Search results

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.

The Purpose of the study was to investigate the construct validity and internal consistency of the LaMI among staff in the context of elderly care in Sweden.

Questionnaire data from a longitudinal study of staff working in elderly care were used. Data were collected using the Leadership and Management Inventory. First data collection was for explorative factor analysis (n = 1,149), and the second collection, one year later, was for confirmatory factor analysis (n = 1,061).

The explorative factor analysis resulted in a two-factor solution that explained 70.2% of the total variance. Different models were tested in the confirmatory factor analysis. The final model, a two-factor solution where three items were omitted, showed acceptable results.

The instrument measures both leadership and management performance and can be used to continually measure managers’ performances as perceived by staff to identify areas for development.

Urban MICE competitiveness research consists of two clusters, one that is public-statistics-based and another that is questionnaire-based. Supply-side research on urban MICE competitiveness is rare. Based on the findings of Chen (2014) and other scholars, the purpose of this paper is to design counterpart statistical indicators to empirically analyze CMCA member cities.

After calculating the standardized Z value of the original statistical data for 17 CMCA member cities, the authors conducted confirmatory factor analysis for the first-level principal components, based on which hierarchical clustering was performed; then, regression analysis was conducted with the MICE profit factor as the dependent variable and the cost factor, tight support factor and facilitating factor as the independent variables to support publishing articles.

The confirmatory factor analysis showed that the urban MICE competitiveness indicators from the supply-side perspective include the profit factor, cost factor, tight support factor and facilitating factor.

On the basis of research findings from the demand perspective and the literature review, the authors constructed an urban MICE competitiveness indicator system from the perspective of the supply side and conducted principal component analysis. However, because of the inaccessibility of panel data, the current data were only sufficient to conduct the research. If panel data could be acquired, further research could be conducted to perfect the current indicator system for urban MICE competitiveness.

The findings suggest that tourism total income, tourism foreign exchange income, inbound tourist number, number of exhibitions, exhibition area, number of UFI member cities and number of ICCA member cities were the main reason for the gap between different cities’ competitiveness and the reform focus for improving urban MICE competitiveness. The cost factor had a significantly negative influence on urban MICE competitiveness, implying that the higher the average hotel room price and revenue per available room, the less competitive the MICE host city is.

The tight support factor exerts a significant positive influence on urban MICE competitiveness from the supply-side perspective, while the cost factor exerts a significant negative influence. The findings suggest that the tourism total income, tourism foreign exchange income, inbound tourist number, number of exhibitions, exhibition area, number of UFI member cities and number of ICCA member cities were the main reason for the gap between different cities’ competitiveness and the reform focus for improving urban MICE competitiveness. The cost factor had a significantly negative influence on urban MICE competitiveness, implying that the higher the average hotel room price and revenue per available room, the less competitive the MICE host city is.

The research bridge the empirical statistics and the questionnaire-based perception study on urban MICE tourism image, and advance to construct an empirical statistics based indicator system for urban MICE tourism image.

The purpose of this paper is to evaluate the insights of founding entrepreneurs to understand what they consider as motivating factors in their decision to act upon entrepreneurial intentions. Using this information, the entrepreneurial trigger event influence was conceptualized, and a scale developed for use in subsequent testable models.

Qualitative and quantitative techniques were used to construct an instrument that measures the presence and influence of entrepreneurial behavior triggers. The concept of triggering events was explored with 14 founding entrepreneurs. Themes emerged from this enquiry process which informed the development of four primary entrepreneurial triggering events. Over 600 entrepreneurs participated in the study. Exploratory factor analysis was used to identify dimensions of entrepreneurial triggers and was tested using confirmatory factor analysis.

Entrepreneurs perceive that personal fulfillment and job dissatisfaction serve as two significant trigger events which will lead individuals to engage in entrepreneurial behaviors. This research supports theorizing that suggests entrepreneurial trigger events have influence in motivating individuals to act upon entrepreneurial intentions and some trigger events may have more influence toward behavior than others.

This research is subject to multiple limitations. Trigger events were limited to those identified in literature and the interviews. Most entrepreneurs participating in this study were from a limited geographic region. The entrepreneurs in this study reported their triggering event based on their memory which could have been affected by inaccurate recall or memory bias. No attempt has been made to model the comparative effects of the different variables on entrepreneurial outcomes. Finally, the entrepreneurial trigger event instrument did not measure the participant's demographics or psychographics which could have played a role in the influence of reported trigger event.

This study extends previous research that trigger events serve as catalysts for entrepreneurial behavior. Findings support the premise that different types of triggers have different levels of influence as antecedents of entrepreneurial behavior. Specifically, positive, negative, internal and external entrepreneurial triggering events were explicated. The Entrepreneurial Trigger Event Scale created to facilitate this study enables researchers to explore the effects of types and perceived influences of precipitating trigger events on the intentions of the individual that result in entrepreneurial behavior. The optimized instrument further expanded Shapero's (1975) proposed theory of the origins of entrepreneurial behavior.

The development of a scale provides researchers with the opportunity to include the influence of entrepreneurial trigger events, as perceived by entrepreneurs, in future testable models. Entrepreneurial development organizations can use the knowledge to assist in understanding when potential entrepreneurs may act upon entrepreneurial intentions. Information gained can have significant implications for understanding the initiation of entrepreneurial behavior, entity establishment and business growth.

This research responds to a call for investigation into the influence of entrepreneurial trigger events on a person's decision to act upon entrepreneurial intentions. It is an early attempt to conceptualize a relevant construct of entrepreneurial trigger event influence and to develop a scale for use in empirical testing. It is distinguished by using planned behaviors, push and pull, motivation and drive reduction theories. These theories are applied to the perceptions of successful entrepreneurs to develop a construct and validate it.

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.

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 research has three objectives: one is to develop measuring criteria for ascertaining performance of customs clearance firms, another is to test reliability and validity of the factors, and the third is to analyze the relationship between customer service and firm performance. This research gathered the data from customs clearance firms. Reliability and validity concerned with the collected data are tested by exploratory factor analysis and confirmatory factor analysis and the relationship between variables is tested by analyzing structural equation modeling. The results are as follows. There are no problems in reliability and validity. According to the result of the analysis, customer service is divided into customer focus, customer needs, customer response and flexibility and performance is classified into customer performance and financial performance. The result of empirical tests is as follows. Customer focus has a positive effect on customer performance and financial performance. Flexibility has a positive effect on both types of performance. This means that firms which have discriminative services and a high level of flexibility through collaboration with customers can achieve high levels of customer performance and financial performance.

Technological advancements in games increased the popularity of online gaming. The rapid expansion of the eSports market may largely be attributed to the ever-increasing popularity amongst Generation Y amateur gamers. The primary objective of this study is to determine the factors influencing Generation Y amateur gamers' ongoing eSports gameplay intentions.

This study used the extended unified theory of acceptance as the theoretical framework. Data analysis included exploratory principal component analysis, confirmatory factor analysis and path analysis.

The results of the confirmatory factor analysis suggest that Generation Y amateur gamers' ongoing eSports gameplay intentions is an eight-factor model that is reliable, valid and has acceptable model fit. The results of the path analysis indicate that habit, price-value, flow, effort expectancy and facilitating conditions have a statistically significant positive influence on amateur gamers' ongoing eSports gameplay intentions, whilst social influence and hedonic motivation have a negative but non-significant influence on those intentions.

The sample was formed using only amateur eSports gamers. In this regard, the opportunity exists to research professional eSports gamers. This study only focussed on Generation Y members between 18 and 36 years old. As a result, there is an opportunity for researchers to research the different generations of South African eSports gamers to determine whether there are any differences or similarities between generational segments.

The results of this study clearly indicate that flow, together with habit are salient contributors to ongoing gameplay intentions amongst amateur eSports gamers in South Africa. A reasonable assumption that can be made here is that flow is also instrumental in encouraging habitual gaming, which increases the importance of flow in overall ongoing gameplay intentions. This suggests that R&D expenditure should be directed at enhancing user engagement by building increased levels of flow into eSports games.

eSports game developers can also achieve a desired state of flow by creating daily challenges that reward players when the players achieve specific objectives, which will encourage gamers to enter a state of flow when provided with challenges to complete. However, these in-game challenges should have a variety of levels regarding difficulty, ranging from beginner, intermediate and advanced levels so as not to exceed the effort expectancy of different groups of players. Game developers should provide regularly updated challenges to gamers to ensure that eSports games remain enjoyable and does not become predictable.

Given the nascence of research on eSports behaviour, the results of this study provide a novel addition to the knowledge pool, particularly in terms of amateur eSports behavioural intentions. Interestingly, hedonic motivation and social influence were non-significant negative predictors of Generation Y amateur gamers' ongoing eSports gameplay intentions. The recommendations provide various marketing strategies and opportunities for eSports business expansion.

The purpose of this paper is to demonstrate that common method variance, specifically single-source bias, threatens the validity of a university-created student assessment of instructor instrument, suggesting that decisions made from these assessments are inherently flawed or skewed. Single-source bias leads to generalizations about assessments that might influence the ability of raters to separate multiple behaviors of an instructor.

Exploratory factor analysis, nested confirmatory factor analysis and within-and-between analysis are used to assess a university-developed, proprietary student assessment of instructor instrument to determine whether a hypothesized factor structure is identifiable. The instrument was developed over a three-year period by a university-mandated committee.

Findings suggest that common method variance, specifically single-source bias, resulted in the inability to identify hypothesized constructs statistically. Additional information is needed to identify valid instruments and an effective collection method for assessment.

Institutions are not guaranteed valid or useful instruments even if they invest significant time and resources to produce one. Without accurate instrumentation, there is insufficient information to assess constructs for teaching excellence. More valid measurement criteria can result from using multiple methods, altering collection times and educating students to distinguish multiple traits and behaviors of individual instructors more accurately.

This paper documents the three-year development of a university-wide student assessment of instructor instrument and carries development through to examining the psychometric properties and appropriateness of using this instrument to evaluate instructors.