The Incentive Mechanism of Knowledge Sharing in Cross-Border Business Models Based on Digital Technologies

Abstract

This paper aims to solve the time-constrained problems of knowledge sharing caused by geographical distance and cultural differences in cross-border business models by proposing a novel knowledge sharing model based on principal–agent theory. Given that digital technologies (DTs) can solve the information asymmetry issue, this paper analyses and compares the contract parameters given by the principal, the efforts of the agent, and the changes in the expected profits of both parties before and after the application of DTs and therefore discusses the influence of various relevant factors in incentive contracts; the relationship between the expected profit of both parties and the various relevant factors is analyzed through numerical simulations. The results show that, in cross-border business models considering the time value of knowledge, the principal is affected not only by “information rent” and “channel loss” but also by the “time cost”. The application of DTs can effectively reduce all three of these costs. More importantly, the principal’s incentive coefficient and the agent’s effort are related to this time constraint and the application of DTs.

Incentive contract design considering quotas production: A principal-agent perspective

“…For instance, automotive sectors in several nations grappling with the ramifications of greenhouse gases have instantiated fuel–vehicle production quotas [ 11 , 16 ]. Wang et al [ 31 ] integrate knowledge sharing into cross-border supply chains within a minimum constraint scenario and probe their inherent incentives. Li et al [ 41 ] constructed a two-tiered principal-agent model that encapsulated governments, manufacturers, and suppliers to formulate contracts that fostered collaborative mitigation strategies.…”

“…Similar to Ref. [ 31 ], this study assumes that incentive contracts are composed of fixed payments plus incentive payments, as demonstrated in Eq. (1) : …”

“…This section presents the specific assignment of each parameter to the model. The numerical settings for the base case were based on the numerical analyses of Wang et al [ 31 ], Sun et al [ 54 ], and Zhang and Xu [ 55 ]. Drawing on these studies, we set the following parameters to focus on the response of our model: In the supply chain model, the initial values of the relevant parameters are be , , , , , , , , , and .…”

“…This differs from our focus on quota production. Other studies have prioritized production quotas [ [30] , [31] , [32] ]; our model integrates principals’ effortful actions, an element absent in their assessments. Existing studies have also touched on output or bonus quotas [ 33 , 34 ], but they diverge fundamentally from our model; they limit the maximum output, whereas our production quotas set the minimum.…”

Sustainable Quality-Incentive Contract Design of Public Technology Innovation Procurement under Asymmetry Information

“…The design of existing incentive mechanisms often focuses on reducing product costs [18][19][20] or increasing production [12]. Most studies ignore the dual-asymmetry information of adverse selection and moral hazard, and only consider the problem of single-asymmetry information [21,22].…”