{"id":12281,"date":"2022-11-14T06:05:36","date_gmt":"2022-11-14T11:05:36","guid":{"rendered":"https:\/\/www.servsig.org\/wordpress\/?p=12281"},"modified":"2023-06-20T05:40:14","modified_gmt":"2023-06-20T09:40:14","slug":"cfp-jpim-ai-based-stakeholder-engagement","status":"publish","type":"post","link":"https:\/\/www.servsig.org\/wordpress\/2022\/11\/cfp-jpim-ai-based-stakeholder-engagement\/","title":{"rendered":"CfP JPIM: AI-based Stakeholder Engagement"},"content":{"rendered":"\n
\"\"<\/figure><\/div>\n\n\n\n

Call for Paper for a Special Issue of the Journal of Product Innovation Management<\/em>.<\/p>\n\n\n\n

Artificial Intelligence, Stakeholder Engagement, and Innovation Value<\/strong><\/p>\n\n\n\n

Guest Editors: Praveen Kopall\u00e9, Costas Katsikeas, Giampaolo Viglia, and Linda Hollebeek<\/p>\n\n\n\n

Deadline: 30 October 2023<\/strong><\/p>\n\n\n\n

Managers increasingly adopt, incorporate, and rely on an ever-growing range of artificial intelligence (AI)-based technologies and applications (Wetzels, 2021; Garbuio & Nidthida, 2021). For example, companies such as Amazon or IBM are using artificially intelligent innovations in their human resource management (HRM) planning and implementation (e.g., by scanning candidates\u2019 r\u00e9sum\u00e9s, recording and interpreting interviewees\u2019 responses, and managing employee churn; Bailey et al., 2019; Vrontis et al., 2021). Likewise, firms like Tesco and Starbucks are leveraging marketing-based AI applications, by providing product recommendations to (prospective) customers, personalizing brand-related content, segmenting customers, and optimizing their pricing strategies, among others (Verganti et al. 2020; Huang & Rust, 2021). Moreover, operations management-based AI applications, which can be used to facilitate tasks including production\/sales forecasting, operation-related anomaly prediction, and (big) data analytics, have also taken off in leading organizations including Walmart, Philips, and eBay, to name a few (Cappa et al., 2021; Raisch & Krakowski, 2021).<\/p>\n\n\n\n

Key benefits of these AI-based innovations include enhanced efficiency, improved prediction (e.g., of individuals\u2019 needs or behaviors), and reduced human error and time to market (Hollebeek et al., 2021), thus offering significant value to firms and their stakeholders (Eisingerich et al., 2021; Brynjolfsson et al., 2019). Quantifying these benefits, global consultancy firm Gartner has forecast AI technology to achieve a compound annual growth rate of 28%, from $692bn in 2017 to $5.025 trillion in 2025 (Lovelock et al., 2018). Likewise, PwC (2021) estimates that \u201cAI could contribute up to $15.7 trillion to the global economy in 2030.\u201d Particularly in a (post-)Covid environment featuring a growing desire for contactless interactions, the demand for AI-based solutions is surging (Khemasuwan & Colt, 2021; Spanjol & Noble, 2020). Given AI\u2019s potentially transformative impact on innovation management, literature in this area is rapidly emerging (Garbuio et al., 2021; Haefner et al., 2021). However, little remains known regarding the drivers, dynamics, characteristics, and outcomes of AI adoption on different organizational stakeholders\u2019 engagement with these applications (e.g., Kumar et al., 2019; Hughes et al., 2019) and their perceived AI-based innovation value (Ganotakis & Love, 2012), thus exposing a pertinent literature-based gap and leaving managers in the dark regarding these issues that are of growing importance to their business (Hyve, 2019).<\/p>\n\n\n\n

With its stakeholder theory-informed roots that date back to the 1980s (e.g., Freeman, 1984), stakeholder engagement is subject to a rich academic discourse (e.g., Donaldson and Preston, 1995; Watson et al., 2018), in which stakeholders are viewed as \u201cany group or individual who can affect or is affected by [the firm]\u201d (Freeman 1984, p. 46), including its employees, customers, suppliers, investors, owners, strategic partners, competitors, government, the media, local community organizations, etc. In this literature stream, stakeholder engagement, defined as \u201ca stakeholder\u2019s [cognitive, emotional, and behavioral] resource endowment in his\/her role-related interactions, activities, and\/or relationships\u201d(Hollebeek et al., 2022, p. 328), has been identified as a key stakeholder management metric (Viglia et al., 2018; Menguc et al., 2017; O\u2019Riordan & Fairbrass, 2014). In particular, elevated stakeholder engagement is conducive to enhanced stakeholder trust, dialogue, and collaboration, in turn boosting (e.g., innovation-related) returns and stakeholder-perceived value (e.g., Katsikeas et al., 2016; Moreau, 2011). However, as specific firm stakeholders\u2019 needs, interests, and engagement typically differ and may even oppose one another (Freeman et al., 2010), little is known regarding different firm stakeholders\u2019 engagement with AI-based applications or their drivers, dynamics, potential tensions, and consequences, whether for the focal stakeholder, other stakeholders, or the firm (e.g., Wijayati et al., 2022; Perez-Vega et al., 2021), thus warranting further exploration.<\/p>\n\n\n\n

In other words, despite the advances made in the individual topic areas of AI, stakeholder engagement, and innovation value, understanding of the intersection of different stakeholders\u2019 engagement with specific AI-based applications and their perceived innovation value lags behind. For example, while authors, including Heller et al. (2021) or Eisingerich et al. (2021) explore AI\u2019s role in fostering customer engagement, understanding of its effect on other or multiple stakeholders\u2019 engagement \u2013 while pivotal for firms \u2013 remains limited (e.g., Huang et al., 2021; Sj\u00f6din et al. 2019; PwC, 2019), necessitating further exploration.<\/p>\n\n\n\n

In response to this gap, this interdisciplinary Special Issue solicits state-of-the-art submissions that explore the role of AI applications in developing, nurturing, or optimizing specific stakeholders\u2019 engagement (e.g., with the brand or firm) and perceived innovation value. To be considered for publication in the Special Issue, manuscripts should offer a substantial original contribution to AI-, stakeholder engagement-, and innovation management research. We welcome conceptual, methodological, qualitative, quantitative, or mixed-methods contributions grounded in a range of perspectives that offer insight into issues including, but not limited to, the following:<\/p>\n\n\n\n

– Conceptual development of the AI\/stakeholder engagement interface
– AI-based stakeholder engagement\u2019s nomological network
– AI-based engagement\u2019s impact on stakeholder-, innovation-, and firm performance
– Stakeholders\u2019 potential AI-based differences, tensions, or vulnerabilities
– Methodological issues at the AI\/stakeholder engagement interface<\/strong><\/p>\n\n\n\n

The deadline for submissions to this Special Issue is October 30, 2023, via the Journal of Product Innovation Management\u2019s online submission portal<\/a>. When submitting your manuscript, please select the Special Issue (SI): AI-based Stakeholder Engagement <\/strong>from the drop-down menu. Submissions should be prepared in accordance with the Journal of Product Innovation Management\u2019s editorial policy and author guidelines<\/a>.<\/p>\n\n\n\n

The guest editors will screen submissions to ensure their suitable scope, fit with the journal\u2019s aims and objectives, and relevance to the Special Issue topic. Manuscripts that do not pass the initial screening will be returned to the authors, while the others will be peer-reviewed in accordance with the Journal of Product Innovation Management\u2019s guidelines and procedures. The Special Issue\u2019s publication is planned for the second half of 2025.<\/p>\n\n\n\n

Queries can be directed at the Special Issue Guest Editors:
– Martin Wetzels<\/a>, Professor of Marketing, EDHEC Business School
– Costas Katsikeas<\/a>, Arnold Ziff Research Chair in Marketing & International Management, University of Leeds
– Giampaolo Viglia<\/a>, Professor of Marketing, University of Portsmouth and Universit\u00e0 della Valle d\u2019Aosta
– Linda D. Hollebeek<\/a>, Professor of Marketing, Vilnius University and Tallinn University of Technology<\/p>\n\n\n\n

More details and references available here<\/a>. <\/p>\n","protected":false},"excerpt":{"rendered":"

Call for Paper for a Special Issue of the Journal of Product Innovation Management. Artificial Intelligence, Stakeholder Engagement, and Innovation Value Guest Editors: Praveen Kopall\u00e9, Costas Katsikeas, Giampaolo Viglia, and Linda Hollebeek Deadline: 30 October 2023 Managers increasingly adopt, incorporate, and rely on an ever-growing range of artificial intelligence (AI)-based technologies and applications (Wetzels, 2021; […]<\/p>\n","protected":false},"author":12,"featured_media":12282,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[5,10],"tags":[521,178,917],"_links":{"self":[{"href":"https:\/\/www.servsig.org\/wordpress\/wp-json\/wp\/v2\/posts\/12281"}],"collection":[{"href":"https:\/\/www.servsig.org\/wordpress\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.servsig.org\/wordpress\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.servsig.org\/wordpress\/wp-json\/wp\/v2\/users\/12"}],"replies":[{"embeddable":true,"href":"https:\/\/www.servsig.org\/wordpress\/wp-json\/wp\/v2\/comments?post=12281"}],"version-history":[{"count":5,"href":"https:\/\/www.servsig.org\/wordpress\/wp-json\/wp\/v2\/posts\/12281\/revisions"}],"predecessor-version":[{"id":12750,"href":"https:\/\/www.servsig.org\/wordpress\/wp-json\/wp\/v2\/posts\/12281\/revisions\/12750"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.servsig.org\/wordpress\/wp-json\/wp\/v2\/media\/12282"}],"wp:attachment":[{"href":"https:\/\/www.servsig.org\/wordpress\/wp-json\/wp\/v2\/media?parent=12281"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.servsig.org\/wordpress\/wp-json\/wp\/v2\/categories?post=12281"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.servsig.org\/wordpress\/wp-json\/wp\/v2\/tags?post=12281"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}