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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.

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.

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.

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.

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.

Through a survey of firm’s experiences with strategic alliances and a structural equation modeling approach, the aim of this study is to stimulate further interest in modeling and empirical research in the area of N-loop learning. Although the concepts of single-loop and double-loop learning, in particular, are well established in the literature, limited research has been directed toward their empirical validation and finer understanding.

Based on a large sample of technology firms, a MIMIC model is proposed and tested with respect to the development of collaborative know-how via the adoption and conduct of different structural choices on how to deploy strategic alliances (single-loop vs double-loop approach). Results are cross-validated.

Based on the results of two structural equation models, the findings support the fit of the proposed conceptual model and the notion that, overall, the greater the extent of double-loop over single-loop learning, the higher the level of collaborative know-how derived.

The call for the empirical investigation of N-loop learning is met by providing an example of survey-based research. The possible benefits of “double-loop” over “single-loop” learning are modeled and tested empirically.

Sustainable supply chain (SSC) provides one opportunity to achieve competitive advantage. To achieve SSC through triple bottom line (TBL) – economic, environment and social – is extensively discussed. Most literature in dealing with environmental issues undermine social dimension even though its potential to bring outstanding results by earning customers loyalty and commitment is immense. Local orientation and different context motivate firms to prioritize sustainability dimensions differently. The purpose of this paper is to conceptualize SSC performance as three dimensional second-order formative construct which is caused by three first-order reflective constructs. Further, the authors examined effect of sustainable performance on barriers to sustainability through collaboration.

The model is validated by data collected from industries in India using both partial least squares and covariance based structural equation modeling. The authors find the model is valid for both manufacturing and service sectors.

In Indian context, social dimension is most and environmental dimension is least important differentiating it from developed economy. The authors find sustainable performance subsequently mitigates barriers and risks to sustainability, thereby reducing its impact over time.

This study conceptualizes SSC performance as three dimensional second-order formative construct which is caused by three first-order reflective constructs. Given criticisms to TBL for being western-centric, this study unearths insightful phenomena having implications for both developing and developed world. Further, the authors find sustainable performance reduces effects of barriers to collaboration necessary to achieve SSC. This study contributes to both theory and practice by modeling sustainability performance.

The purpose of this paper is to test the properties of the well-known three-dimensional adjustment scale, established by Black et al. (1988, 1989), namely, its dimensionality and internal consistency. The theoretical basis of the construct is discussed in relation to formative and reflective measurement approaches.

Two different ways of organizing the adjustment items (random/non-random) were used to assess the internal consistency of the three-dimensional adjustment scale. The quantitative analysis presented is based on survey data from 468 assigned expatriates in Asia that were subjected to an exploratory and confirmatory factor analysis as well as a structural equation modeling – more specifically the multiple indicators multiple causes model (MIMIC).

The study revealed that the adjustment construct is possibly misspecified, especially the general adjustment dimension, that was tested as a formative, not a reflective scale. There is further evidence that the wrong measurement approach skewed the coefficient that connects adjustment to performance, which is the key construct in its nomological network. Moreover, the dimensionality and the internal consistency of the scale are deteriorated to a large extent by randomization of the items. The findings highlight the need for a clear concept definition that would lead to an appropriate operationalization of the construct.

The study is one of the few rigorously testing the properties of a construct that has been used for almost 30 years, thus yielding some novel conclusions about its stability and consistency.

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.

The development of new advanced materials, such as photopolymerizable resins for use in stereolithography (SLA) and Ti6Al4V manufacture via selective laser melting (SLM) processes, have gained significant attention in recent years. Their accuracy, multi-material capability and application in novel fields, such as implantology, biomedical, aviation and energy industries, underscore the growing importance of these materials. The purpose of this study is oriented toward the application of new advanced materials in stent manufacturing realized by 3D printing technologies.

The methodology for designing personalized medical devices, implies computed tomography (CT) or magnetic resonance (MR) techniques. By realizing segmentation, reverse engineering and deriving a 3D model of a blood vessel, a subsequent stent design is achieved. The tessellation process and 3D printing methods can then be used to produce these parts. In this context, the SLA technology, in close correlation with the new types of developed resins, has brought significant evolution, as demonstrated through the analyses that are realized in the research presented in this study. This study undertakes a comprehensive approach, establishing experimentally the characteristics of two new types of photopolymerizable resins (both undoped and doped with micro-ceramic powders), remarking their great accuracy for 3D modeling in die-casting techniques, especially in the production process of customized stents.

A series of analyses were conducted, including scanning electron microscopy, energy-dispersive X-ray spectroscopy, mapping and roughness tests. Additionally, the structural integrity and molecular bonding of these resins were assessed by Fourier-transform infrared spectroscopy–attenuated total reflectance analysis. The research also explored the possibilities of using metallic alloys for producing the stents, comparing the direct manufacturing methods of stents’ struts by SLM technology using Ti6Al4V with stent models made from photopolymerizable resins using SLA. Furthermore, computer-aided engineering (CAE) simulations for two different stent struts were carried out, providing insights into the potential of using these materials and methods for realizing the production of stents.

This study covers advancements in materials and additive manufacturing methods but also approaches the use of CAE analysis, introducing in this way novel elements to the domain of customized stent manufacturing. The emerging applications of these resins, along with metallic alloys and 3D printing technologies, have brought significant contributions to the biomedical domain, as emphasized in this study. This study concludes by highlighting the current challenges and future research directions in the use of photopolymerizable resins and biocompatible metallic alloys, while also emphasizing the integration of artificial intelligence in the design process of customized stents by taking into consideration the 3D printing technologies that are used for producing these stents.