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AbstractKnowing your customers and their needs is a topic that has attracted increasing interest in the business and academic worlds. In line with this, constructing customer knowledge has come under examination in this study. A firm's ability to construct customer knowledge creates solid ground for responding better to its customers' needs. In the business‐to‐business markets, customers are demanding increasingly knowledge‐intensive services. Therefore, examining the topic is particularly important in this specific context. In this study, the purpose is to find out how customer knowledge is constructed in knowledge‐intensive customer relationships. To accomplish this purpose, a qualitative multiple case study is organized around seven case relationships allowing within‐case and cross‐case comparisons. The findings of this study describe a variety of practices knowledge‐intensive firms can utilize in constructing customer knowledge in their daily activities. This study helps KIBS organizations in their efforts to create a source of competitive advantage as customer knowledge is a critical asset for firms, especially in a fast‐changing knowledge‐intensive environment.

This article approaches the relationship between the categories of custom and law by means of an experiment with cartographic metaphors of scale and location. In Papua New Guinea, the relationship of custom to law is configured by the canonization of custom (the concept as it is known in studies of legal pluralism) in the Constitution of the Independent State of Papua New Guinea and in the Underlying Law Act 2000. However, the status of this universalizing category is complicated by its relationship to the putatively local category of kastom, as it is known throughout Papua New Guinea. I argue that the two categories, custom and kastom, do not share an equivalent relationship to law because they occupy different levels of scale. In the discourses of legal elites, custom encompasses kastom. Whereas for many "smaller‐scale" ethnic and language groups within the country, kastom and law are simply two potential categories of efficacious action, among many others, in highly specific and localized "mixes." These mixes lose their intelligibility when elites attempt to replicate them at the level of the state.

PurposeThis study aims to investigate the impact of three types of online customer-to-customer interaction qualities on customers' participation intention through customer–firm affection in online mass service contexts to address the influence of several types of intercustomer interactions.Design/methodology/approachThe data were amassed using retrospective experience sampling. The hypothesized relationships were examined utilizing structural equation modeling.FindingsThe results demonstrate that the perceived quality of the friend-interaction (e.g. [non-]verbal online interaction with friends), neighboring customer-interaction (e.g. [non-]verbal online interaction with stranger users) and the audience-interaction (crowding) has a significant impact upon customer participation intention, mediated by customer–firm affection.Research limitations/implicationsThis research was performed in the situation of online mass services (e.g. massively multiplayer online role-playing games). Future studies could extend the findings by conducting further studies across various types of services and by comparing results across different categories of mass services (e.g. hedonic vs utilitarian).Practical implicationsOnline mass service marketers should focus on facilitating all three types of online customer-to-customer interactions (i.e. friend-, neighboring customer-, and audience-interaction). For example, online game developers may need to require users to communicate and collaborate with not only friends but also stranger users to progress and succeed in online multiplayer games.Originality/valueThe current study differs from prior research by addressing the influences of not only online intercustomer interaction qualities but also customer–firm affection on customer participation intention.

PurposeThe term customer intimacy has been used both in academia and business, albeit lacking clear definition and empirical validation. The authors in this paper aim to develop a measure of customer intimacy in business‐to‐business contexts and to assess its reliability and validity, as well as its relevance, within a nomological relationship marketing network.Design/methodology/approachA multi‐method (qualitative/exploratory and quantitative/confirmatory structural modelling), multi‐staged (test, re‐test) research approach is used and applied in the UK and Germany.FindingsThe results show that customer intimacy is a second order construct reflected by the three formative dimensions of mutual understanding, closeness, and value perception. The results also show that customer intimacy is a relevant relationship indicator, distinct from the central relationship indicators of trust and commitment. It impacts relationship commitment levels, customer induced word‐of‐mouth, repurchase intentions, information disclosure, customer availability, and leads to an advisor status with the customer. Moreover, customer intimacy mediates relationship marketing's central trust commitment link.Research limitations/implicationsThe main limitations that should be addressed by future studies are: reliance on the key informant technique on one side of the supplier‐buyer dyad; cross‐sectional design.Practical implicationsThis study shows that achieving and managing customer intimacy is a relevant managerial goal and task for firms and shows managers how it can be measured and managed.Originality/value.This study, for the first time, presents a measure for customer intimacy and assesses its quality and impact empirically. The measure will be of significant value in making customer‐centric, relationship management approaches more accountable.

PurposeThis study presents the applicability of a model-based approach for loyalty program forecasting using smartphone app in the digital strategy of the retail industry.Design/methodology/approachThe authors develop a dynamic model with the cyclical structure of customer segments through customer experience. They use time-series data on the number of members of the loyalty program, "Seven Mile Program" and confirm the validity of the approximate calculation of customer segment share, customer segment sales share and aggregate sales performance. The authors present three medium-term forecast scenarios after the launch of a smartphone payment service linked with the loyalty program.FindingsThe sum of the two customer segment shares for forecasting (the sum of the quasi-excellent and excellent customer ratios) is about 30% in each scenario, consistent with an essential customer loyalty (true loyalty) share obtained in the existing empirical study.Research limitations/implicationsDigital strategy in the retail industry should focus more on estimating and forecasting average amounts of customer segments and the number of aggregated customers through the digitalization on the customer side than on individual customer journeys and responses.Practical implicationsMulti-scenario evaluation through simulation of dynamic models from a systemic view can be used for decision-making in retailing digital strategies.Originality/valueThis study builds a model that integrates the cyclicality of customer segment transition through customer experiences into a loyalty matrix framework, which is a method that has previously been used in the hospitality industry.

PurposeThe profitability of individual customers can show substantial variation, both in money amounts and in margins (percentages). The literature suggests that larger customers have a higher customer profitability margin: a dollar in revenue from a large customer generates more profit than a dollar in revenue from a small customer. The purpose of this paper is to explore the relationship between customer size and the customer profitability margin.Design/methodology/approachDraws up a model with five variables (customer size, product margin, exchange efficiency, support, customer profitability margin) and hypothesizes the relationships between the variables. Uses LISREL to test the relationships on a database from a business‐to‐business setting.FindingsThe relationship between customer size and customer profitability margin is not direct, but runs through other variables, mainly exchange efficiency. It is not the result of larger customers paying higher product margins or having fewer customer support demands.Research limitations/implicationsAdds to the empirical literature on customer profitability. Ideally, this would be done using panel data rather than the cross‐sectional data used in this paper.Practical implicationsProfitability data at the level of individual customers provide useful insights. Customer size as such is not a driver of the customer profitability margin. Identify the trade‐offs between customer size, product margins (discounts), support demands, and exchange costs that ultimately lead to customer profitability.Originality/valueAdds to the empirical literature on customer profitability and offers practical implications for managing customer relationships.