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The purpose of this study is to draw on the updated information system success model, perceived value and new product novelty to identify the factors that may influence user satisfaction and loyalty with paid knowledge platforms.

The authors used the survey method to collect 540 valid sample data. The structural equation modelling (SEM) technique was employed to test the proposed research model and hypotheses.

The findings suggested that system, information and service quality significantly affected the perceived utilitarian value, while service quality and new product novelty had significant impact on perceived hedonic value. Besides, both the perceived utilitarian value and the perceived hedonic value had a significant effect on user satisfaction and further significantly impacted user loyalty. The authors also found user differences, including gender, education level and use frequency, which had a significant influence on perceived utilitarian value, perceived hedonic value and user loyalty.

The results can help researchers and practitioners better understanding the factors that influence user satisfaction and loyalty with paid knowledge platforms.

The authors applied the theories of perceived value, new product novelty and user loyalty to the domain of paid knowledge platforms and explored the factors influencing the user satisfaction and loyalty to paid knowledge platforms.

This study aims to examine the factors influencing undergraduates' intention to use university digital libraries by integrating the information system success model and affinity theory.

Based on the 265 valid responses gathered through a survey, the structural equation modelling (SEM) technique was employed to test the research model and hypotheses.

The results indicated that system quality and digital libraries (DLs)' affinity significantly affect undergraduates' user satisfaction. However, information quality and service quality does not. User satisfaction has significant impact on undergraduates' intention to use university digital libraries.

Librarians and service providers should focus on enhancing the system quality of digital library and DLs' affinity, to improve the undergraduates' user satisfaction, further motivating undergraduates to use university digital libraries.

The information system success model is enriched by affinity as an additional construct.

The purpose of this study is to explore the information needs and behaviors of Chinese first-time mothers from the perspective of information journey theory.

This study uses the popular coding language Python to write a program to extract 366 posts published by first-time mothers in the Babytree community of China's largest maternal and infant platform. Content analysis is used to analyze and encode the collected data.

This study summarizes the information needs of first-time mothers in China specifically, which includes six aspects of health, pregnancy care, postpartum parenting, socialization, self-actualization, and entertainment. Then, based on its hierarchical and stage characteristics, more flexible information needs matrix for Chinese first-time mothers has been developed to reflect their changing 15 types of information needs more fully. Finally, it constructs the information journey model of Chinese first-time mothers including five stages.

This is the first time that information journey theory has been applied to the research on information needs and behaviors of first-time mothers. The authors have also further expanded the information seeking and acquisition phases and found new gaps in the phases to further refine the information journey model. This study can help us better understand the online information needs and behaviors of Chinese first-time mothers and provide support for organizations and online health community managers to develop new information services or improve the quality of existing services.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-10-2021-0538.

The purpose of this study is to explore the factors impacting information poverty in western China and investigate to what extent these determinants contribute to information poverty in these areas.

Structural equation modeling (SEM) technique was used to analyze 232 valid responses collected from a survey to examine the research model and hypotheses in this study.

The results indicate that information literacy, information supply and information and communication technologies (ICTs) positively and significantly affect information poverty, while social prejudice and information orientation had no significant effects on information poverty.

Public libraries, government departments and other institutions should pay attention to the significant impact of information literacy, information supply and ICTs on information poverty and formulate corresponding systems and policies to alleviate or reduce information poverty.

In the past, few studies have focused on information poverty in western China and most of the existing research on information poverty adopts qualitative research methods, such as interview, systematic literature review and so on, while quantitative research is rare. In addition, the focus of these research studies was on one or two aspects, and a few of them can systematically study the influencing factors of information poverty. Inspired by the theories of information literacy, social prejudice and information poverty, this study comprehensively used a questionnaire survey and SEM to investigate the influences of information literacy, social prejudice, information supply, information orientation and ICTs on information poverty.

This paper aims to explore the switching intention and behaviour of cloud storage services (CSS) individual users in China by integrating the variables of switching cost and habit into the expectation disconfirmation theory.

Based on 419 valid responses, structural equation modelling was used to examine the research model.

The results indicated that perceived usefulness and expectation disconfirmation have a positive and negative effect on user satisfaction, respectively. While expectation disconfirmation has a negative impact on perceived usefulness, user satisfaction positively affects users’ habit and switching cost. At the same time, switching intention is affected significantly and negatively by perceived usefulness, user satisfaction, as well as switching cost, where in switching intention and habit can commendably predict switching behaviour. The results can guide for CSS providers on how to successfully retain users in the competitive CSS market.

Previous researches have investigated the effects of perceived usefulness, switching cost and user traits on CSS adoption and continuance intention, as well as behaviour; they neglected the antecedents of switching cost and the effect of user habit on them. Additionally, relatively few studies have been devoted to an empirical examination of the switching behaviour from a particular CSS product to its rival products at the individual user level. This research tries to fill these gaps.

The purpose of this study is to explore the effects of recommendation algorithm, product reputation, new product novelty, privacy concern and privacy protection behavior on users’ satisfaction and continuance intention to use short-form video application (APP).

Based on the existing theories, the research model of this study was developed and 445 valid data were collected through a questionnaire survey. The partial least squares structural equation modeling (PLS-SEM) was employed for data analysis to test the research model and hypotheses.

The results reveal that the recommendation algorithm has a significant positive effect on user satisfaction, new product novelty and privacy concern. The influence of recommendation algorithm on privacy concern is negatively moderated by product reputation. Privacy concern has a significant and positive impact on privacy protection behavior, and privacy protection behavior has a significant and positive impact on user satisfaction. New product novelty also has significant impact on user satisfaction.

This study is one of the earliest studies to incorporate recommendation algorithm as a construct into the college students’ continuance intention to use short-form video APP. The influence of reputation as a moderator variable on the relationship between algorithm and privacy concerns is also investigated.

The purpose of this paper is to propose an effective and economical management platform to realize real-time tracking and tracing for prepackaged food supply chain based on Internet of Things (IoT) technologies, and finally ensure a benign and safe food consumption environment.

Following service-oriented architecture, a flexible layered architecture of tracking and tracing platform for prepackaged food is developed. Besides, to reduce the implementation cost while realizing fine-grained tracking and tracing, an integrated solution of using both the QR code and radio-frequency identification (RFID) tag is proposed. Furthermore, Extensible Markup Language (XML) is adopted to facilitate the information sharing among applications and stakeholders.

The validity of the platform has been evaluated through a case study. First, the proposed platform is proved highly effective on realizing prepackaged food tracking and tracing throughout its supply chain, and can benefit all the stakeholders involved. Second, the integration of the QR code and RFID technologies is proved to be economical and could well ensure the real-time data collection. Third, the XML-based method is efficient to realize information sharing during the whole process.

The contributions of this paper lie in three aspects. First, the technical architecture of IoT-based tracking and tracing platform is developed. It could realize fine-grained tracking and tracing and could be flexible to adapt in many other areas. Second, the solution of integrating the QR code and RFID technologies is proposed, which could greatly decrease the cost of adopting the platform. Third, this platform enables the information sharing among all the involved stakeholders, which will further facilitate their cooperation on guaranteeing the quality and safety of prepackaged food.

The purpose of this study is to explore mitigation measures for cash flow interruption during the epidemic and provide decision support to ensure the regular operation and robustness of the supply chain (SC).

Considering the scenarios of production capacity and demand disruption during the epidemic, the authors adopt system dynamics (SD) to construct a three-echelon SC financial system consisting of a core manufacturer, a capital-constrained retailer and the customer. In different interruption scenarios, through the decision adjustments of stakeholders, the differences in performance are compared to explore solutions for SC robust optimization.

The results show that partial credit guarantee (PCG) could solve cash flow interruption and maintain the regular operation of the SC. During epidemic, with the product price increases, the revenue of stakeholders and the robustness are generally negatively correlated. But when the manufacturer's production capacity is fully interrupted, increasing product price is the right decision for the retailer and could simultaneously promote performance and robustness.

This paper primarily focuses on the PCG under the cash flow interruption caused by epidemics. The authors adopt the supply chain finance (SCF) theory and SD method to supplement and expand existing research on interruption management of SC. It is a pioneering study to explore the robustness of the SC financial system under disruptions.

The sensorless external force estimation of robot manipulator can be helpful for reducing the cost and complexity of the robot system. However, the complex friction phenomenon of the robot joint and uncertainty of robot model and signal noise significantly decrease the estimation accuracy. This study aims to investigate the friction modeling and the noise rejection of the external force estimation.

A LuGre-linear-hybrid (LuGre-L) friction model that combines the dynamic friction characteristics of the robot joint and static friction of the drive motor is proposed to improve the modeling accuracy of robot friction. The square root cubature Kalman filter (SCKF) is improved by integrating a Sage Window outer layer and a nonlinear disturbance observer (NDOB) inner layer. In the outer layer, Sage Window is integrated in the square root Kalman filter (W-SCKF) to dynamically adjust noise statistics. NDOB is applied as the inner layer of W-SCKF (NDOB-WSCKF) to obtain the uncertain state variables of the state model.

A peg-in-hole contact experiment conducted on a real robot demonstrates that the average accuracy of the estimated joint torque based on LuGre-L is improved by 4.9% in contrast to the LuGre model. Based on the proposed NDOB-WSCKF, the average estimation accuracy of the external joint torque can reach up to 92.1%, which is improved by 4%–15.3% in contrast to other estimation methods (SCKF and NDOB).

A LuGre-L friction model is proposed to handle the coupling of static and dynamic friction characteristics for the robot manipulator. An improved SCKF is applied to estimate the external force of the robot manipulator. To improve the noise rejection ability of the estimation method and make it more resistant to unmodeled state variable, SCKF is improved by integrating a Sage Window and NDOB, and a NDOB-WSCKF external force estimator is developed. Validation results demonstrate that the accuracy of the robot dynamics model and the estimated external force is improved by the proposed method.

Based on the context of the Internet of Things (IoT), the territorial public emergency supplies will be networked, platform-based management, unified emergency dispatch. The problem of supplies dispatching in the “last kilometer” of emergency is solved, and the supplies needed in the disaster area are promptly delivered to the hands of the victims so that they can quickly be rescued after the disaster and to save valuable time for rapid rescue, which can greatly decrease casualties and property losses. This paper aims to discuss these issues.

By analyzing the shortage of existing emergency supplies dispatching research and taking all factors such as disaster area demand, social reserve, road conditions, mode of transport, loading limit, disaster area satisfaction rate and road capacity into consideration under the background of IoT, a variety of the territorial emergency supplies dispatching model with more rescue points, more affected areas are constructed. The objective function of the model is to aim in finding the shortest rescue time, giving the solution algorithm, and finally simulating the simulation case.

Based on the context of the IoT, the territorial public emergency supplies will be networked, platform-based management, unified emergency dispatch. Considering factors such as road conditions, modes of transport and road capacity, the authors construct a number of emergency rescue plans, multiple disaster scenarios and various emergency supplies dispatching models. The authors simulate the situation through simulation cases with the shortest time being the ultimate goal. The problem of supplies dispatching in the “last kilometer” of emergency is solved, and the supplies needed in the disaster area are promptly delivered to the hands of the victims so that they can quickly be rescued after the disaster and to save valuable time for rapid rescue, which can greatly decrease casualties and property losses.

This paper provides little research on the dispatch of emergency supplies. The problems of direct dispatch from the rescue point to the affected area and dispatch of supplies without relying on the arrival of emergency supplies at the rear are addressed. Therefore, this study does not focus on the arrival of emergency supplies at the rear but on direct dispatching issues during territorial public emergency supplies from the rescue point to the disaster point.