The exact text we saved

This is the version exactly as it was saved, character for character. The SHA-256 hash below is a 64-character code worked out from that text. Run the same text through SHA-256 and you get the same code; change a single letter and the code comes out completely different. Each version also stores the previous version’s hash, which chains them together so no version can be swapped out quietly.

TRUVACE RECORD VERSION
record: TRV-2026-2727
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-11-12T17:15:32.317032Z
status: published
lens: g_space
sector: business
headline: Automated Versus Human Agents: A Meta-Analysis of Customer Responses to Robots, Chatbots, and Algorithms and Their Contingencies
dek: This meta-analysis examines when three types of automated agents (AAs)—robots, chatbots, and algorithms—are equivalent to human agents (HAs) in marketing roles. An analysis of 943 effect sizes from 327 studies provides novel insights. First, customers may be skeptical of AAs; however, they value their performance and eventually choose or buy from them as if they were interacting with HAs. Second, each of the three AA types has a unique set of contingencies that affect its human equivalence; previously identified…
gain_title: A meta-analysis of 943 effect sizes from 327 studies found that customers, though skeptical of robots, chatbots and algorithms, value their performance and eventually choose or buy from them as if dealing with human agents.
problem_title: (none)
trace_subject: (none)
gain_reading: A meta-analysis of 943 effect sizes from 327 studies found that customers, though skeptical of robots, chatbots and algorithms, value their performance and eventually choose or buy from them as if dealing with human agents.
gain_evidence: they value their performance and eventually choose or buy from them as if they were interacting with HAs
problem_reading: (none)
problem_evidence: (none)
quick_read: A meta-analysis in the Journal of Marketing pooled 943 effect sizes from 327 studies to test when robots, chatbots and algorithms perform as well as human agents in marketing roles. Customers may start out skeptical of automated agents, but they value how well the agents perform and eventually choose or buy from them as they would from humans.

The review finds that each of the three agent types has its own set of conditions that determine how closely it matches a human. Conditions identified in earlier work do not carry over from one type to another and can even push in opposite directions, so a finding about chatbots cannot be assumed to hold for robots or algorithms.

The authors use the results to say when automated agents can replace human ones in marketing roles to release capacity and alleviate labor shortages, and they set out a future research agenda.
limitation: Contingencies identified in earlier research do not generalize across robots, chatbots and algorithms and can have opposing effects, so the conclusions on human equivalence depend on the agent type and task.
tag: Evidence-backed gain
key_points: The analysis covers 943 effect sizes drawn from 327 studies of customer responses to robots, chatbots and algorithms. | Customers may be skeptical of automated agents, yet they eventually choose or buy from them as if they were dealing with human agents. | Each of the three agent types has its own contingencies affecting how equivalent it is to a human agent. | Contingencies found in earlier research do not generalize across agent types and can have opposing effects. | A newly identified contingency is the multifaceted concept of artificial intelligence required to fulfill a task. | Some contingencies make automated agents seem more humanlike, while others make their machine nature stand out.
rundown: The study asks when robots, chatbots and algorithms are equivalent to human agents in marketing roles. It combines 943 effect sizes from 327 studies, so the conclusions rest on a broad body of earlier experiments rather than one trial.

The main result is a gap between attitude and behaviour: customers may be skeptical of automated agents, but they value their performance and eventually choose or buy from them as if interacting with humans. Each agent type has distinct contingencies, and some earlier findings reverse from one type to another.

The authors extend the concept of automated social presence, describing automated agents as hybrid beings that give customers both a feeling of interacting with a humanlike entity and a feeling of interacting with a machine. They recommend where automated agents can replace human ones to release capacity and ease labor shortages.
sources:
- peer_reviewed | Journal of Marketing | https://doi.org/10.1177/00222429251344139 | 2025-05-09
prev: 0000000000000000000000000000000000000000000000000000000000000000

SHA-256 hash

042a183dd40761ad5e8f07911a9357bc6de88c167ab80c67209f74c79a9aca15

Previous version’s hash

0000000000000000000000000000000000000000000000000000000000000000