Evidence map›Paper›PMID 39027428›Full record

ArticleHeliyon2024

Exploring the Chatbot usage intention-A mediating role of Chatbot initial trust.

Jyothsna M, Venkata Subbaiah P, Natalia Kryvinska

Abstract read
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Jyothsna MDepartment of Marketing, GITAM School of Business, GITAM (Deemed to be University) Visakhapatnam, Andhra Pradesh-530045, India.
Venkata Subbaiah PDepartment of Marketing, GITAM School of Business, GITAM (Deemed to be University) Visakhapatnam, Andhra Pradesh-530045, India.
Natalia KryvinskaInformation Systems Department, Faculty of Management, Comenius University in Bratislava, Odbojárov 10, 82005, Bratislava 25, Slovakia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chatbots, an integral part of Digitalization, are becoming the cornerstone of modern-day marketing practices. This study's main objective is to identify the Chabot traits that have a bearing on users' confidence, acceptability, and engagement. Chatbots hold much potential for customer support in terms of service efficiency, cost savings, and customer experience. In addition to saving business costs, chatbots improve customer engagement, by reducing time and effort they need to spend in doing their business transactions. Aspiring, well-educated, and tech-savvy Gen Z customers perceive chatbots as highly compatible with their preferred method of seeking product-related information. As chatbots play a significant role in the marketing process, this study aims to identify the chatbot traits that influence customers' confidence, acceptance, and engagement with chatbots. Using the PLS-SEM tool/technique we computed a structural equation measurement model to test the traits leading to Chabot trust. The study also found that perceived ease of use, performance expectations, and social influence of chatbots are all greatly enhanced by trust on the part of the customers. Detailed statistical analysis showed that the trust that consumers have in chatbots strongly influences consumers' intentions, loyalty, and engagement levels. While gender had no impact on consumer intentions to use chatbots, the age of the respondents played a substantial role in their plans to use chatbots.

Indexed as

And customer engagementChatbot initial trustCustomer usage intentionLoyalty

Identifiers

PMID39027428
PMCPMC11254518

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.