Order Fulfillment Cycle Time Estimation for On-Demand Food Delivery

Author(s):  
Lin Zhu ◽  
Wei Yu ◽  
Kairong Zhou ◽  
Xing Wang ◽  
Wenxing Feng ◽  
...  
Processes ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 1274
Author(s):  
Ngoc Bao Tu Nguyen ◽  
Gu-Hong Lin ◽  
Thanh-Tuan Dang

The COVID-19 pandemic has boosted the growth of the online food delivery (OFD) market in every corner of the world. In Vietnam, the food delivery service is rising rapidly and opening a large gateway of opportunities for numerous OFD platforms, also making it a competing business market in this country. Thus, to keep up with the ever-changing market dynamics, there are numerous measures and dimensions for the OFD entrepreneurs to take into consideration towards sustainable development. This paper’s objective is to evaluate major OFD companies in Vietnam based on a comprehensive set of criteria, which are social and environmental criteria (healthy and safety, information security, and environmental impact), economic criteria (delivery cost, operational capability, and risk management), service quality (order fulfillment, delivery speed, convenience of payment, online/offline service level, and customer feedback), and technology (web design, real-time tracking systems, and marketing techniques). To achieve this objective, this work proposes a multi-criteria decision-making (MCDM)-based framework combining the fuzzy analytic hierarchy process (FAHP) and the weighted aggregated sum product assessment (WASPAS). The FAHP is used to generate criteria weights in which fuzzy set theory is applied to translate the linguistic evaluation statements of experts. Then, WASPAS is used to rank the OFD companies against the selected criteria. The evaluation criteria that have obtained maximum weight priority in the FAHP analysis are “convenience of payment”, “delivery speed”, “online service level”, “order fulfillment”, and “delivery cost”. From the final ranking of WASPAS, Foody is today the best performing OFD player in Vietnam regarding the selected criteria, followed by GrabFood and Now. The proposed methodology can be an accurate and robust evaluation model for the industry, while the managerial implications of this study provide significant materials for decision-makers in the OFD market in improving their businesses towards sustainable development.


2013 ◽  
Vol 17 ◽  
pp. 96-103
Author(s):  
Rong-Chang Chen ◽  
Chih-Hui Shieh ◽  
Kai-Ting Chan ◽  
Shin-Yi Chiu ◽  
Jyun-You Fan ◽  
...  

Author(s):  
TOLY CHEN ◽  
YU-CHENG LIN

A fuzzy-neural fluctuation smoothing rule is proposed in this study to improve the performance of scheduling jobs with various priorities in a semiconductor manufacturing factory. The fuzzy-neural fluctuation smoothing rule is modified from the well-known fluctuation smoothing rule by improving the accuracy of estimating the remaining cycle time of a job, which is done by applying Chen's fuzzy-neural approach with multiple buckets. To evaluate the effectiveness of the proposed methodology, production simulation is also applied in this study. According to experimental results, incorporating a more accurate remaining cycle time estimation mechanism did improve the scheduling performance especially in reducing the average cycle times. Besides, the fuzzy-neural fluctuation smoothing rule was also shown to be a Pareto optimal solution for scheduling jobs with various priorities in a semiconductor manufacturing factory.


Author(s):  
T Chen

A post-classifying fuzzy-neural approach is proposed in this study for estimating the remaining cycle time of each job in a wafer fabrication plant, which has seldom been investigated in past studies but is a critical task for the wafer fabrication plant. In the methodology proposed, the fuzzy back-propagation network (FBPN) approach for job cycle time estimation is modified with the proportional adjustment approach to estimate the remaining cycle time instead. Besides, unlike existing cycle time estimation approaches, in the methodology proposed a job is not preclassified but rather post-classified after the estimation error has been generated. For this purpose, a back-propagation network is used as the post-classification algorithm. To evaluate the effectiveness of the methodology proposed, production simulation is used in this study to generate some test data. According to experimental results, the accuracy of estimating the remaining cycle time could be improved by up to 64 per cent with the proposed methodology.


2016 ◽  
Vol 2 (3) ◽  
pp. 89 ◽  
Author(s):  
Anas Mutakin ◽  
Musa Hubeis

The objectives of this research were (1) Assess the supply chain structure of cement products in PT Indocement Induk Prakarsa (ITP) Tbk; (2) Conduct performance measurement of supply chain management (SCM) for cement products in PT ITP Tbk approach Supply Chain Operations Reference (SCOR) model version 9.0; (3) Provide alternatives solution to the problem after the measurement is known along with suggestions of measurement and analysis activities of SCM at PT ITP Tbk. Calculation of performance metrics level 1 is the perfect order fulfillment (POF) 82.43%, order fulfillment cycle time (OFCT) 2 days, the cost of good sold (COGS) 53.84% and cash-to-cash cycle time (CTCCT) 53 days. Opportunity value that is calculated using the lost opportunity measure (LOM) is a POF registration COGS Rp 552,146,310,636 and Rp 127,956,658,590. The mapping level 2 shows PT ITP Tbk have performance lowest deliver process, because the expedition and transportation of cement is less effective and efficient in sending customer orders. Mapping level 3 shows in detail the process of delivering PT ITP Tbk, so it can answer why deliver a low performance. From the results of the overall SCM performance PT ITP Tbk good enough, but needs to be improved on the expedition and the distribution of transportation to reach the target business objectives set PT ITP Tbk, which is improving customer service and increase profits.


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Arianna Seghezzi ◽  
Riccardo Mangiaracina

PurposeThis paper focusses on on-demand food delivery (ODFD), i.e. the delivery of freshly prepared meals to customers' homes, enabled by the use of online platforms. In ODFD, a key process is represented by last-mile deliveries (LMDs): they directly affect customers (the delivery price influences their purchase intention), riders (the compensation drives their willingness to perform deliveries) and platforms (deliveries are very expensive). In this context, this work aims to investigate the economic performances of ODFD LMDs.Design/methodology/approachThis study adopts a multi-method threefold process. First, it develops a model that – after the generation of customers' demand and the assignment of deliveries to available riders – identifies incomes and costs faced by an ODFD operator. Second, the model is applied to a base case in Milan (Italy). Third, sensitivity analyses are performed (on daily demand and riders' salary).FindingsThe analyses allow – besides the identification of significant values associated to ODFD profitability – to draw general insights about delivery price (e.g. free delivery is not economically sustainable), daily demand (e.g. greater demand values do not only improve positive results but also worsen negative ones) and fixed/variable wage mix (e.g. increasing the variable wage enhances the profitability for platforms).Originality/valueOn the academic side, this word enhances extant literature about ODFD, proposing a model – with multidisciplinary implications – to strategically investigate profitability conditions of LMDs. On the managerial side, it provides support for (logistics/marketing) ODFD practitioners since it allows to evaluate the potential impact of significant decisions on profitability.


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