Alok Baveja

Dynamics of Core Competencies in Leading Multinational Companies

This article examines the core competencies of twelve leading multinational companies. It explores their competencies, how they were developed, and how they are shifting over time. Successful companies rely on three types of competencies: superior technological know-how, reliable processes, and close external relationships. Different approaches are needed to develop each types of competency. While these firms have historically relied on technological know-how and reliable processes, they are planning more close external relationships for the future. External relationships help these firms strengthen and extend their traditional competencies while responding to the demands of globalization, mass customization, enhanced quality, and rapid technological change.

Approximation Algorithms for Disjoint Paths and Related Routing and Packing Problems

Given a network and a set of connection requests on it, we consider the maximum edge-disjoint paths and related generalizations and routing problems that arise in assigning paths for these requests. We present improved approximation algorithms and/or integrality gaps for all problems considered; the central theme of this work is the underlying multicommodity flow relaxation. Applications of these techniques to approximating families of packing integer programs are also presented.

A data-driven software tool for enabling cooperative information sharing among police departments

Abstract Police departments utilize information technology for combating crime, however, mostly for tactical purposes. This paper presents an Artificial-Intelligence software, Crime Similarity System (CSS) that helps police departments develop a strategic viewpoint toward decision-making. CSS utilizes socioeconomic, crime and enforcement profiles of cities to generate a list of communities that are best candidates to cooperate and share experiences. By providing a list of relevant similar communities from whom past experience and learnings can be shared, this tool offers the potential for proactive management. CSS provides a user-friendly front-end enabling easy usage. Camden, NJ and Philadelphia, PA police departments were partners in this development effort. Feedback from these two police departments has validated the benefit of this software in uncovering opportunities for police departments to cooperate. An evaluation using human subjects showed that the CSS software provided significantly better support than a conventional database. The modeling framework developed in this work is versatile, potentially useful for applications beyond law enforcement.

Solving machine-loading problem of a flexible manufacturing system with constraint-based genetic algorithm

Abstract Machine-loading problem of a flexible manufacturing system is known for its complexity. This problem encompasses various types of flexibility aspects pertaining to part selection and operation assignments along with constraints ranging from simple algebraic to potentially very complex conditional constraints. From the literature, it has been seen that simple genetic-algorithm-based heuristics for this problem lead to constraint violations and large number of generations. This paper extends the simple genetic algorithm and proposes a new methodology, constraint-based genetic algorithm (CBGA) to handle a complex variety of variables and constraints in a typical FMS-loading problem. To achieve this aim, three new genetic operators—constraint based: initialization, crossover, and mutation are introduced. The methodology developed here helps avoid getting trapped at local minima. The application of the algorithm is tested on standard data sets and its superiority is demonstrated. The solution approach is illustrated by a simple example and the robustness of the algorithm is tested on five well-known functions.

Medical Errors and Quality of Care: From Control to Commitment

Ongoing efforts to reduce medical errors and enhance quality of patient care focus primarily on technological innovations. However, important management issues that underlie about two-thirds of adverse events have commanded insufficient attention. This article examines two alternative management philosophies—control-based and commitment-based—premised on opposite sets of assumptions about human motivation, and it develops a model linking the overall management philosophy with medical errors and quality of care. The current control-based culture and management systems in health care organizations are inherently inadequate in delivering high quality of patient care and safety. Consequently, there is a need to transform them for bringing further improvements in clinical outcomes. Implementing commitment-based management will foster collaboration, communication, coordination, and teamwork, the essential mechanisms for reducing medical errors and rendering high-quality health care.

Divide and Conquer: Rohm and Haas' Response to a Changing Specialty Chemicals Market

Rohm and Haas is caught between giant raw-material suppliers and powerful retailers at opposite ends of the supply chain. In the early 1990s, several new competitors entered the emulsions market, threatening the companys largest business unit, Polymers and Resins (P and R). P and R also faced increasing price pressure from customers and calls to improve the rate of return to corporate shareholders. In 1995, P and R formed a redesign team to examine its precepts. Over a three-year period, we aligned P and R operations around well-defined business policies, segregating products into make-to-stock and make-to-order supply channels, prioritizing customers, and serving nonstrategic customers through distributors. These changes saved millions of dollars, increased productive capacity, and transformed the business into a leaner, more disciplined operating unit.

Modeling the response of illicit drug markets to local enforcement

Abstract Local-level enforcement has been cited as an effective drug enforcement strategy by some policy makers and experts. A more intensive tactic, with focus on a specific target area and referred to as “crackdowns”, has been implemented in some cities. In this paper, we analyze a mathematical model due to Caulkins, to study the effect of focussed enforcement on drug markets. Specifically, we consider both fixed and dynamic enforcement policies. Our analysis suggests that drug dealing can be effectively controlled only if enforcement resources exceed a certain threshold level, and that the success of a crackdown operation may be lost fairly quickly if care is not taken to prevent the market from returning. This should provide enforcement officials with analytically derived “rules of thumb” to help make improved policy decisions.

A collaborative framework to minimise knowledge loss in new product development

In todays consumer era, of rapidly shortened product life cycles, new product development has become essential for both growth and survival of organisations. The agility of new product development is governed by the effectiveness and efficiency of an organisations intelligence and knowledge-management skills. In this rapidly changing dynamic and multi-layered environment, recognising, managing and preventing Knowledge Loss can be a key determinant of success of an organisation. In this paper, we argue for a collaborative network structure within the organisation to prevent knowledge loss in new product development. Based on our first-hand observations via an in-depth case study of six Indian auto-component manufacturing companies, we identify the sources of K-loss. We recommend ways to create collaboration pools that increase flow of information and communication and help mitigate knowledge loss throughout the value chain. We summarise our finding as usable rules-of-thumb for helping senior and middle-level managers develop and leverage collaborative networks for effectively managing knowledge loss for their organisations.

Regional Repositioning of Empty Containers: Case for Inland Depots

Regional repositioning of empty containers involves empty container movement between regional importers, marine terminals, depots, and export customers. This chain movement generates unproductive empty vehicle miles in the region. The problem of empty vehicle miles becomes more prominent because empty container depots are located close to the port and customers are inland. Considering the double-digit increase in containerized trade volumes and the persistent trade imbalance that strain existing depot capacities in major import areas, this paper focuses on the optimal location of new container depots and the repositioning of empty containers in a region. It proposes a system of inland depots for empty containers (IDEC) in which new depots would be built closer to customer clusters. An IDEC system can minimize the total system costs (cost of opening new depots plus repositioning cost of empties) and provide additional required capacity. The paper presents a mathematical model of such a system and discusses its feasibility and effectiveness. The proposed system is evaluated for a region based on the New York–New Jersey port region. Results show that by building inland depots, empty vehicle miles traveled and total system cost of repositioning empties are reduced significantly. At the same time, capacity is added to the system, preventing a shortfall that would result from the increase in trade and the trade imbalance. The authors believe that an IDEC system has great potential in optimizing regional empty moves.

The stochastic queue center problem

This paper considers the Stochastic Queue Center problem, which seeks to locate a single facility with a center-type objective in an M/G/1 queue operating environment. The objective function that we consider is to minimize a positive weighted linear function of the square of the average response time and the variance of the response time to a call. The Stochastic Queue Center problem is discussed on both a discrete and a network location topology. When potential facility locations are restricted to a finite set of discrete points, an efficient algorithm is developed to solve for the optimal facility location parametrically in the arrival rate. By exploiting convexity properties of the objective function, we develop an efficient finite-step algorithm to find the Stochastic Queue Center on a network. The major conclusion of this work is that incorporating the variance term in the objective function has a major impact on the choice of the optimal location. We illustrate the results with an example drawn from a potential application of the model for locating an emergency transport center serving different municipalities in Camden County, NJ.