Walter O. Rom

Outsourcing decision support: a survey of benefits, risks, and decision factors

Purpose – The purpose of this study is twofold. The first is to provide a structured review of the vast amount of outsourcing literature that has accumulated in the past two decades using a decision support framework. The second purpose is to statistically analyze the contents of the studies to identify commonalities as well as gaps, in order to suggest directions for future research.Design/methodology/approach – The contents of more than 200 publications are analyzed using a variety of approaches. A decision support framework is used to first classify whether the studies address outsourcing benefits, risks, motivations or factors. Next, each classification is further described by the type of benefits, risks, etc. Additional relevant contents such as type of organization, and the location of the outsourcing practice are also considered. Multivariate analyses consisting of cross tabulations, chi‐square testing and cluster analysis are used for categorizing the studies with the aim of identifying relationsh...

An investigation of buffer sizing techniques in critical chain scheduling

In this paper, we introduce two methods for determining feeding buffer sizes in critical chain project scheduling. Both methods integrate project characteristics into the formulation. Specifically, one of them incorporates resource tightness while the other uses network complexity. Both methods are tested and compared to two commonly suggested methods in the literature, the cut and paste method and the root square error method, as well as using no buffer as a benchmark. The comparison is done by means of a simulation study using the Patterson data set. The test results indicate that both of the suggested methods generate smaller buffer sizes while providing sufficient protection against delays in project completion time.

A Study of Price and Quality in Service Operations

Studies the relationship between perceived price and perceived quality for the three types of services, namely, pure, mixed, and quasi‐manufacturing classified by Chase and Tansik, and the relative importance of five dimensions of service quality identified by Parasuraman et al. Finds that the relationship between perceived price and the five dimensions of service quality appears to be very weak for pure and quasi‐manufacturing services, but is statistically significant for mixed service. Reliability dimension is statistically significant for all three types of service. Tangible dimension is a critical variable for mixed service while the empathy dimension is important for quasi‐manufacturing service. On the other hand, the relationship between perceived price and overall service‐quality is significant for quasi‐manufacturing service, but is weak for pure and mixed services.

An empirical investigation of project evaluation criteria

In this article, we report on an empirical study conducted in the USA to determine the performance measures project managers commonly use to evaluate the success of their projects. Specifically, we identify project managers’ orientations toward using internal and/or customer driven measures of performance. We also investigate the priority given to these measures at different stages of a project by identifying the primary objective at those stages. In general we find that project managers’ primary success measure is quality and their most important objective is meeting customer needs. The priority given to this objective does not change during various stages of a project regardless of the project type and industry classification. The choice of performance measures, however, is influenced by project type and industry classification.

Solving the Assignment Problem by Relaxation

This paper presents a new algorithm for solving the assignment problem. The algorithm is based on a scheme of relaxing the given problem into a series of simple network flow transportation problems for each of which an optimal solution can be easily obtained. The algorithm is thus seen to be able to take advantage of the nice properties in both the primal and the dual approaches for the assignment problem. The computational bound for the algorithm is shown to be 0n3 and the average computation time is better than most of the specialized assignment algorithms.

Order acceptance using genetic algorithms

This paper uses a genetic algorithm to solve the order-acceptance problem with tardiness penalties. We compare the performance of a myopic heuristic and a genetic algorithm, both of which do job acceptance and sequencing, using an upper bound based on an assignment relaxation. We conduct a pilot study, in which we determine the best settings for diversity operators (clone removal, mutation, immigration, population size) in connection with different types of local search. Using a probabilistic local search provides results that are almost as good as exhaustive local search, with much shorter processing times. Our main computational study shows that the genetic algorithm always dominates the myopic heuristic in terms of objective function, at the cost of increased processing time. We expect that our results will provide insights for the future application of genetic algorithms to scheduling problems. Scope and purpose: The importance of the order-acceptance decision has gained increasing attention over the past decade. This decision is complicated by the trade-off between the benefits of the revenue associated with an order, on one hand, and the costs of capacity, as well as potential tardiness penalties, on the other. In this paper, we use a genetic algorithm to solve the problem of which orders to choose to maximize profit, when there is limited capacity and an order delivered after its due date incurs a tardiness penalty. The genetic algorithm improves upon the performance of previous methods for large problems.

Ensuring quality in resource constrained project scheduling

This study constitutes an initial effort for modeling and solving resource constrained project scheduling problems with the objective of maximizing quality. Two mixed integer formulations of the problem are introduced. The first formulation assumes integral activity durations and completion times. These assumptions are relaxed in the second formulation. In both formulations the quality of a project is measured by the amount of rework required and the corresponding additional cost incurred. These quality measures are expressed in a common unit of measure and incorporated into the objective function. The second mixed integer formulation is found to be more efficient and thus computational results are reported based on that model. A set of resource constrained scheduling problems are solved using the quality objective and traditional objective functions from the literature. In general it is found that the schedules obtained when maximizing quality outperform the schedules obtained with minimizing makespan or maximizing the net present value of project cash flows objectives in terms of makespan, cost and computational times.

Solving the resource constrained project scheduling problem with optimization subroutine library

In this paper we present three new models for the resource constrained project scheduling problem, using two objective functions: minimizing the makespan and maximizing the net present value of the cash flows of the activities. In these models, compared to the models in the literature, we relax one of the most constraining assumptions about the integrality of the activity durations and the project time line. Furthermore resources are assumed to be partially-renewable. These models have multiple uses in Operations Management in that they can be used to solve resource constrained MRP problems. The models are found to be amenable to solution using the Optimization Subroutine Library (OSL). Extensive computational experiments with OSL on a total of 1400 problems with different parameter settings are reported. Detailed analysis is done to determine the factors that affect the computational efficiency of the code and the models. In general, results demonstrate that OSL is a powerful tool for solving the models with either objective function. Optimal solutions are obtained with reasonable computational effort. A discussion of the application of several special features of OSL is also given.

MRP in a job shop environment using a resource constrained project scheduling model

One of the most difficult tasks in a job shop manufacturing environment is to balance schedule and capacity in an ongoing basis. MRP systems are commonly used for scheduling, although their inability to deal with capacity constraints adequately is a severe drawback. In this study, we show that material requirements planning can be done more effectively in a job shop environment using a resource constrained project scheduling model. The proposed model augments MRP models by incorporating capacity constraints and using variable lead time lengths. The efficacy of this approach is tested on MRP systems by comparing the inventory carrying costs and resource allocation of the solutions obtained by the proposed model to those obtained by using a traditional MRP model. In general, it is concluded that the proposed model provides improved schedules with considerable reductions in inventory carrying costs.

Evaluation of process tools in systems analysis

Abstract Process tools are used during Systems Analysis to describe the process logic of bubbles in Data Flow Diagrams. We conducted two experiments to determine the relative merits of three process tools: Structured English from textual tool category; Decision Tables from tabular tool category; and Nassi-Schneiderman Charts from graphical tool category. We measured three performance types: tool-based comprehension to find understandability of the information in the tool itself; context-based comprehension to find understandability of information in the tool in combination with the information in the rest of structured specification; and the time of comprehension. Unlike most previous research that show graphical tools are the best, our results are different. We show that textual tools (Structured English) are better than both graphical tools (N-S Chart) and tabular tools (Decision Tables), when the problem size is smaller and the users are technically (computer) oriented. The tabular tools (Decision Tables) are better than graphical tools and textual tools, when the problem is moderately large and the users are non-technically (management) oriented.