The Role of Schedule Mismatch in Ending Inventory Decisions in the Presence of Price Cuts

In the high‐tech sector, component suppliers are often able to offer preannounced price cuts (price markdowns) to manufacturers due to technological innovation that allows them to produce the existing components at lower costs. In this context, manufacturers (buyers) are primarily concerned with their existing inventory carried beyond the price cuts in order to lower inventory costs. In this research, we develop a newsvendor‐based decision model for this problem based on our experience in industry and a focal case study environment. Specifically, we consider the issue of delivery and demand uncertainties, and the interplay of the buying firm's operating hours and the transportation carrier's delivery hours, which combine to influence inventory costs and order fulfillment. We illustrate the results with numerical examples and sensitivity analyses, using a real world data set. We found that stockout cost plays a critical role in the ending inventory decisions. Lowering stockout cost will benefit buyers from lower risk of obsolescence costs.     

Supply Chain Networks With Multiple Retailers: A Test of the Emerging Theory on Inventories,Stockouts, and Bullwhips

While various approaches to mitigating the bullwhip effect have been proposed, the composition of the underlying supply chain is often taken for granted. This article develops a set of simulation models to investigate changes to the supply chain itself and their impact on the bullwhip effect, on‐hand inventory, and stockouts. It is shown that particular supply chain networks have an impact on the bullwhip effect. Furthermore, the impact of supply chain networks on the bullwhip effect is moderated by the demand forecasting technique used. Finally, supply chain networks, forecasting techniques, and their interactions are found to influence on‐hand inventory levels and stockout rates for firms within the supply chain. Results also suggest that no one particular type of supply chain network dominates in terms of dampening the bullwhip effect, lowering on‐hand inventory levels, or reducing stockout rates. The optimal network depends on the forecasting technique used and other supply chain factors.     

Intertemporal pricing strategies for fashion tech products with consumption externalities

With the rapid development of technology, more and more products tend to both meet customers’ functional needs and provide stylish consumption experiences at thesame time. We define them as “fashion tech” products. In practice there exist two opposite consumption externalities associated with “fashion tech” products. One, some customers are more likely to purchase the product if fewer customers can afford or have access to it to advertise their prosperity or good taste. In contrast, other customers’ utility increases with the rising number of other customers. Thus the firm needs to consider such consumption externalities in their pricing decisions in order to appropriately position products and maximize profits. In such contexts, this paper optimizes intertemporal pricing strategies for fashion tech products selling to strategic customers with two kinds of externalities. We find that a markdown strategy is always optimal. In addition, it is appropriate for the firm to use slight markdowns when both the fraction of snobs and probability of stockout are small or use sharp markdowns otherwise.     

Flying under the radar: Foreign firm visibility and the efficacy of political strategies in emerging economies

Although emerging markets hold great potential, foreign firms operating in those markets are exposed to a comparatively higher level of risk as compared to developed markets. We examine the role of foreign firms’ visibility in shaping the effect of the strategies they deploy to reduce their exposure to environmental risk. Building on and extending research on political strategies we develop hypotheses and test them against data from 173 MNE subsidiaries operating in six emerging economies. We find that visibility affects not only the strength, but also the direction of the association between political strategies and foreign firms’ exposure to risk. Our findings enhance understanding of the use of different political strategies for reducing their exposure to risk and of the moderating role of their visibility in emerging markets.     

An empirical analysis of demand variations and markdown policies for fashion retailers

In this paper, using data from a leading specialty apparel retailer, we empirically examine the determinants of a retailer's dynamic pricing policy and investigate consumer response to price changes (markdowns) throughout a fashion product's selling season using a product diffusion setting. In order to do that, we first develop and estimate a markdown pricing model and a consumer demand model that capture the important characteristics of the fashion apparel market. Next, we use the estimates from these two models to design and simulate four alternative markdown pricing policies to investigate the impact of these different policies on consumer demand and retailer revenues. Our results, in line with the previous literature, show that markdowns implemented early in the season but small in magnitude generate the highest retailer revenues. Our paper not only provides a comprehensive empirical framework for fashion apparel retailers that is easy to implement, but also shows that using this framework will lead to timely decision making and will improve sale and revenue outcomes in the fast paced fashion world.     

Hit and Run or Sit and Wait? Contestability Revisited in a Price-Comparison Site-Mediated Market

The price-comparison site, with its (near-)zero sunk costs of entry, would appear to approximate the “almost perfectly contestable market” envisaged by the contestability theorists where “hit-and-run” entry was conjectured to constrain sellers to zero-profit outcomes. We investigate hit and run using a unique unbalanced panel of 295 digital-camera markets mediated by NexTag.com. We find, however, in line with Farrell (1986a)’s prediction, a bifurcation of strategies with low reputation/smaller participants favouring a hit-and-run strategy involving lower entry prices and shorter forays into the market than their high reputation/larger rivals. Furthermore, the former entrants induce a much larger price response from low-reputation incumbents, reflecting the more intense rivalry for the price-sensitive consumers willing to eschew retailer reputations.     

Is the online-offline buy-online-pickup-in-store retail strategy best among other product delivery strategies under variable lead time?

Every industry improves customer satisfaction by either preventing stockout situations or fulfilling the customer's demand by reducing lead time and variance of the lead time with several services offered. This study considers online selling, offline selling, and buy-online-pickup-in-store policies for selling products from retail stores. This study builds a characteristic relation between buy-online-pickup-in-store, backorder, and on-hand inventory by giving an exact total profit function instead of the expected profit function. The marginal values on lead time and variance of the lead time earn more exact outcomes for any retail strategy. The specific transportation cost for different retail strategies is considered and tested. This paper shows the analytical results which prove that the total profit of the sustainable supply chain is a convex function of both lead time and variance of the lead time. As different channel selling is crucial to any industry for increasing customer demand, the retailer sells their products by hybrid channel and advertises their products online to make them more famous. The model is solved through a classical optimization technique to get a semi-closed-form solution. In this method, it is possible to find out the optimum results for the decision variables separately by equating the first order partial derivative of the total profit with respect to the decision variables to zero and the global optimality by the Hessian matrix. A numerical experiment is conducted here, and the result shows that the supply chain system gives 14.48% more profit if advertisement policy is applied. The supply chain system gives 57.31% less profit and 72.72% less profit when only an online or offline channel is adopted, respectively. A sensitivity analysis is done for the managerial effects of cost parameters on the total profit.     

Changing the game to compete: Innovations in the fashion retail industry from the disruptive business model

Unprecedented competition and emergent technologies have posed a challenge to many traditional retailers in recent years. Yet within this competitive environment, emerging innovative business models have thrived and successfully disrupted the industry. We analyze the nature of disruptive business-model innovations and the ways they disrupt the fashion retail industry. To that end, we examine three disruptors in the industry: born-digital brands, AI-enabled demand forecasting and product design, and collaborative consumption. After introducing the concept of disruptive business-model innovation, we discuss the three disruptors’ effects on the fashion industry. We find that all of these models keenly answer fundamental needs unmet by current business models, such as offering quality products at a competitive price, curated services, and sustainable consumption. At the same time, all three disruptors suggest effective operation models for handling demand uncertainty, inventory management, and timely responses to the market, all of which are inherent issues for current push supply chains and forecast-based, inventory-driven systems. Based on this analysis, we discuss important implications for both academics and industry practitioners.     

AN INVESTIGATION INTO THE EFFECT OF FULL‐SCALE SUPPLY CHAIN MANAGEMENT SOFTWARE ADOPTIONS ON INVENTORY BALANCES AND TURNS

Supply chain management (SCM) software vendors, analysts, and others claim that firms implementing SCM software stand to benefit by being able to reduce inventory holdings and increase inventory turns. We theorize that full‐scale implementations lead to system‐wide inventory optimization, which in turn leads to cost improvement associated with inventory balances and turns. To examine the question, we develop an analytical model of inventory optimization, then analyze the effects of the model with a numerical experiment, and finally confirm the results with an empirical examination. We find that firm‐wide implementation is significant in explaining improvement in inventory metrics, relative to pre‐implementation metrics for our sample. Our empirical tests indicate that implementing SCM software across only a portion of the firm does not impact inventory metrics, but that the scale of implementation does. More precisely, we find that firms implementing SCM software across the entire company significantly improve both inventory turns and inventory as a percent of revenue relative to partially‐implementing firms and non‐implementers.     

Predictive abilities of speculators in energy markets

Using nonparametric methodology, I find that speculators are successful in taking profitable positions in energy futures markets, although the magnitude of this effect is lower than that found previously for agricultural markets. A plausible explanation for this difference is that price forecasting is more difficult for energy commodities. Moreover, I find that the energy speculators’ returns are due to the existence of the risk premiums rather than to speculators’ forecasting abilities. Futures risk premium is highly time-variant; notably, energy investors’ profits have been very limited in the GFC and post-GFC period, which coincided with the financialization of commodity markets.     

The Achilles’ heel of the platform business model: Disintermediation

Multisided marketplaces have become fixtures in many contemporary industries. From Amazon to Google, platforms dominate entire markets and have become some of the world’s most valuable companies. Despite their success, these companies have a subtle but potentially fatal weakness: disintermediation. This occurs when buyers and sellers find each other on the platform and then bypass that very platform—and its commission—to complete their transaction directly, off of the platform. This article compiles and illustrates the causes of and remediations to platform disintermediation.     

Channel Intermediaries and Manufacturer Performance: An Exploratory Investigation in an Emerging Market

Channel intermediaries (hereafter, intermediaries) are among the most critical elements of any supply chain as the bulk of manufacturing output is transported through them. However, we have a limited understanding of the approach a manufacturer should take to achieve the dual goal of increasing profitability and intermediary satisfaction. To provide manufacturers with practical strategies to boost their performance and their intermediaries’ satisfaction, we rely on three related studies. In Study 1, through interviews with managers and intermediaries, we find that distribution alignment across intermediary, market, and product types may be a practical strategy for both manufacturers and intermediaries. In Study 2, by using a robust empirical methodology with data from a construction product manufacturer operating in an emerging market, we find that various combinations of intermediary, market, and product types affect the manufacturer’s performance differently. Accordingly, through a supply-side examination, we quantify the revenue impact of reallocating the studied manufacturer’s retail distribution resources among different intermediary-, market-, and product-type combinations. In Study 3, through a field implementation, we find that our recommended intermediary alignment strategy from Study 2 substantially boosts both the manufacturer’s performance (by fourteen percent in revenue and thirteen percent in profit) and intermediaries’ satisfaction (by 7.71%). Thus, with our qualitative, empirical, and field studies, we contribute to the existing research in channel management, emerging market retailing, retail distribution, and marketing strategy.     

How Verifiable Cheap-Talk Can Communicate Unverifiable Information

This study describes a “cheap-talk” model in which sellers can credibly convey unverifiable information by choosing whether or not to exaggerate verifiable information. We find that unexaggerated claims can communicate favorable unverifiable information if buyers are not too likely to verify claims, and sellers with better information care more about future prices than sellers with worse information. However, there is always another equilibrium in which sellers exaggerate all verifiable claims. Laboratory tests show that when buyers infrequently verify the sellers' claims, players converge to the equilibria close to the example provided in instructions. When buyers are very likely to verify claims, players fail to converge to any equilibrium. Both of these results are consistent with an evolutionary learning model, but inconsistent with the intuitive criteria of Cho and Kreps (1987). We discuss the implications of our results for both consumer and financial markets. Helpful comments were received by an anonymous reviewer, Mark Nelson, many doctoral students at Cornell University, and Accounting workshop participants at the University of Texas at Austin. JEL Classification: C73, C92, G14, M3     

Forecasting intermittent demand for inventory management by retailers: A new approach

The forecasting of intermittent demand is a complex task owing to demand fluctuations and interval uncertainty. Intermittent demand is essentially random demand with a high percentage of zero values. In the retail industry, there are many products which face intermittent demand and this poses a problem of inventory management. This study proposes a Markov-combined method (MCM) for forecasting intermittent demand, which takes into account the inventory status and historical sales of products. We divide the prediction process into two stages. In the first stage, the transition probabilities of the four basic states of demand and inventory are calculated. In the second stage, the corresponding and appropriate prediction method is selected according to the predicted state. Further, using two large datasets from the two biggest e-commerce companies in China, we verify our results and show that the MCM forecasts more accurately than the Single Exponential Smoothing (SES), Syntetos-Boylan Approximation (SBA), and Croston (CR) methods. The MCM can be as an alternative method for forecasting intermittent demand because it is easy to compute and typically more accurate than the classical forecasting methods.     

CONSUMER DIRECT FULFILLMENT PERFORMANCE IN INTERNET RETAILING: EMERGENCY TRANSSHIPMENTS AND DEMAND DISPERSION

The collaborative fulfillment of consumer orders by Internet retailers and wholesalers has proven important in the realization of sustainable levels of online profitability. Concentrating on consumer direct fulfillment (or drop shipping), an empirical simulation model evaluates avenues for improving logistical performance. The empirical simulation model centers on the online music CD retailing industry. It evaluates the effects of emergency transshipments and demand dispersion on inventory and product‐release performance, as well as on transportation costs, in consumer direct fulfillment operations. Results show that emergency transshipments improve inventory and product‐release performance in these operations. Furthermore, the inventory‐performance improvements are maximized when inventory facilities fulfill demand that is uniformly balanced across markets primarily assigned to each facility. Finally, gains in inventory and release performance obtained from emergency transshipments outweigh additional transportation costs incurred from a greater reliance on emergency transshipments for consumer direct fulfillment.     

The influence of strategic patterns of internationalization on the accuracy and bias of earnings forecasts by financial analysts

This paper examines how financial analysts’ earnings per share forecasts are affected by strategic patterns that multinational firms have used to expand abroad. Prior empirical studies have examined a firm's internationalization level as a one-dimensional construct involving increased task complexity for financial analysts’ forecasting and therefore resulting in lower accuracy and greater optimistic bias in earnings forecasts. In contrast, we use two strategic patterns of internationalization associated with geographic dispersion and cross-border integration to characterize a firm's international strategy, and find different empirical results using a sample of U.S. public companies with domestic and international operations. The empirical evidence suggests that geographic dispersion contributes to increases in forecasting accuracy and decreases in optimistic bias. Further, the results support that cross-border integration leads to decreases in forecasting accuracy. The two strategic patterns of internationalization are a consequence of managerial choices and therefore these results are important for managers, investors and shareholders as they help explain the linkages between international strategies and earnings forecasts by financial analysts.     

Hurry! Sale Ends Soon: The Impact of Limited Inventory Availability Disclosure on Consumer Responses to Online Stockouts

A prevalent challenge for online retail supply chain managers is maintaining and managing adequate inventory levels to support and fulfill consumer orders and purchases. Interestingly, this challenge is not only about maintaining inventory availability, but also how to effectively disclose and communicate inventory availability, particularly if a stockout occurs. This article investigates a conceptual model that explores the impact of online inventory availability disclosure on consumer perceptions in the context of a stockout. Based on expectation disconfirmation theory, the core of the model is the notion that limited inventory availability would stimulate expected consumer competition, which in turn, causes consumers to not be as negatively impacted by stockouts. Contrary to this prediction, however, the results of this experimental study show that consumers are actually more dissatisfied when low inventory availability items are out‐of‐stock. This is likely due to the combined impacts of a stockout encounter and a “loss” of a competitive shopping scenario. Thus, implications of these findings for future research and supply chain practice are offered accordingly.     

Investigating the Effects of Daily Inventory Record Inaccuracy in Multichannel Retailing

Inventory record inaccuracy (IRI) challenges multichannel retailers in fulfilling both brick‐and‐mortar and direct channel demands from their distribution centers. The nature and damaging effects of IRI largely go unnoticed because retailers assume daily IRI remains stable over time within the replenishment cycle. While research shows that a high level of IRI is damaging, in reality the level of IRI can change every day. We posit that daily IRI variation increases the uncertainty in the system to negatively affect inventory and service levels. Our research uses data collected daily from a multichannel retailer to ground a discrete‐event simulation experiment. Going beyond testing just the level of IRI, we evaluate daily IRI variation's impact on operating performance. What we find in our empirical data challenges extant assumptions regarding the characteristics of IRI. In addition, our simulation results reveal that daily IRI variation has a paradoxical effect: it increases inventory levels while also decreasing service levels. Moreover, we also reveal that brick‐and‐mortar and direct channels are impacted differently. Our findings show that assumptions and practices that ignore daily IRI variation need revising. For managers, we demonstrate how periods of multiday counting help assess their daily IRI variation and indicate what the causes may be.     

Pricing Experience Goods in Information Good Markets: The Case of eBusiness Service Providers

We study the pricing strategies of firms providing a service in experience good markets with switching costs. Using data on vendors providing “hosting and related services” at an early stage of the market, we test for pricing distortions that follow from oligopolistic competition with quality uncertainty and switching costs. We find that firms with a brand name charge a premium for their product – leveraging the reputation accumulated in closely related markets. As the theoretical literature suggests, we also find that the type of pricing distortions along the product line depends on consumers’ expectations about quality. If consumers underestimate the quality of the product, firms behave as if they discount introductory contracts in order to build trust, and later on markup upgraded contract. In contrast, firms that offer a quality level that is lower than consumers’ expectations markup initial contracts while discounting upgraded ones.     

Trader networks and options risk management

We examine the effect of trading partner concentration and a matrix of variables which dictate the relative importance of a trader to the network on a set of large member proprietary traders’ risk. An increased closeness centrality and concentration of trading among network partners are found to reduce price, volatility and rebalancing risk. We further explore the nature of trading concentration established through traders’ recurring trading relationships to find that trading with an established and small network has a positive, yet costly, effect on inventory management. Relationships among market makers are important to managing their portfolio of risk.