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This paper presents the second-generation estimates for the Italian engineering industry in 1911, a year documented both by the customary demographic census, and the first industrial census. The first part of this paper uses the census data to estimate the industry’s value added, sector by sector; the second further disaggregates each sector by activity, and estimates the value added, employment, physical product, and metal consumption of each one. A third, concluding section dwells on the dependence of cross-section estimates on time-series evidence. Three appendices detail the specific algorithms that generate the present estimates; a fourth, a useful sample of firm-specific data.

In today’s world, the possibility to collect and analyze unprecedented quantities of data pertaining not only to the operation of private and public sectors, but also to the lives of individuals, bears the potential to employ the data as invaluable source of information, and possibly knowledge. The latter, in turn, may lead to innovation, and innovation-led sustainable growth and development of our societies. Inasmuch as the promise inherent in – what tends to be termed – big data is huge, so are also the caveats related to the prospect of exploiting the benefits of big data. In this chapter, it is argued that four challenges beset the possibility of effective and efficient use of big data today. These include: a substantial degree of ignorance as to what big data actually is; the challenge of obtaining quality data; the challenge of the utilization of big data in the decision-making process; and, finally, the twin ethical and legal challenge pertaining to the acquisition and the use of big data. It is also argued that the awareness of the existence of these caveats enables a critical insight into the promise big data brings about for our societies today. This chapter dwells on these issues.

With the advent of the fourth industrial revolution and the intelligent economy, this conceptual chapter explores the evolution of educational governance from one based on governing by numbers and evidence-based governance to one constituted around governance by data or data-based educational governance. With the rise of markets and networks in education, Big Data, machine data, high-dimension data, open data, and dark data have consequences for the governance of national educational systems. In doing so, it draws attention to the rise of the algorithmization and computerization of educational policy-making. The author uses the concept of “blitzscaling”, aided by the conceptual framing of assemblage theory, to suggest that we are witnessing the rise of a fragmented model of educational governance. I call this governance with a “big G” and governance with a “small g.” In short, I suggest that while globalization has led to the deterritorializing of the national state, data educational governance, an assemblage, is bringing about the reterritorialization of things as new material projects are being reconstituted.

The field of Supply Chain Management (SCM) has mainly focused on applications for large firms, where significant amount of theory has been developed in the last decades. Little attention has been received by micro and small enterprises (MSEs) that in Latin America represent approximately 99% of all businesses and are the key for the development of the economy, employment, and growth of the region. Due to MSEs' lack of productivity, only a fraction of them survive and thus contribute to Latin America's economic growth. In this chapter, we discuss the connection between MSEs' productivity growth and SCM. We present key takeaways from the literature and summarized different research approaches used to study this emerging field, specifically related to the impact of the size of the company, the use of surveys to gather data, and the importance of field interventions. We also present a large-scale project (i.e., MIT GeneSys) that focuses on improving survival of MSEs in developing countries and discuss some preliminary learnings gained via conducting shadowing/immersion of ∼250 MSEs from Mexico, Colombia, Chile, Ecuador, Peru, and Bolivia. We conclude the chapter by presenting some recommendations for the future research agenda for the emerging field of SCM for MSEs in Latin America.

The strategic management literature emphasizes the concept of business intelligence (BI) as an essential competitive tool. Yet the sustainability of the firms’ competitive advantage provided by BI capability is not well researched. To fill this gap, this study attempts to develop a model for successful BI deployment and empirically examines the association between BI deployment and sustainable competitive advantage. Taking the telecommunications industry in Malaysia as a case example, the research particularly focuses on the influencing perceptions held by telecommunications decision makers and executives on factors that impact successful BI deployment. The research further investigates the relationship between successful BI deployment and sustainable competitive advantage of the telecommunications organizations. Another important aim of this study is to determine the effect of moderating factors such as organization culture, business strategy, and use of BI tools on BI deployment and the sustainability of firm’s competitive advantage.

This research uses combination of resource-based theory and diffusion of innovation (DOI) theory to examine BI success and its relationship with firm’s sustainability. The research adopts the positivist paradigm and a two-phase sequential mixed method consisting of qualitative and quantitative approaches are employed. A tentative research model is developed first based on extensive literature review. The chapter presents a qualitative field study to fine tune the initial research model. Findings from the qualitative method are also used to develop measures and instruments for the next phase of quantitative method. The study includes a survey study with sample of business analysts and decision makers in telecommunications firms and is analyzed by partial least square-based structural equation modeling.

The findings reveal that some internal resources of the organizations such as BI governance and the perceptions of BI’s characteristics influence the successful deployment of BI. Organizations that practice good BI governance with strong moral and financial support from upper management have an opportunity to realize the dream of having successful BI initiatives in place. The scope of BI governance includes providing sufficient support and commitment in BI funding and implementation, laying out proper BI infrastructure and staffing and establishing a corporate-wide policy and procedures regarding BI. The perceptions about the characteristics of BI such as its relative advantage, complexity, compatibility, and observability are also significant in ensuring BI success. The most important results of this study indicated that with BI successfully deployed, executives would use the knowledge provided for their necessary actions in sustaining the organizations’ competitive advantage in terms of economics, social, and environmental issues.

This study contributes significantly to the existing literature that will assist future BI researchers especially in achieving sustainable competitive advantage. In particular, the model will help practitioners to consider the resources that they are likely to consider when deploying BI. Finally, the applications of this study can be extended through further adaptation in other industries and various geographic contexts.

Purpose – The aim of this study is to provide insights into the factors affecting the banks’ use of financial information in financial statements of small- and medium-sized enterprise (SME) which has implications for the governance of these important organizations. Specifically, this study assesses the views of bank lending officers on their demand for and use of financial information relating to SMEs.

Design/methodology/approach – The study uses the data collected from a quantitative study in the form of a postal questionnaire survey. The model is constructed based on the data collected and the use of structural equation modelling (SEM).

Findings – The research finds that the main factor affecting the use of financial information is the directors’ perceptions of the role of accounting. Bank lending officers tend to use a great variety of sources of information to make lending decisions and do not rely on financial information provided by SMEs. Direct contacts with the SMEs were extensively used and were perceived as having a significant effect on the utility of information.

Research limitations/implications – The limitation of the study lies in the relatively small sample of respondents and the response rate.

Practical implications – The model is important as it can aid the banks’ understanding of the business activities of the smaller company sector. This leads to improved relationships between the banks and smaller companies and more positive lending decisions.

Originality/value –The model is of interest to the banks and other parties. The model may also be of interest to accounting regulators and standard setters to clarify the issue of how financial information of smaller companies is used. The model implies the revision of the current reporting frameworks to improve the transparency of the corporate governance in SMEs in the context of the less developed reporting environment of transitional economies.