Dynamic pricing models for ERP systems under network externality

Enterprise Resource Planning (ERP) systems vendors face great challenges to enhance their market position and maximize their profits. Being able to simultaneously predict the diffusion of an ERP and to determine the right price to charge to a customer is a complex task. Earlier work has demonstrated evidence of network effect in the diffusion of ERP software in industries. In light of this evidence, we investigate in this paper the benefit of a dynamic pricing strategy for ERP systems vendors in a business network governed by a quantitative diffusion model. Based on a real scenario in the automotive industry, those quantitative models are integrated into a simulation-based optimization approach to tackle the problem. Our findings are promising and establish the foundation of a powerful decision support tool for ERP systems vendors.     

Flexibility and rigidity in customization and build-to-order production

This paper deals with the efforts of firms to tailor their products to the needs of individual customers. The overall aim is to analyse the features of the evolving activity structures where customized offerings are created with ‘near mass production efficiency’. The paper begins with a literature review outlining modularity and build-to-order production as key features of customizing. The empirical setting of the case study is Volvo Cars' activity structure for build-to-order production. This structure is compared with previous means of making products available. The conclusion of the study is that activity structures for build-to-order production require extensive coordination, exchange of information, and interaction across company boundaries. The analysis shows that these structures rely on flexibility in some dimensions, while in others they build on rigidity. The paper concludes with implications for suppliers regarding how to combine flexibility and rigidity in order to be able to customize at reasonable costs.     

Constraint programming for project-driven manufacturing

Project-driven manufacturing, based on the make-to-order or the build-to-order principle and predominant in small and medium-size enterprises (SMEs), calls for an efficient solution of large combinatorial problems, especially in such areas as task scheduling or resource management. This paper addresses the problem of finding a computationally effective approach to scheduling a new project subject to constraints imposed by a multi-project environment. A constraint programming (CP) modeling framework is discussed in the context of an efficient decomposition of the constraint satisfaction problem (CSP) and the evaluation of strategies for pruning the search tree. The proposed approach is illustrated through examples of its application to the evaluation of a new production order.     

Revenue management for make-to-order manufacturing systems with a real-life application

Abstract

Due to successful applications of revenue management in the airline industry, in recent years, there has been a growing interest to adopt revenue management in make-to-order (MTO) manufacturing systems. Several interrelated decision problems such as order acceptance/rejection, short-term capacity planning, due date assignment, and order scheduling need to be studied simultaneously in order to manage revenues effectively in MTO manufacturing systems. Both the producer’s and customer’s requirements need to be taken into account through some negotiation mechanisms that are sensitive to the service-level reputation of the manufacturing companies. In this article, we propose a new dynamic bid price–based revenue management model that considers all of the aforementioned decision problems simultaneously. A simulation optimization approach is utilized in order to determine the best possible values of control parameters for bid price, due date assignment, and price increment/reduction mechanisms. The performance of the proposed integrated revenue management model is tested on both a hypothetical example and a real problem of a bridal gown company. The computational results show that the proposed model provides significant improvements in total revenue compared to other static and dynamic bid price policies.     

Integrated production planning with sequence-dependent family setup times

This paper proposes an integrated optimization model of aggregate production planning (APP), family disaggregation planning, and family scheduling problems in hierarchical production planning (HPP) systems considering sequence-dependent family setup times. The model obtains the optimal production plan for each product type and product family in each period, together with the globally optimal production sequence of product families in all planning periods. The proposed model is tested with randomly generated experimental data consistent with what is prevalent in the manufacturing industry and its results are compared with those of the traditional HPP models. Our results show that the integrated model realizes greater cost savings.     

An integrated production–distribution model for the dynamic location and allocation problem with safety stock optimization

The design and management of a multi-stage production–distribution system is one of the most critical problems in logistics and in facility management. Companies need to be able to evaluate and design different configurations for their logistic networks as quickly as possible. This means coordinating the entire supply chain effectively in order to minimize costs and simultaneously optimize facilities location, the allocation of customer demand to production/distribution centers, the inbound and outbound transportation activities, the product flows between production and/or warehousing facilities, the reverse logistics activities, etc.Full optimization of supply chain is achieved by integrating strategic, tactical, and operational decision-making in terms of the design, management, and control of activities. The cost-based and mixed-integer programming model presented in this study has been developed to support management in making the following decisions: the number of facilities (e.g. warehousing systems, distribution centers), the choice of their locations and the assignment of customer demand to them, and also incorporate tactical decisions regarding inventory control, production rates, and service-level determination in a stochastic environment. This paper presents an original model for the dynamic location–allocation problem with control of customer service level and safety stock optimization. An experimental analysis identifies the most critical factors affecting the logistics cost, and to finish, an industrial application is illustrated demonstrating the effectiveness of the proposed optimization approach.     

Preparing industrial suppliers for customer integration

In real world markets and business markets in particular, the idea of customized products and services receives increasing attention. A management tool called customer integration has been developed as an approach to master the challenges originating from customization for a supplier. Customer integration competence is the organizational quality that results from this tool after being implemented. Putting this together, we can hypothesize a causal relation between customer integration competence and market success. In order to confirm this hypothesis, the paper presents a conceptualization of customer integration competence. To accomplish this, references are made to competence models from psychology, success factor research and organizational science. The concept was validated through a survey with 78 industry experts from business markets responding. Customer integration competence measured in this way was then contrasted to a second measure capturing market success. Regression analysis supports our hypothesis strongly. Finally, implications for marketing research as well as marketing practice are presented.     

Selecting make-to-stock and postponement policies for different products in a chemical plant: A case study using discrete event simulation

We present a guideline for selecting the inventory management policy for a specialty chemical plant that produces products with limited shelf life, by producing multiple grades of bulk chemical and packaging them into a large variety of bottles. The policy for each product was selected based on a cost-benefit analysis, using the multiple objectives of maximizing the on time order fulfillment, minimizing the production (cleaning and shelf life expiration) and inventory costs. To generate realistic cost estimates, we developed a discrete event simulation model that included demand variability, planning and scheduling policies, and operational details. We evaluated three different policies: make-to-stock (MTS), postponement, and combined MTS/postponement. We also evaluated different storage media and optimized the number of storage units for products selected for postponement. A combined MTS/postponement policy, in which postponement is applied to products with low to medium demand and high expiration provided lowest costs without significantly impacting the customer on time order fulfillment. For all other products, a MTS policy is applied to maximize order fulfillment on time, reduce cleaning costs and to reduce number of storage units.     

Scheduling a multi-stage fabrication shop for efficient subsequent assembly operations

Consideration is given to scheduling the operation of a multi-stage fabrication shop producing the component parts of a major commercial refrigerators producer. The objective of this scheduling problem is the determination of both production sequences and lot quantities at each stage so as to meet production targets and ensure continuous operation of subsequent assembly stations. After describing the problem within its natural context, we present an algorithm for the dynamic scheduling of the fabrication shop. This applies general planning principles adapted to the needs of the environment under consideration and makes use of existing heuristic rules for arriving at sequencing decisions. Although in no sense optimal, the algorithm can provide good feasible solutions to a previously not formally analysed problem. After being incorporated into a systematic computer-aided scheduling procedure, the algorithm has been actually implemented, demonstrating considerable improvements over previous fabrication shop scheduling practice.     

Small Firm Marketing: A Comparison of Eastern and Western Marketing Practices

This article reports on the analysis of 110 published, undisguised stories about Chinese owner-managers in Hong Kong and determines whether Chinese small firms exhibit the same marketing activities and behavior as their Western counterparts. Content analysis suggests that Chinese small firms are production oriented, whereas small American firms are customer oriented. Chinese small firms are also found to have limited marketing expenditure while their owner-managers have limited marketing expertise. The findings also suggest that Chinese small firms do little strategic marketing planning. One possible reason for this may be that Chinese owner-managers apply innovative tactics and change their marketing planning techniques to suit the characteristics of their firms and their particular circumstances. Thus, it is not unusual to find that Chinese small firm marketing can be described as entrepreneurial and their marketing planning activities as unstructured.