Assessing stakeholder network engagement
Okazaki, Shintaro, Plangger, Kirk, Roulet, Thomas and Menéndez, Héctor D. 
ORCID: https://orcid.org/0000-0002-6314-3725
(2021)
Assessing stakeholder network engagement.
European Journal of Marketing, 55
(5)
.
pp. 1359-1384.
ISSN 0309-0566
[Article]
(doi:10.1108/EJM-12-2018-0842)
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Abstract
Purpose: With the popularity of social media platforms, firms have now tangible means not only to reach out to their stakeholders, but also to closely monitor those interactions. Yet, there are limited methodological advances on how to measure a firm’s stakeholder networks, and the level of engagement firms have with these networks. Drawn upon the customer engagement and stakeholder theory literature, this study proposes an approach to calculate a firm’s Stakeholder Network Engagement (SNE) index.
Design: After deriving the SNE index formula mathematically, we illustrate how the SNE index functions using eight firms’ online Corporate Social Responsibility (CSR) networks across four diverse industries.
Findings: We propose and illustrate a new approach of capturing the SNE in a stakeholder network for use by academic and practical researchers.
Research limitations/implications: Researchers can use the SNE index to assess engagement in stakeholder networks in various contexts.
Practical implications: Managers can use the SNE index to assess, benchmark and improve the nature and quality of their CSR strategies to derive greater return on their CSR investments.
Originality: Building on the stakeholder, communication and network analysis literatures, we conceptualise SNE in four theoretical dimensions: diffusion, accessibility, interactivity, and influence. Then, we mathematically derive and empirically illustrate an index that measures SNE.
| Item Type: | Article |
|---|---|
| Keywords (uncontrolled): | Stakeholder relationships, Twitter, Corporate social responsibility, Social media, Metric development, Stakeholder multiplicity theory, Stakeholder network engagement |
| Research Areas: | A. > School of Science and Technology > Computer Science |
| Item ID: | 32815 |
| Notes on copyright: | © 2020, Emerald Publishing Limited. This AAM is provided for your own personal use only. It may not be used for resale, reprinting, systematic distribution, emailing, or for any other commercial purpose without the permission of the publisher |
| Useful Links: | |
| Depositing User: | Hector Menendez Benito |
| Date Deposited: | 13 Apr 2021 08:49 |
| Last Modified: | 26 Jan 2023 19:48 |
| URI: | https://eprints.mdx.ac.uk/id/eprint/32815 |
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