scholarly journals Automation of Food Delivery Service in Railways

2021 ◽  
Vol 1 (1) ◽  
pp. 1
Author(s):  
Anudeepa Kholapure ◽  
Yash Pawse ◽  
Sai Karthik Nandigama ◽  
Mrinal Malkar ◽  
Vaibhavi Amal
Keyword(s):  
Food Delivery ◽  
Delivery Service

Digital Literacy Approach in Food Delivery Service Application

2021 ◽  
Author(s):  
Tiurida Lily Anita ◽  
Arif Zulkarnain ◽  
Amia Luthfia ◽  
Sari Ramadanty ◽  
Abdul Rauf Ridzuan
Keyword(s):  
Digital Literacy ◽  
Food Delivery ◽  
Delivery Service ◽  
Service Application

Courier Routing and Assignment for Food Delivery Service Using Reinforcement Learning

2021 ◽  
pp. 107871
Author(s):  
Aysun Bozanta ◽  
Mucahit Cevik ◽  
Can Kavaklioglu ◽  
Eray M. Kavuk ◽  
Ayse Tosun ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
Food Delivery ◽  
Delivery Service

scholarly journals Automation of Food Delivery Service in Railways

2021 ◽  
Vol 1 (1) ◽  
pp. 1
Author(s):  
Mrinal Malkar ◽  
Sai Karthik Nandigama ◽  
Anudeepa Kholapure ◽  
Yash Pawse ◽  
Vaibhavi Amal
Keyword(s):  
Food Delivery ◽  
Delivery Service

scholarly journals A Study on Improvement Effect of Shopping Environment by the Food Delivery Service

2016 ◽  
Vol 35 (Special_Issue) ◽  
pp. 201-206
Author(s):  
Satoshi TSUCHIYA ◽  
Keishi TANIMOTO ◽  
Hiromi KURAMOCHI
Keyword(s):  
Food Delivery ◽  
Delivery Service ◽  
Improvement Effect

scholarly journals COMPARISON INTENT RECOGNITION ON FOOD DELIVERY SERVICE COMPLAINT IN TWITTER WITH RECURRENT AND CONVOLUTIONAL NEURAL NETWORK

2020 ◽  
Vol 5 (1) ◽  
Author(s):  
Irfan Nasrullah ◽  
Rila Mandala
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Food Delivery ◽  
Learning Rate ◽  
Batch Size ◽  
Optimal Result ◽  
Intent Recognition ◽  
Delivery Service ◽  
Customer Relation Management ◽  
Large Fluctuations

In this research, the case of intent classification for Customer Relation Management (CRM) how to handle complaints as a domain to be followed up, where datasets are extracted from the conversation on Twitter. The research objectives support three key findings to comparing the CNNs and BRNNs model to intent recognition by vectorization text: (1) Which architecture performs better (accuracy) depends on how important it is to semantically understand the whole sequence and (2) Learning rate changes performance relatively smoothly, while the optimal result iterated by change hidden size and batch size result in large fluctuations. (3) Last, how word vectorization is able to define sub-domain of the complaints by word vector classification.

scholarly journals CO-BRANDING ONLINE FOOD DELIVERY: PERUBAHAN MODEL BISNIS WISATA KULINER LOKAL KHAS YOGYAKARTA

AdBispreneur ◽  
2019 ◽  
Vol 3 (3) ◽  
pp. 177
Author(s):  
Eska Nia Sarinastiti ◽  
Nabilla Kusuma Vardhani
Keyword(s):  
Business Model ◽  
Service Providers ◽  
Food Delivery ◽  
Study Data ◽  
Structured Interviews ◽  
Culinary Tourism ◽  
Delivery Service ◽  
Business To Consumer ◽  
Food Tourism ◽  
Business To Business

 The aim of this research is examining the implementation of co-branding by the food delivery service and its influence on the local culinary tourism business model of Yogyakarta. This research uses qualitative research with an exploratory study. Data collection was conducted through semi-structured interviews with 13 owners of Yogyakarta’s local culinary. The results showed that co-branding was carried out jointly with GoFoodPartner, but if it was not incorporated into GoFoodPartner co-branding was carried out directly between GoFood and the culinary business management. As for GrabFood, co-branding is done partially to businesses that are not part of their official cooperation partners. The culinary tourism business model has been changing by online food delivery service providers. The change is they have not only done business to consumer (B2C) but then also develop its business model into Business to Business (B2B) and Business to Business to Consumer (B2B2C). It changes the business model of culinary tourism developed into a food tourism business model.   Penelitian ini mengkaji tentang implementasi co-branding oleh layanan food delivery tersebut dan pengaruhnya pada model bisnis wisata kuliner lokal khas Yogyakarta. Penelitian ini menggunakan jenis penelitian kualitatif dengan metode eksploratory. Pengumpulan data dilakukan melalui wawancara semi-terstruktur dengan 13 pelaku usaha wisata kuliner lokal khas Yogyakarta didukung observasi serta dokumentasi. Hasil penelitian menunjukan bahwa co-branding dilakukan secara bersama-sama antara GoFood dan pelaku usaha wisata kuliner yang tergabung dalam GoFoodPartner, akan tetapi jika tidak tergabung dengan GoFoodPartner co-branding dilakukan secara terpisah antara GoFood dan pelaku usaha wisata kuliner. Sementara untuk GrabFood juga demikian, co-branding dilakukan secara partial untuk pelaku usaha wisata yang bukan masuk dalam mitra kerjasamanya. Model bisnis wisata kuliner yang dilakukan terdapat perubahan dengan adanya layanan online food delivery. Perubahan tersebut terdapat pada tidak hanya business to consumer (B2C), akan tetapi model bisnisnya berkembang juga menjadi Business to Business (B2B) dan Business to Business to Consumer (B2B2C). Perubahan model bisnis tersebut mendorong perkembangan model bisnis culinary tourism menjadi model bisnis food tourism.

scholarly journals Factors Affecting Customer Satisfaction & Loyalty in Online Food Delivery Service during COVID-19 Pandemic: Its Relation with Open Innovation

2021 ◽  
Author(s):  
Yogi Tri Prasetyo ◽  
Hans Tanto ◽  
Martinus Mariyanto ◽  
Christopher Hanjaya ◽  
Michael Nayat Young ◽  
...  
Keyword(s):  
Customer Satisfaction ◽  
Structural Equation ◽  
Food Delivery ◽  
Ease Of Use ◽  
Equation Modeling ◽  
Perceived Ease Of Use ◽  
New Normal ◽  
Delivery Service ◽  
Factors Influencing ◽  
Customer Satisfaction And Loyalty

Online food delivery service (OFDS) has been widely utilized during the new normal of COVID-19 pandemic especially in a developing country such as Indonesia. The purpose of this study was to determine factors influencing customer satisfaction & loyalty in OFDS during the new normal of COVID-19 pandemic in Indonesia by utilizing an extended Theory of Planned Behavior (TPB) approach. 253 respondents voluntarily participated and answered 65 questions. Structural equation modeling (SEM) indicated that Hedonic Motivation (HM) was found to have the highest effect on customer satisfaction, followed by Price (P), Information Quality (IQ), and Promotion (PRO). Interestingly, this study found out that usability factors such as Navigational Design (ND) and Perceived Ease of Use (PEOU) were not significant to customer satisfaction and loyalty in OFDS during the new normal of COVID-19. This study can be the theoretical foundation that could be very beneficial for OFDS investors, IT engineers, and even academicians. Finally, this study can be applied and extended to determine factors influencing customer satisfaction and loyalty in OFDS during the new normal of COVID-19 in other countries.

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