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Outgrower scheme as a contractual agreement between farmers and some funding entities has in recent times found proliferation among resource poor farmers in Ghana, especially in northern Ghana. This contractual arrangement, which involves the provision of farm inputs, and in some cases, technical support by the implementing company and the repayment by farmers with portions of their harvest, is often regarded as an effective way to mutually improve the outcomes of both smallholder farmers and outgrower companies. The study aims to analyse. the level of awareness, nature of input package, determinants of participation and intensity of participation in input credit scheme by smallholder rice farmers in the Mamprugu Moagduri District of Ghana’s North East Region, using the Integrated Water Management and Agriculture Development (IWAD) scheme as a case.

Using a quantitative analytical approach, the study gathers information from 233 randomly selected smallholder rice farmers consisting of 150 participants and 83 non-participants using a structured questionnaire. Descriptive statistics, as well as the Tobit model, are the methods used in the analysis.

The results show that while factors such as age, marital status, number of dependents and farming experience only influenced participation in the scheme, religion, age, sex, number of dependents and farming experience influenced intensity of participation.

This study calls for the adoption of sustainable approaches by input credit companies in their credit support to smallholder farmers rather than the current ad hoc support during each cropping season.

Credit is essential in the farm business because it facilitates the adoption of productive technologies such as irrigation. However, access to credit remains a significant hurdle for sub-Saharan Africa, including Ghanaian farmers. Therefore, the authors assessed credit utilization and the intensity of borrowing by irrigated rice farmers in the Upper East region. In addition, how extension moderates the amount borrowed was analysed.

The multistage sampling approach was used in the study. The Tono and Vea irrigation schemes were purposively selected. Proportionally, 318 rice farmers were sampled from the Tono irrigation scheme and 159 from the Vea irrigation scheme. Cragg's double hurdle and moderation analysis were used.

It was uncovered that gender, age, years of farming, total farm size, rice farm size, contract farming and off-farm employment explain farmers' decision to borrow. On the other hand, the intensity of borrowing was influenced by gender, age, years of farming, rice farm size, contract farming and the number of extension contact. The moderation analysis revealed that extension contact improves the amount borrowed by farmers.

While there are irrigated rice farmers in other regions of Ghana, this study was limited to rice farmers under the Tono and Vea Irrigation schemes in the Upper East region.

This study investigated the moderating role of extension contact on amount borrowed in Ghana. This makes a modest addition to the limited literature on the moderating role of extension and credit access.

The food industry is continuously developing its online services called food delivery applications (FDAs). This study aims to evaluate FDA's importance–performance and identify strategies to maximize its potential gains from a business partner's perspective.

Data are collected from 208 FDA partners in Indonesia. Importance–performance analysis (IPA) is applied to evaluate the FDA feature and extended the theory of potential gain in customer value (PGCV) to achieve potential gains from FDA business partners.

This study provides a clear and measurable direction for future research to develop FDA performance. Owning customer data, revenue sharing and competitive advantage are the most potential gains from joining the FDA from the business partner perspective.

The respondents are restaurants from the micro, small, and medium enterprises levels. Further research should involve middle to upper level restaurants to discover all business partners' perceptions. This will be very helpful for FDA providers interested in improving the best performance for all their partners.

FDA providers must focus on improving and maintaining the features of owning customer data, revenue sharing, competitive advantage, stable terms and conditions, customer interface, building customer loyalty, online presence, user credit rating, promotion and offers, delivery service and sales enhancement to increase consumer satisfaction and meet the expectations desired by business partners.

This research provides a meaningful theoretical foundation for future work. It extends the theory of PGCV using the value of a partner perspective as a substitute for customer value; hence, the authors call it a potential gain in partner value.

This paper explores the effectiveness of using blockchain technology to solve financial constraints faced by small- and medium-sized suppliers in a capital-constrained supply chain.

To characterize the impact of blockchain on credit period and enterprise credit level, the study formulates a newsvendor model to analyze a supply chain in which a financially constrained supplier sells products to a financially sound manufacturer, subject to uncertain demand. The study investigates three repayment methods: the benchmark case without blockchain and two blockchain-enabled cases with the hybrid repayment mode and single repayment mode (SRM), respectively. The study derives and compares the equilibria under each repayment method to characterize their impact.

When the bank interest rate is low and the carbon cap is also low, choosing to implement blockchain technology leads to higher profitability for the manufacturer than not utilizing it. Within the framework of blockchain technology, when comparing the two repayment models, the manufacturer exhibits a preference for SRM. Furthermore, under specific conditions of the bank interest rate, blockchain technology can effectively facilitate consensus among supply chain members in terms of channel selection.

The results derived in this paper provide novel managerial implications to the capital-constrained members in terms of pricing decisions and order quantity under demand uncertainty considering blockchain technology, which transfers the creditor's rights to the bank and shortens the collection time. In addition, blockchain technology enables efficient and intelligent collaborative development of supply chains, which can reduce carbon emissions during the transportation of goods.

Few studies incorporate blockchain technology into supply chain finance, and this paper considers the credit period and capital's time value for a capital-constrained supplier facing the adoption of blockchain technology within a stochastic demand environment.

Given the importance of credit rating agencies’ (CRAs) assessment in affecting international financial markets, it is useful for policymakers and investors to be able to forecast it properly. Therefore, this study aims to forecast sovereign risk perception of the main agencies related to Brazilian bonds through the application of different machine learning (ML) techniques and evaluate their predictive accuracy in order to find out which one is best for this task.

Based on monthly data from January 1996 to November 2018, we perform different forecast analyses using the K-Nearest Neighbors, the Gradient Boosted Random Trees and the Multilayer Perceptron methods.

The results of this study suggest the Multilayer Perceptron technique is the most reliable one. Its predictive accuracy is relatively high if compared to the other two methods. Its forecast errors are the lowest in both the out-of-sample and in-sample forecasts’ exercises. These results hold if we consider the CRAs classification structure as linear or logarithmic. Moreover, its forecast errors are not statistically associated with periods of changes in CRAs’ opinion of any sort.

To the best of the authors’ knowledge, this study is the first to evaluate the performance of ML methods in the task of predicting sovereign credit news, including not only the sovereign ratings but also the outlook and credit watch status. In addition, the authors investigate whether the forecasts errors are statistically associated with periods of changes in sovereign risk perception.

Online food delivery has been prevalent in recent years worldwide, especially during the COVID-19 pandemic, and people's consumption behaviors have changed significantly. This study aims to investigate the consumption behavior of young adults using online food delivery platforms during the COVID-19 pandemic and focuses on the dominant factors influencing their decision to use online food delivery platforms.

Semi-structured interviews including 14 young adults aged 18–25 living in Hong Kong were conducted to collect data about their perspectives on online food delivery platforms in five areas. This research adopted the stimulus-organism-response model (S-O-R model) to analyze how the factors influence young adult users' loyalty and satisfaction with online food delivery platforms.

Thematic analyses revealed that young adults were attracted to online food delivery platforms for their numerous benefits. They had a high frequency of usage and significant spending. Usability, usefulness, satisfaction and loyalty influenced young adults' behaviors on online food delivery platforms. Participants were overall satisfied with their experiences, but platforms still had room for improvement.

Few prior studies investigated the factors affecting the consumer experience and behavioral intention of online food delivery for young adults in Asia. This study contributes to understanding young adults' experiences and problems with online food delivery platforms. It provides practical insights for system engineers and designers to improve the current services and for the governments to enhance the existing regulatory loopholes.

This paper aims to present a literature review of the most recent optimisation methods applied to Credit Scoring Models (CSMs).

The research methodology employed technical procedures based on bibliographic and exploratory analyses. A traditional investigation was carried out using the Scopus, ScienceDirect and Web of Science databases. The papers selection and classification took place in three steps considering only studies in English language and published in electronic journals (from 2008 to 2022). The investigation led up to the selection of 46 publications (10 presenting literature reviews and 36 proposing CSMs).

The findings showed that CSMs are usually formulated using Financial Analysis, Machine Learning, Statistical Techniques, Operational Research and Data Mining Algorithms. The main databases used by the researchers were banks and the University of California, Irvine. The analyses identified 48 methods used by CSMs, the main ones being: Logistic Regression (13%), Naive Bayes (10%) and Artificial Neural Networks (7%). The authors conclude that advances in credit score studies will require new hybrid approaches capable of integrating Big Data and Deep Learning algorithms into CSMs. These algorithms should have practical issues considered consider practical issues for improving the level of adaptation and performance demanded for the CSMs.

The results of this study might provide considerable practical implications for the application of CSMs. As it was aimed to demonstrate the application of optimisation methods, it is highly considerable that legal and ethical issues should be better adapted to CSMs. It is also suggested improvement of studies focused on micro and small companies for sales in instalment plans and commercial credit through the improvement or new CSMs.

The economic reality surrounding credit granting has made risk management a complex decision-making issue increasingly supported by CSMs. Therefore, this paper satisfies an important gap in the literature to present an analysis of recent advances in optimisation methods applied to CSMs. The main contribution of this paper consists of presenting the evolution of the state of the art and future trends in studies aimed at proposing better CSMs.

Primary agricultural cooperative credit societies (PACSs) in India are considered to be the backbone of the last mile delivery of rural credit for landless and marginal farmers and the poorest sections of the society. Contribution of PACS in social welfare is well documented. However, in spite of being such important form of organization at the grass root level, the authors find a typical baffling phenomenon which is fluctuating growth of PACS. Given that PACS have not been able to establish a consistent growth rate, thus hindering its trajectory to become a strong and consolidated organizational form, it is natural to investigate and identify those success factors that are critical for a newly formed PACS to survive and sustain. Hence it is necessary to undertake a strategic assessment of the function of PACS and hence identify those critical success factors (CSFs). This paper aims to address this issue.

The authors review the existing literature and conduct interview with experts and other stakeholders with the purpose to gain a view of the strategic situation of PACS in India, especially with respect to their birth and death processes and identify a set of factors that are critical to the survival and sustenance of PACS. Based on the inputs from the experts, we modelled the interrelationships amongst these CSFs using interpretive structural modelling (ISM). Further, fuzzy Matriced’ Impacts Croise's Multiplication Appliquée a UN Classement (MICMAC) analysis is performed to cluster these CSFs into four quadrants based on their influence and dependence in the system.

The findings point out that a hierarchical interconnected structure exists amongst the CSFs that influence the survival and sustenance of the PACSs. “Quality and Motivation of Management” was found to be driving all other factors so far the survival of any PACS is considered. Also the authors have found that “Loan Recovery” is the most sensitive factor that needs to be taken care of for the sustenance of PACS. These findings are in the expected line and commensurate with the conventional wisdom yet to be documented till date.

It is a forward-looking analysis that tries to find out the CSFs for the survival of PACS in order to face the changing economic scenario of India which is still agrarian in nature. Both in terms of research question as well as methodology, to the best of the authors’ knowledge, this is first of its kind so far PACS are concerned being one of the most important but neglected entities in India; so far the last mile rural agricultural credit delivery is concerned, this study will help the policy makers to develop a holistic viewpoint in relation to long term sustenance of PACS.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-05-2022-0331

Know your customer (KYC), accounting standards, issuance, clearing, and trade settlement became the major barrier to implement accounting, accountability and assurance process in supply chain finance (SCF). Blockchain technology features have the potential to solve accounting problems. This research focuses on exploring how blockchain technology provides solutions to overcome the barriers of accounting process in SCF. The benefits, opportunities, costs and risks related to blockchain adoption are also explored.

Multi-case study and qualitative methods are used with a framework based on blockchain role to overcome the accounting process barriers. Ten blockchain projects in SCF and 29 interviews of participants as a unit of analysis are considered.

The findings indicate that blockchain technology offers solutions to solve accounting, accountability and assurance problems in SCF. Validity, verification, smart contracts, automation and enduring data on trade transactions potentially solve those barriers. However, it is also necessary to consider costs such as implementation, technology, education and integration costs. Then there are possible risks such as regulatory compliance, operational, code development and scalability risk. This finding reflects the current status of blockchain technology roles in SCF.

This study unveils blockchain's SCF accounting potential, emphasizing multi-case method limitations and future research prospects. Diverse contexts challenge findings' applicability, warranting cross-industry studies for deeper insights. Addressing selection bias and integrating quantitative measures can enhance understanding of blockchain's accounting impact.

Accounting professionals can get an idea of the future direction and impact of blockchain technology on accounting, accountability and assurance processes.

This study provides initial findings on the potential, costs and risks of blockchain that is beneficial for parties involved in SCF, especially for banks and insurance underwriters. In addition, the findings also provide direction for the contribution of blockchain technology to accounting theory in the future.

The confirmation of receipt of orders by consumers means that the online retailer actually receives the payments on many retail platforms (e.g. Taobao). In order to recoup funds as soon as possible, the retailer will take steps (e.g. improving the level of delivery and adopting a rebate policy) to encourage consumers to confirm receipt earlier. It is significant for the retailer to identify an appropriate strategy and determine the optimal product price. To address the above issues, this paper examines and compares the pricing strategies and profits under different strategies to show some managerial insights for the retailer's decision-making.

In this paper, the authors discuss four models, i.e. adopting common delivery and offering consumers no rebates, adopting common delivery and offering rebates, adopting fast delivery and offering no rebates and adopting fast delivery and offering rebates, which the retailer may consider. Under different models, consumer utility and firm's profit structure are disparate. After comparing the retailer's profits under four models, the optimal strategy, profit and product price are obtained.

Some interesting results are as follows. When the cost of fast delivery is not very high, improving the level of delivery would bring more profit to the retailer and create a positive impact on consumers. Interestingly, our results also show that offering proper rebates to stimulate consumers to confirm receipt early only serves to improve the profit only when the motivation of consumers to confirm the receipt is very low. Moreover, the authors find that a higher level of delivery services can promote the implementation of the rebate policy to improve the retailer's earnings.

This paper is the first study on the transaction mode of retail platforms and the problem of confirming receipt by a model-based method.