Marketing Strategies Correlate Sales Growth among MSMEs in Zambia

Purpose: The purpose of this study was to examine the effect of marketing strategies on performance of MSMEs in Zambia. The study was conducted out of the need to understand the roles played by marketing strategies on performance of MSMEs in Zambia. The objective was to present the results of a rigorous assessment of marketing strategies applied by the MSMEs and their effect on business performance.Methodology: A descriptive, correlational design was used for this study.  A structured questionnaire was administered as a google form to 177 MSME owners/ managers in Lusaka and Copper belt Province.  The study was limited to MSMEs that were registered with PACRA and were members of the Zambia Chambers of Small and Medium Business Association. Yamane Taro’s sampling formula was used to determine the desired sample. Two measures (a) marketing strategies and (b) sales growth were the main variables. Data were analysed by using the SPSS statistical program, version 28 (SPSS Inc.). Descriptive statistics (means, medians, SDs, and ranges) were computed. Normality was assessed by using histograms and ordinal logistic regression analyses to determine correlates.Findings: Four out of the five dominant marketing strategies that were used had significant positive impacts on sales growth among the MSMEs. These variables are: the Radio (Wald χ2(1) = 32.682, p = .001), WhatsApp (Wald χ2(1) =12.480, p = 0.001), Facebook (Wald χ2(1) =5.702, p = 0.017) and Newspaper (Wald χ2(1) =9.510, p = 0.001).Research limitations/implications: The findings are limited to the MSMEs in Zambia. The study of market strategies and performance is a very complex activity; due to lack of agreed definitions and variables for marketing strategies and performance among scholars. Therefore, to gather rich data on such research work may be best accomplished if the researchers consider various marketing strategies and performance variables. This will enrich the understanding on marketing strategies and MSMEs’ performance relationship.Practical implication: The findings of this research work offer guidance to owners or managers of MSMEs on how to adopt marketing strategies which could enhance firm performance.    The study concludes that marketing strategies can provide the additional competitive edge to MSMEs by consistently enhancing Sales growth. In this regard, MSMEs should pursue the consistent adoption of marketing strategies as a way of improving their performance. The study also revealed that the marketing activity of the MSME is influenced by the personality of the owner-manage. Further, the study suggests that more investigations be carried on other MSMEs performance indicators rather than the sales growth only.Keywords: Marketing Strategies, MSMEs Performance, Sales Growth. DOI: 10.7176/EJBM/15-11-05 Publication date:June 30th 2023

Characterizing and Investigating the Electrophysiological Properties of the Plastic Cricket Auditory System in Response to Cooling

The auditory system of the Mediterranean field cricket (Gryllus bimaculatus) is capable of profound compensatory plasticity. Following deafferentation due to the loss of an auditory organ, the dendrites of intermediate auditory neuron Ascending Neuron 2 (AN-2) grow across the midline and functionally connect to contralateral afferents. The loss of the auditory organ can be mimicked with reversible cold-deactivation, in which cooled Peltier elements silence the auditory organ and its afferents. Though this would presumably prevent AN-2 from firing, cooling instead induces a novel firing pattern called DOPE (delayed-onset, prolonged-excitation). In this study, intracellular physiological recordings were completed before, during, and after cooling in response to “chirp” and “pulse” sounds. Analysis was performed within and across crickets to characterize DOPE. Results revealed expected variability across individuals, as well as a wider spread of onset delay and a decrease in spike frequency and number of spikes per burst relative to baseline within individuals during cooling. Generally, subsequent warming only partially restored the neuronal responses to baseline as measured by all three parameters. This was particularly true in response to “pulse” stimuli. Future experiments will investigate if DOPE is caused by synaptic inputs or intrinsic properties of AN-2, as well as the role of inhibition in the circuit. Eventually, we hope to develop a complete model of the auditory circuit for future investigations of plasticity, with ramifications for treating human neuronal injury

Linkages between animal and human health sentinel data

INTRODUCTION: In order to identify priorities for building integrated surveillance systems that effectively model and predict human risk of zoonotic diseases, there is a need for improved understanding of the practical options for linking surveillance data of animals and humans. We conducted an analysis of the literature and characterized the linkage between animal and human health data. We discuss the findings in relation to zoonotic surveillance and the linkage of human and animal data. METHODS: The Canary Database, an online bibliographic database of animal-sentinel studies was searched and articles were classified according to four linkage categories. RESULTS: 465 studies were identified and assigned to linkage categories involving: descriptive, analytic, molecular, or no human outcomes of human and animal health. Descriptive linkage was the most common, whereby both animal and human health outcomes were presented, but without quantitative linkage between the two. Rarely, analytic linkage was utilized in which animal data was used to quantitatively predict human risk. The other two categories included molecular linkage, and no human outcomes, which present health outcomes in animals but not humans. DISCUSSION: We found limited use of animal data to quantitatively predict human risk and listed the methods from the literature that performed analytic linkage. The lack of analytic linkage in the literature might not be solely related to technological barriers including access to electronic database, statistical software packages, and Geographical Information System (GIS). Rather, the problem might be from a lack of understanding by researchers of the importance of animal data as a 'sentinel' for human health. Researchers performing zoonotic surveillance should be aware of the value of animal-sentinel approaches for predicting human risk and consider analytic methods for linking animal and human data. Qualitative work needs to be done in order to examine researchers' decisions in linkage strategies between animal and human data

The Experience of Children Living with Sensory Processing Disorder

Sensory processing disorder (SPD) is a neurological condition that alters the way an individual perceives sensory information. Although the condition has been studied for more than 40 years, SPD remains a difficult condition to diagnose, treat, and live with because it affects individuals uniquely, and the symptoms can change from childhood to adulthood. For children diagnosed with SPD, the misinterpretation of sensory cues can cause difficulties in family, social, and academic settings. While there is some research on the assessment and treatment of SPD, what is missing is a deeper understanding of the family, social and academic challenges these children and their families face. The purpose of this case study was to examine the experiences of children diagnosed with SPD, as told by 4 parents and their occupational therapist in semi-structured interviews. Four themes emerged from the analysis: family dynamics (challenges within the family structure), support impact (seeking and having support), emotion and balance (overcoming the struggles related to the emotional demand), and an SPD child (the search for balance for the child and the family). The results may serve as a catalyst to encourage positive social change for the children with SPD and their families by expanding the available knowledge on the challenges of SPD

An OLAP-GIS System for Numerical-Spatial Problem Solving in Community Health Assessment Analysis

Community health assessment (CHA) professionals who use information technology need a complete system that is capable of supporting numerical-spatial problem solving. On-Line Analytical Processing (OLAP) is a multidimensional data warehouse technique that is commonly used as a decision support system in standard industry. Coupling OLAP with Geospatial Information System (GIS) offers the potential for a very powerful system. For this work, OLAP and GIS were combined to develop the Spatial OLAP Visualization and Analysis Tool (SOVAT) for numerical-spatial problem solving. In addition to the development of this system, this dissertation describes three studies in relation to this work: a usability study, a CHA survey, and a summative evaluation.The purpose of the usability study was to identify human-computer interaction issues. Fifteen participants took part in the study. Three participants per round used the system to complete typical numerical-spatial tasks. Objective and subjective results were analyzed after each round and system modifications were implemented. The result of this study was a novel OLAP-GIS system streamlined for the purposes of numerical-spatial problem solving.The online CHA survey aimed to identify the information technology currently used for numerical-spatial problem solving. The survey was sent to CHA professionals and allowed for them to record the individual technologies they used during specific steps of a numerical-spatial routine. In total, 27 participants completed the survey. Results favored SPSS for numerical-related steps and GIS for spatial-related steps.Next, a summative within-subjects crossover design compared SOVAT to the combined use of SPSS and GIS (termed SPSS-GIS) for numerical-spatial problem solving. Twelve individuals from the health sciences at the University of Pittsburgh participated. Half were randomly selected to use SOVAT first, while the other half used SPSS-GIS first. In the second session, they used the alternate application. Objective and subjective results favored SOVAT over SPSS-GIS. Inferential statistics were analyzed using linear mixed model analysis. At the .01 level, SOVAT was statistically significant from SPSS-GIS for satisfaction and time (p < .002).The results demonstrate the potential for OLAP-GIS in CHA analysis. Future work will explore the impact of an OLAP-GIS system in other areas of public health

Evaluation of SOVAT: An OLAP-GIS decision support system for community health assessment data analysis

Background. Data analysis in community health assessment (CHA) involves the collection, integration, and analysis of large numerical and spatial data sets in order to identify health priorities. Geographic Information Systems (GIS) enable for management and analysis using spatial data, but have limitations in performing analysis of numerical data because of its traditional database architecture. On-Line Analytical Processing (OLAP) is a multidimensional datawarehouse designed to facilitate querying of large numerical data. Coupling the spatial capabilities of GIS with the numerical analysis of OLAP, might enhance CHA data analysis. OLAP-GIS systems have been developed by university researchers and corporations, yet their potential for CHA data analysis is not well understood. To evaluate the potential of an OLAP-GIS decision support system for CHA problem solving, we compared OLAP-GIS to the standard information technology (IT) currently used by many public health professionals. Methods. SOVAT, an OLAP-GIS decision support system developed at the University of Pittsburgh, was compared against current IT for data analysis for CHA. For this study, current IT was considered the combined use of SPSS and GIS ("SPSS-GIS"). Graduate students, researchers, and faculty in the health sciences at the University of Pittsburgh were recruited. Each round consisted of: an instructional video of the system being evaluated, two practice tasks, five assessment tasks, and one post-study questionnaire. Objective and subjective measurement included: task completion time, success in answering the tasks, and system satisfaction. Results. Thirteen individuals participated. Inferential statistics were analyzed using linear mixed model analysis. SOVAT was statistically significant (α = .01) from SPSS-GIS for satisfaction and time (p < .002). Descriptive results indicated that participants had greater success in answering the tasks when using SOVAT as compared to SPSS-GIS. Conclusion. Using SOVAT, tasks were completed more efficiently, with a higher rate of success, and with greater satisfaction, than the combined use of SPSS and GIS. The results from this study indicate a potential for OLAP-GIS decision support systems as a valuable tool for CHA data analysis. © 2008 Scotch et al; licensee BioMed Central Ltd

pyJacqQ: Python Implementation of Jacquez's Q-Statistics for Space-Time Clustering of Disease Exposure in Case-Control Studies

Jacquez's Q is a set of statistics for detecting the presence and location of space-time clusters of disease exposure. Until now, the only implementation was available in the proprietary SpaceStat software which is not suitable for a pipeline Linux environment. We have developed an open source implementation of Jacquez's Q statistics in Python using an object-oriented approach. The most recent source code for the implementation is available at https://github.com/sjirjies/pyJacqQ under the GPL-3. It has a command line interface and a Python application programming interface