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The purpose of this study is to explore customer engagement (CE) in Facebook brand communities. It clusters Facebook brand fans to establish whether an existing typology holds in a diverse sample, and examines the differences in CE between the clusters. The predictive capabilities of CE on an important brand outcome, electronic word-of-mouth (eWOM), are determined.

In total, 493 respondents participated in an online survey. A two-step cluster analysis was conducted to determine the fan types. ANOVA was used to assess the differences in CE between the clusters. Multiple regression determined the predictive capabilities of CE on eWOM.

This research confirms the Facebook fan typology on a more diverse sample. Significant differences exist between the fan types on CE (captivation and gratification) and CE significantly predicts eWOM.

Future research could include motivations behind brand fan behavior. Using other CE measures may bring a different view. Theoretical perspectives other than social identity theory (SIT) may elicit other insights.

Insights into brand fan segments’ behavior and engagement allow brand managers to develop targeted marketing interactions. Gratification engagement is a stronger driver of eWOM, suggesting that brands should focus on marketing actions that will encourage gratification.

This research expands on Facebook brand fan typologies and explores CE as a multi-dimensional construct, rather than as a mere “like” action. Additionally, it determines the predictive capabilities of CE dimensions on eWOM. The findings suggest that SIT could be useful when examining CE in brand communities.

The purpose of this paper is to introduce the global text project (GTP) case. The unique developments of the case provide insight of the many challenges and opportunities created within the open source movement.

A case study was used to illustrate some of the most pertinent and interesting developments in the field of marketing, alluding to the open source environment. A Wikibook was created in collaboration with all the participants of a graduate course and the development of this offering initiated a project called the GTP.

The open source movement has created new ways of thinking and acting. The contributions, modifications and improvements by all users to the original product provide a platform of continuous improvement and development.

The value of the paper lies in the lessons and challenges learnt from the case especially by those managing the GTP.

The publication of papers in scholarly journals is an important channel for the dissemination of academic knowledge. Analyzing academic content provides useful insights into how services marketing evolves over a selected time frame. The purpose of this paper is to determine key trends published in the Journal of Services Marketing during the recent 11‐year period from 1998 to 2008.

This paper presents a content analysis of the papers published in the Journal of Services Marketing during the period 1998‐2008. A total of 417 papers, excluding book reviews, were analyzed. Descriptive statistics provide an overview of the research contributions.

The main finding is that most of the papers published in the Journal of Services Marketing during the recent 11‐year period are research‐based papers. Other findings include a trend towards co‐authorship, the use of surveys and empirical data, adults as research subjects, factor analysis, structural equation modeling, and analysis of variance as the most popular statistical techniques. Based on a keyword analysis most papers are related to service quality and customer service.

Researchers who wish to publish in this journal can use the findings as a guideline in preparing for their submission. The study gives an overview of the types of papers published in this journal. The analysis also shows that there is no preference for a particular topic for publication which stimulates new and varied contribution from researchers.

This is the first content analysis conducted of the scholarly contribution to this journal that shows the trends in services research topics.

In this unashamedly polemical piece it is argued that we should not jump into bed with virtue too quickly. It is suggested that the concept of virtue is dangerously ill defined, so it becomes what those in power hegemonically define it to be; that virtue’s rise may serve factional political purposes within social science; that system implications are frequently missed, side-lined or minimised so that virtue niavely becomes a purely individual construct; that aspirational codes, which expect a-contextual demonstration of ‘virtue’ from practitioners, need to be tempered with a dose of reality; and that the achievable ‘good enough’ is better than the unrealisable and idealised virtuously ‘perfect’. It is suggested that the implied centrality of ‘virtue’ in research is problematic, that being ‘critically virtuous’ has limits, and that better education will not necessarily lead to morality and integrity in research – any more than it does in the general population. Finally it is argued that ethics committees should focus on (probable) behaviours, rather than rather than imagined motives or vague character traits. Locating virtue in an individual is dangerous because it allows the system to blame and punish an individual, rather than acknowledge the collective responsibility of the whole system. It is suggested that we need to move from a purist pursuit of virtue to a more realistic and nuanced appreciation of the real world consequences of its adoption. Whilst the present emphasis on sound research ethics and responsibility is a positive development, we need to slow down.

The purpose of this paper is to report on papers presented at the ninth annual Southern African online user group conference on 3‐5 June 2008 in Pretoria.

Conference report.

The focus was very much on the changes facing librarians daily, changes in users as well as in technology. This was addressed in subthemes such as the Google generation, news alerting services, institutional repositories and end‐user training.

Librarians must be on the forefront of innovative use of technology if they are to attract and retain the new users.

The purpose of this paper is to assess the appropriateness of equal weights estimation (sumscores) and the application of the composite equivalence index (CEI) vis-à-vis differentiated indicator weights produced by partial least squares structural equation modeling (PLS-SEM).

The authors rely on prior literature as well as empirical illustrations and a simulation study to assess the efficacy of equal weights estimation and the CEI.

The results show that the CEI lacks discriminatory power, and its use can lead to major differences in structural model estimates, conceals measurement model issues and almost always leads to inferior out-of-sample predictive accuracy compared to differentiated weights produced by PLS-SEM.

In light of its manifold conceptual and empirical limitations, the authors advise against the use of the CEI. Its adoption and the routine use of equal weights estimation could adversely affect the validity of measurement and structural model results and understate structural model predictive accuracy. Although this study shows that the CEI is an unsuitable metric to decide between equal weights and differentiated weights, it does not propose another means for such a comparison.

The results suggest that researchers and practitioners should prefer differentiated indicator weights such as those produced by PLS-SEM over equal weights.

To the best of the authors’ knowledge, this study is the first to provide a comprehensive assessment of the CEI’s usefulness. The results provide guidance for researchers considering using equal indicator weights instead of PLS-SEM-based weighted indicators.

Owing to religious and economic preferences in Muslim-dominated countries, middle-income customers are at the heart of banks’ strategic targeting. This study aims to investigate selected middle-income Islamic bank customers from Sylhet, one of Bangladesh’s top religious and cultural cities, to examine their perceptions of the Islamic banking services.

This study forwards three determinants of overall satisfaction. These are perceived relative advantage (PRA), perceived risk management (PRM) and perceived customer engagement (PCE). The study has used structured questionnaire and collected complete data on 300 middle-income Islamic bank users. The data was analysed using exploratory factor analysis (EFA), confirmatory factor analysis (CFA) and structural equation modelling (SEM).

While all the three selection factors significantly influence overall satisfaction, PCE has greater positive impact on overall customer satisfaction, followed by PRA and PRM. “Convenient location”, “competitive charges” and “return on deposit despite low earnings” are the top three instruments measuring “PCE”. Religion did not qualify as a standalone selection factor. The results are robust across tests conducted by using EFA, CFA and SEM.

Gross purchasing power of middle-income class in Bangladesh grew from 7% to over 30% during the past decade, and the purchasing power of this class stood at US$100bn. Having a greater portion of this population as Muslims, banks can design products and marketing campaigns by using the three selection criteria that offer a combination of faith and non-faith-based variables.

Similar studies on the middle-income customer group have been rare, especially from the Islamic banking perspective. These findings offer a concise list of three factors for the bank managers to build their strategies. With respect to the Vision 2021, these findings carry greater socio-economic significance given the transition of Bangladesh to a middle-income country.

Generalized structured component analysis (GSCA) and partial least squares path modeling (PLSPM) are two key component-based approaches to structural equation modeling that facilitate the analysis of theoretically established models in terms of both explanation and prediction. This study aims to offer a comparative evaluation of GSCA and PLSPM in a predictive modeling framework.

A simulation study compares the predictive performance of GSCA and PLSPM under various simulation conditions and different prediction types of correctly specified and misspecified models.

The results suggest that GSCA with reflective composite indicators (GSCA_R) is the most versatile approach. For observed prediction, which uses the component scores to generate prediction for the indicators, GSCA_R performs slightly better than PLSPM with mode A. For operative prediction, which considers all parameter estimates to generate predictions, both methods perform equally well. GSCA with formative composite indicators and PLSPM with mode B generally lag behind the other methods.

Future research may further assess the methods’ prediction precision, considering more experimental factors with a wider range of levels, including more extreme ones.

When prediction is the primary study aim, researchers should generally revert to GSCA_R, considering its performance for observed and operative prediction together.

This research is the first to compare the relative efficacy of GSCA and PLSPM in terms of predictive power.