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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.

The purpose of this paper is to describe the issues, tradeoffs, and models relating to two important sets of problems that arise in supply chain management – complexities in extended supply chains and network coordination in globally dispersed supply chains. This paper highlights the role of logistics in enhancing the competitiveness of firms that operate a global supply chain.

The methodology used in this paper encompasses conceptual research and detailed literature review of key issues.

This review indicates that the key challenges faced by supply chain managers due to extended supply chains are non‐stationary demand, variability propagation, and inventory imbalances. For network coordination managers must determine the role of facilities in a global network, identify the optimal location and capacity of facilities as well as role of consolidation hubs. For the above challenges, the tradeoffs in terms of four key drivers of supply chain performance – transportation, inventory, information, and facilities and relate these to key measures of supply chain performance are described. Important directions for future research are also identified.

Test cases are needed to validate and refine the framework presented. Developing case studies that gather appropriate data to test out the models described would be important.

Companies with a global supply chain as well as third party logistics companies will find the framework presented in this paper very useful.

A new integrated framework that incorporates key decision issues like complexities of extended supply chains and network coordination into the firm's decision making has been presented. This has not been reported in previous research.

There are a number of new techniques which have recently been developed for improving the design and economic justification of distribution facilities and management systems. These new techniques are important because they provide quantitative methods for handling the real‐life tradeoffs which are usually involved between storage, handling, transporting, information processing, and customer service. In essence, the objective of distribution management is to identify and implement these optimum tradeoffs so as to achieve maximum profit to the firm.

This research aims to explore the fine-grained relationships between nurse staffing and hospital operational performance with respect to care quality and operating costs. The authors also investigate the moderation effect of competition in local hospital markets on these relationships.

A six-year panel data is assembled from five separate sources to obtain information of 2,524 USA hospitals. Fixed-effect (FE) models are used to test the proposed hypotheses.

First, nurse staffing is initially associated with improved care quality until nurse staffing reaches a turning point, beyond which nurse staffing is associated with worse care quality. Second, a similar pattern applies to the relationship between nurse staffing and operating costs, although the turning point is at a much lower nurse staffing level. Third, market competition moderates the relationship between nurse staffing and care quality so that the turning point of nurse staffing will be higher when the degree of competition is higher. This shift of turning point is also observed in the relationship between nurse staffing and operating costs.

The study identifies three ranges of nurse staffing in which hospitals will likely experience simultaneous improvements, a tradeoff or simultaneous decline of care quality and operating costs when investing in more nursing capacity. Hospitals should adjust nurse staffing levels to the right directions to achieve better care or reduce operating costs.

Nurses constitute the largest provider group in hospitals and profoundly impact care quality and operating costs among all health care professionals. Optimizing the level of nurse staffing, therefore, can significantly impact the care quality and operating costs of hospitals.

The study aims to introduce two new models of project scheduling by incorporating potential quality loss cost (PQLC) in time–cost tradeoff problems by overcoming the drawbacks of the existing Kim, Khang and Hwang (KKH) model. The proposed methods are named the Revised KKH-I (RKKH-I) and Revised KKH-II (RKKH-II) models for project scheduling.

The performance of the existing KKH model has been tested using a numerical example followed by the identification of the main shortcomings of the KKH method. Later, a concrete effort has been made to address its shortcomings while improving its performance significantly. The comparative analysis of the Revised KKH models with the original model has also been presented along with sensitivity analyses.

The study recognizes that the construct on which the original KKH method was built is important; however, certain drawbacks make it unable to consider PQLC in projects, thus making its practical use questionable. The comparative analysis of the proposed methodology with the original method demonstrated that the new models (RKHH-I and II) are more comprehensive and intelligent than the existing KKH model.

The comparative analysis of the original KKH model and its improved version reveals that the revised model is far more suitable for project scheduling. The study is important for project managers who recognize project scheduling being one of the key parameters associated with project management process, crucial to control every day during the management of projects.

The optimization and tradeoff of cost-time-quality-risk in one dimension and this four-dimensional problem in ambiguous mode and risk can be neither predicted nor estimated. This study aims to solve this problem and rank fuzzy numbers using an innovative algorithm “STHD” and a special technique “radius of gyration” (ROG) for fuzzy answers, respectively.

First, it is the optimization of a fully fuzzy four-dimensional problem which has never been dealt with in regard to risk in ambiguous mode and complexities. Therefore, the risk is a parameter which has been examined neither in probability and estimableness mode nor in the ambiguous mode so far. Second, it is a fully fuzzy tradeoff which, based on the principle of incompatibility “Zadeh, 1973”, proposes that when the complexity of a system surpasses the limited point, it becomes impossible to define the performance of that system accurately, precisely and meaningfully. The authors believe that this principle is the source of fuzzy logic. Third, for calculating and ranking fuzzy numbers of answers, a special technique for fuzzy numbers has been used. Fourth, For the sake of ease, precision and efficiency, an innovative algorithm called the technique of hunting dolphins “STHD” has been used. Finally, the problem is very close to reality. By applying risk in ambiguous mode, the problem has been realistically looked at.

The results showed that the algorithm was highly robust, with its performance depending very little on the regulation of the parameters. Ranking fuzzy numbers using the ROG indicated the flexibility of fuzzy logic, and it was also determined that the most appropriate regulations were to ensure low time, risk and cost but maximum quality in calculations, which were produced non-uniformly based on the levels of Pareto answers.

The ROG and Chanas Fuzzy Critical Path Method as developed by other researchers have been used. Despite the increase in limitations, parameters can develop. The originality of this study with regard to evaluating the results of tradeoff combinatorial optimization is upon decision-making which has a special and highly strategic role in the fate of the project, with the research been conducted with a special approach and different tools in a fully fuzzy environment.

Regulatory pressure, consumer awareness, and the quest for competitive advantage place sustainable products in today’s decision-making spotlight. The purpose of this paper is to explore supply chain dynamics as they relate to sustainable product programs and to empirically develop a framework to align efforts across the supply chain to bring sustainable products to market.

Grounded in systems design, stakeholder theory, and the theory of planned behavior, the authors conduct an inductive empirical study of 28 European and US companies.

The authors make three contributions. First, the authors identify six dimensions of product sustainability, which map to the Greenhouse Gas Protocol’s sustainability scope model. Second, the authors model relational dynamics using systems diagrams to provide a framework that: first, communicates a common understanding of product sustainability; and second, facilitates tradeoff analysis. Third, the authors elaborate behaviors needed to reduce ambiguity and compliance costs.

Managers can use the framework to assess product sustainability and evaluate tradeoffs across product dimensions and supply chain participants. Using this insight, managers can design sustainable product programs that engage supply chain participants.

By identifying dimensions, defining costs, and uncovering tradeoffs, managers can more effectively implement sustainable product programs.

The framework provides a much needed source of clarity to mitigate role ambiguity, reduce compliance costs, and promote collaborative behavior in bringing sustainable products to market.

This paper seeks to frame and model the environmental issues and impacts associated with the management of pallets throughout the entire life cycle, from materials to manufacturing, use, transportation to end‐of‐life disposal.

A linear minimum cost multi‐commodity network flow problem is developed to make pallet‐related decisions based on both environmental and economic considerations.

This paper presents a review of the environmental impacts associated with pallets by life cycle stage. The types of materials used to fabricate pallets, the methods by which they are treated for specific applications, and various pallet management models are described with respect to embodied energies, toxicity and emissions. The need for companies to understand the cost, durability, and environmental impact tradeoffs presented by pallet choices is highlighted. The paper introduces a model to assist in choosing both how pallets are managed and the material they are constructed of that balances these tradeoffs.

There is limited research on the environmental impact of different management approaches of large‐scale pallet operations. The proposed model and approach will provide companies seeking to engage in more sustainable practices in their supply chains and distribution with insights and a decision‐making tool not previously available.

The purpose of this article is to propose a new framework for examining the relationship between the consumer and the product, focusing not on the benefits the consumer seeks to maximize, but on the other side of the ledger—the costs the consumer seeks to minimize. These costs tend to fall into the same categories of costs faced by other participants in the distribution channel. By conceptualizing the consumer as an active channel member, rather than as a passive recipient of products and services, we are able to present a systematic matrix of the total costs that consumers may weigh against benefits in their shopping, purchasing, and use decisions. On the basis of this framework, we suggest ways in which product and / or channel designers can improve their performance through deeper insights into consumers' cost tradeoffs.

The purpose of this paper is to identify requirements and tradeoffs on logistics services for enhanced circularity of materials and resources.

Based on multiple case study design and abductive reasoning, the study investigates 13 different product categories. The data were analyzed based on theoretical, a priori codes from the literature review. Inductive, emerging codes were added to the coding scheme during the analysis.

Requirements of logistics services to support slowing of resource flows are categorized with respect to initiator, location of the service, single or multiple actors, and transportation of parts, products and people. Moreover, the study identifies new logistics tradeoffs: material and people, knowledge and people, and information and knowledge. Transportation of product, people and parts can be reduced by increasing local knowledge and improve information sharing.

This review contributes to the understanding of the relationship between logistics services and enhancement of circularity by highlighting requirements on logistics services in the aftermarket supply chain that support slowing of resource flows. To enhance circularity, logistics services must extend the traditional material information flow with the flow of people and knowledge, respectively.

The categorization provides practitioners and researchers with an overview of requirements and tradeoffs on logistics services to enhance circularity of a particular circular cycle. The implications will provide an opportunity to address environmental impact of transportation and improve the utilization of scarce materials.

Variety of tradeoffs in logistics services can enhance slowing and hence circularity of scarce materials.

First, the authors illustrate how traditional tradeoffs in logistics such as flow of materials, resources and people need to be addressed to enhance circularity through slowing. Second, the authors identify two new tradeoffs in logistics services: knowledge flow and degree of customer involvement.