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The purpose of this chapter is to examine voice as an empowerment practice in a manufacturing company. The case study follows a qualitative approach to analyse employee voice and types of empowerment from a structural perspective. Findings suggest a variety of voice arrangements to empowering employees such as voice surveys, meetings, e-suggestions, opinion boxes and informal means such as casual meetings and walkarounds. In addition, employee voice is linked to types of empowerment such as information sharing, upward problem solving, task autonomy and attitudinal shaping. Further research would benefit from an exploration of employees’ feelings regarding voice mechanisms to examine the psychological perspective of empowerment.

This chapter discusses the phenomenon of online marketplaces for science, technology, engineering, and math (STEM) talent and highlights its effect on knowledge creation and innovation through on-demand contract employment and problem solving of scientific challenges by online communities of experts globally. In particular, the authors discuss the key dynamics and events driving the development of the online marketplaces for innovation. Relying on data from various online platforms, including novel data from one of the world’s largest online platforms, the chapter characterizes the phenomenon, including the geographic dispersion of users and distribution of income, and discusses important implications and challenges for research and development (R&D) and innovation management in organizations. These include the need to develop new organizational and managerial capabilities, intellectual property (IP) protection issues, the ability of balancing internal and external innovation processes, and implications on the changing identity of R&D workers.

In particular, it is worth mentoring new and more efficient solutions that can meet the increasingly specific needs of each company, especially in food management. A business intelligence (BI) solution can help your food company better understand and manage business processes more effectively. Management information is essential for all levels of an organisation to make quick and correct decisions. However, what exactly is BI, and what can it mean for a food company?

The PRISMA stands for (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) and content analysis strategy used the SLR (systematic literature review) methodology to examine 151 papers published in peer-reviewed academic journals and industry reports between 2016 and 2023.

The findings show that artificial intelligence and digitalisation are linked to the UN 2030 Agenda. BI management ranks first (66%), followed by crop and land mapping systems (40%), agricultural machinery monitoring tools (39%) and decision support systems (31%). The road to digital transformation remains extended, with the main impediments being more compatibility between enterprise systems and a shortage of expertise.

The section relating to methodological perspective adopts the PRISMA methodology for systematic review. Interoperability is easily managed by assigning qualified teams to projects. The added value of a consulting firm with extensive project management experience in the food industry is closely related to the results achieved.

BI: What exactly is it, and why a data-driven culture is essential in the food and beverage industry?

The railway track system is the platform by which loads from moving trains are transferred to the underlying soil or supporting infrastructure such as bridges. The most common type of railway track system is ballasted track, which has been in use for over a century. Ballasted track has proved versatile. It can be constructed using locally available materials and with modifications to the rails and sleepers, crossings transferring trains from one route to another can be created. The structure of a ballasted track system consists of two main parts. The upper portion, termed the superstructure, comprises the rails, fastenings and sleepers. It is formed of components whose shape, stiffness and strength are designed and closely controlled. Below the superstructure is the substructure, which comprises the ballast and sub-ballast. Although the materials used in the substructure may have been specified, their engineering properties and geometric placement are less well controlled. In this chapter, we will explore how a typical ballasted track system transfers load to the ground and the ways in which the track form deteriorates, requiring maintenance and eventually renewal.

Aviation is not only one of the key contributors to the economy and social structure of the world but it is also an industry whose environmental impacts are being closely monitored. Aircraft efficiency and technological advancements have significantly reduced aviation noise and emissions in recent decades. Nevertheless, as the need for passenger and freight transportation grows, the aviation sector is becoming a primary source of environmental issues and a significant driver of global warming. This chapter focusses on environmentally sustainable aviation with a net-zero emission target. It also highlights sustainable aviation policies and collaborative initiatives in the aviation industry to meet the 2050 net-zero emission goal. While the industry's efforts have increased opportunities recently, the industry has also had to face several challenges to achieve the net-zero aviation target.

IV estimation is examined when some instruments may be invalid. This is relevant because the initial just-identifying orthogonality conditions are untestable, whereas their validity is required when testing the orthogonality of additional instruments by so-called overidentification restriction tests. Moreover, these tests have limited power when samples are small, especially when instruments are weak. Distinguishing between conditional and unconditional settings, we analyze the limiting distribution of inconsistent IV and examine normal first-order asymptotic approximations to its density in finite samples. For simple classes of models we compare these approximations with their simulated empirical counterparts over almost the full parameter space. The latter is expressed in measures for: model fit, simultaneity, instrument invalidity, and instrument weakness. Our major findings are that for the accuracy of large sample asymptotic approximations instrument weakness is much more detrimental than instrument invalidity. Also, IV estimators obtained from strong but possibly invalid instruments are usually much closer to the true parameter values than those obtained from valid but weak instruments.

This contribution discusses a continuum model of large discrete networks in planar domains. For this model, the Kirchhoff law, boundary conditions and capacity constraints lead in a system optimisation approach to a infinite dimensional constrained optimisation problem and to “mixed” variational inequalities. Mixed finite element methods can be formulated for these variational inequalities such that computable discretizations of the continuum problem are obtained.

Many dynamic problems in economics are characterized by large state spaces which make both computing and estimating the model infeasible. We introduce a method for approximating the value function of high-dimensional dynamic models based on sieves and establish results for the (a) consistency, (b) rates of convergence, and (c) bounds on the error of approximation. We embed this method for approximating the solution to the dynamic problem within an estimation routine and prove that it provides consistent estimates of the modelik’s parameters. We provide Monte Carlo evidence that our method can successfully be used to approximate models that would otherwise be infeasible to compute, suggesting that these techniques may substantially broaden the class of models that can be solved and estimated.