Types Of Sellers Research Articles

Third-Degree Price Discrimination in Two-Sided Markets

We investigate the welfare effects of third-degree price discrimination by a two-sided platform that enables interaction between buyers and sellers. Sellers are heterogeneous with respect to their per-interaction benefit, and, under price discrimination, the platform can condition its fee on sellers’ type. In a model with linear demand on each side, we show that price discrimination (i) increases participation on both sides, (ii) enhances total welfare, and (iii) may result in a strict Pareto improvement, with both seller types being better off than under uniform pricing. These results, which are in stark contrast to the traditional analysis of price discrimination, are driven by the existence of cross-group network effects. By improving the ability to monetize seller participation, price discrimination induces the platform to attract more buyers, which then increases seller participation. The Pareto improvement result means that even those sellers who pay a higher price under discrimination can be better off, because of the increased buyer participation. This paper was accepted by Joshua Gans, business strategy. Funding: A. de Cornière acknowledges funding from ANR [Grant ANR-17-EURE-0010] (Investissements d’Avenir program). Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2023.02788 .

Bayes goes big: Distributed MCMC and the drivers of E-commerce conversion

This work researches the drivers of e-commerce conversion of one of the largest e-commerce companies in the Netherlands. We focus on product page conversion, i.e., the probability that a customer who visits a specific product page also buys the product. This probability differs between products, which we explain by a variety of factors like pricing, delivery times, reviews, seller type, and the quality of the content. Understanding the drivers of conversion is the first step in increasing it, and therefore an important step in increasing overall sales. We describe the process of transforming Big Data into valuable insights using Bayesian statistics and apply a Bayesian Binomial model to a dataset of 15 million records using a distributed MCMC algorithm. In addition, we apply a simple Binomial GLM on a small sample of these 15 million records for comparison. We find that using the full 15 million records results in a significant reduction in the variance of the estimated parameters. In terms of the actual drivers of e-commerce conversion, we observe that products with competitive pricing, short delivery times, and good content all achieve a higher conversion on average. Furthermore, reviews, average review score, and the number of reviews for a product have a large positive effect on conversion compared to other characteristics. This provides a unique insight into what makes people decide whether or not to purchase a product.

Taste over waste: How seller type affects consumer purchase intention toward imperfect produce

Although imperfect produce may not differ from regular produce in the dimensions of taste or nutrition, most of consumers unwilling to purchase them, thus, reducing the waste of imperfect produce is crucial for both environmental preservation and food conservation. Through four online experiments in China (covering in total 888 respondents), we provided evidence that consumers are more willing to purchase imperfect produce sold by producers compared to those sold by professional sellers. Pilot study (N = 300) shows that individuals held the lay belief that producers (e.g., farmers) provide natural and healthy produce, while professional sellers (e.g., sales clerks) focus on presale selection. Furthermore, Study 1 (N = 200) found that the sale of imperfect produce by producers elicits a greater purchase intention than that by professional sellers in the context of live streaming shopping. Study 2 (N = 200) then replicated the finding of Study 1 and found that this effect is mediated by the dual mechanism of perceived health and perceived effort in the offline retailing context. Additionally, Study 3 (N = 188) reveals that adding a claim of imperfection causes augments the sales performance of professional sellers in the online shopping context. This finding suggests that adding a claim of imperfection causes can enhance the efficacy of professional sellers in marketing imperfect produce.

House Rent Prediction

Abstract: Forecasting rental trends is crucial for many individuals as rental rates in the real estate market tend to escalate annually. Some people want a house with low rent and a usable area, so our article furnishes valuable insights into rental expenses, catering to individuals seeking prospective tenants. Hence, considering our demographic profile, it's essential to employ a systematic approach for predicting future residential rental prices. Buyers who rent accommodation according to their specific needs will know the perfect duration for renting. Many factors, such as seller type, bedroom count, layout type, property type, locality, price, area, furnish type, and bathroom count, influence rent. This study explores and applies multiple regression models Including linear regression, Random Forest regression, and gradient boosting regression, and XG boosted regression algorithm in Machine learning is utilized for prediction of the rental rate of a residence

Customer Satisfaction on Digital Marketing

Customer Satisfaction on Digital Marketing

Hedonic analysis of attributes and factors affecting small ruminant price in Benin, West Africa

The demand for small ruminants is increasing, but livestock production is not very market oriented. Understanding buyers' preferences allows breeders to orient their production and make more profit. This research aimed to determine the attributes of small ruminants and other specific factors that explain price variations of small ruminants in ordinary period. Twenty-one markets were selected using stratified sampling. Data were collected in these markets on September 2020 from 432 small ruminant transactions between sellers and buyers and analysed with the hedonic regression model. Results showed that the price of goats purchased for slaughter and breeding were respectively 9.4 % and 7.2 % higher than those bought for trade. At the same time, when sheep were purchased for breeding, consumption and catering, their prices were respectively 14.5 %, 10.3 % and 9.4 % higher than those purchased for trade. The attributes weight, age (2–4 years old), sex (female), coat colour (white), body condition (good), breed (sahelian breeds for sheep and djallonke breed for goats) and absence of horn determined significantly and positively the small ruminant's price. In addition to these attributes, the small ruminant prices varied according to type of market and seller, but the buyer had less control over these factors. Thus, it is important to improve attributes preferred by buyers through training for breeders on the control of small ruminant reproduction. These attributes should also be considered when developing strategies to improve the small ruminant sector to transform traditional livestock farming into market-oriented livestock farming. Facilitating access to information through the establishment of functional market information systems will enable breeders to move towards market-oriented livestock systems.

The Gut Feeling of Rational Acting: Differentiation in Cognitive Strategies Within Commercial and Recreational Sellers in Hybrid Digital Social Media Markets

In the realm of cybercrime, technologies that facilitate illicit activities also produce uncertainties based on the hybridity between digital communication and offline presence. Social media platforms have blurred the lines between types of drug sellers, bringing the recreational and the commercial into the same marketplace. In the Nordic data used in this paper, 52 text-based qualitative interviews with recreational and commercial sellers are analyzed via process and variance analysis to identify the relationship between cognitive strategies and seller positions. We ask how sellers’ decision-making processes differ and intersect. Theoretically, we use cognitive sociology to enrich understanding of culture, trust, and rational decision-making in this context. Our findings reveal that recreational sellers often adopt a low-risk, low-gain strategy rooted in cognitive biases, reflecting the recreational nature of their engagement. In contrast, commercially competent sellers employ more complex cognitive strategies, including gut feelings, thus adjusting their decisions with less reliance on initial assessments, leading to a more calculated approach with higher risk tolerance. We conclude with a discussion of intervention strategies; here, we argue for the need for a dual strategy that targets and capitalizes on the differences in cognitive biases in an effective way that poses less harm to recreational sellers.

The effectiveness of certification services on e-commerce platforms considering network externalities

The fees of different certification services are charged in different ways: For example, T-mall.com (one of the leading e-commerce platforms in China) uses a total certification service, where each type of seller participating in the platform must purchase certification services; Pinduoduo.com (another Chinese e-commerce platform) uses an alternative certification service, where after paying a transaction fee, each seller participating in the platform can choose whether to purchase certification services. This paper studies how the choice of certification services affects the participation decisions of both sellers and buyers, as well as the revenue and quality level (the proportion of high-quality sellers of all participating sellers) of a platform. According to previous research, network externalities also affect sellers’ and buyers’ participation strategies. Studies on the effectiveness of different certification services for e-commerce platforms have rarely considered both positive and negative network externalities. The results of constructed game-theoretic models show that both the certification capability and the certification cost play critical roles in determining which certification services can generate more revenue. If a platform provides certification services, the total certification service always generates a higher quality level than the alternative certification service. Furthermore, the applicable scope of certification services (defined as the certification strategy space), can be broadened by increasing both the profit ratio (the ratio between the profit of H-type sellers and L-type sellers) and the value ratio (the ratio between the value of H-type sellers and L-type sellers). Counterintuitively, a higher certification capability does not always yield a higher certification fee.

Exploring buyer’s preferences to propose strategies to improve dog welfare in Brazil

ABSTRACT This study aimed to investigate trends and concerns related to the commercialization of dogs in Brazil. The authors analyzed 1,500 ads for the sale of Miniature Schnauzer, Chihuahua, and German Spitz breeds using the methodology of hedonic price analysis. Marginal and relative values of attributes were calculated for puppy sex, coat, age, pedigree, vaccination and deworming, seller type and region, using ordinary least squares. The most valued attributes for each breed were identified as selling by kennels, pedigree, and coat color. The results suggest that this market niche is willing to pay for guarantees of better dog breeding, which represents an opportunity for the development of certification labels for origin and good practices for kennels. Such labels could become an effective strategy to ensure greater transparency and better welfare standards in the Brazilian dog market. This study also provides valuable insights for the development of guidelines and public policies aimed at improving animal welfare and reducing information asymmetry in the pet market.

Research on the Influence of Sellers’ Responses on Brand Avoidance of Potential Consumers

In recent years, the development of online platforms has significantly expanded the dissemination of online reviews at an astonishing speed. The undeniable impact it has on consumers and sales necessitates addressing the issue of reducing brand avoidance behavior caused by negative reviews, which remains a prominent concern among academics and sellers. To enhance communication between sellers and consumers while minimizing misunderstandings, numerous platforms have introduced the sellers' responses function. With various types of sellers' responses available, different response strategies yield distinct effects. This paper aims to investigate how diverse seller replies influence potential consumers' brand avoidance by examining their classification and impact in conjunction with previous literature on factors influencing brand avoidance.

Withholding and damage in Bayesian trade mechanisms

We study the optimality of allowing the designer to withhold or damage resources in Bayesian incentive compatible mechanisms for bilateral trade with independent private values. The following results hold when the buyer and the seller have discrete value distributions. Burning money or withholding the good from both traders never enhances welfare. Similarly, damaging the good for the buyer cannot increase welfare. By contrast, damaging the good for the seller may improve welfare. However, such welfare improvements are possible only if the damage hurts some lower valuation type of seller more severely than the highest valuation type. Results extend to the case of continuous value distributions under certain hypotheses regarding virtual values. Methods also apply to optimal Bayesian implementation for allocation problems. In the absence of property rights, damaging goods for any agent has negative welfare consequences.

Marketplace Scalability and Strategic Use of Platform Investment

The scalability of a marketplace depends on the operations of the marketplace platform and its sellers’ capacities. In this study, we explore one strategy that a marketplace platform can use to enhance its scalability: providing an ancillary service to sellers. In our model, a platform can choose whether and when to provide this service to sellers and, if so, what prices to charge and which types of sellers to serve. Although such a service helps small sellers, we highlight that the provision of such a service can diminish the incentives of large sellers to make their own investment, thereby reducing their potential output. When the output reduction by large sellers is substantial, the platform may not want to provide the ancillary service, and, even if it does, it may choose to set a price higher than its marginal cost to motivate large sellers to scale. The platform may also choose to strategically delay the provision of the service.This paper was accepted by Hemant Bhargava, information systems.Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2022.4522 .

Properties of Malicious Social Bots

The paper considers the ability to describe malicious bots using their characteristics, which can be the basis for building models for recognising bot parameters and qualitatively analysing attack characteristics in social networks. The following metrics are proposed using the characteristics of VKontakte social network bots as an example: trust, survivability, price, seller type, speed, and expert quality. To extract these metrics, an approach is proposed that is based on the methods of test purchases and the Turing test. The main advantage of this approach is that it proposes to extract features from the data obtained experimentally, thereby obtaining a more reasonable estimation than the expert approach. Also, an experiment on extracting metrics from malicious bots of the VKontakte social network using the proposed approach is described, and an analysis of the metrics' dependence is carried out. The experiment demonstrates the possibility of metrics extracting and analysis. In general, the proposed metrics and the approach to their extraction can become the basis for the transition from binary attack detection in social networks to a qualitative description of the attacker and his capabilities, as well as an analysis of the evolution of bots.

PREDICTION OF CAR RESELLING PRICES USING MACHINE LEARNING

It is generally known that, taking wise and challenging decisions is really a crucial task in every business. To propose a novel solution for this challenge, this research work majorly focuses on one of the retail businesses i.e., used car sales business. The proposed research work shows that, the predictive analytical models will be a great add- on to business mainly for assisting the decision making process. The major objective of our paper is to build a prediction model i.e., a fair price mechanism to predict the cars selling price based on their features like the car model, the number of years that a car is old, the type of fuel it uses, the type of seller, the type of transmission and the number of kilometers that the car has driven so far. This paper will help to get an approximation about selling price of a used car based on its features and reduces the seller and consumer risk in business. The proposed model utilizes the machine learning algorithms and regression techniques of statistics like linear, decision tree and random forest regressions to achieve this task. KEYWORDS Used car sales business, decision making process, machine learning algorithms, regression techniques, linear, decision tree and random forest regressions.

Changing Market Structure and Evolving Ways to Compete: Evidence from Retail Gasoline

This paper examines the pricing behavior of sellers in a market undergoing a significant restructuring, using data from the ongoing introduction of self-service technology in the Korean gasoline market in the 2000s. I provide evidence that full-service premium increased during the market transition. I further show that a monopolistic competition model is not enough to explain the increasing premium.The pricing behavior of sellers differs by product position: self-service sellers compete for price-sensitive consumers, whereas full-service sellers differentiate their product by offering a variety of bundled products and services, such as coffee, carwash or even nail salons, to compete for less-price-sensitive consumers.Taken together, the strategic choices of sellers evolve in different ways when the market structure changes, with each type of seller using its unique position, resulting in an increase in full-service premium during the market transition from full-service to self-service.

Auction-Promoted Trading for Multiple Federated Learning Services in UAV-Aided Networks

Federated learning (FL) represents a promising distributed machine learning paradigm that allows smart devices to collaboratively train a shared model via providing local data sets. However, problems considering multiple co-existing FL services and different types of service providers are rarely studied. In this paper, we investigate a multiple FL service trading problem in Unmanned Aerial Vehicle (UAV)-aided networks, where FL service demanders (FLSDs) aim to purchase various data sets from feasible clients (smart devices, e.g., smartphones, smart vehicles), and model aggregation services from UAVs, to fulfill their requirements. An auction-based trading market is established to facilitate the trading among three parties, i.e., FLSDs acting as buyers, distributed located client groups acting as data-sellers, and UAVs acting as UAV-sellers. The proposed auction is formalized as a 0-1 integer programming problem, aiming to maximize the overall buyers’ revenue via investigating winner determination and payment rule design. Specifically, since two seller types (data-sellers and UAV-sellers) are considered, an interesting idea integrating <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">seller pair</i> and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">joint bid</i> is introduced, which turns diverse sellers into virtual seller pairs. Vickrey-Clarke-Groves (VCG)-based, and one-sided matching-based mechanisms are proposed, respectively, where the former achieves the optimal solutions, which, however, is computationally intractable. While the latter can obtain suboptimal solutions that approach to the optimal ones, with low computational complexity, especially upon considering a large number of participants. Significant properties such as truthfulness and individual rationality are comprehensively analyzed for both mechanisms. Extensive experimental results verify the properties and demonstrate that our proposed mechanisms outperform representative methods significantly.

Representations and warranties insurance in mergers and acquisitions

To mitigate information asymmetry in acquisitions, the seller makes contractual representations and warranties (referred to as “R&W” or “reps”) about the state of the target, such as attesting to the accuracy of the target’s financial statements. While seller indemnities allow buyers to impose costs due to breaches in the reps discovered after the deal’s close, these indemnities involve significant contracting costs. To mitigate these costs, the acquisition parties have increasingly turned to purchasing representations and warranties insurance. Using a proprietary and novel sample of R&W insurance policies issued worldwide for acquisitions of non-public targets, we find that the demand for R&W insurance, the premium charged for it, and the likelihood of a claim being filed are correlated with industry metrics for valuation uncertainty, the type of acquirer and seller, and the target’s legal regime. In particular, we find higher demand for R&W insurance and a higher R&W insurance premium charged when the target belongs to an industry with weaker internal controls. We also find that a higher premium is charged when the target is in an industry with relatively high levels of R&D to sales, indicating that the insurance company expects unrecognized intangible assets to have a greater risk of future claims. Our study adds to our understanding of how parties reduce target valuation uncertainty and the role of disclosures and R&W insurance policies in private mergers and acquisitions transactions.

Beyond grain: the potential of cowpea in local markets of Mali

PurposeThe authors assess the development potential of cowpea beyond grain in local markets in Mali by: (1) identifying trader types and types of cowpea products sold; (2) examining trader roles; (3) estimating gross margins and their determinants; and (4) discussing policy opportunities to further develop the value chain.Design/methodology/approachThe authors analyze data collected through observation and semi-structured questionnaires from 487 sellers in 26 markets, including market, seller, and product characteristics. The authors also calculate gross margins and conduct a regression analysis to identify influential factors.FindingsThe authors identify several types of cowpea sellers in local markets, including processor-retailers, retailers of fresh leaves and fodder, and grain retailers, collectors and wholesalers. Women dominate the marketing of processed products and fresh leaves. The marketing of boiled cowpeas offers retailers higher margin rates compared to fritters and pancakes. Grain sellers, who are mostly men, have lower margins but sell larger quantities. Processor-retailers bring more value to the cowpea value chain. Specialization of the seller in cowpea, regional location of the market and day of the market fair all influence gross margins.Research limitations/implicationsFuture work should explore consumer preferences for different types of cowpea products.Originality/valueThis study of the cowpea value chain in Mali has revealed the multidimensional character of the cowpea plant, which goes far beyond its grain and highlight the important roles played by women.

Quality of information offered to women by drug sellers providing medical abortion in Nigeria: Evidence from providers and their clients.

BackgroundEvidence confirmed that the demand for medical abortion (MA) increased significantly during the COVID-19 outbreak in many developing countries including Nigeria. In an abortion-restrictive setting like Nigeria, local pharmacies, and proprietary patent medicine vendors (PPMVs) continue to play a major role in the provision of MA including misoprostol. There is the need to understand these providers' knowledge about the use of misoprostol for abortion and the quality of information they provide to their clients. This analysis is focused on assessing the quality of care provided by both drug seller types, from drug sellers' and women's perspectives.MethodologyThis study utilized primary data collected from drug sellers (pharmacists and PPMVs) and women across 6 Local Government Areas in Lagos State, Nigeria. The core sample included 126 drug sellers who had sold abortion-inducing drugs and 386 women who procured abortion-inducing drugs from the drug sellers during the time of the study. We calculate quality-of-care indices for the care women received from drug sellers, drawing on WHO guidelines for medication abortion provision. The index based on information from the sellers had two domains—technical competency and information provided to clients, while the index from the women's perspectives includes an additional domain, client experience.ResultsResults show that the majority of drug sellers in the sample, 56% (n = 70), were pharmacists. However, far more than half of women 60% (n = 233) had visited PPMVs. Overall, the total quality score amongst all drug sellers (mean 0.48, SD0.15) was higher than the total score calculated based on women's responses (mean 0.39, SD 0.21). Using our quality-of-care index, pharmacies and PPMVs seem to have similar technical competency (mean score of 0.23, SD 0.13 in both groups (range 0–1), whilst PPMV's performed better on the information provided to client domain (mean score of 0.79, SD 0.17 compared with pharmacies 0.69, SD 0.25). Based on women's reports, PPMVs scored better on both quality of care domains (technical competency and information provided to clients) compared with pharmacies.Program/Policy ImplicationIn resource-constrained settings such as Nigeria, particularly in the context of health emergencies like COVID-19, there is the need to continue to strengthen and engage PPMVs' capacity and skills in dispensing and administration of MA drugs as a harm reduction strategy. Also, there is the need to target frontline providers in pharmacies for training and skill upscale in MA provision.

STUDY OF GOAT MARKET PRICE IN AFAR REGION DUBTI MARKET ETHIOPIA

The study's main goal is to look at the factors that influence goat market prices in the Dubti market in Ethiopia's Afar region. The study tried to determine the impact of market features (such as transaction time, buyer and seller type) on goat market price in the study site. The corrected R-square value indicates that the explanatory factors in the model explain 77 % in goat price per head. The current observation revealed that animal traits (bodily condition, age, and weight) as well as market features (seller type) had a significant impact on goat market price fluctuation in the studied area. The regression analysis of the price per kg of live weight model indicated that live weight of animals was significant in all sample markets at a 1% percent confidence level. Goat body condition has a considerable impact on goat price variation over the full sample markets. Goat prices are also affected by market features such as the type of sellers, the buyer's objective, and the time of transaction on a market day. Providing facilities such as weighting scales, services such as consistent marketing material, and using a regulated grading system might help to avoid subjective pricing.