Logistic Process Research Articles

The nexus between digital financial knowledge and financial inclusion: digital financial attitudes and behaviour as mediators enhancing financial inclusion

Purpose The purpose of this study is to measure financial inclusion (FI) and to examine the role of digital financial literacy (DFL) and its components, and various socio-demographics in relation to FI. In addition, the mediating effect of digital financial attitudes (DFA) on the relationship between digital financial knowledge (DFK) and digital financial behaviour (DFB), as well mediating effect of DFA and DFB on the relationship between DFK and FI, is being explored.Design/methodology/approach Using a cross-sectional research design, we utilize a dataset from the survey of adults’ financial literacy in Bosnia and Herzegovina, collected from the representative sample of 1,096 adults in 2022. The main methodology relies on logistic and ordinal logistic regression analyses and PROCESS for mediation analyses.Findings The findings suggest that the effect of DFK on DFB is partially mediated by DFA. In addition, the effect of DFK on FI is fully mediated through three pathways: DFA, DFB, and DFA and DFB in serial mediation. Age, education, employment status and residence are significantly related to FI. Internet access is significant only for FI scores but not for adults’ banking status. Although women are almost twice as unbanked as men, we find no gender-based differences in financial product holdings, FI or adults’ banking status.Practical implications There is a need to enhance DFK and DFA to enable adults to use financial products. Financial institutions could use our results in designing and promoting their services.Social implications Policy implications are seen in the need for developing national strategies for financial education, with an emphasis on strengthening DFL, especially DFK and DFA, which will enhance the formal FI of adults. Also, governments should work on expanding Internet access.Originality/value The results make a contribution to the theory of planned behaviour. They contribute to the limited empirical evidence of the mediating role of DFA in relationship to DFB, as well as the mediating role of DFA and DFB in relationship to FI.

Supply Chain Management Construction: The Role of IoT in Human Resource Management and Green Logistics

Environmental practices are incorporated into the supply chain management and logistic process of human resource management. It is referred to as a green logistics supply chain. To reduce the negative effects of logistical activities on the environment, sustainable transportation, eco-friendly packaging, and effective waste management techniques are used. Adopting environmentally conscious supply chain practices can improve a company's environmental reputation while lowering carbon emissions, increasing operational effectiveness, and saving money on human resource management. In order to adopt sustainable practices across every aspect of the value chain, from acquiring raw materials to delivering completed items to clients, this strategy necessitates coordination across stakeholders in the supply chain management and logistic process. In general, using a green logistic supply chain is a crucial approach for companies looking to grow sustainability while reducing their environmental impact. Using IoT in human resource management can boost operational effectiveness, cut down on transportation expenses, and boost customer satisfaction. For instance, current information on inventory levels, the quality of goods, and shipment status can be provided by smart sensors and devices, allowing businesses to optimize the way they manage their supply chains and reduce waste in human resource management.

An integrated method to identify and improve logistical gaps

ABSTRACT This paper reviews the critical elements of the SCOR model and its applications in solving logistical problems. It also discusses the theoretical approach to BSC concepts and the analysis of the tactical scenario and a company’s restrictions. The study is inductive, validating theoretical aspects that can be generalised through empirical testing. The proposed methodology integrates the BSC and SCOR models, aligning operational and strategic indicators, to performance measurement and achieving profitability objectives. The model integrated suppliers, improving inventory management and productivity, and its structure is defined from the company’s main decisions related to supply chain processes. The SCOR and Balanced Scorecard models were tested in a logistic process in a hardware store, with no known background in the literature on its application in this industry. These two models were integrated into a unified tool, with an indicator dashboard as an output, to support decision-making at both strategic and operational (logistics) levels.

Quasi-stationary distribution for continuous-state branching processes with competition

We study quasi-stationary distribution of the continuous-state branching process with competition introduced by Berestycki et al. (2018). This process is defined as the unique strong solution to a stochastic integral equation with jumps. An important example is the logistic branching process proposed by Lambert (2005). We establish the strong Feller property, trajectory Feller property, Lyapunov condition, weak Feller property and irreducibility, respectively. These properties together allow us to prove that if the competition is strong enough near +∞, then there is a unique quasi-stationary distribution, which attracts all initial distributions with exponential rates.

Effect of green technology for a production system through a reverse logistic process

In modern times, customers are increasingly aware of the environmental risks posed by the premature expiration of smart products. To safeguard the environment, companies have embraced green technology when procuring products. As a result, it is challenging for business managers to capture the market by offering the best quality products at a reasonable price, regardless of the economic situation. This paper presents a production model incorporating reverse logistics to identify defective products. The model involves learning through production and utilizes green technologies. Additionally, a portion of the assembled products is remanufactured after being received from consumers. The remanufactured items are screened and distributed to markets. Both new and remanufactured products are sold to the market based on their quality in the first and second markets, respectively. To reduce product spoilage, manufacturers employ green technology like liquid cooling technology. The numerical results demonstrate that by investing in liquid cooling technology, the production store can reduce spoilage items by 8.50%, a positive environmental outcome regarding waste reduction, and due to the learning effect, the total cost can decrease by 1.44%. The paper includes numerical and sensitivity analyses accompanied by graphs.

Analysis of Central Warehouse Location and Logistics Distribution Land and Sea Modes

Distribution Center Warehouse has a very important role in logistics process and selecting the most strategic location is a must. Strategic location in Bali Province will give certain advantage to logistics company with travelling time as a point of view. Industrial Revolution 4.0 enable us finding such location with the help of computer simulation software such as AnyLogic. This research use AnyLogic capability to compare travelling time for 2 case of Distribution Center Warehouse: Mangupura and Negara. This comparison takes into account logistic process of delivering goods to Bali Province via sea transport (Gilimanuk Port). Result shows that Distribution Center Warehouse in Negara has an advantage compare to Mangupura in term of travelling time.

A systematic approach to the supply of non-metallic construction materials on river transportation

n the presented study, the process of extraction and supply of non-metallic building materials on river transport is described from a systematic point of view. In the course of the study, functional and organizational models of a generalized river transport enterprise were developed for the system of extraction and supply of non-metallic building materials, as well as several organizational models of the following functional subsystems included in it: pre-production, extraction and production of non-metallic building materials, supply management, planning, logistics. Special attention is paid to the study of the pre-production stage of the logistic process of extraction and production of these materials. A systematic approach has made it possible to show that currently the weakest link in the supply of non-metallic building materials by river transport is the backward technical base of production and transshipment of non-metallic building materials. This is due to the fact that the modernization of mining equipment is hampered, on the one hand, by the practical absence of its production by domestic enterprises, and, on the other hand, by sanctions restrictions on foreign supplies. This affects the cost and quality of non-metallic construction materials supplied; environmental processes accompanying the extraction process. Additionally, the weak development of digital technologies in interaction with customers has an impact on supply management in general, and the lack of a scientifically based inventory management system in the process of year-round production and supply affects the level of service and cost of supplies.

IMPROVING A CIRCULAR REVERSE LOGISTICS TO HANDLE PRODUCT RETURN: INSIGHTS FROM A GLOBAL ELECTRONICS SERVICES PROVIDER

In the retail industry, consumers often return goods for various reasons, including damage, flaws, or plain dissatisfaction. The storing of returned goods can result in insufficient arrangement of the existing storage space and capacity. Such issue can cause problems like longer processing times, higher operating costs, and reduced customer satisfaction, hence necessitating prompt response. Therefore, this case study was conducted in a global electronics services provider to examine how circular reverse logistics can enhance the handling of product returns as well as developing a smart product return strategy. It is believed that creating a plan for product returns and integrating internal process improvements with external collaboration are highly important. The results showed that the organisation can establish a circular reverse logistic process to lower the cost and amount of product returns, enhance consumer service, and boost profitability. Such findings can benefit organisations wishing to establish circular reverse logistics procedures to handle product returns.

Surface sanitation as a recommended treatment for preventing fungal infection and extending the shelf life of watermelon

Watermelon ranks fifth in Malaysian fruit production after coconut, durian, banana and pineapple. Its export value has increased significantly at 6.2%, from 60 thousand MT (2018) to 64 thousand MT. Losses happen throughout the supply chain, especially during the production and logistic process. The watermelon supply chain involves one- or twotier supply chain, which comprises movement from producers, wholesalers, retailers and final users. A preliminary survey had been conducted to estimate the postharvest losses percentage along the supply chain. The total postharvest loss for watermelon in Malaysia was high at 33%, with losses at the collection centre accumulating the highest percentage (56%). This high loss needs to be addressed as it will affect the farmers’ income and lead to an increase in food waste in the agriculture sector. A study on sanitation treatment to reduce fungal infection and extend the shelf life of watermelon was conducted. Sanitation treatments consisted of dipping the watermelon fruit in water treated with 250 ppm sodium hypochlorite for 30 seconds (Treatment 1) and spraying the peduncle with 250 ppm propiconazole fungicide (Treatment 2). Unsanitized fruit was set as control (Treatment 3). Results showed that sanitized watermelon samples (dipped in sodium hypochlorite or sprayed with propiconazole) rated acceptable until four weeks of storage at the ambient temperature of 27°C. Unsanitized fruit was infected with mould and thus rated as poor. Biochemical properties were not affected by sanitation treatment. In conclusion, sanitation using 250 ppm sodium hypochlorite or 250 ppm propiconazole helps slow down the fungal infection and extends the shelf life of watermelon fruit up to four weeks. This sanitation treatment is recommended to be included in the watermelon postharvest handling procedure to maintain good quality, reduce losses and expand the market for domestic and export.

Tree-informed Bayesian multi-source domain adaptation: cross-population probabilistic cause-of-death assignment using verbal autopsy.

Determining causes of deaths (CODs) occurred outside of civil registration and vital statistics systems is challenging. A technique called verbal autopsy (VA) is widely adopted to gather information on deaths in practice. A VA consists of interviewing relatives of a deceased person about symptoms of the deceased in the period leading to the death, often resulting in multivariate binary responses. While statistical methods have been devised for estimating the cause-specific mortality fractions (CSMFs) for a study population, continued expansion of VA to new populations (or "domains") necessitates approaches that recognize between-domain differences while capitalizing on potential similarities. In this article, we propose such a domain-adaptive method that integrates external between-domain similarity information encoded by a prespecified rooted weighted tree. Given a cause, we use latent class models to characterize the conditional distributions of the responses that may vary by domain. We specify a logistic stick-breaking Gaussian diffusion process prior along the tree for class mixing weights with node-specific spike-and-slab priors to pool information between the domains in a data-driven way. The posterior inference is conducted via a scalable variational Bayes algorithm. Simulation studies show that the domain adaptation enabled by the proposed method improves CSMF estimation and individual COD assignment. We also illustrate and evaluate the method using a validation dataset. The article concludes with a discussion of limitations and future directions.

Development of Intellectual Decision Making System for Logistic Business Process Management

Development of Intellectual Decision Making System for Logistic Business Process Management

Logistics-based design of collection system for asbeston-containing roof structures

Asbestos-containing roofing materials are an increasing hazard, which justifies their replacement by environmentally friendly roofing materials. Replacements can be carried out on an individual initiative basis, but a coordinated, systemic replacement will have a more significant impact. In order for such systemic asbestos removal to be successful from economics and logistics point of view, it is necessary to plan the associated logistics processes, as asbestos removal generates a significant transportation demand due to the large amount of waste generated. In the framework of this paper, the author presents an algorithm to plan the logistic process of centralized asbestos removal. A simple calculation method is presented to determine the cost of collection.

MODIFIED GENETIC ALGORITHM APPROACH FOR SOLVING THE TWO-STAGE LOCATION PROBLEM

Context. Optimization of logistics processes is one of the important tasks of supply chain management in various fields, including medicine. Effective coordination in medical logistics is essential to ensure public health and prosperity. This is especially essential during global emergencies when the rapid and efficient distribution of medicines is critical. In addition, professional logistics management is critical to delivering humanitarian aid, where the timely transportation of medical supplies and resources can be lifesaving. The most advanced technologies and algorithms are being used to improve medical logistics processes. This paper considers modifying the genetic algorithm for solving the two-stage location problem in supply chain management in the distribution of medicines and medical equipment.
 Objective. The work aims to build a model and develop an algorithm for solving a two-stage location problem in the context of the medical logistics problem with further analysis of their applications and performance.
 Method. We propose to use a genetic algorithm to solve a two-stage logistics problem. The peculiarities of this algorithm are the modification of evaluation procedures and the use of mixed mutation, which allows for solving the problem effectively, considering irregularities in the statement regarding the subject – the limits on the centers’ location at several stages of the logistic process.
 Results. The paper deals with a two-stage location problem with constraints on the maximum number of centers. Considering the specific requirements of medical logistics in the transportation context of medicines and medical equipment, a mathematical model and modification of the genetic algorithm are proposed. The developed algorithm is tested on model tasks and can produce effective solutions for problems ranging in size from 25 to 1000. The solution process takes longer for larger problems with dimensions from 1001 to 2035. Additionally, the influence of increasing the maximum generations number on the time of execution is investigated. When the maximum generation value increases from 50 to 100 and from 100 to 150 generations, the algorithm’s execution time increases by 45.69% and 51.68%, respectively. 73% of the total execution time is dedicated to the evaluation procedure. The algorithm is applied to the medical logistics problem in the Dnipropetrovsk region (Ukraine). An efficient solution is obtained within an acceptable execution time.
 Conclusions. A mathematical model for a two-stage location problem in the context of medical logistics is introduced. It considers the peculiarities of the medical field. A solution algorithm based on a genetic approach is developed and applied to the medical logistics problem. The algorithm has been tested on model tasks of varying sizes, with a comprehensive analysis conducted on the correlation between the problem size and the algorithm’s running time. In addition, it is investigated how the maximum number of generations affects the algorithm’s execution time. The role of each stage in the genetic algorithm research towards the overall effectiveness of the algorithm is researched. The obtained results indicate high efficiency and wide application possibilities of the proposed mathematical model and algorithm. The developed method demonstrates high performance and reliability.

Unsupervised segmentation and clustering time series approach to Southern Africa rainfall regime changes

AbstractAnalysis of hydro‐climatological time series and spatiotemporal dynamics of meteorological variables has become critical in the context of climate change, especially in Southern African countries where rain‐fed agriculture is predominant. In this work, we compared modern unsupervised time series and segmentation approaches and commonly used time series models to analyse rainfall regime changes in the coastal, sub‐humid and semi‐arid regions of Southern Africa. Rainfall regimes change modelling and prediction inform farming strategies especially when choosing measures for mixed crop–livestock farming systems, as farmers can decide to do rainwater harvesting and moisture conservation or supplementary irrigation if water resources are available. The main goal of this study was to predict/identify rainfall cluster trends over time using regression with hidden logistic process (RHLP) or hidden Markov model regression (HMMR) supplemented by autoregressive integrated moving average (ARIMA) and Facebook Prophet models. Historical time series rainfall data was sourced from meteorological services departments for selected site over an average period of 55 years. Commonly used approaches forecasted an upward rainfall trend in the coastal and sub‐humid regions and a declining trend in semi‐arid areas with high variability between and within seasons. For all sites, Ljung‐Box Test Statistics suggested the existence of autocorrelation in rainfall time series data. Prediction capabilities were investigated using the root mean square error (RMSE), mean absolute error (MAE) and mean absolute percentage error (MAPE) which indicated not much difference between ARIMA and Facebook Prophet models. RHLP and HMMR offered a unique clustering and segmentation approach examining between and within‐season rainfall variability. A maximum of 20 unique rainfall clusters with similar trend characteristics were determined as going beyond this brought non‐significant difference to regime changes. A clear trend was exhibited from 1980 going backwards as compared to recent years signifying how unpredictable is rainfall in Southern Africa. The unsupervised approaches predicted a clear cluster trend in coastal than in sub‐humid and semi‐arid and the performance was assessed using Akaike information criteria and log‐likelihood which showed improvement in prediction power as the number of segmentation clusters approaches 20.

Retail robots as sales assistants: how speciesism moderates the effect of robot intelligence on customer perceptions and behaviour

PurposeRetailers increasingly endeavour to implement artificial intelligence (AI) innovations, such as humanoid social robots (HSRs), to enhance customer experience. This paper investigates the interactive effect of HSR intelligence and consumers' speciesism on their perceptions of retail robots as sales assistants.Design/methodology/approachThree online experiments testing the effects of HSRs' intellectual intelligence on individuals' perceived competence and, consequently, their decision to shop at a retail store that uses HSRs as sales assistants are reported. Furthermore, the authors examine whether speciesism attenuates these effects such that a mediation effect is likely to be observed for individuals low in speciesism but not for those with high levels of speciesism. Data for all studies were collected on Prolific and analysed with SPSS to perform a logistic regression and PROCESS 4.0 (Hayes, 2022) for the mediation and moderated-mediation analysis.FindingsThe findings show that the level of speciesism moderates the relationship between HSR intellectual intelligence and perceived competence such that an effect is found for low but not for high HSR intelligence. When HSR intellectual intelligence is low, individuals with higher levels of speciesism (vs low) rate the HSR as less competent and display lower HSR acceptance (i.e. customers' decision to shop using retail robots as sales assistants).Originality/valueThis research responds to calls in research to adopt a human-like perspective to understand the compatibility between humans and robots and determine how personality traits, such as a person's level of speciesism, may affect the acceptance of AI technologies replicating human characteristics (Schmitt, 2019). To the best of the authors' knowledge, the present research is the first to examine the moderating role of speciesism on customer perceptions of non-human retail assistants (i.e. human-like and intelligent service robots). This study is the first to showcase that speciesism, normally considered a negative social behaviour, can positively influence individuals' decisions to engage with HSRs.

The relationship between depressive mood and non-suicidal self-injury among secondary vocational school students: the moderating role of borderline personality disorder tendencies.

Non-suicidal self-injury (NSSI) has become an important public health issue of global concern, often occurring in adolescents, and depressive mood is closely related to NSSI. In addition, NSSI is considered a symptom of borderline personality disorder. It has been found that adolescents in secondary vocational schools are more vulnerable to behavior and emotional disorders than those in general high schools. This study investigated the risk factors associated with NSSI affecting secondary vocational school students and analyzed the role of borderline personality disorder tendencies in promoting the occurrence of NSSI among students with depressive moods. A total of 1,848 Chinese secondary vocational students completed a self-report questionnaire. The homemade NSSI behavior questionnaire, Patient Health Questionnaire-9 and Personality Diagnostic Questionnaire-4 were used in this survey. Binary logistic regression and PROCESS software analysis were used to explore the influencing factors associated with NSSI and to test for moderating effects. Female (OR = 3.412, 95% CI 2.301-5.060), drinking history (OR = 2.007, 95% CI 1.383-2.911), history of suicidal death exposure (OR = 3.161, 95% CI 1.999-4.999), depressive mood (OR = 2.436, 95% CI 1.668-3.558) and borderline personality disorder tendencies (OR = 2.558, 95% CI = 1.764-3.711) were independent risk factors for NSSI. Borderline personality disorder tendencies (B = 0.047, p = 0.000) moderated the relationship between depressive mood and NSSI. The stronger the borderline personality tendencies, the more NSSI behavior occurred when they were depressive. Borderline personality disorder tendencies in secondary vocational school adolescents significantly enhance the association of depressive mood with NSSI. There is a moderating role for borderline personality disorder tendencies in depressive mood and NSSI.

A new approach to sustainable logistic processes with q-rung orthopair fuzzy soft information aggregation.

In recent years, as corporate consciousness of environmental preservation and sustainable growth has increased, the importance of sustainability marketing in the logistic process has grown. Both academics and business have increased their focus on sustainable logistics procedures. As the body of literature expands, expanding the field's knowledge requires establishing new avenues by analyzing past research critically and identifying future prospects. The concept of "q-rung orthopair fuzzy soft set" (q-ROFSS) is a new hybrid model of a q-rung orthopair fuzzy set (q-ROFS) and soft set (SS). A q-ROFSS is a novel approach to address uncertain information in terms of generalized membership grades in a broader space. The basic alluring characteristic of q-ROFS is that they provide a broader space for membership and non-membership grades whereas SS is a robust approach to address uncertain information. These models play a vital role in various fields such as decision analysis, information analysis, computational intelligence, and artificial intelligence. The main objective of this article is to construct new aggregation operators (AOs) named "q-rung orthopair fuzzy soft prioritized weighted averaging" (q-ROFSPWA) operator and "q-rung orthopair fuzzy soft prioritized weighted geometric" (q-ROFSPWG) operator for the fusion of a group of q-rung orthopair fuzzy soft numbers and to tackle complexities and difficulties in existing operators. These AOs provide more effective information fusion tools for uncertain multi-attribute decision-making problems. Additionally, it was shown that the proposed AOs have a higher power of discriminating and are less sensitive to noise when it comes to evaluating the performances of sustainable logistic providers.

TAPHONOMIC INDICATORS OF DEAD OCEAN QUAHOG (ARCTICA ISLANDICA) SHELL AGE IN THE DEATH ASSEMBLAGE OF THE MID-ATLANTIC BIGHT CONTINENTAL SHELF

ABSTRACT Taphonomic indicators are often used to assess time-since-death of skeletal remains. These indicators frequently have limited accuracy, resulting in the reliance of other methodologies to age remains. Arctica islandica, commonly known as the ocean quahog, is a relatively widespread bivalve in the North Atlantic, with an extended lifespan that often exceeds two hundred years; hence, their shells are often studied to evaluate climate change over time. This report evaluates taphonomic age using 117 A. islandica shells collected from the Mid-Atlantic Bight offshore of the Delmarva Peninsula with radiocarbon dates extending from 60–4,400 cal years BP. These shells had varying degrees of taphonomic alteration produced by discoloration and degradation of periostracum. To determine if a relationship exists between taphonomic condition and time-since-death, radiocarbon ages were compared with the amount of remaining periostracum and type of discoloration. Old shells (individuals that died long ago) were discolored orange with no periostracum while younger shells (individuals that died more recently) had their original color, with some periostracum. Both the disappearance of periostracum and appearance of discoloration followed a logistic process, with 50% of shells devoid of periostracum and 50% discolored in about 1,000 years. The logistic form of long-term taphonomic processes degrading shell condition is first reported here, as are the longest time series for taphonomic processes in death assemblages within the Holocene record. This relationship can be utilized for triage when deciding what shells to age from time-averaged assemblages, permitting more efficient application of expensive methods of aging such as radiocarbon dating.

Oil price uncertainty and unemployment dynamics: Nonlinearities matter

Using a logistic smooth transition autoregressive process for the monthly U.S. unemployment rate with oil price uncertainty as a transition variable, we investigate the impact of high and low oil price uncertainty states on the unemployment rate. We find that the unemployment rate rises and is more persistent in a high oil price uncertainty state than in a low oil price uncertainty state. Additionally, our analysis of generalized impulse response functions shows that an oil price uncertainty shock increases the unemployment rate in the high oil price uncertainty state but has no significant effect in the low oil price uncertainty state. The asymmetric response of the unemployment rate varies depending on the sign and size of the shocks and is contingent upon the initial history of the economy. Our findings are robust to different specifications and suggest that policymakers should consider these relationships and take a more nuanced approach to policies designed to mitigate the adverse impact of oil price uncertainties on the labor market.

Logistics Outsourcing Services and Performance of Firms in the Tele-Communications Sector: A Case of Airtel Rwanda Ltd

This study assessed the effect of out-sourcing services on performance of firms in telecommunication sector with reference to Airtel Rwanda Ltd. The specific objectives were to determine effect of financial systems, network monitoring tools services, and supplier network responsiveness outsourcing on organizational performance of Airtel Rwanda Plc the study provides useful data to management of Airtel to assist it in service delivery and quality performance for the outsourced services. The study targeted 65 senior managers and key employees at Airtel Rwanda Ltd and sampled 56 respondents using Yamane formula. Primary and secondary data collection techniques were both using through questionnaire and interview guide. Data was analyzed using Pearson’s correlation analysis to establish the relationship between variables. Results to the first objective show that the logistic process response to unexpected demand changes and the effectiveness in delivery of shipments both scored means of 4.597. These variables scored means of 4.376, 4.376 and 4.038 respectively. There was the significant correlation between rapidly adjusts warehouse capacity to address demand changes and project time (r=.206; p-value=.000). Results to the second objective that all respondents agreed that their company uses outsourcing in its operations and as a result, they indicated that the supply chain operating system responds rapidly to changes in product volume demanded by customers (mean 4.921). The grand mean of these factors was 4.498 showing that generally there was higher responsiveness of the supply chain systems to customer needs. For  the effect on responds rapidly to changes in product mix demanded by customers on quality, time cost, the study ascertained that responds rapidly to changes in product mix demanded by customers is statistically significant with quality (r=0.122*;p value=0.035). Results on effectively expedites emergency customer orders felt that it is significantly correlated with an increase of quality of services (r=0.123*; p value=0.034). Results to the third objective shows that the grand mean was 4.155. It was indicated that major suppliers consistently accommodated requests (mean of 4.712) and the major suppliers changed product volume in a relatively short time (Mean of 4.259). Results show that major suppliers consistently accommodate our requests was insignificant with the quality of services (r=0.080, p-value=.0169), and major suppliers consistently accommodate our requests was insignificantly correlated with efficient and effective use of cost (r=0.013, p-value=.822). Finally, the study found a significant correlation between Major suppliers consistently accommodate our requests and timely delivered of services to beneficiaries (r=0.105, p-value=0.071). All the correlations were statistically significant given that the p value was < 0.05 proposing that an increase in major suppliers consistently accommodate our requests was insignificant with the quality of services increase quality of services, timely delivered, efficient and effective use of cost allocated and vice versa. In conclusion, the study concludes that Airtel Rwanda Plc in Rwanda have outsourced financial system billing. Airtel Plc had outsourced networking monitoring tools which play a pertinent role to the organizational success. Airtel has masts/towers and fleet management that contribute to organizational performance.  Finally, the study recommends that to adopt masts/towers and fleet management in means, the government should revise competition policy, and contract duration for outsourcing activities. Future studies should consider conducting similar research in different types of companies for comparison of results with the aim of coming into consensus on the generalization of the results. Keywords: Outsourcing, in-housing development, telecommunication, core business activities.