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The purpose of this paper is to estimate the Tanzanian shadow economy (SE) from 2003 to 2015 and test the statistical relationships between the SE and its potential causes and indicators.

The econometric analysis is based on a multiple indicators multiple causes (MIMIC) model. To calibrate the SE from the estimates, the authors adopt the value of 55.4 percentage of the SE to official GDP from the literature for the base year 2005.

The SE ranges from 52 to 61 per cent of official GDP and slightly decreases from 2013 to 2015. Increase in inflation, unemployment and government spending were the main drivers of the SE dynamics.

Given the challenges facing estimation of the SE (e.g. small sample size, exogenous estimate to calibrate the model, meaning of the latent variable), quantification of SE should be considered to be rough measures.

To lower the size of the SE, the government needs to keep inflation and unemployment stable over time, to reduce government spending because it creates pressure on tax collection due to the limited tax base.

This is the first study specifically focused on Tanzanian SE based on the MIMIC approach. Existing estimates of Tanzanian SE are calculated by monetary models or apply a common MIMIC specification to the worldwide context.

The purpose of this paper is to examine the effect of gender on pre‐service teachers' computer attitudes.

A total of 157 pre‐service teachers completed a survey questionnaire measuring their responses to four constructs which explain computer attitude. These were administered during the teaching term where participants were attending a technology course. Structural equation modeling, in particular, confirmatory factor analysis and multiple indicators, multiple causes (MIMIC) modeling were used for data analysis.

No statistical significance is found for gender in the four constructs of computer attitude. However, the mean scores for males are higher for three of the constructs. Overall, the data in this study provides evidence to support the notion that computer attitude is a multidimensional construct.

This study contributes to the continuing interests among researchers to study the effect of gender towards the computer. The results of this study did not support others which found significant differences in computer attitudes by gender. This may be due to heavy reliance of computers in many educational institutions for teaching and learning which consequently granted equal access to male and female users. Methodologically, this study had employed MIMIC model as the technique to assess the effect of gender on computer attitude. MIMIC modeling is superior to conventional techniques (e.g. t‐test, ANOVA) because it is capable of analyzing latent and observed indicators.

This paper contributes to the literature concerning the Nigerian informal economy (IE) by estimating its size from 1991 to 2017 and identifying the major causes.

A structural equation approach in the form of the multiple indicators multiple causes (MIMIC) method is used to estimate the size of the Nigerian IE.

The results indicate that vulnerable employment and urban population as a percentage of the total population are the main drivers of the IE in Nigeria. The IE in Nigeria ranges from 38.83% to 57.55% of gross domestic product (GDP).

As a result of the empirical challenges in the estimation of the IE, the estimates of Nigeria's IE are considered to be rough estimates.

The authors calibrated the MIMIC model with the official estimate of the informal sector published by the Nigerian National Bureau of Statistics (NBS). This was an attempt to combine the national accounting approach, to estimate the size of IE, with the MIMIC approach, and to estimate the trend of informality.

The potential for differential functioning of performance assessments across ratings sources has gained recent research interest. This study used multiple-group confirmatory factor analysis (MGCFA) to examine whether measures of task and contextual performance are invariant across both supervisors and subordinates. As an extension, multiple indicators multiple causes modeling (MIMIC) was used to examine potential covariates of task and contextual performance ratings on latent task and contextual performance variability. Consistent with previous research, I found measurement invariance across subordinate- and supervisor ratings. Moreover, MIMIC results showed supervisor and subordinate demographic variables systematically influenced latent task and contextual performance variability despite measurement invariance over these rating sources. Implications for multi-source performance systems are discussed.

Results from international large-scale assessments, such as PISA surveys, suggest that boys do better in math and science, whereas girls do better in reading. How do gender gaps vary across subjects, when estimated simultaneously? Building on the work of Tsai, Smith, and Hauser (2017), we answer this question by applying a multilevel-MIMIC model that enables us to estimate gender gaps in two ways: gender differences in the effects of observed family and school factors on math, science, and reading scores; and the “adjusted” gender gaps in test scores across all three subjects after controlling for observables. We apply the model to 2012 PISA data of students aged 15–16 and enrolled in 9th or 10th grade in three East Asian (Japan, South Korea, and Taiwan) and three Western countries (USA, Germany, and the Czech Republic) that represent both similar and different types of school systems. Our findings indicate that the gender gap in math or science achievement in Western countries, favoring boys, does not necessarily apply to the East Asian countries examined here, while all three East Asian countries exhibit similar features of gender reading gaps in the 10th grade. There is evidence indicating that observed background and school factors impact boys’ and girls’ achievement in a similar way in USA, Japan, Korea, Taiwan, and the Czech Republic, but not in Germany. Overall, gender differences in family and school influences do not account for gender differences in academic achievement in any of the six countries.

This paper aims to study a scale development and validation process for an integrative marketing–operations alignment (MOA) theory. This theory was derived from several distinct theories that have attempted to explain the interaction between marketing and operations functions of manufacturing organizations. An initial qualitative research and literature review identified five antecedents to the MOA construct (decision coordination, reward system, information exchange, leadership strategy and performance evaluation) as well as two outcomes (customer orientation and competitor orientation).

The scale was developed and validated using successive testing processes including exploratory factor analysis, confirmatory factor analysis and structural equation modeling (LISREL).

The outcome of the research is a tested and validated model of MOA. While more work needs to be done to test and potentially extend the theory, this research has produced a basic functional model of the MOA process.

The limitations include target populations, choice of industry and geography and cross-sectional time horizon of the study.

This study represents an original contribution to the organizational theory literature, as it provides both a sound theoretical basis and a validated measurement model for the proposed theory of MOA. While this research does draw on existing models, it is more comprehensive and theory-based than the existing models.

The purpose of this paper is to investigate factors affecting farmers’ perceptions and knowledge of soil testing benefits and fertilizers use in Northern Haiti.

Data were collected from 452 farmers within 17 localities in Northern Haiti. The findings reveal that farmers currently have little or no knowledge of soil testing benefits and but know better about fertilizer use. The soil testing benefits and knowledge on fertilizers use were collected using Likert scale. Analyses were done using structural equations model and choice model.

Factors such as farm size, participation in project, rice, banana and cocoa growers, affect farmers’ perceptions and knowledge of soil testing benefits. Factors affecting willingness to pay include group membership, type of crops grown, whether farmer’ land is on the slope, his farm size and whether he participates in the US Agency for International Development (USAID) project. Knowledge on fertilizer use is influenced by rice and banana growers, fertilizer use, participation in soil testing program and AVANSE/USAID. The effects of both latent variables are found to be positive but non-significant.

As policy implication; farmers need training module to be better informed on soil testing benefits.

Soil testing is a novel agricultural input that is being popularized in developing countries. For sustainability of the laboratory to be installed, this study is needed to fill the gap in research on farmers’ behaviors toward and demand of soil testing in Northern Haiti.

This study aims to provide insights on how different sources of information concerning a quality assurance program (QAP) influence consumers’ wine purchase likelihood, profiles of consumers most likely to use QAPs (demographics, wine consumption and expenditures, wine involvement behaviors) and consumer attitudes toward QAPs.

Data are from a 2021 survey of 1,191 wine consumers in Tennessee and other US states. A multiple indicators multiple causes model is used to estimate how consumer demographics, wine consumption and expenditure patterns and several wine-involvement measures influence likelihood of using QAPs from eight provider sources when making wine purchase decisions. Sources include university, government, third-party certifiers, wineries and wine associations at the state, regional, national and international levels.

Wine consumers have an interest in QAP information when making wine purchase decisions. Not all QAP provider information is used equally, with almost 69% of the sample indicating the use of state wine association QAPs, but less than 44% indicating the use of government agency QAPs or third-party QAPs. Wine consumers’ demographics also influence the use of QAP information. Males, higher income consumers, residing outside of Tennessee and more wine-involved consumers are more likely to use QAPs. Consumers view QAPs as indicators of overall wine quality, ingredient quality and wine consistency rather than necessarily a means of building knowledge about local wines.

To the best of the authors’ knowledge, this paper is the first to examine not only QAP use from multiple providers but also how demographics, wine consumption, wine expenditures and wine-involvement impact QAP use.

Economic and financial integration (hereafter, economic integration) among economies has been a fertile area of research. Yet, what we argue is that economic integration needs new thoughts to adequately model the recent challenges to the global economy by developing a new index/measure of economic integration. The new index will not only shed invaluable insights into the drivers of economic integration between Australia and the Middle East but will also help craft economic, trade, and commercial policies to achieve the desired type of integration with Australia's trading partners. Our analysis is undertaken on a cross section of 140 countries for the year 2011, to understand the causes and indicators of integration. Our model combines changes in real GDP, per capita GDP, percentage of educational expense, and gender inequality as causal factors to explain integration as a latent variable. We use three indicators of integration: (1) a standard measure of economic integration, (2) exports and imports as a percentage of GDP, (3) flows of foreign direct investment. We then explore the linkages between these indicators, or manifestations of integration, and a number of its possible causes. In terms of the new index we rank 140 nations and note that Australia is ranked among the top 20 nations in terms of integration with the global economy. Except Israel and Oman, Australia's trade partners in the Middle East have little integration with the global economy. In a similar vein, we also find that Australia's northern neighbors – especially Indonesia, Malaysia, Thailand, Cambodia, Myanmar, Sri Lanka, India – are yet to get well-integrated with the global economy. As a result, we argue, Australia can lead these countries from Southeast Asia and the Middle East to form closer ties with the global economy via Australia and, by doing so, Australia can create unprecedented economic and social benefit.