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Ting Yang, Ivan Ka Wai Lai, Zhao-Bin Fan and Qing-Min Mo
The purpose of this paper is to identify the factors that explain the acceptance of self-service ordering systems (SOSs) for restaurants and to explore the effects of…
The purpose of this paper is to identify the factors that explain the acceptance of self-service ordering systems (SOSs) for restaurants and to explore the effects of “self-service system service quality” (SSQ) and “interpersonal service quality” (ISQ) on the acceptance factors extended from the Unified Theory of Acceptance and Use of Technology model.
This study targets customers who have recently used SOSs to order foods in middle-class restaurants. In total, 402 valid survey samples were obtained. Partial least squares (PLS) analysis was used to examine the factors of user acceptance of using SOSs.
The results of the PLS-SEM analysis indicate that SSQ has a significant effect on accuracy expectancy, speed expectancy and effort expectancy; ISQ has a significant effect on accuracy expectancy, speed expectancy, effort expectancy and facilitating conditions; and accuracy expectancy, speed expectancy, effort expectancy, social influence, facilitating conditions and budget expectancy significantly influence user acceptance of SOSs. Furthermore, user experiences moderate the effect of speed expectancy and effort expectancy on user acceptance.
This study introduces three technology acceptance factors (accuracy, speed and budget) for researchers to consider in the future. It also extends the knowledge about the human service factor when middle-class restaurants adopt self-service technologies (SSTs). Recommendations are provided for system developers to improve the system quality of SSTs and service staff to rethink their roles in adopting SSTs in the service industry.
PLS-SEM分析结果表明, SSQ对准确预期、速度预期、努力预期, 有显著作用; ISQ对于准确预期、速度预期、努力预期、以及辅助条件, 有显著作用; 准确预期、速度预期、努力预期、社会影响、辅助条件、以及预算预期对于SOSs用户接受有显著作用。此外, 用户体验调节速度预期和努力预期对于用户接受的作用。
本论文新增了三种科技接受因子（准确度、速度、和预算）, 为未来的科研创造土壤。本论文还扩展了我们对于人员服务因子在中等餐厅采用SSTs的认知。本论文建议系统开发者应该提高SST系统质量, 以及建议服务人员重新审视在服务产业采用SST中自己的位置。
Bin Zhao, Haoquan Tan, Chi Zhou and Haiyang Feng
Information technology-enabled gig platforms connect freelancers with consumers to provide short-term services or asset sharing. The growth of gig economy, however, has…
Information technology-enabled gig platforms connect freelancers with consumers to provide short-term services or asset sharing. The growth of gig economy, however, has been accompanied by controversy, and, recently, food delivery platforms have been criticized for using data-driven techniques to set strict delivery time limits, resulting in negative externality. This study aims to provide managerial implications on the decisions of delivery time and subsidy for food delivery platforms.
The authors develop an analytical framework to investigate the optimal delivery time and subsidy provided to delivery drivers to maximize the gig platform's profit and compare the results with those of a socially optimal outcome.
The study reveals that it is optimal for the platform to shorten the delivery time and raise the subsidy when the food price becomes higher; nevertheless, the platform should shorten the delivery time and lower the subsidy in response to a higher delivery fee. Increases in the food price or delivery fee have non-monotonic effects on the number of fulfilled orders and the platform's profit. In addition, the authors solve the socially optimal outcome and find that a socially optimal delivery time is longer than the platform's preferred length when the delivery fee is high and the negative externality is strong.
The food delivery platform's optimal decision on delivery time is derived after taking negative externality into account, which is rarely considered in the prior literature but is a practically important problem.