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Purpose – Partial least squares (PLS) path modeling has become a pivotal empirical research method in international marketing. Owing to group comparisons' important role in research on international marketing, we provide researchers with recommendations on how to conduct multigroup analyses in PLS path modeling.

Methodology/approach – We review available multigroup analysis methods in PLS path modeling and introduce a novel confidence set approach. A characterization of each method's strengths and limitations and a comparison of their outcomes by means of an empirical example extend the existing knowledge of multigroup analysis methods. Moreover, we provide an omnibus test of group differences (OTG), which allows testing the differences across more than two groups.

Findings – The empirical comparison results suggest that Keil et al.'s (2000) parametric approach can generally be considered more liberal in terms of rendering a certain difference significant. Conversely, the novel confidence set approach and Henseler's (2007) approach are more conservative.

Originality/value of paper – This study is the first to deliver an in-depth analysis and a comparison of the available procedures with which to statistically assess differences between group-specific parameters in PLS path modeling. Moreover, we offer two important methodological extensions of existing research (i.e., the confidence set approach and OTG). This contribution is particularly valuable for international marketing researchers, as it offers recommendations regarding empirical applications and paves the way for future research studies aimed at comparing the approaches' properties on the basis of simulated data.

Alongside structural equation modeling (SEM), the complementary technique of partial least squares (PLS) path modeling helps researchers understand relations among sets of observed variables. Like SEM, PLS began with an assumption of homogeneity – one population and one model – but has developed techniques for modeling data from heterogeneous populations, consistent with a marketing emphasis on segmentation. Heterogeneity can be expressed through interactions and nonlinear terms. Additionally, researchers can use multiple group analysis and latent class methods. This chapter reviews these techniques for modeling heterogeneous data in PLS, and illustrates key developments in finite mixture modeling in PLS using the SmartPLS 2.0 package.

The purpose of this paper is to investigate the extent to which organizational level of functionality is affected by its leadership, its staff, the way task is performed in the organization (culture), and the structural and governance makeup of organizations. This study also determined the direct and indirect impacts of these variables on organizational functionality in general and drawing lessons to educational organizations in specific.

This is a quantitative study. Data from 185 participants were analyzed using SPSS software version 24. The data analysis procedure for this study followed various steps. First, multiple factor analysis was conducted to narrow the long list of items and to create a manageable list of construct variables for analyses. Then path analysis, using a series of multiple regression, was conducted to identify the degree of relationship between the independent and dependent variables. Finally, a path model coefficient diagram was created.

Using path analysis, a new model that depicts the level of interactions among the proposed variables and the extent and direction of influence of each variable on organizational level of functionality has been created. In addition, a path diagram that illustrates the model is provided and explained. This study also determined the direct and indirect impacts of these variables on organizational functionality. Finally, conclusions and implications of the study for educational organizations were presented.

It should be noted that path analysis studies, by nature, are based on assumptions provided by the researchers. Hence, future studies using different variables and different assumption may not necessarily generate the same result. In addition, this study looked at a broader view of organizations rather than a specific type.

This study expanded the use of organizational diagnosis frameworks, beyond studying organizational performance, to study organizational level of functionality which can be used to diagnose the level of function (or dysfunction) of organizations in a holistic manner.

The present study contributes to the body of literature in organizational diagnosis in various ways; chief of which is the creation of a new path model which shows the direct and indirect effects of specific variables in numeric terms.

Unlike previous studies on the topic, this study suggests that organizational level of functionality should be studied using variables internal to the organization, because any two organizations of similar purpose and capacity, located in similar environment, could function differently due to factors internal to the organizations. Investigating organizational level of functionality using variables internal to the organization is assumed to provide a deeper diagnosis and self-assessment as it minimizes the noises created by variables external to the organization. All the variables in this study are therefore carefully selected to be internal to organizations.

Smart card-based E-payment systems are receiving increasing attention as the number of implementations is witnessed on the rise globally. Understanding of user adoption behavior of E-payment systems that employ smart card technology becomes a research area that is of particular value and interest to both IS researchers and professionals. However, research interest focuses mostly on why a smart card-based E-payment system results in a failure or how the system could have grown into a success. This signals the fact that researchers have not had much opportunity to critically review a smart card-based E-payment system that has gained wide support and overcome the hurdle of critical mass adoption. The Octopus in Hong Kong has provided a rare opportunity for investigating smart card-based E-payment system because of its unprecedented success. This research seeks to thoroughly analyze the Octopus from technology adoption behavior perspectives.

Cultural impacts on adoption behavior are one of the key areas that this research posits to investigate. Since the present research is conducted in Hong Kong where a majority of population is Chinese ethnicity and yet is westernized in a number of aspects, assuming that users in Hong Kong are characterized by eastern or western culture is less useful. Explicit cultural characteristics at individual level are tapped into here instead of applying generalization of cultural beliefs to users to more accurately reflect cultural bias. In this vein, the technology acceptance model (TAM) is adapted, extended, and tested for its applicability cross-culturally in Hong Kong on the Octopus. Four cultural dimensions developed by Hofstede are included in this study, namely uncertainty avoidance, masculinity, individualism, and Confucian Dynamism (long-term orientation), to explore their influence on usage behavior through the mediation of perceived usefulness.

TAM is also integrated with the innovation diffusion theory (IDT) to borrow two constructs in relation to innovative characteristics, namely relative advantage and compatibility, in order to enhance the explanatory power of the proposed research model. Besides, the normative accountability of the research model is strengthened by embracing two social influences, namely subjective norm and image. As the last antecedent to perceived usefulness, prior experience serves to bring in the time variation factor to allow level of prior experience to exert both direct and moderating effects on perceived usefulness.

The resulting research model is analyzed by partial least squares (PLS)-based Structural Equation Modeling (SEM) approach. The research findings reveal that all cultural dimensions demonstrate direct effect on perceived usefulness though the influence of uncertainty avoidance is found marginally significant. Other constructs on innovative characteristics and social influences are validated to be significant as hypothesized. Prior experience does indeed significantly moderate the two influences that perceived usefulness receives from relative advantage and compatibility, respectively. The research model has demonstrated convincing explanatory power and so may be employed for further studies in other contexts. In particular, cultural effects play a key role in contributing to the uniqueness of the model, enabling it to be an effective tool to help critically understand increasingly internationalized IS system development and implementation efforts. This research also suggests several practical implications in view of the findings that could better inform managerial decisions for designing, implementing, or promoting smart card-based E-payment system.

The purpose of this paper is to critically review the latest approaches for capturing and explaining heterogeneity in partial least squares (PLS) path modelling and to classify these into a methodological taxonomy. Furthermore, several areas for future research effort are introduced in order to stimulate ongoing development in this important research field.

Different approaches to treat heterogeneity in PLS path models are introduced, critically evaluated and classified into a methodological taxonomy. Future research directions are derived from a comparison of benefits and limitations of the procedures.

The review reveals that finite mixture‐PLS can be regarded as the most comprehensive and commonly used procedure for capturing heterogeneity within a PLS path modelling framework. However, further research is necessary to explore the capabilities and limitations of the approach.

Directions for additional research, common to most latent class detection procedures include the verification and comparison of available approaches, the handling of large data sets, the allowance of varying structures of path models, the profiling of segments and the problem of model selection.

Whereas modelling heterogeneity in covariance structure analysis has been studied for several years, research interest has only recently been devoted to the question of clustering in PLS path modelling. This is the first contribution which critically consolidates available approaches, discloses problematic aspects and addresses significant areas for future research.

This research explores perceptions of knowledge management processes held by managers and employees in a service industry. To date, empirical research on knowledge management in the service industry is sparse. This research seeks to examine absorptive capacity and its four capabilities of acquisition, assimilation, transformation and exploitation and their impact on effective knowledge management. All of these capabilities are strategies that enable external knowledge to be recognized, imported and integrated into, and further developed within the organization effectively. The research tests the relationships between absorptive capacity and effective knowledge management through analysis of quantitative data (n = 549) drawn from managers and employees in 35 residential aged care organizations in Western Australia. Responses were analysed using Partial Least Square-based Structural Equation Modelling. Additional analysis was conducted to assess if the job role (of manager or employee) and three industry context variables of profit motive, size of business and length of time the organization has been in business, impacted on the hypothesized relationships.

Structural model analysis examines the relationships between variables as hypothesized in the research framework. Analysis found that absorptive capacity and the four capabilities correlated significantly with effective knowledge management, with absorptive capacity explaining 56% of the total variability for effective knowledge management. Findings from this research also show that absorptive capacity and the four capabilities provide a useful framework for examining knowledge management in the service industry. Additionally, there were no significant differences in the perceptions held between managers and employees, nor between respondents in for-profit and not-for-profit organizations. Furthermore, the size of the organization and length of time the organization has been in business did not impact on absorptive capacity, the four capabilities and effective knowledge management.

The research considers implications for business in light of these findings. The role of managers in providing leadership across the knowledge management process was confirmed, as well as the importance of guiding routines and knowledge sharing throughout the organization. Further, the results indicate that within the participating organizations there are discernible differences in the way that some organizations manage their knowledge, compared to others. To achieve effective knowledge management, managers need to provide a supportive workplace culture, facilitate strong employee relationships, encourage employees to seek out new knowledge, continually engage in two-way communication with employees and provide up-to-date policies and procedures that guide employees in doing their work. The implementation of knowledge management strategies has also been shown in this research to enhance the delivery and quality of residential aged care.

Collaborative consumption (CC), a unique business model, provides several monetary and non-monetary benefits to customers. Several adapted theory of planned behaviour (TPB)-based models were developed and tested to understand this consumption behaviour with the findings inconsistent and fragmented. Thus, this study aims to develop a general and consistent TPB model using a meta-analytic path analysis to better understand customers’ CC adoption behaviour.

Using 37 studies, a meta-analysis was performed adopting several analytical methods; bivariate analysis, moderation analysis and path analysis.

The universal TPB model shows that factors, that is, trust, attitude, perceived environmental responsibility and communication facilities, drive both perceived usefulness and CC. However, subjective norms, such as perceived behavioural control and emotional value, drive only perceived usefulness. Moderation analysis shows that the relationships between variables used in the proposed TPB model tends to vary depending on five moderators, that is, countries’ economic development level, type of CC, sample size, sample type and survey administration method.

The consideration of only quantitative papers and papers written in English language in this meta-analysis may bias the study’s findings.

Based on the findings regarding important factors that consumers consider when adopting CC, this study provides insightful recommendations to companies facilitating CC.

By developing the universal TPB model, this study theoretically contributes to the TPB model, and by conducting the moderation test, the study contextually contributes to the TPB literature in the CC context.

Purpose – Revisiting Fornell et al.'s (1996) seminal study, this chapter looks at the evidence for observed and unobserved heterogeneity within data underlying the American customer satisfaction index (ACSI) model. Examining data for two specific industries (utilities and hotels) reveals only modest differences. However, we suppose that unobserved heterogeneity critically affects the results. These insights provide the basis for shaping further differentiated ACSI model analyses and more precise interpretations.

Methodology/approach – This study applies the partial least squares (PLS) path modeling method and uses empirical data to estimate and compare the ACSI model results on the aggregate and industry-specific data levels. In addition, the finite mixture PLS path modeling (FIMIX-PLS) method is employed to further examine across industry similarities and within industry differences.

Findings – This research uncovers unobserved heterogeneity that guides forming three segments of customers within each industry. The major segment in each industry represents customers that are fairly loyal (i.e., neither disloyal nor extremely loyal) while the other two smaller segments are not as similar across the two industries. Our study identifies substantial differences across these segments within each industry. An importance-performance map analysis illustrates these differences and provides the basis for managerial implications.

Originality/value of the chapter – The unobserved heterogeneity revealed within industries in a given country (i.e., the United States of America) underlines the need to be open to differences within populations, beyond the observed heterogeneity across distinct groups or cultures, and the need to reconsider reporting requirements in academic research.

This study extends research on one of the most frequently cited school leadership frameworks by examining the psychometric properties of the instrument designed to assess many of the practices included in that framework.

Using data collected from 1,401 teachers the study examined the instrument’s measurement invariance, score reliabilities, as well as construct and predictive validities. Polytomous latent trait models (Many-Facet Rasch model), scale and principal component analysis using second-order Confirmatory Factor Analysis, and Structural Equation Modeling (SEM)-Path modelling were used for these purposes.

Findings report levels of score reliability and valid score inferences. Results concerning the predictive validity of the instrument indicate a complex set of relations among the domains of leadership practices measured by the instrument, variables selected as mediators of leaders’ influence, and their direct and indirect effects on student learning.

This study provides researchers with a reliable and valid instrument for use in their future research. Data for the study were provided by elementary teachers in one US state. The extent to which results of the instrument are valid across different cultural and organizational settings remains to be determined.

Leadership developers may find the instrument useful for assessing the strengths and weaknesses of those participating in their programs while leaders themselves many find the instrument useful for self-diagnosis.

This study contributes to the development of school leadership measures by including Rasch modeling among the methods used for examining the instrument’s psychometric properties.