A Hedged Monte Carlo Approach to Real Option Pricing

In this work we are concerned with valuing optionalities associated to invest or to delay investment in a project when the available information provided to the manager comes from simulated data of cash flows under historical (or subjective) measure in a possibly incomplete market. Our approach is suitable also to incorporating subjective views from management or market experts and to stochastic investment costs. It is based on the Hedged Monte Carlo strategy proposed by Potters et al (2001) where options are priced simultaneously with the determination of the corresponding hedging. The approach is particularly well-suited to the evaluation of commodity related projects whereby the availability of pricing formulae is very rare, the scenario simulations are usually available only in the historical measure, and the cash flows can be highly nonlinear functions of the prices.Comment: 25 pages, 14 figure

The effect of supply chain management challenges on research and development projects using Fuzzy DEMATEL and TOPSIS approach

Purpose: This paper aimed to identify, classify and prioritize supply chain management challenges for research-development projects in the R&D organization.Research Methodology: Based on previous literature and interview with related experts, the initial challenges of SCM for research-development projects in Iran organization were extracted. Thereafter, the identified challenges were finalized, classified, and prioritized. For this purpose, a semi-interview and questionnaire were designed, applied, and then analyzed using some statistical methods. Validation of the results was done through several interviews. Finally, the necessary modifications were made to the factors of environmental sustainability associated with the COVID-19 crisis. Results: In this study, the challenges of SCM for research-development projects in Iran organization were divided into six categories: cultural, motivational, contextual, process, infrastructural, and capabilities. Thereafter, suggested solutions were presented which describe how the challenges of SCM in research-development projects may be removed progressively. Limitations: This research is only described in project-based organizations. The study was limited to construction projects in different cities of Iran.Contribution: The prioritized challenges of SCM are a guideline for managers or decision-makers of R&D projects which will enable them, resolve challenges or improve on decision making. It also serves as a useful base for researchers to expand further research concerning the challenges of SCM in other research-development organizations. This study may present high value for researchers in the SCM field for research-development projects. Also, this study presents several solutions for the improvement of challenges considering the level of their importance to SCM

Influential Article Review- Annual Capital Outflow for an Institutional Investment Firm: A Flow-through Approach to Coordination of Network Support Chain Preparation and Financial Planning

This paper examines finance. We present insights from a highly influential paper. Here are the highlights from this paper: A common side effect of cross-linked global economies is that well-positioned middle-class companies are acquired by institutional investors, which formulate unreasonable return expectations in many cases. Therefore, the resulting payouts are often not in line with business operations so that even world market leaders get into trouble or close. In this context, we consider the case of a sanitary company, which had to manage the described situation after a business takeover. In order to coordinate the annual cash outflows to the investor with intra-organizational supply chain planning and financial planning, we propose a mixed-integer non-linear programming model that is based on the flow-to-equity discounted cash flow method. The objective is to maximize the present value of equity while determining annual cash outflows to the institutional investor during his engagement. As the decisions of the investor during his engagement influence possible operations of the company after his engagement, the residual value of equity (that influences the selling price) is considered. The modeling is based on cash flow series, which result from supply chain operations and restructuring on the one hand, and from financial transactions on the other. Financing is characterized by interest rates depending on the period the credit starts, the credit period, the debt limit of the company and the current total debt. As the latter is a result of the optimization, non-linearity arises. Nevertheless, both the expected demand scenario and further randomly generated demand scenarios of the sanitary company could be solved to the optimum with the commercial optimization package GAMS 23.8/SCIP 2.1.1 within acceptable computation times, if capacity profiles are assigned to the locations to depict feasible and/or preferred capacity developments. For our overseas readers, we then present the insights from this paper in Spanish, French, Portuguese, and German

The impact of data quality and analytical capabilities on planning performance: insights from the automotive industry

Conventional wisdom suggests that data quality plays a central role for compiling valid and reliable plans to make the right decisions. At the same time, it is acknowledged that planning processes are both data and knowledge intensive and characterized by the human-computer interface. However, there are limited academic investigations on how data quality and analytical capabilities simultaneously impact planning performance. Drawing on the conceptual approach of business analytics, we introduce the notion of analytical capabilities, which is operationalized through three distinct resources: IT-usability, user competence, and analytical execution. To assess the impact of data quality and analytical capabilities on planning performance, we develop a structural equation model, which is then tested using data from the automotive industry. Our results suggest that analytical capabilities are a significant mediator for the effect of data quality on planning performance

Impact of Health Capital and Education on Infant Mortality Rate of Districts of Punjab

Economies with large labor population and labor oriented production face problems of quality of labor provided. This quality can be divided into two components; one the skill component and other the health component. The purpose of the paper is to identify the root causes of low health standards in the working population. The district wise data of Punjab (Pakistan), revealed that fertility rate, number of hospitals, literacy rate, and proxy income are the major determinants that can reduce Infant Mortality Rate, and the time being dummy variable in GMM model indicated the health standard to be depreciated in 2011 as compared to 200

3D printing the future: scenarios for supply chains reviewed

Purpose: The aim of this paper is to evaluate existing scenarios for 3D Printing in order to identify the “white space” where future opportunities have not been proposed or developed to date. Based around aspects of order penetration points, geographical scope and type of manufacturing, these gaps are identified. Design/methodology/approach: A structured literature review has been carried out on both academic and trade publications. As of the end of May 2016, this identified 128 relevant articles containing 201 future scenarios. Coding these against aspects of existing manufacturing and supply chain theory has led to the development of a framework for identify “white space” in existing thinking. Findings: The coding shows that existing future scenarios are particularly concentrated on job shop applications and pull based supply chain processes, although there are fewer constraints on geographical scope. Five distinct areas of “white space” are proposed, reflecting various opportunities for future 3DP supply chain development. Research limitations: Being a structured literature review, there are potentially articles not identified through the search criteria used. The nature of the findings is also dependent upon the coding criteria selected. However, these are theoretically derived and reflect important aspect of strategic supply chain management. Practical implications: Practitioners may wish to explore the development of business models within the “white space” areas. Originality/value: Currently, existing future 3DP scenarios are scattered over a wide, multi-disciplinary literature base. By providing a consolidated view of these scenarios, it is possible to identify gaps in current thinking. These gaps are multidisciplinary in nature and represent opportunities for both academics and practitioners to exploit

Role of Optimal Production Plan at the Focal Firm in Optimization of the Supply Chain

Supply chain management and optimization is a critical aspect of modern enterprises and an expanding area of research. Modeling and optimization are the traditional tools of supply chain management. The techniques have been used by many companies for planning, manufacturing, and other decision areas in supply chains. Current study is motivated by the fact that optimization studies in supply chain management have mostly considered network optimization. Supply chain management however, requires alignment between the supply chain partners at the tactical level. As a first step towards achieving this goal, current study presents a model that incorporates the activity level planning at the focal firm in a supply chain. This paper presents a new mixed integer programming model that incorporates optimization of production planning at the focal firm while optimizing the strategic alignment of the supply chain entities. The model represents a four step, multi-echelon supply chain including supplier, warehouse, manufacturer, and retailer. The manufacturer in this network represents the focal firm. This model is an attempt to integrate the production planning decisions in the network optimization decisions

PRODUCTION PLANNING MULTI-PRODUCT AND MULTI-MACHINE PROBLEMS IN ORDER TO MAXIMIZE THE ECONOMIC PERFOMANCE

Este artigo propõe um novo método que visa à maximização do resultado econômico operacional, através do planejamento de produção. O modelo utiliza um algoritmo de otimização que envolve quatro áreas de análise: mercado, produção, custos e por fim o resultado econômico. O objetivo é a maximização do lucro. A aplicação do modelo ocorre em uma empresa de manufatura que tem se caracterizado por alta variabilidade na definição dos preços de venda. Os resultados deste estudo indicam que pequenas variações nos preços de venda podem comprometer substancialmente os lucros globais do sistema produtivo

Modelo de planificación táctica de cultivos bajo incertidumbre

Introduction- Currently, decision making is one of the most important processes in crop planning and the uncertainties experienced by fields in open field conditions. This is necessary to develop planning models that incorporate these uncertainties as presented in the next investigation. Objective- To apply a tactical model for the optimization of the supply chain in the production of passion fruit for three producers in the municipality of Suaza, Huila considering three probable scenarios to support the planning decisions, to serve as a tool to support the making of decisions in crop planning. Methodology- The chosen modeling is a stochastic bi-stage program where the decisions in the first stage are taken to satisfy the uncertain results of the second stage. The proposed model determines how many hectares each producer must plant to minimize costs considering yield, leaving the price as the source of uncertainty for the second stage. Finally, the expected utility is analyzed under different scenarios. Results- The results of the model show that risk-sharing strategies based on cooperation between producers can achieve higher profits in different scenarios and meet market needs; in the pessimistic scenario a profit of $15,982,562.62 can be achieved. Conclusions- Applying models under uncertainty allow us to obtain recommendations on planning processes to make decisions that conform to a stochastic approach compared to the results obtained without considering uncertainty, and in turn propose collaborative farm management strategies.The resulting model shows a starting point to establish more robust production plans that adjust to the needs of producers, considering the importance of variables and random parameters on planting decisions.Introducción- Actualmente la toma de decisiones es uno de los procesos más importantes dentro de la planificación de cultivos dadas las incertidumbres experimentadas por los agricultores en condiciones de campo abierto, esto hace necesario el desarrollo de modelos de planeación que incorporen estas incertidumbres como se presenta en la siguiente investigación. Objetivo- Aplicar un modelo táctico para la optimización de la cadena de suministro en la producción de maracuyá para tres productores en el municipio de Suaza, Huila considerando tres escenarios probables para sustentar las decisiones de planificación, que sirva como herramienta de apoyo a la toma de decisiones en la planificación del cultivo. Metodología- El modelado elegido es un programa estocástico bi-etapa donde las decisiones en la primera etapa se toman para satisfacer los resultados inciertos de la segunda etapa. El modelo propuesto, determina qué cantidad de hectáreas debe sembrar cada productor para minimizar los costos considerando el rendimiento, dejando el precio como la fuente de incertidumbre para la segunda etapa. Finalmente, se analiza la utilidad esperada bajo diferentes escenarios. Resultados- Los resultados del modelo muestran que las estrategias de riesgo compartido a partir de la cooperación entre productores pueden lograr mayores utilidades en los diferentes escenarios y cumplir con las necesidades del mercado; en el escenario pesimista se puede lograr una utilidad de$15.982.562,62. Conclusiones- Aplicar modelos bajo incertidumbre permite obtener recomendaciones sobre procesos de planificación para tomar decisiones que se ajustan a un enfoque estocástico en comparación con los resultados obtenidos sin considerar la incertidumbre, y a su vez plantear estrategias colaborativas de gestión de finca. El modelo resultante muestra un punto de partida para establecer planes de producción más robustos que se ajusten a las necesidades de los productores, considerando la importancia de variables y parámetros aleatorios sobre las decisiones de plantación