The Economics of Digitization

We examine the effect of COVID-19 epidemic and the subsequent stay-at-home order on market efficiency in China’s online markets. Through a comparison of price dispersion changes across online retail platforms around the lockdown date with the corresponding period in the 2019 lunar year—with the use of a unique and extensive online retail price dataset—we find a counterintuitive decrease in product price dispersion during the epidemic, which is contrary to conventional economic expectations during adverse events. Our study differentiates products by crisis-time demand elasticity—e.g., food versus clothing—and by online search intensity. This reveals that the lockdown and prolonged stay-at-home period facilitated online searches by consumers, which reduced information costs and enhanced market efficiency. The pandemic-induced decrease in price dispersion can be largely attributed to heightened online search activity: after we adjust for the intensity of search, the remaining pandemic effect on price dispersion becomes positive. China’s resilient online market acted as a protective buffer during the COVID-19 crisis. The transition from offline to online markets and increased search activities bolstered online market functionality and mitigated the epidemic’s repercussions.

Quality-Adjusted Consumer Surplus: Measurement, Effects, and Determinants in Online Markets

We investigate pricing behaviour and market dynamics for both online branches of Multi-Channel Retailers (MCRs) and online-only retailers (Dotcoms), based on a set of panel data collected for 2 years in the online DVD market. We find that prices of MCRs and Dotcoms both go down with time, but prices of MCRs decrease in a significantly faster speed, implying that difference in the average prices between the two types of retailers is getting smaller with time. We also compare the price dispersion and its dynamics between MCRs and Dotcoms. We find that the price dispersion among MCRs is much bigger than that among Dotcoms at the beginning. But such a difference gets smaller with time as the price dispersion among Dotcoms becomes bigger. Our results suggest that the two types of retailers will not only charge similar average prices in long term, but also have similar price dispersions. But our findings show that price dispersion among all retailers goes up with time, indicating that prices do not converge in the Internet market. Branding makes significant difference on both the price and the price dispersion.

Ample empirical studies in the e-commerce literature have documented that the price dispersion in online markets is 1) as large as that in offline markets, 2) persistent across time, and 3) only partially explained by observed eretailers’ attributes. Buying on the internet market is risky to consumers. First of all, consumers and the products they purchase are separated in time. There is a delay in time between the time consumers pay and the time they receive the orders. Second, consumers and the products they purchase are separated in space. Consumers cannot physically touch or examine the products at the point of purchase. As such, online markets involve an adoption process based on the interaction of consumers’ experiences in the form of references, recommendations, word of mouth, etc. The social network externalities introduced by the interaction of consumer’s experiences reduces the risk of seller choice and allows some sellers to charge higher prices for even homogeneous products. This research aims to study online market price dispersion from the social network externalities perspective. Our model posits that consumers are risk averse and assess the risk of having a satisfactory transaction from a seller based on the two dimensions of the seller’s social network externalities: quantity externality (i.e., the size of the seller’s social network) and quality externality (i.e., the satisfactory transaction probability of the seller’s social network). We further investigate the moderating effect of product value for consumers on the impact of social network externality on online market price dispersion. Our model yields several important propositions which we empirically test using data sets collected from eBay. We found that 1) both quantity externality and quality externality of social network are salient in driving online price dispersion, and 2) the salience of social network externality is stronger for purchase behavior in higher value product categories.

Why did conventional retailers with established brands hesitate to enter online markets for a substantial period of time? I model the entry decision of a conventional firm as a dilemma: a firm's early entry to the online market would increase that market's popularity and, as a result, shift the demand for the product from the conventional market to the online market. On the other hand, a firm's failure to enter the online market early will allow the competing online firm to increase its brand value due to the increase in demand for its online product. The results show that given the take-off probability - the probability that the popularity of the online market will increase - a conventional firm will delay its entry into the online market whenever brand effects are not substantial, to protect its profits in the monopolistic conventional market.

Driven by the rapid development of Internet technology, advertising communication channels and presentation forms have undergone profound transformations., However, the mechanism and effect of new advertising forms on commercial sales performance have not yet been fully demonstrated. This study explores the non-linear impact mechanism of advertising investment on sales through empirical analysis, focusing on the effect differences between traditional advertising and digital hybrid advertising and the law of diminishing marginal utility. Based on the e-commerce advertising and sales data(2019-2023) from Kaggle platform, a multiple linear regression model is constructed, and it is found that the total advertising investment is significantly positively correlated with sales and the marginal contribution of digital hybrid advertising is significantly higher than that of traditional advertising. However, the marginal decreasing effect of advertising input did not pass the significance test, possibly due to the fact that advertising input did not reach the saturation threshold in the data or the complexity of the nonlinear relationship. The study further reveals the impact of channel heterogeneity on advertising effectiveness and proposes a dynamic budget allocation strategy: prioritizing investment in digital advertising channels and reducing investment in inefficient traditional channels. Limitations include insufficient data timeliness, omitted variable bias, and endogeneity issues. Future research needs to expand the data dimensions, introduce machine learning models, and explore ad content quality and cross-channel synergies.

About Our Authors

PurposeThe purpose of this research is to take into consideration the country effect in online and offline environments and compares price levels and dispersion online v. offline across the two largest Continental European markets, thus adding a new dimension in price comparisons and multichannel pricing strategies.Design/methodology/approachBased on an empirical analysis of data collected in one product category (CDs), our findings for France and Germany show that price levels ‐including shipping costs – are always higher online than offline in each country and price dispersion is persistent across markets. Calculating mean prices for the two countries, ANOVA tests reveal significant differences among the two sets of data. Using standard deviation as the measurement for price dispersion, Levene statistics reveal a higher degree of online price dispersion than offline and statistically significant differences between the two sample countries.FindingsEven if our approach need to be extended to more product categories and more countries, our article may be interesting for practitioners, policy makers and managers. It clearly shows that the “frictionless capitalism and cost transparency hypothesis” has proven to be wrong most of the time even if many retailers still believe they must sacrifice the possibility of pricing up when they go on the internet. As demonstrated by our findings, retailers can take advantage of online relative indifference to price to capture some margin premium and enjoy excellent results.Originality/valueOur results also demonstrate that, even if results show some similarities and common trends, differences among France and Germany still remain important. As a consequence, marketers should continue to approach the European marketplace with full awareness of its diversity.

About Our Authors

The price dispersion means different prices for same goods. In the internet economy, many economists reckon that the price dispersion in the e-commerce markets should descend along with the dropping of search cost. However, the correlative studies reach a contrary opinion: there not only exist price dispersion in the e-commerce market, but also has larger dispersion degree than the traditional market, thereby gaining a ‘price paradox’ that is inconsistent with traditional economic principle. Based on the adverse selection perspective, this paper wants to provide another interpretation about the price dispersion in the e-commerce markets. Actual data from five online markets in China serves as a case study to help analyse the price dispersion. The results show the different kinds of markets have the different price dispersion that depends on the degree of adverse selection. Finally, the paper probes into resolving approaches eliminating and decreasing price dispersion in order to advance the business efficiency.

At the end of 2019, the sudden outbreak of the pandemic brought a significant impact on the sales of agricultural products in China and all over the world. To reduce the unmarketable problem caused by the pandemic in the agricultural industry, operators who used to focus on offline sales changed their marketing strategy and began to build online sales channels through e-commerce platforms and adopt various online marketing strategies to improve their marketing performance. Furthermore, the performance of online marketing of agricultural products is affected by the interaction of multiple factors in the complex environment. This study aims to distinguish between the performance of different online marketing strategies by using necessary comparative analysis (NCA) and qualitative comparative analysis (QCA) method, to help operators to grasp the critical elements of the online marketing of agricultural products, and how configuration effective impact the online marketing performance. The results show that: (1) NCA’s results show that a single online marketing dimension cannot constitute the necessary conditions for producing high marketing performance of agricultural products, but e-commerce broadcasting, visual effects and government cooperation play an obvious role in improving marketing performance. (2) online marketing performance is influenced by the interaction of various strategies, and no single factor has a significant effect on it. (3) a good online marketing performance configuration path is divided into four, namely “the government cooperation—e-commerce broadcasting” domination; “the government cooperation—visual effects—e-commerce broadcasting” leading; “customer relationship—the government cooperation—visual effects—e-commerce broadcasting” leading; “platform number—visual effects—e-commerce broadcasting” leading. (4) There are four driving paths with no-good online marketing performance, and there is a causal asymmetric relationship of the driving paths with good online marketing performance. This study provides management enlightenment for agricultural operators on how to effectively improve the performance of online marketing, help operators to solve practical problems, and facilitate the development of agricultural e-commerce.

Frictionless electronic commerce is a made-up story and online price dispersion is high and steady. There is not enough proof that online prices are decreasing and becoming alike. Although the studies show that prices dispersion on the Internet is decreased, they are steady yet. Therefore, this study aims to determine the important dimensions of electronic retailers' heterogeneity and examine the markets elements that influence price dispersion. The rapid development of e-commerce in Iran has made this task feasible. Questionnaire and observation were the methods used for collecting the data in this study. 106 identical products from 56 electronic retailers and 948 price quotes in different products categories such as books, CDs, laptops, mobiles, monitors, MP3s and digital cameras in online market have been used as data. 140 questionnaires have been developed for evaluating electronic retailers' characteristics. The method used in this analysis is statistical which mostly were factor analysis, cluster and regression analyses. It has been proved that services provided by electronic retailers could be described by five basic factors. Also, the results revealed that market and electronic retailers' characteristics are the main explanatory variables of price dispersion among electronic retailers.

Why are product prices in online markets dispersed in spite of very small search costs? To address this question, we construct a unique dataset from a Japanese price comparison site, which records price quotes offered by e-retailers as well as customers’ clicks on products, which occur when they proceed to purchase the product. The novelty of our approach is that we seek to extract useful information on the source of price dispersion from the shape of price distributions rather than focusing merely on the standard deviation or the coefficient of variation of prices, as previous studies have done. We find that the distribution of prices retailers quote for a particular product at a particular point in time (divided by the lowest price) follows an exponential distribution, showing the presence of substantial price dispersion. For example, 20 percent of all retailers quote prices that are more than 50 percent higher than the lowest price. Next, comparing the probability that customers click on a retailer with a particular rank and the probability that retailers post prices at a particular rank, we show that both decline exponentially with price rank and that the exponents associated with the probabilities are quite close. This suggests that the reason why some retailers set prices at a level substantially higher than the lowest price is that they know that some customers will choose them even at that high price. Based on these findings, we hypothesize that price dispersion in online markets stems from heterogeneity in customers’ preferences over retailers; that is, customers choose a set of candidate retailers based on their preferences, which are heterogeneous across customers, and then pick a particular retailer among the candidates based on the price ranking.

Consumer electronics such as Liquid Crystal Televisions (LCD-TVs) can be purchased at conventional stores or through internet online stores since the late 90's. On the internet, consumers can simultaneously compare prices at online price-comparing sites (e.g., kakaku.com in Japan). Thus, the prices are expected to be lower and less dispersed on the internet. According to a quantitative analysis, the former result is supported but the latter is not. Empirical studies on the existence and persistence of price dispersion among online stores have been done since the late 90's (see Pan et al. 2004). An early study compared online and offline prices (Bailey, 1998) and found that price dispersion among online stores was at least as great as among traditional conventional stores. Baye et al. (2004) studied the online monthly prices of popular consumer electronics products listed at shopper.com and concluded price dispersion is persistent across products and time. Moreover, we found that the online minimum prices of several types of LCD-TVs are more likely to be listed by online shops in Tokyo than in Osaka at kakaku.com. This implies that the online prices are lower in a larger city. Since the paper of Stigler (1961), there are numerous theoretical studies regarding price dispersion. Stigler (1961) investigated the consumer search behavior under given price dispersion. Salop and Stiglitz (1977) consider the equilibrium price dispersion with high and low price pure strategies for uninformed and informed consumers. Varian (1980) introduced the mixed strategy to explain the persistency of price dispersion. These papers mainly studied offline retail markets and supposed there was incomplete information on prices. On the internet, to the contrary, there is no cost to search for the lowest prices. Thus, Smith and Brynjolfsson (2001) claimed that differences in service quality among online stores is the main source of price dispersion. However, Pan et al. (2002) concluded that such differences are not the main source of price dispersion. This paper considers price dispersion in online and offline markets from a geographical aspect. We investigated the linear online rural market with two big cities lacated on the edges. The access costs, which include access fees, computer skills, and set-up costs to use the Internet infrastructure such as a home computer, credit card, were assumed to be heterogeneous among consumers. We showed that the price dispersion among online stores is larger than among the offline stores, and that the larger the population in the city, the lower the equilibrium prices. The key source of price dispersion is transportation costs, internet access fees, and differences in the population.JEL Classification: D21, D43

The study was driven by the growing trend of online shopping among students and the need to understand how digital marketing strategies impact their purchasing decisions on e-commerce platforms like Shopee. This research aims to evaluate the influence of online marketing on the purchasing decisions of students at STIE Latifah Mubarokiyah Suryalaya, in Tasikmalaya, Indonesia, specifically using the Shopee platform. Online marketing facilitates the transaction of goods and services via the Internet, providing the convenience of shopping without time and space constraints and allowing consumers to select products based on their preferences. The study employs a descriptive quantitative approach, involving 77 respondents selected through purposive random sampling. Data collection includes both primary and secondary sources, which are analyzed using simple regression, correlation analysis, determination analysis, and hypothesis testing. The findings reveal that online marketing strategies significantly influence students' purchasing behaviour on e-commerce platforms, with a correlation coefficient of 0.694 and a determination coefficient of 48.1%. This indicates that nearly half of the variability in student purchase decisions can be attributed to online marketing strategies. Moreover, the study offers new insights into how specific online marketing tactics, such as targeted advertisements and social media promotions, uniquely influence student preferences and purchasing patterns. These findings highlight the importance of personalized marketing approaches in shaping consumer behaviour. The study also suggests that further research should explore additional factors influencing consumer behaviour in e-commerce to achieve a more comprehensive understanding.