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The purpose of this paper is to explore the possibility of an enhanced continuous liquid interface production (CLIP) with a porous track-etched membrane as the oxygen-permeable window, which is prepared by irradiating polyethylene terephthalate membranes with accelerated heavy ions.

Experimental approaches are carried out to characterize printing parameters of resins with different photo-initiator concentrations by a photo-polymerization matrix, to experimentally observe and theoretically fit the oxygen inhibition layer thickness during printing under conditions of pure oxygen and air, respectively, and to demonstrate the enhanced CLIP processes by using pure oxygen and air, respectively.

Owing to the high permeability of track-etched membrane, CLIP process is demonstrated with printing speed up to 800 mm/h in the condition of pure oxygen, which matches well with the theoretically predicted maximum printing speed at difference light expose. Making a trade-off between printing speed and surface quality, maximum printing speed of 470 mm/h is also obtained even using air. As the oxygen inhibition layer created by air is thinner than that by pure oxygen, maximum speed cannot be simply increased by intensifying the light exposure as the case with pure oxygen.

CLIP process is capable of building objects continuously instead of the traditional layer-by-layer manner, which enables tens of times improvement in printing speed. This work presents an enhanced CLIP process by first using a porous track-etched membrane to serve as the oxygen permeable window, in which a record printing speed up to 800 mm/h using pure oxygen is demonstrated. Owing to the high permeability of track-etched membrane, continuous process at a speed of 470 mm/h is also achieved even using air instead of pure oxygen, which is of significance for a compact robust high-speed 3D printer.

The purpose of this paper is to provide a framework of replication pricing of derivatives and identify funding valuation adjustment (FVA) and credit valuation adjustments (CVA) as price components.

The authors propose the notion of bilateral replication pricing. In the absence of funding cost, it reduces to unilateral replication pricing. The absence of funding costs, it introduces bid–ask spreads.

The valuation of CVA can be separated from that of FVA, so-called split up. There may be interdependence between FVA and the derivatives value, which then requires a recursive procedure for their numerical solution.

The authors have assume deterministic interest rates, constant CDS rates and loss rates for the CDS. The authors have also not dealt with re-hypothecation risks.

The results of this paper allow user to identify CVA and FVA, and mark to market their derivatives trades according to the recent market standards.

For the first time, a line between the risk-neutral pricing measure and the funding risk premiums is drawn. Also, the notion of bilateral replication pricing extends the unilateral replication pricing.

This paper focuses on the differences in domain intellectual structure discovery between author bibliographic coupling analysis (ABCA) and author co-citation analysis (ACA) considering all authors. The purpose of this study is to examine whether and in what ways these two all-author network approaches yield different results.

The sample was collected from the database of Web of Science, including all articles published in Scientometrics and Journal of Informetrics from 2011 to 2020. First, 100 representative authors were selected from each set, and ABCA matrices and ACA matrices were constructed. Second, factor analysis was carried out on the matrices, to detect the intellectual structure of scientometrics and informetrics.

The intellectual structures identified by ABCA and ACA are similar overall, but the results differ somewhat when it comes to specific structures. The ABCA is more sensitive to some highly collaborative research teams and presents a clearer picture of current intellectual structures and trends while ACA seems to have some advantages in representing the more traditional and proven research topics in the field. The combined use of ABCA and ACA allows for a more comprehensive and specific intellectual structure of research fields.

This paper compares the performance of ABCA and ACA detecting the intellectual structure of the domain from the perspective of all authors, revealing the intellectual structure of scientometrics and informetrics comprehensively.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-12-2020-0540.

This study aims to examine if the participation of live-stream influencers (LSIs) affects tipping frequency on live streaming platforms, and further investigate the mediating and moderating mechanisms.

Quasi-experiment and difference-in-differences models are used for data analysis. Propensity score matching is used to address potential unobservable endogeneity.

Real-time live streaming data reveal that LSIs’ participation significantly improves tipping frequency in live streaming rooms. Also, more users are attracted to the live streaming rooms and more users become active in participation. Additionally, the positive impact of LSIs’ participation is enhanced in the live streaming rooms with a greater number of relationship links between users.

The findings clarify the new role of influencers and reveal the mechanisms on how LSIs benefit the platforms.

The findings offer novel insights into implementing influencer marketing to interactive social media platforms, by encouraging influencer participation, user relationship building and influencer network growth.

This study highlights the value of LSIs for interactive social media platforms in terms of organic growth, revenue generation and cost reduction.

Risks resulted from asymmetric information have become crucial barriers for commercial banks to implement supply chain finance (SCF) – mainly the inventory pledge financing (IPF). At the same time, online financial service providers (OFSPs) are emerging as strong competitors in the SCF market. As a result, commercial banks need to update their traditional SCF business models and alleviate their over-dependence on OFSPs.

The authors employ a multi-case-study method to investigate how the Internet of things (IoT) and blockchain technologies can be jointly leveraged to mitigate SCF risks. In-depth interviews were conducted to depict the business models and their novel ecosystem to reinforce traditional banks' ability in SCF services.

From the perspective of information asymmetry, the authors categorize IPF risks into three groups based on the principal-agent theory: collateral, warehousing and liquidity risk. The findings suggest that IoT can primarily improve traditional banks' information acquisition ability, and blockchain can facilitate credible information transformation, enabling banks to acquire knowledge from collaterals. Besides, the e-platform in the new architecture increases banks' involvement in the supply chain and builds a fair network to curtail warehousing risks. The employment of smart contracts and collaborative mechanism ensure process and outcome control in mitigating liquidity risks.

The research contributes to the literature by confirming the role of emerging technologies in reducing information asymmetry risks. Besides, the findings provide valuable insights for practitioners to promote effective practices and approaches in IPF.

The paper aims to help enterprises gain valuable knowledge about big data implementation in practice and improve their information management ability, as they accumulate experience, to reuse or adapt the proposed method to achieve a sustainable competitive advantage.

Guided by the theory of technological frames of reference (TFR) and transaction cost theory (TCT), this paper describes a real-world case study in the banking industry to explain how to help enterprises leverage big data analytics for changes. Through close integration with bank's daily operations and strategic planning, the case study shows how the analytics team frame the challenge and analyze the data with two analytic models – customer segmentation (unsupervised) and product affinity prediction (supervised), to initiate the adoption of big data analytics in precise marketing.

The study reported relevant findings from a longitudinal data analysis and identified some key success factors. First, non-technical factors, for example intuitive analytics results, appropriate evaluation baseline, multiple-wave implementation and selection of marketing channels critically influence big data implementation progress in organizations. Second, a successful campaign also relies on technical factors. For example, the clustering analytics could promote customers' response rates, and the product affinity prediction model could boost efficient transaction and lower time costs.

For theoretical contribution, this paper verified that the outstanding characteristics of online mutual fund platforms brought up by Nagle, Seamans and Tadelis (2010) could not guarantee organizations' competitive advantages from the aspect of TCT.

Leader secure-base support, consisting of leader availability, noninterference and encouragement of growth, has important implications for stimulating employee proactivity. This study is aimed at examining whether, why and when leader secure-base support may motivate employees to engage in approach job crafting behavior. Drawing upon regulatory focus theory, we propose leader secure-base support is positively associated with employee approach job crafting via employee state promotion focus. Based on cue consistency theory, we further examine the moderating role of organizational learning culture in the associations of leader secure-base support with employee state promotion focus and subsequent approach job crafting.

Two-wave data were collected from 281 Chinese workers. Path analyses with Mplus 7 were conducted to test the hypotheses.

As predicted, we found that leader secure-base support was positively related to employee state promotion focus and, in turn, facilitated employee approach job crafting. Moreover, organizational learning culture accentuated the impact of leader secure-base support on employee job crafting process.

This study is the first to examine the influence of leader secure-base support on employee job crafting. It also identifies a boundary condition for such an influence.

Bearing friction moments are important factors that affect the vibrations of rotor systems. The bearing friction moments are related to the dimension parameters, lubrication conditions and manufacturing errors of support bearings. This work studies the effects of the bearing friction moments on the vibrations of rotor systems.

The rotor is separated into several shaft elements for formulating a flexible rotor. The time-varying friction moment (TFM) is affected by the time-varying contact loads. The vibrations of FRS from the TFM and Palmgren's friction moment (PFM) calculation methods are compared. Moreover, the effects of the rotor offset and radial clearance on the frequency-amplitude characteristics of FRS are studied.

The TFM method is more consistent with the actual operation mechanisms. The rotor offset and radial clearance can significantly affect the nonlinear vibrations of FRS. This work provides a new reference and research method for the vibration analysis of rotor systems considering the friction effects.

The elastohydrodynamic lubrication (EHL), elastic hysteresis and differential sliding are considered. A flexible rotor system (FRS) dynamic model considering the TFM is proposed. The vibrations of FRS from the TFM calculation method and empirical calculation formula are compared. The effects of the rotor offset and radial clearance on the frequency–amplitude characteristics of FRS are studied.

A critical step in influencer marketing is influencer outreach, where a brand reaches out to an influencer and forms a partnership. Yet little is known about how factors related to this process might influence the outcomes of sponsored posts. To address this gap, the authors investigated whether, how and when the order of influencers' product use and brand outreach (i.e. use/outreach order) affects post persuasiveness.

The authors conducted three experimental studies. Studies 1 and 2 examined the effect of disclosure type (use-first, outreach-later vs. outreach-first, use-later vs. no disclosure) on consumers' responses to the post. Study 3 investigated the moderating effects of compensation disclosure type.

The results revealed that when the influencer used the product before (vs. after) being contacted by the brand, consumers had more favorable attitudes about the product and greater purchase intention upon reading the sponsored posts; perceived information diagnosticity mediated this effect. However, this tendency was mitigated if the influencer disclosed the specific monetary payment from the brand.

This research advances understanding of sponsorship disclosure and provides a way to manage its impact on message persuasiveness.

As one natural fiber, yak cashmere has been used more and more widely on textile processing due to its excellent warmth retention property. Yarn spinning is the first and the most important step of textile processing. Yarn spinning is closely related to the fiber properties. That is, for giving the optimization spinning process of one new fiber, the properties of the new fiber should be studied firstly. Meanwhile, during the studying of the properties of the new fiber, comparative analysis method was usually used. That is, the property of the new fiber was common comparatively analyzed with other fibers. During the comparative analysis, the spinning process can be optimized. Therefore, in the paper, the properties of the yak cashmere were studied in detail and comparatively analyzed.

The brown yak cashmere, cyan yak cashmere, white cashmere fiber, purple cashmere fiber, cyan cashmere fiber, camel hair fiber and mohair fiber, were chosen as the samples. The fiber length, fineness, strength, curls, moisture regain, mass specific resistance, surface morphology, infrared spectrum, melting behavior, thermal weight loss, friction, x-ray, were tested and comparatively analyzed.

It is shown that the compositions of yak cashmere and cashmere are similar, and makes the physical properties of yak cashmere and cashmere fiber similar. Comparing with the mohair, camel hair and cashmere fiber, the average length of yak cashmere is smaller and the dispersion of length distribution is larger, and the dispersion of yak cashmere strength is larger, which makes the yarn spinning of yak cashmere difficult, especially the high count pure yarn. However, comparing with the mohair, camel hair and cashmere fiber, the friction coefficient and friction effect of yak cashmere is larger, and yak cashmere fiber has relatively less curls and larger crimp rate and crimp recovery rate, and can improve the fiber spinnability.

In the paper, taking the brown yak cashmere, cyan yak cashmere, white cashmere fiber, purple cashmere fiber, cyan cashmere fiber, camel hair fiber, mohair fibers as the samples, the properties of the yak cashmere were studied in detail. The fiber length, fineness, strength, curls, moisture regain, mass specific resistance, surface morphology, infrared spectrum, melting behavior, thermal weight loss, friction, x-ray, were tested and comparatively analyzed. The studies can establish foundation for the optimization of the yak cashmere spinning process, and also can provide information for the end uses of the fiber.