Knowledge-Based Dynamic Capabilities and Competitive Advantage – Data Analysis and Interpretations

  • Vaneet Kaur
Part of the Innovation, Technology, and Knowledge Management book series (ITKM)


The chapter discusses the results of pre-testing as well as presents the descriptive and inferential statistical data analysis of the present study. The chapter ensures the adequacy of survey response and gives the background of the respondents by analyzing the demographic profiles. This is followed by data purification and analysis by using descriptive statistics. For the purpose of ensuring the application of multivariate techniques for analyzing data, the survey responses have been screened to ensure normality, linearity, homoscedasticity and multicollinearity. A panoply of research techniques like correlation, regression, analysis of variance, exploratory factor analysis, confirmatory factor analysis, structural equation modelling have been used to analyze the data. Thereafter, the results of these techniques are presented in a meaningful manner to arrive at relevant conclusions. Interpretations have been done under three broad themes namely Knowledge-Management Process Capabilities, Higher-Order Dynamic Capabilities and Competitive Advantage.


  1. Al-Ababneh, M. M. (2015). Employees’ service innovation behavior and new service development in four-and five-star hotels. International Journal of Tourism & Hospitality Reviews, 1(1), 13–22.CrossRefGoogle Scholar
  2. Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411–423.Google Scholar
  3. Azwar, S. A., Suganda, E., Tjiptoherijanto, P., & Rahmayanti, H. (2013). Model of sustainable urban infrastructure at coastal reclamation of North Jakarta. Procedia Environmental Sciences, 17, 452–461.CrossRefGoogle Scholar
  4. Babin, R., & Nicholson, B. (2009). Corporate social and environmental responsibility in global IT outsourcing. MIS Quarterly Executive, 8(4), 123–132.Google Scholar
  5. Baron, R. M., & Kenny, D. A. (1986). The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51(6), 1173–1182.CrossRefGoogle Scholar
  6. BasuMallick, C. (2016). Given its earnings results, buy accenture on the recent pullback. Retrieved April 11, 2017 from
  7. BasuMallick, C. (2017). Buy accenture’s stock on dips. Retrieved April 14, 2017 from
  8. Baumgartner, H., & Homburg, C. (1996). Applications of structural equation modeling in marketing and consumer research: A review. International Journal of Research in Marketing, 13(2), 139–161.CrossRefGoogle Scholar
  9. Bayyurt, N., & Rizvi, S. (2015). Impact of talent management on perceived organizational effectiveness: Service industry in Lahore, Pakistan. Research Journal of Business and Management, 2(4), 468–487.Google Scholar
  10. Boer, D. D., Delnoij, D., & Rademakers, J. (2011). The discriminative power of patient experience surveys. BMC Health Services Research, 11(1), 332.CrossRefGoogle Scholar
  11. Brainerd, C. J., Wang, Z., & Reyna, V. F. (2013). Superposition of episodic memories: Overdistribution and quantum models. Topics in Cognitive Science, 5(4), 773–799.Google Scholar
  12. Cao, Y., & Zhao, L. (2013). Analysis of patent management effects on technological innovation performance. Baltic Journal of Management, 8(3), 286–305.CrossRefGoogle Scholar
  13. Castellanos-Ryan, N., & Conrod, P. J. (2011). Personality correlates of the common and unique variance across conduct disorder and substance misuse symptoms in adolescence. Journal of Abnormal Child Psychology, 39(4), 563–576.CrossRefGoogle Scholar
  14. Chan, F., Lee, G. K., Lee, E. J., Kubota, C., & Allen, C. A. (2007). Structural equation modeling in rehabilitation counseling research. Rehabilitation Counseling Bulletin, 51(1), 44–57.CrossRefGoogle Scholar
  15. Chang, L. C., & Liu, C. H. (2008). Employee empowerment, innovative behavior and job productivity of public health nurses: A cross-sectional questionnaire survey. International Journal of Nursing Studies, 45(10), 1442–1448.CrossRefGoogle Scholar
  16. Chaudhary, M. (2013). Role of children in the family buying process.Google Scholar
  17. Chen, H. S., & Hsieh, T. (2011). The effect of atmosphere on customer perceptions and customer behavior responses in chain store supermarkets. African Journal of Business Management, 5(24), 10054.CrossRefGoogle Scholar
  18. Chinomona, R., & Pretorius, M. (2011). Major dealers’ expert power in distribution channels. South African Journal of Economic and Management Sciences, 14(2), 170–187.CrossRefGoogle Scholar
  19. Cieciuch, J., & Davidov, E. (2012). A comparison of the invariance properties of the PVQ-40 and the PVQ-21 to measure human values across German and Polish Samples. Survey Research Methods, 6(1), 37–48.Google Scholar
  20. Doll, W. J., Xia, W., & Torkzadeh, G. (1994). A confirmatory factor analysis of the end-user computing satisfaction instrument. MIS Quarterly, 18, 453–461.CrossRefGoogle Scholar
  21. Ertz, M., Karakas, F., & Sarigöllü, E. (2016). Exploring pro-environmental behaviors of consumers: An analysis of contextual factors, attitude, and behaviors. Journal of Business Research, 69(10), 3971–3980.Google Scholar
  22. Ferraro, R., Escalas, J. E., & Bettman, J. R. (2011). Our possessions, our selves: Domains of self-worth and the possession–self link. Journal of Consumer Psychology, 21(2), 169–177.CrossRefGoogle Scholar
  23. Fersht, P. (2016). IBM, Infosys, Accenture and Cognizant lead in the industry’s first design thinking blueprint. Retrieved April 5, 2017 from
  24. Fitzhugh, S. L. (2012). The coherence formation model of illustrated text comprehension: A path model of attention to multimedia text. Temple University.Google Scholar
  25. Fujisato, H., Ito, M., Takebayashi, Y., Hosogoshi, H., Kato, N., Nakajima, S., & Horikoshi, M. (2017). Reliability and validity of the Japanese version of the Emotion Regulation Skills Questionnaire. Journal of Affective Disorders, 208, 145–152.CrossRefGoogle Scholar
  26. Gencer, R., Kiremitci, O., & Boyacioglu, H. (2011). Spectator motives and points of attachment: An investigation on professional basketball. Journal of Human Kinetics, 30, 189–196.CrossRefGoogle Scholar
  27. Gerbing, D. W., & Anderson, J. C. (1984). On the meaning of within-factor correlated measurement errors. Journal of Consumer Research, 11(1), 572–580.CrossRefGoogle Scholar
  28. Gill, S., Winters, D., & Friedman, D. S. (2006). Educators’ views of pre-kindergarten and kindergarten readiness and transition practices. Contemporary Issues in Early Childhood, 7(3), 213–227.CrossRefGoogle Scholar
  29. Graham, C. (2016). Strategic management and leadership for systems development in virtual spaces (pp. 102–105). Hershey: Igi Global.CrossRefGoogle Scholar
  30. Gumanga, S. K., & Kwame-Aryee, R. A. (2012). Menstrual characteristics in some adolescent girls in Accra, Ghana. Ghana Medical Journal, 46(1).Google Scholar
  31. Hadadi, M., Ebrahimi Takamjani, I., Ebrahim Mosavi, M., Aminian, G., Fardipour, S., & Abbasi, F. (2016). Cross-cultural adaptation, reliability, and validity of the Persian version of the Cumberland Ankle Instability Tool. Disability and Rehabilitation, 8288(February), 1–9. Scholar
  32. Hair, J. F., Anderson, R. E., Babin, B. J., & Black, W. C. (2010). Multivariate data analysis: A global perspective (Vol. 7). Upper Saddle River: Pearson.Google Scholar
  33. Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (1998). Multivariate data analysis (5th ed.). Upper saddle River: Prentice Hall.Google Scholar
  34. Hermida, R. (2015). The problem of allowing correlated errors in structural equation modeling: Concerns and considerations. Computational Methods in Social Sciences, 3(1), 5.Google Scholar
  35. Hooper, D., Coughlan, J., & Mullen, M. (2008). Structural equation modelling: Guidelines for determining model fit. Articles, 2.Google Scholar
  36. Hsu, C. L., & Lu, H. P. (2004). Why do people play on-line games? An extended TAM with social influences and flow experience. Information & Management, 41(7), 853–868.CrossRefGoogle Scholar
  37. Hu, L. T., & Bentler, P. M. (1998). Fit indices in covariance structure modeling: Sensitivity to underparameterized model misspecification. Psychological Methods, 3(4), 424–453.CrossRefGoogle Scholar
  38. Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55.CrossRefGoogle Scholar
  39. Irawan, K. I. (2013). Kukuyaan program as a form of community empowerment and river revitalization: Case study of Cikapundung river, Bandung, West Java.Google Scholar
  40. Isah, A. D. (2016). Urban public housing in Northern Nigeria: The search for indigeneity and cultural practices in design. Springer.Google Scholar
  41. İşgüven, P., Yörük, G., & Çizmecioğlu, F. M. (2015). Educational needs of adolescents regarding normal puberty and menstrual patterns. Journal of Clinical Research in Pediatric Endocrinology, 7(4), 312–322.CrossRefGoogle Scholar
  42. Kamaruddin, K., & Abeysekera, I. (2013). Intellectual capital and public sector performance. Bingley: Emerald Group Publishing.CrossRefGoogle Scholar
  43. Kam Sing Wong, S., & Tong, C. (2013). New product success: Empirical evidence from SMEs in China. Journal of Business & Industrial Marketing, 28(7), 589–601.CrossRefGoogle Scholar
  44. Kasim, H. A., & Shahibi, M. S. (2015). The emergence of knowledge-based technologies in promoting knowledge sharing behavior. Review of Knowledge Economy, 2(1), 14–29.CrossRefGoogle Scholar
  45. Kaur, V., & Mehta, V. (2016a). Knowledge-based dynamic capabilities: A new perspective for achieving global competitiveness in IT sector. Pacific Business Review International, 1(3), 95–106.Google Scholar
  46. Kaur, V., & Mehta, V. (2016b). Leveraging knowledge processes for building higher-order dynamic capabilities: An empirical evidence from IT sector in India. JIMS 8M, 21(3), 37–47.Google Scholar
  47. Kline, R. B. (1998). Principles and practice of structural equation modeling. New York: Guilford Press.Google Scholar
  48. Kotchick, B. A., Dorsey, S., & Heller, L. (2005). Predictors of parenting among African American single mothers: Personal and contextual factors. Journal of Marriage and Family, 67(2), 448–460.CrossRefGoogle Scholar
  49. Lin, M. J. J., Tu, Y. C., Chen, D. C., & Huang, C. H. (2013). Customer participation and new product development outcomes: The moderating role of product innovativeness. Journal of Management & Organization, 19(3), 314–337.CrossRefGoogle Scholar
  50. Long, D. A., & Perkins, D. D. (2003). Confirmatory factor analysis of the sense of community index and development of a brief SCI. Journal of Community Psychology, 31(3), 279–296.CrossRefGoogle Scholar
  51. Lu, Y. C., Chang, Y. Y., & Shu, B. C. (2009). Mental symptoms in different health professionals during the SARS attack: A follow-up study. Psychiatric Quarterly, 80(2), 107.CrossRefGoogle Scholar
  52. Mafini, C. (2015). Investigating antecedent factors to job performance: Contemporary evidence from government supply management professionals. Acta Commercii, 15(1), 1–11.CrossRefGoogle Scholar
  53. Mandal, K., Bandyopadhyay, G., & Roy, K. (2011). Quest for different strategic dimensions of channel management: An empirical study. Journal of Business Studies Quarterly, 3(2), 25.Google Scholar
  54. Manyema, M. (2014). Factors associated with bacterial vaginosis in sexually active women enrolled in the Microbicide Development Program 301 Study (Doctoral dissertation).Google Scholar
  55. Marsh, H. W., Balla, J. R., & McDonald, R. P. (1988). Goodness-of-fit indexes in confirmatory factor analysis: The effect of sample size. Psychological Bulletin, 103(3), 391–410.CrossRefGoogle Scholar
  56. Martinez-Lopez, F. J., Gázquez-Abad, J. C., & Gijsbrecht, E. (Eds.). (2016). Advances in national brand and private label marketing: Third international conference. Cham: Springer.Google Scholar
  57. Maydeu-Olivares, A. (2017). Assessing the size of model misfit in structural equation models. Psychometrika, 1–26.Google Scholar
  58. Mirzaie, K., Sadighi, B., & Hanzaee, K. H. (2012). Investigation of the effect of sociological and cultural factors on the conspicuous consumption of university students. Archives des Sciences, 65(4).Google Scholar
  59. Muhammadak, S. A., & Saadb, R. A. (2016). Moderating effect of attitude toward ZaNat payment on the relationship between moral reasoning and intention to pay ZaNat.Google Scholar
  60. Muncherji, N., & Dhar, U. (2009). Creating wealth through strategic HR and entrepreneurship. Excel Books India.Google Scholar
  61. Nguyen, T. N. Q. (2010). Knowledge management capability and competitive advantage: An empirical study of Vietnamese enterprises.Google Scholar
  62. Nguyen, N. T. D., & Aoyama, A. (2014). Achieving efficient technology transfer through a specific corporate culture facilitated by management practices. The Journal of High Technology Management Research, 25(2), 108–122.CrossRefGoogle Scholar
  63. Nguyen, Q. T. N., & Neck, P. A. (2008, July). Knowledge management as dynamic capabilities: Does it work in emerging less developed countries. In Proceedings of the 16th Annual Conference on Pacific Basin Finance, Economics, Accounting and Management (pp. 1–18).Google Scholar
  64. Nirmal, R. (2016). Indian IT firms late movers in digital race. Retrieved February 19, 2017 from
  65. Niu, X. Y., Song, K., Lee, C., & Huang, G. H. (2009). A study of the antecedents and consequences of C-JI and A-JI in a typical Chinese machine tool company. In Management Science and Engineering, 2009. ICMSE 2009. International Conference on (pp. 398–407). IEEE.Google Scholar
  66. Numthavaj, P., Bhongmakapat, T., Roongpuwabaht, B., Ingsathit, A., & Thakkinstian, A. (2017). The validity and reliability of Thai Sinonasal Outcome Test-22. European Archives of Oto-Rhino-Laryngology, 274(1), 289–295.CrossRefGoogle Scholar
  67. Petróczi, A., & Nepusz, T. (2011). Methodological considerations regarding response bias effect in substance use research: is correlation between the measured variables sufficient? Substance Abuse Treatment, Prevention, and Policy, 6(1), 1.CrossRefGoogle Scholar
  68. Phadnis, S. (2014). TCS, Cognizant pull ahead of Infosys, Wipro. Retrieved April 1, 2017 from
  69. Pícha, K., Skořepa, L., & Navrátil, J. (2013). Assessment of the results of the strategic orientation on regional and local products in food retail. Acta universitatis agriculturae et silviculturae Mendelianae Brunensis, 61(4), 1061–1068.CrossRefGoogle Scholar
  70. Piland, S. G., Motl, R. W., Guskiewicz, K. M., McCrea, M., & Ferrara, M. S. (2006). Structural validity of a self-report concussion-related symptom scale. Medicine and Science in Sports and Exercise, 38(1), 27–32.CrossRefGoogle Scholar
  71. Qureshi, M. I., Iftikhar, M., Bhatti, M. N., Shams, T., & Zaman, K. (2013). Critical elements in implementations of just-in-time management: Empirical study of cement industry in Pakistan. Springerplus, 2(1), 645.CrossRefGoogle Scholar
  72. Rahman, S. U., Saleem, S., Akhtar, S., Ali, T., & Khan, M. A. (2014). Consumers’ adoption of apparel fashion: The role of innovativeness, involvement, and social values. International Journal of Marketing Studies, 6(3), 49.CrossRefGoogle Scholar
  73. Rahmayanti, H. (2014). The analysis of community adaptation process in constructing disaster-prone city (A Study on West Padang).Google Scholar
  74. Ring, L., Höfer, S., McGee, H., Hickey, A., & O’Boyle, C. A. (2007). Individual quality of life: Can it be accounted for by psychological or subjective well-being? Social Indicators Research, 82(3), 443–461.CrossRefGoogle Scholar
  75. Sampe, F. (2012). The influence of organizational learning on performance in Indonesian SMEs.Google Scholar
  76. Sanner, M. A., Nydahl, A., Desatnik, P., & Rizell, M. (2006). Obstacles to organ donation in Swedish intensive care units. Intensive Care Medicine, 32(5), 700–707.CrossRefGoogle Scholar
  77. Shan, S., Li, C., Yao, W., Shi, J., & Ren, J. (2014). An empirical study on critical factors affecting employee satisfaction. Systems Research and Behavioral Science, 31(3), 447–460.CrossRefGoogle Scholar
  78. Snook, E. M. (2008). Physical activity, self-efficacy, and quality of life in multiple sclerosis. Annals of Behavioral Medicine, 35(1), 111.CrossRefGoogle Scholar
  79. Sood, V. (2016). Indian IT: Back to the future. Retrieved April 3, 2017 from
  80. Steele, J. P. (2008). Conflict efficacy: Antecedents and consequences. Kansas State University.Google Scholar
  81. Su, C. C., Lee, F. L., & Lin, G. (2017). Does site architecture matter? The political implications of public-versus private-oriented social network sites in China. Asian Journal of Communication, 27(2), 134–153.CrossRefGoogle Scholar
  82. Theriou, G., & Chatzoudes, D. (2015). Exploring the entrepreneurship-performance relationship: evidence from Greek SMEs. Journal of Small Business and Enterprise Development, 22(2), 352–375.CrossRefGoogle Scholar
  83. Tran, T., & Chan, K. T. (2016). Developing cross-cultural measurement in social work research and evaluation. Oxford University Press.Google Scholar
  84. Traymbak, S., Kumar, P., & Jha, A. N. (2017). Examining moderating effects of gender between role stress and job satisfaction among software employees. Purushartha: A Journal of Management Ethics and Spirituality, 9(2).Google Scholar
  85. Yadav, J. K., & Krishnan, O. (2017). Memorable tourism experiences: Vivid memories and feelings of Nostalgia for Houseboat tourism.Google Scholar
  86. Yeung, N. T. Y., & Yeung, A. S. (2001). Does school motivation change over secondary school years?.Google Scholar
  87. Zheng, S., Zhang, W., & Du, J. (2011). Knowledge-based dynamic capabilities and innovation in networked environments. Journal of Knowledge Management, 15(6), 1035–1051.CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Vaneet Kaur
    • 1
  1. 1.The University of Texas at DallasRichardsonUSA

Personalised recommendations