Search results
1 – 10 of over 12000Christopher F. Parmeter, Zhiyuan Zheng and Patrick McCann
The link between the magnitude of a bandwidth and the relevance of the corresponding covariate in a regression has recently garnered theoretical attention. Theory suggests that…
Abstract
The link between the magnitude of a bandwidth and the relevance of the corresponding covariate in a regression has recently garnered theoretical attention. Theory suggests that variables included erroneously in a regression will be automatically removed when bandwidths are selected via cross-validation procedure. However, the connections between the bandwidths of the variables that are smoothed away and the insights from these same variables when properly tested for statistical significance have not been previously studied. This paper proposes a variety of simulation exercises to examine the relative performance of both cross-validated bandwidths and individual and joint tests of significance. We focus on settings where the hypothesis of interest may focus on a single data type (e.g., continuous only) or a mix of discrete and continuous variables. Moreover, we propose an extension of a well-known kernel smoothing significance test to handle mixed data types. Our results suggest that individual tests of significance and variable-specific bandwidths are very close in performance, but joint tests and joint bandwidth recognition produce substantially different results. This underscores the importance of testing for joint significance when one is trying to arrive at the final nonparametric model of interest.
Leopold Bayerlein and Omar Al Farooque
The purpose of this paper is to evaluate the changes of accounting policy choices and the harmonisation of accounting practices for two important financial reporting items within…
Abstract
Purpose
The purpose of this paper is to evaluate the changes of accounting policy choices and the harmonisation of accounting practices for two important financial reporting items within and between three IFRS adopting countries. Furthermore, it aims to address methodological shortcomings in the prior harmonisation literature through the introduction of two newly developed significance assessment methodologies.
Design/methodology/approach
The influence of the mandatory IFRS adoption in Australia (AUS), Hong Kong (HK) and the UK on deferred taxation (DT) and goodwill (GW) accounting practices as well as the within and between country harmonisation of accounting practices is investigated through an event type study. These investigations are conducted using a McNemar test with Bowker extension as well as the Split C‐Index with a newly developed bootstrapping significance testing methodology.
Findings
This study demonstrates that the mandatory IFRS adoption in the analysed countries is linked to a significant harmonisation of DT and GW accounting practices between AUS, HK and the UK. Furthermore, the increase of adequate accounting policy information in the financial reporting documents of UK firms over the period of this study is identified as an important harmonisation accelerator.
Originality/value
This study adds to the prior literature due to its focus on the mandatory IFRS adoption within the analysed countries. Furthermore, the introduction of two newly developed methodologies to evaluate the significance of accounting policy choice changes and harmonisation over time addresses an important methodological shortcoming in the prior literature.
Details
Keywords
Marko Sarstedt, Jörg Henseler and Christian M. Ringle
Purpose – Partial least squares (PLS) path modeling has become a pivotal empirical research method in international marketing. Owing to group comparisons' important role in…
Abstract
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.
Jan-Michael Becker, Jun-Hwa Cheah, Rasoul Gholamzade, Christian M. Ringle and Marko Sarstedt
Partial least squares structural equation modeling (PLS-SEM) has attracted much attention from both methodological and applied researchers in various disciplines – also in…
Abstract
Purpose
Partial least squares structural equation modeling (PLS-SEM) has attracted much attention from both methodological and applied researchers in various disciplines – also in hospitality management research. As PLS-SEM is relatively new compared to other multivariate analysis techniques, there are still numerous open questions and uncertainties in its application. This study aims to address this important issue by offering guidance regarding its use in contexts with which researchers struggle.
Design/methodology/approach
The authors examine the most prominent questions and answers posed in a well-known PLS-SEM discussion forum. The authors do so by using a text analysis technique to identify the most salient topics.
Findings
The data analysis identifies three salient PLS-SEM topics (i.e. bootstrapping and significance testing, higher-order constructs and moderation).
Research limitations/implications
The results allow us to address the PLS-SEM community’s main methodological issues. The authors discuss each area separately and provide explanations and guidelines.
Practical implications
The guidelines on the most important PLS-SEM topics provide decision-making and application aids. In this way, the authors make a decisive contribution to clarifying ambiguities when applying the PLS-SEM method in hospitality management research and other disciplines.
Originality/value
There has as yet been no systematic analysis of this kind in the field of PLS-SEM; the authors, therefore, present the first research results. The findings and recommendations provide guidance for PLS-SEM applications in hospitality research and practice.
Details
Keywords
Swapnil Undale, Ashish Kulkarni and Harshali Patil
Coronavirus (COVID-19) pandemic forced nationwide lockdown in India. During the period of lockdown usage of eWallet increased by 44%. With the increased usage of digital…
Abstract
Purpose
Coronavirus (COVID-19) pandemic forced nationwide lockdown in India. During the period of lockdown usage of eWallet increased by 44%. With the increased usage of digital transactions, cyber-crime attacks also increased as much as by 86%. The socio-economic environment and the peoples’ mindset in the country yet not ready for this kind of rise in digital transactions. The purpose of this study is to capture “security concern” and “comfortability” in regard to using eWallet during the COVID-19 pandemic situation. The study further investigated the influence of demographics such as gender and income on “security concern” and “comfortability” in using eWallet.
Design/methodology/approach
This was an empirical study. The respondents were selected using a purposive sampling method. Only those people who had been using eWallet were included in the survey. The questionnaire was circulated to 100 respondents who agreed to participate in the survey. After scrutiny total of 43 questionnaires were found to be completely filled in all aspects, and thus used for analysis. This study used an innovative multi-method approach for analysis. The hypotheses were tested using two methods: the conventional p-value method and the robust BCa bootstrap method. The effect size was also reported.
Findings
The findings suggest that female users are more concerned about eWallet security than male users. This study showed that people from the middle-income group are more concerned about the security of digital payments than the people from the lower-income group.
Research limitations/implications
This study covered the influence of two demographic variables “gender” and “income” on security and comfort in using eWallets. Other demographic variables such as age, education, occupation and area of residence (rural or urban) need to be investigated with the inclusion of rural populations. From the findings of this study, this paper argues that the middle-income group in India is more risk intolerant than the lower-income group while higher and lower-income groups are indifferent. A separate detailed study is recommended for additional support. This study used an innovative multi-method approach of analysis and use of bootstrapping. This may encourage other researchers to adopt such approaches.
Practical implications
This study showed that irrespective of the forceful adoption; security concerns are prevailing and on the rise. This is an alarm to developers and service providers that, although the use of eWallets increased exponentially during this COVID-19 pandemic, it is a forceful adoption and not willful. They should not get deceived by rise in eWallet users and must endeavor to improve the security of eWallets otherwise, there may be a sharp decline in eWallet users once the COVID-19 pandemic is over.
Originality/value
This study attempted to capture the comfortability and security concerns of eWallet users during the COVID-19 pandemic. This study used an innovative multi-method approach of analysis and used bootstrapping in addition to the conventional p-value method to test the significance. This study showed that irrespective of the forceful adoption of eWallets owing to the COVID-19 pandemic, security concerns are prevailing and on the rise. The study confirms that gender has an influence on eWallet security. The findings of this study are in partial conformity with the findings of previous researchers.
Details
Keywords
Zongwu Cai, Jingping Gu and Qi Li
There is a growing literature in nonparametric econometrics in the recent two decades. Given the space limitation, it is impossible to survey all the important recent developments…
Abstract
There is a growing literature in nonparametric econometrics in the recent two decades. Given the space limitation, it is impossible to survey all the important recent developments in nonparametric econometrics. Therefore, we choose to limit our focus on the following areas. In Section 2, we review the recent developments of nonparametric estimation and testing of regression functions with mixed discrete and continuous covariates. We discuss nonparametric estimation and testing of econometric models for nonstationary data in Section 3. Section 4 is devoted to surveying the literature of nonparametric instrumental variable (IV) models. We review nonparametric estimation of quantile regression models in Section 5. In Sections 2–5, we also point out some open research problems, which might be useful for graduate students to review the important research papers in this field and to search for their own research interests, particularly dissertation topics for doctoral students. Finally, in Section 6 we highlight some important research areas that are not covered in this paper due to space limitation. We plan to write a separate survey paper to discuss some of the omitted topics.
Siqi Wang, Jun-Hwa Cheah, Chee Yew Wong and T. Ramayah
This study aims to evaluate the usage of partial least squares structural equation modeling (PLS-SEM) in journals related to logistics and supply chain management (LSCM).
Abstract
Purpose
This study aims to evaluate the usage of partial least squares structural equation modeling (PLS-SEM) in journals related to logistics and supply chain management (LSCM).
Design/methodology/approach
Based on a structured literature review approach, the authors reviewed 401 articles in the field of LSCM applying PLS-SEM published in 15 major journals between 2014 and 2022. The analysis focused on reasons for using PLS-SEM, measurement model and structural model evaluation criteria, advanced analysis techniques and reporting practices.
Findings
LSCM researchers sometimes did not clarify the reasons for using PLS-SEM, such as sample size, complex models and non-normal distributions. Additionally, most articles exhibit limited use of measurement models and structural model evaluation techniques, leading to inappropriate use of assessment criteria. Furthermore, progress in the practical implementation of advanced analysis techniques is slow, and there is a need for improved transparency in reporting analysis algorithms.
Originality/value
This study contributes to the field of LSCM by providing clear criteria and steps for using PLS-SEM, enriching the understanding and advancement of research methodologies in this field.
Details
Keywords
Boon L. Lee, Andrew Worthington and Clevo Wilson
Existing studies of school efficiency primarily specify teacher inputs as the number of teachers and perhaps the student-teacher ratio. As a result, there is no direct qualitative…
Abstract
Purpose
Existing studies of school efficiency primarily specify teacher inputs as the number of teachers and perhaps the student-teacher ratio. As a result, there is no direct qualitative recognition of the learning environment. The purpose of this paper is to incorporate the learning environment directly into the assessment of school efficiency.
Design/methodology/approach
The authors employ data envelopment analysis to derive efficiency scores and the double-bootstrap truncated regression approach in Simar and Wilson’s (2007) Journal of Econometrics to quantify the sources of efficiency in 430 Queensland state primary schools. In the first stage, the outputs of student National Assessment Program-Literacy and Numeracy scores and the inputs of full-time equivalent teaching staff and cumulative capital expenditure per student are used to measure efficiency. In the second stage, the authors specify an index of community socio-educational advantage, class size, the share of teachers with postgraduate qualifications, funds spent on professional development, and surveyed opinions from parents/caregivers, students, staff and principals on the learning environment to explain these measures of efficiency.
Findings
Socio-economic background and the teaching environment affect school efficiency. Although not all variables related to teacher contribution are significant, there is evidence to suggest that teachers have a positive influence on student performance hence school efficiency. Teachers ability to clearly explain the requirements of schoolwork tasks and listening to student opinions sets an ideal student engagement environment which can have a profound impact on student learning.
Practical implications
From a policy perspective, policy makers should target resources at inefficient schools aimed at enhancing student learning through teacher development and, at the same time, providing financial and non-financial educational assistance to students and their families from a low socio-educational background.
Originality/value
This is the first large-scale primary school efficiency analysis to incorporate the Simar and Wilson (2007) approach to explaining the determinants of efficiency, including teaching environment from the perspective of students, teachers and other stakeholders.
Details
Keywords
Shrikant Mulik, Manjari Srivastava, Nilay Yajnik and Vas Taras
This paper aims to develop and empirically test a model of relationships between antecedents and outcomes of flow experience of users of massive open online courses (MOOC).
Abstract
Purpose
This paper aims to develop and empirically test a model of relationships between antecedents and outcomes of flow experience of users of massive open online courses (MOOC).
Design/methodology/approach
The researchers surveyed individuals primarily from India, who had enrolled in at least one MOOC offered by MOOC providers such as Coursera, edX and FutureLearn. The data were collected from 310 individuals using an online questionnaire. The partial least squares technique of structural equation modeling (PLS-SEM) was used to test the reliability and validity of the data, and the study’s hypothesized relationships.
Findings
The study found support for identification of telepresence, challenge and skill as antecedents of flow experience. MOOC satisfaction and MOOC usage intention were found to be the outcomes of flow experience, as hypnotized. The study also found the mediating role of MOOC satisfaction in the relationship of flow experience and MOOC usage intention.
Practical implications
The findings indicate that if the MOOC providers can orchestrate flow experience for MOOC users then that will increase the satisfaction of MOOC users, which will lead to increase in MOOC adoption.
Originality/value
The study makes the contribution towards better understanding of flow experience in the context of MOOC usage by identifying both antecedents and outcomes of flow experience. Further, it highlights the influencing role of flow experience on MOOC adoption.
Details
Keywords
Cristiano A.B. Castro, Felipe Zambaldi and Mateus Canniatti Ponchio
This paper aims to conceptualize two dimensions of active innovation resistance (AIR): cognitive active resistance and emotional active resistance. A scale to measure this…
Abstract
Purpose
This paper aims to conceptualize two dimensions of active innovation resistance (AIR): cognitive active resistance and emotional active resistance. A scale to measure this construct is proposed and tested.
Design/methodology/approach
Three studies were conducted, with sample sizes of 195, 190 and 186, to test the discriminant, convergent, nomological and criterion validity of the proposed AIRc+e scale and to analyze its explanatory and predictive power. Data were gathered using the online platform of a US-based research company.
Findings
The authors provide evidence that AIR is a two-dimension construct comprising a cognitive and an emotional dimension. AIR was modeled as a third-order construct, comprising two second-order constructs, cognitive active resistance and emotional active resistance. The impact of adding an emotion dimension to active resistance was therefore assessed, and the results indicated that the explanatory and predictive power of the AIR measure improved as expected.
Practical implications
Consumers are most likely to resist innovations launched onto the marketplace, either prior to or after evaluating them. A better understanding of the reasons behind their resistance to innovation, as well as of its mechanisms, is of great importance in decreasing an innovation’s chances of failure.
Originality/value
This study proposes that incorporating emotion into the assessment of AIR will result in a deeper understanding of adoption and rejection behavior, expanding the current knowledge of consumer behavior in innovation-related, new product adoption and decisions.
Details