A combinatorial auction to sell TV broadcasting rights in league sports

The centralized sale of TV broadcasting rights in league sports constitutes a cartel which in many European countries is allowed only if it complies with certain conditions set by competition authorities. Two of the most important conditions are: i) partial unbundling, i.e. the rights must be unbundled into several separate packages; and ii) the no-single-buyer rule, i.e. the packages must be sold to different broadcasters. This article shows how a combinatorial auction can be employed to sell broadcasting rights allocating them endogenously based on the broadcasters’ bids and, thus, without requiring the seller to pre-determine the packages of such rights. This feature can address various competition policy issues, including facilitating market entry and preventing coordination among bidders. Also, a combinatorial auction has the potential to achieve higher levels of allocative efficiency and higher revenue levels compared to auctions with pre-determined packages of broadcasting rights.     

Online shopping continuance after COVID-19: A comparison of Canada,Germany and the United States

The COVID-19 pandemic brought about an increase in online shopping because of government-imposed restrictions and consumer anxiety over the potential health risk associated with in-store shopping. By end of 2021, many health concerns had been alleviated through efforts such as vaccinations and reductions in hospitalizations in certain countries. Some governments started to relax their restrictions and consumers started to return to in-store shopping, creating the possibility that the volume of online shopping would decrease once stores reopened. However, consumers may continue to shop online more than they did prior to the pandemic because of their experience during the lockdown. This study seeks to understand the factors that explain the potential of online shopping continuance. A novel model is constructed by extending ES-QUAL, and adding hedonic motivation, social shopping and health susceptibility as mediators. Empirical data is collected from Canada, Germany and the US. We find that convenience and efficiency, as well as security for some females, are important factors contributing to online shopping's perceived usefulness and, ultimately, intentions to continue shopping online. In addition, creating an enjoyable online shopping experience adds to these continuance intentions.     

Social effects of topic propagation on Weibo

Weibo, China’s largest microblogging platform, has become one of the key information-sharing platforms in modern society. This study examines topic propagation in relation to microblogging from the perspective of the “peer effect.” Using data of hot topics from Weibo, we analyze how the social effect and propagation pathway influence the topic propagation process. We propose a spatial and temporal heterogeneity diffusion model that includes endogenous and exogenous social effects and is based on but different from the Bass diffusion model. We find that most propagation pathways end after a single level of propagation. The endogenous social effect in microblogs primarily influences the inflow of topics. Such endogenous social effect, combined with the multiplier effect, motivates most users to share a microblog topic in a short period of time. The exogenous social effect primarily influences the outflow of topics, and therefore, the microblog topics of a small number of popular users’ account for most of the share volume. Our results are robust to potential serial correlation, reflection problem, and potential self-selection due to user status.The findings reveal that group characteristics affect individuals’ behaviors and choices in relation to the topic propagation process on microblogging platforms. The use of a spatial and temporal heterogeneity diffusion model and the robustness of the analysis process provide new information for scholars in this field.     

Online food delivery companies' performance and consumers expectations during Covid-19: An investigation using machine learning approach

Online food delivery (OFD) businesses flourished during COVID-19; however, OFD companies experienced different challenges and customers' expectations. This paper uses social media data to explore OFD companies' performance and customers' expectations during the COVID-19 pandemic. The most important topics in developed and developing countries are identified using machine learning. Results show that customers in India are more concerned about social responsibility, while financial aspects are more important in the US. Overall, customers in India are more satisfied with OFD companies during the COVID-19 pandemic than the US customers. We further find that factors such as OFD companies' brand, market size, country, and COVID-19 waves play a crucial role in moderating customer sentiment. The results of the study offer several managerial insights.     

Developing and validating a multidisciplinary scale of E-retailing website elements

The purpose of this article is to theoretically identify the salient elements of e-retailing websites and empirically verify them through a rigorous scale development process. A mixed method approach was followed to achieve these objectives: a qualitative (content analysis) and a quantitative approach (factorial and confirmatory surveys). Three findings emerge from the current study. First: this study provides sound empirical support for e-retailing website elements as a high-order construct that consists of eight first-order factors. Second, the current research suggests that the measurement instrument for e-retailing website elements, which contains 54 items, is a valid and reliable using the following factors: hedonic website design elements, technical website design elements, website experiential elements, website relational elements, product-related elements, order-related elements, security-related elements and social media presence. Third, the proposed measurement instrument of e-retailing website elements strongly predicts e-satisfaction and e-trust. The key contribution of this study stems from developing and validating a multidisciplinary scale that synthesizes and integrates the major perspectives of e-retailing website elements.     

The impact of COVID-19 on the evolution of online retail: The pandemic as a window of opportunity

Pandemic-related shocks have induced an unexpected volatility into the evolution of online sales, making it difficult for retailers to cope with frequently occurring, drastic changes in demand. Relying on a socio-technical approach, the purpose of this paper is to (a) offer a deeper insight into the driving forces of online sales during the pandemic, and (b) investigate whether pandemic-related shocks accelerate the long-term growth of online retail. Novel, high-frequency data on GPS-based population mobility and government stringency is used to demonstrate how time spent in residential areas and governmental restrictions drive the monthly evolution of online sales in 23 countries. We deconstruct these effects into three main phases: lure-in, lock-in, and phase-out. Lastly, using time series analysis, we show that the pandemic has induced a level shift into the long-term growth trend of the online retail sector in the majority of countries investigated.     

What online game spectators want from their twitch streamers: Flow and well-being perspectives

Over the last five years, live-streaming platforms, such as Twitch and YouTube, have been dramatically developed and used for individuals' broadcast of digital content, including online video games. Consequently, online game live-streamers have played an important role in the business industry (e.g., advertisements) as well as the online video game industry. By focusing on this context, this study identifies streamer attributes and live-streaming mobile application attributes, and examines how each attribute influences spectators’ flow experience, psychological well-being, commitment, and loyalty toward their favorite streamer. Based on the cognitive appraisal theory and social media influencer literature, the authors classify streamer attributes (i.e., friendship, interaction, and streamer skills) and live-streaming mobile application attributes (i.e., perceived usefulness, technology & functional quality, convenience, and security quality) in the context of Twitch. The data were collected from Twitch users in the United States via two waves. The empirical findings indicated: (1) friendship, technology & functional quality, convenience, and security quality significantly affected flow experience; (2) friendship, streamer skills, convenience, and security quality significantly influenced psychological well-being; (3) flow experience significantly impacted commitment and loyalty; (4) psychological well-being had a significant effect on commitment; and (5) commitment significantly affected loyalty. The empirical findings of this study provide meaningful implications to scholars and practitioners in the social media and online video game contexts.     

Nowcasting food inflation with a massive amount of online prices

The consensus in the literature on providing accurate inflation forecasts underlines the importance of precise nowcasts. In this paper, we focus on this issue by employing a unique, extensive dataset of online food and non-alcoholic beverages prices gathered automatically from the webpages of major online retailers in Poland since 2009. We perform a real-time nowcasting experiment by using a highly disaggregated framework among popular, simple univariate approaches. We demonstrate that pure estimates of online price changes are already effective in nowcasting food inflation, but accounting for online food prices in a simple, recursively optimized model delivers further gains in the nowcast accuracy. Our framework outperforms various other approaches, including judgmental methods, traditional benchmarks, and model combinations. After the outbreak of the COVID-19 pandemic, its nowcasting quality has improved compared to other approaches and remained comparable with judgmental nowcasts. We also show that nowcast accuracy increases with the volume of online data, but their quality and relevance are essential for providing accurate in-sample fit and out-of-sample nowcasts. We conclude that online prices can markedly aid the decision-making process at central banks.