Journal Articles

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3-Category pedagogical framework for context based ambient learning
(IEEE, 2013) Mwendia, Simon N.; Waiganjo, Peter; Oboko, Robert
Mobile phones have taken centre stage in transforming people’s lives in all sectors of African economies. With regard to Education sector, studies show that, there is high prevalence of mobile phones among learners in African universities but no computer prevalence. However, E-learning technologies are not readily available among learners. Learners are therefore forced to access content from few fixed locations with internet connectivity such as cyber cafes and workplace, eliminating access flexibility in learning. The ‘Mobile phone rich’ but ‘computer poor’ context prevailing in African universities presents an opportunity to establish an appropriate type of learning that utilizes mobile phones rather than computers. This paper explores existing categories of m-learning projects and proposes a 3-category framework to provide better understanding of ambient learning and allow integration of future ambient learning projects situated in different learning environments.
A comparison of two sample approaches to regression calibration for measurement error correction
(International Journal of Statistics and Applied Mathematics, 2023) Kamun, Samuel J; Nyakundi, Cornelious; Simwa, Richard O
This study compares ways for improving regression calibration. This is a method for combining two samples in order to reduce measurement error and improve the relative efficiency of linear regression models. Since two or more samples are more likely than a single sample to accurately represent the population under study, two samples are used in regression calibration to produce a realistic picture of the actual population. In this investigation, we compared independent estimates derived from two samples using a weight equal to the reciprocal of the estimated sampling probability. The study also examined the estimations produced after combining the two datasets into one, and modified the weight of each sample unit accordingly. The most typical application of regression calibration methods is to account for bias in projected responses induced by measurement inaccuracies in variables. Because of its simplicity, this method is commonly utilized. The conditional expectation of the genuine response is estimated using regression calibration, given that the predictor variables are measured with error and the other covariates are assessed without error. Instead of the unknown genuine response, predictors are estimated and used to examine the link between response and result. Regression calibration programs necessitate extensive knowledge of unobservable true predictors. This information is frequently collected from validation studies that employ unbiased measurements of true predictors. The results of two sample strategies were employed and compared in this study. Device fault, laboratory mistake, human error, difficulty documenting or completing measurements, self-reported errors, and intrinsic vibrations of the underlying instrument can all cause measurement inaccuracies. Covariate measurement error has three consequences: In addition to obscuring data features and making graphical model analysis more difficult, estimates of statistical model parameters might be skewed, and effectiveness in detecting correlations between variables can be severely impaired. This study's two sampling procedures produced satisfactory results.
A contextualized and personalized model to predict user interest using location-based social networks
(Elsevier Ltd., 2016) Mburu, Lucy W.; Li, Ming; Sagl, Günther; Fan, Hongchao
The accurate determination of user interest in terms of geographic information is essential to numerous mobile applications, such as recommender systems and mobile advertising. User interest is greatly influenced by the usage context and varies across individuals; therefore, a user interest model should incorporate these individual needs and propensities. In this paper, we present an approach to model user interest in a contextualized and personalized manner based on location-based social networks. Multinomial logistic regression is employed to quantify the relationship between user interest and usage context at both the aggregate and individual levels. The proposed approach is tested in a real-world application using Foursquare check-ins issued between February and June 2014 in the three major cities of Chicago, Los Angeles and New York. Results demonstrate the capability of the contextualization process for capturing contextual influences on user interest, and that such influences can be observed at a fine-grained scale at the individual level through the personalization process. The proposed approach therefore enables contextualized and personalized estimation of user interest, thereby contributing useful information to follow-up mobile applications.
A knowledge-as-a-service support framework for ambient learning in Kenya
(13th IADIS International Conference Information Systems, 2020) Mburu, Lucy W.; Karanja, Richard; Nyaga, Simon M.
Knowledge as a Service (KaaS) is a relatively new model, albeit one that is rapidly gaining popularity within cloud computing environments. Over the recent years, learners have experienced a constant need to access on demand knowledge that is fully aligned with the paradigm of cloud computing. This need stems from the knowledge that users will be able to access applications and the information therein on demand, without the restrictions that are usually imposed by time and space. The KaaS model terms knowledge as the understanding of information based on its relevance to a specific context and problem area, thus forming a valuable resource for the human decision-making process. As motivated by the global sustainable development goal of ensuring inclusive and equitable quality education to promote learning opportunities for all, this research has developed a framework that is hinged on KaaS and utilizes knowledge from ambient learning systems. The main aim is to provide a platform for disseminating and exploiting the available knowledge to aid the learning process and, thus, to improve the quality of education on the ambient learning system. The research further explores how collaborative effort can be used to form a knowledge network that allows access to heterogeneous sources of knowledge. The research outcomes will benefit knowledge consumers such as the developers of ambient learning systems.
A visual analytic framework for monitoring terror attacks: a case study of Mandera county, Kenya
(KCA University, 2025) Mong'are, Brion G.
Terrorism remains a persistent and evolving threat in Kenya, particularly in border counties such as Mandera, which face heightened vulnerability due to their proximity to Somalia. The Country’s ongoing instability, weak governance structures, and the presence of terrorist groups like al-Shabaab (AS) create fertile ground for cross-border militant activity, posing significant challenges to both regional security and local stability. A critical gap in current counterterrorism efforts is the absence of localised, data-driven frameworks capable of monitoring and predicting terrorist activities in real time. This study addresses that gap by developing a Visual Analytics (VA) framework tailored to monitor, analyse, and predict terrorist incidents, using Mandera County as a case study. Beyond processing complex datasets, the framework offers strategic guidance to decision-makers, enhancing situational awareness and enabling proactive counterterrorism interventions. The core objective is to strengthen counterterrorism strategies through spatiotemporal data mining techniques, such as cluster analysis, association analysis, and outlier detection, to derive actionable insights from both structured and unstructured data sources. The methodology integrates data from social media, security reports, and established databases such as the Global Terrorism Database (GTD) and the Armed Conflict Location & Event Data Project (ACLED). Visuals in the framework are guided by Shneiderman’s Visual Information-Seeking Mantra: “overview first, zoom and filter, then details on demand.” Through this approach, the system identifies attack hotspots, temporal patterns, and early warning indicators, delivering a user-centric tool for informed decision-making. Findings demonstrate the framework’s effectiveness in predicting high-risk areas and attack types, with particular emphasis on armed assaults and improvised explosive device (IED) incidents, which constitute over 50% of recorded attacks in Mandera. The results show improved allocation of security resources, enhanced inter-agency coordination, and timely intervention capabilities. Key recommendations include deploying the framework in high-risk regions, integrating it with existing security infrastructure, and expanding its use to other terrorism-affected areas. The framework’s scalable and adaptable design positions it as a valuable tool for strengthening counterterrorism efforts across Kenya and similar contexts.
Affirmative action funds and the growth of small and medium enterprises (smes) in Nairobi county
(European American Journals, 2026) Waswa, Fanice N.; Abdi, Ismail A.
Small and medium-sized enterprises (SMEs) are critical drivers of economic growth, yet many face barriers such as limited financing and weak managerial capacity. This study examined the influence of affirmative action funds on SME growth in Nairobi County, focusing on the Uwezo Fund, Youth Enterprise Development Fund (YEDF), and Women Enterprise Fund (WEF). Anchored on growth, human capital, and social capital theories, the study adopted a cross-sectional survey design with a sample of 376 SMEs selected using Yamane’s formula. Data was collected through questionnaires and analyzed using SPSS, applying descriptive statistics, regression, and correlation methods. Findings revealed that all three funds positively impacted SME growth: Uwezo Fund enhanced credit access through group lending, YEDF strengthened managerial skills via training, and WEF provided affordable financing that enabled expansion. The study recommends broadening fund outreach, simplifying access, and integrating mentorship and market linkages to foster inclusive, sustainable SME development in Kenya.
Ambient learning - knowledge as a service model: towards the achievement of sustainable development goal four
(IEEE, 2018) Mwendia, Simon N.; Karanja, Richard G.
Studies show that United Nations Sustainable Development Goal Four is yet to be achieved. This paper presents an artefact named “Ambient learning- Knowledge as a Service model” for describing how actionable knowledge can be extracted from ambient learning systems to support improvement and consequently facilitate the achievement of Sustainable Development Goal Four. A creative process was adopted to guide the development of the model. The process involved carrying out problem analysis through literature review, designing the model by combining ambient learning and Knowledge as a Service concept and demonstrating its application by developing a prototype. Evaluation results revealed that C4.5 algorithm that is implemented in Waikato Environment for Knowledge Analysis (WEKA) software is suitable for extracting knowledge from ambient learning systems while Swi-prolog software can be applied to create a tool for knowledge delivery.
Ambient learning conceptual framework for bridging digital divide in higher education
(IGI Global, 2014) Mwendia, Simon N.; Wagacha, Peter W.; Oboko, Robert
According to ITU (2012), digital divide is the difference between countries in terms of levels of ICT development. This difference remains significant. In 2011, the ICT Development Index (IDI) value of developed countries (6.52) was twice as high as that of developing countries (3.24). The need to link the digital divide for universal broadband Internet access is within the key international development goals, which include World Summit on the Information Society (WSIS) goals and Millennium Development Goals (MDGs). Ambient learning is the next generation of M-learning (Bick, Kummer, Pawlowski, & Veith, 2007), which allows flexible content access by considering learner's current situation and learning context (Kofod-Petersen, et al., 2008). However, ambient learning has not yet attained a state of common understanding (Winker, Scharf, Hahn, & Herczeg, 2011) and is not widely used or adopted (Bick, et al., 2007). This chapter presents a theoretical conceptual framework to foster creativity for innovative ambient learning applications, which can be used to bridge the digital gap between universities in developed and developing countries.
An empirical approach to mobile learning on mobile ad hoc networks
(Institute of Electrical and Electronics Engineers (IEEE), 2020) Mwendia, Simon N.; Ichaba, Mutuma; Musau, Felix
Mobile Ad hoc Networks (MANETs) are made up of mobile nodes that are interconnected wirelessly, while topology changes as mobile nodes join and leave the network. MANETs do not depend on fixed infrastructure. Due to their dynamism and low cost (no infrastructure is needed), MANETs have been proposed as a mechanism suitable for carrying out mobile learning (m-Leaning) in developing countries. However, systematic literature review indicates that the existing MANETs-based m-Learning models are disadvantaged because they fail to identify possible routing protocols able to support such models. As a result, it becomes very difficult to implement the existing MANET-based m-Learning models. This paper characterizes MANETs-based m-Learning proposed by [1]. Thereafter, it uses area, nodes, and data packets information as basic scalar parameters on Zone Routing Protocol (ZRP) simulated on NS-2 and ZRP code supplemented with positional and directional information of nodes in the Intrazonal Routing Protocol (IARP) on OMNET++. According to simulation results, a directional-positional enhanced ZRP outperforms regular ZRP on packet delivery ratio, delay and overall data packet throughput. Results from the simulation suggests that a supplemented ZRP is a feasible routing protocol for supporting m-Learning in a typical university campus based on the identified basic scalar parameters and characterization of [1].
Analysing Volatility Persistence in the Nairobi Securities Exchange: The Role of Exchange and Interest Rates
(Statistics, Optimization & Information Computing Journal, 2025) Mulinge, Anthony; Moyo,Edwin; Jere, Stanley; Kasumo, Christian; Nwokolo, Peter C.; Mwaanga, Clement; Mushala, Wamulume
In this paper, the main objective was to analyse the influence of exchange and interest rates on volatility persistence using asymmetric GARCH models (EGARCH and TGARCH) on NSE data. The analysis of the relationship between stock return volatility, exchange, and interest rates on volatility persistence was performed using the models ARMA (1, 2) -EGARCH (1,1) and ARMA (1, 2) -TGARCH (1,1) under the student t distribution and the generalised error distribution assumption using the NSE daily 20-share price index, interest rates, and exchange rates from 02/01/2015 to 31/12/2024 accounting for 3106 observations. The degree of persistence in the conditional variance equations slightly increased for the ARMA(1,2)-TGARCH(1,1) model and there was a slight reduction for the ARMA(1,2)-EGARCH(1,1) with the inclusion of interest rate and exchange rate which was consistent regardless of the error term distribution assumption. Generally, information shocks increase volatility persistence, and negative shocks have a greater impact than positive shocks. The coefficient of the exchange rate ($\delta_2$) is positive and statistically significant for ARMA (1,2)-TGARCH (1,1). Hence, we deduce that the volatility in the NSE can be explained by the exchange rate, and there exists a positive relationship. Therefore, it is evident that stock returns are positively related to changes in exchange rates. The government should implement policy measures to control the exchange rate, such as real-time disclosure of financial information, trading volumes, and corporate actions, as these affect stock returns.
Analysis of community properties and node properties to understand the structure of the bus transport network
(ScienceDirect, 2016) Mburu, Lucy W.; Sun, Yeran; Wang, Shaohua
Akin to most infrastructures, intraurban bus networks are large and highly complex. Understanding the composition of such networks requires an intricate decomposition of the network into modules, taking into account the manner in which network links are distributed among the nodes. There exists for each set of highly interlinked nodes little connectivity with the next set of highly interlinked nodes. This inherent property of nodes makes community detection a popular approach for analyzing the structure of complex networks. In this study, we attempt to understand the structure of the intraurban bus network of Ireland’s capital city, Dublin in a two-step approach. We first analyze the modular structure of the network by identifying potential communities. Secondly, we assess the prominence of each network node by examining the module-based topological properties of the nodes. Results of this empirical study reveal a clear pattern of independent communities, indicating thus, an implicit multi-community structure of the intraurban bus network. Examination of the geographic characteristics of the identified communities shows a degree of socio-economic divisions of the Dublin city. Furthermore, a large majority of the important nodes (vital transportation hubs) are located at the city center, implying that most of the bus lines in Dublin city tend to intersect the city’s core.
Antecedents of Brand Loyalty in Leading Supermarket Chains in Kenya: The Mediating Role of Customer Satisfaction
(International Institute for Science, Technology, and Education, 2017) Muturi, Francis M; Omwenga, Jane; Owino, Edward
The purpose of the study was to establish the extent to which customer satisfaction mediates the relationship between service quality, brand image, customer perceived value with brand loyalty in leading supermarket chains in Kenya. The population of interest comprised of customers of supermarkets in Kenya. A supermarket store sample of 30 stores from Nairobi and Nakuru counties was picked at random from the list of the stores of the four main supermarkets (Nakumatt, Uchumi, Naivas & Tusky’s). A sample of 384 customer respondents was interviewed. The study used multiple linear regression analysis in a four step process which established that customer satisfaction significantly affects brand loyalty. The study also shows that customer satisfaction fully mediates the relationship between service quality, brand image, customer perceived value with brand loyalty in leading supermarkets in Kenya. The dimensions of brand Image, service quality and customer perceived value dimensions are antecedent to brand loyalty and are a significant marketing tool for retail stores that wish to enhance the customers repurchase intention and the intention to recommend. A higher level of customer satisfaction leads to brand loyalty which is paramount to being competitive in the marketplace. The study recommends that supermarkets must strive towards increasing customer satisfaction with a view of enhancing brand loyalty and market share retention.
Antecedents of Customer Perceived Value: Evidence of Mobile Phone Customers in Kenya.
(International Journal of Business and Social Science, 2014) Owino, Edward O.
As the mobile phone industry in Kenya gets competitive, customer retention becomes an imperative precursor to firm performance. For this reason, the study was so conceived to examine factors that influence customer perceived value amongst Kenyan mobile phone customers. The study analysed perceived service quality and the perception of price amongst cell phone users. A survey of 400 randomly selected respondents was undertaken. A structured instrument covering background information, customer expectation and customer perception was adopted in primary data collection. The results shows that perceived quality of service and perceived price determine customer’s perception of value. The results indicate the existence of a significant differences exist between what customers expect and what they perceive they experience after a service encounter. Service managers should compete on providing services of high value to gain a competitive edge in this market.
Applying Data Mining in Graduates’ Employability : A Systematic Literature Review
(International Journal of Engineering Pedagogy, 2023) Mburu, Lucy W.; Mwendia, Simon N.; Mpia, Héritier N.
Envisaging an adequate IT/IS solution that can mitigate the employability problems is imperative because nowadays there is a high rate of unemployed graduates. Thus, the main goal of this systematic literature review (SLR) was to explore the application of data mining techniques in modeling employability and see how those techniques have been applied and which factors/variables have been retained to be the most predictors or/and prescribers of employability. Data mining techniques have shown the ability to serve as decision support tools in predicting and even prescribing employability. The review determined and analyzed the machine learning algorithms used in data mining to either predict or prescribe employability. This review used the PRISMA method to determine which studies from the existing literature to include as items for this SLR. Hence, 20 relevant studies, 16 of which are predicting employability and 4 of which are prescribing employability. These studies were selected from reliable databases: ScienceDirect, Springer, Wiley, IEEE Xplore, and Taylor and Francis. According to the results of this study, various data mining techniques can be used to predict and/or to prescribe employability. Furthermore, the variables/factors that predict and prescribe employability vary by country and the type of prediction or prescription conducted research. Nevertheless, all previous studies have relied more on skill as the main factor that predict and/or prescribe employability in developed countries and none studies have been conducted in unstable developing countries. Therefore, the need to conduct research on predicting or prescribing employability in such countries by trying to use contextual factors beyond skill as features.
Approximations of ruin probabilities under financial constraints
(Applied Mathematical Sciences, 2022) Simwa, Richard O; Odiwuor, Calvine O; Onyango, Fredrick
In this paper, we investigate the approximate ruin probabilities un-der ﬁnancial constraints (interest rate, inﬂation, and taxation). We formulate a risk process whose premium inﬂow is inﬂuenced by the economic eﬀects of inﬂation and interest rate. Thereafter we invokethe Albrecher-Hipp loss-carried-forward tax scheme from which an ex-act formula for the ruin probability for exponentially distributed claimsis derived. Finally, an explicit asymptotic formula when the claims have sub-exponential distribution is also derived using the Pollaczek-Khintchine formula.
Assessment of Shareholder Strategy – An Internal Corporate Social Responsibility Perspective on Organizational Commitment in Five-Star Hotels in Kenya
(Asian Journal of Economics, Business and Accounting, 2023) Maalim, Bashir M; Kibe, Lucy W; Ndolo, Jackson
In Kenya, Five-Star hotels are leading in employees’ turnover within the hotel industry at 68%. This surpasses the healthy turnover range (0-15%) and affect organizational performance through the high cost incurred to replace experienced workers. Workers’ commitment in an organization plays a vital role in addressing turnover intentions. The objective of this study was to assess the influence of shareholder strategy on organizational commitment in five-star hotels in Kenya. The study applied descriptive research design, cross-sectional approach and quantitative method to examine the study variables. A total of 216 hotel managers in five-star hotels in Kenya was the target population of the study, out of this, 144 hotel managers were selected as sample size in 2021. A self-administered questionnaire was used to collect data and a response rate of 86.8% was obtained. The study applied both descriptive and inferential statistical approaches to analyze data with tabulation, figures and narrative output presentation. The study found that Shareholder Strategy has statistically significant and positive effect and explains 53.1% variation of the Organizational Commitment in Five-Star hotels in Kenya. Empowering the workers with ability for decision-making, problem solving, and planning activities fosters loyalty and commitment which drastically reduces turnover intentions. The study recommends to the hotel management and Kenya Association of Hotelkeepers & Caterers to strive to formulate and implement CSR embedded Shareholder Strategy for raising workers’ Commitment with the aim to attract, motivate, and retain workers. The study suggests replication of the study in the same or other sectors to develop further the Internal CSR field.
Auditors’ Professional Experience and Financial Sustainability of County Governments
(International Journal of Finance, 2026) Kiarie, Anthony N.
Purpose: This study investigated the effect of an auditor’s professional experience on the financial sustainability of county governments in Kenya. Methodology: A descriptive research design was employed, targeting all 47 counties in Kenya. A sample of 123 respondents was selected, and data were obtained through structured questionnaires utilizing a five-point Likert scale. Instrument reliability was verified through a pilot test, yielding a Cronbach’s alpha of 0.7. Data analysis was conducted using SPSS, applying both descriptive and inferential statistics, including multivariate regression and structural equation modeling. Findings: The findings established that auditors’ professional experience exerts a positive and statistically significant effect on financial sustainability. It concludes that sustained investment in auditor capacity-building is vital for improving governance and ensuring long-term financial sustainability within devolved government units. Unique Contribution to Theory, Policy, and Practice: The study extends on the existing public sector auditing and financial sustainability literature by empirically demonstrating, within the Kenyan county government context, the significant linkage between auditors’ professional experience and financial sustainability, while reinforcing legitimacy, stewardship, and inspired confidence theories in public financial management discourse. The study further provides empirical evidence to county governments and policymakers that auditors’ professional experience is a critical governance resource for enhancing financial sustainability, thus justifying greater investment in auditor capacity development, retention, and professional training within devolved units.
Bayesian Model Averaging in Modeling of State Specific Failure Rates in HIV/AIDS Progression
(Mathematics and Statistics, 2022) Simwa, Richard O; Mwirigi, Nahashon; Wainaina, Mary; Sewe, Stanley
In modeling HIV/AIDS progression, we carried out a comprehensive investigation into the risk factors for state-specific-failure rates to identify the influential co-variates using Bayesian Model averaging method (BMA). BMA provides a posterior probability via Markov Chain Monte Carlo (MCMC) for each variable that belongs to the model. It accounts for model uncertainty by averaging all plausible models using their posterior probabilities as the weights for model-averaged predictions and estimates of the required parameters. Patients' age, and gender, among other co-variates, have been found to influence the state-specific-failure rates highly. However, the impact of each of the factors on the state specific-failure was not quantified. This paper seeks to evaluate and quantify the contribution of the patient's age and gender, CD4 cell count during any two consecutive visits, and state movement on the state-specific-failure rates for patients transiting either to the same, better or worse state. We used R Studio statistical Programming software to implement the method by applying BMS and BMA packages. State movement had a comparatively large coefficient with a posterior inclusion probability (PIP) of 0.8788 (87.88%). Hence, the most critical variable followed by observation-two-CD4-cell-count with a PIP of 0.1416 (14.16%), age and gender were the last with a PIP of 0.0556 (5.56%) and 0.0510 (5.10%) respectively for patients transiting to the same state. For patients transiting to a better state, the patients' age group dominated with a PIP of 0.9969 (99.69%), followed by patients' gender with a PIP of 0.0608 (6.08%). Patients' CD4 cell count during the second observation had the least PIP of 0.0399 (3.99%). For patients transiting to a worse disease state, patients CD4 cell count during the second observation proved to be the most important, with a PIP of 0.6179(61.79%) followed by state movement with a PIP of 0.2599 (25.99%), patients gender tailed with a PIP of 0.0467 (4.67%).
Board attributes and sustainability reporting of selected listed nonfinancial firms in anglophone Sub-Saharan African countries: A multinomial logistic regression
(ScienceDirect., 2024) Kariuki, Peter Wang'ombe.; Lewa, Elias Mwasambu.; Gatimbu, Karambu Kiende.
Abstract Resource depletion, social inequality, and climate change are key among the global issues affecting the modern corporate world. Corporate sustainability is a major agenda at corporate boards. Stakeholders are increasingly demanding corporate responsibility in the wake of global resource depletion. Sustainability reporting has been experienced differently in different regions, with emerging economies being adversely stuck. Combating the bearing effects has been difficult due to a lack of synergy among the nations as well as a lack of harmonized corporate disclosure. Understanding the global socioeconomic and environmental concerns requires a close examination of the major determinants of sustainability reporting. Grounded on the agency, stakeholders, and legitimacy theory, this study aims to evaluate the influence of board attributes on sustainability reporting. Using a multinomial logistic regression model, the study assessed 110 nonfinancial firms listed in 10 Sub-Saharan African (SSA) countries from 2016 to 2021. The study analysed the influence of board attributes on sustainability reporting. The result indicates that board size, board meetings, board independence, and board gender diversity have a positive influence on sustainability reporting. The finding provides policy implications and insight into the need for more representative boards with increased gender diversity and independence. Additionally, an optimal frequency of board meetings is needed to strengthen oversight, efficacy, and transparency of sustainability reporting initiatives in SSA. Larger representative board sizes could be rewarded with tax concessions.
Business shared services model as a catalyst of cost reduction in East African Breweries Limited
(Future X Journal, 2023) Nyakundi, Nicholas; Owino, Edward
The business shared services model (BSSM) seeks to integrate service delivery between the headquarters and subsidiaries for the general good. In this paper, the role of BSSM as a catalyst of cost reduction in a manufacturing firm was explored. The predictive power of human resource shared services, finance shared services, logistic shared services, and customer shared services on cost reduction in East African Breweries Limited (EABL) was determined. Using a sample survey of 149 employees, it was established that a BSSM is a positive catalyst of cost reduction in the manufacturing sector in EABL. Adoption of BSSM fosters a distinct culture of collaboration resulting in efficacy in logistics services delivery.