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This chapter presents a new conceptual framework of institutional research (IR). The framework refines previously studied dimensions of IR and integrates them into the higher order concept of knowledge management. Previously studied dimensions of IR include the institution’s organizational sectors (e.g., academic, human resources), the functions for which information is used (e.g., operations, strategic management), and the resources supporting IR (e.g., technology, funding). The framework innovates by specifying what competencies are required to carry out IR activities and how to assign a level of development to each competency. This operationalization permits the creation of an assessment tool enabling us to move from general and intuitive statements about development to specific and behavioral levels which are actionable. The framework formulation was validated with a group of IR experts in Chile. The framework can be used to assess one institution, to compare an institution to a peer group, or to compare groups of institutions at the regional, national, or international levels.

The multidimensional structure of boredom poses unique measurement challenges related to scale length and statistical modeling. We systematically address these concerns in two studies. In Study 1, we use item response theory to shorten the 29-item Multidimensional State Boredom Scale (MSBS) (Fahlman et al., 2013). In Study 2, we use structural equation modeling to compare two theoretically consistent multidimensional structures of boredom (superordinate and multivariate) with the most commonly used, yet theoretically inconsistent, structure in boredom research (unidimensional parallel model). Our findings provide support for modeling boredom as multidimensional and demonstrate the impact of model selection on effect sizes and significance.

This paper compares two alternative methods for measuring multidimensional poverty. This question has become extremely important in recent years, both in the scientific literature and in social policy. We propose to use latent class analysis to evaluate poverty in Spain. We make use of the “fuzzy set” approach, and compare the results achieved from these two methodologies.

The health emergency resulting from the SARS-CoV-2 virus is a public health crisis with serious effects on all social dimensions. This chapter has estimated the effects that this pandemic could potentially have on tourism activities in Ecuador. The scenario methodology was the method of choice since it allows analyzing the environment and comparing different internal and external factors, placing them in a future context for the tourism sector. The data were obtained using the following: (1) UNWTO estimates anticipate that the pandemic will cause a decrease in tourist arrivals and income between −50% and −78% across the world; and (2) a simulation of the pandemic's possible impacts on employment, production and taxes that would cause drops of 50%, 70% and 78% in the demand for accommodation and food and beverage services that represent economic activities that are directly related to tourism.

The results confirm that in scenario 1, losses will amount to 1.327 million US dollars; in scenario 2, to 1.600 million USD; while for scenario 3, the country will stop receiving more than 1.700 million USD. Eight sectors of the economy will suffer 95% of the impact on job loss: the food and beverage service stands out from the rest, since 77 out of 10 jobs lost will come from those types of activities. The two other sectors that would suffer significant impacts would be trade and accommodation activities, which account for 8% and 5%, respectively, of the total number of jobs lost.

Most poverty research has explored monetary poverty. This chapter presents and analyzes the global multidimensional poverty index (MPI) estimations for China. Using China Family Panel Studies (CFPS), we find China’s global MPI was 0.035 in 2010 and decreased significantly to 0.017 in 2014. The dimensional composition of MPI suggests that nutrition, education, safe drinking water, and cooking fuel contribute most to overall non-monetary poverty in China. Such analysis is also applied to subgroups, including geographic areas (rural/urban, east/central/west, provinces), as well as social characteristics such as gender of the household heads, age, education level, marital status, household size, migration status, ethnicity, and religion. We find the level and composition of poverty differs significantly across certain subgroups. We also find high levels of mismatch between monetary and multidimensional poverty at the household level, which highlights the importance of using both complementary measures to track progress in eradicating poverty.

There has been a rapid expansion in the literature on the measurement of multidimensional poverty in recent years. This paper focuses on the longitudinal aspects of multidimensional poverty and its link to dynamic income poverty measurement. Using panel household survey data in Vietnam from 2007, 2008, and 2010, the paper analyses the prevalence and dynamics of both multidimensional and monetary poverty from the same dataset. The results show that the monetary poor (or non-poor) are not always multidimensionally poor (or non-poor) – indeed the overlap between the two measures is much less than 50 percent. Additionally, monetary poverty shows faster progress as well as a higher level of fluctuation than multidimensional poverty. We suggest that rapid economic growth as experienced by Vietnam has had a larger and more immediate impact on monetary than on multidimensional poverty.