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Execution: The Missing Link in Retail Operation
Abstract
In spite of making substantial investments in information technology planning systems, retailers are struggling with two execution problems—" inventory record inaccuracy" and "misplaced stock keeping units (SKUs)"—that are hurting their performance and ability to satisfy customers. At one leading retailer, sixty-five percent of their inventory records were inaccurate (i.e., recorded inventory levels did not reflect actual inventory levels). Misplaced SKUs, at another leading retailer, prevented one in six customers who requested help from a sales associate from finding the products that were available in a store. These execution problems reduce profits by more than 10%. Moreover, performance along these two dimensions of execution varies substantially among stores within the same chain that use identical information technology. By examining the systematic differences that exist among stores, this article identifies the drivers of inventory record inaccuracy and misplaced SKUs and recommends steps retailers can take to improve operational execution in their chains.
... Misplacement of stock can occur when a consumer places products in unreachable areas. Inventory misplacement is considered the most expensive and prevalent reason for the discrepancy in supply chains (Raman et al., 2001) because it influences stock administration in two ways. When an item is lost in the stockroom, the loss is noticed only when the item is considered to be out of stock, thereby reducing the business accessibility of the item to the customer; however, the physical stock remains unchanged and consequently increases the holding cost (Taleizadeh et al., 2020). ...
... The retailer's first lot is fulfilled by remanufactured items collected in the last replenishment cycle. Items are stored in the retailer's stockroom, where a small portion of the lot is misplaced in the warehouse (Raman et al., 2001). ...
... com/articles/view?16510. Other required information regarding the misplacement of the inventory is taken from Raman et al. (2001). However, no articles on product types like tennis rackets were not found N. Saxena and B. Sarkar in the literature for management concerning visibility and profitability; therefore, a reasonable estimation has been done for the system. ...
Practitioners face two significant issues: product inaccuracy and transparency in supply chain management. Blockchain is a highly secure and trustworthy means of storing data. Radio frequency identification incorporation is essential if reliability is at a low level. Incorporating radio frequency identification can improve supply chain management in terms of product's visibility for the best replenishment strategy. A production and replenishment coordination via mathematical modeling is visualized through a three-echelon supply chain with a non-reliable production process, and the retailer deals with misplacement issues. The manufacturer handles the inventory flowing reversely and is responsible for proper end-of-life treatment, either repairing or remanufacturing. Repairs are sold in bulk on the secondary market, and remanufactured items are used to prevent retailers' shortages. In this model, radio frequency identification technology on the physical surface is combined with a blockchain on the cyber surface, containing all the information about the product, including its location and attributes. A comparative study is provided for the traditional supply chain with misplacement versus a blockchain-based supply chain with radio frequency identification. An analytical approach is used to arrive at the optimum policy for the practitioners, and numerical analysis illustrates the problem. Numerical experiments indicate that the technology is highly profitable for supply chain management. Radio frequency identification technology can increase profit by up to 61%. After discrepancy, holding cost is the second most sensitive parameter for the profit function. If the holding cost is higher, profit can be increased by 40% using radio frequency identification and blockchain. The negative effect of misplacement is reduced with an increasing demand rate, but the reduction rate is very slow. The choice of not adopting radio frequency identification can only be successful if demand is so high that it can reduce the effect of misplacement.
... Misplacement of inventory could occur when a consumer has put products in unreachable areas. Inventory misplacement is considered the most expensive and prevalent reason for the discrepancy in supply chains [17] because it influences stock administration in two ways. When an item is lost in the stockroom, the loss is noticed only when the item is considered to be out of stock, thereby reducing the business accessibility of the item to the customer; however, the physical stock stays unaltered and consequently builds the holding cost [24] [18] was the first to address inventory inaccuracy. ...
... When an item is lost in the stockroom, the loss is noticed only when the item is considered to be out of stock, thereby reducing the business accessibility of the item to the customer; however, the physical stock stays unaltered and consequently builds the holding cost [24] [18] was the first to address inventory inaccuracy. Another study to prove the existence of the inventory inaccuracy problem was given by [17]. They found that the inaccuracy rate of inventory records was 65%, and the loss due to this inaccuracy was approximately 10%. ...
... [18] was the first to address inventory inaccuracy. The inventory accuracy problem was also proven by [17] in their study. They found that inventory records are approximately 65% inaccurate, and the loss resulting from this inaccuracy was around 10%. ...
Inventory inaccuracy emerges as a significant management issue, leading to profit losses within the supply chain network. This study focused on randomly misplaced inventory. Here an integrated inventory model has been constructed with two-stage production with two manufacturing units. The first manufacturer produces semi-finished goods, while the second manufacturer produces the finished items. The reliability becomes a concern if the first manufacturer's production capacity is higher than that of the second one. Hence, process reliability has been considered to make the model more realistic. Proper handling of used products has been considered for sustainability purposes, and these items are either remanufactured or repaired. The manufacturer bears the stock out, and the remanufactured items are supposed to deal with the absence of material. Moreover, as the repairing may be cost-effective while remanufacturing, the manufacturer opts to repair the remaining items and resell them in the secondary market. The discrepancy resulted in a two-way loss to the retailer, as it reduced the product's business accessibility and built up the holding cost of the material. It is investigated with stochastic misplacement at the retailer's end, following the first kind's beta distribution. Idle time costs have also been considered. An analytical approach uses to derive the best policy for the provided model, and the numerical analysis illustrates the managerial perspicacity. The model's limitations have also been discussed, and a linear relationship is built between production cost and minimum selling price using the curve fitting least square method.
... Given that most retail backrooms are 15-20% of a retailer's store area [9] and are often home to many SKUs, there is a significant propensity for losing or misplacing products. Replenishing stock from backrooms can lead to putting all the items in the backroom, as opposed to stocking some on shelves, forgetting to replenish the sales floor, or failing to do so in a timely fashion [10]. It is important to note that most backrooms do not have assigned locations for items, and generally suffer from a lack of automation, often due to budget constraints [9]. ...
... Misplaced products in the backroom can result in incorrect shelf stocking, contributing to IRI or "phantom stockouts" (an issue that we discuss in a later section). For instance, after a case of products arrives at a store from the distributor, the products can be misplaced or lost [10], given the size and often unorganized nature of backrooms. If an employee later records or updates the inventory in the system and fails to record the misplaced items, IRI will occur and, as a result, the shelves may not be replenished appropriately. ...
... Corsten and Gruen [4], and Raman [10] point out that many inventory systems do not delineate between backroom location stock and shelf stock, meaning the inventory in backrooms is not well tracked, thus making them more susceptible to IRI. Few employees have time to count backroom inventory and compare on-hand inventory to system inventory, as backrooms are not prioritized when customers require attention on the sales floor. ...
This paper explores the impact of retail store backrooms on inventory record inaccuracies (IRI) and waste. A trend in the retail industry is operating in the absence of a backroom. Benefits of operating without a backroom can include more employee presence on the sales floor, quicker replenishment (or the elimination of traditional backroom to shelf replenishment entirely), lower on-hand inventory, and the reduction of waste in the form of time, labor, cashflow, and product obsolescence. By conducting a literature review of the published literature on retail backrooms, this paper explores two additional unstated benefits to retailers operating without a backroom; specifically, the reduction of IRI and waste—an angle that has been previously understudied in the current academic literature. The objectives of this paper include defining a link between the existence of a backroom and waste/IRI, presenting an opportunity for future research in this area of study, and providing practical advice for corporations that wish to operate with or without a backroom.
... Internally, inventory management, marketing strategies, human resource practices, and technological innovation are widely regarded as crucial drivers of retail success. Inventory management, for example, plays a pivotal role in ensuring product availability and minimizing stockouts, which directly impact customer satisfaction and sales revenue [8]. Similarly, effective marketing strategies-such as promotions, pricing, and merchandisingcan help retailers attract new customers and retain existing ones [2]. ...
... Notably, inventory turnover also emerged as a significant factor, though its impact on profit margins was weaker, suggesting that while efficient inventory management boosts sales, it may not directly translate into higher profitability. This is consistent with studies that emphasize the importance of balancing inventory efficiency with cost control [8]. ...
This paper provides a comprehensive review of key factors influencing retail enterprise performance, utilizing multivariate regression models to explore internal and external drivers. With the retail industry facing increasing competition, understanding how variables such as marketing strategies, supply chain efficiency, and consumer behavior interact to shape business outcomes is essential. Through an in-depth analysis of existing literature, the paper identifies both traditional and emerging factors—like digital transformation and omnichannel strategies— that significantly impact performance. By applying regression techniques, the paper highlights the interplay between these variables and provides practical insights for retail decision-makers. Furthermore, the study discusses the strengths and limitations of various regression models, offering suggestions for future research aimed at refining analytical approaches to retail performance forecasting
... The leading causes of inaccuracy in inventory cited by literature are human errors in the execution of tasks (such as receiving, picking, shipping, delivery, and scanning) and incorrect records (Barratt et al., 2018;Best et al., 2022;Chuang & Oliva, 2015;Drohomeretski & Favaretto, 2013;Lei et al., 2018;Rekik et al., 2019a, b;Sarac et al., 2010), theft (Qin et al., 2017;Su et al., 2021;Waller et al., 2006) obsolescence (Kang & Gershwin, 2005), incorrect location (Brown et al., 2001;Raman et al., 2001), lack of training (Brown et al., 2001), long time between physical inventories (DeHoratius & Raman, 2008), damage (Rekik et al., 2019b), shrinkage (Chuang & Oliva, 2015;Lei et al., 2018;Wang et al., 2016), lack of clear procedures (Raman et al., 2001), low employee remuneration or motivation (DeHoratius & Raman, 2008), inaccessible inventory (Lei et al., 2018), lack of CC (Brown et al., 2001). Best et al. (2022) demonstrated that items' misplacement rate was one of the main drivers of positive IRI. ...
... The leading causes of inaccuracy in inventory cited by literature are human errors in the execution of tasks (such as receiving, picking, shipping, delivery, and scanning) and incorrect records (Barratt et al., 2018;Best et al., 2022;Chuang & Oliva, 2015;Drohomeretski & Favaretto, 2013;Lei et al., 2018;Rekik et al., 2019a, b;Sarac et al., 2010), theft (Qin et al., 2017;Su et al., 2021;Waller et al., 2006) obsolescence (Kang & Gershwin, 2005), incorrect location (Brown et al., 2001;Raman et al., 2001), lack of training (Brown et al., 2001), long time between physical inventories (DeHoratius & Raman, 2008), damage (Rekik et al., 2019b), shrinkage (Chuang & Oliva, 2015;Lei et al., 2018;Wang et al., 2016), lack of clear procedures (Raman et al., 2001), low employee remuneration or motivation (DeHoratius & Raman, 2008), inaccessible inventory (Lei et al., 2018), lack of CC (Brown et al., 2001). Best et al. (2022) demonstrated that items' misplacement rate was one of the main drivers of positive IRI. ...
Paper aims: The objectives of this paper are: (i) to analyze the impacts of Inventory Record Inaccuracy (IRI) on picking
productivity (PP), lost sales (LS), and warehouse capacity utilization (WCU) for different warehouses; (ii) verify if the Cycle
Counting (CC) implementation is sufficient to reduce IRI and (iii) the number of CC operators to maintain warehouse
performance.
Originality: A causal loop diagram in detail of the IRI and CC variable’s effects in receiving and picking processes is
developed. IRI is separated into ghost and hidden inventory to represent the actual effects in WCU, LS, and PP.
Research method: A dynamic system model is built. Simulations are performed for the five categories of warehouse
performance with different numbers of CC operators.
Main findings: IRI impacts in all warehouses simulated, so managers should monitor IRI besides employee productivity. CC
can reduce IRI in all types of warehouses. The number of CC operators to be implemented is different for each warehouse.
Implications for theory and practice: Several implications for theory and practice are discussed. For example, IRI impacts
more ADV and BIC warehouses without CC implementation. In TYP, ADV, and BIC warehouses CC is sufficient to reduce
IRI. In MO and DIS warehouses, other improvements are needed.
... shelf sizes, selling of items in case packs) may cause positive inventory discrepancies or modulate their intensity. We extend prior research that investigated causes of IRI (Raman et al., 2001;Fleisch and Tellkamp, 2005;Kull et al., 2013;Barratt et al., 2018). The main contribution of our work is the investigation of new influence factors of positive IRI and the analysis of interaction effects between them in a single simulation. ...
... For each IRI source, an individual probability distribution is used. The implementation of the IRI sources (in terms of type and probability distribution) was taken from the related literature (Raman et al., 2001;Fleisch and Tellkamp, 2005;Condea et al., 2012) as well as from initial individual discussions with loss protection managers from a group of retailers. All considered sources of IRI were comprehensively discussed, validated and approved in the subsequent practitioner workshop. ...
Purpose
Ensuring high on-shelf availability at low inventory costs remains an important challenge in retailing. Inaccurate inventory records, i.e. discrepancies between the stock records displayed in the inventory system and the stock quantity actually found in the retail store, have been identified as one of the most important drivers of retail stockouts in the past. The purpose of this work is to investigate the causes of positive inventory discrepancies in retailing, i.e. where there is more inventory on-hand than identified by the inventory system.
Design/methodology/approach
Based on input from retailers, the authors develop a simulation model of a retail store that considers various error-prone processes and study in a full factorial test design how the different operational errors may drive inventory discrepancies, paying special attention to the sources of positive inventory record inaccuracies.
Findings
This makes it possible to gain insights into the process parameters retailers need to adjust to avoid inventory records becoming inaccurate. In addition, the authors analyze how positive inventory discrepancies relate to stockouts to further our understanding of the role so-called phantom products may play in a retailing context.
Originality/value
While negative inventory discrepancies (where the stock that is available in the store is less than what the system displays) and their sources (theft, shrinkage, etc.) have been discussed quite frequently in the literature, the causes of positive inventory discrepancies (where the available inventory exceeds the system inventory) have received much less attention.
... • Inventory data are known to often be inaccurate [34][35][36]. Ref. [37] found that in their study, 65% of inventory records were inaccurate. Inventory data inaccuracy for fruits and vegetables occurs due to product code entry errors during weighing by customers at the display area or at the checkouts by employees. ...
... There are some limitations to our study. First, data could be partially inaccurate due to recording errors at retailers [34,35], which we try to correct using inventory correction data at the store level and by eliminating obvious data errors. Second, there is no recorded data for inventory age, which is the main driver for spoilage in the fruit and vegetable category. ...
Spoilage reduction in fresh product supply chains is an important challenge and represents great opportunities for cost savings and reduced environmental and social footprints. The purpose of this paper is to identify the drivers of spoilage and to discuss how these insights can be used to reduce spoilage.We use panel data techniques to quantify the drivers of spoilage in the days-fresh category using daily spoilage and supply chain data (457,539 store-SKU level observations) for fresh fruits and vegetables at Switzerland’s largest retailer. We quantify to what extent inventory, promotions, delivery type, commitment changes, order variations, order cycle, and quality issues influence spoilage. We discuss the mechanisms through which inventory age and product standards impact spoilage of days-fresh products. Our novel findings underline the necessity for specialized supply chain processes, tracking inventory age and damage, and collaboration with supply chain partners in the management of this fundamental product category.
... The retail workforce is a key to resolving execution issues (Raman et al., 2001), such as inventory record inaccuracy (DeHoratius and Raman, 2007), and phantom stockouts at retailers (Ton and Raman, 2010). Phantom stockouts occur when a product is available in the store but not on the right shelf (Fisher and Raman, 2010). ...
... Decreasing store labor is associated with a higher percentage of phantom products. A one-standard-deviation increase in the percentage of phantom products is associated with a 1% decrease in-store sales, which translates to a loss of roughly 7% of the net income (assuming a 30% gross margin) generated by an average store (Raman et al., 2001). Despite substantial changes in retailing (e.g., methods and time of delivery, store locations, shopping habits and product offerings) (Grewal and Levy, 2007), store associates continue to be the critical "sales messengers" mostly responsible for retailers' success. ...
Retail workforce optimization keeps store employees happy, improves customer service, and reduces opportunity costs of lost sales. As workforce compensation costs constitute one of the largest components of retailers' operating costs, there is a widespread tendency to understaff to save on those costs. In the case of workforce undersizing, when a retailer decides to increase the size of the workforce, the additional workforce not only generates incremental revenue with better sales conversion but also has a positive impact on workforce morale, as the workforce is not overstretched. It also results in higher retention of the retail workforce. Improved retail workforce retention leads to lower hiring and training costs and improved store performance. On the other hand, retail workforce oversizing results in higher payroll costs and decreased engagement of retail employees. Hence, there is a need to find the right number of store employees to provide consistent customer service even during the period of volatile store traffic and still manage compensation costs favorably. The research provides various frameworks to investigate whether retail stores are properly sized and studies the impact of optimal workforce sizing on retail workforce compensation costs and ultimately on store performance.
... Analysis-focused literature is either empirical in nature, or it does not present a specific model nor its optimization. Empirical research focusing on inaccuracy can be found in [20,31] and [22], while [10] present a simulation study and share results and insights. One article found that inaccuracy amounted to 10% of profits over a certain period for a select case [22]. ...
... Empirical research focusing on inaccuracy can be found in [20,31] and [22], while [10] present a simulation study and share results and insights. One article found that inaccuracy amounted to 10% of profits over a certain period for a select case [22]. ...
Many hospital supply chains in the US follow a “stockless” structure, often implemented with the acquisition of new systems promising improved efficiencies and responsiveness. Despite vendor promises, supply chain gains from new technology are often unfulfilled or result in a reduction of performance. A critical component of achieving promised gains is the hospital’s ability to accurately and consistently capture hospital inventory use. In practice, recording demand with perfect, 100% accuracy is infeasible, so our models condition on the level of accuracy in a particular hospital department, or point-of-use (POU) inventory location. Similar to previous literature, we consider actual net inventory and recorded net inventory in developing the system performance measures. We develop two models, optimizing either cost or service level, and we assume a periodic-review, base-stock (or par-level) inventory policy with full backordering. In addition to choosing the optimal order-up-to level, we seek the optimal frequency of inventory counts to reconcile inaccurate records. Results from both models provide insights for supply chain managers in the hospital setting, as well as hospital administrators considering the adoption of similar technologies or systems.
... Phantom stockouts occur when a product is available in the store but not on the right shelf (Fisher& Raman, 2010). A one-standard-deviation increase in the percentage of phantom products is associated with a 1% decrease in-store sales which, translates to a loss of roughly 7% of the net income (assuming a 30% gross margin) generated by an average store (Raman et al., 2001). An increase in-store traffic would lead to more sales, as higher traffic provides more opportunities for sales conversion. ...
... Thus, sales are to be higher when products are shelved properly (Ton & Raman, 2010) and store associates are available to help customers in the purchase process (Fisher et al., 2006). The retail workforce is a key to resolving execution issues (Raman et al., 2001) such as inventory record inaccuracy (DeHoratius & Raman, 2007) and phantom stockouts at retailers (Ton & Raman, 2010). ...
The retail workforce is a strategic lever of the retailer for improving sales growth, market share, and profitability. With optimal retail workforce sizing and structure, customers would get prompt sales assistance and service, shelves should be replenished in a timely manner, store employees should be neither idle nor overstretched, and compensation costs should be managed effectively. Undersizing may hurt retailers in the long run as it affects merchandising capability and customer services, which ultimately hurt store sales and profits. Retail workforce optimization keeps store employees happy, improves customer service, and reduces opportunity costs of lost sales. The research provides various frameworks that outline the impact of undersizing in retail stores on sales and profitability and provides a methodology to determine the optimal workforce size. The research also provides an illustration with various scenarios to investigate whether a retail store is understaffed and calculates the financial impact of undersizing on revenue and profitability.
... Effective inventory management is critical to preventing stockouts and overstocking. Research by Raman et al. (2001) underscores the role of demand forecasting in aligning inventory levels with consumer needs. The integration of real-time inventory tracking systems, such as RFID and IoT sensors, has been shown to improve inventory accuracy and visibility (Zelbst et al., 2010). ...
The logistics sector is a cornerstone of global supply chains, facilitating the timely and efficient movement of goods and services. Despite its critical role, the industry faces persistent challenges, including inefficiencies in shipment tracking, delivery delays, communication gaps, and reliance on outdated technological infrastructure. This research paper investigates these challenges and evaluates advanced solutions such as modern tracking technologies, predictive analytics, and automation in logistics operations. Adopting a mixed-methods approach, the study combines qualitative and quantitative analysis to examine industry trends and propose actionable interventions. The findings highlight the pivotal role of digital transformation in enhancing operational efficiency, minimizing delays, and improving customer satisfaction, ultimately driving the competitiveness of the logistics sector.
... Also, the other rationale reason could be that stores with smaller areas incur lower costs. Finally, the findings of this article are in line with the findings of Raman et al. (2001) and Reiner et al. (2013) regarding the existence of problems in the non-optimal design of store space and the non-optimal arrangement of shelves. ...
Assessing the retail industry's efficiency is pivotal for economic growth and corporate productivity. This study employs a novel approach, utilizing a regression-based Stochastic Data Envelopment Analysis (SDEA) model, Balanced Scorecard (BSC), and Decision Tree. The integration of these methods is a pioneering effort in the retail sector. This is a data-driven decision-making framework, aiding managers in predicting efficient and inefficient Decision-Making Units (DMUs). Results from a case study in 44 retail store chains in Iran indicate that the accuracy of the SDEA model is 99%. The Decision Tree highlights low branch efficiency due to a low customer count, a unique finding in comparison to prior studies.
... According to (Kamali, 2019) taking cases of traditional warehouses in Bahrain, it was found that there are several areas in which the company is probably losing their money, such as excessive material handling, inefficient operations and bottlenecks in their workflow, material damage, inefficient space management, and inefficient material handling equipment (Liu et al., 2014). Other than that, inaccuracy of inventory data is a major problem in the retail industry (Raman et al., 2001). Companies are beginning to implement and adopt technologies to their warehouses. ...
Company X is a modern Indonesian retail company that faces stock inaccuracies continuously and the variances exceeds the limit set by the company that reduce its profits continuously. Variances are difficult to identify since the stock recording in company X is not separated between stock in the warehouse and the store and not using warehouse management system. Business process re-engineering will be carried out by proposed two alternatives using traceability technology for the warehouse management system. Standard operating procedures will also be developed and used as a guide in implementing the system. This study uses qualitative method from a semi-structured interview with the management team, observation, and focus group discussion. The data were analyzed with gap analysis, cause mapping, and analytical hierarchy process to select the proposed alternatives using QR Code and RFID. The results from data processing is show that the company select QR Code as the technology used.
... This error may occur due to the similarity or variety of goods, which is more tangible in more complex supply chains. Thereafter, Raman et al [13] reported that above 65% of the information system inventory of 37 retail stores of Gamma did not correspond to their inventory records. ...
Information and inventory flows are the lifelines of supply chain management which are closely intertwined. However in the real world, there are many errors between these two flows due to the variety of goods the number and variety of products. In this regard, the transaction errors are the common phenomena in supply chain processes such as receiving, selling, warehousing, etc. On the other hand, using RFID to reduce inventory errors via managers has doubts due to its costs. In present study, a novel methodology is provided for analyzing the effect of errors on information system inventory by applying the simulation approach. In addition, quantitative analyzing of RFID role in errors reduction is presented by determination of the optimal amount of inventory. To this, at first, the meaningful difference between profit in the absence and the presence of transaction errors was examined by statistical hypothesis testing and then optimal order quantity in the both of cases with and without the using RFID was calculated based on mathematical modeling. At last, the two-way sensitivity analysis approach is applied to examine the cost-effective using RFID. The results show that only at the point of optimal economic order quantity is always a meaningful difference between profit in the absence and the presence of transaction errors. Also the error rate is the most important factor and sale unit price and shortage cost are others factors, respectively for the cost-effective using RFID technology
... Cannella et al. (2015) demonstrated that in supply chains, even though a sufficiently small misplacement rate would result in significant unnecessary orderings according to a simulation experiment. Raman et al. (2001) found that the inventory misplacement problem caused a leading retailer to lose about 25% of the revenues. In addition, Heese (2007) revealed that 10% of retail stores' profits were lost due to inventory misplacement problems. ...
We investigate the RFID adoption and chain structure (i.e., integrated or decentralized) decisions in two supply chains under two competition modes (i.e., Bertrand or Cournot competition). Each chain consists of a manufacturer and an exclusive retailer, who suffers from inventory misplacement problem. Two supply chains first simultaneously choose chain structure and then decide whether to invest in RFID technology. We develop an analytical model to derive the equilibrium outcomes, then further analyze the interactions between RFID adoption and chain structure under two competition modes. We find that in equilibrium, both chains prefer to choose integration under Cournot competition, while they might be better off from decentralization under Bertrand competition. Moreover, there may exist a prisoner’s dilemma for the equilibrium strategies on RFID adoption and chain structure. Specifically, when both chains adopt RFID, the prisoner’s dilemma occurs if the competition is fierce; when only one chain adopts RFID, the chain who forgoes RFID adoption is easier to trap into the prisoner’s dilemma; when no chain adopts RFID, a high misplacement rate may aggravate the prisoner’s dilemma if the competition is weak, and the supply chain members under Cournot competition may escape such dilemma if the competition is fierce. In addition, competition mode doesn’t affect the optimal strategies for RFID adoption and chain structure. Further, in the case where the manufacturer affords a higher production cost, Cournot competition is more conducive to coordinate chains when competition is weak or relatively fierce, whereas Bertrand competition will be more effective when competition is moderate or very fierce.
... Merchandise is regularly shifted around in retail stores, so the more hours that associates work, the more exposure they have to merchandise placement. Phantom stock-outs may be reduced simply because gaps between employees' shifts are reduced (Raman et al. 2001, Lee et al. 2021. ...
We estimate the causal effects of responsible scheduling practices on store financial performance at the U.S. retailer Gap, Inc. The randomized field experiment evaluated a multicomponent intervention designed to improve dimensions of work schedules—consistency, predictability, adequacy, and employee control—shown to foster employee well-being. The experiment was conducted in 28 stores in the San Francisco and Chicago metropolitan areas for nine months between November 2015 and August 2016. Intent-to-treat (ITT) analyses indicate that implementing responsible scheduling practices increased store productivity by 5.1%, a result of increasing sales (by 3.3%) and decreasing labor (by 1.8%). Drawing on qualitative interviews with managers and quantitative analyses of employee shift-level data, we offer evidence that the intervention improved financial performance through improved store execution. Our experiment provides evidence that responsible scheduling practices that take worker well-being into account can enhance store productivity by motivating additional employee effort and reducing barriers to employees adhering to the scheduled labor plan.
This paper was accepted by David Simchi-Levi, operations management.
Funding: This research was supported by generous grants from the W.K. Kellogg Foundation, the Washington Center for Equitable Growth, the Robert Wood Johnson Foundation, the Institute of International Education in collaboration with the Ford Foundation, the Center for Popular Democracy, the Suzanne M. Nora Johnson and David G. Johnson Foundation, and Gap, Inc.
Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2021.4291 .
... Raman et al. [6] called the gap between strategy and actual results the missing link and named it execution. Reference [7] also adopted this expression, defining execution as the missing link between the goal and the result, and gave a note that this statement comes from Darwin's theory of biological evolution. ...
Over the years, experts have focused their research on ways to increase the executive capacity of university administrators. This is because only by improving the quality of execution of college and university administrative personnel can they actively execute various policies and measures, fully exploit their subjective initiative, and ensure the educational reform of colleges and universities. Increasing the executive capacity of administrative staff can help colleges and universities manage more effectively. Therefore, in the development process of higher education institutions, it is necessary to strengthen the execution of administrative staff, especially the need to adhere to the problem as the basic orientation. Take scientific and practical steps to strengthen administrative personnel’s executive ability in light of current issues with administrative management personnel’s executive power, and establish the groundwork for ensuring the quality of management work. Combining deep learning, this paper proposes a path to improve the executive power of college administrators based on deep learning. To begin, familiarize yourself with the deep noise reduction autoencoder model and support vector regression (SVR) theory and build the DDAE-SVR deep neural network (DNN) model. Then, input a small-scale feature index sample data set and a large-scale short-term traffic flow data set for experiments; then, assess the model’s parameters to achieve the optimal model. Finally, use performance indicators such as MSE and MAPE to compare with other shallow models to verify the effectiveness and advantages of the DDAE-SVR DNN model in the execution improvement path output of university administrators and large-scale data sets.
... By sharing information through suppliers, customers and within organizations we can manage the inventory inaccuracy like damaged, out-of-date, seasonal and incorrect incoming and outgoing deliveries and finally misplaced items (Hollinger & Davis, 2001;Raman et al., 2001). Due to this supply chain performance will decrease, so, to overcome this information sharing has to happen transparently all over the organization. ...
This paper aims to understand the impact of big data analytics on the retail supply chain. For doing so, we set our context to select the best big data practices amongst the available alternatives based on retail supply chain performance. We have applied TODIM (an acronym in Portuguese for Interactive Multi-criteria Decision Making) for the selection of the best big data analytics tools among the identified nine practices (data science, neural networks, enterprise resource planning, cloud computing, machine learning, data mining, RFID, Blockchain and IoT and Business intelligence) based on seven supply chain performance criteria (supplier integration, customer integration, cost, capacity utilization, flexibility, demand management, and time and value). One of the intriguing understandings from this paper is that most of the retail firms are in a dilemma between customer loyalty and cost while implementing the big data practices in their organization. This study analyses the dominance of the big data practices at the retail supply chain level. This helps the newly emerging retail firms in evaluating the best big data practice based on the importance and dominance of supply chain performance measures.
... Also, a study made by Raman et al. (2001) inaccurate inventory records has reduced profits by ten percent. Therefore, accuracy of the inventory records is vital for the performance of an inventory management system and necessary actions should be taken accordingly. ...
Recommendation systems mainly produce a list of recommendations in any field, using one of two methods - via Collaborative Filtering or Content-Based Filtering (Jafarkarimi, Sim, & Saadatdoost, 2012). Collaborative filtering depends on the behaviour of the previous user, such as products that he or she previously purchased or previous assessments, in line with similar decisions made by other users, so that the first user’s wishes can be expected based on the decisions of other users (Melville & Sindhwani, 2010). Content-based filtering is based on bringing similar products with their characteristics to the purchased product (Mooney & Roy, 2000). These methods are often used simultaneously to form a single system called Hybrid Recommender Systems (Balabanović & Shoham, 1997).
... Vehicle operator behaviors influence logistics performance and explain the gap between planned and actual distribution operations (e.g., routes, schedules). Thus, including the operators' knowledge into decision-making models and data-driven analytics will allow for synchronizing information technologies with human experience to achieve better delivery times, increase service level to customers, improve profit, etc. [50,51]. ...
Last-mile operations in forward and reverse logistics are responsible for a large part of the costs, emissions, and times in supply chains. These operations have increased due to the growth of electronic commerce and direct-to-consumer strategies. We propose a novel data- and model-driven framework to support decision making for urban distribution. The methodology is composed of diverse, hybrid, and complementary techniques integrated by a decision support system. This approach focuses on key elements of megacities such as socio-demographic diversity, portfolio mix, logistics fragmentation, high congestion factors, and dense commercial areas. The methodological framework will allow decision makers to create early warning systems and, with the implementation of optimization, machine learning, and simulation models together, make the best utilization of resources. The advantages of the system include flexibility in decision making, social welfare, increased productivity, and reductions in cost and environmental impacts. A real-world illustrative example is presented under conditions in one of the most congested cities: the megacity of Bogota, Colombia. Data come from a retail organization operating in the city. A network of stakeholders is analyzed to understand the complex urban distribution. The execution of the methodology was capable of solving a complex problem reducing the number of vehicles utilized, increasing the resource capacity utilization, and reducing the cost of operations of the fleet, meeting all constraints. These constraints included the window of operations and accomplishing the total number of deliveries. Furthermore, the methodology could accomplish the learning function using deep reinforcement learning in reasonable computational times. This preliminary analysis shows the potential benefits, especially in understudied metropolitan areas from emerging markets, supporting a more effective delivery process, and encouraging proactive, dynamic decision making during the execution stage.
... This issue is particularly important in supply chain and operations-related tasks, such as retail shelf audits. High-quality shelf-level inventory information can yield substantial benefits for companies by maximizing the effectiveness of retail operations and supplier performance, with subsequent impacts on customer experience and firm profits (Chuang et al. 2016, Raman et al. 2001. ...
For the execution of many supply chain operations tasks, firms are increasingly engaging in crowdsourcing – the act of dynamically delegating work via digital channels to for‐hire individuals intermittently available in the marketplace (also called “the crowd”). The success of this practice hinges on the ability to efficiently attract workers that produces quality work from among the crowd. We draw on the foundations of Self‐determination Theory and the Heuristic‐Systematic Model to examine the ways that variations in messages presented to crowdsourced agents can serve as a mechanism to enhance participation and associated performance outcomes. Data from a field experiment involving a retail inventory audit task reveal that messages appealing to the crowd’s consumer identity, as opposed to crowdsourcing platform identification or firm identification, generally lead to superior performance outcomes, particularly shorter reservation time, higher task quality approval, and post‐task satisfaction. However, these effects are contingent on the valence of the message frame and the nature of the task. These findings shed light on elements critical to the successful utilization of this new type of crowdsourced “employment” in supply chain and operation tasks and suggests the careful crafting of crowdsourced task messages as a low‐cost way for managers to improve task performance outcomes.
... Retail is about offering the right product in the right place at the right time at the right price [1]. However, in-store operations pose complicated issues related to backroom control, staff optimization, product assortment, and consumer response [2]. Due to their complicated nature, store run failures such as misreporting sales and incorrect product placement are common even in financially successful retailers [3]. ...
“On-Shelf Availability” (OSA) or “Out of Stock” (OOS) in a store is a key factor for customer satisfaction. Shelf availability is a critical issue for both manufacturers and retailers, fixing it improves consumer value, fosters consumer brand loyalty and shopper loyalty to the store, increases sales, and most importantly, increases the profitability of the category. Likewise, the logistics rationalization in the supply chain is a key factor for the profitability of the business. The present research establishes an OSA methodology that through the reception and replacement processes with Category Management (CATMAN) will increase profits and the level of customer satisfaction, also achieving a better inventory. From January to October 2019, the percentage of OSA was raised from 78.3% to 92.4%. This methodology can be applied to different supermarkets, adapting CATMAN to avoid OOS.
... Merchandise is regularly shifted around in retail stores, so the more hours that associates work, the more exposure they have to merchandise placement. Phantom stock-outs may be reduced simply because gaps between employees' shifts are reduced (Raman et al. 2001, Lee et al. 2021. ...
... Also, a study made by Raman et al. (2001) inaccurate inventory records has reduced profits by ten percent. Therefore, accuracy of the inventory records is vital for the performance of an inventory management system and necessary actions should be taken accordingly. ...
In today’s economy, efficient inventory management is vital for
all companies. Business environment, which is considered as volatile,
uncertain, complex, and ambiguous (VUCA), big savings can be achieved
with efficient inventory management. Effective implementation and
management of inventory management system is vital for a company’s
success. The success of such implementation not only affects the profit but
also customer satisfaction. The goal of this chapter is to summarize the challenges faced and propose a framework to overcome these challanges.
... Studies argue that it is no more just merchandising, which is important for successful retailing, what is becoming more and more important nowadays is other aspects of store operations which include various other aspects including inventory management [12]. the accuracy level of inventory available in the store is significantly poor and this was attributed to issues with inventory replenishment systems and inventory planning methodology [13]. Because of various data related issues including inventory accuracy levels, many fail to implement the automated replenishment system and strongly recommend that different replenishment tools must be applied with real-time inventory issues [14]. ...
The complex nature of brick-and-mortar lifestyle retailing both from supply-side and demand-side owing to a sheer vast number of unique designs, products, brands, and categories the retailer mandatorily need to offer in their stores as part of their product assortment, added with limitation in terms of opportunity available for the store to retain consumers for a longer period just because of increasing competition from both organized and unorganized lifestyle retailers, makes it furthermore important for any organized brick-and-mortar lifestyle retailer to be more careful and efficient in ensuring appropriate adaptation of emerging information communication and computation tools (ICCT). It is observed that a majority of lifestyle retailers in India believe that they have adopted the latest ICCT tools and solutions and are yielding accurate outputs that can be used for interpretation and decision-making. This belief/assumption always distracts them from evaluating the adaptation level of existing ICCT tools and solutions by their employees across levels in the hierarchy, rather they spend most of their time finding ICCT tools and solutions which are new in the market to be integrated with their existing systems. In these six months' long research work we have evaluated the existing adaptation level and understanding of ICCT of a select national level brick-and-mortar lifestyle retailer in India; identified key loopholes in ICCT adaptation; experimented to derive insights and inferences, and suggested appropriate adaptation methods for efficient usage of ICCT. Results have demonstrated that rather working on identifying new ICCT tools and solutions if the retailer just focuses on modifying the input methodologies of their existing ICCT tools and solution they would reduce overall expenses incurred by them in returning the inventory which is ordered using an ICCT by 74.31 percent and also save on their overall consumer communication expenses by 19.82 percent.
Problem definition: Inaccurate records of inventory occur frequently and, by some measures, cost retailers approximately 4% in annual sales. Detecting inventory inaccuracies manually is cost-prohibitive, and existing algorithmic solutions rely almost exclusively on learning from longitudinal data, which is insufficient in the dynamic environment induced by modern retail operations. Instead, we propose a solution based on cross-sectional data over stores and stock-keeping units (SKUs), viewing inventory inaccuracies as a problem of identifying anomalies in a (low-rank) Poisson matrix. State-of-the-art approaches to anomaly detection in low-rank matrices apparently fall short. Specifically, from a theoretical perspective, recovery guarantees for these approaches require that nonanomalous entries be observed with vanishingly small noise (which is not the case in our problem and, indeed, in many applications). Methodology/results: So motivated, we propose a conceptually simple entrywise approach to anomaly detection in low-rank Poisson matrices. Our approach accommodates a general class of probabilistic anomaly models. We show that the cost incurred by our algorithm approaches that of an optimal algorithm at a min-max optimal rate. Using synthetic data and real data from a consumer goods retailer, we show that our approach provides up to a 10× cost reduction over incumbent approaches to anomaly detection. Along the way, we build on recent work that seeks entrywise error guarantees for matrix completion, establishing such guarantees for subexponential matrices, a result of independent interest. Managerial implications: By utilizing cross-sectional data at scale, our novel approach provides a practical solution to the issue of inventory inaccuracies in retail operations. Our method is cost-effective and can help managers detect inventory inaccuracies quickly, leading to increased sales and improved customer satisfaction. In addition, the entrywise error guarantees that we establish are of interest to academics working on matrix-completion problems.
History: This paper was selected for Fast Track in M&SOM from the 2022 MSOM Supply Chain Management SIG Conference.
Funding: Financial support from the National Science Foundation Division of Civil, Mechanical, and Manufacturing Innovation [Grant CMMI 1727239] is gratefully acknowledged.
Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2023.0146 .
Efficiently managing retail space is critical as the increase in product variety is in conflict with limited shelf space and instore replenishment constraints. This paper develops a general framework for retail space management and presents a decision support model with the related problems within the framework of optimizing assortment, shelf space assignment and replenishment. An integrative approach to these planning problems becomes particularly relevant for fast-moving consumer goods and groceries, where stores are regularly replenished from distribution centers. The planning problem at hand is a multi-product shelf space allocation problem where demand is a composite function of the shelf space allocated and assortment-related demand substitution, and actual replenishment practices from retail are incorporated. The model developed extends existing models of shelf space management by jointly considering space-elastic demand and assortment-based substitution and integrating restocking constraints. For the latter, we consider real-world replenishment processes of retailers that distinguish between period-based and ad-hoc replenishment from the backroom. We develop three solution approaches that are based on efficient pre-processing and a nonlinear binary integer programming formulation of the problem. The computation tests based on retail data show the efficiency of the solution approaches in terms of computation time and solution quality. We reveal the improvement in profit levels that can be achieved from integrating assortments, shelf space planning and replenishment where challenges arise in obtaining feasible solutions with limited shelf space and replenishment constraints. We also use sensitivity analyses to demonstrate the high impact of replenishment constraints on profits and solution structures.
This chapter studies the emergence of blockchain technology as an effective tool for providing transparency in supply chains. We first discuss how supply chain applications of this technology differ from cryptocurrency networks, and identify why this technology is useful in supply chains. We then classify its applications into three types: improvement of process efficiency, supply chain optimization, and creation of new and innovative use cases. These three types of applications are differentiated by their ease of implementation and scope of benefits. For each type of application, we select recent successful examples and use both interviews with the companies and secondary publications to examine the value generation potential.KeywordsBlockchainSupply chain transparencySustainable operations
Studies on effective distribution practices specific to the paper industry are largely non-existent. Therefore, through our exploratory research, we first identify key elements of physical distribution in existing literature. Secondly, we empirically investigate the extent to which these elements influence non-cost-based (such as inventory turnover, order fulfillment etc.) measures of distribution performance in the paper industry. Using a sample of 95 National Paper Trade Association member firms, we create three performance groups (low, medium, and high). Then, we use analysis of variance (ANOVA) to test for any differences in the adoption of the physical distribution elements among these groups. Further, through partial least squares regression analysis, we attempt to identify those elements of physical distribution which may be most critical in explaining the differences in distribution performance. Our results provide general support for the importance of the key elements identified in this study.
Practitioners have long known that item-level tracking of products with the aid of radio frequency identification (RFID) has an exceptionally high potential for application with omnichannel fulfillment. Investments in both RFID and omnichannel expanded, but there was a lack of studies to assess their benefits. The introduction of omnichannel retailing is a big challenge for managers since it demands higher stocking levels due to the higher shrinkage cost. This research focuses on modeling one of the promising RFID applications: in-store merchandise tracking on item level. This model shows how a combination of consumers' response to stockout in omnichannel retailing coupled with item-level RFID tracking ensures inventory reduction, leading to higher on-shelf availability and lower cost. Thus, a modeling approach allows defining the value of the costly investment in the in-store location tracking in omnichannel fulfillment. A comparison is made between three scenarios: no-omnichannel and no-RFID; omnichannel without RFID; and omnichannel with RFID. In addition, this study examines under which parameters of costs, backlogging, brand and store switching, and other conditions one scenario could be more profitable for a retailer than another. The main finding of the study suggests the retailer's profitability could increase significantly as a result of the combined effect of investment in omnichannel fulfillment and item-level RFID. At the same time, the optimal inventory could be reduced. This study supports evidence of the higher return on investment in item-level RFID tracking of fashion products in omnichannel retailing.
Во фокусот на овој труд е управувањето со залихите кое директно влијаат наподобрување на ефикасноста и зголемување на ефективноста на компанијата. Менаџментот езаинтересиран за залихите и затоа ги планира и контролира. Поради тоа, потребен е ажурен системна нивна евиденција. Со вистинска стратегија и алатки за управување со залихите, се оптимизиранивото на залиха во магацинот. Порастот на вредноста на неконкурентни залихи е сигнал за лошоработење и потенцијална загуба. Менаџментот треба постојано да го анализира нивото на залихи,како на залихите кои се чуваат како предмети за работа, исто така и на залихите на готовитепроизводи и стоки, со цел да ги намали или избегне финансиските расходи од нивно непотребночување. Одржувањето на вистински потребното ниво на залихи, има големо влијание на успешностакај сите бизниси, независно од големината.
Purpose
The findings of this paper throw light on the focal research areas within RFID in the supply chain, which serves as an effective guideline for future research in this area. This research, therefore, contributes to filling the gap by carrying out an SLR of contemporary research studies in the area of RFID applications in supply chains. To date, SLR augmented with BA has not been used to study the developments in RFID applications in supply chains.
Design/methodology/approach
We analyze 556 articles from years 2001 to date using Systematic Literature Review (SLR). Contemporary bibliometric analysis (BA) tools are utilized. First, an exploratory analysis is carried, out revealing influential authors, sources, regions, among other key aspects. Second, a co-citation work analysis is utilized to understand the conceptual structure of the literature, followed by a dynamic co-citation network to reveal the evolution of the field. This is followed by a multivariate analysis is performed on top-100 cited papers, and k-means clustering is carried out to find optimal groups and identify research themes. The influential themes are then pointed out using factor analysis.
Findings
An exploratory analysis is carried out using BA tools to provide insights into factors such as influential authors, production countries, top-cited papers and frequent keywords. Visualization of bibliographical data using co-citation network analysis and keyword co-occurrence analysis assisted in understanding the groups (communities) of research themes. We employed k-means clustering and factor analysis methods to further develop these insights. A historiographical direct citation analysis also unveils potential research directions. We observe that RFID applications in the supply chain are likely to benefit from the Internet of Things and blockchain Technology along with the other machine learning and visualization approaches.
Originality/value
Although several researchers have researched RFID literature in relation to supply chains, these reviews are often conducted in the traditional manner where the author(s) select paper based on their area of expertise, interest and experience. Limitation of such reviews includes authors’ selection bias of studies to be included and limited or no use of advanced BA tools for analysis. This study fills this research gap by conducting an SLR of RFID in supply chains to identify important research trends in this field through the use of advanced BA tools.
Universal health coverage (UHC) is an integral part of the United Nations sustainable development goals. The private sector plays a prominent role in achieving UHC, being the primary source of essential medicines for many people. However, many private healthcare facilities in low‐ and middle‐income countries (LMICs) have insu_cient stocks of essential medicines. At the same time, these same facilities carry excessive quantities of certain drugs, leading to obsolescence. This suggests poor inventory control. To propose potential remedies it is vital to fully understand the underlying causes. In semi‐structured interviews with managers of private healthcare facilities in Nairobi, we asked them about their 1) inventory control systems, 2) inventory control skills, 3) time/human resource constraints, 4) budget constraints, 5) motivations for inventory control, and 6) suppliers. Our results suggest that the problems are driven by resource limitations (budget and time/human resources), managerial issues (relating to skills and systems), and market mechanisms that limit overage and underage costs. Unavailability at the supplier level and motivations for inventory control are relatively minor issues. We posit that the key causes are interlinked and stem from wider issues in the market and regulatory environment. Our results challenge prevalent beliefs about medicine supply chains in LMICs and lead to alternative hypotheses. Testing these hypotheses could improve our understanding of inventory management in private healthcare facilities and aid progress in achieving UHC.
Inventory record inaccuracy (IRI) is the mismatch between the quantity that is recorded in a company’s inventory management system and the quantity that is actually physically available.IRI can lead to significant issues in retail, e.g., by causing stockouts and revenue losses triggered by unnecessary replenishment.
This paper evaluates the effects of IRI on retail store inventory and sales manage-ment performance. We propose a novel network data envelopment analysis (NDEA)model, capable of setting store-level performance standards more accurately than state-of-the-art models. To support managers in identifying the root causes of IRI and in setting realistic target for mitigating IRI, the insights of the proposed NDEA model are used to develop two novel performance indicators: the IRI improvement potential and the IRI improvement workload.This research uses real-life data of an international fashion retailer. The data set contains in-formation of more than 5,250,000 inventory items kept in 81 retail stores. The computational experiments show the benefit of using relative measures to quantify IRI levels accurately across SKUs. Furthermore, decomposing store-level management into inventory management and sales management is found to be highly beneficial for evaluating the impact of IRI on store-level performance. Numerical results also demonstrate that IRI improvement is small for near-efficient stores and remarkably large for highly inefficient stores.
This paper presents a novel queueing model describing the operational process of a semi-attended self-checkout counter for retail stores. Specifically, we consider an M/M/(1+c) queueing system with two-phase heterogeneous service scheme, where the arrival of customers at the check-out system follows a Poisson process. After using the matrix-geometric method to analyze the queueing system in a steady state, important performance measures are developed. We evaluate a single-objective (i.e., cost minimization) problem based on the expected cost function per unit time, and then apply the canonical particle swarm optimization algorithm to solve it. A bi-objective optimization model used to minimize the expected cost and the expected waiting time of customers is also formulated. The proposed analytical approach makes it possible to achieve an appropriate balance between operational costs and service quality.
A “phantom stockout" is a retail stockout phenomenon caused by unobserved inventory shrinkage. Unlike conventional stockouts that can be corrected by inventory replenishment, a phantom stockout persists and requires human inspection. In this paper, we formulate such a problem as an infinite‐horizon Bayesian dynamic program with joint inventory inspection and replenishment decisions. This problem is challenging to solve due to non‐convexity and high dimensionality. However, we find that under the Bernoulli shrinkage process, the optimal inventory inspection policy has a simple threshold structure that depends on the number of consecutive zero‐sales periods since the last inspection, while the optimal inventory replenishment policy is the same as the optimal policy without inventory shrinkage. Our numerical studies further demonstrate that this simple and intuitive policy can be an effective heuristic for more general shrinkage processes.
Dirty data exist in many systems. Efficient and effective management of dirty data is in demand. Since data cleaning may result in useful data lost and new dirty data, this research attempts to manage dirty data without cleaning and retrieve query result according to the quality requirement of users. Since entity is the unit for understanding objects in the world and many dirty data are led by different descriptions of the same real-world entity, this chapter defines the entity data model to manage dirty data and then it proposes EntityManager, a dirty data management system with entity as the basic unit, keeping conflicts in data as uncertain attributes. Even though the query language is SQL, the query in the system has different semantics on dirty data. To process queries efficiently, this research proposes novel index, data operator implementation, and query optimization algorithms for the system.
Although small local retailers have been increasingly adopting e-channels, survey-based studies on this industry sector are relatively rare. This paper examines the effect of an IT resource on e-channel performance in small brick-and-click retailers. The research model includes both the direct and indirect effects of e-IT competence on e-channel performance. Empirical data gathered from 147 North American florists who use a website as an e-channel verify these mediation effects. The results show that the direct effect of e-IT competence on e-channel performance is significant in the absence of the mediators but is eliminated by introducing mediators, which demonstrates a true mediation mechanism. The findings of this research provide important implications for managing an e-retail system, particularly for small retailers with limited resources.
This case captures inventory management process in an Indian convenience store. Unlike retail stores in developed countries, Indian convenience stores are a special format of organized retailing, where retailers open multiple smaller stores in a town instead of one big centralised store. An excellent inventory management process is the key to make such stores perform well. This case describes inventory management problems faced by an Indian convenience store chain and asks students to propose solutions to these problems. This case illustrates how processes realities and their IT solutions differ in an emerging economy. Using inventory management process as an example, this teaching case can introduce students to the process and technological realities in an Indian context and differences between India and the West.
Problem definition: Brick-and-mortar (B&M) retailers must enhance the customer in-store experience to better compete with online retailers. Fitting rooms in B&M stores play a critical role in the customer experience as a venue to experience products and examine alternatives. High traffic in fitting rooms, however, obstructs the customer’s ability to choose a product. In this paper, we (1) examine the impact of fitting room traffic on store performance using archival data, (2) identify phantom stockouts as a plausible mechanism for this impact, and (3) provide a potential solution and quantify the magnitude of its impact using two field experiments. Academic/practical relevance: The consumer purchase decision process framework has been widely used in disciplines such as marketing and information systems. We consider the impact of high traffic in fitting rooms on customer’s purchase decision process. We show that high traffic in fitting rooms affects store sales negatively as it can obstruct customers’ ability to perform information search, evaluation of alternatives, or both. Methodology: We use archival data analysis, a field study, and a field experiment to demonstrate our findings. Results: We demonstrate an inverted-U relationship between fitting room traffic and sales using archival data analysis. Our field study reveals that high traffic in fitting rooms exacerbates phantom stockouts, which could contribute to the decline in sales. Finally, through field experiments at two retailers, we show that a timely backend recovery operation through a dedicated fitting room associate reduces phantom stockouts and increases sales by 22.4%–22.7%. Managerial implications: First, contrary to conventional wisdom that traffic drives sales, we identify that fitting room traffic beyond a certain point can hurt store sales. Second, we find a large magnitude of phantom stockouts in fitting rooms. Finally, we show that dedicated fitting room labor can significantly boost store sales by alleviating phantom stockouts. Our proposed solution was adopted by both retail organizations that we worked with.
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