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  • 1.
    Hallgren, Mattias
    Linköping University, Department of Production Economics.
    Competitive strategies and manufacturing focus: an empirical analysis2006In: Fourteenth International Working Seminar on Production Economics,2006, 2006, p. 199-208Conference paper (Other academic)
  • 2.
    Hallgren, Mattias
    Linköping University, Department of Management and Engineering.
    Competitive strategies and manufacturing focus: an empirical analysis2007In: International Journal of Production EconomicsArticle in journal (Refereed)
  • 3.
    Hallgren, Mattias
    Linköping University, Department of Management and Engineering. Linköping University, The Institute of Technology.
    Manufacturing Strategy, Capabilities and Performance2007Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    This dissertation addresses the topic of manufacturing strategy, especially the manufacturing capabilities and operational performance of manufacturing plants. Manufacturing strategy research aims at providing a structured decision making approach to improve the economics of manufacturing and to make companies more competitive.

    The overall objective of this thesis is to investigate how manufacturing companies make use of different manufacturing practices or bundles of manufacturing practices to develop certain sets of capabilities, with the ultimate goal of supporting the market requirements. The thesis aims to increase the understanding of the role of operations management and its immediate impact on manufacturing performance. Following the overall research objective three areas are identified to be of particular interest; to investigate (i) the relationship among different dimensions of operational performance, (ii) the way different performance dimensions are affected by manufacturing practices or bundles of manufacturing practices, (iii) whether there are contingencies that may help explain the relationships between dimensions of manufacturing capabilities or the effects of manufacturing practices or bundles of manufacturing practices on operational performance.

    The empirical elements in this thesis use data from the High Performance Manufacturing (HPM) project. The HPM project is an international study of manufacturing plants involving seven countries and three industries.

    The research contributes to several insights to the research area of manufacturing strategy and to practitioners in manufacturing operations. The thesis develops measurements for and tests the effects of several manufacturing practices on operational performance. The results are aimed at providing guidance for decision making in manufacturing companies. The most prominent implication for researchers is the manifestation of the customer order decoupling point as an important contingency variable to consider when studying manufacturing operations.

    List of papers
    1. Quantification in manufacturing strategy: a methodology and illustration
    Open this publication in new window or tab >>Quantification in manufacturing strategy: a methodology and illustration
    2006 (English)In: International Journal of Production Economics, ISSN 0925-5273, Vol. 104, no 1, p. 113-124Article in journal (Refereed) Published
    Abstract [en]

    Strategic decision-making is often based on conceptual and qualitative models. Considering the vast amount of quantitative models in the literature, it is most interesting and important to explore the possibilities to expand the modelling base for decision-making with quantitative models that can provide deeper analysis, new insights and allow for finer sensitivity analysis. The purpose of this paper is to explore various aspects of quantification in manufacturing strategy-related issues. We review current approaches to quantitative modelling and study how quantitative models are being used and can be used for strategic decision-making in manufacturing. We create a framework and methodology for quantitative modelling for manufacturing strategy, based on market requirements, manufacturing capabilities, manufacturing actions within decision categories, and quantitative modelling approach. The framework methodology includes seven stages of quantification, for the purpose of measuring, linking, comparing, and modelling. The aim of the paper is to provide a structure that can aid in the modelling of strategic manufacturing decisions to improve the capabilities to meet market requirements.

    Keywords
    Manufacturing strategy; Operations; Quantitative modelling
    National Category
    Engineering and Technology
    Identifiers
    urn:nbn:se:liu:diva-14542 (URN)10.1016/j.ijpe.2005.09.004 (DOI)
    Available from: 2007-05-25 Created: 2007-05-25 Last updated: 2010-06-14
    2. Differentiating manufacturing focus
    Open this publication in new window or tab >>Differentiating manufacturing focus
    2006 (English)In: International Journal of Production Research, ISSN 0020-7543, Vol. 44, no 18-19, p. 3863-3878Article in journal (Refereed) Published
    Abstract [en]

    In order for a manufacturing firm to be competitive, by supporting the market requirements through the manufacturing function, manufacturing should focus on a narrow set of tasks. Focused manufacturing is concerned with the perspectives when designing a manufacturing facility, be it a factory, plant, or plant within a plant. Traditionally, focus has been on the product, the process, or the manufacturing task based on competitive priorities (order winners and qualifiers). So far, the literature implies that a certain facility should have only one focus. In this paper, we present a framework that differentiates focus with respect to different parts of the manufacturing value chain. The point around which focus needs to be differentiated is the customer order decoupling point. We associate alternative types of focus relative to the customer order decoupling point, separating the upstream and downstream parts, and create a framework for choosing focus and how to differentiate manufacturing focus.

    National Category
    Engineering and Technology
    Identifiers
    urn:nbn:se:liu:diva-14543 (URN)10.1080/00207540600702290 (DOI)
    Available from: 2007-05-25 Created: 2007-05-25
    3. Competitive strategies and manufacturing focus: an empirical analysis
    Open this publication in new window or tab >>Competitive strategies and manufacturing focus: an empirical analysis
    2007 (English)In: International Journal of Production EconomicsArticle in journal (Refereed) Submitted
    National Category
    Production Engineering, Human Work Science and Ergonomics
    Identifiers
    urn:nbn:se:liu:diva-14544 (URN)
    Available from: 2007-05-25 Created: 2007-05-25 Last updated: 2010-05-31
    4. Competitive capabilities: a contingency perspective
    Open this publication in new window or tab >>Competitive capabilities: a contingency perspective
    2007 (English)In: Journal of Operations Management, ISSN 0272-6963, E-ISSN 1873-1317Article in journal (Other academic) Submitted
    Abstract [en]

    In this paper we present and test an alternative model for competitive capabilities.Traditionally, a cumulative model has been viewed as having one sequence of buildingoperations capabilities in a firm in support of market needs, including quality,delivery, cost efficiency and flexibility. Although appealing as a conceptual model,empirical testing has not been able to fully support the cumulative model. This paperacknowledges the need for differentiated approaches to managing capability indifferent operating environments. The competitive capability model that is presented istested empirically using data from the High Performance Manufacturing (HPM) study,including three industries and seven countries – a total of 211 plants. The results showthat there is empirical support for differentiating the competitive capabilities; firmsproducing to stock follow a path of quality, delivery and cost, whereas those producingto customer order exhibit a capability path in the order of quality, delivery andflexibility. Thus, while quality and delivery are common, cost and flexibility acts asdifferentiators contingent upon the manufacturing environment.

    Keywords
    Operations strategy; Empirical research; Competitive capabilities; Decoupling point
    Identifiers
    urn:nbn:se:liu:diva-53024 (URN)
    Available from: 2010-01-14 Created: 2010-01-14 Last updated: 2017-12-12
    5. Flexibility configurations: Empirical analysis of volume and product mix flexibility
    Open this publication in new window or tab >>Flexibility configurations: Empirical analysis of volume and product mix flexibility
    2009 (English)In: Omega: The International Journal of Management Science, ISSN 0305-0483, E-ISSN 1873-5274, Vol. 37, no 4, p. 746-756Article in journal (Refereed) Published
    Abstract [en]

    In this paper we address flexibility and investigate the relationship between volume and product mix flexibility. One view of flexibility is that of being a capability in itself: another view is that of flexibility as an enabler, providing the manufacturing system with properties on which other competitive capabilities are built. In this research, the latter view of flexibility is used, where flexibility acts as a second order competitive criterion. The aim is to differentiate between two dimensions of flexibility important to the manufacturing value chain, i.e., volume and product mix flexibility, and to investigate how different flexibility configurations are related to Various manufacturing practices. A clustering research approach is used to identify groups of companies based on flexibility configurations. The groups are then analyzed with respect to characteristics and impact on operational performance. For the empirical investigation, we use empirical data from the high performance manufacturing (HPM) study, including three industries and seven countries-a total of 211 plants. We find that flexibility configurations based on high or low levels of volume and mix flexibility combinations show significant differences both in terms of operational performance, and in terms of emphasis put into different flexibility source factors.

    Place, publisher, year, edition, pages
    Kidlington, Oxford, United Kingdom: Pergamon Press, 2009
    Keywords
    Empirical research, Flexible manufacturing, Operations management, Survey, Value chain
    National Category
    Production Engineering, Human Work Science and Ergonomics
    Identifiers
    urn:nbn:se:liu:diva-16407 (URN)10.1016/j.omega.2008.07.004 (DOI)000262063700002 ()
    Note

    Original Publication: Mattias Hallgren and Jan Olhager, Flexibility configurations: Empirical analysis of volume and product mix flexibility, 2009, OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE, (37), 4, 746-756. http://dx.doi.org/10.1016/j.omega.2008.07.004 Copyright: Elsevier Science B.V., Amsterdam. http://www.elsevier.com/

    Available from: 2009-02-09 Created: 2009-01-23 Last updated: 2017-12-14Bibliographically approved
    6. Lean and agile manufacturing: external and internal drivers and performance outcomes
    Open this publication in new window or tab >>Lean and agile manufacturing: external and internal drivers and performance outcomes
    2009 (English)In: International Journal of Operations & Production Management, ISSN 0144-3577, E-ISSN 1758-6593, Vol. 29, no 10, p. 976-999Article in journal (Refereed) Published
    Abstract [en]

    Purpose - Lean and agile manufacturing are two initiatives that are used by manufacturing plant managers to improve operations capabilities. The purpose of this paper is to investigate internal and external factors that drive the choice of lean and agile operations capabilities and their respective impact on operational performance. Design/methodology/approach - Lean and agile manufacturing are each conceptualized as a second-order factor and measured through a bundle of distinct practices. The competitive intensity of industry and the competitive strategy are modeled as potential external and internal drivers, respectively, and the impact on quality, delivery, cost, and flexibility performance is analyzed using structural equations modeling. The model is tested with data from the high performance manufacturing project comprising a total of 211 plants from three industries and seven countries. Findings - The results indicate that lean and agile manufacturing differ in terms of drivers and outcomes. The choice of a cost-leadership strategy fully mediates the impact of the competitive intensity of industry as a driver of lean manufacturing, while agile manufacturing is directly affected by both internal and external drivers, i.e. a differentiation strategy as well as the competitive intensity of industry. Agile manufacturing is found to be negatively associated with a cost-leadership strategy, emphasizing the difference between lean and agile manufacturing. The major differences in performance outcomes are related to cost and flexibility, such that lean manufacturing has a significant impact on cost performance (whereas agile manufacturing has not), and that agile manufacturing has a stronger relationship with volume as well as product mix flexibility than does lean manufacturing. Research limitations/implications - Cross-sectional data from three industries and seven countries are used, and it would be interesting to test this model for more industries and countries. Practical implications - The results provide insights into the factors that influence the choice of lean or agile manufacturing for improving operations, and the results that can be obtained. Originality/value - To the authors knowledge, this is the first large-scale empirical survey of leanness and agility simultaneously, using data from manufacturing firms in Europe, Asia, and North America. The model incorporates a wide perspective on factors related to lean and agile manufacturing, to be able to identify similarities and differences.

    Place, publisher, year, edition, pages
    Emerald Group Publishing Limited, 2009
    Keywords
    Lean production, Agile production, Operations management
    National Category
    Engineering and Technology
    Identifiers
    urn:nbn:se:liu:diva-51776 (URN)10.1108/01443570910993456 (DOI)000271206100001 ()
    Available from: 2009-11-18 Created: 2009-11-17 Last updated: 2017-12-12Bibliographically approved
  • 4.
    Hallgren, Mattias
    et al.
    Linköping University, Department of Production Economics.
    Johansson, Pontus
    Linköping University, The Institute of Technology. Linköping University, Department of Production Economics.
    Koppla värdekedjan till affärsstrategin2005In: Produktionsstrategi, Vol. 1, no 2Article in journal (Other (popular science, discussion, etc.))
  • 5.
    Hallgren, Mattias
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Production Economics.
    Olhager, Jan
    Linköping University, The Institute of Technology. Linköping University, Department of Production Economics.
    At the crossroads of sandcone and customer order decoupling point theory: a practice based analysis2006In: Decision Sciences Institute Annual Meeting - Decision Making to Increase Business Value,2006, 2006, p. 122-122Conference paper (Other academic)
  • 6.
    Hallgren, Mattias
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Production Economics.
    Olhager, Jan
    Linköping University, The Institute of Technology. Linköping University, Department of Production Economics.
    Cumulative capabilities - a dual approach2006In: EUROMA 2006 - Moving up the value chain vol 2,2006, Glasgow: University of Strathclyde , 2006, p. 271-Conference paper (Refereed)
    Abstract [en]

      

  • 7.
    Hallgren, Mattias
    et al.
    Linköping University, Department of Production Economics. Linköping University, The Institute of Technology.
    Olhager, Jan
    Linköping University, Department of Production Economics. Linköping University, The Institute of Technology.
    Differentiating Manufacturing Focus2005In: International Conference on Production Research,2005, Salerno, Italy: University of Salerno , 2005Conference paper (Refereed)
  • 8.
    Hallgren, Mattias
    et al.
    Linköping University, Department of Management and Engineering. Linköping University, The Institute of Technology.
    Olhager, Jan
    Linköping University, Department of Management and Engineering, Production Economics . Linköping University, The Institute of Technology.
    Differentiating manufacturing focus2006In: International Journal of Production Research, ISSN 0020-7543, Vol. 44, no 18-19, p. 3863-3878Article in journal (Refereed)
    Abstract [en]

    In order for a manufacturing firm to be competitive, by supporting the market requirements through the manufacturing function, manufacturing should focus on a narrow set of tasks. Focused manufacturing is concerned with the perspectives when designing a manufacturing facility, be it a factory, plant, or plant within a plant. Traditionally, focus has been on the product, the process, or the manufacturing task based on competitive priorities (order winners and qualifiers). So far, the literature implies that a certain facility should have only one focus. In this paper, we present a framework that differentiates focus with respect to different parts of the manufacturing value chain. The point around which focus needs to be differentiated is the customer order decoupling point. We associate alternative types of focus relative to the customer order decoupling point, separating the upstream and downstream parts, and create a framework for choosing focus and how to differentiate manufacturing focus.

  • 9.
    Hallgren, Mattias
    et al.
    Linköping University, Department of Management and Engineering, Production Economics. Linköping University, The Institute of Technology.
    Olhager, Jan
    Linköping University, Department of Management and Engineering, Production Economics. Linköping University, The Institute of Technology.
    Flexibility configurations: Empirical analysis of volume and product mix flexibility2009In: Omega: The International Journal of Management Science, ISSN 0305-0483, E-ISSN 1873-5274, Vol. 37, no 4, p. 746-756Article in journal (Refereed)
    Abstract [en]

    In this paper we address flexibility and investigate the relationship between volume and product mix flexibility. One view of flexibility is that of being a capability in itself: another view is that of flexibility as an enabler, providing the manufacturing system with properties on which other competitive capabilities are built. In this research, the latter view of flexibility is used, where flexibility acts as a second order competitive criterion. The aim is to differentiate between two dimensions of flexibility important to the manufacturing value chain, i.e., volume and product mix flexibility, and to investigate how different flexibility configurations are related to Various manufacturing practices. A clustering research approach is used to identify groups of companies based on flexibility configurations. The groups are then analyzed with respect to characteristics and impact on operational performance. For the empirical investigation, we use empirical data from the high performance manufacturing (HPM) study, including three industries and seven countries-a total of 211 plants. We find that flexibility configurations based on high or low levels of volume and mix flexibility combinations show significant differences both in terms of operational performance, and in terms of emphasis put into different flexibility source factors.

  • 10.
    Hallgren, Mattias
    et al.
    Linköping University, Department of Production Economics.
    Olhager, Jan
    Linköping University, Department of Production Economics.
    Kvantitativa produktionsstrategiska modeller2004In: Produktionslogistik 2004,2004, 2004, p. 193-204Conference paper (Other academic)
  • 11.
    Hallgren, Mattias
    et al.
    Linköping University, Department of Management and Engineering, Production Economics. Linköping University, The Institute of Technology.
    Olhager, Jan
    Linköping University, Department of Management and Engineering, Production Economics. Linköping University, The Institute of Technology.
    Lean and agile manufacturing: external and internal drivers and performance outcomes2009In: International Journal of Operations & Production Management, ISSN 0144-3577, E-ISSN 1758-6593, Vol. 29, no 10, p. 976-999Article in journal (Refereed)
    Abstract [en]

    Purpose - Lean and agile manufacturing are two initiatives that are used by manufacturing plant managers to improve operations capabilities. The purpose of this paper is to investigate internal and external factors that drive the choice of lean and agile operations capabilities and their respective impact on operational performance. Design/methodology/approach - Lean and agile manufacturing are each conceptualized as a second-order factor and measured through a bundle of distinct practices. The competitive intensity of industry and the competitive strategy are modeled as potential external and internal drivers, respectively, and the impact on quality, delivery, cost, and flexibility performance is analyzed using structural equations modeling. The model is tested with data from the high performance manufacturing project comprising a total of 211 plants from three industries and seven countries. Findings - The results indicate that lean and agile manufacturing differ in terms of drivers and outcomes. The choice of a cost-leadership strategy fully mediates the impact of the competitive intensity of industry as a driver of lean manufacturing, while agile manufacturing is directly affected by both internal and external drivers, i.e. a differentiation strategy as well as the competitive intensity of industry. Agile manufacturing is found to be negatively associated with a cost-leadership strategy, emphasizing the difference between lean and agile manufacturing. The major differences in performance outcomes are related to cost and flexibility, such that lean manufacturing has a significant impact on cost performance (whereas agile manufacturing has not), and that agile manufacturing has a stronger relationship with volume as well as product mix flexibility than does lean manufacturing. Research limitations/implications - Cross-sectional data from three industries and seven countries are used, and it would be interesting to test this model for more industries and countries. Practical implications - The results provide insights into the factors that influence the choice of lean or agile manufacturing for improving operations, and the results that can be obtained. Originality/value - To the authors knowledge, this is the first large-scale empirical survey of leanness and agility simultaneously, using data from manufacturing firms in Europe, Asia, and North America. The model incorporates a wide perspective on factors related to lean and agile manufacturing, to be able to identify similarities and differences.

  • 12.
    Hallgren, Mattias
    et al.
    Linköping University, Department of Management and Engineering. Linköping University, The Institute of Technology.
    Olhager, Jan
    Linköping University, Department of Management and Engineering, Production Economics . Linköping University, The Institute of Technology.
    Quantification in manufacturing strategy: a methodology and illustration2006In: International Journal of Production Economics, ISSN 0925-5273, Vol. 104, no 1, p. 113-124Article in journal (Refereed)
    Abstract [en]

    Strategic decision-making is often based on conceptual and qualitative models. Considering the vast amount of quantitative models in the literature, it is most interesting and important to explore the possibilities to expand the modelling base for decision-making with quantitative models that can provide deeper analysis, new insights and allow for finer sensitivity analysis. The purpose of this paper is to explore various aspects of quantification in manufacturing strategy-related issues. We review current approaches to quantitative modelling and study how quantitative models are being used and can be used for strategic decision-making in manufacturing. We create a framework and methodology for quantitative modelling for manufacturing strategy, based on market requirements, manufacturing capabilities, manufacturing actions within decision categories, and quantitative modelling approach. The framework methodology includes seven stages of quantification, for the purpose of measuring, linking, comparing, and modelling. The aim of the paper is to provide a structure that can aid in the modelling of strategic manufacturing decisions to improve the capabilities to meet market requirements.

  • 13.
    Hallgren, Mattias
    et al.
    Linköping University, Department of Production Economics.
    Olhager, Jan
    Linköping University, Department of Production Economics.
    Quantitative Modelling for Manufacturing Strategy: A Framework and Illustrations2004In: Thirteenth International Working Seminar on Production Economics,2004, 2004, p. 97-109Conference paper (Other academic)
  • 14.
    Hallgren, Mattias
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Production Economics.
    Olhager, Jan
    Linköping University, The Institute of Technology. Linköping University, Department of Production Economics.
    Resurssnål och flexibel produktion: drivkrafter och effekter2006In: PLANs Forsknings- och tillämpningskonferens - Effektivitet och samverkan i försörjningskedjor,2006, Stockholm: PLAN , 2006, p. 174-Conference paper (Refereed)
  • 15.
    Hallgren, Mattias
    et al.
    Linköping University, Department of Management and Engineering, Production Economics. Linköping University, The Institute of Technology.
    Olhager, Jan
    Linköping University, Department of Management and Engineering, Production Economics. Linköping University, The Institute of Technology.
    Schroeder, Roger G.
    University of Minnesota, USA .
    A hybrid model of competitive capabilities2011In: International Journal of Operations & Production Management, ISSN 0144-3577, E-ISSN 1758-6593, Vol. 31, no 5, p. 511-526Article in journal (Refereed)
    Abstract [en]

    Purpose – The purpose of this paper is to present and test a new model for competitive capabilities.Traditionally, a cumulative model has been viewed as having one sequence of building competitivecapabilities in a firm in support of market needs, including quality, delivery, cost efficiency andflexibility. Although appealing as a conceptual model, empirical testing has not been able to fullysupport the cumulative model. This paper acknowledges the need for a hybrid approach to managingcapability progression. It brings together the literature on trade-offs, cumulative capabilities, andorder winners and qualifiers.Design/methodology/approach – A new hybrid approach for modelling competitive capabilities istested empirically using data from the high performance manufacturing (HPM) study, round 3,including three industries and seven countries – a total of 211 plants.Findings – The hybrid model shows significantly better fit with the data from the sample than thecumulative models suggested by previous literature. Empirical support is found for the traditionalperception that a high level of quality is a prerequisite for a high level of delivery performance.However, cost efficiency and flexibility do not exhibit a cumulative pattern. Instead, the results showthat they are developed in parallel. The findings suggest that a balance between cost efficiency andflexibility is built upon high levels of quality and delivery performance.Research limitations/implications – Since we limit the empirical investigation to three industriesand seven countries, it would be interesting to extend the testing of this model to more industries andcountries. This research shows that combining perspectives and insights from different researchstreams – in this case, trade-off theory and the concepts of cumulative capabilities, and order winnersand qualifiers – can be fruitful.Practical implications – The results of this paper provides managers with guidelines concerningthe configuration of competitive capabilities. First, a qualifying level of quality needs to be attained,followed by a qualifying level of delivery. Then, a balance between potential order winners, i.e. costefficiency and flexibility, needs to be attained.Originality/value – This paper presents a new approach to modelling competitive capabilities thatsynthesises previous research streams and perspectives from cumulative capabilities, contestingcapabilities (trade-offs), and order winners and qualifiers.

  • 16.
    Hallgren, Mattias
    et al.
    Linköping University, Department of Management and Engineering, Production Economics . Linköping University, The Institute of Technology.
    Olhager, Jan
    Linköping University, Department of Management and Engineering, Production Economics . Linköping University, The Institute of Technology.
    Schroeder, Roger G.
    Operations and Management Science Department, Carlson School of Management, University of Minnesota, 321 19th Ave. S, Minneapolis, MN 55455, USA.
    Competitive capabilities: a contingency perspective2007In: Journal of Operations Management, ISSN 0272-6963, E-ISSN 1873-1317Article in journal (Other academic)
    Abstract [en]

    In this paper we present and test an alternative model for competitive capabilities.Traditionally, a cumulative model has been viewed as having one sequence of buildingoperations capabilities in a firm in support of market needs, including quality,delivery, cost efficiency and flexibility. Although appealing as a conceptual model,empirical testing has not been able to fully support the cumulative model. This paperacknowledges the need for differentiated approaches to managing capability indifferent operating environments. The competitive capability model that is presented istested empirically using data from the High Performance Manufacturing (HPM) study,including three industries and seven countries – a total of 211 plants. The results showthat there is empirical support for differentiating the competitive capabilities; firmsproducing to stock follow a path of quality, delivery and cost, whereas those producingto customer order exhibit a capability path in the order of quality, delivery andflexibility. Thus, while quality and delivery are common, cost and flexibility acts asdifferentiators contingent upon the manufacturing environment.

  • 17.
    Olhager, Jan
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Production Economics.
    Hallgren, Mattias
    Linköping University, The Institute of Technology. Linköping University, Department of Production Economics.
    Lean and agile manufacturing: drivers and performance outcomes2006In: POMS 2006 - Production and Operations Management,2006, 2006, p. 96-96Conference paper (Other academic)
  • 18.
    Olhager, Jan
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Management and Engineering, Production Economics .
    Hallgren, Mattias
    Linköping University, The Institute of Technology. Linköping University, Department of Management and Engineering, Production Economics .
    West, Martin
    Volvo AB.
    Manufacturing strategy alignment2008In: World Conference on Production and Operations Management,2008, Tokyo: POMS , 2008Conference paper (Refereed)
    Abstract [en]

    The competitive positions of manufacturing firms is typically considered to stem from the strategic alignment between market opportunities and manufacturing abilities; the foundation for manufacturing strategy. In this paper we investigate the role of alignment in a broader sense, including the business strategy. We review the concept of alignment between business strategy, manufacturing strategy, and other functional strategies, and develop a conceptual model linking alignment to manufacturing strength and operational performance. We test this model with data from the High Performance Manufacturing study; a total of 238 plants from three industries and eight countries. The results indicate that the alignment between manufacturing strategy and business strategy is of the utmost importance for manufacturing strength and subsequently high performance. The impact of alignment with other functional strategies is however non-significant. Still, the relationship between business strategy alignment and functional strategy alignment is significant. These results imply that the business strategy is well aligned with the functional strategies, including manufacturing strategy, while the link between functional strategies does not significantly support manufacturing as a competitive resource. The impact of manufacturing strength on operational performance is highly significant.

  • 19.
    Olhager, Jan
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Management and Engineering.
    Hallgren, Mattias
    Linköping University, The Institute of Technology. Linköping University, Department of Management and Engineering.
    West, Martin
    Linköping University, The Institute of Technology. Linköping University, Department of Management and Engineering.
    Manufacturing strategy alignment2007In: The Swedish Production Symposium,2007, Gothenburg: Chalmers , 2007Conference paper (Refereed)
    Abstract [en]

        

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