Repeat Sales Research Articles

Neuromarketing as a Tool for Promoting Injection Medicine Services in Rus

Considering neuromarketing as a tool for promoting injection medicine services in Russia, the study provides an interpretation of the concept of "strategies for promoting injection medicine services using neuromarketing", since with the development of the Internet an independent direction of digital marketing has emerged, which provides significantly more opportunities for promoting goods and services than traditional marketing. The features of the use of neuromarketing technologies in strategies for promoting injection medicine (IM) services are determined. The study of customer preferences does not stand still; neuromarketing and new technologies for tracking consumer behavior by reading emotions and reactions to products or advertising help companies deeply study needs and create what people want. In retail outlets, tracking the customer’s journey with cameras and sensors helps identify those products that most attract the consumer’s attention. The trend that everything should be digitized is telling companies to change their mechanisms for collecting and processing consumer information. All information about the client must be digitalized in one way or another. End-to-end analytics consists of several levels: advertising, leads, sales, repeat sales. Tools are determined depending on the specifi cs and size of the company. PR and promotion is a technology in marketing, thanks to which public opinion about an organization, brand, and personality is formed over the long term. The goal of PR is to create a proper and mutually beneficial partnership between the company and society, providing reliable information about the company, products and services.

The impact of customer perceived value on customer satisfaction and loyalty toward the food delivery robot service

研究目的食品配送机器人服务（FDRS）是一种使用自主配送机器人改变移动食品订购的新型服务。尽管FDRS公司在美国各地的服务扩张迅猛, 但对于顾客感知价值、顾客满意度和忠诚度的理解仍有限, 而这对于促进重复销售至关重要。因此, 本研究旨在考察顾客对FDRS的感知价值, 确定影响顾客对FDRS满意度的先决条件, 并调查顾客对FDRS及使用FDRS的餐厅的满意度和忠诚度的影响。研究方法本研究以美国18岁以上并且在过去12个月内使用过FDRS的顾客为样本, 共收集到323份回答。采用描述性统计、确认性因素分析和结构方程模型进行数据分析。研究发现本研究的结果显示功能性、价格和情感价值对顾客满意度有积极影响。当前研究还表明, 顾客满意度对FDRS及餐厅的忠诚度有积极影响。研究创新/价值本研究可以说是首次调查顾客对FDRS购买后的体验, 从而增进对顾客对该服务行为的理解。此外, 本研究采用了来自消费价值理论的多维消费价值方法, 为探索FDRS背景下顾客感知价值、满意度和忠诚度之间的关系提供了一个单一的框架。

Tracking Residential Real Estate Capital Growth In NSW by Constructing A Price Index from Sales Transactions

The main objective of this paper is to investigate residential real estate capital growth in the state of NSW (Australia). Tracking capital growth has been instrumental for tracing price variations & value growth of residential real estate. More specifically, residential real estate past sales transactions can be utilized to track capital growth using repeat sales approach. Ordinary least squared method was used to fit a linear model and construct a price index. The results were used to establish a yearly and quarterly price index for the whole state as well as for each respective district. The research shows that while using a mean price as a measure for tracking growth can produce misleading results, the capital growth-tracking can be carried out more accurately by the means of investigating repeat sales. Furthermore, the research reveals trends in the property market as well as areas with the highest and lowest growth. The results produced can help investors, banks, and government organizations to compare capital growth across different districts at different times and drive lending, investment, or development decisions.

The effect of school zone on housing prices: evidence from a quasi-natural experiment in New Zealand

We analyse a quasi-experiment where a much sought-after state secondary school with no close substitutes unexpectedly reduced its enrolment zone twice over a three-year period. We use difference-in-differences to estimate the impact of the two downsizings on housing sales prices. We use controls for housing characteristics for pooled cross section or housing fixed effects for repeat sales, test for parallel trends, and conduct numerous robustness checks. In our main analysis, we find the first downsizing may decrease housing prices between 3.2% and 12.9%, with most estimates statistically significant, while the second downsizing may decrease prices between 2.1% and 7.2%, with most estimates insignificant. Tests in the pre-treatment period suggest parallel trends cannot be rejected, though some cross section interactions are significant when the two downsizings are analysed separately. We conclude the school zone’s first downsizing likely had a negative effect on housing prices of a small to moderate magnitude.

Impact of demolitions on neighboring property values in Detroit

AbstractUrban blight is a complex problem that has been challenging for cities in the United States “Rust Belt” region for many decades. However, in the wake of the real estate and financial crisis, it is also a growing challenge for urban communities in many states such as California, Arizona, Nevada, and Texas. Detroit was particularly hit hard, where more than 40,000 blighted structures were identified in 2014. To curb blight, the city mobilized the most extensive demolition program in the country. Funded through the Federal Hardest Hit Fund (HHF), the Detroit Demolition Program began in 2014 and has demolished more than 20,800 properties at the cost of over $250 million. Furthermore, during 2009–2015, the city demolished 11,400 structures with hazardous materials such as asbestos. In this article, we assess the impacts of demolitions on the value of neighboring properties using a Repeat Sales (RS) regression approach. Specifically, we use housing sales price information from 2009 through 2019 to construct real estate price indices. We also rely on information from the 2009 Detroit Residential Survey to differentiate by dilapidation and blight levels before the start of the program. On average, blight removal through the demolition program does not appear to have been capitalized into the residential property prices. However, when considering the effect of ex‐ante program property characteristics, we find a modest positive effect of demolitions on property prices in areas with a low level of blight before the demolitions. Given the magnitude of the observed effect and the high costs associated with the demolition program, our results highlight the need for further research on alternative blight removal strategies that might provide a more cost‐effective solution to this urban challenge.

Biochemical Evaluation of Some Fruit Characteristics of Blueberry Progenies Obtained from 'Simultan × Duke'.

The popularity of Vaccinium corymbosum blueberry cv. has increased over time because its fruits are highly valued for their taste, aroma, and multiple ways of use. A field trial with two genotypes and their hybrids was organized during 2021-2022 at the Research Institute for Fruit Growing Pitesti-Maracineni, Romania. This paper proposes a comparative analysis of the quality of berries in 17 hybrids of the 'Simultan' and 'Duke' cultivars, selected by the size and the soluble solid content, in agreement with the objectives of the blueberry breeding program. The genotype influence on berry weight, total soluble solids, pH, vitamin C, total polyphenols, total flavonoids, total anthocyanins, lycopene, β-carotene, and antioxidant activity was determined considering the climatic factors. The results showed that fruit weight varied between 1.22 and 2.47 g, total soluble solids reached a maximum of 19.22 °Brix, and the pH oscillated between 3.14 and 3.89. Vitamin C content varied from 9.52 to 18.69 mg in 100 g fresh weight, with an average of 14.35 mg/100 g. Total polyphenol, flavonoid, and anthocyanin contents averaged 709.92 mg gallic acid equivalent in 100 g fresh weight, 165.48 mg catechin equivalent in 100 g fresh weight, and 81.88 mg cyanidin-3-O-glucoside equivalent in 100 g fresh weight, respectively. Results show that the strategy of growers to produce blueberries with a large diameter, visually attractive for traders and consumers, is not sufficient for repeat sales. Our study proves that large fruits do not have the highest content of bioactive compounds. Smaller berries had higher polyphenol, lycopene, and β-carotene contents. It is recommended that the selection of the hybrid in the breeding program also takes into account the content of bioactive compounds.

School quality as a catalyst for bidding wars and new housing development

AbstractWe provide new evidence of the demand for better schools as manifested in bidding wars and changes to the built environment. Using repeat sales before and after a redistricting, we exploit shocks to school quality arising from the continuous, unexpected redistricting of school attendance boundaries in Atlanta. We find that houses redistricted to higher (lower) quality schools are more (less) likely to be involved in a market‐driven bidding war. Similarly, undeveloped, redistricted parcels that receive a positive (negative) school quality shock are more (less) likely to be developed. School quality shocks also have a causal effect on house prices and time‐on‐market.

The price paid: Heuristic thinking and biased reference points in the housing market

Does the power of reference points mean that minute differences in a purchase price then reverberate in future sales prices? In this research, I show that if previous sales prices are round numbers, defined as multiples of £1,000 (e.g. £231,000), subsequent sales prices entail a considerable premium relative to similar properties that were previously priced at charm numbers that are marginally below those round numbers (e.g. £230,999 or £230,950). Using a sample of repeat sales from the Greater London region from 1995 to 2017, I estimate the premium to be approximately 4 percent after controlling for property characteristics and a large set of fixed effects. Increasing public accessibility of information attenuates the effect. Tax considerations, financial constraints, and pricing errors cannot explain the result. I propose a framework of reference dependence and left-digit bias to explain the result, highlighting the presence of behavioural biases in household decisions, even when very high stakes are involved.

Selection Bias in Housing Price Indexes: The Characteristics Repeat Sales Approach*

AbstractThe widely used repeat sales method for constructing house price indexes only uses data for properties that sell twice or more. This makes it susceptible to selection bias as price movements for these properties may not be representative of those for the stock of homes. We outline a novel approach to modelling repeat sales, which allows for a home's characteristics to influence its price movement. This allows us to impute price changes for the stock of homes and control for selection‐on‐observables. Using data for Florida from 2002 to 2020 we find that selection effects significantly exaggerated the volatility of Florida's housing prices.

Recommend or Not: Is Generation the Key? A Perspective from the SOR Paradigm for Online Stores in Colombia

Word-of-mouth behavior is one of the most effective marketing communications. Despite not being able to be controlled by the company, it can be influenced. Its importance lies in its effectiveness in repeat sales and attracting new customers. However, in the study of consumer behavior, it has been shown that the differences between subgroups can be relevant for the business sector, allowing it to generate specific strategies for each segment. In that respect, this research aims to find the determinants of WOM in generations X and Y to know the meanings these consumers give to the elements proposed within the SOR paradigm. A quantitative study was conducted using a sample of 537 e-commerce customers surveyed with a structured questionnaire to test the proposed relationships. Results are analyzed with structural equations, and a multigroup analysis is presented to find the differences between generation X and generation Y. The results indicate that, for millennials, the ease of use of electronic stores is essential to enjoying the shopping experience. Implications are discussed in the paper.

House Price Prediction Using Exploratory Data Analysis and Machine Learning with Feature Selection

In many real-world applications, it is more realistic to predict a price range than to forecast a single value. When the goal is to identify a range of prices, price prediction becomes a classification problem. The House Price Index is a typical instrument for estimating house price discrepancies. This repeat sale index analyzes the mean price variation in repeat sales or refinancing of the same assets. Since it depends on all transactions, the House Price Index is poor at projecting the price of a single house. To forecast house prices effectively, this study investigates the exploratory data analysis based on linear regression, ridge regression, Lasso regression, and Elastic Net regression, with the aid of machine learning with feature selection. The proposed prediction model for house prices was evaluated on a machine learning housing dataset, which covers 1,460 records and 81 features. By comparing the predicted and actual prices, it was learned that our model outputted an acceptable, expected values compared to the actual values. The error margin to actual values was very small. The comparison shows that our model is satisfactory in predicting house prices.

The Impact of Legalizing Accessory Dwelling Unit Rentals on Property Values: Evidence from Ogden, Utah

We study the impact of legalizing the rental of Accessory Dwelling Units (ADUs) on property values. We use a dataset of property sales in Ogden, Utah both before and after a policy change legalizing ADU rentals in 2016. We apply repeat sales and differences-in-difference methods to evaluate the impact of the ordinance on property values. Theoretically, the ordinance could increase property values due to the higher expected returns available from ADU rental income, however, potential congestion, noise, and parking issues could alternatively cause property values to decrease. In our analysis, we find no significant impact of ADU legalization on property values in areas affected by the policy change compared to unaffected areas. These results are robust to a number of different model specifications. Several features of Ogden’s real estate market and policy environment may also contribute to this null result including challenges in effectively prohibiting black market long-term ADU rentals in areas where they remain illegal and/or property owners using ADUs for short-term vacation rentals which is legal city-wide. These results suggest that legalizing residential ADU rentals may be an effective way to increase the supply of affordable rental housing and provide supplemental income to homeowners without negatively impacting property values.

Neighborhood Heterogeneity: Implication to the Weighted Repeat Sales Method

ABSTRACT Does the degree of neighborhood heterogeneity, in and of itself, contribute to the cross-sectional price variations beyond that attributable to differences in physical characteristics within the neighborhood? This study presents theoretical and empirical investigations to confirm that the degree of property heterogeneity within the neighborhood can explain a significant portion of the cross-sectional price variations. Using the MLS data in south Florida, we conduct a series of regression analyses that yield consistent and robust results indicating that (1) neighborhood heterogeneity, whether structural or demographic, exhibits significant explanatory power to the pricing variations; (2) the market volatility, in contrast, only explains a small portion of the pricing variation, which confirms the finding of Case and Shiller; and (3) market liquidity, though not a neighborhood heterogeneity measure, does have a significant and negative effect on the pricing variation, suggesting that the availability of comparable sales can reduce pricing variation. These findings can potentially lead to an improvement over the widely-used Weighted Repeat Sales (WRS) method for constructing home price indices.

How does transfer duty relates to housing demand in the city of Johannesburg, South Africa?

PurposeAcknowledging that housing forms a large part of households’ and country’s long-term wealth, the South African Government has implemented various housing-related policies towards that end. Among these, the government has extended transfer duty exemption to house buyers – both individuals or natural persons and companies or other parties – to enable them buy houses of their choices since January 1950 to date. This paper aims to investigate the relationship between historical transfer duty exemption and housing demand in the City of Johannesburg (CoJ) over a longer period, where a comprehensive data set on house sales and other predictors was available.Design/methodology/approachThis paper uses multi-year data on repeat house sales from 2010 to 2020 and other macro- and socio-economic variables to test the relationship between transfer duty exemption and housing demand in the CoJ, a core part of Gauteng province, South Africa. After cleaning the original data, final analysis was based on 139,121 repeat sales transactions. Data was analyzed in R.FindingsFindings suggest that, when macro-, socio-economic and yearly effects are controlled, transfer duty has a damping effect on housing demand in the CoJ. The results were consistent across all the estimated models. While the motivation behind the implementation of transfer duty exemption in South Africa continues to encourage home ownership, these findings are unexpected because they do not offer support to that policy intention. These unexpected results are partly explained by the prevailing complexities of the housing market and related policies and the progressive tax regime. However, there are welfare effects that all buyers achieve across the housing market ecosystem.Originality/valueThis paper extends work on housing markets research in South Africa through the investigation of mortgage-based housing market in the CoJ that presents one of the densest, developed, bustling and growing housing market in the country. It also presents a fertile ground where all the effects of all the housing policies coalesce – in the statistical sense, one can control the effect of some aspects of housing policies, while appropriately testing the link between a specific policy (in this case, transfer duty exemption) and housing dynamics.

REAL ESTATE PRICE INDICES CALCULATION METHODS: METHODOLOGICAL REVIEW

Sri Lankan Real Estate market is experiencing a boom after the post war period. In the present context investments in real estate markets have been increased by both local and international investors where international investors play a significant role. Even though there are more investment opportunities in the Sri Lankan Real Estate market, the absence of a proper mechanism to identify the price trends in real estate properties have become a vital issue which bothers investors in the decision-making process. Filling this research gap in Sri Lankan context is of vital importance not only to the potential investors and policy makers in the Real Estate market but also to professionals in other businesses who will be benefited equally while serving their information thirst. The thirst. The data collection was purely literature based. Among the available sources, there are different types of indices available worldwide. Among them, real estate price indexes were selected for further analysis purposes. Many methods have been applied to calculate the real estate price index, yet no review has done to identify which method is most suitable for Sri Lanka. This paper aims to present a critical review of the real estate price index calculation methods and techniques already applied. Real estate price index calculation methods were used as data of this study and it was collected through 35 Google scholar indexed Journal articles during 2000-2020. Critical review method and descriptive review method were used to analyze the data according to the chronological order. As per the analysis of the literature, there are 6 main methods to calculate the property price index such as, Simple Mean/ Median method, Stratification or mix adjustment method, Hedonic Regression method, Repeat sales method and Appraisal-Based methods. However, results emphasized many methods are quantitative as well as the Hedonic Regression method is the most commonly and widely used method. In addition, it is appropriate method to construct a property price index in Sri Lanka.
 Keywords: Real Estate Price Index, Hedonic Regression Model, Repeat Sale model,Appraisal Methods

Consumer's Behaviour while Purchasing Apparels in Sale Period

Consumer behaviour study is an effort to comprehend the buying pattern of the final consumer. Consumer's frequency of purchase and buying habits depict how sellers and marketers are promoting their product and luring customers time and again through their attractive sales promotion deals. Brain finds pleasure in the pursuit of inexpensive, and by tapping on the same idea, sellers are introducing repeat sales and low price deals along with added benefits to make their customers loyal towards them, thereby making the competition between physical and online retail store fierce day by day. This study examines the impact of influential determinants of consumer's buying decision for clothes during sales with respect to various demographic variables. The comprehensive study analyzed factors that affect the purchase of apparels from physical and/or online retail store. The result also provides deeper insight into different forms of sales customers prefer while searching for the best deal. It helps in understanding consumer's buying habits and making consumer's experience economical and memorable. It is ideal for marketers and sellers to take into consideration the fact that demographic variables are the underlying determinants to cater to customers' needs and wants, and in order to meticulously understand the habits of customers, it should be carefully administered to be able to let customers' repeat their purchase of apparels from physical and/or online retail store.

Property value effects of the Hemlock wooly adelgid infestation in New England, U.S.A.

We investigate residential property-price effects of the spread of the Hemlock wooly adelgid infestation northward through central portions of Connecticut and Massachusetts, USA. We find that hemlock trees and the accompanying adelgid infestation within 0.1 km buffers of properties affect sale prices, but the results do not extend to buffers of 0.5 and 1.0 km's. Further, within the 0.1 km buffer, only the healthiest hemlock trees contribute positively to property values. We investigated the robustness of the results to three data interpolation methods, Kriging, Inverse Distance Weighting and Spline, and while there was some minor difference in outcomes the results are robust to these interpolation methods. Two property-price models were estimated, a traditional hedonic model with spatial fixed effects and a repeat sale model. The models provide substantially different property-price impacts and care needs to be taken when interpreting these estimates. Both approaches are limited but in different ways; the hedonic by potentially omitted variables and the repeat-sales by a limited number of observations. Our results provide some support for the repeat-sale model as the hedonic model with spatial fixed effects underperformed when both models were estimated using the same data.

Health Crisis and Housing Market Effects - Evidence from the U.S. Opioid Epidemic

We present evidence on the effect of a public health crisis on housing markets through the lens of the recent opioid crisis in the U.S. Using data on opioid prescriptions and repeat sales in Ohio, we find that house price changes around opioid dispensaries are negatively associated with the quantity of opioids dispensed. To explore a causal inference, we use a potentially cleaner measure of supply that is based on vertical integration. We estimate that a one standard deviation increase in the standardized number of pills dispensed by vertically integrated pharmacies is associated with a 5.8% decrease in house price appreciation. Our work informs the broader policy discussion on economic costs resulting from health crises.

A Spatial Dynamic Factor Repeat Sales Model for Real Estate

A Spatial Dynamic Factor Repeat Sales Model for Real Estate

Relevance of Marketing Strategies for Gas Stations in China – An Analysis Using SPSS

This study aims to find out the relevance of marketing strategies for gas stations in China. According to IBISWorld, the companies holding the largest market shares in China’s gas station industry include China Petrochemical Corporation, China National Petroleum Corporation, Sinochem Corporation, China National Offshore Oil Corporation, and BP (China) Holdings Limited. Marketing has changed over the past several years. Similarly, gas station marketing is all about more customers, greater sales, and higher profits. Technology provides many different marketing tools to see more fresh faces at the door, increase repeat sales, and improve profits. Word-of-mouth advertising should be encouraged, especially when contests are being held. The prizes from these contests may include car essentials, free coffee, free car wash, or coupons to be used at convenience stores. Customers who have won these contests would surely go around advertising the particular gas station, ultimately bringing in more customers. Other than that, managers can boost the sales volume through radio promotions as well. This study also aims to give future businessmen and women some ideas on how to deal with different kinds of strategies when it comes to marketing, especially in China in hope to cater and prove to the people of China the possibility of promoting businesses, such as the oil industry.