Fluctuations that characterise airport traffic make planning for efficient operations difficult. This study examines air cargo traffic at Murtala International Airport, Lagos, Nigeria, and Kotoka International Airport, Accra, Ghana. The study focused on the trend of cargo volume, origin, and destination and forecasted the cargo volume at the airports. Air cargo data from 1991-2022 were collected from the Federal Airport Authority of Nigeria (FAAN) and Ghana Airport Company Limited (GACL). Descriptive techniques using line graphs and GIS mapping were used to analyse data. Time series techniques of moving and weighted averages, exponential smoothing, and least square techniques were used to forecast the cargo volume of the airports. The study found a characteristic fluctuating pattern of cargo flow. Nigeria’s dominating export cargo types are general goods, edible items, and hair attachments. Ghana’s dominating export cargo types were pineapple, general goods, and papaya. Germany, followed by Ethiopia and Turkey, dominate the origin of import cargo, while the United Kingdom, UAE, and Turkey dominate the destination of export cargo from Nigeria. Luxembourg, Turkey, and the UK dominate the origin of import cargo, while the UK, Netherlands, UAE, and Qatar dominate the destination of export cargo in Ghana. The least-square technique predicts 3.67% and 2.3% growth of cargo traffic in Nigeria and Ghana, respectively. An increasing trend in cargo volume was predicted for both airports. Both countries need to strategise on their relationships with other countries and develop policies that will increase cargo flow by air.
Passenger traffic at airports is characterised by fluctuations resulting from the influence of several factors. The influence of each factor is different, leading to unpredictable passenger traffic patterns that make planning difficult. Previous studies used geographic, demographic, and economic variables as exploratory factors to examine air travel demand. The study explores several variables to confirm airports and airlines’ characteristics as demand factors for domestic air travel in Nigeria. Data for the study were collected by administering a questionnaire to respondents at major domestic airports in Nigeria. The variables were presented in the 5-point Likert Scale for respondents to rank in order of significance. Exploratory and confirmatory factor analyses (EFA and CFA) were employed to identify the significant factors affecting passenger traffic at domestic airports in Nigeria. EFA reduced fifteen variables to four orthogonal factors influencing passenger traffic at domestic airports. CFA validates airport and airline services, demographics, economic factors, and airport size and facilities as significant factors affecting passenger traffic at domestic airports in Nigeria. The model fit test shows CMIN/DF = 2.263; CFI = 0.940; GFI = 0.929; NFI = 0.901; and RMSEA = 0.078. The result identifies airport and airline characteristics as factors influencing passenger traffic at the domestic airport in any country. It implies that airport and airline characteristics significantly influence domestic air traffic and needs to be included in modelling. Identifying airport and airline characteristics as air travel determinants make this study unique for policy decisions to forecast domestic passenger traffic in a country.
Policies are supposedly made such that their implementation for present growth does not hamper future development. However, it has been challenging to effectively implement some policy decisions based on stakeholders’ reactions to their sustainability in the air cargo industry. This paper examined the factors affecting air cargo policy decisions and their implementation in Nigeria by employing the quantitative research method and conducting a survey of stakeholders by random sampling at the Lagos International Airport through a well-designed research questionnaire. The data collected were analyzed using exploratory factor analysis (EFA) and partial least square structural equation modeling (PLS-SEM). Before estimating the PLS-SEM model, latent factors were constructed using EFA. The results reveal that the factors affecting the air cargo policy decisions and implementation include the policy formulation process, stakeholders’ interests and commitment, policy goals and implementation, and corruption and governance. The results imply that fundamental public policy issues prevail in Nigeria’s air cargo sector development programs. This study provides insight into the reasons behind opposition to implementing certain air cargo policy decisions in Nigeria. It offers directions for addressing the problems of poor policy decisions that do not guarantee future development. In practice, the study advocates the all-inclusive stakeholders’ involvement in Nigeria’s policy formulation process for the air cargo industry.
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