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The food processing industry is growing with retail and catering supply chains. With the rising complexity of food products and the need to address food customization expectations, food processing systems are progressively shifting from production line to job-shops that are characterized by high flexibility and high complexity. A food job-shop system processes multiple items (i.e. raw ingredients, toppings, dressings) according to their working cycles in a typical resource and capacity constrained environment. Given the complexity of such systems, there are divergent goals of process cost optimization and of food quality and safety preservation. These goals deserve integration at both an operational and a strategic decisional perspective. The twofold purpose of this paper is to design a simulation model for food job-shop processing and to build understanding of the extant relationships between food flows and processing equipment through a real case study from the catering industry.

The authors designed a simulation tool enabling the analysis of food job-shop processing systems. A methodology based on discrete event simulation is developed to study the dynamics and behaviour of the processing systems according to an event-driven approach. The proposed conceptual model builds upon a comprehensive set of variables and key performance indicators (KPIs) that describe and measure the dynamics of the food job-shop according to a multi-disciplinary perspective.

This simulation identifies the job-shop bottlenecks and investigates the utilization of the working centres and product queuing through the system. This approach helps to characterize how costs are allocated in a flow-driven approach and identifies the trade-off between investments in equipment and operative costs.

The primary purpose of the proposed model relies on the definition of standard resources and operating patterns that can meet the behaviour of a wide variety of food processing equipment and tasks, thereby addressing the complexity of a food job-shop. The proposed methodology enables the integration of strategic and operative decisions between several company departments. The KPIs enable identification of the benchmark system, tracking the system performance via multi-scenario what-if simulations, and suggesting improvements through short-term (e.g. tasks scheduling, dispatching rules), mid-term (e.g. recipes review), or long-term (e.g. re-layout, working centres number) levers.

Third-party logistic providers (3PLs) continuously strive for controlling and improving their performances to gain a competitive advantage. The challenging environment where they operate is affected by high variety in type and number of clients, the inventory mix and the demand profiles they have to meet. Consequently, better understanding the dynamics of warehousing operations and the characteristics of the inventory mix is critical to handle such a complexity.

This paper proposes a decision-support framework, suited for 3PL warehouse practitioners, that aids to design and implement effective and affordable activities for measuring and improving the warehousing performances. Such goal is pursued by the framework by leading the managers through an initial mapping and diagnosis of the system, then by developing a tailored measurement system to track the performance, paving the way to the identification of the criticalities and the potential improvement scenarios.

This paper presents a case study on the implementation of the proposed framework at a warehouse of an Italian 3PL provider to introduce a new storage assignment policy and reduce the travelling time for order picking. Furthermore, the paper exemplifies how the framework contributes to enhance the awareness of managers on warehousing operations and the involvement of the personnel throughout the improvement process.

The proposed framework can be implemented by operations managers of 3PL warehouses who want to pursue general performance improvement projects. With respect to the case study, this framework contributes to identify the storage assignment policy that reduces the travelling for order picking in the observed warehouse of 8 percent in a month but is intended to address to even other areas of improvement in 3PL warehousing environments.

Instead of focusing on the proper methods and models that optimize a specific task or performance indicator, it provides a general framework that leads the managers through the decisional process, from the preliminary diagnosis of the system, to its benchmarking, towards the implementation of corrective and improving solutions.

Personalization of products, mix variability and short time to market are the most important factors that have forced companies to a new form of organization during past years. A very common reply to this question is a lean organization based on flexibility of productive lines, reduction of storage and integration among company sections. In this context, quite differently from a traditional system, the maintenance function must work efficiently. Also the maintenance division must contribute to the success of the factory. Aims to introduce a methodology for a soft and tenable application of the principles of total productive maintenance (TPM) in Italian factories. The first step of the study is an explanation of the actual situation, usually based on traditional or on productive maintenance. After a brief introduction, focuses on TPM links with productive maintenance in order to suggest a method for TPM. Concludes with a real application of TPM in a big factory, with a description of a world leader in plant manufacturing for the ceramics industry.

This paper aims to introduce, apply and validate, through a realistic case study, an analytical cost model to support the design of the tow-train feeding system for mixed-model assembly lines managed according to the just-in-time concept. The fleet size and inventory level, minimizing the total annual cost, are the key model goals, while the tow-train shipping capacity and the service level are the decisional variables to set.

The model computes the material handling, inventory and stockout rising costs of the tow-train feeding system and looks for their minimization. It further computes the expected lead time between consecutive round-trips and the Kanban card number, distinguishing among parts and assembly lines, overcoming the simplifying hypothesis assuming a constant lead time for all parts. The model is validated against a dedicated case study stressing its strengths in terms of cost and inventory-level reduction.

The proposed approach is found to be effective if compared to the standard literature in the field of Kanban system design. The 10.76 per cent cost saving is experienced for the considered case study, and the inventory level is closer to the field-experienced profile.

The model adopts a practical perspective, making it easy and applicable to common operative industries.

The literature neglects to consider the differences in the part consumption when estimating the lead time between tow-train round-trips. The proposed model overcomes such limitations and strengthens the model applicability and performances.

Recently, material flows have been viewed as an integral part of the overall manufacturing system and a critical factor in SCM. Static approaches and theoretical models are ineffective in considering all variables and constraints involved in complex instances: these often require a lot of computing time and present poor flexibility in terms of model changes. VIS approach is a valid way to support design and management decisions in order to achieve the integrated optimisation of the whole chain, but literature does not discuss difficulties and time required in applying it, or its related costs.

Discrete/continuous hybrid simulation tools are used in order to model and simulate several operating conditions in combination with different system configurations.

The discussion of the industrial cases shows the importance of simulation in supporting decisions concerning the design and management of supply chains in their great complexity and in a stochastic competitive and extended context.

The paper deals with five significant industrial cases, which are simulated in collaboration with important enterprises and belong to different industrial sectors, in order to obtain an original quantitative analysis of time and costs resulting from a simulation optimisation based on the introduction of a set of innovative performance indices.

We investigate the innovative supply chain contracts developed and implemented by Barilla, the leading Italian pasta company, in sourcing high-quality durum wheat from farmers in Northern Italy in the Emilia Romagna region.

Using case study techniques to gather information, we captured the evolution of the supply chain contracts adopted by Barilla. We gained information mainly through semi-structured interviews with Barilla’s managers, co-op and consortium managers representing farmers, Barilla’s quantitative data related to contracts’ elements and structure, preliminary experimental results, agri-business magazines, industry reports, and academic literature.

These contracts helped the company improve not only its long-term profits and strategic objectives such as supply security, but also the farmers’ income as well as environmental sustainability, thus providing triple bottom line benefits.

We investigate how Barilla and its suppliers – with the support of additional stakeholders, such as regional institutions – combine in their innovative contracts fixed and market-based prices as well as quality and sustainability-based premiums for desired triple bottom line benefits.

Lucas Aerospace has received an order from McDonnell Douglas for lightweight cargo handling systems for installation in the MD‐11 transport aircraft.

New British vibration technology that makes ageing aircraft safer, more comfortable and durable, has been developed by Ometron Ltd.

The purpose of this paper is to explore the relationship between clientelist relationships and economics in public relations practice in European Mediterranean countries and Latin America. It considers the cases of Greece, Italy, Portugal, Spain, Brazil, Chile, and Mexico.

This paper uses a critical-conceptual method through a re-conceptualization of themes from secondary qualitative analyses of existing qualitative data sets and reviews of published qualitative papers.

The public relations practice in these two regions is similar. The characteristics of the public relations landscape in these countries must be understood in relation to a broader history of clientelism and economics emphasizing government relationships at the expense of other publics, as well as the lack of scale economies. Persuasive models are prevalent, although a number of forces – including integration in supranational organizations, democratization, and globalization – have strengthened the use of symmetrical models.

This is not an empirical survey, there is a need of quantitative studies among practitioners and government officials that can measure empirically the nature of their relationships in a number of countries. This essay opens a door for future studies and cross-cultural comparisons about the role that clientelism plays in the PR practice of cultures and countries.

The paper offers useful background information, such as the primacy that media relations still have in the public relations practice, for foreign public relations executives, agency heads, and managers of public relations who are directly involved with or managing international public relations campaigns in these countries.

Clientelism is a cultural concept that translates to the work of organizations and consequently public relations as a form of organizational behavior.

This paper brings to the table the importance of the concept of clientelism in the PR practice as well as the existence of a similar PR culture between countries that are on different continents.

Internet data hold many promises for demographic research, but come with severe drawbacks due to several types of bias. The purpose of this paper is to review the literature that uses internet data for demographic studies and presents a general framework for addressing the problem of selection bias in non-representative samples.

The authors propose two main approaches to reduce bias. When ground truth data are available, the authors suggest a method that relies on calibration of the online data against reliable official statistics. When no ground truth data are available, the authors propose a difference in differences approach to evaluate relative trends.

The authors offer a generalization of existing techniques. Although there is not a definite answer to the question of whether statistical inference can be made from non-representative samples, the authors show that, when certain assumptions are met, the authors can extract signal from noisy and biased data.

The methods are sensitive to a number of assumptions. These include some regularities in the way the bias changes across different locations, different demographic groups and between time steps. The assumptions that we discuss might not always hold. In particular, the scenario where bias varies in an unpredictable manner and, at the same time, there is no “ground truth” available to continuously calibrate the model, remains challenging and beyond the scope of this paper.

The paper combines a critical review of existing substantive and methodological literature with a generalization of prior techniques. It intends to provide a fresh perspective on the issue and to stimulate the methodological discussion among social scientists.