Search results

Planning for increased contractor profits should start at the time the contract is signed because low profits and lack of profitability are the primary causes of contractor failure. The purpose of this paper is to propose an integrated profit maximization model (IPMM) that aims for maximum expected profit by using time-cost tradeoff analysis, adjusted start times of activities, minimized financing cost and minimized extension of work schedule beyond the contract duration. This kind of integrated approach was never researched in the past.

IPMM is programmed into an automated system using MATLAB 2016a. It generates an optimal work schedule that leads to maximum profit by means of time-cost tradeoff analysis considering different activity acceleration/deceleration methods and adjusting the start/finish times of activities. While doing so, IPMM minimizes the contractor’s financing cost by considering combinations of different financing alternatives such as short-term loans, long-term loans and lines of credit. IPMM also considers the impact of extending the project duration on project profit.

IPMM is tested for different project durations, for the optimality of the solutions, differing activity start/finish times and project financing alternatives. In all cases, contractors can achieve maximum profit by using IPMM.

IPMM considers a deterministic project schedule, whereas stochastic time-cost tradeoff analysis can improve its performance. Resource allocation and resource leveling are not considered in IPMM, but can be incorporated into the model in future research. Finally, the long computational time is a challenge that needs to be overcome in future research.

IPMM is likely to increase profits and improve the chances of contractors to survive and grow compared to their competitors. The practical value of IPMM is that any contractor can and should use IPMM since all the data required to run IPMM is available to the contractor at the time the contract is signed. The contractor who provides information about network logic, schedule data, cost data, contractual terms, and available financing alternatives and their APRs can use an automated IPMM that adjusts activity start times and durations, minimizes financing cost, eliminates or minimizes time extensions, minimizes total cost and maximizes expected profit.

Unlike any prior study that looks into contractors’ profits by considering the impact of only one or two factors at a time, this study presents an IPMM that considers all major factors that affect profits, namely, time-cost tradeoff analysis, adjusted start times of activities, minimized financing cost and minimized extension of work schedule beyond the contract duration.

This paper aims to investigate the problem of searching for the equilibrium in the housing market, the mortgage lending market and the insurance market in the process of selling the residential property. Three classes of markets are established in three modes, which reflect the interdependence of the firms’ interests in these markets through the parameters of their integration. The paper aims to determine the prices in these markets on the basis of the compromises among the conflicting interests of the related firms, and, in addition, to assess the rationality of integration for firms, which are participants in the process of selling the residential property.

On the basis of the revenue sharing contracts and the supply chain coordination methods, the optimization models of the housing realtor, the mortgage bank and the insurance company are developed. The models consider the interdependence of the firms’ interests, the monopolistic competition in these markets and the conditions of the firms’ individual rationality in the interaction process.

The results of the study are as follows. First, as a consequence of a decrease in the demand curves in monopolistic competition, the housing market, the mortgage market and the insurance market are interconnected, therefore, the optimization models of the firms in these markets are interdependent through the revenue sharing parameters. Second, in these markets the individual firms’ sales optimums are not identical, therefore, the interests of the firms are contradictory. Third, in the realtor-bank-insurer system, the equilibrium satisfies the condition of zero revenue sharing payments between the agents; additionally, the equilibrium prices in these markets are mutually independent. Fourth, in the disequilibrium, the prices in these markets are interrelated, i.e. the price in one market increases with the price in another market, if the payment is directed from the former to the latter, and vice versa.

The results of the study are applicable in practice, if the markets demonstrate the decreasing demand curves and if the needs of buyers in related markets are interconnected.

The interaction between the realtor and the mortgage bank enables the realtor to raise its sales and the bank to increase in the number of loans, i.e. it leads to growth of their profits. The interaction between the insurer and the mortgage bank enables the insurer to increase in the number of policies and the bank to reduce the risk of lending, i.e. it leads to an increase in their profits. The identification of the individual firms’ sales optimums enables agents to determine the terms of the contracts of these interactions, which are compromises from the positions of each transaction participants. In addition, the firms’ optimums indicate the predictions of the equilibrium market prices.

In comparison with the studies in the contract theory framework, first, the mathematical description of the complicated (three-agent) system of interactions is proposed; second, the optimal choice non-linear models are developed, which take into account the non-linear demand functions in the monopolistic competition markets; third, the equilibrium of the agents with contradictory interests is investigated. In the later item, the authors establish that the revenue sharing contracts in the complimentary demands functions systems do not require the payments between the participants. Fourth, the authors prove that, in the equilibrium of these markets, the housing prices, the mortgage interest rates and the insurance rates are mutually independent and equal to the prices in the isolated markets.

This paper aims to study a strategic decision of banks in Thailand to signal their types to the market and derive the optimal credit derivatives contract to guarantee their loans and credibly signal their quality under different economic determinants, namely, the maximum credit risk investment constraint, opportunity cost and opaqueness of the credit derivative market.

Contract theory is deployed to derive the expected payoff of different bank types under different economic and financial constraints. Hence, different bank types offer derivatives contracts to signal their loan quality and resell their loans in the secondary loan markets of Thailand.

The optimal derivatives contract is constructed on a basis of asymmetric information when banks have more private information concerning quality of their loans. A digital credit default swap is an optimal derivatives contract to send credible signal when banks are restricted to the maximum investment constraint. Moreover, profit of banks is reduced, as the optimal derivatives contract is more costly when banks are subjected to positive opportunity cost and opacity of the credit derivatives market. These results depict impact of changes of the maximum credit risk investment constraint on Thai credit derivatives market.

The optimal credit derivatives design that signifies bank types and facilitates loan purchase agreement has not been studied in Thai secondary loan markets before. In addition, this study provides insights of banks' strategic decisions to signal their types and transfer risk to risk buyers in Thai markets.

Corporate social responsibility (CSR) has now been paid notable attention by a large number of firms. The aim of this paper is to investigate a better way to implement CSR in a socially responsible supply chain with different channel leaderships.

Started from measuring CSR by purely taking consumer surplus into account, a stylized centralized channel and two different decentralized channels are first developed and examined for equilibria in the socially responsible chain. Furthermore, this paper extends to a socially irresponsible supply chain and a broader practice of CSR by simultaneously incorporating environmental externality and consumer surplus into CSR.

With the analytical studies, several interesting and important results and managerial insights are clearly revealed. For example, but not limited to, it is found that: (1) Compared with the leader, the follower can effectively implement CSR for a better performance in both pure and socially responsible profits in the decentralized channel; (2) undertaking socially responsible concerns does not always mean reducing the economic profit and conversely being socially irresponsible does not always induce an increase in economic profit for the socially responsible member(s); (3) CSR concern level plays a key role in both the pure and socially responsible profit. An increase in CSR concern level clearly increases the socially responsible profit and poses an ambiguous impact on pure profit depending on different channel leaderships: it decreases the centralized channel in pure profit but increases the pure profit with the decentralized channel under certain conditions; and (4) interestingly, the authors find that decentralization can outperform centralization regarding on both pure and socially responsible channel profits by properly implementing CSR concern levels.

The results derived in this paper provide novel managerial implications to the socially responsible members in terms of pricing decisions, order quantity and CSR practice. In addition, this paper assists the socially responsible supply chain in determining the optimal channel leadership to undertake CSR. That is, decentralization may achieve a better performance than integration under certain market conditions.

To the best of the authors' knowledge, this paper is the first attempt to explore the interactive of the CSR practice and channel leadership in a socially responsible supply chain.

Providers of cloud computing storage services (CCSS) charge offers in several unit bundles for a lump sum per bundle. This non-linear pricing approach is known as a bucket-pricing plan (BPP). If a customer exploits the purchased bucket, he/she can opt for the next higher bucket or refrain from further CCSS use. CCSS suppliers are faced with an optimization problem concerning the number of buckets as well as their lower and upper storage volume boundaries. The purpose of this paper is to develop a model, which supports CCSS suppliers in deriving a BPP-structure and which maximizes their profit in varying market constellations.

The authors develop a multi-period model of tariff choice decisions of private customers of CCSS. The model is applied in Monte Carlo simulations to determine profit-maximal tariff structures as a function of different market characteristics such as median demand saturation, demand heterogeneity, average price per storage unit and bucket ceiling allocation (identical size of each bucket within the frame set by the lower and upper overall boundary, varying sizes of the buckets offered, so that the interval between two ceilings consecutively increases for subsequent buckets) and type of a customer’s utility function.

The simulation analysis suggests that demand heterogeneity and average price per unit are the most influential factors for CCSS tariff structure optimization. Price plans with more than two buckets tend to generate higher profits than simple schemes with two buckets only if demand heterogeneity is low and the average price per storage unit is high and/or median saturation level of customers is low.

Despite the popularity of BPP among providers of CCSS for consumers, there is a lack of scholarly modeling work on the profit implications of the number of buckets entailed in a scheme and the size/ceilings of the various buckets on offer. The model suggested in this paper is a first step toward narrowing this research gap.

Purpose: The purpose of this paper is to describe a decision support tool based on various types of contracts in a two‐level supply chain. A supply chain (SC) consists of disparate but interdependent members, dependent on each other to manage various resources (inventory, money and information). The conflicting objectives between these members may cause uncertainties in supply and demand, which can be managed by adopting coordination with the help of contracts (such as buyback, revenue sharing and quantity flexibility). Design/methodology/approach: A decision support tool for SC coordination using contracts (DSTSCCC) has been developed to explore the applicability of contracts and to compare different types of contracts in various situations. The DSTSCC is comprised of an analytical module, which is an extension of the classical newsboy problem and a simulation module. Findings: DSTSCCC helps in determining decision variables for different scenarios of contracts in the best interest of all SC members as well as whole SC. Practical implications: DSTSCCC is a simple‐to‐use and easy‐to‐implement decision making tool which helps in taking decisions prior to the actual start of SC activities. The prior decisions may help to handle future exceptions. SC members may jointly select the most profitable contract to share risks and rewards. Originality/value: DSTSCCC comprised of analytical module and simulation module presents an Integrative framework which cannot be dealt in isolation. The output of analytical module becomes input for simulation to quantify performance measures. The improvement in performance measures after satisfying the objectives of all SC members helps in realizing coordination in SC.

This essay explores certain aspects of single product industry basic systems of the type Sraffa develops in Part I of Production of Commodities by Means of Commodities. It focusses on triangular trade as the simplest expression of the more general n-commodity case. Two elements of the framework are explored: (i) the relation of exchange between all commodities, conceived as the configuration of exchange which is applicable to the subsistence and surplus models, and (ii) the value/price expressions of labour time, applicable to the surplus model only, which posits the productivity of, remuneration to and extraction from living labour added to the system. This analysis complements and extends the Marxian reading of Sraffa’s notions of surplus and deficit industries first explored in Carter (2014b). The methodology of ‘given quantities’ in expositing the relations developed is adopted in this essay as it corresponds to the same method employed by Sraffa. This allows readers to easily move from the present essay to Sraffa’s book and importantly his archival notes which are now for all interested parties available as colour digital images on the Wren Library website.

This paper aims to study the implication of the stochastic gross-profit-per-day objective on the ship profitability and the ship capacity and speed.

The paper has used the mathematical model and the solution methodology given by El Noshokaty, 2013, 2014, 2017a, 2017b, and SOS, 2019.

The paper finds that if the ship owner follows the rate concept and the cargo demand forecast, he can improve the profitability of his company and be able to select the proper capacities and speeds for the ships used.

The findings are not only useful for the shipping or other cargo transport companies but also for businesses like gas reservoir development, car assembly lines in the industry, cooperative farming and crop harvesting in agriculture, port cargo handling in trade and road paving in construction.

The contribution of this paper lies in notifying the ship owners of the possible profitability improvement and the consequences of building ships of larger capacities and slower speeds.

The purpose of this paper is to deal with profit maximization problem of two-layer supply chain (SC) under fuzzy stochastic demand having finite mean and unknown variance. Buyback policy is employed from the retailer to supplier. The profit of the supplier solely depends on the order size of the retailers. However, the loss of shortage items is related to loss of profit and goodwill dependent. The authors develop the profit function separately for both the retailer and supplier, first, for a decentralized system and, second, joining them, the authors get a centralized system (CS) of decision making, in which one is giving more profit to both of them. The problem is solved analytically first, then the authors fuzzify the model and solve by fuzzy Hausdorff distance method.

The analytical models are formed for both centralized and decentralized systems under non-cooperative and cooperative environment with suitable constraints. A significant assumption on density function, namely Cauchy-type density function, is introduced for demand rate because of its wider range of the retailers’ satisfactions. Fuzzy Hausdorff metric is incorporated within the fuzzy components of the fuzzy sets itself. Using this method, the authors find out closure values of both centralized and decentralized policies, which is an essential part of any cooperative and non-cooperative two-layer SC models. Moreover, the authors take care of the profit values with corresponding ambiguities for both the systems explicitly.

It is found that the centralize policy of SC could only be able to maximize the profit of both the retailers and suppliers. All analytical results are illustrated numerically along with sensitivity analysis and side by side comparative studies between Hausdorff and Euclidean distance measure are done exclusively.

The main focus of attention of the proposed model is given to usefulness of Hausdorff distance. Unlike other distances, Hausdorff distance can take special care on the similarity measures of different fuzzy sets. Researchers have been engaged to use Hausdorff distance on the different fuzzy sets but, in this study, the authors have used it within the components of a same fuzzy set to gain more closure values than other methods.

The use of this Hausdorff distance approach is totally new as per literature survey suggested yet. However, the Cauchy-type density function has not been introduced anywhere in SC management problems by modern researchers still now. In crisp model, the sensitivity on goodwill measures really provides a special attention also.

Library managers are facing a problem. Not only won't it go away, but it's been increasing, seemingly at an exponential rate. What is this problem? The increase in the prices libraries are paying for journal subscriptions. In larger academic libraries, this rapid increase has kept pressure on the materials budget, thereby affecting the budget for books along with serials. But what determines journal prices? What forces drive them? And what actions might libraries or universities take to change the pattern of journal prices?