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This paper aims to explore the role of configurations of relationship quality dimensions for explaining sources of behavioral outcomes in the globalized manufacturing industry.

A joint analysis of behavioral and objective performance data from globalized manufacturing links perceptual customer metrics that relate to dimensions of relationship quality (i.e. attitudinal loyalty, perceived customer orientation, customers’ perceived innovativeness of the supplier and perceived customer influence on supplier innovation) with behavioral outcomes (i.e. share of wallet (SOW) and customer account profitability). Using data from a global business-to-business (B2B) customer survey together with archival performance data from a multinational mechanical engineering firm, a fuzzy set qualitative comparative analysis (fsQCA) is performed.

The fsQCA results suggest that perceptual customer metrics related to innovation can be relevant aspects of relationship quality, in line with Anderson and Mittal’s (2000) satisfaction-repurchase-profitability chain framework and its adaptation to SOW. However, the underlying complexities in the different combinations of attributes in the recipe are such that they are not equifinal in leading to higher SOW or higher profitability. This paper finds indications for non-linearities between perceptual measures investigated and profitability of customer accounts, with particular relevance for the role of perceived customer orientation, perceived product innovativeness of the supplier and attitudinal loyalty.

The analysis faces a number of limitations, starting with its reliance on cross-sectional survey data, which does not enable us to account for feedback mechanisms, for example, arising from customer perceptions regarding innovation aspects. The lack of a multidimensional conceptionalization of the perceptual customer constructs may have limited the analysis, considering also recent evidence from retail companies in the furniture sector in Spain, suggesting that the multidimensional conceptualization of relationship value explained satisfaction and loyalty levels to a greater extent than the one-dimensional conceptualization (Ruiz-Martínez et al., 2019).

In terms of managerial implication, the results suggest that customers perceive limited value in participating in the focal firm’s innovation value chain funnel, hence customer loyalty cannot be bought using simple incentive strategies. The results with regard to customer account profitability suggest that B2B customers investigated here may distinguish when interacting with their globalized supplier in the innovation funnel: they may see a positive customer value when the innovation is a product, and thus, relation-specific, whereas they may see limited customer value when innovation is considered in more generic terms (customers’ perceived influence on supplier innovation in general).

This paper starts from the premise that perceptual customer metrics can matter for supplier performance, as the customer relationship and customer value management research has shown. However, there is limited empirical evidence from globalized manufacturing sectors incorporating perceptual constructs in behavioral outcomes, and limited evidence assessing customer-perceived value in such sectors through alternate approaches to main-effects focused analyzes. We employ qualitative comparative analysis using fuzzy sets (Russo et al., 2019) to address these gaps, focusing on two key behavioral outcomes, namely, customer account profitability and SOW.

The current study conceptualizes and empirically tests a new model of market brand equity (MBE). This model, that not just provides an understanding of customer mindsets toward the brand, as most empirical models do, but also measures the marketing benefits of such mindsets. The present study offers two models. One is comprehensive and theoretical while the other is an empirical model. The empirical model is a practical model drawn from the more comprehensive and conceptualized model. The hypothesized empirical MBE model is tested using structural equation modeling (SEM) analysis followed by a formula that offers a method to calculate and rank competitive brands in the market place. The purpose of this paper is to conclude with a discussion of the implications of the model.

The findings of the present research are based on a representative sample of 964 cellular phone users selected randomly from an Israeli internet panel were analyzed. The questions related to the dimensions of the brand equity needed a more intimate relationship of the customers with the brand. Thus, those questions were asked only with regard to the brand that the respondents were mainly using. These questions were concerned with brand knowledge, brand commitment and brand overall attitude. The other questions that the respondents answered were about three other brands on the market. All dimensions, except purchase barriers, were measured on a ten-point scale.

SEM analysis was used to test the hypothesized MBE model as well as alternative models. The results, which supported the hypothesized model, indicated that knowledge has a strong positive effect on image, personality and attitude. Image has a positive effect on attitude, but that of personality was insignificant. Attitude, image and personality have a positive effect on commitment. Commitment affects recommendation strongly and positively. Both commitment and recommendation have a positive and significant effect on potential market share.

The limitations of the current research are that it was not measured over time and that only one product category has been tested. In addition to dealing with these limitations, future research may also add additional marketing performance outcome variables such as the ability to obtain premium prices and to exercise brand power in relation to channels of distribution.

The model presented in this paper provides the marketer with the ability to compare, from a competitive perspective, the relative average in the market place of customer mindset, customer performance and marketing performance. The analysis also reveals whether to invest in strengthening customer mindset or in capturing a greater market share. When the brand leader is far from its followers, an additional analysis may be required and it may be necessary to increase the sensitivity of the analysis by examining separately (without the leading brand) the relative differences between the follower brands. Moreover, the measurement questions should be adjusted to fit different product categories. For example, in testing the MBE in the service industry, “product performance,” which is a component of brand commitment, should be measured by the “quality of service.” But the way of using the model will not change. Another example for future research may be found in sport marketing, such as among football or basketball clubs. In such instances, performance – winning or losing – or even the quality of the players on the team may be considered. It is suggested here that the MBE’s measurement of fast-moving products vs slow moving ones. However, in such cases the model would probably show a significant difference in involvement with the brands of fast-moving products displaying much lower customers’ involvement then brands of slow-moving products.

The empirical model suggested in this study is a new and practical market-based brand equity that uses commitment as the main construct, building brand equity to represent the performance outcome of the customer mindset used in the models noted above. The current study also offers a new practical and useful formula for calculating and ranking MBE.

The purpose of this study is to offer a “brand equity model” that will help football organizations to manage their appeal.

The proposed model utilizes structural equation modelling analysis to test the hypothesized marketing brand equity (MBE) model. The empirical part of the research stems from a large survey of 1,300 Israeli football fans.

As expected, knowledge about the team, the team’s image and its perceived personality significantly predicted positive attitudes toward the team. This in turn predicted commitment, which predicted recommendation, which predicted intentions. The linear regression to extract the seven parameters weights was highly significant (F = 163.5, p < 0.001) and explained 52 per cent (R² = 0.518) of the depended variable “price premium”.

The new MBE model suggested here provides a relative index of brand equity for football club organizations that enables them to competitively compare the marketing equity of their club to that of their rivals. The MBE model also shows that commitment is a central component in the football club’s brand equity model. The current MBE model is the only model that provides a weight for each of the components. Each respective weight represents the internal contribution of each component to the final brand equity index. These weights indicate where an effort should be made to improve the equity of the brand.

Football teams may also need to focus on the constructs underlying the commitment (Shuv-Ami, 2012) of fans to their football club organization, that is, the team performance and satisfaction stemming from the fans’ experience with their team and the feelings of loyalty and involvement that represent the degree of fan engagement with the team. Although football teams do what they can to improve performance, much can be done in marketing to improve the other constructs and, thus, fan commitment. Improving the experience of fans, both on and off the field, regardless of whether the team is winning or losing, builds fan engagement.

The current research suggests two new brand equity models for football club organizations. One is a comprehensive theoretical model that combines and expands current conceptual brand equity models (Keller, 1993, 2008; Aaker, 1991, 1996; Keller and Lehmann, 2006); the other is an empirical model that makes it practical to measure the marketing strength or the brand equity of football clubs. The new empirical MBE suggested here provides a relative index of brand equity for football club organization that enable them to compare competitively the marketing equity of their club to that of their rivals. The MBE model also shows, for the first time, that commitment is a central component in the football club brand equity model. The current MBE is the only model that provides a weight for each of its component.

This paper seeks to provide evidence that the long‐term success of capital‐intensive technology products requires continuous integration of innovations in the form of new features and capabilities that meet broad user preferences.

Magnetic resonance imaging (MRI) research centers, which represent lead users in this industry, are used as a case study. An online survey was developed to identify and rank the main factors behind brand switching, then secondary sources are used to confirm the research results.

A multi‐faceted approach to data collection is used to show that product innovations in the form of specific features are the main motive for switching to a new technology, consistent with the expectation that lead users seek technologies that maintain leading‐edge positions.

There are limitations to generalizing from this case study to other industries. The findings can be generalized to industries with similar characteristics, such as aircraft and heavy machinery manufacturing. In practice, managers should find a reliable strategy to assess factors underpinning brand switching that is unique to their industry. Determining the main factors behind switching is a critical matter when defining the appropriate strategy to keep their market share from eroding.

The literature reports considerable research that investigates brand switching. However, most of it focuses on highly competitive markets for consumer goods. This paper addresses a paucity of knowledge about what influences lead users of capital‐intensive products to switch between brands.