305
Views
0
CrossRef citations to date
0
Altmetric
Original Articles

Does Knowledge Sharing Belief of Data Analysts Impact Their Behavior?

ORCID Icon

References

  • Endres ML, Endres SP, Chowdhury SK, Alam I. Tacit knowledge sharing, self-efficacy theory, and application to the open source community. J Knowl Manag. 2007:11(3):92–103.
  • Obitade PO. Big data analytics: a link between knowledge management capabilities and superior cyber protection. J Big Data. 2019;6(1):1–28. doi:10.1186/s40537-019-0229-9.
  • Ghasemaghaei M. Does data analytics use improve firm decision making quality? The role of knowledge sharing and data analytics competency. Decision Support Systems. 2019;120:14–24. doi:10.1016/j.dss.2019.03.004.
  • Janssen M, van der Voort H, Wahyudi A. Factors influencing big data decision-making quality. J Bus Res. 2017;70:338–45. doi:10.1016/j.jbusres.2016.08.007.
  • Sivarajah U, Kamal MM, Irani Z, Weerakkody V. Critical analysis of Big Data challenges and analytical methods. J Bus Res. 2017;70:263–86. doi:10.1016/j.jbusres.2016.08.001.
  • Hsu M-H, Ju TL, Yen C-H, Chang C-M. Knowledge sharing behavior in virtual communities: the relationship between trust, self-efficacy, and outcome expectations. Int J Hum Comput Stud. 2007;65(2):153–69. doi:10.1016/j.ijhcs.2006.09.003.
  • Akter S, Wamba SF, Gunasekaran A, Dubey R, Childe SJ. How to improve firm performance using big data analytics capability and business strategy alignment? Int J Prod Econ. 2016;182:113–31. doi:10.1016/j.ijpe.2016.08.018.
  • Ghasemaghaei M, Calic G. Can big data improve firm decision quality? The role of data quality and data diagnosticity. Decis Support Syst. 2019;120:38–49. doi:10.1016/j.dss.2019.03.008.
  • Eslami SP, Hassanein K. Understanding Data Analytics Recommendation Execution: the Role of Recommendation Quality. J Comput Inf Syst. 2022;1–14. doi:10.1080/08874417.2021.2010150.
  • Gupta M, George JF. Toward the development of a big data analytics capability. Inf Manag. 2016;53(8):1049–64. doi:10.1016/j.im.2016.07.004.
  • Hannila H, Silvola R, Harkonen J, Haapasalo H. Data-driven begins with DATA; potential of data assets. J Comput Inf Syst. 2022;62(1):29–38. doi:10.1080/08874417.2019.1683782.
  • Cao G, Tian N, Blankson C. Big data, marketing analytics, and firm marketing capabilities. J Comput Inf Syst. 2021;1–10. doi:10.1080/08874417.2020.1842270.
  • Davenport TH, Prusak L. Working knowledge: managing what your organization knows. Boston (MA 210): Harvard Business School Press; 1998.
  • Using people analytics in HR | Deloitte Insights. [accessed 2019 February 8]. ttps://www2.deloitte.com/insights/us/en/focus/human-capital-trends/2017/people-analytics-in-hr.html.
  • Mennecke BE, Valacich JS. Information is what you make of it: the influence of group history and computer support on information sharing, decision quality, and member perceptions. J Manag Inf Syst. 1998;15(2):173–97. doi:10.1080/07421222.1998.11518213.
  • Varun Grover THD. General perspectives on knowledge management: fostering a research agenda. J Manag Inf Syst. 2001;18:5–21.
  • Hsseinoiun S, Abdullah R, Jusoh YY, Jabar M. Information System Success and Knowledge Grid Integration in Facilitating Knowledge Sharing Among Big Data Community. In: 2018 Fourth International Conference on Information Retrieval and Knowledge Management (CAMP). Kota Kinabalu (Malaysia): IEEE; 2018. p. 1–5.
  • Ajzen I. Attitudes, personality, and behavior. Homewood (IL): US. Dorsey Press; 1988 [accessed 2021 Aug]. http://www.101148/radiology166:3340772.
  • Ajzen I. The theory of planned behavior. Organ Behav Hum Decis Process. 1991;50(2):179–211. doi:10.1016/0749-5978(91)90020-T.
  • Notani AS. Moderators of perceived behavioral control’s predictiveness in the theory of planned behavior: a meta-analysis. J Consum Psychol. 1998;7(3):247–71. doi:10.1207/s15327663jcp0703_02.
  • Chae BK, Yang C, Olson D, Sheu C. The impact of advanced analytics and data accuracy on operational performance: a contingent resource based theory (RBT) perspective. Decis Support Syst. 2014;59:119–26. doi:10.1016/j.dss.2013.10.012.
  • Ghasemaghaei M, Hassanein K, Turel O. Increasing firm agility through the use of data analytics: the role of fit. Decision Support Systems. 2017;101:95–105. doi:10.1016/j.dss.2017.06.004.
  • Goodhue DL, Thompson RL. Task-technology fit and individual performance. MIS Q. 1995;19(2):213–36. doi:10.2307/249689.
  • Müller O, Fay M, Vom Brocke J. The effect of big data and analytics on firm performance: an econometric analysis considering industry characteristics. J Manag Inf Syst. 2018;35(2):488–509. doi:10.1080/07421222.2018.1451955.
  • Ghasemaghaei M. The role of positive and negative valence factors on the impact of bigness of data on big data analytics usage. Int J Inf Manage. 2020;50:395–404. doi:10.1016/j.ijinfomgt.2018.12.011.
  • Abbasi A, Zeng D, Chen Y, Chen H, Nunamaker JF Jr. Enhancing predictive analytics for anti-phishing by exploiting website genre information. J Manag Inf Syst. 2015;31(4):109–57. doi:10.1080/07421222.2014.1001260.
  • Ghasemaghaei M, Calic G. Does big data enhance firm innovation competency? The mediating role of data-driven insights. J Bus Res. 2019;104:69–84. doi:10.1016/j.jbusres.2019.07.006.
  • Grant RM. Prospering in dynamically-competitive environments: organizational capability as knowledge integration. Organ Sci. 1996;7(4):375–87. doi:10.1287/orsc.7.4.375.
  • Pearlson KE, Saunders CS, Galletta DF. Managing and using information systems: a strategic approach. Hoboken (NJ): John Wiley & Sons; 2019.
  • Wang Z, Sharma PN, Cao J. From knowledge sharing to firm performance: a predictive model comparison. J Bus Res. 2016;69(10):4650–58. doi:10.1016/j.jbusres.2016.03.055.
  • Szulanski G. Exploring internal stickiness: impediments to the transfer of best practice within the firm. Strateg Manag J. 1996;17(S2):27–43. doi:10.1002/smj.4250171105.
  • Bock G-W, Zmud RW, 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. 2005;29(1):87–111. doi:10.2307/25148669.
  • Ghasemaghaei M, Turel O. Possible negative effects of big data on decision quality in firms: the role of knowledge hiding behaviours. Inf Syst J. 2020;31(2):268–93.
  • Kalman ME. The effects of organizational commitment and expected outcomes on the motivation to share discretionary information in a collaborative database: communication dilemmas and other serious games. University of Southern California; 1999.
  • He W, Wei -K-K. What drives continued knowledge sharing? An investigation of knowledge-contribution and-seeking beliefs. Decis Support Syst. 2009;46(4):826–38. doi:10.1016/j.dss.2008.11.007.
  • Chow CW, Deng FJ, Ho JL. The openness of knowledge sharing within organizations: a comparative study of the United States and the People’s Republic of China. J Manag Account Res. 2000;12(1):65–95. doi:10.2308/jmar.2000.12.1.65.
  • Kalling T, Styhre A. Knowledge sharing in organizations. København: Copenhagen Business School Press; 2003.
  • Hsieh JP-A, Rai A, Keil M. Understanding digital inequality: comparing continued use behavioral models of the socio-economically advantaged and disadvantaged. MIS Q. 2008;32(1):97–126. doi:10.2307/25148830.
  • Pavlou PA, Fygenson M. Understanding and predicting electronic commerce adoption: an extension of the theory of planned behavior. MIS Q. 2006;30(1):115–43. doi:10.2307/25148720.
  • Sheppard BH, Hartwick J, Warshaw PR. The theory of reasoned action: a meta-analysis of past research with recommendations for modifications and future research. J Consum Res. 1988;15(3):325–43. doi:10.1086/209170.
  • Rhodes RE, Jones LW, Courneya KS. Extending the theory of planned behavior in the exercise domain: a comparison of social support and subjective norm. Res Q Exerc Sport. 2002;73(2):193–99. doi:10.1080/02701367.2002.10609008.
  • La Barbera F, Ajzen I. Control interactions in the theory of planned behavior: rethinking the role of subjective norm. Eur J Psychol. 2020;16(3):401. doi:10.5964/ejop.v16i3.2056.
  • Bock G-W, Kankanhalli A, Sharma S. Are norms enough? The role of collaborative norms in promoting organizational knowledge seeking. Eur J Inf Syst. 2006;15(4):357–67. doi:10.1057/palgrave.ejis.3000630.
  • Chennamaneni A, Teng JT, Raja MK. A unified model of knowledge sharing behaviours: theoretical development and empirical test. Behav Inf Technol. 2012;31(11):1097–115. doi:10.1080/0144929X.2011.624637.
  • Venkatraman N. Strategic orientation of business enterprises: the construct, dimensionality, and measurement. Manage Sci. 1989;35(8):942–62. doi:10.1287/mnsc.35.8.942.
  • Hambrick DC. Some tests of the effectiveness and functional attributes of Miles and Snow’s strategic types. Acad Manag Ann. 1983;26:5–26.
  • Burns T, Stalker GM. The management of innovation. London: Tavistock Publishing; 1961. Cited in Hurley, RF and Hult, GTM (1998) Innovation, Market Orientation, and Organisational Learning: An Integration and Empirical Examination Journal of Marketing 62:42–54.
  • Emery FE, Trist EL. The causal texture of organizational environments. Hum Relat. 1965;18(1):21–32. doi:10.1177/001872676501800103.
  • Lawrence P, Lorsch J. Organization and environment. Boston: Division of Research, Harvard Business School; 1967. LawrenceOrganization and Environment1967
  • Tosi HL Jr, Slocum JW Jr. Contingency theory: some suggested directions. J Manage. 1984;10(1):9–26. doi:10.1177/014920638401000103.
  • Hrebiniak LG, Joyce WF. Organizational adaptation: strategic choice and environmental determinism. Adm Sci Q. 1985;30(3):336–49. doi:10.2307/2392666.
  • Zajac EJ, Kraatz MS, Bresser RK. Modeling the dynamics of strategic fit: a normative approach to strategic change. Strateg Manag J. 2000;21:429–53.
  • Volberda HW, van der Weerdt N, Verwaal E, Stienstra M, Verdu AJ. Contingency fit, institutional fit, and firm performance: a metafit approach to organization–environment relationships. Organ Sci. 2012;23(4):1040–54. doi:10.1287/orsc.1110.0687.
  • Svetlik I, Stavrou-Costea E, Lin H-F. Knowledge sharing and firm innovation capability: an empirical study. Int J Manpow. 2007;28(3):315–32.
  • Bock GW, Kim Y-G. Breaking the myths of rewards: an exploratory study of attitudes about knowledge sharing. IRMJ. 2002;15(2):14–21. doi:10.4018/irmj.2002040102.
  • Cabrera Á, Collins WC, Salgado JF. Determinants of individual engagement in knowledge sharing. Int J Hum Resour Manag. 2006;17(2):245–64. doi:10.1080/09585190500404614.
  • Cavaliere V, Lombardi S, Giustiniano L. Knowledge sharing in knowledge-intensive manufacturing firms. An empirical study of its enablers. J Knowl Manag. 2015;19(6):1124–45. doi:10.1108/JKM-12-2014-0538.
  • Foss NJ, Husted K, Michailova S. Governing knowledge sharing in organizations: levels of analysis, governance mechanisms, and research directions. J Manag Stud. 2010;47(3):455–82. doi:10.1111/j.1467-6486.2009.00870.x.
  • Grodal S, Nelson AJ, Siino RM. Help-seeking and help-giving as an organizational routine: continual engagement in innovative work. Acad Manag Ann. 2015;58(1):136–68. doi:10.5465/amj.2012.0552.
  • Kankanhalli A, Tan BC, Wei -K-K. Understanding seeking from electronic knowledge repositories: an empirical study. J Am Soc Inf Sci Technol. 2005;56(11):1156–66. doi:10.1002/asi.20219.
  • Ghasemaghaei M, Ebrahimi S, Hassanein K. Data analytics competency for improving firm decision making performance. J Strateg Inf Syst. 2018;27(1):101–13. doi:10.1016/j.jsis.2017.10.001.
  • Strong DM, Volkoff O. Understanding organization—enterprise system fit: a path to theorizing the information technology artifact. MIS Q. 2010;34(4):731–56. doi:10.2307/25750703.
  • Bhattacherjee A, Premkumar G. Understanding changes in belief and attitude toward information technology usage: a theoretical model and longitudinal test. MIS Q. 2004;28(2):229–54. doi:10.2307/25148634.
  • Fishbein M, Ajzen I. Belief, attitude, intention, and behavior: an introduction to theory and research. Philos Rhetor. 1977;10(2):130–32.
  • Lee S, Lee H, Lee J. A study on relationship among knowledge state, IT support, knowledge sharing process and outcomes in startup teams. J Inf Technol Serv. 2016;15:173–93.
  • Morgeson FP, Humphrey SE. The Work Design Questionnaire (WDQ): developing and validating a comprehensive measure for assessing job design and the nature of work. J Appl Psychol. 2006;91(6):1321. doi:10.1037/0021-9010.91.6.1321.
  • Raghunathan S. Impact of information quality and decision-maker quality on decision quality: a theoretical model and simulation analysis. Decis Support Syst. 1999;26(4):275–86. doi:10.1016/S0167-9236(99)00060-3.
  • Burleson BR, Levine BJ, Samter W. Decision making procedure and decision quality. Hum Commun Res. 1984;10(4):557–74. doi:10.1111/j.1468-2958.1984.tb00032.x.
  • Eisenhardt KM, Martin JA. Dynamic capabilities: what are they? Strateg Manag J. 2000;21(10–11):1105–21. doi:10.1002/1097-0266(200010/11)21:10/11<1105::AID-SMJ133>3.0.CO;2-E.
  • Robert LP Jr, Dennis AR, Ahuja MK. Social Capital and Knowledge Integration in Digitally Enabled Teams. Inf Syst Res. 2008;19(3):314–34. doi:10.1287/isre.1080.0177.
  • Ickes W, Gonzalez R. ‘Social’ cognition and social cognition: from the subjective to the intersubjective. Small Group Research. 1994;25(2):294–315. doi:10.1177/1046496494252008.
  • Dumas TL, Phillips KW, Rothbard NP. Getting closer at the company party: integration experiences, racial dissimilarity, and workplace relationships. Organ Sci. 2013;24(5):1377–401. doi:10.1287/orsc.1120.0808.
  • Gnambs T, Kaspar K. Disclosure of sensitive behaviors across self-administered survey modes: a meta-analysis. Behav Res Methods. 2015;47(4):1237–59. doi:10.3758/s13428-014-0533-4.
  • Podsakoff PM, MacKenzie SB, Lee J-Y, Podsakoff NP. Common method biases in behavioral research: a critical review of the literature and recommended remedies. J Appl Psychol. 2003;88(5):879. doi:10.1037/0021-9010.88.5.879.
  • Churchill GA, Iacobucci D. Marketing research: methodological foundations. New York: Dryden Press; 2006.
  • Johnson JS, Friend SB, Lee HS. Big data facilitation, utilization, and monetization: exploring the 3Vs in a new product development process. J Prod Innov Manage. 2017;34(5):640–58. doi:10.1111/jpim.12397.
  • Joshi AW. When does customer orientation hinder (help) radical product innovation? The role of organizational rewards. J Prod Innov Manage. 2016;33(4):435–54. doi:10.1111/jpim.12301.
  • Reid SE, Roberts D, Moore K. Technology vision for radical innovation and its impact on early success. J Prod Innov Manage. 2015;32(4):593–609. doi:10.1111/jpim.12221.
  • Schleimer SC, Faems D. Connecting interfirm and intrafirm collaboration in NPD projects: does innovation context matter? J Prod Innov Manage. 2016;33(2):154–65. doi:10.1111/jpim.12296.
  • Armstrong JS, Overton TS. Estimating nonresponse bias in mail surveys. J Mark Res. 1977;14(3):396–402. doi:10.1177/002224377701400320.
  • Chen Y, Wang Y, Nevo S, Jin J, Wang L, Chow WS. IT capability and organizational performance: the roles of business process agility and environmental factors. Eur J Inf Syst. 2014;23(3):326–42. doi:10.1057/ejis.2013.4.
  • Ain N, Vaia G, DeLone WH, Waheed M. Two decades of research on business intelligence system adoption, utilization and success–A systematic literature review. Decis Support Syst. 2019;125:113113. doi:10.1016/j.dss.2019.113113.
  • Chen AJ, Watson RT, Boudreau M-C, Karahanna E. An institutional perspective on the adoption of Green IS & IT. Australas J Inf Syst. 2011;17(1). doi:10.3127/ajis.v17i1.572.
  • George JF, Gupta M, Giordano G, Mills AM, Tennant VM, Lewis CC. The effects of communication media and culture on deception detection accuracy. MIS Q. 2018;42(2):551–75. doi:10.25300/MISQ/2018/13215.
  • Wellman B. Doing it ourselves: the SPSS manual as sociology’s most influential recent book. Required reading: sociology’s most influential books. 1998. p. 71–78.
  • Benlian A, Koufaris M, Hess T. Service quality in software-as-a-service: developing the SaaS-Qual measure and examining its role in usage continuance. J Manag Inf Syst. 2011;28(3):85–126. doi:10.2753/MIS0742-1222280303.
  • Hair JF, Anderson RE, Tatham RL, Black WC. Multivariate data analysis with readings. Englewood Cliff (NJ): Prentce; 1995.
  • Bagozzi RP, Fornell C. Theoretical concepts, measurements, and meaning. In: Fomell, C, editor. A second generation of multivariate analysis. Vol. II: measurement and evaluation. New York: Praeger; 1982.
  • Cheung GW, Lau RS. Testing mediation and suppression effects of latent variables: bootstrapping with structural equation models. Organ Res Methods. 2008;11(2):296. doi:10.1177/1094428107300343.
  • Chen H, Chiang RH, Storey VC. Business intelligence and analytics: from big data to big impact. MIS Q. 2012;36(4):1165–88. doi:10.2307/41703503.
  • Ajzen H. Understanding attitudes and predicting social behavior. Englewood Cliffs; 1980.
  • Lin H-F, Lee -G-G 2004. Perceptions of senior managers toward knowledge-sharing behaviour. Management decision.
  • Davenport TH. The human side of Big Data and high-performance analytics. International Institute for Analytics. 2012;1(1):1–13.
  • Butler B, Sproull L, Kiesler S, Kraut R. Community effort in online groups: who does the work and why. Leadership at a Distance: Research in Technologically Supported Work. 2002;1:171–94.
  • Goswami AK, Agrawal RK. Explicating the influence of shared goals and hope on knowledge sharing and knowledge creation in an emerging economic context. J Knowl Manag. 2019;24(2):172–95.
  • Van Den Hooff B, De Ridder JA. Knowledge sharing in context: the influence of organizational commitment, communication climate and CMC use on knowledge sharing. J Knowl Manag. 2004;8(6):117–30. doi:10.1108/13673270410567675.
  • Chen DQ, Preston DS, Swink M. How the use of big data analytics affects value creation in supply chain management. J Manag Inf Syst. 2015;32(4):4–39. doi:10.1080/07421222.2015.1138364.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.