Effects of service attributes and competition on electronic word of mouth: an elaboration likelihood perspective

The management of electronic word of mouth (eWOM) is critical in e-commerce. In this study, on the basis of the elaboration likelihood model (ELM), we constructed a model of factors influencing eWOM by dividing merchants' attributes into the central and peripheral routes, which correspond to consumers' systematic and heuristic cognitive modes respectively. We then tested the developed model by using a cross-sectional data set. The results of this study indicate that the degree of competition faced by merchants has a significant negative association with eWOM. Moreover, price level and location moderate the relationship between competition and eWOM. The services of reservation and group buying have positive associations with eWOM. This research has three main contributions. First, we explored the effect of competition on eWOM. Second, we validated the feasibility of applying the ELM to the catering industry by dividing merchant attributes into the central and peripheral routes; this approach is consistent with systematic and heuristic cognitive theories. Finally, this research provides practical suggestions for eWOM management in the catering industry.

Ghosts in the Machine: How Marketing and Human Capital Investments Enhance Customer Growth When Innovative Services Leverage Self-Service Technologies

Practice and Policy Abstract

Seller Organization and Percentage Fee Design in the Daily Deal Market

The prosperity of the daily deal business has attracted more sellers to participate in daily deal campaigns with offering discounted deals via online platforms like Groupon and Juhuasuan. This gives rise to a new challenge for online platforms on how to efficiently organize a limited number of sellers to conduct daily deal campaigns. Our paper makes the first attempt to understand how different seller organization formats can influence the firms’ equilibrium strategies and profits in the daily deal market. We focus on two prevalent seller organization formats. (1) The seller agglomeration strategy: the platform (e.g., Groupon) does not distinguish the sellers’ type in each round of the campaign. (2) The seller segmentation strategy: the platform (e.g., Juhuasuan) organizes sellers of the same type in each round. Comparing to the agglomeration strategy, we show that the segmentation strategy can eliminate internal information asymmetry among competing sellers and thus can improve the sellers’ pricing efficiency and facilitate the platform to charge a higher percentage fee. This uncovers the value of seller segmentation and theoretically explains why platforms should carefully segmentate sellers in daily deal campaigns, although considerable efforts are required to enroll sellers.

How should local Brick-and-Mortar retailers offer delivery service in a pandemic World? Self-building Vs. O2O platform

The Covid-19 pandemic has dramatically changed consumer purchase behavior, and the "stay-at-home order" policy has altered the operations of brick-and-mortar (B&M) retail stores. These changes have induced local B&M retailers to start online retailing with home delivery as an added option. B&M retailers can choose to offer online retailing on their own (referred to as self-building mode) or via a third-party online-to-offline (O2O) platform (referred to as platform mode). This paper investigates how the interplay between capacity, pricing, and online retailing mode is affected by the absence/presence of the pandemic. We characterize the equilibrium between the B&M retailer and the O2O platform provider. We find that the impact of the "stay-at-home orders" on B&M retailers differs by the online retailing mode. Interestingly, we find that the "stay-at-home orders" does not necessarily lower the B&M retailer's profit if they engage in online retailing. Under self-building mode, the stay-at-home order leaves the B&M retailer with just the online channel. We identify the threshold delivery cost above (below) which the B&M retailer's profit is lower (higher) than before. Under the platform mode, the "stay-at-home order" alters the retailer's sales channel from dual channel to single channel, which mitigates the competition between the retailer and the O2O platform. The retailer's profit increases if it has sufficiently high capacity. Finally, we extend the model to examine the effect of a "reopening policy" with a government subsidy. We find that although the subsidy improves the B&M retailer's profitability, it may hurt the consumer surplus under some conditions. We suggest that governments take the B&M retailer's capacity and operations mode into account when designing subsidy policies.

Business Analytics in E-Commerce: A Literature Review

This paper attempts to identify the value and the use of business analytics (BA) in E-commerce, and challenges and trends associated with BA in E-commerce. It systematically examines the literature about BA, with a particular focus on E-commerce. BA has critical value in E-commerce. BA has been used in customer analysis and website usage analysis. The most important factor for the value of E-commerce BA is customer. This paper also suggests an E-commerce BA research model which describes the BA iterative process from data to analysis, to decision, to estimation, and separates BA analysis results as functional-level and competitive-level results. Challenges identified in this paper hold theoretical and practical implications. Future studies could seek an enhanced understanding of BA through quantitative analysis.

Deal or No Deal? Online Deals, Retailer Heterogeneity, and Brand Evaluations in a Competitive Environment

Daily deal platforms, such as Groupon, peaked in the mid-2000s, by letting retailers offer 50% promotions to consumers using an app. When used right, retailers were able to get consumers to try them for the first time and build a customer base. When used wrong, retailers lost revenue unnecessarily and sometimes went out of business. Even now, in 2020, you can find lovers and haters of daily deals, and yet they remain an integral part of the marketing mix for many retailers. One lingering question about these deals remained: How do customers perceive a retailer that offers daily deals before going to the retailer? Do retailers look desperate or confident? Through a series of laboratory experiments, we test whether offering a deal changes consumers’ preconsumption brand evaluations. Our research shows that brand evaluations are contingent on the retailer type (i.e., price segment and age), the success of the current deals offered (i.e., number of page visits and purchases), and the number of competitors that are also using deals. Together, our work demonstrates specific conditions where offering deals may lead to positive or negative consumer perceptions even before arriving at the retailer.

Turning Liabilities of Global Operations into Assets: IT-Enabled Social Integration Capacity and Exploratory Innovation

Practice and Policy Abstract: