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

Il simbolico e la via del movimento delle donne

Symbolic politics has been one of the key phrases in Italian feminism since the 1970s. This text describes the historical origins and significance of this concept together with the difference in the use of the symbolic dimension in traditional male politics. The most important difference is that female politics are born from living and affective relations which cannot be permanently established and rotate around non-formalized procedural practices. The sense that emerges is felt during the actual process and the symbolic is therefore experienced and transformed from the inside with the authority that comes from these practices, which influence and modify each other due to their closeness. They spread by proximity.

Deviation Detection in Clinical Pathways Based on Business Alignment

Several unexpected behaviors may occur during actual treatment of clinical pathways, which will have negative impact on the implementation and the future work. To increase the performance of current deviation detection algorithms, a method is presented according to business alignment, which can effectively detect the anomaly in the implementation of the clinical pathways, provide judgment basis for the intervention in the process of the clinical pathway implementation, and play a crucial role in improving the clinical pathways. Firstly, the noise in diagnosis and treatment logs of clinical pathways will be removed. Then, the synchronous composition model is constructed to embody the deviations between the actual process and the theoretical model. Finally, A ∗ algorithm is selected to search for optimal alignment. A clinical pathway for ST-Elevation Myocardial Infarction (STEMI) under COVID-19 is used as a case study, and the superiority and effectiveness of this method in deviation detection are illustrated in the result of experiments.

The effectiveness of e-entrepreneurship training programs in the emerging markets (GCC)

The study aimed to examine the effectiveness of e-entrepreneurship training programs (EETP) content (curriculum), EETP period, EETP trainers (instructors – individual mentor’s role) and EETP candidates’ input (involvement and contribution)) in the higher educational institutions (HEI) in the emerging markets (EM) particularly in the Gulf Countries Council (GCC). The survey instrument was pre-tested to establish its validity and reliability and the quantitative statistical data that emerged from the administration of the survey were analyzed using t-tests, factor analysis, and analysis of variance and correlations (ANOVA). the study concluded that the curriculum defines the experiences presented to the learner, hence the great influence on curriculum effectiveness. Instructors also are the actual implementers of the curriculum. Additionally, they guide students in the actual process. Their role reflects their influence on the effectiveness of EETP.

Hybrid modeling method of dust suppression efficiency for dry fog dust suppression process

The original mechanism model of dust suppression efficiency for dry fog dust suppression could not guide the actual process. In order to accurately predict the dust suppression efficiency in the process, a new mechanism model was established by my analysis of the process. But there were some factors that I could not establish the model. So a hybrid model combining mechanism model and support vector machine (SVM) was proposed. Using the data of dry fog dust suppression oval process, the hybrid model was simulated. The simulation results show that the hybrid model can accurately predict the dry fog dust suppression.

USE OF THE BMP SYSTEM FOR BLOCKING OF DANGEROUS ENERGIES DURING REALIZATION OF WORKS FROM REPAIR AND MAINTENANCE OF TECHNIQUE

Creating healthy and safe working conditions is the main task of the employer when performing high-risk work. Practice shows that the cause of accidents during the repair and maintenance of equipment are uncoordinated and erroneous actions of staff, resulting in incorrect supply of hazardous energy to the installation where people work. In order to prevent injuries at metallurgical enterprises there is a need to revise and modernize the existing approach to control the supply of hazardous energy during repairs, improve the current labeling system of access to repairs of technological equipment based on the experience of advanced world technologies. Audit). The BMP system is used to perform maintenance and repair of equipment, as well as any other cases where personnel need to enter the danger zone, and includes not only the actual process of blocking and marking, but also all other activities: documentation, organization of storage and issuance of BMP devices, training and testing of personnel knowledge According to the analysis, the current tag system at the metallurgical enterprises of Ukraine is inferior in efficiency to the BMP system, which allows you to almost completely eliminate the risks associated with the human factor in the repair and maintenance of equipment. The foreign experience of using hazardous energy blocking and labeling systems and the existing legal framework on this issue in Ukraine are analyzed. According to the results of research, the basic principles of using the BMP system at the enterprises of the metallurgical industry are established. The sequence of BMP procedure implementation is offered. The information on the basis of which the BMP map is formed is considered in detail. An important stage in the formation of this map is the assessment of industrial risks of exposure to hazardous energies in the process of repair and maintenance of equipment. The direction of further research on the implementation of the BMP system and the legalization of the BMP standard at the state level is substantiated.

Trajectory Track for the Landing of Carrier Aircraft with the Forecast on the Aircraft Carrier Deck Motion

The paper presents a prediction method of deck lateral-directional motion for the control of landing trajectory of aircraft. Firstly, through the analysis of the process of aircraft returning to the ship, the modeling of the motion has been built. Secondly, in view of the delay of trajectory tracking captured in the actual process of aircraft landing on the ship, the error caused by the carrier motion signal has been analyzed. Based on the simulation results, the recommended prediction time of carrier motion has been proposed.

Mathematical simulation analysis of optimal detection of shot-putters’ best path

In order to consider many uncertain factors in the process of shot-put, a fuzzy optimisation model of shot-put is proposed. With the help of fuzzy anthropometric data and strength data, the model calculates the fuzzy solution set of the athlete's best throwing mode and throwing distance with a known probability distribution, which reflects the actual process of shot throwing better than the non-fuzzy optimisation model. Then, using MATLAB6 software, the program design of the model solving and the user interface of optimisation software are developed, which realises fast calculation and good user interaction function. Finally, the actual measurement data of university shot-putters are used to verify the feasibility and effectiveness of the fuzzy optimisation model.

An optimized PSO-ANN model for improved prediction of water treatment desalination plant performance

An accurate prediction of the performance of water treatment desalination plants could directly improve the global socio-economic balance. In this regard, many researchers have been engaged in the various artificial intelligence applied soft computing techniques to predict actual process outcomes. Inspired by the significance of such techniques, an optimized Particle Swarm Optimization based Artificial Neural Network (PSO-ANN) technique has been proposed herewith to predict an accurate performance of the reverse osmosis (RO) based water treatment desalination plants. Literature suggests that the improvements of the soft computing models depend on their modeling parameters. Therefore, we have included an extended list of nine modeling parameters with a systematic indepth investigation to explore their optimal values. Finally, the model's simulations results (R2 = 99.1%, Error = 0.006) were found superior than the existing ANN models (R2 = 98.8%, Error = 0.060), with the same experimental datasets. Additionally, the simulation results recommend that among many parameters considered, the number of hidden layer nodes (n), swarm sizes (SS), and the weight of inertia (ω) play a major role in the model optimization. This study for a more accurate prediction of the plant's performance shall pave the way for the process design and control engineers to improve the plant efficiency further.