Abstract
The masonry brick small-scale manufacturing industry plays a significant role towards the socio-economic development of surrounding communities at ground level. The masonry brick manufacturing small-scale industry assists in the development of the building and construction industries, and it is a source of income for both the small-scale enterprises and employees. The industry creates employment opportunities for the unskilled, semi-skilled and skilled human capital. Thus, the industry contributes towards the gross domestic product (GDP) and economy of South Africa. However, there are unprecedented productivity challenges amongst others, involving inefficient productivity improvement systems and value-adding drivers that impede the growth in productivity of the masonry brick small-scale manufacturing enterprises.
The study aimed to develop and test a conceptual model that integrates a network of identified research constructs related to productivity improvement systems involving ergonomics, human resource management (HRM), just-in-time (JIT), business process re-engineering (BPR), total quality management (TQM) and technology and value-adding drivers that the masonry brick manufacturing small-scale enterprises located within the province of Gauteng, in the City of Johannesburg Metropolitan Municipality and City of Tshwane Metropolitan Municipality can utilise to enhance their productivity. Thus, attaining long-term market and financial feasibility. To develop this conceptual model, the study extensively explored literature on various productivity improvement systems and value-adding drivers that assisted with the design of the research questionnaire that was used to measure participants’ perceptions regarding the identified research constructs and how they impact their productivity.
A mixed-method research design was used to collect data from the owners, managers and brick makers in the masonry brick manufacturing small-scale industry within the province of Gauteng. An explanatory sequential approach was used, where the researcher commenced by gathering data of a quantitative nature, which was preceded by collecting information of a qualitative nature, which aided the researcher in identifying similarities, differences and potential gaps. This assisted the author to make the necessary alterations.
The data collection and analysis took place in two phases. The initial phase involved conducting a quantitative study. The quantitative data was collected using research questionnaires that were distributed (face-to-face method) to potential participants within the small-scale brick manufacturing industry. Out of 322 (N = 100%), approximately 252 (n = 78%) were completed. This yielded a valid response rate of 63% (Table 4.1), thus generating a failure to return rate of 22%. The gathered data was analysed using IBM Statistical Package for Social Science (SPSS) version 29.0. These statistical tools assisted with generating frequency distribution tables, measures of central tendency (mean), measures of dispersion (standard deviation), reliability test analysis, factor analysis (FA), correlation analysis and structural equation modelling (SEM).
Confirmatory factor analysis (CFA) measured the construct reliability, convergent and discriminant validity. This was followed by factor analysis (FA) using factor loadings to identify items within each
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latent variable below 0.7. The items with factor loadings below 0.7 were removed to improve the composite reliability (CR) and average of variation expected (AVE), thus supporting the model fit of the study.
Pearson’s product correlation analysis was used to ascertain the nature of the relationship between identified constructs involving productivity improvement systems, value-adding drivers, mediators comprising human, physical and technological capital factors and productivity growth within the small-scale masonry brick manufacturing enterprises. The results showed that all 27 relationships between the constructs were significantly positive, and the statistical p-value was below the recommended 0.01 level. The structural equation model revealed that only 10 out of the 21 paths identified were statistically significant. Those constructs that were not confirmed had weak positive or negative relationships with p-values above 0.01. Furthermore, out of the 10 paths identified, technological capital (TC) was a strong mediator between technology (TEC) and productivity growth (PG) according to the results generated from the total and specific indirect effects.
The second phase was a qualitative study, interviews and case study observations provided qualitative data respectively (see Appendix C interview guide distributed and followed during the interviews). It was deduced from the analysed data that the masonry brick small-scale manufacturing enterprises lacked the efficient use of productivity improvement systems through human, physical and technological capital factors due to a lack of knowledge, understanding and application of these tools in order to improve productivity within their organisations.
In relation to comparisons between the quantitative results and qualitative findings, the study found that the masonry brick small-scale manufacturing enterprises showed the lowest proportion of producing bricks, inefficient continuous operational process and managerial systems in place that would project the importance of enhancing the manner or methods of making bricks for productivity growth of these enterprises. Furthermore, these enterprises lack adequate brick makers, training and incentives, personal protective equipment, proper combustion process (firing/ baking), unsafe working environment and inadequate working environment that adversely influence the overall operational process of brick making and productivity output.
The findings from interviews conducted revealed that there was no evidence of emerging technologies in the masonry brick small-scale manufacturing enterprises. Thus, pointing out that these small-scale masonry brick enterprises are not technologically inclined with industry 3.0 – 4.0. However, the results highlighted that the technological capital (TC) was a strong mediator between technology (TEC) as a system and productivity growth (PG) within the masonry brick small-scale manufacturing enterprises.
From a quantitative perspective, the participants were limited in terms of their perceptions and experiences regarding the subject matter(s) of inquiry. However, from a qualitative perspective, the study was able to probe, account for, and document what goes into the process of making bricks from the relationship between owners/ managers with the suppliers, preparation of materials, forming of
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masonry bricks, brick stock inventory and customer service through a direct observational case study method. This assisted with magnifying what could have been unnoticed or overlooked pertaining to the impact of productivity improvement systems and value-adding drivers, mediated by human, physical and technological capital factors for productivity growth of masonry brick small-scale manufacturing enterprises.
Based on the mixed method used, the integration of quantitative results with qualitative findings, considering some of the discussed similarities, differences and gaps within the masonry brick small-scale manufacturing enterprises, this study recommends that technology capital and technology matrix mix model be developed for productivity growth within the masonry brick small-scale manufacturing enterprises.