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A growing body of literature points to the importance of public service motivation (PSM) for the performance of public organizations. The purpose of this paper is to assess the method predominantly used for studying this linkage by comparing the findings it yields without and with a correction suggested by Brewer (2006), which removes the common-method bias arising from employee-specific response tendencies.

First, the authors conduct a systematic review of published empirical research on the effects of PSM on performance and show that all studies found have been conducted at the individual level. Performance indicators in all but three studies were obtained by surveying the same employees who were also asked about their PSM. Second, the authors conduct an empirical analysis. Using survey data from 240 organizational units within the Swiss federal government, the paper compares results from an individual-level analysis (comparable to existing research) to two analyses where the data are aggregated to the organizational level, one without and one with the correction for common-method bias suggested by Brewer (2006).

Looking at the Attraction to Policy-Making dimension of PSM, there is an interesting contrast: While this variable is positively correlated with performance in both the individual-level analysis and the aggregated data analysis without the correction for common-method bias, it is not statistically associated with performance in the aggregated data analysis with the correction.

The analysis is the first to assess the robustness of the performance-PSM linkage to a correction for common-method bias. The findings place the validity of at least one part of the individual-level linkage between PSM and performance into question.

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.

The research studies the role of contextual moderating variables on the relationship between person-oriented leadership behaviors (POLBs) and team performance. The authors claim that the varying effect sizes between POLBs and team performance are large because of the context the team is functioning in. Therefore, based on the framework of Johns (2006), this paper aims to investigate the moderating role of the relevant demographic (leader gender), social (in-group collectivism and team size), task (skill differentiation) and methodological (common method bias and the rater of the team performance) contextual variables in the study.

The authors accumulated evidence from 48 independent primary studies (N team = 4,276) to run the meta-analytic analyses. The authors followed the procedures described by Schmidt and Hunter (2015). For the categorical moderators, the analyzes were aided by the Hunter–Schmidt meta-analysis programs (2.0) (Schmidt and Le, 2014), which is an interactive software using a random-effects model. In the analyzes for the continuous moderators, the authors used Lipsey and Wilson’s (2001) statistical package for the social sciences macros and run meta-regressions using a random-effects model with unrestricted maximum likelihood.

The results indicate that the relationship weakens when female leaders exhibit these behaviors and when the team size increases. On the other hand, in-group collectivism strengthens the relationship. The study also found that the common method bias and the assessment method of the team performance are significant moderators altering the relationship.

The study highlights the perceptual differences and biases based on leader gender. Acknowledging these biases may help practitioners to appreciate the female qualities in leadership and decrease the undervaluation of female effectiveness. To create high-performing teams, leaders in high in-group collectivist countries are expected to develop a family feeling in the team by showing their concern for personal issues and build close interpersonal relationships. Researchers should use multiple sources to assess the predictor and criterion variables and also opt for more objective assessment methods for team performance.

With this study, the authors follow a substantively different perspective compared to the past meta-analytic reviews on this relationship. Rather than testing the inquiry whether there is a relationship between the two variables, the authors specifically focus on the role of contextual moderating variables. Several researchers have acknowledged that contextual considerations are critical in leadership-team performance research. Nevertheless, the body of research remains to be not cohesive. Thus, the study answers a call in the leadership area for a more context-based and cohesive understanding of the effects of leadership on team performance.

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.

Citizens are substantial stakeholders in every e-government system, thus their willingness to use and ability to access the system are critical. Unequal access and information and communication technology usage, which is known as digital divide, however has been identified as one of the major obstacles to the implementation of e-government system. As digital divide inhibits citizen’s acceptance to e-government, it should be overcome despite the lack of deep theoretical understanding on this issue. This research aimed to investigate the digital divide and its direct impact on e-government system success of local governments in Indonesia as well as indirect impact through the mediation role of trust. In order to get a comprehensive understanding of digital divide, this study introduced a new type of digital divide, the innovativeness divide.

The research problems were approached by applying two-stage sequential mixed method research approach comprising of both qualitative and quantitative studies. In the first phase, an initial research model was proposed based on a literature review. Semi-structured interview with 12 users of e-government systems was then conducted to explore and enhance this initial research model. Data collected in this phase were analyzed with a two-stage content analysis approach and the initial model was then amended based on the findings. As a result, a comprehensive research model with 16 hypotheses was proposed for examination in the second phase.

In the second phase, quantitative method was applied. A questionnaire was developed based on findings in the first phase. A pilot study was conducted to refine the questionnaire, which was then distributed in a national survey resulting in 237 useable responses. Data collected in this phase were analyzed using Partial Least Square based Structural Equation Modeling.

The results of quantitative analysis confirmed 13 hypotheses. All direct influences of the variables of digital divide on e-government system success were supported. The mediating effects of trust in e-government in the relationship between capability divide and e-government system success as well as in the relationship between innovativeness divide and e-government system success were supported, but was rejected in the relationship between access divide and e-government system success. Furthermore, the results supported the moderating effects of demographic variables of age, residential place, and education.

This research has both theoretical and practical contributions. The study contributes to the developments of literature on digital divide and e-government by providing a more comprehensive framework, and also to the implementation of e-government by local governments and the improvement of e-government Readiness Index of Indonesia.

Structural equation modeling (SEM) is a powerful multivariate statistical technique that requires careful application. The use of SEM in international business research has substantially increased recently, necessitating a critical evaluation of its use in the field. Through an analysis of 148 articles in the international business (IB) literature, we detail the state of current use of SEM in IB research and compare its use to the established best practices. In many instances, SEM's use in IB has been faulty, suggesting that authors may have drawn incorrect conclusions. To expand the IB field's knowledge base, methodological accuracy is essential. Based on our review of the technique's use in IB research coupled with the established practices in the social science literature, we provide practical suggestions for better applying SEM in the IB literature.

Self-report questionnaires are the predominant method used in human resource management (HRM) research to assess employees’ work-related psychological constructs (e.g., processes, states, and attributes). However, this method is associated with significant shortcomings, including the introduction of self-serving bias and common method variance when used exclusively. In this chapter, the authors challenge the assumption that individuals themselves are the only accurate source of the self-focused information collected in HRM research. Instead, the authors propose that other-ratings – ratings of a target individual that are provided by a workplace observer, such as a coworker, supervisor, or subordinate – can accurately assess commonly measured work-related psychological constructs. The authors begin by explaining the advantages of other-ratings for HRM research and practice, reviewing the history of other-ratings and how they emerged in the personality and person-perception literature, and outlining how they have been used in HRM research to date. Then, the authors build upon Funder’s (1995) realistic accuracy model to develop a theoretical argument detailing why workplace others should be able to accurately judge how another employee thinks and feels about work. Next, the authors highlight existing evidence in the literature on the accuracy of other-ratings and present the results of a preliminary meta-analysis on the ability of other-ratings to predict self-ratings of work-related psychological constructs. Finally, the authors discuss potential moderators of other-rating accuracy and reflect on a number of practical considerations for researchers looking to use other-ratings in their own work. The authors intend for this chapter to meaningfully contribute to the larger conversation on HRM research methods. Other-ratings are a simple, yet powerful, addition to the methodological toolkit of HRM researchers that can increase flexibility in research design and improve the overall quality of research.

This paper considers threats to the internal validity of field studies that utilize survey data. Compared to laboratory experiments and field experiments, field surveys should be strong in realism, practical significance, and normative quality. However, there are substantial threats to internal validity that fall into the general categories of sampling and measurement. We consider these issues and how to deal with them. We pay special attention to the existence and impact of common method variance including strategies for avoiding it, methods for assessing it, and approaches to correcting for it. Our objective is to provide a road map for better use of survey methods.

The concept and practice of e-services has become essential in business transactions. Yet there are still many organizations that have not developed e-services optimally. This is especially relevant in the context of Indonesian Airline companies. Therefore, many airline customers in Indonesia are still in doubt about it, or even do not use it. To fill this gap, this study attempts to develop a model for e-services adoption and empirically examines the factors influencing the airlines customers in Indonesia in using e-services offered by the Indonesian airline companies. Taking six Indonesian airline companies as a case example, the study investigated the antecedents of e-services usage of Indonesian airlines. This study further examined the impacts of motivation on customers in using e-services in the Indonesian context. Another important aim of this study was to investigate how ages, experiences and geographical areas moderate effects of e-services usage.

The study adopts a positivist research paradigm with a two-phase sequential mixed method design involving qualitative and quantitative approaches. An initial research model was first developed based on an extensive literature review, by combining acceptance and use of information technology theories, expectancy theory and the inter-organizational system motivation models. A qualitative field study via semi-structured interviews was then conducted to explore the present state among 15 respondents. The results of the interviews were analysed using content analysis yielding the final model of e-services usage. Eighteen antecedent factors hypotheses and three moderating factors hypotheses and 52-item questionnaire were developed. A focus group discussion of five respondents and a pilot study of 59 respondents resulted in final version of the questionnaire.

In the second phase, the main survey was conducted nationally to collect the research data among Indonesian airline customers who had already used Indonesian airline e-services. A total of 819 valid questionnaires were obtained. The data was then analysed using a partial least square (PLS) based structural equation modelling (SEM) technique to produce the contributions of links in the e-services model (22% of all the variances in e-services usage, 37.8% in intention to use, 46.6% in motivation, 39.2% in outcome expectancy, and 37.7% in effort expectancy). Meanwhile, path coefficients and t-values demonstrated various different influences of antecedent factors towards e-services usage. Additionally, a multi-group analysis based on PLS is employed with mixed results. In the final findings, 14 hypotheses were supported and 7 hypotheses were not supported.

The major findings of this study have confirmed that motivation has the strongest contribution in e-services usage. In addition, motivation affects e-services usage both directly and indirectly through intention-to-use. This study provides contributions to the existing knowledge of e-services models, and practical applications of IT usage. Most importantly, an understanding of antecedents of e-services adoption will provide guidelines for stakeholders in developing better e-services and strategies in order to promote and encourage more customers to use e-services. Finally, the accomplishment of this study can be expanded through possible adaptations in other industries and other geographical contexts.