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A conceptual framework of the adoption of innovations in organizations: a meta-analytical review of the literature

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Abstract

Studies on the adoption of innovations in organizations are abundant and have introduced many different factors that are likely to influence adoption decisions yet, somehow, without an integrated view among them and with somehow contradictory empirical results. This study introduces a conceptual framework in which the attributes of innovation–adoption decision linkages in organizations are mediated by both the behavioral preferences of managers and organizations’ resources and moderated by the innovation life cycle. It further meta-analytically tests the framework’s predictions on 185 primary empirical studies. The findings are expected to contribute to the literature on the adoption of innovations by deepening the theoretical conditions and empirical factors that are likely to influence adoption decisions in organizations. The study also has implications for practice, since it sheds light on the factors that practitioners can leverage to manage the diffusion of innovations.

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References

  • Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In J. Kuhl & J. Beckmann (Eds.), Action-control: From cognition to behavior (pp. 11–39). Heidelberg: Springer.

    Google Scholar 

  • Ajzen, I. (1987). Attitudes, traits, and actions: Dispositional prediction of behavior in personality and social psychology. In L. Berkowitz (Ed.), Advances in experimental social psychology (pp. 1–63). New York: Academic Press.

    Google Scholar 

  • Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes,50(2), 179–211.

    Google Scholar 

  • Ajzen, I. (1996). The social psychology of decision making. In E. T. Higgins & A. W. Kruglanski (Eds.), Social psychology: Handbook of basic principles (pp. 297–325). New York, NY: Guilford.

    Google Scholar 

  • Ajzen, I., & Driver, B. L. (1992). Contingent value measurement: On the nature and meaning of willingess to pay. Journal of Consumer Psychology,1(4), 297–316.

    Google Scholar 

  • Alam, S. S., & Noor, M. K. M. (2009). ICT adoption in small and medium enterprises: An empirical evidence of service sectors in Malaysia. International Journal of Business and Management,4(2), 112–125.

    Google Scholar 

  • Alexandra, V., & Kassim, E. S. (2013). Factors of social networking use as a business tool among micro-enterprises. Paper presented at the 3rd international conference on research and innovation in information systems (ICRIIS), Kuala Lumpur, Malaysia, November 27–28, 2013.

  • Anderson, N., Potočnik, K., & Zhou, J. (2014). Innovation and creativity in organizations a state-of-the-science review, prospective commentary, and guiding framework. Journal of Management,40(5), 1297–1333.

    Google Scholar 

  • Angle, H. L., & Van de Ven, A. H. (1989). Suggestions for managing the innovation journey. In A. H. Van de Ven, H. L. Angle, & M. S. Poole (Eds.), Research on the management of innovation: The Minnesota studies (pp. 663–698). New York: Oxford University Press.

    Google Scholar 

  • Arend, R. J. (2014). Social and environmental performance at SMEs: Considering motivations, capabilities, and instrumentalism. Journal of Business Ethics,125(4), 541–561.

    Google Scholar 

  • Arpaci, I. (2013). Organizational adoption of mobile communication technologies. Ankara: Middle East Technical University.

    Google Scholar 

  • Arts, J. W. C., Frambach, R. T., & Bijmolt, T. H. A. (2011). Generalizations on consumer innovation adoption: A meta-analysis on drivers of intention and behavior. International Journal of Research in Marketing,28(2), 134–144.

    Google Scholar 

  • Attewell, P. (1992). Technology diffusion and organizational learning: The case of business computing. Organization Science,3(1), 1–19.

    Google Scholar 

  • Aubert, B. A., Schroeder, A., & Grimaudo, J. (2012). IT as enabler of sustainable farming: An empirical analysis of farmers’ adoption decision of precision agriculture technology. Decision Support Systems,54(1), 510–520.

    Google Scholar 

  • Bamberger, P. (2008). From the editors beyond contextualization: Using context theories to narrow the micro-macro gap in management research. Academy of Management Journal,51(5), 839–846.

    Google Scholar 

  • Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review,84(2), 191–215.

    Google Scholar 

  • Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management,17(1), 99–120.

    Google Scholar 

  • Bass, B. M., & Stogdill, R. M. (1990). Handbook of leadership. New York: The Free Press.

    Google Scholar 

  • Bauer, T. N., Bodner, T., Erdogan, B., Truxillo, D. M., & Tucker, J. S. (2007). Newcomer adjustment during organizational socialization: A meta-analytic review of antecedents, outcomes, and methods. Journal of Applied Psychology,92(3), 707.

    Google Scholar 

  • Begg, C. B. (1994). Publication bias. In H. Cooper & L. V. Hedges (Eds.), The handbook of research synthesis (pp. 399–409). New York: Russel Sage Foundation.

    Google Scholar 

  • Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological Bulletin,107(2), 238–246.

    Google Scholar 

  • Blalock, H. (1961). Causal inferences in nonexperimental research. Chapel Hill: University of North Carolina Press.

    Google Scholar 

  • Bobko, P., & Rieck, A. (1980). Large sample estimators for standard errors of functions of correlation coefficients. Applied Psychological Measurement,4(3), 385–398.

    Google Scholar 

  • Borenstein, M., Hedges, L. V., Higgins, J. P., & Rothstein, H. R. (2009). Introduction to meta-analysis. West Sussex: Wiley.

    Google Scholar 

  • Brown, R. L. (1997). Assessing specific mediational effects in complex theoretical models. Structural Equation Modeling: A Multidisciplinary Journal,4(2), 142–156.

    Google Scholar 

  • Bruque, S., & Moyano, J. (2007). Organisational determinants of information technology adoption and implementation in SMEs: The case of family and cooperative firms. Technovation,27(5), 241–253.

    Google Scholar 

  • Brynjolfsson, E., Hitt, L. M., & Yang, S. (2002). Intangible assets: Computers and organizational capital. Brookings Papers on Economic Activity,2002(1), 137–181.

    Google Scholar 

  • Bullock, R. J., & Svyantek, D. J. (1985). Analyzing meta-analysis: Potential problems, an unsuccessful replication, and evaluation criteria. Journal of Applied Psychology,70(1), 108–115.

    Google Scholar 

  • Caiazza, R. (2016). A cross-national analysis of policies affecting innovation diffusion. Journal of Technology Transfer,41(6), 1406–1419.

    Google Scholar 

  • Camisón-Zornoza, C., Lapiedra-Alcamí, R., Segarra-Ciprés, M., & Boronat-Navarro, M. (2004). A meta-analysis of innovation and organizational size. Organization Studies,25(3), 331–361.

    Google Scholar 

  • Camisón-Zornoza, C., & Villar-López, A. (2014). Organizational innovation as an enabler of technological innovation capabilities and firm performance. Journal of Business Research,67(1), 2891–2902.

    Google Scholar 

  • Carney, M., Gedajlovic, E. R., Heugens, P. P., Van Essen, M., & Van Oosterhout, J. H. (2011). Business group affiliation, performance, context, and strategy: A meta-analysis. Academy of Management Journal,54(3), 437–460.

    Google Scholar 

  • Chen, M.-J. (1996). Competitor analysis and interfirm rivalry: Toward a theoretical integration. Academy of Management Review,21(1), 100–134.

    Google Scholar 

  • Chen, J., Damanpour, F., & Reilly, R. R. (2010). Understanding antecedents of new product development speed: A meta-analysis. Journal of Operations Management,28(1), 17–33.

    Google Scholar 

  • Cheung, M. W. L. (2009). Comparison of methods for constructing confidence intervals of standardized indirect effects. Behavior Research Methods,41(2), 425–438.

    Google Scholar 

  • Cheung, M. W. L., & Chan, W. (2005). Meta-analytic structural equation modeling: A two-stage approach. Psychological Methods,10(1), 40–64.

    Google Scholar 

  • Cohen, J., & Cohen, P. (1983). Applied multiple regression/correlation analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum Associates Inc.

    Google Scholar 

  • Cohen, W. M., & Levinthal, D. A. (1990). Absorptive capacity: A new perspective on learning and innovation. Administrative Science Quarterly,35(1), 128–152.

    Google Scholar 

  • Colquitt, J. A., LePine, J. A., & Noe, R. A. (2000). Toward an integrative theory of training motivation: A meta-analytic path analysis of 20 years of research. Journal of Applied Psychology,85(5), 678.

    Google Scholar 

  • Cordano, M., & Frieze, I. H. (2000). Pollution reduction preferences of U.S. environmental managers: Applying Ajzen’s theory of planned behavior. Academy of Management Journal,43(4), 627–641.

    Google Scholar 

  • Crespo, Á. H., & del Bosque, I. R. (2008). The effect of innovativeness on the adoption of B2C e-commerce: A model based on the theory of planned behaviour. Computers in Human Behavior,24(6), 2830–2847.

    Google Scholar 

  • Crossan, M. M., & Apaydin, M. (2010). A multi-dimensional framework of organizational innovation: A systematic review of the literature. Journal of Management Studies,47(6), 1154–1191.

    Google Scholar 

  • Daft, R. L. (1978). A dual-core model of organizational innovation. Academy of Management Journal,21(2), 193–210.

    Google Scholar 

  • Damanpour, F. (1991). Organizational innovation: A meta-analysis of effects of determinants and moderators. Academy of Management Journal,34(3), 555–590.

    Google Scholar 

  • Damanpour, F., Walker, R. M., & Avellaneda, C. N. (2009). Combinative effects of innovation types and organizational performance: A longitudinal study of service organizations. Journal of Management Studies,46(4), 650–675.

    Google Scholar 

  • Daryanto, A., Khan, H., Matlay, H., & Chakrabarti, R. (2013). Adoption of country-specific business websites. The case of UK small businesses entering the Chinese market. Journal of Small Business and Enterprise Development,20(3), 650–660.

    Google Scholar 

  • Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly,13(4), 319–340.

    Google Scholar 

  • Downs, J. G. W., & Mohr, L. B. (1976). Conceptual issues in the study of innovation. Administrative Science Quarterly,21(4), 700–714.

    Google Scholar 

  • Dulany, D. E., Jr. (1961). Hypotheses and habits in verbal “operant conditioning”. Journal of Abnormal and Social Psychology,63(2), 251–263.

    Google Scholar 

  • Dutton, J. E., & Jackson, S. E. (1987). Categorizing strategic issues: Links to organizational action. Academy of Management Review,12(1), 76–90.

    Google Scholar 

  • Ettlie, J. E. (1983). Organizational policy and innovation among suppliers to the food processing sector. Academy of Management Journal,26(1), 27–44.

    Google Scholar 

  • Fern, E. F., & Monroe, K. B. (1996). Effect-size estimates: Issues and problems in interpretation. Journal of Consumer Research,23(2), 89–105.

    Google Scholar 

  • Fiedler, K., Schott, M., & Meiser, T. (2011). What mediation analysis can (not) do. Journal of Experimental Social Psychology,47(6), 1231–1236.

    Google Scholar 

  • Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley.

    Google Scholar 

  • Fisher, J. D., Fisher, W. A., Bryan, A. D., & Misovich, S. J. (2002). Information-motivation-behavioral skills model-based HIV risk behavior change intervention for inner-city high school youth. Health Psychology,21(2), 177–186.

    Google Scholar 

  • Frambach, R. T., & Schillewaert, N. (2002). Organizational innovation adoption. A multi-level framework of determinants and opportunities for future research. Journal of Business Research,55(2), 163–176.

    Google Scholar 

  • Gajendran, R. S., & Harrison, D. A. (2007). The good, the bad, and the unknown about telecommuting: Meta-analysis of psychological mediators and individual consequences. Journal of Applied Psychology,92(6), 1524–1541.

    Google Scholar 

  • Gallivan, M. J. (2001). Organizational adoption and assimilation of complex technological innovations: Development and application of a new framework. ACM SIGMIS Database,32(3), 51–85.

    Google Scholar 

  • Gamal Aboelmaged, M. (2010). Predicting e-procurement adoption in a developing country: An empirical integration of technology acceptance model and theory of planned behaviour. Industrial Management and Data Systems,110(3), 392–414.

    Google Scholar 

  • Ghobakhloo, M., & Tang, S. H. (2013). The role of owner/manager in adoption of electronic commerce in small businesses: The case of developing countries. Journal of Small Business and Enterprise Development,20(4), 754–787.

    Google Scholar 

  • Gómez, J., & Vargas, P. (2012). Intangible resources and technology adoption in manufacturing firms. Research Policy,41(9), 1607–1619.

    Google Scholar 

  • Gooding, R. Z., & Wagner, J. A. (1985). A meta-analytic review of the relationship between size and performance. Administrative Science Quarterly,30(3), 462–481.

    Google Scholar 

  • Gu, V. C., Cao, Q., & Duan, W. (2012). Unified Modeling Language (UML) IT adoption—A holistic model of organizational capabilities perspective. Decision Support Systems,54(1), 257–269.

    Google Scholar 

  • Gupta, P., Seetharaman, A., & Raj, J. R. (2013). The usage and adoption of cloud computing by small and medium businesses. International Journal of Information Management,33(5), 861–874.

    Google Scholar 

  • Hambrick, D. C., & Mason, P. A. (1984). Upper echelons: The organization as a reflection of its top managers. Academy of Management Review,9(2), 193–206.

    Google Scholar 

  • Hameed, M. A., Counsell, S., & Swift, S. (2012). A meta-analysis of relationships between organizational characteristics and IT innovation adoption in organizations. Information and Management,49(5), 218–232.

    Google Scholar 

  • Harland, P., Staats, H., & Wilke, H. A. (1999). Explaining proenvironmental intention and behavior by personal norms and the theory of planned behavior. Journal of Applied Social Psychology,29(12), 2505–2528.

    Google Scholar 

  • Harrison, D. A., Mykytyn, P. P., Jr., & Riemenschneider, C. K. (1997). Executive decisions about adoption of information technology in small business: Theory and empirical tests. Information Systems Research,8(2), 171–195.

    Google Scholar 

  • Hauser, J., Tellis, G. J., & Griffin, A. (2006). Research on innovation: A review and agenda for marketing science. Marketing Science,25(6), 687–717.

    Google Scholar 

  • He, Q., Duan, Y., Fu, Z., & Li, D. (2006). An innovation adoption study of online e-payment in chinese companies. Journal of Electronic Commerce in Organizations,4(1), 48–69.

    Google Scholar 

  • Henderson, D., Sheetz, S. D., & Trinkle, B. S. (2012). The determinants of inter-organizational and internal in-house adoption of XBRL: A structural equation model. International Journal of Accounting Information Systems,13(2), 109–140.

    Google Scholar 

  • Heyder, M., Theuvsen, L., & Hollmann-Hespos, T. (2012). Investments in tracking and tracing systems in the food industry: A PLS analysis. Food Policy,37(1), 102–113.

    Google Scholar 

  • Higgins, J., & Thompson, S. G. (2004). Controlling the risk of spurious findings from meta-regression. Statistics in Medicine,23(11), 1663–1682.

    Google Scholar 

  • Hossain, M. A., & Quaddus, M. (2015). Radio frequency identification (RFID) adoption: A cross-sectional comparison of voluntary and mandatory contexts. Information Systems Frontiers,17(5), 1057–1076.

    Google Scholar 

  • Hsing Wu, C., Kao, S.-C., & Lin, H.-H. (2013). Acceptance of enterprise blog for service industry. Internet Research,23(3), 260–297.

    Google Scholar 

  • Hsu, P.-F., Ray, S., & Li-Hsieh, Y.-Y. (2014). Examining cloud computing adoption intention, pricing mechanism, and deployment model. International Journal of Information Management,34(4), 474–488.

    Google Scholar 

  • Hung, S.-Y., Hung, W.-H., Tsai, C.-A., & Jiang, S.-C. (2010). Critical factors of hospital adoption on CRM system: Organizational and information system perspectives. Decision Support Systems,48(4), 592–603.

    Google Scholar 

  • Hussin, H., Nor, R. M., & Suhaimi, M. A. (2008). Perceived attributes of e-commerce and the adoption decision: The case of Malaysian SMEs. Jurnal Teknologi Maklumat and Multimedia,5(1), 107–125.

    Google Scholar 

  • Jackson, E. L. (2008). Behavioural determinants of the adoption of forward contracts by Western Australian wool producers. Curtin: Curtin University of Technology.

    Google Scholar 

  • Jarrett, S. M. (2003). Factors affecting the adoption of e-business in the aerospace industry. Nova: Nova Southeastern University.

    Google Scholar 

  • Jeon, B. N., Han, K. S., & Lee, M. J. (2006). Determining factors for the adoption of e-business: The case of SMEs in Korea. Applied Economics,38(16), 1905–1916.

    Google Scholar 

  • Jeyaraj, A., Rottman, J. W., & Lacity, M. C. (2006). A review of the predictors, linkages, and biases in IT innovation adoption research. Journal of Information Technology,21(1), 1–23.

    Google Scholar 

  • Kaplan, S. (2008). Cognition, capabilities, and incentives: Assessing firm response to the fiber-optic revolution. Academy of Management Journal,51(4), 672–695.

    Google Scholar 

  • Kapoor, K. K., Dwivedi, Y. K., & Williams, M. D. (2014a). Innovation adoption attributes: A review and synthesis of research findings. European Journal of Innovation Management,17(3), 327–348.

    Google Scholar 

  • Kapoor, K. K., Dwivedi, Y. K., & Williams, M. D. (2014b). Rogers’ innovation adoption attributes: A systematic review and synthesis of existing research. Information Systems Management,31(1), 74–91.

    Google Scholar 

  • Kaufmann, D., Kraay, A., & Mastruzzi, M. (2010). The worldwide governance indicators: A summary of methodology, data and analytical issues. World Bank policy research working paper (Vol. 5430).

  • Kennedy, M. T., & Fiss, P. C. (2009). Institutionalization, framing, and diffusion: The logic of TQM adoption and implementation decisions among U.S. hospitals. Academy of Management Journal,52(5), 897–918.

    Google Scholar 

  • Keupp, M. M., Palmié, M., & Gassmann, O. (2012). The strategic management of innovation: A systematic review and paths for future research. International Journal of Management Reviews,14(4), 367–390.

    Google Scholar 

  • Kimberly, J. R., & Evanisko, M. R. (1981). Organizational innovation: The influence of individual, organizational, and contextual factors on hospital adoption of technological and administrative innovations. Academy of Management Journal,24(4), 689–713.

    Google Scholar 

  • King, W. R., & He, J. (2006). A meta-analysis of the technology acceptance model. Information and Management,43(6), 740–755.

    Google Scholar 

  • Kurnia, S., Choudrie, J., Mahbubur, R. M., & Alzougool, B. (2015). E-commerce technology adoption: A Malaysian grocery SME retail sector study. Journal of Business Research,68(9), 1906–1918.

    Google Scholar 

  • Lau, R. R., Sigelman, L., Heldman, C., & Babbitt, P. (1999). The effects of negative political advertisements: A meta-analytic assessment. American Political Science Review,93(4), 851–875.

    Google Scholar 

  • Lee, Y., & Larsen, K. R. T. (2009). Threat or coping appraisal: Determinants of SMB executives’ decision to adopt anti-malware software. European Journal of Information Systems,18(2), 177–187.

    Google Scholar 

  • Lefebvre, L. A., Lefebvre, E., Elia, E., & Boeck, H. (2005). Exploring B-to-B e-commerce adoption trajectories in manufacturing SMEs. Technovation,25(12), 1443–1456.

    Google Scholar 

  • Lefebvre, L. A., Lefebvre, E., & Harvey, J. (1996). Intangible assets as determinants of advanced manufacturing technology adoption in SME’s: Toward an evolutionary model. IEEE Transactions on Engineering Management,43(3), 307–322.

    Google Scholar 

  • Leung, M. T. (2005). Determinants of the adoption of technological innovations in organizations. Hong Kong: Hong Kong Polythechnic University.

    Google Scholar 

  • Levin, S. G., Levin, S. L., & Meisel, J. B. (1987). A dynamic analysis of the adoption of a new technology: The case of optical scanners. Review of Economics and Statistics,69(1), 12–17.

    Google Scholar 

  • Li, X., Troutt, M. D., Brandyberry, A., & Wang, T. (2011). Decision factors for the adoption and continued use of online direct sales channels among SMEs. Journal of the Association for Information Systems,12(1), 1–31.

    Google Scholar 

  • Lieberman, M. B., & Montgomery, D. B. (1988). First-mover advantages. Strategic Management Journal,9(S1), 41–58.

    Google Scholar 

  • Lin, C.-Y., & Ho, Y.-H. (2011). Determinants of green practice adoption for logistics companies in China. Journal of Business Ethics,98(1), 67–83.

    Google Scholar 

  • Lin, C.-H., Lin, I.-C., Roan, J.-S., & Yeh, J.-S. (2012). Critical factors influencing hospitals’ adoption of HL7 version 2 standards: An empirical investigation. Journal of Medical Systems,36(3), 1183–1192.

    Google Scholar 

  • Lipsey, M. W., & Wilson, D. B. (2001). Practical meta-analysis. Thousand Oaks, CA: Sage.

    Google Scholar 

  • Livengood, R. S., & Reger, R. K. (2010). That’s our turf! Identity domains and competitive dynamics. Academy of Management Review,35(1), 48–66.

    Google Scholar 

  • Marcati, A., Guido, G., & Peluso, A. M. (2008). The role of SME entrepreneurs’ innovativeness and personality in the adoption of innovations. Research Policy,37(9), 1579–1590.

    Google Scholar 

  • March, J. G., & Simon, H. A. (1958). Organizations. New York: Wiley.

    Google Scholar 

  • Martinez-Garcıa, C. G., Dorward, P., & Rehman, T. (2013). Factors influencing adoption of improved grassland management by small-scale dairy farmers in central Mexico and the implications for future research on small holder adoption in developing countries. Livestock Science,152(2–3), 228–238.

    Google Scholar 

  • Messerschmidt, C. M., & Hinz, O. (2013). Explaining the adoption of grid computing: An integrated institutional theory and organizational capability approach. Journal of Strategic Information Systems,22(2), 137–156.

    Google Scholar 

  • Meyers, L. S., Gamst, G., & Guarino, A. J. (2006). Applied multivariate research: Design and interpretation. Thousand Oaks, CA: Sage.

    Google Scholar 

  • Miller, C. C., & Cardinal, L. B. (1994). Strategic planning and firm performance: A synthesis of more than two decades of research. Academy of Management Journal,37(6), 1649–1665.

    Google Scholar 

  • Miller, D., & Friesen, P. H. (1982). Innovation in conservative and entrepreneurial firms: Two models of strategic momentum. Strategic Management Journal,3(1), 1–25.

    Google Scholar 

  • Mitchell, T. R. (1985). An evaluation of the validity of correlational research conducted in organizations. Academy of Management Review,10(2), 192–205.

    Google Scholar 

  • Montazemi, A. R., & Qahri-Saremi, H. (2015). Factors affecting adoption of online banking: A meta-analytic structural equation modeling study. Information and Management,52(2), 210–226.

    Google Scholar 

  • Nasco, S. A., Toledo, E. G., & Mykytyn, P. P. (2008). Predicting electronic commerce adoption in Chilean SMEs. Journal of Business Research,61(6), 697–705.

    Google Scholar 

  • Nigbur, D., Lyons, E., & Uzzell, D. (2010). Attitudes, norms, identity and environmental behaviour: Using an expanded theory of planned behaviour to predict participation in a kerbside recycling programme. British Journal of Social Psychology,49(2), 259–284.

    Google Scholar 

  • North, D. C. (1990). Institutions, institutional change and economic performance. Cambridge: Cambridge University Press.

    Google Scholar 

  • Oliver, R. L., & Bearden, W. O. (1985). Crossover effects in the theory of reasoned action: A moderating influence attempt. Journal of Consumer Research,12(3), 324–340.

    Google Scholar 

  • Ozusaglam, S., Robin, S., & Wong, C. Y. (2018). Early and late adopters of ISO 14001-type standards: Revisiting the role of firm characteristics and capabilities. Journal of Technology Transfer,43(5), 1318–1345.

    Google Scholar 

  • Perrow, C. (1994). Accidents in high-risk systems. Technology Studies,1(1), 1–20.

    Google Scholar 

  • Pierce, J. L., & Delbecq, A. L. (1977). Organization structure, individual attitudes and innovation. Academy of Management Review,2(1), 27–37.

    Google Scholar 

  • Porter, B. E. (2005). Time and implementing change. British Journal of Educational Technology,36(6), 1063–1065.

    Google Scholar 

  • Powell, W. W., & DiMaggio, P. J. (2012). The new institutionalism in organizational analysis. Chicago: University of Chicago Press.

    Google Scholar 

  • Premkumar, G. (2003). A meta-analysis of research on information technology implementation in small business. Journal of Organizational Computing and Electronic Commerce,13(2), 91–121.

    Google Scholar 

  • Premkumar, G., & Roberts, M. (1999). Adoption of new information technologies in rural small businesses. Omega,27(4), 467–484.

    Google Scholar 

  • Quaddus, M., & Hofmeyer, G. (2007). An investigation into the factors influencing the adoption of B2B trading exchanges in small businesses. European Journal of Information Systems,16(3), 202–215.

    Google Scholar 

  • Reed, R., & DeFillippi, R. J. (1990). Causal ambiguity, barriers to imitation, and sustainable competitive advantage. Academy of Management Review,15(1), 88–102.

    Google Scholar 

  • Riemenschneider, C. K., Harrison, D. A., & Mykytyn, P. P. (2003). Understanding IT adoption decisions in small business: Integrating current theories. Information and Management,40(4), 269–285.

    Google Scholar 

  • Rivkin, J. W. (2000). Imitation of complex strategies. Management Science,46(6), 824–844.

    Google Scholar 

  • Riyadh, A. N., Rahman, A., & Tanha, M. (2012). Factors affecting internet adoption in the garments industry in Bangladesh: A structural equation modeling (SEM) approach. D.U. Journal of Marketing,15(1), 1–29.

    Google Scholar 

  • Rogers, E. M. (1983). Diffusion of innovations. New York: The Free Press.

    Google Scholar 

  • Rosenbusch, N., Brinckmann, J., & Bausch, A. (2011). Is innovation always beneficial? A meta-analysis of the relationship between innovation and performance in SMEs. Journal of Business Venturing,26(4), 441–457.

    Google Scholar 

  • Rosenbusch, N., Rauch, A., & Bausch, A. (2013). The mediating role of entrepreneurial orientation in the task environment–performance relationship: A meta-analysis. Journal of Management,39(3), 633–659.

    Google Scholar 

  • Rosenthal, R. (1979). The “file drawer problem” and tolerance for null results. Psychological Bulletin,86(3), 638–641.

    Google Scholar 

  • Rosenthal, R. (1991). Meta-analytical procedures for social research. Newbury Park, CA: Sage.

    Google Scholar 

  • Rosenthal, R., & Rubin, D. B. (1982). A simple, general purpose display of magnitude of experimental effect. Journal of Educational Psychology,74(2), 166.

    Google Scholar 

  • Ross, L. (1977). The intuitive psychologist and his short-comings. In L. Berkowitz (Ed.), Advances in experimental social psychology (Vol. 10, pp. 173–220). New York: Academic Press.

    Google Scholar 

  • Ryan, M. J. (1982). Behavioral intention formation: The interdependency of attitudinal and social influence variables. Journal of Consumer Research,9(3), 263–278.

    Google Scholar 

  • Schmidt, F. L., & Hunter, J. E. (2004). Methods of meta-analysis: Correcting error and bias in research findings. Thousand Oaks, CA: Sage.

    Google Scholar 

  • Schumpeter, J. A. (1934). The theory of economic development: An inquiry into profits, capital, credit, interest, and the business cycle. Cambridge, MA: Harvard University Press.

    Google Scholar 

  • Schwartz, S. H., & Howard, J. A. (1984). Internalized values as moderators of altruism. In E. Staub, D. Bar-Tal, J. Karylowski, & J. Reykowski (Eds.), Development and maintenance of prosocial behavior (pp. 229–255). New York, NY: Plenum.

    Google Scholar 

  • Scott, W. R. (2001). Institutions and organizations. Thousand Oaks, CA: Sage.

    Google Scholar 

  • Segaar, D., Bolman, C., Willemsen, M. C., & de Vries, H. (2006). Determinants of adoption of cognitive behavioral interventions in a hospital setting: Example of a minimal-contact smoking cessation intervention for cardiology wards. Patient Education and Counseling,61(2), 262–271.

    Google Scholar 

  • Seyal, A. H., & Rahman, M. N. A. (2003). A preliminary investigation of e-commerce adoption in small & medium enterprises in Brunei. Journal of Global Information Technology Management,6(2), 6–26.

    Google Scholar 

  • Shadish, W. R. (1996). Meta-analysis and the exploration of causal mediating processes: A primer of examples, methods, and issues. Psychological Methods,1(1), 47–65.

    Google Scholar 

  • Sheth, J. N. (1973). A model of industrial buyer behavior. Journal of Marketing,37(4), 50–56.

    Google Scholar 

  • Sobel, M. E. (1982). Asymptotic intervals for indirect effects in structural equations models. In S. Leinhart (Ed.), Sociological methodology (pp. 290–312). San Francisco: Jossey-Bass.

    Google Scholar 

  • Steadman, L., Rutter, D., & Field, S. (2002). Individually elicited versus modal normative beliefs in predicting attendance at breast screening: Examining the role of belief salience in the theory of planned behaviour. British Journal of Health Psychology,7(3), 317–330.

    Google Scholar 

  • Stern, P. C., Dietz, T., Abel, T., Guagnano, G. A., & Kalof, L. (1999). A value-belief-norm theory of support for social movements: The case of environmentalism. Human Ecology Review,6(2), 81–97.

    Google Scholar 

  • Subramanian, A., & Nilakanta, S. (1996). Organizational innovativeness: Exploring the relationship between organizational determinants of innovation, types of innovations, and measures of organizational performance. Omega,24(6), 631–647.

    Google Scholar 

  • Swanson, E. B. (1994). Information systems innovation among organizations. Management Science,40(9), 1069–1092.

    Google Scholar 

  • Tabachnick, B. G., & Fidell, L. S. (1996). Using multivariate statistics. New York: Harper & Collins.

    Google Scholar 

  • Tajfel, H., & Turner, J. C. (2004). The social identity theory of intergroup behavior. In J. T. Jost & J. Sidanius (Eds.), Key readings in social psychology. Political psychology (pp. 276–293). New York, NY: Psychology Press.

    Google Scholar 

  • Taylor, S., & Todd, P. (1995). Decomposition and crossover effects in the theory of planned behavior: A study of consumer adoption intentions. International Journal of Research in Marketing,12(2), 137–155.

    Google Scholar 

  • Teece, D. J. (1986). Profiting from technological innovation: Implications for integration, collaboration, licensing and public policy. Research Policy,15(6), 285–305.

    Google Scholar 

  • Thompson, S. H. T., Sijie, L., & Kee-hung, L. (2009). Adopters and non-adopters of e-procurement in Singapore: An empirical study. Omega,37(5), 972–987.

    Google Scholar 

  • Thong, J. Y. (1999). An integrated model of information systems adoption in small businesses. Journal of Management Information Systems,15(4), 187–214.

    Google Scholar 

  • Thong, J. Y. (2001). Resource constraints and information systems implementation in Singaporean small businesses. Omega,29(2), 143–156.

    Google Scholar 

  • Thong, J. Y., & Yap, C.-S. (1995). CEO characteristics, organizational characteristics and information technology adoption in small businesses. Omega,23(4), 429–442.

    Google Scholar 

  • Tidd, J. (2001). Innovation management in context: Environment, organization and performance. International Journal of Management Reviews,3(3), 169–183.

    Google Scholar 

  • Tolbert, P. S., & Zucker, L. G. (1983). Institutional sources of change in the formal structure of organizations: The diffusion of civil service reform, 1880–1935. Administrative Science Quarterly,28(1), 22–39.

    Google Scholar 

  • Tornatzky, L. G., & Klein, K. J. (1982). Innovation characteristics and innovation adoption-implementation: A meta-analysis of findings. IEEE Transactions on Engineering Management,29(1), 28–43.

    Google Scholar 

  • Triandis, H. C. (1979). Values, attitudes, and interpersonal behavior. Nebraska Symposium on Motivation,27(1), 195–259.

    Google Scholar 

  • Tsai, M.-C., Lee, W., & Wu, H.-C. (2010). Determinants of RFID adoption intention: Evidence from Taiwanese retail chains. Information and Management,47(5–6), 255–261.

    Google Scholar 

  • Tung, L. L., & Rieck, O. (2005). Adoption of electronic government services among business organizations in Singapore. Journal of Strategic Information Systems,14(4), 417–440.

    Google Scholar 

  • Uzoka, F.-M. E., & Ndzinge, T. (2009). Empirical analysis of biometric technology adoption and acceptance in Botswana. Journal of Systems and Software,82(9), 1550–1564.

    Google Scholar 

  • Vagnani, G., & Volpe, L. (2017). Innovation attributes and managers’ decisions about the adoption of innovations in organizations: A meta-analytical review. International Journal of Innovation Studies,1(2), 107–133.

    Google Scholar 

  • van Oorschot, J. A. W. H., Hofman, E., & Halman, J. I. M. (2018). A bibliometric review of the innovation adoption literature. Technological Forecasting and Social Change,134(9), 1–21.

    Google Scholar 

  • Viswesvaran, C., & Ones, D. S. (1995). Theory testing: Combining psychometric meta-analysis and strucutural equations modeling. Personnel Psychology,48(4), 865.

    Google Scholar 

  • Waarts, E., Everdingen, Y. M., & Hillegersberg, J. (2002). The dynamics of factors affecting the adoption of innovations. Journal of Product Innovation Management,19(6), 412–423.

    Google Scholar 

  • Wang, M. C., & Bushman, B. J. (1999). Integrating results through meta-analytic review using SAS software. Cary, NC: SAS Institute.

    Google Scholar 

  • Weigel, F. K., Hazen, B. T., Cegielski, C. G., & Hall, D. J. (2014). Diffusion of innovations and the theory of planned behavior in information systems research: A meta-analysis. Communications of the Association for Information Systems,34(1), 31–43.

    Google Scholar 

  • Weng, M.-H., & Lin, C.-Y. (2011). Determinants of green innovation adoption for small and medium-size enterprises (SMES). African Journal of Business Management,5(22), 9154–9163.

    Google Scholar 

  • Westphal, J. D., Gulati, R., & Shortell, S. M. (1997). Customization or conformity? An institutional and network perspective on the content and consequences of TQM adoption Administrative Science Quarterly,42(2), 366–394.

    Google Scholar 

  • Wolfe, R. A. (1994). Organizational innovation: Review, critique and suggested research. Journal of Management Studies,31(3), 405–431.

    Google Scholar 

  • Wolfswinkel, J. F., Furtmueller, E., & Wilderom, C. P. (2013). Using grounded theory as a method for rigorously reviewing literature. European Journal of Information Systems,22(1), 45–55.

    Google Scholar 

  • Wozniak, G. D. (1987). Human capital, information, and the early adoption of new technology. The Journal of Human Resources,22(1), 101–112.

    Google Scholar 

  • Xu, J., & Quaddus, M. (2012). Examining a model of knowledge management systems adoption and diffusion: A partial least square approach. Knowledge-Based Systems,27(1), 18–28.

    Google Scholar 

  • Zaltman, G., Duncan, R., & Holbek, J. (1973). Innovations and organizations. New York: Wiley.

    Google Scholar 

  • Zmud, R. W., & Apple, L. E. (1992). Measuring technology incorporation/infusion. Journal of Product Innovation Management,9(2), 148–155.

    Google Scholar 

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  1. Sapienza, University of Rome, 9, Castro Laurenziano Street, 00191, Rome, Italy

    Gianluca Vagnani, Corrado Gatti & Luca Proietti

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  1. Gianluca Vagnani
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Vagnani, G., Gatti, C. & Proietti, L. A conceptual framework of the adoption of innovations in organizations: a meta-analytical review of the literature. J Manag Gov 23, 1023–1062 (2019). https://doi.org/10.1007/s10997-019-09452-6

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