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Big data analytics (BDA) and machine learning (ML) can be used to identify the influencing factors of online service supply chains (OSSCs) and can help in the formulation of optimal pricing strategies. This paper analyzes the influencing factors of customer online shopping from the demand-side perspective and formulates optimal pricing strategies from the supply-side perspective.

This paper uses ML and the Stackelberg game approach to discuss OSSC management. ML's feature selection algorithm is used to identify the important influencing factors of 12,330 customers' online shopping intention data using four different classifiers. The Stackelberg game approach is used to analyze the pricing strategies of integrators and suppliers in OSSCs.

First, the feature selection algorithm can improve the efficiency of optimization in big data samples of OSSCs. Second, the level of visualization and the quality of information (page value) will affect the purchase behavior of customers. Finally, the relationship between the optimal pricing and the level of visualization is obtained through the Stackelberg game approach.

This paper reveals the phenomenon of “mystery customers,” and the results of this paper can provide insights and suggestions regarding the decision-making behavior of integrators and suppliers in OSSC management.

Considering customer behavior intention, this paper uses a data-driven method to explore the influencing factors and pricing strategies of OSSCs. The empirical results enrich the existing OSSC management research, proposing that the level of product visualization and information quality plays an important role in OSSCs.

The Internet of Things (IoT) platform empowers the digital transformation of the manufacturing industry by providing information technology services. Simultaneously, it enters the market by offering smart products to consumers. In light of different service fee scenarios, this article explores the optimal decision-making for the platform. It investigates the pricing models and entry decisions of IoT platforms.

In this study, we have formulated a game-theoretic model to scrutinize the influence of the IoT platform ventured into the smart device market on the pre-existing suppliers operating under subscription-based and usage-based pricing agreements.

Our outcome shows that introducing an IoT platform’s smart device has a differential effect on manufacturers depending on their contract type. Notably, our research indicates that introducing the platform’s own smart device within the subscription-based model does not negatively impact the profitability of incumbent manufacturers, so long as there is a noticeable discrepancy in the quality of the smart devices. However, our findings within the usage-based model demonstrate that despite the variance in smart device quality differentiation, the platform’s resolution to launch their device and impose their pricing agreements adversely affects established manufacturers. Additionally, we obtain valuable Intel regarding the platform’s entry strategies and contractual inclinations. We demonstrate that the platform is incentivized to present its smart device when reasonable entry costs remain. Furthermore, the platform prefers subscription-based contracts when the subscription fee is relatively high in non-platform entry and entry cases.

These findings hold significant practical implications for firms operating in an IoT-based supply chain.

An exploratory sample of 114 personal home pages, drawn from a home page directory available on the World Wide Web (People Page Directory: http://www.peoplepage.com), was analysed to detect patterns and trends in home page content and design. Covered in the analysis were types of informational content included in the home pages; internal organisation and structure of the content, including type and number of hypertext links; miscellaneous content elements, such as ‘sign guestbook’ and number of hits to the page; and physical design features such as photos, motion and audio elements. Metaphors used in the design of the pages and degree of self‐revelation were also considered. The home pages displayed a great variety of content and of specific types of formatting within broader formatting approaches. While some content elements were quite popular, none of them — not even name — was found on all home pages. Nor did the pages evidence reliance on any single dominant metaphor, such as home page as ‘home’ in the sense of domicile. It appears that though certain features may be frequently found in it, the personal home page as a social institution is still very much under development.

This study aims to investigate the effects of irregular groove textures on the friction and wear performance of sliding contact surfaces. These textures possess multiple depths and asymmetrical features. To optimize the irregular groove texture structure of the sliding contact surface, an adaptive genetic algorithm was used for research and optimization purposes.

Using adaptive genetic algorithm as an optimization tool, numerical simulations were conducted on surface textures by establishing a dimensionless form of the Reynolds equation and setting appropriate boundary conditions. An adaptive genetic algorithm program in MATLAB was established. Genetic iterative methods were used to calculate the optimal texture structure. Genetic individuals were selected through fitness comparison. The depth of the groove texture is gradually adjusted through genetic crossover, mutation, and mutation operations. The optimal groove structure was ultimately obtained by comparing the bearing capacity and pressure of different generations of micro-convex bodies.

After about 100 generations of iteration, the distribution of grooved textures became relatively stable, and after about 320 generations, the depth and distribution of groove textures reached their optimal structure. At this stage, irregular texture structures can support more loads by forming oil films. Compared with regular textures, the friction coefficient of irregular textures decreased by nearly 47.01%, while the carrying capacity of lubricating oil films increased by 54.57%. The research results show that irregular texture structures have better lubrication characteristics and can effectively improve the friction performance of component surfaces.

Surface textures can enhance the friction and lubrication performance of metal surfaces, improving the mechanical performance and lifespan of components. However, surface texture processing is challenging, as it often requires multiple experimental comparisons to determine the optimal texture structure, resulting in high trial-and-error costs. By using an adaptive genetic algorithm as an optimization tool, the optimal surface groove structure can be obtained through simulation and modeling, effectively saving costs in the process.

This study aims to examine the components and evolution of the Chinese wine festival market using the Dalian International Wine and Dine Festival (DIWDF) as a case study.

Adopting a longitudinal approach, survey data were collected from attendees of the first, fifth and seventh DIWDF in 2012, 2016 and 2018, respectively. Cluster analysis segmented attendees by wine and festival experience and consumption features. Comparative analysis was conducted to examine segment differences by demography, festival motivation, satisfaction and intention. Changes in segments over time were examined across the three times.

The following three clusters were identified: “wine-novice fest-newbies,” “occasional drinker fest-goers” and “wine-lover fest-enthusiasts.” Over the study period, the proportion of “wine-lover fest-enthusiasts” increased significantly while the percentages of the other two segments decreased, demonstrating the evolution of the Chinese wine festival market and their consumer impacts.

This study offers straightforward indicators of market value via consumption features for both wine businesses and festival organizers. The characteristics of the segments and their inter-linkage have important implications for developing product mix, targeting strategies, festival service design and market development.

This is the first known empirical research globally to investigate relationships among market segments both horizontally (differences between segments) and vertically (development over time) and to incorporate both wine- and festival-related consumption features.

The objective of this research work is to study the artificial intelligence (AI)-based product benefits and problems of the agritech industry. The research variables were developed from the existing review of literature connecting to AI-based benefits and problems, and 90 samples of primary data from agritech industry managers were gathered using a survey of a well-structured research questionnaire. The statistical package of IBM-SPSS 21 was utilized to analyze the data using the statistical techniques of descriptive and inferential statistical analysis. Results show that better information for faster decision-making has been ranked as the topmost AI benefit. This implies that the executives of agritech units have a concern about the quality of decisions they make and resistance to change from employees and internal culture has been ranked as the topmost AI problem.

The purpose of this paper is to summarize the research of construction conflict from 1991 to 2020 and propose research directions for future scholarly work. During the recent decades, it is widely accepted that construction conflict is inevitable, and conflict management has become an important component of project management. However, few works were done to map the global study in this field, there is limited review that evaluates the current stage of construction conflict research.

This study adopted a holistic literature review approach that incorporates bibliometric search and scientometric analysis. A total of 698 bibliographic records from the Web of Science core collection database were collected for the scientometric analysis. CiteSpace5.7 was adopted for the science mapping purpose in this study.

Through co-authorship analysis, co-word analysis and co-citation analysis, influential scholars and journals are identified. Several research trends are highlighted according to the scientometric analyses of the construction conflict topics. For example, the application of simulation and algorithms to the study of construction conflict management systems.

Construction is a resource-intensive, multi-participant and multi-targeted industry. Conflicts always exist in the whole life cycle of construction projects, it is important for industry practitioners to be updated of the latest movement and progress of the academic research.

This study contributed to the body of knowledge in construction conflict and bridge the research gap in the thorough review of previous research work.

Nested within institutional theory and the political economy perspective, this study aims to examine Chinese outward foreign direct investments (OFDI)-supporting organizations and fostering mechanisms for its SMEs in Europe’s largest economy, Germany.

The authors conduct a multiple-case study to present rich insights from elite interviews with representatives of Chinese and German governmental organizations, intermediary parties and specialized OFDI consultants. In addition, the authors analyze secondary data such as presentations, websites, brochures, social media and recent Chinese OFDI policies for SMEs. The findings are triangulated by interviewing business owners and senior executives of seven Chinese SMEs that have invested in Germany.

Cooperating with Germany’s federal government, China’s ministries implemented an effective OFDI support network in Germany, which connects and benefits both economies. This includes Chinese governmental organizations, privately-held national champions, German–Chinese business associations and linked intermediary parties. These organizations support SMEs through four main mechanisms: networking and information, mutually beneficial knowledge transfer between innovation partners, lobbying for potential cooperation and an objective picture of Chinese OFDI and facilitating investment services.

This study advances OFDI theory and contributes to the growing discussion on the internationalization of Chinese SMEs by shedding light on China’s OFDI support organizations and mechanisms in the German market. The study also offers practical contributions. Understanding better how governments can spur internationalization is vital, as it determines the effectiveness of policymaking and fosters international mutual understanding, cultural exchange and firm growth and innovation (Ahlstrom, 2010), and hence ultimately contributes positively to society. Moreover, knowing the specific OFDI support organizations and measures China is currently adopting can serve as a helpful orientation for Chinese entrepreneurs who plan to invest in Germany.

Diffusion of a new technology and its required infrastructure is a complex process involving various adaptive decision makers interacting with each other, and this is extremely true in diffusion of alternative fuel vehicles. The purpose of this paper is to explore the dynamics of alternative fuel vehicles/infrastructure diffusion through a case study about the diffusion of NGVs (natural gas vehicles) in Shanghai, China.

This paper first provides a case study of the adoption of NGVs in Shanghai; then the major infrastructure and economic indicators, obstacles in the market penetration process are analyzed. Finally, an agent‐based model is established to simulate the diffusion of NGVs in Shanghai.

The findings show that several factors limited the adoption of NGV in Shanghai. The initial distribution of refueling stations can be critical to determining whether the technology/infrastructure system survives to become mature and successful. Therefore, the strong support offered to consumers and equipment suppliers from government is important for the market penetration. These findings are also applicable to other alternative fuel vehicles such as hydrogen.

Little real‐world observations have been carried out on the dynamics of alternative fuel vehicles/infrastructure. The paper can enrich people's understanding about the dynamics of diffusion of alternative fuel vehicles/infrastructure and gives policy implications for initializing and keeping a successful demonstration project.

The purpose of this paper is to assess the adoption of internet of things (IoT) element with the view of increasing usage so that benefits of convenience, increased performance and timely completion of work can be improved. This research was conducted so that there can be increase in the usage of IoT elements for construction performance and sustainability.

The study adopted survey design and various construction professionals were used to assessing the level of adoption of IoT elements. Convenience sample was used by distributing the structured questionnaire to registered professionals. Mean score, bar chart, Kruskal–Wallis H test, one-sample t-test and Shapiro–Wilk were used for analyzing the data gathered.

The findings revealed that wireless fidelity, visualization, wireless sensor networks, Bluetooth, electronic product code and internet protocol are the most adopted element of IoT in the industry. The study also shows that there are areas where there is no significance attached by construction professionals in the usage of IoT elements. These are data storage and analytics, barcode, Zigbee, gateway, near field communication and actuators. It is recommended that less significant areas can be improved through training and educating professionals about the whole concept of IoT and other design professionals. When the importance of IoT elements are understood it will help in the level of adoption.

This paper highlights the possible ways of increasing the adoption of IoT elements with a view to achieving better usage for convenience, high productivity of workers and easy access to information.