Factors influencing branchless banking for microfinance in Sudan: Theoretical perspectives and future directions

In Sudan more than 40% live below the poverty line and getting basic financial service poses a challenge to financial institutions. Most of these unserved populations live in far-flung areas that make it difficult for microfinance institutions to reach them. But the enormous growth of mobile technology industry has created new opportunity to expand financial services to this unserved population. Branchless banking is one of the latest technologies that have been employed in different developing countries to expand financial services to the unbanked poor. Despite the potential benefits and relevance of Branchless banking to Sudan, there are still very few studies on Branchless banking in Sudan. To address this gap in the literature, this study aims to investigate the factors that are essential to the development of branchless banking in Sudan using mobile technology. This is a research-in-progress paper, the critical review of the literature so far revealed that there are essential factors for the success of branchless banking in Sudan e.g. the identification of the industry key players and their roles, the enabling regulatory environment, the infrastructure readiness and Sudanese cultural values. The paper will provide regulators and policy makers in Sudan a way forward to expedite the development of suitable Branchless banking for microfinance in Sudan

Mobile CRM development for real estate agents

Purpose – Real estate agents are professionals who need up-to-date and accurate information about their clients in order to maintain profitable and long-lasting relationships with each of them. A satisfied customer can be very valuable and profitable in the long term. This research focuses on solving the problem of the lack of a mobile Customer Relationship Management (CRM) adapted to the needs of professionals. The importance of solving this problem is related to the importance of optimizing work and resources in a highly abundant information industry. Design/methodology/approach – It was developed of a CRM for mobile devices capable of managing information about the customers and business partners of each user, which provides a set of features well defined by the professionals. These features were collected through 15 face-to-face interviews and validated with six video conference interviews with industry specialists. For the development and evaluation of this artefact was followed the DSR methodology, corresponding each interview to an iteration of this model. Findings – From this research resulted a selection of functionalities considered essential to the real estate agent’s work. These features were successfully implemented in a mobile application that real estate agents appreciate for its simplicity and that they feel adds real value to their daily lives. Using this service, the productivity and performance of real estate agents might be improved. Originality/value – It was verified that the mobile CRM solution developed is a desired solution by real estate agents in terms of customer portfolio management, enhancing the evolution of their relationships and monitoring professional’s performance.info:eu-repo/semantics/acceptedVersio

Incremental willingness to pay: a theoretical and empirical exposition

Applications of willingness to pay (WTP) have shown the difficultly to discriminate between various options. This reflects the problem of embedding in both its specific sense, of options being nested within one another, and its more-general sense, whereby respondents cannot discriminate between close substitutes or between more-disparate rivals for the same budget. Furthermore, high proportions of reversals between WTP-value and simple preference based rankings of options are often highlighted. Although an incremental WTP approach was devised to encourage more differentiated answers and a higher degree of consistency among respondents, a theoretical basis for this approach has not been elucidated, and there is little evidence to show that this approach might indeed achieve greater consistency between explicit and implicit rankings inferred from WTP values.We address both these issues. Following our theoretical exposition, standard and incremental approaches were compared with explicit ranking in a study assessing preferences for different French emergency care services. 280 persons, representative of the French adult population, were interviewed. Half received the incremental version, the other half the standard version. Results suggest that the incremental approach provides a ranking of options fully in line with explicit ranking. The standard approach was reasonably consistent with explicit ranking but proved unable to differentiate between the five most preferred providers, as predicted by theory. Our findings suggest that the incremental approach provides results which can be used in priority-setting contexts

BLOCKCHAIN-BASED SOLUTIONS FOR HUMANITARIAN SUPPLY CHAIN MANAGEMENT

The outbreak of the novel COVID-19 demonstrates how pandemics disturb supply chains (SC) all across the world. Policymakers and private-sector partners are increasingly acknowledging that we cannot tackle today\u27s issues without leveraging the promise of new technology. Blockchain technology is increasingly being adopted to help humanitarian efforts in various fields. This paper presents conceptual research designed to assess how Blockchain distributed ledger technology can be leveraged to enhance humanitarian supply chain management (HSCM). This paper fills the present research gap on the Blockchain\u27s potential implications for HSCM by proposing a framework built on the foundations of five prominent institutional economic theories: social exchange theory, principal-agent theory, transaction cost theory, resource-based view, and network theory. These theories could be utilized to generate research topics that are theory-based and industry-relevant. This conceptual framework assists institutions in making decisions about how to recover and rebuild their SC during disasters

Enhancing Dynamic Production Scheduling And Resource Allocation Through Adaptive Control Systems With Deep Reinforcement Learning

Traditional production scheduling and resource allocation methods often struggle to adapt to changing conditions in manufacturing environments. To address this challenge, this study leverages an adaptive control system integrated with a Deep Deterministic Policy Gradient (DDPG) alongside a particle swarm optimization algorithm to enable real-time production scheduling and allocation of resources. The system continuously learns from generated production data and adjusts production schedules with resource allocations based on evolving conditions such as demand fluctuations and resource availability. By harnessing the capabilities of Deep Reinforcement learning, the proposed approach of applying the DDPG algorithm to simulate the environment improves production efficiency, minimizes delays, and optimizes resource utilization. Through conducted experiments, the effectiveness of the DDPG-Particle Swarm Optimization technique (DRPO) was demonstrated in enhancing dynamic production scheduling and resource allocation in simulated manufacturing settings. This study presents a significant step towards intelligent, self-improving production control systems that can navigate complex and dynamic manufacturing environments

Alternative Approaches to the Empirical Validation of Agent-Based Models

This paper draws on the metaphor of a spectrum of models ranging from the most theory-driven to the most evidence-driven. The issue of concern is the practice and criteria that will be appro- priate to validation of different models. In order to address this concern, two modelling approaches are investigated in some detailed – one from each end of our metaphorical spectrum. Windrum et al. (2007) (http://jasss.soc.surrey.ac.uk/10/2/8.html) claimed strong similarities between agent based social simulation and conventional social science – specifically econometric – approaches to empirical modelling and on that basis considered how econometric validation techniques might be used in empirical social simulations more broadly. An alternative is the approach of the French school of \'companion modelling\' associated with Bousquet, Barreteau, Le Page and others which engages stakeholders in the modelling and validation process. The conventional approach is con- strained by prior theory and the French school approach by evidence. In this sense they are at opposite ends of the theory-evidence spectrum. The problems for validation identified by Windrum et al. are shown to be irrelevant to companion modelling which readily incorporate complexity due to realistically descriptive specifications of individual behaviour and social interaction. The result combines the precision of formal approaches with the richness of narrative scenarios. Companion modelling is therefore found to be practicable and to achieve what is claimed for it and this alone is a key difference from conventional social science including agent based computational economics.Social Simulation, Validation, Companion Modelling, Data Generating Mechanisms, Complexity

Prosumer behaviour in emerging electricity systems

This dissertation investigates the interface between technology and society in the emerging electricity systems and in particular the role of the energy prosumer in the energy transition. It contributes to the understanding of the role of consumers in emerging electricity systems within the current EU energy policy context where consumer active participation is regarded as "a prerequisite for managing the energy transition successfully and in a cost-effective way". Emerging energy systems are characterized by a high level of complexity, especially for what concerns the behaviour of social actors. Social actors interact through physical and social networks by sharing information and learning from one another through social interactions. These interactions determine self-organization and emergent behaviours in energy consumption patterns and practices. I argue that the best suited tool to study emergent behaviours in energy consumption patterns and practices, and to investigate how consumers' preferences and choices lead to macro behaviours is agent based modelling. To build a sound characterization of the energy prosumer, I review the current social psychology and behavioural theories on sustainable consumption and collect evidence from EU energy prosumers surveys, studies and demand side management pilot projects. I employ these findings to inform the development of an agent based model of the electricity prosumer, Subjective Individual Model of Prosumer – SIMP, and its extended version, SIMP-N, that includes the modelling of the social network. I apply SIMP and SIMP-N models to study the emergence in consumer systems and how values and beliefs at consumer level (as defined by social psychology and behavioural theories and informed by empirical evidence) and social dynamics lead to macro behaviours. More specifically, I explore the diffusion of smart grid technologies enabled services among a population of interacting prosumers and evaluate the impact of such diffusion on individual and societal performance indicators under different policy scenarios and contextual factors. The analysis of the simulation results provides interesting insights on how different psychological characteristics, social dynamics and technological elements can strongly influence consumers' choices and overall system performance. I conclude proposing a framework for an integrated approach to modelling emerging energy systems and markets that extend the SIMP model to also include markets, distribution system operator and the electricity network

A Survey: Approaches for Detecting the Autism Spectrum Disorder

A brain disease mean autism spectrum disorder affects a person's ability to connect, communicate, and remember. Though autism is capable of being diagnosed regardless of age, most of the disorder's signs begin to appear around its initial two years of life and increase as time goes on. People with autism suffer from a wide range of difficulties, such sensory problems, action impairments, intellectual disabilities, and psychological disorders including depression and anxiety. Autism has been rising at an unacceptably rapid pace surrounding around the globe. Autism detection involves an enormous amount of time and money. The early detection of autism might be highly advantageous in regards to treating patients with the right medical treatments at the correct moment in time. It could prevent the individual's illnesses before developing severe and could help in decreasing future expenses associated to a diagnosis that was delayed. Thereby, the requirement to develop a rapid, trustworthy, and simple examination device that can make predictions is essential. Autism Spectrum Disorder (ASD) has been gaining momentum presently more quickly than at any time earlier. Diagnostic evaluation of autistic characteristics is extremely expensive and time-consuming as well. The advancement of algorithms for machine learning (ML) and Artificial intelligence (AI) have made it achievable to identify autism fairly earlier. Although the reality of numerous studies have been carried out performed utilising different techniques, these studies have not contributed to any definitive conclusions regarding the capacity of predicting autism attributes in regards to different age categories. Thereby, the objective of this research is to predict Autism among people of all ages and to provide an effective model for prediction using various ML approaches

A mobile CRM development for real estate

Real estate (RE) agents are professionals who need up-to-date and accurate information about their clients in order to maintain profitable and long-lasting relationships with each of them to prosper in such a competitive industry. The research focuses on one problem: unexistance of mobile solution, adapted to the needs of RE agents, that integrates only their needed features. The creation of this allows them to improve their performance and optimize their results, making it possible to invest more time in building relationships and less in secretarial tasks. The importance of solving this problem is related to the importance of optimizing work and resources in a highly abundant information industry. Through this service digitalization, the productivity and performance of RE agents can be improved. The research consists in the development of a Costumer Relationship Management (CRM) for mobile devices capable of managing information about the customers and business partners of each user, which provides agenda services and also a visual information system capable of showing the progress of the agent and other statistical analysis. All functionalities implemented were collected through 15 face-to-face interviews and validated with seven videoconference interviews. All of them were made using different specialists. For the development and evaluation of this artifact was followed the DSR methodology corresponding to each interview made to an iteration of this model. It was verified that the mobile CRM solution is an added value in terms of customer portfolio management, enhancing the development of their relationships, and in monitoring the performance of professionals.Os agentes imobiliários são profissionais que necessitam de informação atualizada e precisa sobre os seus clientes para conseguirem manter relações profícuas e duradouras com cada um deles, a fim de prosperarem numa indústria tão competitiva. A dissertação concentra-se num problema: não existe uma solução mobile, criada à medida das necessidades dos agentes imobiliários, capaz de melhorar o seu desempenho e otimizar os seus resultados, tornando possível investir mais tempo no trabalho da relação com o cliente e menos com tarefas de secretaria. A importância da resolução deste problema está relacionada com a importância de otimizar trabalho e recursos numa indústria altamente abundante de informação. Através da digitalização destes serviços a produtividade e performance dos agentes imobiliários podem ser melhoradas. A pesquisa consiste no desenvolvimento de um Costumer Relationship Management (CRM) para dispositivos móveis capaz de gerir informação sobre os clientes e parceiros de negócio de cada utilizador, que forneça serviços de agenda e ainda um sistema de informação visual capaz de mostrar os progressos do agente e outras análises estatísticas. Todas as funcionalidades implementadas foram recolhidas através de 15 entrevistas presenciais e validadas com sete entrevistas por vídeo-conferencia. Para esta validação do artefacto seguiu-se a metodologia DSR correspondendo cada entrevista feita a uma iteração deste modelo. Verificou-se que a solução mobile de CRM é uma mais-valia ao nível da gestão da carteira de clientes potenciando o desenvolvimento das suas relações, e ao nível da monitorização da performance dos agentes imobiliários