Final published version
Licence: CC BY: Creative Commons Attribution 4.0 International License
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - The impact of artificial intelligence adoption for business-to-business marketing on shareholder reaction
T2 - A social actor perspective
AU - Zhan, Yuanzhu
AU - Xiong, Yangchun
AU - Han, Runyue
AU - Lam, Hugo K.S.
AU - Blome, Constantin
PY - 2024/3/27
Y1 - 2024/3/27
N2 - While AI applications are becoming ever more important in B2B marketing operations, there is a lack of research to examine whether and how shareholders react to firms' AI-enabled B2B marketing initiatives. Accordingly, the purpose of this study is to explore this process by theoretically building on the social actor perspective of the firm and investigating the impact of AI-enabled B2B marketing initiatives on shareholder reaction measured by abnormal stock returns. By adopting a propensity score matching (PSM) method to generate an artificial control group of firms without adopting AI-enabled B2B marketing initiatives, we conduct an event study based on 174 sample firms (87 treatment firms and 87 matched control firms) publicly listed in the US between 2011 and 2020. The test results suggest that firms implementing AI for B2B marketing receive greater stock returns than their industry peers without AI implementation. In addition, the stock return is more remarkable for firms operating in turbulent environments and with less complex customer bases. A qualitative focus group discussion was conducted to further complement and enrich the findings. This study provides the first empirical evidence regarding the shareholder reaction to AI-enabled B2B marketing initiatives. The results reveal the significance of the fit between AI-enabled B2B marketing values and firms' business environments. It encourages future studies to investigate AI implementation from the social actor perspective.
AB - While AI applications are becoming ever more important in B2B marketing operations, there is a lack of research to examine whether and how shareholders react to firms' AI-enabled B2B marketing initiatives. Accordingly, the purpose of this study is to explore this process by theoretically building on the social actor perspective of the firm and investigating the impact of AI-enabled B2B marketing initiatives on shareholder reaction measured by abnormal stock returns. By adopting a propensity score matching (PSM) method to generate an artificial control group of firms without adopting AI-enabled B2B marketing initiatives, we conduct an event study based on 174 sample firms (87 treatment firms and 87 matched control firms) publicly listed in the US between 2011 and 2020. The test results suggest that firms implementing AI for B2B marketing receive greater stock returns than their industry peers without AI implementation. In addition, the stock return is more remarkable for firms operating in turbulent environments and with less complex customer bases. A qualitative focus group discussion was conducted to further complement and enrich the findings. This study provides the first empirical evidence regarding the shareholder reaction to AI-enabled B2B marketing initiatives. The results reveal the significance of the fit between AI-enabled B2B marketing values and firms' business environments. It encourages future studies to investigate AI implementation from the social actor perspective.
KW - AI in B2B marketing
KW - Customer complexity
KW - Event study
KW - Industry dynamism
KW - Social action theory
U2 - 10.1016/j.ijinfomgt.2024.102768
DO - 10.1016/j.ijinfomgt.2024.102768
M3 - Journal article
AN - SCOPUS:85185586691
VL - 76
JO - International Journal of Information Management
JF - International Journal of Information Management
SN - 0268-4012
M1 - 102768
ER -