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The purpose of this paper is to study the cooperation and pricing strategies for e-commerce platforms when considering seller classification.

E-commerce platforms serve to facilitate trade and generate revenue from the participants. By classifying the sellers in the market into two types (the individual sellers vs the professional sellers), the authors examine how the interaction between the two types of sellers affects the platform’s cooperation and pricing decisions. Specifically, the authors compare two cooperation strategies for the platform: cooperating only with the professional sellers (strategy I); and cooperating with both the two types of sellers (strategy II).

When the platform attractiveness for the professional sellers is high enough, strategy II is absolutely beneficial than strategy I; whereas when the platform attractiveness for the professional sellers is low and the performance requirement of the individual sellers is relatively high, strategy I will be more beneficial.

For a platform choosing strategy II, it should make effort to differentiate between the different types of sellers by the product or service quality.

The paper is among the first to study the cooperation and pricing strategies for the e-commerce platform with seller classification.

The main purpose of the paper is timing analysis of mixed critical applications on the multicore system to identify an efficient task scheduling mechanism to achieve three main objectives improving schedulability, achieving reliability and minimizing the number of cores used. The rise in transient faults in embedded systems due to the use of low-cost processors has led to the use of fault-tolerant scheduling and mapping techniques.

The paper opted for a simulation-based study. The simulation of mixed critical applications, like air traffic control systems and synthetic workloads, is carried out using a litmus-real time testbed on an Ubuntu machine. The heuristic algorithms for task allocation based on utilization factors and task criticalities are proposed for partitioned approaches with multiple objectives.

Both partitioned earliest deadline first (EDF) with the utilization-based heuristic and EDF-virtual deadline (VD) with a criticality-based heuristic for allocation works well, as it schedules the air traffic system with a 98% success ratio (SR) using only three processor cores with transient faults being handled by the active backup of the tasks. With synthetic task loads, the proposed criticality-based heuristic works well with EDF-VD, as the SR is 94%. The validation of the proposed heuristic is done with a global and partitioned approach of scheduling, considering active backups to make the system reliable. There is an improvement in SR by 11% as compared to the global approach and a 17% improvement in comparison with the partitioned fixed-priority approach with only three processor cores being used.

The simulations of mixed critical tasks are carried out on a real-time kernel based on Linux and are generalizable in Linux-based environments.

The rise in transient faults in embedded systems due to the use of low-cost processors has led to the use of fault-tolerant scheduling and mapping techniques.

This paper fulfills an identified need to have multi-objective task scheduling in a mixed critical system. The timing analysis helps to identify performance risks and assess alternative architectures used to achieve reliability in terms of transient faults.

Retailers are increasingly adding multiple platform apps. For instance, Hilton Hotel is listed on booking.com, Expedia and TripAdvisor. The purpose of this study is to examine whether and how the adoption of a second homogenous mobile platform app by new and existing consumers affects their purchasing behavior in both the original app and the overall platform apps.

With 604,864 unique data from a Chinese fast-food company, which sequentially add three food delivery platforms, this paper explores the influence of a second homogeneous mobile platform app adoption on consumer purchase frequency, order size and spending.

The results of the log-linear regression model show that multiplatform consumers are more profitable than single-platform consumers. For both existing and new consumers, multiplatform adoption would increase purchase frequency, decrease order size and increase total spending with the retailer. However, for existing consumers, multiplatform adopters are more likely to buy less frequently, spend less per order and have lower total spending in the original platform app.

This paper contributes to platform addition and multichannel literature by empirically finding that multiplatform adopters, both new and existing consumers, are more profitable than single-platform consumers. Managerially, the results suggest that companies should not hesitate to add multiple platforms and should encourage consumers to use multiple mobile apps.

First, this study examines the multiplatform addition effect on both new and existing consumers, which has not been discussed yet. Second, this study contributes to multichannel literature by finding that multiplatform consumers are more profitable than single-platform consumers. Third, unlike Rong et al. (2021), this study supports that channel capability theory is still valid in the homogenous mobile-to-mobile channel expansion context.

This study examines how contributors with different achievement goals participate under the influence of two common motivators/demotivators on crowdsourcing platforms, namely system design features and task nature.

A free simulation experiment was conducted among undergraduate students with the use of a crowdsourcing platform for two weeks.

The results indicate that contributors with a strong performance-approach goal get better scores and participate in more crowdsourcing tasks. Contributors with a strong mastery-avoidance goal participate in fewer heterogeneous tasks.

Contributors with different achievement goals participate in crowdsourcing tasks to different extents under the influence of the two motivators/demotivators. The inclusion of the approach-avoidance dimension in the performance-mastery dichotomy enables demonstrating the influence of motivators/demotivators more specifically. This article highlights differentiation between the quality and the quantity of heterogeneous crowdsourcing tasks.

Management is advised to approach performance-approach people if a leaderboard and a point system are incorporated into their crowdsourcing platforms. Also, management should avoid offering heterogeneous tasks to mastery-avoidance contributors. System developers should take users' motivational goals into consideration when designing the motivators in their systems.

The study sheds light on habitual achievement goals, which are relatively stable in comparison to contributors' motives and states. The relationships between achievement goals and motivators/demotivators are more persistent across time. This study informs system designers' decisions to include appropriate motivators for sustained contributor participation.

Technology has dramatically changed the nature of interorganizational relationships and the ways partners interact with each other. In the new platform business model, platform technology usage seems to work as a governance mechanism to regulate operations and manage platform builder–platform participant relationships. To respond to these changes, this study aims to examine how platform technology usage in platform operations influenced the relationship quality between the platform builder and platform participants by promoting perceptions of three types of justice (procedural, distributive and informational).

The authors propose that it is through the perception of three types of justice (procedural, distributive and informational) that platform technology usage exerts its governance effect on the platform relationship. In doing this, the authors seek to answer the following two related research questions in the platform setting: How does platform technology usage drive relationship performance via different types of justice perceptions? Which type of justice affects relationship performance most effectively?

The results from a survey of 384 participant firms from two of the largest digital platforms for mobile/PC application in China reveal that platform technology usage leads to better relationship performance through enhanced perceptions of procedural, distributive, and informational justice. The positive impacts of procedural justice and distributive justice on relationship performance are greater than that of informational justice, while the impacts of procedural justice and distributive justice show no significant differences.

These findings provide novel insights into the role and mechanisms of platform technology usage in platform relationship management.

With the rapid development of the digital economy, an increasing number of digitalized two-sided platforms have deployed the tying strategy to leverage their market power from the core two-sided product to other two-sided products in the competitive market, which transforms the competition among single platforms into that among platform ecological networks. To clarify the mechanism of the formation of the digital platform ecological networks, this paper aims to analyze the expansion and stability of platform ecology by exploring the impacts of network externalities and sellers’ heterogeneity on the tying strategy of two-sided platforms.

This paper develops a game model of two-sided platforms based on Choi and Jeon (2021), which highlights the decisive influence of non-negative price constraints (NPC) on platforms’ tying motivation. Taking the operating systems market as an example, we expand from the perspective of platform service differences to relax the NPC and explore the internal logic of platform ecosystem expansion.

Platforms have an incentive to charge lower prices or even subsidize buyers when the network externalities on the sellers’ side are relatively strong. When the product is highly differentiated and heterogenous, platforms are motivated to tie to capture more buyers with a lower price and grab excess profits from sellers. Eventually, tying is able to consolidate the two-sided platform ecological networks by excluding competitors, capturing user value and deterring entry.

In order to describe the characteristics of platform ecological network more generally, this paper extends the research based on the analyses of Choi and Jeon (2021) by (1) allowing horizontal differences between tied products and (2) relaxing the NPC. Unlike Choi and Jeon (2021), this paper allows platforms to charge users of two-sided platforms at negative prices (or to subsidize them). (3) Setting simultaneous pricing in two-sided platforms. Classical two-sided market theory stresses that the presence of cross-network externalities can give rise to a “chicken and egg” problem.

Considering the emergence of e-commerce platforms and their integration into marketing channels, this paper aims to investigate how artificial intelligence (AI) resources – both technological and human – possessed by e-commerce platforms can enhance their channel power by acquiring market-based assets (relational and intellectual).

Based on resource-based theory and resource orchestration theory, the authors developed a framework tested using survey data gathered from the sellers, which incorporated six key variables: the e-commerce platform’s AI technology resources and human resources, rational and intellectual market-based assets, intraplatform competition and channel power. The analyses are performed using the regression analysis technique.

The empirical findings indicate that both technological and human AI resources are crucial in building channel power. In addition, market-based assets serve as a mediator in this relationship, while intraplatform competition moderates the effect of intellectual market-based assets on channel power negatively.

This study contributes to the existing literature by exploring how e-commerce platforms’ AI resources affect their channel power. The results offer valuable guidance to managers and researchers on optimizing AI resources to improve channel power.

This paper focuses on decision making related to the use of strategic inventory allocation in product platform design. The purpose of the paper is to present a novel approach to managing product variety by considering product and manufacturing strategy, and considering the supply chain benefits.

Discrete event simulation is used for analyzing product platform performance in terms of inventory level and throughput. Simulation parameters such as lead times and safety stock allocation are optimized by using an analytical model of strategic safety stock allocation.

The results show that strategic safety stock allocation supports product platform strategy by increasing production output, and reducing inventory level and customer order queues at a higher level of product variety.

Linking the safety stock allocation and product platform strategy facilitates simultaneous product and process design by providing the most optimum platform strategy at minimum safety stock allocation.

Strategic safety stock allocation facilitates decision making with regard to lean strategy by reducing inventory level, agile strategy by increasing the amount of product variety and outputs, and responsiveness by reducing the number of customer order queues.

The paper presents an innovative customer order decoupling point decision.

In the presence of coronavirus disease 2019 (COVID-19), due to the social distance restriction, consumers' regular consumption behaviors and patterns have been changing fundamentally. Thereafter, an innovative group buying model has emerged and developed explosively with a specific focus on consumer's location, known as community-based group buying (CGB). The purpose of this paper is to investigate the transfer mechanism of user's trust in dyadic contexts of social and commercial role-playing in the CGB program.

This study adopts an empirical research method, with an online and offline questionnaire survey, a total of 382 responses have been obtained. Then, both descriptive analysis and hierarchical regression analysis are conducted to explore the dual roles of group leader and its corresponding effects on consumers' trust (i.e. emotional trust and behavioral trust) and engagement actions (i.e. purchase and share) in the CGB program.

Results indicate that resident's trust and their perception of group leader's friend role can positively enhance their engagement actions in the CGB programs. Meanwhile, for the purpose of profit maximization, the group leader is more willing to play a friend role in transactions no matter whether the role conflict exists.

Research findings provide some managerial insights for CGB platform on the selection and training of group leaders and the incentive mechanism design.

The purpose of this paper is to build a seven‐degrees of freedom (DOF) parallel‐serial robot system which has the advantage of mechanical novelty and simplicity compared with the existing platforms, and to share the experience of converting a popular motion base to an industrial robot for use in full‐mission tank training processes of three armored arms.

By studying the concept of the robot system, a novel parallel‐serial robot with seven DOF driven by electrical servo motors is built. And the transmission modules and Hooke joints are explored and designed in detail. Then the inverse kinematics based on coupling compensation and time‐jerk synthetic optimization methods for trajectory planning of the simulator are presented and further discussed in order to satisfy the requirements of high stability and perfect performance. In advance, the feasibility and applicability of this triune parallel‐serial robot system are verified.

A prototyped test shows that the performance of the system is of a satisfaction with real‐time tracking any trajectories given by the visual system smoothly. Finally, the characteristics of the robot system are realized and verified by experiments and an industrial application.

The triune full‐mission tank training simulator developed in this paper has been used in the military industry and it has a great potential application.

This successful usage of the novel and simple parallel robot system in the military industry expands the range of its applications in real‐life task more operators training. And the proposal methods of inverse kinematics based on coupling compensation and trajectory planning enhanced the theoretical research of the parallel robot.