Optimal Amount Of Investment Research Articles

A theory of competitive industry dynamics with innovation and imitation

Empirical evidence on industry life-cycle reveals a pattern in which innovation rates remain fairly stable or are perhaps even higher at early stages, while patenting increases sharply as the industry matures. This increase in patenting in later stages is accompanied by net exit and lower rates of output growth and price decline. In this paper, we develop a dynamic model of a competitive industry with innovation and imitation that is consistent with these stylized facts. We derive an equilibrium growth path, along which leading firms invest in increasing the stock of technological knowledge and choose not to prevent imitation by other firms as long as the industry remains relatively small. As the industry expands including new entry, the leaders' optimal amount of investment gradually declines. We show that under some rather general conditions, there would exist a scale of the industry where innovating firms would choose to start preventing free imitation, bringing further expansion of the industry through new entry to a halt and causing net exit.

An integrated vendor-managed inventory model for a two-echelon system with order cost reduction

Simultaneously reducing inventory levels of raw materials, work-in-process, and finished items has become a major focus for supply chain management. In order to achieve a higher degree of coordination and automation among the supply chain parties, the supply chain sometimes invests in reducing the ordering cost to streamline and speed up transactions via the application of information technology. In this paper, an integrated vendor-managed inventory (VMI) model is presented for a single vendor and multiple buyers, where the vendor purchases, and processes raw materials and then delivers finished items to multiple buyers. A joint relevant cost model is developed with constant production and demand rates under the assumption that the buyers’ ordering cycles may be different and that each buyer can replenish more than once in one production cycle, in which the investment decision is also considered. A solution procedure of the optimal investment amount and replenishment decision for all the buyers and the vendor is proposed. Three numerical examples with an exponential ordering cost function are presented to provide insight.

The optimal investment in FMCG distribution process with continuous delay of payment

Due to globalisation, the FMCG distributors in the developing countries are struggling to capture and retain their market share from the multinational companies. To attract the retailers, the distributors supply on credit and collect the amount in unequal weekly instalments. When the supply on credit becomes inevitable, the distributors have to find out ways of optimising the investment. Moreover, the investment has to be shared among the retailers depending on their demand and payment policy, to maximise the sales and minimise the balance payment. This paper proposes a model for FMCG distribution on credit supply in the developing countries. Genetic Algorithm (GA) is employed to obtain the optimal amount of investment required and to search for the optimal replenishment policy to each retailer based on his demand and payment policy. A case of biscuits and confectionery products distribution is taken for study and the results are compared with the existing system.

Competitive Innovation and Information Flows in a Growing Industry

Case studies reveal a pattern of rapid industrial growth propelled by innovation and quick diffusion of new technologies, especially among emerging industries exposed to global competition. At the firm level, the distribution of innovative activity is highly skewed, while productivity growth is not strongly related to a firm's innovative activity. In this paper, we develop a dynamic model of a competitive industry that is consistent with these stylized facts. We derive an equilibrium growth path, along which a leading firm invests in increasing the stock of technological knowledge and chooses not to prevent spillovers to other firms as long as the industry remains relatively small. As the industry expands including new entry, the leader's optimal amount of investment gradually declines. The leading firm may also choose to start keeping its innovations secret somewhere along the equilibrium growth path, bringing technology diffusion and further expansion of the industry to a halt. Policy implications include beneficial effects of the absence of tariff protection, and possible beneficial effects of moderate costs of intellectual property rights protection.

An integrated inventory model for a single vendor and multiple buyers with ordering cost reduction

Forming strategic alliances and utilizing modern information technologies have been the two most important ways for firms to gain such competitive advantages as lower logistics costs and secure customers’ loyalty. In this paper, we consider an integrated inventory system where a single vendor purchases and processes raw materials in order to deliver finished items to multiple buyers. The vendor and all buyers are willing to invest in reducing the ordering cost (e.g., establishing an electronic data interchange based inventory control system) in order to decrease their joint total cost. The amount of investment determines the planned ordering cost and hence affects their replenishment decisions. One major managerial implication from this ordering cost reduction is that the efforts to streamline and speedup transactions via the application of information technologies may result in a higher degree of coordination and automation among allied trading parties. An analytical model is developed to derive the optimal investment amount and replenishment decisions for both vendor and buyers. The exponential ordering cost function is then applied to our general model, and a numerical analysis is performed to provide interesting insights of the model. Numerical results show that the vendor and all the buyers can benefit directly from substantial cost savings by this ordering cost reduction investment.

Investing in ordering cost reduction for integrated inventory systems

In this paper, we investigate an integrated inventory system where a single vendor purchases and processes raw materials in oreler to deliver finished items to multiple buyers. The vendor and all buyers jointly invest in reducing the ordering cost (e.g., establishing electronic data interchange based ordering systems) to decrease their joint total cost. The amount of investment determines the planned ordering cost and hence affects their inventory replenishment decisions. An analytical model is developed to decide the optimal investment amount and lot sizes for both vendor and buyers. In addition, we apply an exponential ordering cost function to our general model to provide interesting insights of the model. Numerical results show that the integrated inventory system can benefit substantially from this ordering cost reduction investment.

Optimal trading from minimizing the period of bankruptcy risk

Assuming that financial markets behave similar to random walk processes we derive a trading strategy with variable investment which is based on the equivalence of the period of bankruptcy risk and the risk to profit ratio. We define a state dependent predictability measure which can be attributed to the deterministic and stochastic components of the price dynamics. The influence of predictability variations and especially of short term inefficiency structures on the optimal amount of investment is analyzed in the given context and a method for adaptation of a trading system to the proposed objective function is presented. Finally we show the performance of our trading strategy on the DAX and S&P 500 as examples for real world data using different types of prediction models in comparison.

A trading strategy with variable investment from minimizing risk to profit ratio

Assuming that financial markets behave similar to non-stationary random walk processes we derive an optimal trading strategy with variable investment for minimizing the risk to profit ratio over the trading period. We define a predictability measure which can be attributed to the deterministic and stochastic components of the price dynamics. The influence of predictability variations and especially of structures of short-term inefficiencies on the optimal amount of investment is analyzed in the given context. Finally, we show the performance of our trading strategy on an artificial price dynamics and on the DAX and S&P 500 as examples for real-world data using different types of prediction models in comparison.

Optimal batch size and investment in multistage production systems with scrap

In this paper, we study the problem of selecting the optimum production batch size in multistage manufacturing facilities with scrap and determining the optimal amount of investment. We analyse the effect of investment for quality improvement on the reduction of the proportion of defectives, and the effect of this reduction on processing cost, setup cost, holding cost, and profit loss. The quality characteristic of the product manufactured is assumed to be normally distributed with a mean equal to the target value. The purpose of the investment is to reduce the variance of the quality characteristic and hence the proportion of defectives. The model assumes known demand, which must be satisfied completely, scrappage at each stage and profit loss due to scrap. Using this model, the optimal values of the production quantity and the proportion of defectives for minimizing the total cost are obtained. The optimal investment is then obtained using the relationship between the investment and the proportion of defectives.

Optimal Investment in Urban Drainage: A Framework for Cost‐Benefit Analysis

This article addresses some basic issues (including distributional weights, discount rates, and the value of life) in the cost‐benefit analysis of urban drainage and provides a framework for the estimation of the optimal amount of investment for flood mitigation. This involves: (i) estimating the expected total damage from flooding in present‐value terms before flood mitigation; (ii) deriving the reduction in expected total damage as the average recurrent interval of flooding increases; (iii) estimating how this interval increases with the amount of investment in flood mitigation; and (iv) choosing the optimal investment by equating marginal benefit and marginal cost. The framework is also applicable to other accident or damage mitigation investments and some issues discussed are relevant to all types of cost‐benefit analysis.

Dynamic Process Improvement

This paper explores the economics of investing in gradual process improvement, a key component, with empirically supported importance, of the well known Just-in-Time and Total Quality Control philosophies. We formulate a Markov decision process, analyze it, and apply it to the problem of setup reduction and process quality improvement. Instead of a one-time investment opportunity for a large predictable technological advance, we allow many smaller investments over time, with potential process improvements of random magnitude. We use a somewhat nonstandard formulation of the immediate return, which facilitates the derivation of results. The policy that simply maximizes the immediate return, called the last chance policy, provides an upper bound on the optimal investment amount. Furthermore, if the last chance policy invests in process improvement, then so does the optimal policy. Each continues investing until a shared target state is attained. We derive fairly restrictive conditions that must be met for the policy of investing forever in process improvements to be optimal. Decreasing the uncertainty of the process (making the potential improvements more predictable) has a desirable effect: the total return is increased and the target state increases, so the ultimate system is more productive. Numerical examples are presented and analyzed.

A use for the 'index of profitability'

The concept of 'index of profitability', used to identify optimal investment options, is developed to provide a test for the optimal amount of investment on each option.

Log-linear probability models: an application to the analysis of timing of first birth.

Using data (the initial sample was 5533 women aged 14 to 24) from the National Longitudinal Surveys conducted by Ohio State University's Center for Human Resource Research, and the log linear probability technic, the impact of family background variables and personal characteristics on the timing of 1st birth are examined. These factors are expected to affect age at entry into motherhood directly, and indirectly, through education. A variable which increases the education attainment of either father or mother will indirectly delay childbearing. The study attempts to disentangle direct and indirect influences, and determine whether some effects may be nonlinear. Regarding other variables: 1) maternal employment only slightly increases the likelihood of an early 1st birth; 2) a broken home is associated with more than a 100% increase in the probability of an early birth; and 3) planning to be employed at 35 is associated with a higher likelihood of bearing the 1st child at an early age, confirming the human capital theory that the optimal amount of investment in human capital is a positive function of how long one plans to use it. Total effects of race on both age at transition to motherhood and school are great, being almost double for nonwhites for probabilities of an early 1st birth; the probability of having dropped out of school by the date of the 1st birth is 0.3185 for nonwhites, but only 0.2260 for whites. In conclusion, parental education, race, and whether the young woman grew up in an intact family are significant variables. Number of siblings and plans for age 35 have opposite direct and indirect influences. Nonlinearities in the impact of some explanatory variables on age at 1st birth and education are shown. This study illustrates the potential usefulness of log linear probability models, and may provide a framework for the statistical analysis of a wide range of economic issues.