ISSN 1671-3710
CN 11-4766/R

Advances in Psychological Science ›› 2023, Vol. 31 ›› Issue (11): 1981-1993.doi: 10.3724/SP.J.1042.2023.01981

• Conceptual Framework •     Next Articles

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

HUANG Min-xue, LIU Yuan   

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

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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