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This study aimed to develop a psychometrically reliable job satisfaction (JS) measure for university employees, guiding administrative decisions and monitoring satisfaction over time in public universities.

A JS survey developed by a Brazilian federal university’s sustainability committee containing 58 items across physical, cognitive and organizational domains was longitudinally tested with 1,214 responses collected. The data were analyzed using Item Response Theory (IRT) analysis, employing the Graded Response Model, with tools such as frequency analysis, item characteristic curve, and full-information factor analysis in RStudio. The scale’s criterion validity was also established via expert qualitative interpretation.

The instrument’s internal consistency was confirmed as the results demonstrated its high reliability with a marginal reliability coefficient of 0.95. Significant findings revealed that recognition and supervisor relationships were key discriminators of JS and that workers began to perceive satisfaction when basic environmental conditions were met.

It is important to mention that the application of this scale is specifically limited to higher education institutions and may not be directly applicable to other educational settings or industry sectors without modifications.

Although numerous measures and scales have been developed to assess JS, one elaborated by using IRT in a public university environment was lacking. Due to shifting dynamics in the workplace, traditional measurement of JS has proven inadequate, necessitating a more precise, accessible and updated tool. The developed scale allows precisely targeted interventions to improve JS and can be reapplied to evaluate their effectiveness. This research thus contributes a valuable tool for academic organizational psychology, enhancing the understanding of the measurement of JS.

The main purpose of this study is to test for the interaction effect of digital literacy in the relationship between financial technologies (FinTechs) of biometrics and mobile money and digital financial inclusion among the unbanked poor women, youth and persons with disabilities (PWDs) in rural Uganda.

Covariance-based structural equation modeling was used to construct the interaction effect using data collected from the unbanked poor women, youth and PWDs located in the four regions in Uganda as prescribed by Hair et al. (2022).

The findings from this study are threefold: first; the results revealed a positive interaction effect of digital literacy between FinTechs of biometrics and mobile money and digital financial inclusion. Second; the results also confirmed that biometrics identification positively promotes digital financial inclusion. Lastly; the results showed that mobile money positively promotes digital financial inclusion. A combination of FinTechs of biometrics and mobile money together with digital literacy explain 29% variation in digital financial inclusion among the unbanked poor women, youth and PWDs in rural Uganda.

The data for this study were collected mainly from the unbanked poor women, youth and PWDs. Further studies may look at data from other sections of the vulnerable population in under developed financial markets. Additionally, the data for this study were collected only from Uganda as a developing country. Thus, more data may be obtained from other developing countries to draw conclusive and generalized empirical evidence. Besides, the current study used cross sectional design to collect the data. Therefore, future studies may adopt longitudinal research design to investigate the impact of FinTechs on digital financial inclusion in the presence of digital literacy across different time range.

The governments in developing countries like Uganda should support women, youth, PWDs and other equally vulnerable groups, especially in the rural communities to understand and use FinTechs. This can be achieved through digital literacy that can help them to embrace digital financial services and competently navigate and perform digital transactions over digital platforms like mobile money without making errors. Besides, governments in developing countries like Uganda can use this finding to advocate for the design of appropriate digital infrastructures to reach remote areas and ensure “last mile connectivity for digital financial services' users.” The use of off-line solutions can complement the absence or loss of on-line network connectivity for biometrics and mobile money to close the huge digital divide gap in rural areas. This can scale-up access to and use of financial services by the unbanked rural population.

This paper sheds more light on the importance of digital literacy in the ever complex and dynamic global FinTech ecosystem in the presence of rampant cyber risks. To the best of the authors' knowledge, limited studies currently exist that integrate digital literacy as a moderator in the relationship between FinTechs and digital financial inclusion, especially among vulnerable groups in under-developed digital financial markets in developing countries. This is the novelty of the paper with data obtained from the unbanked poor women, youth and PWDs in rural Uganda.

This study aims to analyze the capacity of ecotourists to exhibit behavior that aligns with the ecotourist scale using the Rasch model measurement.

The data was gathered using an online survey incorporating the five tenets of ecotourism using a seven-point rating scale on domestic tourists in Indonesia. Descriptive statistics, cross-tabulation and Rasch model measurement were used to analyze the data.

The ecotourist identification scale measurement items were reliable and satisfactory. The most challenging behavior for ecotourists was using the services of a tour guide who was concerned about the environment. Meanwhile, respecting cultural differences around the tourist destination was the most accessible behavior. Most respondents demonstrated a fit response pattern and satisfactorily met the validity and reliability criteria.

This study did not compare ecotourists’ ability to behave by the type of conservation visited as its limitation. However, it provides a significant methodological contribution to developing a measurement of ecotourist behavior implemented in well-established behavioral theories.

Integrating ecotourism into education, incentivizing eco-friendly tourism practices, promoting awareness, supporting local businesses, respecting local values and ensuring safe travels.

To the best of the authors’ knowledge, this study is the first of its kind to be conducted in Indonesia. It uses a unique and innovative method to reveal the unobserved variables in ecotourists’ behavior. The findings confirm that tourists’ behaviors align with the five tenets of ecotourism.

This study evaluated the impact of a faculty training program on student assessment using the Kirkpatrick model.

A self-reported survey assessed 111 Saudi and non-Saudi participants' satisfaction. Subjective and objective measures (self-reported measures, assessment literacy inventory and performance-based assessment tasks) gauged participants' learning level. Pre- and post-training data were collected from 2020 to 2022.

A highly significant effect on satisfaction (>80%) and learning levels was observed, as manifested by workplace practices of student assessment (>70%, the cut-off score). Pre- and post-training comparisons of participants' satisfaction and assessment literacy scores showed significant improvements following training. Multiple regression analyses showed no significant effects for gender and educational attainment but a substantial impact of academic cluster on participants' student assessment skills.

Long-term effects of training faculty on assessment practices and student achievement will be studied at the institutional level in future research.

The current study contributes to human capital investment via faculty training on student assessment, helping them comply with assessment best practices. This assures the quality, fairness and consistency of assessment processes across disciplines in higher education institutions, enhances assessment validity and trust in educational services and may support institutional accreditation.

This study provides opportunities for sharing best practices and helps establish a community of practice. It enhances learning outcomes achievement and empowers higher education graduates with attributes necessary to succeed in the labor market. The human capital investment may have a long-term impact on overall higher education quality.

This study contributes to the scarce literature investigating the impact of training faculty from different clusters on student assessment using subjective and objective measures. It provides developing and evaluating a long-term student assessment program following the Kirkpatrick model.

The understanding regarding the impact of entrepreneurial intentions on the job insecurity and depression is limited in the longitudinal settings, organizations need to know which factors can be added to decrease the psychological and career issues of visiting or contract employees. Thus, this research aims to investigate the person vocation fit and entrepreneurial leadership as a moderator in the relation of entrepreneurial intentions, job insecurity and depression in within- and between-person level with the time of 4 months' time lag.

The data was gathered by using survey method from visiting faculty of universities located in Punjab, in the longitudinal design of 4-wave months and M.plus software was used to do the mediation and moderation analysis.

Results revealed that job insecurity mediated the entrepreneurial intentions and depression, the person vocation fit and entrepreneurial leadership moderated the entrepreneurial intentions and job insecurity link in the following month.

This paper contributes in the literature of entrepreneurship and career management, by considering the role of person vocation fit and entrepreneurial leadership in the organizations of emerging countries that have high unemployment rate and mental health issues. This paper provides nuanced understanding of how these two constructs have influenced the entrepreneurial intentions-job insecurity-depression within- and between-person level in the visiting or contract employees. Therefore, made strong contribution to the theory of person- environment fit, the entrepreneurial event theory and the contingency theory in the longitudinal data. In addition, to generalize the results, this theoretical framework should be tested in the other geographic area and industries.

The findings give practitioners, e.g. managers, policy- makers and counselors, with an idea how to decrease the feelings of job insecurity and depression in visiting or contract employees. They can promote the culture of innovation by giving training of entrepreneurial leadership and hiring the employees who have person vocation fit, all of these factors can lead to enhance the positive organizational image in potential and existing employees as well as it will also decrease the unemployment issue in emerging countries.

In past, scholars focused on the consequences of job insecurity and its harms but none emphasized on the aspects of entrepreneurship regarding the visiting faculty of universities. Like how entrepreneurial intentions can gradually decrease the job insecurity and depression among them and how the strengthen of person vocation fit and entrepreneurial leadership role their play monthly in this regard.

The purpose of this study is to revisit the measures of internal consistency for multi-item scales in hospitality research and compare the performance of Cronbach’s α, omega total (ω_Total), omega hierarchical (ω_H), Revelle’s omega total (ω_RT), Minimum Rank Factor Analysis (GLB_fa) and GLB algebraic (GLB_a).

A Monte Carlo simulation was conducted to compare the performance of the six reliability estimators under different conditions common in hospitality research. Second, this study analyzed a data set to complement the simulation study.

Overall, ω_Total was the best-performing estimator across all conditions, whereas ω_H performed the poorest. α performed well when factor loadings were high with low variability (high/low) and large sample sizes. Similarly, ω_RT, GLB_fa and GLB_a performed consistently well when loadings were high and less variable as well as the sample size and the number of scale items increased. Of the two GLB estimators, GLB_a consistently outperformed GLB_fa.

This study provides hospitality managers with a better understanding of what reliability is and the various reliability estimators. Using reliable instruments ensures that organizations draw accurate conclusions that help them move closer to realizing their visions.

Though popular in other fields, reliability discussions have not yet received substantial attention in hospitality. This study raises these discussions in the context of hospitality research to promote better practices for assessing the reliability of scales used within the hospitality domain.

The development of an effective corporate vision is a necessary issue for corporate performance, and it is a key issue for corporate sustainable development as well. The recognition of questions like “what is the role of corporate vision in corporate performance” is directly related to the attitude and practice of entrepreneurs and managers toward the development of corporate vision as well as the effectiveness of the corporate vision itself. To better answer the questions concerning the role of corporate vision development and effectively guide the practice of corporations, the authors study the pathways and mechanisms by which corporate visions operate to assist businesses in achieving high performance.

The article completes the construction of indicators to measure each dimension of the corporate vision in line with social cognitive theory and analyzes the relationship between corporate vision and corporate performance by combining qualitative comparative analysis (QCA) and necessary condition analysis (NCA) research methods. The article provides insights into the logic of constructing and adjusting corporate visions from a process perspective.

The mechanisms by which corporate visions can be articulated, accepted and transformed within the organization are also the means by which corporate visions can improve corporate performance. In a dynamic environment, the corporate vision setting and acceptance process integrates the requirements of various stakeholders, leading to the adjustment and acceptance of the corporate vision. As a result, the vision has continuous validity in a changing environment. Both start-ups and non-start-ups can benefit from the guidance provided by a strong corporate vision in overcoming a variety of issues and obstacles to produce strong business performance.

This is the first study that shows the relationship between corporate vision and corporate performance from a process perspective. The authors are interested in understanding which characteristics for building a corporate vision are more accepted by organizational members and, in turn, create high corporate performance. The authors also explore the conditions for corporate vision acceptance. This research has positive implications for shedding some light on the mechanisms by which corporate visions improve corporate performance.

The paper provides a detailed historical account of Douglass C. North's early intellectual contributions and analytical developments in pursuing a Grand Theory for why some countries are rich and others poor.

The author approaches the discussion using a theoretical and historical reconstruction based on published and unpublished materials.

The systematic, continuous and profound attempt to answer the Smithian social coordination problem shaped North's journey from being a young serious Marxist to becoming one of the founders of New Institutional Economics. In the process, he was converted in the early 1950s into a rigid neoclassical economist, being one of the leaders in promoting New Economic History. The success of the cliometric revolution exposed the frailties of the movement itself, namely, the limitations of neoclassical economic theory to explain economic growth and social change. Incorporating transaction costs, the institutional framework in which property rights and contracts are measured, defined and enforced assumes a prominent role in explaining economic performance.

In the early 1970s, North adopted a naive theory of institutions and property rights still grounded in neoclassical assumptions. Institutional and organizational analysis is modeled as a social maximizing efficient equilibrium outcome. However, the increasing tension between the neoclassical theoretical apparatus and its failure to account for contrasting political and institutional structures, diverging economic paths and social change propelled the modification of its assumptions and progressive conceptual innovation. In the later 1970s and early 1980s, North abandoned the efficiency view and gradually became more critical of the objective rationality postulate. In this intellectual movement, North's avant-garde research program contributed significantly to the creation of New Institutional Economics.

This study aims to capture how the association between a multichannel relational communication strategy (MRCS) and customer performance is contingent upon such customer performance (low- versus high-performance customers) and to reconcile past contradictory results in this marketing-related topic. To this end, the authors propose and validate the method of quantile regression as an unconventional, yet effective, means to proceed to that reconciliation.

This study collected data from 4,934 customers of a private pension fund firm and accounted for both firm- and customer-initiated relational communication channels (RCCs) and for customer lifetime value (CLV). This study estimated a generalized linear model and then a quantile regression model was used to account for customer performance heterogeneity.

This study finds that specific RCCs present different levels of association with performance for low- versus high-performance customers, where outcome customer performance is the dependent variable. For example, the relation between firm-initiated communication (FIC) and performance is stronger for low-CLV customers, whereas the relation between customer-initiated communication (CIC) and performance is increasingly stronger for high-CLV customers but not for low-CLV ones. This study also finds that combining different forms of FIC can result in a negative association with customer performance, especially for low-CLV customers.

The authors tested the conceptual model in one single firm in the specific context of financial services and with cross-sectional data, so there should be caution when extrapolating this study’s findings.

This study offers nuanced and precise managerial insights on recommended resource allocation along with relational communication efforts, showing how managers can benefit from adopting a differentiated-customer performance approach when designing their MRCS.

This study provides an overview of the state of the art of MRCS, proposes a contingency analysis of the relationship between MRCS and performance based on customer performance heterogeneity and suggests the quantile method to perform such analysis and help reconcile past contradictory findings. This study shows how the association between RCCs and CLV varies across the conditional quantiles of the distribution of customer performance. This study also addresses a recent call for a more holistic perspective on the relationships between independent and dependent variables.

In this paper, a mixture of exponential and Rayleigh distributions in the proportions α and 1 − α and all the parameters in the mixture distribution are estimated based on fuzzy data.

The methods such as maximum likelihood estimation (MLE) and method of moments (MOM) are applied for estimation. Fuzzy data of triangular fuzzy numbers and Gaussian fuzzy numbers for different sample sizes are considered to illustrate the resulting estimation and to compare these methods. In addition to this, the obtained results are compared with existing results for crisp data in the literature.

The application of fuzziness in the data will be very useful to obtain precise results in the presence of vagueness in data. Mean square errors (MSEs) of the resulting estimators are computed using crisp data and fuzzy data. On comparison, in terms of MSEs, it is observed that maximum likelihood estimators perform better than moment estimators.

Classical methods of obtaining estimators of unknown parameters fail to give realistic estimators since these methods assume the data collected to be crisp or exact. Normally, such case of precise data is not always feasible and realistic in practice. Most of them will be incomplete and sometimes expressed in linguistic variables. Such data can be handled by generalizing the classical inference methods using fuzzy set theory.