The role of AI robotics and marketing execution capabilities in B2B value realization and accumulation under technological uncertainty

Purpose This study aims to examine how artificial intelligence (AI) robotics capability is associated with customer value realization (CVR) and brand value (BV) in business-to-business (B2B) markets, and whether marketing execution capability (MEC) explains these relationships under technological uncertainty. Design/methodology/approach Drawing on the resource-based view and resource orchestration perspectives, this study uses unbalanced panel data from 234 Chinese B2B firms (2011–2022). AI-enabled robotics capability is measured using patent portfolio data, whereas MEC is constructed as a multidimensional index using principal component analysis. A moderated mediation model was tested using fixed-effects regression with cluster-robust standard errors. Findings AI robotics capability (AI-RC) does not exhibit an automatic direct association with CVR and BV; rather, its value potential is realized when firms can effectively execute, coordinate and deliver AI-enabled offerings through MEC, supporting it as a transformational mechanism. However, technological uncertainty weakens the positive association between AI-RC and MEC. This dual-value framework demonstrates that the value potential of AI-robotics capability is conditional on the strength of MEC and the level of technological uncertainty. Practical implications For managers, AI robotics should be viewed not merely as operational tools but also as strategic resources that require strong MEC to convert technical knowledge into CVR and BV through consistent articulation, coordination and delivery. Originality/value This study contributes to the B2B marketing scholarship by (1) introducing a dual-value framework that integrates customer-side (customer value realization) and firm-side (brand value) outcomes; (2) positioning MEC as an execution-oriented marketing capability and arguing that the relationship between technological and marketing capabilities is task-contingent rather than uniformly complementary; and (3) demonstrating technological uncertainty as a boundary condition.

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Publication Details

Journal
Journal of Business and Industrial Marketing
Published
2026-10-18
DOI
https://doi.org/10.1108/jbim-07-2025-0709
Primary Topic
Innovation and Knowledge Management
Type
article
Field-Weighted Citation Impact
0.00
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article

The role of AI robotics and marketing execution capabilities in B2B value realization and accumulation under technological uncertainty

Rafique Ahmed Khuhro, Dapeng Liang, Rohail Ashraf, Muhammad Asif Khan
Journal of Business and Industrial Marketing
Innovation and Knowledge Management
article

The role of AI robotics and marketing execution capabilities in B2B value realization and accumulation under technological uncertainty

Rafique Ahmed Khuhro, Dapeng Liang, Rohail Ashraf, Muhammad Asif Khan
article en

Abstract

Purpose This study aims to examine how artificial intelligence (AI) robotics capability is associated with customer value realization (CVR) and brand value (BV) in business-to-business (B2B) markets, and whether marketing execution capability (MEC) explains these relationships under technological uncertainty. Design/methodology/approach Drawing on the resource-based view and resource orchestration perspectives, this study uses unbalanced panel data from 234 Chinese B2B firms (2011–2022). AI-enabled robotics capability is measured using patent portfolio data, whereas MEC is constructed as a multidimensional index using principal component analysis. A moderated mediation model was tested using fixed-effects regression with cluster-robust standard errors. Findings AI robotics capability (AI-RC) does not exhibit an automatic direct association with CVR and BV; rather, its value potential is realized when firms can effectively execute, coordinate and deliver AI-enabled offerings through MEC, supporting it as a transformational mechanism. However, technological uncertainty weakens the positive association between AI-RC and MEC. This dual-value framework demonstrates that the value potential of AI-robotics capability is conditional on the strength of MEC and the level of technological uncertainty. Practical implications For managers, AI robotics should be viewed not merely as operational tools but also as strategic resources that require strong MEC to convert technical knowledge into CVR and BV through consistent articulation, coordination and delivery. Originality/value This study contributes to the B2B marketing scholarship by (1) introducing a dual-value framework that integrates customer-side (customer value realization) and firm-side (brand value) outcomes; (2) positioning MEC as an execution-oriented marketing capability and arguing that the relationship between technological and marketing capabilities is task-contingent rather than uniformly complementary; and (3) demonstrating technological uncertainty as a boundary condition.

Journal of Business and Industrial Marketing
Industrial University of Ho Chi Minh City (VN), Harbin Institute of Technology (CN), University of Haripur (PK), Northumbria University (GB)
Openalex Percentile: Top 8%
Innovation and Knowledge Management
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