Purpose

This study aims to provide insights into human–algorithm interaction in revenue management (RM) decision-making and to uncover the underlying heuristics and biases of overriding systems’ recommendations.

Design/methodology/approach

Following constructivist traditions, 20 in-depth interviews were conducted with revenue optimisers, analysts, managers and directors with vast experience in over 25 markets and working with different RM systems (RMSs) at the property and corporate levels. The hermeneutics approach was used to interpret and make meaning of the participants’ lived experiences and interactions with RMSs.

Findings

The findings explain the nature of the interaction between RM professionals and RMSs, the cognitive mechanism by which the system users judgementally adjust or override its recommendations and the heuristics and biases behind override decisions. Additionally, the findings reveal the individual decision-maker characteristics and organisational factors influencing human–algorithm interactions.

Research limitations/implications

Although the study focused on human–system interaction in hotel RM, it has larger implications for integrating human judgement into computerised systems for optimal decision-making.

Practical implications

The study findings expose human biases in working with RMSs and highlight the influencing factors that can be addressed to achieve effective human–algorithm interactions.

Originality/value

The study offers a holistic framework underpinned by the organisational role and expectation confirmation theories to explain the cognitive mechanisms of human–system interaction in managerial decision-making.

中文翻译：

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人机交互和酒店收益管理中的启发式和偏见凌驾于决策之上

 目的

本研究旨在深入了解收益管理 (RM) 决策中人与算法的交互，并揭示优先系统建议的潜在启发和偏差。

设计/方法论/途径

遵循建构主义传统，我们对收入优化者、分析师、经理和董事进行了 20 次深度访谈，他们在超过 25 个市场拥有丰富的经验，并在房地产和企业层面使用不同的 RM 系统 (RMS)。解释学方法用于解释参与者的生活经历以及与 RMS 的互动并赋予其意义。

 发现

研究结果解释了 RM 专业人员和 RMS 之间互动的本质、系统用户判断性调整或推翻其建议的认知机制，以及推翻决策背后的启发法和偏见。此外，研究结果揭示了影响人与算法交互的个人决策者特征和组织因素。

研究局限性/影响

尽管该研究重点关注酒店 RM 中的人机交互，但它对于将人类判断整合到计算机系统中以实现最佳决策具有更大的意义。

 实际意义

研究结果揭示了人类在使用 RMS 时存在的偏见，并强调了可以解决以实现有效的人机交互的影响因素。

 原创性/价值

该研究提供了一个以组织角色和期望确认理论为基础的整体框架，以解释管理决策中人与系统相互作用的认知机制。