Online Price Research Articles

Investigating the Factors Influencing Online Purchase Intention: An Empirical Study

Online shopping has grown in popularity recently all around the world, and many companies havemoved their emphasis to e-commerce. However, the willingness of customers to make onlinepurchases is a key factor in the success of online businesses. Thus, in order for businesses to createefficient online marketing strategies and boost their online sales, it is imperative that they have athorough understanding of the factors that affect consumers' intention to make an online purchase.Consumers' intentions to make online purchases are influenced by a number of things in themarketing industry. These variables include social impact, website quality, product information,perceived value, and trust.To closely examine these elements and examine how important they arein affecting consumers' intention to make an online purchase. By being aware of these aspects,businesses will be better able to decide how to improve their online presence and draw in moreonline customers, which will ultimately result in more sales and long-term success.Businesses cancustomize their online marketing efforts to match consumers' wants and expectations by studyingthe variables that affect consumers' intention to make an online purchase. The researcher hadconsidered 207 online customers to Investigate the Factors that influence online purchase intentionand found that Consumers' purchase intentions are significantly shaped by the convenience, welldesigned websites offering wide selection of items, recommendations and evaluations fromfriends, family, and online groups quality and price, degree of store loyalty Brand reputationcustomer’s age, gender, and income.

Consumers’ free riding: Pricing and retailer service decisions in a closed-loop supply chain

Increased awareness of environmental and social responsibility has prompted many manufacturers to adopt product recycling programs. In addition, with the development of the internet and e-commerce, the supply chain structure has changed from a single physical store to a mode in which online and offline outlets coexist. At the same time, consumers usually obtain a product’s information in a physical store before purchasing it online, which is recognized as free-riding behavior. In this paper, we apply a Stackelberg game to explore the joint effects of free-riding and the reverse revenue-sharing ratio on pricing strategies and offline retailer service decisions. We show that the reverse revenue-sharing ratio impacts the online and offline prices under different decision-making models in quite opposite ways; that is, the ratio positively (negatively) impacts the online and offline prices in centralized (decentralized) decision-making modes. In contrast, the free-riding rate has the same impacts on online and offline price decisions in different decision modes. More specifically, the free-riding rate has a positive (negative) impact on the online (offline) price in both modes. In addition, we show that the reverse revenue ratio has the same impact on the retail service investment decision under different decision models; that is, the retailer service is positively correlated with the reverse revenue ratio. However, when the free-riding rate is greater than 0.5, the relationship between retail service and the free-riding rate under the centralized model is positively correlated; in other cases, the relationship between the two is negatively correlated under different decision models. We also show that the adjustment space of the price strategy (retail service investment) will be influenced by the combination of the reverse revenue-sharing ratio and consumer free-riding behavior.

The Influence of Online Promotion, Service Quality, and Price on The Sustainability of Culinary Msmes In Parepare City After The Covid-19 Pandemic In The Perspective of Maslahah

Abstract
 The purpose of this study is to determine the effect of online promotion, service quality, and price on the sustainability of culinary MSMEs in the city of Parepare after the COVID-19 pandemic in the perspective of the community. This type of research is a mixed method. The approach used is a descriptive and associative approach. The research was conducted in Parepare City to MSME actors. Data collection techniques and instruments were carried out through the distribution of questionnaires to 50 samples. The methods used to test the hypothesis are by using pearson product moment correlation analysis techniques, multiple linear regression, f test, coefficient of determination (R2) and interview. The results showed; 1) Online promotion (X1) is very good, evidenced by respondents' answer scores of 88% in the category of 84.01% - 100% with a very good classification. 2) Service quality (X2) is good, evidenced by respondents' answer scores of 83% in the category of 68.01% - 84.00% with a good classification. 3) The price adjustment (X3) is very good, evidenced by the respondent's answer score of 85% in the category of 84.01% - 100% with a very good classification. 4) Sustainability (Y) is very good, evidenced by respondents' answer scores of 85% in the category of 84.01% - 100% with a very good classification. 5) There is no relationship between online promotion (X1) and weak significance to the sustainability variable (Y), evidenced by significance values of 0.088 > 0.05, so there is no correlation. 6) There is no relationship between service quality (X2) and weak significance to the sustainability variable (Y), evidenced by a significance value of 0.122 > 0.05, so there is no correlation. 7) There is no relationship between price (X3) and weak significance to the variable sustainability (Y) as evidenced by a significance value of 0.129> 0.05. 8) Online promotion (X1), service quality (X2), and pricing (X3) have no partial effect on sustainability (Y), as evidenced by their respective significance values of 0.140, 0.229, 0.211 > 0.05, concluded to have no effect. 9) Online promotion (X1), service quality (X2), and price (X3) simultaneously have no significant effect on sustainability (Y), evidenced by a sig of 0.097> 0.05 or a calculated F value of 2.234 < Ftable 2.81 is concluded to have no effect. (10) The most dominant variable for sustainability (Y) is online promotion (X1) with an unstandardized coefficients value of 0.244.( 11) MSME actors in Parepare City maintain the sustainability of their business by implementing good strategies in accordance with the principles of Hajiyyah benefit.

How pop-ups drive online sales: moderating effects of online promotions

PurposeThis study aims to examine how the effect of pop-ups on an omnichannel brand’s subsequent online sales is moderated by the brand’s online price and premium promotions, paid search and popularity signaling.Design/methodology/approachUsing a difference-in-differences approach, this study appraises variations in two similar Chinese apparel brands’ online sales before and after one of the brands’ implementations of its pop-ups and how the brand’s online promotions modify the pop-ups’ effect.FindingsUnique, interactive pop-ups boost brands’ subsequent online sales. Online price promotions negatively moderate the effect; online premium promotions and paid search positively moderate it. Moreover, the product’s popularity diminishes the extent to which a pop-up stimulates online demand. These findings can be partially generalized to other categories, such as utilitarian products.Practical implicationsOnly certain online strategies enhance the effect of pop-ups on brands’ online sales, so practitioners should strategically select appropriate promotion combinations when they operate pop-ups and allocate resources across channels. In addition, the moderating influence of online promotions on pop-ups depends on the type of product being promoted.Originality/valuePop-ups offer proven abilities to deliver sensory experiences to online shoppers, reinforce brand awareness and loyalty and boost online sales. This study extends prior research by examining how various online promotions moderate pop-ups’ effects.

Analysis of the Influence of Online Promotion, Product Packaging and Price on Purchasing Decisions with Price as a Moderating Variable

This study aims to find out how online promotions, product packaging and prices affect purchasing decisions for culinary products "Cau Nugget" and to determine the effect of price moderation on online promotions in determining purchasing decisions. This study used a quantitative method involving consumer Instagram followers 'Cau Nugget' as a population and a sample of 121 respondents. The results of the study found that, of the three existing factors, online promotions did not have a significant influence on purchasing decisions. Meanwhile, product packaging and price have a significant effect on purchasing decisions. This study proves that price negatively moderates online promotions on purchasing decisions, as well as being the indicator that has the highest impact on purchasing decisions.
 Keywords: Online Promotion; Product Packaging; Price; Buying Decision; Home Industry

Stock Price Forecast based on ARIMA Model-Taking Yowant Technology and New Oriental Online as Examples

With the growth in the personal standard of living, public play is also undergoing tremendous changes. Increasingly people begin to take note of and participate in share market investment. Shares have high returns, but also high risks. Many factors limit the share market and unpredictable prices. The share price forecast is of great significance. So, since the birth of the share market, stock price prediction has been a hard nut for shareholders and researchers to probe. This paper selects the closing prices of Shenzhen A-share Yowant Technology and Hong Kong stock New Oriental Online as the time series empirical analysis data forecasts the change price trend of these two stocks in the next 30 days by establishing the ARIMA model, and analyzes which stock will rise more. The empirical results show that the imitative effect of the model is well, and the conclusion is that Hong Kong shares of New Oriental Online will increase significantly in the future, which can supply utility assistance for enterprises and investors enterprises to make corresponding decisions.

Mechanism design for Mobility-as-a-Service platform considering travelers’ strategic behavior and multidimensional requirements

Mobility-as-a-Service (MaaS) is an emerging transport model which provides access to a combination of travel modes through a single platform. A MaaS operator sits between travelers and transport service providers (TSPs), acting as a broker who purchases mobility resources from individual TSPs, constructs seamless transport services, and then sells them to travelers in response to their demand. To ensure the sustainability of such platforms, the key challenge lies in matching travelers to TSPs so that travelers’ individual needs are satisfied, TSPs gain nonnegative profits and system efficiency is achieved. To solve this matching and pricing problem, travelers’ truthful valuations and travel requirements are needed, while such information is usually unknown to operators beforehand. In this study, we develop an auction-based online mobility resource allocation and pricing mechanism to solve this problem, taking into account travelers’ strategic behavior. We first propose an offline (static) mechanism using a Vickrey–Clarke–Groves (VCG) based pricing scheme to ensure incentive compatibility, individual rationality, and system efficiency. We then develop an online mechanism based on the dynamic learning algorithm to obtain the near-optimal solution and compare it to a customized greedy based algorithm. We compare both online mechanisms to the offline VCG based mechanism and theoretically prove the competitive ratios. The efficiency and performance of the proposed mechanisms are demonstrated through a numerical study.

Effects of online shopping channel and price discount on near-expiry food sales

Consumers have an aversion to purchasing near-expiry food products, which leads to enormous food waste and economic loss. Given the importance of this issue, past research has studied the effect of impending expiration date on product sales, but its focus has been limited to perishable food products. Since the expiration dates of non-perishable food products are treated as less important than those of perishable food products, we expect that the resulting effect on sales largely varies by shopping environment. With the growing importance of online shopping in food sales, we examine how the effect of impending expiration date differs between mobile and PC shopping environments. By analyzing a unique data set from an online salvage store, we find that consumer aversion toward near-expiry products is more salient in the PC shopping environment than in the mobile shopping environment. However, when there is a deeper price promotion, the between-channel difference is reduced as the sensitivity of an impending expiration date on sales increases in the mobile shopping environment. These findings not only represent novel contributions to the literature but also provide managerial implications for practitioners.

Online food prices and shocks to product availability since Covid-19

ABSTRACT Using web-scraping, we have gathered daily data on prices and product availability for over 50,000 unique food items from 7 major retailers in Poland since January 2020. We find a 24% drop in product availability during the first COVID-19 wave in April 2020. Next, with two-step and iterative GMM applied to a variety of specifications, we show a modest price response to stockouts, as a 10% decline in food product availability leads to an immediate 0.5% rise in prices throughout the first COVID-19 wave. During the subsequent pandemic waves, this link disappears. We also detect only a 4% drop in product availability following the onset of the Russian invasion of Ukraine in February 2022, thus we suspect that the recent price movements are linked primarily to cost and demand factors. Our evidence is indicative of retailers fearing consumer anger during unorthodox times.

An investigation of the nexus between online impulsive buying and cognitive dissonance among Gen Z shoppers: Are female shoppers different?

PurposeThough online impulsive buying emerged mostly in Western cultures, it has been widely expanded as a key pattern among online customers in emerging markets. Interestingly, while few studies suggest that engaging in unplanned purchase actions (i.e. impulsive buying) is not always associated with negative emotions among customers (i.e. postpurchase cognitive dissonance), others suggest that impulsive buying is directly associated with cognitive dissonance. This paper aims to investigate and understand the key antecedents of online impulsive buying among Moroccan Gen Z consumers, and how it contributes to postpurchase dissonance. The authors also try to gain deeper insights by investigating the disparities between males and females using mutigroup analysis.Design/methodology/approachBased on data collected from 333 Moroccan Gen Zers, the hypothesized model was empirically tested using a partial least squares estimation.FindingsFirst, the results confirm that impulsive buying is positively associated with postpurchase dissonance. Second, while hedonic shopping motivation, fear of missing out and materialism were found to significantly impact online impulsive buying, price value and online reviews had no significant effect on online impulsive purchases. The importance–performance matrix also suggests that the fear of missing out is the most important factor leading to online impulsive buying, followed by hedonic shopping motivation and materialism. Finally, the results confirm that female shoppers are more likely to engage in impulsive buying behavior, and this was mainly due to higher fear of missing out, hedonic shopping motivation and materialism.Practical implicationsFirst, the study findings can help online merchants to construct well-designed online shopping platforms and effective e-marketing tactics to stimulate purchase intentions among Gen Z shoppers. Online merchants should also attempt to reduce the negative feelings associated with unplanned buying behavior by introducing additional incentives, effective consumer interactivity and flexible return policies. This would help online suppliers in retaining customers and transforming impulse purchases into more recurrent ones. Second, online retailers should take into consideration the differences between male and female consumers by appealing to the role of gender in purchase situations when marketing their products and services. Finally, the findings offer interesting implications to society by allowing online shoppers to make well-informed purchase decisions without being influenced by personal and products’ traits.Originality/valueWhile prior research assessed the investigated constructs in separate models, the study suggests an integrated framework that incorporates different determinants of online impulsive shopping as well as its impact on postpurchase cognitive dissonance. Additionally, the authors explored the moderating effect of gender to gain deeper insights with regard to the disparities between males and females while engaging in online impulsive buying. To the best of the authors’ knowledge, this study is the first of its kind to investigate the antecedents of online impulsive buying among Gen Z consumers in Arab countries and Africa.

DIVINE: A pricing mechanism for outsourcing data classification service in data market

Although data mining plays an essential role in enhancing business decision-making, currently, there are hardly any suitable online platforms available that can facilitate outsourcing data classification services in data markets. This paper presents an efficient and flexible online service platform architecture for data classification and delves into an in-depth study on pricing design to maximize revenue. To construct this online service platform, we address three significant challenges. Firstly, we focus on efficiently modeling accurate classifiers while minimizing consumption. Secondly, we design a flexible pricing mechanism with multiple levels. Lastly, we maximize online revenue based on incomplete information. Through comprehensive consideration of these three challenges, this paper proposes a query-based Data classIfication serVice with onlIne priciNg mEchanism, named DIVINE, which determines the transaction price of data classification services by learning buyers' valuations online. The theoretical analysis of this paper illustrates that DIVINE can ensure a constant (1+ϵ) competitive ratio compared to the maximal offline revenue with complete information. Finally, DIVINE is evaluated on UCI databases. The experimental results show that it not only exhibits low consumption, multiple levels, and two kinds of robustness but also outperforms existing state-of-the-art pricing mechanisms in terms of revenue, which can achieve about 90% of the optimal offline revenue and validates the theoretical analysis.

Pandemic pricing: Evidence from German grocery e‐commerce

AbstractThe sudden demand spike for online grocery purchases during the Covid‐19 pandemic and supply bottlenecks caused by disrupted global value chains put immense pressure on prices. We analyze the prices of the largest German online grocers to test how these challenges affected prices during the first wave of the pandemic. Using a large dataset of online price quotes, we shed light on the magnitude of price changes across retailer types, product categories, and stages of the pandemic. We show that online prices went up as the intensity of Covid‐19 containment measures increased. The magnitude of price increases was heterogeneous across retailers and product categories: pure online retailers showed a lower price response compared to hybrid stores, while the prices of essential food items such as baby foods and pantry products increased more than those of other product categories or beverages. [EconLit Citations: E31, Q31].

Measuring Policy Performance in Online Pricing with Offline Data: Worst-case Perspective and Bayesian Perspective

Measuring Policy Performance in Online Pricing with Offline Data: Worst-case Perspective and Bayesian Perspective

The Influence of Online Customer Reviews, Prices, and Sales Promotions on Buying Interests in the Tokopedia Marketplace

In early 2020, Indonesia was affected by the COVID-19 Pandemic; this increased the habits of Indonesian people shopping online through marketplaces such as Tokopedia, Shopee, Lazada and so on. Marketplaces are competing to provide attractive offers during the Pandemic. The value of shopping transactions at Shopee is 40%, Tokopedia is 30%, and Lazada is 16%. It is known that Shopee is the most popular marketplace for Indonesians at the peak of Harbolnas 2021 compared to Tokopedia. This study aims to determine the effect of online customer reviews, prices and sales promotions on purchase intention at Tokopedia. The population of this research is Tokopedia users in Indonesia, with a total sample of 174 respondents. The method used is quantitative, and the data is processed using SmartPLS 3.2.9 software. The results of this study indicate that the OCR variable, price and sales promotion have a positive effect on purchase intention. The independent variable that has the most dominant influence on the dependent variable of purchase intention is the online customer review factor.

Building heritage brand equity through social media sales promotion: The role of Power Distance

AbstractThis paper aims to look into the moderating effect of individual's cultural characteristics—Power Distance—on the relationship between the use of discounts and gifts and the formation of the brand equity of a heritage tourist site is assessed. The results of a quasi‐experimental 2×2 factorial design among Internet users from two countries and using two different promotional stimuli showed: a positive effect of sales promotions on social media on the formation of brand equity of a heritage tourist site; a lesser effect of online price discounts than free gifts; the moderating role of Power Distance on the formation of brand equity.

The roles of cooperative advertising and endogenous online price discount in a dual-channel supply chain

Cooperative advertising and product price discount are important roles of influencing manufacturer and (online) retailer decisions in supply chains. This paper develops a model to explicitly explore the impacts of practical online price discount and different cooperative advertising modes on a dual-channel supply chain consisting of a manufacturer and an e-platform. The manufacturer can sell a product to end consumers through an offline channel and an online channel; the latter is implemented by the e-platform which charges a commission fee under an agency selling arrangement. Our results show that offering a price discount in the online channel may be not better for the manufacturer, which can be determined by a threshold policy in terms of the effect of the online price discount on the online market demand. Further, the optimal price discount level offered will remains at a relatively low level. We also show that the online price discount level is always the lowest under bilateral cooperative advertising setting, but might be the highest under unilateral cooperative advertising setting. By comparison with unilateral cooperative advertising, the increase in the manufacturer’s profit under bilateral cooperative advertising is obtained by reducing the e-platform’s profit. Such a “benefit-oneself-at-the-expense-of-others” method may be harmful to the total profit of the overall supply chain, which may evidently explain why bilateral cooperative advertising is rarely used in practice.

The Impact of Online Review and Price on Consumer’s Hotel Booking Intention at Online Travel Agency: Trust as a Mediating Variable

The Impact of Online Review and Price on Consumer’s Hotel Booking Intention at Online Travel Agency: Trust as a Mediating Variable

Assortments and prices in online grocery retailing

Grocery retailing is undergoing rapid changes. New store formats and market channels, the entry of additional large players, and increasing multichannel activities on the supply side are accompanied by heterogeneous and changing consumer preferences. Retailers are increasingly competing in both price and variety. The question arises: how do product assortments affect retailers' prices? Larger assortments may be attractive for consumers who derive utility from variety or search for niche products. Retailers with a deeper assortment might be in a position to realize higher prices. Our study is the first to quantify the assortment-depth elasticity of price in online retailing, and the magnitude of assortment depth at which a further expansion of the assortment may no longer allow for a higher average price level. We collect a unique dataset for major online full-assortment grocery retailers in Germany and show that an increasing depth of grocery assortment raises online prices. The depth elasticity of price is below unity, and the influence is nonlinear.

Online Pricing Incentive to Sample Fresh Information

Today mobile users such as drivers are invited by content providers (e.g., Tripadvisor) to sample fresh information of diverse paths to control the age of information (AoI). However, selfish drivers prefer to travel through the shortest path instead of the others with extra costs in time and gas. To motivate drivers to route and sample diverse paths, this paper is the first to propose online pricing for a provider to economically reward drivers for diverse routing and control the actual AoI dynamics over time and spatial path domains. This online pricing optimization problem should be solved without knowing drivers' costs and even arrivals, and is intractable due to the curse of dimensionality in both time and space. If there is only one non-shortest path, we leverage the Markov decision process (MDP) techniques to analyze the problem. Accordingly, we design a linear-time algorithm for returning optimal online pricing, where a higher pricing reward is needed for a larger AoI. If there are a number of non-shortest paths, we prove that pricing one path at a time is optimal, yet it is not optimal to choose the path with the largest current AoI. Then we propose a new backward-clustered computation method and develop an approximation algorithm to alternate different paths to price over time. Perhaps surprisingly, our analysis of approximation ratio suggests that our algorithm's performance approaches closer to optimum given more paths.

Online Pricing with Polluted Offline Data

Online Pricing with Polluted Offline Data