This paper proposes a framework for selecting energy storage technology (EST) for small-scale renewable energy systems. The present study was able to achieve this using the results that were generated from a Preference Ranking Organisation Method for Enrichment Evaluation (PROMETHEE) and a fuzzy quality function deployment (FQFD) model. Using the FQFD model, experts' opinions were incorporated into the framework during the evaluation of the techno-economic requirements importance for the selection process. The FQFD model considered system safety, availability, flexibility, reliability and effectiveness as customers’ requirements, while nominal voltage, nominal discharge current, peak measured voltage, operating cost and cost of energy were among the techno-economic requirements. During the framework application, a questionnaire was used to collect information from experts on the techno-economic requirements importance, while information on the techno-economic (eleven) requirements for four ESTs were obtained from literature. The FQFD model results were incorporated into a PROMETHEE and TOPSIS models. The PROMETHEE and the TOPSIS models identified Lithium-Ion EST as the best EST for small-scale renewable energy systems.

The growth in renewable energy study has resulted in the expansion of mini-grids projects across different communities in developing countries. However, there is a need to ensure that a suitable business model is selected during the provision of mini-grid services in developing countries. This study presents a framework for ranking mini-grid business models. The proposed framework is a multi-criteria multi-decision (MCMD) making tool. The framework combines Criteria Importance Through Inter-criteria Correlation (CRITIC), TOPSIS (Technique for Order Performance by Similarity to Ideal Solution) and WASPAS (weighted aggregated sum product assessment) methods. An interval type-2 fuzzy sets (IT2FSs) is used to convert the responses from decision-makers into crisp values. The applicability of the proposed framework was tested using Nigeria as a case study. Four potential mini-grid (private, government, community-based and public-private) business models for the case study were ranked using twelve criteria. The average values for the subjective and objective weight methods showed that electricity traffic and energy demand were the least and the most important criteria, respectively, for selecting a mini-grid business model. The results obtained showed that the best mini-grid model was a private model using a TOPSIS framework. A WASPAS framework ranked the community-based business model as the best model. This study results showed mini-grid business models in developing countries should be either private or community-based business models.

The improvement in the provision of banking services to customers enhances bank’s performance (profitability and productivity) and the amounts of dividend declared to shareholders as well as bank’s competitiveness. One means of fast tracking the service time for bank customers is through the use of self-servicing machines, such as automated teller machine (ATM). Total service cost, expected waiting time in queue, ATM utilization and percentage of customer loss are some of the performance indices that are used to evaluate the service rendered by a bank’s ATM. This study proposes a framework for evaluating the performance of ATM by integrating queuing model and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methodology. Applicability of the framework was tested using practical data obtained from four banks in Nigeria. It was observed that the average ATM usage in the study area was less than 50%. The TOPSIS results identified Bank A as the best ranked bank. In addition, the results obtained revealed that banks with two ATM were ranked higher than banks with more than two ATM.

Retrofitting technologies have helped to manage energy consumptions in residential, public and industrial buildings. However, understanding of the technical and economic considerations for selection of appropriate retrofitting technology is still evolving and divergent. Thus, this study presents a framework that combines techno-economic requirements as a means for evaluating the important retrofitting criteria and suitable lighting retrofit technologies for building projects. The framework is hinged on the unique features of entropy fuzzy and TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) methods. The analysis of the lighting technology selection was performed from technical, economic and techno-economic perspectives. During the application of the proposed framework, four lighting technologies (CFL, T5, E-ballast and T8-electronic) and nine techno-economic criteria were considered. The most and least important techno-economic criteria for the case study were net present value and electricity saved, respectively. The least and most suitable retrofitting technologies were T8-electronic and CFL, respectively, from techno-economic perspective. T5 and T8-electronic were identified as the most suitable lighting technologies from an economic and technical perspectives, respectively. This discrepancy in the results justified the need for the techno-economic approach for the retrofitting technologies evaluation.

Decision-making process is an integral part of every sporting event across the globe. This process uses inputs from single to multi-decision makers. To make a sporting event a success, appropriate decision making needs to be made starting from hosting-right to the end of the event. Thus, this study presents a framework that scientifically determines the hosting-right for a sporting event. The framework is based on techno-economic analysis of potential hosting locations for a sporting event. Techno-economic criteria are analysed using fuzzy TOPSIS (technique for order preference by similarity to ideal solution) method. The analysis of the hosting-right is also performed through technical, economic, techno-economic and cost-benefit ratio perspectives. A case study of national sports festival in Nigeria is used to demonstrate the applicability of the proposed framework. Twelve technical and eight economic criteria are considered in the proposed framework. Six loca-tions are considered during the implementation of the proposed framework. The results obtained show that the issue of hosting-right award depends on the evaluation criteria that are considered by decision-makers.

Business process evaluation is a common norm in small-medium-large industries globally and information obtained during such evaluation have been used in simulating future performance of most industries using mathematical models such as Autoregressive Integrated Moving Average (ARIMA) and artificial neural network (ANN). This study explored the possibility of predicting port productivity and berth effectiveness of seaport using ANN and ARIMA. A comparative analysis of multi-layer perceptron (MLP) back propagation algorithm and ARIMA performance was carried out based on ships days at port, days at berth and tonnage which serves as model inputs, while port productivity and berth effectiveness were the model outputs. The MLP-ANN and ARIMA (1, 0, 4- port productivity) and (1, 0, 4-berth effectiveness) results were compared based on their coefficient of correlation and mean square error. The coefficient of correlation for port productivity prediction using MLP-ANN was 0.998. This value outperformed that of ARIMA (0.9862) for port productivity. The coefficient of correlation of 0.9956 and 0.9928 were obtained for berth effectiveness using MLR and ARIMA, respectively.