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

Optimal Order Batching in Warehouse Management: A Data-Driven Robust Approach

Optimizing warehouse processes has direct impact on supply chain responsiveness, timely order fulfillment, and customer satisfaction. In this work, we focus on the picking process in warehouse management and study it from a data perspective. Using historical data from an industrial partner, we introduce, model, and study the robust order batching problem (ROBP) that groups orders into batches to minimize total order processing time accounting for uncertainty caused by system congestion and human behavior. We provide a generalizable, data-driven approach that overcomes warehouse-specific assumptions characterizing most of the work in the literature. We analyze historical data to understand the processes in the warehouse, to predict processing times, and to improve order processing. We introduce the ROBP and develop an efficient learning-based branch-and-price algorithm based on simultaneous column and row generation, embedded with alternative prediction models such as linear regression and random forest that predict processing time of a batch. We conduct extensive computational experiments to test the performance of the proposed approach and to derive managerial insights based on real data. The data-driven prescriptive analytics tool we propose achieves savings of seven to eight minutes per order, which translates into a 14.8% increase in daily picking operations capacity of the warehouse.

Integrated zone picking and vehicle routing operations with restricted intermediate storage

The competitiveness of a retailer is highly dependent on an efficient distribution system. This is especially true for the supply of stores from distribution centers. Stores ask for high flexibility when it comes to their supply. This means that fast order processing is essential. Order processing affects different subsystems at the distribution center: orders are picked in multiple picking zones, transferred to intermediate storage, and delivered via dedicated tours. These processing steps are highly interdependent. The schedule for picking needs to be synchronized with the routing decisions to ensure availability of orders at the DC’s loading docks when their associated tours are scheduled. Concurrently, intermediate storage represents a bottleneck as capacity for order storage is limited. The simultaneous planning of picking and routing operations with restricted intermediate storage is therefore relevant for retail practice but has not so far been considered within an integrated planning approach. Our work addresses this task and discusses an integrated zone picking and vehicle routing problem with restricted intermediate storage. We present a comprehensive model formulation and introduce a general variable neighborhood search for simultaneous consideration of the given planning stages. We also present two alternative sequential approaches that are motivated by the prevailing planning situation in industry. Numerical experiments and a case study show the need for an integrated planning approach to obtain practicable results. Further, we identify the impact of the main problem characteristics on overall planning and provide valuable insights for the application of these findings in industry.

Distinct higher-order representations of natural sounds in human and ferret auditory cortex

Little is known about how neural representations of natural sounds differ across species. For example, speech and music play a unique role in human hearing, yet it is unclear how auditory representations of speech and music differ between humans and other animals. Using functional ultrasound imaging, we measured responses in ferrets to a set of natural and spectrotemporally matched synthetic sounds previously tested in humans. Ferrets showed similar lower-level frequency and modulation tuning to that observed in humans. But while humans showed substantially larger responses to natural vs. synthetic speech and music in non-primary regions, ferret responses to natural and synthetic sounds were closely matched throughout primary and non-primary auditory cortex, even when tested with ferret vocalizations. This finding reveals that auditory representations in humans and ferrets diverge sharply at late stages of cortical processing, potentially driven by higher-order processing demands in speech and music.

Common and distinct predictors of non-symbolic and symbolic ordinal number processing across the early primary school years

What are the cognitive mechanisms supporting non-symbolic and symbolic order processing? Preliminary evidence suggests that non-symbolic and symbolic order processing are partly distinct constructs. The precise mechanisms supporting these skills, however, are still unclear. Moreover, predictive patterns may undergo dynamic developmental changes during the first years of formal schooling. This study investigates the contribution of theoretically relevant constructs (non-symbolic and symbolic magnitude comparison, counting and storage and manipulation components of verbal and visuo-spatial working memory) to performance and developmental change in non-symbolic and symbolic numerical order processing. We followed 157 children longitudinally from Grade 1 to 3. In the order judgement tasks, children decided whether or not triplets of dots or digits were arranged in numerically ascending order. Non-symbolic magnitude comparison and visuo-spatial manipulation were significant predictors of initial performance in both non-symbolic and symbolic ordering. In line with our expectations, counting skills contributed additional variance to the prediction of symbolic, but not of non-symbolic ordering. Developmental change in ordering performance from Grade 1 to 2 was predicted by symbolic comparison skills and visuo-spatial manipulation. None of the predictors explained variance in developmental change from Grade 2 to 3. Taken together, the present results provide robust evidence for a general involvement of pair-wise magnitude comparison and visuo-spatial manipulation in numerical ordering, irrespective of the number format. Importantly, counting-based mechanisms appear to be a unique predictor of symbolic ordering. We thus conclude that there is only a partial overlap of the cognitive mechanisms underlying non-symbolic and symbolic order processing.

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.