This study investigates the impact of information asymmetry on hotel pricing in Taiwan, particularly how this dynamic shifted before and during the COVID-19 pandemic. Price discrimination, a key marketing strategy offering varying prices to different consumer groups based on attributes or price information, leads to price dispersion. The hotel industry's characteristics—non-storability, inelastic supply, and quasi-fixed investments—make price discrimination attractive for profit maximization across online and offline channels. Information asymmetry, where buyers and sellers have unequal access to market information, distorts prices. Hoteliers might charge unfair prices due to information barriers, while consumers might overspend. The COVID-19 pandemic significantly impacted the global hotel industry; many countries implemented restrictions to curb the virus's spread. This study focuses on Taiwan, which effectively managed the pandemic without widespread lockdowns or migration restrictions. The researchers selected Taiwan because its domestic tourism industry functioned relatively normally during 2019-2020, providing a unique context to assess the impact of the pandemic on information asymmetry in the hotel sector. The digital era has impacted tourism transactions, with digitalization facilitating the verification of identities, reputation assessments, and communication, strengthening consumers’ bargaining power. The pandemic further accelerated the digitalization of tourism, with hotels adopting unique digital solutions, yet Taiwan still faced issues of fragmentation and incomplete ICT application. This study used the two-tier stochastic frontier model (SFA2tier), a robust method to analyze incomplete information in various domains. This approach dissects opposing facets and captures individual heterogeneity, providing insights into changes in information asymmetry's impact on lodging prices. This study aims to quantitatively assess shifts in information asymmetry in the Taiwanese hotel market during the pandemic, a gap in current literature. This will provide a new perspective for future research and insights into the impact of the pandemic on Taiwan's tourism economy and its digital transformation.

The literature review examines existing research on hotel pricing and information asymmetry. Studies on hotel pricing have used various approaches: hedonic pricing models, which analyze the relationship between room rates and hotel attributes; revenue management pricing (RMP), which focuses on optimizing price strategies given a fixed supply; and game theory models, which explore interactions between hotels and other market actors. Factors influencing hotel prices include seasonality, location, length of stay, market share, and star ratings. Studies focusing on information asymmetry in the hotel market highlight the bargaining power of both hoteliers and consumers, with tourists often using bargaining to obtain value. Information asymmetry can lead to price dispersion, impacting hotel performance and causing skepticism among consumers regarding transparency in areas like health and safety. The digital era introduces new factors to this asymmetry; online reviews, ratings, and reputation play a significant role in shaping pricing and consumer choices. Quality certifications and electronic word-of-mouth can alleviate this asymmetry. The conceptual framework presented links information availability, bargaining intention and power, and the final bargaining outcome to hotel prices, considering hoteliers' (price, service quality, location, eWOM, online reviews, rankings), consumers' (cultural, sociodemographic, personality traits), and market-related factors (hotel concentration, environment, search engines, government policy).

The study employed a two-tier stochastic frontier model (SFA2tier) to analyze information asymmetry in Taiwan's hotel lodging prices. This model builds upon previous research using similar methods to analyze various economic phenomena. The model posits that the final lodging price (P) is a function of the lowest acceptable price for suppliers (P), the highest acceptable price for consumers (P), and a parameter (η) representing the market information in the price determination process. The model is expanded to show the information held by both consumers and hoteliers. Equation (1) shows how the final price (P) is determined, with η (0 to 1) representing the market information distribution. Equation (2) expands on this, considering consumer surplus and the hotel's surplus. Equation (3) presents the two-tier stochastic frontier model, where P represents the lodging price, µ(x) is the fair lodging price (function of individual characteristics x), and ε is the error term. The error term is composed of two components: w, representing hoteliers' surplus from information advantage, and u, representing consumer surplus from information advantage. The model uses maximum likelihood estimation (MLE) to estimate parameters. The probability density function (equation 4) is developed for the error term assuming exponential distribution for w and u and normal distribution for v. The log-likelihood function (equation 5) is then used for the MLE. The study uses equations (6a) and (6b) to determine the conditional distributions of u and w, with equations (7a) and (7b) calculating their conditional expectations. Net surplus (NS), used to reflect information asymmetry's overall impact, is calculated using equation (8). The advantage of the two-tier model lies in the ability to assess information mastery without pre-assumptions about relative advantages of hoteliers and consumers.

The study used data from the Taiwan Bureau of Tourism Statistics (July 2019-November 2020), resulting in 2032 observations after data cleaning. Table 1 presents descriptive statistics, showing the average lodging price (NT$ 3527.39), number of rooms, and employee counts. Table 2 presents OLS and two-tier stochastic frontier model estimation results. The translog function (equation 9) was used. Results indicate a significant negative impact of the number of hotel rooms, managerial employees, and hotel room department employees on room prices. The two-tier model offers a more granular understanding of the dynamics than OLS. Table 3 shows that hoteliers' surplus exceeded the baseline price by 30.31%, while consumers' surplus resulted in a 14.51% price reduction; the discrepancy resulted in a 15.81% higher-than-baseline price. Hoteliers' surplus was higher before the COVID-19 outbreak than after. Consumers' information advantage increased post-outbreak. Table 3 also presents quantile analysis: at Q1, the net surplus is 0.59; the disparity widens at Q2 and Q3. Figure 2 shows the surplus distribution for hoteliers and consumers before and after the pandemic. Post-epidemic hotel surplus is concentrated to the left, while consumer surplus shifted right, demonstrating the post-pandemic shift towards more consumer information. Table 4 shows regional disparities: before the pandemic, hotels in most regions had more information than consumers. The information divergence reduced post-outbreak, especially in urban areas. Figure 3 shows the change in net surplus in metropolitan areas (2019-2020); the net surplus in 2019 was significantly higher than in 2020. Figure 4 shows the proportion of domestic tourist accommodation in Taiwan's counties and cities from 2019 to 2020. There is a noticeable increase in the proportion of local tourists after the pandemic. The decrease in information asymmetry is attributed to changes in consumer group structures (reduction in international tourists post-pandemic) and hoteliers' responses to reduced tourist numbers (more price information and promotions).

The findings address the research question by quantitatively demonstrating the impact of information asymmetry on hotel pricing in Taiwan and how this changed during the COVID-19 pandemic. The study showed that information asymmetry significantly affects prices, with hoteliers generally having more information and greater bargaining power. The COVID-19 outbreak led to a considerable reduction in this information asymmetry, especially in metropolitan areas. This is largely explained by the shifting consumer base towards more domestically focused tourism and strategic responses by hotels aiming to attract limited customers. The results emphasize the importance of transparency in the hotel industry. The reduction in information asymmetry has implications for market efficiency, consumer welfare, and the competitiveness of the hotel industry. The findings highlight the dynamic relationship between public health crises, tourism behavior, and market information.

This study offers several key contributions: it quantifies information asymmetry in Taiwan's hotel market, introduces a new method for assessing this asymmetry, offers a detailed analysis of the impact of COVID-19 on this asymmetry, and provides practical implications for both hoteliers and tourism authorities. The findings suggest that hoteliers should prioritize transparency to increase consumer surplus and enhance their reputation, while governments should encourage transparency and provide support for consumers with limited information. Further research could explore this using panel data to assess the intertemporal aspects of buyer and seller information mastery.

The study's limitations include the use of maximum likelihood estimation in the two-tier stochastic frontier model, which is sensitive to initial value conditions and sample size and may have convergence issues. The data limitations prevent the analysis of fixed or random effects. Future research could employ panel data to address these limitations.