Advertisement

The impact of big data on world-class sustainable manufacturing

  • Rameshwar Dubey
  • Angappa GunasekaranEmail author
  • Stephen J. Childe
  • Samuel Fosso Wamba
  • Thanos Papadopoulos
ORIGINAL ARTICLE

Abstract

Big data (BD) has attracted increasing attention from both academics and practitioners. This paper aims at illustrating the role of big data analytics in supporting world-class sustainable manufacturing (WCSM). Using an extensive literature review to identify different factors that enable the achievement of WCSM through BD and 405 usable responses from senior managers gathered through social networking sites (SNS), we propose a conceptual framework using constructs obtained using reduction of gathered data that summarizes this role; test this framework using data which is heterogeneous, diverse, voluminous, and possess high velocity; and highlight the importance for academia and practice. Finally, we conclude our research findings and further outlined future research directions.

Keywords

Big data World class sustainable manufacturing Social networking site Confirmatory factor analysis Sustainable manufacturing 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Fawcett SE, Waller MA (2014) Supply chain game changers—mega, nano, and virtual trends—and forces that impede supply chain design (ie, building a winning team). J Bus Logist 35(3):157–164CrossRefGoogle Scholar
  2. 2.
    Accenture (2013) The role of big data and analytics in the developing world. Report, available at: http://www.accenture.com/SiteCollectionDocuments/PDF/Accenture-ADP-Role-Big-Data-And-Analytics-Developing-World.pdf. Accessed on 8 June 2015
  3. 3.
    Wamba SF, Akter S, Edwards A, Chopin G, Gnanzou D (2015) How ‘big data’ can make big impact: findings from a systematic review and a longitudinal case study. Int J Prod Econ. doi: 10.1016/j.ijpe.2014.12.031 Google Scholar
  4. 4.
    Perrey J, Spillecke D, Umblijs A (2013) Smart analytics: how marketing drives short-term and long-term growth. McKinsey Quarterly, July, 2013 (http://www.mckinsey.com/client_service/marketing_and_sales/latest_thinking/big_data_analytics_and_the_future_of_marketing_and_sales). Accessed on 14 Dec 2014
  5. 5.
    Manyika J, Chui M, Brown B, Bughin J, Dobbs R, Roxburgh C, Byers AH (2011) Big data: the next frontier for innovation, competition, and productivityGoogle Scholar
  6. 6.
    McAfee A, Brynjolfsson E, Davenport TH, Patil DJ, Barton D (2012) Big data: the management revolution. Harv Bus Rev 90(10):61–67Google Scholar
  7. 7.
    Chen H, Chiang RH, Storey VC (2012) Business intelligence and analytics: from big data to big impact. MIS Q 36(4):1165–1188Google Scholar
  8. 8.
    Hayes RH, Wheelwright SC (1984) Restoring our competitive edge: competing through manufacturing, vol 8. Wiley, New YorkGoogle Scholar
  9. 9.
    Flynn BB, Schroeder RG, Flynn EJ (1999) World class manufacturing: an investigation of Hayes and Wheelwright’s foundation. J Oper Manag 17(3):249–269CrossRefGoogle Scholar
  10. 10.
    Keeso A (2014) Big data and environmental sustainability: a conversation starter. Smith School Working paper series.Working paper 14–04 (http://www.smithschool.ox.ac.uk/library/working-papers/workingpaper%2014-04.pdf). Accessed 7 May 2015
  11. 11.
    Fan J, Han F, Liu H (2014) Challenges of big data analysis. Nat Sci Rev 1(2):293–314CrossRefGoogle Scholar
  12. 12.
    Bughin J, Chui M, Manyika J (2010) Clouds, big data, and smart assets: ten tech-enabled business trends to watch. McKinsey Q 56(1):75–86Google Scholar
  13. 13.
    Mayer-Schönberger V, Cukier K (2013) Big data: a revolution that will transform how we live, work, and think. Houghton Mifflin Harcourt, New YorkGoogle Scholar
  14. 14.
    Dijcks J-P (2013) Oracle: big data for the enterprise. Redwood Shores, OracleGoogle Scholar
  15. 15.
    White M (2012) Digital workplaces: vision and reality. Bus Inf Rev 29(4):205–214CrossRefGoogle Scholar
  16. 16.
    Forrester (2012) The big deal about big data for customer engagement business: leaders must lead big data initiatives to derive value. Available: http://www.forrester.com/The+Big+Deal+About+Big+Data+For+Customer+Engagement/fulltext/-/E-RES72241. Accessed 5 June 2015
  17. 17.
    Boyd D, Crawford K (2012) Critical questions for big data: provocations for a cultural, technological, and scholarly phenomenon. Inf Commun Soc 15(5):662–679CrossRefGoogle Scholar
  18. 18.
    Mark AB, Laney D (2012) The importance of ‘big data’: a definition. Gartner, Jun, 21Google Scholar
  19. 19.
    McGahan A (2013) Unlocking the big promise of big data. Totman Manag 6(1):53–57Google Scholar
  20. 20.
    Sun EW, Chen YT, Yu MT (2015) Generalized optimal wavelet decomposing algorithm for big financial data. Int J Prod Econ. doi: 10.1016/j.ijpe.2014.12.033 Google Scholar
  21. 21.
    Gandomi A, Haider M (2015) Beyond the hype: big data concepts, methods, and analytics. Int J Inf Manag 35(2):137–144CrossRefGoogle Scholar
  22. 22.
    Davenport TH (2012) The human side of Big Data and high-performance analytics. International Institute for Analytics. pp 1–13Google Scholar
  23. 23.
    Jacobs A (2009) The pathologies of big data. Commun ACM 52(8):36CrossRefGoogle Scholar
  24. 24.
    Waller MA, Fawcett SE (2013) Data science, predictive analytics, and big data: a revolution that will transform supply chain design and management. J Bus Logist 34(2):77–84CrossRefGoogle Scholar
  25. 25.
    Bi Z, Cochran D (2014) Big data analytics with applications. J Manag Anal 1(4):249–265Google Scholar
  26. 26.
    Gong Q, Yang Y, Wang S (2014) Information and decision-making delays in MRP, KANBAN, and CONWIP. Int J Prod Econ 156:208–213CrossRefGoogle Scholar
  27. 27.
    Hazen BT, Boone CA, Ezell JD, Jones-Farmer LA (2014) Data quality for data science, predictive analytics, and big data in supply chain management: an introduction to the problem and suggestions for research and applications. Int J Prod Econ 154:72–80CrossRefGoogle Scholar
  28. 28.
    Chae BK (2015) Insights from hashtag #supplychain and Twitter Analytics: considering Twitter and Twitter data for supply chain practice and research. Int J Prod Econ 165:247–259CrossRefGoogle Scholar
  29. 29.
    Li J, Tao F, Cheng Y, Zhao L (2015) Big Data in product lifecycle management. Int J Adv Manuf Technol. 1-18.Google Scholar
  30. 30.
    Hall RW (1987) Attaining manufacturing excellence: just-in-time, total quality, total people involvement. Dow Jones-Irwin, HomewoodGoogle Scholar
  31. 31.
    Gunn TG (1987) Manufacturing for competitive advantage: becoming a world class manufacturer. Ballinger publishing company, BostonGoogle Scholar
  32. 32.
    Steudel HJ, Desruelle P (1992) Manufacturing in the ‘90s: how to become a mean, lean world-class competitor. Van Nostrand Reinhold CompanyGoogle Scholar
  33. 33.
    Roth AV, Giffi CA, Seal GM (1992) Operating strategies for the 1990s: elements comprising world-class manufacturing. In: Voss C (ed) Manufacturing strategy. Process and Content, Chapman & Hall, London, pp 133–165Google Scholar
  34. 34.
    Flynn BB, Schroeder RG, Flynn EJ, Sakakibara S, Bates KA (1997) World-class manufacturing project: overview and selected results. Int Oper Prod Manag 17(7):671–685CrossRefGoogle Scholar
  35. 35.
    Brown S, Squire B, Blackmon K (2007) The contribution of manufacturing strategy involvement and alignment to world-class manufacturing performance. Int J Oper Prod Manag 27(3):282–302CrossRefGoogle Scholar
  36. 36.
    Sharma M, Kodali R (2008) Development of a framework for manufacturing excellence. Meas Bus Excell 12(4):50–66CrossRefGoogle Scholar
  37. 37.
    Garetti M, Taisch M (2012) Sustainable manufacturing: trends and research challenges. Prod Plan Control 23(2-3):83–104CrossRefGoogle Scholar
  38. 38.
    Jovane F, Yoshikawa H, Alting L, Boër CR, Westkamper E, Williams D, Paci AM (2008) The incoming global technological and industrial revolution towards competitive sustainable manufacturing. CIRP Ann Manuf Technol 57(2):641–659CrossRefGoogle Scholar
  39. 39.
    Kaebernick H, Kara S, Sun M (2003) Sustainable product development and manufacturing by considering environmental requirements. Robot Comput Integr Manuf 19(6):461–468CrossRefGoogle Scholar
  40. 40.
    Kumaraguru S, Rachuri S, Lechevalier D (2014) Faceted classification of manufacturing processes for sustainability performance evaluation. Int J Adv Manuf Technol 75(9-12):1309–1320CrossRefGoogle Scholar
  41. 41.
    Le Bourhis F, Kerbrat O, Hascoët JY, Mognol P (2013) Sustainable manufacturing: evaluation and modeling of environmental impacts in additive manufacturing. Int J Adv Manuf Technol 69(9-12):1927–1939CrossRefGoogle Scholar
  42. 42.
    Young P, Byrne IG, Cotterell M (1997) Manufacturing and the environment. Int J Adv Manuf Technol 13(7):488–493CrossRefGoogle Scholar
  43. 43.
    Azzone G, Noci G (1998) Identifying effective PMSs for the deployment of “green” manufacturing strategies. Int J Oper Prod Manag 18(4):308–335CrossRefGoogle Scholar
  44. 44.
    Gunasekaran A, Spalanzani A (2012) “Sustainable of manufacturing services: investigation for research and applications”. Int J Prod Econ 140(1):35–47CrossRefGoogle Scholar
  45. 45.
    Noci G (1997) Designing ‘green’ vendor rating systems for the assessment of a supplier's environmental performance. Eur J Purch Supply Manag 3(2):103–114CrossRefGoogle Scholar
  46. 46.
    Sánchez AM, Pérez MP (2001) Lean indicators and manufacturing strategies. Int J Oper Prod Manag 21(11):1433–1452CrossRefGoogle Scholar
  47. 47.
    Flammer C (2013) Corporate social responsibility and shareholder reaction: the environmental awareness of investors. Acad Manag J 56(3):758–781CrossRefGoogle Scholar
  48. 48.
    Carter CR, Rogers DS (2008) A framework of sustainable supply chain management: moving toward new theory. Int J Phys Distrib Logist Manag 38(5):360–387CrossRefGoogle Scholar
  49. 49.
    Kannegiesser M, Günther HO (2014) Sustainable development of global supply chains—part 1: sustainability optimization framework. Flex Serv Manuf J 26(1-2):24–47CrossRefGoogle Scholar
  50. 50.
    Rusinko CA (2007) Green Manufacturing: an evaluation of environmentally sustainable manufacturing practices and their impact on competitive outcomes. IEEE Trans Eng Manag 54(3):445–454CrossRefGoogle Scholar
  51. 51.
    Molamohamadi Z, Ismail N (2013) Developing a new scheme for sustainable manufacturing. Int J Mater Mech Manuf 1(1):1–5Google Scholar
  52. 52.
    Prabhu VV, Jeon HW, Taisch M (2012) Modeling green factory physics—an analytical approach. In: Automation Science and Engineering (CASE), 2012 IEEE International Conference on (pp. 46-51). IEEEGoogle Scholar
  53. 53.
    Gunasekaran A, Irani Z, Papadopoulos T (2013) Modelling and analysis of sustainable operations management: certain investigations for research and applications. J Oper Res SocGoogle Scholar
  54. 54.
    Garbie IH (2013) DFSME: design for sustainable manufacturing enterprises (an economic viewpoint). Int J Prod Res 51(2):479–503CrossRefGoogle Scholar
  55. 55.
    Garbie IH (2014) An analytical technique to model and assess sustainable development index in manufacturing enterprises. Int J Prod Res 52(16):4876–4915CrossRefGoogle Scholar
  56. 56.
    Dubey R, Gunasekaran A, Chakrabarty A (2015) World-class sustainable manufacturing: framework and a performance measurement system. Int J Prod Res. doi: 10.1080/00207543.2015.1012603 Google Scholar
  57. 57.
    Despeisse M, Ball PD, Evans S, Levers A (2012) Industrial ecology at factory level—a conceptual model. J Clean Prod 31(3–4):30–39CrossRefGoogle Scholar
  58. 58.
    Opresnk D, Taisch M (2015) The value of Big Data in servitization. Int J Prod Econ 165:174–184CrossRefGoogle Scholar
  59. 59.
    Siaminwe L, Chinsembu K, Syakalima M (2005) Policy and operational constraints for the implementation of cleaner production. J Clean Prod 13:1037–1047CrossRefGoogle Scholar
  60. 60.
    Berkel V (2007) Cleaner production and eco-efficiency in Australian small firms. Int J Environ Technol Manag 7(5/6):672–693CrossRefGoogle Scholar
  61. 61.
    Deif AM (2011) A system model for green manufacturing. Int J Clean Prod 19(14):1553–1559CrossRefGoogle Scholar
  62. 62.
    Law KM, Gunasekaran A (2012) Sustainability development in high-tech manufacturing firms in Hong Kong: motivators and readiness. Int J Prod Econ 137(1):116–125CrossRefGoogle Scholar
  63. 63.
    Singh A, Singh B, Dhingra AK (2012) Drivers and barriers of green manufacturing practices: a survey of Indian industries. Int J Eng Sci 1(1):5–19Google Scholar
  64. 64.
    Dües CM, Tan KH, Lim M (2013) Green as the new Lean: how to use Lean practices as a catalyst to greening your supply chain. J Clean Prod 40:93–100CrossRefGoogle Scholar
  65. 65.
    van Hoof B, Lyon TP (2013) Cleaner production in small firms taking part in Mexico’s Sustainable Supplier Program. J Clean Prod 41:270–282CrossRefGoogle Scholar
  66. 66.
    Dutta D, Bose I (2015) Managing a big data project: the case of Ramco Cements limited. Int J Prod Econ. doi: 10.1016/j.ijpe.2014.12.032 Google Scholar
  67. 67.
    Zhu Q, Sarkis J, Geng Y (2005) Green supply chain management in China: pressure, practices and performance. Int J Oper Prod Manag 25(5):449–468CrossRefGoogle Scholar
  68. 68.
    Tsoulfas GT, Pappis CP (2006) Environmental principles applicable to supply chains design and operation. J Clean Prod 14(1):1593–1602CrossRefGoogle Scholar
  69. 69.
    Sarkis J, Zhu Q, Lai K (2011) An organizational theoretic review of green supply chain management literature. Int J Prod Econ 130(1):1–15CrossRefGoogle Scholar
  70. 70.
    Bierma TJ, Wasterstraat FL (1999) Cleaner production from chemical suppliers: understanding shared savings contracts. J Clean Prod 7(2):145–158CrossRefGoogle Scholar
  71. 71.
    Vachon S, Klassen RD (2006) Green project partnership in the supply chain: the case of the package printing industry. J Clean Prod 14(6/7):661–671CrossRefGoogle Scholar
  72. 72.
    Hsu CW, Hu AH (2009) Applying hazardous substance management to supplier selection using analytic network process. J Clean Prod 17(2):255–264CrossRefGoogle Scholar
  73. 73.
    Bai C, Sarkis J (2010) Greener supplier development: analytical evaluation using rough set theory. J Clean Prod 17(2):255–264Google Scholar
  74. 74.
    Ku CY, Chang CT, Ho HP (2010) Global supplier selection using fuzzy analytic hierarchy process and fuzzy goal programming. Qual Quant 44(4):623–640CrossRefGoogle Scholar
  75. 75.
    Testa F, Iraldo F (2010) Shadows and lights of GSCM (green supply chain management): determinants and efects of these practices based on a multinational study. J Clean Prod 18(10/11):953–962CrossRefGoogle Scholar
  76. 76.
    Atlas M, Florida R (1998) “Green Manufacturing.” In: R. Dorf (ed) Handbook of technology management. CRC PressGoogle Scholar
  77. 77.
    Chien MK, Shih LH (2007) An empirical study of the implementation of green supply chain management practices in the electrical and electronic industry and their relation to organizational performances. Int J Environ Sci Technol 4(3):383–394Google Scholar
  78. 78.
    Hsu CW, Hu AH (2008) Green supply chain management in the electronic industry. Int J Sci Technol 5(2):205–216CrossRefGoogle Scholar
  79. 79.
    Luthra S, Kumar V, Kumar S, Haleem A (2011) Barriers to implement green supply chain management in automobile industry using interpretive structural modeling technique: an Indian perspective. J Ind Eng Manag 4(2):231–257Google Scholar
  80. 80.
    Jabbour CJC, Jabbour ABLDS, Govindan K, Teixeira AA, Freitas WRDS (2013) Environmental management and operational performance in automotive companies in Brazil: the role of human resource management and lean manufacturing. J Clean Prod 47:129–140CrossRefGoogle Scholar
  81. 81.
    Rao P, Holt D (2005) “Do green supply chains lead to competitiveness and economic performance?”. Int J Oper Prod Manag 25(9):898–916CrossRefGoogle Scholar
  82. 82.
    Seuring S, Müller M (2008) Core issues in sustainable supply chain management—a Delphi study. Bus Strateg Environ 17(8):455–466CrossRefGoogle Scholar
  83. 83.
    Eltayeb T, Zailani S, Ramayah T (2011) Green supply chain initiatives among certified companies in Malaysia and environmental sustainability: investigating the outcomes. Resour Conserv Recycl 55:495–506CrossRefGoogle Scholar
  84. 84.
    Baines T, Brown S, Benedettini O, Ball P (2012) Examining green production and its role within the competitive strategy of manufacturers. J Ind Eng Manag 15(1):53–87Google Scholar
  85. 85.
    Pauli G (1997) Zero emissions: the ultimate goal of cleaner production. J Clean Prod 5(1/2):109–113CrossRefGoogle Scholar
  86. 86.
    Murovec N, Erker RS, Prodan I (2012) Determinants of environmental investments: testing the structural model. J Clean Prod 37:265–277CrossRefGoogle Scholar
  87. 87.
    Prajogo D, Chowdhury M, Yeung AC, Cheng TCE (2012) The relationship between supplier management and firm’s operational performance: a multi-dimensional perspective. Int J Prod Econ 136(1):123–130Google Scholar
  88. 88.
    Pereira-Moliner J, Claver-Cortes E, Molina-Azorin J, Tari J (2012) Quality management, environmental management and firm performance: direct and mediating effects in the hotel industry. J Clean Prod 37:82–92CrossRefGoogle Scholar
  89. 89.
    Gavronski I, Paiva EL, Teixeira R, de Andrade MCF (2013) ISO 14001 certified plants in Brazil—taxonomy and practices. J Clean Prod 39:32–41CrossRefGoogle Scholar
  90. 90.
    Mudgal RK, Shankar R, Talib P, Raj T (2010) Modelling the barriers of green supply chain practices: an Indian perspective. Int J Logist Syst Manag 7(1):81–107CrossRefGoogle Scholar
  91. 91.
    Diaz-Elsayed N, Jondral A, Greinacher S, Dornfeld D, Lanza G (2013) Assessment of lean and green strategies by simulation of manufacturing systems in discrete production environments. CIRP Ann Manuf Technol 62(1):475–478CrossRefGoogle Scholar
  92. 92.
    Jasiulewicz-Kaczmarek M (2013) Sustainability: orientation in maintenance management—theoretical background. In: EcoProduction and Logistics. Springer, Berlin, pp 117–134CrossRefGoogle Scholar
  93. 93.
    Farish M (2009) Plants that are green [Toyota’s lean manufacturing]. Eng Technol 4(3):68–69CrossRefGoogle Scholar
  94. 94.
    Franchetti M, Bedal K, Ulloa J, Grodek S (2009) Lean and green-industrial engineering methods are natural stepping stones to green engineering. Ind Eng 41(9):24Google Scholar
  95. 95.
    Hajmohammad S, Vachon S, Klassen RD, Gavronski I (2013) Lean management and supply management: their role in green practices and performance. J Clean Prod 39:312–320CrossRefGoogle Scholar
  96. 96.
    Azevedo SG, Carvalho H, Cruz Machado V (2011) The influence of green practices on supply chain performance: a case study approach. Transp Res E Logist Transp Rev 47(6):850–871CrossRefGoogle Scholar
  97. 97.
    Bhateja AK, Babbar R, Singh S, Sachdeva A (2012) Study of the critical factor finding’s regarding evaluation of green supply chain performance of Indian scenario for manufacturing sector. Int J Comput Eng Manag 15(1):74–80Google Scholar
  98. 98.
    Seman NAA, Zakuan N, Jusoh A, Arif MSM, Saman MZM (2012) Green supply chain management: a review and research direction. Int J Manag Value Supply Chains 3(1):1–18CrossRefGoogle Scholar
  99. 99.
    Whitelock VG (2012) Alignment between green supply chain management strategy and business strategy. Int J Procurement Manag 5(4):430–451CrossRefGoogle Scholar
  100. 100.
    Pochampally KK, Gupta SM, Govindan K (2009) Metrics for performance measurement of a reverse/closed-loop supply chain. Int J Bus Perform Supply Chain Model 1(1):8–32CrossRefGoogle Scholar
  101. 101.
    Ageron B, Gunasekaran A, Spalanzani A (2012) Sustainable supply management: an empirical study. Int J Prod Econ 140(1):168–182CrossRefGoogle Scholar
  102. 102.
    Churchill GA Jr (1979) A paradigm for developing better measures of marketing constructs. J Mark Res 16(1):64–73MathSciNetCrossRefGoogle Scholar
  103. 103.
    Gerbing DW, Anderson JC (1988) An updated paradigm for scale development incorporating unidimensionality and its assessment. J Mark Res 25(2):186–192CrossRefGoogle Scholar
  104. 104.
    Lomborg S, Bechmann A (2014) Using APIs for data collection on social media. Inf Soc 30(4):256–265CrossRefGoogle Scholar
  105. 105.
    Hargittai E (2007) Whose space? Differences among users and non‐users of social network sites. J Comput-Mediat Commun 13(1):276–297CrossRefGoogle Scholar
  106. 106.
    Berg BL, Lune H, Lune H (2004) Qualitative research methods for the social sciences, vol 5. Pearson, BostonGoogle Scholar
  107. 107.
    Kwak H, Lee C, Park H, Moon S (2010) What is Twitter, a social network or a news media?. In Proceedings of the 19th international conference on World wide web (pp. 591-600). ACMGoogle Scholar
  108. 108.
    Tufekci Z (2008) Grooming, gossip, Facebook and MySpace: what can we learn about these sites from those who won’t assimilate? Inf Commun Soc 11(4):544–564CrossRefGoogle Scholar
  109. 109.
    Braunscheidel MJ, Suresh NC (2009) The organizational antecedents of a firm’s supply chain agility for risk mitigation and response. J Oper Manag 27(2):119–140CrossRefGoogle Scholar
  110. 110.
    Eckstein D, Goellner M, Blome C, Henke M (2015) The performance impact of supply chain agility and supply chain adaptability: the moderating effect of product complexity. Int J Prod Res. doi: 10.1080/00207543.2014.970707 Google Scholar
  111. 111.
    Khalili A, Chen J (2007) Variable selection in finite mixture of regression models. J Am Stat Assoc 102(479):1025–1038MathSciNetzbMATHCrossRefGoogle Scholar
  112. 112.
    Städler N, Bühlmann P, Van De Geer S (2010) ℓ 1-penalization for mixture regression models. Test 19(2):209–256MathSciNetzbMATHCrossRefGoogle Scholar
  113. 113.
    Becker JM, Rai A, Ringle CM, Völckner F (2013) Discovering unobserved heterogeneity in structural equation models to avert validity threats. MIS Q 37(3):665–694Google Scholar
  114. 114.
    Fan J, Liao Y (2014) Endogeneity in high dimensions. Ann Stat 42(3):872–917MathSciNetzbMATHCrossRefGoogle Scholar
  115. 115.
    Golub GH, Van Loan CF (2012) Matrix computations (Vol. 3). JHU PressGoogle Scholar
  116. 116.
    Chen IJ, Paulraj A (2004) Towards a theory of supply chain management: the constructs and measurements. J Oper Manag 22(2):119–150CrossRefGoogle Scholar
  117. 117.
    Cohen J, Cohen P, West SG, Aiken LS (2013) Applied multiple regression/correlation analysis for the behavioral sciences, 3rd edn. Erlbaum, HillsdaleGoogle Scholar
  118. 118.
    Curran PJ, West SG, Finch JF (1996) The robustness of test statistics to nonnormality and specification error in confirmatory factor analysis. Psychol Methods 1(1):16–29CrossRefGoogle Scholar
  119. 119.
    Hair JF, Anderson RE, Tatham RL, Black WC (1998) Multivariate data analysis. Prentice-Hall, Upper Saddle RiverGoogle Scholar
  120. 120.
    Fornell C, Larcker DF (1981) Structural equation models with unobservable variables and measurement error: algebra and statistics. J Mark Res 18(1):39–50CrossRefGoogle Scholar
  121. 121.
    Tenenhaus M, Vinzi VE, Chatelin YM, Lauro C (2005) PLS path modeling. Comput Stat Data Anal 48(1):159–205MathSciNetzbMATHCrossRefGoogle Scholar
  122. 122.
    Wetzels M, Odekerken-Schröder G, Van Oppen C (2009) Using PLS path modeling for assessing hierarchical construct models: guidelines and empirical illustration. MIS Q 33(1):177–195Google Scholar
  123. 123.
    Whetten DA (1989) What constitutes a theoretical contribution? Acad Manag Rev 14(4):490–495CrossRefGoogle Scholar
  124. 124.
    Agarwal R, Dhar V (2014) Editorial—big data, data science, and analytics: the opportunity and challenge for is research. Inf Syst Res 25(3):443–448Google Scholar
  125. 125.
    Bhatt GD, Grover V (2005) Types of information technology capabilities and their role in competitive advantage: an empirical study. Journal of Management Information Systems, 22(2):253–277Google Scholar

Copyright information

© Springer-Verlag London 2015

Authors and Affiliations

  • Rameshwar Dubey
    • 1
  • Angappa Gunasekaran
    • 2
    Email author
  • Stephen J. Childe
    • 3
  • Samuel Fosso Wamba
    • 4
  • Thanos Papadopoulos
    • 5
  1. 1.Symbiosis Institute of Operations ManagementConstituent of Symbiosis International UniversityNew NashikIndia
  2. 2.Charlton College of BusinessUniversity of Massachusetts DartmouthNorth DartmouthUSA
  3. 3.College of Engineering, Mathematics and Physical SciencesUniversity of ExeterEXETERUK
  4. 4.NEOMA Business School, RouenMont Saint Aignan CedexFrance
  5. 5.Department of Business and ManagementUniversity of SussexBrightonUK

Personalised recommendations