Sidhartha R. Das

Building competitive advantage on manufacturing resources

Abstract Todays dynamic and global competitive forces require new thinking about the implications of manufacturing for achieving superiority in the marketplace. This article suggests that a resource-based perspective offers an innovative approach to thinking about and developing a manufacturing strategy. According to this approach, a companys manufacturing strategy must capitalize on, and add to, its resources and capabilities. To show how executives can use the resource-based approach, categories of manufacturing resources are defined. The next section of the article discusses the important attributes of manufacturing resources, their relationship with distinctive competence, and their impact on competitive advantage. Finally, the article explains how manufacturing strategy can effectively leverage these resource attributes to obtain an enduring competitive advantage that leads to high performance.

A Savings Index Heuristic Algorithm for Flowshop Scheduling with Sequence Dependent Set-up Times

This paper considers the permutation flowshop scheduling problem with significant sequence dependent set-up times and develops a savings index heuristic algorithm to find an approximately minimum makespan schedule. The proposed algorithm determines the savings in time associated with a particular sequence and selects the sequence with the maximum time savings as the best heuristic solution. Computational experience indicating the effectiveness and efficiency of the proposed savings index heuristic algorithm are reported and discussed.

Examining a firm's decisions with a contingency framework for manufacturing flexibility

Purpose – To examine and analyze the decision process that a firm undergoes for acquiring an advanced manufacturing system to obtain manufacturing flexibility for its operations.Design/methodology/approach – A case study approach is used to examine these decision processes. A conceptual contingency‐based framework from the literature is used to guide the analysis. The framework proposes that four exogenous variables – strategy, environmental factors, organizational attributes, and technology – guide a firms decisions on choice and adoption of manufacturing flexibility, which has an effect on the firms performance.Findings – The analysis shows that these decisions are aligned with the various relationships in the framework. The framework therefore helps understand and explain the above decision processes. Further, the paper expands the concept of “fit” between the variables in the framework.Research limitations/implications – Several research propositions are developed based on the findings of this study...

Modeling global facility location decisions: integrating marketing and manufacturing decisions

Rapid changes in today’s global markets are forcing businesses to re‐examine and improve the ways they compete. Integration of facility location decisions in global marketing and manufacturing strategies provides an important means for firms to compete in global markets. This paper proposes that manufacturing utility can be related to marketing utility through facility location decisions. Consequently, it presents a mathematical model for global facility location that integrates marketing and manufacturing decisions in a global context. It also presents a four‐stage evolutionary model that can guide managers in making global facility location decisions.

The Effect of Information Technology Investments in Healthcare: A Longitudinal Study of its Lag, Duration, and Economic Value

This research develops a framework that disaggregates investments in IT in the healthcare industry into four distinct categories: investments in patient management IT (PMIT), transactional support IT (TSIT), communications IT (CIT), and administrative IT (AIT). In a longitudinal study, financial and operational data from several hospitals spanning 26 years are analyzed to examine the lag as well as duration of the effect of these IT investments on hospital costs and labor productivity. The results reveal that TSIT capital has an immediate effect on medical labor and administrative labor productivities, and a lagged but durable effect on operating costs. CIT capital has an immediate but short-term effect on medical labor and administrative labor productivities. AIT capital has an immediate but short-term effect on medical labor productivity. PMIT capital, on the other hand, increases operating costs, an effect that is immediate but short-term. Finally, post hoc marginal analysis reveals that among the four types of IT investments, CIT has the maximum economic value effect on hospital productivity, followed by TSIT, and then AIT; with PMIT having a minimal economic value effect.

Designing service processes: a design factor based process model

The challenge of increased service quality and productivity in the service industry cannot be met by simply adapting the present product-oriented operations management techniques to a people-oriented endeavour. We must develop a new perspective, one that encompasses the uniqueness of service organisations while capturing the knowledge gained from manufacturing over the last hundred years. This paper explores how service processes can be designed from this new perspective. It identifies six major design factors that are to be used when designing service processes and discusses how they are related. It also describes a process model that uses these design factors for designing service processes.

Antecedents of innovativeness in technology-based services (TBS): : Peering into the black box of entrepreneurial orientation

Innovativeness is the organizations capability for developing and introducing innovations. We argue that new combinations and recombinations of prior and new knowledge (by way of creating, assembling, and transforming knowledge) result in innovativeness in an organization. We further assert that a knowledge-based focus on innovativeness is particularly important for firms that are technology-based. The majority of studies focusing on innovativeness are in the entrepreneurship arena, and a large number of studies consider innovativeness as one of three dimensions of the entrepreneurial orientation (EO) construct, the other two dimensions being proactiveness and risk-taking. However, recent research has suggested peering into the black box of EO by disaggregating the EO construct and examining the interrelationships among its three components. Hence, using the knowledge-based view and drawing from multiple disciplines, our study conceptualizes innovativeness as a criterion variable and investigates the antecedent role of proactiveness and risk-taking propensity on innovativeness in the context of technology-based services (TBS). We hypothesize that both proactiveness and risk-taking propensity exhibit a curvilinear relationship with innovativeness and introduce organizational structure formality as a moderator to further explicate these relationships. Our results show that proactiveness has a curvilinear (inverted U relationship) with innovativeness, and that this relationship is attenuated by organizational structure formality. Additional analysis indicates that in TBS firms, risk-taking propensity has a positive linear relationship with innovativeness, and this relationship is accentuated by organizational structure formality. Finally, we discuss important conceptual and practical implications of our study and provide suggestions for future research.

The successful development of information systems for FMS: some useful lessons

The successful development of information systems for flexible manufacturing systems depends on several factors. Many studies have been investigating these factors during the development of information systems for various applications. Examines findings from the MIS literature and derives some lessons on how they can be used in the development of an information system for FMS.

An efficient heuristic for scheduling batches of parts in a flexible flow system

Flexible manufacturing systems (FMSs) are a class of automated systems that can be used to improve productivity in batch manufacturing. Four stages of decision making have been defined for an FMS—the design, planning, scheduling, and control stages. This research focuses on the planning stage, and specifically in the area of scheduling batches of parts through the system.The literature to date on the FMS planning stage has mostly focused on the machine grouping, tool loading, and parttype selection problems. Our research carries the literature a step further by addressing the problem of scheduling batches of parts. Due to the use of serial-access material-handling systems in many FMSs, the batch-scheduling problem is modeled for a flexible flow system (FFS). This model explicitly accounts for setup times between batches that are dependent on their processing sequence.A heuristic procedure is developed for this batch-scheduling problem—the Maximum Savings (MS) heuristic. The MS heuristic is based upon the savings in time associated with a particular sequence and selecting the one with the maximum savings. It uses a two-phase method, with the savings being calculated in phase I, while a branch-and-bound procedure is employed to seek the best heuristic solution in phase II. Extensive computational results are provided for a wide variety of problems. The results show that the MS heuristic provides good-quality solutions.

The uncapacitated multi‐period facilities location problem with profit maximization

The literature on the facilities location problem is quite extensive with a wide variety of solution methods for addressing these problems where the objective is cost minimization. Develops a branch and bound algorithm for solving the uncapacitated, multi‐period facility location problem where the objective is to maximize profits. The solution method uses a number of simplification and branching decision rules to solve the problem efficiently. Extensive computational results on the algorithm’s performance are provided. The results indicate that the algorithm provides optimal solutions in substantially less time than LINDO.