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This paper forms an e-commerce supply chain that include a manufacturer providing products and an online platform providing service. The reselling platform mode and the agent platform mode are considered through an exploration of the manufacturer Stackelberg (MS), vertical Nash (VN), platform Stackelberg (PS) power structures. The purpose of this paper is to explore the pricing and platform service decisions under different platform selling modes and channel power structures.

Based on the game theory models, this paper investigates the interaction between the manufacturer and the online platform under four different scenarios. The optimal solutions of four models are provided. Through comparison analyses, this paper evaluates the impacts of platform selling mode and channel power structure on the pricing and platform service decisions and the members’ profits.

The manufacturer prefers the MS power structure in any platform mode. The online platform prefers the PS (MS) power structure under a low (high) service cost efficiency in the reselling platform mode, while prefers the PS and VN power structures in the agent platform mode. Moreover, the manufacturer prefers the agent (reselling) platform mode under a low (high) service cost efficiency in any power structure. The online platform prefers the reselling platform mode in the MS and PS power structures, while prefers the reselling (agent) platform mode under a low (high) service cost efficiency in the VN power structures.

The analysis result provides important managerial implications that help the supply chain members develop a better understanding of the selection of the platform selling mode and the effect of the channel power structure in the presence of platform service.

This article aims to reveal the factors influencing the sustainable development of mobile e-commerce from both user and operational perspectives. It fills the gap in qualitative research on the sustainable development of artificial intelligence (AI) technology in mobile e-commerce based on the grounded theory. This study provides valuable insights and inspiration for sustainable development in this field and lays the theoretical foundation and research reference for future studies.

Based on the grounded theory (GT), interview method was used to conduct the study.

The impact of AI applications on mobile e-commerce is mainly reflected in three stages of the customer shopping process. They are pre-shopping, mid-shopping and after-shopping AI services and each of the three stages has its own separate dimensions that need attention. The study and its persistence aspects are discussed.

The results of this study can provide forward-looking suggestions and paths for the construction and optimization of future e-commerce platforms, contribute to the sustainable development of e-commerce and contribute to the sustainable and healthy growth of the social economy.

This study proposes sustainable development measures for the application of AI in mobile e-commerce, from operation to supervision, which is an important reference for promoting coordinated and rapid socio-economic development.

We investigate the extended service strategy choices of competing manufacturers and examine their impact on the retail platform.

We construct a supply chain model with a retail platform as the leader and manufacturers as the followers. Manufacturers face differential consumer preferences on the same agency retail platform, and they can sell a bundled extended service product and sell a separate product without any extended service.

The sale of extended warranty services on the retail platform leads to lower pricing of the manufacturers' products and changes in the product market structure in response to differences in consumer preferences. The retailing platform tends to provide an extended warranty conditionally. The sale of extended warranty services on a retail platform would be detrimental to the interests of the manufacturer who sells products with extended warranty services and in favor of the manufacturer who sells products without them.

The equilibrium results of the retail platform’s non-sales and sales of extended warranty services for the no-extended warranty product under the same commission rate and differential commission rate models are discussed, and the product structure of the market is investigated, respectively.

This study investigates how role overload in the sharing economy leads to emotional exhaustion, which restricts value co-creation activity, and also investigates the moderating effect of perceived platform support.

Two experimental investigations and field research questionnaires were given to respondents with shared mobility industry expertise.

First, role overload detrimentally affects service providers' value co-creation behavior; second, emotional exhaustion acts as a mediator between role overload and value co-creation behavior; and finally, perceived platform support moderates the adverse effect of role overload on emotional exhaustion.

To the best of the authors' knowledge, this study is the first to explore the antecedents of value co-creation behavior from the service provider's perspective, extending the application of COR theory in a sharing economy context.

First, alternative mediators between role overload and emotional exhaustion were not identified. Second, other dimensions of role overload and their impacts were not examined. Lastly, this study did not explore broader perspectives beyond algorithms.

This study recommends that managers reduce role overload ex ante in terms of clarifying responsibilities and obligations, providing substantive resource support and rationalizing order allocation, respectively.

Digital innovation requires organizations to reconfigure their information technology infrastructure (ITI) to cultivate creativity and implement fast experimentation. This research inquiries into ITI generativity, an emerging concept demoting a critical ITI capability for organizational digital innovation. More specifically, it conceptualizes ITI generativity across two dimensions—namely, systems and applications infrastructure (SAI) generativity and data analytics infrastructure (DAI) generativity—and examines their respective social and technical antecedents and their impact on digital innovation.

This research formulates a theoretical model to investigate the social and technical antecedents along with innovation outcomes of ITI generativity. To test this model and its associated hypotheses, a survey was administered to IT professionals possessing knowledge of their organization's IT architecture and digital innovation performance. The dataset, comprising responses from 140 organizations, was analyzed using the partial least squares technique.

Results reveal that both dimensions of ITI generativity contribute to digital innovation performance, with the effect of DAI generativity being more pronounced. In addition, SAI and DAI generativities are driven by social and technical factors within an organization. More specifically, SAI generativity is positively associated with the usage of a digital application services platform and IT human resources, whereas DAI generativity is positively linked to the usage of a data analytics services platform, data analytics services usability and data analytics human resources.

This research contributes to the literature on digital innovation by introducing ITI generativity as a crucial ITI capability and deciphering its role in digital innovation. It also offers useful insights and guidance for practitioners on how to build ITIs to achieve better digital innovation performance.

Using perspectives from the technology affordance and social capital theories, this study aims to unpack the process through which platform-enabled co-development unfolds in supply chain contexts. Specifically, it explores how innovation outcomes can be fostered through platform affordances and supply chain relationship (SCR) capital.

The paper integrates literature on digital platforms, SCRs and co-development to produce an integrative framework, developing propositions on the relationships among digital platforms, SCR capital and innovation outcomes.

The authors identify affordances for distinctive strategic use of platforms: value co-creation, relationship building and strategic learning. The authors discuss ways in which each affordance contributes to the advances in SCR capital, thus altogether enabling focal firms to orchestrate and integrate internal and external resources to attain incremental and radical innovation.

Based on the proposed research framework, further empirical studies can use quantitative data to measure the relationship between affordances and SCR capital and use longitudinal case studies to explore how affordances and SCR capital evolve to provide more fine-grained and contextualised information in different research settings.

This paper sheds light on how the relation between the adoption of digital platforms and SCR capital shapes digitally enabled service co-development. The authors provide an alternative explanation of resource integration in platform-mediated supply chain contexts and enrich the related literature on how digital platforms can maximise value from introducing ambidextrous innovation by leveraging internal and external resources.

Online food delivery has been prevalent in recent years worldwide, especially during the COVID-19 pandemic, and people's consumption behaviors have changed significantly. This study aims to investigate the consumption behavior of young adults using online food delivery platforms during the COVID-19 pandemic and focuses on the dominant factors influencing their decision to use online food delivery platforms.

Semi-structured interviews including 14 young adults aged 18–25 living in Hong Kong were conducted to collect data about their perspectives on online food delivery platforms in five areas. This research adopted the stimulus-organism-response model (S-O-R model) to analyze how the factors influence young adult users' loyalty and satisfaction with online food delivery platforms.

Thematic analyses revealed that young adults were attracted to online food delivery platforms for their numerous benefits. They had a high frequency of usage and significant spending. Usability, usefulness, satisfaction and loyalty influenced young adults' behaviors on online food delivery platforms. Participants were overall satisfied with their experiences, but platforms still had room for improvement.

Few prior studies investigated the factors affecting the consumer experience and behavioral intention of online food delivery for young adults in Asia. This study contributes to understanding young adults' experiences and problems with online food delivery platforms. It provides practical insights for system engineers and designers to improve the current services and for the governments to enhance the existing regulatory loopholes.

Establishing and developing digital science and education evaluation platforms (DSEEPs) have several practical implications for the development of China's science, technology and education. Identifying and analyzing the key factors influencing DSEEP user experience (UX) can improve the users' willingness to use the platform and effectively promote its sustainable development.

First, a literature survey, a five-element model of UX and semi-structured interviews were used in this study to develop a DSEEP UX-influencing factor model, which included five dimensions and 22 influencing factors. Second, the model validity was verified using questionnaire data. Finally, the key influencing factors were identified and analyzed using a fuzzy decision-making trial and evaluation laboratory (fuzzy-DEMATEL) method.

Fourteen influencing factors, including diverse information forms and comprehensive information content, are crucial for the DSEEP UX. Its optimization path is “‘Function Services’ → ‘Information Resources’ → ‘Interaction Design’ → ‘Interface Design’ and ‘Visual Design’.” In this regard, platform managers can take the following measures to optimize UX: strengthening functional services, improving information resources, enhancing the interactive experience and considering interface effects.

This study uses a combination of qualitative and quantitative research methods to determine the key influencing factors and optimization path of DSEEP UX. Optimization suggestions for UX are proposed from the perspective of platform managers, who provide an effective theoretical reference for innovating and developing a DSEEP.

The importance of service firms cooperating with digital platforms is widely acknowledged. The authors study three contractual relationships (fixed-cost, cost-sharing, and profit-sharing) between service firms (specifically hotels) and digital platforms in a highly fragmented service supply chain to examine which of these contract types optimizes profits.

The authors extend prior models analyzing the optimal expected total profit from the travel service firm (hotel)–digital platform relationship, providing new insights into each contract type’s ability to coordinate decentralized systems and optimize profits for both parties.

This study finds that fixed cost contracts cannot coordinate the decentralized system. Cost-sharing contracts can coordinate the decentralized system but only allow one channel profit split. In contrast, profit-sharing contracts may not always perfectly coordinate the decentralized system but support alternative profit allocations. Practically, both profit-sharing and cost-sharing contracts are preferable to fixed-cost contracts.

The paper includes implications for travel service firm managers to consider when structuring contracts with digital platforms to focus on profit optimization. Profit-sharing contracts are most preferable when cost and revenue data are fully shared between parties, while cost-sharing contracts are preferable over fixed-cost contracts.

This study extends prior investigations into the utility of different contract types on the optimal profit of a travel service firm (hotel)-digital platform provider relationship. The research fills a gap in the literature concerning the contracts used in these relationship types.

This study examines the Robo-Advisors (RA) based on Artificial Intelligence (AI), a new service that digitises and automates investment decisions in the financial and banking industries to provide low-cost and personalised financial advice. The RAs use objective algorithms to select portfolios, reduce behavioural biases, and improve transactions. They are inexpensive, accessible, and transparent platforms. Objective algorithms improve the believability of portfolio selection.

This study adopts a qualitative approach consisting of an exploratory examination of seven different RA case studies and analyses the RA platforms used in the banking industry.

The findings provide two different approaches to running a business that are appropriate for either fully automated or hybrid RAs through the realisation of two platform model frameworks. The research reveals that relying solely on algorithms and not including any services involving human interaction in a company model is inadequate to meet the requirements of customers in decision-making.

This study emphasises key robo-advisory features, such as investor profiling, asset allocation, investment strategies, portfolio rebalancing, and performance evaluation. These features provide managers and practitioners with new information on enhancing client satisfaction, improving services, and adjusting to dynamic market demands.

This study fills the research gap related to the analysis of RA platform models by providing a meticulous analysis of two different types of RAs, namely, fully automated and hybrid, which have not received adequate attention in the literature.