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The purpose of the present study is to determine how the cash conversion cycle (CCC) affects the financial performance of manufacturing companies in Bangladesh.

The authors have collected data of 61 Dhaka Stock Exchange (DSE)-listed firms from the 10 distinct manufacturing industries of Bangladesh for 18 years, from 2003 to 2020. The data have been analyzed through the two-steps system generalized method of moment (GMM) regression model, using profitability indicators return on asset (ROA) and earnings per share (EPS) as dependent variables, while CCC has been used as the independent variable, whereas asset turnover (ATO) and financial leverage (LEV) were used as control variables to assess the relationship between the CCC and financial performance.

The findings indicated that CCC has a negative connection with profitability – ROA and EPS, with the connection between CCC and EPS being highly significant. This indicates that reducing the inventory conversion time, reducing the period of receivable collection and making payments to creditors with potential delays might help Bangladeshi manufacturing firms boost their profitability. In addition, the firm-specific characteristics, namely ATO and LEV significantly affect the firm's profitability.

The research was based only on secondary sources and information was scarce. This research was conducted to determine the impact of the CCC on the corporate profitability of the manufacturing sector solely. There might be many other working capital variables that are still unexplored through this study.

The current study's findings are consistent with the traditional rule that minimizing the firm's days of the cash cycle may optimize financial performance. The results of this research have added to the existing body of knowledge on the topic of working capital management (WCM). Future research endeavors can be initiated for assessing the impact of the CCC on the firm's profitability in other industrial sectors or to identify other working capital variables that have much impact on corporate profitability.

This study is an original work of the researchers and adds value to the current literature in the domain of WCM and corporate profitability. The present study is the first one that covers firms in all the manufacturing industries in Bangladesh. The corporate managers, creditors, investors and other concerned stakeholders will be benefited from the findings of the present study.

This paper aims to investigate the possible non-linear effect of net working capital (NWC) level on profitability for Middle East and North Africa (MENA) region listed companies. Furthermore, the study tests the possible interactive effect of cash levels on the relationship between NWC and profitability.

NWC level is the independent variable and profitability is the dependent variable using two proxies, return on assets (ROA) and returns on equity (ROE). Control variables are size, leverage, gross domestic product growth and sales revenue growth. The generalized method of moments was used to analyze the data of 134 consumer-goods listed firms in 12 MENA countries for the period 2013–2019.

The results demonstrate that NWC levels had a non-linear effect on profitability using ROA as a profitability proxy while results were insignificant using ROE as a profitability proxy. Furthermore, results show the absence of interactive effects between NWC, cash levels and both profitability proxies.

The study fills a gap in the working capital management (WCM) literature by providing new evidence on WCM’s non-linear effect of corporate performance in the MENA region emerging markets using the consumer-goods industry sample. The study contributes to the financial managers’ working capital optimization efforts in the MENA region by providing evidence on the usefulness of WC optimization efforts in the region from a financial performance point of view. According to the researchers’ knowledge, a few studies attempted to investigate this non-linear relationship for neither MENA region countries nor the consumer-goods industry.

This paper presents an experimental investigation in establishing the relationship between FDM process parameters and tensile strength of polycarbonate (PC) samples using the I-Optimal design.

I-optimal design methodology is used to plan the experiments by means of Minitab-17.1 software. Samples are manufactured using Stratsys FDM 400mc and tested as per ISO standards. Additionally, an artificial neural network model was developed and compared to the regression model in order to select an appropriate model for optimisation. Finally, the genetic algorithm (GA) solver is executed for improvement of tensile strength of FDM built PC components.

This study demonstrates that the selected process parameters (raster angle, raster to raster air gap, build orientation about Y axis and the number of contours) had significant effect on tensile strength with raster angle being the most influential factor. Increasing the build orientation about Y axis produced specimens with compact structures that resulted in improved fracture resistance.

The fitted regression model has a p-value less than 0.05 which suggests that the model terms significantly represent the tensile strength of PC samples. Further, from the normal probability plot it was found that the residuals follow a straight line, thus the developed model provides adequate predictions. Furthermore, from the validation runs, a close agreement between the predicted and actual values was seen along the reference line which further supports satisfactory model predictions.

This study successfully investigated the effects of the selected process parameters - raster angle, raster to raster air gap, build orientation about Y axis and the number of contours - on tensile strength of PC samples utilising the I-optimal design and ANOVA. In addition, for prediction of the part strength, regression and ANN models were developed. The selected ANN model was optimised using the GA-solver for determination of optimal parameter settings.

The proposed ANN-GA approach is more appropriate to establish the non-linear relationship between the selected process parameters and tensile strength. Further, the proposed ANN-GA methodology can assist in manufacture of various industrial products with Nylon, polyethylene terephthalate glycol (PETG) and PET as new 3DP materials.

Eradicating extreme poverty remains one of the most significant and challenging sustainable development goals (SDGs) in the Middle East and North African (MENA) region. The latest World Bank statistics from 2018 show that extreme poverty in MENA increased from 2.6% to 5% between 2013 and 2015. MENA ranks third among developing regions for extreme poverty and fell short of halving extreme poverty by 2015 – the target established by the United Nations’ (UN) millennium development goals, the precursor to the SDGs. The purpose of this study is to analyze the impact of financial inclusion on extreme poverty for a sample of 34 countries over the period 1990–2017.

Using system general method of moments dynamic panel estimation methodology on annual data for 11 MENA countries and 23 emerging markets (EMs) over the period 1990 – 2017, this study begins by estimating the impact of financial inclusion – using measures of access and usage – on the eradication of extreme poverty by 2030, the first goal of the SDGs.

The results of the study indicate that, on one hand, financial access measures have a positive, statistically significant impact on reducing extreme poverty for the full sample and the MENA region. The second part of the study uses a gap analysis against four poverty targets – 0%, 1.5%, 3% and 5% – and shows that no MENA country and few EM countries will be able to close the extreme poverty gap and reach the target of 0% by 2030 by depending solely on improvements in financial access. These targets are based on the two benchmarks set by the World Bank and the UN, with intermediaries to capture error and give a fuller picture of what is possible. However, if improvements in financial inclusion alone can bring every EM and MENA country except Djibouti and Romania to bring the most accessible target of reducing global extreme poverty to no more than 5% by 2030.

While research on poverty reduction in the region tends to focus on financial development and governance, less attention has been paid to the role of financial inclusion. SDG 1 – eliminating poverty in all its forms – explicitly highlights the importance of access to financial services. Indeed, evidence from Argentina, India, Kenya, Malawi, Niger and other countries demonstrates the ways in which financial inclusion can impact poverty (Klapper, El-Zoghbi and Hess, 2016). When people are included in the financial system, they are better able to improve their health, invest in education and business and make choices that benefit their entire families. Financial inclusion advances governments, too: introducing vast segments of the population into the financial system by digitizing social transfers, for example, can cut government costs and reduce leakage, with benefits that ripple across society. Yet, the links between financial inclusion and poverty reduction in MENA are less established. This study aims to analyze the importance of financial inclusion in addressing extreme poverty by 2030, the year UN member states set as a target for achieving the SDGs.

The article aims to share the viewpoint of the author on the impact of the innovative teaching pedagogy adopted by him in teaching the accounting courses on the satisfaction of the participants in a premier Indian Business School.

The experiment was carried over by introducing an innovative teaching approach by the author among the first-year participants of the Management Program. At the end of the experiment, the participants were asked to rate the teaching approach on a five-point scale besides offering the qualitative feedback on the impact of the experiment on their learning outcomes.

The paper concludes that the participants were highly satisfied with the teaching approach adopted by the author.

The study contributes to the theory and practitioners on accounting education in many ways. First, it is offering evidence on the impact of teaching pedagogy on the satisfaction of the participants of the accounting courses of an emerging market business school. Second, the accounting educators of the emerging countries may replicate the experiment in their institutes. Third, the educators of other courses in the business schools may make an effort to measure the impact of the teaching approach on the feedback of their learners.

This paper addresses the trade-off between asset investment and food safety in the design of a food catering production plant. It analyses the relationship between the quality decay of cook-warm products, the logistics of the processes and the economic investment in production machines.

A weekly cook-warm production plan has been monitored on-field using temperature sensors to estimate the quality decay profile of each product. A multi-objective optimisation model is proposed to (1) minimise the number of resources necessary to perform cooking and packing operations or (2) to maximise the food quality of the products. A metaheuristic simulated annealing algorithm is introduced to solve the model and to identify the Pareto frontier of the problem.

The packaging buffers are identified as the bottleneck of the processes. The outcome of the algorithms highlights that a small investment to design bigger buffers results in a significant increase in the quality with a smaller food loss.

This study models the production tasks of a food catering facility to evaluate their criticality from a food safety perspective. It investigates the tradeoff between the investment cost of resources processing critical tasks and food safety of finished products.

The methodology applies to the design of cook-warm production. Catering companies use cook-warm production to serve school, hospitals and companies. For this reason, the application of this methodology leads to the improvement of the quality of daily meals for a large number of people.

The paper introduces a new multi-objective function (asset investment vs food quality) proposing an original metaheuristic to address this tradeoff in the food catering industry. Also, the methodology is applied and validated in the design of a new food production facility.