Advertisement

Quality & Quantity

, Volume 53, Issue 3, pp 1301–1324 | Cite as

Publishing? You can count on knowledge, experience, and expectations

  • Paulo Lopes HenriquesEmail author
  • Carla Curado
  • Mírian Oliveira
  • Antônio Carlos Gastaud Maçada
Article
  • 84 Downloads

Abstract

The study based on an online survey covering 655 researchers from hard and soft sciences addresses the influence of different conditions on academic publishing. Results show that (1) hard sciences academics publish more than soft sciences; (2) there are resemblances in academic publishing; (3) there are differences in the sufficient conditions sets for the two groups of sciences which may be explained by differences in scientific conceptual frameworks and research methods applied in each group of disciplines; (4) conditions leading to the absence of publishing reveal similarities and differences among hard and soft sciences academics. The study contribute to: (1) the debate on the questionable generalization of scientific publications indexes and rankings due to the nature of research published coming from different scientific universes; (2) identify pathways for achieving higher performance in academic publishing; (3) allow research centers’ managers to better manage the centers aiming to achieve upper output levels.

Keywords

Research antecedents Academic publishing productivity Hard sciences Soft sciences Qualitative comparative analysis 

Notes

Acknowledgements

The authors are grateful for the support provided by CAPES (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brazil), CNPq (Conselho Nacional de Desenvolvimento Científico e Tecnológico - Brazil) and FCT (Fundação para a Ciência e Tecnologia - Portugal) under the project UID/SOC/04521/2013.

References

  1. Abbott, A.: Chaos of Disciplines. University of Chicago Press, Chicago (2001)Google Scholar
  2. Abramo, G., Cicero, T., D’Angelo, C.: Revisiting size effects in higher education research productivity. High. Educ. 63(6), 701–717 (2012)Google Scholar
  3. Bäker, A.: Non-tenured post-doctoral researchers’ job mobility and research output: an analysis of the role of research discipline, department size, and coauthors. Res. Policy 44(3), 634–650 (2015)Google Scholar
  4. Barney, J.: Firm resources and sustained competitive advantage. J. Manag. 17(1), 99–120 (1991)Google Scholar
  5. Barney, J.: Resource-based theories of competitive advantage: a ten-year retrospective on the resource-based view. J. Manag 27, 643–650 (2001)Google Scholar
  6. Basedau, M., Richter, T.: Why do some oil exporters experience civil war but others not? Investigating the conditional effects of oil. Eur. Sci. Rev. 6(4), 549–574 (2014)Google Scholar
  7. Becher, T.: The significance of disciplinary differences. Stud. High. Educ. 19(2), 151–161 (1994)Google Scholar
  8. Bell, R.G., Filatotchev, I., Aguilera, R.V.: Corporate governance and investors’ perceptions of foreign IPO value: an institutional perspective. Acad. Manag J. 57(1), 301–320 (2014)Google Scholar
  9. Blau, P.M.: Power and Exchange in Social Life, p. 352. Wiley, New York (1964)Google Scholar
  10. Bock, G.W., Kim, Y.G.: Breaking the myths of rewards: an exploratory study of attitudes about knowledge sharing. Info. Resour. Manag. J. 15(2), 14–21 (2002)Google Scholar
  11. Bock, G.W., Zmud, R.W., Kim, Y.G., Lee, J.N.: Behavioral intention formation in knowledge sharing: examining: the roles of extrinsic motivators, social-psychological forces, and organizational climate. MIS Q. 29(1), 87–111 (2005)Google Scholar
  12. Bozeman, B., Gaughanb, M.: How do men and women differ in research collaborations? An analysis of the collaborative motives and strategies of academic researchers. Res. Policy 40(10), 1393–1402 (2015)Google Scholar
  13. Burke, L.A., James, K.: An empirical investigation of faculty research productivity and implications for practice. Int. J. Manag Pract. 1(2), 109–130 (2005)Google Scholar
  14. Chai, S., Shih, W.: Bridging science and technology through academic–industry partnerships. Res Policy 45(1), 148–158 (2016)Google Scholar
  15. Chennamaneni, A., Teng, J.T.C., Raja, M.K.: A unified model of knowledge sharing behaviours: theoretical development and empirical test. Behav. Inf. Technol 31(11), 1097–1115 (2012)Google Scholar
  16. Clement, R.W., Stevens, G.E.: Performance appraisal in higher education: comparing departments of management with other business units. Public Pers. Manage. 18(3), 263–279 (1989)Google Scholar
  17. Cohen, W.M., Levinthal, D.A.: Absorptive-capacity—a new perspective on learning and innovation. Adm. Sci. Q. 35(1), 128–152 (1990)Google Scholar
  18. Cook, G.A.: G.H. Mead’s social behaviorism. J. Hist. Behav. Sci. 13, 307–316 (1977)Google Scholar
  19. Cress, D.M., Snow, D.A.: The outcomes of homeless mobilization: the influence of organization, disruption, political mediation, and framing. Am. J. Sociol. 105(4), 1063–1104 (2000)Google Scholar
  20. Crilly, D.: Predicting stakeholder orientation in the multinational enterprise: amid-range theory. J. Int. Bus. Stud. 42(5), 694–717 (2011)Google Scholar
  21. Crilly, D., Zollo, M., Hansen, M.T.: Faking it or muddling through? Understanding decoupling in response to stakeholder pressures. Acad. Manage. J. 55(6), 1429–1448 (2012)Google Scholar
  22. Cruz-Castro, L., Sanz-Menéndez, L.: Mobility versus job stability: assessing tenure and productivity outcomes. Res. Policy 39(1), 27–39 (2010)Google Scholar
  23. Curado, C., Bontis, N.: The knowledge based-view of the firm and its theoretical precursor. Int. J. Learn. Intellect. Cap. 3(4), 367–381 (2006)Google Scholar
  24. Curado, C., Henriques, P.L., Oliveira, M., Matos, P.V.: A fuzzy-set analysis of hard and soft sciences publication performance. J. Bus. Res. 69(11), 5348–5353 (2016)Google Scholar
  25. De Meur, G., Rihoux, B.: L’Analyse Quali-Quantitative Comparée: Approche, Techniques et Applications en Sciences Humaines. Bruylant-Academia, Louvain-la-Neuve (2002)Google Scholar
  26. Emerson, R.M.: Social exchange theory. Annu. Rev. Sociol. 2, 335–362 (1976)Google Scholar
  27. Fiss, P.C.: A set-theoretic approach to organizational configurations. Acad. Manage. Rev. 32(4), 1180–1198 (2007)Google Scholar
  28. Fiss, P.C.: Building better causal theories: a fuzzy set approach to typologies in organization research. Acad. Manage. J. 54(2), 393–420 (2011)Google Scholar
  29. Fullwood, R., Rowley, J., Delbridge, R.: Knowledge sharing amongst academics in UK universities. J. Knowl. Manag. 17(1), 123–136 (2013)Google Scholar
  30. George-Walker, L., Tyler, M.A.: Collaborative concept mapping: connecting with research team capacities. Educ. Res. Int. 1–10. ID 836068 (2014)Google Scholar
  31. Geuna, A., Kataishi, R., Toselli, M., Guzmán, E., Lawson, C., Fernandez-Zubieta, A., Barros, B.: SiSOB data extraction and codification: a tool to analyze scientific careers. Res. Policy 44(9), 1645–1658 (2015)Google Scholar
  32. Gilbert, B.A., Campbell, J.T.: The geographic origins of radical technological paradigms: a configurational study. Res. Policy 44(2), 311–327 (2015)Google Scholar
  33. Gonzalez-Brambila, C., Veloso, F.M.: The determinants of research output and impact: a study of Mexican researchers. Res. Policy 36(7), 1035–1051 (2007)Google Scholar
  34. Gouldner, A.: For sociology. Am. J. Sociol. 78, 1063–1093 (1973)Google Scholar
  35. Grant, R.: Towards a knowledge-based view of the firm. Strateg. Manag. J. 17(s2), 109–122 (1996)Google Scholar
  36. Greckhamer, T., Misangyi, V.F., Elms, H., Lacey, R.: Using qualitative comparative analysis in strategic management research: an examination of industry, corporate, and business-unit effects. Organ. Res. Methods 11(4), 695–726 (2008)Google Scholar
  37. Hau, Y.S., Kim, B., Lee, H., Kim, Y.-G.: The effects of individual motivations and social capital on employees’ tacit and explicit knowledge sharing intentions. Int. J. Inf. Manag. 33(2), 356–366 (2013)Google Scholar
  38. Henriques, P.L., Curado, C.: Gender bias in promotion: is it real. Adv. Bus. Relat. Sci. Res. J. 4(2), 139–151 (2013)Google Scholar
  39. Hill, M., Hill, A.: Investigação por Questionário. Lisboa: Edições Sílabo (2002)Google Scholar
  40. Hitt, M., Bierman, L., Shimizu, K., Kockhar, R.: Direct and moderate effects of human capital on strategy and performance in professional service firms: a resource-based perspective. Acad. Manage. Rev. 44(1), 13–28 (2001)Google Scholar
  41. Homans, C.G.: Social behavior as exchange. Am. J. Sociol. 62, 597–606 (1958)Google Scholar
  42. Hsu, C.-L., Lin, J.C.-C.: Acceptance of blog usage: the roles of technology acceptance, social influence and knowledge sharing motivation. Inf. Manag. 45(1), 65–74 (2008)Google Scholar
  43. Huang, Q., Davison, R.M., Gu, J.: Impact of personal and cultural factors on knowledge sharing in China. Asia Pac. J. Manag. 25(3), 451–471 (2008)Google Scholar
  44. Hunter, L.A., Leahey, E.: Parenting and research productivity: new evidence and methods. Soc. Stud. Sci. 40(3), 433–451 (2010)Google Scholar
  45. Jung, J.: Faculty research productivity in Hong Kong across academic discipline. High. Educ. Stud. 2(4), 1–13 (2012)Google Scholar
  46. Kankanhalli, A., Tan, B.C.Y., Wei, K.-K.: Contributing knowledge to electronic knowledge repositories: an empirical investigation. MIS Q. 29(1), 113–143 (2005)Google Scholar
  47. Kaya, N., Weber, M.: Faculty research productivity: gender and discipline differences. J. Fam. Consu. Sci. 95(4), 46–52 (2003)Google Scholar
  48. Kim, K.K., Umanath, N.S., Kim, J.Y., Ahrens, F., Kim, B.: Knowledge complementarity and knowledge exchange in supply channel relationships. Int. J. Inf. Manag. 32(1), 35–49 (2012)Google Scholar
  49. Kogut, B., Zander, U.: Knowledge of the firm, combinative capabilities, and the replication of technology. Organ. Sci. 3(3), 383–397 (2012)Google Scholar
  50. Koys, D.J.: Judging academic qualifications, professional qualifications, and participation of faculty using AACSB guidelines. J. Educ. Bus. 83(4), 207–213 (2008)Google Scholar
  51. Kuo, T.H.: How expected benefit and trust influence knowledge sharing. Ind. Manag. Data Sys. 113(4), 506–522 (2013)Google Scholar
  52. Kyvik, S.: Changing trends in publishing behavior among university faculty 1980–2000. Scientmetr. 58(1), 35–48 (2003)Google Scholar
  53. Lee, S., Bozeman, B.: The impact of research collaboration on scientific productivity. Soc. Stud. Sci. 35(5), 673–702 (2005)Google Scholar
  54. Liao, L.: Knowledge-sharing in R&D departments: a social power and social exchange theory perspective. Int. J. Hum. Resour. Manag. 19(10), 1881–1895 (2008)Google Scholar
  55. Lin, H.F.: Knowledge sharing and firm innovation capacity: an empirical study. Int. J. Manpw. 28(3–4), 315–332 (2007)Google Scholar
  56. Lindner, J.R., Murphy, T.H., Briers, G.E.: Handling nonresponse in social science research. J. Agric. Educ. 42(4), 43–53 (2001)Google Scholar
  57. Mas-Verdú, F., Ribeiro-Soriano, D., Roig-Tierno, N.: Firm survival: the role of incubators and business characteristics. J. Bus. Res. 68(4), 793–796 (2015)Google Scholar
  58. Meng, Y.: Collaboration patterns and patenting: exploring gender distinctions. Res. Policy 45(1), 56–67 (2016)Google Scholar
  59. Meyer, A.D., Tsui, A.S., Hinings, C.R.: Configurational approaches to organizational analysis. Acad. Manag. J. 36(6), 1175–1195 (1993)Google Scholar
  60. Misangyi, V.F., Acharya, A.G.: Substitutes or complements? A configurational examination of corporate governance mechanisms. Acad. Manag. J. 57(6), 1681–1705 (2014)Google Scholar
  61. Podsakoff, P., MacKenzie, S., Lee, J., Podsakoff, N.: Common method biases in behavioral research: a critical review of the literature and recommended remedies. J. Appl. Psychol. 88, 879–903 (2003)Google Scholar
  62. Radhakrishna, R., Doamekpor, P.: Strategies for generalizing findings in survey research. J. Ext. On-line 46(2), 2TOT1 (2008)Google Scholar
  63. Ragin, C.C.: Fuzzy-Set Social Science. University of Chicago Press, Chicago (2000)Google Scholar
  64. Ragin, C.C.: Set relations in social research: evaluating their consistency and coverage. Political Anal. Adv. Access 5, 1–20 (2006)Google Scholar
  65. Ragin, C.C.: Redesigning Social Inquiry: Fuzzy Sets and Beyond. University of Chicago Press, Chicago (2008)Google Scholar
  66. Ragin, C.C.: Qualitative comparative analysis using fuzzy sets (fsQCA). In: Rihoux, B., Ragin, C.C. (eds.) Configurational Comparative Methods: Qualitative Comparative Analysis (QCA) and Related Techniques, pp. 87–121. Sage Publications, Thousand Oaks (2009)Google Scholar
  67. Ragin, C.C., Drass, K.A., Davey, S.: Fuzzy-set/qualitative comparative analysis, version 2.0. www.u.arizona.edu/~cragin/fsQCA/download/setup_fsQCA.exe (2003)
  68. Ragin, C.C., Fiss, P.C.: Net effects analysis versus configurational analysis: An empirical demonstration. In: Ragin, C.C. (ed.) Redesigning Social Inquiry: Fuzzy Sets and Beyond, pp. 190–212. University of Chicago Press, Chicago (2008)Google Scholar
  69. Reid, F.: Creating a knowledge-sharing culture among diverse business units. Employ. Relat. Today 30(3), 43–49 (2003)Google Scholar
  70. Rihoux, B., Ragin, C.C.: Configurational Comparative Methods: Qualitative Comparative Analysis (QCA) and Related Research. Sage, Los Angeles (2009)Google Scholar
  71. Ryoo, S.Y., Kim, K.K.: The impact of knowledge complementarities on supply chain performance through knowledge exchange. Expert Syst. Appl. 42(6), 3029–3040 (2015)Google Scholar
  72. Saad, A., Haron, H.: A case study of academics’ knowledge sharing motivations at Malaysian Public Academic Institutions. J. Educ. Vocat. Res. 4(9), 265–274 (2013)Google Scholar
  73. Sabharwala, M., Hub, Q.: Participation in university-based research centers: Is it helping or hurting researchers? Res. Policy 42(6–7), 1301–1311 (2013)Google Scholar
  74. Sakakibara, M.: Knowledge sharing in cooperative research and development. Manage. Decis. Econ. 24(2–3), 117–132 (2003)Google Scholar
  75. Schneider, C.Q., Wagemann, C.: Standards of good practice in qualitative comparative analisys (QCA) and fuzzy-sets. Comp. Sociol. 9, 1–22 (2010)Google Scholar
  76. Schneider, M.R., Schulze-Bentrop, C., Paunescu, M.: Mapping the institutional capital of high-tech firms: a fuzzy-set analysis of capitalist variety and export performance. J. Int. Bus. Stud. 41, 246–266 (2010)Google Scholar
  77. Seggie Steven, H., Griffith David, A.: What does it take to get promoted in marketing academia? Understanding exceptional publication productivity in the leading marketing journals. J. Mark. 73(1), 122–132 (2009)Google Scholar
  78. Sheehan, B.S., Welch, A.R.: The Australian academic profession. In: Altbach, P.G. (ed.) The International Academic Profession: Portraits of Fourteen Countries. Jossey-Bass Publishers, San Francisco (1996)Google Scholar
  79. Shepherd, C.D., Carley, S.S., Stuart, R.S.: An exploratory investigation of the periodic performance evaluation processes for marketing faculty: a comparison of doctoral granting and non-doctoral-granting universities. J. Mark. Educ. 31(2), 143–153 (2009)Google Scholar
  80. Shin, J.C., Cummings, W.K.: Multi-level analysis of academic publishing across discipline: research performance, collaboration, and time on research. Scientmetr. 85(2), 582–594 (2010)Google Scholar
  81. Smithson, M., Verkuilen, J.: Fuzzy Set Theory: Applications in the Social Sciences. Sage Publications, Thousand Oaks (2006)Google Scholar
  82. Stanton, A.D., Taylor, R.L., Stanaland, A.J.: An examination of the relationship between research attitudes and behaviors of business school faculty. Acad. Educ. Leadersh. J. 13, 37–50 (2009)Google Scholar
  83. Subramaniam, M., Venkatraman, N.: Determinants of transnational new product development capability: testing the influence of transferring and deploying tacit overseas knowledge. Strateg. Manag. J. 22(4), 359–378 (2001)Google Scholar
  84. Tartari, V., Salter, A.: The engagement gap: exploring gender differences in university—industry collaboration activities. Res. Policy 44(6), 1176–1191 (2015)Google Scholar
  85. Teodorescu, D.: Correlates of faculty publication productivity: a cross-national analysis. High. Educ. 39(2), 201–222 (2000)Google Scholar
  86. van Rijnsoever, F.J., Hessels, L.K., Vandeberg, R.L.J.: A resource-based view on the interactions of university researchers. Res. Policy 37(8), 1255–1266 (2008)Google Scholar
  87. Vasileiadou, E., Vliegenthart, R.: Research productivity in the era of the internet revisited. Res. Policy 38(8), 1260–1268 (2009)Google Scholar
  88. Webber, K.L.: Factors related to faculty research productivity and implications for academic planners. Plan. High. Educ. 39(4), 32–43 (2011)Google Scholar
  89. White, C.S., James, K., Burke, L.A., Allen, R.S.: What makes a “research star”? Factors influencing the research productivity of business faculty. Int. J. Prod. Perform. Manag. 61(6), 584–602 (2012)Google Scholar
  90. Willema, A., Buelens, M.: Knowledge sharing in inter-unit cooperative episodes: the impact of organizational structure dimensions. Int. J. Info. Manag. 29(2), 151–160 (2009)Google Scholar
  91. Woodside, A.G.: Moving beyond multiple regression analysis to algorithms: calling for adoption of a paradigm shift from asymmetric thinking in data analysis and crafting theory. J. Bus. Res. 66(4), 463–472 (2013)Google Scholar
  92. Woodside, A.G., Zhang, M.: Cultural diversity and marketing transactions: Are market integration, large community size, and world religions necessary for fairness in ephemeral exchanges? Psychol. Mark. 30(3), 263–276 (2013)Google Scholar
  93. Yao, Z., Yang, Z., Fisher, G.J., Ma, C., Fang, E.: Knowledge complementarity, knowledge absorption effectiveness, and new product performance: the exploration of international joint ventures in China. Int. Bus. Rev. 22(1), 216–227 (2013)Google Scholar
  94. Zadeh, L.A.: Fuzzy sets. Inf. Control 8, 338–353 (1965)Google Scholar
  95. Zadeh, L.A.: The role of fuzzy logic in the management of uncertainty in expert systems. Fuzzy Sets Syst. 11, 197–198 (1983)Google Scholar
  96. Zadeh, L.A.: Toward a theory of fuzzy information granulation and its centrality in human reasoning and fuzzy logic. Fuzzy Sets Syst. 90, 111–127 (1997)Google Scholar
  97. Zamarripa, E.J.: Evaluating research productivity. SRA J. 26(3–4), 17–27 (1994)Google Scholar
  98. Zappa, P.: The network structure of knowledge sharing among physicians. Qual. Quant. 45(5), 1109–1126 (2011)Google Scholar
  99. Zhou, Y., Volkwein, J.F.: Examining the influences on faculty department intentions: a comparison of tenured versus non-tenured faculty at research universities using NSOPF-99. Res. High. Educ. 45(2), 139–176 (2004)Google Scholar

Copyright information

© Springer Nature B.V. 2018

Authors and Affiliations

  1. 1.Advance/CSG - ISEG – Lisbon School of Economics & Management - Universidade de LisboaLisboaPortugal
  2. 2.Pontifical Catholic University of Rio Grande do Sul (PUCRS)Porto AlegreBrazil
  3. 3.Universidade Federal do Rio Grande do Sul (UFRGS)Porto AlegreBrazil

Personalised recommendations