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The Western-centric nature of research into corporate social responsibility (CSR) has left gaps in one’s understanding of local culture's role in augmenting or undermining the impact of firms' CSR policies. This paper constructs and tests variables measuring “Confucian values” mediation between Chinese employees' perceived CSR and their job satisfaction, organizational commitment and organizational citizenship behavior.

The hypotheses were tested through structural equation modeling, using data from 311 responses completed by employees at Chinese private companies, located in China's Cheng-Yu economic area (Chongqing and Chengdu).

Chinese employees' perceived CSR had a positive significant effect on job attitudes (job satisfaction and organizational commitment). However, perceived CSR had no significant positive impact on organizational citizenship behavior. The authors also found that Confucian values are a partial mediator between perceived CSR and job attitudes and a full mediator between perceived CSR and organizational citizenship behavior.

The results enrich one’s understanding of cultural values in these relationships and suggest further research into how firms and governments in Confucian-based societies can better operationalize Confucian values to argument the firm's and country's CSR identity, thus improving job attitudes and public relations among customers who share this cultural heritage. For non-Confucian societies and foreign firms operating in China, the results encourage searches for Confucian value substitutes, such as trust and education, to incorporate into CSR mechanisms that promote these values among employees. The authors suggest approaches for furthering these agendas.

Consumption volatility is a key source of economic growth volatility; thus, it is an important factor in designing macroeconomic policy. The purpose of this paper is to investigate the factors that determine household consumption volatility, using urban household survey (UHS) data over the period 2002–2009 in 18 provinces in China.

Both a traditional variance decomposition method and an advanced variance decomposition method are used.

The traditional variance decomposition method suggests that heterogeneity of consumption goods is the key to analyze consumption volatility in China. Consumption of transportation makes the highest aggregate contribution and per-unit volatility in consumption volatility, whereas consumption of food makes the second highest aggregate contribution and the lowest per-unit volatility. Further investigation with the advanced variance decomposition method, which allows the authors to capture intertemporal dynamics and cross-household differences simultaneously, finds that the main factor determining the consumption volatility in China is intertemporal dynamics, rather than cross-household differences.

Future research could fruitfully explore four issues. First, consumption upgrading has increased the volatility of China’s household consumption. How much will this affect economic growth in China under its “new normal” conditions, and how should the Chinese government respond? Second, differences between UHS data and aggregate data in the calculations of consumption risk sharing need to be investigated. Third, it is important to investigate the channels through which the Chinese government can enhance its ability to spread consumption risks and thus reduce consumer consumption volatility. Finally, further study could extend the current 18 provinces to a nation-wide sample and update the data beyond 2009 to estimate the impact of the global financial crisis.

The results suggest that when policy makers design macroeconomic policies to smooth consumption volatility, they should consider heterogeneity in household consumption goods, regional disparity and intertemporal dynamics simultaneously. Well-managed volatility of Chinese household consumption can contribute to a stable economic growth in China and the world.

Well-managed volatility of Chinese household consumption can contribute to a stable economic growth in China and the world.

This paper fills this gap by using China’s UHS data to assess consumption volatility from the perspectives of heterogeneity in household consumption goods, cross-household differences and intertemporal dynamics. We make three contributions to the literature. The first contribution of this paper consists of demonstrating the contributions of heterogeneity in household consumption goods to consumption volatility. The second contribution consists of using the advanced variance decomposition method proposed by Crucini and Telmer (2012). This decomposition methodology allows the authors to examine whether household consumption volatility is due to cross-household differences or intertemporal dynamics. The third contribution is that this paper takes Chinese residents’ consumption fluctuations as the starting point to analyze the impact of consumption fluctuations on the future trend of China’s economy.

The purpose of this paper is to investigate the nonlinear dynamics of the aircraft assembly lines. An approach for modeling and analyzing the production rate of an aircraft assembly line is introduced using the chaos theory.

First, two key system variables including reliability and learning ability are considered to control the dynamics model. The discrete-time dynamics equation of the production rate is established as a function of the reliability and the learning rate. Then an improved Gauss-learning curve is proposed and applied to aircraft assembling condition. Finally, the bifurcation diagrams and the maximal Lyapunov exponents are used and applied to the experimental study to analyze the dynamic behavior under different combinations of parameters.

On the basis of the experimental study, it is shown that chaotic behavior really exists in the aircraft assembly lines. The reliability and the Gauss-learning curve can nonlinearly affect the production rate.

This paper applied nonlinear dynamics and chaotic theory to the production analyses of the aircraft assembly lines for the first time. The proposed model has been successfully applied to a practical case, and the result justifies its advantage as well as feasibility to both theory and engineering application.

This study aims to investigate the factors that influence young consumers' purchase intention towards dietary supplements (DS) in Malaysia.

The supplement industry in Malaysia has been growing rapidly recently due to a paradigm shift in healthcare management, from curative to prevention. Thus, it has sparked interest to conduct a study on the factors that influence young consumers' purchase intentions towards DS. With a response rate of 74.5%, a survey questionnaire was used to elicit data from 149 Gen-Y respondents who consume supplements on a regular basis.

The results revealed that the influencing factors towards purchase decisions among these Gen-Y respondents aged between 17 and 25 are based on product knowledge and product quality. The implications of these findings and directions for future research are outlined at the end of this paper.

This study offers empirical insights from the perspective of an emerging digital economy on the factors that influence young consumers' purchase intentions towards DS in Malaysia.

Literature indicates that global geographic diversification (GD) has mixed effects on a multinational corporation’s (MNC) performances. The purpose of this paper is to examine how an MNC’s GD influences its stock market and financial performances directly and indirectly via operational performance (i.e. changes in inventory levels).

Using firm-level data collected from Compustat database for the period 2000-2011 and estimating a mediating regression model, the authors examine the direct and indirect effects of GD on an MNC’s stock market (Tobin’s q) and financial performances (ROA), with inventory level being a mediator. Additionally, the examination is implemented separately under two economic situations: financial crisis vs without financial crisis.

The results show that GD enhances an MNC’s stock market performance, while deteriorating its financial performance in the presence of a financial crisis. In contrast, GD has little direct impact on an MNC’s stock market and financial performances during periods without financial crisis. The indirect effects of GD are mediated by changes in inventory levels.

This study suggests that MNCs need to carefully weigh the benefits and costs of global strategy obtained through GD. The results also indicate that GD is highly appreciated by the stock market investors during economic downturns and tighter inventory management may further enhance firm values.

This paper is the first empirical research to estimate both direct and indirect effects of GD via inventory in the operations management literature, highlighting the value of GD depending on the different economic situations and echoing the role of operations in implementing GD.

This study aims to provide a time- and price-sensitive market strategy for merchants to handle the markdown price strategy. The market demand for perishable products is usually price – and quality (freshness) – sensitive. The proper handling of markdown-price strategies can help merchants enhance competitiveness and maximize operational performance.

A markdown strategy consisting of price and markdown time was developed to explore the properties of market strategies based on the dynamic quality evaluation. The strategy considers multiple price discounts and multiple markdown times. The optimal price decisions in each stage and the optimal markdown times were derived during the selling season.

The results showed the following. A retailer always raises the initial price if it wants to adopt multiple price-markdown strategies. A high initial price may lead to a high inventory at the early stage and bring the next price reduction in advance. Large price discounts can be used to reduce the inventory later. The higher the previous price, the shorter the interval between the next price reduction. The markdown strategies showed that the regular discount as a new business model is not the best pricing model for perishable products. A time- and price-sensitive strategy, however, can increase operational performance and provide new insights for perishable products.

The results showed the following. A retailer always raises the initial price if it wants to adopt multiple price-markdown strategies. A high initial price may lead to a high inventory at the early stage and bring the next price reduction in advance. Large price discounts can be used to reduce the inventory later. The higher the previous price, the shorter the interval between the next price reduction. The markdown strategies showed that the regular discount as a new business model is not the best pricing model for perishable products. A time- and price-sensitive strategy, however, can increase operational performance and provide new insights for perishable products.

Enhancing the initiative and enthusiasm of emergency preparedness behaviors among Medical and Health Organization (MHO) staff is an effective measure to prevent and reduce losses from emergencies. In this study, emergency preparedness behavioral intentions were divided into noncooperative behavioral intentions (EPNCBI) and cooperative behavioral intentions (EPCBI) to discuss the impact brought by quality of life (QoL). The mediating effects of psychological capital (PsyCap) and perceived organizational support (POS) were also considered.

A web-based questionnaire was used for MHO staff in China, and a structural equation analysis of the data collected from 243 participants was conducted to test the hypotheses.

The empirical results reveal that: (1) QoL had a positive effect on EPNCBI, PsyCap and POS; (2) PsyCap had a positive effect on EPNCBI and EPCBI; (3) POS had a positive effect on PsyCap and EPCBI; (4) PsyCap mediated the relationship between QoL and EPNCBI, and the relationship between POS and EPNCBI; (5) PsyCap and POS mediated the relationship between QoL and EPCBI.

Improving MHO staff’s QoL is an effective way to enhance positive behavioral outcomes. Furthermore, these findings could provide managers with valuable insight focusing their limited resources on enhancing the emergency preparedness of MHO staff by reinforcing the level of PsyCap and POS.

This study provides important updated considerations for the application of positive psychology in the field of emergency preparedness.

Modeling and analysis of dimensional variation propagation is a crucial support technology for variation reduction, product/process design evaluation and recognition of variation source. However, owing to the multi-deviation (i.e. part deviations and fixture deviations) and multi-interaction (i.e. part-to-part interaction, part-to-fixture interaction and station-to-station interaction) in assembly processes, it is difficult for designers to describe or understand the variation propagation (or accumulation) mechanism clearly. The purpose of this paper is to propose a variation propagation modeling and analysis (VPMA) method based on multiple constraints aiming at a single station.

Initially, part-to-part constraints (PPCs) and part-to-fixture constraints (PFCs) are applied for the multi-interaction of assembly, and multiple constraints graph (MCG) model is proposed for expressing PPCs, PFCs, parts, as well as the variation propagation relation among them. Then, locating points (LPs) are adopted for representing the deviations in constraints, and formulas for calculating the deviations of LPs are derived. On that basis, a linearized relation between LPs’ deviations and part’s locating deviations is derived. Finally, a wing box is presented to validate the proposed method, and the results indicate the methodology’s feasibility.

MCG is an effective tool for dimensional VPMA, which is shown as an example of this paper.

Functions of geometric constraints in dimensional variation propagation are revealed, and MCG is proposed to formulize dimensional variation propagation.

Design is a time-consuming process for mechanical production. Some design structures frequently occur in different products and can be shared by multiple assembly models. Thus, identifying these structures and adding them to a design knowledge library significantly speed up the design process. Most studies addressing this issue have traditionally focused on part models and have not extended to assembly models. This paper aims to find a method for common design structure discovery in assembly models.

Computer-aided design models have a great deal of valuable information defined by different designers in the design stages, especially the assembly models, which are actually carriers of information from multiple sources. In this paper, an approach for discovering a common design structure in assembly models is proposed by comparing information from multiple sources. Assembly models are first represented as attribute connection graphs (ACGs), in which we mainly consider topological information and various attributes of parts and connections. Then, we apply a K-means clustering method based on a similarity analysis of different attributes to classify the parts and connections and transform ACGs of assemblies into type code graphs (TCGs). After this, a discovery algorithm that improves upon fast frequent subgraph mining is used to identify common design structures in assemblies.

A new method was developed for discovering common design structures in assembly models, considering the similarity of information from multiple sources and allowing some differences in the details to keep both commonalities and individualities of common design structures.

Experiments show that the proposed method is efficient and can produce a reasonable result.

This discovery method helps designers find common design structures from different assembly models and shorten the design cycle. It is an effective approach to build a knowledge library for product design that can shorten the design cycle.