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For a better understanding of the preferences and differences of young consumers in emerging wine markets, this study aims to propose a clustering method to segment the super-new generation wine consumers based on their sensitivity to wine brand, origin and price and then conduct user profiles for segmented consumer groups from the perspectives of demographic attributes, eating habits and wine sensory attribute preferences.

We first proposed a consumer clustering perspective based on their sensitivity to wine brand, origin and price and then conducted an adaptive density peak and label propagation layer-by-layer (ADPLP) clustering algorithm to segment consumers, which improved the issues of wrong centers' selection and inaccurate classification of remaining sample points for traditional DPC (DPeak clustering algorithm). Then, we built a consumer profile system from the perspectives of demographic attributes, eating habits and wine sensory attribute preferences for segmented consumer groups.

In this study, 10 typical public datasets and 6 basic test algorithms are used to evaluate the proposed method, and the results showed that the ADPLP algorithm was optimal or suboptimal on 10 datasets with accuracy above 0.78. The average improvement in accuracy over the base DPC algorithm is 0.184. As an outcome of the wine consumer profiles, sensitive consumers prefer wines with medium prices of 100–400 CNY and more personalized brands and origins, while casual consumers are fond of popular brands, popular origins and low prices within 50 CNY. The wine sensory attributes preferred by super-new generation consumers are red, semi-dry, semi-sweet, still, fresh tasting, fruity, floral and low acid.

Young Chinese consumers are the main driver of wine consumption in the future. This paper provides a tool for decision-makers and marketers to identify the preferences of young consumers quickly which is meaningful and helpful for wine marketing.

In this study, the ADPLP algorithm was introduced for the first time. Subsequently, the user profile label system was constructed for segmented consumers to highlight their characteristics and demand partiality from three aspects: demographic characteristics, consumers' eating habits and consumers' preferences for wine attributes. Moreover, the ADPLP algorithm can be considered for user profiles on other alcoholic products.

Previous studies have reached inconsistent conclusions on foreign direct investment (FDI) technology spillovers and corporate innovation. The main purpose of this paper is to explore the technological spillover effects of FDI from the microperspective of firm linkages induced by geographic distance. Further analysis is conducted on the impact and mechanism of this spillover on the innovation quality of Chinese enterprises. The conclusions drawn from this paper can guide Chinese enterprises' foreign capital utilization and innovation strategy choices.

Using the data of China's A-share listed companies from 2009 to 2019, this paper explores the role of FDI technology spillover in enterprise innovation quality through a two-way fixed-effect model. The robustness of the results is proven by substituting variables, adding industry fixed effects and excluding high-profit groups, and further using the two-stage least squares (2SLS) method to alleviate the empirical endogeneity problem.

These findings indicate that FDI technology spillover based on geographic proximity has a positive impact on the innovation quality of Chinese enterprises. However, there are different impacts for different types of enterprises. FDI technology spillover has a positive impact on the innovation quality of non-state-owned enterprises (non-SOEs) and small- and medium-sized enterprises (SMEs), while it has no effect on state-owned enterprises (SOEs) and large enterprises. The authors also find that the degree of financing constraints and R&D investment are important transmission mechanisms between FDI technology spillover and enterprise innovation quality.

This study ignores industry characteristics when considering foreign enterprises around Chinese enterprises. In fact, technology spillover effects differ across industries. When the authors matched microdata to regions, only the provincial level was considered. Therefore, there is still room for further research. In future research, the authors should consider industry characteristics and group foreign enterprises and Chinese enterprises in the same industry and in different industries to explore industry differences in technology spillover. In addition, when matching corporate data to regions, the authors can match to the city level and draw city-level conclusions.

This study is different from previous studies that focus on the quantity of enterprise innovation or innovation output. The authors focus on the role of technological spillovers in the quality of Chinese enterprise innovation, enriching research in the field of enterprise innovation quality. In addition, the current FDI technology spillover indicators are technically difficult to measure at the micro level. The authors draw inspiration from the theory of the geographical structure of financial supply and combine the creation methods of macro and micro indicators in existing articles in other fields. The authors ingeniously construct a new FDI technical spillover indicator. This indicator combines the commonly used regional FDI technology spillover with the geographic proximity of enterprises at the microlevel by constructing an interaction term between the two. This indicator not only alleviates the endogeneity problem to a certain extent but also has implications for future research in the field of FDI technology spillovers at the micro level.

(1) FDI technology spillovers are an effective way to improve the innovation quality of local enterprises, especially for non-SOEs and SMEs. Therefore, The authors suggest that in the context of dual circulation, the Chinese government should continue to open wider to the outside world and encourage foreign enterprises to invest in China. (2) In future development, managers of SOEs and large enterprises should create an innovation incentive mechanism. Moreover, they should change their vertical management structure and make full use of their policy advantages and budget advantages to increase innovation activities. In the process of acquiring technology spillovers, enterprises need to solve their own financing constraints.

First, this study solves a technical problem. It is technically difficult to measure the current FDI technical spillover indicators at the micro level. This study innovatively constructs a new FDI technology spillover indicator that combines regional FDI technology spillovers with the microperspective of the geographical proximity of enterprises. This approach not only alleviates certain endogeneity problems in the empirical evidence but also enriches relevant research in the field of technology spillover. In addition, this study focuses on the impact and mechanism of this spillover, which addresses the current research gap among previous studies that mainly focus on innovation quantity and ignore innovation quality.

The purpose of this study is to propose a new consumer value segmentation method for low-dimensional dense market datasets to quickly detect and cluster the most profitable customers for the enterprises.

In this study, the comprehensive segmentation bases (CSB) with richer meanings were obtained by introducing the weighted recency-frequency-monetary (RFM) model into the common segmentation bases (SB). Further, a new market segmentation method, the CSB-MBK algorithm was proposed by integrating the CSB model and the mini-batch k-means (MBK) clustering algorithm.

The results show that our proposed CSB model can reflect consumers' contributions to a market, as well as improve the clustering performance. Moreover, the proposed CSB-MBK algorithm is demonstrably superior to the SB-MBK, CSB-KMA and CSB-Chameleon algorithms with respect to the Silhouette Coefficient (SC), the Calinski-Harabasz (CH) Index , the average running time and superior to the SB-MBK, RFM-MBK and WRFM-MBK algorithms in terms of the inter-market value and characteristic differentiation.

This paper provides a tool for decision-makers and marketers to segment a market quickly, which can help them grasp consumers' activity, loyalty, purchasing power and other characteristics in a target market timely and achieve the precision marketing.

This study is the first to introduce the CSB-MBK algorithm for identifying valuable customers through the comprehensive consideration of the clustering quality, consumer value and segmentation speed. Moreover, the CSB-MBK algorithm can be considered for applications in other markets.

Sandwich structures with well-designed cellular cores exhibit superior shock resistance compared to monolithic structures of equal mass. This study aims to develop a comprehensive analytical model for predicting the dynamic response of cellular-core sandwich structures subjected to shock loading and investigate their application in protective design.

First, an analytical model of a clamped sandwich beam for over-span shock loading was developed. In this model, the incident shock-wave reflection was considered, the clamped face sheets were simplified using two single-degree-of-freedom (SDOF) systems, the core was idealized using the rigid-perfectly-plastic-locking (RPPL) model in the thickness direction and simplified as an SDOF system in the span direction. The model was then evaluated using existing analytical models before being employed to design the sandwich-beam configurations for two typical engineering applications.

The model effectively predicted the dynamic response of sandwich panels, especially when the shock-loading pulse shape was considered. The optimal compressive cellular-core strength increased with increasing peak pressure and shock-loading impulse. Neglecting the core tensile strength could result in an overestimation of the optimal compressive cellular-core strength.

A new model was proposed and employed to optimally design clamped cellular-core sandwich-beam configurations subjected to shock loading.

Since the opening of China (aka, reform and opening-up), a great number of rural residents have migrated to large cities in the past 40 years. Such a one-way population inflow to urban areas introduces nontrivial social conflicts between urban natives and migrant workers. This study aims to investigate the most discussed topics about migrant workers on Sina Weibo along with the corresponding sentiment divergence.

An exploratory-descriptive-explanatory research methodology is employed. The study explores the main topics on migrant workers discussed in social media via manual annotation. Subsequently, guided LDA, a semi-supervised topic modeling approach, is applied to describe the overall topical landscape. Finally, the authors verify their theoretical predictions with respect to the sentiment divergence pattern for each topic, using regression analysis.

The study identifies three most discussed topics on migrant workers, namely wage default, employment support and urban/rural development. The regression analysis reveals different diffusion patterns contingent on the nature of each topic. In particular, this study finds a positive association between urban/rural development and the sentiment divergence, while wage default exhibits an opposite relationship with sentiment divergence.

The authors combine unique characteristics of social media with well-established theories of social identity and framing, which are applied more to off-line contexts, to study a unique phenomenon of migrant workers in China. From a practical perspective, the results provide implications for the governance of urbanization-related social conflicts.

This paper aims to explore the value of geographic diversification in the context of deglobalization, drawing evidence from a quasi-natural experiment – the Brexit referendum that took place on 23 June 2016 in the UK.

This study applies an event study methodology to estimate the impact of the Brexit vote on a cross-section of firms with varying levels of geographic diversification – undiversified UK firms, UK firms with significant operations in the European Union (EU) and globally diversified UK firms. This study deploys a Heckman two-stage regression approach to address sample selection bias.

This study finds that undiversified UK firms experienced negative cumulative abnormal returns (CARs) around the Brexit referendum. The value of UK firms with majority sales within the UK declined by 0.9 percentage points, on average, in the three days centred on the Brexit referendum. In contrast, UK firms that are globally diversified, with the majority of sales within the EU are unaffected, while diversified firms in the rest of the world generated positive CARs of 1.8 percentage points over the same period. These results are robust to firm characteristics, selection bias and alternative measures of CARs and diversification.

This study is subject to some limitations that open avenues for future work. There are a few available proxies of diversification and further work on developing other proxies is much needed. Further work may also examine the long-term impact of diversification on UK firms. This study considered Brexit as a quasi-natural experiment, and this study could be applied to other deglobalization events like COVID-19 and can enhance the generalizability of diversification strategy in the deglobalized world. Findings may stimulate future work to explore how another form of diversification – product diversification has affected firm returns around Brexit. Finally, this study has focused on the UK as its base case. It may be interesting to corroborate the findings by exploring the impact of Brexit on European firms, who hitherto Brexit, had some operations in the UK.

This work offers some insights for policymakers and regulators around the impact of deglobalization on local firms. Findings suggest that these trends significantly negatively impact the most vulnerable firms (smaller firms with less global reach), while their larger counterparts with significant global reach might be insulated. This finding is important for determining the nature of support needed by different firms in times of deglobalization. The work also offers insights to managers of firms operating in countries where there are real prospects of deglobalization. Specifically, the work highlights the importance of geographic diversification when free movement of goods, services and people is restricted.

This study shows that a certain group of globally diversified firms earned significantly higher returns from the prospect of the UK leaving the EU, thereby highlighting the value of geographic diversification in a time of deglobalization.

The purpose of this study is, to compare laser-based additive manufacturing and subtractive methods. Laser-based manufacturing is a widely used, noncontact, advanced manufacturing technique, which can be applied to a very wide range of materials, with particular emphasis on metals. In this paper, the governing principles of both laser-based subtractive of metals (LB-SM) and laser-based powder bed fusion (LB-PBF) of metallic materials are discussed and evaluated in terms of performance and capabilities. Using the principles of both laser-based methods, some new potential hybrid additive manufacturing options are discussed.

Production characteristics, such as surface quality, dimensional accuracy, material range, mechanical properties and applications, are reviewed and discussed. The process parameters for both LB-PBF and LB-SM were identified, and different factors that caused defects in both processes are explored. Advantages, disadvantages and limitations are explained and analyzed to shed light on the process selection for both additive and subtractive processes.

The performance of subtractive and additive processes is highly related to the material properties, such as diffusivity, reflectivity, thermal conductivity as well as laser parameters. LB-PBF has more influential factors affecting the quality of produced parts and is a more complex process. Both LB-SM and LB-PBF are flexible manufacturing methods that can be applied to a wide range of materials; however, they both suffer from low energy efficiency and production rate. These may be useful when producing highly innovative parts detailed, hollow products, such as medical implants.

This paper reviews the literature for both LB-PBF and LB-SM; nevertheless, the main contributions of this paper are twofold. To the best of the authors’ knowledge, this paper is one of the first to discuss the effect of the production process (both additive and subtractive) on the quality of the produced components. Also, some options for the hybrid capability of both LB-PBF and LB-SM are suggested to produce complex components with the desired macro- and microscale features.

The horizontal rotational single-sheet tester (RSST) suffers from weaknesses such as the reduced size of test samples, measurement disturbances due to magnetic flux leakage and nonhomogeneity of field in the measurement area. Although the vertical RSST allows to overcome the first two aforementioned drawbacks, the heterogeneity of the field in the test sample remains an issue. In addition, there is still a lack of device standardization to ensure test repeatability, as already is well established with the Epstein frame. This paper aims to investigate the influence of several parameters on the field homogeneity in the test sample.

A fully 3D finite element model of a vertical RSST is developed and used to perform a sensibility study on several geometrical parameters.

The influence of several parameters on the field homogeneity in the test sample, such as the geometrical dimensions of the yokes, the presence or not of holes drilled inside the test sample for B-coil placement as well as the size of the H-coils and B-coils, is addressed.

It is expected that this study will contribute to the optimization and standardization vertical RSSTs.

Selection of resilient suppliers has attracted the attention of researchers in the past one decade. The devastating effect of COVID-19 in emerging economies has provided great impetus to the selection of resilient suppliers. Under volatile and uncertain business scenarios, supplier selection is often done under imprecise and incomplete information, making the traditional decision-making methods ineffective. The purpose of this paper is to demonstrate the application of a fuzzy decision-making method for resilient supplier selection.

A group of three decision makers was considered for evaluating various alternatives (suppliers) based on their performance under different primary, sustainability and resilience criteria. Experts' opinion about each criterion and alternative was captured in linguistic terms and was modelled using fuzzy numbers. Then, an algorithm for solving resilient supplier selection problem based on the trapezoidal intuitionistic fuzzy technique for order preference by similarity to ideal solution (TrIFTOPSIS) was introduced and demonstrated through a case study.

A closeness coefficient was used to rank the suppliers based on their distances from intuitionistic fuzzy positive-ideal solution and intuitionistic fuzzy negative-ideal solution. Finally, the proposed fuzzy decision making model was applied to a real problem of supplier selection in the clothing industry.

The presented TrIFTOPSIS model provides an effective route to prioritise and select resilient suppliers under imprecise and incomplete information. This is the first application of intuitionistic fuzzy multi-criteria decision-making for resilient supplier selection.