Volume 12 (2021): Issue 1 (December 2021)

Railroad is one of the primary modes to transport hazardous materials (hazmat) in North America. For instance, Canadian railroads carried around 50 million tons of hazmat in 2018. Given the inherent danger of trains carrying hazmat, this study aimed at exploring a novel way towards mitigation of the associated risk. This study sought to investigate whether proper rail track infrastructure investment can mitigate the risk from hazmat shipments. To this end, a methodology was developed and then applied to the Canadian railroad network. The proposed three-step methodology captured the differing perspectives of rail carriers and regulatory agencies, and entailed (1) ascertaining the risk-level of various yards and links in the given railroad network, (2) specifying potential candidates for infrastructure investment, and (3) finding the optimum set of investment decisions. The proposed methodology was then applied to the Canadian railroad network to demonstrate that significant risk-reduction can be achieved by adding alternative rail-links around the riskiest locations (i.e. the network hot-spots), and also to show that risk-reduction function is non-linear with non-monotonous behavior. The study showed the possibility of significant hazmat risk reduction through alternative rail-links that could take traffic away from the network hot-spots. The methodology and the results from the Canadian case can be used by railroad companies and policy makers to estimate the value of potentially risk-reducing infrastructure investments.

Companies are facing numerous pressures and challenges in order to be competitive in the market and meet the requirements of their customers which require an improvement in the supply chain practices of the firms to be more effective and efficient for sustainable competitive advantage. This study examines the use of a multi-criteria decision making method using analytic network process (ANP) to estimate the how supply chain activities of the selected manufacturing firms’ influences its firm performance in other to enhance the satisfaction of customers. The population of the study is the manufacturing firms quoted in the Nigeria stock exchange. An ANP-based questionnaire was administered to Managers of selected manufacturing firms for pairwise comparison of supply chain factors relative influences and dependencies on their customers. A nonlinear network model was built to capture all the factors of supply chain practices and firms performance into clusters, nodes and dependences for the purpose of estimating various influences supply chain practices on the performance of the various companies studied.. Data collected were analysed using software of Super decision 3.0version. The results revealed factors of supply chain practices that have a great connection with one another and strong relationship indicating that without the implementing the key factors of supply chain there would not be a significant improvement in the performance of the organisation which will also affects the desire of the customers. The ANP model has helped to show the interdependencies and feedback among the various factors of practices of supply chain to augment the level of performance of the firms.

Nigeria deployed Intergovernmental Panel on Climate Change (IPCC) top-down approach which generalizes transport emissions, is not detailed to localize solutions based on sectors. This identified gap was filled using IPCC’s Bottom-Up approach. Quantitative research design was employed using a descriptive survey to determine fuel consumption, vehicle and drivers characteristics through the use of a 30-item instrument named GHG emission estimation instrument (GHGEEI) to estimate the quantity of GHGs from vehicular emissions of commercial road passenger transport activities within the selected routes in Iyana-ipaja, differentiate emission estimates by vehicle categories (Tricycle referred to as ‘Keke’, Shuttle,‘Danfo’14, 18 and 22-seaters) and determine the relative contribution of each commercial road passenger vehicle type according to its age, fuel type, number of engine plugs, and frequency of service. Quota sampling technique was used to identify the strata and their frequency in the population and then convenience sampling was used to select 15% of the quota population for each stratum. Results from the study showed that 10,259.88kg/CO₂e, of Carbon dioxide (CO₂), 3.65kg/CO₂e of Methane (CH₄), and 0.58kg/CO₂e of Nitrous Oxide (N₂O) was emitted daily on the selected areas.

Purpose: Following the banning of expanded polystyrene packaging material, the fast food restaurant industry was serendipitously plunged into green sourcing initiatives for its packaging materials leading to heightened efforts on evaluating the suitability of various suppliers of green packaging material. This study therefore sought to assess the performance of selected suppliers on supplier performance metrics of total cost of ownership, quality of sourced material and delivery performance, in Zimbabwe’s restaurant industry.

Methodology: Data was collected from senior procurement officers of 30 officially registered fast food restaurants in Zimbabwe. Each restaurant randomly selected 5 suppliers from their supplier lists. Each unit was asked to rate their 5 major suppliers of packaging material leading to an effective sample size of 150 suppliers. Structural Equation Modeling (SEM) was used to analyse data in AMOS. The five steps in SEM, that is: model specification, model identification, parameter estimation, model evaluation and modification were done.

Findings: The findings in this study revealed that green sourcing leads to improved procurement performance in terms of total cost of ownership, quality of the materials sourced, and delivery performance.

Implications for theory and practice: It was therefore recommended that practically the restaurant industry should explore various options of green packaging material ranging from recyclable and reusable plastic, paper, aluminium and steel material.

Originality and value: Although the study was done in a single market, there is dearth in literature on green sourcing in frontier markets, of which the study provides empirical evidence from the restaurant industry in Sub-Saharan Africa.

This study examined the environmental attitude of drivers towards vehicle emission. The survey design that employed a five point Likert scale questionnaire and administered to 402 respondents (drivers) generated the data analysed. Data analysis involved descriptive and regression statistical tools. The results suggest that there was significant association between respondents’ sex, occupation, education and their environmental attitudes. A greater percentage (87. 3%) of the respondents was slightly more likely to agree that emissions from cars and trucks have serious impact on air quality. Majority (57.5%) of the respondents who were civil servants appeared to possess positive (favourable) attitudes towards the influence of emissions on the environment. Logistic regression suggest that respondents’ sex, occupation, education and vehicle’s purpose, income, age and social group significantly predicted their environmental attitudes. The study concludes that most of the sample possessed positive (favourable) environmental attitude towards vehicle emissions. This suggests that the environmental attitude of drivers towards emissions is not responsible for poor air quality. The policy implications of the findings include the need for the adoption of the polluter-pay-principle to reduce the volume of vehicles on our road, the necessity of promoting mass public transportation (such as the BRT and LAGBUS) as a way of reducing vehicle emission. Finally, sensitization program through social groups and schools is imperative.