Applying a Structured Industry Model Development Process to Support Digital Transformation Efforts: A Case Study of the Online Learning Industry

Applying a Structured Industry Model Development Process to Support Digital Transformation Efforts: A Case Study of the Online Learning Industry

Michael A. Erskine, Stoney Brooks, Christina DiValentin, Taylor Kendal
Copyright: © 2022 |Pages: 16
DOI: 10.4018/JECO.292475
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Abstract

While business models transformed how we describe organizations, the authors apply equivalent modeling to describe industries. Specifically, the authors propose and implement a structured industry model development process (SIMDP) based on the design science research methodology (DSRM). Moreover, our novel approach conceptualizes an industry model scaffolded through academic research and managerial guidance. An industry model creates a holistic view of any target industry to a) guide digital transformation efforts, b) reveal model components and linkages that may not be immediately evident, and c) support strategic decision-making within organizations considering the expansion and refinement of existing business models. The authors demonstrate the SIMDP’s efficacy using a case study of the online learning industry and evaluate the resulting industry model. Finally, the authors suggest future research directions and discuss the practical implications of the SIMDP and its resulting artifacts.
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Introduction

Changing customer expectations, fierce global competition, and rapid technological evolution have encouraged organizations in nearly every industry to respond by implementing digital transformation efforts. Digital transformation is “a process that aims to improve an entity by triggering significant changes to its properties through combinations of information, computing, communication, and connectivity technologies (Vial, 2019).” Such transformation efforts attempt to integrate digital technology throughout an organization’s core to remain relevant and maintain stakeholder value (Kim, 2020). Unlike digitizing and improving an organization’s process model, digital transformations attempt to digitize and improve the organization’s business model. Far from moving services online (digitization) or IT-enabled process improvements (digitalization) (Venkatesh et al., 2019), digital transformation is “a planned digital shock to what may be a reasonably functioning system” (Andriole, 2017, p. 2). Therefore, such transformation efforts effectively redefine the organization itself.

While some organizations have been reluctant to consider digital transformation due to the costs, talent shortages, and necessary cultural changes within the organization, the COVID-19 pandemic has demonstrated the benefits of effective digital transformation. For example, adopting digital business components prepared existing retailers with mechanisms to provide products during mandatory closures and stay-at-home orders that constrained physical shopping. However, digital transformation is not only about brick-and-mortar industries. Digital transformation efforts should not be constrained to organizations that have been slow to adopt digitization as such transformation can also benefit IT-enabled organizations that seek to remain relevant. For instance, a logistics provider may consider expanding into new markets by developing partnerships with sharing economy platform providers (e.g., Uber). Other IT-enabled industries, such as those grounded in e-commerce, also benefit.

While e-commerce organizations rely on a digital foundation, such organizations are not impervious to the need to consider ongoing digital transformation at the strategic level (e.g., Reinartz et al., 2019). Therefore, much digital strategy, transformation and business model research is in the context of e-commerce (e.g., Hansen & Sia, 2015; Kim, 2020). Contemporary e-commerce organizations might even consider creating ‘virtual’ organizations, supplemented through various digital partners, instead of attempting to control all organizational aspects (Simmons et al., 2013; Zott & Amit, 2013).

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