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The purpose of this paper is to examine the performance impact of foreign ventures' exploration and exploitation strategies in emerging markets. Exploration and exploitation represent key strategic choices and have been extensively studied in the context of domestic markets. Yet the implication of such innovation strategies for foreign ventures operating in emerging markets has been under-researched. We aim to investigate whether foreign ventures can realize the value of exploration and exploitation strategies in emerging markets and also the moderating role of marketing capability and operation flexibility to enable the implementation process.

This study adopts the hierarchical moderated regression approach using a sample of foreign ventures operating in high-tech manufacturing industries in China.

The authors find that both exploration and exploitation have positive effects on firms' financial performance. Marketing capability strengthens the performance impact of exploration, but exhibits no such impact of exploitation. Moreover, operation flexibility positively moderates the effects of both exploration and exploitation on performance.

This study provides important insights into whether foreign ventures can boost performance through exploration and exploitation strategies in emerging markets as well as the implementation-level factors that can facilitate such positive effects.

The study is novel in revealing the moderating role of marketing capability and operation flexibility in facilitating the performance outcome of exploration and exploitation strategies.

The purpose of this paper is to examine the direct and interaction effects of relational governance and two control mechanisms, output control and process control in the context of international exchange relationships. Cross-border exchange relationships receive growing attention in the literature. Yet extant research has mainly examined single governance mechanisms. Among the few studies that investigate the interaction effects of relational governance and control mechanisms, some believe that the two mechanisms have conflicting effects, whereas others argue that they are complementary in nature.

Based on a sample of 184 Chinese export ventures, the empirical paper adopts the hierarchical moderated multiple regression approach.

The authors find that relational governance contributes positively to export performance, while output control leads negatively to export performance. The findings further suggest that output control complements relational governance to enhance export performance when combined. However, process control and relational governance substitute each other and reduce effectiveness when used simultaneously.

The study sheds new light on the ongoing debate about whether control mechanisms substitute or complement relational governance.

The study is novel in addressing the issue of how relational governance interacts differently with two control mechanisms in the international exchange relationships.

Examines the issue of how variations in language used in advertising affect advertising preference with a sample of bilingual, Korean Americans. Uses past literature to hypothesise that the level of acculturation would moderate ethnic consumers’ preference for advertisements in English versus their native language. Extends previous research in the field of ethnic advertising by considering whether findings from studies conducted with Hispanic American consumers are applicable to Asian Americans. Shows that no significant differences were detected in bilingual Korean American preferences for advertisements in which the message was presented in English as compared with those that used Humgul (Korean language) to communicate with the audience. Concludes with suggestions for further research.

Examines the fifthteenth published year of the ITCRR. Runs the whole gamut of textile innovation, research and testing, some of which investigates hitherto untouched aspects. Subjects discussed include cotton fabric processing, asbestos substitutes, textile adjuncts to cardiovascular surgery, wet textile processes, hand evaluation, nanotechnology, thermoplastic composites, robotic ironing, protective clothing (agricultural and industrial), ecological aspects of fibre properties – to name but a few! There would appear to be no limit to the future potential for textile applications.

Among the growing number of data mining (DM) techniques, outlier detection has gained importance in many applications and also attracted much attention in recent times. In the past, outlier detection researched papers appeared in a safety care that can view as searching for the needles in the haystack. However, outliers are not always erroneous. Therefore, the purpose of this paper is to investigate the role of outliers in healthcare services in general and patient safety care, in particular.

It is a combined DM (clustering and the nearest neighbor) technique for outliers’ detection, which provides a clear understanding and meaningful insights to visualize the data behaviors for healthcare safety. The outcomes or the knowledge implicit is vitally essential to a proper clinical decision-making process. The method is important to the semantic, and the novel tactic of patients’ events and situations prove that play a significant role in the process of patient care safety and medications.

The outcomes of the paper is discussing a novel and integrated methodology, which can be inferring for different biological data analysis. It is discussed as integrated DM techniques to optimize its performance in the field of health and medical science. It is an integrated method of outliers detection that can be extending for searching valuable information and knowledge implicit based on selected patient factors. Based on these facts, outliers are detected as clusters and point events, and novel ideas proposed to empower clinical services in consideration of customers’ satisfactions. It is also essential to be a baseline for further healthcare strategic development and research works.

This paper mainly focussed on outliers detections. Outlier isolation that are essential to investigate the reason how it happened and communications how to mitigate it did not touch. Therefore, the research can be extended more about the hierarchy of patient problems.

DM is a dynamic and successful gateway for discovering useful knowledge for enhancing healthcare performances and patient safety. Clinical data based outlier detection is a basic task to achieve healthcare strategy. Therefore, in this paper, the authors focussed on combined DM techniques for a deep analysis of clinical data, which provide an optimal level of clinical decision-making processes. Proper clinical decisions can obtain in terms of attributes selections that important to know the influential factors or parameters of healthcare services. Therefore, using integrated clustering and nearest neighbors techniques give more acceptable searched such complex data outliers, which could be fundamental to further analysis of healthcare and patient safety situational analysis.

Circular pipelines are mostly used for pneumatic conveyance in industrial processes. For optimum and efficient production in industries that use a pipeline for conveyance, tomographic image of the transport particles is paramount. Sensing mechanism plays a vital role in process tomography. The purpose of this paper is to present a two‐dimensional (2‐D) model for sensing the characteristics of electrostatic sensors for electrical charge tomography system. The proposed model uses the finite‐element method.

The domain is discretized into discrete shapes, called finite elements, by using a MATLAB. Each of these elements is taken as image pixels, on which the electric charges carried by conveyed particles are transformed into equations. The charges' interaction and the sensors installed around the circumference, at the sensing zone of the conveying pipeline are related by the proposed model equations. A matrix compression technique was also introduced to solve the problem of unevenly sensing characteristics of the sensors due to elements' number's concentration. The model equations were used to simulate the modeled electrostatic charge distribution carried by the particles moving in the pipeline.

The simulated results show that the proposed sensors are highly sensitive to electrostatic charge at any position in the sensing zone, thereby making it a good candidate for tomographic image reconstruction.

Tomographic imaging using finite element method is found to be more accurate and reliable compared to linear and filtered back projection method.

The purpose of this paper is to examine whether environmental dynamism can drive firms to adopt sustainability, taking into consideration the mediating role of the innovation process, strategic flexibility and human resource development in this relationship.

The proposed framework is tested by confirmatory factor analysis and finally structural equation modeling (SEM) using the survey data from 513 Greek firms.

The results show that environmental dynamism drives firms to sustainability, but the introduction of innovation process, strategic flexibility and human resource development fully mediate the effect of this relationship.

This study explores three organizational factors. In future research it would be very interesting to explore other topics that affect sustainability. Moreover, it might be useful for researchers to examine firms' digital capability and ambidextrous sustainability.

This study offers clear implications for managers, proving that innovation process, strategic flexibility and human resource development are critical factors in achieving sustainability.

This empirical study determines the contribution of environmental dynamism to sustainability taking into consideration the role of three critical organizational factors as mediators in this relationship.