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This paper aims to empirically test the effect of list price and bidding strategies in ascending auctions of residential real estate.

Three regression models are estimated, using a unique data set from 629 condominium apartments in the inner-city of Stockholm, Sweden, sold between January 2010 and December 2011.

The results show that jump bidding has the predicted effect of reducing competition by scaring off bidders. However, a higher average bid increment leads to a higher selling price. Furthermore, results show that a fast auction in terms of average time between bids acts to increase the probability of so-called auction fever as both the number of bidders and the selling price are positively correlated with the speed of the auction. While the average behavior of all auction participants, in terms of jump bidding and time between bids, significantly affects auction outcomes, differences in strategies applied by winners and losers show mixed results. The results of this study with respect to sellers’ list price strategy show that underpricing is an ineffective strategy in terms of enticing more bidders to participate in the auction. Furthermore, underpricing is not sufficient to have a positive effect on the selling price.

This paper is one of the first papers to empirically analyze how different bidding strategies affect the outcome of residential real estate auctions in terms of competition and the final selling price.

The role of list price is often discussed in a narrative describing sellers’ preferences or sellers’ price expectations. This paper aims to investigate a set of list price strategies that real estate brokers have available to influence the outcome of the sale, which may be many times self-serving.

By analyzing real estate brokers’ arguments on the choice of the list price level, a couple of hypotheses are formulated with regard to different expected outcomes that depend on the list price. This study empirically tests two hypotheses for the underlying incentives in the choice of list price from the real estate broker’s perspective: lower list price compared to market value leads to the higher sales price, lower list price compared to market value leads to a quicker sale. To investigate the two hypotheses, this paper adopts different methodological frameworks: H1 is tested by running a classical hedonic model, while H2 is tested through a duration model. This study further tests the hypotheses by splitting the full sample into two different price segments: above and below the median list price.

The results show that H1 is rejected for the full sample and for the two sub-samples. That is, contrary to the common narrative among brokers that underpricing leads to a higher sales price, underpricing lower sales price. H2, however, receives support for the full sample and for the two sub-samples. The latter result points to that brokers may be tempted to recommend a list price significantly below the expected selling price to minimize their effort while showing a high turnover of apartments.

Although there are a large number of previous studies analyzing list price strategies in the housing market, this paper is one of the few empirical studies that address the effect of list price choice level on auction outcomes of non-distressed housing sales.

This paper aims to explore two research questions. The first focuses on the main methodological characteristics of previous studies in the field of price and revenue research in terms of commercial peer-to-peer accommodation platforms (P2P APs). The second compares the 33 articles and identifies the convergent and divergent findings. The literature review outlines some future research avenues.

This paper is a literature review that explore the price and revenue determinants in the field of P2P APs (such as Airbnb). The methodology shows how the sample was defined and is based on three steps: selection of papers, sample selection, and coding. The research was carried out in March 2020 and generated an initial sample composed of roughly 3,000 articles. A two-stage inclusion/exclusion process was applied to select the final sample, which includes 33 articles.

The empirical findings report the main antecedents of price and revenue as well as the methodological domains of the analyzed papers. Focusing on determinants, six blocks of variables were identified. The listing variables (48%), host characteristics (18%), location (12%), guest review (11%), destination characteristics (11%) and external comparison (1%). For each block, convergent and divergent findings are illustrated.

The main limitations of this study relate to the criteria used in selecting the sample and the manual coding activity. This last decision (manual coding activity) was based on the limited number of papers available and the wide spectrum of variables used.

The practical implications are many, and they include a greater awareness of the variables that influence price and revenue as well as the impact that these variables could have on rates. Furthermore, managers interested in analyzing specific topics or variables can find analytical support in the information reported in the appendices.

The evidence provided is useful both for scholars considering further research in this field and for practitioners seeking to define pricing policies. Some future research avenues have been outlined, including new topics for development and methodological advancements.

Crowdfunding, especially reward-based crowdfunding, has quickly evolved into a commonly used vehicle for innovating entrepreneurs to develop their products. Many crowdfunding platforms allow creators maximum flexibility in terms of the prices and rewards offered in a project to gain sufficient capital. However, creators need to understand how to design project rewards and how to select a pricing strategy, in addition to whether the creator should spend resources on designing multiple rewards of varying quality. The purpose of this paper is to address these issues by answering whether and why there are significant differences in the application of early-bird and versioning pricing strategies in crowdfunding.

This paper develops a two-stage dynamic game model with incomplete information, proposes a corollary calculated by analyzing a perfect Bayesian equilibrium, and then tests Corollary 1 by empirical analysis.

Contrary to the findings of other studies, the results show that an early-bird pricing strategy is likely better than a versioning pricing strategy for earning greater revenue in a crowdfunding context, on average. This finding means that creators do not have to spend as much in designing rewards of various qualities; rather, they should only provide multiple price options for high-quality rewards. However, if the heterogeneity of target backers’ valuations and the quality difference between two types of products are adequately high, a versioning pricing strategy may be a good choice for creators.

This paper provides a reference for creators regarding the selection of pricing strategies and the design of reward quality when launching crowdfunding projects.

This paper explains an interesting and practical issue in the design of reward quality and the selection of a pricing strategy after fully considering the role of the crowdfunding all-or-nothing mechanism and special backer behavior.

This paper aims to explore the dynamics and performance of on-premise wine trade business.

The study involved in-depth interviews with six on-premise businesses in Seoul, South Korea. The data obtained were methodically analysed to understand the impact of different variables through a qualitative business dynamic model.

Customer satisfaction and number of customers are key performance factors for on-premise wine trade business. Customer satisfaction is driven by servicescape, wine lists and front-line employees. However, the length of wine list impacts directly on inventory costs and staff knowledge, while the number of service staff in the business has a non-linear effect on profits, as service staff does not grow linearly with the number of customers.

One important limitation is that the business dynamics model, which is based on South Korean cases, used only owners/sommeliers’ perspectives but not consumers’ perspectives. There are two implications. First, in terms of on-premise wine trade, the alignment of servicespace, front-line employees, wine lists and pricing strategy is key to shape customers’ expectations and confirm the market positioning of the business. Second, for wineries, understanding the dynamics of on-premise wine trade can help them to find strategies to position their wines.

The paper offers two contributions. Firstly, the paper provides the first exploratory study on the business dynamics of on-premise wine trade businesses, which complements existing wine-buying behaviour studies. Secondly, the study explores the on-trade channel in South Korea, providing insights into an important Asian market.

Why do some retail networks operate shop-in-shops along with stand-alone units while others do not? Drawing on a resource-based and intellectual capital (IC) perspective as a broad theoretical lens, the purpose of this paper is to focus on retailer-run shop-in-shops and examine the determinants of their adoption.

To gain a comprehensive understanding of shop-in-shop adoption by retail branded networks, a research design mixing a quantitative study (n = 170) and a qualitative study (n = 19) was adopted to test nine hypotheses regarding these determinants of the adoption of retailer-run shop-in-shops and explore in greater depth the processes whereby they actually occur.

The main findings show that intangible resources are major determinants of the choice to operate shop-in-shops while tangible resources are minor determinants. The more robust results of the analysis lie in the positive effect of own-label merchandise range, premium pricing strategy, positioning based on symbols, retail concept fast renewal and high sector specialisation on the choice to operate a shop-in-shop. The effect of financial constraints on the decision to expand via shop-in-shops is limited.

The authors emphasise the importance of marketing-related and company-related characteristics in differentiating the likelihood of retail networks to expand via shop-in-shops. These results lend support to the relevance of a resource-based and IC perspective in explaining the propensity of retailers to develop via shop-in-shops.

The decision to operate shop-in-shops should depend on the extent to which intangible resources – the most important being retail positioning grounded in symbols, an own-label merchandise range, and a high retail branded network reputation – can be valued and enhanced. Expanding a retail network via shop-in-shops does not appear to be a financially constrained expansion strategy: it must be considered as a relevant first best strategy when an independent and young retail company has intangible resources to value but limited tangible resources.

The study contributes to channel management and retailing research in four ways. First, it precisely delineates the specific characteristics of shop-in-shops. Second, it provides theoretical explanations – based on a resource and IC perspective – of determinants that influence the choice of shop-in-shops. Third, it empirically tests the influence of marketing-related and company-related characteristics when adopting shop-in-shops. Fourth, it provides insights into how adopting shop-in-shops. To the authors’ knowledge, the research is on the first to analyse theoretically and test the determinants for the choice of retailer-run shop-in-shops.

This paper aims to revisit the issue of anchoring effects in real estate markets to consider the current dual-processing theory of mind.

The effects of high and low anchors in a price estimation task are, thus, explained by both Systems 1 and 2 as these play a key role in the guess of the “correct” list price. The authors also take into account the mediation of overconfidence in the estimates and how confidence relates to cognitive ability. Moreover, the authors nuance the field experiment by considering the decisions taken by professional real estate agents and amateur students alike because experts are expected to be less prone to cognitive biases.

The large anchoring index of 67 per cent found for the real estate agents suggests these professionals make their judgment unconsciously by priming (and thus, using their System 1), despite being overconfident. In contrast, an even larger anchoring index for the undergraduates (86 per cent) was found, as expected for nonexperts. However, the authors suggest the students’ judgments use their System 2 because they are clueless in their non-anchored estimates and, as result, consider the list prices as a heuristic to deliberately anchor and adjust.

Anchoring effects in real estate markets have not been approached so far by the dual-processing theory of mind.

The purpose of this paper is to determine whether anchoring and adjustment as heuristic-driven bias and herding behaviour influences listed property fund managers in South Africa’s property investment decisions. The study contributes to the understanding of the influence of heuristic-driven bias and herding behaviour on property investment decisions made in a highly volatile environment.

This study is focused on the subject field of behavioural finance and follows a survey-based design. A questionnaire was finalised after completion of the pilot study and was sent via e-mail to fund managers of all South African-based property funds listed on the Johannesburg Securities Exchange. Non-parametric statistical measures were used.

Consistency with other studies suggests that anchoring and adjustment may exist in the decisions made by listed property fund managers. However, fund managers tend to not adjust to new information due to the current socio-political environment in South Africa rather than a lack of understanding of the new information.

It is recommended that investors form developed and emerging economies take notice of the highly volatile circumstances in which property fund managers in an emerging economy such as South Africa have to make investment decisions. The probability of missed gains as a result of conservative investment strategies may have an impact on future returns.

This study enhanced the understanding of the role that heuristic-driven bias plays in the South African property industry and more importantly, it went some way towards enhancing understanding of behavioural aspects and their influence on property investment decision making in an emerging market.

Three scenario-based experiments were conducted to explore the influence of the base option’s price format (just-at vs just-below) on tourists’ upgrade intention. The findings of this research indicated that tourists are more inclined to upgrade the option when the base option’s price is presented in a just-at condition due to the mediating role of tourists’ price perceptions of the upgrade option. This study discovered that the just-at (vs just-below) pricing strategy can lower tourists’ price perceptions of the upgrade choice. This research further explored the moderating of tourists’ mindsets. It was found the threshold-crossing effect will disappear for tourists with fixed mindsets. This study also provides practical implications for travel service providers to set up appropriate pricing strategies to attract tourists to make upgrade decisions.

The demand for accurate property value estimation by valuation report end users has led to a shift towards advanced property valuation modelling techniques in some property markets and these require a sizeable number of data set to function. In a situation where there is a lack of a centralised transaction data bank, scholars and practitioners usually collect data from different sources for analysis, which could affect the accuracy of property valuation estimates. This study aims to establish the suitability of different data sources that are reliable for estimating accurate property values.

This study adopts the Lagos metropolis property market, Nigeria, as the study area. Transaction data of residential properties are collected from two sources, i.e. from real estate firms (selling price) and listing prices from an online real estate company. A portion of the collected data is fitted into the artificial neural network (ANN) model, which is used to predict the remaining property prices. The holdout sample data are predicted with the developed ANN models. Thereafter, the predicted prices and the actual prices are compared so as to establish which data set generates the most accurate property valuation estimates.

It is found that the listing data (listing prices) produced an encouraging mean absolute error (MAE), root mean square error (RMSE) and mean absolute percentage error (MAPE) values compared with the firms’ data (selling prices). An MAPE value of 26.93 and 29.96 per cent was generated from the listing and firms’ data, respectively. A larger proportion of the predicted listing prices had property valuation error of margin that is within the industry acceptable standard of between ±0 and 10 per cent, compared with the predicted selling prices. Also, a higher valuation accuracy was recorded in properties with lower values, compared with expensive properties.

The opaqueness in real estate transactions consummated in developing nations could be attributed to why selling prices (data) could not produce more accurate valuation estimates in this study than listing prices. Despite the encouraging results produced using listing prices, there is still an urgent need to maintain a robust and quality property data bank in developing nations, as obtainable in most developed nations, so as to achieve a sustainable global property valuation practice.

This study does not investigate the relationship between listing prices and selling prices, which has been conducted in previous studies, but examines their suitability to improve property valuation accuracy in an emerging property market. The findings of this study would be useful in property markets where property transaction data bank is not available.