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This study aims to find evidence of a possible relationship between three constructs that are generally investigated separately: entrepreneurial orientation, understood as entrepreneurship on the organizational level; marketing capability, seen as a highly competitive factor for the organization; and business performance, highlighted as a focus of the entire organization.

A survey-based quantitative approach was adopted with a cross-sectional temporal perspective. To arrive at results that can be compared, the study uses factor analysis and structural equations modeling techniques, with estimations of maximum likelihood for testing the quality of fit of the measures to the structural models, using SPSS 21 and AMOS 16 software. Data were collected at the 27th EXPOSUPER, which is a trade fair at which 35,000 visitors were present. The data collection instrument used is a questionnaire previously validated by Reis Neto et al. (2013a). The first section covers control variables chosen to profile the firms, the second contains entrepreneurial orientation variables, the third comprises marketing capability variables and the fourth section contains business performance variables, all using seven-point Likert response scales.

Tests of the entrepreneurial orientation measurement scale produced interesting results in this application within the retail supermarket industry. The results of exploratory factor analysis indicated that a scale with three dimensions was significant. The relationship between entrepreneurial orientation and marketing capability (H1) is positive, through the intermediate dimensions of innovation, proactiveness and risk-taking, used by firms’ management, contributing to their efforts to research and manage the market, to develop products and services and to offer better prices. Exploratory factor analysis and confirmatory factor analysis showed that four of the scale’s dimensions of the marketing capability were significant: market research, market management, new product development and pricing. Comparison of these results with those of Reis Neto et al. (2013a) reveals a difference, as although their result, achieved using structural equations modeling, also had four factors; the promotion dimension was the most significant and absorbed the other variables. Despite these differences, confirmatory factor analysis and structural equations modeling demonstrated that this construct met the minimum conditions for adequacy, where (H2), formulated to test the relationship between the marketing capability construct, was confirmed. The final construct analyzed in this study was business performance, initially suggested by González-Benito et al. (2009), and also used by Reis Neto et al. (2013a). They used the dimensions profitability, market value and market response, and in the present study, after exploratory factor analysis, confirmatory factor analysis and structural equations modeling, the results were identical to those authors results, in that (H3), formulated with the objective of testing the relationship between the entrepreneurial orientation construct and business performance, was confirmed, and although this was not the most robust of the relationships postulated in the three hypotheses, but was of lower significance.

Although this study has achieved its objective, one of the study’s limitations relates to the data collection instrument, which was subject to failures in terms of the number of variables to be analyzed in each dimension. This led to elimination of certain dimensions during the analyses. Another limitation is related to the method used in the study. When questionnaires are used as data collection instruments, respondents often may not understand the true meaning of questions, which could lead them to choose any option, thereby stripping the results of credibility. In view of this limitation, it is suggested that future researchers conduct qualitative studies, using the case study method, which could offer greater clarity and increase understanding of the results related to these subjects. Even considering that this study has certain limitations and restrictions affecting generalization, it is hoped that it raises new questions, interests and inspirations, improving and complementing understanding of this strong social and economic sector.

It is identify the relationship between entrepreneurial orientation and marketing capability, since to date there is no evidence from studies confirming the existence of such a relationship. This statement was based on the results of a bibliographic survey conducted using the ProKnow-C, knowledge development process-constructivist methodology, in which, this originality was positive and significant, offering new studies from this point of view.

Factor analysis is the most used tool in organizational research and its widespread use in scale validations contribute to decision-making in management. However, standard factor analysis is not always applied correctly mainly due to the misuse of ordinal data as interval data and the inadequacy of the former for classical factor analysis. The purpose of this paper is to present and apply the Bayesian factor analysis for mixed data (BFAMD) in the context of empirical using the Bayesian paradigm for the construction of scales.

Ignoring the categorical nature of some variables often used in management studies, as the popular Likert scale, may result in a model with false accuracy and possibly biased estimates. To address this issue, Quinn (2004) proposed a Bayesian factor analysis model for mixed data, which is capable of modeling ordinal (qualitative measure) and continuous data (quantitative measure) jointly and allows the inclusion of qualitative information through prior distributions for the parameters’ model. This model, adopted here, presents considering advantages and allows the estimation of the posterior distribution for the latent variables estimated, making the process of inference easier.

The results show that BFAMD is an effective approach for scale validation in management studies making both exploratory and confirmatory analyses possible for the estimated factors and also allowing the analysts to insert a priori information regardless of the sample size, either by using the credible intervals for Factor Loadings or by conducting specific hypotheses tests. The flexibility of the Bayesian approach presented is counterbalanced by the fact that the main estimates used in factor analysis as uniqueness and communalities commonly lose their usual interpretation due to the choice of using prior distributions.

Considering that the development of scales through factor analysis aims to contribute to appropriate decision-making in management and the increasing misuse of ordinal scales as interval in organizational studies, this proposal seems to be effective for mixed data analyses. The findings found here are not intended to be conclusive or limiting but offer a useful starting point from which further theoretical and empirical research of Bayesian factor analysis can be built.

This study has two objectives. The first aim is to ascertain whether innovation and market orientation have direct, indirect, and causal effects on customer service. The second objective is to ascertain whether market orientation has a moderating effect on the relationship between innovation and customer service. This research follows three distinct methodologies. The first approach uses Cronbach’s alpha coefficient in order to check reliability while an exploratory factor analysis and a confirmatory factory analysis ascertain validity. The second method uses the analysis of structural equation models to test a causal link between variables. The third methodology uses a moderated regression analysis to verify the moderating effects. As our analysis results show, intelligence generation and intelligence dissemination have a moderating effect on the relationship between innovation and flexibility. These results can be interpreted as follows: firstly, customs clearance firms can provide superior service to customers if they strive to understand customer needs and provide them with flexible service at the same time. Secondly, these firms can enhance their flexibility of service in all departments though innovation and information sharing acquired from the market.

The main aim of this study is to explore the appropriate factors in measuring COVID-19-induced supply chain disruptions and the impact of these disruptions on the economic vulnerability of small-scale farmers in Sri Lanka.

The findings revealed that most of the farmers have continued to cultivate even during the pandemic despite several challenges which affected their economic status. Therefore, it is concluded that COVID-19-induced transportation and demand disruptions exacerbated the economic vulnerability of small-scale farmers over the disruptions in supply and production.

The findings of this study are crucial for formulating novel policies to improve the sustainability of the Sri Lankan agricultural sector and alleviate the poverty level of Agri-communities in the countryside. As farming is a vital sector in the economy, increased attention ought to be given on facilitating farmers with government-encouraged loans or allowances for their financial stability. Further, the respective government authorities should develop programs for importing and distributing adequate quantities of fertilizers among all the farmers at controlled prices so that they can continue their operations without any interruption. Moreover, the government could engage in collaboratively work with private organizations to streamline the Agri-input supply process. There should be a government initiative for critical consideration of the issues of farming families and their continued motivation to engage in agriculture. Thus, farmers' livelihoods and agricultural prosperity could be upgraded through alternative Agri-inputs and marketing strategies, providing financial assistance, encouraging innovative technology, etc.

Despite the significance and vulnerability of the vegetable and fruit sector in Sri Lanka, there is a limitation in the empirical studies conducted on the supply chain disruptions caused by COVID-19 measures and their implications on the farmers' livelihood. Furthermore, previous empirical research has not employed adequate quantitative tools to analyze the situation or appropriate variables in evaluating COVID-19-induced disruptions. Hence, the current study explored the appropriate factors for measuring COVID-19-induced supply chain disruption using exploratory factor analysis. Then, the impact of those factors on the economic vulnerability of the small scale farmers was revealed through the ordinal logistics regression analysis.

This paper aims to identify the factors that can affect the overall graduate employability (OGE) of the private university graduates of Bangladesh. The authors carefully selected six such employable factors after searching the existing literature. Those six factors: academic performance (AP), technical skills (TS), communication skills (CS), personality (PE), leadership & motivational skills (LMS); and teamwork and problem solving skills (TPSS), had been considered as the independent variables while OGE had been considered as the single dependent variable.

The authors collected the primary data from a valid sample of 360 employers through a structured questionnaire working as the hiring managers. Those respondents were selected on a random basis. The authors used exploratory factor analysis to validate the items under those independent variables and structural equation modeling with AMOS (24) to test the hypothesized relationship between each independent variable and the dependent one.

After proper statistical analysis, the results revealed that AP, PE, CS and TPSS can positively and significantly influence the OGE of Bangladeshi graduates while LMS and TS have positive but insignificant influence over OGE.

Based on the findings, this paper can help scholars in further investigating the employability factors.

This explorative study will guide the fresh graduates in developing their required employability skills while assisting the employers in recruiting suitable candidates with the required skills and performance.

This is one of the few attempts that focused on the employability factors of private university graduates in Bangladesh. The authors are well confident that this empirical paper can shed some light on the fresh graduates’ employability and conducting further investigations on it.

This study explores the main factors considered when shippers and container shipping lines select their import/export and transshipment ports. In the present study, 38 container port selection indices were chosen from the previous research and field interviews. The scores of the 38 items were collected via survey to the three major maritime/port market players: shippers, shipping lines, and container terminal operators. In order to analyze the different priorities imposed on the port selection factors by the three market players, the ANOVA method has been employed. The empirical test shows the different perceptions about port selection attributes among service suppliers and demanders. In addition, the 38 items have been categorized into seven key factors through an exploratory factor analysis. The ANOVA technique was employed again to analyze the perspective differences for the port selection factors among the market players. The results show that there are significant differences among the players assessing the importance of the three port choice factors: liners and terminal operators give more weight to ‘hinterland and terminal basic conditions’ than shippers; terminal operators do not take ‘line operation’ as seriously as carriers and shippers; the factor of ‘terminal operation’ is more significantly considered by liners and terminal operators than by shippers.

Measuring internal response of online learning is seen as fundamental to absorptive capacity which stimulates knowledge assimilation. However, the evaluation of practice and research of validated instruments that could effectively measure online learning response behavior is limited. Thus, in this study, a new instrument was designed based on literature to determine the structural variables that exist in the online learning response behavior.

A structured survey was designed and distributed to 410 Malaysian students enrolled in higher-education institutions. The questionnaire has 38 items, all of which were scored using a seven-point likert scale. To begin with, exploratory factor analysis with three types of extraction methods (i.e. principal component, principal axis factoring and maximum likelihood) was used as the method for comparing the outcomes of each extraction method's grouping variables by constantly using a varimax rotation method. In the second phase, reliability analysis was performed to determine the reliability level of the grouping variables, and finally, correlation analysis was performed to determine the discriminant nomological validity of the grouping variables.

The findings revealed that nine grouping variables were retrieved, with all items having a good value of factor loading and communalities, as well as an adequate degree of reliability. These extracted variables have good discriminant and nomological validity, as evidenced by correlation analysis, which confirmed that the directions of relationships among the extracted dimensions follow the expected theory (i.e. positive direction) and the correlation coefficient is less than 0.70.

This study proposes a comprehensive set of questionnaires that measure the student's online learning response behavior. These questionnaires have been developed on the basis of an extensive literature review and have undergone a rigorous process of validity and reliability for the purpose of enhancing students' online learning response behavior.

This study's findings will aid academic practitioners in assessing the online learning response behavior of students, as well as enhancing the questionnaire's boost factor when administered in an online learning environment.

This paper aims to explore and analyse stakeholders’ perceptions of the development priorities and suggests more effective strategies to assist sustainable economic growth in the United Arab Emirates (UAE).

The authors use the World Bank data set, which collects various stakeholders’ opinions on the UAE development. First, the exploratory factor analysis has been applied to detect the main groups of development priorities. Second, the fuzzy cluster analysis has been conducted to detect the groups of stakeholders with different attitudes towards the importance of extracted groups of priorities. Third, clusters have been compared according to demographics, media usage and shared prosperity goals.

The two main groups of development priorities have been extracted by the exploratory factor analysis: economic priorities and sustainability priorities. Four clusters have been detected according to the level of motivation when it comes to the economic and sustainability priorities: Cluster 1 (High economic – High sustainability), Cluster 2 (High economic – Medium sustainability), Cluster 3 (High economic – Low sustainability) and Cluster 4 (Low economic – Low sustainability). Members of the cluster that prefer a high level of economic and sustainability priorities (Cluster 1) also prefer more diversified economic growth providing better employment opportunities and better education and training for young people in the UAE.

Limitations stem from the survey being conducted on a relatively small sample using the data collected by the World Bank; however, this data set allowed a comparison of various stakeholders. Future research should consider a broader sample approach, e.g. exploring and comparing all of the Gulf Cooperation Council (GCC) countries; investigating the opinions of the expatriate managers living in the UAE that are not from GCC countries; and/or including other various groups that are lagging, such as female entrepreneurs.

Several practical implications were identified regarding education and media coverage. Since respondents prioritize the economic development factors over sustainability factors, a media campaign could be developed and executed to increase sustainability awareness. A campaign could target especially male citizens since the analysis indicates that males are more likely to affirm high economic and low sustainability priorities than females. There is no need for further diversification of media campaigns according to age since the analysis did not reveal relevant differences in age groups, implying there is no inter-generational gap between respondents.

This paper contributes to the literature by comparing the perceived importance of various development goals in the UAE, such as development priorities and shared prosperity indicators. The fuzzy cluster analysis has been used as a novel approach to detect the relevant groups of stakeholders in the UAE and their developmental priorities. The issue of media usage and demographic characteristics in this context has also been discussed.

This study aims to provide a measurement model, and the underlying constructs and items, for Logistics 4.0 in manufacturing companies. Industry 4.0 technology for logistics processes has been termed Logistics 4.0. Logistics 4.0 and its elements have seen varied conceptualizations in the literature. The literature has mainly focused on conceptual and theoretical studies, which supports the notion that Logistics 4.0 is a relatively young area of research. Refinement of constructs and building consensus perspectives and definitions is necessary for practical and theoretical advances in this area.

Based on a detailed literature review and practitioner focus group interviews, items of Logistics 4.0 for manufacturing enterprises were further validated by using a large-scale survey with practicing experts from organizations located in Central Europe, the Northeastern United States of America and Northern Thailand. Exploratory and confirmatory factor analyses were used to define a measurement model for Logistics 4.0.

Based on 239 responses the exploratory and confirmatory factor analyses resulted in nine items and three factors for the final Logistics 4.0 measurement model. It combines “the leveraging of increased organizational capabilities” (factor 1) with “the rise of interconnection and material flow transparency” (factor 2) and “the setting up of autonomization in logistics processes” (factor 3).

Practitioners can use the proposed measurement model to assess their current level of maturity regarding the implementation of Logistics 4.0 practices. They can map the current state and derive appropriate implementation plans as well as benchmark against best practices across or between industries based on these metrics.

Logistics 4.0 is a relatively young research area, which necessitates greater development through empirical validation. To the best of the authors knowledge, an empirically validated multidimensional construct to measure Logistics 4.0 in manufacturing companies does not exist.

This paper aims to develop and validate a scale to measure knowledge-sharing motives at work. It is aimed to construct a scale which is explicitly different from knowledge-sharing behavior and to develop a comprehensive and domain-specific scale for this special kind of work motivation.

The constructed scale was tested in two studies. Survey data (n = 355) were used to perform an exploratory factor analysis. Results were further tested on survey data from the core public sector (n = 314) and the health sector (n = 315). A confirmatory factor analysis confirms the results in both samples. The developed scale was further validated internally and externally.

The analysis underlines that knowledge-sharing motivation and knowledge-sharing behavior are different constructs. The data suggest three dimensions of knowledge-sharing motives: appreciation, growth and altruism and tangible rewards. While it is suggested that the developed scale works in the public as well as the private sector context, it is found that knowledge sharing of public employees is merely driven by “growth and altruism” and “appreciation of coworkers.”

No comprehensive and reproducible scale to measure knowledge-sharing motives, which is different from behavior and domain-specific as well, was available in the literature. Therefore, such a scale has been constructed in this study. Furthermore, this study uses samples from different organizational sectors to deepen the understanding of knowledge sharing in context.