Innovation in e-Business Models: a Net-Enabled Business Innovation Cycle (NEBIC) Theory Perspective
Bibliographic record
Abstract
Despite potentially increased sales and operational efficiencies, a surprising number of firms have not adopted e-business. Annual surveys of e-business use in Canada and other Organization for Economic Co-operation and Development (OECD) countries reveal significant differences in adoption rates between sectors. The surveys identify product characteristics as a key rationale for not adopting online selling. There are examples, however, of firms in all sectors that have discovered how to use online selling (i.e., through direct retailing, portals, online auctions - or other models). This research identifies the key internal capabilities that let firms implement online selling tools and reconfigure their way of doing business, by innovating their business model, to take advantage of e-business. \n \nWheeler’s (2002) Net-Enabled Business Innovation Cycle (NEBIC) model is a theoretical framework for studying the process of implementing e-business tools as technology innovations for business growth where “net-enablement” refers to a firm’s innovative use of networks connected via information technologies. The NEBIC model suggests four sets of capabilities a firm needs to create value for its customers by utilizing technology: choosing enabling technologies, matching technology benefits with economic opportunities, executing business innovation for growth, and assessing customer value. The model is grounded in dynamic capability and absorptive capacity theories, offering an integrated way to adopt an e-business application, such as online selling, using internal capabilities that management can develop through planning, knowledge acquisition, training, and recruitment. \n \nThis research is the first to operationalize the constructs in the NEBIC model and increase the understanding of the firm capabilities required to implement online selling as a technology innovation for business growth. The study also extends the NEBIC model by developing a construct to measure the innovation in business models firms need as they implement online selling tools. Data gathered from a national sample of Canadian firms are analyzed to test four hypotheses. These concern net-enablement capabilities, and the selection and implementation of online selling, together with the associated outcome of such innovation in terms of business model innovation. \n \nThe overarching hypothesis is that firms that successfully select and implement online selling have better developed net-enablement capabilities. Further, those firms will innovate their business model. The research to test these hypotheses proceeded in two stages. First, exploratory research accessed both current literature and feedback from academic and professional experts to identify and develop scales and measurements for the net-enablement constructs of the research model. In the second empirical stage, these scales were used to measure capability development and business model innovation in a cross-section sample of Canadian firms. Responses to an online survey were analyzed to test the statistical properties of the scales, and structural equation modeling (SEM) assessed the hypothesized relationships between net-enablement capability for online selling and actual business model innovation. \n \nThe research contributes to the literature on e-business adoption, and the application of dynamic capability and absorptive capability theories for technology adoption. In particular, it provides empirical support for Wheeler’s NEBIC model for e-business tools selection and implementation. The data confirm that firms with better-developed net-enablement capabilities are more likely to select and implement online selling tools successfully. The data also substantiate the view that online sellers have indeed innovated their business models to incorporate the practical tools of online selling. \n \nPractitioners considering extending their market through online sales are advised to assess their net-enablement capability first. The scales developed through this research provide a tool for identifying these important capabilities and routines within organizations. It is particularly important that firms looking to incorporate online selling should evaluate (and develop as necessary) their ability to access new technology; evaluate their strategic options and match them with the benefits of the proposed technology; handle, manage, and implement the project; and reconfigure elements of their business model, i.e., make changes to their product or service and its payment methods. Successful online sellers do not depend on a single factor; rather they develop “net-enablement” capability, a continuous and multi-faceted process of related capability sets that involve all parts of the organization.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.011 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".