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In this paper we introduce a simulative model, designed and developed to optimally manage an integrated finished goods inventory system, and suitable for adoption in a wide range of make to stock manufacturing firms. The goal of the model is to manage optimally finished goods inventory levels, in order to minimize costs deriving from holding inventory and from adjustment to the master production schedule (MPS) to prevent stock‐outs. A trade off is sought between these costs components. The input variables of the model are: safety stock levels, assessed through coefficients k1, k2 and k3, and the stochastic distribution functions of products demand. The model performances are assessed considering the annual total cost for the inventory management. The model is then tested by a numerical application. The case considered refers to a major firm operating in the zootechnical feeds production industry.

Deals with the issues related to the implementation, in a manual finished goods warehouse, of an ERP information system aimed at improving warehouse internal logistics efficiency. Specifically it is observed that the mere implementation of an integrated warehouse management information system does not actually guarantee the optimization of warehouse logistics. Rather, to improve the overall systems efficiency, it is required that ERP implementation be combined with the redesign and the reorganization of warehouse logistics and processes. This means that to achieve an effective synergic effect and thus effectively increase systems efficiency, both these steps have to be undertaken concurrently, grounding the reorganization and redesign phase on the implementation fallouts )in first place higher traceability levels gained(. The whole project is then applied to a real case of a finished goods manual warehouse, with pile storage systems.

This paper presents the results of a panel of experts, made up of academics in the field of operations and supply chain management, enterprise requirement planning software developers, and end‐users, whose work has aimed at defining the main features that characterize an enterprise modeller for the fashion industry. The characteristics required by the enterprise requirement planning enterprise modeller have been identified, with specific attention to the production planning and control module. Because of the peculiarities of this line of business, it is widely recognized that both vendors and buyers would benefit from such a tool. For the formers, the availability of a pre‐customized reference model would represent a competitive advantage in the marketplace, for the latter, on the other hand, it would enhance the effectiveness, the efficiency and the likelihood of success of the enterprise requirement planning implementation project.

To present a multi‐attribute approach for the selection and ranking of the most suitable 3PL service provider.

The approach is based on the TOPSIS technique (Technique for Order Preference by Similarity to Ideal Solution) and the fuzzy set theory.

A quantitative methodology based on a structured framework, for the selection of the most appropriate 3PL service provider.

Future research may attempt to compare the results of the methodology proposed with those of other Multi Attribute Group Decision Making methods. In particular, the selection tree could be developed in a multi‐tier hierarchy, trying to punctually address the relationships between the upper tier criteria and the lower level ones. With multi‐tier hierarchies, the performance of AHP could be compared with the one obtained with TOPSIS, not only with respect to “technical suitability” but also in terms of easiness to implement, shortcomings and general managerial viability.

From the application of the methodology to a real case, the approach proposed emerges as an appropriate tool, which makes it possible to easily and effectively rank alternatives. Conversely the most critical issue pointed out by the real case application is the preliminary “request of information” phase, which has to be given critical attention. The availability of a well structured body of knowledge about potential candidates emerged as the true discriminant for an effective analysis.

The originality of the paper is threefold: first, an original framework of criteria for the selection of the most suitable 3PL service provider is presented. Second, an original methodology based on a fuzzy TOPSIS approach is presented. Third, the practical implications and drawbacks are discussed by means of a real case application.

This research seeks to provide an understanding of the MRP adoption process using classic adoption models for prediction. To this end, four classical adoption models were used to provide the foundation for the constructs tested in this study. The framework of research strives to investigate the relationships between benefit analysis, feasibility studies, organizational willingness and the mediating construct, MRP positive evaluation. A statistical analysis on a sample of 109 small and medium‐sized firms was carried out which revealed that these constructs play an important role in the decision making process leading, ultimately, to MRP adoption. The analysis has, thus, lent support to the adoption models considered and might provide useful indications to managers seeking to maximize the investment in MRP packages.

Purpose – Departure time choice not only depends on the desire to carry out activities at certain times and places; it is a complex decision making process influenced by travel conditions, congestion levels, activity schedules, and external trip factors. To estimate departure time choice models capturing the factors influencing it in appropriate form, a complex data collection procedure allowing to obtain detailed input data from different sources and at different time periods is required.

The main aim of this chapter is to describe and discuss the survey methodology we used in a time-of-day choice project, involving the collection of revealed preference (RP) and stated preference (SP) data to estimate hybrid discrete departure time choice models incorporating latent variables. Preliminary model results are also presented as an example.

Methodology/approach – Data was obtained from 405 workers at different private and public institutions located in the centre of Santiago, Chile. The survey process had three different stages and used various collection methods (e-mail, web-page, and personal interviews at the workplace) in order to satisfy efficiency, reliability and cost criteria.

The RP component survey design was based on the last origin-destination survey implemented in Santiago (i.e. a travel diary filled under an activity recall framework). Relevant level-of-service measures at different time periods were obtained from GPS data measured from instrumented vehicles in the public and private transport networks. A SP-off-RP optimal design considering dependence among attribute levels was also developed. Finally, several 1–7 Likert scale questions were included to incorporate the latent variables.

Findings – The survey methodology described in this chapter represents a successful experience in terms of collecting high quality data, from different sources, with the aim of estimating appropriate time-of-day choice models. The data collection process was carried out in different stages, by means of web pages, email, and personal interviews. The data was further enriched with level-of-service attributes measured at different times of the day with unusual precision. Preliminary results reported in this chapter show that data obtained through this methodology are appropriate to model time-of-day choices.

Originality/value of chapter – The novelty of the survey methodology described in this chapter is the collection of data of a different nature for time-of-day choice modelling through the integration of different collection techniques.

Acquisition of very precise information about preferred departure/arrival times, level of service at different times of the day, detailed information about flexibility in schedules, employment information and attitudes towards departure times, should allow practitioners to estimate hybrid time-of-day choice models incorporating latent variables.

This paper aims to map the evolution of hydrogen-based technologies (HBTs) by examining the patenting activity associated to these technlogies from 1930 to 2020. In doing so, the study provides a novel perspective on the development of HBTs and offers implications for managers and policymakers.

We collected patent data at the level of patent families (PFs). Our sample includes 317,089 PFs related to hydrogen production and 62,496 PFs to hydrogen storage. We examined PF data to delineate the state of the art and major technical advancements of HBTs.

Our analysis provides evidence of an increasing patenting activity in the area of HBTs, hence suggesting relatively high levels of expectations on the economic potential of these technologies. US and Japan hold the largest proportion of PFs related to HBTs (about 60%), while European applicants hold the highest proportion of highly cited PFs (about 60%). While firms represent the applicant with the highest share of PFs, our analysis reveals that firms holding HBT PFs are primarily from the chemical sector.

While our analysis is limited to examining patent data which capture some aspects of the innovation activity around HBTs (namelly, patented inventions), our study enriches existing literature by performinng a patent analysis on a much larger sample of data when compared to previous studies.

Two main implications emerge from our study. Firstly, there seems to be an urgent need to support the emergence of a dominant design so as to facilitate the consolidation and diffusion of the HBTs, hence the transition to a more sustainable energy production. Secondly, the majority of HBT PFs are held by a small number of countries. This, in turn, suggests opportunities to develop cross-country cooperation (e.g. international agreements, research and technology offices) to support the development and adoption of HBTs globally.

Considering the results obtained in this study, from a social point of view, the attention that organizations have paid to hydrogen related technologies is evident. This suggests that the development HBTs can function as a social enabler for a sustianable energy transition.

Extant research has focused on the individual components of the hydrogen chain. As a result, we lack a comprehensive understanding of the progress made in the area of HBTs. To address this gap, this study examined HBTs by focusing on both production and storage technologies since their initial developments, hence adopting an observation period of about 70 years.

This book provides an international perspective on improving information to support transportation decision making. It comprises a selection of papers plus workshop syntheses from the 9th International Conference on Transport Survey Methods in Chile in November 2011. The conference was organized into 14 workshops with both paper presentations and discussions in the workshops forming the majority of the conference activity. The papers reported primarily on research pertaining to continuous improvement in transport survey methods — the backbone of the transportation data pipeline in most countries. But some papers also addressed the new ways in which innovation — notably technological innovation — is being applied to the capture and analysis of data to produce necessary information faster, better, and less expensively. The conference program built on a rich legacy of intellectual pursuits spanning the past two decades, and it is anticipated that the conference will continue into the future. Thus, the contents of this book represent a 5–10 year view through a moving window on the international state of the practice and concerns in transport survey methods.