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Over recent decades both Europe and the United States have experienced an increase in the share of service-related jobs in total employment. Although narrowing in all European countries, a significant gap in the share of service jobs relative to the United States still persists. The aim of the chapter is to identify the main drivers of the service sector employment share in the EU-15 as well as its gap relative to the United States. The analysis is carried out for the aggregate service sector, 4 sub-sectors and 12 service sector branches over the period 1970–2003. We find some evidence to support the hypothesis that a number of labour market regulations – such as union density and the degree of centralisation of wage bargaining – together with the mismatch between workers' skills and job vacancies, have affected Europe's ability to adjust efficiently to the reallocation of labour from manufacturing into services. Furthermore, we find significant heterogeneity in the relative weight of the various determinants of the employment share across sub-sectors and branches.

The purpose of this paper is to provide a conceptual framework of staged development that examines strategies of domestic companies, government policies, and impacts of foreign multinational companies (MNCs) at different periods of catch‐up of latecomers.

A multi‐case approach is employed to examine four domestic telecom‐equipment companies that have significant impact on China's telecom‐equipment industry. They are: Huawei Technology Corporation (Huawei), Shenzhen Zhongxin Technology Corporation (ZTE), Datang Telecom Technology Corporation, Ltd (Datang), and Great Dragon Information Technology (GDT).

This paper identifies four distinct stages of the catching‐up process, featuring different institutional environment, government involvement, and the ensuing actions of foreign MNCs and domestic companies. During the initial stage, China's government decision of directly leapfrogging to the most advanced switch equipment had a profound impact, because it led to both heavy reliance on foreign MNCs and the pursuance of switch research and development (R&D) by domestic research institutes and new technology companies. The dominance of foreign MNCs is challenged during the growth stage, because several domestic companies ascended and gained the capability to produce large‐scale, stored program controls and the government directly leveraged support in R&D, marketing, and finance. Although many uncompetitive domestic companies failed during the filtration stage, the management training received from foreign MNCs and newly available financing options provided necessary resources for some domestic companies to survive and expand. Domestic leaders globalized their marketing, production, and R&D functions and to become MNCs themselves in the globalization stage, thus finalizing the catching‐up.

The Chinese experiences shed light on late‐industrialization for other developing economies by suggesting that to catch‐up in high‐tech industries, government can become involved strategically to form a competitive and efficient market environment for innovation.

The paper proposes a new conceptual framework to analyze catching‐up of domestic companies as latecomers. This framework can be used to study catching‐up in other sectors in late‐industrializing countries.

The purpose of this paper is to introduce a project development framework (PDF) aiming to find socially beneficial public infrastructure provision (PIP) projects in the transport sector. From this perspective, the current paper focuses on the framework of finding an optimized PIP organizational model based on which the projects will be both economically and financially viable and will meet the interests of all the stakeholders. From this perspective, the objective of the current paper is to find in the design phase of the projects, a PIP organizational model for the transport sector, that generates the socially required economic internal rate of return (hereinafter EIRR), thus providing the society with the added social values from the relevant infrastructure projects and, at the same time, ensuring relevant level of the financial internal rate of return (hereinafter FIRR) for the private companies interested in investing in relevant assets. This allows finding socially beneficial PIP organizational model according to the adopted PDF.

The methodology aiming to develop the PDF focuses on analyzing both the economic and financial effectiveness of the PIP projects by exploring different combinations of available options for business, contractual, and financial models of relevant projects. Based on the example of the Republic of Armenia it is shown how the EIRR can be calculated for the PIP projects using the adopted PDF by taking into consideration the transport sector specifics of the country.

The main advantage of the designed framework is that it focuses on the calculation of the EIRR not only based on the different design options, but also explores the influence of the chosen procurement models on the economic output of the projects. The identification and the calculation of the positive and negative externalities (benefits and losses of the projects) in the economic values within the current PDF serve as the main instrument for the development of the PIP optimized socially beneficial/viable organizational models. The main privilege of the paper is that it considers the social aspect of the project together with the financing aspect without extruding any interests of the parties.

The uniqueness and the novelty of the adopted PDF is that it considers the efficiency of the PIP projects based on the analysis of not only the design options that influence the economic and financial output of the projects, but also compares the impact of the different combinations of the existing privatization, partnership, contractual, financial, and business models on the level of the EIRR and the FIRR. The socially beneficial infrastructure (economically viable) model generates economically and financially viable projects. Thus, the public partner is provided with the highest social value while the private partner is guaranteed a desired financial return.

This chapter presents the outcome of an empirical study titled ‘Knowledge Sharing and Transfer (KST) that Really Works: An exploration of KST in Sub-Saharan South African Public Sector Institutions’. Enablers of KST were explored through the lens of lived experiences of managers working at Gautrain Management Agency (GMA), a rail transport public sector operator in South Africa. Qualitative data were collected from 15 managers and analysed using Thematic and Trans Positional Cognition Approach (TPCA) qualitative analytical tools. Four themes, essential originating antecedent factors, complementary people enabling factors, organisational enabling factors and effective KST implementing factors emerged. Rahman’s KST model was adopted as a theoretical framework and used to better understand the study findings. The current study affirms two elements within the theoretical framework, namely, complementary people enabling factors and organisational enabling factors, while the remaining two, essential originating antecedent factors and effective KST implementing factors, were not affirmed. This study contributes a new KST framework that helps business managers understand KST from the South African public sector practitioners’ perspectives, which represents this study’s contribution to the business performance measurement body of knowledge and practice.

Infrastructure investment is one of the few high-calibre real alternative assets with a strong prominence in the portfolios of institutional investors, especially those with a liability-driven investment strategy. This has seen increased institutional investor interest in infrastructure for reasons such as diversification benefits and inflation hedging abilities, resulting in the substantial growth in non-listed and listed investment products offering access to the infrastructure asset class, and complementing the existing route via direct investment. This paper aims to assess the investment attributes of non-listed infrastructure over Q3:2008–Q2:2019, compared with other global listed assets of infrastructure, property, stocks and bonds.

Quarterly total returns were derived from the valuation-based MSCI global non-listed quarterly infrastructure asset index over Q2:2008–Q:2019, which were then filtered to decrease the valuation smoothing effects. A similar set of returns data was also collected for the other global asset classes. The average annual return, annual risk, risk-adjusted performance and portfolio diversification benefits for non-listed infrastructure and other asset investment classes were then computed and compared. Lastly, a constrained optimal asset allocation analysis was performed to validate the performance enhancement role of global non-listed infrastructure in a mixed-asset investment framework.

Global non-listed infrastructure delivered the strongest average annual total return performance, outperforming the other asset classes and provided investors with total returns that linked strongly with inflation. Global non-listed infrastructure also provided investors with one of the least volatile investment returns because of its ability to ensure predictable total returns delivery. This means that on the Sharpe ratio risk-adjusted return basis, non-listed infrastructure was also the strongest performing asset. This performance was also delivered with significant portfolio diversification benefits with all assets, resulting in non-listed infrastructure contributing to the mixed-asset portfolios across the entire portfolio risk spectrum.

Aside from better risk-return trade-offs, institutional investors are getting more secular with their portfolios for alternative assets that are able to provide other investment benefits such as predictable long-term performance and inflation-linked returns. A further improvement in performance and diversification benefits could be achieved by enriching existing investment portfolios with real alternative assets, one of which is the infrastructure asset class. For institutional investors, having exposure to and being part of the development, delivery and management of infrastructure assets are important, as they are one of the few real assets having considerable significance in the context of society, economy and investment needs.

This is the first research paper that empirically investigates the investment attributes of the non-listed infrastructure at a global level. This research enables empirically validated, more informed and practical decision-making by institutional investors in the infrastructure asset class, especially via the non-listed pathway. The ultimate aim of this paper is to empirically validate the strategic role of non-listed infrastructure as an important alternative asset in the institutional real asset investment space, as well as in the overall portfolio context.

Optimization of energy planning for growth and sustainable development has become very important in the context of climate change mitigation imperatives in developing countries. Existing models do not capture developing country realities adequately. The purpose of this paper is to conceptualizes a framework for energy strategy optimization of the Indian energy sector, which can be applied in all emerging economies.

Hierarchical multi‐objective policy optimization methodology adopts a policy‐centric approach and groups the energy strategies into multi‐level portfolios based on convergence of objectives appropriate to each level. This arrangement facilitates application of the optimality principle of dynamic programming. Synchronised optimization of strategies with respect to the common objectives at each level results in optimal policy portfolios.

The reductionist policy‐centric approach to complex energy economy modelling, facilitated by the dynamic programming methodology, is most suitable for policy optimization in the context of a developing country. Barriers to project implementation and cost risks are critical features of developing countries which are captured in the framework in the form of a comprehensive risk barrier index. Genetic algorithms are suitable for optimization of the first level objectives, while the efficiency approach, using restricted weight stochastic data envelopment analysis, is appropriate for higher levels of the objective hierarchy.

The methodology has been designed for application to the energy sector planning for India's 12th Five Year Plan for which the objectives of faster growth, better inclusion, energy security and sustainability have been identified. The conceptual framework combines, within the policy domain, the bottom‐up and top‐down processes to form a hybrid modelling approach yielding optimal outcomes, transparent and convincing to the policy makers. The research findings have substantial implications for transition management to a sustainable energy framework.

The methodology is general in nature and can be employed in all sectors of the economy. It is especially suited to policy design in developing countries with the ground realities factored into the model as project barriers. It offers modularity and flexibility in implementation and can accommodate all the key strategies from diverse sectors along with multiple objectives in the policy optimization process. It enables adoption of an evidence‐based and transparent approach to policy making. The research findings have substantial value for transition management to a sustainable energy framework in developing countries.

In the search for appropriate solutions to cope with ever increasing road traffic, cities and urban agglomerations across Europe are placing great emphasis on new transport and mobility solutions, and electric mobility in particular. Being located at the intersection of the three constituent sectors automotive, information and communication technologies and green energy, electric mobility is perceived as future-oriented sector. Innovation in the sector not only requires the collaboration and exchange of knowledge, but also an increase in skilled workforces and distinct job qualifications. These demands emerge, on the one hand, through the electrification of cars, which results in structural changes in the entire value chain. On the other hand, growing customer and service orientation further accelerate such developments. So far, the knowledge about the concrete demands for engineers as knowledge carriers and innovation driver is rather scarce. To shed some light on this issue, the purpose of this paper is to discuss companies’ altered demand for engineers in electric mobility and the role of networks (e.g. clusters).

This paper discusses two regions characterised as traditional automotive regions (Stuttgart in Germany and Alsace/Franche-Comté in France) and the shift in demands of the companies in these regions using the engineering workforce as an example. Electric mobility related companies were surveyed and asked about their current need of engineers. In addition, the survey investigated the companies’ ways of recruiting engineers, their spatial scope of search for employees and the skills and thematic courses needed to solve the lack of qualifications. The survey results are discussed against a background of regional framework settings and influencing factors of both the regions analysed.

This paper finds that there is a shift in qualification demands of engineers involved in the sector of transport and mobility. Initiated by the processes along the entire value chain, new skills are required by companies. The current engineers are asked to mix their technical know-how with service orientation and knowledge of new markets.

The world is becoming increasingly mobile. Within the last decades, the number of daily commuters has expanded producing high capacities of road traffic. This has brought several challenges for cities and regions. To face them new transport and mobility concepts are of key importance for cities and regions. Along these lines, well-skilled human capital in the form of engineers is needed to expand the concepts with their skills and knowledge.

The purpose of this paper is to present a methodology of comparing concession projects developed in different transport sub-sectors. The methodology is tested in the comparison of three different cases, each of which represent a particular mode of transport: a road development project, a city tramway project and a port lock construction initiative.

A fuzzy logic approach methodology is applied in carrying out the comparison between cases. Granulation is achieved by employing a Contextual (Ws) Risk Analysis Framework, as risks constitute the basis to public private partnership (PPP) structure. Linguistic variables are then used to describe the comparative findings.

The methodology presented allows for the comparison of three cases from different transport sub-sectors. Identification of similarities provides the potential to transfer experience from one sector to the other. With respect to the three cases studied, it was identified that traffic risk seems to be passed on to the private operators in relation to the level of exclusivity. Finally, PPP projects initiated by central government (as opposed to those initiated by local governments) seem to be more finance-driven than service-driven.

As the number of cases to be compared increases, quantitative comparative analysis fuzzy set values can be included in order to carry out a full analysis. The present approach should be considered introductory, as fuzzy sets are not generated due to the limited number of surveys (cases) compared (hence the term “pre-fuzzy”).

The methodology presented and the cases tested indicate the possibility for knowledge/experience transfer and the transferability of best practices.

Cross-sub-sectoral comparisons for transport PPP projects have not been identified in literature.

This study aims to identify and analyse energy intensity in Indonesia’s manufacturing industry based on industrial sub-sector, island region, technology intensity, firm size, type of ownership and exporter status to determine which of these characteristics have the highest potential to decrease energy intensity.

Using firm characteristics data from statistics of large and medium industries in Indonesia, this study decomposed energy consumption of Indonesian firms into economic activity, economic structure and energy intensity for the period 2010–2014 through the logarithmic mean Divisia index (LMDI).

The results showed the decomposed energy intensity based on the six sub-categories. From the sub-categories, several characteristics which induced the most increases in energy intensity are highlighted. Several industrial sub-sectors were classified as highly energy-consuming, including rubber and plastic products, glass and non-metal mineral products, food, electrical machinery and apparatus, chemical, paper, motor vehicles and trailers and tobacco. Results from other sub-categories indicated that firms with high energy intensity were located in the Java--Bali region, had medium technology intensity and were exporters. Meanwhile, firm size and ownership type sub-categories did not show clear differences in energy intensity.

This study provides more focused policy recommendations for related policymakers and stakeholders to emphasise the most energy-inefficient and energy-intensive firm based on the results from each sub-category and hence policy priorities to reduce energy consumption can be well-targeted.

This study contributes to the field through a more thorough energy intensity analysis based on the classification of Indonesian firm characteristics to provide a more detailed insight on the cause of the ever-increasing energy intensity level in the country.

Although scientific research community has shown considerable interest in identifying critical success factors (CSFs) for public-private partnership (PPP) projects, yet effort at assessing and compare CSFs within similar PPP infrastructure projects received scant attention. The purpose of this paper is to identify, assess, and compare the CSFs in PPP transport infrastructure projects.

The study adopted literature review and three PPP case studies including structured interviews and review of documentary reports in each case study. The outcome of literature review provided a total list of 26 identified success factors, which was used to design a case study protocol using failure mode and effect analysis (FMEA) technique. FMEA was conducted on each 26 identified success factor to assess their criticality in the three PPP case studies.

The results of FMEA revealed a total of ten CSFs in the concession of the road; four CSFs in the concession of the airport; and eight CSFs in the concession of the seaport. Also, the cross-case analysis showed the three prevalent CSFs, this includes government involvement by providing guarantees, political support, and project economic viability.

The study findings including lessons learnt in each case study would positively influence policy development towards PPP transport infrastructure projects and the manner in which partners (i.e. public and private sector) go about the development of PPP transport projects.

This research would help PPP stakeholders to focus their attention and priorities in managing the identified CSFs in achieving long-term success in PPP transport infrastructure projects implementation.