Search results

The research practice in management research is dominantly based on structural equation modeling (SEM), but almost exclusively, and often misguidedly, on covariance-based SEM. The purpose of this paper is to question the current research myopia in management research, because the paper adumbrates theoretical foundations and guidance for the two SEM streams: covariance-based and variance-based SEM; and improves the conceptual knowledge by comparing the most important procedures and elements in the SEM study, using different theoretical criteria.

The study thoroughly analyzes, reviews and presents two streams using common methodological background. The conceptual framework discusses the two streams by analysis of theory, measurement model specification, sample and goodness-of-fit.

The paper identifies and discusses the use and misuse of covariance-based and variance-based SEM utilizing common topics such as: first, theory (theory background, relation to theory and research orientation); second, measurement model specification (type of latent construct, type of study, reliability measures, etc.); third, sample (sample size and data distribution assumption); and fourth, goodness-of-fit (measurement of the model fit and residual co/variance).

The paper questions the usefulness of Cronbach's α research paradigm and discusses alternatives that are well established in social science, but not well known in the management research community. The author presents short research illustration in which analyzes the four recently published papers using common methodological background. The paper concludes with discussion of some open questions in management research practice that remain under-investigated and unutilized.

The purpose of this paper is to demonstrate that common method variance, specifically single-source bias, threatens the validity of a university-created student assessment of instructor instrument, suggesting that decisions made from these assessments are inherently flawed or skewed. Single-source bias leads to generalizations about assessments that might influence the ability of raters to separate multiple behaviors of an instructor.

Exploratory factor analysis, nested confirmatory factor analysis and within-and-between analysis are used to assess a university-developed, proprietary student assessment of instructor instrument to determine whether a hypothesized factor structure is identifiable. The instrument was developed over a three-year period by a university-mandated committee.

Findings suggest that common method variance, specifically single-source bias, resulted in the inability to identify hypothesized constructs statistically. Additional information is needed to identify valid instruments and an effective collection method for assessment.

Institutions are not guaranteed valid or useful instruments even if they invest significant time and resources to produce one. Without accurate instrumentation, there is insufficient information to assess constructs for teaching excellence. More valid measurement criteria can result from using multiple methods, altering collection times and educating students to distinguish multiple traits and behaviors of individual instructors more accurately.

This paper documents the three-year development of a university-wide student assessment of instructor instrument and carries development through to examining the psychometric properties and appropriateness of using this instrument to evaluate instructors.

This study aims to construct a mental health service system for middle school students in the post-COVID-19 era with the framework of Six Sigma DMAIC (define, measure, analyze, improve and control) and analyze the influencing factors of the mental health service system to study the implementation strategies of quality-oriented mental health services in middle schools.

This study was conducted in Tianjin, China, from September to November 2022, and 350 middle school students from Tianjin Public Middle School were selected as subjects. A questionnaire survey was used to collect data. In this study, the Six Sigma DMAIC method, sensitivity analysis method, exploratory factor analysis and principal component analysis were used to analyze the mental health services provided to middle school students.

Based on the Six Sigma DMAIC framework, this study indicates that the contribution rate of the mental health service process factor is the largest in the post-COVID-19 era. The mental health cultivation factor ranks second in terms of its contribution. Mental health quality and policy factors are also important in the construction of middle school students’ mental health service system. In addition, the study highlights the importance of parental involvement and social support in student mental health services during the post-COVID-19 era.

To the best of the authors’ knowledge, a study on middle school students’ mental health in the post-Covid-19 era has not yet been conducted. This study developed a quality-oriented mental health system and analyzed the influencing factors of mental health for middle school students based on data analysis and the Six Sigma DMAIC method.

The purpose of this paper is to examine empirically the effect of cultural and social acceptance on CEO leadership.

Several instruments were used to capture key concepts (i.e. Organisational Culture Profile, Marlowe‐Crowne Social Desirability Scale, Transformational Leadership Inventory, and Leader Reward and Punishment Questionnaire), which were examined using confirmatory factor analysis. Data were collected from 635 Australian CEOs.

The results of hierarchical multi‐regression analysis clarified the importance of self‐deception and impression management as influential context factors, and how both operate at the pinnacle of organisations. The study also identifies that transformational and transactional leadership behaviours were uniquely influenced by specific cultural dimensions, and suggests that CEOs use combinations of these behaviours to respond to four cultural dimensions (i.e. emphasis on rewards, performance orientation, innovation, and stability) in order to produce competitive advantages.

The study highlights how CEOs are still vulnerable to conforming to the social norms of their organisation and also how CEOs use a repertoire of leadership behaviours, in response to the importance of different cultural dimensions.

The paper contributes to the leadership literature by directly addressing how context impacts on CEO leadership in three specific areas: social acceptance needs, demographics and culture. Further, the study investigates CEO transformational and transactional leadership behaviours rather than global constructs, and directly addresses the common method variance issue.

Several research studies on Lean Six Sigma (LSS) have been done using the survey methodology. However, the use of surveys often relies on the measurement of variables, which cannot be directly observed, with attendant measurement errors. The purpose of this study is to develop a methodological framework consisting of a combination of four tools for identifying and assessing measurement error during survey research.

This paper evaluated the viability of the framework through an experimental study on the assessment of project management success in a developing country environment. The research design combined a control group, pretest and post-test measurements with structural equation modeling that enabled the assessment of differences between honest and fake survey responses. This paper tested for common method variance (CMV) using the chi-square test for the difference between unconstrained and fully constrained models.

The CMV results confirmed that there was significant shared variance among the different measures allowing us to distinguish between trait and faking responses and ascertain how much of the observed process measurement is because of measurement system variation as opposed to variation arising from the study’s constructs.

The study was conducted in one country, and hence, the results may not be generalizable.

Measurement error during survey research, if not properly addressed, can lead to incorrect conclusions that can harm theory development. It can also lead to inappropriate recommendations for practicing managers. This study provides findings from a framework developed and assessed in a LSS project environment for identifying faking responses. This paper provides a robust framework consisting of four tools that provide guidelines on distinguishing between fake and trait responses. This tool should be of great value to researchers.

Coopetition, namely, the interplay between cooperation and competition, has received a good deal of interest in the business-to-business marketing literature. Academics have operationalised the coopetition construct and have used these measures to test the antecedents and consequences of firms collaborating with their competitors. However, business-to-business marketing scholars have not developed and validated an agreed operationalisation that reflects the dimensionality of the coopetition construct. Thus, the purpose of this study is to develop and validate a multi-dimensional measure of coopetition for marketing scholars to use in future research.

To use a highly cooperative and highly competitive empirical context, sporting organisations in New Zealand were sampled, as the key informants within these entities engaged in different forms of coopetition. Checks were made to ensure that the sampled entities produced generalisable results. That is, it is anticipated that the results apply to other industries with firms engaging in similar business-to-business behaviours. Various sources of qualitative and quantitative data were acquired to develop and validate a multi-dimensional measure of coopetition (the COOP scale), which passed all major assessments of reliability and validity (including common method variance).

The results indicated that coopetition is a multi-dimensional construct, comprising three distinct dimensions. First, local-level coopetition is collaboration among competing entities within a close geographic proximity. Second, national-level coopetition is cooperation with rivals within the same country but across different geographic regions. Third, organisation-level coopetition is cooperation with competitors across different firms (including with indirect rivals), regardless of their geographic location and product markets served. Indeed, organisation-level coopetition extends to how companies engage in coopetition in domestic and international capacities, depending on the extent to which they compete in similar product markets in comparison to industry rivals. Also, multiple indicators were used to measure each facet of the coopetition construct after the scale purification stage.

Prior coopetition-based investigations have predominately been conceptual or qualitative in nature. The scarce number of existing scales have significant problems, such as not appreciating that coopetition is a multi-dimensional variable, as well as using single indicators. In spite of a recent call for research on the multiple levels of coopetition, there has not been an agreed measure of the construct that accounts for its multi-dimensionality. Hence, this investigation responds to such a call for research by developing and validating the COOP scale. Local-, national- and organisation-level coopetition are anticipated to be the main facets of the coopetition construct, which offer several avenues for future research.

Based on the interpersonal interaction perspective of team cohesion, this study aims to examine the effects of team boundedness, formal coordination and organization tenure diversity on both task and social cohesion. The authors test for the interaction effect of organization tenure diversity on the relationships between the independent variables and the dimensions of team cohesion.

Data was collected from 111 software development teams and aggregated to the team level. Common latent factor test for common method bias showed no significant bias. Structural equation modelling (SEM) was used to test all the hypotheses.

SEM results show that team boundedness and formal coordination have positive and significant association with both dimensions of team cohesion. Formal coordination was found to be a stronger positive predictor for task cohesion than for social cohesion. Organization tenure diversity was found to be a stronger negative predictor for social cohesion than for task cohesion. Organization tenure diversity in the team moderates the relationship between formal coordination and task cohesion.

The data was collected using a cross-sectional design. However, the authors have mitigated the effect of common method variance by adopting both procedural and statistical methods.

This paper expands extant literature by examining the antecedents of two important components of team cohesion, task and social cohesion. The authors proposed and found that the independent variables have different impacts on task and social cohesion. This study furthers both theory and practice by considering team boundedness as a variable of interest and its impact on internal team dynamics.

In management accounting research, the capabilities of Partial Least Squares Structural Equation Modelling (PLS-SEM) have only partially been utilized. These yet unexploited capabilities of PLS-SEM are a useful tool in the often explorative state of research in management accounting. After reviewing eleven top-ranked management accounting journals through the end of 2013, 37 articles in which PLS-SEM is used are identified. These articles are analysed based on multiple relevant criteria to determine the progress in this research area, including the reasons for using PLS-SEM, the characteristics of the data and the models, and model evaluation and reporting. A special focus is placed on the degree of importance of these analysed criteria for the future development of management accounting research. To ensure continued theoretical development in management accounting, this article also offers recommendations to avoid common pitfalls and provides guidance for the advanced use of PLS-SEM in management accounting research.

This paper seeks to discuss reliability problems associated with questionnaires, commonly employed in library and information science. It aims to focus on the effects of “common method variance” (CMV), which is a form of bias, and ways of countering these effects.

The paper critically reviews the use of existing tools for demonstrating reliability in questionnaire‐based studies. In particular, it focuses on Cronbach's alpha, “Harman's single factor test” and Lindell and Whitney's “marker variable” approach. The paper introduces an illustrative case study based on the work on metacognition and web searching. It goes on to make recommendations for researchers considering using a questionnaire‐based approach.

CMV is a problem affecting questionnaire‐based studies in different disciplines across social and information science. Where questionnaire items are more abstract, CMV has been found to be more of a problem. The widely used Cronbach alpha measure, of the reliability of a questionnaire, may often be affected by CMV. Where method bias dominates the results, a high alpha score may do no more than indicate that the questionnaire consistently allows participants to accede to their biases. “Harman's single factor test” is criticised as lacking sufficient foundation, and it is concluded that it should not be used. The marker variable approach is a useful option but must be applied with caution.

A number of practical implications for researchers are drawn. Questionnaire‐based work investigating abstract constructs should be assumed to carry a high likelihood of CMV, and therefore should attempt to avoid it and demonstrate the degree of success in this regard. Otherwise, interpretation of the results should assume CMV. A number of approaches to assessing and isolating CMV are discussed.

The paper draws attention to a problem that is arguably often overlooked in questionnaire‐based studies, namely method bias. It discusses a number of approaches whereby it may be identified and controlled.

Following the call for awareness of accepted reporting practices by Ringle, Sarstedt, and Straub in 2012, the purpose of this paper is to review and analyze the use of partial least squares structural equation modeling (PLS-SEM) in Industrial Management & Data Systems (IMDS) and extend MIS Quarterly (MISQ) applications to include the period 2012-2014.

Review of PLS-SEM applications in information systems (IS) studies published in IMDS and MISQ for the period 2010-2014 identifying a total of 57 articles reporting the use of or commenting on PLS-SEM.

The results indicate an increased maturity of the IS field in using PLS-SEM for model complexity and formative measures and not just small sample sizes and non-normal data.

Findings demonstrate the continued use and acceptance of PLS-SEM as an accepted research method within IS. PLS-SEM is discussed as the preferred SEM method when the research objective is prediction.

This update on PLS-SEM use and recent developments will help authors to better understand and apply the method. Researchers are encouraged to engage in complete reporting procedures.

Applications of PLS-SEM for exploratory research and theory development are increasing. IS scholars should continue to exercise sound practice by reporting reasons for using PLS-SEM and recognizing its wider applicability for research. Recommended reporting guidelines following Ringle et al. (2012) and Gefen et al. (2011) are included. Several important methodological updates are included as well.