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Abnormal behaviors such as rework, backlog, changes and claims generated by project organizations are unavoidable in complex projects. When abnormal behaviors emerge, the previously normal state of interactions between organizations will be altered to some extent. However, previous studies have ignored the associations and interactions between organizations in the context of abnormal organizational behaviors (AOBs), making this challenging to cope with AOBs. As a result, the objective of this paper is to explore how to reduce AOBs in complex projects at the organizational level from a network perspective.

To overcome the inherent limitations of a single case study, this research integrated two data collection methods: questionnaire survey and expert scoring method. The questionnaire survey captured the universal data on the influence possibility of AOBs between complex project organizations and the expert scoring method got the influence probability scores of AOBs between organizations in the case. Using these data, four organizational influence network models of AOBs based on a case were developed to demonstrate how to destroy AOBs networks in complex projects using network attack theory (NAT).

First, the findings show that controlling AOBs generated by key organizations preferentially and improving the ability of key organizations can weaken AOBs network, enabling more effective coping strategies. Second, the owners, government, material suppliers and designers are identified as key organizations across all four influence networks of AOBs. Third, change and claim behaviors are more manageable from the organizational level.

Project managers can target specific organizations for intervention, weaken the AOBs network by applying NAT and achieve better project outcomes through coping strategies. Additionally, by taking a network perspective, this research provides a novel approach to comprehending the associations and interactions between organizations in the context of complex projects.

This paper proposes a new approach to investigating AOBs in complex projects by simultaneously examining rework, backlog, change and claim. Leveraging NAT as a novel tool for managing the harmful effects of influence networks, this study extends the knowledge body in the field of organizational behavior (OB) management and complex project management.

This study aims to explore how the concept of extended self-influences luxury shopping tourism consumption among Chinese tourists. It explores why luxury shopping is important for Chinese tourists. Specifically, this study focuses on a strategically important emerging market segment: post-1990s female Chinese tourists.

To explore the link between the extended self and luxury shopping tourism consumption among post-1990s Chinese female tourists, this study adopted a qualitative and interpretive approach. A total of 22 semi-structured in-depth interviews were carried out to collect the data.

This qualitative inquiry found that luxury shopping during overseas holidays has some subtle differences from luxury shopping in China, as the conceptualisation of luxury is highly context-based. Through a focus on gender and generational differences, the current study reveals that the idea of individuality has started to influence their luxury purchases.

The study shows how different selves are associated with luxury shopping. It thus provides empirical evidence regarding the reasons behind their motivation, especially for shopping overseas to get a good price and an exclusive and enjoyable luxury shopping experience abroad. Also, it was found that curiosity about buying luxury products is viewed as less favoured and logical shopping will be a future trend. Individuality is becoming a trend for younger consumers.

Theoretically, by linking the “extended self” with luxury shopping tourism, this study provides the social-psychological aspects of luxury shopping tourism. Instead of focusing on particular destinations, this study provides compressed but also focused inquiries to explore how the concept of the self-influences post-1990s female Chinese tourists’ shopping consumption while on holiday, and how this luxury shopping experience influences their concept of the self.

本文运用“延伸自我”概念对中国泳客在境外购买奢侈品的行为和意义进行探讨, 从而进一步了解中国游客对奢侈品的消费形态。 研究主要专注在中国90后女性市场, 女性市场已被许多学者以即市场营销人员认定为新兴市场领域。

通过22个深度访谈的所得数据表明境外奢侈品高买行为与自我概念有着紧密的联系, 并为消费者购买动机背后的原因提供了实证

在境外旅游过程中购买奢侈品有非常大的价格优势, 同时又能为消费者提供独特的购物体验, 中国90后女性的奢侈品购买行为日趋理性并在出行之前做好详细的购物计划, 个性的展示将成为中国年轻女性奢侈品消费的主导因素。

该研究的理论贡献是探索自我概念如何影响90年代后中国女性游客在境外旅行度假时的奢侈品购物行为, 以及这种奢侈品购物体验如何影响其自我概念。

关键词 购物，中国游客，女性， 延伸自我，自我概念

文章类型 研究论文

El estudio se dedica a explorar cómo influir el conceptöauto-extensión¨ al comportamiento de comprar los artículos de lujo en el extranjero entre los chinos turísticos, también a explorar la importancia de tal caso para ellos.

Este estudio ha adaptado un enfoque cualitativo entre 22 entrevistas en profundidad semiestructuradas para la recopilación de datos y muestra cómo se asocian diferentes seres con las compras de lujo.

Por lo tanto, se proporciona las pruebas evidentemente sobre las razones detrás de su motivación. Comprar artículos de lujo durante los viajes al extranjero tiene una gran ventaja de precio, al tiempo que las ofrece una experiencia especial. Estos actos se están volviendo más racionales y tienen planes de compras detallados antes de viajar. La exhibición de la personalidad se convertirá en el factor dominante en cuanto al consumo de artículos de lujo por parte de tales chinas.

Principalmente se enfoca a un nuevo campo del mercado en lo cual los consumidores son las chicas quienes nacieron después del año 1990.

This study reveals the green building development path and analyzes the optimal government subsidy equilibrium through evolutionary game theory and numerical simulation. This was done to explore the feasible measures and optimal incentives to achieve higher levels of green building in China.

First, the practice of green building in China was analyzed, and the specific influencing factors and incentive measures for green building development were extracted. Second, China-specific evolutionary game models were constructed between developers and homebuyers under the market regulation and government incentive mechanism scenarios, and the evolutionary paths were analyzed. Finally, real-case numerical simulations were conducted, subsidy impacts were mainly analyzed and optimal subsidy equilibriums were solved.

(1) Simultaneously subsidizing developers and homebuyers proved to be the most effective measure to promote the sustainability of green buildings. (2) The sensitivity of developers and homebuyers to subsidies varied across scenarios, and the optimal subsidy level diminished marginally as building greenness and public awareness increased. (3) The optimal subsidy level for developers was intricately tied to the building greenness benchmark. A higher benchmark intensified the developer’s responsiveness to losses, at which point increasing subsidies were justified. Conversely, a reduction in subsidy might have been appropriate when the benchmark was set at a lower level.

The expeditious advancement of green buildings holds paramount importance for the high-quality development of the construction industry. Nevertheless, the pace of green building expansion in China has experienced a recent deceleration. Drawing insights from the practices of green building in China, the exploration of viable strategies and the determination of optimal government subsidies stand as imperative initiatives. These endeavors aim to propel the acceleration of green building proliferation and materialize high-quality development at the earliest juncture possible.

The model is grounded in China’s green building practices, which makes the conclusions drawn more specific. Furthermore, research results provide practical references for governments to formulate green building incentive policies.

The traditional vision system cannot automatically adjust the feature point extraction method according to the type of welding seam. In addition, the robot cannot self-correct the laying position error or machining error. To solve this problem, this paper aims to propose a hierarchical visual model to achieve automatic arc welding guidance.

The hierarchical visual model proposed in this paper is divided into two layers: welding seam classification layer and feature point extraction layer. In the welding seam classification layer, the SegNet network model is trained to identify the welding seam type, and the prediction mask is obtained to segment the corresponding point clouds. In the feature point extraction layer, the scanning path is determined by the point cloud obtained from the upper layer to correct laying position error. The feature points extraction method is automatically determined to correct machining error based on the type of welding seam. Furthermore, the corresponding specific method to extract the feature points for each type of welding seam is proposed. The proposed visual model is experimentally validated, and the feature points extraction results as well as seam tracking error are finally analyzed.

The experimental results show that the algorithm can well accomplish welding seam classification, feature points extraction and seam tracking with high precision. The prediction mask accuracy is above 90% for three types of welding seam. The proposed feature points extraction method for each type of welding seam can achieve sub-pixel feature extraction. For the three types of welding seam, the maximum seam tracking error is 0.33–0.41 mm, and the average seam tracking error is 0.11–0.22 mm.

The main innovation of this paper is that a hierarchical visual model for robotic arc welding is proposed, which is suitable for various types of welding seam. The proposed visual model well achieves welding seam classification, feature point extraction and error correction, which improves the automation level of robot welding.

Browsing knowledge documents in a peer-to-peer (P2P) environment is difficult because knowledge documents in such an environment are large in quantity and distributed over different peers who organize the documents according to their own views. This paper aims to propose a method for constructing a personal knowledge map for a peer to facilitate knowledge browsing and alleviate information overload in P2P environments.

The research presents a method for constructing a personal knowledge map. The method adopts an ontology-concept-tree-based classification algorithm to recognize a peer’s personal knowledge structure and construct a personal knowledge map, and uses a self-organizing map algorithm to cluster and visualize the knowledge documents. The correctness of the created knowledge map is evaluated with a collection of abstracts of academic papers.

The method for constructing a personal knowledge map is the main finding of this research. The evaluation shows that the created knowledge map is good in quality.

The proposed method provides a way for P2P platforms to understand their users’ knowledge background, as well as to improve the P2P platform environment. However, the proposed method will not help a peer when he has nothing in his individual knowledge document repository (i.e. the “cold start” problem). The method also requires a relatively good ontology base for a P2P document sharing system to use the method effectively.

It is novel that the proposed method organizes the knowledge documents related to a peer’s knowledge background into a personal knowledge map. Moreover, the created knowledge map combines the advantages of a hierarchical display and a map display. It has values for a distributed P2P environment to facilitate users’ knowledge browsing and to alleviate information overload.

This paper is written as an attempt to employ the Chinese Social Science Citation Index (CSSCI) in the evaluation of Chinese humanities and social science research.

This paper uses statistics in the CSSCI (2000‐2004) to analyze the academic impact of researchers, papers and works, institutions and regions on Chinese humanities and social science research.

The authors identify 100 highly cited people, 50 highly cited papers, 50 highly cited works, 20 highly productive institutions and 20 highly cited institutions. Also provided is some regional information about Chinese humanities and social science research.

It is hoped that the CSSCI, as well as the analysis and evaluation based on it, will give researchers a better understanding of Chinese humanities and social science research.