Search results

This paper aims to study the influence of innovation on micro, small and medium-sized enterprises (MSME) performance in Colombia through the 403 MSMES survey analysis. In particular, this paper measures the effect of participation in R&D alliances, product innovation and process innovation on it.

MSME performance is measured through a composite index, estimated through principal components analysis using polychoric correlations, which is based on eight self-reported assessments of MSME performance. Then, this measure of performance is related to MSME participation in R&D alliances and the product and process development stance of the MSME based on an adaptation of the Miles and Snow business classification scheme, by means of an ANOVA and a linear regression.

Colombian SMEs are not significantly benefitted from participation on R&D alliances. Instead, their performance appears to be dependent upon their internal innovation efforts directed to product development. Moreover, the results suggest that imitators get a performance almost as high as innovators.

Innovation activities in Colombian SMEs are carried out informally, as they are mostly uninterested to engage in R&D activities and to develop new products by own initiative. Moreover, few of them have an R&D department. In regard to technology, results suggest that almost half of SMEs are classified as followers, namely, they use the same technology as competitors.

One popular method to assess discriminant validity in structural equation modeling is the heterotrait-monotrait ratio of correlations (HTMT). However, the HTMT assumes tau-equivalent measurement models, which are unlikely to hold for most empirical studies. To relax this assumption, the authors modify the original HTMT and introduce a new consistent measure for congeneric measurement models: the HTMT2.

The HTMT2 is designed in analogy to the HTMT but relies on the geometric mean instead of the arithmetic mean. A Monte Carlo simulation compares the performance of the HTMT and the HTMT2. In the simulation, several design factors are varied such as loading patterns, sample sizes and inter-construct correlations in order to compare the estimation bias of the two criteria.

The HTMT2 provides less biased estimations of the correlations among the latent variables compared to the HTMT, in particular if indicators loading patterns are heterogeneous. Consequently, the HTMT2 should be preferred over the HTMT to assess discriminant validity in case of congeneric measurement models.

However, the HTMT2 can only be determined if all correlations between involved observable variables are positive.

This paper introduces the HTMT2 as an improved version of the traditional HTMT. Compared to other approaches assessing discriminant validity, the HTMT2 provides two advantages: (1) the ease of its computation, since HTMT2 is only based on the indicator correlations, and (2) the relaxed assumption of tau-equivalence. The authors highly recommend the HTMT2 criterion over the traditional HTMT for assessing discriminant validity in empirical studies.

Coopetition is ubiquitous in the economy, but managing effectively this type of relationship between firms remains a challenge for many organizations. This paper investigates the coopetition within corporate groups and focus on factors that determine the simultaneous competition and cooperation between subsidiaries therein.

Drawing on a dataset of 121 corporate groups listed on the Warsaw Stock Exchange (WSE), this paper theoretically advances and empirically validates the impact of 18 factors which determine the coopetition relationship.

This study's findings confirm the importance of an organizational design among external and internal drivers of intrafirm coopetition. However, the role of an environmental uncertainty as a driver of intrafirm coopetition is not proven. Furthermore, the paper finds that internal determinants explain the phenomenon of coopetition between subsidiaries within a corporate group more than determinants related to the environment.

The paper contributes to the coopetition theory by empirical identification of drivers of intrafirm coopetition and advances the corporate groups studies by exploring internal relationships (cooperation and competition) and the determinants therein.

People visit malls not only to buy a product they need but also to enjoy the atmosphere or environment of the shopping center. Based on design and eco-natural environment, the purpose of this paper is to analyze the attraction factors of shopping centers.

The sample comprised 449 consumers from 25 different shopping centers in Bogota. The structural equation model (AMOS) enables the authors to discuss the influence of the design of green and natural spaces in the commercial management of shopping centers, given its positive and significant effect on the intention to visit.

Shopping centers are, by definition, spaces with a high level of design of the commercial environment. In this case, as evidenced in the results of this research, the design of ecological spaces and environments has the potential of becoming a field of interest for the commercial management of shopping centers, given its potential effect on visiting and shopping intentions.

The main originality of this study was to empirically include and demonstrate the influence of design and natural eco-environment on the intention to visit, along with other elements considered in previous investigations. Therefore, identification of specific empirical findings related to the way attraction factors work allows marketing directors and managers to improve their management decisions concerning design and implementation of marketing strategies, tactical decision guidance, decision-making assessment or control, and the proposal of alternative positioning attributes, such as the design, management, and arrangement of eco-natural environments that allow to increase the number of visits and purchases within these establishments.

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 this study is to assess the impact of cyberfraud in the South African banks with the aim to provide recommendations to effectively mitigate it.

The study uses a qualitative approach involving the use of structured questionnaires. The questionnaires were made available to the staff of 17 licensed banks in South Africa who deal with management, operation, administration and banking services. Two hypotheses were formulated and non-parametric statistical analyses involving the use of Chi-square test, Fischer’s Exact test and Spearman’s correlation were carried out. The two hypotheses formulated were tested to draw a conclusion.

The results obtained indicate that the impact of cyberfraud in the South African banking industry is highly significant and has affected the reputation of some of the banks. This calls for the need to review the diverse ways of curbing cyberfraud to lessen their impact and that of associated fraud risks on the banking operation.

This study provides an analysis on the relationship cyberfraud occurrences and the reputation of South African banks. The implementation of the recommendations may reinforce the existing security measures in the fight against cyberfraud.

The novelty of this study lies in the fact that the assessment of the impact of cyberfraud on the banking industry in South Africa has not been sufficiently highlighted by the existing literature.

People are increasingly responsible for making sound financial decisions to foster their financial satisfaction and well-being, which magnifies the importance of financial literacy, and this concept and measurement is still not yet crystallized in the literature, specifically capturing different behavior perceptions. Moreover, there is not a distinction based on different classifications of behavior, such as over or underconfidence, to understand the relation between literacy and decision process. To fill this gap, this paper aims to investigate whether the financial literacy conceptual model proposed applies similarly to every group independently of their previous self-confidence perception. For this purpose and quality control, OECD (2016) data were used with a final sample of 1,487 Brazilian citizens. Quantitative analysis technique using partial least squares structural equations path modeling and differences between groups using multi-group analysis was applied. In line with general studies, when analyzing the financial literacy usual model for the group as a whole, financial knowledge construct positively influences self-confidence, and both together positively affect financial behavior. However, for individuals with low financial knowledge and low self-confidence, as well as for those with too much or too little confidence, the model did not hold. Therefore, self-confidence perception influences the way financial knowledge is used for financial decisions and should be addressed in financial education and training to be more effective.

To operationalize the variables and test the paper’s hypotheses, the authors used the methodology developed in OECD (2016), based on the research instrument’s Brazilian application adapted from the questionnaire developed in OECD (2015), with data initially used and made available by Garber and Koyama (2016). Based on the recommendations of Hair Jr et al. (2017a, 2017b), the authors used partial least squares modeling PLS-PM (SmartPLS 3.2.6) to estimate the structural models.

Concerning structural relationships, the final model showed knowledge with a positive influence on self-confidence, self-confidence with a positive effect on behavior and knowledge with a positive influence on behavior, both directly and, through its relationship with self-confidence, indirectly. This underscores that, for the total sample, the greater people’s knowledge and self-confidence, the better their behavior. The unexpected absence of attitude in the final model, even allowing for potential measurement problems, brings up an important reflection on the mediating effect that the self-control variable may exert between attitude and behavior. A person may believe that saving for the future is important (attitude) but whether they actually save (behavior) may depend on self-control, which is needed to prevent immediate gains from being prioritized in practice.

The findings reported so far concern the study’s total sample. However, as expected from the literature review that provides the basis for the sixth and the most important hypothesis, respondents were found to be heterogeneous in terms of knowledge and self-confidence levels. These differences were evaluated by means of multi-group analyses that indicated that the model does not apply to respondents with low knowledge and low self-confidence and to those who are over- and underconfident. This implies inferring that financial education programs may be of little use if they only address technical knowledge development and fail to consider behavioral aspects such as those related to self-confidence, as this paper points out, and others. This signals the importance of diagnosing people’s profiles to enable developing solutions capable of minimizing the presence of behavioral biases. This need to be studied further.

The results imply inferring that financial education programs may be of little use if they only address technical knowledge development and fail to consider behavioral aspects such as those related to self-confidence, as this paper points out, and others. Models must be reviewed in light of natural diferences of cognition and lead to customized financial education.

This signals the importance of diagnosing people’s profiles to enable developing solutions capable of minimizing the presence of behavioral biases. Therefore, not only training topics in personal finance but also a deeper education program since the kindergarden must be considered.

Its practical contribution is to suggest the development of financial education programs that also take account of the potential presence of behavioral biases, which may prevent the misallocation of (scarce) public- and private-sector funds stemming from a limited focus on developing the population’s actual financial knowledge.

As the superiority of sports celebrities' endorsements has been questioned, the purpose of this study is to identify various types of endorsers' direct and indirect effects on consumers' purchase intentions.

Empirical data were collected from 240 useful responses to an online experiment, and research hypotheses were tested using (moderated) serial mediation analyses.

The study's findings indicate that an endorser has a positive influence on consumers' purchase intentions through their perceptions of the advertisement and the endorsed brand. A moderated serial mediation analysis finds differences in the four types of endorsers analyzed. A sports celebrity is the most effective type of endorser in increasing consumers' purchase intentions, whereas endorsements by company managers and peer consumers, while also positive, are less effective in influencing advertising outcomes. An expert's endorsement is comparable to that of a manager but not significant.

The generalizability of the study's findings is limited because of a restricted data sample, the use of fictitious endorsers and the limited number of product categories and brands analyzed.

The study systematically analyzes the behavioral influence of four types of endorsers on consumers' purchase intentions, mediated by their perceptions of the advertisements and the endorsed brand. The results of this analysis extend the current state of endorsement research, indicating that endorsements should be integrated into companies' marketing strategies and provide marketing professionals practical guidance on which type of endorser is most effective in influencing advertising outcomes.

This study explored Croatian nursing students' knowledge and attitudes regarding brominated flame retardants (BFRs) as indicators of their predisposition to educate future patients. The purpose of the study was to identify knowledge gaps and barriers and to propose possible remedies.

The cross-sectional survey was conducted on a convenience sample of 114 nursing students at undergraduate and graduate levels from three Croatian universities during the winter semester in the academic year 2018–2019. Descriptive and inferential statistical  analyses were performed using STATISTICA 13 software.

Slightly over half of the students (58.49%) were knowledgeable of BFR health effects and 45.28% showed knowledge about its presence in the environment. Only 33.02% of students identified prenatal exposure effects and 24.53% answered correctly about legislative actions. Participants expressed modest interest in the topic (M = 3.15, SD = 1.35). Although informing the public on the health consequences of BFRs was important to them (M = 4.18, SD = 1.03), they did not perceive health-care providers as primarily responsible for communicating that information.

There is a need to enhance related content in the curriculum to improve students' knowledge. Raising students' awareness regarding the role of nurses in clinical and policy arenas is proposed to facilitate active participation in improving environmental health.

The purpose of this paper is to examine the relationship between an individual's social capital context and entrepreneurship using a multi-level modelling framework.

This paper uses data from 87,007 individual level observations across 428 regions in 37 countries. The data comes from the 2010 and 2016 Life in Transition Surveys. The paper uses a principal component analysis to identify the different dimensions of an individual's social capital context. Subsequently, a multi-level model is employed examining the relationship between the components of an individual's social capital context and entrepreneurship (which is proxied by an individual's attempt to set up a business), whilst controlling for both country and regional effects.

Greater levels of networking, informal connections and tolerance of others have a significant positive relationship with entrepreneurial activity. Trust of institutions and others have a negative relationship with entrepreneurial activity. Regional and country differences are also important for entrepreneurship, demonstrating the importance of the multi-level and social contextual environment for business development.

Firstly, the authors present a broad, but comprehensive social contextual framework incorporating many measures of social capital when examining the importance of social capital for business development. Secondly, the work provides interesting results on the “bright and dark sides of trust” for entrepreneurship, answering calls for improved understandings on the positive and negative relationships between social capital and entrepreneurial activity. Thirdly, the paper extends the burgeoning but limited number of studies that examine the multi-level contextual environment of entrepreneurial activities.