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The survey of the curricula of the B.Sc. Construction Technology and Management and the HND Building Technology programmes has revealed that site management courses are important in Building Technology education in Ghana. It also showed that site management courses offered under the B.Sc. Construction Technology and Management programme deal much with construction cost, quality, safety, security, construction resources planning and control etc. The knowledge requirements for site managers identified from the literature on the impact of construction activities on the environment (Table 2) is given little or no attention in current site management courses. Environmental impact of construction site activities is not taught as a separate course in the B.Sc. Construction Technology and Management curricula (Table 2). However, environmental impact of construction activities and site organization are topics taught under CTM 354 Post-Contract Planning and Control course in the second semester of the third year. Other environment-related topics taught in the fourth year are, health and safety in plant operation (under CTM 451 Plant Management), materials control, quality assurance, and purchasing (under CTM 455 Materials Management). Interview with the course lecturer revealed that protection of the natural vegetation is discussed under BT 251 Soils and Foundation Systems in the second year of the programme. The study show that important knowledge areas such as those addressing environmental concerns of dust and noise generation, and land and water contamination (Table 1), are not given adequate

Table 2 The survey of the curricula of the B.Sc. Construction Technology and Management and the HND Building Technology programmes has revealed that site management courses are important in Building Technology education in Ghana. It also showed that site management courses offered under the B.Sc. Construction Technology and Management programme deal much with construction cost, quality, safety, security, construction resources planning and control etc. The knowledge requirements for site managers identified from the literature on the impact of construction activities on the environment (Table 2) is given little or no attention in current site management courses. Environmental impact of construction site activities is not taught as a separate course in the B.Sc. Construction Technology and Management curricula (Table 2). However, environmental impact of construction activities and site organization are topics taught under CTM 354 Post-Contract Planning and Control course in the second semester of the third year. Other environment-related topics taught in the fourth year are, health and safety in plant operation (under CTM 451 Plant Management), materials control, quality assurance, and purchasing (under CTM 455 Materials Management). Interview with the course lecturer revealed that protection of the natural vegetation is discussed under BT 251 Soils and Foundation Systems in the second year of the programme. The study show that important knowledge areas such as those addressing environmental concerns of dust and noise generation, and land and water contamination (Table 1), are not given adequate

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The research involved a total of 457 respondents. The males constituted 65% while the females formed 35%. The majority of respondents (65%) were local resident of Bogosc and the six villages. A total of 129 mining workers constituting 28% participated in the research. Members of the Traditional Council constituted 3% while and the Towr Development Committee constituted 4%. The head of Health, Safety, and Environmenta development (HSE) department was also involved in the research (Table 2). ae ae See Se Se ae eee eee ee ere In the search for gold much vegetation and soil is removed to get access to the gold ore and to make accessible roads to the mining site(s). After the ore is taken, the area is often left at the mercy of the prevailing climatic conditions such as torrential double maxima rains, which often removes the top layer of the soil containing plant nutrients and hastens all forms of erosion- decreasing soil fertility. In fact, the continuous decline of soil nutrients has led to land degradation, low farm yield and scarcity of food respectively. It was therefore not surprising that the majority of the participants ranked farm (24%) and vegetation destruction (22%) as the most devastating effects of mining operations in area. The construction of roads to link mining pits, processing plants and wastes dumps and domestic roads further added to the degradation. Unfortunately the sloppy nature of the land and high rainfall pattern in the area, has further aided the development of numerous ditches at the sides of constructed roads.
The research involved a total of 457 respondents. The males constituted 65% while the females formed 35%. The majority of respondents (65%) were local resident of Bogosc and the six villages. A total of 129 mining workers constituting 28% participated in the research. Members of the Traditional Council constituted 3% while and the Towr Development Committee constituted 4%. The head of Health, Safety, and Environmenta development (HSE) department was also involved in the research (Table 2). ae ae See Se Se ae eee eee ee ere In the search for gold much vegetation and soil is removed to get access to the gold ore and to make accessible roads to the mining site(s). After the ore is taken, the area is often left at the mercy of the prevailing climatic conditions such as torrential double maxima rains, which often removes the top layer of the soil containing plant nutrients and hastens all forms of erosion- decreasing soil fertility. In fact, the continuous decline of soil nutrients has led to land degradation, low farm yield and scarcity of food respectively. It was therefore not surprising that the majority of the participants ranked farm (24%) and vegetation destruction (22%) as the most devastating effects of mining operations in area. The construction of roads to link mining pits, processing plants and wastes dumps and domestic roads further added to the degradation. Unfortunately the sloppy nature of the land and high rainfall pattern in the area, has further aided the development of numerous ditches at the sides of constructed roads.
Table 3: Views of Local People on the Negative Effects of Mining Activities
Table 3: Views of Local People on the Negative Effects of Mining Activities
Table 4: SO Concentration for the Period November 1998 to December 1999
Table 4: SO Concentration for the Period November 1998 to December 1999
Furthermore, suspended solids (ranging from colloidal to settleable materials) from waste mining dumps have also resulted in stream pollution. In one year, 5.6 million tonnes of waste materials were deposited in water bodies (HSE, 2000). The Chujah waste dump remains the worst potential problem in its immediate environs due to the steepness of the sideways and the lack of terracing. Surface run-off and rainfalls erodes such waste materials and deposit them in the immediate drainage systems. For instance, river Mansi became choked, during the dry season of 2000 because of eroded materials fram wacta diimne
Furthermore, suspended solids (ranging from colloidal to settleable materials) from waste mining dumps have also resulted in stream pollution. In one year, 5.6 million tonnes of waste materials were deposited in water bodies (HSE, 2000). The Chujah waste dump remains the worst potential problem in its immediate environs due to the steepness of the sideways and the lack of terracing. Surface run-off and rainfalls erodes such waste materials and deposit them in the immediate drainage systems. For instance, river Mansi became choked, during the dry season of 2000 because of eroded materials fram wacta diimne
Table 5: The Effect of Air over Pressure and Noise on Structures. participants complained of the development of cracks in buildings especially, in Dumas and some part of Bogoso. This is because; ground vibration and air pressure affect the foundation and subsequent stability of buildings. Ground vibration can cause damage o. total collapse of building. Air over pressure on the other hand is more commonly the source of secondary rattling and annoyance which can induce breakage of doors anc windows. However, it is important to note that, the extent of any of these damage: depended on the structure and the magnitude of the impact as well as the proximity o: the building to the blasting zone. It was further revealed that the magnitude of grounc vibration and air blast felt depended on the quantity of explosives used or detonatec instantaneously. This was described as the charge per delay. The smaller the charge pe. delay or the longer the distance from the blast site, the smaller the ground vibration anc air blast. The opposite is true. Table 5 shows the effect that is associated with th different levels of noise measure in Decibels.
Table 5: The Effect of Air over Pressure and Noise on Structures. participants complained of the development of cracks in buildings especially, in Dumas and some part of Bogoso. This is because; ground vibration and air pressure affect the foundation and subsequent stability of buildings. Ground vibration can cause damage o. total collapse of building. Air over pressure on the other hand is more commonly the source of secondary rattling and annoyance which can induce breakage of doors anc windows. However, it is important to note that, the extent of any of these damage: depended on the structure and the magnitude of the impact as well as the proximity o: the building to the blasting zone. It was further revealed that the magnitude of grounc vibration and air blast felt depended on the quantity of explosives used or detonatec instantaneously. This was described as the charge per delay. The smaller the charge pe. delay or the longer the distance from the blast site, the smaller the ground vibration anc air blast. The opposite is true. Table 5 shows the effect that is associated with th different levels of noise measure in Decibels.
Hearst Tower elevation and lobby interior showing atrium feature escalator running through a 3-story water sculpture titled “Icefall”. Culled from New York Architecture Images — Midtown
Hearst Tower elevation and lobby interior showing atrium feature escalator running through a 3-story water sculpture titled “Icefall”. Culled from New York Architecture Images — Midtown
opens the way for a conscious effort to think about a desired future (Beatly, 1995). Even though all definitions ultimately address the environmental and ecological impact of human development, different entities define the term slightly differently to accommodate their individual objectives (Jeon & Amekudzi, 2005). A broad definition of sustainable transport tends to favour more integrated approaches that include improved travel choices, economic incentives, institutional reforms, land use management and technological innovation (Litman & Burwell, 2006). These individual interventions may yield marginal impact, but if implemented as a package they can produce substantial benefits (Litman, 2003). Sustainable transportation is achieved by maximizing the extent to which it benefits the economy, environment and the social well-being of the general population (Jeon & Amekudzi, 2005). This relationship is depicted graphically in Figure 1. Formally addressing sustainability and including it into a planning process requires redefining the metrics by which the performance of transport systems are measured and on which planning and programming decisions are based. Sustainability also requires assessment of both direct and indirect impacts of transportation (Litman, 2003). Seeing the growing concern for sustainable transport, its ability to provide equitable distribution of transportation benefits and the potential for poverty mitigation by providing all inclusive transport system, developing countries must embrace sustainable transportation planning.
opens the way for a conscious effort to think about a desired future (Beatly, 1995). Even though all definitions ultimately address the environmental and ecological impact of human development, different entities define the term slightly differently to accommodate their individual objectives (Jeon & Amekudzi, 2005). A broad definition of sustainable transport tends to favour more integrated approaches that include improved travel choices, economic incentives, institutional reforms, land use management and technological innovation (Litman & Burwell, 2006). These individual interventions may yield marginal impact, but if implemented as a package they can produce substantial benefits (Litman, 2003). Sustainable transportation is achieved by maximizing the extent to which it benefits the economy, environment and the social well-being of the general population (Jeon & Amekudzi, 2005). This relationship is depicted graphically in Figure 1. Formally addressing sustainability and including it into a planning process requires redefining the metrics by which the performance of transport systems are measured and on which planning and programming decisions are based. Sustainability also requires assessment of both direct and indirect impacts of transportation (Litman, 2003). Seeing the growing concern for sustainable transport, its ability to provide equitable distribution of transportation benefits and the potential for poverty mitigation by providing all inclusive transport system, developing countries must embrace sustainable transportation planning.
Table 2 Barriers to the implementation of ISO 14000 EMS in the Ghanaian construction industry- opinion of consultants
Table 2 Barriers to the implementation of ISO 14000 EMS in the Ghanaian construction industry- opinion of consultants
Using the t-test, * indicates that the score is significantly above 3.000 at 5% level. Copyright © 2010 Faculty of Architecture and Building Technology, Kwame Nkrumah University of Science and Technology. 1° IPGRC-KNUST
Using the t-test, * indicates that the score is significantly above 3.000 at 5% level. Copyright © 2010 Faculty of Architecture and Building Technology, Kwame Nkrumah University of Science and Technology. 1° IPGRC-KNUST
3.3 Effective measures to promote ISO 14000 EMS The views of the various groups of respondents regarding the measures which could be taken to promote the implementation of ISO 14000 in the Ghanaian construction industry were sought. The mean scores of the of the various measures and the t-test results at 5% significance level, are summarized in Tables 4 to 6 for the contractors, consultants and clients respectively.
3.3 Effective measures to promote ISO 14000 EMS The views of the various groups of respondents regarding the measures which could be taken to promote the implementation of ISO 14000 in the Ghanaian construction industry were sought. The mean scores of the of the various measures and the t-test results at 5% significance level, are summarized in Tables 4 to 6 for the contractors, consultants and clients respectively.
Table 4 Effective measures to promote ISO 14000 EMS in the Ghanaian construction industry- opinion of contractors Using the t-test, * indicates that the score is significantly above 3.000 at 5% level. Table 5 Effective measures to promote ISO 14000 EMS in the Ghanaian construction industry- opinion of consultants
Table 4 Effective measures to promote ISO 14000 EMS in the Ghanaian construction industry- opinion of contractors Using the t-test, * indicates that the score is significantly above 3.000 at 5% level. Table 5 Effective measures to promote ISO 14000 EMS in the Ghanaian construction industry- opinion of consultants
Figure 1; Building bioclimatic C hart of Kumasi (Amos-A banyie et al, 2009)
Figure 1; Building bioclimatic C hart of Kumasi (Amos-A banyie et al, 2009)
Figure 2: General pattern of indoor air temperature in office buildings in Kumasi 2. METHODS The Energy Plus (E+) simulation software was used to carry out a comparative performance analysis. A control model was developed based on the characteristics of a conventional Ghanaian mode of office building design, as defined in the Ghana building regulation. The walls were made of a lightweight mass of 150mm thick cement-sand blocks and the roof of 150mm thick reinforced concrete slab. The dimensions of models are 2.44m high, 1.22m wide and 2.44m deep. This is based on the proportions of the ceiling height, width and depth of a typical bay in Ghana. A series of comparative simulations were performed using climatic data of Kumasi. Simulation model:
Figure 2: General pattern of indoor air temperature in office buildings in Kumasi 2. METHODS The Energy Plus (E+) simulation software was used to carry out a comparative performance analysis. A control model was developed based on the characteristics of a conventional Ghanaian mode of office building design, as defined in the Ghana building regulation. The walls were made of a lightweight mass of 150mm thick cement-sand blocks and the roof of 150mm thick reinforced concrete slab. The dimensions of models are 2.44m high, 1.22m wide and 2.44m deep. This is based on the proportions of the ceiling height, width and depth of a typical bay in Ghana. A series of comparative simulations were performed using climatic data of Kumasi. Simulation model:
Figure 3: Outdoor and indoor temperatures of control model and model 1 Model 2: Light-weight mass with 27% window to floor ratio and night ventilated In this series, the window is reduced by 50% in the test model while maintaining the light weight mass and the night ventilation rate of 1OACH. The maximum temperature in the test model is lower by a small margin of 0.9°C as compared to the control model (Figure 4). This could be attributed to the reduced solar heat gain through the windows of the test cell (50% window verses 100%-sized windows). At night the minimum temperatures have a difference of 0.8°C, which is same as in the previous series.
Figure 3: Outdoor and indoor temperatures of control model and model 1 Model 2: Light-weight mass with 27% window to floor ratio and night ventilated In this series, the window is reduced by 50% in the test model while maintaining the light weight mass and the night ventilation rate of 1OACH. The maximum temperature in the test model is lower by a small margin of 0.9°C as compared to the control model (Figure 4). This could be attributed to the reduced solar heat gain through the windows of the test cell (50% window verses 100%-sized windows). At night the minimum temperatures have a difference of 0.8°C, which is same as in the previous series.
‘International Postgraduate Research Conference on the Built Environme D.K Fugar and E. Adinyira (Eds) NUST, 2010 Model 3: Light-weight mass with no window and night ventilated In this series, the window is eliminated in the test model while maintaining the light weight mass and the night ventilation rate. Because there is no window in the test model, its maximum temperature is still lower than the control cell. The difference between the maximum temperatures in both cells increased to 1.9°C, compared to 0.9°C in the previous test model. But the temperature inside the test model was still outside (above) the comfort zone. At night. the minimum temperatires in the test model are lower than those in the contro]
‘International Postgraduate Research Conference on the Built Environme D.K Fugar and E. Adinyira (Eds) NUST, 2010 Model 3: Light-weight mass with no window and night ventilated In this series, the window is eliminated in the test model while maintaining the light weight mass and the night ventilation rate. Because there is no window in the test model, its maximum temperature is still lower than the control cell. The difference between the maximum temperatures in both cells increased to 1.9°C, compared to 0.9°C in the previous test model. But the temperature inside the test model was still outside (above) the comfort zone. At night. the minimum temperatires in the test model are lower than those in the contro]
Figure 5: Outdoor and indoor temperatures of control model and model 5 Test Model 6: medium-weight mass with no window and night ventilated In this series the window is eliminated in the test model but is ventilated at night Because there is no window in the test model, its maximum temperature is lower than the control cell. The difference between the maximum temperatures in both models increase: to 1.9°C, compared to 1.5°C in the previous test. At night, the mean minimum temperatures in the test model are lower than those in the control model, but not quite a: low as the outdoor minimum temperature. mass with concrete which is heavy weight mass. Both models have 100% windows however only the test model is ventilated at night. I'he maximum temperatures inside both cells are wider apart (3.4°C) than in the previou: series (1.9°C). Since both models have their windows at 100% of their size, the difference between the daytime maximum temperatures in the control model and the tes model is due to the effect of the thermal inertia of the mass, which is cooled at night by ventilation (Fig. 6). At night, when the fans are activated in the test model, the minimun temperature inside this model is much higher than the temperature in the control mode by 0.34°C
Figure 5: Outdoor and indoor temperatures of control model and model 5 Test Model 6: medium-weight mass with no window and night ventilated In this series the window is eliminated in the test model but is ventilated at night Because there is no window in the test model, its maximum temperature is lower than the control cell. The difference between the maximum temperatures in both models increase: to 1.9°C, compared to 1.5°C in the previous test. At night, the mean minimum temperatures in the test model are lower than those in the control model, but not quite a: low as the outdoor minimum temperature. mass with concrete which is heavy weight mass. Both models have 100% windows however only the test model is ventilated at night. I'he maximum temperatures inside both cells are wider apart (3.4°C) than in the previou: series (1.9°C). Since both models have their windows at 100% of their size, the difference between the daytime maximum temperatures in the control model and the tes model is due to the effect of the thermal inertia of the mass, which is cooled at night by ventilation (Fig. 6). At night, when the fans are activated in the test model, the minimun temperature inside this model is much higher than the temperature in the control mode by 0.34°C
Figure 6: Outdoor and indoor temperatures of control model and model 7 Test Model 8: heavy-weight mass with 54% window to floor ratio In this series the window of the experimental cell is reduced to 50% of the original size while maintaining the extra mass. Because the window is smaller, the maximum temperature in the experimental cell is lower than in the control cell and the difference between the maximum temperatures in both cells increases to 3.9°C, compared to 3.4°C in the previous series (Fig. 7). At night, the minimum temperatures in the test model are always higher than those in the control model by a mean of 0.42°C.
Figure 6: Outdoor and indoor temperatures of control model and model 7 Test Model 8: heavy-weight mass with 54% window to floor ratio In this series the window of the experimental cell is reduced to 50% of the original size while maintaining the extra mass. Because the window is smaller, the maximum temperature in the experimental cell is lower than in the control cell and the difference between the maximum temperatures in both cells increases to 3.9°C, compared to 3.4°C in the previous series (Fig. 7). At night, the minimum temperatures in the test model are always higher than those in the control model by a mean of 0.42°C.
Figure 7: Outdoor and indoor temperatures of control model and model 8
Figure 7: Outdoor and indoor temperatures of control model and model 8
Figure 8: Outdoor and indoor temperatures of control model and model 9
Figure 8: Outdoor and indoor temperatures of control model and model 9
Table 3: Difference of indoor maximum temperature of models below that of control model
Table 3: Difference of indoor maximum temperature of models below that of control model
Table 2: Comparison of the maximum average temperatures in the control model The indoor maximum temperatures in the low-mass models have the smallest difference with the control model. During the cooler days the indoor maximum was above the outdoor’s, in spite of the night ventilation. In the case of the high-mass building, as shown in Figs. 9 and 11, the night ventilation has lowered the indoor maximum temperature are consistently below the control model’s indoor maximum. The daily rates of change in the indoor maxima of the light weight mass building were close to the changes in the outdoor average temperature. The daily rates of change in the indoor maxima of the high-mass building were smaller, about one half, in comparison with the changes in the outdoor average temperature.
Table 2: Comparison of the maximum average temperatures in the control model The indoor maximum temperatures in the low-mass models have the smallest difference with the control model. During the cooler days the indoor maximum was above the outdoor’s, in spite of the night ventilation. In the case of the high-mass building, as shown in Figs. 9 and 11, the night ventilation has lowered the indoor maximum temperature are consistently below the control model’s indoor maximum. The daily rates of change in the indoor maxima of the light weight mass building were close to the changes in the outdoor average temperature. The daily rates of change in the indoor maxima of the high-mass building were smaller, about one half, in comparison with the changes in the outdoor average temperature.
Figure 9: Temperature difference ratio for models at night ventilation rate of 10ACH = Nowindow m Window-to-floor ratio = 27% mWindow-to-floor ratio = 54% The best TDR is in series 9, which performs far better, over four times, than the control model. The TDR is twice as good when the window is eliminated (Figure 3). This observation provided the basis for the development of the predictive formula for the expected indoor maximum temperatures, which is described below. An equation that predicts TDR as a function of the floor to window ratio (FWR) is derived for the high mass models. One point for each percentage value of window size in each thermal mass is plotted. Each of these points is the average TDR for that percentage of window. To determine the predictive equation, each series has at least three values, which represent three window sizes.
Figure 9: Temperature difference ratio for models at night ventilation rate of 10ACH = Nowindow m Window-to-floor ratio = 27% mWindow-to-floor ratio = 54% The best TDR is in series 9, which performs far better, over four times, than the control model. The TDR is twice as good when the window is eliminated (Figure 3). This observation provided the basis for the development of the predictive formula for the expected indoor maximum temperatures, which is described below. An equation that predicts TDR as a function of the floor to window ratio (FWR) is derived for the high mass models. One point for each percentage value of window size in each thermal mass is plotted. Each of these points is the average TDR for that percentage of window. To determine the predictive equation, each series has at least three values, which represent three window sizes.
Figure 10: Correlation between the sum of south and north window to floor ratio and the TDR performance in the models with varying thermal mass, all night ventilated at 1OACH.
Figure 10: Correlation between the sum of south and north window to floor ratio and the TDR performance in the models with varying thermal mass, all night ventilated at 1OACH.
Table 5: Overheated and comfortable hours for seven days in control model Copyright © 2010 Faculty of Architecture and Building Technology, Kwame Nkrumah University of Science and Technology. 1° IPGRC-KNUST
Table 5: Overheated and comfortable hours for seven days in control model Copyright © 2010 Faculty of Architecture and Building Technology, Kwame Nkrumah University of Science and Technology. 1° IPGRC-KNUST
Table 4: Number and percentage of overheated hours for models night ventilated at 10 ACH
Table 4: Number and percentage of overheated hours for models night ventilated at 10 ACH
Table 6: Overheated and comfortable hours for seven days in model 9 se NN EE OD The paper demonstrates that it is possible to reduce the peak indoor temperature throug the effect of the thermal capacity of the building mass, amount solar radiation throug! the window and night-time cooling in the warm-humid climate of the Ashanti region o! Ghana. The study employed a comparative analysis of numerical models based on the characteristics of Ghanaian mode of office building design, as defined in the Ghane building regulation, using the Energy Plus (E+) simulation software. Various models o! varying thermal mass and window-to-floor ratio were analysed and the results were compared. The potential of cooling performances through the reduction of indoor peak temperature were rated by evaluating three variables: (1) maximum indoor temperatures (2) temperature difference ratio (TDR); and (3) percentage of overheated hours. The thermal mass of a model affects thermal inertia so that the peak temperature i: reduced and delayed, thus reducing the cooling load. The improved thermal capacity o!
Table 6: Overheated and comfortable hours for seven days in model 9 se NN EE OD The paper demonstrates that it is possible to reduce the peak indoor temperature throug the effect of the thermal capacity of the building mass, amount solar radiation throug! the window and night-time cooling in the warm-humid climate of the Ashanti region o! Ghana. The study employed a comparative analysis of numerical models based on the characteristics of Ghanaian mode of office building design, as defined in the Ghane building regulation, using the Energy Plus (E+) simulation software. Various models o! varying thermal mass and window-to-floor ratio were analysed and the results were compared. The potential of cooling performances through the reduction of indoor peak temperature were rated by evaluating three variables: (1) maximum indoor temperatures (2) temperature difference ratio (TDR); and (3) percentage of overheated hours. The thermal mass of a model affects thermal inertia so that the peak temperature i: reduced and delayed, thus reducing the cooling load. The improved thermal capacity o!
Table 1: Housing samples for questionnaire administration The semi-structured interview questionnaire was administered to the heads of households or to the spouses of the heads of household in the sampled household. One household head per house was engaged in the interview and questionnaire administration. The research was conducted between the months of July to September, 2009. nn EE EE Beneficiaries were randomly selected in all four locations visited; these were interviewed given the fact that they have been resident in the areas for more than a month. Out of the 120 questionnaires sent out, 78 were received back as shown on table 1 below. The generalisation of the findings of the study to the entire Gauteng Province is in line with the recommendation of Tan (2002) for the determination of sample size. However, considering the nature of subsidized housing and housing subsidy allocation criteria and the entire Housing Subsidy Scheme and beneficiaries’ behaviour, the findings are indicative of what the likely trends are and the issues that need urgent attention.
Table 1: Housing samples for questionnaire administration The semi-structured interview questionnaire was administered to the heads of households or to the spouses of the heads of household in the sampled household. One household head per house was engaged in the interview and questionnaire administration. The research was conducted between the months of July to September, 2009. nn EE EE Beneficiaries were randomly selected in all four locations visited; these were interviewed given the fact that they have been resident in the areas for more than a month. Out of the 120 questionnaires sent out, 78 were received back as shown on table 1 below. The generalisation of the findings of the study to the entire Gauteng Province is in line with the recommendation of Tan (2002) for the determination of sample size. However, considering the nature of subsidized housing and housing subsidy allocation criteria and the entire Housing Subsidy Scheme and beneficiaries’ behaviour, the findings are indicative of what the likely trends are and the issues that need urgent attention.
Table 2: Opinion on the level of satisfaction 1, DISCUSSION OF FINDINGS Where RSI is the relative satisfaction index and Ya is the total sum of the number of the responses; o is the response per each variable rated as shown on table 2 below. Using the equation stated above, the indices for housing satisfaction (RSI) were evaluated for all the variables of housing rated. The results are presented in table 3 below under section C of discussion of findings.
Table 2: Opinion on the level of satisfaction 1, DISCUSSION OF FINDINGS Where RSI is the relative satisfaction index and Ya is the total sum of the number of the responses; o is the response per each variable rated as shown on table 2 below. Using the equation stated above, the indices for housing satisfaction (RSI) were evaluated for all the variables of housing rated. The results are presented in table 3 below under section C of discussion of findings.
The majority of the respondents in the survey were women (65.4%) while 34.6% were men as in figure 4.1 above. Even though the sample was randomly selected, it appears that there is a predominance of women as owners of housing units. This was in line with the promotion of the housing needs of marginalised women.
The majority of the respondents in the survey were women (65.4%) while 34.6% were men as in figure 4.1 above. Even though the sample was randomly selected, it appears that there is a predominance of women as owners of housing units. This was in line with the promotion of the housing needs of marginalised women.
Figure 4.2 above shows that a combined percentage of 51.2% are either married or living together with a spouse. However, 42.3% of the beneficiaries’ were never married, but they have dependents which enabled them to meet the qualifying criteria for the Housing Subsidy Scheme. Copyright © 2010 Faculty of Architecture and Building Technology, Kwame Nkrumal University of Science and Technology. 1° [PGRC-KNUST
Figure 4.2 above shows that a combined percentage of 51.2% are either married or living together with a spouse. However, 42.3% of the beneficiaries’ were never married, but they have dependents which enabled them to meet the qualifying criteria for the Housing Subsidy Scheme. Copyright © 2010 Faculty of Architecture and Building Technology, Kwame Nkrumal University of Science and Technology. 1° [PGRC-KNUST
Figure 4.5: Provinces beneficiaries’ were born
Figure 4.5: Provinces beneficiaries’ were born
Figure 4.6: Beneficiaries’ highest educational qualification
Figure 4.6: Beneficiaries’ highest educational qualification
Figure 4.7: Beneficiaries’ current employment status. 2 Section B: Socio-Economic profile Findings revealed that 37.2% of the respondents are unemployed / looking for work as in Figure 4.7. The largest proportion had only achieved Grade 11 or lower (Standard 9 or lower - final year of secondary education). The fact they have only achieved Grade 11 or lower (Standard 9 or lower) might contribute to them being unemployed. This showed that more people are unemployed in the Gauteng and at the country at large. However, 28.2% were employed, and of the total percentage employed (28.2%), 37.3% are women, while 29.6% are men.
Figure 4.7: Beneficiaries’ current employment status. 2 Section B: Socio-Economic profile Findings revealed that 37.2% of the respondents are unemployed / looking for work as in Figure 4.7. The largest proportion had only achieved Grade 11 or lower (Standard 9 or lower - final year of secondary education). The fact they have only achieved Grade 11 or lower (Standard 9 or lower) might contribute to them being unemployed. This showed that more people are unemployed in the Gauteng and at the country at large. However, 28.2% were employed, and of the total percentage employed (28.2%), 37.3% are women, while 29.6% are men.
The survey as shown in figure 7.8 above showed that a combined total of 89.4% have their monthly household income between RO - R3,500 per month. This is in line with the Housing Department policy that to qualify as a beneficiary of a housing subsidy, the gross household income should be between RO - R3,500 per month. Only a combined total of 10.6% earned above the R3,500 mark, and are not supposed to be allocated a subsidized housing unit because they do not meet the qualifying criteria.
The survey as shown in figure 7.8 above showed that a combined total of 89.4% have their monthly household income between RO - R3,500 per month. This is in line with the Housing Department policy that to qualify as a beneficiary of a housing subsidy, the gross household income should be between RO - R3,500 per month. Only a combined total of 10.6% earned above the R3,500 mark, and are not supposed to be allocated a subsidized housing unit because they do not meet the qualifying criteria.
Figure 4.9: beneficiaries’ primary home usage Findings as shown in figure 4.9 above revealed that 96.2% of the respondents indicatec that they use their houses (solely) for private residential function (only). When furthe
Figure 4.9: beneficiaries’ primary home usage Findings as shown in figure 4.9 above revealed that 96.2% of the respondents indicatec that they use their houses (solely) for private residential function (only). When furthe
Further findings as represented in figure 4.11 above revealed that 94.9% of the respondents have not used their houses for any sort of financial security since it was allocated to them. Only 3.8% have used their houses for financial security. This might be due to the fact that most beneficiaries do not know the worth of what has been given to them because of lack of housing education; as such they cannot appreciate if the housing unit can be used for any other things like the house being collateral for a loan (financial security) apart from the basic home usage. The other issue with beneficiaries not using their houses as a source of financial security might be due to “poverty thinking and mindset”. Most beneficiaries might be thinking that they will not be listened to (taken serious) when they approach the lending institutions. Since beneficiaries use their housing unit basically for private residential function only, respondents were further asked the part of the house mostly used. Figure 9.4 showed that 50.7% respondents use the kitchen mostly. When respondents were asked why this part of the houses is used mostly, 60.0% said they use the area mostly because the house is not partitioned internally; it is an open hall, so it forms part of their daily lives.
Further findings as represented in figure 4.11 above revealed that 94.9% of the respondents have not used their houses for any sort of financial security since it was allocated to them. Only 3.8% have used their houses for financial security. This might be due to the fact that most beneficiaries do not know the worth of what has been given to them because of lack of housing education; as such they cannot appreciate if the housing unit can be used for any other things like the house being collateral for a loan (financial security) apart from the basic home usage. The other issue with beneficiaries not using their houses as a source of financial security might be due to “poverty thinking and mindset”. Most beneficiaries might be thinking that they will not be listened to (taken serious) when they approach the lending institutions. Since beneficiaries use their housing unit basically for private residential function only, respondents were further asked the part of the house mostly used. Figure 9.4 showed that 50.7% respondents use the kitchen mostly. When respondents were asked why this part of the houses is used mostly, 60.0% said they use the area mostly because the house is not partitioned internally; it is an open hall, so it forms part of their daily lives.
asked if the home is used for other things apart from the primary home usage, 91.0% asserted that they do not use it for other things. However, 9.0% did indicate that apart from the primary home use, they also use it for other things. Among the 9.0% that use their homes for other things, 28.6% use their homes to run tuck shop as shown in figure 4.10, while 14.3% use their homes for day care centres, salon businesses, internet café and business centres, selling of beer and to carry out other personal works as shown in figure 4.10. Figure 4.11: Beneficiaries’ have used their houses for any financial security
asked if the home is used for other things apart from the primary home usage, 91.0% asserted that they do not use it for other things. However, 9.0% did indicate that apart from the primary home use, they also use it for other things. Among the 9.0% that use their homes for other things, 28.6% use their homes to run tuck shop as shown in figure 4.10, while 14.3% use their homes for day care centres, salon businesses, internet café and business centres, selling of beer and to carry out other personal works as shown in figure 4.10. Figure 4.11: Beneficiaries’ have used their houses for any financial security
Table 3: Perceived Level of unit satisfaction according to beneficiaries
Table 3: Perceived Level of unit satisfaction according to beneficiaries
Copyright © 2010 Faculty of Architecture and Building Technology, Kwame Nkrumat University of Science and Technology. 1°' IPGRC-KNUST
Copyright © 2010 Faculty of Architecture and Building Technology, Kwame Nkrumat University of Science and Technology. 1°' IPGRC-KNUST
and community atrectea by housing development and to facilitate the active participation of all relevant stakeholders in housing development. Further findings to weigh the original intended expectations when first shortlisted to be given a house and when given the house; revealed that four out of ten different elements of the housing units were met. It can therefore be subjectively concluded that the Department of Housing did not succeeded in meeting the housing needs of the occupants, but from the basic expectation of an improved living conditions from shack and more comfort that previous living, it can be said that beneficiaries are thus satisfied with the overall housing condition even though most of their expectations were not met. Literature did inform that when the gap between what is expected and what is received decreases; residential satisfaction increases (Darkwa, 2006). Residential satisfaction is a subjective evaluation and relies heavily on the beneficiaries’ views, perceptions, previous experiences, behaviour, norms, values and emotions (Francescato, 1998). Lu (1999) also observed that residential satisfaction is a complex construct, affected by a variety of environmental and socio-demoaraphic variables. However, as shown in figure 4.13 above, 29.6% respondent indicated that the house had met their shelter needs as revealed by the survey.
and community atrectea by housing development and to facilitate the active participation of all relevant stakeholders in housing development. Further findings to weigh the original intended expectations when first shortlisted to be given a house and when given the house; revealed that four out of ten different elements of the housing units were met. It can therefore be subjectively concluded that the Department of Housing did not succeeded in meeting the housing needs of the occupants, but from the basic expectation of an improved living conditions from shack and more comfort that previous living, it can be said that beneficiaries are thus satisfied with the overall housing condition even though most of their expectations were not met. Literature did inform that when the gap between what is expected and what is received decreases; residential satisfaction increases (Darkwa, 2006). Residential satisfaction is a subjective evaluation and relies heavily on the beneficiaries’ views, perceptions, previous experiences, behaviour, norms, values and emotions (Francescato, 1998). Lu (1999) also observed that residential satisfaction is a complex construct, affected by a variety of environmental and socio-demoaraphic variables. However, as shown in figure 4.13 above, 29.6% respondent indicated that the house had met their shelter needs as revealed by the survey.
The second semester was used to work on metaphorical themes developed through a method of conceptual art (PED, 2007). Thus, by perceiving images of projects of architectural masters (such as Calatrava, Lord Foster, Renzo Piano, Will Alsop, Rem Koolhaas, Shigeru Ban, Zaha Hadid, Herzog & De Meuron, etc), the framework of the projects (concepts) were extracted and developed into themes. The developed themes were not the ideas on which the masters designed the projects. For instance, the museum in Fig. 1 was perceived to have resulted from subtractions from an initial mass (cube) and Fig. 2 was alleged to have been conceived out of manipulating multiple cubes. Source: Architecture now, volume 2, p. 105
The second semester was used to work on metaphorical themes developed through a method of conceptual art (PED, 2007). Thus, by perceiving images of projects of architectural masters (such as Calatrava, Lord Foster, Renzo Piano, Will Alsop, Rem Koolhaas, Shigeru Ban, Zaha Hadid, Herzog & De Meuron, etc), the framework of the projects (concepts) were extracted and developed into themes. The developed themes were not the ideas on which the masters designed the projects. For instance, the museum in Fig. 1 was perceived to have resulted from subtractions from an initial mass (cube) and Fig. 2 was alleged to have been conceived out of manipulating multiple cubes. Source: Architecture now, volume 2, p. 105
Source: Photograph taken by the author during a field trip
Source: Photograph taken by the author during a field trip
An outline of an object embodying different shapes (Fig. 3) was to be transformed in 3D space. The main objective was recognizing the ability to create new shapes by performing basic movements (with any chosen shape) in space. The students were to use translation (vertical, horizontal or inclined) and rotational movements, and the possibility to relate the moving shape to a line, area (shape) or volume was also considered. Besides, the use of knowledge on basic elements of design and composition was employed. 2 Subtractions from the mass
An outline of an object embodying different shapes (Fig. 3) was to be transformed in 3D space. The main objective was recognizing the ability to create new shapes by performing basic movements (with any chosen shape) in space. The students were to use translation (vertical, horizontal or inclined) and rotational movements, and the possibility to relate the moving shape to a line, area (shape) or volume was also considered. Besides, the use of knowledge on basic elements of design and composition was employed. 2 Subtractions from the mass
Fig. 4. An example of a form in transition exercise (Coffie R.) Fig. 4 and 5 show results on the “form in transition”, and Fig. 6 to 8 illustrate the outcome of the “subtractions from the mass” project. The manipulation of basic shapes results is demonstrated in Fig. 9 to 11.
Fig. 4. An example of a form in transition exercise (Coffie R.) Fig. 4 and 5 show results on the “form in transition”, and Fig. 6 to 8 illustrate the outcome of the “subtractions from the mass” project. The manipulation of basic shapes results is demonstrated in Fig. 9 to 11.
Fig. 7. An example of subtractions from the mass exercise (Allen O.)
Fig. 7. An example of subtractions from the mass exercise (Allen O.)
Fig. 9. An example of manipulation of basic shapes exercise (Djangmah J.)
Fig. 9. An example of manipulation of basic shapes exercise (Djangmah J.)
Construction site managers in Ghana will soon be required to evaluate the environmental impact of their construction sites just as in many countries in the world. This is because environmental management is a key element of site plans demanded by construction clients and local authorities and a requirement of company environmental management systems (Esin and Cosgun, 2007; Teixeira, 2005; Polat and Ballard, n.d.). Construction site managers are therefore expected to possess adequate knowledge of the environmental management areas identified in Table 1. This requires the introduction of environmental impact of construction site activities into Building Technology education curricula in Ghana. Site management courses in current Building Technology curricula are expected to cater for the above environmental concerns.
Construction site managers in Ghana will soon be required to evaluate the environmental impact of their construction sites just as in many countries in the world. This is because environmental management is a key element of site plans demanded by construction clients and local authorities and a requirement of company environmental management systems (Esin and Cosgun, 2007; Teixeira, 2005; Polat and Ballard, n.d.). Construction site managers are therefore expected to possess adequate knowledge of the environmental management areas identified in Table 1. This requires the introduction of environmental impact of construction site activities into Building Technology education curricula in Ghana. Site management courses in current Building Technology curricula are expected to cater for the above environmental concerns.
Figure 1: Project cost and changes to cost curves [source: PMBOK, 2008]
Figure 1: Project cost and changes to cost curves [source: PMBOK, 2008]
Figure 2: A representation of BSIW carried out in Ghana [source: Field Survey, June, 2007] Conceptually, the study was undertaken within the framework that, building services have cost variability being extremely high after project construction. The study sought to find the categories of BSIW carried out in Ghana. It was revealed that, the most common BSIW was for plumbing and electrical services. Other services such as gas, fire and safety preventions as well as lifts installations were gradually creeping into the sector. The Figure 2 below shows a representation of BSIW carried out in Ghana.
Figure 2: A representation of BSIW carried out in Ghana [source: Field Survey, June, 2007] Conceptually, the study was undertaken within the framework that, building services have cost variability being extremely high after project construction. The study sought to find the categories of BSIW carried out in Ghana. It was revealed that, the most common BSIW was for plumbing and electrical services. Other services such as gas, fire and safety preventions as well as lifts installations were gradually creeping into the sector. The Figure 2 below shows a representation of BSIW carried out in Ghana.
Figure 4; Average cost variability in building category types [Source: Field Survey, June 2007] From the study with cost consultants, classifying buildings into categories according to its final use such as residential, office accommodation, hospital, education, ware house and airport, it was observed that, the cost variability which existed in each category of building type was unique. An average range from 4.44% to as much as 129.68% was realized. Figure 4 gives a graphical representation of the average variability that existed amongst the study data.
Figure 4; Average cost variability in building category types [Source: Field Survey, June 2007] From the study with cost consultants, classifying buildings into categories according to its final use such as residential, office accommodation, hospital, education, ware house and airport, it was observed that, the cost variability which existed in each category of building type was unique. An average range from 4.44% to as much as 129.68% was realized. Figure 4 gives a graphical representation of the average variability that existed amongst the study data.
Figure 3: Cost of BSIW in relation to total building cost in Ghana [Source: Field Survey, J une, 2007] generally referred to as the project management or the triple constraint. Cost being one of the arms of the triple constraint triangle is a very important factor to any client in building (PMI, 2008). According to Greeno and Hall (2005), in general, building services contributes to an average of 50% of the total cost of a building project and in some specialized cases, could be as high as 75%. Another study conducted by Y asin in the UK revealed that, building services component is approximately 50 -60% of the total cost of a typical building. However, this study indicated that, in Ghana, BSIW formed an average of 35% (34.74%) of the total building cost. Figure 3 shows a graphical representation of this revelation. This percentage figure can be as high as 92% and as low as 11% depending on the services required and the type of building.
Figure 3: Cost of BSIW in relation to total building cost in Ghana [Source: Field Survey, J une, 2007] generally referred to as the project management or the triple constraint. Cost being one of the arms of the triple constraint triangle is a very important factor to any client in building (PMI, 2008). According to Greeno and Hall (2005), in general, building services contributes to an average of 50% of the total cost of a building project and in some specialized cases, could be as high as 75%. Another study conducted by Y asin in the UK revealed that, building services component is approximately 50 -60% of the total cost of a typical building. However, this study indicated that, in Ghana, BSIW formed an average of 35% (34.74%) of the total building cost. Figure 3 shows a graphical representation of this revelation. This percentage figure can be as high as 92% and as low as 11% depending on the services required and the type of building.
The study further sought the perception of stakeholders on what could be the potential causes of variability in the cost of BSIW. From the study, although 8.84% and 17.64% of architects out of the total sampled consultants attributed the cause of variability to labour management and capital management respectively, the Pareto Chart plotted attributed the major causes to variations, under estimating and fluctuations in that order. The graph is represented in Figure 5.
The study further sought the perception of stakeholders on what could be the potential causes of variability in the cost of BSIW. From the study, although 8.84% and 17.64% of architects out of the total sampled consultants attributed the cause of variability to labour management and capital management respectively, the Pareto Chart plotted attributed the major causes to variations, under estimating and fluctuations in that order. The graph is represented in Figure 5.
Fig. 3. Schematic plan of offices in KCR Fig. 2. Schematic plan of offices in CAP
Fig. 3. Schematic plan of offices in KCR Fig. 2. Schematic plan of offices in CAP
Table 1: Information on selected buildings
Table 1: Information on selected buildings
Table 2: Overview of base case simulation scenarios Using the calibrated thermal performance simulation models, we explored various improvement options (concerning glazing and shading, ventilation, thermal mass, efficient lighting) that could reduce cooling loads as well as the need for extensive active devices for air-conditioning. Information regarding the various scenarios considered fo1 the simulations is summarized in Tables 2 and 3. Cooling energy loads (sensible and latent) were used as the performance indicator (active operation assumption).
Table 2: Overview of base case simulation scenarios Using the calibrated thermal performance simulation models, we explored various improvement options (concerning glazing and shading, ventilation, thermal mass, efficient lighting) that could reduce cooling loads as well as the need for extensive active devices for air-conditioning. Information regarding the various scenarios considered fo1 the simulations is summarized in Tables 2 and 3. Cooling energy loads (sensible and latent) were used as the performance indicator (active operation assumption).
Source: Construction database of the building designer in Tas (EDSL 2008) Table 3: Overview of simulated improvement scenarios
Source: Construction database of the building designer in Tas (EDSL 2008) Table 3: Overview of simulated improvement scenarios
Fig. 7. Comparison of mean outdoor temperature measurements at office locations (DL) with Kumasi weather station data (MET)
Fig. 7. Comparison of mean outdoor temperature measurements at office locations (DL) with Kumasi weather station data (MET)
Fig. 8. Mean daily temperature and relative humidity values (averaged over all days in a month) in CAP building.
Fig. 8. Mean daily temperature and relative humidity values (averaged over all days in a month) in CAP building.
Fig. 10. Outdoor air temperature segments (WF) as against measurements (DL) at building location (KC R) As mentioned earlier, simulation model calibration was performed using segments of a standard weather file with a good fit to our local measurements. Fig. 10 and 11 show samples of time intervals where the weather file data (WF) and our measurements at building sites (DL) showed a relatively good agreement. These weather file segments were subsequently used to predict indoor temperature values and compare those with the respective measured temperatures.
Fig. 10. Outdoor air temperature segments (WF) as against measurements (DL) at building location (KC R) As mentioned earlier, simulation model calibration was performed using segments of a standard weather file with a good fit to our local measurements. Fig. 10 and 11 show samples of time intervals where the weather file data (WF) and our measurements at building sites (DL) showed a relatively good agreement. These weather file segments were subsequently used to predict indoor temperature values and compare those with the respective measured temperatures.
Fig. 9. Mean daily temperature and relative humidity values (averaged over all days in a month) in KCR building (based on measured data from 8 am to 5 pm)
Fig. 9. Mean daily temperature and relative humidity values (averaged over all days in a month) in KCR building (based on measured data from 8 am to 5 pm)
Fig. 12. Measured versus simulation indoor air temperatures in CAP
Fig. 12. Measured versus simulation indoor air temperatures in CAP
Fig. 13. Measured versus simulation indoor air temperatures in KCR
Fig. 13. Measured versus simulation indoor air temperatures in KCR
Table 4: Simulated annual cooling loads [kKWh'm™~a’‘] for all buildings
Table 4: Simulated annual cooling loads [kKWh'm™~a’‘] for all buildings
Fig. 14. Overview of the relationship between measured and simulated indoor air temperatures in four reference buildings
Fig. 14. Overview of the relationship between measured and simulated indoor air temperatures in four reference buildings
Table 5: Mean overheating (OH, in K) and fraction of time (FOT in %) with indoor conditions within the comfort zone (from 8 am to 5 pm, assumed indoor air speed 1.0 m.s”)
Table 5: Mean overheating (OH, in K) and fraction of time (FOT in %) with indoor conditions within the comfort zone (from 8 am to 5 pm, assumed indoor air speed 1.0 m.s”)
Fig. 15. Mean daily temperature and relative humidity values in J anuary at building CAP (based on simulated data from 8am to 5pm) together with thermal comfort zones corresponding to different indoor air speed assumptions
Fig. 15. Mean daily temperature and relative humidity values in J anuary at building CAP (based on simulated data from 8am to 5pm) together with thermal comfort zones corresponding to different indoor air speed assumptions
Table 6: PMV and PPD (in % ) for all buildings 6 Estimated annual energy use, costs, CO2 emission and retrofitting (payback me)
Table 6: PMV and PPD (in % ) for all buildings 6 Estimated annual energy use, costs, CO2 emission and retrofitting (payback me)
Table 7: Total annual energy use, costs, and CO>2 emission reduction potential (by upgrading the buildings from the base case (BC) to CI cases Copyright © 2010 Faculty of Architecture and Building Technology, Kwame Nkrumah University of Science and Technology. 1° IPGRC-KNUST
Table 7: Total annual energy use, costs, and CO>2 emission reduction potential (by upgrading the buildings from the base case (BC) to CI cases Copyright © 2010 Faculty of Architecture and Building Technology, Kwame Nkrumah University of Science and Technology. 1° IPGRC-KNUST
Figure 1: Economic and Social Importance of Improving Strategic Management of Public Procurement, Source: Adopted and Adapted from Idea International (2009) government-financed procurement alone. Several studies have confirmed that procurement management is a valuable instrument for implementing pro-social equity policies and has, historically, been used by governments to encourage more equitable social benefits (Westring, 1997; Larmour, 2006; Cavill and Sohail, 2005). As explained by Idea International (2009) and supported by other studies, the attainment of these economic benefits through PRM then creates a better chance to achieve millennium development goals and embark on other government objectives; enhanced respect for rule of law; increased access by local market to government contracts; improvements in social sector services; better environmental management; and improved corporate social responsibility (Walker, Segon and Rowlinson, 2008; Waddock, 2006). The establishment of a specialized unit committee enshrined in the Public Procurement Act 2003 (Act 663), which is mandated to provide training and capacity building for
Figure 1: Economic and Social Importance of Improving Strategic Management of Public Procurement, Source: Adopted and Adapted from Idea International (2009) government-financed procurement alone. Several studies have confirmed that procurement management is a valuable instrument for implementing pro-social equity policies and has, historically, been used by governments to encourage more equitable social benefits (Westring, 1997; Larmour, 2006; Cavill and Sohail, 2005). As explained by Idea International (2009) and supported by other studies, the attainment of these economic benefits through PRM then creates a better chance to achieve millennium development goals and embark on other government objectives; enhanced respect for rule of law; increased access by local market to government contracts; improvements in social sector services; better environmental management; and improved corporate social responsibility (Walker, Segon and Rowlinson, 2008; Waddock, 2006). The establishment of a specialized unit committee enshrined in the Public Procurement Act 2003 (Act 663), which is mandated to provide training and capacity building for
systems approach are establishing precise and useful objectives, planning study methods and then testing achievement of objectives (Cohen, 1987). Implicit in the three key phases of the instructional systems approach is called instructional alignment (Lochun, 2006; Cohen, 1987); design coherence (Knight, 2002); and constructive alignment (Biggs, 1996). Constructive alignment refers to the matching or aligning of learning and teaching activities, course team philosophy and assessment methods. Linking constructive alignment to the instructional systems approach, the study methods planned and implemented should provide affordances in the learning environment (Knight, 2002) and these in turn would assist students in the achievement of the precise course objectives (Biggs, 1996). The constructive alignment approach has as a key element the centrality of the learner’s activities in learning (Lochun, 2006; Biggs, 2003). The teacher’s role is to create appropriate learning environments that engage the student in learning activities that enable them to meet the learning outcomes (Lochun, 2006; Tepper, 2008). As depicted in Figure 2 below, the basic premise of the whole constructive alignment system is that the curriculum is designed so that the learning activities and assessment tasks are aligned with the learning outcomes that are intended in the course (Biggs, 2003: 1996). Figure 2: Aligning learning outcomes, learning and teaching activities and the assessment. Source: Adopted and Adapted from Biggs (1996)
systems approach are establishing precise and useful objectives, planning study methods and then testing achievement of objectives (Cohen, 1987). Implicit in the three key phases of the instructional systems approach is called instructional alignment (Lochun, 2006; Cohen, 1987); design coherence (Knight, 2002); and constructive alignment (Biggs, 1996). Constructive alignment refers to the matching or aligning of learning and teaching activities, course team philosophy and assessment methods. Linking constructive alignment to the instructional systems approach, the study methods planned and implemented should provide affordances in the learning environment (Knight, 2002) and these in turn would assist students in the achievement of the precise course objectives (Biggs, 1996). The constructive alignment approach has as a key element the centrality of the learner’s activities in learning (Lochun, 2006; Biggs, 2003). The teacher’s role is to create appropriate learning environments that engage the student in learning activities that enable them to meet the learning outcomes (Lochun, 2006; Tepper, 2008). As depicted in Figure 2 below, the basic premise of the whole constructive alignment system is that the curriculum is designed so that the learning activities and assessment tasks are aligned with the learning outcomes that are intended in the course (Biggs, 2003: 1996). Figure 2: Aligning learning outcomes, learning and teaching activities and the assessment. Source: Adopted and Adapted from Biggs (1996)
a) 0 cells b) 0 cells c) 0 cells d) 0 cells .0%) have expected frequencies less than 5. The minimum expected cell frequency is 12.4; .0%) have expected frequencies less than 5. The minimum expected cell frequency is 16.0; .0%) have expected frequencies less than 5. The minimum expected cell frequency is 13.5; .0%) have expected frequencies less than 5. The minimum expected cell frequency is 11.8. ee a Table 1: Chi Square Test of Procurement Management Knowledge Areas
a) 0 cells b) 0 cells c) 0 cells d) 0 cells .0%) have expected frequencies less than 5. The minimum expected cell frequency is 12.4; .0%) have expected frequencies less than 5. The minimum expected cell frequency is 16.0; .0%) have expected frequencies less than 5. The minimum expected cell frequency is 13.5; .0%) have expected frequencies less than 5. The minimum expected cell frequency is 11.8. ee a Table 1: Chi Square Test of Procurement Management Knowledge Areas
Table 1.0 Summary of Responses of Questionnaires sent out
Table 1.0 Summary of Responses of Questionnaires sent out
Figure 1: Weighting of factors that cause cash flow deviation of contractors
Figure 1: Weighting of factors that cause cash flow deviation of contractors
Table 2. Overall Ranking: Management of Cash Flow Deviation Factors on C onstruction Duntanto tn Channa
Table 2. Overall Ranking: Management of Cash Flow Deviation Factors on C onstruction Duntanto tn Channa
Table 3. Significant testing of factors contractor’s cash flow management factors Where S means significant factor and N means insignificant factor.
Table 3. Significant testing of factors contractor’s cash flow management factors Where S means significant factor and N means insignificant factor.
1“ International Postgraduate Research Conference on the Built Environme F.D.K Fugar and E. Adinyira (Eds) KNUST, 2010 Copyright © 2010 Faculty of Architecture and Building Technology. Kwame Nkrumah University of Science and Technology. 1° IPGRC KNUST
1“ International Postgraduate Research Conference on the Built Environme F.D.K Fugar and E. Adinyira (Eds) KNUST, 2010 Copyright © 2010 Faculty of Architecture and Building Technology. Kwame Nkrumah University of Science and Technology. 1° IPGRC KNUST
KRINUOL, ZULU An approach adopted to enhance the cash flow situation of the contractors towards fast delivery was advance mobilization. This was after advance mobilization guarantee had been submitted and approved by the project consultants. All the contractors were given advance mobilization. 66.7% of the contractors received their payments within the first 3 weeks (1-7 days, 16.7% 8-15 days, while 8.3% 16-21 days). These disbursement arrangements lead little variation in the planned disbursement as shown on Figure 2.
KRINUOL, ZULU An approach adopted to enhance the cash flow situation of the contractors towards fast delivery was advance mobilization. This was after advance mobilization guarantee had been submitted and approved by the project consultants. All the contractors were given advance mobilization. 66.7% of the contractors received their payments within the first 3 weeks (1-7 days, 16.7% 8-15 days, while 8.3% 16-21 days). These disbursement arrangements lead little variation in the planned disbursement as shown on Figure 2.
Copyright © 2010 Faculty of Architecture and Building Technology. Kwame Nkrumah University of Science and Technology. 1° IPGRC-KNUST
Copyright © 2010 Faculty of Architecture and Building Technology. Kwame Nkrumah University of Science and Technology. 1° IPGRC-KNUST
Table I.: Positions held by respondents able I shows that more than half of the respondents were quantity surveyors and engineers. Th lajority (56 percent) of the respondents have more than five years experience in the constructio dustry. A total of twenty five percent of the respondents work for organisations having mor 1an 300 employees and only 17% had less than 25 employees. The rest (58%) had more than 2 nd less than 300 employees. This confirms that the majority of organisations were drawn fror 1edium and large organisations are per classification of the Ghanaian Statistics Service (GSC) he respondents were asked to rate these barriers on a four-point scale from “strongly disagree 1 to “strongly agree” = 4. Thus using the criticality cut off point of 2.40, represente greement levels. The reliability and internal consistency of the survey instrument comprisin 1e 7 barriers items found in Table II was examined using the cronbach’s alphas coefficient. Th ‘ronbach’s Alpha value was 0.670 (F-statistic = 2.899, Sig. = 0.009) alpha equal to 0.7 thu \dicating a high reliability of scales (Nunnally, 1978).
Table I.: Positions held by respondents able I shows that more than half of the respondents were quantity surveyors and engineers. Th lajority (56 percent) of the respondents have more than five years experience in the constructio dustry. A total of twenty five percent of the respondents work for organisations having mor 1an 300 employees and only 17% had less than 25 employees. The rest (58%) had more than 2 nd less than 300 employees. This confirms that the majority of organisations were drawn fror 1edium and large organisations are per classification of the Ghanaian Statistics Service (GSC) he respondents were asked to rate these barriers on a four-point scale from “strongly disagree 1 to “strongly agree” = 4. Thus using the criticality cut off point of 2.40, represente greement levels. The reliability and internal consistency of the survey instrument comprisin 1e 7 barriers items found in Table II was examined using the cronbach’s alphas coefficient. Th ‘ronbach’s Alpha value was 0.670 (F-statistic = 2.899, Sig. = 0.009) alpha equal to 0.7 thu \dicating a high reliability of scales (Nunnally, 1978).
Notes: * Significant difference at 95 percent confidence level. 'The mean score (MS) based on participants levels of agreement on the agreement level of a scale of 4 = strongly agree, 3 = agree, 2 = disagree, and 1 = strongly disagree ; 7R = Ranking * Intemational Postgraduate Research Conference on the Built Environment '.D.K Fugar and E. Adinyira (Eds) “NUST. 2010 For the contractors, the means ranged between 3.21 (brl = awareness of risk management processes) and 2.61 (br4 = lack of information); for clients between 3.30 (br1 = awareness of risk management processes) and 2.83 (br6 = time constraints); and finally for consultants, between 3.17 (br2 =lack of experience) and 2.83 (br6 = time constraints). Based on the data presented in Table II, it is clear that all the barriers were deemed to be crucial or important as they scored above the 2.40 cut off point. However, examination of Table II indicates that there was a disparity in the ranking of the barriers by the construction professions working the three different types of organisations. The top three barriers according to the professions working for contractors were as follows: “br1 = awareness of risk management processes (mean = 3.21); “br5 = availablity of specialist risk management consultants” (mean = 3.03); and “br6 = time constraints” (mean = 2.94). The clients also ranked “brl = awareness of risk management processes (mean = 3.30) highly, followed by “br2 = lack of experience” (mean = 3.26); and “‘br7 = implementation cost” (mean = 3.04). On the other hand, the consultants viewed “br2 = lack of 2xperience” (mean = 3.17) as critical followed by “br4 =lack of information” (mean = 3.15); and “br3 = lack of co-ordination between parties involved” (mean = 3.15).
Notes: * Significant difference at 95 percent confidence level. 'The mean score (MS) based on participants levels of agreement on the agreement level of a scale of 4 = strongly agree, 3 = agree, 2 = disagree, and 1 = strongly disagree ; 7R = Ranking * Intemational Postgraduate Research Conference on the Built Environment '.D.K Fugar and E. Adinyira (Eds) “NUST. 2010 For the contractors, the means ranged between 3.21 (brl = awareness of risk management processes) and 2.61 (br4 = lack of information); for clients between 3.30 (br1 = awareness of risk management processes) and 2.83 (br6 = time constraints); and finally for consultants, between 3.17 (br2 =lack of experience) and 2.83 (br6 = time constraints). Based on the data presented in Table II, it is clear that all the barriers were deemed to be crucial or important as they scored above the 2.40 cut off point. However, examination of Table II indicates that there was a disparity in the ranking of the barriers by the construction professions working the three different types of organisations. The top three barriers according to the professions working for contractors were as follows: “br1 = awareness of risk management processes (mean = 3.21); “br5 = availablity of specialist risk management consultants” (mean = 3.03); and “br6 = time constraints” (mean = 2.94). The clients also ranked “brl = awareness of risk management processes (mean = 3.30) highly, followed by “br2 = lack of experience” (mean = 3.26); and “‘br7 = implementation cost” (mean = 3.04). On the other hand, the consultants viewed “br2 = lack of 2xperience” (mean = 3.17) as critical followed by “br4 =lack of information” (mean = 3.15); and “br3 = lack of co-ordination between parties involved” (mean = 3.15).
Although the overall results suggest that statistical differences were found in only 2 out of the 7 barriers, it is still evident that there was a disparity in the ranking of these barriers. This suggests that construction professionals within the Ghanaian construction industry, irrespective of the sector (clients, consultants or contractors) that they worked for generally have different opinions regarding the barriers influencing the deployment of RAMP. As such, the null hypothesis of no significant difference in the perception of different types of organisations to the barriers to RAMP is not upheld.
Although the overall results suggest that statistical differences were found in only 2 out of the 7 barriers, it is still evident that there was a disparity in the ranking of these barriers. This suggests that construction professionals within the Ghanaian construction industry, irrespective of the sector (clients, consultants or contractors) that they worked for generally have different opinions regarding the barriers influencing the deployment of RAMP. As such, the null hypothesis of no significant difference in the perception of different types of organisations to the barriers to RAMP is not upheld.
Table 1: Summary of Distributed and Received Questionnaire
Table 1: Summary of Distributed and Received Questionnaire
Table 2. Personal particulars of respondents
Table 2. Personal particulars of respondents
Table 3: The extent of worker satisfaction with aspects of work
Table 3: The extent of worker satisfaction with aspects of work
Table 4: Worker response on their desire to be in the construction industry
Table 4: Worker response on their desire to be in the construction industry
|‘ International Postgraduate Research Conference on the Built Environme ‘.D.K Fugar and E. A dinyira (Eds) KNUST, 2010 Again Tables 4,5,6,7 and 8 provide data on workers’ response to factors affecting worker job satisfaction in the following thematic areas: (1) desire to be in the construction industry, (2) work environment and worker job satisfaction, (3) Worker’s own characteristics and job satisfaction, (4) Human Relations and Worker Job Satisfaction, and (5) supervision and job satisfaction respectively. The responses of workers were measured on the scale 5, 4, 3, 2, and 1 respectively for strongly agree, agree, uncertain, disagree and strongly disagree.
|‘ International Postgraduate Research Conference on the Built Environme ‘.D.K Fugar and E. A dinyira (Eds) KNUST, 2010 Again Tables 4,5,6,7 and 8 provide data on workers’ response to factors affecting worker job satisfaction in the following thematic areas: (1) desire to be in the construction industry, (2) work environment and worker job satisfaction, (3) Worker’s own characteristics and job satisfaction, (4) Human Relations and Worker Job Satisfaction, and (5) supervision and job satisfaction respectively. The responses of workers were measured on the scale 5, 4, 3, 2, and 1 respectively for strongly agree, agree, uncertain, disagree and strongly disagree.
Table 6. Worker’s own characteristics and job satisfaction
Table 6. Worker’s own characteristics and job satisfaction
Table 5. Worker response to work environment and job satisfaction
Table 5. Worker response to work environment and job satisfaction
Copyright © 2010 Faculty of Architecture and Building Technology. Kwame Nkrumah University of Science and Technology. 1° IPGRC-KNUST
Copyright © 2010 Faculty of Architecture and Building Technology. Kwame Nkrumah University of Science and Technology. 1° IPGRC-KNUST
Table 11. Worker Response to Retention and J ob Satisfaction
Table 11. Worker Response to Retention and J ob Satisfaction
Table 12.C hi -square test of workers satisfaction with demographic variables
Table 12.C hi -square test of workers satisfaction with demographic variables
Though some foreign companies are owned by sole proprietors, they have a Board of Directors (BOD) who manages the companies. They also have organizational structures outlining the role and hierarchy of personnel which to a large extent is adopted in practice (Table 2). However policies of the parent companies are generally adapted at the discretion of the MD. In the case of the JV, a BOD compnising representatives of the mother company and the local partners take policy decisions. Employees of local companies however have direct access to the Managing Director or General Manager which is not the case in foreign companies. All classes of companies were found to have defined organizational structures showing the functional and organizational relationships between personnel. These structures were generally flat. However, in local firms these exist as documents but not practiced and did not have adequately trained personnel to execute this function. A majority of foreign companies however have qualifies HR personnel though they do not give them autonomy.
Though some foreign companies are owned by sole proprietors, they have a Board of Directors (BOD) who manages the companies. They also have organizational structures outlining the role and hierarchy of personnel which to a large extent is adopted in practice (Table 2). However policies of the parent companies are generally adapted at the discretion of the MD. In the case of the JV, a BOD compnising representatives of the mother company and the local partners take policy decisions. Employees of local companies however have direct access to the Managing Director or General Manager which is not the case in foreign companies. All classes of companies were found to have defined organizational structures showing the functional and organizational relationships between personnel. These structures were generally flat. However, in local firms these exist as documents but not practiced and did not have adequately trained personnel to execute this function. A majority of foreign companies however have qualifies HR personnel though they do not give them autonomy.
ee ee ee ee ee Se ee oe This function comprises reward management and a satisfying psychological contract. Companies thrive on their ability to attract and retain highly skilled and the right calibre of personnel, within a budget. Professionals negotiate their salaries individually based on a grading system: functional roles, whereas artisans and labourers are daily rated as per the CBA as wages: weekly, fortnightly, or salaried, depending on the agreement. Additional financial and non-financial rewards are generally based on management discretion and availability of resources (Table 4).
ee ee ee ee ee Se ee oe This function comprises reward management and a satisfying psychological contract. Companies thrive on their ability to attract and retain highly skilled and the right calibre of personnel, within a budget. Professionals negotiate their salaries individually based on a grading system: functional roles, whereas artisans and labourers are daily rated as per the CBA as wages: weekly, fortnightly, or salaried, depending on the agreement. Additional financial and non-financial rewards are generally based on management discretion and availability of resources (Table 4).
Table 2: Relative Importance Index and Rank of Delay Factors according to Clients, Contractors and Consultants
Table 2: Relative Importance Index and Rank of Delay Factors according to Clients, Contractors and Consultants
Figure 1: Pattern of contribution of CPFs to accident causation (Adapted from Surgji et al. (2001) and Haslam et al. (2005)) As demonstrated by the above review, CPFs do not directly cause accidents but do so throug! other accident causal factors. These other causal factors which directly lead to accidents ar proximal causal factors (PFs) (Suraji et al., 2001; Haslam et al., 2005), and these are closer t accident events than CPFs. CPFs being distal to accident events are therefor distal/root/originating causal factors (Suraji et al., 2001; Haslam et al., 2005) and it is by thei introduction of the proximal factors that CPFs contribute to accident causation. CPFs also to large extent emanate from the client’s brief, design decisions and project management decision at the pre-construction stage of project procurement (cf. Suraji et al. (2001), Haslam et al. (2005 and Cheng et al. (2005)). Building on this brief background, the process/pattern by which a CP! contributes to accidents could thus be illustrated as shown in Figure 1.
Figure 1: Pattern of contribution of CPFs to accident causation (Adapted from Surgji et al. (2001) and Haslam et al. (2005)) As demonstrated by the above review, CPFs do not directly cause accidents but do so throug! other accident causal factors. These other causal factors which directly lead to accidents ar proximal causal factors (PFs) (Suraji et al., 2001; Haslam et al., 2005), and these are closer t accident events than CPFs. CPFs being distal to accident events are therefor distal/root/originating causal factors (Suraji et al., 2001; Haslam et al., 2005) and it is by thei introduction of the proximal factors that CPFs contribute to accident causation. CPFs also to large extent emanate from the client’s brief, design decisions and project management decision at the pre-construction stage of project procurement (cf. Suraji et al. (2001), Haslam et al. (2005 and Cheng et al. (2005)). Building on this brief background, the process/pattern by which a CP! contributes to accidents could thus be illustrated as shown in Figure 1.
Table 1: An illustration of the extent of contribution of C PFs to accident causation RAO SA A SERS Ee AE whose decisions CPFs emanate could by this insight select CPFs that contribute less to accident causation (i.e. have a lower potential to cause H&S harm).
Table 1: An illustration of the extent of contribution of C PFs to accident causation RAO SA A SERS Ee AE whose decisions CPFs emanate could by this insight select CPFs that contribute less to accident causation (i.e. have a lower potential to cause H&S harm).
Szymberski (1997) indicated that the ideal situation is for construction worker safety to be « prime consideration of the project planners and designers at the conceptual and preliminary design phases in project procurement. The influence of pre-construction decision making/planning on the H&S outcomes of projects is also acknowledged by Sir John Egai (Strategic Forum for Construction, 2002), the Office of Government Commerce Procuremen Guide 10 (Office of Government Commerce, 2004), and the Construction (Design anc Management) Regulations 2007 (CDM 2007) which aims at integrating H&S into the management of projects from the design concept onwards (Health and Safety Commission 2007).
Szymberski (1997) indicated that the ideal situation is for construction worker safety to be « prime consideration of the project planners and designers at the conceptual and preliminary design phases in project procurement. The influence of pre-construction decision making/planning on the H&S outcomes of projects is also acknowledged by Sir John Egai (Strategic Forum for Construction, 2002), the Office of Government Commerce Procuremen Guide 10 (Office of Government Commerce, 2004), and the Construction (Design anc Management) Regulations 2007 (CDM 2007) which aims at integrating H&S into the management of projects from the design concept onwards (Health and Safety Commission 2007).
Fig.1: Percentage of occupants who generally found their office climate to be poor and the mean yearly indoor temperatures Fig.2: Percentage of occupants who had backache, eyestrain and headache
Fig.1: Percentage of occupants who generally found their office climate to be poor and the mean yearly indoor temperatures Fig.2: Percentage of occupants who had backache, eyestrain and headache
temperatures. Fig. 2 shows the percentage of occupants who had backache, eyestrain and headache as health complaints. In addition, Fig. 3 shows the percentage of occupants who had general fatigue, respiratory problems and sore throat as health complaints. Moreover, the percentage of occupants who had neck pain, rheumatic pains, stiffness of limbs and nasal irritation are shown in Fig. 4. Fig. 5 addresses the percentage of occupants who had diverse health complaints, perception of poor office climate and mean indoor temperatures of the buildings.
temperatures. Fig. 2 shows the percentage of occupants who had backache, eyestrain and headache as health complaints. In addition, Fig. 3 shows the percentage of occupants who had general fatigue, respiratory problems and sore throat as health complaints. Moreover, the percentage of occupants who had neck pain, rheumatic pains, stiffness of limbs and nasal irritation are shown in Fig. 4. Fig. 5 addresses the percentage of occupants who had diverse health complaints, perception of poor office climate and mean indoor temperatures of the buildings.
Fig.5: Percentage of occupants who had diverse health complaints, perception of poor office climate and mean indoor temperature of the workspaces
Fig.5: Percentage of occupants who had diverse health complaints, perception of poor office climate and mean indoor temperature of the workspaces
Table 2: Total Variance Explained Copyright © 2010 Faculty of Architecture and Building Technology. Kwame Nkrumah University of Science and Technology. 1° IPGRC-KNUST
Table 2: Total Variance Explained Copyright © 2010 Faculty of Architecture and Building Technology. Kwame Nkrumah University of Science and Technology. 1° IPGRC-KNUST
5.1 Number of Factors Extracted From Table 2 factor 1 has total variance of 28,591, which is 42.613% of the total variance of the 67 factors; factor 2 has total variance of 3,438, which is 5.131% of the total variance of the 67 factors. The Cumulative % column is the sum of the percentage variances for that factor and the factors that precede it in the table. From Table 2 it is seen that about 52% of the total variance is explained by the first three factors. The factors are arranged in decreasing order of total variance
5.1 Number of Factors Extracted From Table 2 factor 1 has total variance of 28,591, which is 42.613% of the total variance of the 67 factors; factor 2 has total variance of 3,438, which is 5.131% of the total variance of the 67 factors. The Cumulative % column is the sum of the percentage variances for that factor and the factors that precede it in the table. From Table 2 it is seen that about 52% of the total variance is explained by the first three factors. The factors are arranged in decreasing order of total variance
Figure 1: Scree Plot of Factors (C omponents)
Figure 1: Scree Plot of Factors (C omponents)
Copyright © 2010 Faculty of Architecture and Building Technology. Kwame Nkrumah University of Science and Technology. 1° IPGRC-KNUST
Copyright © 2010 Faculty of Architecture and Building Technology. Kwame Nkrumah University of Science and Technology. 1° IPGRC-KNUST
Copyright © 2010 Faculty of Architecture and Building Technology. Kwame Nkrumah University of Science and Technology. 1° IPGRC-KNUST
Copyright © 2010 Faculty of Architecture and Building Technology. Kwame Nkrumah University of Science and Technology. 1° IPGRC-KNUST
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