Power negotiation on the tango dancefloor: The adoption of AI in B2B marketing

Keegan, Brendan James; Canhoto, Ana Isabel; Yen, Dorothy A.

doi:10.1016/j.indmarman.2021.11.001

Cited by 28 publications

(16 citation statements)

References 59 publications

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“…The topic of Artificial Intelligence [AI] has become more prevalent in research studies. Keegan et al, [41] investigated the lack of empirical research on the adoption of AI in B2B marketing among business managers and engineers and academic experts in the field of AI. The researchers argued that AI adoption priorities and motives shape the power dynamics among the various network actors, including focal firms, AI suppliers and technology giant companies [41].…”

Section: Technological Factorsmentioning

confidence: 99%

“…Keegan et al, [41] investigated the lack of empirical research on the adoption of AI in B2B marketing among business managers and engineers and academic experts in the field of AI. The researchers argued that AI adoption priorities and motives shape the power dynamics among the various network actors, including focal firms, AI suppliers and technology giant companies [41]. Their findings are that, in the context of AI adoption in B2B, both technology and expertise are key sources of power and that data create and perpetuate power negotiations and renegotiations in the network.…”

Section: Technological Factorsmentioning

confidence: 99%

“…Their findings are that, in the context of AI adoption in B2B, both technology and expertise are key sources of power and that data create and perpetuate power negotiations and renegotiations in the network. Furthermore, [41] contributes to the power dependence theory (PDT) by showing that, through the adoption process, network actors' power is exchanged, exercised, counter-balanced and perpetuated, creating fluid network dynamics [41]. SMEs can leverage on the PDT [41] to extend their WSMA reach and strengthen their position in their specific eCommerce networks and industries.…”

Section: Technological Factorsmentioning

confidence: 99%

“…Furthermore, [41] contributes to the power dependence theory (PDT) by showing that, through the adoption process, network actors' power is exchanged, exercised, counter-balanced and perpetuated, creating fluid network dynamics [41]. SMEs can leverage on the PDT [41] to extend their WSMA reach and strengthen their position in their specific eCommerce networks and industries.…”

Section: Technological Factorsmentioning

confidence: 99%

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Adoption of Web 2.0 Social Media eCommerce in SMEs: Conceptualising Theories and Factors for Zambia

Shemi¹

2024

Social Media - Opportunities and Risks

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The application of Web 2.0 social media in eCommerce and e-marketplaces (ECEMs) in developing countries has been on the increase in recent times especially during Covid19 and beyond. However, it is still unclear what theoretical foundations and factors guide ECEM in small and medium enterprises (SMEs) in emerging markets such as Zambia. Generally, the understanding of eCommerce using Web 2.0 social media applications (WSMAs) in SMEs has lacked rigour over time as focus has shifted to pressing issues such as Covid19. This paper purposes to investigate the theoretical foundations and factors influencing WSMA for new eCommerce era in developing countries with particular emphasis on SMEs in Zambia. The methodological research design employs a qualitative study approach using literature reviews, coupled with content analysis of purposively selected articles. Results show that theories such as TAM, TPB, UTAUT2, TOE, TTF, DIT, among others, have guided eCommerce research in SWMA. Behavioural, technological and organisational factors such as trust, ease of use, after-sales logistics, price flexibility have been prevalent, among others. The paper ends with recommendations and strategies for continued adoption of WSMA by SMEs with similar geographical contexts to Zambian context.

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Section: Technological Factorsmentioning

confidence: 99%

Section: Technological Factorsmentioning

confidence: 99%

Section: Technological Factorsmentioning

confidence: 99%

Section: Technological Factorsmentioning

confidence: 99%

See 2 more Smart Citations

Adoption of Web 2.0 Social Media eCommerce in SMEs: Conceptualising Theories and Factors for Zambia

Shemi¹

2024

Social Media - Opportunities and Risks

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“…A broad study of the impact of AI and its capability on business performance appears ( Denicolai et al, 2021 ; Mikalef and Gupta, 2021 ). The existing literature dedicated to the study of the impact of AI on industries, such as banking and finance ( Huynh et al, 2020 ), manufacturing ( Bag et al, 2021c ), automated retailing ( Pillai et al, 2020 ), logistics ( Chien et al, 2020 ), marketing ( Keegan et al, 2022 ), coaching services ( Kim et al, 2021b ), and customer relationship management ( Chatterjee et al, 2021a ), among other areas. In comparison, these studies concentrated on the impact of AI on firm innovation processes and management practices, technological innovation ( Liu et al, 2020a ), and the relationship between AI learning and entrepreneurial performance ( Khalid, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

The Impact of Artificial Intelligence on Firm Performance: An Application of the Resource-Based View to e-Commerce Firms

2022

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The application of artificial intelligence (AI) technology has evolved into an influential endeavor to improve firm performance, but little research considers the relationship among artificial intelligence capability (AIC), management (AIM), driven decision making (AIDDM), and firm performance. Based on the resource-based view (RBV) and existing findings, this paper constructs a higher-order model of AIC and suggests a research model of e-commerce firm AIC and firm performance. We collected 394 valid questionnaires and conducted data analysis using partial least squares structural equation modeling (PLS-SEM). As a second-order variable, AIC was formed by three first-order variables: basic, proclivity, and skills. AIC indirectly affects firm performance through creativity, AIM, and AI-driven decision making. Firm creativity, AIM, and AIDDM are essential variables between AIC and firm performance. Innovation culture (IC) positive moderates the relationship between firm creativity and AIDDM as well as the relationship between AIDDM and firm performance. Environmental dynamism (ED) positive mediates the connection between AIM and AIDDM. Among the control variables, firm age negatively affects firm performance, and employee size does not. This study helps enterprises leverage AI to improve firm performance, achieve a competitive advantage, and contribute to theory and management practice.

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Artificial intelligence in marketing research and future research directions: Science mapping and research clustering using bibliometric analysis

Thakur,

Kushwaha

2023

Glob Bus Org Exc

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The marketing environment has experienced significant advancements due to the transformative influence of technologies such as artificial intelligence, data analytics, decision sciences, and robotics. These innovations have entirely reshaped the fundamental marketing principles as we know them. This study uses bibliometric analysis to conduct a systematic literature review of research on Artificial Intelligence (AI) in marketing and provides future research directions. It also aims to identify the most influential and productive contributors and progression of research on AI in marketing. The bibliographic data of 317 documents on artificial intelligence in marketing research was extracted from the Scopus database. The bibliometric analysis is performed to comprehensively understand the most influential and productive articles, authors, sources, and the top contributing countries and institutions towards the discipline of AI in marketing research. The results and the publication trend show exponential growth yearly in AI in marketing research. Furthermore, it discovered four main thematic clusters: Data mining and deep learning in decision support systems, big data and generative AI in marketing, AI‐enabled commerce, and chatbots and marketing Tech that represent the recent research being carried out under AI in marketing. The trending topics recognized are marketing algorithms for decision‐making, AI‐enabled marketing, the Internet of Things (IoT) and marketing, natural language processing and customer service, robotic services, and chatbots. This study also emphasizes potential future research areas, building upon the established thematic clusters.

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Power negotiation on the tango dancefloor: The adoption of AI in B2B marketing

Cited by 28 publications

References 59 publications

Adoption of Web 2.0 Social Media eCommerce in SMEs: Conceptualising Theories and Factors for Zambia

Adoption of Web 2.0 Social Media eCommerce in SMEs: Conceptualising Theories and Factors for Zambia

The Impact of Artificial Intelligence on Firm Performance: An Application of the Resource-Based View to e-Commerce Firms

Artificial intelligence in marketing research and future research directions: Science mapping and research clustering using bibliometric analysis

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