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Research on the relationship between customer satisfaction and customer loyalty has advanced to a stage that requires a more thorough examination of moderator variables. Limited research shows how moderators influence the relationship between customer satisfaction and customer loyalty in a service context; this article aims to present empirical evidence of the conditions in which the satisfaction‐loyalty relationship becomes stronger or weaker.

Using a sample of more than 700 customers of DIY retailers and multi‐group structural equation modelling, the authors examine moderating effects of several firm‐related variables, variables that result from firm/employee‐customer interactions and individual‐level variables (i.e. loyalty cards, critical incidents, customer age, gender, income, expertise).

The empirical results suggest that not all of the moderators considered influence the satisfaction‐loyalty link. Specifically, critical incidents and income are important moderators of the relationship between customer satisfaction and customer loyalty.

Several of the moderator variables considered in this study are manageable variables.

This study should prove valuable to academic researchers as well as service and retailing managers. It systematically analyses the moderating effect of firm‐related and individual‐level variables on the relationship between customer satisfaction and loyalty. It shows the differential effect of different types of moderator variables on the satisfaction‐loyalty link.

We argue that entrepreneurship research should use meta-analysis to integrate the findings of the field. A meta-analytical approach has several advantages as compared with narrative reviews: First, narrative reviews are likely to bias empirical evidence because they are limited by the information-processing capacities of the reviewers (Tett, Jackson, & Rothstein, 1991). This is often a downward bias leading to the conclusion of little positive knowledge in the field. For example, frequency counts of significant results ignore sampling errors of individual studies, reliability problems of instruments, range restrictions of samples, dichotomization of continuous variables, imperfect construct validity, and extraneous factors (Hunter & Schmidt, 2004). These issues usually result in a higher incidence of Type II errors (i.e., rejecting the hypothesis wrongly). Thus, narrative reviews are more likely to lead to the conclusion that there are no relationships between independent and dependent variables in entrepreneurship when in fact they are (Hunter & Schmidt, 1990; Tett et al., 1991). Second, meta-analysis accumulates studies based on a set of explicit decision rules and, therefore, is less biased by subjective perceptions of the reviewer than narrative reviews. Meta-analyses require judgments as well, e.g., when defining the area of the study or coding moderator variables. However, the decisions are public and open to criticism and replication by other scientists (Johnson & Eagly, 2000). Third, meta-analysis is based on many studies and, thus, avoids the influence of single studies. Fourth, meta-analysis controls for sampling error variance and, thus, controls for power deficits of individual studies (Hunter & Schmidt, 2004). For example, the Brockhaus and Nord (1979) study is frequently cited in the entrepreneurship literature for providing evidence that there is no relationship of personality characteristics with entrepreneurship. However, this study is based on a small sample of 31 business owners and therefore, has serious statistical power problems. Noteworthy, the effect sizes of small samples are less precise in estimating a population value than effect sizes of larger samples. Fifth, meta-analyses can correct many errors of individual studies (Hunter & Schmidt, 2004). Since meta-analyses estimate population correlations between given variables, it is important to correct for errors of studies (e.g., unreliability, range restriction, and sampling error) to achieve unbiased estimates. Sixth, meta-analysis allows an assessment of the magnitude of relationships and, thus, provides more precise and often comparable assessments of the validity of concepts. Thus, meta-analyses support the assessment of the practical significance of findings. Seventh, meta-analysis tests for variations in relationships across studies and, therefore, allows an assessment of the generalizeability of effects. If the size of reported relationships varies considerably between different studies, there will be context conditions that account for these variations. These context conditions are moderators that affect the size of relationships. The moderators may include study characteristics, method moderators, and theoretical moderators. Thus, meta-analyses also help to identify areas for new studies. Finally, meta-analysis techniques allow to test more than one independent and/or moderator variable by using methods based on regression analysis (Lipsey & Wilson, 2001). Using such procedures allows to estimate the independent contribution of variables on results, to control for methodological variables, and to test the interactions between moderator variables.

This paper seeks to explore how moderation can and should be modeled in cross‐national/cultural contexts. A multi‐national study of consumer involvement is utilized to demonstrate proper methods for modeling the different types of moderation.

Using data from a consumer survey regarding wine purchasing preferences conducted in Australia, New Zealand and the USA, the paper demonstrates how to identify moderators of form and of strength. A form moderator is modeled using multiplicative interactions while a strength moderator is modeled using multi‐group analyses in structural equation modeling (SEM). Differences in consumers across the three countries are examined from the results.

This study suggests that search behavior is positively influenced by involvement in New Zealand and the USA but not in Australia. It also shows that perceived risk of occasion decreases involvement in all three countries, while partial support for the positive effects of importance of tradition on involvement is found. Furthermore, “perceived risk of occasion,” identified as a moderator of form, is found to significantly moderate the relationship between importance of tradition and involvement in the US sample only. Finally, the results demonstrate significant differences across the three samples in relationships among importance of tradition, perceived risk of occasion, involvement, and search behavior, indicating that the country variable has significant moderator effects.

Understanding form vs strength moderation is important when evaluating multi‐national/cultural differences so that proper methodology can be utilized. This paper provides international marketing researchers with guidelines on how to model interactions and multi‐group comparisons using SEM.

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 report the results of a survey of business schools examining the impact of market orientation on overall business school performance. The authors extend previous research by examining the possible moderating influence of accrediting body affiliation and administrative position of key informants on the relationships between the components of market orientation (customer orientation, competitor orientation, and inter-functional coordination) and overall performance for each of three markets (student, parent, and employer). Research objectives are stated in terms of 18 hypotheses.

The authors apply moderated regression analysis following the methodology used by Sharma, Durand, and Gur-Arie (1981) and Slater and Narver (1994), examining the variable relationships within schools affiliated through two accrediting bodies, from the perspective of business school deans and chief academic officers.

Results suggest moderating effects for three of the 18 relationships that were tested. Intelligence gathered from survey research within higher education is indicated to vary somewhat depending on key informant characteristics (accrediting body affiliation and administrative position in this study).

These results have practical implications for strategic planning within higher education. A better understanding of the differences within higher education will assist decision makers in responding to intelligence gathered within their own university, and will also assist them with strategies involving other universities (such as competitors or global partners).

These results within higher education have implications for survey research more broadly, supporting concerns by Phillips (1981) and others that researchers be mindful of key informant characteristics and other factors that could bias their judgments regarding organizational properties and other variables under investigation.

This chapter reviews the methods available to hospitality and tourism researchers to perform moderation analysis with continuous variables in partial least squares structural equation modeling (PLS-SEM), with the objective of enhancing understanding and encouraging the use of these techniques in future papers. The product term method is presented first, followed by an empirical example/application in the context of hospitality and tourism. Two extensions, namely the two-stage approach that can help cope with formative and higher-order constructs, and the orthogonalizing approach that can help generate more accurate results and overcome multicollinearity among tourism variables in the presence of a continuous moderator variable, are then presented and discussed. The chapter concludes by presenting guidelines and recommendations for improving the use of interaction effects in analyses of tourism variables, as well as highlighting ongoing developments in both the product term method and PLS-SEM software.

The purpose of this paper is to explain how to model moderating effects of composites using partial least squares (PLS) path modeling. It provides the methodological underpinning of moderating effects in general and describes the various approaches for forming the interaction term, i.e., the product indicator approach, the two-stage approach, and orthogonalization.

The paper discusses the use of standardized vs unstandardized construct scores and introduces spotlight analysis as a useful way to report findings.

Researchers should rely on unstandardized estimates when analyzing moderating effects. Centering or orthogonalization can help improve the interpretability of path coefficients.

PLS software implementations should facilitate unstandardized estimates.

This paper formulates step by step guidelines for analyzing moderating effects of composites using PLS path modeling. It is the first to propose spotlight analysis for PLS path modeling.

This paper seeks to measure the relationship between organizational climate (OCL) with organizational commitment meta‐analytically and the moderators influencing them.

A meta‐analytic research method was used in this research to determine the strength of relationship, fail safe n and presence of heterogeneity in study.

The unfavourable OCL (Case 2) (k=40, n=66,318) is correlated negatively with organizational commitment with confidence interval range varying from −0.552 to −0.562. The favourable OCL (Case 1) (k=89, n=53.865) is correlated positively with confidence interval range varying from 0.509 to 0.521. This research reviewed 106 valid studies after screening from 256 studies. Ten moderators were utilized to see the degree of change in relationship. Case 1 had four moderators namely gender, tenure, age, educational background, while for Case 2, there were two major moderators namely tenure and age.

The conclusions of this research are limited to employees based in organizations located in the USA and as such cannot be generalized for very dissimilar countries/cultures.

To minimize the unfavourable OCL, role conflicts, supervisor employee relations, leadership styles, decision making needs to be minimized and focus should be more on favourable climate enhancing variables in order to have substantial employee organization commitment or employee retention.

This study combines the previous available research on relationship between OCL and organization commitment and strives to find the study‐based moderators for comprehension of meta‐analysis results.

This study aims to integrate extant research on eWallet adoption to better understand the key antecedents to eWallet use intention and examine whether the relationships differ across multiple moderators.

To integrate eWallet adoption findings, the unified theory of acceptance and use of technology (UTAUT) and its extensions were utilized. Meta-analyses estimated the relationships between eWallet use intention and seven antecedents and the intercorrelations between antecedents. A total of 28 effects were calculated, utilizing 48 studies and 444 individual effect sizes, using 14,802 subjects. Using meta-analytically derived values, regression and relative weight analysis then determined each antecedent's relative utility. Furthermore, moderator analyses examined whether eight theoretically based moderators influenced the relationships between the antecedents and eWallet use intention.

Price value, hedonic motivation, facilitating conditions and social influence had the strongest relationships with the intention to use eWallets, accounting for virtually all the unique variance. The three weakest antecedents, however, still explained a large percentage of variance. No relationships were significantly moderated.

Due to the lack of data in primary studies, some UTAUT moderators could not be analyzed. Also, common method variance may impact the findings because the primary studies used cross-sectional surveys.

This study provides guidance regarding how companies can increase eWallet adoption rates, which have lagged in certain countries. These recommendations include specific techniques for tailoring messages and emphasizing features and benefits.

To the best of the authors’ knowledge, this is the first integrative meta-analysis conducted on eWallet use. Combining meta-analysis, regression and relative weight analysis, this study provides an integration of what is currently known about eWallet use intentions.

The current study aims to systematically review the existing literature, identify the main determinants that impact individuals’ perceptions, attitude, intention and behavior and meta-analytically evaluate their respective strength. Moreover, this study examines the specific mechanism through which more distal factors, such as trust, risk, experience and enjoyment influence individuals’ decision in the context of online auction markets. Finally, the moderating effects of contextual and methodological factors that could potentially influence the relationships are explored. During the past two decades, a large number of empirical studies examined the factors that hinder or foster individuals’ initial and continued acceptance of online auction marketplaces.

Based on the effect sizes reported, 91 studies, including 95 independent samples (N = 36.788), the current study utilizes bivariate meta-analysis, meta-analytic structural equation modeling and weighted least squares regression moderator analysis to examine the nature of the identified relationships, the mechanisms through which they operate and the boundary conditions under which they do or do not hold.

The results show that trust and experience explain individuals’ initial usage intention, while risk and experience explain actual usage behavior, indicating that these variables are viable extensions to the technology acceptance model in the context of online auction marketplaces. The results also demonstrate that, once individuals participate in online auction markets, trust and enjoyment are important predictors of satisfaction, which, in turn, is the strongest determinant of loyalty intention. Furthermore, the results demonstrate that cultural context acts as moderator and, to some degree, explains the mixed empirical findings in prior research.

This study contributes to the existing literature by identifying the main determinants and their average direct and indirect effect on the individuals’ decisions in online auction marketplaces. The findings provide critical insights into the complex network of relationships which impact individuals’ perceptions, attitude, intention and behavior to initially and continuously use online auction marketplaces. Furthermore, the result contributes to the existing research by examining the effect of contextual and methodological boundary conditions – moderating factors that are difficult to test in primary studies.