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The paper aims to investigate how customer satisfaction can be achieved in the context of digital platform services, its influence on electronic word of mouth (eWOM) and how such relationships can be moderated by perceived technological innovativeness (PTI).

The research framework was developed and empirically tested using an online survey and analysed using structural equation modelling (SEM). Data were gathered from 501 Uber customers in London, UK.

The study recognises and confirms that trust and cost saving enhanced customer satisfaction in Uber mobility services, which has a positive impact on eWOM. There are other findings regarding users who share rides vs those who do not share. Furthermore, it has been found that PTI moderates the relationship between customer satisfaction and eWOM.

The research draws on collaborative consumption literature and contributes to the antecedents of customer satisfaction in digital economy literature: trust, environmental impact, cost saving and utility. The study offers an empirical validation of the role of PTI in enhancing eWOM. The paper breaks new ground for a better understanding of how PTI can moderate the influence of customer satisfaction and eWOM in digital platforms.

With the development of digitalization and interconnection, there is a growing need for enterprise customers to ensure the compatibility of the third-party components they are using in the manufacturing process, thus raising the integration requirements for the Industrial Internet platform and its third-party developers. Therefore, our study investigates the optimal integration decision of the Industrial Internet platform while considering its access price, the integration cost, and the net utility derived by enterprise customers from the third-party components.

We model a two-sided Industrial Internet platform that connects customers on the demand side to the developers on the supply side. We then explore the integration decision of the Industrial Internet platform and its important factors by solving the optimal profit function.

First, despite the high integration cost of third-party developers, the platform still chooses to integrate when enterprise customers derive high utility from the third-party components. Second, due to the compatibility effect, charging the enterprise customers a higher price may reduce the platform profits when these customers derive low utility from the third-party components. Third, the platform profits will increase along with the integration cost of third-party developers when it is low in the case where enterprise customers derive low utility from third-party components.

Our findings offer insightful takeaways for the Industrial Internet platform when making integration decisions.

An increasing number of customers are using customer-to-customer (C2C) platforms to buy and sell products and services. Despite this growth, little research has examined customer experiences with C2C e-commerce. This study examines how informational and emotional interactions affect customer patronage behaviors by increasing customer trust in both sellers and platforms.

A self-administered questionnaire was used to collect data from 181 customers of C2C platforms in the United States. Partial least squares structural equation modeling was used to analyze the data.

The results show that informational interactions affect customer trust both in sellers and platforms, resulting in customer loyalty. The findings also show that emotional interactions affect customer trust in sellers. Multi-group analyses suggest that the impacts of informational and emotional interactions on trust vary depending on customer demographics.

Theoretical implications in this study arise from (1) examination of customer experiences with C2C platforms using the stimulus-organism-response framework, (2) identification of the role of informational and emotional interactions in the formation of trust and (3) exploration of the ways in which customer gender, age and income affect the connection between experiences and consequences in C2C settings.

From a practical perspective, this study provides useful guidelines to help C2C business practitioners increase customer patronage behavior by means of interactions and trust.

This study provides practical and academic implications by examining how customer interactions affect customer trust in e-commerce C2C platforms.

This paper aims to identify the dimensions of digital platforms' services quality and their impact on customers' purchase intent based on customer experience.

The research has a mixed method. Qualitative data is gathered by using of systematic literature review and Delphi method and quantitative data is gathered through survey of 412 experts from three well-known restaurant industry platforms. These restaurant digital platforms were Snapfood, Changal and Chelivery.

The results indicate the effect of platforms' service quality dimensions on customer hedonic and cognitive experiences. Also, the results indicate that the platforms' customers attach different priority to the various dimensions of platforms' services quality which are platform services' ease of use, platform information quality, services and products quality, platform customers interaction, platform design, platform response speed, platform services' trustiness, platform services' security and platform responsibility. Finally, the results showed that all of these dimensions have positive impact on customers' purchase intent based on their experiences.

The development of digital service platforms despite being new, has recently great progress, but, many dimensions of digital platforms' services quality have been not well-known yet. The present research has cleared the subject.

This study proposes a conceptual framework for analyzing customer management strategies and their effects on Internet-based platform performance based on a review of the relevant literature, and provides directions for future research.

A literature review of relevant research articles on customer management in platform firms was conducted.

First, a framework based on the market maker view of platform firms suggests customer acquisition, customer retention and customer governance are the main customer management subprocesses toward improving platform firm performance. Second, the most studied customer management strategies for each subprocess contribute to platform performance based on the mechanisms of building customer network, developing customer network effect and managing sustainable customer networks.

This study proposes a framework that identifies customer acquisition, customer retention and customer governance as three key customer management subprocesses in platform firms. It also summarizes the most studied customer management strategies/actions for each subprocess. With this analytical framework, it identifies underexplored key issues in customer management for further research.

This study elicits the critical attributes, consequences and values associated with the purchasing process in the context of cross-border e-commerce (CBEC). The purpose is to provide a better understanding of the fundamental factors that determine consumer values in CBEC.

The study applies the means-end-chain theory and soft-laddering techniques to interview 60 CBEC consumers to construct an implication matrix and a hierarchical value map (HVM) of the consumer purchasing process, consisting of attribute-consequence-value (A-C-V) paths.

By analyzing the significant linkages, elements, ladders and chains in the HVM, four dominant A-C-V paths were identified: economic-driven, efficiency-driven, progress-driven and quality-driven paths.

This study included only Chinese CBEC buyers. This limitation might affect the generalizability of the conclusions as culture, purchase habits and economic development differ between China and other countries.

The results of this study provide CBEC practitioners an understanding of the consumer purchasing process and how consumer values are associated with platform characteristics. Thus, the results aid practitioners in allocating resources and developing CBEC platforms in an appropriate manner and direction.

This study sheds lights on the emerging phenomenon of CBEC. By applying the means-end-chain approach, the study provides a comprehensive HVM for interpreting the consumer online purchasing process in this novel context. By illustrating the dominant paths, this research provides deeper theoretical insights into the specific focuses of CBEC consumer purchasing.

Digital platforms have grown significantly in recent years. Although high platform failure risks (PFR) have plagued the industry, the literature has only given this issue scant treatment. Customer sentiments are crucial for platforms and have a growing body of knowledge on its analysis. However, previous studies have overlooked rich contextual information emb`edded in user-generated content (UGC). Confronting the research gap of digital platform failure and drawbacks of customer sentiment analysis, we aim to detect signals of PFR based on our advanced customer sentiment analysis approach for UGC and to illustrate how customer sentiments could predict PFR.

We develop a deep-learning based approach to improve the accuracy of customer sentiment analysis for further predicting PFR. We leverage a unique dataset of online P2P lending, i.e., a typical setting of transactional digital platforms, including 97,876 pieces of UGC for 2,467 platforms from 2011 to 2018.

Our results show that the proposed approach can improve the accuracy of measuring customer sentiment by integrating word embedding technique and bidirectional long short-term memory (Bi-LSTM). On top of that, we show that customer sentiment can improve the accuracy for predicting PFR by 10.96%. Additionally, we do not only focus on a single type of customer sentiment in a static view. We discuss how the predictive power varies across positive, neutral, negative customer sentiments, and during different time periods.

Our research results contribute to the literature stream on digital platform failure with online information processing and offer implications for digital platform risk management with advanced customer sentiment analysis.

Omnichannel has become increasingly important with the development of e-commerce. In omnichannel, merchants expect customers to get the products and services at anytime, anywhere and in any way, and the same is true for customers. This drives multihoming in online platforms for both merchants and customers. Thus, once both customers and merchants are multihomed, what price and subsidy decisions should be made between platforms to compete to obtain optimal profits? The main purpose of this paper is to solve these problems and provide decision-making for two-sided platforms in omnichannel.

This study builds a dual Hotelling model to capture the utility and network effects of customers and merchants on two-sided platforms. This study introduces the exposure effect and convenience effect of multihomed customers and merchants in the model and analyzes the impact of these effects in the market with multihoming on one side. Then, this study extends the model to the market with multihoming on both sides and makes the pricing decision for two-sided platform when considering the exposure effect and convenience effect through an equilibrium solution. Finally, this study also uses numerical analysis to simulate the decision and profit of the platform.

This paper finds that the convenience effect will only increase social welfare when customers are single-homed and merchants are multihomed. In addition, when both users are multihomed, the platform will subsidize to attract merchants and customers if the convenience effect and exposure effect are relatively high. This study also finds that network effects come not only from the same platform but also from another platform in the case with multihoming on both sides. And network effects in the heterogeneous platform will be reduced by the convenience effect and exposure effect.

According to the behavioral characteristics of merchants and customers in omnichannel, this paper first adopts the dual Hotelling model to study the pricing of two-sided platforms with multihoming on both sides. This paper shows that network effects originate not only from the same platform but also from another platform and that the exposure effect and the convenience effect can exist as cross-platform network effects, which provides a new explanation for network effects in markets with multihoming on both sides. This research extends the theory of network effects and plays an important role in the development of two-sided platforms in omnichannel.

The purpose of this paper is to explain how ecosystems and platforms have evolved to manage customer information and to identify the management, research and teaching implications of this evolution.

This paper is based on research and industrial experience of two of the co-authors in customer relationship management, further developed with other co-authors in the field of business models, the research and teaching experience of the university authors and cross-functional literature reviews in the areas of strategy, marketing, economics, organizational behaviour and information management.

This paper shows that digitalization, cloud computing and new information-based platforms are beginning to change how customer information is being managed, creating new opportunities for improving marketing, customer relationship management and business strategy.

The impact of platforms on the management of customer information needs to be confirmed by primary empirical research.

This paper identifies the need for senior marketing management to examine closely how internal and external/public customer information platforms may enhance their capability for managing customers and setting new strategic directions.

The emergence of giant multi-sided platforms has clear implications for data protection and privacy, which need to be explored more in research.

This paper highlights the move to customer information platforms and identifies how senior managers should consider them as an option for better customer information management and as a basis for new business strategies.