Journey of customers in this digital era: Understanding the role of artificial intelligence technologies in user engagement and conversion

Bag, Surajit; Srivastava, Gautam; Bashir, Mamoon Al; Kumari, Sushma; Giannakis, Mihalis; Chowdhury, Abdul Hannan

doi:10.1108/bij-07-2021-0415

Cited by 59 publications

(38 citation statements)

References 116 publications

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“…In today's digitalized era, the marketplace has transformed into market space (Prentice et al, 2020). Bag et al (2021d) empirically tests and further establishes that deploying AI technologies impacts user engagement and conversion positively. AI could be used in engagement marketing that is personalized for each customer.…”

Section: Development Of Hypothesesmentioning

confidence: 94%

A study of artificial intelligence on employee performance and work engagement: the moderating role of change leadership

Wijayati

Rahman

Fahrullah

et al. 2022

IJM

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PurposeThis paper aims to explore employee perceptions of companies engaged in services and banking of the role of change leadership on the application of artificial intelligence (AI) that will impact the performance and work engagement in conditions that are experiencing rapid changes.Design/methodology/approachThis study has used a quantitative research approach, and data analysis uses an approach structural equation modeling (SEM) supported by program computer software AMOS 22.0. A total of 357 respondents were involved in this study, but only 254 were qualified. In this study, the respondent is an employee of companies engaged in the services and banking sector in the East Java, Indonesia region.FindingsThe results reveal that AI has a significant positive effect on employee performance and work engagement. Change leadership positively moderates the influence of AI on employee performance and work engagement.Originality/valueThe development of this model has a novelty by including the moderating variable of the role of change leadership because, in conditions that are experiencing rapid changes, the role of leaders is essential. After all, leaders are decision-makers in the organization. The development of this concept focuses on studies of companies engaged in services and banking. Employee performance is an essential determinant in the organization because it will improve organizational performance. In addition, the application of AI in organizations will experience turmoil, so that the critical role of leaders is needed to achieve success with employee work engagement.

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Section: Development Of Hypothesesmentioning

confidence: 94%

A study of artificial intelligence on employee performance and work engagement: the moderating role of change leadership

Wijayati

Rahman

Fahrullah

et al. 2022

IJM

View full text Add to dashboard Cite

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“…Corporations can gain a competitive edge, allowing them to react better to market transformations occurring in the immediate future (Belanche et al, 2019). This disruptive technology has transformed how customers interact, enhancing user engagement and conversion (Bag et al, 2022). However, a dark side of AI-integrated business analytics confirms that operational inefficiency to handle significantly correlates to poor revenue growth and staff discontent, which puts a company at a competitive disadvantage (Rana et al, 2022).…”

Section: Theoretical Background 21 Revolution Of Artificial Intelligencementioning

confidence: 99%

Customer experiences in the era of artificial intelligence (AI) in context to FinTech: a fuzzy AHP approach

Arora¹,

Gupta²,

Devi

et al. 2023

BIJ

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PurposeThe financial technology (FinTech) era has brought a revolutionary change in the financial sector’s customer experiences at the national and global levels. The importance of artificial intelligence (AI) in the context of FinTech services for enriching customer experiences has become a new norm in this modern era of technological advancement. So, it becomes crucial to understand the customer’s perspective. The current research ranks the factors and sub-factors influencing customers’ perceptions of AI-based FinTech services.Design/methodology/approachThe sample size for this study was decided to be 970 respondents from four Indian cities: Mumbai, Delhi, Kolkata and Chennai. The Fuzzy-AHP technique was used to identify the primary factors and sub-factors influencing customers’ experiences with AI-enabled finance services. The factors considered in the study were service quality, trust commitment, personalization, perceived convenience, relationship commitment, perceived sacrifice, subjective norms, perceived usefulness, attitude and vulnerability. The current research is both empirical and descriptive.FindingsThe study’s three top factors are service quality, perceived usefulness and perceived convenience, all of which have a significant impact on customers’ experience with AI-enabled FinTech services discussing sub-criteria three primary criteria for customers’ experience for FinTech services include: “Using FinTech would increase my effectiveness in managing a portfolio (A2)”, “My peer groups and friends have an impact on using FinTech services (SN3)” and “Using FinTech would increase my efficacy in administering portfolio (PU2)”.Research limitations/implicationsThe current study is limited to four Indian cities, with 10 factors to understand customers’ preferences in FinTech. Further research can focus on other dimensions like perceived ease of use, familiarity, etc. Future studies can have a broader view of different geographical locations and consider new tech to understand customer perceptions better.Practical implicationsThe study’s findings will significantly assist businesses in determining the primary aspects influencing customers’ experiences with AI-enabled financial services. As a result, they will develop strategies and policies to entice clients to use AI-powered FinTech services.Originality/valueExisting AI research investigated several vital topics in the context of FinTech services. On the other hand, the current study ranked the criteria in understanding customer experiences. The research will substantially assist marketers, business houses, academicians and practitioners in understanding essential facets influencing customer experience and contribute significantly to the literature.

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“…Research conducted by [5], [6] aims to improve the decision-making process for supermarkets in organizing their product catalogs. The research focuses on determining the relationship between products purchased at a particular store by utilizing the Apriori algorithm and Market Basket Analysis.…”

Section: Literature Reviewmentioning

confidence: 99%

Market Basket Analysis Using FP-Growth Algorithm to Design Marketing Strategy by Determining Consumer Purchasing Patterns

Rahayu

2023

J. Appl. Data Sci.

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The development and competition that exists in the business world today leads every manager or company to be more dexterous in making marketing strategies to increase sales. Various things are done to keep up with existing market competition, such as analyzing customer purchase transaction data to serve as a policy determination and decision-making system in making marketing strategies. In determining marketing strategies, it can be done by taking transaction data to see existing purchase or transaction patterns. Market Basket Analysis is part of a data mining method that uses the FP-Growth algorithm technique to find out associated products. This research uses data taken from sales transaction data archives as much as 150 sales transaction data and 26 product data. In this study, it is determined that the minimum support value is 50% and the minimum confidence is ≥ 0.75 From the test results, 9 products have superior support values and meet the minimum value. From the test results, a rule with a confidence value of 0.870 was obtained: D → W (if consumers buy Wardah Lightening Gentle Wash, then buy Azarine Sunscreen SPF50), and 0.808: A → E → O (if consumers buy Emina Face Wash, then buy Azarine Night Moisturizer and Himalaya Neem Mask).

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Journey of customers in this digital era: Understanding the role of artificial intelligence technologies in user engagement and conversion

Cited by 59 publications

References 116 publications

A study of artificial intelligence on employee performance and work engagement: the moderating role of change leadership

A study of artificial intelligence on employee performance and work engagement: the moderating role of change leadership

Customer experiences in the era of artificial intelligence (AI) in context to FinTech: a fuzzy AHP approach

Market Basket Analysis Using FP-Growth Algorithm to Design Marketing Strategy by Determining Consumer Purchasing Patterns

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