Effect of Inventory Management Activities on Retailers’ Satisfaction in Inyange Industries Limited in Gasabo District, Rwanda

This research examined the effect of inventory management activities on retailer satisfaction in manufacturing industries in Rwanda from the year of 2016 to 2021. The mixed approach of both qualitative and quantitative data were used as research design to collect results from 121 respondents from 174 who were expected as sample size of the study by the use of simple random and stratified sampling techniques. Before, the actual process of data collection the researcher pre-tested the questionnaire survey and the key informant interview, which were used later for collecting data from the field. Thus, the quantitative data were analyzed using both descriptive as percentage distribution and inferential statistics represented by multiple linear regressions. Thus, the regression coefficients demonstrated that ?1 =.241, with p=0.002 < 0.05 at sig. level of 5% which proves that IOP had a statistically positive and significant effect on the satisfaction of retailers; ?2 = .311 with p=0.001 < 0.05 at a sig. level of 5% implying that ISM had a positive and statistical significant effect on satisfaction of retailers; and ?1 = .402 with p= 0.000 < 0.05 at a sig. level of 5% implying that IDM had demonstrated a positive and statistical significant effect on retailers’ satisfaction in IIL between 2016 and 2021. The respective coefficients further indicate that 24.1 %, 31.1% and 40.2% of the variability in retailers’ satisfaction can be attributed to inventory order processing, inventory storage management and inventory distribution management respectively. The research recommends IIL to adopt JIT inventory practices all the time to avoid inventory costs while retailers need to accurately forecast demand and make orders before they experience stock-outs which affects the supply chain. It is hoped that this study will encourage IIL to sustainably adopt inventory management activities that will continue to sustain their retailer satisfaction. The study may also motivate other researchers to conduct research covering the whole country in order to improve its reliability. Keywords: Inventory Management Activities, Retailer Satisfaction, Manufacturing Industries, Rwanda

Effect of Inventory Management Activities on Retailers’ Satisfaction in Inyange Industries Limited in Gasabo District, Rwanda

This research examined the effect of inventory management activities on retailer satisfaction in manufacturing industries in Rwanda from the year of 2016 to 2021. The mixed approach of both qualitative and quantitative data were used as research design to collect results from 121 respondents from 174 who were expected as sample size of the study by the use of simple random and stratified sampling techniques. Before, the actual process of data collection the researcher pre-tested the questionnaire survey and the key informant interview, which were used later for collecting data from the field. Thus, the quantitative data were analyzed using both descriptive as percentage distribution and inferential statistics represented by multiple linear regressions. Thus, the regression coefficients demonstrated that ?1 =.241, with p=0.002 < 0.05 at sig. level of 5% which proves that IOP had a statistically positive and significant effect on the satisfaction of retailers; ?2 = .311 with p=0.001 < 0.05 at a sig. level of 5% implying that ISM had a positive and statistical significant effect on satisfaction of retailers; and ?1 = .402 with p= 0.000 < 0.05 at a sig. level of 5% implying that IDM had demonstrated a positive and statistical significant effect on retailers’ satisfaction in IIL between 2016 and 2021. The respective coefficients further indicate that 24.1 %, 31.1% and 40.2% of the variability in retailers’ satisfaction can be attributed to inventory order processing, inventory storage management and inventory distribution management respectively. The research recommends IIL to adopt JIT inventory practices all the time to avoid inventory costs while retailers need to accurately forecast demand and make orders before they experience stock-outs which affects the supply chain. It is hoped that this study will encourage IIL to sustainably adopt inventory management activities that will continue to sustain their retailer satisfaction. The study may also motivate other researchers to conduct research covering the whole country in order to improve its reliability. Keywords: Inventory Management Activities, Retailer Satisfaction, Manufacturing Industries, Rwanda

MACHINE LEARNING APPROACH FOR TENAGA NASIONAL BERHAD (TNB) OVERHEAD POWERLINE AND ELECTRICITY POLE INVENTORY USING MOBILE LASER SCANNING DATA

Electricity assets recognition and inventory is a fundamental task in the geospatial-based electrical power distribution management. In Malaysia, Tenaga Nasional Berhad (TNB) aims to complete their assets inventory throughout the country by 2022. Previous research has shown that a method for assets detection especially for TNB is still at an early stage, which mainly relied on manual extraction of the assets from different data sources including mobile laser scanner (MLS). This research aims at evaluating a geospatial method based on machine learning to classify the TNB assets using high density MLS data. The MLS data was collected using Riegl VMQ-1 HA scanner and supported by the base station and control points for point cloud registration purpose. In the first stage the point clouds were classified into ground and non-ground objects. The non-ground points were further classified into different landcover types i.e. vegetation, building, and other classes. The points classified as other classes were used for overhead powerline and electricity poles classification using random forest-based Machine Learning (ML) approach in LiDAR 360 software. Based on the classified point clouds, detailed characteristics of electricity poles (i.e. number of poles, height, diameter and inclination from ground) and overhead powerlines (number of cable segments) were estimated. This information was validated using field collected reference data. The results show that the detection accuracy for electricity poles and overhead power line are 65% and 63% respectively. The estimation of length, diameter and height of the spun pole from point clouds has produced Root Mean Square Error (RMSE) value of 0.081cm, 0.263 cm and 0.372 cm respectively. Meanwhile for the concrete pole, the length, diameter and height has been successfully estimated with the value of RMSE of 0.034 cm, 0.029 cm and 0.331 cm respectively. The length of overhead powerline was estimated with 59.02 cm RMSE. In conclusion, the MLS data had show promising results for a semi-automatic detection and characterization of TNB overhead powerlines and poles in the sub-urban area. Such outcome can be used to support the inventory and maintenance process of the TNB assets.

Design of Prototype Information System for Tracking & Tracing Fish Distribution Based on Mobile Agent

The National Fish Logistics System or often called SLIN is an Indonesian Ministry of Maritime Affairs and Fisheries program that aims to maintain the stability of the production and marketing systems and control the disparity in national fish prices. Central Sulawesi is the Province that becomes the main corridor of this program. The inefficient distribution monitoring process generally causes several problems in the field of fisheries distribution management that still often occur today by the regional Ministry of Maritime Affairs and Fisheries. It indicates that SLIN is not yet running optimally. This study purpose a prototype design of fish distribution tracking based on a mobile agent that can use to help consumers to track distribution channels and get information about the origin of the fish to be purchased. The data will further process for monitoring fish distribution in a real-time manner by the regional Ministry of Maritime Affairs and Fisheries. A proper monitoring mechanism will undoubtedly help the government in making policies and conducting supervision to make the SLIN implementation successful in Central Sulawesi. By the research, we found that the proposed method can gather data from every level fish distribution agent then processed the data to inform about distribution line and the origin of the fish for the consumer. The proposed solution framework could be implemented and nearly fit with current implementation criteria. The framework later can be a base framework for developing a more advanced information system for SLIN in Central Sulawesi Region.

THE DECADES OF RESEARCH ON SCM AND ITS ADVANCEMENTS: COMPREHENSIVE FRAMEWORK

Supply Chain Management (SCM), a corporate strategy approach to materials and distribution management, has been evolving over the last decades from traditional marketing and production functions. The purpose of the study is to explore the bibliometric data of Supply Chain Management and its advancements. Besides, it describes from the origins of traditional SCM to the progress of modern SCM 4.0, with reference to the benefits, function, importance and limitations of all five branches of SCM. The methodology includes a detailed and systematic review of scientific articles published in Scopus indexed journals. The data were obtained from the Scopus database between 1990 and 2021 in order to achieve the study’s desired outcome. Boolean operators and filtering were applied to obtain relevant data. In addition, VOSviewer software is used to visually classify and analyse bibliometric data distribution and network using cluster maps. The study’s findings were divided into three main categories: publication period, coauthorship and citations, with the results demonstrating the diverse needs of SCM in the globalised digital era. Further, the results emphasise that SCM and its advancements have unique merits around the world, but Sustainable SCM and SCM 4.0 remain the most popular as they play a vital role in changing environmental concerns. In addition, the findings reveal that the visualization networks of each category exhibit the strengths and connections of publications. These visualization networks, followed by their analysis, explain the new insight to the present research. This research also paves the way for future research into the evolving trends of SCM in today’s technologically advanced world.

Application of Visual Sensing Image Processing Technology under Digital Twins to the Intelligent Logistics System

Since the founding of the People’s Republic of China, the advantages of logistics are neglected, and the scale operation and the welfare in the industry are difficult to achieve due to the influence of the economic system and social environment. Therefore, a new intelligent logistics distribution management system based on machine vision and visual sensor image processing technology is constructed to respond to the shortcomings of the traditional system, including slow efficiency, huge cost, complex data, and low degree of informatization. Through the analysis and research on the visual sensor image processing technology and the order processing, receipt management, distribution management, scheduling management, and return management that affect logistics distribution, a simulation experiment is used to verify that the visual sensor image processing technology is rigorous, intelligent, and efficient and has high precision. The intelligent logistics distribution management system can effectively solve the problems existing in the traditional logistics distribution management. The experimental results show that the visual sensor image processing technology can collect and analyze the target image and effectively track and monitor it in the logistics distribution process. The average distribution precision of the intelligent logistics distribution management system reaches more than 99.5%, which is greatly improved compared with 90% of the traditional logistics distribution. And it can greatly improve the distribution efficiency, which increases by about 26.5%. The study realizes the information management of the logistics system and automatically completes all the work according to the designed program, so that the real-time dynamic distribution can be transmitted to the urban logistics distribution at any time.