Vicki L. Smith-Daniels

Moving Forward and Making a Difference: Research Priorities for the Science of Service

Given the significant, sustained growth in services experienced worldwide, Arizona State University’s Center for Services Leadership embarked on an 18-month effort to identify and articulate a set of global, interdisciplinary research priorities focused on the science of service. Diverse participation from academics in a variety of disciplines working in institutions around the world—in collaboration with business executives who lead organizations ranging from small startups to Global 1000 companies—formed the basis for development of the priorities. The process led to the identification of the following 10 overarching research priorities: • Fostering service infusion and growth • Improving well-being through transformative service • Creating and maintaining a service culture • Stimulating service innovation • Enhancing service design • Optimizing service networks and value chains • Effectively branding and selling services • Enhancing the service experience through cocreation • Measuring and optimizing the value of service • Leveraging technology to advance service For each priority, several important and more specific topic areas for service research emerged from the process. The intent is that the priorities will spur service research by shedding light on the areas of greatest value and potential return to academia, business, and government. Through academic, business, and government collaboration, we can enhance our understanding of service and create new knowledge to help tackle the most important opportunities and challenges we face today.

Maximizing the net present value of a project subject to materials and capital constraints

Abstract Large projects in a variety of industries must be scheduled subject to constraints on capital availability with the objective of maximizing their net present value. The effects of capital and materials costs and constraints have been discussed separately in the project management literature, but they have yet to be treated in an integrated fashion. A framework summarizing the previous research on resource constrained project scheduling is presented in this article and the limited role of monetary objectives in the previous research is illustrated. A new approach to the project scheduling problem is presented where the net present value of a project is maximized subject to capital and material constraints. The major benefit of this approach is that it allows managers to optimize the monetary objectives for a project. A series of examples illustrates the necessity of considering materials costs and constraints in project management. The inclusion of materials management factors in developing a project schedule is shown to lead to lower total project costs. It is demonstrated that the failure to consider materials in the initial planning of a project may lead to either unprojected delays in a project, higher costs, or both. Continued research on this problem is needed in a number of areas. Due to the computational complexity and importance of this problem in practice, it is necessary to develop heuristic approaches to derive project schedules. Future research should compare the results for the existing approaches that minimize project duration to those with monetary objective functions to determine the magnitude of the monetary difference between the former and the latter. Finally, the approach considered in this article should be extended to the multiproject environments where it is necessary to make capital allocation decisions among competing projects.

Heuristic scheduling of capital constrained projects

Abstract The movement to product and process development projects that involve joint ventures among strategic partners, as well as the increasing prevalence of projects within organizations has led to increased implementation of project scheduling methods. It is frequently the case that a capital constraint is placed on a project, thus limiting the number and value of activities that can be scheduled to occur simultaneously. However, the quantity of capital available to schedule activities can increase as additional cash is received as progress payments for completed activities. Since the project managerso objective is to maximize project Net Present Value (NPV), it is important for the manager to develop a schedule that balances the early receipt of progress payments (which improve NPV and increase the capital balance available), with the delay of particularly large expenditures. Due to the intractability of optimal methods, the use of heuristic methods is required to solve problems of practical size. This paper presents the first test of heuristic methods for solving this problem. We use information from a relaxed optimization-guided model that employs information from the unconstrained NPV-optimal problem in heuristic procedure for solving the capital constrained problem. An experimental design is employed to test the heuristics that includes multiple factor levels for a number of project characteristics, including capital utilization, frequency of progress payments, and project network structure. The results indicate very good relative performance for the optimization-guided procedures as compared to two benchmark heuristics.

Heuristic scheduling of resource-constrained projects with cash flows

Resource-constrained project scheduling with cash flows occurs in many settings, ranging from research and development to commercial and residential construction. Although efforts have been made to develop efficient optimal procedures to maximize the net present value of cash flows for resource-constrained projects, the inherent intractability of the problem has led to the development of a variety of heuristic methods to aid in the development of near-optimal schedules for large projects. This research focuses on the use of insights gained from the solution of a relaxed optimization model in developing heuristic procedures to schedule projects with multiple constrained resources. It is shown that a heuristic procedure with embedded priority rules that uses information from the revised solution of a relaxed optimization model increases project net present value. The heuristic procedure and nine different embedded priority rules are tested in a variety of project environments that account for different network structures, levels of resource constrainedness, and cash-flow parameters. Extensive testing with problems ranging in size from 21 to 1000 activities shows that the new heuristic procedures dominate heuristics using information from the critical path method (CPM), and in most cases outperform heuristics from previous research. The best performing heuristic rules classify activities into priority and secondary queues according to whether they lead to immediate progress payments, thus front loading the project schedule.

Optimal project scheduling with materials ordering

Abstract A mixed integer 0–1 programming formulation of a Project Scheduling-Materials Ordering Problem (PSMOP) is presented that provides an optimal schedule of project activities and materials orders. It is proven that an optimal solution may be found by decomposing the problem into the derivation of the project schedule and the subsequent derivation of materials lot sizes.

Location and service mix decisions for a managed health care network

Abstract For managers of managed health care organizations, the problem of designing a competitive multiple facility network cannot be solved by existing mathematical models. This paper thus presents a nonlinear integer model for determining a facilities design strategy that embodies the economic tradeoffs encompassed in a competitive strategy: minimizing cost and maximizing market share. The integrated location and service mix model determines the number, location and service offerings of facilities that maximize profitability in a two-level hierarchical referral delivery network where an organizations market share is represented by a multiplicative competitive interaction model. To demonstrate the usefulness of the proposed integrated model, a series of problems is solved by an interchange heuristic and compared to the solutions derived by a simpler approach that ignores market competition.

A Heuristic Procedure for Scheduling Packaging Lines in Process Industries

Abstract Process industries produce non-differentiable products which are packaged into a variety of sizes during the final production stage. In this environment, product family changeovers are performed during an off-shift period, while item changeovers, which are shorter in duration, may be performed during a shift. A heuristic for scheduling packaging lines is presented where a family setup cost is charged for an off-shift changeover and item lot sizes are determined subject to limited capacity and setup times.