Advertisement

Production Engineering

, Volume 13, Issue 1, pp 21–32 | Cite as

The degree of inventory centralization for food manufacturers

  • Nona Fortian Corts
  • Zaza Nadja Lee Herbert-Hansen
  • Samuel Brüning Larsen
  • Waqas KhalidEmail author
Production Management
  • 94 Downloads

Abstract

For food manufacturers, limited shelf-lives and ‘freshness’ requirements increase inventory holding costs. Accuracy in choosing the most advantageous degree of inventory centralization (MADIC) is therefore central for competitiveness. While extant research contains several industry-generic factors that influence centralization decisions, influencing factors for food manufacturers, in particular, is under-explored. This paper identifies the factors that influence the MADIC for food manufacturers and develops a method that integrates all factors for MADIC-determination. The study examines a single case facilitating deep-dives into unknown areas. Results show nine factors of which three are specific to food manufacturing. Furthermore, the paper details how practitioners can determine a MADIC-score on a 1–100 scale for their particular operations. While food manufacturing inventory centralization literature is scarce, this paper contributes to a holistic study of multiple relevant factors and a method that integrates all factors into one result.

Keywords

Centralization Decentralization Food manufacturing Inventory management Case study research Multicriteria decisions 

References

  1. 1.
    Abrahamsson M (1993) Time-based distribution. Int J Logist Manag 4(2):75–84.  https://doi.org/10.1108/09574099310805000 CrossRefGoogle Scholar
  2. 2.
    Baker P (2007) An exploratory framework of the role of inventory and warehousing in international supply chains. Int J Logist Manag 18(1):64–80.  https://doi.org/10.1108/09574090710748171 CrossRefGoogle Scholar
  3. 3.
    Wilson RA (2006) 17th annual state of logistics report®: “Embracing security as a core business function”. Council of Supply Chain Management Professionals, Lombard, ILGoogle Scholar
  4. 4.
    Protopappa-Sieke M, Seifert RW (2010) Interrelating operational and financial performance measurements in inventory control. Eur J Oper Res 204(3):439–448.  https://doi.org/10.1016/j.ejor.2009.11.001 CrossRefzbMATHGoogle Scholar
  5. 5.
    Lemoine OW, Skjoett-Larsen T (2004) Reconfiguration of supply chains and implications for transport. Int J Phys Distrib Logist Manag 34:793–810CrossRefGoogle Scholar
  6. 6.
    Pedersen SG, Zachariassen F, Arlbjørn JS (2012) Centralisation vs de‐centralisation of warehousing: a small and medium‐sized enterprise perspective. J Small Bus Enterp Dev 19(2):352–369.  https://doi.org/10.1108/14626001211223946 CrossRefGoogle Scholar
  7. 7.
    Prater E, Biehl M, Smith MA (2001) International supply chain agility—tradeoffs between flexibility and uncertainty. Int J Oper Prod Manag 21(5–6):823–839.  https://doi.org/10.1108/01443570110390507 CrossRefGoogle Scholar
  8. 8.
    Helo P, Ala-Harja H (2018) Green logistics in food distribution—a case study. Int J Logist Res Appl 21:464–479CrossRefGoogle Scholar
  9. 9.
    Etienne EC (2005) Supply chain responsiveness and the inventory illusion. Supply Chain Forum Int J 6(1):48–65.  https://doi.org/10.1080/16258312.2005.11517138 MathSciNetCrossRefGoogle Scholar
  10. 10.
    Manufacturing statistics—NACE Rev. 2—statistics explained. http://ec.europa.eu/eurostat/statistics-explained/index.php/ Manufacturing_statistics_-_NACE_Rev._2. Accessed 04 Feb 2018
  11. 11.
    Dani S (2015) Food supply chain management and logistics: from farm to fork. Kogan Page Publishers, LondonGoogle Scholar
  12. 12.
    Verdouw CN, Wolfert J, Beulens AJM, Rialland A (2016) Virtualization of food supply chains with the internet of things. J Food Eng 176:128–136.  https://doi.org/10.1016/j.jfoodeng.2015.11.009 CrossRefGoogle Scholar
  13. 13.
    Cooper MC (1983) Freight consolidation and warehouse location strategies in physical distribution systems. J Bus Logist 4:53–74Google Scholar
  14. 14.
    Zinn W, Levy M, Bowersox DJ (1989) Measuring the effect of inventory centralization/decentralization on aggregate safety stock: the “square root law” revisited. J Bus Logist 10:1Google Scholar
  15. 15.
    Croxton KL, Zinn W (2005) Inventory considerations in network design. J Bus Logist 26:149–168CrossRefGoogle Scholar
  16. 16.
    Chopra S, Meindl P (2007) Supply chain management. strategy, planning & operation. In: The summary of management. Gabler, pp 265–275Google Scholar
  17. 17.
    Snyder LV, Shen Z-JM (2006) Supply and demand uncertainty in multi-echelon supply chains. Submitted for publication, Lehigh University, 15, ChicagoGoogle Scholar
  18. 18.
    Corbett CJ, Rajaram K (2003) Aggregation of uncertainty and multivariate dependence: the value of pooling of inventories under non-normal dependent demandGoogle Scholar
  19. 19.
    Schmitt AJ, Sun SA, Snyder LV, Shen Z-JM (2015) Centralization versus decentralization: risk pooling, risk diversification, and supply chain disruptions. Omega-Int J Manag Sci 52:201–212.  https://doi.org/10.1016/j.omega.2014.06.002 CrossRefGoogle Scholar
  20. 20.
    Teo CP, Ou J, Goh M (2001) Impact on inventory costs with consolidation of distribution centers. IIE Trans (Inst Ind Eng) 33(2):99–110.  https://doi.org/10.1023/A:1007646817627 Google Scholar
  21. 21.
    Wanke PF, Zinn W (2004) Strategic logistics decision making. Int J Phys Distrib Logist Manag 34:466–478CrossRefGoogle Scholar
  22. 22.
    Jonsson P, Mattsson S-A (2011) Logistik: Läran Om Effektiva Materialflöden—Patrik Jonsson, Stig-Arne Mattsson—Häftad (9789144110776$4|Bokus, LundGoogle Scholar
  23. 23.
    Chen MS, Lin CT (1989) Effects of Centralization on Expected Costs in a Multi-location Newsboy Problem. J Oper Res Soc 40(6):597–602.  https://doi.org/10.1057/jors.1989.97 CrossRefzbMATHGoogle Scholar
  24. 24.
    Mahmoud MM (1992) Optimal inventory consolidation schemes: a portfolio effects analysis. J Bus Logist 13:193Google Scholar
  25. 25.
    Das C, Tyagi R (1997) Role of inventory and transportation costs in determining the optimal degree of centralization. Transp Res Part E Logist Transp Rev 33:171–179CrossRefGoogle Scholar
  26. 26.
    Juga J (1995) Redesigning logistics to improve performance. Int J Logist Manag 6:75–84CrossRefGoogle Scholar
  27. 27.
    Li W, Ahuja H, Batcha MF, Jiang B, Li F. Centralization or decentralization: the dilemma of schneider electric case study report, UCD Michael Smurfit Graduate Business SchoolGoogle Scholar
  28. 28.
    Petersson S, Sturesson S (2014) Centralization of inventory management for spare parts. Lunds Universitet, LundGoogle Scholar
  29. 29.
    Frost A (2014) Measuring effects on inventory by centralization for a wholesaler in the industry sector: a case study (Master's thesis, Høgskolen i Molde-Vitenskapelig høgskole i logistikk)Google Scholar
  30. 30.
    Yano CA, Lee HL (1995) Lot sizing with random yields: a review. Oper Res 43:311–334CrossRefzbMATHGoogle Scholar
  31. 31.
    Wanke PF, Saliby E (2009) Consolidation effects: whether and how inventories should be pooled. Transp Res Part E Logist Transp Rev 45:678–692CrossRefGoogle Scholar
  32. 32.
    Oskarsson B, Aronsson H, Ekdahl B (2013) Modern logistik: för ökad lönsamhet. Liber, The HagueGoogle Scholar
  33. 33.
    Maister DH (1976) Centralisation of inventories and the “square root law”. Int J Phys Distrib 6:124–134CrossRefGoogle Scholar
  34. 34.
    Erlebacher SJ, Meller RD (2000) The interaction of location and inventory in designing distribution systems. IIE Trans Inst Ind Eng 32(2):155–166.  https://doi.org/10.1080/07408170008963888 Google Scholar
  35. 35.
    Miranda PA, Garrido RA (2004) Incorporating inventory control decisions into a strategic distribution network design model with stochastic demand. Transp Res Part E Logist Transp Rev 40(3):183–207.  https://doi.org/10.1016/j.tre.2003.08.006 CrossRefGoogle Scholar
  36. 36.
    Ozsen L, Coullard CR, Daskin MS (2008) Capacitated warehouse location model with risk pooling. Nav Res Logist 55 (4):295–312.  https://doi.org/10.1002/nav.20282 MathSciNetCrossRefzbMATHGoogle Scholar
  37. 37.
    Fleischmann B (2016) The impact of the number of parallel warehouses on total inventory. OR Spectr 38(4):899–920.  https://doi.org/10.1007/s00291-016-0442-2 MathSciNetCrossRefzbMATHGoogle Scholar
  38. 38.
    Stulman A (1987) Benefits of centralized stocking for the multi-centre newsboy problem with first come, first served allocation. J Oper Res Soc 38(9):827–832.  https://doi.org/10.2307/2582323 MathSciNetCrossRefzbMATHGoogle Scholar
  39. 39.
    Ballou RH (2011) Expressing inventory control policy in the turnover curve. J Bus Logist 26(2):143–164.  https://doi.org/10.1002/j.2158-1592.2005.tb00209.x CrossRefGoogle Scholar
  40. 40.
    Shapiro JF, Wagner SN (2009) Strategic inventory optimization. J Bus Logist 30:161–173CrossRefGoogle Scholar
  41. 41.
    Tempelmeier H (2011) Inventory management in supply networks: problems, models, solutions, vol 2. Aufl. Books on Demand, NorderstedtGoogle Scholar
  42. 42.
    Christiansen B (ed) (2015) Handbook of research on global supply chain management. IGI Global, PennsylvaniaGoogle Scholar
  43. 43.
    Ronen D, Zinn W, Levy M, Bowersox DJ (1990) Inventory centralization/decentralization—the’square root. J Bus Logist 11(2):129Google Scholar
  44. 44.
    Evers PT (1995) Expanding the square root law: an analysis of both safety and cycle stocks. Logist Transp Rev 31(1):1–20Google Scholar
  45. 45.
    Pedersen SG (2010) Centralization vs de-centralization of warehousing: a small and medium-sized enterprise perspective. In: Proceedings 22nd Annu. Nofoma Conf. Syddansk Universitet, Institut for Entreprenørskab og RelationsledelseGoogle Scholar
  46. 46.
    Chandler AD (1962) Strategy and structure: chapters in the history of the industrial enterprise. MIT Press, CambridgeGoogle Scholar
  47. 47.
    Axsäer S (2005) A simple decision rule for decentralized two-echelon inventory control. Int J Prod Econ 93:53–59CrossRefGoogle Scholar
  48. 48.
    Wagner SM, Jönke R, Eisingerich AB (2012) A strategic framework for spare parts logistics. Calif Manag Rev 54(4):69–92.  https://doi.org/10.1525/cmr.2012.54.4.69 CrossRefGoogle Scholar
  49. 49.
  50. 50.
    Fisher M (1997) What is the right supply chain for your product? Harv Bus Rev 75(2):105–117Google Scholar
  51. 51.
    Beer S (2001) Food supply chain management: issues for the hospitality and retail sectors. Butterworth-Heinemann, OxfordGoogle Scholar
  52. 52.
    Maloni MJ, Brown ME (2006) Corporate social responsibility in the supply chain: an application in the food industry. J Bus Ethics 68:35–52CrossRefGoogle Scholar
  53. 53.
    Akkerman R, Van Der Meer D, Van Donk DP (2010) Make to stock and mix to order: choosing intermediate products in the food-processing industry. Int J Prod Res 48:3475–3492CrossRefzbMATHGoogle Scholar
  54. 54.
    Liang C-C (2013) Smart inventory management system of food-processing-and-distribution industry. Proced Comput Sci 17:373–378CrossRefGoogle Scholar
  55. 55.
    Kranenburg AA, Van Houtum GJ (2007) Effect of commonality on spare parts provisioning costs for capital goods. Int J Prod Econ 108:221–227CrossRefGoogle Scholar
  56. 56.
    Kärkkäinen M (2003) Increasing efficiency in the supply chain for short shelf life goods using RFID tagging. Int J Retail Distrib Manag 31:529–536CrossRefGoogle Scholar
  57. 57.
    Wacker J (1998) A definition of theory: research guidelines for different theory-building research methods in operations management. J Oper Manag 16:361–385CrossRefGoogle Scholar
  58. 58.
    Voss C, Tsikriktsis N, Frohlich M (2002) Case research in operations management. Int J Oper Prod Manag 22(2):195–219.  https://doi.org/10.1108/01443570210414329 CrossRefGoogle Scholar
  59. 59.
    Yin RK (2003) Case study research: design and methods. Sage Publications, Thousand OaksGoogle Scholar
  60. 60.
    Vissak T (2010) Recommendations for using the case study method in international business research. Qual Rep 15:370–388Google Scholar
  61. 61.
    Hilmola O-P, Hejazi A, Ojala L (2005) Supply chain management research using case studies: a literature analysis. Int J Integr Supply Manag 1:294CrossRefGoogle Scholar
  62. 62.
    Yin RK (1994) Case study research: design and methods. Sage Publications, Thousand OaksGoogle Scholar
  63. 63.
    Frankel R, Naslund D, Bolumole Y (2005) The “white space” of logistics research: a look at the role of methods usage. J Bus Logist 26:185–209CrossRefGoogle Scholar
  64. 64.
    Thomas DR (2006) A general inductive approach for analyzing qualitative evaluation data. Am J Eval 27:237–246CrossRefGoogle Scholar
  65. 65.
    Cross N (2008) Engineering design methods. Wiley, United States, pp xii, 217 sGoogle Scholar
  66. 66.
    Hansen ZNL, Larsen SB, Nielsen AP, Groth A, Gregersen NG, Ghosh A (2018) Combining or separating forward and reverse logistics. Int J Logist Manag 29:216–236CrossRefGoogle Scholar
  67. 67.
    Gregersen N, Herbert-Hansen ZNL (2018) Inventory centralization decision framework for spare parts. Prod Eng 12(3–4):353–365.  https://doi.org/10.1007/s11740-018-0814-3 CrossRefGoogle Scholar

Copyright information

© German Academic Society for Production Engineering (WGP) 2019

Authors and Affiliations

  1. 1.Implement Consulting GroupHellerupDenmark
  2. 2.The Danish National ArchivesCopenhagenDenmark
  3. 3.Technical University of DenmarkLyngbyDenmark
  4. 4.Mechanical DepartmentTechnical University of DenmarkLyngbyDenmark

Personalised recommendations