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This paper aims to examine the optimal sourcing strategies and pricing decisions of competing toy manufacturers and to discuss how manufacturers’ decisions are impacted by competition.

The authors consider a single-period model to characterise the competition between two competing toy manufacturers. Both of them are free to choose between virgin material and recycled material. The authors consider two types of consumers: sensitive consumers who are concerned about product safety and prefer the toy made of virgin material and insensitive consumers who do not care what material is used in the toy. The competing manufacturers play a Cournot competition.

The results reveal a special case of a win-win situation for both the manufacturer and the consumer. In addition, an increasing number of sensitive consumers does not always raise the price of virgin-material toys.

The authors derive the manufacturer’s equilibrium sourcing strategies, corresponding market-clearing prices and profits obtained.

The paper investigates how toy manufacturers’ optimal sourcing strategies are impacted by competition, considering market segments.

This paper aims to study the impact of manufacturer’s upgrading strategy of durable products on the retailer’s decision on trade-in program and her decision on the secondary market.

This paper develops a channel that consists of a manufacturer and a retailer, where the manufacturer releases an upgraded product, and the retailer introduces a trade-in program for consumers, simultaneously, decides whether to enter the secondary market. These approaches are modeled through Stackelberg game.

This paper reveals that the optimal conditions for manufacturer to release upgraded products and retailer to resell used products in the secondary market, and it reveals that under what conditions it is profitable for retailer to enter the secondary market under product upgrade levels.

If the manufacturer’s upgrade level is low, it is profitable for the retailer to enter the secondary market. However, if the manufacturer’s upgrade level is high, it is unprofitable for the retailer to enter the secondary market.

In this paper, the active secondary market, upgrading of new products, consumer market segmentation and especially, the upgrade degree of new products as a function of consumer demand are considered simultaneously.

Opaque selling has become popular among service providers in recent years. Although many researchers have investigated the optimality of opaque selling for service providers focusing on heterogeneous consumers, one question remaining unexplored is how the service providers’ optimal decisions are impacted by competitive intensity in a heterogeneous market. This paper aims to determine the conditions under which opaque selling is optimal for competing service providers.

The paper takes a Hotelling model to characterize the competition between two service providers. The authors also consider the interaction between the service providers and intermediary. Service providers act as game leaders and determine whether they should cooperate with the intermediary to introduce the opaque service.

The authors find that two competing service providers do not always benefit from opaque selling in a heterogeneous market consisting of leisure and business consumers, and the competitive intensity plays a significant role in the service providers’ decision optimization. Opaque selling allows service providers to acquire more profit in a highly competitive market or when the market contains a large proportion of leisure consumers. Otherwise, it is optimal for service providers without introducing the opaque selling.

The paper examines the optimality of opaque selling for competing service providers, and provides the suggestions to optimize the service providers’ decisions.

The paper investigates how the service providers’ optimal decisions are impacted by competitive intensity, considering the interaction between the service providers and intermediary.

The purpose of this paper is to investigate the effect of user’s learning style (including accommodators, divergers, convergers, and assimilators) on user’s satisfaction on the web-based learning system and their learning effectiveness.

This experimental research used the college students from a technology institute in Taiwan as the subject sources. By using the Kolb’s learning style model, the students are classified as four types of learners: convergers, divergers, assimilators, and accommodators. The authors analyzed the relationships among the different learning styles with their effectiveness of learning and satisfaction of using the web-based learning system. The mediation effect of gender is also presented.

This research indicates that: first, the satisfaction of the web-based learning system has significant influence on the learning performance of learners; second, different learning styles learners have no significant effect to the satisfaction on using the web-based learning system; third, learning effectiveness has significant difference among different learning style learners on the web-based learning system; the learning effectiveness of accommodators and divergers was significantly higher than the assimilators; fourth, different learning styles learners show significant difference in gender proportion. In addition to accommodators, whose proportion of women is higher than men, the other three learning styles’ proportions in men are higher than women.

This study was grounded in the Kolb’s learning style theory. The authors provide implications for academic studies in e-learning research stream that aimed at understanding the role of learning style as well as gender differences in the asynchronous web-based learning system.

Results from this study provided the implications for students, educators, and e-learning system designers. The design of teaching materials as well as functions of e-learning systems should take learners’ learning style into consideration to ensure the best learning outcome.

This study examined the students’ learning style as well as gender differences in the asynchronous web-based learning system. An experiment was conducted to ensure the data were collected in a controlled environment, thus, offer the value that most of the prior study lacks.

The purpose of this paper is to examine the evolution of collaboration among researchers in Library Hi Tech based on the co-authorship network analysis.

The Library Hi Tech publications were retrieved from Web of Science database between 2006 and 2017. Social network analysis based on co-authorship was analyzed by using BibExcel software and a visual knowledge map was generated by Pajek. Three important social capital indicators: degree centrality, closeness centrality and betweenness centrality were calculated to indicate the co-authorship. Cohesive subgroup analysis which includes components and k-core was then applied to show the connectivity of co-authorship network of Library Hi Tech.

The results indicated that around 42 percent of the articles were written by single author, while an increasing trend of multi-authored articles suggesting the collaboration among researchers in librarian research field becomes popular. Furthermore, the social network analysis identified authorship network with three core authors – Markey, K., Fourie, I. and Li, X. Finally, six core subgroups each included six or seven tightly connected researchers were also identified.

This study contributed to the existing literature by revealing the co-authorship network in librarian research field. Key researchers in the major subgroup were identified. This is one of the limited studies that describe the collaboration network among authors from different perspectives showing a more comprehensive co-authorship network.

The purpose of this paper is to present the knowledge structure based on the articles published in Library Hi Tech. The research hotspots are expected to be revealed through the keyword co-occurrence and social network analysis.

Data sets based on publications from Library Hi Tech covering the time period from 2006 to 2017 were extracted from Web of Science and developed as testbeds for evaluation of the CiteSpace system. Highly cited keywords were analyzed by CiteSpace which supports visual exploration with knowledge discovery in bibliographic databases.

The findings suggested that the percentage of publications in the USA, Germany, China, and Canada are high. Further, the most popular keywords identified in Library Hi Tech were: “service,” “technology,” “digital library,” “university library,” and “academic library.” Finally, four research issues were identified based on the most-cited articles in Library Hi Tech.

While keyword plays an important role in scientific research, limited studies paid attention to the keyword analysis in librarian research. The contribution of this study is to systematically explore the knowledge structure constructed by the keywords in Library Hi Tech.

This study adopted the collaborative consumption triangle to explore the influence of online food delivery platforms (OFDP) on consumer purchase intentions. It investigates the effects of restaurants' corporate social responsibility (CSR) practices, individuals' food neophilic tendencies (FNT), and platforms' perceived benefits on purchase intention within OFDP. Furthermore, the study analyses differences in consumers' pro-environmental behaviour (PEB) on OFDP.

The 497 participants conducted a web-based self-completion survey, using structural equation modelling to analyse the path structure of consumer purchasing intention. Furthermore, differences in PEB among OFDP consumers were compared through multigroup analysis.

The findings indicate that CSR influences the perceived value of sustainability and that the perceived value of sustainability influences purchase intention. Additionally, the influence of the perceived value of sustainability on purchase intention is more pronounced among consumers with low PEB compared to those with high PEB.

The findings may not be generalisable to other countries due to cultural differences, CSR policies, and strategies for promoting sustainable development.

The study provides valuable contributions related to (1) restaurants increasing their revenue and meeting their long-term sustainable development goals; (2) providing reusable containers policy and reusable containers policy and category tags for restaurants within OFDP.

This study is a pioneering work examining factors influencing purchase intentions within OFDP from the tripartite collaborative consumption perspective post-COVID-19 and focuses on the differences in PEB concerning OFDP.

Robotic arms’ interactions with the external environment are growing more intricate, demanding higher control precision. This study aims to enhance control precision by establishing a dynamic model through the identification of the dynamic parameters of a self-designed robotic arm.

This study proposes an improved particle swarm optimization (IPSO) method for parameter identification, which comprehensively improves particle initialization diversity, dynamic adjustment of inertia weight, dynamic adjustment of local and global learning factors and global search capabilities. To reduce the number of particles and improve identification accuracy, a step-by-step dynamic parameter identification method was also proposed. Simultaneously, to fully unleash the dynamic characteristics of a robotic arm, and satisfy boundary conditions, a combination of high-order differentiable natural exponential functions and traditional Fourier series is used to develop an excitation trajectory. Finally, an arbitrary verification trajectory was planned using the IPSO to verify the accuracy of the dynamical parameter identification.

Experiments conducted on a self-designed robotic arm validate the proposed parameter identification method. By comparing it with IPSO1, IPSO2, IPSOd and least-square algorithms using the criteria of torque error and root mean square for each joint, the superiority of the IPSO algorithm in parameter identification becomes evident. In this case, the dynamic parameter results of each link are significantly improved.

A new parameter identification model was proposed and validated. Based on the experimental results, the stability of the identification results was improved, providing more accurate parameter identification for further applications.