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Post-acquisition control is a crucial factor affecting acquisition performance. We investigate how post-acquisition control strategy affects cross-border acquisition performance of Chinese multinational enterprises (MNEs) through a configurational perspective.

Based on 70 cross-border acquisition cases by Chinese MNEs, we adopt fuzzy-set qualitative comparative analysis (fsQCA) to study the combined effects of strategic control, operational control, institutional distance, cultural distance, relative capacity and business relatedness on the cross-border acquisition performance.

On the basis of fuzzy set analysis of multiple interdependent factors, we identify six configurations that are conductive to achieving high cross-border acquisition performance and two configurations that relate to the absence of high performance, thus shedding light on the casually complex nature of performance drivers of acquisitions.

This study provides a holistic, configurational approach to investigating cross-border acquisition performance by emerging market firms. Our results provide some compelling evidence that accounts for the causal complexity of post-acquisition control strategies and acquisition outcomes in the context of emerging economies.

This paper examines how the level of low-carbon awareness (LCA) affects the remanufacturing strategy in a supply chain with an original equipment manufacturer (OEM) and an independent remanufacturer (IR) competing with each other.

Game theory and operations optimization.

The studies analytically characterize the threshold levels of the LCA in response to which the OEM and the IR will change their remanufacturing strategies from no remanufacturing to partial remanufacturing and then to full remanufacturing. In addition, the studies reveal that as compared with the OEM, the IR has more flexibility in terms of the market entry to remanufacturing with the level of LCA increasing. With the extended studies, it is exhibited that the above findings are robust to a good extent.

It can provide decision support for remanufacturing enterprises.

The purpose of this study is to develop luminescence sensors for the detection of nitroaromatic compounds (NACs) and metal ions to protect human health and prevent environmental pollution.

The composition and morphology of Eu-metal-organic frameworks (MOF) (1) were well characterized by powder X-ray diffraction, elemental analyses, Fourier-transform infrared spectroscopy, thermogravimetric analysis, X-ray photoelectron spectroscopy and scanning electron microscopy. The emission spectrum displays that 1 has significant characteristic emission bands of Eu(III) ions. The authors further investigated the fluorescence sensing performances of 1 to NACs and metal ions.

The results show that Eu-MOF (1) exhibits significant fluorescence quenching effect toward p-nitroaniline and Fe³⁺ ions with good stability and recyclability. This means that 1 can be used as a multifunctional sensing material for the detection of p-nitroaniline and Fe³⁺ ions.

The authors have successfully synthesized a fluorescence Eu-based sensing material under hydrothermal conditions. In addition, the fluorescence property and sensing performances for detecting NACs and metal ions were studied. The results suggest that 1 has highly selective fluorescence quenching toward p-nitroaniline and Fe³⁺ ions with not only high sensitivity and selectivity but also excellent stability and recyclability. Furthermore, this study has confirmed that the multifunctional MOF material is very useful in environment pollutants’ detection and monitoring.

This study aims to look into consumers' green consumption intention by incorporating social media exposure, environmental concern and habit into theory of planned behavior (TPB) in the context of China advocating green consumption.

Based on the data collected from online survey, this study use partial least squares structural equation modeling (PLS-SEM) to analysis the measurement model and structure model.

The results show attitude, social media exposure, environmental concern and subjective norms are important determinants of consumers' intention to purchase green products.

This study explores the new associations between the major constructs of the TPB model in green consumption. This study also expanded the TPB model by adding three extra factors, namely social media exposure, habit and environmental concern. In addition, this study attempts to bridge the gap between attitude and intention from a new perspective by using social media exposure as a moderating variable.

Rural credit cooperatives (RCCs) have long dominated China’s rural credit market and met most of agricultural credit demands while the existing literature seldom examines their contribution to agricultural sector. The purpose of this paper is to provide empirical evidence on the contribution of RCCs to agricultural growth, using China’s provincial panel data from 1997 to 2014.

Both static fixed effects models and two-step generalized method of moment dynamic panel data models, which control the endogeneity, are employed to identify the causality from RCC credit to agricultural growth in China.

The results show that the credit from RCCs increases the agricultural output significantly. A 1 percent increase in RCC credit leads to agricultural growth of about 0.08 percent, which is robust to various empirical specifications. Further study shows that the contribution of RCC credit to agricultural growth decreases from the most developed eastern region to the least developed western region and increases over time.

The results imply that RCC credit is critical in financing agricultural activities by relaxing rural credit constraints and intense competition strengthens the contribution of RCCs to agricultural growth by improving managerial efficiency and developing diversified financial products to meet better rural credit demands.

To the authors’ knowledge, this is first empirical study on the effect of RCC credit on agricultural growth despite of many on the role of financial development in agricultural growth.

As an advanced manufacturing method, additive manufacturing (AM) technology provides new possibilities for efficient production and design of parts. However, with the continuous expansion of the application of AM materials, subtractive processing has become one of the necessary steps to improve the accuracy and performance of parts. In this paper, the processing process of AM materials is discussed in depth, and the surface integrity problem caused by it is discussed.

Firstly, we listed and analyzed the characterization parameters of metal surface integrity and its influence on the performance of parts and then introduced the application of integrated processing of metal adding and subtracting materials and the influence of different processing forms on the surface integrity of parts. The surface of the trial-cut material is detected and analyzed, and the surface of the integrated processing of adding and subtracting materials is compared with that of the pure processing of reducing materials, so that the corresponding conclusions are obtained.

In this process, we also found some surface integrity problems, such as knife marks, residual stress and thermal effects. These problems may have a potential negative impact on the performance of the final parts. In processing, we can try to use other integrated processing technologies of adding and subtracting materials, try to combine various integrated processing technologies of adding and subtracting materials, or consider exploring more efficient AM technology to improve processing efficiency. We can also consider adopting production process optimization measures to reduce the processing cost of adding and subtracting materials.

With the gradual improvement of the requirements for the surface quality of parts in the production process and the in-depth implementation of sustainable manufacturing, the demand for integrated processing of metal addition and subtraction materials is likely to continue to grow in the future. By deeply understanding and studying the problems of material reduction and surface integrity of AM materials, we can better meet the challenges in the manufacturing process and improve the quality and performance of parts. This research is very important for promoting the development of manufacturing technology and achieving success in practical application.

This paper aims to examine consumer preference for ethical fashion products by focusing on the importance of animal welfare attribute. To explain the attitude-behavior gap, this research proposes to explore the costs and sacrifices associated with the adoption of responsible behaviors.

To analyze in which manner the animal welfare attribute impacts the consumer preference, the authors carried two quantitative studies in the Italy context. The first one (n = 224) proposes to measure the importance of this attribute in the case of luxury vs accessible fashion. The second study (n = 101) examines how the attention given to animal welfare information could vary between prosocials and proselfs. Conjoint analyses that consider “proportion of real fur”; “information about animal treatment” and “price” attributes have been realized. To take into account the individuals characteristics, cluster analysis helped to identify different profiles of consumers.

The results reveal that even if consumers continue to prefer products made entirely from animal fur, they are sensitive to the information on the animal treatment conditions. Also, the animal welfare is not the most important criterion in explaining preference for a fashion product. This result varies, however, regarding the consumers’ social value orientation. Individuals with a high level of prosocial values give more importance to the animal welfare attribute and are less reluctant to the reduction of the proportion of real fur in the clothes. Proself consumers associate a higher sacrifice with the consumption of animal-friendly fashion products.

This research enriches the limited literature on the consumers’ response to animal-friendly products. By considering the consumers’ social value orientation, it provides a better understanding of the attitude-behavior gap in animal-friendly fashion consumption. However, further studies should focus on the way of adapting communication on eco-products to the consumer profile. Moreover, it seems interesting to explore how the integration of innovative environmentally friendly materials can be accepted by the target. Replicating this research with representative consumer samples from different countries is also necessary.

From a practical point of view, this research offers implications for managers operating in fashion apparel industry by giving insights on the consumers’ preference for animal friendly fashion.

This study gives recommendations to help convincing consumers about the importance of animal welfare attribute and to increase their preference for animal-friendly fashion products.

Despite the extensive use of animal fibers, fur and skins in the production of textiles, the few researchers who have shed the light on the consumers’ response to animal-friendly products have considered mainly the case of food. Also, the marketing literature gives little explanation of the attitude-behavior gap in ethical fashion consumption. By examining the consumers’ social value orientation, this study provides a better understanding of this gap.

This research proposes a text analytics–based framework that examines the utility of online customer reviews in evaluating automobile manufacturers and discovering their consumer-perceived weaknesses.

The proposed framework integrates aspect-level sentiment analysis with the house of quality (HoQ), TOPSIS, Pareto chart and fishbone diagram. While sentiment analysis mines and quantifies review-embedded consumer opinions on various automobile attributes, the integrated HoQ-TOPSIS analyzes the quantified opinions and evaluates the manufacturers. The Pareto charts assist in discovering consumer-perceived weaknesses of the underperforming manufacturers. Finally, the fishbone diagram visually represents the results in the form with which the manufacturing community is acquainted.

The proposed framework is tested on a review data set collected from CarWale, a well-known car portal in India. Selecting five manufacturers from the mid-size car segment, the authors identified the worst-performing one and discovered its weak attributes.

The proposed framework can help the manufacturers in evaluating competitor; identifying consumers' contemporary interests; discovering own and their competitors' weak attributes; assessing the suppliers and sending early warnings; detecting the hazardous defects. It can assist the component suppliers in devising process improvement strategies; improving their customer network; comparing them with competitors. It can support the customers in identifying the best available alternative.

The proposed framework is first of its kind to integrate the sentiment analysis with (1) HoQ-TOPSIS to assess the manufacturers; (2) Pareto chart to discover their weaknesses; (3) fishbone diagram to visually represent the results.

In the vast majority of published papers, the optimal reactive power dispatch (ORPD) problem is dealt as a single-objective optimization; however, optimization with a single objective is insufficient to achieve better operation performance of power systems. Multi-objective ORPD (MOORPD) aims to minimize simultaneously either the active power losses and voltage stability index, or the active power losses and the voltage deviation. The purpose of this paper is to propose multi-objective ant lion optimization (MOALO) algorithm to solve multi-objective ORPD problem considering large-scale power system in an effort to achieve a good performance with stable and secure operation of electric power systems.

A MOALO algorithm is presented and applied to solve the MOORPD problem. Fuzzy set theory was implemented to identify the best compromise solution from the set of the non-dominated solutions. A comparison with enhanced version of multi-objective particle swarm optimization (MOEPSO) algorithm and original (MOPSO) algorithm confirms the solutions. An in-depth analysis on the findings was conducted and the feasibility of solutions were fully verified and discussed.

Three test systems – the IEEE 30-bus, IEEE 57-bus and large-scale IEEE 300-bus – were used to examine the efficiency of the proposed algorithm. The findings obtained amply confirmed the superiority of the proposed approach over the multi-objective enhanced PSO and basic version of MOPSO. In addition to that, the algorithm is benefitted from good distributions of the non-dominated solutions and also guarantees the feasibility of solutions.

The proposed algorithm is applied to solve three versions of ORPD problem, active power losses, voltage deviation and voltage stability index, considering large -scale power system IEEE 300 bus.