Linking Business Analytics to Decision Making Effectiveness: A Path Model Analysis

While business analytics is being increasingly used to gain data-driven insights to support decision making, little research exists regarding the mechanism through which business analytics can be used to improve decision-making effectiveness (DME) at the organizational level. Drawing on the information processing view and contingency theory, this paper develops a research model linking business analytics to organizational DME. The research model is tested using structural equation modeling based on 740 responses collected from U.K. businesses. The key findings demonstrate that business analytics, through the mediation of a data-driven environment, positively influences information processing capability, which in turn has a positive effect on DME. The findings also demonstrate that the paths from business analytics to DME have no statistical differences between large and medium companies, but some differences between manufacturing and professional service industries. Our findings contribute to the business analytics literature by providing useful insights into business analytics applications and the facilitation of data-driven decision making. They also contribute to managers' knowledge and understanding by demonstrating how business analytics should be implemented to improve DME.

[1]  Sidney E. Harris,et al.  Firm Size and the Information Technology Investment Intensity of LIfe Insurers , 1991, MIS Q..

[2]  Mark A. Mone,et al.  Formal Strategic Analyses and Organizational Performance: Decomposing the Rational Model , 2007 .

[3]  Deepak K. Datta,et al.  Strategic Decision Processes: Critical Review and Future Directions , 1993 .

[4]  Jim Lee,et al.  Does Size Matter in Firm Performance? Evidence from US Public Firms , 2009 .

[5]  John M. Ward,et al.  Beyond strategic information systems: towards an IS capability , 2004, J. Strateg. Inf. Syst..

[6]  Scott B. MacKenzie,et al.  Construct Measurement and Validation Procedures in MIS and Behavioral Research: Integrating New and Existing Techniques , 2011, MIS Q..

[7]  Raymond P. M. Chow,et al.  Market Orientation, Relationship Marketing Orientation, and Business Performance: The Moderating Effects of Economic Ideology and Industry Type , 2005 .

[8]  Andrew Schwarz,et al.  Examining the Impact of Multicollinearity in Discovering Higher-Order Factor Models , 2014, Commun. Assoc. Inf. Syst..

[9]  Sunil Mithas,et al.  Business Analytics: Radical Shift or Incremental Change? , 2012, Commun. Assoc. Inf. Syst..

[10]  Michael L. Tushman,et al.  Information Processing as an Integrating Concept in Organizational Design. , 1978 .

[11]  E. Sadler‐Smith Cognitive Style and the Management of Small and Medium-Sized Enterprises , 2004 .

[12]  Clyde W. Holsapple,et al.  A unified foundation for business analytics , 2014, Decis. Support Syst..

[13]  Marko Sarstedt,et al.  Partial least squares structural equation modeling (PLS-SEM): An emerging tool in business research , 2014 .

[14]  Veda C. Storey,et al.  Business Intelligence and Analytics: From Big Data to Big Impact , 2012, MIS Q..

[15]  Scott B. MacKenzie,et al.  Common method biases in behavioral research: a critical review of the literature and recommended remedies. , 2003, The Journal of applied psychology.

[16]  C. Fornell A Second generation of multivariate analysis : classification of methods and implications for marketing research , 1985 .

[17]  Tony S. Wirjanto,et al.  Path Dependence of Dynamic Information Technology Capability: An Empirical Investigation , 2011, J. Manag. Inf. Syst..

[18]  Hugh J. Watson,et al.  Tutorial: Big Data Analytics: Concepts, Technologies, and Applications , 2014, Commun. Assoc. Inf. Syst..

[19]  Straub,et al.  Editor's Comments: An Update and Extension to SEM Guidelines for Administrative and Social Science Research , 2011 .

[20]  T. Davenport,et al.  Data to Knowledge to Results: Building an Analytic Capability , 2001 .

[21]  Richard P. Bagozzi,et al.  Assessing Construct Validity in Organizational Research , 1991 .

[22]  Dominic Barton,et al.  Making advanced analytics work for you. , 2012, Harvard business review.

[23]  E. Iyer,et al.  Corporate Environmentalism: Antecedents and Influence of Industry Type , 2003 .

[24]  Vijay Khatri,et al.  Business analytics: Why now and what next? , 2014 .

[25]  Marko Sarstedt,et al.  Editorial - Partial Least Squares Structural Equation Modeling: Rigorous Applications, Better Results and Higher Acceptance , 2013 .

[26]  T. Davenport Competing on analytics. , 2006, Harvard business review.

[27]  D. Hickson,et al.  SUCCESS IN DECISION MAKING: DIFFERENT ORGANIZATIONS, DIFFERING REASONS FOR SUCCESS , 1995 .

[28]  Jay R. Galbraith Organization Design: An Information Processing View , 1974 .

[29]  Alex Pentland,et al.  Big Data and Management , 2014 .

[30]  Carol Stoak Saunders,et al.  Information Processing View of Organizations: An Exploratory Examination of Fit in the Context of Interorganizational Relationships , 2005, J. Manag. Inf. Syst..

[31]  Ing‐Chung Huang,et al.  Human capital disclosure and organizational performance , 2012 .

[32]  C. Perrow A FRAMEWORK FOR THE COMPARATIVE ANALYSIS OF ORGANIZATIONS , 1967 .

[33]  Claudia van Oppen,et al.  USING PLS PATH MODELING FOR ASSESSING HIERARCHICAL CONSTRUCT MODELS : GUIDELINES AND EMPIRICAL , 2022 .

[34]  William H. DeLone Firm Size and the Characteristics of Computer Use , 1981, MIS Q..

[35]  David A. Nadler,et al.  A model for diagnosing organizational behavior , 1980 .

[36]  Frank Moers,et al.  The Issue of Endogeneity within Theory-Based, Quantitative Management Accounting Research , 2007 .

[37]  Wynne W. Chin,et al.  Structural equation modeling analysis with small samples using partial least squares , 1999 .

[38]  Rolph E. Anderson,et al.  Multivariate Data Analysis (7th ed. , 2009 .

[39]  Blaize Horner Reich,et al.  IT alignment: what have we learned? , 2007, J. Inf. Technol..

[40]  P. Shrout,et al.  Mediation in experimental and nonexperimental studies: new procedures and recommendations. , 2002, Psychological methods.

[41]  Jayanth Jayaram,et al.  Contingency relationships of firm size, TQM duration, unionization, and industry context on TQM implementation - A focus on total effects , 2010 .

[42]  D. A. Kenny,et al.  The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. , 1986, Journal of personality and social psychology.

[43]  J. Hair Multivariate data analysis , 1972 .

[44]  Joan C. Woodward Management and technology , 1958 .

[45]  Anandhi S. Bharadwaj,et al.  A Resource-Based Perspective on Information Technology Capability and Firm Performance: An Empirical Investigation , 2000, MIS Q..

[46]  Terry S. Overton,et al.  Estimating Nonresponse Bias in Mail Surveys , 1977 .

[47]  Emilio Paolucci,et al.  Assessing the importance of industry in the adoption and assimilation of IT: Evidence from Italian enterprises , 2011, Inf. Manag..

[48]  D. Chambers,et al.  Strategic decision-making processes: the role of management and context , 1998 .

[49]  James T. C. Teng,et al.  Research Note - Do Large Firms Become Smaller by Using Information Technology? , 2013, Inf. Syst. Res..

[50]  Mark J. Zbaracki,et al.  Strategic decision making , 1992 .

[51]  Jeffrey R. Edwards,et al.  Reflections on Partial Least Squares Path Modeling , 2014 .

[52]  Henry L. Tosi,et al.  Contingency Theory: Some Suggested Directions , 1984 .

[53]  James D. Thompson,et al.  Technology, Organization, and Administration , 1957 .

[54]  M. Jelinek Technology, Organizations, and Contingency , 1977 .

[55]  I. Yeoman Competing on analytics: The new science of winning , 2009 .

[56]  Mark P. Sharfman,et al.  Does Decision Process Matter? A Study Of Strategic Decision-making Effectiveness , 1996 .

[57]  Peter Weill,et al.  An Assessment of the Contingency Theory of Management Information Systems , 1989, J. Manag. Inf. Syst..

[58]  Joe Peppard,et al.  Why IT Fumbles Analytics , 2013 .

[59]  Detmar W. Straub,et al.  Specifying Formative Constructs in Information Systems Research , 2007, MIS Q..

[60]  Varun Grover,et al.  Examining the Relational Benefits of Improved Interfirm Information Processing Capability in Buyer-Supplier Dyads , 2013, MIS Q..

[61]  P. Swamidass,et al.  Explaining manufacturing technology use, firm size and performance using a multidimensional view of technology , 1998 .