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"Automobile production"
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Does Adding Inventory Increase Sales? Evidence of a Scarcity Effect in U.S. Automobile Dealerships
What is the relationship between inventory and sales? Clearly, inventory could increase sales: expanding inventory creates more choice (options, colors, etc.) and might signal a popular/desirable product. Or, inventory might encourage a consumer to continue her search (e.g., on the theory that she can return if nothing better is found), thereby decreasing sales (a scarcity effect). We seek to identify these effects in U.S. automobile sales. Our primary research challenge is the endogenous relationship between inventory and sales—e.g., dealers influence their inventory in anticipation of demand. Hence, our estimation strategy relies on weather shocks at upstream production facilities to create exogenous variation in downstream dealership inventory. We find that the impact of adding a vehicle of a particular model to a dealer’s lot depends on which cars the dealer already has. If the added vehicle expands the available set of submodels (e.g., adding a four-door among a set that is exclusively two-door), then sales increase. But if the added vehicle is of the same submodel as an existing vehicle, then sales actually decrease. Hence, expanding variety across submodels should be the first priority when adding inventory—adding inventory within a submodel is actually detrimental. In fact, given how vehicles were allocated to dealerships in practice, we find that adding inventory actually lowered sales. However, our data indicate that there could be a substantial benefit from the implementation of a “maximize variety, minimize duplication” allocation strategy: sales increase by 4.4% without changing the total number of vehicles at each dealership.
This paper was accepted by Vishal Gaur, operations management.
Journal Article
Toward an understanding of learning by doing
We investigate learning by doing using detailed data from a major auto producer’s assembly plant. We focus on the acquisition, aggregation, transmission, and embodiment of the knowledge stock built through learning. We find that most knowledge was not retained by plant workers despite their importance as a learning conduit. This is consistent with the plant’s systems for productivity measurement and improvement. We further explore how learning at the hundreds of processes along the production line undergirds plantwide productivity. Our results shed light on how productivity gains accrue at the plant level and how firms apply managerial inputs to expand production.
Journal Article
Management Practices, Relational Contracts, and the Decline of General Motors
General Motors was once regarded as the best-managed and most successful firm in the world. However, between 1980 and 2009, GM's US market share fell from 46 to 20 percent, and in 2009 the firm went bankrupt. We argue that the conventional explanation for this decline—namely high legacy labor and healthcare costs—is seriously incomplete, and that GM's share collapsed for many of the same reasons that many highly successful American firms of the 1960s were forced from the market, including a failure to understand the nature of the competition they faced and an inability to respond effectively once they did. We focus particularly on the problems GM encountered in developing the relational contracts essential to modern design and manufacturing, and we discuss a number of possible causes for these difficulties. We suggest that GM's experience may have important implications for our understanding of the role of management in the modern, knowledge-based firm and for the potential revival of manufacturing in the United States.
Journal Article
The evolution of lean Six Sigma
Purpose - Although research has been undertaken on the implementation of lean within various industries, the many tools and techniques that form the \"tool box\", and its integration with Six Sigma (mainly through case studies and action research), there has been little written on the journey towards the integration of the two approaches. This paper aims to examine the integration of lean principles with Six Sigma methodology as a coherent approach to continuous improvement, and provides a conceptual model for their successful integration.Design methodology approach - Desk research and a literature review of each separate approach is provided, followed by a view of the literature of the integrated approach.Findings - No standard framework for lean Six Sigma or its implementation exists. A systematic approach needs to be adopted, which optimises systems as a whole, focusing the right strategies in the correct places.Originality value - This paper contributes to knowledge by providing an insight into the evolution of the lean Six Sigma paradigm. It is suggested that a clear integration of the two approaches must be achieved, with sufficient scientific underpinning.
Journal Article
An Approach to Predicting Energy Demand Within Automobile Production Using the Temporal Fusion Transformer Model
The increasing share of renewable energies within energy systems leads to an increase in complexity. The growing complexity is due to the diversity of technologies, ongoing technological innovations, and fluctuating electricity production. To continue to ensure a secure, economical, and needs-based energy supply, additional information is needed to efficiently control these systems. This impacts public and industrial supply systems, such as vehicle factories. This paper examines the influencing factors and the applicability of the Temporal Fusion Transformer (TFT) model for the weekly energy demand forecast at an automobile production site. Seven different TFT models were trained for the weekly forecast of energy demand. Six models predicted the energy demand for electricity, heat, and natural gas. Three models used a rolling day-ahead forecast, and three models predicted the entire week in one step. In the seventh model, the rolling day-ahead forecast was used again, with the three target values being predicted in the same model. The analysis of the models shows that the rolling day-ahead forecasting method with a MAPE of 13% already delivers good results in predicting the electrical energy demand. The prediction accuracy achieved is sufficient to use the model outcomes as a basis for weekly operational planning and energy demand reporting. However, further improvements are still required for use in automated control of the energy system to reduce energy procurement costs. The models for forecasting heat and natural gas demands still show too high deviations, with a MAPE of 62% for heat demand and a MAPE of 39% for natural gas demand. To accurately predict these demands, further factors must be identified to explain the demand.
Journal Article
The Knowledge Spillover Effect of Multi-Scale Urban Innovation Networks on Industrial Development: Evidence from the Automobile Manufacturing Industry in China
Multi-scale urban innovation networks are important channels for intra- and inter-city knowledge spillovers and play an important role in urban industrial innovation and growth. However, there is a lack of direct evidence on the impact of multi-scale urban innovation networks on industrial development. Drawing upon the “buzz-and-pipeline” model, this paper analyzes the impact of multi-scale urban innovation networks on industrial development by taking the automobile manufacturing industry in China’s five urban agglomerations as an example. Firstly, based on the Form of Correlation between International Patent Classification and Industrial Classification for National Economic Activities (2018) and co-patents, we construct urban innovation networks on three different geographical scales, including intra-city innovation networks, inter-city innovation networks within urban agglomerations, and innovation networks between cities within and beyond urban agglomerations. Then, we employ the ordinary least squares model with fixed effects at the urban agglomeration level to explore the impact of urban multi-scale knowledge linkages on the development of the automobile manufacturing industry and the results showed that urban innovation networks at three different geographical scales have different impacts on industrial development. Specifically, intra-city innovation networks have a facilitating effect on industrial development, while both inter-city innovation networks within urban agglomerations and innovation networks between cities within and beyond urban agglomerations have an inverted U-shaped impact on industrial development. The interactions between urban innovation networks on three different geographical scales have a negative effect on industrial development. Simultaneously, the agglomeration level of urban industry plays a positive moderating role in the impacts of multi-scale urban innovation networks on industrial development.
Journal Article
Nash equilibrium as a tool for the Car Sequencing Problem 4.0
This paper introduces a new concept to solve car sequencing problem called the Car Sequencing Problem 4.0, focuses the paint shop. The problem of effective car sequencing in the paint shop is caused by the specifics of the production process itself and the structure of the production line. Sequencing of cars as required by the painting process is justified economically. The main goal is to minimize the number of costly changeovers of the painting guns because of color changes and to synchronize those with periodic cleanings, forced by technological requirements. For this purpose, a buffer located in the paint shop is applied. In this paper a game theoretic framework is presented to analyze the problem. Three games are introduced: Buffer Slot Assignment Game–Buffer-OutShuttle Game called the BSAG-BOSG, In–Out Shuttle Game and its modification called modified In–Out Shuttle Game. Based on the simulations performed the efficiency of the algorithms is verified using several datasets.
Journal Article
Understanding Chinese automobile firms: past, present and path to be world class
Purpose
This paper aims to quest the strategies and paths of Chinese automobile firms for being world class. It analyzes their strengths and potentials in comparison with the development experience of the global examples and provides policy recommendations for cultivating world-class automobile firms.
Design/methodology/approach
The authors apply the analytic hierarchy process method to evaluate the competitiveness of automobile firms with multiple indicators.
Findings
The evaluation results suggest that Chinese automobile firms still lagged behind their world-class peers. Especially, Chinese domestic firms developed unevenly so that they could not make progress in the core parametric dimensions. Nevertheless, Chinese firms could achieve world class, at least in some niche segments, supported by its accumulated technological capacity and tremendous market size.
Originality/value
This research is the first scholarly work to evaluate the competitiveness of Chinese automobile firms and provides insightful comments on its industrial policies in the automobile industry. This may be valuable for policymaking in the automobile sector of China and other developing economies.
Journal Article