Excess momentum or excess inertiado companies adopt technologies at the right time?

  1. Anna Daviy 1
  2. Elena Shakina 1
  1. 1 National Research University Higher School of Economics, Saint Petersburg, Russia
Revista:
European Research on Management and Business Economics

ISSN: 2444-8834

Ano de publicación: 2021

Volume: 27

Número: 3

Páxinas: 49-61

Tipo: Artigo

DOI: 10.1016/J.IEDEEN.2021.100174 DIALNET GOOGLE SCHOLAR

Outras publicacións en: European Research on Management and Business Economics

Resumo

Drawing on the literature on organizational change, technological change, and inertia, this paper explores how the moment that companies choose to initiate a technological change relative to other companies from the same regional and industrial context influences the company’s performance. In particular, we test the excess inertia and excess momentum phenomena that refer to timely and untimely technological shifts in companies. A data set comprising about 1000 of the largest Russian companies, affiliated with 19 industries, located in most of the Russian regions, for 10 years starting from 2008, is used. Applying a multi-level approach of hierarchical linear modeling, we estimated the region environment effect and the industry effect on sales and productivity. The use of moderation effects of the correspondent technology adoption with the average lag or lead from the representative company in the industry or region, could help us demonstrate what digital technologies are probably associated with the excess inertia and the excess momentum phe- nomena on the industry and regional level. The results reveal that the industry effect is a major determinant of firm productivity, whereas sales are mainly influenced by the region effect. Our investigation also found that companies are more likely to exhibit excess inertia rather than excess momentum.

Información de financiamento

Financiadores

Referencias bibliográficas

  • Abdolmohammadi, M. J. (2005). Intellectual capital disclosure and market capitaliza- tion. Journal of Intellectual Capital, 6(3), 397–416. doi:10.1108/ 14691930510611139.
  • Abeysekera, I. (2006). The project of intellectual capital disclosure: Researching the research. Journal of Intellectual Capital, 7(1), 61–75. doi:10.1108/ 14691930610639778.
  • Aksu, M., & Kosedag, A. (2006). Transparency and disclosure scores and their determi- nants in the istanbul stock exchange. Corporate Governance: An International Review, 14(4), 277–296. doi:10.1111/j.1467-8683.2006.00507.x.
  • Ali, M., & Miller, L. (2017). ERP system implementation in large enterprises−a system- atic literature review. Journal of Enterprise Information Management, 30(4), 666– 692.
  • Ancona, D. G., Goodman, P. S., Lawrence, B. S., & Tushman, M. L. (2001). Time: A new research lens. Academy of Management Review, 26(4), 645–663. doi:10.5465/ amr.2001.5393903.
  • Anderson, P., & Tushman, M. L. (1990). Technological Discontinuities and Dominant Designs: A Cyclical Model of Technological Change. Administrative Science Quar- terly, 35(4), 604–633. doi:10.2307/2393511.
  • Andrews, D., Nicoletti, G., & Timiliotis, C. (2018). Digital technology diffusion: A matter of capabilities, incentives or both? Paris: OECD Publishing. doi:10.1787/7c542c16- en.
  • Aral, S., Brynjolfsson, E., & Wu, D. J. (2006). Which came first, it or productivity? Virtu- ous cycle of investment and use in enterprise systems. Virtuous cycle of investment and use in enterprise systems, 1, 1819–1840.
  • Aral, S., & Weill, P. (2007). IT assets, organizational capabilities, and firm performance: How resource allocations and organizational differences explain performance vari- ation. Organization Science, 18(5), 763–780. doi:10.1287/orsc.1070.0306.
  • Bamiatzi, V., Bozos, K., Cavusgil, S. T., & Hult, G. T. M. (2016). Revisiting the firm, indus- try, and country effects on profitability under recessionary and expansion periods: A multilevel analysis: Firm, Industry, and Country Effects on Profitability. Strategic Management Journal, 37(7), 1448–1471. doi:10.1002/smj.2422.
  • Banker, R. D., Chang, H., & Kao, Y. (2002). Impact of Information technology on public accounting firm productivity. Journal of Information Systems, 16(2), 209–222. doi:10.2308/jis.2002.16.2.209.
  • Barnett, W. P., & Freeman, J. (2001). Too much of a good thing? Product proliferation and organizational failure. Organization Science, 12(5), 539–558. doi:10.1287/ orsc.12.5.539.10095.
  • Benitez-Amado, J., & Walczuch, R. M. (2012). Information technology, the organiza- tional capability of proactive corporate environmental strategy and firm performance: A resource-based analysis. European Journal of Information Systems, 21(6), 664–679. doi:10.1057/ejis.2012.14.
  • Besson, P., & Rowe, F. (2012). Strategizing information systems-enabled organizational transformation: A transdisciplinary review and new directions. The Journal of Stra- tegic Information Systems, 21(2), 103–124. doi:10.1016/j.jsis.2012.05.001.
  • Bresnahan, T. F., Brynjolfsson, E., & Hitt, L. M. (2002). Information technology, work- place organization, and the demand for skilled labor: Firm-level evidence. The Quarterly Journal of Economics, 117(1), 339–376. doi:10.1162/ 003355302753399526.
  • Brynjolfsson, E. (1993). The productivity paradox of information technology. Communi- cations of the ACM, 36(12), 66–77.
  • Brynjolfsson, E., Rock, D., & Syverson, C. (2017). Artificial intelligence and the modern productivity paradox: A clash of expectations and statistics (No. w24001; p. w24001). National Bureau of Economic Research. doi:10.3386/w24001.
  • Burton, R. M., Lauridsen, J., & Obel, B. (2002). Return on assets loss from situational and contingency misfits. Management Science, 48(11), 1461–1485. doi:10.1287/ mnsc.48.11.1461.262.
  • Chan, C. M., Makino, S., & Isobe, T. (2010). Does subnational region matter? Foreign affiliate performance in the United states and China. Strategic Management Journal, 31(11), 1226–1243. doi:10.1002/smj.854.
  • Chen, D.-. N., & Liang, T.-. P. (2011). Knowledge evolution strategies and organizational performance: A strategic fit analysis. Electronic Commerce Research and Applica- tions, 10(1), 75–84. doi:10.1016/j.elerap.2010.10.004.
  • Chen, W., & Srinivasan, S. (2020). Going digital: Implications for firm value and perfor- mance. Harvard Business School Working Paper, Boston. doi:10.26226/morressier 5f0c7d3058e581e69b05d0ea.
  • Chen, Y.-Y. K., Jaw, Y.-. L., & Wu, B.-. L. (2016). Effect of digital transformation on organ- isational performance of SMEs: Evidence from the Taiwanese textile industry’s web portal. Internet Research, 26(1), 186–212. doi:10.1108/IntR-12-2013-0265.
  • Cho, V. (2006). Factors in the adoption of third-party B2B portals in the textile industry. Journal of Computer Information Systems, 46(3), 18–31.
  • Colombo, M. G., & Delmastro, M. (2002). The determinants of organizational change and structural inertia: Technological and organizational factors. Journal of Econom- ics & Management Strategy, 11(4), 595–635.
  • Coluccia, D., Fontana, S., & Solimene, S. (2017). The influence of voluntary disclosure on the volatility of firms from a multi-stakeholder perspective. International Journal of Managerial and Financial Accounting, 9(1), 44–67. doi:10.1504/IJMFA.2017.084049.
  • Cusolito, A. P., Lederman, D., & Pe~na, J. (2020). The effects of digital-technology adoption on productivity and factor demand: Firm-level evidence from developing countries. World Bank, Washington. http://documents1.worldbank.org/curated/en/ 829161595512126439/pdf/The-Effects-of-Digital-Technology-Adoption-on-Productiv ity-and-Factor-Demand-Firm-level-Evidence-from-Developing-Countries.pdf.
  • Dalenogare, L. S., Benitez, G. B., Ayala, N. F., & Frank, A. G. (2018). The expected contri- bution of Industry 4.0 technologies for industrial performance. International Jour- nal of Production Economics, 204, 383–394. doi:10.1016/j.ijpe.2018.08.019.
  • DeGeest, D. S., & O’Boyle, E. H. (2014). Timing is everything: Multilevel event history analysis as a tool to model change over time in social ventures. Social entrepreneur- ship and research methods: 9 (pp. 215−240). Emerald Group Publishing Limited, Bingley. doi:10.1108/S1479-838720140000009016.
  • Digitalisation in Europe 2020-2021: Evidence from the EIB Investment Survey. (2021). European Investment Bank. https://www.eib.org/attachments/efs/digitalisation_i n_europe_2020_2021_en.pdf
  • Drisko, J., & Maschi, T. (2015). Content analysis. Content Analysis.
  • Dumay, J., & Cai, L. (2014). A review and critique of content analysis as a methodology for inquiring into IC disclosure. Journal of Intellectual Capital, 15(2), 264–290. doi:10.1108/JIC-01-2014-0010.
  • Engelst€atter, B. (2009). Enterprise systems and labor productivity: Disentangling com- bination effects (No. 09-040). ZEW Discussion Papers, Mannheim.
  • Erkan, A., Fainshmidt, S., & Judge, W. Q. (2016). Variance decomposition of the country, industry, firm, and firm-year effects on dividend policy. International Business Review, 25(6), 1309–1320.
  • Espinoza, H., Kling, G., McGroarty, F., O’Mahony, M., & Ziouvelou, X. (2020). Estimating the impact of the Internet of Things on productivity in Europe. Heliyon, 6(5), e03935. doi:10.1016/j.heliyon.2020.e03935.
  • Farrell, J., & Saloner, G. (1985). Standardization, Compatibility, and Innovation. The RAND Journal of Economics, 16(1), 70–83. doi:10.2307/2555589.
  • F avero, L. P. L., Serra, R. G., dos Santos, M. A., & Brunaldi, E. (2018). Cross-classified mul- tilevel determinants of firm’s sales growth in Latin America. International Journal of Emerging Markets, 13(5), 902–924. doi:10.1108/IJoEM-02-2017-0065.
  • Forman, C. (2005). The corporate digital divide: Determinants of internet adoption. Management Science, 51(4), 641–654. doi:10.1287/mnsc.1040.0343.
  • Franzosi, R. (2004). Content analysis. Handbook of Data Analysis, 547–565.
  • Galy, E., & Sauceda, M. J. (2014). Post-implementation practices of ERP systems and their relationship to financial performance. Information & Management, 51(3), 310–319. doi:10.1016/j.im.2014.02.002.
  • Gaur, A., & Kumar, M. (2018). A systematic approach to conducting review studies: An assessment of content analysis in 25 years of IB research. Journal of World Business, 53(2), 280–289. doi:10.1016/j.jwb.2017.11.003.
  • Goldszmidt, R. G. B., Brito, L. A. L., & de Vasconcelos, F. C. (2011). Country effect on firm performance: A multilevel approach. Journal of Business Research, 64(3), 273–279. doi:10.1016/j.jbusres.2009.11.012.
  • Griffith, R., Huergo, E., Mairesse, J., & Peters, B. (2006). Innovation and productivity across four european countries. Oxford Review of Economic Policy, 22(4), 483–498. doi:10.1093/oxrep/grj028.
  • Gurumurthy, R., Camhi, J., & David, S. (2020,. May 26). 2020 Digital transformation sur- vey | Deloitte Insights. https://www2.deloitte.com/us/en/insights/topics/digital- transformation/digital-transformation-survey.html
  • Gurumurthy, R., & Schatsky, D. (2019,. March 13). Digital Maturity Model and Digital Piv- ots | Deloitte Insights. https://www2.deloitte.com/us/en/insights/focus/digital-matu rity/digital-maturity-pivot-model.html
  • Haislip, J. Z., & Richardson, V. J. (2017). The effect of customer relationship manage- ment systems on firm performance. International Journal of Accounting Information Systems, 27, 16–29. doi:10.1016/j.accinf.2017.09.003.
  • Hannan, M. T., & Freeman, J. (1984). Structural inertia and organizational change. Amer- ican Sociological Review, 49(2), 149–164. doi:10.2307/2095567.
  • Hausberg, J. P., Liere-Netheler, K., Packmohr, S., Pakura, S., & Vogelsang, K. (2019). Research streams on digital transformation from a holistic business perspective: A systematic literature review and citation network analysis. Journal of Business Eco- nomics, 89(8−9), 931–963. doi:10.1007/s11573-019-00956-z.
  • Haveman, H. A. (1992). Between a rock and a hard place: organizational change and performance under conditions of fundamental environmental transformation. Administrative Science Quarterly, 37(1), 48–75. doi:10.2307/2393533.
  • Heilig, L., Lalla-Ruiz, E., & Voß, S. (2017). Digital transformation in maritime ports: Analysis and a game theoretic framework. NETNOMICS: Economic Research and Electronic Networking, 18(2−3), 227−254. https://doi.org/10.1007/s11066-017- 9122-x
  • Hirsch, S., & Schiefer, J. (2016). What causes firm profitability variation in the EU food industry? A redux of classical approaches of variance decomposition: WHAT CAUSES FIRM PROFITABILITY VARIATION IN THE EU FOOD INDUSTRY? Agribusi- ness, 32(1), 79–92. doi:10.1002/agr.21430.
  • Hitt, L. M., & Brynjolfsson, E. (1996). Productivity, business profitability, and consumer surplus: Three different measures of information technology value. MIS Quarterly, 20(2), 121–142. doi:10.2307/249475.
  • Hoppe, H. C. (2000). Second-mover advantages in the strategic adoption of new tech- nology under uncertainty. International Journal of Industrial Organization, 18(2), 315–338. doi:10.1016/S0167-7187(98)00020-4.
  • Hoppe, H. C. (2002). The timing of new technology adoption: theoretical models and empirical evidence. The Manchester School, 70(1), 56–76. doi:10.1111/1467- 9957.00283.
  • Hrebiniak, L. G., & Joyce, W. F. (1985). Organizational adaptation: strategic choice and environmental determinism. Administrative Science Quarterly, 30(3), 336–349. doi:10.2307/2392666.
  • Hur, J.-. Y., Cho, W., Lee, G., & Bickerton, S. H. (2019). The “Smart Work” Myth: How bureaucratic inertia and workplace culture stymied digital transformation in the Relocation of South Korea’s Capital. Asian Studies Review, 43(4), 691–709. doi:10.1080/10357823.2019.1663786.
  • ICT Development Index. (2017). International Telecommunication Union (ITU). https:// www.itu.int/net4/ITU-D/idi/2017/index.html
  • Kane, G. C., Palmer, D., Phillips, A. N., Kiron, D., & Buckley, N. (2016). Aligning the orga- nization for its digital future. MIT Sloan Management Review, 58(1), 1–27. https:// sloanreview.mit.edu/projects/aligning-for-digital-future/.
  • Kelly, D., & Amburgey, T. L. (1991). Organizational inertia and momentum: a dynamic model of strategic change. Academy of Management Journal, 34(3), 591–612. doi:10.5465/256407.
  • Korovkin, V. (2020). The digital life of russian regons 2020: What defines the digital divide? SKOLKOVO Institute for Emerging Market Studies (IEMS), Moscow.
  • Kotha, R., Zheng, Y., & George, G. (2011). Entry into new niches: The effects of firm age and the expansion of technological capabilities on innovative output and impact. Strategic Management Journal, 32(9), 1011–1024. doi:10.1002/smj.915.
  • Krippendorff, K. (1980). Content Analysis: An Introduction to Its Methodology.
  • Kumar, G. (2013). Voluntary disclosures of intangibles information by U.S.-listed Asian companies. Journal of International Accounting, Auditing and Taxation, 22(2), 109– 118. doi:10.1016/j.intaccaudtax.2013.07.002.
  • Lam, A. (2005). Organizational Innovation. In J. Fagerberg, D. Mowery, R. Nelson (Eds.), The oxford handbook of innovation (pp. 115−147). Oxford university press.
  • Lanzolla, G., & Suarez, F. F. (2012). Closing the Technology adoption−use divide: The role of contiguous user bandwagon. Journal of Management, 38(3), 836–859. doi:10.1177/0149206310369938.
  • Leonhardt, D., & Hanelt, A. (2018). Outsiders No More? An Empirical Investigation of the Effect of Digital Institutional Pressure on Corporate IT, 18, 1504–1520.
  • Li, D., Chau, P. Y., & Lai, F. (2010). Market orientation, ownership type, and e-business assimilation: Evidence from Chinese firms. Decision Sciences, 41(1), 115–145.
  • Li, L., Su, F., Zhang, W., & Mao, J.-. Y. (2018). Digital transformation by SME entrepre- neurs: A capability perspective. Information Systems Journal, 28(6), 1129–1157. doi:10.1111/isj.12153.
  • Lyytinen, K., & Newman, M. (2008). Explaining information systems change: A punctu- ated socio-technical change model. European Journal of Information Systems, 17(6), 589–613. doi:10.1057/ejis.2008.50.
  • Ma, X., Tao, F., Zhang, M., Wang, T., & Zuo, Y. (2019). Digital twin enhanced human- machine interaction in product lifecycle. Procedia CIRP, 83, 789–793. doi:10.1016/j. procir.2019.04.330.
  • Majumdar, S. K., & Bhattacharjee, A. (2014). Firms, markets, and the state: institutional change and manufacturing sector profitability variances in India. Organization Sci- ence, 25(2), 509–528. doi:10.1287/orsc.2013.0844.
  • Martin, C., & Leurent, H. (2017). Technology and innovation for the future of production: Accelerating value creation. Geneva Switzerland: World Economic Forum. http:// www3.weforum.org/docs/WEF_White_Paper_Technology_Innovation_Future_of_ Production_2017.pdf.
  • Melville, Kraemer, & Gurbaxani (2004). Review: Information technology and organiza- tional performance: an integrative model of IT business value. MIS Quarterly, 28(2), 283–322. doi:10.2307/25148636.
  • Milliou, C., & Petrakis, E. (2011). Timing of technology adoption and product market competition. International Journal of Industrial Organization, 29(5), 513–523. doi:10.1016/j.ijindorg.2010.10.003.
  • Morakanyane, R., Grace, A., & O’Reilly, P. (2017). Conceptualizing digital transformation in business organizations: A systematic review of literature. Digital Transformation − From Connecting Things to Transforming Our Lives, 427–443. doi:10.18690/978- 961-286-043-1.30.
  • Nicolaou, A. (2004). Firm performance effects in relation to the implementation and use of enterprise resource planning systems. Journal of Information Systems, 18(2), 79–105.
  • Nicoletti, G., von Rueden, C., & Andrews, D. (2020). Digital technology diffusion: A mat- ter of capabilities, incentives or both? European Economic Review, 128, 103513.
  • N u~nez-Merino, M., Maqueira-Marín, J. M., Moyano-Fuentes, J., & Martínez-Jurado, P. J. (2020). Information and digital technologies of Industry 4.0 and Lean supply chain management: A systematic literature review. International Journal of Production Research, 58(16), 5034–5061. doi:10.1080/ 00207543.2020.1743896.
  • Nuryyev, G., Wang, Y. P., Achyldurdyyeva, J., Jaw, B. S., Yeh, Y. S., Lin, H. T., et al. (2020). Blockchain technology adoption behavior and sustainability of the business in tourism and hospitality SMEs: An empirical study. Sustainability, 12(3), 1256.
  • Nwankpa, J., & Roumani, Y. (2016). IT capability and digital transformation: A firm per- formance perspective. ICIS 2016 Proceedings, 5, 3839–3854. https://aisel.aisnet.org/ icis2016/ISStrategy/Presentations/4.
  • Parshakov, P., & Shakina, E. (2020). Do companies disclose intellectual capital in their annual reports? New evidence from explorative content analysis. Journal of Intel- lectual Capital, 21(6), 853–871. doi:10.1108/JIC-03-2019-0040.
  • Paunov, C., & Planes-Satorra, S. (2019). How are digital technologies changing innova- tion?: Evidence from agriculture, the automotive industry and retail (OECD Science, Technology and Industry Policy Papers No. 74). Paris: OECD Publishing. https://doi. org/10.1787/67bbcafe-en.
  • Pejic-Bach, M., Bertoncel, T., Me sko, M., & Krsti c, Z. (2020). Text mining of industry 4.0 job advertisements. International Journal of Information Management, 50, 416–431. doi:10.1016/j.ijinfomgt.2019.07.014.
  • P erez-Nordtvedt, L., Payne, G. T., Short, J. C., & Kedia, B. L. (2008). An entrainment-based model of temporal organizational fit, misfit, and performance. Organization Science, 19(5), 785–801. doi:10.1287/orsc.1070.0330.
  • Piccoli, G., & Lui, T.-. W. (2014). The competitive impact of information technology: Can commodity IT contribute to competitive performance? European Journal of Infor- mation Systems, 23(6), 616–628. doi:10.1057/ejis.2013.20.
  • Quattrone, P., & Hopper, T. (2001). What does organizational change mean? Specula- tions on a taken for granted category. Management Accounting Research, 12(4), 403–435. doi:10.1006/mare.2001.0176.
  • Reeves, M., & Deimler, M. (2011). Adaptability: The new competitive advantage. July 1, (pp. 135−141). Boston: Harvard Business Review, July−August 2011. https://hbr. org/2011/07/adaptability-the-new-competitive-advantage.
  • Ritala, P., Huotari, P., Bocken, N., Albareda, L., & Puumalainen, K. (2018). Sustainable business model adoption among S&P 500 firms: A longitudinal content analysis study. Journal of Cleaner Production, 170, 216–226. doi:10.1016/j.jcle- pro.2017.09.159.
  • Ruivo, P., Oliveira, T., & Neto, M. (2014). Examine ERP post-implementation stages of use and value: Empirical evidence from Portuguese SMEs. International Journal of Accounting Information Systems, 15(2), 166–184. doi:10.1016/j.accinf.2014.01.002.
  • Rumelt, R. P. (1991). How much does industry matter? Strategic Management Journal, 12(3), 167–185. doi:10.1002/smj.4250120302.
  • Russia - Country Commercial Guide. Information & Communication Technology. (2020). Official Website of the International Trade Administration. https://www.trade.gov/ knowledge-product/russia-information-technologies
  • Russia Integrates: Deepening the Country’s Integration in the Global Economy. (2019). The World Bank. http://hdl.handle.net/10986/34994
  • Sabherwal, R., Jeyaraj, A., & Wright State University. (2015). Information technology impacts on firm performance: An Extension of Kohli and Devaraj (2003). MIS Quar- terly, 39(4), 809–836. doi:10.25300/MISQ/2015/39.4.4.
  • Sahaym, A., & Nam, D. (2013). International diversification of the emerging-market enterprises: A multi-level examination. International Business Review, 22(2), 421– 436.
  • S anchez-Sellero, P., S anchez-Sellero, M. C., S anchez-Sellero, F. J., & Cruz-Gonz alez, M. M. (2015). Effects of innovation on technical progress in Spanish manufacturing firms. Science, Technology and Society, 20(1), 44–59. doi:10.1177/ 0971721814561396.
  • Sastry, M. A. (1997). Problems and paradoxes in a model of punctuated organizational change. Administrative Science Quarterly, 42(2), 237–275. doi:10.2307/2393920.
  • Sebastian, I. M., Ross, J. W., Beath, C., Mocker, M., Moloney, K. G., & Fonstad, N. O. (2017). How big old companies navigate digital transformation. MIS Quarterly Executive, 16(3), 197–213. https://aisel.aisnet.org/misqe/vol16/iss3/6.
  • Shakina, E., Parshakov, P., & Alsufiev, A. (2021). Rethinking the corporate digital divide: The complementarity of technologies and the demand for digital skills. Technologi- cal Forecasting and Social Change, 162, 120405. doi:10.1016/j. techfore.2020.120405.
  • Short, J. C., Ketchen, D. J., Bennett, N., & du Toit, M. (2006). An examination of firm, industry, and time effects on performance using random coefficients modeling. Organizational Research Methods, 9(3), 259–284. doi:10.1177/1094428106287572.
  • Short, J. C., McKenny, A. F., Ketchen, D. J., Snow, C. C., & Hult, G. T. M. (2016). An empiri- cal examination of firm, industry, and temporal effects on corporate social perfor- mance. Business & Society, 55(8), 1122–1156. doi:10.1177/0007650315574848.
  • Sousa-Zomer, T. T., Neely, A., & Martinez, V. (2020). Digital transforming capability and performance: A microfoundational perspective. International Journal of Operations & Production Management, ahead-of-print(ahead-of-print), 1095–1128. doi:10.1108/IJOPM-06-2019-0444.
  • Suarez, F., & Lanzolla, G. (2005). The half-truth of first-mover advantage. Harvard busi- ness review, 83(4), 121–134.
  • Tallman, S., Jenkins, M., Henry, N., & Pinch, S. (2004). Knowledge, clusters, and compet- itive advantage. Academy of management review, 29(2), 258–271.
  • Ta ̧stan, H., & G€onel, F. (2020). ICT labor, software usage, and productivity: Firm-level evidence from Turkey. Journal of Productivity Analysis, 53(2), 265–285.
  • The Global Innovation Index 2020: Who Will Finance Innovation? (2020).Cornell Univer- sity, INSEAD, and WIPO. https://www.wipo.int/edocs/pubdocs/en/wipo_pub_ gii_2020.pdf
  • Thelwall, M., & Sud, P. (2012). Webometric research with the Bing Search API 2.0. Jour- nal of Informetrics, 6(1), 44–52. doi:10.1016/j.joi.2011.10.002.
  • Tushman, M. L., & Anderson, P. (1986). Technological discontinuities and organiza- tional environments. Administrative Science Quarterly, 31(3), 439–465. doi:10.2307/2392832.
  • Tushman, M. L., & Romanelli, E. (1985). Organizational evolution: A metamorphosis model of convergence and reorientation. Research in Organizational Behavior, 7, 171–222.
  • Tushman, M. L., & Smith, W. K. (2002). Organizational technology. The blackwell com- panion to organizations (pp. 386−414). Wiley-Blackwell, Boston.
  • UN Secretary-General’s Data Strategy 2020-22. (2020). UNITED NATIONS. https://www. un.org/en/content/datastrategy/images/pdf/UN_SG_Data-Strategy.pdf
  • Vial, G. (2019). Understanding digital transformation: A review and a research agenda. The Journal of Strategic Information Systems, 28(2), 118–144. doi:10.1016/j. jsis.2019.01.003.
  • Volberda, H. W., van der Weerdt, N., Verwaal, E., Stienstra, M., & Verdu, A. J. (2012). Contingency fit, institutional fit, and firm performance: A metafit approach to organization−environment relationships. Organization Science, 23(4), 1040–1054. doi:10.1287/orsc.1110.0687.
  • Wang, C. C., & Lin, G. C. S. (2008). The Growth and Spatial Distribution of China’s ICT Industry: New Geography of Clustering and Innovation, 49.
  • Wu, I.-. L., & Chen, J.-. L. (2014). A stage-based diffusion of IT innovation and the BSC performance impact: A moderator of technology−organization−environment. Technological Forecasting and Social Change, 88, 76–90. doi:10.1016/j.tech- fore.2014.06.015.
  • UNDP Digital Strategy. (2019). UNDP. 44(2), 145−192. Retrieved from https://digital strategy.undp.org/
  • Zouaghi, F., Hirsch, S., Garcia, M.S., .Zouaghi, F., Hirsch, S., & Garcia, M.S. (.2016). WHAT DRIVES FIRM PROFITABILITY? A MULTILEVEL APPROACH TO THE SPANISH AGRI-FOOD SECTOR. https://doi.org/10.22004/AG.ECON.244762