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After completion of the case study, the students will be able to understand the challenges faced by cocoa farmers in developing countries and their impact on the cocoa value chain, describe the need for a business to create a business model that offers social impact in small developing economies, explore innovative business models, such as vertical integration, for addressing transparency and fair compensation issues in agricultural supply chains, analyze the role that start-ups can play in disrupting the commodities supply chain and building a national competitive advantage and examine how a values-driven business can gain the trust of stakeholders and create a profitable ecosystem.

This case study describes the innovative business model of Inaru Corporation, a pioneering venture founded by two sisters, Janett Liriano and Erika, aimed at revolutionizing the cocoa industry in the Dominican Republic. This case study outlines the challenges faced by cocoa farmers in the country, including low productivity, exploitation by middlemen and lack of value addition. Inaru’s innovative business model aimed to disrupt the traditional supply chains by prioritizing fair compensation for farmers, investing in sustainable practices and vertically integrating cocoa production from farming to manufacturing. Through direct relationships with producers, profit-sharing agreements, and a commitment to ethical business practices, Inaru sought to empower cocoa farmers and cultivate a more equitable and sustainable cocoa industry. Inaru was a model for ethical and caring business practices where it shared the profits with its farmers. By operating a profit-sharing model and sharing its fortune with other women, Inaru was helping create gender equity in the cocoa sector. Inaru planned to scale its business model to other cocoa-producing countries and even transfer its business model strategy to other commodities beginning with the coffee segment in Dominican Republic. By exploring Inaru’s case study, students gain a deep understanding of how businesses can drive positive change, create value for stakeholders and contribute to sustainable development goals.

This case was written for use in teaching graduate and postgraduate management courses in entrepreneurship and economics, politics and business environment.

Teaching notes are available for educators only.

CSS 3: Entrepreneurship.

The purpose of this study was to development of a new chocolate-flavored powdered food supplement enriched with mesquite pod flour, oak extract and agave fructans, with proper sensory characteristics as well as its physicochemical and glycemic quality.

A powdered shake was formulated using experimental design (23) with mesquite (Prosopis laevigata) pod flour, oak (Quercus convallata) extracts, nonalkalinized cocoa, agave fructans, milk protein and xanthan gum. Sensory analysis (choice profile method, ranking test, focus group, quantitative descriptive analysis), moisture, ash, fiber, protein and lipids, pH, color, wettability, dispersibility and rheological tests were done. Phenolic profiling analysis to samples was done by ultraperformance liquid chromatography coupled to photodiode array detection and electrospray ionization tandem mass spectrometry, antioxidant activity was measured by 2,2’-Azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt radical cation, ferric reducing antioxidant power and oxygen radical absorbance capacity, glycemic index (GI) and glycemic load were evaluated.

The main sensory attributes in the powders were chocolate, bitter, astringent, grass/linseed flavors (p < 0.05). The product has protein [66.9%], carbohydrates [22.0%], lipids [1.6%], ash [2.7%] and moisture [6.8%], with wettability (23 s), and dispersibility of 77.9%. Catechin, epicatechin, gallocatechin, procyanidin B2, chlorogenic, coumaric and ferulic acids were identified. GI and caloric load not show differences between men (73.3±2.4, 4.4±0.1) and women (67.0±2.1, 4.1±0.1) (p > 0.05).

The use of mesquite pods, oak and agave fructans in powder food supplement is an alternative to obtain a product high in protein, with good sensory properties, antioxidant activity and moderate GI.

This paper examines the role price fluctuations associated with internationally traded commodities play in inflationary conditions and inflation uncertainty among economies in Sub-Saharan Africa.

Using a panel 32 countries from the sub-region from 1996 to 2019, this study employed Two-Step System Generalized Method of Moments (GMM) estimation technique in its analysis.

Empirical evidence demonstrates that fluctuations in forex-adjusted price of crude oil, gold and cocoa have significant positive impact on inflation while forex-adjusted changes in price of cotton tend to have significant negative influence on consumer price inflation among economies in the sub-region. Additionally, the study found that gold, cocoa and cotton price changes on the international market have significant positive impact on inflation uncertainty in the sub-region (rise in price leads to increase rate of inflation uncertainty). Furthermore, improved regulatory quality and growth in output growth (GDP per capita growth) were found to help in stabilizing inflation uncertainty (reduce inflation uncertainty) among economies in the sub-region during periods of persistent growth in general price levels.

The study present a different approach based on individual economy forex-adjusted global prices of internationally traded commodities instead of general prices often used in the literature and assessed the effects such adjusted commodity prices have on inflation and inflation uncertainty. Additionally, the moderating role of regulatory quality and output growth between surmised nexuses are also examined.

Solar power forecasting will have a significant impact on the future of large-scale renewable energy plants. Predicting photovoltaic power generation depends heavily on climate conditions, which fluctuate over time. In this research, we propose a hybrid model that combines machine-learning methods with Theta statistical method for more accurate prediction of future solar power generation from renewable energy plants. The machine learning models include long short-term memory (LSTM), gate recurrent unit (GRU), AutoEncoder LSTM (Auto-LSTM) and a newly proposed Auto-GRU. To enhance the accuracy of the proposed Machine learning and Statistical Hybrid Model (MLSHM), we employ two diversity techniques, i.e. structural diversity and data diversity. To combine the prediction of the ensemble members in the proposed MLSHM, we exploit four combining methods: simple averaging approach, weighted averaging using linear approach and using non-linear approach, and combination through variance using inverse approach. The proposed MLSHM scheme was validated on two real-time series datasets, that sre Shagaya in Kuwait and Cocoa in the USA. The experiments show that the proposed MLSHM, using all the combination methods, achieved higher accuracy compared to the prediction of the traditional individual models. Results demonstrate that a hybrid model combining machine-learning methods with statistical method outperformed a hybrid model that only combines machine-learning models without statistical method.

Global demand for agricultural commodities, including beef, soy, and palm oil, has driven tropical deforestation throughout the 21st century, threatening biodiversity and ecosystem services while contributing significantly to greenhouse gas emissions. Deforestation in the tropics is a wicked problem because there is no consensus on its solution, conflicting moral and political considerations among stakeholders, and uncertainty about the potential effects of intended solutions. Faced with such complex policy challenges, jurisdictional approaches (JAs) are being increasingly embraced as potential means of increasing policy capacity to tackle deforestation and support the Sustainable Development Goals. JAs integrate tools such as public and private regulations, collaborative planning processes, and payments for ecosystem services to respond to the complexity that characterizes deforestation. In this chapter, we study PROAmazonia, an anti-deforestation JA implemented in Ecuador’s Amazon region since 2017.

Our study shows that enhancing policy capacities to manage wicked problems associated with deforestation requires confronting the inherent complexity of these problems and the wider socio-environmental system in which they emerge. However, this requires integrated policy strategies that exceed the scope of JAs, also demanding support from wider governance structures.

The purpose of this paper is to scrutinize the safe haven benefits of 13 individual commodities for the USA and Chinese equity sectors during the financial turmoil period. Therefore, sectoral investors in the USA and China could invest in those specific commodities that provide stable returns during the health crisis and financial turmoil periods.

The daily data spans from February 1, 2015, to July 28, 2022. The present study applies several different approaches to analyzing the data set. The author apply the cross-quantilogram (C.Q) methodology to capture the lead-lag bivariate quantile interdependence between two stationary time series variables during the bearish, bullish and normal periods. Then the study used the hedging effectiveness (HE) and conditional diversification benefits (CDB) approaches to capture the hedging and diversification benefits of commodity classes and individual commodities.

The noteworthy findings of the quantilogram methodology reveal that livestock and agriculture commodities serve as better refuges as compared to the precious metals and energy index in both countries. On average, precious metals failed to serve as safe haven investments for the USA and Chinese equity market sectors. All energy commodities except soybean oil had strong comovements with China and the US equity sectors during bearish, bullish and normal periods. Lean hogs, fiddler cattle and live cattle are perfect hedging assets for both countries due to the presence of blue color at normal and bullish periods in all C.Q heat-maps. The HE table depicts that commodity indices and individual commodities failed to serve as hedging assets for the Chinese equity sectors. But commodities are semistrong hedging assets for the US equity sectors and the S&P 500 due to the average HE values being 0.7 and above. The CDB values depict that precious metals provide diversification benefits in both equity markets.

The present study results have important implications for equity sector investors of the USA and China in suggesting particular commodity during the financial turmoil period. During the bearish market condition, risk averse equity sector investors can invest in livestock commodities and agriculture commodities, due to their relatively stable returns. In addition, policymakers can use the analysis insights to formulate policy tools and monitoring mechanisms, effectively mitigating the unfavorable effects arising from asymmetric dependence between commodities and equity sectors during the upper tail, middle and lower tail. Policymakers can suggest equity investors to invest in which commodity during extreme conditions.

The current study has the following points of originality. First, to the best of the author’s knowledge, this is the first study to investigate the individual commodities’ roles as safe havens taken from all four major commodity classes. More importantly, it is also noticeable that the safe haven abilities of commodities are usually tested for the stock market, but the equity sectors are ignored. Therefore, the present study used both stock market and sectoral indices data.

Preferential market access is a pillar of the enabling clause in international trade, and as such has received scholarly attention in the recent past. This study aims to empirically examine intensity and utilisation of Uganda’s preferential market access.

Secondary data at the six-digit level of the harmonised system was sourced from the International Trade Centre’s and UN COMTRADE’s Trade Map database on trade flows to compute; trade intensity indices, Balsa’s revealed comparative advantage (RCA) indices and the existing potential trade. The time period was 2013–2022.

It is evident that Uganda is not taking full advantage of its preferential market access. The findings of the trade intensity analysis revealed that the strength of trade relations between Uganda and its preferential markets has been consistently weak in the period 2013–2022, while the intensity of trade relations with its FTA partners has been strong. The RCA results revealed that all Uganda’s agricultural exports to its preferential markets have a comparative advantage, with exports of roses reporting an exceptionally high RCA relative to other agricultural exports. The RCA results also show that the comparative advantage of Uganda’s coffee exports recovered after a significant fall in the period 2014–2022. The analysis of the existing potential for trade reveals a disproportionally low market share held by Uganda across all product lines, notably, only 2.3% of the US$29bn coffee imports in its preferential markets.

One limitation of this study is that it primarily relied on quantitative data from the International Trade Centre and thus lacks an exhaustive understanding of the circumstances at the export firm level. Qualitative data, such as interviews with exporters and policymakers, could provide deeper insights into the specific challenges and opportunities faced by Ugandan businesses in these markets.

This paper highlights the need for additional trade facilitation measures to address preferential market access bottlenecks such as stringent rules of origin and call for an aggressive government intervention in enhancing the export readiness of SMEs in Uganda. In addition, the paper is informative to Uganda’s exporters regarding the existing and potential increase in their exports to international markets.

The strength of Uganda’s trade relations with its preferential markets is empirically examined in this paper and provides useful insights for enhancing utilisation of preferential market access by beneficiary countries.

Severe inequality from climate change exists between the Global North and Global South. The North significantly contributes to climate change yet retreats to protect itself against its harmful impacts. Conversely, members of the Global South bear the brunt of the climate crisis with limited protection against its destructive effects. Climate justice aims to address this inequality. This paper explores the effects of climate change reforms and policies that have been established to foster accountability and climate justice.

This research follows a qualitative exploratory case study method. It draws on a supply- and demand-led approach and local accounts to analyse the (in)effectiveness with which six national and international reforms and policies have achieved accountability for climate justice. The research analysed a variety of empirical documents including contemporary research, reports, academic literature, non-government and government documents and policies, media releases and Pacific Islander accounts.

Climate change reforms and policies, which come together to form supply-side accountability, have largely failed to engender accountability in the Global North for the impacts of climate change. Nor have they mitigated climate change to any tangible extent at all. This has created a system of modern-day climate apartheid. Improving accountability and remediating climate injustices going forward will require a focus on demand-led instruments and accountability, which includes the voice of citizens.

This paper responds to AAAJ’s special issue call for examining accounting and accountability with regard to environmental and climate racism. Limited research to date explores the issue of climate apartheid and climate justice and its relationship with accountability. This research attempts to fill that gap.

The COVID-19 pandemic has had a devastating impact on all facets of education. This led to educational institutions deploying blended and online systems for teaching and learning. The purpose of this study was to assess the role of blended learning in promoting quality education during the COVID-19 pandemic.

The qualitative research design was deployed in this study and enabled the researcher to collect data via in-depth interviews. Twenty-five (25) tertiary institutions accredited by the Ghana Tertiary Education Commission (GTEC) were randomly selected to participate in this study. The registrars of the institutions were purposively selected and served as the participants for the study. Thematic content analysis was used to analyze the data collected via the interview. Ethical considerations were adhered to during the study.

The study established that COVID-19 had a devastating effect on tertiary institutions; multiple technological and open-sourced systems were deployed for teaching and learning; blended learning was adopted to augment the traditional face-to-face mode of teaching and learning due to its ease of use, usefulness and accessibility as it was used for quizzes and assignments, accessing lecture notes, among others. Despite these, the deployment of technological and blended systems was met with challenges that somehow affected effective teaching, learning.

The study was limited to 25 tertiary educational institutions in Ghana. It was again limited to the COVID-19 era.

This research aids in understanding the extent of the impact of COVID-19 on teaching and learning and how blended learning is currently deployed and used in tertiary institutions in Ghana. The findings are relevant to policymakers and management of educational institutions as it informs them of the right method and tools to deploy for teaching and learning during pandemics.

As educational institutions globally are dealing with the effect of the COVID-19 pandemic, it is prudent to look into how tertiary institutions in Ghana deploy blended learning to facilitate teaching and learning. Thus, this paper is original as it fills the relevant literature gap in terms of scope, setting, methodology and findings.

Though agriculture has the potential for job creation for the growing population; nevertheless, most Nigerian youth merely see the agricultural sector as a viable opportunity for livelihood. In the quest for food security, as encapsulated in sustainable development goals (SDGs), youth participation in agriculture is essential to unlock the agricultural sector’s potential and ensure adequate food production.

This study examined the factors influencing youth involvement in agriculture and its impact on food security in Nigeria, using Ekiti and Kwara States. The study engaged a multi-stage random sampling approach. The first stage involved a purposeful selection of the states among youth in agriculture-related activities. The second stage involved randomly selecting five Local Government Areas (LGAs) from each state. The third stage involved a random selection of five communities in the selected LGAs, making it a total of 25 communities for each state. Finally, 20 households were selected per community. In total, 500 respondents were selected from each of the two states, making it a total of 1,000 respondents for the survey. The Foster-Greer-Thorbeck (FGT) analysis uses the logit regression and the Propensity Score Matching (PSM) techniques.

The results showed that a large proportion (about 95%) of the youth farmers in the study area fell below the food security line (N6448.45) and are food insecure. Findings from the PSM showed that youth in agriculture has no significant impact on food security. The findings from the logit regression showed that gender, age, level of education, land ownership, income, safety net or social protection and value chain are significant determinants of youth participation in agriculture.

This study contributes to the literature by examining the determinants of youth in agriculture and its impact on food security in Nigeria, using Ekiti and Kwara States, by engaging the FGT, logit regression and PSM.

This study contributes to the literature by examining the determinants of youth in agriculture and its impact on food security in Nigeria, using Ekiti and Kwara States, by engaging the FGT, logit regression and PSM.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-04-2021-0197