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Process flexibility (PF) is seen as a hedging instrument against demand uncertainty. This paper aims to examine capacity decisions for both flexible and dedicated processes under production policies such as make-to-order and make-to-stock. The study identifies some relative benefits, in terms of expected profit, of the process flexible plant over the dedicated ones. Furthermore, the advantage appears to be contingent upon the decision on the preset service level.

Using the sample-based optimization procedure, a detailed computational analysis is undertaken to identify the conditions under which a flexible plant is preferred over a dedicated plant. A combination of genetic algorithm and sample-based optimization procedure is used to capture the effects of preset service level. The factors controlled in this paper include the demand variance, demand correlation, capacity investment cost and the product price.

According to this study, in a dedicated process changing to a flexible process is not justified for the same level of demand correlation even with high demand variance. In fact, a strict control on the preset service level prefers the dedicated strategy. The advantage of a flexible plant increases as the demand correlation decreases, product price decreases, price asymmetry increases or capacity investment cost increases. With a preset service level constraint, a flexible process should be preferred to a dedicated one only when the capacity investment cost is high or the products have low contribution margins.

The PF index is introduced in this paper to measure the benefit of a flexible plant over a group of dedicated plants. The benefits were found to be contingent upon the decision on the required service level.

The purpose of this study is to categorize and analyse the drivers and barriers of Lean Manufacturing (LM) and subsequently, based on the structural model develop a house of lean management which will give an idea to the academicians and practitioners about the factors that are critical to implement lean practices in an organization.

A list of drivers and barriers was prepared based on the literature review and opinions from experts. Total Interpretive Structural Modelling (TISM) was utilized to build a structural hierarchy of the drivers and barriers of LM. The structural hierarchy was utilized to build the house of lean management.

Based on the hierarchy developed, the elements (drivers and barriers) of LM are classified into three groups: bottom-level, middle-level and top-level elements. To develop a house of lean management, bottom-level of elements were considered as a foundation, middle-level elements were considered as pillars and top-level elements were considered as a beam. Finally, foundation, pillars and beam of the house were used to support the roof (which is value to customers and profitability to firm).

The outcome of this research can assist researchers as well as practitioners to enhance the significant drivers and to reduce the impact of hazardous barriers for the better implementation of lean practices.

This research is a novel approach, as it visibly demonstrates both the drivers and barriers, examines the interrelationships among them in order and shows them pictorially as the house of lean management.

Addresses the dynamic, continual‐improvement nature of the JIT implementation process. Learning curves are incorporated to analyse the impact of continual reduction of processing time variation over time. The results provide valuable information on the relationship between the level of processing time variation, the output rate of the production system, and inventory between work processes. The methodology used in this study incorporates an additional dimension in analysing JIT. It also provides a general and effective tool for decision makers facing the complex task of implementing pull production processes.

This study aims to examine the effects of energy consumption on economic growth by means of a panel data analysis of 75 net energy-importing countries for the period 1990 to 2012.

For the purpose of the analysis, the countries are classified into two groups, and each group is then classified into subgroups. The first group is formed based on the energy import dependence of the countries and is classified into two subgroups according to whether their dependence is greater than or less than 50 per cent. The second group is formed based on the income level of the countries and is classified into four subgroups, specifically, low-income economies, lower-middle-income economies, upper-middle-income economies and high-income economies.

The findings obtained for both panel data and for each country indicate that there is a positive and statistically significant relationship between energy consumption and economic growth over the long term such that energy consumption contributes more to economic growth as the import dependence of the country decreases. Moreover, the effect of energy consumption on economic growth decreases as the income level of the country increases. This indicates that the efficient use of energy is as important as energy consumption, which is regarded as an important indicator of economic development.

The authors expect that these findings will make a valuable contribution to the results of future studies, as they analyze the relationships among the variables by including the energy intensities of the countries.

Este estudio examina los efectos del consumo de energía en el crecimiento económico, mediante un análisis de datos de panel de 75 países importadores netos de energía para el período 1990-2012.

A los efectos del análisis, los países se clasifican en dos grupos y cada grupo luego se clasifica en subgrupos. El primer grupo se forma en base a la dependencia de los países en materia de importación de energía y se clasifica en dos subgrupos según su dependencia sea superior o inferior al 50%. El segundo grupo se forma sobre la base del nivel de ingresos de los países y se clasifica en cuatro subgrupos: economías de ingresos bajos, economías de ingresos medios-bajos, economías de ingresos medios-altos y economías de ingresos altos.

Los hallazgos obtenidos, tanto para los datos de panel como para cada país, indican que existe una relación positiva y estadísticamente significativa entre el consumo de energía y el crecimiento económico a largo plazo, de modo que el consumo de energía contribuye más al crecimiento económico a medida que disminuye la dependencia de las importaciones del país. Además, el efecto del consumo de energía en el crecimiento económico disminuye a medida que aumenta el nivel de ingresos del país. Esto indica que el uso eficiente de la energía es tan importante como el consumo de la misma, que se considera un indicador importante del desarrollo económico.

Los autores esperan que estos hallazgos aporten una valiosa contribución para estudios futuros, ya que analizan las relaciones entre las variables mediante la inclusión de las intensidades de los países.

Consumo de energía, Crecimiento económico, Importadores netos de energía, Panel de datos

Artículo de investigación

Presents a hierarchical production planning (HPP) model that integrates aggregate‐type planning, family disaggregate planning, lot‐sizing, job scheduling and evaluation of the final production plans into a complete planning and scheduling system. In‐corporation of a simple heuristic scheduling algorithm into the HPP model is the primary contribution. The scheduling routine schedules the jobs based on just‐in‐time (JIT) concept and provides detailed shopfloor information such as job tardiness, bottleneck work centres, capacity level, inventory or shortage level and number of set‐ups. This information is critical for effective shopfloor management. Experimental results indicate that the performance of the present model is better than the existing models in general. However, the model is truly superior under tight capacity conditions.

When is it more profitable for multinational manufacturers to manufacture in high-cost environments and when in low-cost environments? While the literature offers many cues to answer this question, too little empirical research directly addresses this. In this study, we quantitatively and empirically investigate the financial effect of companies' production footprint in low-cost and high-cost environments for different types of production networks.

Using the data of 770 multinational manufacturing companies, we analyze the relationship between production footprints and profitability during four calendar semesters in 2018 and 2019 (N = 2,940), investigating the moderating role of companies' production network type.

We find that companies with networks distinguished by both high levels of product complexity and process sophistication profit the most from producing to a greater extent in high-cost countries. For these companies, shifting production to low-cost countries would be associated with negative performance implications.

Our findings suggest that the production geography of companies should be attuned to their network type, as defined by the companies' process sophistication and product complexity. Manufacturing in low-cost countries is not always the best choice, as doing so can adversely affect profits if the products are highly innovative and the production processes are complex.

We contribute to the scarce empirical literature on managing global production networks and provide a data-driven analysis that contributes to answering some of the enduring questions in this critical area.

The problem is concerned with a single manufacturing enterprise producing varieties of products which are being distributed through a set of regional warehouses. The operations of each regional warehouse in the distribution subsystem is considered to be quasi‐autonomous in the sense that the decentralisation is granted to the extent of formulating and operating their own cost structure and transportation modes. For the production subsystem there is a need for aggregation of regional ordering policies to take advantage of the single manufacturing facilities. The boundaries of both subsystems are highly interactive. The simulation approach suggested in this study highlights the causal behaviour of the interacting boundaries and formulates a feedback control model in order to derive the various operational parameters of the total system. The effect of disturbance of the operational parameters on the total system behaviour has been studied through experimental design and analysis of variance.

This study aims to validate the link between production manipulation and a firm’s performance variability (fundamentals and stock returns). It explores whether executives' risk-taking incentives encourage production deviations around the normal level during uncertainty.

Utilizing panel data of manufacturing firms from Compustat over three decades, the study investigates production management practices during economic uncertainty. The Economic Policy Uncertainty Index (EPU) is employed as a key metric. The empirical strategy involves documenting the effect of economic uncertainty on overproduction and underproduction, examining the role of executive compensation and assessing the impact on risk.

The research finds that risk-taking incentives increase over/underproduction, particularly amplifying the extent of underproduction during uncertainty. Production deviation rises, indicating that firms take greater risk by engaging in abnormal business operations. The study’s results are robust against various econometric methods, emphasizing the influence of risk-taking incentives on corporate production decisions.

While providing valuable insights, the study acknowledges inherent limitations, including factors influencing production decisions beyond risk-taking incentives. Further research could explore additional determinants for a comprehensive understanding.

The findings highlight the potential dark side of executive compensation that motivates suboptimal risk-taking decisions, impacting risk, cost of capital and firm performance. Policymakers and compensation committees can use these insights to design efficient systems that mitigate moral hazard problems associated with productivity changes.

The study emphasizes the broader social implications of production manipulation under uncertainty. It prompts discussions on the ethical considerations of managerial opportunism, its potential consequences for stakeholders and market dynamics.

This study contributes to the literature by examining the role of economic uncertainty on production manipulation and the influence of risk-taking incentives. It extends the earnings management literature by considering real activity manipulation and emphasizing the importance of decomposing production deviation into positive and negative values.

The recent transformations brought about by the globalisation of markets have increased the competitive pressure for firms operating in traditional sectors, and in particular for those in industrial districts. The authors' aim is to understand the extent to which firms responded to these new challenges. More particularly, they investigate the determinants of innovation at firm level focusing on the role of firm's outsourcing strategies.

Drawing on an original firm‐level dataset, the authors analyse the determinants of innovation in a typical Italian industrial district, i.e. the hosiery district of Castel Goffredo in the Third Italy. They apply econometric techniques, in particular OLS and Tobit models.

The authors' findings suggest that industrial districts are evolving towards a differentiated organisational structure in which innovation is driven by firms, which are focused on core competences and high valued added activities.

The authors' results should be interpreted with some caution, since the cross‐sectional design of their data does not allow them to fully control for potential reverse causation effects, which might be relevant for some of the explanatory variables. Their data do not allow them to include additional instrumental variables, thus they cannot control for endogeneity. Therefore, their interpretation is limited to comment the extent and regularity of the relation between dependent and explanatory variables.

The evidence presented in this study corroborates some arguments highlighted in the current debate about the evolution of industrial districts. A network‐based organisation is the dominant organisational structure. The authors have some evidence on the importance of size as driver of innovation.

The authors find original evidence at firm level on the relation between organisational change, in the form of outsourcing, and innovation in the context of an industrial district. They also find empirical support to arguments debated in the recent policy debates on whether small firms can be regarded as engines of innovation in industrial districts.

Describes a model of a hierarchical planning system to provide a comprehensive approach to the complex production planning and scheduling problem. The model supplies a link between long‐term and short‐term planning; the three tiers of the hierarchy implement: long‐term inventory planning on a cost minimization basis; shorter‐term production planning; and daily sequencing. Emphasizes efficient processing and transmission of information.