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The goal of the Convention on the Rights of Persons with Disabilities (CRPD) is to secure the rights of persons with disabilities as full and equal members of society. Achieving these objectives requires appropriate and high-quality data for identifying disability gaps and areas of exclusion. Such data can be then used to develop policies and programmes to address that exclusion, and then to monitor and evaluate their effectiveness. However, researchers and policy makers face a number of challenges when collecting this data. This chapter reviews the various approaches to collecting data on disability, identifying potential sources of relevant data, including through surveys and repurposing of data collated for administrative means. It discusses at length the legal and ethical issues involved in their collection and use for alternative purposes, providing a comprehensive exploration of issues relating to participation, privacy, big data and rights of access. It concludes by suggesting ways forward for creating disability data systems that can fully support efforts to achieve a fully inclusive society.

A methodological approach is required that complements studies based on surveys, providing a perspective with greater truthfulness and coverage. The study aims to develop a methodology to validate psychological/managerial constructs using data from Google Trends, taking as a case study a critical thinking (CT) scale in organizational domains previously supported by survey data.

The developed methodology consists of eight stages, in which the following is integrated: (1) Internet search interest data (19 Spanish-speaking countries); (2) deductive research processes (e.g. theoretical model, linguistic manifestations, fieldwork, data matrix, analysis statistical, reporting); (3) psychometric properties (e.g. construct validity, criterion validity, reliability) and (4) objective data to examine criterion validity (e.g. unemployment rate).

The application of the methodology produces evidence that supports the reliability (Cronbach’s alpha, Guttman’s λ₄), construct validity (intra-correlations and correlations with reference variables: “entrepreneurship,” “critical thinking,” “soccer,” “beer,” “pornography”) and criterion validity (prediction of unemployment rate) of the CT scale.

The methodology makes it possible to support or invalidate the quality of construct measurement scales by planning, capturing and processing data available on the internet.

This manuscript is useful for research in business management (and related areas), which is intensive in the use of psychological/managerial constructs.

The methodology uses a new type of evidence; it is noninvasive, usually more truthful than responses to surveys, and has greater coverage of people participating indirectly in the study.

Gig microentrepreneurs are individuals who have embraced short-term gigs as an entrepreneurial agency for both financial and social livelihood. Based on surveys in 2020 and 2023, the research reported here presents a comprehensive, empirical portrait of two cohorts of gig microentrepreneurs. This portrait captures the similarities and differences of gig microentrepreneurs in terms of offline and online business models and the nature of gig work. Recognizing that there is not a “typical” gig microentrepreneur will help ensure that this gig business model continues to evolve without boundaries in terms of demographics, motivations and behavior and will enable marketing and entrepreneurship scholars to better assist in entrepreneurial growth and development. The purpose of this paper is to gain a better understanding of the gig microentrepreneur regardless of the nature of the gig work.

The research involved two separate surveys in the USA. The first survey took place in July 2020, and the second survey took place in April 2023 after major changes had taken place in the economy and in society (e.g. the COVID pandemic). Both surveys used samples generated by Dynata, an online consumer panel company with access to more than 70 million consumers worldwide who have agreed to participate as panel members.

The surveys provided answers to questions about the demographic and behavioral aspects of gig microentrepreneurs, including who they are, the number and type of gig activities in which they participate, the financial livelihood generated from gig income, the social livelihood inherent in gig work and dissatisfaction with being a microentrepreneur in the gig economy. These findings produced insights into why individuals engage in gig activities and the positive and negative impacts of that engagement. Based on the findings, nuances and trends within the gig economy and among gig microentrepreneurs are identified and discussed.

The research limitations include lack of generalizability outside of the USA, use of panel data and survivor bias.

Consumers, gig microentrepreneurs, companies and government agencies can benefit from the growth in the gig economy. The vast array of gig activities in which gig microentrepreneurs engage clearly shows the need for an on-demand workforce. There are both economic and societal benefits to having a labor-force that can meet a breadth of demands with varying timeframes.

Whether gig microentrepreneurs are engaging in gig work to augment their income because of economic insecurity or for intrinsic reasons, the motivations and behaviors of the gig microentrepreneurs are indicative of the talent and resources needed to keep the US economy moving forward positively.

As noted by several scholars conducting research on the gig economy, little is known about gig microentrepreneurs – who they are, what they do and why they do it. Current research on the gig economy tends to focus on online platform companies. This research offers an exploratory look at microentrepreneurs who engage in gig activities both online and offline without geographic or technological boundaries.

Project bundling is an innovative practice that groups or bundles several infrastructure projects into a single contract. While project bundling has various benefits, agencies are facing some challenges when bundling their projects, including properly assessing the feasibility (or infeasibility) of project delivery methods (PDMs) of interest. More specifically, project owners face the challenge of properly selecting between traditional and alternative PDMs for their bundled projects. Although some research efforts were devoted to providing guidelines in relation to different aspects related to project bundling, no previous study was conducted to help project owners performing PDMs-related feasibility analysis for bundled projects, which differ from normal, singly delivered projects. To fill this knowledge gap, this paper develops a decision-support tool that assists agencies in deciding whether they should select a traditional or alternative PDM (i.e. whether to go with the Design-Bid-Build (DBB) PDM or not) for their bundled projects.

An analytical methodology comprised of four main steps was followed in this paper. First, an expert survey was developed and distributed to industry experts to quantify the importance of 25 project bundling objectives. Second, principal component analysis was used to determine the weights for the different project bundling objectives. Third, a series of statistical tests was implemented to identify different feasibility tiers. Fourth, a user-friendly decision-support tool was developed, and its capabilities were demonstrated.

The results showed that six tiers exist to classify the feasibility (or infeasibility) of traditional PDMs (i.e. the DBB method) for bundled projects. The research outcomes have also reflected that the following five project bundling objectives contribute the most to making traditional PDMs (i.e. the DBB method) more feasible for bundled projects: (1) Having well-defined design features; (2) Requiring prior knowledge or experience with similar project size and scope; (3) Completing the overall project on schedule; (4) Keeping rate of expenditures within cash flow plan; and (5) Acquiring specific legislative, regulatory and jurisdictional requirements early on.

This research adds to the body of knowledge by equipping agencies and project owners with a decision-support system that helps them identify whether traditional or alternative PDMs are more appropriate for the specific objectives of their bundling program(s). By making the right PDM decision, project owners can enhance their bundling practices (especially in relation to the PDM proper selection) and ultimately the performance of their bundled projects.

“The latest available cross-country data presented in the PEPPER V Report (Lowitzsch and Hashi, 2024) can be viewed by examining EFP in and of itself as an isolated subject or it can be viewed in a much wider set of contexts. Widening the lens in order to examine EFP in the context of the concentration of capital ownership and the concentration of capital income can help observers establish EFP’s span of relevance. In particular US data on capital income show that policy makers need to be aware that EFP can have an important role in narrowing the income and wealth gap for the working middle class when the concentration of capital ownership and capital income is high and when real wage growth is low.”

“Against this background, this article makes a very straightforward observation that the relevance of EFP in an economic system, in a country, and for the average employee in a country is related to the trend in the concentration of capital ownership and capital income. Interest in the idea is potentially increased or decreased by trends in real wages. Atkinson, who many consider the founder of modern wealth concentration scholarship, “focuses on the increasing share of capital incomes a source of income inequality among individuals” (Cirillo et al., 2017, p. 1). Indeed, we consider the difference between labour’s share and capital’s share to be a critically important fundamental problem of political economy. This essay asserts that when this concentration is high and real wages are flat, other things being equal, EFP may be more relevant. When the concentration of capital ownership and capital income is high, this means that ownership and income on that ownership is thinly spread in the population. When real wages are flat, this means that the rate at which fixed wages can replenish wealth is decreasing. As a result, both trends would make EFP more relevant.”

The conceptual model suggested for this article asserts that the relevance of EFP can be viewed as a function of narrowing income and wealth options for the working middle class when the concentration of capital ownership and capital income is high and when real wage growth is low. Does this relevance change across economic systems? There is no question that the future understanding of these issues requires adding metrics to the statistical methodologies of different regions and countries and adding to existing reports and analyses that focus on both the dynamics of and trends in capital income (property income in the EU) and on the EUR and USD value of EFP at the mean and at the median for different income levels of the population

This article presents – for the first time – a society-wide measure of the impact of EFP on one economy, namely, the US For further research, it makes sense to build on the comparable data available on the distribution of capital ownership and have similar research on the distribution of capital income for both the EU and the US along with measures of the EUR and USD values of EFP.

The purpose of this study is to explore the incorporation of the sustainable development goals (SDGs) at the National University of Moreno (Universidad Nacional de Moreno, UNM, in Spanish), focusing on teaching and research activities, encountering difficulties from primary and secondary information sources, to integrate the SDGs, and contribute with actions for their incorporation into teaching and learning processes and research, in a newly established university.

To describe the implementation of the SDGs, an empirical study was conducted using a mixed methodology for data collection. Data collected from the survey were combined with information from the UNM project database for the period 2017–2022. Non-parametric methods were used to analyse both sets of data.

This study provides an initial overview of SDG implementation at UNM, allowing the identification of constraints and challenges to scale up contributions to the SDGs at UNM, as well as the generation of relevant action lines in the interaction with university's authorities.

Conducting studies through questionnaires has limitations, similar to other cases analysed. To increase the validity of the data, prior consultations were carried out. In addition, the database of research projects was used to identify the application of the SDGs in research. However, an approximation of the current situation could be obtained.

Particular importance was given to the challenges encountered during the data analysis phase in relation to capacity building needs. This enabled a set of actions to be defined to bring the SDGs closer to the UNM.

Although the paper used methodologies already proposed by other authors, such as survey collection, its value lies in demonstrating the possibility of using them to analyse whether the SDGs are integrated into teaching and research activities in a recently founded university, where the SDGs are integrated into its principles. The analysis also complements the survey results with information from project databases, which has not yet been analysed in the literature. Based on the results, activities are designed so that the SDGs could begin to guide teaching and research activities.

This study aims to evaluate the effectiveness of tax incentives provided by the Ethiopian government in spurring private investment and job creation, using unique administrative and survey data.

The study employs a dataset covering large- and medium-scale manufacturing in Ethiopia from 2012 to 2018, combined with administrative data on actual tax payments and statutory obligations to gauge the impact of tax incentives. Regression analysis using the generalized method of moments (GMM) is used to examine the relationship between tax incentives and employment, taking into account variations in production, distribution and financial costs.

The study finds that tax incentives do not significantly affect employment at conventional significance levels. The incentive elasticity of employment appears to diminish as production, distribution and financial costs increase. Consequently, the incentives provided by the government have not had a substantial impact on employment generation within the manufacturing sector.

This study is unique for its comprehensive analysis of tax incentives in the Ethiopian manufacturing sector using both administrative and survey data. It highlights that increasing production and financial costs can offset the employment benefits of these incentives, emphasizing the need for a more favorable business environment for private investors.

This study aims to evaluate the quality of information recorded in Behaviour Monitoring Charts (BMC) for Behaviours that Challenge (BtC) in dementia in an older adult inpatient dementia service in the North of England (Aim I) and to understand staff perceptions and experiences of completing BMC for BtC in dementia (Aim II).

Descriptive statistics and graphs were used to analyse and interpret quantitative data gathered from BMC (Aim I) and Likert-scale survey responses (Aim II). Thematic analysis (Braun and Clarke, 2006) was used to analyse and interpret qualitative data collected from responses to open-ended survey questions and, separately, focus group discussions (Aim II).

Analysis of the BMCs revealed that some of the data recorded relating to antecedents, behaviours and consequences lacked richness and used vague language (i.e. gave reassurance), which limited its clinical utility. Overall, participants and respondents found BMC to be problematic. For them, completing BMCs were not viewed as worthwhile, the processes that followed their completion were unclear, and they left staff feeling disempowered in the systemic hierarchy of an inpatient setting.

Functional analysis of BMC helps identify and inform appropriately tailored interventions for BtC in dementia. Understanding how BMCs are used and how staff perceive BMC provides a unique opportunity to improve them. Improving BMC will support better functional analysis of BtC, thus allowing for more tailored interventions to meet the needs of people with dementia.

The advantages of applying big data analytics for organizations to boost innovation performance are enormous. By collecting and analysing substantial amounts of data, firms can discern what works for their customer needs and update existing products while innovating new ones. Notwithstanding the evidence about the effects of big data analytics, the link between big data analytics and innovation performance is still underestimated. Especially in today's fast-changing and complicated environments, companies cannot simply take big data analytics as one innovative technical tool without fully understanding how to deploy it effectively.

This study tries to investigate this relationship by building on the knowledge absorptive capacity perspective. The authors conceptualized effective use of big data analytics tools as one general absorptive capacity rather than a simple technical element or skill. Specifically, effectively utilize big data analytics tools can provide values and insights for new product innovation performance in a turbulent environment. Using online survey data from 108 managers, the authors assessed their hypotheses by applying the structural equation modelling method.

The authors found that big data analytics capacity, which can be conceptualized as one absorptive capacity, can positively influence product innovation performance. The authors also found that environmental turbulence has strong moderation effects on these two main relationships.

These results establish big data analytics can be regarded as one absorptive capacity, which can positively boost an organization's innovation performance.

Value-based healthcare suggested using patient-reported information to complement the information available in the medical records and administrative healthcare data to provide insights into patients' perceptions of satisfaction, experience and self-reported outcomes. However, little attention has been devoted to questions about factors fostering the use of patient-reported information to create value at the system level.

Action research design is carried out to elicit possible triggers using the case of patient-reported experience and outcome data for breast cancer women along their clinical pathway in the clinical breast network of Tuscany (Italy).

The case shows that communication and engagement of multi-stakeholder representation are needed for making information actionable in a multi-level, multispecialty care pathway organized in a clinical network; moreover, political and managerial support from higher level governance is a stimulus for legitimizing the use for quality improvement. At the organizational level, an external facilitator disclosing and discussing real-world uses of collected data is a trigger to link measures to action. Also, clinical champion(s) and clear goals are key success factors. Nonetheless, resource munificent and dedicated information support tools together with education and learning routines are enabling factors.

Current literature focuses on key factors that impact performance information use often considering unidimensional performance and internal sources of information. The use of patient/user-reported information is not yet well-studied especially in supporting quality improvement in multi-stakeholder governance. The work appears relevant for the implications it carries, especially for policymakers and public sector managers when confronting the gap in patient-reported measures for quality improvement.