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The aim of this chapter is to investigate the different business co-operation mechanisms within two different Portuguese industries, with particular regards to the nature of the industry and to the places in which these industries are embedded.

This chapter uses qualitative data to explore the mechanisms associated to forms of business co-operation in enterprising places.

Manufacturing industries require a particular location of activities and, in many cases, these firms cluster in local productive systems. In such cases, co-operation mechanisms assume particular forms. Production is a critical business activity in traditional manufacturing industries, while its relative importance is smaller for other industries.

The findings obtained in this research do not allow generality of the results. However, it provides an in-depth explanation of the mechanisms of business co-operation taking place in enterprising places and elsewhere.

This chapter compares two contrasting Portuguese industries, allowing to suggest that some of the business co-operation mechanisms are particular of certain business contexts. It contrasts a manufacturing, traditional and geographically concentrated industry (furniture) with a service-based, modern and geographically dispersed industry (events organisation). In addition, it allows to gain insights on the evolution of business co-operation as it uses data collected from two different generations of entrepreneurs within the furniture industry.

There are many cognitive training tests purporting to both measure older people’s cognitive performance, several of which come with associated training that are deemed to improve cognition. This chapter describes cognitive tests that have been claimed to be linked to driver behaviour, and that training on them could improve driver behaviour. Of special interest are tests that could be completed at home on a computer, as it is suggested this could capture many individuals who are worried about attending a driver assessment centre and are not likely to be referred. Findings suggest that UFOV (Useful Field of View) Time Making Trail (A and B) and Dual N have research suggesting that training on them could improve driver performance for older drivers. However, the robustness of the research is debateable. There are also two physiological tests – a neck and shoulder and a general fitness test that also show promising results for improving driver performance. In addition, education and training is purported to improve driver behaviour, but although there is positive feedback from older people who attend and some short-term improvements, research on long-term improvements on driver behaviour are not yet evident. Overall, there are promising results from individual cognitive, physiological tests and from education and training suggesting that reflection on action and feedback from the task is important to improving driver performance but more research is needed.

Fear appeals are persuasive messages that attempt to arouse fear to motivate or influence behaviour change and are widely used in health promotion. This chapter analyses how fear appeal messaging was used by the Namibian and South African mainstream print media to communicate COVID-19 during the two countries’ main waves of the pandemic. Specifically, we examine the framing strategies that the media used to persuade behaviour change. Mainstream media has enormous potential to influence health-related behaviour and perceptions. Therefore, it is compelling to examine the mainstream media’s framing of COVID-19. This study draws on framing theory to examine media frames and the use of fear appeal in the coverage of COVID-19 in the top English-language newspapers in the two countries. We argue in this chapter that using fear appeals in public health communication by the media may be counterproductive as a tool of persuasion.

Due to the increasing size and complexity of construction projects, construction engineering and management involves the coordination of many complex and dynamic processes and relies on the analysis of uncertain, imprecise and incomplete information, including subjective and linguistically expressed information. Various modelling and computing techniques have been used by construction researchers and applied to practical construction problems in order to overcome these challenges, including fuzzy hybrid techniques. Fuzzy hybrid techniques combine the human-like reasoning capabilities of fuzzy logic with the capabilities of other techniques, such as optimization, machine learning, multi-criteria decision-making (MCDM) and simulation, to capitalise on their strengths and overcome their limitations. Based on a review of construction literature, this chapter identifies the most common types of fuzzy hybrid techniques applied to construction problems and reviews selected papers in each category of fuzzy hybrid technique to illustrate their capabilities for addressing construction challenges. Finally, this chapter discusses areas for future development of fuzzy hybrid techniques that will increase their capabilities for solving construction-related problems. The contributions of this chapter are threefold: (1) the limitations of some standard techniques for solving construction problems are discussed, as are the ways that fuzzy methods have been hybridized with these techniques in order to address their limitations; (2) a review of existing applications of fuzzy hybrid techniques in construction is provided in order to illustrate the capabilities of these techniques for solving a variety of construction problems and (3) potential improvements in each category of fuzzy hybrid technique in construction are provided, as areas for future research.

Most setup management techniques associated with electronic assembly operations focus on component similarity in grouping boards for batch processing. These process planning techniques often minimize setup times. On the contrary, grouping with respect to component geometry and frequency has been proved to further minimize assembly time. Thus, we propose the Placement Location Metric (PLM) algorithm to recognize and measure the similarity between printed circuit board (PCB) patterns. Grouping PCBs based on the geometric and frequency patterns of components in boards will form clusters of locations and, if these clusters are common between boards, similarity among layouts can be recognized. Hence, placement time will decrease if boards are grouped together with respect to the geometric similarity because the machine head will travel less. Given these notions, this study develops a new technique to group PCBs based on the essences of both component commonality and the PLM. The proposed pattern recognition method in conjunction with the Improved Group Setup (IGS) technique can be viewed as an extended enhancement to the existing Group Setup (GS) technique, which groups PCBs solely according to component similarity. Our analysis indicates that the IGS performs relatively well with respect to an array of existing setup management strategies. Experimental results also show that the IGS produces a better makespan than its counterparts over a low range of machine changeover times. These results are especially important to operations that need to manufacture quickly batches of relatively standardized products in moderate to larger volumes or in flexible cell environments. Moreover, the study provides justification to adopt different group management paradigms by electronic suppliers under a variety of processing conditions.

Lean manufacturing, a philosophy that revolutionized the manufacturing industry, is often linked to the Toyota Production System (TPS). At the core of a lean company, one can observe proper implementation of lean manufacturing tools and practices such as just-in-time, work teams, cellular manufacturing, lean layout, etc. The goal of lean production is to minimize the waste producing activities while offering the same or enhanced quality to customers.

The aim of this research is to investigate the implementation degree of lean manufacturing and its tools and practices focusing on the case of an SME in Albania as a concrete example. Higher attention is given to some of the pillars of lean manufacturing such as just-in-time and cellular manufacturing.

In this case study, researchers observed a variety of features of lean production. Just-in-time was implemented to a certain extent and cellular manufacturing at a more surprising level, which was facilitated especially by the U-shaped facility layout designs observed during the site visits. The value stream mapping showed a proper group technology in place and the management displayed signs of engagement and future advancement desire regarding this philosophy.

This chapter describes the approach to sustainable rail passenger rolling stock in terms of interior passive safety requirements within the European market. It is intended to give the background and logistical approach for the future introduction of a standard as an aid for the design and validation of the interiors of passenger rail vehicles. Also discussed is the acceptance of the proposed European-based standard into the regulatory system of the technical specifications for interoperability. Methodologies for design assessment and validation will be discussed. This chapter is intended to encourage an acceptance of the standard for interior passive safety as a realistic and cost-effective method of improving rail vehicle safety in terms of the passenger interfaces with the rail stock interior.

With numerous and ambiguous sets of information and often conflicting requirements, construction management is a complex process involving much uncertainty. Decision makers may be challenged with satisfying multiple criteria using vague information. Fuzzy multi-criteria decision-making (FMCDM) provides an innovative approach for addressing complex problems featuring diverse decision makers’ interests, conflicting objectives and numerous but uncertain bits of information. FMCDM has therefore been widely applied in construction management. With the increase in information complexity, extensions of fuzzy set (FS) theory have been generated and adopted to improve its capacity to address this complexity. Examples include hesitant FSs (HFSs), intuitionistic FSs (IFSs) and type-2 FSs (T2FSs). This chapter introduces commonly used FMCDM methods, examines their applications in construction management and discusses trends in future research and application. The chapter first introduces the MCDM process as well as FS theory and its three main extensions, namely, HFSs, IFSs and T2FSs. The chapter then explores the linkage between FS theory and its extensions and MCDM approaches. In total, 17 FMCDM methods are reviewed and two FMCDM methods (i.e. T2FS-TOPSIS and T2FS-PROMETHEE) are further improved based on the literature. These 19 FMCDM methods with their corresponding applications in construction management are discussed in a systematic manner. This review and development of FS theory and its extensions should help both researchers and practitioners better understand and handle information uncertainty in complex decision problems.

In this chapter, we consider the model of call center incoming call forecasting and staffing-level optimization. We first present the structure of the model and how an agent-based modeling technique could enrich the decision rule and the model. A matrix layout is introduced to present the model so that it can be understood in an efficient way from the perspective of a programmer. The agent-based queuing model will be used in forecasting. We then utilize the bisection method and stepwise method to optimize the staff level to satisfy a target range service-level criteria. Call center management could use the model in practice for their management forecasting and optimization decision-making process in terms of how many agents they need to achieve the target business efficiency goal.