Online Grocer Research Articles

Exercising Market Power Without Using Prices: Service Time in Online Grocery

This paper studies how online grocers use service time to respond to local competition and demand conditions when prices are uniformly set at the national level. Using comprehensive data collected twice a week over three years from 172 Israeli local markets, we show that an online grocer sets identical prices in all markets. By contrast, service time is shorter in more competitive markets and on low-demand days. Next, we exploit regional and temporal variation in entry decisions to examine how the incumbent adjusts its service time when new online grocers enter the market. The incumbent’s service time falls significantly on low-demand days and in monopolistic markets. This decrease begins shortly before entry and is greater when the entrant poses a larger competitive threat. On high-demand days and in competitive markets we do not find a significant change in service time in the months surrounding entry. Our findings suggest that firms use service time to exercise their local market power when prices are unresponsive and that operational considerations affect the extent to which they respond. This paper was accepted by Joshua Gans, business strategy. Funding: Financial support by Eli Hurvitz Institute of Strategic Management, The Henry Crown Institute of Business Research in Israel, The Maurice Falk Institute for Economic Research in Israel Ltd., Coller Foundation, and the Israeli Science Foundation [Grant 568/17] is gratefully acknowledged. Supplemental Material: The online appendices and data files are available at https://doi.org/10.1287/mnsc.2022.01820 .

Bi-Objective Job-Shop Scheduling Considering Human Fatigue in Cobotic Order Picking Systems: A Case of an Online Grocer

Increasing online retail has resulted in increased automation in order picking systems, leading to new challenges and opportunities in task scheduling. The job-shop scheduling problem is an optimization problem essential in such systems, but existing JSP literature often overlooks workplace fatigue, which harms employees’ well-being and costs U.S. employers up to €127 billion annually. In this work, we propose fatigue consideration in the job-shop scheduling problem in a cobotic order picking system to mitigate its negative effects. We present a new bi-objective mixed integer nonlinear programming problem formulation that considers worker fatigue and productivity during schedule optimisation. To put the results of simulated optimisation in perspective, we experimentally validate the fatigue model and scheduling results in a real operation. The mathematical model finds solutions that conventional single-objective optimisation cannot, allowing fractional fatigue distribution improvements more than 4x larger than the decrease in productivity they require in 53% of the considered virtual cases. The experiments show that our predictive fatigue model has an average RMSE of 2.20 kcal/min in estimating energy expenditure rates compared to heart rate measurements. It also shows a low correlation, meaning it is unfit for application. On the other hand, fatigue-conscious schedules show no clear benefit regarding measured and perceived fatigue. However, the scheduling model could also use heart rate measurements that do not show these inaccuracies. Our study highlights the need to further develop and validate the mathematical formulation and fatigue model and extend to other human factors and indirect fatigue effects.

Online food prices during the COVID-19 pandemic.

During the coronavirus disease‐2019 pandemic, online grocery shopping experienced a never seen popularity in many countries. To study how the globally active online grocer Amazon Fresh reacted to this extraordinary demand increase, we analyzed a large dataset of daily price quotes for over 19,000 products for the customer location, Los Angeles. We found that contrary to the US consumer food price index, the overall price level at Amazon Fresh did not increase during the pandemic, but even slightly decreased for several product groups. Amazon seems to follow its low‐price strategy also in the grocery sector, even in times of high demand. However, during the lockdown phase, there were more price increases for certain highly demanded product groups such as frozen and prepared foods. Moreover, fewer prices were communicated as promotional prices. Because this change did not influence the general price level, we conclude that such promotional prices are used more as a marketing tool than as a price‐setting instrument.

HUMANOID ROBOT IN UK WAREHOUSE TEST

Engineers at online grocer Ocado Technology have successfully trialled a humanoid robot able to help workers with maintenance tasks at its automated warehouse in Hatfield, Hertfordshire.

EBT Payment for Online Grocery Orders: a Mixed-Methods Study to Understand Its Uptake among SNAP Recipients and the Barriers to and Motivators for Its Use

ObjectiveTo examine Supplemental Nutrition Assistance Program (SNAP) recipients' use of the first online supermarket accepting Electronic Benefit Transfer (EBT) payment. MethodsIn this mixed-methods study, the authors collected EBT purchase data from an online grocer and attempted a randomized controlled trial in the South Bronx, New York City, followed by focus groups with SNAP beneficiaries aged ≥18 years. Participants were randomized to shop at their usual grocery store or an online supermarket for 3 months. Focus groups explored barriers and motivators to online EBT redemption. ResultsFew participants made online purchases, even when incentivized in the randomized controlled trial. Qualitative findings highlighted a lack of perceived control over the online food selection process as a key barrier to purchasing food online. Motivators included fast, free shipping and discounts. Conclusions and ImplicationsElectronic Benefit Transfer for online grocery purchases has the potential to increase food access among SNAP beneficiaries, but challenges exist to this new food buying option. Understanding online food shopping barriers and motivators is critical to the success of policies targeting the online expansion of SNAP benefits.

A capacitated vehicle routing problem with order available time in e-commerce industry

ABSTRACTIn this article, a variant of the well-known capacitated vehicle routing problem (CVRP) called the capacitated vehicle routing problem with order available time (CVRPOAT) is considered, which is observed in the operations of the current e-commerce industry. In this problem, the orders are not available for delivery at the beginning of the planning period. CVRPOAT takes all the assumptions of CVRP, except the order available time, which is determined by the precedent order picking and packing stage in the warehouse of the online grocer. The objective is to minimize the sum of vehicle completion times. An efficient tabu search algorithm is presented to tackle the problem. Moreover, a Lagrangian relaxation algorithm is developed to obtain the lower bounds of reasonably sized problems. Based on the test instances derived from benchmark data, the proposed tabu search algorithm is compared with a published related genetic algorithm, as well as the derived lower bounds. Also, the tabu search algorithm is compared with the current operation strategy of the online grocer. Computational results indicate that the gap between the lower bounds and the results of the tabu search algorithm is small and the tabu search algorithm is superior to the genetic algorithm. Moreover, the CVRPOAT formulation together with the tabu search algorithm performs much better than the current operation strategy of the online grocer.

Architecting MexGro: introducing online experience for shopping ethnic products

Subject area Marketing plan; virtual shopping; consumer behavior. Study level/applicability Undergraduate. Case overview This case discusses the e-commerce plan of new online grocery company in Mexico, MexGro, which is planning to emerge as low-cost outlet as compared to the brick-and-mortar establishments in the market. MexGro is an online grocer with a round-the-clock call center to process phone-based orders and to provide customer support. The grocery online company is aimed at setting up a virtual grocery shop by the name of MexGro S.A de C.V to serve cross-cultural products to the Hispanic and Asian communities in Mexico. The MexGro, being a virtual shop, need not pay for checkout clerks; display cases, or parking lots, online grocers can drop prices below those of retail stores and remain profitable. This case explores online consumer-shopping behavior, the economics of online and offline grocery distribution, and the challenges of uniting a pure information business with a mundane package delivery service. Expected learning outcomes This case may be discussed towards learning developing effective online marketing planning strategy for the niche markets. The specific learning objectives of the case are: to analyze the virtual marketing planning constituents for developing customer-centric marketing within a niche and explore the possibilities of sustainable business growth to encourage strategic thinking towards developing online marketing plan and develop effective communications among the consumers and to address the critical online planning issues, such as what are the prospects for grocery shopping on the internet. The case allows students to grapple with the strategic and tactical decisions on planning for the online marketing companies. Students will also become familiar with key questions/issues raised by the various executives of the company in formulating the online marketing plan for ethnic grocery in a niche business environment: the case challenges students to think about how online grocer creates the most value for customers and how grocer will likely be able to overcome the competition from the brick-and-mortar grocers. Should Wal-Mart be aggressive in launching its grocery brand? The case raises issues to debate on how the organizational and system decisions are faced by managers in developing a virtual shopping culture in Mexico as the company has the goal to move among more efficient competitors in the supermarket industry, and How the online marketing plan can be implemented within a niche. This case study would take students through the rise of a private brand to the strategies of its sustainability in the competitive marketplace. This case illustrates the importance of using new variables in developing an effective marketing plan when companies reinforce their products in the niche markets. The discussion in the case allows students an opportunity to evaluate online marketing planning and their brands in a niche as well as in a competitive marketplace. Supplementary materials Teaching notes are available for educators only. Please contact your library to gain login details or email support@emeraldinsight.com to request teaching notes.

Tariff Choice with Consumer Learning and Switching Costs

Consumers choosing flat-rate contracts tend to have insufficient usage to warrant the cost, particularly for new products. We propose and estimate a Bayesian learning model of tariff and usage choice that explains this flat-rate bias without relying on behavioral misjudgments or tariff-specific preferences. For new products, consumers are uncertain about both their utility relative to the population mean and the mean itself. We show that this latter uncertainty inflates prior variances, which leads consumers to weight their private signals more heavily when updating beliefs. Posteriors are unbiased across products. For a given product, however, the unknown mean yields a “winner's curse”: Consumers with high posteriors tend to overestimate their utility. These consumers choose fixed-rate tariffs and lower their usage as they correct their beliefs. The flat-rate bias arises when switching costs deter them from changing tariffs. Using the estimated model, the authors find that tariff menus are ineffective screening devices for price discrimination by an online grocer. Predicted revenues increase by 20% when the per-use tariff is dropped, because more consumers choose and stay with the flat rate.

Stockouts in Online Retailing

Demand uncertainty and supply rigidity often create inventory shortages. Inventory shortages can have adverse consequences on both short- and long-term customer behaviors. Using data from an online grocer, this study has the following three main objectives: First, the authors empirically investigate the true nature of shortage costs by examining how stockouts and fulfillment rates affect customer's purchase behavior in both the short and long run. Second, the authors study how consumers’ reactions to inventory shortages differ across customer segments. They use these observations to illustrate how the seller might benefit from prioritizing fulfillment policies according to customer traits. Third, the authors study how the impact of inventory shortages varies across product categories. Using these insights, the authors discuss how the seller should allocate limited resources to improve order fulfillment across these categories. Overall, the authors find that stockout rates have a dramatic but nonlinear impact on the seller's profitability. This suggests that the firm can achieve many of the benefits of improving fulfillment rates through small decreases in stockout rates. They also find significant differences in how different types of customers respond to stockouts and that prioritizing inventory according to transaction history measures and basket contents can lead to large increases in contribution while only requiring moderate reductions in stockout rates.

Tariff Choice with Consumer Learning and Switching Costs

Consumers choosing contracts tend to have insufficient usage to warrant the cost, particularly for new products. We propose and estimate a Bayesian learning model of tariff and usage choice that explains this flat-rate bias'' without relying on behavioral misjudgments or tariff-specific preferences. For new products, consumers are uncertain about both their utility relative to the population mean and the mean itself. This latter uncertainty inflates prior variances, which leads consumers to weight their private signals more heavily when updating beliefs. Posteriors are unbiased across products. For a given product, however, the unknown mean yields a winner's curse'': consumers with high posteriors tend to overestimate their utility. These consumers choose fixed-rate tariffs and lower their usage as they correct their beliefs. The bias arises when switching costs deter them from changing tariffs. Using the estimated model, we find tariff menus are ineffective screening devices for price discrimination by an online grocer. Predicted revenues increase by 20 percent when the per-use tariff is dropped, since more consumers choose and stay with the flat rate.

I’ll have the ice cream soon and the vegetables later: A study of online grocery purchases and order lead time

How do decisions made for tomorrow or 2 days in the future differ from decisions made for several days in the future? We use data from an online grocer to address this question. In general, we find that as the delay between order completion and delivery increases, grocery customers spend less, order a higher percentage of “should” items (e.g., vegetables), and order a lower percentage of “want” items (e.g., ice cream), controlling for customer fixed effects. These field results replicate previous laboratory findings and are consistent with theories suggesting that people’s should selves exert more influence over their choices the further in the future outcomes will be experienced. However, orders placed for delivery tomorrow versus 2 days in the future do not show this want/should pattern, and we discuss a potential explanation.

Dynamic pricing of multiple home delivery options

Abstract Online grocers accept delivery bookings and have to deliver groceries to consumers’ residences. Grocery stores operate on very thin margins. Therefore, a critical question that an online grocery store needs to address is the cost of home delivery operations. In this paper, we develop a Markov decision process-based pricing model that recognizes the need to balance utilization of delivery capacity by the grocer and the need to have the goods delivered at the most convenient time for the customer. The model dynamically adjusts delivery prices as customers arrive and make choices. The optimal prices have the following properties. First, the optimal prices are such that the online grocer gains the same expected payoff in the remaining booking horizon, regardless of the delivery option independently chosen by a consumer. Second, with unit order sizes, delivery prices can increase due to dynamic substitution effects as there is less time left in the booking horizon.

Mental accounting and small windfalls: Evidence from an online grocer

We study the effect of small windfalls on consumer spending decisions by comparing the purchases online grocery customers make when redeeming $10-off coupons with the purchases they make without coupons. Controlling for customer fixed effects and other variables, we find that grocery spending increases by $1.59 when a $10-off coupon is redeemed. The extra spending associated with coupon redemption is focused on groceries that a customer does not typically buy. These results are consistent with the theory of mental accounting but are not consistent with the standard permanent income or lifecycle theory of consumption. While the hypotheses we test are motivated by mental accounting, we also discuss some alternative psychological explanations for our findings.

Can In-Store Displays Improve Category Sales and Brand Market Share in Online Stores? A Study on the Overall Effectiveness and Differences between Display Types in an Online FMCG Context

Our study investigates the overall effects of in-store displays (ISD) on category sales and brand market share in an online shopping context, and compares the differences in effectiveness between ISD types. Using data from an online grocer, we examine three online ISD types that match with traditional ones: first screen (entrance), banner (end-of-aisle) and shelf tag (in-aisle) displays. Empirical results for 10 categories confirm that online ISD may substantially increase brand market share and to a lesser extent, category sales. Our results also demonstrate that not all types are equally effective. First screen displays clearly have the strongest effect on market share: they benefit from their placement on the 'entrance' location, central on-screen position and direct purchase link. While they only feature 1 SKU, banner displays typically feature all SKUs of a brand, yet, are placed on border-screen positions on traveling-zone pages without a direct purchase link. Based on our results, the advantage of banner displays does not weigh up against the advantages of first screen displays in most cases. Shelf tags, finally, may be very useful in attracting attention to interesting promotions, but appear to have no or at most a limited effect on their own.

Mental Accounting and Small Windfalls: Evidence from an Online Grocer

We study the effect of small windfalls on consumer spending decisions by comparing the purchases online grocery customers make when redeeming $10-off coupons with the purchases they make without coupons. Controlling for customer fixed effects and other variables, we find that grocery spending increases by $1.59 when a $10-off coupon is redeemed. The extra spending associated with coupon redemption is focused on groceries that a customer does not typically buy. These results are consistent with the theory of mental accounting but are not consistent with the standard permanent income or lifecycle theory of consumption. While the hypotheses we test are motivated by mental accounting, we also discuss some alternative psychological explanations for our findings.

I'll Have the Ice Cream Soon and the Vegetables Later: A Study of Online Grocery Purchases and Order Lead Time

How do decisions made for tomorrow or two days in the future differ from decisions made for several days in the future? We use data from an online grocer to address this question. In general, we find that as the delay between order completion and delivery increases, grocery customers spend less, order a higher percentage of items (e.g., vegetables), and order a lower percentage of want items (e.g., ice cream), controlling for customer fixed effects. These findings are all consistent with theories suggesting that people's should selves exert more influence over their choices the further in the future outcomes will be experienced. However, orders placed for delivery tomorrow versus two days in the future do not show this want/should pattern, and we discuss a potential explanation.

The Perishability of Online Grocers*

ABSTRACTIn this article we explore the profitability of different operations models used by online grocers and develop a linear demand model in a competitive setting to better understand the trade‐offs made by two competing online grocers in choices for distribution strategy (leverage or direct) and product focus (perishable or nonperishable). We find that the results derived in the duopoly setting are different from those in a monopolistic setting. Specifically, we determine that there is a threshold value for the secondary competitive effects in the demand function that determines how the prices and profitability of an online grocer will be affected by the supply chain length of its competitor. There is also a threshold value for the ratio of supply chain lengths of the two competitors that determines whether product perishability increases or decreases profits. We demonstrate that the existence of this threshold is robust when considering capacity constraints. Further, we show, assuming that supply chain length can be optimized, how the relative size of the infrastructure change cost (when compared with that of the competitor) coupled with the perishability of the product determines the profitability of an investment leading to a shorter supply chain.

Customer Acquisition Promotions and Customer Asset Value

In this article, the author addresses the question of how a firm's acquisition efforts influence the composition of the customer portfolio. The first part of the research is a conceptual model that illustrates how customer uncertainty provides an explanation for why promotionally acquired customers have lower repurchase rates and smaller lifetime values. The second part of the research involves empirical analyses of customer-level data from a newspaper and an online grocer. In both data sets, acquisition discount depth is negatively related to repeat-buying rates and customer asset value. For example, a 35% acquisition discount results in customers with about one-half the long-term value of non-promotionally acquired customers.

The effect of shipping fees on customer acquisition, customer retention, and purchase quantities

The growth of the e-commerce sector has highlighted the importance of shipping fees. We empirically study the effects of shipping fees and marketing activities on customer acquisition, customer retention, and average expenditures using data from an online grocer. We find that shipping fees greatly influence order incidence rates and graduated shipping fees significantly affect average expenditures. The analysis indicates that customer acquisition is more sensitive to order size incentives while retention is more influenced by base shipping fee levels. Furthermore, a profitability analysis suggests that shipping policies that provide incentives for larger order sizes may outperform free shipping promotions and standard increasing fees structures.

The Effect of Product Assortment Changes on Customer Retention

This research investigates the impact of a large-scale assortment reduction on customer retention, utilizing a model we develop to explore the effect on sales at both the store level and the category level simultaneously. We apply our model to a data set provided by an online grocer. The data contain detailed household purchase records for every category in the store. Our results indicate that the reduction in assortment reduces overall store sales, a result that contrasts with that of all of the recent studies on assortment reductions (Food Marketing Institute. 1993. Variety or duplication: A process to know where you stand. Prepared by Willard Bishop Consulting and Information resources, Inc., in cooperation with Frito Lay; Drèze, Xavier, Stephen J. Hoch, Mary E. Purk. 1994. Shelf management and space elasticity. J. Retailing 70(4) 301–326; Broniarczyk, Susan M., Wayne D. Hoyer, Leigh McAlister. 1998. Consumers' perceptions of the assortment offered in a grocery category: The impact of item reduction. J. Marketing Res. 35(May) 166–176; Boatwright, Peter, Joseph C. Nunes. 2001. Reducing assortment: An attribute-based approach. J. Marketing 65(July) 50–63; Boatwright, Peter, Joseph C. Nunes. 2004. Correction note for “Reducing assortment: An attribute-based approach.” J. Marketing. Forthcoming). We find the reduction had a negative effect on both shopping frequency and purchase quantity, and we find that the decline in shopping frequency resulted in a greater loss than did the reduction in purchase quantities. We also find that the impact of the assortment cut varies widely by category, with less-frequently purchased categories more adversely affected. The variation in the assortment reduction's impact across categories suggests that managers compare select categories in order to moderate the overall loss in sales.