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The purpose of this paper is to investigate how customers’ upgrading/downgrading _(t−1) behavior may be predictive of future spending. Further, this paper also investigates how customers’ post-consumption evaluations of upgrades and downgrades [satisfaction_(t−1) and perceived value_(t−1)] may moderate the relationship between upgrades/downgrades and future spending.

The predictions are tested using a large longitudinal data set of river cruise purchases (N = 48,103) and largely replicated using a data set of zoo membership purchases (N = 2,469).

Satisfaction_(t−1) mitigates the positive relationship between prior upgrades_(t−1) and future spending_(t). In contrast, perceived value_(t−1) magnifies the positive relationship between prior upgrades_(t−1) and future spending_(t). However, no positively moderating effects are observed to alleviate the negative relationship between prior downgrades_(t−1) and future spending_(t).

This research suggests that managers should work hard early in customer–firm relationships because of an asymmetric difficultly in altering the trajectory of an established relationship. Specifically, relationships that are trending downward (as consecutive downgrades would suggest) are difficult to repair – a mechanism to alter this trajectory is not observed. In contrast, relationships that are trending upward (as consecutive upgrades would suggest) can be improved with high perceived value evaluations but also degraded with high satisfaction evaluations.

This research should recast marketers’ understanding of the value of customers’ upgrade and downgrade decisions. Instead of using customers’ upgrade or downgrade decisions as the dependent variable, or final outcome in buyer behavior, this study shows how the accumulation of prior upgrades and prior downgrades, over time, acts as a bellwether of the customer–firm relationship. Further, to the best of the authors’ knowledge, this study is the first to connect these upgrade/downgrade decisions to customers’ evaluations of those purchases to understand how individual purchases can impact the overall customer–firm relationship.

This paper aims to develop an appropriate model for customer-experience management (CEM) for the banking-services sector.

The research method used in this study is qualitative. Techniques used for data collection and data analysis are based on the grounded theory method and include open, axial and selective coding to develop a hierarchical model. Information and data, based initially on concepts in the literature, are gathered as open code through expert interviews with 11 academic and 20 industry experts from Iran. Research data are classified and filtered by micro and macro categories and validated and edited to provide the final model.

The final model of the study is based on expecting, conceptual and caretaking factors. Micro dimensions and related propositions for the banking industry are also identified.

The final model should have practical uses in the banking sector, enabling banking managers to successfully incorporate CEM into their strategy by focusing on the key elements.

The development of a model to measure customer experience is an important indicator for performance improvements in the banking industry. This is one of the few papers to propose an appropriate model for CEM for the banking-services sector and the first to do so in an Iranian context.

The increased digital interactions in the B2B industry have enhanced the importance of customer engagement as a measure of firm performance. This study aims to map and analyze temporal and spatial journeys for customer engagement in B2B markets from a bibliometric perspective.

The extant literature on customer engagement research in the B2B context was analyzed using bibliometric analysis. The citation analysis, keyword analysis, cluster analysis, three-field plot and bibliographic coupling were used to map the intellectual structure of customer engagement in B2B markets.

The research on customer engagement in the B2B context was studied more in western countries. The analysis suggests that customer engagement in B2B markets will take centre stage in the coming times as digital channels make it easier to track critical metrics besides other key factors. Issues like digital transformation, the use of artificial intelligence for virtual engagement, personalization, innovation and salesforce management by leveraging technology would be critical for improved B2B customer engagement.

The study provides a comprehensive reference to scholars working in this domain.

The study makes a pioneering effort to comprehensively analyze the vast corpus of literature on customer engagement in B2B markets for business insights.

Cross-channel integration improves the operations of multi-channel and omnichannel marketing and increase firms' overall performance. By addressing the extant gaps in current literature, this configurational analysis aims to test the combined effects of organizational, channel and environmental factors on cross-channel integration.

Data were collected from a sample of 180 manufacturers. Necessary condition analysis (NCA) was used to test whether two organizational factors (firm size and IT capability), one environmental factor (environmental dynamism) and two channel factors (channel diversity and proportion of direct channels) were necessary or unnecessary conditions for high cross-channel integration. Fuzzy-set qualitative comparative analysis (fsQCA) was applied to analyze the configurational factors of high vs low cross-channel integration.

First, firm size and IT capability are non-linear and substitute for each other in affecting cross-channel integration in a diversified channel system with a high proportion of direct channels. Second, in a dynamic environment, firms with large size and IT advantage could achieve high cross-channel integration by diversifying channel types or increasing the proportion of direct channels. Third, the effect of channel diversity and proportion of direct channels on cross-channel integration is asymmetric depending on other antecedent conditions.

The authors tested a configurational framework developed from multiple theoretical perspectives. The authors' empirical findings contribute to the literature by providing insights into the mechanisms underlying the formation of high and low cross-channel integration. The results suggest multiple ways for firms to promote cross-channel integration by adjusting channel factors based on configurational conditions.