Climate change is receiving increasing attention in recent years. The transportation sector contributes substantially to increased fuel consumption, greenhouse gas (GHG) emissions, and poor air quality, which imposes a serious respiratory health hazard. Road transport has made a significant contribution to this effect. Consequently, many countries have attempted to mitigate climate change using various strategies. This study analysed and compared the number of policies and other approaches necessary to achieve reduced fuel consumption and carbon emission. Frequency aggregation indicates that the mitigation policies associated with driving behaviours adopted to curtail this consumption and decrease hazardous emissions, as well as a safety enhancement. Furthermore, car-sharing/carpooling was the least investigated approach to establish its influence on mitigation of climate change. Additionally, the influence of such driving behaviours as acceleration/deceleration and the compliance to speed limits on each approach was discussed. Other driving behaviours, such as gear shifting, compliance to traffic laws, choice of route, and idling and braking style, were also discussed. Likewise, the influence of aggression, anxiety, and motivation on driving behaviour of motorists was highlighted. The research determined that driving behaviours can lead to new adaptive driving behaviours and, thus, cause a significant decrease of vehicle fuel consumption and CO₂ emissions.

Construction labor productivity is critical to the success of the industry. It is thus, important for the estimation and scheduling of construction project. However, most of the traditional construction firms have no accurate data on labor productivity. Therefore, this paper aims to identify through literature review those factors that affect labor production rate and evaluate their effects on the performance of the industry. The research made use of the 44 returned questionnaires from the contractors firms. Statistical package for social sciences (SPSS) to compute the mean score for each factor. These factors were subsequently ranked based on the mean score value.The results of the analysis has shown that, based on the management level factors “lack of motivation and incentive, lack of equipment, disruption of power and water supply and inspection delay” are the most significant factors affecting labour productivity each with mean score values of 0.79, 0.44, 0.38 and 0.35 respectively. Also based on the site level factors “lack of adequate skillful worker with specific scope of work” at site, delay in material supply, weather, access to the site, crew size and communication problems between foreign and local staff are the top six most significant factors affecting labour productivity each with the mean score values of 0.77, 0.75, 0.75, 0.66, 0.61 and 0.53 respectively. Similarly, all the respondents seem to have agreed in their perception on the severity of factors affecting labour productivity.

Variation does not only affect labour productivity but also leads to the dispute, time and cost overrun. Consequently, it affects projects performance. It is, therefore, imperative for construction professionals to eliminate unnecessary additional cost from a project so as to optimize the client’s benefit against input resources. This paper identifies and examines the most significant causes that contribute to the variation orders. Also, Nigerian construction industry is used as a case study. Variation orders causing factors were assessed. Questionnaires were administered to clients, consultants and contractors to elicit information regarding variation causing factors. These factors were analyzed using frequency aggregation, mean score method and subsequently ranked according to their severity. The result revealed three most significant causes of variation which are: ‘Change of plan’’ with the highest frequency of 58% then followed by ‘‘Conflicting contract documents (50%). The next most frequent causing factors were the “substitution of materials” and “change in design” each with frequency of 43%. The least causing factor of variation was the “error and omission in design” with the frequency of 10%. Also differing site condition, new government regulation, weather condition were identified as other cause of variation with the frequency of 27%, 29% and 10% respectively. It has also shown that most critical source of variation order is the client due to change of plan then followed by consultant due to conflicting contract document.

Estimation of cost for building and civil engineering projects with minimum error at the conceptual stage of project development is crucial for planning. This paper evaluated the most significant cost escalation causing factors in building and civil engineering projects. Questionnaires were administered to clients, consultants and contractors to elicit information regarding their opinions with regard to these factors. Mean score value for each factor was determined. Also level of agreement of ranking of such factors between groups was investigated. The results of the analysis show that the most significant causes were the “Fluctuation of price of material” and “Variations” with the highest mean score values of 3.9 and 3.73 respectively. Also there was agreement in the opinions between all the groups with regard to these factors. A linear multiple regression models for the prediction of final cost of construction of building and civil engineering projects were developed using Statistical Package for Social Sciences (SPSS).