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The well-operating condition of journal bearing is the assurance to keep superior performance of water-lubricated twin-screw compressor. To design the journal bearing more reasonably for this type of compressor, this paper aims to study the effects of rotating speed and design parameters on bearing characteristics, considering surface roughness and bending deformation of the shaft at the same time.

The average Reynolds equation considering the effect of surface roughness is adopted and solved by finite difference method and successive over-relaxation method to calculate pressure distribution with real bearing shapes and boundary conditions. The bending deformation of the shaft is calculated using simply supported beam model of variable cross-section.

The dynamic lubrication characteristics of four water-lubricated journal bearings in twin-screw air compressor are calculated and analyzed. In addition, the static characteristics of journal bearing including friction coefficient, film thickness ratio distribution and water film pressure distribution are calculated numerically with different rotating speed and design parameters. Moreover, some design principles of water-lubricated bearing for twin-screw compressor are put forward.

The lubrication characteristics of the water-lubricated journal bearing in twin-screw air compressor are calculated considering surface roughness and bending deformation of the shaft at the same time. The paper’s results may provide design guidelines for journal bearing in this kind of twin-screw compressor.

Compared with the fierce price competition in 1998, the well‐order price competition is witnessed in Chinese iron and steel industry now and the pricing behaviors of steel firms also follow the certain rules. Based on the methods of collecting the secondary data and interviewing, this paper examines the pricing behaviors of firms to explain the how Chinese steel firms make their pricing decisions and maintain the well‐order competitive relationship among them. The authors found out that (1) most Chinese steel companies adopt a kind of strategic perspective in their pricing decision making, in which understanding of the market trend and the close attention to their competitors are both important; (2) there obviously exists price leader and followers in Chinese iron and steel industry, and the relationship between price leader and followers is relatively stable and the factor behind this phenomenon is the existence of a kind of informal platform of communication among competitors, government and trade associations.

The purpose of this paper is to simplify the Explicit Nonlinear Model Predictive Controller (ENMPC) by linearizing the trajectory with Quantum-behaved Pigeon-Inspired Optimization (QPIO).

The paper deduces the nonlinear model of the quadrotor and uses the ENMPC to track the trajectory. Since the ENMPC has high demand for the state equation, the trajectory needed to be differentiated many times. When the trajectory is complicate or discontinuous, QPIO is proposed to linearize the trajectory. Then the linearized trajectory will be used in the ENMPC.

Applying the QPIO algorithm allows the unequal distance sample points to be acquired to linearize the trajectory. Comparing with the equidistant linear interpolation, the linear interpolation error will be smaller.

Small-sized quadrotors were adopted in this research to simplify the model. The model is supposed to be accurate and differentiable to meet the requirements of ENMPC.

Traditionally, the quadrotor model was usually linearized in the research. In this paper, the quadrotor model was kept nonlinear and the trajectory will be linearized instead. Unequal distance sample points were utilized to linearize the trajectory. In this way, the authors can get a smaller interpolation error. This method can also be applied to discrete systems to construct the interpolation for trajectory tracking.

The purpose of this paper is to integrate the corporate market and non‐market behaviors (such as social, legal, and political activities) into the research of competitive interaction.

“Structured content analysis” is used in analyzing the longitudinal data of five real estate enterprises from an industrial journal during the last seven years.

Competitive interactions with market and non‐market contents involve the expanded competitive scope, behaviors, and relationships. New explanations beyond previous literatures are provided to explain the expanded competitive behaviors (especially in resource‐oriented and mixed scope) by analyzing the characteristics of actions and responses.

Firms must effectively focus on the interaction of market and non‐market competitive behaviors. Industrial competitors in the market environment can engage in collaborative or cooperative actions with non‐market issues in order to obtain collective benefits.

This paper expands on previous studyies of competitive interaction by integrating the important non‐market content, especially categorizing it in the Chinese transitional environment with typical evidence.

Despite the importance of innovation in business performance, investigation into innovation in services is scanty and lacking consensus. In retailing, it is a topic that has been awakening considerable academic and business interest in recent years. In this study context, this work aims to analyse innovation in retail experiences from two aspects – marketing innovation and technological innovation – to understand the role it exercises in satisfaction and subsequent recommendation.

The authors’ objective is to investigate the direct and indirect influence of marketing and technological innovation on satisfaction and word-of-mouth (WOM) through three core constructs: store image, consumer value and store brand equity. SEM methodology is applied on a sample of 820 retail customers of grocery, clothing, furniture an electronics store.

The results show that technological innovation is more important than marketing innovation in shaping image, value and satisfaction. At the same time, store image is the variable that most influences customer satisfaction and that satisfaction is a very significant antecedent of WOM behaviour. Practical implications for retail managers and further research are presented.

The main value of this work has been to go deeper into the study of retail innovation, both in marketing and technologies, and its direct and indirect effects on satisfaction and subsequent recommendation through store image, consumer value and store brand equity. It is a new line of study, which is still fragmented and with little empirical evidence.

Infrastructural revolution, intense competition and customer attraction towards organised apparel retailing in India are potentially affecting traditional retailing. The authors seek to identify the factors that customers perceive during shopping in organised apparel retail store. This study also investigates the indirect effects of identified factors on behavioural outcomes such as loyalty.

The study randomly selected the customers immediately after shopping to minimise the experience's carryover effects. A sample of 648 customers was collected. Data were analysed using multivariate analysis of covariance.

The study has found that in-store logistics is the second order factor with ease of return, on-shelf availability, product accessibility, shopping convenience, and product information as the variables. The result shows that in-store logistics, store environment, store communication, merchandise assortment, perceived price and employee attribute influence customer satisfaction. As expected, these factors indirectly influence the loyalty.

This study focused on organised multi-brand apparel retailing, and the survey was conducted in a tier-II city of India only. Hence, any attempt to generalise the findings must be undertaken with caution.

In the context of multi-brand retailing, competition is fierce. New entrants and traditional apparel retailers hesitate to adopt organised apparel retailing. The findings of this study can be helpful for new entrants and traditional apparel retailers to adopt organised apparel retailing.

Previous studies in the field of multi-brand retailing have mainly focused on the marketing aspect of retail stores. This study contributes to the operations aspect and tests the impact of operational function (in-store logistics) on customer satisfaction.

Negotiation is crucial to business alliances, but this process can become more complicated if there are language barriers and differences in cultural values, customs, and lifestyles, such as Western businesses negotiating in the People’s Republic of China (PRC). Previous studies have presented models of the Chinese negotiating process but these are primarily from the US. This study examines the negotiating experiences of selected New Zealand investors who have had experiences negotiating either Foreign Direct Investment (FDI) or short‐term sales agreements in the PRC to create two conceptual models. The results provide some interesting insights for doing business in China.

The purpose of this paper is to comprehensively investigate the combined influence of a firm's political connection and diversification on corporate performance, and to explore whether firm's political connection has an impact on the diversification effect, and whether this diversification effect would promote its performance significantly or not.

The research used a regression model to explore the correlation among political connection, diversification strategy, and corporate performance. The research subjects are the private enterprises listed on Shanghai and Shenzhen Stock Exchange in China for the period 2002‐2005.

The study found that: first, for those firms without political connections, the relationship between diversification strategy and corporate performance displayed an “inverted U” curve; for firms with political connection, the relationship was a “reverse L”. Second, firms with political connections are more likely to implement a diversification strategy, especially unrelated diversification. Third, when implementing an internationalization strategy, private enterprises with political connections are more likely to expand through unrelated diversification strategy. Fourth, the diversification of the enterprises with political connection are more likely to promote the short‐term accounting performance than those without political connection, but the unrelated diversification of politically connected enterprises would have a negative impact upon its future performance, that is to damage the company's market value.

The paper expands the literature on the relationship between diversification and firm performance. It contributes to the research about the influence of political connection upon corporate performance.

The purpose of this paper is to explore the prediction of competitive response based on the characteristics of market and non‐market actions comprehensively, and develop a four‐stage decision‐making model of firm's competitive action, which is significant for Chinese practicing managers when formulating and implementing the strategies, and further predicting competitors' strategic choices.

The research adopted the method of structured content analysis and carried out the survey in Chinese home appliance industry, mainly covering the largest firms, including TCL, Hisense, Changhong, Konka, Haier, and Skyworth. The method of multiple regression analysis was employed to test the hypotheses.

The results show that in order to comprehensively forecast competitor's responding behaviors, the firms could not only limit their perspective to market field but also pay attention to non‐market. Additionally, in the process of dynamic interaction, the attacking or responding action is not independent and it is related significantly to another three type decisions, which are market and non‐market, strategic and tactic, and collective and individual. Further, the study asserts that, in market field, tactic activity is more likely to trigger competitor's response than strategic one, while in non‐market, the situation is just the opposite. Meanwhile, the study figured out that individual market attack is easier to trigger individual market and non‐market response, as well as collective market response. While for non‐market action, whatever it is individual or collective, both would be easy to provoke competitor's collective response.

The research findings extend the existing competitive interaction theory to non‐market field. When forecasting competitor's choice of the competitive action, the firms could not only limit their perspective to market field but also pay attention to non‐market, attaching importance to certain situation of competitor's taking such non‐market action as corporate philanthropy, etc. to launch an attack or a response for gaining competitive advantage.

Underground logistics system (ULS) is recognized as sustainable alleviator to road-dominated urban logistics infrastructure with various social and environmental benefits. The purpose of this study is to propose effective modeling and optimization method for planning a hub-and-spoke ULS network in urban region.

Underground freight tunnels and the last-mile ground delivery were organized as a hierarchical network. A mixed-integer programming model (MIP) with minimum system cost was developed. Then a two-phase optimization schema combining Genetic-based fuzzy C-means algorithm (GA-FCM), Depth-first-search FCM (DFS-FCM) algorithm and Dijkstra algorithm (DA), etc. was designed to optimize the location-allocation of ULS facilities and customer clusters. Finally, a real-world simulation was conducted for validation.

The multistage strategy and hybrid algorithms could efficiently yield hub-and-spoke network configurations at the lowest objective cost. GA-FCM performed better than K-means in customer-node clustering. The combination of DFS-FCM and DA achieved superior network configuration than that of combining K-means and minimum spanning tree technique. The results also provided some management insights: (1) greater scale economies effect in underground freight movement could reduce system budget, (2) changes in transportation cost would not have obvious impact on ULS network layout and (3) over 90% of transportation process in ULS network took place underground, giving remarkable alleviation to road freight traffic.

Demand pairs among customers were not considered due to lacking data. Heterogeneity of facilities capacity parameters was omitted.

This study has used an innovative hybrid optimization technique to address the two-phase network planning of urban ULS. The novel design and solution approaches offer insights for urban ULS development and management.