Investigating the impact of e-business on supply chain collaboration in the German automotive industry

Frank Weingarten, Paul Humphreys, Alan McKittrick, Brian Fynes

Research output: Contribution to journalArticle

54 Citations (Scopus)

Abstract

Purpose – The internet and web-based technologies have enabled the integration of information systems across organisational boundaries in ways that were hitherto impossible. The measurement of e-business (EB) value has been traditionally considered as a single construct. However, the desire to develop a comprehensive understanding of the impact of EB applications from a theoretical perspective has resulted in the modelling of multiple EB constructs. The impact of EB enabled collaboration on operational performance was also investigated. The purpose of this paper is to explore the enabling role of multiple dimensions of EB investigating if all EB applications impact directly and positively on supply chain collaboration. Design/methodology/approach – A web-based survey was carried out to collect data within the German automotive industry. Structural equation modelling was conducted to test the measurement and structural model. Findings – The results provide justification for the modelling of EB in multiple dimensions. Furthermore, some EB applications impacted positively on supply chain collaboration whilst some did not. The results also proved that EB enabled collaboration impacted directly and positively on the multiple dimensions of operational performance tested. Practical implications – EB applications cannot be viewed by practising managers as being universally beneficial in improving collaboration across a buyer-supplier boundary. However, the results reveal that, by carefully selecting the most appropriate EB applications, operations improvement benefits can be realised across a range of operational metrics due to enhanced supply chain collaboration. Originality/value – The deconstruction of EB into multiple constructs will enable the measurement of EB value to be more accurately assessed. Furthermore, the direct impact of EB-enabled collaboration to facilitate interaction and integration and its impact on operational performance adds to the body of knowledge within the larger research field of supply chain collaboration.
LanguageEnglish
Pages25-48
JournalInternational Journal of Operations & Production Management
Volume33
Issue number1
DOIs
Publication statusPublished - 9 Jan 2013

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Automotive industry
Supply chains
Industry
Supply chain collaboration
Electronic business
Information systems
Managers
Internet

Cite this

@article{58ce5effc9414254be9066a76229441b,
title = "Investigating the impact of e-business on supply chain collaboration in the German automotive industry",
abstract = "Purpose – The internet and web-based technologies have enabled the integration of information systems across organisational boundaries in ways that were hitherto impossible. The measurement of e-business (EB) value has been traditionally considered as a single construct. However, the desire to develop a comprehensive understanding of the impact of EB applications from a theoretical perspective has resulted in the modelling of multiple EB constructs. The impact of EB enabled collaboration on operational performance was also investigated. The purpose of this paper is to explore the enabling role of multiple dimensions of EB investigating if all EB applications impact directly and positively on supply chain collaboration. Design/methodology/approach – A web-based survey was carried out to collect data within the German automotive industry. Structural equation modelling was conducted to test the measurement and structural model. Findings – The results provide justification for the modelling of EB in multiple dimensions. Furthermore, some EB applications impacted positively on supply chain collaboration whilst some did not. The results also proved that EB enabled collaboration impacted directly and positively on the multiple dimensions of operational performance tested. Practical implications – EB applications cannot be viewed by practising managers as being universally beneficial in improving collaboration across a buyer-supplier boundary. However, the results reveal that, by carefully selecting the most appropriate EB applications, operations improvement benefits can be realised across a range of operational metrics due to enhanced supply chain collaboration. Originality/value – The deconstruction of EB into multiple constructs will enable the measurement of EB value to be more accurately assessed. Furthermore, the direct impact of EB-enabled collaboration to facilitate interaction and integration and its impact on operational performance adds to the body of knowledge within the larger research field of supply chain collaboration.",
author = "Frank Weingarten and Paul Humphreys and Alan McKittrick and Brian Fynes",
note = "Reference text: Anderson, J.C. and Gerbing, D.W. (1988), “Structural equation modeling in practice: a review and recommended two-step approach”, Psychological Bulletin, Vol. 103 No. 3, pp. 411-23. Armstrong, J.S. and Overton, T.S. (1977), “Estimating nonresponse bias in mail surveys”, Journal of Marketing Research, Vol. 14 No. 3, pp. 396-402. Arshinder, A.K. and Deshmukh, S.G. (2008), “Supply chain coordination: perspectives, empirical studies and research directions”, International Journal of Production Economics, Vol. 115 No. 2, pp. 316-35. Bakker, E., Zheng, J., Knight, L. and Harland, C. (2008), “Putting e-commerce adoption in a supply chain context”, International Journal of Operations & Production Management, Vol. 28 No. 4, pp. 313-30. Bakos, Y. and Katsamakas, E. (2008), “Design and ownership of two-sided networks: implications for internet platforms”, Journal of Management Information Systems, Vol. 25 No. 2, pp. 171-202. Banker, R.D., Barhan, I.R., Chang, H. and Lin, S. (2006), “Plant information systems, manufacturing capabilities, and plant performance”, MIS Quarterly, Vol. 30 No. 2, pp. 315-37. Barua, A., Konana, P., Whinston, A.B. and Yin, F. (2004), “An empirical investigation of net-enabled business value”, MIS Quarterly, Vol. 28 No. 4, pp. 585-620. Bollen, K.A. (1989), Structural Equations with Latent Variables, Wiley, New York, NY. Boone, T. and Ganeshan, R. (2007), “The frontiers of e-business technology and supply chains”, Journal of Operations Management, Vol. 25 No. 6, pp. 1195-8. Byrne, B. (1998), Structural Equation Modelling with Lisrel, Prelis, and Simplis: Basic Concepts, Applications, and Programming, Lawrence Erlbaum Associates, London. Cannon, J.P. and Perreault, W.D. Jr (1999), “Buyer-seller relationships in business markets”, Journal of Marketing Research, Vol. 36 No. 4, pp. 439-60. Cao, M. and Zhang, Q. (2011), “Supply chain collaboration: impact on collaborative advantage and performance”, Journal of Operations Management, Vol. 29 No. 3, pp. 163-80. Chen, I.J. and Paulraj, A. (2004), “Towards a theory of supply chain management: the constructs and measurements”, Journal of Operations Management, Vol. 22 No. 2, pp. 119-50. Impact of e-business applications 41 Chen, I.J., Paulraj, A. and Lado, A.A. (2004), “Strategic purchasing, supply management, and firm performance”, Journal of Operations Management, Vol. 22 No. 5, pp. 505-23. Chidambaram, L. (1996), “Relational development in computer-supported groups”, MIS Quarterly, June, pp. 143-65. Da Silveira, G.J.C. and Cagliano, R. (2006), “The relationship between inter-organizational information systems and operations performance”, International Journal of Operations & Production Management, Vol. 26 No. 3, pp. 232-53. Das, A., Narasimhan, R. and Talluri, S. (2006), “Supplier integration – finding an optimal configuration”, Journal of Operations Management, Vol. 24 No. 5, pp. 563-82. De Toni, A. and Tonchia, S. (2001), “Performance measurement systems models, characteristics and measures”, International Journal of Operations & Production Management, Vol. 21 Nos 2/1, pp. 46-70. Deloitte Research (2002), Directions in Collaborative Commerce: Managing the Extended Enterprise, available at: www.deloitte.com/dtt/cda/doc/content/DTT_DR_DirectionsCC. pdf (accessed 17 June 2009). Devaraj, S., Krajewski, L. and Wei, J.C. (2007), “Impact of e-business technologies on operational performance: the role of production information integration in the supply chain”, Journal of Operations Management, Vol. 25 No. 6, pp. 1199-216. Dillman, D. (2000), Mail and Internet Surveys: The Tailored Design Method, Wiley, New York, NY. Dyer, J. and Singh, H. (1998), “The relational view: cooperative strategy and sources of interorganizational competitive advantage”, Academy of Management Review, Vol. 23 No. 4, pp. 660-79. Faems, D., Looy, B. and Debakere, K. (2005), “Interorganisational collaboration and innovation: toward a portfolio approach”, The Journal of Product Innovation Management, Vol. 22 No. 3, pp. 238-50. Froehle, C.M. and Roth, A.V. (2004), “New measurement scales for evaluating perceptions of the technology-mediated customer service experience”, Journal of Operations Management, Vol. 22 No. 1, pp. 1-21. Frohlich, M.T. and Westbrook, R. (2001), “Arcs of integration: an international study of supply chain strategies”, Journal of Operations Management, Vol. 19 No. 2, pp. 185-200. Gerbing, D.W. and Anderson, J.C. (1992), “Monte Carlo evaluations of goodness of fit indices for structural equation models”, Sociological Methods and Research, Vol. 21 No. 2, pp. 132-60. Gerbing, D.W., Hamilton, J.G. and Freeman, E.B. (1994), “A large-scale second-order structural equation model of influence of management participation on organizational planning benefits”, Journal of Management, Vol. 20 No. 4, pp. 859-85. Handley, S.M. and Benton, W.C. Jr (2009), “Unlocking the business outsourcing process model”, Journal of Operations Management, Vol. 27 No. 5, pp. 344-61. Hu, L. and Bentler, P.M. (1999), “Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives”, Structural Equation Modelling, Vol. 6 No. 1, pp. 1-55. Jeffers, P.I., Muhanna, W.A. and Nault, B.R. (2008), “Information technology and process performance: an empirical investigation of the interaction between IT and non-IT resources”, Decision Sciences, Vol. 39 No. 4, pp. 703-35. Johnson, D., Allen, B. and Crum, M. (1992), “The state of EDI usage in the motor carrier industry”, Journal of Business Logistics, Vol. 13 No. 2, pp. 43-68. IJOPM 33,1 42 Johnson, P.F., Klassen, R.D., Leenders, M.R. and Awaysheh, A. (2007), “Utilizing e-business in supply chains: the impact of firm characteristics and teams”, Journal of Operations Management, Vol. 25 No. 6, pp. 1255-74. Kahn, K.B. and Mentzer, J.T. (1996), “Logistics and interdepartmental integration”, International Journal of Physical Distribution and Logistics Management, Vol. 26 No. 8, pp. 6-14. Kent, J.L. and Mentzer, J.T. (2003), “The effect of investment in interorganizational information technology in a retail supply chain”, Journal of Business Logistics, Vol. 24 No. 2, pp. 155-75. Kohli, R. and Grover, V. (2008), “Business value of IT: an essay on expanding research directions to keep up with the times”, Journal of the Association for Information Systems, Vol. 9 No. 1, pp. 23-39. Kroll, J. and Kroll, B. (2005/2006), Taschenbuch der Automobilwirtschaft 2005/2006, Dekra, Stuttgart. Lambert, D.M. and Harrington, T.C. (1990), “Measuring nonresponse bias in customer service mail surveys”, Journal of Business Logistics, Vol. 11 No. 2, pp. 5-25. Lee, H.L., Padmanabhan, V. and Whang, S. (1997), “Information distortion in a supply chain: the bullwhip effect”, Management Science, Vol. 43 No. 4, pp. 546-58. Li, S., Rao, S.S., Ragu-Nathan, T.S. and Ragu-Nathan, B. (2005), “Development and validation of a measurement instrument for studying supply chain management practices”, Journal of Operations Management, Vol. 23 No. 6, pp. 618-41. MacCallum, R.C., Browne, M.W. and Sugawara, H.M. (1996), “Power analysis and determination of sample size for covariance structure models: practical issues”, Psychological Methods, Vol. 1 No. 1, pp. 130-49. MacKay, D.R. (1993), “The impact of EDI on the components sector of the Australian automotive industry”, Journal of Strategic Information Systems, Vol. 2 No. 3, pp. 243-63. Massetti, B. and Zmud, R.W. 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Investigating the impact of e-business on supply chain collaboration in the German automotive industry. / Weingarten, Frank; Humphreys, Paul; McKittrick, Alan; Fynes, Brian.

Vol. 33, No. 1, 09.01.2013, p. 25-48.

Research output: Contribution to journalArticle

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T1 - Investigating the impact of e-business on supply chain collaboration in the German automotive industry

AU - Weingarten, Frank

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N1 - Reference text: Anderson, J.C. and Gerbing, D.W. (1988), “Structural equation modeling in practice: a review and recommended two-step approach”, Psychological Bulletin, Vol. 103 No. 3, pp. 411-23. Armstrong, J.S. and Overton, T.S. (1977), “Estimating nonresponse bias in mail surveys”, Journal of Marketing Research, Vol. 14 No. 3, pp. 396-402. Arshinder, A.K. and Deshmukh, S.G. (2008), “Supply chain coordination: perspectives, empirical studies and research directions”, International Journal of Production Economics, Vol. 115 No. 2, pp. 316-35. Bakker, E., Zheng, J., Knight, L. and Harland, C. (2008), “Putting e-commerce adoption in a supply chain context”, International Journal of Operations & Production Management, Vol. 28 No. 4, pp. 313-30. Bakos, Y. and Katsamakas, E. (2008), “Design and ownership of two-sided networks: implications for internet platforms”, Journal of Management Information Systems, Vol. 25 No. 2, pp. 171-202. Banker, R.D., Barhan, I.R., Chang, H. and Lin, S. (2006), “Plant information systems, manufacturing capabilities, and plant performance”, MIS Quarterly, Vol. 30 No. 2, pp. 315-37. Barua, A., Konana, P., Whinston, A.B. and Yin, F. (2004), “An empirical investigation of net-enabled business value”, MIS Quarterly, Vol. 28 No. 4, pp. 585-620. Bollen, K.A. (1989), Structural Equations with Latent Variables, Wiley, New York, NY. Boone, T. and Ganeshan, R. (2007), “The frontiers of e-business technology and supply chains”, Journal of Operations Management, Vol. 25 No. 6, pp. 1195-8. Byrne, B. (1998), Structural Equation Modelling with Lisrel, Prelis, and Simplis: Basic Concepts, Applications, and Programming, Lawrence Erlbaum Associates, London. Cannon, J.P. and Perreault, W.D. Jr (1999), “Buyer-seller relationships in business markets”, Journal of Marketing Research, Vol. 36 No. 4, pp. 439-60. Cao, M. and Zhang, Q. (2011), “Supply chain collaboration: impact on collaborative advantage and performance”, Journal of Operations Management, Vol. 29 No. 3, pp. 163-80. Chen, I.J. and Paulraj, A. (2004), “Towards a theory of supply chain management: the constructs and measurements”, Journal of Operations Management, Vol. 22 No. 2, pp. 119-50. Impact of e-business applications 41 Chen, I.J., Paulraj, A. and Lado, A.A. (2004), “Strategic purchasing, supply management, and firm performance”, Journal of Operations Management, Vol. 22 No. 5, pp. 505-23. Chidambaram, L. (1996), “Relational development in computer-supported groups”, MIS Quarterly, June, pp. 143-65. Da Silveira, G.J.C. and Cagliano, R. (2006), “The relationship between inter-organizational information systems and operations performance”, International Journal of Operations & Production Management, Vol. 26 No. 3, pp. 232-53. Das, A., Narasimhan, R. and Talluri, S. (2006), “Supplier integration – finding an optimal configuration”, Journal of Operations Management, Vol. 24 No. 5, pp. 563-82. De Toni, A. and Tonchia, S. (2001), “Performance measurement systems models, characteristics and measures”, International Journal of Operations & Production Management, Vol. 21 Nos 2/1, pp. 46-70. Deloitte Research (2002), Directions in Collaborative Commerce: Managing the Extended Enterprise, available at: www.deloitte.com/dtt/cda/doc/content/DTT_DR_DirectionsCC. pdf (accessed 17 June 2009). Devaraj, S., Krajewski, L. and Wei, J.C. (2007), “Impact of e-business technologies on operational performance: the role of production information integration in the supply chain”, Journal of Operations Management, Vol. 25 No. 6, pp. 1199-216. Dillman, D. (2000), Mail and Internet Surveys: The Tailored Design Method, Wiley, New York, NY. Dyer, J. and Singh, H. (1998), “The relational view: cooperative strategy and sources of interorganizational competitive advantage”, Academy of Management Review, Vol. 23 No. 4, pp. 660-79. Faems, D., Looy, B. and Debakere, K. (2005), “Interorganisational collaboration and innovation: toward a portfolio approach”, The Journal of Product Innovation Management, Vol. 22 No. 3, pp. 238-50. Froehle, C.M. and Roth, A.V. (2004), “New measurement scales for evaluating perceptions of the technology-mediated customer service experience”, Journal of Operations Management, Vol. 22 No. 1, pp. 1-21. Frohlich, M.T. and Westbrook, R. (2001), “Arcs of integration: an international study of supply chain strategies”, Journal of Operations Management, Vol. 19 No. 2, pp. 185-200. Gerbing, D.W. and Anderson, J.C. (1992), “Monte Carlo evaluations of goodness of fit indices for structural equation models”, Sociological Methods and Research, Vol. 21 No. 2, pp. 132-60. Gerbing, D.W., Hamilton, J.G. and Freeman, E.B. (1994), “A large-scale second-order structural equation model of influence of management participation on organizational planning benefits”, Journal of Management, Vol. 20 No. 4, pp. 859-85. Handley, S.M. and Benton, W.C. Jr (2009), “Unlocking the business outsourcing process model”, Journal of Operations Management, Vol. 27 No. 5, pp. 344-61. Hu, L. and Bentler, P.M. (1999), “Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives”, Structural Equation Modelling, Vol. 6 No. 1, pp. 1-55. Jeffers, P.I., Muhanna, W.A. and Nault, B.R. (2008), “Information technology and process performance: an empirical investigation of the interaction between IT and non-IT resources”, Decision Sciences, Vol. 39 No. 4, pp. 703-35. Johnson, D., Allen, B. and Crum, M. (1992), “The state of EDI usage in the motor carrier industry”, Journal of Business Logistics, Vol. 13 No. 2, pp. 43-68. IJOPM 33,1 42 Johnson, P.F., Klassen, R.D., Leenders, M.R. and Awaysheh, A. (2007), “Utilizing e-business in supply chains: the impact of firm characteristics and teams”, Journal of Operations Management, Vol. 25 No. 6, pp. 1255-74. Kahn, K.B. and Mentzer, J.T. (1996), “Logistics and interdepartmental integration”, International Journal of Physical Distribution and Logistics Management, Vol. 26 No. 8, pp. 6-14. Kent, J.L. and Mentzer, J.T. (2003), “The effect of investment in interorganizational information technology in a retail supply chain”, Journal of Business Logistics, Vol. 24 No. 2, pp. 155-75. Kohli, R. and Grover, V. (2008), “Business value of IT: an essay on expanding research directions to keep up with the times”, Journal of the Association for Information Systems, Vol. 9 No. 1, pp. 23-39. Kroll, J. and Kroll, B. (2005/2006), Taschenbuch der Automobilwirtschaft 2005/2006, Dekra, Stuttgart. Lambert, D.M. and Harrington, T.C. (1990), “Measuring nonresponse bias in customer service mail surveys”, Journal of Business Logistics, Vol. 11 No. 2, pp. 5-25. Lee, H.L., Padmanabhan, V. and Whang, S. (1997), “Information distortion in a supply chain: the bullwhip effect”, Management Science, Vol. 43 No. 4, pp. 546-58. Li, S., Rao, S.S., Ragu-Nathan, T.S. and Ragu-Nathan, B. (2005), “Development and validation of a measurement instrument for studying supply chain management practices”, Journal of Operations Management, Vol. 23 No. 6, pp. 618-41. MacCallum, R.C., Browne, M.W. and Sugawara, H.M. (1996), “Power analysis and determination of sample size for covariance structure models: practical issues”, Psychological Methods, Vol. 1 No. 1, pp. 130-49. MacKay, D.R. (1993), “The impact of EDI on the components sector of the Australian automotive industry”, Journal of Strategic Information Systems, Vol. 2 No. 3, pp. 243-63. Massetti, B. and Zmud, R.W. 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PY - 2013/1/9

Y1 - 2013/1/9

N2 - Purpose – The internet and web-based technologies have enabled the integration of information systems across organisational boundaries in ways that were hitherto impossible. The measurement of e-business (EB) value has been traditionally considered as a single construct. However, the desire to develop a comprehensive understanding of the impact of EB applications from a theoretical perspective has resulted in the modelling of multiple EB constructs. The impact of EB enabled collaboration on operational performance was also investigated. The purpose of this paper is to explore the enabling role of multiple dimensions of EB investigating if all EB applications impact directly and positively on supply chain collaboration. Design/methodology/approach – A web-based survey was carried out to collect data within the German automotive industry. Structural equation modelling was conducted to test the measurement and structural model. Findings – The results provide justification for the modelling of EB in multiple dimensions. Furthermore, some EB applications impacted positively on supply chain collaboration whilst some did not. The results also proved that EB enabled collaboration impacted directly and positively on the multiple dimensions of operational performance tested. Practical implications – EB applications cannot be viewed by practising managers as being universally beneficial in improving collaboration across a buyer-supplier boundary. However, the results reveal that, by carefully selecting the most appropriate EB applications, operations improvement benefits can be realised across a range of operational metrics due to enhanced supply chain collaboration. Originality/value – The deconstruction of EB into multiple constructs will enable the measurement of EB value to be more accurately assessed. Furthermore, the direct impact of EB-enabled collaboration to facilitate interaction and integration and its impact on operational performance adds to the body of knowledge within the larger research field of supply chain collaboration.

AB - Purpose – The internet and web-based technologies have enabled the integration of information systems across organisational boundaries in ways that were hitherto impossible. The measurement of e-business (EB) value has been traditionally considered as a single construct. However, the desire to develop a comprehensive understanding of the impact of EB applications from a theoretical perspective has resulted in the modelling of multiple EB constructs. The impact of EB enabled collaboration on operational performance was also investigated. The purpose of this paper is to explore the enabling role of multiple dimensions of EB investigating if all EB applications impact directly and positively on supply chain collaboration. Design/methodology/approach – A web-based survey was carried out to collect data within the German automotive industry. Structural equation modelling was conducted to test the measurement and structural model. Findings – The results provide justification for the modelling of EB in multiple dimensions. Furthermore, some EB applications impacted positively on supply chain collaboration whilst some did not. The results also proved that EB enabled collaboration impacted directly and positively on the multiple dimensions of operational performance tested. Practical implications – EB applications cannot be viewed by practising managers as being universally beneficial in improving collaboration across a buyer-supplier boundary. However, the results reveal that, by carefully selecting the most appropriate EB applications, operations improvement benefits can be realised across a range of operational metrics due to enhanced supply chain collaboration. Originality/value – The deconstruction of EB into multiple constructs will enable the measurement of EB value to be more accurately assessed. Furthermore, the direct impact of EB-enabled collaboration to facilitate interaction and integration and its impact on operational performance adds to the body of knowledge within the larger research field of supply chain collaboration.

U2 - 10.1108/01443571311288039

DO - 10.1108/01443571311288039

M3 - Article

VL - 33

SP - 25

EP - 48

IS - 1

ER -