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The purpose of this paper is to illustrate how international business (IB) researchers can benefit from meta-analytic structural equation modeling (MASEM) by introducing a statistically rigorous approach (i.e. two-stage meta-analytic structural equation modeling or TSSEM) and comparing it with a conventional approach (i.e. the univariate-r approach). The illustration and comparison present a methodological overview of MASEM that will assist IB researchers in selecting an optimal method.

In this paper, the MASEM method is elaborated upon, and methodological issues are addressed, by comparing the TSSEM and the univariate-r approaches using an empirical illustration. In this illustrative example, which is based on transaction cost economics, the effects of a firm’s internal factors on its levels of commitment in an international entry strategy are examined.

The MASEM method can help IB researchers to test and build on IB theories by synthesizing findings in the extant literature because this method reflects the theoretical complexity of IB (e.g. intercorrelationships among factors). Comparing the two approaches of MASEM, it is found in this study that due to its statistical rigorousness TSSEM has methodological advantages in helping IB researchers test theoretical models.

This is the first study to introduce MASEM into the discipline of IB strategies. In this paper, the authors introduce an advanced research method and illustrate two ways of using it.

In this meta-analysis, the authors investigate the relationship between self-construal and conflict management strategies and shed light on the inconsistent findings in the literature. Moreover, they examine the mediating role of face concerns in this relationship. Importantly, the present meta-analysis is the first to test the assumptions of face-negotiation theory with the meta-analytic structural equation modeling (MASEM), which enabled the authors to test the hypothesized relationships in one single model.

The authors used the method of MASEM to test the relationship between self-construal and conflict management and assess the mediating role of face concerns. In this regard, the authors employed one-stage meta-analytic structural equation modeling to perform MASEM and its moderators.

Two hundred fifty-four effect sizes based on thirty-three studies were pooled in this meta-analysis. The authors found that individuals with stronger independent self-construal and stronger self-face concerns were more likely to use forcing. Moreover, the relationship between independent self-construal and forcing was mediated by self-face concerns. Individuals with a stronger interdependent self-construal and individuals with stronger other-face concerns were more likely to use problem-solving and yielding. The relationship between interdependent self-construal and problem-solving and yielding was mediated by other-face concerns. Finally, interdependent self-construal also had an indirect effect, via other-face concern, on avoiding and compromising.

The present meta-analysis is the first effort that the authors are aware of to test the assumptions of face-negotiation theory (FNT) using MASEM method. The authors used one-stage meta-analytic structural equation modeling viewed as the state of the methods to perform MASEM and its moderators. They employed full information meta-analytic structural equation modeling to show the generalizability and heterogeneity of structural equation modeling parameters. They applied studentized deleted residuals to assess outlier analysis and also conducted different methods to perform MASEM to check the robustness of the findings resulted. Finally, the current study adds multiple methods of assessing for publication bias.

Understanding consumer behavior across various contexts within marketing has long been the focus of studies. Although many models are used in explaining consumers' behavior, one of these is the Model of Goal-Directed Behavior (MGB), which is becoming prominent in explaining consumers' behavior in marketing. Given its popularity, prior research on MGB has shown inconsistent outcomes regarding the casual association of MGB variables. To overcome this, the authors have adopted a meta-analytic review of the marketing studies grounded on MGB theory in examining the consumers' behavior.

The study reviewed and analyzed 611 correlations from 27 studies with 31 samples (combined sample size of 9588) using a meta-analytic structural equation modeling (MASEM) technique.

The outcomes of MASEM confirm the significance of all the proposed relationships in the MGB model. However, the attitude has shown a strong influence on desire formation among all the proposed MGB relationships. Further, past buying experience and positive anticipated emotions strongly affect desire in developed nations compared to developing nations.

The current work has considered the possibility of various recommended moderators (e.g. culture, crisis situation, sample size, method of data collection, etc.); however, the study lacks to consider the dimension of gender dominance in it. Hence, future researchers should keep it in mind while conducting similar studies. Future scholars can also perform a comparative study on MGB across the domains and subdomains to know more insights.

The current work offers a better understanding of MGB application in marketing. As this work is one of the first meta-analyses on MGB application in marketing that also considers the effect of various moderators, it thus adds knowledge to the literature on MGB in marketing. It will also help the future researchers to understand MGB as a framework and its application in marketing.

The authors examined intellectual capital (IC) components, namely human, structural and relational capital, on firm performance (FP) and innovation performance (IP), while also examining the role of knowledge management (KM) in this context.

The authors employed a meta-analysis using 81 studies from 2006 to 2020 using bivariate analysis, meta-analytic structure equation modeling (MASEM) and fuzzy-set qualitative comparative analysis (fsQCA) to study IC components on FP and IP.

The MASEM results show that IC affects positively on FP, but not in a significant level and affects positively and significantly on IP. The findings also reveal that the moderation effect of KM affects positively on FP but not on IP. Additionally, the fsQCA analysis shows that KM and its multidimensional role has a positive impact on FP and IP and has a potential to be consistent as a dynamic component for IC.

The results may be limited by different statistical biases and inverse causality issues or associated with contextualities related to the studies of the sample selected by our criteria.

Managers can identify the appropriate IC elements and act accordingly. The study suggests that mobilizing human, structural, relational and knowledge capital must begin from the firms' birth and continue further during firms' stages of the business.

IC is the bridge of evolution for future societies. Knowing how its components impact all levels of corporate environment indirectly influences how societies build up their social bases and policies to fulfill new professional generations.

By using the MASEM and fsQCA, the authors have more detailed insights into the multidimensional context of KM in IC components on firm and innovation performance identifying configurations of intangible resources.

The purpose of this study is to reveal a sequential mediating process of the impact of shared leadership on team performance by studying the sequential mediating effect of team trust and team learning behavior.

This study develops and examines a sequential mediation model using the meta-analytic structural equation modeling (MASEM) method. The sample adopted consists of 347 independent effect sizes extracted from 280 empirical papers (288 independent studies, N = 21,888 groups).

The results indicate that team trust and team learning behavior play a sequential mediating effect in the shared leadership–team performance relationship.

The findings suggest that practitioners should share leadership functions and responsibilities among talented team members. Furthermore, practitioners should strengthen the emotional interaction among team members and give positive feedback to the team's intensive learning behaviors.

By identifying the sequential mediating effect of team trust and team learning behavior, this study not only advances the understandings of a comprehensive mediating process through which shared leadership enhances team performance, but also offers new insights into the interrelationship of different types of mediating mechanisms (i.e. team emergent state and team process) in the shared leadership–team performance relationship.

Informed by the resource-based view of the firm, dynamic capabilities theory and contingency theory, this study examines the impact of Industry 4.0 (IR4.0) technologies adoption on firm performance (FP) while accounting for the mediating role of innovation ambidexterity (IA) and moderating roles of contextual and methodological factors that drive the performance gains of the phenomenon.

A random-effect model in comprehensive meta-analysis (CMA) is used to synthesize 113 studies in 115 independent samples with 192,188 observations.

This analysis demonstrates that IR4.0 digital technologies are directly related to financial and non-financial performance, disclosing that the performance effect on non-financial is the largest. Moreover, there is a complementary partial mediation role of the impacts of IR4.0 on FP by IA. Furthermore, this focal relationship is moderated by boundary-spanning conditions: contextual factors – firm size, business type, economic development, industry sector and methodological factors – proxy of FP, sample size and study type.

The results imply that IR4.0 produces financial and non-financial benefits by enabling firms to develop dynamic capabilities like innovation ambidexterity, which informs managers and practitioners that unless IR4.0 technologies and IA strategies are combined together to generate superior FP, IR4.0, in and of itself, would produce a less positive impact on FP than the combined impact of IR4.0 and IA. Therefore, managers should focus on converting IR4.0 resources to dynamic capabilities like IA by leveraging open innovation strategies or building IR4.0-based coordination mechanisms by creating cross-unit business synergies.

To the best of the authors' knowledge, per the literature review, this is the first meta-analysis structural equation modeling study on the interplay between IR4.0, innovation ambidexterity and firm performance.

Wine consumer behavior has long been a topic of discussion among scholars and industry professionals aiming to understand the underlying predictors of key behavioral outcomes. To help explain wine consumer behavior, concepts such as involvement, expertise, loyalty, satisfaction and perceived risk are often examined. The overarching objective of this study is to determine the relationship between these predictors and their impact on wine purchase intention utilizing a meta-analytical structural equation modeling (MASEM) technique.

As MASEM provides substantive evidence regarding the relationships between theoretical constructs through the combination of multiple studies, the researchers’ aim is to make definitive statements about the predictors of purchase intention.

Findings revealed several relationships that support previous research but also identified relationships that contradict previous literature. This study contributes valuable insights into consumer behavior that wine brands can utilize to improve their marketing efforts.

Wine marketers with a greater understanding of the stronger predictors of purchase intention should be able to create marketing plans that drive wine sales.

Despite the abundance of research that has utilized these theoretical constructs to demonstrate their propensity for determining behavioral outcomes such as purchase intention, no previous attempts have synthesized this body of literature through the use of meta-analysis.

Information technology has been recognized as one of the keys to improved productivity in organizations. Yet, existing research has not paid sufficient attention to how information systems (ISs) influence the creative performance of individual users. The paper aims to discuss this issue.

This study draws on the theories of flow and cognitive load to establish a model of the predicted influences. The authors hypothesize that the information technology supports creativity by engaging individuals in a creative process and by lowering their cognitive load related to the process. To test these hypotheses, the authors employ a meta-analytical structural equation modeling approach using 24 previous studies on creativity and ISs use.

The results suggest that factors that help the user to maintain an interest in the performed task, immerse the user in a state of flow, and lower a person’s cognitive load during IS use can affect the user’s creative performance.

The findings imply that a combination of the theories of flow and cognitive load complements the understanding of how ISs influence creativity.

This paper proposes an explanation on why ISs affect creativity, which can be used by scholars to position further research, and by practitioners to implement creativity support systems.

This study investigated the underlying influence mechanism between mHealth service quality (SQ) and users' adoption intention and compared the differences of consumer individual decision-making behaviors between the pre-adoption stage and the post-adoption stages.

This study built the pre-adoption and post-adoption models based on the stimulus-organism-response (S-O-R) model. Besides, this study collected 14,221 independent samples from 40 studies of pre-adoption intention to use and 12,876 independent samples from 36 studies of post-adoption intention to continue using and used meta-analysis structural equation modeling (MASEM) method to explore the formation of mHealth service quality influence on consumers toward adoption intention.

The results showed that (1) service quality positively trigger users' cognition response (i.e. perceived usefulness, perceived ease of use and perceived trust) and further positively drove the adoption and continuance intention; (2) there are similarities and differences in the relative importance of users' cognitive response between service quality and adoption intention at pre-adoption and post-adoption stages; (3) perceived trust (PTRU) played the most significant mediator in predicting users' adoption intention in both two stages; (4) perceived usefulness had a stronger influence than perceived ease of use (PEOU) on the adoption intention in pre-adoption while the result was just opposite in post-adoption stage.

This study could help service providers effectively allocate their limited resources to improve user adoption intention.

This study is the first one to open the black box of the underlying influence mechanisms between mHealth service quality and individual adoption intention in mHealth services and show differences in consumer decision-making according to the adoption stage. It provides a new perspective to the research in mHealth.

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.