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Different approaches and attitudes to advanced manufacturing technology need to be adopted in pursuit of competitive advantage. The US sets an example here and it is argued that the UK must invest in AMT and its management. It is also suggested that the education and training of managers to handle AMT must become a priority if Britain is not to lose all the advantages gained over the past ten years.

This article is the second half of a series concerning advanced decisions. Central to the problem of AMT (advanced manufacturing technology) is that investment is uncertainty. Under consideration is a highly expensive innovation, often bringing unprecedented operational routines and organisational impacts. The intangible benefits of AMT are dealt with here, and how to quantify them.

Arend W. D. Vos has been appointed general manager of European operations for PPG Industries' Coatings and Resins Division.

Empirical studies show substantial variation across immigrants in the rate and direction of assimilation along various dimensions (e.g., cross-ethnic contact, language, identity). To explain this variation, past research has focused on identifying exogenous factors, such as discrimination, human capital, and settlement intention. In this chapter we argue that variation in immigrant outcomes emerges endogenously through positive interaction effects between dimensions of assimilation. We propose a new assimilation model in which processes of social influence and selection into congruent social environments give rise to multiple long-term equilibria. In this model, migrants who are already assimilated along many dimensions tend to also adapt along other dimensions, while less assimilated migrants become more strongly embedded in their ethnic group.

To test the assimilation model, we derive a number of hypotheses, which we evaluate using trend analysis and dynamic panel regression on data from the Longitudinal Survey of Immigrants to Canada.

The data mostly confirm the hypotheses, providing overall support for the assimilation model.

Our theory and findings suggest that immigrants would follow divergent assimilation trajectories even in the absence of a priori population heterogeneity in external factors.

The positive interaction effects between cultural and structural dimensions of assimilation suggest that mixed policies that promote integration while seeking to prevent loss of identity go against the natural tendency for cultural and structural assimilation to go hand in hand.

The present chapter proposes a novel model of immigrant assimilation and an empirical test.

The purpose of this paper is to propose a methodological framework that combines several data envelopment analysis (DEA) models to deal with the problem of evaluating and ranking advanced manufacturing technologies (AMTs) without introducing any subjectivity in the analysis.

The methodology follows a two-phase procedure. First, the relative efficiency of every technology is calculated by implementing different DEA cross-efficiency models generating the same number of high-order indicators as efficiency vectors. Second, high-order indicators are used as outputs in a SBM-DEA super-efficiency model to obtain a comprehensive DEA-like composite indicator.

The framework is implemented to evaluate a sample of flexible manufacturing systems. Comparing it to other methods, results show that the methodology provides reliable information for AMTs selection and effective support to management decision-making.

This paper contributes to the body of knowledge about the utilization of DEA to select AMTs. The framework has several advantages: a discriminating power higher than the basic DEA models; no subjective judgment relative to weights necessary to aggregate single indicators and choice of aggregation function; no need to perform any transformation normalizing original data; independence from the unit of measurement of the DEA-like composite indicator; and great flexibility and adaptability allowing the introduction of further variables in the analysis.

This article is the first half of a series concerning advanced manufacturing technology (AMT) investment decisions. Individual problems with formalised techniques in this field are reduced by the frequency of their joint use in organisations. The article emphasises that it is important to appreciate that the nature, costs and benefits of AMT are complex and the systems have a far‐reaching impact on the organisation.

In social marketing practice, there is no all-encompassing approach that guides researchers and practitioners to build theory-driven social marketing interventions. While the Co-create–Build–Engage (CBE) process offers a roadmap for marketing application, including outlining when and where social marketing’s eight benchmark principles have been applied, limited practical guidance on how and when theory should be applied is offered. This paper reports one case study demonstrating how theory was applied to deliver a theory-informed well-being behavior change intervention.

This paper proposes and applies a new five-step theory-driven social marketing intervention build process (BUILD) drawn from an extensive base of social marketing research and application. Using a case study method, we showcase how the five-step process was applied to inform the design, build and implementation of a well-being behavior change intervention.

This study proposes a five-step process to build theory-driven social marketing interventions called BUILD: Begin with the objective, Use theory, Initiate program design, Let’s produce and Develop the engagement plan. This study provides a step-by-step and easy-to-follow BUILD process which outlines how social marketers can apply a selected theory to inform program design and implementation.

The BUILD process offers a roadmap to build theory-driven social marketing interventions that include all elements of intervention development, namely, objective-setting, theory evaluation, selection and application, producing the program and planning for program engagement.

This study provides a novel five-step process to help social marketing researchers and practitioners build theory-driven social marketing interventions.

The idea that a significant portion of what consumers do, feel, and think is driven by automatic (or “implicit”) cognitive processes has sparked a wave of interest in the development of assessment tools that (attempt to) capture cognitive processes under automaticity conditions (also known as “implicit measures”). However, as more and more implicit measures are developed, it is becoming increasingly difficult for consumer scientists and marketing professionals to select the most appropriate tool for a specific research question. We therefore present a systematic overview of the criteria that can be used to evaluate and compare different implicit measures, including their structural characteristics, the extent to which (and the way in which) they qualify as “implicit,” as well as more practical considerations such as ease of implementation and the user experience of the respondents. As an example, we apply these criteria to four implicit measures that are (or have the potential to become) popular in marketing research (i.e., the implicit association test, the evaluative priming task, the affect misattribution procedure, and the propositional evaluation paradigm).