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Self-crosslinked long fluorocarbon acrylate polymer latex has good hydrophobic and oleophobicity, weather resistance, aging resistance, stability and other excellent properties, which make the polymer be widely used in coatings, dyes, adhesives and other products. The purpose of this study is to prepare self-crosslinked long fluorocarbon acrylate polymer latex via semi-continuous seeded emulsion technology and carry out comparative study on two different cross-linked monomers.

Methyl methacrylate (MMA) and butyl acrylate (BA) were used as the main monomers, dodecafluoroheptyl methacrylate (DFMA) as the fluoromonomer, hydroxypropyl methacrylate (HPMA) and N-methylol acrylamide (NMA) as cross-linked monomers, and 1-allyloxy-3–(4-nonylphenol)-2-propanol polyoxyethylene (10) ether (ANPEO10) and 1-allyloxy-3–(4-nonylphenol)-2-propanol polyoxyethylene (10) ether ammonium sulfate (DNS-86) as compound emulsifiers via the semicontinuous-seeded emulsion polymerization.

The properties of the polymer emulsions, which are prepared with two different cross-linked monomers, are compared and discussed, and it is concluded that HPMA is more suitable for the preparation of self-crosslinked polymer emulsions. The formula of the polymer latex is ANPEO10: DNS-86 = 1:1, and the mass ratio of the monomers used in the polymer is MMA: BA: DFMA: HPMA = 14.40:14.40:0.60:0.60.

Self-crosslinked long fluorocarbon acrylate polymer latex can be used in many fields such as coatings, dyes, adhesives and other products.

The self-crosslinked long fluorocarbon acrylate polymer latex is prepared by mixing the nonionic emulsifier ANPEO10 and the anionic emulsifier DNS-86 when potassium persulfate is used as the thermal decomposition initiator and the semicontinuous-seeded emulsion technology is adopted and the comparative study on two different cross-linked monomer is carried out, which is not reported in the open literatures.

This study investigates how artificial intelligence (AI) chatbots persuade customers to accept their recommendations in the online shopping context.

Drawing on the elaboration likelihood model, this study establishes a research model to reveal the antecedents and internal mechanisms of customers' adoption of AI chatbot recommendations. The authors tested the model with survey data from 530 AI chatbot users.

The results show that in the AI chatbot recommendation adoption process, central and peripheral cues significantly affected a customer's intention to adopt an AI chatbot's recommendation, and a customer's cognitive and emotional trust in the AI chatbot mediated the relationships. Moreover, a customer's mind perception of the AI chatbot, including perceived agency and perceived experience, moderated the central and peripheral paths, respectively.

This study has theoretical and practical implications for AI chatbot designers and provides management insights for practitioners to enhance a customer's intention to adopt an AI chatbot's recommendation.

1. The study investigates customers' adoption of AI chatbots' recommendation.

2. The authors develop research model based on ELM theory to reveal central and peripheral cues and paths.

3. The central and peripheral cues are generalized according to cooperative principle theory.

4. Central cues include recommendation reliability and accuracy, and peripheral cues include human-like empathy and recommendation choice.

5. Central and peripheral cues affect customers' adoption to recommendation through trust in AI.

6. Customers' mind perception positively moderates the central and peripheral paths.

The study investigates customers' adoption of AI chatbots' recommendation.

The authors develop research model based on ELM theory to reveal central and peripheral cues and paths.

The central and peripheral cues are generalized according to cooperative principle theory.

Central cues include recommendation reliability and accuracy, and peripheral cues include human-like empathy and recommendation choice.

Central and peripheral cues affect customers' adoption to recommendation through trust in AI.

Customers' mind perception positively moderates the central and peripheral paths.

The conflict between institutionalism and neoclassicism in the 20th century has been investigated by scholars over the years. Many of them believe that in the postwar period, neoclassicism triumphed while institutionalism largely disappeared. The present chapter takes a very different view. The late 20th century represents a broad synthesis of neoclassical and institutional themes in a methodology we call pragmatic empiricism. That approach combines the mathematical model building and theoretical formalism of neoclassical economics with the institutional economist’s data-driven statistical analysis and concern for developing institutional forms. We use as a case study the history of American locational economics from the 1930s to the present. The mixing of institutional and neoclassical themes is quite evident in the work of three young scholars at Harvard who effectively initiated American locational economics. In the postwar period, we find a series of outstanding, well-published papers that capture the spirit of the “founders.” These papers do use more modeling, but they also focus on major institutional developments. A broader review of locational works is consistent with the pragmatic empiricism label. The history of locational economics supports the claim that institutionalism, far from disappearing, continues to provide fundamental questions and techniques for modern pragmatic empiricism.

One of the most neglected sources of energy loss is streetlights that generate too much light in areas where it is not required. Energy waste has enormous economic and environmental effects. In addition, due to the conventional manual nature of operation, streetlights are frequently seen being turned ‘ON’ during the day and ‘OFF’ in the evening, which is regrettable even in the twenty-first century. These issues require automated streetlight control in order to be resolved. This study aims to develop a novel streetlight controlling method by combining a smart transport monitoring system powered by computer vision technology with a closed circuit television (CCTV) camera that allows the light-emitting diode (LED) streetlight to automatically light up with the appropriate brightness by detecting the presence of pedestrians or vehicles and dimming the streetlight in their absence using semantic image segmentation from the CCTV video streaming. Consequently, our model distinguishes daylight and nighttime, which made it feasible to automate the process of turning the streetlight ‘ON’ and ‘OFF’ to save energy consumption costs. According to the aforementioned approach, geo-location sensor data could be utilised to make more informed streetlight management decisions. To complete the tasks, we consider training the U-net model with ResNet-34 as its backbone. Validity of the models is guaranteed with the use of assessment matrices. The suggested concept is straightforward, economical, energy-efficient, long-lasting and more resilient than conventional alternatives.

This chapter provides an overview of the strategic implications of chatbot use and implementation, including potential applications in marketing, and factors affecting customer acceptance. After presenting a brief history and a classification of conversational artificial intelligence (AI) and chatbots, the authors provide an in-depth review at the crossroads between marketing, business, and human–computer interaction, to outline the main factors that drive users' perceptions and acceptance of chatbots. In particular, the authors describe technology-related factors and chatbot design characteristics, such as anthropomorphism, gender, identity, and emotional design; context-related factors, such as the product type, task orientation, and consumption contexts; and users-related factors such as sociodemographic and psychographic characteristics. Next, the authors detail the strategic importance of chatbots in the field of marketing and their impact on consumers' perceived service quality, satisfaction, trust, and loyalty. After discussing the ethical implications related to chatbots implementation, the authors conclude with an exploration of future opportunities and potential strategies related to new generative AI technologies, such as ChatGPT. Throughout the chapter, the authors offer theoretical insights and practical implications for incorporating conversational AI into marketing strategies.

Enterprises build online product community to expect users to contribute: opinion sharing (content contribution) and product consumption (product contribution). Previous literature rarely focused on both. The purpose of this paper is to explain user contribution mechanism by identifying content contribution and product contribution.

This research chose Xiaomi-hosted online product community (bbs.xiaomi.cn) and Huawei-hosted online product community (club.huawei.com) where users can freely share ideas and buy products at the same time. Data were crawled from 109,665 community users to construct dependent variable measurement, and 611 questionnaires were used to verify research hypotheses.

The results indicate that both cognitive needs and personal integration needs have a significant positive impact on browse behavior; social integration needs and hedonic needs have a significant positive impact on content contribution behavior. Browse behavior not only directly affects but also indirectly influences product contribution through content contribution behavior.

Findings of this research provide community managers with useful insights into the relationship between content contribution and product contribution.

This study explains the formation mechanism of user product contribution and reveals the relationship between user content contribution and product contribution in online product community. This paper provides a different way of theorizing user contributions by incorporating uses and gratifications theory into the “Motivation-Behavior-Result” framework.

This research aims to present a novel cooperative control architecture designed specifically for roads with variations in height and curvature. The primary objective is to enhance the longitudinal and lateral tracking accuracy of the vehicle.

In addressing the challenges posed by time-varying road information and vehicle dynamics parameters, a combination of model predictive control (MPC) and active disturbance rejection control (ADRC) is employed in this study. A coupled controller based on the authors’ model was developed by utilizing the capabilities of MPC and ADRC. Emphasis is placed on the ramifications of road undulations and changes in curvature concerning control effectiveness. Recognizing these factors as disturbances, measures are taken to offset their influences within the system. Load transfer due to variations in road parameters has been considered and integrated into the design of the authors’ synergistic architecture.

The framework's efficacy is validated through hardware-in-the-loop simulation. Experimental results show that the integrated controller is more robust than conventional MPC and PID controllers. Consequently, the integrated controller improves the vehicle's driving stability and safety.

The proposed coupled control strategy notably enhances vehicle stability and reduces slip concerns. A tailored model is introduced integrating a control strategy based on MPC and ADRC which takes into account vertical and longitudinal force variations and allowing it to effectively cope with complex scenarios and multifaceted constraints problems.

This study aims to investigate the effect of the dynamics and potential of the board of directors on investment efficiency and the comparability of financial information in companies listed on the Tehran Stock Exchange.

The number of observations for this study includes 1,218 observations from companies listed on the Tehran Stock Exchange during 2014–2020. The authors used econometric statistical methods such as multiple linear regression, the Chow and Hausman test and the Kendall correlation coefficient using Eviews software to conduct the research. To measure the board’s effectiveness, two variables are used, including board dynamics and potential.

The results showed a positive and significant relationship between dynamics, board potential and investment efficiency. Also, no significant relationship was observed between the board dynamics and the comparability of financial information. Finally, a positive and significant relationship exists between the board’s potential and the comparability of financial information.

The importance of this research is the use of board proxies, including the dynamics and potential of the board. In addition, other variables of board characteristics, such as size, independence, ownership and gender, and the relationship between these variables with investment efficiency and comparability of financial information, have been examined in this study.

Improving digital work experience is critical for the job performance of individuals and the competitiveness of organizations due to their increasing use. This paper investigates how organization support affects the digital work experience of individuals differently depending on their levels of information technology (IT) identity.

Drawing upon the IT identity literature and the conservation of resources (COR) theory, a conceptual model is developed, tested and validated using the data collected in Australia through an experimental design in which IT identity is manipulated.

This study reveals a nuanced impact of organization support on shaping digital work experience. Specifically, it finds that technical support is more effective in improving the digital work experience of individuals with a high level of IT identity, whereas well-being support is more effective in enhancing the digital work experience of individuals with a low level of IT identity.

This research contributes to the IT identity literature by introducing a novel experimental design to manipulate IT identity in the digital work context. It also contributes to the digital work literature by introducing a resource perspective for identifying well-being support, technical support and IT identity as the key resources in shaping digital work experience and calling for attention to IT identity as a boundary condition on the effectiveness of organization support. The findings can help organizations formulate better strategies and policies to improve digital work experience by providing tailored support to individuals with different levels of IT identity.

This study aims to focus on the surface mount technology (SMT) mass production process of Sn-9Zn-2.5Bi-1.5In solder. It explores it with some components that will provide theoretical support for the industrial SMT application of Sn-Zn solder.

This study evaluates the properties of solder pastes and selects a more appropriate reflow parameter by comparing the microstructure of solder joints with different reflow soldering profile parameters. The aim is to provide an economical and reliable process for SMT production in the industry.

Solder paste wettability and solder ball testing in a nitrogen environment with an oxygen content of 3,000 ppm meet the requirements of industrial production. The printing performance of the solder paste is good and can achieve a printing rate of 100–160 mm/s. When soldering with a traditional stepped reflow soldering profile, air bubbles are generated on the surface of the solder joint, and there are many voids and defects in the solder joint. A linear reflow soldering profile reduces the residence time below the melting point of the solder paste (approximately 110 s). This reduces the time the zinc is oxidized, reducing solder joint defects. The joint strength of tin-zinc joints soldered with the optimized reflow parameters is close to that of Sn-58Bi and SAC305, with high joint strength.

This study attempts to industrialize the application of Sn-Zn solder and solves the problem that Sn-Zn solder paste is prone to be oxidized in the application and obtains the SMT process parameters suitable for Sn-9Zn-2.5Bi-1.5In solder.