Reshaping the contexts of online customer engagement behavior via artificial intelligence: A conceptual framework

Perez‐Vega, Rodrigo; Kaartemo, Valtteri; Lages, Cristiana Raquel; Razavi, Niloofar Borghei; Männistö, Jaakko

doi:10.1016/j.jbusres.2020.11.002

Cited by 91 publications

(48 citation statements)

References 70 publications

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Section: Discussionmentioning

confidence: 99%

“…Yet, the number of studies in this area is the second lowest among the six clusters revealed in this study. Noteworthily, the use of new age technologies such as artificial intelligence, big data and machine learning is promising for online and personalized engagement marketing (Kumar et al, 2019;Hollebeek et al, 2021;Perez-Vega et al, 2021), which is relevant for customer relationship management and service quality improvements, but nonetheless remains relatively underexplored in bank marketing. Thus, future research in this direction is highly encouraged.…”

Section: Ways Forwardmentioning

confidence: 99%

See 1 more Smart Citation

Past, present and future of bank marketing: a bibliometric analysis of International Journal of Bank Marketing (1983–2020)

Kumar

Xiao

Pattnaik

et al. 2021

IJBM

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PurposeThis study aims to provide an overview of bank marketing through a retrospection of the International Journal of Bank Marketing (IJBM), the leading journal for bank marketing.Design/methodology/approachThis study conducts a bibliometric analysis to analyze the performance and intellectual structure of bank marketing literature curated through IJBM between 1983 and 2020.FindingsThis study sheds light on the growing influence and impact of IJBM on the field of bank marketing through six major clusters (themes): relationship marketing and service quality in banking and financial services, consumer behavior in banking and financial services, customer satisfaction and loyalty in banking and financial services, electronic or online banking and financial services, Islamic banking and financial services, and service failure and recovery in banking and financial services.Research limitations/implicationsThough this study offers a state-of-the-art overview of bank marketing through the lens of IJBM, the insights remain limited to the accuracy and availability of bibliographic data of the journals from Scopus.Originality/valueTo the best of the authors' knowledge, this study represents the first objective assessment of bank marketing and IJBM. Thus, this study should be useful to past and prospective authors, editorial board members, editors, readers and reviewers to gain a one-stop understanding about bank marketing through the contributions of IJBM.

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Section: Discussionmentioning

confidence: 99%

Section: Ways Forwardmentioning

confidence: 99%

Past, present and future of bank marketing: a bibliometric analysis of International Journal of Bank Marketing (1983–2020)

Kumar

Xiao

Pattnaik

et al. 2021

IJBM

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“…Changes in sales processes involve the use of real‐time feedback to feed changes in sales pitches and communication materials. There are high expectations in terms of AI‐enabled systems facilitating personalization of customer experiences (Kumar et al, 2019) and helping marketers use a wide variety of solicited and unsolicited form of customer engagement to improve marketing outcomes (Perez‐Vega et al, 2021). Finally, changes in consumer behavior are related to the adoption of AI‐enabled technologies for aspects related to information search as well as behavioral changes derived from advancements in technology (e.g., the implications on consumer behavior once self‐driving cars become prevalent).…”

Section: Analysis and Findingsmentioning

confidence: 99%

AI in marketing, consumer research and psychology: A systematic literature review and research agenda

Mariani

Perez‐Vega

Wirtz

2021

Psychology and Marketing

182

144

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This study is the first to provide an integrated view on the body of knowledge of artificial intelligence (AI) published in the marketing, consumer research, and psychology literature. By leveraging a systematic literature review using a data‐driven approach and quantitative methodology (including bibliographic coupling), this study provides an overview of the emerging intellectual structure of AI research in the three bodies of literature examined. We identified eight topical clusters: (1) memory and computational logic; (2) decision making and cognitive processes; (3) neural networks; (4) machine learning and linguistic analysis; (5) social media and text mining; (6) social media content analytics; (7) technology acceptance and adoption; and (8) big data and robots. Furthermore, we identified a total of 412 theoretical lenses used in these studies with the most frequently used being: (1) the unified theory of acceptance and use of technology; (2) game theory; (3) theory of mind; (4) theory of planned behavior; (5) computational theories; (6) behavioral reasoning theory; (7) decision theories; and (8) evolutionary theory. Finally, we propose a research agenda to advance the scholarly debate on AI in the three literatures studied with an emphasis on cross‐fertilization of theories used across fields, and neglected research topics.

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“…However, big data is not defined only in terms of volume (storage capacity) but also variety (different types of data) and velocity (the speed at which data is created). Big data can be acquired from multiple sources -web log files from the web, text data from surveys, geospatial data from mobile phones, social media are some examples [6]. Hence, data can sometimes be collected specifically for a certain form of analytics [7].…”

Section: Overview Of Big Data Analyticsmentioning

confidence: 99%

Role of Big Data Analytics in Belt and Road Initiative (BRI): Multivariate Analysis with Gaussian Distribution of Data

Raju¹,

Wang²,

Shrestha³

et al. 2021

Frontiers in Artificial Intelligence and Applications

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This manuscript focuses on the Belt and Road Initiative (BRI) of China, whereby the focus is on the engagement of big data analytics to comprehend logistics exertion. China is the trendsetter for revolutionary practices in trade, logistics, and technology. The recent progress the nation is thriving is on ‘One Belt One Road’ project whereby 65 countries are involved. It aims to connect continents and circulate smooth trade between them. This paper addresses the role of the database to identify the inter-model logistics in BRI. The merits of this project in the perspective of economic growth are measured through a quantitative study with 112 samples. Goal-setting theory is used to construct a conceptual framework for the research. Multivariate analysis is executed with SmartPLS 3.3.3 followed by an in-depth structural equation modeling. Normal distribution of data was given importance as in statistics the real-value of random variables whose distributions are not known, thus Gaussian distribution of data was used. Out of 6 Hypotheses, it is noted that five are significantly positive. Hypothesis testing is concluded based on p-value and t-statistics. The outcome of research suggests that big-data analytics is a major contributor in determining the significant model on logistics in Belt and Road Initiative.

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Reshaping the contexts of online customer engagement behavior via artificial intelligence: A conceptual framework

Cited by 91 publications

References 70 publications

Past, present and future of bank marketing: a bibliometric analysis of International Journal of Bank Marketing (1983–2020)

Past, present and future of bank marketing: a bibliometric analysis of International Journal of Bank Marketing (1983–2020)

AI in marketing, consumer research and psychology: A systematic literature review and research agenda

Role of Big Data Analytics in Belt and Road Initiative (BRI): Multivariate Analysis with Gaussian Distribution of Data

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