstream installations. We prove analytically that the inventory-on-hand policy is unstable in practical settings, confirming analytically what has been observed in experimental settings and in practice. We also prove that the installation-stock and echelon-stock policies are stable and analyze their effect on order and inventory fluctuation. Specifically, we show the general superiority of the echelon-stock in our setting and demonstrate analytically the effect of forecasting parameters on order and inventory fluctuations, confirming the results in other research.

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DOI: https://doi.org/10.1080/07408170600967149 

Abstract: In this paper we apply linear control theory to study the effect of various inventory policies on order and inventory variability, which are key drivers of supply chain performance. In particular, we study a two-echelon supply chain with a stationary demand pattern under the influence of three inventory policies: an inventory-on-hand policy that bases orders on the visible inventory at an installation, an installation-stock policy that bases orders on the inventory position (on-hand plus on-order inventory) at an installation, and an echelon-stock policy that bases orders on the inventory position at that installation and all downstream installations. We prove analytically that the inventory-on-hand policy is unstable in practical settings, confirming analytically what has been observed in experimental settings and in practice. We also prove that the installation-stock and echelon-stock policies are stable and analyze their effect on order and inventory fluctuation. Specifically, we show the general superiority of the echelon-stock in our setting and demonstrate analytically the effect of forecasting parameters on order and inventory fluctuations, confirming the results in other research.

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Journal Articles (Professional)

Abstract: Advances in digital technologies open up new avenues for companies to interact with their consumers. End-to-end connectivity is fundamentally changing countless processes, boosting the efficiency of products, improving maintenance operations, and enhancing customer experience. In particular, smart replenishment systems that continuously track inventories at the point-of-consumption (POC) are powerful technologies that radically change supply chains: instead of manual inspections and errands, products are automatically reordered as required. This article outlines what smart replenishment systems are, discusses their benefits, and illustrates how they can be implemented.

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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.

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Abstract: Supply chain management has always been technology oriented and data intensive. But the ongoing explosion of big data and tools that make use of it promise a revolution for companies that can master them.

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Abstract: The new technologies behind Supply Chain 4.0 not only increase efficiency, they may also deliver huge benefits to the customer. Here’s how supply chain managers can leverage SC 4.0 to create game-changing customer experiences—and benefit as well.

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Abstract: Companies struggle to define the value proposition 3D printing brings: While the opportunities for improving products are obvious, how to generate value from it is not. Firms need to first examine its potential and risks along three dimensions: product innovation, customisation, and complexity. Then they need to set clear boundaries for permissible customisation, and decide where to situate 3D printing within their organisation.

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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.

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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.

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Abstract: Forscher haben die Ausbildung und Karrierepfade von Supply-Chain-Führungskräften untersucht. Die Ergebnisse lesen Sie in Teil eins der zweiteiligen Serie "Wer lenkt unsere Supply Chains?"

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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.

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Books

 

Abstract: Despite the spread of automation and new supply chain management paradigms, logistics remains dependent on a rather specific set of skills and competences, whether for managerial, administrative or blue collar jobs, such as trucking or warehousing. This implies that the logistical performance of businesses, industries and nation states is strongly influenced by the quantity and quality of the workforce. Insufficient resources of a competent and properly trained workforce in logistics adversely affect the quality of service, reduce productivity in sectors dependent on logistics and ultimately reduce trade competitiveness. While other interventions that affect logistics performance, such as international infrastructures, trade corridors, regulations and services have already been reviewed extensively, this report is the first to cover the contributions of human resources and how to develop skills and improve competences, especially in developing countries. The study proposes a framework for the skills needed according to the logistics activity (e.g. transportation or warehousing) or the type and level of responsibilities. Based on several sources, including recent surveys carried out by the World Bank and the Kuehne Logistics University, the report uncovers where the skills constraints are according to the type of job or countries. Findings include that logistics is an industry struggling to hire skilled workers, although with differences between rich countries (where trucker shortages are more acute) vs. developing economies (were managerial shortages are more widespread). Typically blue-collar logistics jobs have lower status and lower pay than blue-collar jobs in other industries, and are thus less attractive for skilled workers. In developing countries with a potentially available workforce, lack of vocational preparation for careers in logistics means that less skilled workers are not easily re-skilled. Logistics tasks at the upper end of the occupational hierarchy and those with high IT content often require an upskilling of employees to keep pace with new technology. Yet the problem is not confined to recruitment. The surveys points to limited resources, money and staff time allocated to training, especially in developing countries. Realizing the promise of quality jobs from the growth of logistics worldwide requires a coordinated effort by logistics companies, professional associations, training providers and policymakers. Through a combination of facilitation, regulation, advice, financial instruments and land use planning, governments can exert significant influence. © World Bank

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Conference Proceedings

Book Chapters

DOI: https://doi.org/10.1007/978-3-658-24576-4_7 

Abstract: Die digitale Transformation hat das Potenzial, die Supply Chains zu verändern wie selten zuvor. Eine Vielzahl neuer digitaler Technologien eröffnet kaum abzusehende Möglichkeiten für die Optimierung der Prozesse entlang der Wertschöpfungskette: Der 3-D-Druck erlaubt die kundenspezifische Produktion eines einzigartigen Produkts in Serienqualität, vernetzte Sensoren kontrollieren die Bestände in Regalen oder Kühlschränken samt voll automatisierter Nachbestellungen, und Big Data unterstützt Unternehmen, ihre Lieferfahrzeuge so durch den Verkehr zu führen, dass sie beim Kunden eintreffen, wenn dieser tatsächlich zu Hause ist. Unternehmen aller Branchen müssen die Chancen der Digitalisierung ganzheitlich betrachten und verstehen, wie sie ihre Supply Chain 4.0 realisieren können.

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Case Studies

Abstract: This is part of a case series. The case provides students with a hands-on experience on 3D-printing and the opportunity to discuss possible applications and challenges of 3D-printing. The case is built around the fictional company ForkInc, a material handling equipment manufacturer based in Germany. The after sales business unit is asked by the new CEO look into the application of 3D-priting for spare parts management. In part A of the case, students will first need to identify advantages of the technologiy. Next, the will compare the differences among industries where 3D-printing is already widely applied and discuss drawbacks for the material handling equipment manufacturer. In part B of the case, they will be able to work with a spare parts data set to identify for which parts 3D-printing is a viable option given the drawbacks identified before. Based on high order quantities and low demand rates 3D-printing should be investigated for 6-15% of the products.

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Abstract: This is part of a case series. The case provides students with a hands-on experience on 3D-printing and the opportunity to discuss possible applications and challenges of 3D-printing. The case is built around the fictional company ForkInc, a material handling equipment manufacturer based in Germany. The after sales business unit is asked by the new CEO look into the application of 3D-priting for spare parts management. In part A of the case, students will first need to identify advantages of the technologiy. Next, the will compare the differences among industries where 3D-printing is already widely applied and discuss drawbacks for the material handling equipment manufacturer. In part B of the case, they will be able to work with a spare parts data set to identify for which parts 3D-printing is a viable option given the drawbacks identified before. Based on high order quantities and low demand rates 3D-printing should be investigated for 6-15% of the products.

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Working Papers

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