E‐fulfillment: the strategy and operational requirements

URBAN T.L.

The purpose of this paper is to model and analyze supply contracts with periodical commitment, in which the order quantities are fixed and stationary, with limited flexibility to change the order quantity at a cost to the buyer. A solution methodology is provided for the general, stochastic problem, and consideration is given to specific demand distributions. The deterministic model is also investigated, formulating the problem as a mixed-integer linear program and as a network flow problem. Computational analyses are conducted, and the extension of the basic problem to the multiple-product, multiple-constraint problem is discussed.

Cachon G.P.

This paper studies supply chain demand variability in a model with one supplier and Nretailers that face stochastic demand. Retailers implement scheduled ordering policies: Orders occur at fixed intervals and are equal to some multiple of a fixed batch size. A method is presented that exactly evaluates costs. Previous research demonstrates that the supplier's demand variance declines as the retailers' order intervals are balanced, i.e., the same number of retailers order each period. This research shows that the supplier's demand variance will (generally) decline as the retailers' order interval is lengthened or as their batch size is increased. Lower supplier demand variance can certainly lead to lower inventory at the supplier. This paper finds that reducing supplier demand variance with scheduled ordering policies can also lower total supply chain costs.

Dowlatshahi S.

Reverse logistics, a fairly new concept in logistics, has gained increasing importance as a profitable and sustainable business strategy. I describe a holistic view of reverse logistics and distill 11 insights for successful implementation of reverse logistics from the existing literature and published case studies. The strategic factors consist of strategic costs, overall quality, customer service, environmental concerns, and legislative concerns. The operational factors consist of cost-benefit analysis, transportation, warehousing, supply management, remanufacturing and recycling, and packaging. Insights about these factors together form the state-of-the-art knowledge about the keys to successful design and use of reverse-logistics systems.

Thompson D.E.

Like all companies in the pharmaceutical industry, Eli Lilly and Company knows it needs to grow revenues, profits and shareholder value through constant innovation. When the internal R&D engine will not generate enough to meet growth demands, many industry participants pursue external sources. What we believe makes Lilly different from most of its peers is that it has pursued a collaborative strategy of innovation leverage over headline-grabbing merger and acquisition approaches. With the right critical mass internally, Lilly aims to build truly win-win relationships with other leaders and maintain a reputation of Partner of Choice. The Situation To better understand why this path makes the most sense to Lilly, let's begin with the situation that faces all pharmaceutical companies today. The drug discovery business is one of high risk. Less than 1 percent of drug discovery efforts will result in a commercial product. Those that succeed will take 10 to 15 years to reach the market, with an average invested cost of nearly $0.5 billion. Complicate this equation with the fact that only three of ten products produce a profit and you can see why shareholders expect a high return for this level of risk. Investors demand total shareholder returns on the order of 18-20 percent annually. The Complication The trouble with the products that pharmaceutical companies launch is that they have a limited patent life. Once the patent life expires, the company's return from that product plummets. If the product was a blockbuster, the impact can be enormous. For instance, when Prozac's patent expired, Lilly could expect to eventually lose this $2 billion investment--and as much as $1.6 billion in one year. The company must replace that income and build the business to maintain growth expectations. A further complication is the increasing competition in the pharmaceutical marketplace. In years past, a similar me-too drug launched following a competitive product could expect to produce sufficient return to warrant R&D investment. Today, the fast-moving market places much higher hurdles, which drives pharmaceutical companies to seek more innovative products. Innovation is the key to producing differentiated products and delivering expected shareholder returns. More and better means more shots on goal. As a result, pharmaceutical companies have a voracious appetite for innovation. So what happens when the pharmaceutical company realizes that its internal R&D engine cannot produce in sufficient quantity, quality and diversity to meet the needs of its growth plan? This is the industry's most critical problem, and the basis for this article's discussion. Expansion through Acquisition The merger and acquisition option has been the solution of choice for much of the industry's recent history, especially during the 1990s and up until today. The choice was, in part, based on the presumption that is scalable. That is, it assumes, first, that means more and better chances to develop the right molecules and technology, and second, that the bigger a company is, the more it can develop--almost in one-to-one increments that could be graphed as a simple, ascending straight line. After ten years, it now seems clear that for the most part this strategy did not work--or at least it did not get, and still is not getting--the results expected. Merged companies have generally enjoyed slower sales growth than non-merged companies. Companies that never merged, experienced sales increases of 15 to 20 percent between the middle and end of the 1990s. Merged companies in that period experienced sales increases between 2 and 12 percent. Most important, merged companies typically experience a decrease in innovation--not an increase. For instance, a study of 22 merged companies by the Boston, Massachusetts information services company Centerwatch shows a 25-percent reduction in products in the pipeline one year after a merger--and one-third fewer in the pipeline three years out--even with new innovations added to the pipeline since the merger. …

Jaber M.Y., Bonney M.

Learning curves are a means of representing continuous improvement in firms. Such improvements bring savings in production costs. This may also allow smaller batches to be produced more frequently and hence bring further savings in holding costs. Earlier research advocated that for more realistic modelling of inventory problems, the holding cost should be evaluated means of the internal discount rate of the firm (C. Van Deft, J.P. Vail, International Journal of Production Economics 44 (1996) 255–265). This paper examines whether, when learning is considered, it is reasonable to ignore the effect of continuous time discounting of costs by investigating the effect of learning and time discounting both on the economic manufacturing quantity and minimum total inventory cost. Numerical examples are provided to illustrate the solution procedure for the mathematical model developed. Although the analysis yields different economic order quantities, the difference in cost from the quantities derived using Wilson lot size formula is not significant.

Bell DeTienne K., Jackson L.A.

Knowledge management has become the latest strategy in increasing organizational competitiveness. Proponents are calling it the only solution for competitive advantage in the new century (Evans, 1997; Hedlund, 1994; Hibbard, 1997; Martinez, 1998; Trussler, 1998) and critics are calling it the worst in passing fads (Hibbard, 1997). Robert H. Buckman, CEO of Buckman Labs, says the purpose of the knowledge management and sharing system at his corporation is to “facilitate communication across all of the organization's boundaries, so that the entire company works together to help everyone to be the best they can be” (Buckman, 1998, p. 11). Buckman Labs has become the first name in knowledge management with its innovative and relatively long‐standing (since 1991) approach to harnessing employees' collective knowledge.

Helms M.M., Ettkin L.P., Chapman S.

Supply chain management is built on the principles of partnerships and the development and use of the connections that exist between the links of the chain to provide information that will increase the efficiency of all members in the chain. Success stories abound describing lower costs, shorter lead times and increased customer service. Collaborative forecasting applies supply chain management concepts to the forecasting function and uses available information and technology to force a shift from independent, forecasted demand to dependent, known demand. Eventually, the future of forecasting may evolve to the point where forecasting is not even necessary. Demand information will be supplied completely by supply chain partners and the need to predict demand will be eliminated.

Chang H., Dye C.

Wang T., Chen R.

AbstractThe communication style between seller and consumer is an important component of post‐purchase communication, yet little research has examined the role of nonverbal language in online post‐purchase communication. Given the prevalence of emojis, which convey a sender's emotion, in both social and business communication online, this article aims to examine how the use of animated emojis in online post‐purchase communication differs from the use of static emojis. Through three laboratory experiments, this research shows that consumers' attitudes are more positive when they communicate with sellers who use animated emojis than with sellers who use static emojis in online post‐purchase communications (Studies 1 and 2). We also demonstrate that sellers' use of animated emojis, rather than static emojis, increases consumers' perceived emotional support, which subsequently boosts consumers' positive attitudes (Study 2). Notably, when consumers discuss embarrassing products in online post‐purchase communications, sellers' use of static emojis is more effective than that of animated emojis (Study 3). These findings therefore provide insights into why and when consumers prefer animated emojis and how sellers can use them appropriately in online post‐purchase communications.

Fithriyah M.

Connectivity is the basis of e-commerce development. E-commerce reinforces connectivity and aims to promote a continuous stream of information, logistics, free cash flow, and so forth. A seamless connection between the virtual and physical parts of an e-commerce network could be demonstrated in Cross-Border Ecommerce (CBE). A region-wide e-commerce support environment with a Regional Comprehensive Economic Partnership (RCEP) agreement would undoubtedly support economic stabilization. Notably, this model is positively in line with the restricted conditions during the COVID-19 outbreak (Anshari et al., 2021a). However, business actors should improve connectivity-derived services via technology and the internet in order to add more value to the successful implementation of CBE. Considering today's consumers are more complex, the COVID-19 economic turbulence has resulted in a severe bankruptcy storm for business areas worldwide (Hamdan et al., 2020). Hence, the study aims to identify the potential and opportunities of CBE, which will be explained in detail in this study. The determinants of the successful adoption of CBE remain complex. Therefore, our framework allows us to assess the extent of concerns about CBE opportunities and the potential for accelerating economic recovery during the pandemic COVID-19. In addition, CBE requires new regulations, and Asian nations must actively take part in rule-setting in order to achieve economic benefits. CBE can also provide new opportunities for local businesses where it can reach beyond their borders.

Weaver Z., Bharadwaj R.

Bin location is the smallest possible unit inside a fulfillment center building where a product is stored to pick customer orders. Inventory in each bin inside a modern fulfillment center is tracked by the warehouse management system. Inventory discrepancies between inventory records in the warehouse management system and on hand inventory in the bin are referred to as bin defects. Bin defects in e-commerce fulfillment centers pose significant challenges, impacting operational efficiency, customer satisfaction, legal compliance, and overall profitability. This paper presents a comprehensive predictive model leveraging machine learning techniques to anticipate bin defects within fulfillment centers. The study involves the analysis of historical data primarily encompassing item attributes, location attributes, and any actions that might change the current state of a bin. The proposed model in this paper has been trained, tested, and implemented in an enterprise environment, and it can be easily leveraged by any e-commerce fulfillment centers to optimize their inventory control strategies. Promising predictive capabilities demonstrated by the model substantiate the model’s effectiveness in preemptively identifying defective bins that can severely impact order fulfillment process. A successful integration of this model into organization’s broader inventory management strategy will enable fulfillment centers to proactively implement preventive measures, reducing the occurrence of defects, minimizing inventory losses, reducing labor costs, and optimizing operational workflows. Further implications of this research extend to streamlining quality control processes and fostering a proactive approach toward mitigating inventory defects in fulfillment centers.

Uvet H., Dickens J., Anderson J., Glassburner A., Boone C.A.

PurposeThis research paper aims to examine two hybrid models of logistics service quality (LSQ) and its influence on satisfaction, loyalty and future purchase intention in a business-to-consumer (B2C) e-commerce context. This study extends the literature for LSQ by incorporating the second-order assurance quality construct, which comprises personnel contact quality, order discrepancy handling and order returns, into one of the hybrid models.Design/methodology/approachA survey-based approach is used to collect data. Participant responses to questions concerning multiple LSQ dimensions and behavioral perceptions from their most recent online shopping experience are measured using structural equation modeling.FindingsFindings highlight the importance of including a second-order construct assurance quality as a more explanatory model. Results illustrate that online ordering procedures and assurance quality impact customer satisfaction more than other prominent LSQ dimensions. Furthermore, the findings revealed a customer loyalty is a partial mediator between customer satisfaction and future purchase intention. This underscores the significance of improved logistics services as a competitive edge for e-commerce retailers.Research limitations/implicationsImplications are limited to the e-commerce B2C domain.Practical implicationsThe findings of this study underscore critical LSQ dimensions that garner greater satisfaction and retention in the online shopping experience. The results indicate that the effective and efficient handling of the initial order and any order problem significantly influences customer satisfaction and reaps the long-term benefits of customer retention.Originality/valueThe authors present and empirically test a hybrid model of LSQ in a B2C e-commerce domain that captures many of the important elements of the customer experience as espoused in the literature.

Do A.D., Ta V.L., Bui P.T., Do N.T., Dong Q.T., Lam H.T.

With the boom in e-commerce activities in Vietnam, the market size is expected to reach USD 52 billion by 2025, showing that e-commerce is a highly potential market. This also means that the level of competition between businesses is extremely fierce, so it requires optimization in each activity, especially e-logistics, to ensure smoothness, accuracy, and safety in distributing goods to consumers. Therefore, this study focuses on determining which factors of e-logistics activities affect the satisfaction and loyalty of Generation Z customers and their influence. The team collected opinions from 510 customers who had purchased goods through an e-commerce platform and then analyzed them using Smart-PLS3. The results show that delivery time is the most critical factor determining customer satisfaction, while the availability of goods is the factor that contributes the most to the loyalty of Generation Z customers. In the context of e-commerce development in Vietnam, the research has contributed to business enterprises’ scale of e-logistics service quality and assessed the importance of each factor so that enterprises can base on that to evaluate their service quality and improve satisfaction, loyalty to customers, and competitiveness.

Goedhart J., Haijema R., Akkerman R.

• The replenishment and rationing decision of an omnichannel retailer is modelled. • Product returns significantly affect profit and the inventory and rationing decisions. • Opposed to existing models, we model demand-dependent returns over multiple periods. • A Markov decision process is solved exactly and by deep reinforcement learning (DRL). • DRL is slower in solving small instances but scales well and performs nearly optimal. More brick-and-mortar retailers open an online channel to increase sales. Often, they use the store to fulfil online orders and to receive returned products. The uncertain product returns however complicate the replenishment decision of a retailer. The inventory also has to be rationed over the offline and online sales channels. We therefore integrate the rationing and ordering decisions of an omni-channel retailer in a Markov Decision Process (MDP) that maximises the retailer’s profit. Contrary to previous studies, we explicitly model multi-period sales-dependent returns, which is more realistic and leads to higher profit and service levels. With Value Iteration (VI) an exact solution can only be computed for relatively small-scale instances. For solving large-scale instances, we constructed a Deep Reinforcement Learning (DRL) algorithm. The different methods are compared in an extensive numerical study of small-scale instances to gain insights. The results show that the running time of VI increases exponentially in the problem size, while the running time of DRL is high but scales well. DRL has a low optimality gap but the performance drops when there is a higher level of uncertainty or if the profit trade-off between different actions is minimal. Our approach of modelling multi-period sales-dependent product returns outperforms other methods. Furthermore, based on large-scale instances, we find that increasing online returns lowers the profit and the service level in the offline channel. However, longer return windows do not influence the retailer’s profit.

Gao D., Wang N., He Z., Zhou L.

Titiyal R., Bhattacharya S., Thakkar J.J., Sah B.

Purpose There is limited literature linking e-fulfillment and product type with postpurchase consumer behavior measures like loyalty, even though there has been a rapid increase in e-tailing. E-fulfillment is defined in literature as a sequence of processes. Each process in this sequence is expected to have a different impact on consumer loyalty across product type. Thus relative importance of e-fulfillment processes leading to consumer loyalty. The purpose of this study is to investigate the impact of e-fulfillment on consumer loyalty across two product types: “standard, regular” and “physical product” (e.g. book, clothing, etc.) and “standard, nonregular” and “physical product” (e.g. computer, refrigerator, etc.) using the peak-end rule theory for an e-tailer. Design/methodology/approach To know the consumer loyalty for e-fulfillment across the two product types, the partial least square-structural equation modeling approach aided by the SmartPLS 3 tool was used for data analysis as it avoids biases in the parameter estimation in regression analysis. A total of 603 consumer responses through an online and physically administered questionnaire were obtained and were used for the empirical analysis. Findings Results indicate that for standard, nonregular and physical products, all the e-fulfillment components (customization strategy, website quality, distribution strategy, last mile delivery and return management) positively impact consumer loyalty. Except for the customization strategy, for standard regular and physical product types, all other e-fulfillment components positively impact consumer loyalty. Practical implications This study will be helpful to e-tail managers to configure the e-fulfillment components according to product types, thereby increasing consumer loyalty. Originality/value While some e-fulfillment components have been linked to consumer loyalty in literature, there is no study establishing linkages between e-fulfillment as a construct and consumer loyalty across product types. This has implications for decision makers in e-tail as the study provides e-fulfillment strategy customization across product types for achieving consumer loyalty in e-tail, a key marketing metric.

Kim S., Connerton T.P., Park C.

• The study suggests extended UTAUT-TTF as a novel framework for omnichannel behavior. • BOPS might be a channel strategy that the traditional sector such as auto retail can consider. • Performance/Effort expectancy and Facilitating conditions predict technology adoption. • An individual's innovativeness may significantly affect technology acceptance and usage. • Task-technology fit serves a pivotal role in predicting usage intention of new technology. This study aims to identify the drivers in BOPS (Buy Online & Pick up in Store) usage intention of omnichannel consumers in the automotive retail sector. The study proposes a conceptual framework, extended UTAUT-TTF, synthesizing various theoretical perspectives and revealing the mechanism behind consumer behavior. The research surveyed 436 potential customers in South Korea, incorporating a factorial survey method. The findings suggest that Performance expectancy, Effort expectancy, and Facilitating conditions have a mediation effect through Task-technology fit affecting Usage intention. The results also support the influences of decisive factors in predicting the consumers' preferences to use BOPS. Social influence, however, did not present a significant effect on Usage intention. Personal innovativeness, selected for the extension of UTAUT, was the strongest predictor for the customer's BOPS usage intention. The research contributes to future technology acceptance literature, proposing that UTAUT-TTF can serve an essential role in predicting consumer behavior.

Titiyal R., Bhattacharya S., Thakkar J.J.

Purpose This paper aims to review the literature on “E-fulfillment” with respect to marketing and operations issues in the current dynamic and complex e-tailing environment and thereby generate significant insights. Design/methodology/approach This paper is based on a systematic literature review on e-fulfillment focusing on marketing and operations issues therein. This systematic literature review consists of a critical review on e-fulfillment under planning (review question initialisation), searching (literature search), screening (literature evaluation), extraction and synthesis and reporting phases to conceptualise e-fulfillment. A total of 122 research articles have been reviewed to explore e-fulfillment and to develop key constructs and propositions. Findings This review provides the following three outcomes. First, the varied-fulfillment definitions have been critically reviewed, leading to synthesis, and thereby, an e-fulfillment definition is provided. Further, the variations for e-fulfillment across product types, which have been identified as a key variable for e-fulfillment, have been explored. Second, authors find five e-fulfillment components at the marketing and operations interface: website quality, customisation strategy, distribution strategy, last mile delivery and return management. Continuing with the e-fulfillment interface with marketing, the linkages between e-fulfillment and select post-purchase consumer behaviours measures across different product types have been reviewed. The paper thus with a focus on synthesising e-fulfillment literature from a process perspective emphasises the consumer behaviour metric for measuring e-fulfillment performance. Practical implications This study would help academicians, researchers, e-tailers and practitioners to understand e-fulfillment from a process perspective. For the researcher, it presents areas for future research by giving possible research directions in this emerging area. This study also brings out the impact of e-fulfillment according to product type on the post-purchase consumer behaviour measures, which will help e-tailers to link e-fulfillment to consumer behaviour metrics. Originality/value The paper classifies the fragmented literature to develop constructs and propositions for e-fulfillment. This is the first kind of study on e-fulfillment process and its impact on select post-purchase consumer behaviour measures across product types.

Ahmed M.A., Sagid N.M.

Abstract This research deals with the role of shopping patterns in increasing customer loyalty. An application study and customer satisfaction in the service provided to him through electronic shopping and the aim of this research is to identify the dimensions of electronic service quality and confidence in selling via Internet sites, and the researcher used the method of descriptive analysis, which was based on a component sample From 50 items from Members of a community who are interested in electronic marketing and use simple regression to analyze the data, the study showed the indirect relationship between shopping patterns and customer loyalty. The study found a significant effect of shopping patterns and their dimensions. The study recommended identifying the shopping patterns of customers in order to provide products that suit their needs and desires. The study also recommended the necessity of working to raise the perceived value of the customer by providing products of appropriate quality, as well as raising the level of customer loyalty. In addition, 5 sites were chosen through social networking (Facebook), namely, the girl of Alakaber for clothes - the elegant veil - the cave complex - Handa costumes - Shark costumes to see the quality of the service provided.

Shah B., Singh G.

PurposeIn order to achieve competitive advantage over the physical marketplace, the e-retailers are insisted on endowing with lenient return policies. The piece-wise returns-and-reordering process incurs excessive buffering and unwanted logistics costs which raises overall fulfillment charges. The objective of this study is to re-design e-retail distribution policy by providing temporal storage at logistics service provides' (LSP) location. The impact of recurrent returns on pricing and profit margins are also investigated over time continuum.Design/methodology/approachA framework is developed to reduce the non-value added (NVA) storage and distribution efforts by providing collaborative buffering between LSP and e-retailer. The knapsack based buffering approach is tested and compared with traditional e-retail distribution practices. The revenue sharing concept is mathematically modelled and implemented in GAMS, which finally validated through multiple return scenarios.FindingsThe proposed model outperforms the existing one under all scenarios with different configuration settings of re-ordering, profit margins, and buffer time windows. The distribution cost is found, linearly related to the necessary product buffering space. The findings help to re-design sustainable return policies for individual products so that maximum customer value can be yield with minimum costs.Research limitations/implicationsThis study helps to determine the NVA efforts incurred while storing and delivering multi-time returned products to ensure desired service levels. The revenue sharing model provides pricing strategies for e-retail practitioners deciding which product should store in what quantity for how much time at the shipping agency location so that it fulfils the re-ordering at least waiting and sufficient buffering.Originality/valueThe proposed model extends the role of LPSs as temporary buffer providers to reduce returns-and-reordering fulfilment efforts in the e-retail network. This Collaborative framework offers an opportunity to amend the distribution contracts and policies time by time that enhances e-retailer's performance and customer satisfaction.

郑 铉.

Ran W., Liu S., Zhang Z.

Nowadays, how to offer extremely fast response to customer orders has become a major challenge for warehouse management, especially in e-commerce. Due to the time urgency aspect of some “VIP” orders that need priority processing, one of the most important issues for logistics distribution centres is how to improve the VIP order-picking priority without reducing the common order-picking efficiency. With this consideration, this article put forward a new priority polling model to describe and analyse this problem. We divide orders into priority and common categories according to their time urgency. A mathematical model is established for such a system by applying polling theory, a probability generating function, and an embedded Markov chain. Numerical analysis shows that this priority polling-based picking system can improve the picking efficiency and is well suited to practical operations.

Jimenez G H.S., Rodrigues T.F., Dantas M.M., Cavalcante C.A.

A core activity for achieving an efficient order fulfillment planning in the business-to-consumer (B2C) context is the inventory rationing. This activity is complex and vital once e-tailers must deal with high frequency orders, timely delivery needs, and frequent stock outs, having to employ other fulfillment alternatives such as dropshipping. Particularly, it becomes much more complex when supply disruptions occur. When some eventualities like the malfunctioning of the warehouse management system, a road blockage or a disaster occurs in an unexpected way e-tailers or supplier inventory can result damaged and the access to some geographic areas can be compromised, making hard to manage the inventory. As a consequence, some clients are hampered of receiving their products at the expected time, quantity or quality. This paper puts forward a framework for order fulfillment planning in e-tail stores, based on an inventory rationing model that splits the demand in a partial drop-shipping system. The model does consider the effects of supply disruption, filling the gap of existing models that do not include the respective constraints. Moreover, it reserves the more profitable and lesser inventory-consuming orders for the e-tailer, enabling him to diminish the consequences of the supply disruptions and achieve a profitable and service-oriented fulfillment operation.