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The purpose of this paper is to investigate dynamic food demand in urban China, with use of a complete dynamic demand system – dynamic linear expenditure system-linear approximate dynamic almost ideal demand system (DLES-LA/DAIDS), which pushes forward the techniques of demand analysis.

The authors employ a transitionary demand process and develop a new approach of complete demand system with a two-stage dynamic budgeting: a strongly separable DLES in the first stage and a LA/DAIDS in the second stage. Employing provincial aggregate data (1995-2010) from the China urban household surveys, The authors estimated the demand elasticities for primary food products in urban China.

The results indicate that most primary food products are necessities and price inelastic for urban households in China. The authors also found that the dynamic model tends to yield relatively smaller expenditure elasticities in magnitude than the static models do due to the friction effect of dynamic adjusting costs, such as habit formation, switching costs, and learning process. However, the dynamic effects on own price elasticities are inconclusive due to the add-up restriction.

The research contributes to the demand analysis methodologically, and can be used for better projections in policy simulation models.

This paper methodologically relaxes the restrictive assumption of instant adjustment in static models and allows consumers to make a dynamic decision in food consumption. Empirically, the authors introduce a new complete dynamic demand model and carry out a case study with the use of urban household data in China.

To fully accommodate the correlations between semiconductor product demands and external information such as the end market trends or regional economy growth, a linear dynamic system is introduced in this chapter to improve forecasting performance in supply chain operations. In conjunction with the generic Gaussian noise assumptions, the proposed state-space model leads to an expectation-maximization (EM) algorithm to estimate model parameters and predict production demands. Since the set of external indicators is of high dimensionality, principal component analysis (PCA) is applied to reduce the model order and corresponding computational complexity without loss of substantial statistical information. Experimental study on certain real electronic products demonstrates that this forecasting methodology produces more accurate predictions than other conventional approaches, which thereby helps improve the production planning and the quality of semiconductor supply chain management.

This study investigates the dynamic production structure of the Japanese manufacturing industry by using the adjustment cost approach. The study is to shed some light on the unique dynamic structure of the Japanese manufacturing industry. The study attempts to help design and predict industrial policies that are implemented to enhance domestic investments by the Japanese government.

This study obtains a system of dynamic factor demand and output supply equations by applying the dual approach to the intertemporal value function as represented by the Hamilton–Jacobi equation. By using industrial panel data for 1973–2012 of the Japanese manufacturing industry, the study estimates the system of the behavioral equations and corresponding elasticities. The study uses hypothesis tests and dynamic elasticities to investigate the dynamic structure of the Japanese manufacturing industry.

Estimation results show that labor and capital are quasi-fixed variables that adjust about 0.2 percent annually to the long-run optimum levels. Estimated adjustment rates are very slow as often presumed about the Japanese manufacturing industry, which uses lifetime employment practice and slow decision-making process in investment decisions. The results also show that output supply and factor demand elasticities vary greatly depending on time horizon. Factor demand increases when its own price increases in the short run, suggesting that factor adjustment is mostly determined factor prices in the past due to sluggish factor adjustment. However, factor demand becomes a normal downward-sloping curve in the long run as factor adjustment gets completed.

Japanese manufacturing firms hire employees through lifetime contract to exploit the benefits of dynamic learning-by-doing and execute investments carefully considering all the possible impacts. Under the strategy, adjustment costs for changing workers and capital stock are minimized. Dynamic adjustment model is expected to shed some light on the unique dynamic structure of the Japanese manufacturing industry. However, researches regarding the dynamic factor adjustment of the Japanese manufacturing industry are hard to find. This study is expected to fill the research vacuum.

Motivated by recent research indicating that the operational performance of an enterprise can be enhanced by building a supporting data-driven environment in which to operate, this paper presents a simulation framework that enables an examination of the effects of applying smart manufacturing principles to conventional production systems, intending to transition to digital platforms.

To investigate the extent to which conventional production systems can be transformed into novel data-driven environments, the well-known constant work-in-process (CONWIP) production systems and considered production sequencing assignments in flowshops were studied. As a result, a novel data-driven priority heuristic, Net-CONWIP was designed and studied, based on the ability to collect real-time information about customer demand and work-in-process inventory, which was applied as part of a distributed and decentralised production sequencing analysis. Application of heuristics like the Net-CONWIP is only possible through the ability to collect and use real-time data offered by a data-driven system. A four-stage application framework to assist practitioners in applying the proposed model was created.

To assess the robustness of the Net-CONWIP heuristic under the simultaneous effects of different levels of demand, its different levels of variability and the presence of bottlenecks, the performance of Net-CONWIP with conventional CONWIP systems that use first come, first served priority rule was compared. The results show that the Net-CONWIP priority rule significantly reduced customer wait time in all cases relative to FCFS.

Previous research suggests there is considerable value in creating data-driven environments. This study provides a simulation framework that guides the construction of a digital transformation environment. The suggested framework facilitates the inclusion and analysis of relevant smart manufacturing principles in production systems and enables the design and testing of new heuristics that employ real-time data to improve operational performance. An approach that can guide the structuring of data-driven environments in production systems is currently lacking. This paper bridges this gap by proposing a framework to facilitate the design of digital transformation activities, explore their impact on production systems and improve their operational performance.

The purpose of this paper is to propose a novel demand response method for real‐time (RT) balancing markets, which relies on dynamic demand control (DDC) based on frequency linked RT prices.

A RT balancing market, where the RT price varies inversely with the system frequency, is described. In such a market, producers and consumers can get the RT price, simply by monitoring the frequency deviations themselves. Air conditioning load, the main contributor of summer peaks, is selected for DDC. A physically based model of air conditioner load is taken to simulate the load control. A smart load controller is proposed that changes the thermostat setting with deviations in grid frequency/RT price. Simple examples are simulated to show the load reductions achieved by DDC in a single air conditioner, a group of large number of air conditioners and a RT market consisting of four generation companies and four distribution companies.

The result of simulation on a single air conditioner shows that significant reduction in energy consumption can be achieved during severe frequency dips in a RT market. The results of simulation in an example of a RT market show that such load control not only results in better frequency control but also lowers the RT price of power.

The demand control mechanism suggested in this paper can be applied to Indian market setting but its applicability to other markets might be limited due to differing, reliability standards, market rules, and regulatory framework.

This paper finds that DDC by distribution companies based on RT price/frequency signal not only results in a significant benefit to these companies and consumers but also helps the system operator in frequency regulation. By making the demand‐side participate in frequency regulation, such control can potentially facilitate an increase in renewable energy portfolio.

Chinese beer consumption has undergone major changes within the last decade. The combination of a growing middle class and greater exposure to foreign products has resulted in a significant increase in beer imports. The authors examined transformations in this market and how beer preferences have changed over time. This study focuses on changes is origin-specific preferences (e.g. German beer and Mexican beer) as reflected by habit formation (i.e. dynamic consumption patterns) and changes in demand sensitivity to expenditure and prices.

The authors estimated Chinese beer demand – differentiated by source – using a generalized dynamic demand model that accounted for habit formation and trends, as well as the immediate and long-run effects of expenditures and prices on demand. The authors employed a rolling regression procedure that allowed for model estimates to vary with time. Preference changes were inferred from the changing demand estimates, with a particular focus on changes in habit formation, expenditure allocating behaviour, and own-price responsiveness.

Results suggest that Chinese beer preferences have changed significantly over the last decade, increasing for Mexican beer, Dutch beer and Belgian beer. German beer once dominated the Chinese market. However, all indicators suggest that German beer preferences are declining.

Although China is the world's third largest beer importing country behind the United States and France. Few studies have focused on this market. While dynamic analyses of alcoholic beverage demand are not new, this is the first study to examine the dynamics of imported beer preferences in China and implications for exporting countries.

The purpose of this paper is to investigate market competition for three product types of salmon (smoke, fresh and whole salmon) to understand whether supermarkets are exercising market power over salmon consumers in the UK retail market.

Competition and the corresponding pricing conduct among supermarkets are tested by applying dynamic structural simultaneous system equations and using similar data set used by Jaffry et al. (2003).

The results indicate that the market is competitive for fresh fillets and whole salmon but retailers appeared to exert some level of market power for smoke salmon. The hypothesis that market power is the same for all three products in the study was rejected; further indicating that the market for fresh products are competitive while retailers may be exercising market power over consumers for smoke salmon.

Current data limitations did not allow the investigation to cover the past few years in the modelling process. However, the results are still relevant as there have been no major structural changes in aquaculture products retailing landscape in the recent past.

Concerns over the supermarkets’ exercise of market power over consumers have prompted the competition authorities to continue investigating the situation in the UK supermarket sector since 1996. The most recent investigation by competition authorities was in 2006. In all cases, no evidence of market power was found despite increased market concentration. Results from this study generally uphold the claim of the competition authorities in the UK.

This is the first study to use a model within a structural econometric framework of firms to test for competitiveness of salmon products in the UK market place.

A systems approach is applied to UK personal sector holdings of unit trusts, UK company securities, public‐sector long‐term debt and overseas securities. In the long run, asset holdings are determined primarily by hedging considerations but in the short run there is evidence of speculative activity. Asset shares are influenced by relative yields (including capital gains), inflation, and real expenditure. A two‐step estimation procedure is used: a set of cointegration vectors are estimated for asset shares and dynamics are represented by a systems error feedback model. The four equation system is broadly consonant with the data and coefficient estimates are intuitively acceptable.