PriMera Scientific Engineering (ISSN: 2834-2550)

Literature Review

Volume 3 Issue 4

E-Government Regulation for the Rider’s Delivery Attempt Verification to Remove Issues in Logistic Operation and Protect Customer Rights

Muhammad Younus*, Achmad Nurmandi, Suswanta and Abdul Rehman

September 30, 2023

View PDF

Abstract

The objective of this paper is to share the details related to the standard Delivery Attempt Verification Techniques for accurately determining if the Delivery Attempt made by the Delivery Rider is valid or not against the Order or Parcel ordered Online by the Customer through Shipper E-commerce Site. The Researchers who are working on this research area are using ‘Qualitative Research.’ The Data for the research was taken from the Delivery Mobile Applications, Blogs, social media, and E-commerce Sites, and then it was presented descriptively. The study in this paper tells us that the formation of the Standard Regulation will improve the visibility of Delivery Attempts made on the logistics operations. In Order to achieve it, several steps need to be taken for the successful implementation of the Regulation. This paper will only be limited to the extent to which the challenge currently facing is clearly described, then suggest possible solutions like Live Tracking, Lat-long Capture, Delivery Code, Verification Calls or SMS, etc., for resolving it and how it will work, and finally, what positive impact the solution will have on the Customer and the logistics sector.

Keywords: First Mile; Mid Mile; Last Mile; Logistics; E-Commerce; COD (Cash on Delivery)

References

  1. Alfarizi M and Sari RK. “Analysis of Factors Affecting Customer Behavior of Marketplace Applications: A Case Study of Cash on Delivery (COD) Payment Systems”. 13th International Conference on Advanced Computer Science and Information Systems, ICACSIS (2021).
  2. Alkis A and Kose T. “Privacy concerns in consumer E-commerce activities and response to social media advertising: Empirical evidence from Europe”. Computers in Human Behavior 137 (2022).
  3. Almtiri Z, Miah SJ and Noman N. “Application of E-commerce Technologies in Accelerating the Success of SME Operation”. In Y. X.-S., S. S., D. N., & J. A. (Eds.), 7th International Congress on Information and Communication Technology, ICICT 2022 (2023): 463-470.
  4. Anjum S and Chai J. “Drivers of Cash-on-Delivery Method of Payment in E-Commerce Shopping: Evidence from Pakistan”. SAGE Open 10.3 (2020).
  5. Armstrong CEJ., et al. “Machine learning for classifying and predicting grape maturity indices using absorbance and fluorescence spectra”. Food Chemistry 403 (2023).
  6. Ashrafpour N., et al. “The prerequisites and consequences of customers’ online experience regarding the moderating role of brand congruity: evidence from an Iranian bank”. Journal of Islamic Marketing 13.10 (2022) 2144-2172.
  7. Bighrissen B. “A Study of Barriers to E-Commerce Adoption Among Cooperatives in Morocco”. In A. B. & H. A. (Eds.), International Conference on Business and Technology, ICBT 2021 485 (2023): 557-570.
  8. Bopage G, Nanayakkara J and Vidanagamachchi K. “A strategic model to improve the last mile delivery performance in ecommerce parcel delivery”. 9th International Conference on Industrial Engineering and Operations Management, IEOM 2019, 2019(MAR), 2018-2019 (2019).
  9. Chang S., et al. “Joint optimization of e-commerce supply chain financing strategy and channel contract”. European Journal of Operational Research 303.2 (2022): 908-927.
  10. Cosmi M, Nicosia G and Pacifici A. “Lower bounds for a meal pickup-and-delivery scheduling problem”. In H. J., K. S., M. B.R., U. V., & U. M.S. (Eds.), 17th Cologne-Twente Workshop on Graphs and Combinatorial Optimization, CTW, University of Twente (2019): 33-36.
  11. Das D, Kumar R and Rajak MK. “Designing a reverse logistics network for an e-commerce firm: A case study”. Operations and Supply Chain Management 13.1 (2020): 48-63.
  12. Dasgupta S, Kanchan S and Kundu T. “Creating a KPI tree for monitoring and controlling key business objectives of first mile logistics services”. 9th International Conference on Industrial Engineering and Operations Management, IEOM 2019 (2019): 716-727.
  13. Datta S., et al. “Sanskriti—A Distributed E-Commerce Site Implementation Using BlockChain”. In Lecture Notes on Data Engineering and Communications Technologies, Springer Science and Business Media Deutschland GmbH 139 (2023): 329-346.
  14. Etumnu CE. “A competitive marketplace or an unfair competitor? An analysis of Amazon and its best sellers ranks”. Journal of Agricultural Economics 73.3 (2022): 924-937.
  15. González-Mora C., et al. “Improving open data web API documentation through interactivity and natural language generation”. Computer Standards and Interfaces 83 (2023).
  16. Ha XS., et al. “Scrutinizing Trust and Transparency in Cash on Delivery Systems”. In W. G., C. B., L. W., D. Pietro R., Y. X., & H. H. (Eds.), 13th International Conference on Security, Privacy, and Anonymity in Computation, Communication, and Storage, SpaCCS 2020: Vol. 12382 LNCS (2021): 214-227.
  17. Handhayani T and Hendryli J. “Leboh: An Android Mobile Application for Waste Classification Using TensorFlow Lite”. In A. K. (Ed.), Intelligent Systems Conference, IntelliSys 2022: Vol. 544 LNNS (2023): 53-67.
  18. Hasan F., et al. “E-commerce Merchant Fraud Detection using Machine Learning Approach”. 7th International Conference on Communication and Electronics Systems, ICCES (2022): 1123-1127.
  19. Jaller M and Dennis S. “E-Commerce and Mobility Trends During COVID-19”. In Springer Tracts on Transportation and Traffic 20 (2023): 79-93.
  20. Kahr M. “Determining locations and layouts for parcel lockers to support supply chain viability at the last mile”. Omega (United Kingdom) 113 (2022).
  21. Law C-Y., et al. “Mobile Application for After School Pickup Solution: Malaysia Perspectives”. In A. K. (Ed.), Intelligent Systems Conference, IntelliSys 2022: Vol. 544 LNNS (2023): 68-78.
  22. Li Y., et al. “Product Reviews Analysis of E-commerce Platform Based on Logistic-ARMA Model”. 2021 IEEE International Conference on Power, Intelligent Computing and Systems, ICPICS (2021): 714-717.
  23. Lu S-H., et al. “Improving the efficiency of last-mile delivery with the flexible drones traveling salesman problem”. Expert Systems with Applications 209 (2022).
  24. Luo X., et al. “Nondestructive determination of common indicators of beef for freshness assessment using airflow-three-dimensional (3D) machine vision technique and machine learning”. Journal of Food Engineering 340 (2023).
  25. Luo Z., et al. “A last-mile drone-assisted one-to-one pickup and delivery problem with multi-visit drone trips”. Computers and Operations Research 148 (2022).
  26. McKinlay A, Mitchell G and Bertenshaw C. “Review article: DINED (Delivery-related INjuries in the Emergency Department) part 1: A scoping review of risk factors and injuries affecting food delivery riders”. EMA - Emergency Medicine Australasia 34.2 (2022): 150-156.
  27. McKinlay A, Mitchell G and Bertenshaw C. “Review article: DINED (Delivery-related INjuries in the Emergency Department) part 1: A scoping review of risk factors and injuries affecting food delivery riders”. EMA - Emergency Medicine Australasia 34.2 (2022): 150-156.
  28. Muniasamy A and Bhatnagar R. “Analyzing Online Reviews of Customers Using Machine Learning Techniques”. In R. V.S., S. S.C., T. J.M.R.S., M. C., & S. B. (Eds.), 2nd FICR International Conference on Rising Threats in Expert Applications and Solutions, FICR-TEAS 434 (2022): 485-493.
  29. Muñoz-Villamizar A., et al. “The environmental impact of fast shipping ecommerce in inbound logistics operations: A case study in Mexico”. Journal of Cleaner Production 283 (2021).
  30. Nagpal G., et al. “Use of data analytics to increase the efficiency of last mile logistics for ecommerce deliveries”. In Handbook of Research on Engineering, Business, and Healthcare Applications of Data Science and Analytics IGI Global (2020): 167-180.
  31. Oviedo-Trespalacios O, Rubie E and Haworth N. “Risky business: Comparing the riding behaviours of food delivery and private bicycle riders”. Accident Analysis and Prevention 177 (2022).
  32. Peng Y and Yi J. “Research on the Application of Big Data Technology in the Process of Cross-Border E-Commerce Product Selection”. In W. T., P. S., H. J. W.C., & R. V. M.L. (Eds.), 4th International Conference on Decision Science and Management, ICDSM 260 (2023): 29-37.
  33. Pereira Marcilio Nogueira G., et al. “The environmental impact of fast delivery B2C e-commerce in outbound logistics operations: A simulation approach”. Cleaner Logistics and Supply Chain 5 (2022).
  34. Pérez-Morón JM. “E-commerce in China and Latin America. A Review and Future Research Agenda”. In A. B. & H. A. (Eds.), International Conference on Business and Technology, ICBT 2021 485 (2023): 571-587.
  35. Purwandari B., et al. “Factors Affecting Switching Intention from Cash on Delivery to E-Payment Services in C2C E-Commerce Transactions: COVID-19, Transaction, and Technology Perspectives”. Emerging Science Journal 6 (2022): 136-150. 
  36. Raj NV and Saini JR. “Loyalty Score Generation for Customers Using Sentimental Analysis of Reviews in e-commerce”. In D. P., C. S., B. A., D. S., & S. C. (Eds.), 3rd International Conference on Emerging Technologies in Data Mining and Information Security, IEMIS 2022 490 (2023): 461-473.
  37. Sandoval MG., et al. “A novel districting design approach for on-time last-mile delivery: An application on an express postal company”. Omega (United Kingdom) 113 (2022).
  38. Stefko R., et al. “Gender-generation characteristic in relation to the customer behavior and purchasing process in terms of mobile marketing”. Oeconomia Copernicana 13.1 (2022) 181-223.
  39. Thematic analysis. In Wikipedia (2022).
  40. Tran NAT., et al. “Health and safety risks faced by delivery riders during the Covid-19 pandemic”. Journal of Transport and Health 25 (2022).
  41. Verma R, Dhanda N and Nagar V. “Towards a Secured IoT Communication: A Blockchain Implementation Through APIs”. In S. P.K., W. S.T., T. S., R. J.J.P.C., R. J.J.P.C., & G. M. (Eds.), 3rd International Conference on Computing, Communications, and Cyber-Security, IC4S 2021 421 (2023): 681-692.
  42. Wang M., et al. “A branch-and-price algorithm for location-routing problems with pick-up stations in the last-mile distribution system”. European Journal of Operational Research 303.3 (2022): 1258-1276.
  43. Wu G. “Research on the development path of logistics management innovation in e-commerce environment”. 2020 6th International Conference on Environmental Science and Material Application, ESMA 2020 714.4 (2021).
  44. Xu J., et al. “Flexible sensing enabled packaging performance optimization system (FS-PPOS) for lamb loss reduction control in E-commerce supply chain”. Food Control 145 (2023).
  45. Yin L, Zhong RR and Wang J. “Ontology based package design in fresh E-Commerce logistics”. Expert Systems with Applications 212 (2023).
  46. Yun KK, Yoon SW and Won D. “Interpretable stock price forecasting model using genetic algorithm-machine learning regressions and best feature subset selection”. Expert Systems with Applications 213 (2023).