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The paper aims to quantitatively investigate vacant industrial land valuation accuracy in China, given the importance of the industrial market as an underlying pillar to promote urban growth especially in emerging economies.

In China, the government formulates a Land Benchmark Price (LBP) to serve as a price reference point to sell land rights. To gain an in-depth understanding of the valuation practice by LBP, this paper uses correlation analysis to investigate the varying dynamics between the transaction-based prices and LBP appraisal-based estimates. Furthermore, a margin of error examination investigates the distortion in LBP land appraisals, with an amended LBP presented to improve the accuracy of the current LBP method.

Different influencing factors are identified to impact the actual market transaction prices and the LBP construction, leading to a large discrepancy in industrial land appraisals. A systematic problem is recognised that the construction of the LBP follows urban bid curve theory, whereas the land transaction prices do not, demonstrating that an urgent LBP update is needed to capture the market dynamics for industrial market.

The paper sets out discrepancies in valuation accuracy surrounding the application of the LBP valuation approach in China. This has practical implications for valuers in terms of raising their awareness of the deficiencies in the approach and the pitfalls they need to guard against in their appraisals. It also has implications for developers and investors who rely on valuer appraisals to assess the viability of land purchases; hence, they need to express caution in the appraisal advice sought. Finally, the results demonstrate to the standard setters how they need to modify the LBP equations to better capture market dynamics.

The paper examines valuation accuracy in transitional economies, through valuation differentials between appraised price and the transacted price. The value of the work lies in the analysis of the fundamental differentials between market price and appraised value, which is of importance to investors/developers, practicing valuers, as well as government officials responsible for setting the valuation standards.

Based on appraisal theory and social response theory, this study aims to explore the mechanism of AI failure types on consumer recovery expectation from the perspective of service failure assessment and validate the moderate role of anthropomorphism level.

Three scenario-based experiments were conducted to validate the research model. First, to test the effect of robot service failure types on customer recovery expectation; second, to further test the mediating role of perceived controllability, perceived stability and perceived severity; finally, to verify the moderating effect of anthropomorphic level.

Non-functional failures reduce consumer recovery expectation compared to functional failures; perceived controllability and perceived severity play a mediating role in the impact of service failure types on recovery expectation; the influence of service failure types on perceived controllability and perceived severity is moderated by the anthropomorphism level.

The findings enrich the influence mechanism and boundary conditions of service failure types, and have implications for online enterprise follow-up service recovery and improvement of anthropomorphic design.