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This paper aims to popularize the Bayesian methods among novice management researchers. The paper interprets the results of Bayesian method of confirmatory factor analysis (CFA), structural equation modelling (SEM), mediation and moderation analysis, with the intention that the novice researchers will apply this method in their research. The paper made an attempt in discussing various complex mathematical concepts such as Markov Chain Monte Carlo, Bayes factor, Bayesian information criterion and deviance information criterion (DIC), etc. in a lucid manner.

Data collected from 172 pharmaceutical sales representatives were used. The study will help the management researchers to perform Bayesian CFA, Bayesian SEM, Bayesian moderation analysis and Bayesian mediation analysis using SPSS AMOS software.

The interpretation of the results of Bayesian CFA, Bayesian SEM and Bayesian mediation analysis were discussed.

The management scholars are non-statisticians and are not much aware of the benefits offered by Bayesian methods. Hitherto, the management scholars use predominantly traditional SEM in validating their models empirically, and this study will give an exposure to “Bayesian statistics” that has practical advantages.

This is one paper, which discusses the following four concepts: Bayesian method of CFA, SEM, mediation and moderation analysis.

The purpose of this paper is to examine the effects of atmospherics and affective state on shoppers’ in-store behaviour using the two approaches in structural equation modelling (SEM), i.e. Frequentist and Bayesian approaches. Shoppers’ affective state was tested for its mediating effect on in-store shopping behaviour.

The final sample consists of 382 respondents who were drawn from shoppers at selected apparel stores in six of the most popular shopping malls around Kuala Lumpur (Malaysia). A frequentist approach to SEM is common among researchers and offers generally an analysis of the relationships between multiple latent variables and constructs. Alternatively, the Bayesian SEM (BSEM) approach stems from the diffusion of the model’s posterior distributions using the Markov Chain Monte Carlo technique. More specifically, this technique is inherently more flexible and substantive in determining parameter estimates as compared to the more conventional, the frequentist approach to SEM.

The results show the mixed effects of atmospheric cues in retail setting on shoppers’ affective state. More specifically, the positive direct effect of atmospheric cues (music) on in-store behaviour was confirmed while other atmospheric cues (colour and store layout) were found to be fully mediated by affective state. The Bayesian approach was able to offer more distinctive results complementing the frequentist approach.

Although the current sample size is adequate, it will be interesting to examine how a bigger sample size and different antecedents of in-store behaviour in retailing can affect the comparison between the frequentist approach in SEM and BSEM.

The authors found that a combination of well-designed store atmospherics and layout store can produce pleasurable effects on shoppers resulting in positive affective state. This study found that results from both frequentist and Bayesian approaches complement each other and it may be beneficial for future studies to utilise both approaches in SEM.

This paper met the aim to compare the approaches in SEM and the need to consider both approaches on in-store shopping environment. Overall, the authors contend that the Bayesian approach to SEM is a potentially viable alternative to frequentist SEM, especially when studies are conducted under dynamic conditions such as apparel retailing.

Mega construction projects (MCPs), which play an important role in the economy, society and environment of a country, have developed rapidly in recent years. However, due to frequent social conflicts caused by the negative social impact of MCPs, social risk control has become a major challenge. Exploring the relationship between social risk factors and social risk from the perspective of risk evolution and identifying key factors contribute to social risk control; but few studies have paid enough attention to this. Therefore, this study aims to systematically analyze the impact of social risk factors on social risk based on a social risk evolution path.

This study proposed a social risk evolution path for MCPs explaining how social risk occurs and develops with the impact of social risk factors. To further analyze the impact quantitatively, a social risk analysis model combining structural equation model (SEM) with Bayesian network (BN) was developed. SEM was used to verify the relationship in the social risk evolution path. BN was applied to identify key social risk factors and predict the probabilities of social risk, quantitatively. The feasibility of the proposed model was verified by the case of water conservancy projects.

The results show that negative impact on residents’ living standards, public opinion advantage and emergency management ability were key social risk factors through sensitivity analysis. Then, scenario analysis simulated the risk probability results with the impact of different states of these key factors to obtain management strategies.

This study creatively proposes a social risk evolution path describing the dynamic interaction of the social risk and first applies the hybrid SEM–BN method in the social risk analysis for MCPs to explore effective risk control strategies. This study can facilitate the understanding of social risk from the perspective of risk evolution and provide decision-making support for the government coping with social risk in the implementation of MCPs.

This study aims to evaluate the usage of partial least squares structural equation modeling (PLS-SEM) in journals related to logistics and supply chain management (LSCM).

Based on a structured literature review approach, the authors reviewed 401 articles in the field of LSCM applying PLS-SEM published in 15 major journals between 2014 and 2022. The analysis focused on reasons for using PLS-SEM, measurement model and structural model evaluation criteria, advanced analysis techniques and reporting practices.

LSCM researchers sometimes did not clarify the reasons for using PLS-SEM, such as sample size, complex models and non-normal distributions. Additionally, most articles exhibit limited use of measurement models and structural model evaluation techniques, leading to inappropriate use of assessment criteria. Furthermore, progress in the practical implementation of advanced analysis techniques is slow, and there is a need for improved transparency in reporting analysis algorithms.

This study contributes to the field of LSCM by providing clear criteria and steps for using PLS-SEM, enriching the understanding and advancement of research methodologies in this field.

This paper aims to present several Bayesian specification tests for both in- and out-of-sample situations.

The authors focus on the Bayesian equivalents of the frequentist approach for testing heteroskedasticity, autocorrelation and functional form specification. For out-of-sample diagnostics, the authors consider several tests to evaluate the predictive ability of the model.

The authors demonstrate the performance of these tests using an application on the relationship between price and occupancy rate from the hotel industry. For purposes of comparison, the authors also provide evidence from traditional frequentist tests.

There certainly exist other issues and diagnostic tests that are not covered in this paper. The issues that are addressed, however, are critically important and can be applied to most modeling situations.

With the increased use of the Bayesian approach in various modeling contexts, this paper serves as an important guide for diagnostic testing in Bayesian analysis. Diagnostic analysis is essential and should always accompany the estimation of regression models.

This paper aims to propose a multi-dimensional model on the basis of the key factors of the flexibility and the complexity through structural equation modeling (SEM). Dimensions of the flexibilities and complexity, including 16 main factors and 34 sub-factors, are investigated. The sampling of the research is accomplished using both academic and industrial experts.

A huge electronic questionnaire analysis, including 1,250 samples from which 1,036 were returned, was accomplished in various universities and manufacturing companies throughout the USA, Europe and Asia. Partial least square-SEM (PLS-SEM) is used to test the hypotheses through confirmatory factor analysis.

The results reveal insightful information about the impacts of different dimensions of flexibility on each other and also the effect of the flexibility on the complexity. Finally, system of linear mathematical equations for flexibility-complexity trade-off is proposed. This can be applied to realize the trade-off among dimensions of flexibility and complexity.

Flexible manufacturing systems are formed to meet the needs of the customers. Such systems try to produce products in appropriate quality at the right time and at the specified quantity. These, in turn, require flexibility and will cause complexity. Although flexibility and complexity are both important, there is no comprehensive framework in which the multi-dimensional relationships of the manufacturing flexibility and complexity, as well as their dimensions, are demonstrated.

This study aims to investigate the effects of environmental risk perception on the evaluation of socioeconomic development and subjective well-being in China.

A questionnaire survey was conducted, and data were collected from 408 participants of four major universities and government organizations in Changsha, China. Structural equation modeling (SEM) was used to analyze the collected data and to test the hypotheses with regard to the relationship among latent variables. Bayesian method was used as the statistical inference procedure.

Results show that environmental risk perception has a direct negative influence on perceived socioeconomic development and on subjective total well-being (i.e. both hedonic and eudaimonic well-being). The perceived socioeconomic development has a direct positive effect on the subjective total well-being; thus, it plays a partial mediation role between environmental risk perception and subjective total well-being.

Findings suggest that the environment protection act of the government and their contribution to socioeconomic development will significantly affect the total well-being of people. The empirical analysis is based on survey data; thus, this study may suffer the common problems of questionnaire survey.

Promoting pro-environment and health behaviors is important in developing a happy society.

This study demonstrates a significant negative effect of environmental risk perception on the total well-being of people according to SEM approach. This study determines two independent paths for government and policy makers to increase the total well-being of people in China, namely, increasing socioeconomic value to people and controlling and reducing environmental threats.

This paper aims to serve as an important guide for more rigorous quantitative research in tourism and hospitality.

This paper relies on comments from several methodological experts in the field, as well as the authors’ main observation of the literature.

This paper identifies ten important areas of concern. In each of these areas, the authors provide recommendations for best practices.

There are certainly other issues and concerns that are not covered in this paper. However, the issues addressed can be applied or generalized to most methodological contexts.

This paper does not present results from original research but provides interesting and comprehensive recommendations for more rigorous quantitative research.

This study explores the link between ISO 9001 certification, personal data protection and firm performance using financial balance sheet and survey data. The security aspect of data protection is analyzed based on the major requirements of the General Data Protection Regulation and mapped to the relevant controls of the ISO/IEC 27001/27002 standards.

The research analysis is based on 96 ISO 9001–certified and non-certified publicly traded manufacturing and service firms that responded to a structured questionnaire. The authors develop and empirically test their theoretical model using the structural equation modeling technique and follow a difference-in-differences econometric modeling approach to estimate financial performance differences between certified and non-certified firms accounting for the level of data protection.

The estimates indicate three core dimensions in the areas of “policies, procedures and responsibilities,” “access control management” and “risk-reduction techniques” as desirable components in establishing the concept of data security. The estimates also suggest that the data protection level has significantly impacted the performance of certified firms relative to the non-certified. Controlling for the effect of industry-level factors reveals a positive relationship between data security and high-technological intensity.

The results imply that improving the level of compliance to data protection enhances the link between certification and firm performance.

This study fills a gap in the literature by empirically testing the influence of data protection on the relationship between quality certification and firm performance.

The purpose of this paper is to draw on self‐categorisation theory and nation branding to investigate the social identities and influences which underpin consumer preferences for national brands.

A survey in Mozambique, an underdeveloped African country, compared a domestic mobile phone company whose brand contains the country name against a European brand. Consumer ethnocentrism might arise identifying with the national brand or with Mozambican personalities endorsing the brand. Value‐expressiveness might arise from consumers associating with celebrity endorsers. A dichotomy of youth versus older consumers moderated the relationships between social identities and brand preference. Bayesian structural equation modelling using Monte Carlo simulations estimated the path coefficients from a sample of 611.

Across age groups, ethnocentrism is stronger than value‐expressiveness in determining preference for national brands. Moreover, ethnocentrism is stronger with the older rather than younger consumers. Consumer ethnocentrism stemmed mainly from injunctive influence (IN) with both age groups. With older consumers, value‐expressiveness related significantly to descriptive influence, but not to IN. With youth, neither social influence significantly related to value‐expressiveness.

Single‐item measures might be less effective than multi‐item measures for psychological concepts of social identities and influences.

Understanding the role of social identity in consumer preferences for national brands may help managers heighten consumers' social identities and increase their loyalty for national brands. Shedding light on under‐researched African consumers may help firms doing business in these emerging markets as well as African governments that are attempting to strengthen the perceptions of their nation brand.

This paper bridges research in social psychology and international marketing by investigating the social identities and influences that underpin consumer preferences for national brands.