ISSN 1671-3710
CN 11-4766/R
主办:中国科学院心理研究所
出版:科学出版社

心理科学进展 ›› 2023, Vol. 31 ›› Issue (11): 1981-1993.doi: 10.3724/SP.J.1042.2023.01981

• 研究构想 •    下一篇

人机协同增强型商务信息管理决策采用的心理机制——自我决定理论视角

黄敏学1,2, 刘远1,2()   

  1. 1武汉大学中国营销工程与创新研究中心, 武汉 430072
    2武汉大学经济与管理学院, 武汉 430072
  • 收稿日期:2022-10-21 出版日期:2023-11-15 发布日期:2023-08-28
  • 通讯作者: 刘远, E-mail: 16263617@qq.com
  • 基金资助:
    国家自然科学基金项目(72132008)

Psychological mechanisms underlying adopting human-machine collaboration in augmented managerial decision-making: A perspective of Self-Determination Theory

HUANG Min-xue1,2, LIU Yuan1,2()   

  1. 1Research Center for Marketing Engineering and Innovation of China, Wuhan University, Wuhan 430072, China
    2School of Economics and Management, Wuhan University, Wuhan 430072, China
  • Received:2022-10-21 Online:2023-11-15 Published:2023-08-28

摘要:

随着数据科学和认知智能等新技术的发展, 人机协同的增强型商务信息管理决策逐渐成为组织决策的主流方式, 它的潜在优势也引起了众多实践者和研究者的高度关注。相较于传统的以管理者为中心的组织决策范式, 人机协同决策范式意味着曾经作为工具的机器演变成为了与管理者具有平等地位和同等决策权力的队友。对于管理者而言, 机器这一重要角色的转变弱化了管理者自身在决策过程中的重要性, 甚至导致管理者对人机协同决策产生潜在抵制行为。为了解决这一关键问题, 本研究从自我决定理论出发, 系统地优化人机协同增强型商务信息管理决策模式和功能的设计, 增加管理者对其“造” (技术就绪度)和“用” (技术接受模型)的感知, 以满足管理者的自我决定需要, 从而提高管理者对人机协同增强型商务信息管理决策的采纳意愿。

关键词: 自我决定理论, 技术就绪度, 技术接受模型, 人机协同增强型

Abstract:

With the advent of novel technologies, including data science and cognitive intelligence, business information management decision-making enhanced by human-machine collaboration has progressively developed into the mainstream form of organizational decision-making. Further, its potential advantages have garnered significant attention from many practitioners and researchers. In contrast to the traditional manager-centered paradigm of organizational decision-making, the paradigm of human-machine collaborative decision-making enables the machine, once a tool, to evolve into a team-mate with equal status and decision-making power as the manager. For managers, the transformation in the crucial role of machines erodes the importance of managers in the decision-making process, resulting in potential resistance to human-machine collaborative decision-making. To resolve this vital issue, this study proposes to develop a theoretical model based on the self-determination theory to enhance the perception of “creation” (Technology Readiness Index) and “use” (Technology Acceptance Model) of management decision-making systems by systematically optimizing the model design of human-machine system decision-making to satisfy the self-determination needs of managers and increase their willingness to adopt human-machine collaborative and augmented business information managerial decision-making. This theoretical model not only enhances the diffusion speed of the human-machine paradigm in organizations, but also reduces managers’ potential resistance.

The model explores two progressive levels: (1) Mechanistic analysis: How do the design of the human-computer collaboration model and functional design of the enhanced decision-making system affect managers' self-determination needs and ultimately their willingness to adopt business information management decisions by influencing technology readiness and technology acceptance, respectively? (2) Moderating effects: How do organizational variables moderate the effects of technology readiness and technology acceptance on managers' self-determination needs?

At the level of mechanistic analysis, according to the importance and control from “human” to “machine” in the human-machine collaborative and augmented business information managerial decision-making, the human-machine collaboration model is built in the order of the communication mode design, interaction interface design, work task design, and intelligence degree design. Each design generates optimism and innovation and reduces the discomfort and insecurity caused by the system to give managers the perception of “creation” (Technology Readiness Index). Meanwhile, in the design of the augmented decision-making system functions, the joint decision-making function, iterative optimization decision-making function, cognitive decision-making environment function, updating decision-making knowledge function, and big data deep mining function are designed in turn, which may increase managers' perception of technology acceptance including perceived usefulness and ease of use, and can also enhance managers' perception of the “use” of technology acceptance. With increased optimism and innovation, decreased discomfort and insecurity, and increased perceived usefulness and ease of use, managers experience higher levels of behavioral mastery (Agarwal & Prasad, 1998), self-efficacy (Zeithaml et al., 2002; Meuter et al., 2000), and perceived support control (Dabholkar, 1996). Thus, autonomy, competence, and belonging needs will be met. In this case, managers are intrinsically motivated to adopt the human-machine collaborative and augmented business decision-making. (Jang et al., 2009; Chen & Jang, 2010).

At the level of moderating effects, this study also examines which contingency factors influence the activation of technology readiness and technology acceptance on managers' self-determination needs. Threatening punishment (Deci & Cascio, 1972), restrictive deadlines (Amabile et al., 1976), coercive goals (Mossholder, 1980), and competition (Deci et al., 1981) in external environmental events can affect individuals' extrinsic motivation, and thus, weaken intrinsic motivation. Conversely, any external event that satisfies people's needs for competence, autonomy, and belonging enhances intrinsic motivation for individual behavior. Therefore, this study hypothesizes that transformational leadership, autonomous organization, organic organization, and individualized decision-making scenarios may lead to higher autonomy, efficacy, and a sense of belonging. Consequently, it contributes to the impact of technology readiness and technology acceptance on managers’ self-determination needs.

Key words: self-determination theory, technology readiness index, technology acceptance model, augmented with human-machine collaboration

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