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The purpose of this study is to explore the relationship between ambidextrous leadership and sustainability performance. In addition, this study also discusses how ambidextrous leadership affects sustainability performance through employees' green creativity and green product innovation.

This study obtained research data from a questionnaire survey of 307 manufacturing enterprise leaders in China and used regression and bootstrap analysis to test the research hypotheses.

(1) Ambidextrous leadership positively influences sustainability performance. (2) Employees' green creativity mediates the relationship between ambidextrous leadership and sustainability performance. (3) Green product innovation also mediates the relationship between ambidextrous leadership and sustainability performance. (4) The intermediary chain constructed by employees' green creativity and green product innovation has serial mediation effects on the relationship between ambidextrous leadership and sustainability performance.

This study contributes to the literature on leadership and corporate sustainability by clarifying the relationship between ambidextrous leadership and sustainability performance. Meanwhile, this study reveals the influence mechanism of ambidextrous leadership on sustainability performance by analyzing the serial mediation effects of employees' green creativity and green product innovation.

In a world that is more competitive on a global scale, technologically advanced and demanding than ever before, global situations such as climate change, poverty and inequality, health, migration or security are challenging for decision-makers in political, social or environmental contexts. The interplay of these and other tendencies is referred to as wicked problems, as their increasing complexity can often not be understood or distinguished anymore. Too many different crises, such as climate, economic, political or societal crises, are challenging the vulnerability and resilience of political, economic and community-based systems. Accordingly, focussing on battling single challenges without considering the bigger picture or interconnected processes or circumstances has not led to satisfactory results throughout the past decades. In a tourism industry that is traditionally closely interlinked with numerous sectors or stakeholder groups and therefore often associated with these problems, those in responsibility are particularly required to consider various interests and utilise the synergy potentials between the tourism and non-tourism sector. Accordingly, integrative tourism policy-making needs to include many political areas that are relevant within tourism as well as beyond, such as urban or regional development. As a holistic spatial development approach, the ‘ecosystem of hospitality’ (EoH) can facilitate the identification of interfaces between tourism and these political areas and help to foster a cross-stakeholder collaboration.

The dependency on human expertise for analysis and interpretation is the main reason for wear debris analysis not being used in industry to its full potential and becoming one of the most powerful machine condition monitoring strategies. The dependency on human expertise makes the interpretation and result subjective in nature, costly and time consuming. The purpose of this paper is to review work being done to develop an automatic, reliable and objective wear particle classification system as a solution to the above problem. At the same time it also aims to discuss some common off line test methods being practiced for wear debris analysis.

Computer image analysis is a solution for some of the problems associated with the conventional techniques. First it is tried to efficiently describe the characteristics of computer images of different types of wear debris using a few numerical parameters. Then using some Artificial Intelligence tools, the wear particle classification system can be developed.

Many shape, size and surface parameters are discussed in the paper. Out of these, nine numerical parameters are selected to describe and distinguish six common type of wear debris. Once the type of debris is identified, the mode of wear and hence the machine condition can be assessed.

The present process of fault and condition monitoring of an equipment by wear debris analysis involves human judgment of debris formations. A set‐up standard for comparison of debris will enable the maintenance team to diagnose faults in a comparatively better way.

The aim of this paper is to discuss the difficulties in identifying wear particles and finding out the exact health of equipment, which, due to its subjective nature, is influenced by human errors. An objective method with certain standards for classification of wear particles compatible with an artificial intelligence system will yield some flawless results of wear debris analysis, which has not been attempted in the past as per available literature.

This paper aims to explore the interlock-performance relationship among mainland Chinese firms listed in Hong Kong by taking advantage of a relationship-intensive context whereby such a link is likely to be especially important. Although strategic networks such as interlocking directorates have been found to affect a number of strategic behaviors, the link connecting board interlocks and corporate performance has remained ambiguous. Considerable light has been shed on the strategic networks of firms whose shares are listed abroad, which have been under-studied despite their rising importance in the global economy.

Data come from a particularly interesting historical period – the early 1990s prior to Hong Kong’s 1997 handover to China. Both quantitative and qualitative research have been used.

Empirically, it was found that good performance in an earlier period helps draw outside directors in a later period, and that network centrality and certain types of interlocks help improve performance, albeit with varying degrees. Overall, our results answer the question whether strategic networks such as interlocks matter for corporate performance with a qualified “yes”.

Taking advantage of a relationship-intensive context, this article explores the interlock-performance relationship among mainland Chinese firms listed in Hong Kong. Focus is specifically on the two years, 1993 and 1995, due to their specific historical importance because these two years represent the beginning of Chinese firms’ listing in Hong Kong.

Since institutions are typically conceptualized as “the rules of the game in a society” (North 1990: 3; Scott 1995), “institutional transitions” are defined as “fundamental and comprehensive changes introduced to the formal and informal rules of the game” (Peng 2003: 275). One of the most dramatic sets of institutional transitions in the last two decades has been the political, economic, and social changes sweeping across Central and Eastern Europe (CEE), the newly independent states (NIS) of the former Soviet Union, and the East Asian countries of China and Vietnam. In fact, these institutional transitions are so profound that these countries, formerly known as the Eastern bloc, have now been collectively labeled “transition economies.”

The purpose of this paper is to systematically review knowledge hiding (KH) behaviors in the team context. KH behavior is regarded as unethical and antisocial behavior, detrimental to team development and performance. The nature of its existence should not be allowed in team activities.

Applying a systematic literature review, this study investigated 39 related quantitative studies on KH behavior of employees in team and group contexts. This study discusses the fundamental concept of KH, analyzes current research findings, identifies relevant gaps in the team and group context and sheds light on future direction.

Findings observed that the KH phenomena had gained the interest of scholars since the year 2010. Five main research streams identified in this systematic review are role of leadership, team creativity and innovation, underlying theory, multilevel modeling and KH scale.

The value of this paper is subjected to the specific notion of KH in team background where knowledge sharing should have been promoted instead of KH. This systematic review serves as insight and recognition on the importance of mitigating KH in team. Existing current literature, future research work and trends of KH in the organization may benefit from this new and anticipated behavior within the knowledge management field.

To the best of the authors’ knowledge, this review is the first to review KH behavior in the team context.

Drawing on source credibility theory, this study aims to explore the relationship between influencers’ characteristics and followers’ well-being through followers’ stickiness to influencers’ channels or posts.

The authors gathered data through an online survey of 450 followers. The proposed hypotheses were examined using structural equation modeling.

Results reveal that trustworthiness and physical attractiveness positively affect followers’ stickiness to influencers, while the influence of expertise is not evident. Stickiness has positive impacts on both hedonic and eudaimonic well-being. The findings also show that stickiness mediates the relationships between physical attractiveness and trustworthiness toward both hedonic and eudaimonic well-being.

To the best of the authors’ knowledge, this study is among the first to explore the impact of influencers’ characteristics on followers’ stickiness to influencer webpages. The findings contribute to transformative service research and the theory of stickiness by deepening the understanding of how influencer characteristics contribute to followers’ well-being through the effect of users’ stickiness.

Based on the strategy tripod perspective, this study aims to address how emerging economy multinational enterprises (EMNEs) make a strategic decision of choosing a foreign location for their strategic asset seeking and under what mechanism EMNEs make foreign direct investment (FDI) location choice.

This paper first reviews the literature on strategy tripod and strategic asset seeking strategy of EMNEs. Then, six cases of Chinese multinational enterprises operating in manufacturing industry have been introduced, emphasizing on interactions within three dimensions of strategy tripod framework, namely, resource-based dimension, industry-based dimension and institution-based dimension. By triangulating with multiple sources of archival and interview data, this paper identified a conceptual model presenting location choice mechanisms.

Based on a comparative multi-case study, four mechanisms of EMNEs’ location choice when seek strategic asset by FDI within a strategy tripod framework have been revealed. Specifically, EMNEs make their strategic decision of choosing a foreign location for their strategic asset seeking under mechanisms of seeking complementary resources based on industry characteristics; echoing with institutional dimension of home country when exploitation of resource; matching institutional dimension of host country when consider industry fitness; and institutional leveraging combined with understanding of resource and industry dimensions inside strategy tripod.

The findings shed novel insights into the mechanisms under which EMNEs choose their location for strategic asset-seeking FDI. It also broadens the strategy tripod framework by looking deeper into the characteristics of each dimension within a new research context of EMNEs’ FDI location choice.

The purpose of this paper is to identify, assess and explore potential risks that can affect long‐term viability of enterprise resource planning (ERP) systems in the post‐implementation and exploitation phase.

The research took a large Chinese private group as a case study. A theoretical ERP risk ontology, which was adopted from the literature, was used to frame the study and generate data collection tools. Two questionnaires were thus designed and used to explore ERP post‐implementation risks in the case company.

The study identified 37 risk events, of which seven were identified as the most critical for ERP exploitation in the case company. The findings show that organisational and human‐related risks are the crucial factors for potential ERP failure and not the usually suspect technical risks.

This study contributes to the knowledge of ERP in general, and provides valuable insights into ERP post‐implementation risks in large companies in particular.

The findings will not just be useful in supporting ERP risk identification and management in the large Chinese companies, but will also be beneficial to other large companies in general, which may be confronted with similar ERP exploitation challenges.

The majority of large companies in China and in the West have implemented ERP systems and engaged in the system post‐implementation phase. Most of the existing literature in the field focuses on the process of implementation. This paper looks forward to the risks involved in the post‐implementation phase. Understanding potential risks that may occur during ERP exploitation is vital for these large firms to achieve and sustain business success through their ERP systems.

The purpose of this research is to compare several machine learning techniques on the task of Asian language text classification, such as Chinese and Japanese where no word boundary information is available in written text. The paper advocates a simple language modeling based approach for this task.

Naïve Bayes, maximum entropy model, support vector machines, and language modeling approaches were implemented and were applied to Chinese and Japanese text classification. To investigate the influence of word segmentation, different word segmentation approaches were investigated and applied to Chinese text. A segmentation‐based approach was compared with the non‐segmentation‐based approach.

There were two findings: the experiments show that statistical language modeling can significantly outperform standard techniques, given the same set of features; and it was found that classification with word level features normally yields improved classification performance, but that classification performance is not monotonically related to segmentation accuracy. In particular, classification performance may initially improve with increased segmentation accuracy, but eventually classification performance stops improving, and can in fact even decrease, after a certain level of segmentation accuracy.

Apply the findings to real web text classification is ongoing work.

The paper is very relevant to Chinese and Japanese information processing, e.g. webpage classification, web search.