Order Processing System Research Articles

The Moderating Influence of Enterprise Resource Planning on the Relationship between Electronic Order Processing Systems and Supply Chain Performance of Manufacturing Firms in Uasin Gishu County, Kenya

The Moderating Influence of Enterprise Resource Planning on the Relationship between Electronic Order Processing Systems and Supply Chain Performance of Manufacturing Firms in Uasin Gishu County, Kenya

Physical Distribution Strategies and the Marketing Performance of Bottled Water Companies in Calabar, Nigeria

This research examined the effect of physical distribution strategies on the marketing performance of bottled water companies in Calabar. It employed a cross-sectional survey approach. Primary data were collected from 276 operational personnel of bottled water companies in Calabar through a structured questionnaire. Descriptive statistics were applied to analyze and interpret the data, while multiple linear regression was utilized to test the hypotheses. The results unveiled significant positive impacts of order processing, transportation, inventory, and warehousing management on the marketing performance of bottled water companies in Calabar, Nigeria. Therefore, the study recommends the following, among others: bottled water companies should integrate innovative technologies into their order processing systems, such as automated order placement, and order sorting software to ensure the delivery of accurate and personalized orders to customers at all times; a robust transportation management system characterized by timely carrier scheduling, clear route planning and automated carrier tracking should be in place to enable bottled water companies achieve effective distribution of products to customers when needed; and bottled water companies should prioritize inventory management through strategic inventory planning, automated inventory control and prompt inventory replacement to ensure that inventory resources required for production and customer service are consistently available in appropriate quantities and quality.

Logistics Management Practices and Performance of Government-Owned Sugar Companies In Kenya.

In the recent past, the Kenyan government has not been able to ensure the provision of affordable food. Structural bottlenecks have made it difficult for food produced in the country to reach its intended recipients. This study investigated the effect of logistics management practices on performance of government owned sugar companies in Kenya. It was premised on the proposition that in order to increase competitiveness of government-owned sugar companies, it is important to have a sound understanding of their logistics management practices. Underpinned by resource-based view theory, theory of constraints, systems theory and transaction cost theory, this study provided insights into managing logistics to enhance performance within the context of government owned sugar companies in Kenya. Four specific objectives emanated from this main objective: one, to determine the extent to which inventory management affects performance, two, to assess how order management affects performance, three, to establish how transportation management affects performance, four to determine the extent to which packaging management practices affects performance. Out of these objectives, hypotheses were stated for testing. Through structured questionnaires, data was obtained from 5 government-owned sugar companies. Descriptive and inferential statistics were used to analyze the data and test hypotheses of the relationships stated earlier. The target sample population of the study was 256 supply chain personnel from five Government-owned sugar Companies in Kenya. Data analysis was done using SPSS version 29 using both descriptive and inferential analysis. The study finding revealed that inventory, order, transport, and packaging management significantly influence government-owned sugar manufacturing firms' performance in Kenya, explaining 73.9% of performance variation. ANOVA results confirmed the model's statistical significance (p < 0.05). Further analysis demonstrated positive relationships between inventory, order, transport, and packaging management practices and firm performance. The study suggests government and policymakers allocate resources for collaborative research to enhance state-owned sugar manufacturing firms' logistics management. Researchers should focus on cost reduction, quality control, and technology adoption. Sugar firms need to invest in order processing systems, equipment, and sustainable packaging. Logistics service providers should adopt advanced technologies and collaborate with sugar firms. Further studies should explore additional logistics practices and cross-industry collaborations.

The efect of characteristics of SMEs to the order processing and information system costs

It is apparent that the logistics process can reduce cost in order to have an efficient profit, efficient suitable and efficient economical way to run a sustainable business. This research aimed to study the effect of characteristics of small and medium-sized enterprises (SME) on the reduction of operating costs to get the most benefit and most suitable and the most economical way to run a sustainable business. A case study of logistics of small and medium-sized enterprise entrepreneurs in Pathum Thani Province by using questionnaires to collect 400 sets of data. The results of the study showed that the purchase order and the information system affected the reduction of operating costs. Participants responded the different registered capital of small and medium-sized enterprises (SME) have differences in managing cost systems, and the business uses information systems in the flow of information through electronic processes that are ordered by customers systematically with statistical significance at the level of 0.05.

Improving Automotive Component Supplier Service through Physical Distribution Activities to Original Equipment Manufacturers (OEMs)

Purpose/objectives: The purpose of this study was to investigate whether physical distribution activities can significantly improve customer service for automotive component suppliers to Original Equipment Manufacturers (OEMs) in the Eastern Cape. Design/methodology/approach: By means of non-probability sampling, namely convenience sampling, 50 automotive component suppliers in the Eastern Cape were visited. Each business firm received four questionnaires to be completed by logistics practitioners. Altogether, 126 usable questionnaires were returned. The data were collected by means of a survey using a self-administered, structured questionnaire. Findings/results: The results indicated that physical distribution activities, such as transportation management and order processing, were significant predictors of customer service. Practical implications: The results have managerial implications where the logistics department should continuously update its transportation and order processing systems to keep abreast of the best practices within the automotive industry. The results could be used by managers to highlight the benefits of improved customer service, focusing on a firm’s transportation and order processing activities. Originality/value: Based on the results of the study, it is recommended that automotive component suppliers in the Eastern Cape employ transportation management and order processing (activities of physical distribution) to improve customer service. It is also recommended that the automotive component suppliers regularly benchmark their logistics practices against world-class business firms, as the results may have a positive effect on the way transportation and order processing activities are managed and executed if customer service is to be improved.

Development of an Order Processing System using Google Sheets and Appsheet for a Malaysian Automotive SME Factory Warehouse

The automotive industries in Malaysia have grown well and developed many suppliers in their supply chain including Small Medium Enterprise (SME). The order handling process at a supplier's factory has become one of the most critical areas in the supply chain. Adaptation to technology such as IoT enables the automotive supplier to better manage their customer orders and avoid mistakes that affect the supply chain. In order to improve the order processing activities, a study has focused on developing a mobile device application using Google Appsheet and Google Sheets as a cost-effective system for managing supply orders. A study was conducted in one of Malaysian SME automotive companies, which manages the orders manually by using a log book with a lot of recording and redundant work. By using Google Sheets, all the information and data involved in order processing activities is imported and digitized. Then, a mobile application is created using Appsheet so that the ordering activities and processing can be completed on a mobile device. All information gathered by the mobile app (Google Appsheet) is immediately saved in Google Sheets on an Excel-based database, allowing for further data analysis. The research conducted has managed to integrate these two applications into a system for Malaysia's SME factory to manage the ordering activities in the automotive supply chain. This system enables the user to shorten their order processing time since data is captured in real time and mistakes due to manual error can be avoided.

The Influence of Supply Chain Management Practises on Operational Performance of Quoted Manufacturing Firms in Nigeria: Procurement Outsourcing And Order Process Management View

The study explored the influence of supply chain management practises on operational performance in the manufacturing firms in Nigeria. Conversely, the study adopted the cross-sectional survey research design. Data were primarily sourced through administered questionnaires. A collection of four thousand, nine hundred and eighty-four (4,984) employees of all manufacturing firms listed on the Nigerian Stock Exchange (NSE) and operating in Nigeria's Edo and Delta States make up the study's population. A sample size of 370 was computed using the Yamane’s formula and same number of questionnaires was administered but 318 were found fit in testing the formulated hypotheses. Research data were analyzed, using descriptive and inferential statistical instruments. Based on the ordinary least squares regression, the study revealed that procurement outsourcing (?= 0.082974, t-Statistic= 3.049313 and p<0.05) and order process management (?= 0.349839, t-Statistic= 7.972484 and p<0.05) have positive and statistically significant relationship with operational performance of quoted manufacturing firms in Nigeria. Based on these conclusions, the study suggested that management of manufacturing firms conduct a benchmarking exercise for best players in the industry as a way to improve their procurement outsourcing practices, and that the facility and competence of order processing system should be routinely evaluated using indicators that tracked the flexibility and dependability of order handling. This would allow them to attain and keep up supply chain performance that is unmatched.

An advanced order batching approach for automated sequential auctions with forecasting and postponement

In sequential auctions, all the sub-orders from a buyer need to be sorted and consolidated within a short time window for shipping. Buyer demands and sub-order arrival times are uncertain. The current auction order fulfillment is facing several challenges. Based on a re-engineered Industrial Internet-of-Things (IIoT)-enabled automation system, this paper introduces an order batching approach with forecasting and postponement. Such an approach generates batches considering time interval and buyer completion rate to minimise the total processing time of the auction orders and system response time. The buyer completion rate refers to the ratio of current cumulative and predicted purchase quantity. We use the forecasting method proposed by Kong et al. (2021) to estimate the purchasing quantity. Through a series of computational experiments using real-life data, the proposed order batching method achieves a shorter order processing time and system response time. Results show that the number of auction buyers poses no effect on the performance of the proposed approach. Key parameters of order postponement rule influence on performance.

Analysis of the use of the Redis in the distributed order processing system in the restaurant network

The object of research is a distributed order processing system for a restaurant chain. The subject of the research is the analysis of the use of Redis for managing event queues in distributed systems. When implementing a distributed order processing system in a restaurant chain with a possible load of up to 20,000 users per day, the Redis system was used. Management of 9 distributed subsystems was organized through Redis. This solution showed an increase in the performance of the system under heavy load (from 50 transactions per second), but the response time of the system in some cases of its operation was longer than without using Redis. When working systems using Redis, it is necessary to take into account the amount of data with which Redis will work, since it does not exceed the amount of RAM, the absence of differentiation into users and groups, and the absence of a query language, which is replaced by a key-value scheme. This research is aimed at analyzing the operation of the system during trial operation under real load. We compared the operation of a configured system with Redis enabled and disabled. The main indicators for the analysis were the system response time and the maximum request execution time. The research was carried out for 2 weeks, the first week using the system settings with disabled Redis, the second – with enabled Redis. We selected 2 days with a similar load on the system to each other. Especially indicative are the results of comparing the durations of the longest queries, which show an almost constant value of the duration for the system in the mode of enabled Redis. The hypothesis of an increase in the system response time at low loads was confirmed, but this value not only leveled off at a load of 500 unique users but also became less at loads of 1000 unique users.

Customer Claims in Automobile Spare Parts Industry – A 3PL Perspective

Automobile OEM (Original Equipment Manufacturer) has two key lines of business. One being the main equipment sales and the other being spare parts associated to the original equipment. This line of business is either called as After Sales Market / After Market / Spares Market. As part of wear and tear of spare parts of original equipment service and replacement of spare parts comes into picture. A 3PL organization is selected by OEMs to manage their after sales service. Primary responsibilities of a 3PL includes warehouse management where the spare parts of OEMs are received, stored, order processed and delivered to OEM’s end customers. Hence, 3PL companies have major share in ensuring accurate delivery of spare parts to OEM’s end customers. Any wrong or shortage or excess delivery (which is termed as Customer Claims) impacts the customer satisfaction level and adds up logistics cost to both 3PL organization and OEM. This paper aims at evaluating the core reasons behind customer claims. In completing this research, the population selected for study is from 3 leading automobile OEMs and 1,00,000 samples. The results have shown that the key drivers of customer claims are due to stock management in warehouse managed by 3PL organization in following areas of operation.  Inbound (Gate entry of vehicles, Unloading, Physical verification of unloaded stock, Physical putaway of parts in warehouse storage locations)  Outbound (Customer order registration, Picking instructions from the sales order processing system, Physical picking of parts, Packaging of picked parts, Despatch and Delivery at customer end) In the above-mentioned key process areas ERP (Enterprise Resource Planning) application or WMS (Warehouse Management System) or Inventory Management application plays a significant role in avoiding or minimizing customer claims. Apart from applications and Information Technology systems, skill of staff and operatives, discipline of operatives, system controls influence extensively in customer claims to be generated. Background/Objective: To investigate deeper into causes that impact customer claims from 3PL service provider view. Methods / Statistical analysis: The results are based on about 1,00,000 samples for a periodicity of 6 years from 3 major automobile industry linked 3PL organization. Results/findings: The claim samples showed significantly higher due to pick issues ~ 41.7% and wrong labelling issues ~ 42.34%. Other reasons contribute about 15.96% Conclusion: The analysis offers a clear distribution of root causes in the collected samples.

Development of a central order processing system for optimizing demand-driven textile supply chains: a real case based simulation study

Nowadays, the demand of small-series production and quick response become more and more important in textile supply chains. To meet the increasing trend of customization in garment production, forecast based supply chain model is not suitable any more. Demand-driven garment supply chain is developed and employed more and more. However, there are still many defects in current model for demand-driven supply chains, e.g. long lead time, low efficiency etc. Therefore, in this study we proposed a new collaborative model with central order processing system (COPS) to optimize current demand-driven garment supply chain and improve multiple supply chain performances. Common and important supply chain collaboration strategies, including resource sharing, information sharing, joint-decision making and profit sharing, were merged into this system. Discrete-event simulation technology was utilized to experiment and evaluate the new collaborative model under different conditions based on a real case in France. Multiple key performance indicators (KPIs) were examined for the whole supply chain and also for individual companies. Based on the simulation experiment results, we found that new proposed collaborative model gain improvements in all examined KPIs. New model with COPS performed better under high workload condition than under low workload condition. It can not only increase overall profit level of the whole supply chain but also individual profit level of each company.

Simulation modelling of central order processing system under resource sharing strategy in demand-driven garment supply chains

In this paper we proposed a central order processing system under resource sharing strategy for demand-driven garment supply chains to increase supply chain performances. We examined this system by using simulation technology. Simulation results showed that significant improvement in various performance indicators was obtained in new collaborative model with proposed system.

Parts-to-picker based order processing in a rack-moving mobile robots environment

This paper treats a special parts-to-picker based order processing system, where mobile robots hoist racks and bring them directly to stationary pickers. This technological innovation – known as the Kiva system – heavily influences all traditional planning problems to be solved when operating a warehouse. We, specifically, tackle the order processing in a picking station, i.e., the batching and sequencing of picking orders and the interdependent sequencing of the racks brought to a station. We formalize the resulting decision problem and provide suited solution procedures. In a comprehensive computational study we show that an optimized order picking allows to more than halve the fleet of robots compared to simple decision rules often applied in real-world warehouses.

Simulation Research on Jingdong Orders System Based on Flexsim

Order processing system is the beginning and core part of distribution center operations, and efficient order processing operations can not only improve customer satisfaction but also reduce costs. Therefore, the trade-off analysis between order processing difficulty and quick response time, improving the handling capacity and efficiency while reducing order processing costs are regarded as two big challenges for e-commercial enterprise. Based on queuing model as well as some data collected from Jingdong, a Chinese E-commerce giant, this paper constructed a 3D simulation model by using Flexsim, aiming at solving the bottleneck of the whole system of E-commerce order processing. According to the simulation, the author gives two order processing optimization solution, service stations optimization and queuing optimization to solve the two challenges.

Design and Development of Framework to Create Cloud-Free Reference Repository of IRS Satellite Images for Image Analysis

Technological advancement and increasing availability of high-resolution satellite images, offer the potential for more accurate analyses, by which the detection and quantification of changes could improve greatly. Such remotely-sensed products are expensive and difficult to acquire, which not only prohibits but restricts their use to minimum. This paper aspires to create a reference repository of cloud free satellite images using data received from on board optical sensors of Indian Remote Sensing satellite. By treating the received data with radiometric and geometric correcting processes at various levels, clear images are generated to user environment for early detection of anomalies, mostly during the first level of processing itself. A reference repository will be created using radio-metric cloud free subsampled raw images of size 1K x1K, along with terrain classification tags. Despite, the reference repository framed can be used for developing reference based change algorithms and alerting data product generation system for scene specific corrections, radiometric imbalances, product quality degradation etc. The created reference repository in this paper contains abundant database with spatial data types, data structures and features. Also the sample is suitable for queries on geographic applications and may be utilized in clarifying knowledge-based queries, as a part of User Order Processing System (UOPS).. General Terms This paper can be classified under Remote Sensing and Digital Image Classification.

Six Sigma Application: An Order Management System

Order processing system is investigated using Six Sigma methodology to examine application of Six Sigma Methodology to a business problem that emerges with an Information Technology (IT) Solution as an appropriate alternative. This research was carried out to exhibit Six Sigma approach to business process problem solving. Sustainability in order processing was achieved through IT solutions till any major change comes in business process logic. After conducting this research project it was proved that problem solving techniques among six sigma and traditional IT solutions are somehow similar in temperament and can be used in collaboration for getting proper elucidations. In this paper the statistical tool used is Minitab.

Mapping Activity Diagram to Fuzzy GSPN

Non-functional requirements’ assessment of enterprise architecture in system development, is important for organizations, and makes them protected from additional costs. For this goal Organizations should model their data and processes. Nowadays UML is considered as the most important modeling language, but because it’s a semi-formal language, it’s not qualified for assessment the system, for this in order to evaluate system, UML should transfer to a formal language such as Petri nets. In this paper, a new approach for transforming UML activity diagram to a hybrid Petri net is proposed. This hybrid Petri net is a composition of generalized stochastic Petri nets and Fuzzy Petri nets. Here GSPN has been used to show the time of activity and use them in performance calculation and in order to show the uncertainty in the data and processes of an organization the fuzzy discussion is considered. By combination of FCPN and GSPN a new Petri net is proposed which is called fuzzy generalized stochastic Petri nets. An Order processing system is used to show the performance and the accuracy of the algorithm.

Adoption of web-based order-processing systems: experiences from tier-1 suppliers in the automotive supply chain

This research studies automobile industry suppliers in Thailand, who have implemented VMI using web-based order-processing technology. It examines their motivations and barriers for implementing the technology, and identifies the enabling factors with greatest impact on the outcomes of such implementation. Data was obtained from 70 tier-1 suppliers of the two biggest automobile assemblers in Thailand. Exploratory factor analysis was used to construct motivation, enabling factors, difficulties/barriers and outcomes of web-based order-processing technology implementation. Multiple linear regression was then used to examine the relationships between enabling factors and operational outcomes. The results show that improving customer responsiveness and the need to retain competitive advantage rather than cost-based orientation were the primary drivers of implementation of web-based order processing. This case provides insights to enable successful implementation by organisations that are planning to deploy the technology, particularly in the early stages of technological diffusion in emerging economies.

Effect of closed-loop order processing on the time to initial antimicrobial therapy

The results of a study comparing the average time to initiation of i.v. antimicrobial therapy with closed-versus open-loop order entry and processing are reported. A retrospective cohort study was performed to compare order-to-administration times for initial doses of i.v. antimicrobials before and after a closed-loop order-processing system including computerized prescriber order entry (CPOE) was implemented at a large medical center. A total of 741 i.v. antimicrobial administrations to adult patients during designated five-month preimplementation and postimplementation study periods were assessed. Drug-use reports generated by the pharmacy database were used to identify order-entry times, and medication administration records were reviewed to determine times of i.v. antimicrobial administration. The mean ± S.D. order-to-administration times before and after the implementation of the CPOE system and closed-loop order processing were 3.18 ± 2.60 and 2.00 ± 1.89 hours, respectively, a reduction of 1.18 hours (p < 0.0001). Closed-loop order processing was associated with significant reductions in the average time to initiation of i.v. therapy in all patient care areas evaluated (cardiology, general medicine, and oncology). The study results suggest that CPOE-based closed-loop order processing can play an important role in achieving compliance with current practice guidelines calling for increased efforts to ensure the prompt initiation of i.v. antimicrobials for severe infections (e.g., sepsis, meningitis). Implementation of a closed-loop order-processing system resulted in a significant decrease in order-to-administration times for i.v. antimicrobial therapy.

Self-regulating Message Throughput in Enterprise Messaging Servers – A Feedback Control Solution

Enterprise Messaging is a very popular message exchange concept in asynchronous distributed computing environments. The Enterprise Messaging Servers are heavily used in building business critical Enterprise applications such as Internet based Order processing systems, pricing distribution of B2B, geographically dispersed enterprise applications. It is always desirable that Messaging Servers exhibit high performance to meet the Service Level Agreements (SLAs). There are investigations in this area of managing the performance of the distributed computing systems in different ways such as the IT administrators configuring and tuning the Messaging Servers parameters, implement complex conditional programming to handle the workload dynamics. But in practice it is extremely difficult to handle such dynamics of changing workloads in order to meet the performance requirements. Additionally it is challenging to cater to the future resource requirements based on the future workloads. Though there have been attempts to self-regulate the performance of Enterprise Messaging Servers, there is a limited investigation done in exploring feedback control systems theory in managing the Messaging Servers performance. We propose an adaptive control based solution to not only manage the performance of the servers to meet SLAs but also to pro-actively self-regulate the performance such that the Messaging Servers are capable to meet the current and future workloads. We implemented and evaluated our solution and observed that the control theory based solution will improve the performance of Enterprise Messaging Servers significantly.