Search results

The purpose of this paper is to develop a mathematical model of a make-to-order manufacturing company simultaneously negotiating multiple contingent orders that possess conflicting issues in order to achieve order acceptance decisions (OADs).

The paper developed a mathematical model by incorporating probabilistic theory and some theories of negotiation in the OAD problem. The model helps to harness the relationship between the manufacturer and customers of contingent orders on conflicting issues. A numerical example is enumerated to illustrate the working mechanism and sensitivity of the model developed.

In the negotiation-based OAD system, if more than one customer is willing to negotiate on the offer of manufacturer, rather than engaging in one-to-one negotiation, the manufacturer has to negotiate with all the customers simultaneously to maximize the expected contribution and acceptance probability from all the orders. Also, the numerical example illustrates that, sometimes, rejecting an order/orders from the order set gives better results in terms of the expected contribution than continuing negotiations on them.

Through continuing research efforts in this domain, certain models and strategies have been developed for negotiation on a one-to-one basis (i.e. negotiation by the manufacture with only one customer at a time). One-to-one negotiation will neither help companies to streamline their production systems nor will it maximize the expected contribution. To the best of the author’s knowledge, so far, this is the first instance of research work in the domain of a joint OAD and negotiation framework that attempts to develop a simultaneous negotiation method for arriving at OADs.

The purpose of this paper is to develop a framework for the manufacturer of a make-to-order company to simultaneously negotiate with multiple customers through mediator to achieve order acceptance decisions (OADs).

The paper developed mathematical models for the manufacturer, as well as customers to revise their offers during negotiations. Moreover, the paper also proposed a method for the mediator to carry out his assigned duties to assist in negotiation. In the decision process, mediator acts as a bridge between the manufacturer and customers to reach an agreement. A numerical example is enumerated to illustrate the working mechanism and superiority of proposed framework as compared to the framework where simultaneous negotiations are carried out without the presence of mediator.

Iterative method of negotiation conducted without mediator leads to delay in reaching agreement as the aspiration level of manufacturer offer and counter-offer of customer will never cross each other. In addition, the party who submits the offer first may suffer as the opponent can take the advantage of his/her offer during negotiation, thereby, derailing the issue of fairness. Introducing mediator between the manufacturer and the customer for their negotiations could overcome these two issues. Numerical analysis clearly illustrates that, in average, the rounds of negotiation to reach an agreement can be reduced by 22 percent using proposed negotiation framework. In addition, the fairness in negotiations can be improved by 33 percent with the incorporation of mediator.

Through continuing research efforts in this domain, certain models and strategies have been developed for negotiation. Iterative method of negotiations without mediator will help neither the manufacturer nor the customer in terms of fairness and negotiations round to reach an agreement. To the best of the author’s knowledge, so far, this is the first instance of research work in the domain of OAD and negotiation framework that attempts to incorporate mediator for simultaneous negotiation between manufacturer and customers on multiple issues simultaneously.

The customer enquiry management (CEM) process is of strategic importance in engineer‐to‐order contexts but existing literature does not adequately describe how firms support delivery date setting and order acceptance decisions in practice. This paper seeks to explore how and why the CEM process varies between companies in the capital goods sector, thereby taking a contingency theory approach.

Multi‐case study research involving 18 Italian capital goods manufacturers in four industrial sectors. Face‐to‐face interviews with senior representatives have been conducted. Companies have been grouped into five clusters, based on similarities in their CEM decision‐making modes, to aid analysis.

Three contingency factors were found to be particularly relevant in determining CEM modes: degree of product customization, flexibility of the production system, and uncertainty of the context. These factors affect the choice of specific CEM decision‐making modes. However, a high level of cross‐functional coordination and formalization of the process were found to constitute best practices whatever the contingency factors.

The research focuses on companies belonging to the Italian capital goods sector – findings may differ in other countries and sectors.

The results indicate that all firms, including small and medium‐sized companies, should implement high levels of cross‐functional coordination and formalization in their CEM practices, in order to improve their performance. For other aspects of the CEM process, including supplier and subcontractor monitoring, the company context will indicate whether these aspects are required, according to a need of matching the approach to CEM with specific sets of contingency factors.

This paper provides a rare insight into the CEM processes found in practice.

This paper has been written following the refusal of US Big Six firms to participate in a context‐based research project on the new‐client‐acceptance decision, in spite of their claims that current audit research is too far removed from the realities of practice. The paper aims to problematise the firms’ refusal, arguing that it exemplifies efforts at policing the development of academic knowledge on the part of gatekeepers who strive to make researchers work on technicalities, thereby mitigating the risk that research may tarnish the profession’s legitimacy. Insights into the social construction of the gatekeepers’ efforts at policing knowledge are provided by the multilateral negotiations with the firms, showing initial differences in gatekeepers’ boundaries of acceptable research, and subsequent between‐firm discussions that resulted in the firms’ joint decision to refuse participation.

In a changing and more dynamic market of the 1980s, available mathematical programming algorithms on which production planning in process industries was based did not provide the required responsiveness. Although it is suggested in the literature that a variable cycle times policy will enable the system to react to short‐term demand fluctuations, proposes the use of a fixed cycle times policy. Presents simulation results which show a considerable improvement in service level at a high level of utilization. Presents a three‐tiered hierarchical model which is based on this fixed cycle times policy, which gives insight into the influence that the demand manager has upon the results in the production department. On the other hand, it also reflects the commercial interests. Suggests that for both departments which are this strongly intertwined, a common reference is necessary to improve the general results of the business.

When approaching a stock‐out situation, a company should be able to actively manage the allocation of available products on the basis of customer requirements and priorities as well as contractual relationships. The purpose of this paper is to describe different order promising mechanisms and analyze how well they can contribute to the effective management of stock‐out situations.

The paper provides a formal description and analysis of alternative order promising mechanism applicable in make to stock systems. Numerical analysis is conducted based on the data of a pharmaceutical company.

The paper clearly points out the potential of alternative order promising mechanisms to alleviate the negative consequences associated with a temporary stock‐out situation.

The paper does not consider implications of inventory pre‐allocation to customer classes. Further research should address the interplay between pre‐allocation and different order allocation mechanisms.

The results obtained from this analysis provide guidelines for manufacturers, retailers, and vendors of supply chain software on how to design and utilize order promising systems.

The paper provides a consistent formal approach to modelling order promising mechanisms, introduce new and innovative order promising mechanisms and provide valuable insight into their performance through numerical analysis.

This paper aims to develop a decision support system for predicting the knitting production’s efficiency based on the input parameters of an order. This tool supports the operations managers to make reliable decisions of estimated delivery time, which will result in reducing waste arising from late delivery, overtime and increased labor.

The decision tree method with a set of logical IF-THEN rules is used to determine the knitting production’s efficiency. Each path of the decision tree represents a rule of the following form: “IF <Condition> THEN <Efficiency label>.” Starting with identifying and categorizing input specifications, the model is then applied to the observed data to regenerate the results of efficiency into classification instances.

The production’s efficiency is the result of the interaction between input specifications such as yarn’s component, knitting fabric specifications and machine speed. The rule base is generated through a decision tree built to classify the efficiency into five levels, including very low, low, medium, high and very high. Based on this, production managers can determine the delivery time and schedule the manufacturing planning more accurately. In this research, the correct classification instances, which is simply a ratio of the correctly predicted observations to the total ones, reach 80.17%.

This research proposes a new methodology for estimating the efficiency of weft knitting production based on a decision tree method with an application of real data. This model supports the decision-making process of the estimated delivery time.

This paper aims to enhance the responsiveness of enterprises with regard to delivery schedules in a supply chain. Based on the observations in industry, it seems that companies often re‐negotiate their due‐dates. These phenomena have begun to appear only recently, as a result of the advancements of information technology and flexibility in the supply chain. However, these due‐date re‐negotiation processes are haphazard and ad hoc in nature, and a formal process is needed to respond to market fluctuations more quickly. In this paper, a re‐negotiable order processing method is developed that can change the already‐assigned due‐dates or allow partial shipments to increase the flexibility of firm response to a rush order from a prior customer (PC).

A due‐date re‐negotiation process is defined and a formal system for handling customer orders is proposed. The new data and business process integration model are proposed for the due‐date re‐negotiation process based on RosettaNet's Partner Interface Processes. Web services and ubiquitous computing technologies are used in the proposed system architecture to allow for responsive sales order management.

The paper shows that assigned due‐dates can also be re‐negotiated by enhancing the connectivity and visibility of the supply chain with co‐operative customers. In the early stage of the product life cycle or high‐regional demand variation environments, it is better to re‐negotiate due‐dates than to meet scheduled due‐dates.

In some instances, meeting the due‐date requested by a customer relates to the success or failure of a particular sales order. The proposed re‐negotiation method could help the sales offices of the MF to respond to PC requests quickly and flexibly. Rush orders from PC might be acceptable based on the slack gained through the re‐negotiation of co‐operative customers' assigned orders.

There has been a considerable volume of studies on the due‐date assignment, order releasing, and scheduling problems. However, these previous studies considered due‐dates as exogenous parameters or fixed endogenous variables. In this paper, the assigned due‐dates for pre‐contracted co‐operative customers are considered as re‐negotiable variables. On the other hand, most studies on ubiquitous computing technologies, especially those relate to radio frequency identification (RFID), have focused mostly on asset management and processing time reduction. This paper suggests other benefits of increased visibility and traceability of RFID technology in enhancing responsiveness and flexibility in the sales order management system.

This paper aims to focus on the question whether formalisation of the ordering process can be helpful in achieving responsiveness, while remaining efficient.

Three dimensions of the ordering process are discussed, namely logistical control, information processing and the organisational setting of the ordering process. Data were gathered from case studies at five different production companies.

It is suggested that a highly formalised logistical control structure is essential in achieving responsiveness and efficiency. From the formalisation strategies applied by the companies it can also be concluded that a formalised organisational setting of the ordering process is necessary for being responsive in case the logistical control is characterised by a low degree of formalisation.

The paper presents a detailed operationalisation of the formalisation of three dimensions of the ordering process. This is helpful in formulating guidelines for structuring the ordering process to become more responsive.

Many standard texts (for example, see) identify that business, through the marketing function, relates to the profitable satisfaction of customer needs and wants. In general, however, the concept of cash flow and contribution margins is seldom mentioned in non‐financial texts, except in the case of strategic models such as that described by Henderson, when it tends to be utilised mainly in an abstract and historical sense rather than in a dynamic sense.