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A simple algebraic multigrid (AMG) solver for linear equations is presented, and its performance compared with a conjugate gradient scheme. This multigrid method is extended to solve the discrete Navier—Stokes equations, obtained by applying a finite volume approach to three‐dimensional incompressible flow on a finite element mesh. The resulting multigrid solver is incorporated into a general purpose flow code (ASTEC), where it proves faster than the original solution algorithm, based upon SIMPLE. The linear AMG solver is both efficient and robust, but the extension to include coupling in the Navier—Stokes equations does not converge on all problems.

The introductory chapter includes how to design-in good practices in theory, data collection procedures, analysis, and interpretations to avoid these bad practices. Given that bad practices in research are ingrained in the career training of scholars in sub-disciplines of business/management (e.g., through reading articles exhibiting bad practices usually without discussions of the severe weaknesses in these studies and by research courses stressing the use of regression analysis and structural equation modeling), this editorial is likely to have little impact. However, scholars and executives supporting good practices should not lose hope. The relevant literature includes a few brilliant contributions that can serve as beacons for eliminating the current pervasive bad practices and for performing highly competent research.

This chapter describes and tests the principles of configural theory in the context of hospitality frontline service employees’ happiness-at-work and managers’ assessments of these employees’ quality of work performances. The study proposes and tests empirically a configural asymmetric theory of the antecedents to hospitality employee happiness-at-work and managers’ assessments of employees’ quality of work performance. The findings confirm and go beyond prior statistical findings of small-to-medium effect sizes of happiness-performance relationships. The method includes matching cases of data from surveys of employees (n = 247) and surveys completed by their managers (n = 43) and uses qualitative comparative analysis via the software program fsQCA.com. The findings support the four principles of configural analysis and theory construction: recognize equifinality of different solutions for the same outcome; test for asymmetric solutions; test for causal asymmetric outcomes for very high versus very low happiness and work performance; and embrace complexity. The theory and findings confirm that configural theory and research resolves perplexing happiness–performance conundrums. The study provides algorithms involving employees’ demographic characteristics and their assessments of work facet-specifics which are useful for explaining very high happiness-at-work and high quality-of-work performance (as assessed by managers) – as well as algorithms explaining very low happiness and very low quality-of-work performance.

This chapter describes tenets of complexity theory including the precept that within the same set of data X relates to Y positively, negatively, and not at all. A consequence to this first precept is that reporting how X relates positively to Y with and without additional terms in multiple regression models ignores important information available in a data set. Performing contrarian case analysis indicates that cases having low X with high Y and high X with low Y occur even when the relationship between X and Y is positive and the effect size of the relationship is large. Findings from contrarian case analysis support the necessity of modeling multiple realities using complex antecedent configurations. Complex antecedent configurations (i.e., 2–7 features per recipe) can show that high X is an indicator of high Y when high X combines with certain additional antecedent conditions (e.g., high A, high B, and low C) – and low X is an indicator of high Y as well when low X combines in other recipes (e.g., high A, low R, and high S), where A, B, C, R, and S are additional antecedent conditions. Thus, modeling multiple realities – configural analysis – is necessary, to learn the configurations of multiple indicators for high Y outcomes and the negation of high Y. For a number of X antecedent conditions, a high X may be necessary for high Y to occur but high X alone is almost never sufficient for a high Y outcome.

This paper reports findings from the first annual cycle of a three‐year research project on the provision and use of electronic information systems (EIS) within higher education in the UK. The project, JISC User Surveys: Trends in Electronic Information Services (JUSTEIS), was funded by the Joint Information Systems Committee (JISC) and undertaken at the University of Wales, Aberystwyth (UWA). Students, academics and library staff in 25 universities were surveyed using critical incident and critical success factors methodologies to ascertain the range and nature of EIS use. Provision of these systems by higher education institutions was also investigated via an analysis of their library websites. The findings reported in this paper focus on student use and the purposes for which EIS are employed, and reveal the limited array of EIS used and the ad hoc nature of search strategies adopted across undergraduate and postgraduate bodies within a range of disciplines. There appears to be little or no variation in the pattern of EIS use by the various student groups studied – the effect of the Internet on information seeking by students is hugely significant and the more formal resources, such as JISC‐negotiated resources are little used. There is little evidence of coherent search strategies used by students. Recommendations for both the JISC and higher education are offered.

Recognizing Gigerenzer’s (1991) dictum that scientists’ tools are not neutral (tools-in-use influence theory formulation as well as data interpretation), this chapter reports theory and examines data in ways that transcend the dominant logics for variable-based and case-based analyses. The theory and data analysis tests key propositions in complexity theory: (1) no single antecedent condition is a sufficient or necessary indicator of a high score in an outcome condition; (2) a few of many available complex configurations of antecedent conditions are sufficient indicators of high scores in an outcome condition; (3) contrarian cases occur, that is, low scores in a single antecedent condition associates with both high and low scores for an outcome condition for different cases; (4) causal asymmetry occurs, that is, accurate causal models for high scores for an outcome condition are not the mirror opposites of causal models for low scores for the same outcome condition. The study tests and supports these propositions in the context of customer assessments (n = 436) of service facets and service-outcome evaluations for assisted temporary-transformations of self via beauty salon and spa treatments. The findings contribute to advancing a nuanced theory of how customers’ service evaluations relate to their assessments of overall service quality and intentions to use the service. The findings support the need for service managers to be vigilant in fine-tuning service facets and service enactment to achieve the objective of high customer retention.

This chapter identifies research advances in theory and analytics that contribute successfully to the primary need to be filled to achieve scientific legitimacy: configurations that include accurate explanation, description, and prediction – prediction here refers to predicting future outcomes and outcomes of cases in samples separate from the samples of cases used to construct models. The MAJOR PARADOX: can the researcher construct models that achieve accurate prediction of outcomes for individual cases that also are generalizable across all the cases in the sample? This chapter presents a way forward for solving the major paradox. The solution here includes philosophical, theoretical, and operational shifts away from variable-based modeling and null hypothesis statistical testing (NHST) to case-based modeling and somewhat precise outcome testing (SPOT). These shifts are now occurring in the scholarly business-to-business literature.

The focus of this study is on analyzing influencing factors of antisocial travel-related behaviors – in particular road rage. Building on the concept of redirection, the current chapter develops a theory of natural and planned redirection to derive starting points for demarketing antisocial behaviors. A fuzzy set qualitative comparative analysis (fsQCA) with survey data from 6,811 consumers from the DDB Life Style Study is used to gain insights into the individuals behind road rage. Results show that specific kinds of anti- and prosocial behavior associate with high and low levels of road rage, respectively. The study finds that these prosocial behaviors may function as natural redirection mechanisms and prevent or reduce road rage. Thereby, the findings extend previous analyses of road rage and allow for deriving theoretical and policy implications.

The aim of the JUSTEIS project over the first three cycles (1999‐2002) was to examine the uptake and use of electronic information services in higher education in the UK, so that planning of services could be informed by trends in usage and evidence of specific needs. The objectives were to: examine which services were used by students and academic staff; how senior library staff planned services to purchase content and support its use; and examine how library and information services promoted services through their Web pages. Results over the three years explained the growing popularity of electronic journal services, the acceptance of the search engine model for information retrieval and the important role academic staff play in the promotion of electronic information services for student learning. Conclusions and recommendations concern the need for library and information staff to make their approach to integration of information skills into the curriculum appropriate for the discipline, the type of institution, and its strategy for implementation of any virtual or managed learning environment software.