Logistics Performance, Ratings, and Its Impact on Customer Purchasing Behavior and Sales in E-Commerce Platforms

Problem definition: We examine the impact of logistics performance metrics such as delivery time and customer’s requested delivery speed on logistics service ratings and third-party sellers’ sales on an e-commerce platform. Academic/practical relevance: Although e-commerce retailers like Amazon have recently invested heavily in their logistics networks to provide faster delivery to customers, there is scant academic literature that tests and quantifies the premise that convenient and fast delivery will drive sales. In this paper, we provide empirical evidence on whether this relationship holds in practice by analyzing a mechanism that connects delivery performance to sales through logistics ratings. Prior academic work on online ratings in e-commerce platforms has mostly analyzed customers’ response to product functional performance and biases that exist within. Our study contributes to this stream of literature by examining customer experience from a service quality perspective by analyzing logistics service performance, logistics ratings, and its impact on customer purchase probability and sales. Methodology: Using an extensive data set of more than 15 million customer orders on the Tmall platform and Cainiao network (logistics arm of Alibaba), we use the Heckman ordered regression model to explain the variation in customers’ rating of logistics performance and the likelihood of customers posting a logistics rating. Next, we develop a generic customer choice model that links the customer’s likelihood of making a purchase to the logistics ratings provided by prior customers. We implement a two-step estimation of the choice model to quantify the impact of logistics ratings on customer purchase probability and third-party seller sales. Results: We surprisingly find that even customers with no promise on delivery speed are likely to post lower logistics ratings for delivery times longer than two days. Although these customers are not promised an explicit delivery deadline, they seem to have a mental threshold of two days and expect deliveries to be made within that time. Similarly, we find that priority customers (those with two-day and one-day promise speed) provide lower logistics ratings for delivery times longer than their anticipated delivery date. We estimate that reducing the delivery time of all three-day delivered orders on this platform (which makeup [Formula: see text] 35% of the total orders) to two days would improve the average daily third-party seller sales by 13.3% on this platform. The impact of delivery time performance on sales is more significant for sellers with a higher percentage of three-day delivered orders and a higher spend per order. Managerial implications: Our study emphasizes that delivery performance and logistics ratings, which measure service quality, are essential drivers of the customer purchase decision on e-commerce platforms. Furthermore, by quantifying the impact of delivery time performance on sales, our study also provides a framework for online retailers to assess if the increase in sales because of improved logistics performance can offset the increase in additional infrastructure costs required for faster deliveries. Our study’s insights are relevant to third-party sellers and e-commerce platform managers who aim to improve long-term online customer traffic and sales.

Optimal Route Planning for Truck–Drone Delivery Using Variable Neighborhood Tabu Search Algorithm

The optimal delivery route problem for truck–drone delivery is defined as a traveling salesman problem with drone (TSP-D), which has been studied in a wide range of previous literature. However, most of the existing studies ignore truck waiting time at rendezvous points. To fill this gap, this paper builds a mixed integer nonlinear programming model subject to time constraints and route constraints, aiming to minimize the total delivery time. Since the TSP-D is non-deterministic polynomial-time hard (NP-hard), the proposed model is solved by the variable neighborhood tabu search algorithm, where the neighborhood structure is changed by point exchange and link exchange to expand the tabu search range. A delivery network with 1 warehouse and 23 customer points are employed as a case study to verify the effectiveness of the model and algorithm. The 23 customer points are visited by three truck–drones. The results indicate that truck–drone delivery can effectively reduce the total delivery time by 20.1% compared with traditional pure-truck delivery. Sensitivity analysis of different parameters shows that increasing the number of truck–drones can effectively save the total delivery time, but gradually reduce the marginal benefits. Only increasing either the truck speed or drone speed can reduce the total delivery time, but not to the greatest extent. Bilateral increase of truck speed and drone speed can minimize the delivery time. It can clearly be seen that the proposed method can effectively optimize the truck–drone delivery route and improve the delivery efficiency.

Pregnancy Education Can Reduce Stress and Mothers Remain Fit an Delivery During The Covid 19 Pandemic

Pain in labor can cause blood pressure to increase which causes stress and disrupted labor, this can certainly hamper labor so that the delivery time will be longer. The purpose of the activity is to increase knowledge and understanding of pregnancy exercise which can reduce stress so that delivery runs smoothly during the covid-19 pandemic. The method used is webinar via zoom, question and answer and demonstration and poster distribution. The results of the health webinar activity are named “Pregnancy Gymnastics Education Can Reduce Stress and Mothers Stay Fit During Delivery During Covid-19”. which will be held on Sunday, April 25, 2021, starting at 09.00 to 12.00. In the process of conducting the webinar; The participants looked very enthusiastic when the material was given. Participants participated in the webinar enthusiastically even though it was conducted online. The webinar activity was conducive because the participants paid attention to the material presented well and asked questions.

Forecasting the efficiency of weft knitting production: a decision tree method

Purpose This paper aims to develop a decision support system for predicting the knitting production’s efficiency based on the input parameters of an order. This tool supports the operations managers to make reliable decisions of estimated delivery time, which will result in reducing waste arising from late delivery, overtime and increased labor. Design/methodology/approach The decision tree method with a set of logical IF-THEN rules is used to determine the knitting production’s efficiency. Each path of the decision tree represents a rule of the following form: “IF <Condition> THEN <Efficiency label>.” Starting with identifying and categorizing input specifications, the model is then applied to the observed data to regenerate the results of efficiency into classification instances. Findings The production’s efficiency is the result of the interaction between input specifications such as yarn’s component, knitting fabric specifications and machine speed. The rule base is generated through a decision tree built to classify the efficiency into five levels, including very low, low, medium, high and very high. Based on this, production managers can determine the delivery time and schedule the manufacturing planning more accurately. In this research, the correct classification instances, which is simply a ratio of the correctly predicted observations to the total ones, reach 80.17%. Originality/Values This research proposes a new methodology for estimating the efficiency of weft knitting production based on a decision tree method with an application of real data. This model supports the decision-making process of the estimated delivery time.

Merchants Competing on E-Commerce Platforms

The importance of marketplaces in e-commerce has increased. More and more merchants are trying to use e-commerce platforms as a distribution channel. With the increasing competition, merchants are faced with the challenge of continuing to sell their products to consumers through marketplaces at a profit. This is especially true if the consumer has already chosen a certain product and now only decides from which merchant to buy the product. This chapter therefore examines for different customer segments which merchant-related factors — also and in particular apart from the price — influence the purchase decision. After reviewing relevant literature, various factors are identified through structured interviews. An online survey is then used to simulate a total of 3,485 purchase decisions with different factor characteristics. In addition to the price, the ratings of a merchant and the delivery time are identified as central factors influencing the purchase decision.

KRUCIAL- All in One Delivery Web Application

This is a website for searching availability of any stationary product in the nearby stationary stores of the user, now including the online pharmacy feature and then the user can place the order in any of those stores. The user will enter the product name required. After searching for the availability of that product in the nearby store, the result will be shown (including a description of the product, price of the product, etc). Then the user can compare the price and quality of the product. After that, the user can choose a store from where they want to order the required product. The users can directly explore the website and can continue shopping. And once the order gets confirmed from the store the user will receive confirmation details. Once the order gets delivered the user will receive a feedback form about the experience of shopping with our website and also the delivery time, behavior of that delivery person. The user can also rate and write reviews on our website about the store they have placed their order.

Motives for Decreasing the Curing Time of HTPB-AP Composite Propellants

One of the standard conditions for solidifying composite propellants consist of hydroxyl terminated poly-butadiene as a binder and ammonium perchlorate as oxidizer, is the curing process for certain time in a certain temperature. On this paper, the motives and reasons for the decreasing of this curing time were studied and discussed. The study and discussion include the productivity, cost, delivery, manpower, and maintenance points of view. By experiments and questionnaire work, it was seen that, all the previous points of view were affected positively. Generally, the productivity of the propellant was increased by 100%, the cost of curing process was decreased by 25% of the previous cost, the man power needed for the process of waiting and recording the readings was decreased by 50%, customer delivery process was fasted by 50% of the previous delivery time, and finally the maintenance processes due to equipment depreciation were improved by 50% from the previous. From the whole point of view, it was seen that, the decreasing of the curing time is very useful for the production of the propellant. Finally, it is observed that the decreasing of the curing time to the half time brought the same properties of the standard curing time, and then it is concluded that the deceasing of the curing time can be applied safely and usefully in the casting production line.