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1 – 10 of over 95000Jörg Henseler, Christian M. Ringle and Rudolf R. Sinkovics
In order to determine the status quo of PLS path modeling in international marketing research, we conducted an exhaustive literature review. An evaluation of double-blind reviewed…
Abstract
In order to determine the status quo of PLS path modeling in international marketing research, we conducted an exhaustive literature review. An evaluation of double-blind reviewed journals through important academic publishing databases (e.g., ABI/Inform, Elsevier ScienceDirect, Emerald Insight, Google Scholar, PsycINFO, Swetswise) revealed that more than 30 academic articles in the domain of international marketing (in a broad sense) used PLS path modeling as means of statistical analysis. We assessed what the main motivation for the use of PLS was in respect of each article. Moreover, we checked for applications of PLS in combination with one or more additional methods, and whether the main reason for conducting any additional method(s) was mentioned.
This paper attempts to demystify the technique of causal path modeling for the non‐specialists by presenting aspects of its value for social science and management research and by…
Abstract
This paper attempts to demystify the technique of causal path modeling for the non‐specialists by presenting aspects of its value for social science and management research and by illustrating common misunderstandings about its attributes. Special emphasis is placed on the real world validity of causal relationships depicted in causal path models and on the information that the data‐fitting properties of causal path models provide regarding this issue. Causal path models that are based on research in antecedents of career success are used to illustrate the points that are made. It is stressed that the validity of causal relationships depicted in causal path models is subject to exactly the same methodological restrictions as the validity of causality claims that are made without the use of causal path modeling; and that the purpose of using quantitative techniques in causal path modeling is not to improve certainty on causality direction.
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This article deals with how to test for and evaluate interdependence among control practices in a management control system using structural equation modeling. Empirical research…
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This article deals with how to test for and evaluate interdependence among control practices in a management control system using structural equation modeling. Empirical research on the levers of control (LOC) framework is used as an example. In LOC research, a path model approach to interdependence has been developed. The appropriateness of this approach is evaluated, developed, and compared with the correlation of residuals approach (seemingly unrelated regression) implemented in the wider complementarity literature. Empirical examples of the different models are shown and compared by using a data set on LOC of 120 SBUs in Sweden. The empirical results show that modeling interdependence among control practices in a management control system as non-recursive (bi-directional) paths or as residual correlations evidently affects the conclusions drawn about interdependence in terms of both presence and magnitude. The two models imply different views on how to conceptualize interdependence and are not statistically and empirically comparable. If using non-recursive path models, several model specification issues appear. To be able to identify such models, this needs to be carefully considered in the theory and research design prior to data collection.
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Jörg Henseler, Geoffrey Hubona and Pauline Ash Ray
Partial least squares (PLS) path modeling is a variance-based structural equation modeling (SEM) technique that is widely applied in business and social sciences. Its ability to…
Abstract
Purpose
Partial least squares (PLS) path modeling is a variance-based structural equation modeling (SEM) technique that is widely applied in business and social sciences. Its ability to model composites and factors makes it a formidable statistical tool for new technology research. Recent reviews, discussions, and developments have led to substantial changes in the understanding and use of PLS. The paper aims to discuss these issues.
Design/methodology/approach
This paper aggregates new insights and offers a fresh look at PLS path modeling. It presents new developments, such as consistent PLS, confirmatory composite analysis, and the heterotrait-monotrait ratio of correlations.
Findings
PLS path modeling is the method of choice if a SEM contains both factors and composites. Novel tests of exact fit make a confirmatory use of PLS path modeling possible.
Originality/value
This paper provides updated guidelines of how to use PLS and how to report and interpret its results.
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Shifa Sulaiman and A.P. Sudheer
Most of the conventional humanoid modeling approaches are not successful in coupling different branches of the tree-type humanoid robot. In this paper, a tree-type upper body…
Abstract
Purpose
Most of the conventional humanoid modeling approaches are not successful in coupling different branches of the tree-type humanoid robot. In this paper, a tree-type upper body humanoid robot with mobile base is modeled. The main purpose of this work is to model a non holonomic mobile platform and to develop a hybrid algorithm for avoiding dynamic obstacles. Decoupled Natural Orthogonal Complement methodology effectively combines different branches of the humanoid body during dynamic analysis. Collision avoidance also plays an important role along with modeling methods for successful operation of the upper body wheeled humanoid robot during real-time operations. The majority of path planning algorithms is facing problems in avoiding dynamic obstacles during real-time operations. Hence, a multi-fusion approach using a hybrid algorithm for avoiding dynamic obstacles in real time is introduced.
Design/methodology/approach
The kinematic and dynamic modeling of a humanoid robot with mobile platform is done using screw theory approach and Newton–Euler formulations, respectively. Dynamic obstacle avoidance using a novel hybrid algorithm is carried out and implemented in real time. D star lite and a geometric-based hybrid algorithms are combined to generate the optimized path for avoiding the dynamic obstacles. A weighting factor is added to the D star lite variant to optimize the basic version of D star lite algorithm. Lazy probabilistic road map (PRM) technique is used for creating nodes in configuration space. The dynamic obstacle avoidance is experimentally validated to achieve the optimum path.
Findings
The path obtained using the hybrid algorithm for avoiding dynamic obstacles is optimum. Path length, computational time, number of expanded nodes are analysed for determining the optimality of the path. The weighting function introduced along with the D star lite algorithm decreases computational time by decreasing the number of expanding nodes during path generation. Lazy evaluation technique followed in Lazy PRM algorithm reduces computational time for generating nodes and local paths.
Originality/value
Modeling of a tree-type humanoid robot along with the mobile platform is combinedly developed for the determination of the kinematic and dynamic equations. This paper also aims to develop a novel hybrid algorithm for avoiding collision with dynamic obstacles with minimal computational effort in real-time operations.
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Georg Fassott, Jörg Henseler and Pedro S. Coelho
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…
Abstract
Purpose
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.
Design/methodology/approach
The paper discusses the use of standardized vs unstandardized construct scores and introduces spotlight analysis as a useful way to report findings.
Findings
Researchers should rely on unstandardized estimates when analyzing moderating effects. Centering or orthogonalization can help improve the interpretability of path coefficients.
Practical implications
PLS software implementations should facilitate unstandardized estimates.
Originality/value
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.
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The purpose of this paper is to provide a systematic overview with guidelines how to use partial least squares (PLS) path modeling in longitudinal studies. Practical examples from…
Abstract
Purpose
The purpose of this paper is to provide a systematic overview with guidelines how to use partial least squares (PLS) path modeling in longitudinal studies. Practical examples from a study of the acceptance of battery electric vehicles (BEVs) in corporate fleets are used for demonstration purposes.
Design/methodology/approach
In this study, data at three points in time were collected: before the initial use of a BEV, after three and after six months of extensive usage of BEVs.
Findings
Three different models are identified depending on the research objective and on the data basis. Multigroup analyses are suggested to test the difference between the path coefficients of latent variables at different points in time. Limitations for the use of repeated cross-sectional data have to be observed.
Originality/value
Academics and practitioners will benefit from this paper by receiving an overview of the different PLS path models in longitudinal studies. A decision-tree enables them to make a choice regarding the most appropriate model and suggests a sequence of complementary analyses. So far, there is a lack of a tutorial type paper delivering such guidance.
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Anas Abdelsatar Mohammad Salameh, Hartini Ahmad, Faisal Zulhumadi and Faruq Muhammad Abubakar
This study aims to explore the impact of system quality dimensions, namely, ease of use, accessibility, interactivity and website innovativeness on service quality (SQ) and…
Abstract
Purpose
This study aims to explore the impact of system quality dimensions, namely, ease of use, accessibility, interactivity and website innovativeness on service quality (SQ) and customer satisfaction.
Design/methodology/approach
The study used a quantitative approach, by using a survey method. The unit of analysis was the individual. A total of 618 questionnaires were randomly distributed to university students and staff in Jordan. The partial least square path-modeling method was used in the estimation of causal relationships of the constructs examined in the study.
Findings
The outcomes of this study showed that ease of use, interactivity and website innovativeness have significant positive relationships with the SQ. Consequently, SQ significantly influences customer satisfaction.
Research limitations/implications
Limitations of this research were related to the unit of analysis, as it was conducted within the geographical region of Jordan and the university context, where the culture and level of the technological advancement may be different than other countries.
Practical implications
This research can assist mobile commerce (m-commerce) service policymakers to formulate significant policies that could enhance the nature of services being rendered and thus bring greater benefits to the customers.
Originality/value
This research has extended the body of knowledge on emerging trends in m-commerce innovation adoption, more specifically in the university context. Furthermore, it offers insight on the importance of m-commerce in the minds of customers, in such a way that it will bring about the intention to repeat patronage in the future.
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Edward E. Rigdon, Christian M. Ringle, Marko Sarstedt and Siegfried P. Gudergan
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…
Abstract
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.
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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…
Abstract
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.
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