SpringerLink
Log in

The role of big data analytics capability in the telecommunication sector of Pakistan: the chain mediating effect of data integration capability and data-driven decision making

  • Published:
Quality & Quantity Aims and scope Submit manuscript

Abstract

The current study aimed to explain the effect of big data analytics capabilities on firm performance in the telecommunication sector of Pakistan. The proposed research model examines the effect of big data analytics capabilities on firm performance in the presence of chain mediating effect of data integration capability and data-driven decision-making, along with moderating influence of analytics culture. The research model was developed using the proven theory of resource-based view. In this cross-sectional study, an online questionnaire was used including 34 response items for data collection, whereas SPSS and Smart-PLS 4.0 were used for descriptive statistics & inferential analysis respectively. The results of this study indicate that adoption of big data analytics capabilities positively influence firm performance. It also confirms about the effective implementation of data driven decision making & data integration capability leads to better performance of the organization. However, no moderation of analytics culture on firm performance was found. The results also suggest the managers to take effective decision-making based on data integration for enhancing business performance. Study faces some potential challenges due to high data volume availability, small sample size methodological and sector specifics limitations. Study suggests the potential for future research evaluating this model with two serial mediations like process-oriented dynamic capabilities, business process agility etc. along with some moderators such as customer knowledge management etc. to identify the response in more complicated connections.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (Germany)

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  • Abbas, H., Ze, Y., Ahmad, W.: Competitive Approaches of Strategic Alliance in the Big Data Environment, a Moderating Role of Big Data Predictive Analytics in the Case of Telecommunication Sector of Pakistan. (2021)

  • Abiteboul, S., Benjelloun, O., Milo, T.: Web services and data integration Paper presented at the Web Information Systems Engineering, International Conference on. (2002)

  • Adrian, C., Abdullah, R., Atan, R., Jusoh, Y.Y.: Conceptual model development of big data analytics implementation assessment effect on decision-making. (2018)

  • Akhtar, P., Frynas, J.G., Mellahi, K., Ullah, S.: Big data-savvy teams’ skills, big data‐driven actions and business performance. Br. J. Manag. 30(2), 252–271 (2019)

    Article  Google Scholar 

  • Akter, S., Wamba, S.F., Gunasekaran, A., Dubey, R., Childe, S.J.: How to improve firm performance using big data analytics capability and business strategy alignment? Int. J. Prod. Econ. 182, 113–131 (2016)

    Article  Google Scholar 

  • Al-Alwan, M., Al-Nawafah, S., Al-Shorman, H., Khrisat, F., Alathamneh, F., Al-Hawary, S.: The effect of big data on decision quality: Evidence from telecommunication industry. Int. J. Data Netw. Sci. 6(3), 693–702 (2022)

    Article  Google Scholar 

  • Al-Jaafreh, A., Fayoumi, A.: The Role of Big Data Analytics on Innovation: A Study from The Telecom Industry. (2017)

  • Andresen, E.M.: Criteria for assessing the tools of disability outcomes research. Arch. Phys. Med. Rehabil. 81, S15–S20 (2000)

    Article  Google Scholar 

  • Arens, Y., Chee, C.Y., Hsu, C.-N., Knoblock, C.A.: Retrieving and integrating data from multiple information sources. Int. J. Intell. Coop. Inform. Syst. 2(02), 127–158 (1993)

    Article  Google Scholar 

  • Arunachalam, D., Kumar, N., Kawalek, J.P.: Understanding big data analytics capabilities in supply chain management: Unravelling the issues, challenges and implications for practice. Transp. Res. E. 114, 416–436 (2018)

    Article  Google Scholar 

  • Ashaari, M.A., Amran, A., Ahmad, N.H., Bakri, H., Nazri, S.: Big Data Analytics Technology Capability and Data-Driven Decision Making in Malaysian Higher Education Institutions: A Conceptual Framework Paper presented at the IOP Conference Series: Materials Science and Engineering. (2020)

  • Ashaari, M.A., Singh, K.S.D., Abbasi, G.A., Amran, A., Liebana-Cabanillas, F.J.: Big data analytics capability for improved performance of higher education institutions in the era of IR 4.0: A multi-analytical SEM & ANN perspective. Technol. Forecast. Soc. Chang. 173, 121119 (2021)

    Article  Google Scholar 

  • Awan, U., Shamim, S., Khan, Z., Zia, N.U., Shariq, S.M., Khan, M.N.: Big data analytics capability and decision-making: The role of data-driven insight on circular economy performance. Technol. Forecast. Soc. Chang. 168, 120766 (2021)

    Article  Google Scholar 

  • Aydiner, A.S., Tatoglu, E., Bayraktar, E., Zaim, S.: Information system capabilities and firm performance: Opening the black box through decision-making performance and business-process performance. Int. J. Inf. Manag. 47, 168–182 (2019a)

    Article  Google Scholar 

  • Aydiner, A.S., Tatoglu, E., Bayraktar, E., Zaim, S., Delen, D.: Business analytics and firm performance: The mediating role of business process performance. J. Bus. Res. 96, 228–237 (2019b)

    Article  Google Scholar 

  • Barclay, D., Higgins, C., Thompson, R.: The partial least squares (PLS) approach to casual modeling: personal computer adoption ans use as an Illustration. (1995)

  • Barney, J.: Firm resources and sustained competitive advantage. J. Manag. 17(1), 99–120 (1991)

    Google Scholar 

  • Barney, J.B., Ketchen, D.J. Jr., Wright, M.: The future of resource-based theory: Revitalization or decline? J. Manag. 37(5), 1299–1315 (2011)

    Google Scholar 

  • Barton, D., Court, D.: Making advanced analytics work for you. Harvard Business Rev. 90(10), 78–83 (2012)

    Google Scholar 

  • Bentler, P.M., Chou, C.-P.: Practical issues in structural modeling. Sociol. Methods Res. 16(1), 78–117 (1987)

    Article  Google Scholar 

  • Bharadwaj, A.S.: A resource-based perspective on information technology capability and firm performance: An empirical investigation. MIS Q., 169–196. (2000)

  • Bhatti, A., Malik, H., Kamal, A.Z., Aamir, A., Alaali, L.A., Ullah, Z.: Much-needed business digital transformation through big data, internet of things and blockchain capabilities: Implications for strategic performance in telecommunication sector. Bus. Process. Manage. J. 27(6), 1854–1873 (2021)

    Article  Google Scholar 

  • Bhimani, A., Willcocks, L.: Digitisation,‘Big Data’and the transformation of accounting information. Acc. Bus. Res. 44(4), 469–490 (2014)

    Article  Google Scholar 

  • Bi, S., Zhang, R., Ding, Z., Cui, S.: Wireless communications in the era of big data. IEEE Commun. Mag. 53(10), 190–199 (2015)

    Article  Google Scholar 

  • Brynjolfsson, E., Hitt, L.M., Kim, H.H.: Strength in numbers: How does data-driven decisionmaking affect firm performance? Available at SSRN 1819486. (2011)

  • Bughin, J.: Rea** the benefits of big data in telecom. J. Big Data. 3(1), 1–17 (2016)

    Article  Google Scholar 

  • Cao, G., Duan, Y., Li, G.: Linking business analytics to decision making effectiveness: A path model analysis. IEEE Trans. Eng. Manage. 62(3), 384–395 (2015)

    Article  Google Scholar 

  • Casadesus-Masanell, R., Ricart, J.E.: From strategy to business models and onto tactics. Long Range Plann. 43(2–3), 195–215 (2010)

    Article  Google Scholar 

  • Chan, Y.: Biostatistics 104: Correlational analysis. Singap. Med. J. 44(12), 614–619 (2003)

    Google Scholar 

  • Chen, F., Deng, P., Wan, J., Zhang, D., Vasilakos, A.V., Rong, X.: Data mining for the internet of things: Literature review and challenges. Int. J. Distrib. Sens. Netw. 11(8), 431047 (2015)

    Article  Google Scholar 

  • Chin, W.W.: How to write up and report PLS analyses. In: Handbook of Partial Least Squares, pp. 655–690. Springer (2010)

  • Chin, W.W., Newsted, P.R.: Structural equation modeling analysis with small samples using partial least squares. Stat. Strategies Small Sample Res. 1(1), 307–341 (1999)

    Google Scholar 

  • Chión, S.J., Charles, V., Morales, J.: The impact of organisational culture, organisational structure and technological infrastructure on process improvement through knowledge sharing. Bus. Process. Manage. J. 26(6), 1443–1472 (2019)

    Article  Google Scholar 

  • Churchill, G.A. Jr.: A paradigm for develo** better measures of marketing constructs. J. Mark. Res. 16(1), 64–73 (1979)

    Article  Google Scholar 

  • Danso, A., Adomako, S., Amankwah-Amoah, J., Owusu‐Agyei, S., Konadu, R.: Environmental sustainability orientation, competitive strategy and financial performance. Bus. Strategy Environ. 28(5), 885–895 (2019)

    Article  Google Scholar 

  • Ertemel, A.V.: Consumer insight as competitive advantage using big data and analytics. Int. J. Commer. Finance. 1(1), 45–51 (2015)

    Google Scholar 

  • Fernández, A., del Río, S., López, V., Bawakid, A., del Jesus, M.J., Benítez, J.M., Herrera, F.: Big Data with Cloud Computing: An insight on the computing environment, MapReduce, and programming frameworks. Wiley Interdisciplinary Reviews: Data Min. Knowl. Discovery. 4(5), 380–409 (2014)

    Google Scholar 

  • Ferraris, A., Mazzoleni, A., Devalle, A., Couturier, J.: Big data analytics capabilities and knowledge management: Impact on firm performance. Manag. Decis. 57(8), 1923–1936 (2019)

    Article  Google Scholar 

  • Fornell, C., Larcker, D.F.: Evaluating structural equation models with unobservable variables and measurement error. J. Mark. Res. 18(1), 39–50 (1981)

    Article  Google Scholar 

  • Ghasemaghaei, M.: Understanding the impact of big data on firm performance: The necessity of conceptually differentiating among big data characteristics. Int. J. Inf. Manag. 57, 102055 (2021)

    Article  Google Scholar 

  • Ghasemaghaei, M., Hassanein, K., Turel, O.: Increasing firm agility through the use of data analytics: The role of fit. Decis. Support Syst. 101, 95–105 (2017)

    Article  Google Scholar 

  • Gupta, M., George, J.F.: Toward the development of a big data analytics capability. Inf. Manag. 53(8), 1049–1064 (2016)

    Article  Google Scholar 

  • Hair, J.: A Primer on Partial Least Squares Structural Equations Modeling (PLS-SEM) SAGE. Newcastle upon Tyne, UK. (2014)

  • Hair, J.F., Black, W.C., Babin, B.J., Anderson, R.E.: Canonical correlation: A supplement to multivariate data analysis. In: Multivariate Data Analysis: A Global Perspective, 7th edn. Pearson Prentice Hall Publishing, Upper Saddle River, NJ, USA (2010)

    Google Scholar 

  • Hambrick, D.C.: The top management team: Key to strategic success. Calif. Manag. Rev. 30(1), 88–108 (1987)

    Article  Google Scholar 

  • Hassan, M., Awan, F.M., Naz, A., deAndrés-Galiana, E.J., Alvarez, O., Cernea, A., Kloczkowski, A.: Innovations in genomics and big data analytics for personalized medicine and health care: A review. Int. J. Mol. Sci. 23(9), 4645 (2022)

    Article  Google Scholar 

  • Henseler, J.: PLS-MGA: A non-parametric approach to partial least squares-based multi-group analysis. In: Challenges at the Interface of data Analysis, Computer Science, and Optimization, pp. 495–501. Springer (2012)

  • Hossain, M.E.: An investigation on tourism consumers’ choice behavior towards tour destination loyalty. Curtin University (2013)

  • Hussaina, S., Rehmanb, A., Khokharc, M.N., Ejazd, M., Munire, M.: Impact of big data analytics on firm performance with mediating role of decision-making performance and innovation capability. Int. J. Innov. Creativity Chang. 15, 1153–1172 (2021)

    Google Scholar 

  • Jensen, K., Nguyen, H.T., Do, T.V., Årnes, A.: A big data analytics approach to combat telecommunication vulnerabilities. Cluster Comput. 20, 2363–2374 (2017)

    Article  Google Scholar 

  • Jöreskog, K.G., Sörbom, D.: LISREL 8: User’s reference guide. Scientific Software International (1996)

  • Joshi, A., Kale, S., Chandel, S., Pal, D.K.: Likert scale: Explored and explained. Br. J. Appl. Sci. Technol. 7(4), 396–403 (2015)

    Article  Google Scholar 

  • Kasemsap, K.: Multifaceted applications of data mining, business intelligence, and knowledge management. Intelligent Systems: Concepts, Methodologies, Tools, and Applications, 810–825. (2018)

  • Keshavarz, H., Mahdzir, A.M., Talebian, H., Jalaliyoon, N., Ohshima, N.: The value of big data analytics pillars in telecommunication industry. Sustainability. 13(13), 7160 (2021)

    Article  Google Scholar 

  • Kiron, D., Prentice, P.K., Ferguson, R.B.: The analytics mandate. MIT Sloan Manage. Rev. 55(4), 1 (2014)

    Google Scholar 

  • Kline, R.: Principles and Practice of Structural Equation Modeling Second Edition. New York: Guilford Press, New York (2005)

    Google Scholar 

  • Kościelniak, H., Puto, A.: BIG DATA in decision making processes of enterprises. Procedia Comput. Sci. 65, 1052–1058 (2015)

    Article  Google Scholar 

  • Krejcie, R.V., Morgan, D.W.: Determining sample size for research activities. Educ. Psychol. Meas. 30(3), 607–610 (1970)

    Article  Google Scholar 

  • Krishnamoorthi, S., Mathew, S.K.: Business analytics and business value: A comparative case study. Inf. Manag. 55(5), 643–666 (2018)

    Article  Google Scholar 

  • Kumar, A., Arya, N., Sharma, P.K.: A Research on the Impact of Big Data Analytics on the Telecommunications Sector Paper presented at the International Conference on Information and Communication Technology for Intelligent Systems. (2023)

  • Lamba, H.S., Dubey, S.K.: Analysis of requirements for big data adoption to maximize IT business value Paper presented at the 2015 4th International Conference on Reliability, Infocom Technologies and Optimization (ICRITO)(Trends and Future Directions). (2015)

  • Lehrer, C., Wieneke, A., Vom Brocke, J., Jung, R., Seidel, S.: How big data analytics enables service innovation: Materiality, affordance, and the individualization of service. J. Manage. Inform. Syst. 35(2), 424–460 (2018)

    Article  Google Scholar 

  • Loebbecke, C., Picot, A.: Reflections on societal and business model transformation arising from digitization and big data analytics: A research agenda. J. Strateg. Inf. Syst. 24(3), 149–157 (2015)

    Article  Google Scholar 

  • Lorenzo-Romero, C., Alarcón-del-Amo, M.--C., Constantinides, E.: Determinants of use of social media tools in retailing sector. J. Theoretical Appl. Electron. Commer. Res. 9(1), 44–55 (2014)

    Article  Google Scholar 

  • Lu, Y., Ramamurthy, K.: Understanding the link between information technology capability and organizational agility: An empirical examination. MIS Q., 931–954. (2011)

  • Malaka, I., Brown, I.: Challenges to the organisational adoption of big data analytics: A case study in the South African telecommunications industry Paper presented at the Proceedings of the 2015 annual research conference on South African institute of computer scientists and information technologists. (2015)

  • Manavalan, E., Jayakrishna, K.: A review of internet of things (IoT) embedded sustainable supply chain for industry 4.0 requirements. Comput. Ind. Eng. 127, 925–953 (2019)

    Article  Google Scholar 

  • Marr, B.: Big Data: Using SMART big data, Analytics and Metrics to make Better Decisions and Improve Performance. Wiley (2015)

  • McCarthy, C., Bali, S.: Big Data Analytics and the Telco: How telcos can monetize customer data. Research No. TE010-000312). Europe: Ovum. Doi, 20. (2013)

  • McClelland, S.B.: Training needs Assessment Data-gathering methods:: Part 1, Survey questionnaires. J. Eur. Industrial Train. 18(1), 22–26 (1994)

    Article  Google Scholar 

  • Merendino, A., Dibb, S., Meadows, M., Quinn, L., Wilson, D., Simkin, L., Canhoto, A.: Big data, big decisions: The impact of big data on board level decision-making. J. Bus. Res. 93, 67–78 (2018)

    Article  Google Scholar 

  • Mikalef, P., Pappas, I.O., Krogstie, J., Giannakos, M.: Big data analytics capabilities: A systematic literature review and research agenda. Inform. Syst. e-Business Manage. 16(3), 547–578 (2018)

    Article  Google Scholar 

  • Mikalef, P., Boura, M., Lekakos, G., Krogstie, J.: Big data analytics and firm performance: Findings from a mixed-method approach. J. Bus. Res. 98, 261–276 (2019)

    Article  Google Scholar 

  • Mikalef, P., Krogstie, J., Pappas, I.O., Pavlou, P.: Exploring the relationship between big data analytics capability and competitive performance: The mediating roles of dynamic and operational capabilities. Inf. Manag. 57(2), 103169 (2020)

    Article  Google Scholar 

  • Nilashi, M., Keng Boon, O., Tan, G., Lin, B., Abumalloh, R.: Critical data challenges in measuring the performance of sustainable development goals: Solutions and the role of big-data analytics. Harv. Data Sci. Rev. 5(3), 3–4 (2023)

    Google Scholar 

  • Oh, W., Pinsonneault, A.: On the assessment of the strategic value of information technologies: Conceptual and analytical approaches. MIS Q., 239–265. (2007)

  • Palmatier, R.W., Dant, R.P., Grewal, D.: A comparative longitudinal analysis of theoretical perspectives of interorganizational relationship performance. J. Mark. 71(4), 172–194 (2007)

    Article  Google Scholar 

  • Parikh, A., Haddad, J.: Right-time information for the real-time enterprise. J. Financial Serv. Technol. 3(1), 29–33 (2012)

    Google Scholar 

  • Petter, S., McLean, E.R.: A meta-analytic assessment of the DeLone and McLean IS success model: An examination of IS success at the individual level. Inf. Manag. 46(3), 159–166 (2009)

    Article  Google Scholar 

  • Rapp, A., Trainor, K.J., Agnihotri, R.: Performance implications of customer-linking capabilities: Examining the complementary role of customer orientation and CRM technology. J. Bus. Res. 63(11), 1229–1236 (2010)

    Article  Google Scholar 

  • Said, F., Zainal, D., Abdul Jalil, A.: Big data analytics capabilities (BDAC) and sustainability reporting on Facebook: Does tone at the top matter? Cogent Bus. Manage. 10(1), 2186745 (2023)

    Article  Google Scholar 

  • Sekaran, U., Bougie, R.: Research Methods for Business, A Skill Building Approach. John Willey & Sons. Inc., New York (2003)

    Google Scholar 

  • Sekaran, U., Bougie, R.: Research methods for business: A skill building approach. Language. 20(468p), 25 cm (2010)

    Google Scholar 

  • Shamim, S., Zeng, J., Khan, Z., Zia, N.U.: Big data analytics capability and decision making performance in emerging market firms: The role of contractual and relational governance mechanisms. Technol. Forecast. Soc. Chang. 161, 120315 (2020)

    Article  Google Scholar 

  • Šipuš, D.: Big data analytics for communication service providers Paper presented at the 2016 39th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO). (2016)

  • Spillane, J.P.: Data in practice: Conceptualizing the data-based decision-making phenomena. Am. J. Educ. 118(2), 113–141 (2012)

    Article  Google Scholar 

  • Sreemathy, J., Nisha, S., RM, G.P.: Data integration in ETL using TALEND Paper presented at the 2020 6th international conference on advanced computing and communication systems (ICACCS). (2020)

  • Srinivasan, R., Swink, M.: An investigation of visibility and flexibility as complements to supply chain analytics: An organizational information processing theory perspective. Prod. Oper. Manage. 27(10), 1849–1867 (2018)

    Article  Google Scholar 

  • Tannad, H., Andry, J.F.: The sustainable Logistics: Big Data Analytics and Internet of things. Int. J. Sustainable Dev. Plann., 18(2). (2023)

  • Tenenhaus, M.: PLS Path Modeling Computational Statistics & Data Analysis, v. 48. (2005)

  • Thirathon, U., Wieder, B., Matolcsy, Z., Ossimitz, M.-L.: Impact of big data analytics on decision making and performance Paper presented at the International conference on enterprise systems, accounting and logistics. (2017)

  • Tim, Y., Hallikainen, P., Pan, S.L., Tamm, T.: Actualizing business analytics for organizational transformation: A case study of Rovio Entertainment. Eur. J. Oper. Res. 281(3), 642–655 (2020)

    Article  Google Scholar 

  • Upadhyay, P., Kumar, A.: The intermediating role of organizational culture and internal analytical knowledge between the capability of big data analytics and a firm’s performance. Int. J. Inf. Manag. 52, 102100 (2020)

    Article  Google Scholar 

  • Vidgen, R., Shaw, S., Grant, D.B.: Management challenges in creating value from business analytics. Eur. J. Oper. Res. 261(2), 626–639 (2017)

    Article  Google Scholar 

  • Wamai, J., James, R., Tumuti, J.: Data Integration Capabilities and Performance of Commercial Banks in Kenya. (2022)

  • Wamba, S.F., Gunasekaran, A., Akter, S., Ren, S.J.-., Dubey, R., Childe, S.J.: Big data analytics and firm performance: Effects of dynamic capabilities. J. Bus. Res. 70, 356–365 (2017)

    Article  Google Scholar 

  • Wang, X., He, Y.: Learning from uncertainty for big data: Future analytical challenges and strategies. IEEE Syst. Man. Cybernetics Magazine. 2(2), 26–31 (2016)

    Article  Google Scholar 

  • Wetzels, M., Odekerken-Schröder, G., Van Oppen, C.: Using PLS path modeling for assessing hierarchical construct models: Guidelines and empirical illustration. MIS Q., 177–195. (2009)

  • Woerner, S.L., Wixom, B.H.: Big data: Extending the business strategy toolbox. J. Inform. Technol. 30(1), 60–62 (2015)

    Article  Google Scholar 

  • Worthington, R.L., Whittaker, T.A.: Scale development research: A content analysis and recommendations for best practices. Couns. Psychol. 34(6), 806–838 (2006)

    Article  Google Scholar 

  • Yasmin, M., Tatoglu, E., Kilic, H.S., Zaim, S., Delen, D.: Big data analytics capabilities and firm performance: An integrated MCDM approach. J. Bus. Res. 114, 1–15 (2020)

    Article  Google Scholar 

  • Yu, W., Wong, C.Y., Chavez, R., Jacobs, M.A.: Integrating big data analytics into supply chain finance: The roles of information processing and data-driven culture. Int. J. Prod. Econ. 236, 108135 (2021)

    Article  Google Scholar 

  • Zahid, H., Mahmood, T., Morshed, A., Sellis, T.: Big data analytics in telecommunications: Literature review and architecture recommendations. IEEE/CAA J. Automatica Sinica. 7(1), 18–38 (2019)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. MS Engineering Management, Riphah International University, Lahore, Pakistan

    Muhammad Umar Khan

  2. Institute of Quality & Technology Management, University of the Punjab, Lahore, Pakistan

    Iram Fatima

Authors
  1. Muhammad Umar Khan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Iram Fatima
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

M.U.K. conducted the study and write the initial draft, while I.F. conceptualized the study, supervised the study, revised the draft and critically reviewed it.

Corresponding author

Correspondence to Iram Fatima.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Khan, M.U., Fatima, I. The role of big data analytics capability in the telecommunication sector of Pakistan: the chain mediating effect of data integration capability and data-driven decision making. Qual Quant (2024). https://doi.org/10.1007/s11135-024-01923-9

Download citation

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s11135-024-01923-9

Keywords

Search

Navigation