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In this “Info-plosion” era, recommendation systems (or recommenders) play a significant role in finding interesting items in the surge of online digital activity and e-commerce. The purpose of this paper is to model users' preference evolution to recommend potential items which users may be interested in.

A novel recommendation system, namely evolution-learning recommendation (ELR), is developed to precisely predict user interest for making recommendations. Differing from prior related methods, the authors integrate the matrix factorization (MF) and recurrent neural network (RNN) to effectively describe the variation of user preferences over time.

A novel cumulative factorization technique is proposed to efficiently decompose a rating matrix for discovering latent user preferences. Compared to traditional MF-based methods, the cumulative MF could reduce the utilization of computation resources. Furthermore, the authors depict the significance of long- and short-term effects in the memory cell of RNN for evolution patterns. With the context awareness, a learning model, V-LSTM, is developed to dynamically capture the evolution pattern of user interests. By using a well-trained learning model, the authors predict future user preferences and recommend related items.

Based on the relations among users and items for recommendation, the authors introduce a novel concept, virtual communication, to effectively learn and estimate the correlation among users and items. By incorporating the discovered latent features of users and items in an evolved manner, the proposed ELR model could promote “right” things to “right” users at the “right” time. In addition, several extensive experiments are performed on real datasets and are discussed. Empirical results show that ELR significantly outperforms the prior recommendation models. The proposed ELR exhibits great generalization and robustness in real datasets, including e-commerce, industrial retail and streaming service, with all discussed metrics.

The purpose of this study is to assess the validity and predictability of insights from the investment model (IM) in the context of strategic manufacturer–industrial supplier relationships. IM is a theoretical model in social psychology pertaining to interpersonal relationship discontinuity. This formal empirical test of IM in a different context supports vertical theory borrowing and minimizes the risk of committing atomistic fallacy.

Data collected from 256 sourcing professionals participating in a scenario-based role-playing experiment were analyzed via structural equation modeling. The authors also performed bootstrapping to assess indirect effects.

The IM is generally applicable to the context of interfirm relationship dissolution. Relative to the original context of interpersonal relationship dissolution, three nuances are detected: investment size as an antecedent has lowered prominence in influencing commitment; satisfaction level, quality of alternatives and investment size have non-orthogonal effects on commitment; and satisfaction level influences relationship continuity through and beyond commitment.

The empirical findings broaden boundary conditions for IM insights. Beyond interpersonal relationship dissolution, the IM appears to also describe, explain and predict interfirm relationship dissolution.

Keeping the manufacturer satisfied is critical. Moreover, suppliers should be cautious when entering joint product development agreements.

This study appears to be among the first to formally validate the applicability of IM insights as they pertain to the dissolution of strategic manufacturer–industrial supplier relationships.

This study aims to propose an integrated view and emphasize the importance of bank intangible value binding in customers' robo-advisory adoption. It explores the relationship between robo-advisors and traditional banking and defines the role of bank intangible assets value. It also attempts to understand if trust in the banking institution and the financial consultant determines the effect of these relationships.

The target sample of the study was investors who currently use wealth management services. This study collected 228 valid questionnaires and then executed structural equation model analysis to test the hypotheses.

Results showed that intangible value bindings play a mediating role, which positively affects consumers' willingness to adopt robo-advisors. Consumers' trust in banks and financial consultants are antecedent variables, which positively affect the intangible value bindings between consumers and banks. In addition, when the consumers' investment amount is higher, it will weaken the positive relationship between the intangible value binding and robo-advisor adoption intention.

Most of the past studies have focused on whether robo-advisors would replace personal financial consultants. This study proposes a hybrid model that contains both robo-advisors and traditional banking services, which encourage the acceptance of robo-advisors.

Prior studies on major customer relationships (i.e. embedded ties) focus mostly on the ties between a focal firm and its immediate customers, hindering the understanding of the influence of indirect ties (both upstream and downstream) on a focal firm's operational performance. In this study, the authors analyze how a focal firm's upstream and downstream connectedness and network location affect its productive efficiency.

Utilizing Compustat segment files, the authors constructed large-scale major customer networks covering the period 2007–2013. The authors applied a fixed-effect panel stochastic frontier model to conduct estimation. Moreover, the authors applied an endogenous panel stochastic frontier model to ensure the robustness of the main analysis.

The authors found that a focal firm's upstream and downstream connectedness both have a positive influence on a firm's productive efficiency, whereas a focal firm's centeredness in the major customer network has a negative influence on productive efficiency. Moreover, it was found that centeredness lessens the positive influences of upstream and downstream connectedness on productive efficiency. The post hoc analysis further confirmed that a focal firm's indirect ties, both upstream and downstream, positively influence a focal firm's productive efficiency.

This study contributes to the literature by evaluating the relative effectiveness of a focal firm's direct and indirect major customer ties, both upstream and downstream. More importantly, this study suggests potential exploitation–exploration trade-offs (i.e. productive efficiency vs. innovation) triggered by a firm's network location.

The design and implementation of a broadband quasi-monolithic microwave integrated circuit (q-MMIC) power amplifier (PA) is presented for 0.2 to 2.2 GHz applications.

To obtain an efficient, high-gain and high-power performance with in a compact and low-cost size, the prototype is based on Gallium nitride (GaN) on SiC 0.25-µm transistors, whereas the passive matching networks are realized on an AlN substrate as thin film circuit.

Measured results of the q-MMIC PA across the 0.2 to 2.2 GHz band show at least 32 ± 3 dB small-signal gains, an output power of 7 to 12 W and an average power add efficiency greater than 54%. The q-MMIC occupies an area of 12.8 × 14.5 mm².

To the best of the authors’ knowledge, this work reports the first full integrated PA which covers the frequency range of 0.2 to 2.2 GHz and achieves the combination of highest gain, about 10 W output power, together with the smallest component size among all published GaN PAs to date.

The purpose of this paper is to develop a comprehensive overview of green innovation (GI) in China, which is carried out by reviewing the evolution of GI from 2000 to 2019, and the main type of technology, actors and localizations. When appropriate, GI is compared to non-GI.

The study uses patent data from the European Patent Office database (PATSTAT); these data are processed to map trends and identify the main contributors to GI and the location of such innovation. The findings are then discussed and complemented with academic literature.

Key findings reveal an increasing divergence between GI and nongreen innovation after the 2008 crisis. It is also observed that solar energy appears to be the main component of GI in China, with a shift from photovoltaic thermal energy to solar photovoltaic energy after 2008. Other areas, such as waste management, greenhouse gases capture and climate change adaptation, are less innovative. Companies play an essential role in the development of all types of innovation. In terms of location, green patents are mainly filed in China’s three main megacities. The study also highlights the significant role of the Chinese state, which led policies shaping the trajectories and forms of GI.

This study expands knowledge on GI in China, highlighting its main specificities and the role of key actors. It provides to the reader a comprehensive picture of China’s green policies and innovation realities. The results can therefore be used to improve the understanding of GI evolution in China and facilitate the formulation of new research questions.

Integrating economic and green initiatives into firm strategies is a challenge for firms in various industries. The study aims to incorporate multiple views, i.e. green innovation theory (GIT), the green institutional perspective (GIP) and the natural-resource-based view (NRBV), to develop a comprehensive model to explore why and how firms implement green product innovation (GPI).

The study explores the relationships among institutional pressure, the firm's green resources and GPI. The research also distinguishes two different types of GPI: exploratory GPI and exploitative GPI. A total of 270 valid questionnaires were collected from electrical and electronics manufacturers in Taiwan. The authors employed structural equation modeling (SEM) using analysis of moment structures (AMOS) 23.0 to test the hypotheses.

The results show that institutional pressure has a significant positive correlation with the firm's green resources. Furthermore, institutional pressure has a significantly positive influence on exploratory GPI and exploitative GPI, respectively. The firm's green resources also have a significantly positive effect on both exploratory GPI and exploitative GPI. In addition, institutional pressures have significantly positive indirect effect on both exploratory GPI and exploitative GPI.

Economic benefits and environmental sustainability are the most pressing issues faced by the electrical and electronics industry today. The study's investigation covers Taiwanese electrical and electronics manufacturers only, so the test of the research model has limited generalizability. The authors suggest that to expand the generalizability of the findings, future research should examine this model in the context of other regions such as Southeast Asia, Africa, South America, etc.

The study has many interesting implications for both practitioners and policymakers. The authors' findings suggest that while Taiwanese electrical and electronics manufacturers face significant pressure from customers, competitors and regulation requirements (e.g. waste electrical and electronic equipment [WEEE], restriction of hazardous substances [RoHS] and energy using product [EuP] directives), firms in that sector should efficiently and effectively deploy their green resources and then perform proper GPI (e.g. exploratory GPI or exploitative GPI). These results also serve as a reminder to policymakers that balancing coercive (command-and-control) mechanisms with incentives and voluntary mechanisms is the best means by which to develop motivational and effective GPI policies.

First and foremost, the paper divides GPI into exploratory GPI and exploitative GPI. Furthermore, the research incorporates two important schools of thought, i.e. the GIP and NRBV, thus providing a more holistic view by which to explore why and how companies adopt GPI.

Prior research on green innovation has shown that institutional pressure stimulates enterprises to adopt green innovation. However, an institutional perspective does not explain why firms that face the same amount of institutional pressure execute different environmental practices and innovations. To address this research gap, the authors linked institutional theory with upper echelons theory and organization performance to build a comprehensive research model.

A total of 800 questionnaires were issued. The final usable questionnaires were 195, yielding a response rate of 24.38%. AMOS 23.0 was used to analyze the data and examine the relationships between the constructs in our model.

Institutional pressures affected both green innovation adoption (GIA) and the top management team's (TMT's) response. TMT's response influenced GIA. GIA was an important factor affecting firm performance. Furthermore, TMT's response mediated the relationship between institutional pressure and GIA. Institutional pressures indirectly affected green innovation performance but did not influence economic performance through GIA. Finally, TMT's response indirectly impacted firm performance through GIA.

The authors draw on institutional theory, upper echelons theory, and a performance-oriented perspective to explore the antecedents and consequences of GIA. This study has interesting implications for leaders and managers looking to implement green innovation and leverage it for firm performance to out compete with market rivals as well as to make the changes in collaboration with many other companies including market rivals to gain success in green innovation.

Aluminum alloy is considered an ideal material in aerospace, automobile and other fields because of its lightweight, high specific strength and easy processing. However, low hardness and strength of the surface of aluminum alloys are the main factors that limit their applications. The purpose of this study is to obtain a composite coating with high hardness and lubricating properties by applying GO–PVA over MAO coating.

A pulsed bipolar power supply was used as power supply to prepare the micro-arc oxidation (MAO) coating on 6061 aluminum sample. Then a graphene oxide-polyvinyl alcohol (GO–PVA) composite coating was prepared on MAO coating for subsequent experiments. Samples were characterized by Fourier infrared spectroscopy, X-ray diffraction, Raman spectroscopy and thermogravimetric analysis. The friction test is carried out by the relative movement of the copper ball and the aluminum disk on the friction tester.

Results showed that the friction coefficient of MAO samples was reduced by 80% after treated with GO–PVA composite film.

This research has made a certain contribution to the surface hardness and tribological issues involved in the lightweight design of aluminum alloys.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-12-2023-0427/

The dynamic response of the nuclear power plants (NPPs) with pile foundation reinforcement have not yet been systemically investigated in detail. Thus, there is an urgent need to improve evaluation methods for nonlithological foundation reinforcements, as this issue is bound to become an unavoidable task.

A nonlinear seismic wave input method is adopted to consider both a nonlinear viscoelastic artificial boundary and the nonlinear properties of the overburden layer soil. Subsequently, the effects of certain vital parameters on the structural response are analyzed.

A suitable range for the size of the overburden foundation is suggested. Then, when piles are used to reinforce the overburden foundation, the peak frequencies in the floor response spectra (FRS) in the horizontal direction becomes higher (38%). Finally, the Poisson ratio of the foundation soil has a significant influence on the FRS peak frequency in the vertical direction (reduce 35%–48%).

The quantifiable results are performed to demonstrate the seismic responses with respect to key design parameters, including foundational dimensions, the Poisson Ratio of the soil and the depth of the foundation. The results can help guide the development of seismic safety requirements for NPPs.