Development and Application of Multi Commodity Multi Location Integrated Model for Manufacturing Industry

This paper presented the development and application of Linear Programming to the modeling of Multi-Commodity Multi-Location production-distribution model for manufacturing industry. The Manufacturing industry has two plants, three depots and twenty retailer’s axis in Lagos. The products are based on how they are packaged; Product 1(P1), Product 2(P2), Product 3(P3) and Product 4(P4). TORA software is used in analyzing the data obtained from the company. Comparing the optimal Multi-Commodity Multi-Location transportation cost of One trillion, Five Hundred And Thirty Billion And Four Hundred And Ninety Million Naira to existing transportation cost of truckload Three Trillion, Five Hundred And Forty Four Billion Naira, the difference is Two Trillion, Thirteen Billion And Five Hundred And Ten Million Naira which is Four Hundred And Two Billion And Seven Hundred And Two Million Naira annually resulting to 56.82 percent gain in profit.

Innovative Ecosystem Model of Vaccine Lifecycle Management

The COVID-19 pandemic has severely tested humanity, revealing the need to develop and improve the medical, economic, managerial, and IT components of vaccine management systems. The vaccine lifecycle includes vaccine research and development, production, distribution, and vaccination of the population. To manage this cycle effectively the proper organizational and IT support model of the interaction of vaccine lifecycle management stakeholders is needed—which are an innovation ecosystem and an appropriate virtual platform. A literature review has revealed the lack of methodological basis for the vaccine innovation ecosystem and virtual platform. This article is devoted to the development of a complex approach for the development of an innovation ecosystem based on vaccine lifecycle management and a virtual platform which provides the data exchange environment and IT support for the ecosystem stakeholders. The methodological foundation of the solution, developed in the article, is an enterprise architecture approach, CALS technologies, supply chain management and an open innovation philosophy. The results, presented in the article, are supposed to be a reference set of models for the creation of a vaccine innovation ecosystem, both during pandemics and periods of stable viral load.

Agri-food safety optimized by blockchain technology: review

Blockchain technology is a distributed database, an innovation tool in the agri-food supply chain in processes such as production, distribution, marketing. In this research work, the blockchain technology application in agri-food security processes was evaluated, establishing the best conditions for its adoption in companies, this proposal synthesizes the contributions as a disruptive technology, for this, the information was collected from the period 2018-2020 from the Scopus and Web of Science bases, performing an analysis of the information using the Atlas TI 8.4 software, establishing the focus of the research on a network of codes suggested by some authors. It was found that the contribution of Blockchain for the years of study was traceability 26%, supply chain 17.5%, technological development 10.4%, trust 9.8%, among others. It is concluded that establishing the theoretical link between technology and traceability processes in supply chains, traceability in the agri-food sector is essential to certify information of interest to the stakeholder group. This is because traceability is the transcendental element of the food safety system that allows guaranteeing control in the supply chain when processes are being recorded and enriching the databases, which can be available to the final consumer to check the details of the production cycle and that technological elements generate competitiveness in companies with blockchain in their procedures, promote high levels of transparency, data security, decentralization, among other terms associated with trust, and a better relationship with the consumer is developed and a greater number of sale increasing profitability.

Speculations on the Future of Economic Models in the Wake of Trans/Posthuman Sentient Evolution in Charles Stross’s SF Novel “Accelerando”

Economy, understood as a domain of production, distribution and consumption of goods and services, has been unquestionably comprehended as a social activity, the purpose of which is to satisfy first of all vital material, but also immaterial, needs of the biological natural human being. Whatever the underlying ideology—whether protectionist mercantilism, the physiocrats’ laissez-faire policy, Adam Smith’s free-market capitalism, Karl Marx’s socialist economics, Keynesian state interventionism, or present day neoliberalism—economic considerations have been invariably driven by the fundamental problem of scarcity. The objective of the proposed paper is to present Charles Stross’s speculative predictions, made in his SF novel Accelerando, about the future of economic models in light of trans/posthuman evolution hailed by, among others, Ray Kurzweil, Max More, and Hans Moravec.

A bilevel game model for ascertaining competitive target prices for a buyer in negotiation with multiple suppliers

In this paper, a decision-support is developed for a strategic problem of identifying target prices for the single buyer to negotiate with multiple suppliers to achieve common goal of maintaining sustained business environment. For this purpose, oligopolistic-competitive equilibrium prices of suppliers are suggested to be considered as target prices. The problem of identifying these prices is modeled as a multi-leader-single-follower bilevel programming problem involving linear constraints and bilinear objective functions. Herein, the multiple suppliers are considered leaders competing in a Nash game to maximize individual profits, and the buyer is a follower responding with demand-order allocations to minimize the total procurement-cost. Profit of each supplier is formulated on assessing respective operational cost to fulfill demand-orders by integrating aggregate-production-distribution-planning mechanism into the problem. A genetic-algorithm-based technique is designed in general for solving large-scale instances of the variant of bilevel programming problems with multiple leaders and single follower, and the same is applied to solve the modeled problem. The developed decision support is appropriately demonstrated on the data of a leading FMCG manufacturing firm, which manufactures goods through multiple sourcing.

Mind the adoption gap: Findings from a field experiment designed to scale up the availability of fodder shrub seedlings in Malawi

While dairy production has the potential to diversify smallholder agriculture and increase incomes, there are multiple constraints. One is the consistent provision of quality feed. High protein, leguminous fodder shrubs—also referred to as Fodder Tree Technology (FTT)—can help address this constraint, yet adoption levels are generally low. Implemented in Kenya and Malawi, the Shrubs for Change (S4C) project is employing several approaches to address this situation, including those informed by behavioural science. Given that approximately 500 shrubs per cow are needed to generate enough leaf matter to bolster milk production, promoting FTT at scale necessitates the production, distribution, and successful planting of large numbers of shrub seedlings. We implemented a field experiment in Malawi’s Southern Region in late 2021 to test the effectiveness of a social learning intervention intended to motivate dairy farmers to significantly scale up the production of FTT seedlings. This intervention involved meeting with dairy farmers in 39 randomly selected milk production zones to review the numbers of seedlings being produced vis-à-vis local demand, coupled with the development of action plans to address identified production gaps. While we find that this intervention increased the setting up of private nurseries by 10% (p<0.05), it only increased overall seedling production by an average of 20 additional seedlings per dairy farmer (p>0.1). We offer several explanations for this lower than expected and statistically insignificant result, which point to the need for iterative rounds of engagement with farmers when supporting them to take up FTT and other complex agronomic and sustainable land management innovations.