Managing key interfaces in production planning and control

Guinery, Jane; MacCarthy, Bart L.

doi:10.1080/09537280802658535

Cited by 6 publications

(3 citation statements)

References 27 publications

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“…Range, members, roles and responsibilities Dependence or independence on the knowledge and the knowing subject Dreyfus and Dreyfus, 1986;Doz and Prahalad, 1991;Von Krogh and Roos, 1995;Berryman, 2005; Source abilities Establishment in terms of reputation, practice and motivation; capability to make use of external knowledge Cohen and Levinthal, 1990;Hamel, 1991;Szulanski, 1996;Dixon, 2000 Zahra andGeorge, 2002;Recipient abilities Establishment in terms of motivation, intention, practice and developing capacity Bandura, 1986;Argyris, 1990;Hamel, 1991;Yeung et al, 1999;Prusak, 1999;Pfeffer and Sutton, 2000;Fosfuri and Tribo, 2008 Hedberg, 1981;Dixon, 1994;Nonaka and Takeuchi, 1995;Kostova, 1999;Alavi and Leidner, 2001;Guinery and MacCarthy. 2009 Governance and Coordination…”

Section: Knowledge Transfer Networkmentioning

confidence: 99%

Knowledge management in SMEs and MNCs: matching knowledge mobility mechanisms to supply network configuration profiles

Harrington

Srai

Kumar

2019

Production Planning & Control

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While 'knowledge mobility' presents significantly different challenges for SMEs and MNCs, it is strongly influenced by two common factors: the type of knowledge to be integrated and the configuration of the operations network. Only by understanding the various types of knowledge and how they -and the configuration profile of the network (Nascent, Emerging, or Mature; Local, Regional, or Global; SME or MNC) -affect how knowledge is shared, can a proactive and integrated approach to knowledge management be developed.This study specifically examines knowledge transfer mechanisms in knowledgeintensive manufacturing firms and across their networks. Here, both SMEs and MNCs are required to make critical decisions about the 'level' of collaboration and knowledge sharing with network partners -whether it should be purely transactional or more strategic.A network configuration framework is extended to incorporate knowledge-specific dimensions of analysis, derived from the academic literature on stages of emergence and knowledge transfer theory, and supported by a review of knowledge integration mechanisms in practice. This was supported by benchmarking exercises involving a series of multiorganisational network cases with different types of SME-SME and MNC-SME interactions, and gaining insights on factors that will affect future Knowledge Mobility Configurations through a series of industrial case studies. The resulting Knowledge Mobility Configuration (KMC) framework was tested and refined using five case studies indicative of a growing shift towards information and knowledge-intensive activities -involving production and supply network 'partners' -in both SME and MNC contexts.In terms of contribution, there has been limited empirical research to-date into the determinants of successful knowledge transfers in MNC-SME network contexts. The network configuration element of the KMC framework provides insights on how such networks evolve, and how specific knowledge mobility profiles may evolve over time. Our findings demonstrate the critical role of knowledge management in internationalisation, and that skills, knowledge, technology and organisational processes are integral to any emerging network design criteria and/or 'capability' acquisition assessment. The choice of integration mechanism is not only

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Section: Knowledge Transfer Networkmentioning

confidence: 99%

Knowledge management in SMEs and MNCs: matching knowledge mobility mechanisms to supply network configuration profiles

Harrington

Srai

Kumar

2019

Production Planning & Control

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“…Schedulers use various techniques and options to handle interruptions, such as reallocation of resources and re-arrangement of sequencing details (Fransoo & Wiers, 2006). However, schedulers often need to sacrifice some goals in order to achieve others (Cegarra, 2008;Guinery & MacCarthy, 2009). Thus, scheduling goals are not necessarily static and clearly defined in the schedulers' mind; rather, they are contextual, situation-dependent, and constructed as the situation unfolds.…”

Section: Problem Anticipator and Solvermentioning

confidence: 99%

Informing Implementers of Lean Strategy in Process Industries – The Central Role of Schedulers

Alony¹,

Caputi

Coltman

2011

IISIT

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Lean strategy has been recognized for its benefits to discrete manufacturing industries worldwide. However, implementing Lean strategy in process industries has proven difficult. In an attempt to address this problem, this paper identifies scheduler's decisions as crucial to the successful execution of Lean strategy. The paper examines existing descriptions of schedulers and their roles, in search of their potential impact on this execution. Using a case study from the Australian steel industry, empirical evidence shows that schedulers are critical to the success of Lean strategy. Two paths of impact are suggested: (1) schedulers' role as negotiators and facilitators of business operations, and (2) schedulers' discretion and prioritization of business needs. The paper concludes with suggestions for further research on ways to support schedulers' execution of Lean strategy.

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“…Given the frequency of orders, the cost of electronic components and raw materials, customer locations or the variety of options offered, it can be demonstrated that a solution attempting to optimize only the cost or delivery date of each order separately is unsuitable. A better solution considers more indicators to help make a decision that "satisfices" the majority of stakeholders (Guinery and MacCarthy, 2009). …”

Section: Introductionmentioning

confidence: 99%

A decision support system for modelling and implementing the supply network configuration and operations scheduling problem in the machine tool industry

Maheut

Besga

Uribetxebarria

et al. 2013

Production Planning & Control

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Maheut, JPD.; Besga, JM.; Uribetsebarria, J.; García Sabater, JP. (2014). A decision support system for modelling and implementing the supply network configuration and operations scheduling problem in the machine tool industry. Production Planning and Control. 25 (8) This paper presents a decision support system to simultaneously solve the supply network configuration problem and the operations scheduling problem for the machine tool industry. A novel database structure, which is able to consider alternative operations and alternative bills of material, has been used. An algorithm for complete enumeration to determine all the feasible solutions using stroke graphs is introduced. A multiagent-based simulator evaluates the different key performance indicators that the supply network deals with for each alternative solution (e.g., workload, profits, delivery times, etc.) to determine that "satisficed" by the collaborative decision making among its members. A case study based on a Spanish company that assembles highly customized machines and tools in several European plants is considered. From the experiments results based on data linked to this industry it will be demonstrated that the tool is potentially useful for stakeholders and for the central decision maker to make decisions collaboratively in a multisite context case.

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Managing key interfaces in production planning and control

Cited by 6 publications

References 27 publications

Knowledge management in SMEs and MNCs: matching knowledge mobility mechanisms to supply network configuration profiles

Knowledge management in SMEs and MNCs: matching knowledge mobility mechanisms to supply network configuration profiles

Informing Implementers of Lean Strategy in Process Industries – The Central Role of Schedulers

A decision support system for modelling and implementing the supply network configuration and operations scheduling problem in the machine tool industry

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