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People seem to function according to different models, which implies that in business and social sciences, heterogeneity is a rule rather than an exception. Researchers can investigate such heterogeneity through multigroup analysis (MGA). In the context of partial least squares path modeling (PLS-PM), MGA is currently applied to perform multiple comparisons of parameters across groups. However, this approach has significant drawbacks: first, the whole model is not considered when comparing groups, and second, the family-wise error rate is higher than the predefined significance level when the groups are indeed homogenous, leading to incorrect conclusions. Against this background, the purpose of this paper is to present and validate new MGA tests, which are applicable in the context of PLS-PM, and to compare their efficacy to existing approaches.

The authors propose two tests that adopt the squared Euclidean distance and the geodesic distance to compare the model-implied indicator correlation matrix across groups. The authors employ permutation to obtain the corresponding reference distribution to draw statistical inference about group differences. A Monte Carlo simulation provides insights into the sensitivity and specificity of both permutation tests and their performance, in comparison to existing approaches.

Both proposed tests provide a considerable degree of statistical power. However, the test based on the geodesic distance outperforms the test based on the squared Euclidean distance in this regard. Moreover, both proposed tests lead to rejection rates close to the predefined significance level in the case of no group differences. Hence, our proposed tests are more reliable than an uncontrolled repeated comparison approach.

Current guidelines on MGA in the context of PLS-PM should be extended by applying the proposed tests in an early phase of the analysis. Beyond our initial insights, more research is required to assess the performance of the proposed tests in different situations.

This paper contributes to the existing PLS-PM literature by proposing two new tests to assess multigroup differences. For the first time, this allows researchers to statistically compare a whole model across groups by applying a single statistical test.

Economic globalization is leading large companies to focus on international strategic management. Nowadays, the assets referred to as “corporate intangibles,” such as corporate reputation, are becoming increasingly important because they are considered a key factor for the viability of an organization, and companies therefore need to incorporate them into their scorecards for management. The problem is that their measurement is subjective and latent. These two characteristics impede direct international comparison and require demonstrating the accuracy of comparison via a minimum of two tests – construct equivalence and metric equivalence. As regards corporate reputation, construct equivalence was verified by Naomi Gardberg (2006). However, the subsequent studies did not address metric equivalence. Based on the results of a survey provided by the Reputation Institute (n = 5,950, 50 firms evaluated in 17 countries in the Americas, Europe, Asia and Australia), the degree of RepTrak metric equivalence has been tested, using two different methodologies, multigroup analysis (structural equation model), and a new technique from 2016, the Measurement Invariance of Composite Model procedure from the Partial Least Square Path Modeling family. As one would expect from other cross-cultural studies, reputation metrics do not meet the full metric equivalence, which is why they require standardization processes to ensure international comparability. Both methodologies have identified the same correction parameters, which have allowed validation of the mean and variance of response style by country.

Strategic groups research has been hampered by the poor alignment between theory and methods. This has been due in large part to the lack of significance tests for cluster analysis. Now that significance tests are available, the theoretical and methodological implications are discussed. The paper aims to discuss these issues.

The theory behind strategic groups is reframed to capitalize on the available significance tests. Subsequently, the significance tests are also modified to fit the proposed theory. Due to this integrative approach, this is both a theoretical and a methodological paper.

In lieu of significance tests, finding differences in performance emerged as the litmus test for the existence of discrete strategic groups. The concept of strategic groups gradually evolved to fit this requirement. Now that significance tests are available, these legacy effects of the structure-performance link can be removed. This reveals that three conflicting concepts have been sharing the label of strategic groups: strategic categories, interdependent strategic groups and strategic performance groups. The theory also reveals that the significance tests developed in ecological research need modifications for use in strategic groups research.

A theory is proposed for interdependent strategic groups and a significance test of external isolation is proposed as part of this integrative solution.

This integrative solution appears to resolve the historical mismatch between theory and methods that has plagued this field since its inception. This creates a variety of intriguing areas for future research.

The purpose of this paper is to evaluate the effect of CRM performance and technological innovation on performance of media entrepreneurs considering firm size.

This is an analytical study used to empirically test the hypotheses proposed for SEM techniques using PLS and R packages. It used two steps in this way: the assessment of the outer model and the assessment of the inner model. Moreover, a bootstrapping method was employed to test indirect effects. Data were collected by distributing 127 questionnaires between the managers and deputies of active firms across Rasht, Iran.

The effect of CRM performance on SMEs performance development is partially mediated by media entrepreneurship. Moreover, the effect of technological innovation on SMEs performance development is mediated by media entrepreneurship. Furthermore, permutation test results indicated that there is no significant difference between small- and medium-sized firms.

This study used cross-sectional sampling method that can seriously limit result generalization. Therefore, conducting longitudinal studies is strongly recommended.

The results of IPMA matrix indicated the serious importance of technological innovation, as a variable with the highest importance for SMEs performance development. Nevertheless, this variable has received the lowest importance in the studied population. Therefore, SMEs’ managers should pay sufficient attention to the concepts of “product innovations” and “process innovations.”

This study is of high importance in that it has adopted new and effective indices for statistical analysis. IPMA matrix, permutation test, CTA and FIMIX are examples. In addition, plspm and Matrixpls packages in R were used for the first time in this study.

The current study aims to provide a systematic approach to detecting and identifying social desirability bias (SDB) in survey data using controversial sponsorship as a research context.

We used an experimental approach to manipulate sponsorship situations (e.g. Beer sponsor vs Sports drink sponsor) that could potentially motivate respondents to under-report their perceptions toward the sponsor. By employing both procedural and statistical approaches, our evidence shows that responses toward the controversial sponsor were in fact contaminated by SDB.

The findings of the study provide methodological and practical implications for how sport marketing scholars and practitioners can identify, detect and control SDB in self-report data.

We argue that some survey research in sport marketing may be prone to SDB, but SDB has not received sufficient attention in sport marketing research. We emphasize the importance of detecting (and avoiding/controlling) SDB in sport management research.

Quality function deployment (QFD) is a methodology to translate the “voice of the customer” into engineering/technical specifications (HOWs) to be followed in designing of products or services. For the method to be effective, QFD practitioners need to be able to accurately differentiate between the final weights (FWs) that have been assigned to HOWs in the house of quality matrix. The paper aims to introduce a statistical testing procedure to determine whether the FWs of HOWs are significantly different and investigate the robustness of different rating scales used in QFD practice in contributing to these differences.

Using a range of published QFD examples, the paper uses a parametric bootstrap testing procedure to test the significance of the differences between the FWs by generating simulated random samples based on a theoretical probability model. The paper then determines the significance or otherwise of the differences between: the two most extreme FWs and all pairs of FWs. Finally, the paper checks the robustness of different attribute rating scales (linear vs non-linear) in the context of these testing procedures.

The paper demonstrates that not all of the differences that exist between the FWs of HOW attributes are in fact significant. In the absence of such a procedure, there is no reliable analytical basis for QFD practitioners to determine whether FWs are significantly different, and they may wrongly prioritise one engineering attribute over another.

This is the first article to test the significance of the differences between FWs of HOWs and to determine the robustness of different strength of scales used in relationship matrix.

This article aims to propose guidelines to develop moderation hypotheses, assess moderators using the multigroup analysis and interaction effect approaches and interpret the results of moderation analysis in tourism and hospitality research.

Through a review of 600 articles published in top tourism and hospitality journals from the year 2016 to 2020, and reviewing the literature related to moderation analysis, this study identifies key issues in different steps of moderation analysis and proposes robust guidelines to aid future research.

The results of the systematic review uncovered some key issues in different steps of moderation analysis, such as hypothesis development, moderation assessment and results interpretation. The findings emphasized the typical methodological misconceptions and improper practices for moderation analysis.

Moderation analysis is of great significance to the advancement of theory, and its application has increased significantly in recent years. However, many studies appear to have a limited understanding of moderation analysis and follow questionable practices regarding hypothesis development, moderation assessment and results interpretation, thus leading to suspicious conclusions for theory advancement. By highlighting these methodological issues, this article provides robust guidelines for moderation analysis, which is of great theoretical and methodological significance to the academic research in tourism and hospitality.

As one of the first studies to provide robust guidelines for moderation analysis, based on a critical and systematic review of papers published in top-tier journals in tourism and hospitality and the latest developments on moderation analysis in the wider literature, this article has important theoretical and methodological significance for the academic research in tourism and hospitality as well as general social science disciplines.

The purpose of this paper is to examine the relationship between attitude, subjective norm, perceived behavioural control, religiosity, knowledge and Shariah-compliance with intention to hold Shariah-compliant credit card (SCCC) amongst Muslims and non-Muslims.

Researchers used survey questionnaire to collect data and applied a purposive sampling method, then analyzing the data using descriptive statistics and also multi-group analysis of SmartPLS.

For Muslims, attitude, subjective norm, Shariah-compliance, knowledge and religiosity are positively significant. While for non-Muslims, only attitude and subjective norm are positively significant to intention to hold SCCCs.

The behavioural study only focusses on intention to hold Islamic credit cards, which is constraining the extended model of the theory of planned behaviour (TPB) without the actual performance of the behaviour, which is holding SCCCs. Secondly, the research caters for a single method, namely, quantitative without including the qualitative method to better understand and explore other factors affecting consumers’ behavioural intention. The qualitative part can be carried out by conducting interviews with practitioners, regulators and customers. Thirdly, the cultural dimensions are not combined as parts of TPBs’ antecedents for extended model that could be affecting intention, as Malaysia has diverse ethnic groups with different religious background.

In terms of managerial implications, the findings will further assist financial service providers to develop more effective marketing strategies for Islamic financial products not just to cater for the Muslims but also the non-Muslims, who are increasingly attracted to Islamic banking. As many Muslims are still holding conventional credit cards, it is timely for the Islamic financial institutions to attract them with the SCCCs.

Financial marketers are expected to be qualified and well-versed on the different Islamic product structures and also the conventional products. By having such enables them to enlighten and create awareness amongst the targeted consumers in seeking Shariah-compliant financial-related products.

The research will contribute to new theoretical knowledge of an extended behavioural model in relation to customers’ perception towards SCCCs’ acceptance.

This article examines the direct effect of total quality management (TQM) practices on organizational performance (OP) and innovation (INN), as well as their indirect effect through organizational learning (OL) as a mediating variable. In addition, this survey examines company size as a contextual variable in the relationship between TQM and outcome variables.

A conceptual framework is proposed to test causal links between TQM, OP, INN and OL. To empirically test this framework, 110 questionnaires were collected from large Tunisian quality-certified industries, and 167 questionnaires were collected from small and medium-sized industries (SMIs) in order to examine the effect of company size. In this order, a multigroup analysis (MGA) is performed.

Using the structural equation modeling technique, seven hypotheses are investigated. The results reveal that TQM has a direct and significant positive effect on OP and INN. Data analysis shows that there is a significant positive effect between TQM and OL, while OL positively influences OP and INN. Furthermore, the results illustrate a mediating effect of OL between TQM and OP and INN. The results reveal that large industries and SMIs show significant differences in the relationship, including the conceptual model.

The conceptual framework can be used by practitioners for effective implementation of TQM practices to simultaneously improve operational performance, quality performance and INN. This study also focuses on the role of OL in large-scale industries.

While the relationships between TQM, INN and OP have been examined separately in previous studies, this study examines the relationship between these variables in a unique model in Tunisian industries, including OL as a mediating variable. In addition, it is one of the few studies that considers firm size as a contextual variable and provides an analysis of its effect on the relationships between these variables. This study presents new data and empirical insights into the relationship between these variables.