IT ambidexterity driven patient agility and hospital patient service performance: a variance approach

Hospitals are currently exploring digital options to transform their clinical procedures and their overall engagement with patients. This paper investigates how hospital departments can leverage the ability of firms to simultaneously explore new IT resources and practices (IT exploration) as well as exploit their current IT resources and practices (IT exploitation), i.e., IT ambidexterity, to adequately sense and respond to patients' needs and demands, i.e., patient agility. This study embraces the dynamic capability view and develops a research model, and tests it accordingly using cross-sectional data from 90 clinical hospital departments from the Netherlands through an online survey. The model's hypothesized relationships are tested using Partial Least Squares (PLS) structural equation modeling (SEM). The outcomes demonstrate the significance of IT ambidexterity in developing patient agility, positively influencing patient service performance. The study outcomes support the theorized model can the outcomes shed light on how to transform clinical practice and drive patient agility.

[1]  M. Sarstedt,et al.  A new criterion for assessing discriminant validity in variance-based structural equation modeling , 2015 .

[2]  Varun Grover,et al.  Investigating firm's customer agility and firm performance: The importance of aligning sense and respond capabilities , 2012 .

[3]  S. Kurnia,et al.  The Impact of EA-Driven Dynamic Capabilities, Innovativeness, and Structure on Organizational Benefits: A Variance and fsQCA Perspective , 2021, Sustainability.

[4]  Rogier van de Wetering,et al.  IT-Enabled Clinical Decision Support: An Empirical Study on Antecedents and Mechanisms , 2018 .

[5]  John C. Narver,et al.  The Effect of a Market Orientation on Business Profitability , 1990 .

[6]  Viswanath Venkatesh,et al.  Leveraging Digital Technologies: How Information Quality Leads to Localized Capabilities and Customer Service Performance , 2013, MIS Q..

[7]  P. Basch Quality of health care delivered to adults in the United States. , 2003, New England Journal of Medicine.

[8]  James A. Narus,et al.  Customer value propositions in business markets. , 2006, Harvard business review.

[9]  Andrew M. Farrell,et al.  Insufficient Discriminant Validity: A Comment on Bove, Pervan, Beatty and Shiu (2009) , 2008 .

[10]  Guido Schryen,et al.  Revisiting IS business value research: what we already know, what we still need to know, and how we can get there , 2013, Eur. J. Inf. Syst..

[11]  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.

[12]  R. van de Wetering,et al.  IT-Enabled Clinical Decision Support: An Empirical Study on Antecedents and Mechanisms , 2018, Journal of healthcare engineering.

[13]  William H. DeLone,et al.  IT resources, organizational capabilities, and value creation in public-sector organizations: a public-value management perspective , 2014, J. Inf. Technol..

[14]  E. Erdfelder,et al.  Statistical power analyses using G*Power 3.1: Tests for correlation and regression analyses , 2009, Behavior research methods.

[15]  B. Galliers,et al.  The Journal of Strategic Information Systems , 1996 .

[16]  Rogier van de Wetering,et al.  Enterprise Architecture Resources, Dynamic Capabilities, and their Pathways to Operational Value , 2019, ICIS.

[17]  F. Mavondo,et al.  Organisational capabilities: Antecedents and implications for customer value , 2008 .

[18]  Constantin Blome,et al.  Impact of IT Ambidexterity on New Product Development Speed: Theory and Empirical Evidence , 2019, Decis. Sci..

[19]  C. Gray Seeking Meaningful Innovation: Lessons Learned Developing, Evaluating, and Implementing the Electronic Patient-Reported Outcome Tool , 2020 .

[20]  Trisha Greenhalgh,et al.  Putting the social back into sociotechnical: Case studies of co-design in digital health , 2020, J. Am. Medical Informatics Assoc..

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

[22]  Hung-Tai Tsou,et al.  Performance effects of IT capability, service process innovation, and the mediating role of customer service , 2012 .

[23]  Yi Wang,et al.  IT capability and organizational performance: the roles of business process agility and environmental factors , 2014, Eur. J. Inf. Syst..

[24]  Rajdeep Grewal,et al.  Information Technology Competencies, Organizational Agility, and Firm Performance: Enabling and Facilitating Roles , 2013, Inf. Syst. Res..

[25]  Sharon Swee-Lin Tan,et al.  Electronic Health Records: How Can IS Researchers Contribute to Transforming Healthcare? , 2016, MIS Q..

[26]  C. Gibson,et al.  THE ANTECEDENTS , CONSEQUENCES , AND MEDIATING ROLE OF ORGANIZATIONAL AMBIDEXTERITY , 2004 .

[27]  Willem J. Selen,et al.  Dynamic Capability Building in Service Value Networks for Achieving Service Innovation , 2009, Decis. Sci..

[28]  Kathleen M. Eisenhardt,et al.  DYNAMIC CAPABILITIES, WHAT ARE THEY? , 2000 .

[29]  Kai H. Lim,et al.  How Does IT Ambidexterity Impact Organizational Agility? , 2015, Inf. Syst. Res..

[30]  Gianmario Verona,et al.  The Organizational Drivetrain: A Road To Integration of Dynamic Capabilities Research , 2014 .

[31]  F. Bookstein,et al.  Two Structural Equation Models: LISREL and PLS Applied to Consumer Exit-Voice Theory , 1982 .

[32]  Rogier van de Wetering,et al.  Examining the relationship between a hospital's IT infrastructure capability and digital capabilities: a resource-based perspective , 2018, AMCIS.

[33]  Samyadip Chakraborty,et al.  Impact of IoT Adoption on Agility and Flexibility of Healthcare Organization , 2019, International Journal of Innovative Technology and Exploring Engineering.

[34]  Spencer S Jones,et al.  Unraveling the IT productivity paradox--lessons for health care. , 2012, The New England journal of medicine.

[35]  Eric W. Ford,et al.  The Relationship Between Local Hospital IT Capabilities and Physician EMR Adoption , 2009, Journal of Medical Systems.

[36]  V. Narayanan,et al.  Strategic schemas, strategic flexibility, and firm performance: the moderating role of industry clockspeed , 2007 .

[37]  Varun Grover,et al.  Shaping Agility through Digital Options: Reconceptualizing the Role of Information Technology in Contemporary Firms , 2003, MIS Q..

[38]  Guy Paré,et al.  Knowledge barriers to PACS adoption and implementation in hospitals , 2007, Int. J. Medical Informatics.

[39]  Kecheng Liu,et al.  Integrated clinical pathway management for medical quality improvement – based on a semiotically inspired systems architecture , 2014, Eur. J. Inf. Syst..

[40]  C. Fornell,et al.  Evaluating structural equation models with unobservable variables and measurement error. , 1981 .

[41]  T. Salge,et al.  Hospital innovativeness and organizational performance: evidence from English public acute care. , 2009, Health care management review.

[42]  Eric Overby,et al.  Enterprise agility and the enabling role of information technology , 2006, Eur. J. Inf. Syst..

[43]  Huigang Liang,et al.  Why hospitals adopt patient engagement functionalities at different speeds? A moderated trend analysis , 2018, Int. J. Medical Informatics.

[44]  Rogier van de Wetering,et al.  Achieving digital-driven patient agility in the era of big data , 2021, I3E.

[45]  P. Drnevich,et al.  Clarifying the conditions and limits of the contributions of ordinary and dynamic capabilities to relative firm performance , 2011 .

[46]  Christopher A. Harle,et al.  Interactive systems for patient-centered care to enhance patient engagement , 2016, J. Am. Medical Informatics Assoc..

[47]  Mark Colgate,et al.  Customer Value Creation: A Practical Framework , 2007 .

[48]  Zi-Lin He,et al.  Exploration vs. Exploitation: An Empirical Test of the Ambidexterity Hypothesis , 2004, Organ. Sci..

[49]  F. Bookstein,et al.  Two Structural Equation Models: LISREL and PLS Applied to Consumer Exit-Voice Theory: , 1982 .

[50]  Paul A. Pavlou,et al.  The 'Third Hand': IT-Enabled Competitive Advantage in Turbulence Through Improvisational Capabilities , 2009, Inf. Syst. Res..

[51]  Rajeev Sharma,et al.  Information technology and the search for organizational agility: A systematic review with future research possibilities , 2019, J. Strateg. Inf. Syst..

[52]  Sinan Aral,et al.  I.T. Assets, Organizational Capabilities and Firm Performance: Do Resource Allocations and Organizational Differences Explain Performance Variation? , 2007 .

[53]  Rogier van de Wetering,et al.  IT ambidexterity and patient agility: the mediating role of digital dynamic capability , 2021, ECIS.

[54]  Rajiv Sabherwal,et al.  Information Technology Impacts on Firm Performance: An Extension of Kohli and Devaraj (2003) , 2015, MIS Q..

[55]  Jie Zhen,et al.  Impact of IT governance mechanisms on organizational agility and the role of top management support and IT ambidexterity , 2021, Int. J. Account. Inf. Syst..

[56]  Pei-Fang Hsu,et al.  Integrating ERP and e-business: Resource complementarity in business value creation , 2013, Decis. Support Syst..

[57]  Monideepa Tarafdar,et al.  How do a company's information technology competences influence its ability to innovate? , 2007, J. Enterp. Inf. Manag..

[58]  Indranil R. Bardhan,et al.  Health information technology and its impact on the quality and cost of healthcare delivery , 2013, Decis. Support Syst..

[59]  WeillPeter,et al.  IT Assets, Organizational Capabilities, and Firm Performance , 2007 .

[60]  Ing-Long Wu,et al.  Examining Knowledge Management Enabled Performance for Hospital Professionals: A Dynamic Capability View and the Mediating Role of Process Capability , 2012, J. Assoc. Inf. Syst..

[61]  R. Bakker,et al.  The Contribution of Conceptual Independence to IT Infrastructure Flexibility: The Case of openEHR , 2020 .

[62]  J. March Exploration and exploitation in organizational learning , 1991, STUDI ORGANIZZATIVI.

[63]  Tiago Oliveira,et al.  Mediation role of business value and strategy in firm performance of organizations using software-as-a-service enterprise applications , 2021, Inf. Manag..

[64]  Margaret A. Peteraf,et al.  Dynamic Capabilities and Organizational Agility: Risk, Uncertainty, and Strategy in the Innovation Economy , 2016 .

[65]  Rogier van de Wetering,et al.  Using a Co-Evolutionary is-Alignment Approach to Understand EMR Implementations , 2019, ECIS.

[66]  Ken G. Smith,et al.  The age of temporary advantage , 2010 .

[67]  Ned Kock,et al.  Lateral Collinearity and Misleading Results in Variance-Based SEM: An Illustration and Recommendations , 2012, J. Assoc. Inf. Syst..

[68]  Marko Sarstedt,et al.  Advanced Issues in Partial Least Squares Structural Equation Modeling , 2017 .

[69]  Shu Han,et al.  Changing the Competitive Landscape: Continuous Innovation Through IT-Enabled Knowledge Capabilities , 2010, Inf. Syst. Res..

[70]  Terence T. Ow,et al.  Examining the impact of information technology and patient flow on healthcare performance: A Theory of Swift and Even Flow (TSEF) perspective , 2013 .

[71]  M. V. van Velthoven,et al.  Sustainable Adoption of Digital Health Innovations: Perspectives From a Stakeholder Workshop , 2018, Journal of medical Internet research.

[72]  C. Steele Gray,et al.  Seeking Meaningful Innovation: Lessons Learned Developing, Evaluating, and Implementing the Electronic Patient-Reported Outcome Tool , 2020, Journal of medical Internet research.

[73]  J. Birkinshaw,et al.  THE ANTECEDENTS, CONSEQUENCES AND MEDIATING ROLE OF ORGANIZATIONAL AMBIDEXTERITY , 2004 .

[74]  A. Hayes Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach , 2013 .

[75]  Jan Muntermann,et al.  Paradoxes and the Nature of Ambidexterity in IT Transformation Programs , 2015, Inf. Syst. Res..