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This study aims to capture how the association between a multichannel relational communication strategy (MRCS) and customer performance is contingent upon such customer performance (low- versus high-performance customers) and to reconcile past contradictory results in this marketing-related topic. To this end, the authors propose and validate the method of quantile regression as an unconventional, yet effective, means to proceed to that reconciliation.

This study collected data from 4,934 customers of a private pension fund firm and accounted for both firm- and customer-initiated relational communication channels (RCCs) and for customer lifetime value (CLV). This study estimated a generalized linear model and then a quantile regression model was used to account for customer performance heterogeneity.

This study finds that specific RCCs present different levels of association with performance for low- versus high-performance customers, where outcome customer performance is the dependent variable. For example, the relation between firm-initiated communication (FIC) and performance is stronger for low-CLV customers, whereas the relation between customer-initiated communication (CIC) and performance is increasingly stronger for high-CLV customers but not for low-CLV ones. This study also finds that combining different forms of FIC can result in a negative association with customer performance, especially for low-CLV customers.

The authors tested the conceptual model in one single firm in the specific context of financial services and with cross-sectional data, so there should be caution when extrapolating this study’s findings.

This study offers nuanced and precise managerial insights on recommended resource allocation along with relational communication efforts, showing how managers can benefit from adopting a differentiated-customer performance approach when designing their MRCS.

This study provides an overview of the state of the art of MRCS, proposes a contingency analysis of the relationship between MRCS and performance based on customer performance heterogeneity and suggests the quantile method to perform such analysis and help reconcile past contradictory findings. This study shows how the association between RCCs and CLV varies across the conditional quantiles of the distribution of customer performance. This study also addresses a recent call for a more holistic perspective on the relationships between independent and dependent variables.

The paper aims at generating a better understanding of the design elements and related management practices of strategic account management programs, in order to assist firms wishing to design such programs.

The research process is based on systematic combining of literature, empirical data from interviews with nine multi‐national firms, interaction with the firms during the research, and the knowledge resource base of the Strategic Account Management Association.

A strategic account management program (SAMP) is defined as a relational capability, involving task‐dedicated actors, who allocate resources of the firm and its strategically most important customers, through management practices that aim at inter‐ and intra‐organizational alignment, in order to improve account performance (and ultimately shareholder value creation). The research identified four inter‐organizational alignment design elements: account portfolio definition, account business planning, account‐specific value proposition, account management process; and four intra‐organizational design elements: organizational integration, support capabilities, account performance management, account team profile and skills. The management practices pertinent to each element are discussed.

Firms need to ensure that a SAMP is configured so that there is fit between the design elements discussed. Focus should be put on identifying framing elements that set the foundation for configuring effective programs, as they determine the prerequisites for other elements.

The paper contributes to the literature on strategic account management by summarizing extant research and developing an organizing framework, informed by an empirical study.

The purpose of this paper is to examine how, taking customer relationships as the unit of analysis, the heterogeneity of customer relationship performance influences the heterogeneity of firm performance, and how firms can balance the heterogeneity of customers, customer relationships, and customer portfolios by differentiated business models.

The approach to the topic is one of theoretical analysis and conceptual development.

Value capture is defined as the discounted present value of all future economic profit from the relationship. Three sources of value capture heterogeneity are identified: the customer, the relationship with the customer, and the interdependence between customers in a customer base. Relationship performance can be improved by investing in business model differentiation, in order to facilitate controlled adaptation to specific customer relationships and/or customer portfolios. Firms have to manage parallel business models and a central capability is the ability to create internal fit between the elements of a specific business model.

The research presented relates to business‐to‐business customer relationships. Some of the conceptual thinking will not be applicable in consumer relationships.

A firm should have an optimum mix of customer relationships in its customer base, in relation to firm goals and strategy. Management needs to recognize the heterogeneity of customer relationship performance, and manage customer portfolios accordingly. In order to deal with the heterogeneity, it may be necessary to manage parallel business models. This will necessitate new capabilities, such as customer insight generation, account management, modularized production platforms, and relationship performance control.

For a scholarly audience the paper contributes to the discussion on how marketing improves firm performance by assuming responsibility for increasing firms' market value. For a practitioner audience it offers ideas for genuinely customer‐centric management.

Joint ventures (JVs) are known to create value for their parent firms, in part due to the mutually beneficial sharing of information that occurs at the JV level. Market orientation (MO) is a well-documented strategic orientation that has received little attention in the JV literature, despite considerable research suggesting that MO has a positive effect on performance. This study posits that the MO skills contributed to a new JV by parent firms are likely to play a central role in a shareholder's assessment of the potential for success of a newly announced JV, thereby triggering changes in market value for parent firms.

Computer-Assisted-Text-Analysis (CATA) is used to calculate MO heterogeneity from annual reports, and event-study methodology is used to assess parent firm performance. The authors rely on a US sample of 82 public JV parents involved in 41 new equally-weighted JV formation announcements.

The authors find that heterogeneity on MO's behavioral components (customer orientation, competitor orientation, and coordination) is negatively related to parent performance, while heterogeneity on MO's profitability component is positively related to parent performance. However, the effect of MO's long-term focus heterogeneity on parent performance was not supported.

The results suggest that the benefits of information sharing in partnerships may be of a nuanced nature when it comes to MO. Although heterogeneity in profitability inclination created value for parent firms announcing a new JV; heterogeneity in customer, competitor and coordination market orientations did not appear to be rewarded by shareholders.

Purpose – Revisiting Fornell et al.'s (1996) seminal study, this chapter looks at the evidence for observed and unobserved heterogeneity within data underlying the American customer satisfaction index (ACSI) model. Examining data for two specific industries (utilities and hotels) reveals only modest differences. However, we suppose that unobserved heterogeneity critically affects the results. These insights provide the basis for shaping further differentiated ACSI model analyses and more precise interpretations.

Methodology/approach – This study applies the partial least squares (PLS) path modeling method and uses empirical data to estimate and compare the ACSI model results on the aggregate and industry-specific data levels. In addition, the finite mixture PLS path modeling (FIMIX-PLS) method is employed to further examine across industry similarities and within industry differences.

Findings – This research uncovers unobserved heterogeneity that guides forming three segments of customers within each industry. The major segment in each industry represents customers that are fairly loyal (i.e., neither disloyal nor extremely loyal) while the other two smaller segments are not as similar across the two industries. Our study identifies substantial differences across these segments within each industry. An importance-performance map analysis illustrates these differences and provides the basis for managerial implications.

Originality/value of the chapter – The unobserved heterogeneity revealed within industries in a given country (i.e., the United States of America) underlines the need to be open to differences within populations, beyond the observed heterogeneity across distinct groups or cultures, and the need to reconsider reporting requirements in academic research.

The link between openness and innovative performance has been established as an inverted U-shape relationship, namely, the openness-performance connection is not always positive. The purpose of this paper is to introduce the concept of partner heterogeneity to characterize the influence of “quality” changes in partners on innovative performance, that is, the focus of this paper. Given that partner heterogeneity is crucial in explaining open innovative performance, it is also worth placing the examination of this key construct in emerging regions such as China.

The sample selection of this study covers a wide range of industries, but requires that the sample firms be manufacturing enterprises with an open innovation strategy. With opportunities and challenges associated with partner collaboration toward open innovation, the Chinese province of Zhejiang has established its reputation. Thus, empirical data were collected randomly from data pool of Zhejiang Province Economic and Information Commission, as well as a survey questionnaire. Data were using a cross-sectional survey methodology encompassing diverse organizations, industries, and nations.

Empirical testing of this assumption in a sample of 217 manufacturing firms indicates that partner heterogeneities, which are classified as organizational heterogeneity, industry heterogeneity, and national heterogeneity are all positively associated with innovative performance, but the strength of this association is influenced by environmental turbulence. Technological turbulence significantly and positively modulates the relationships of organizational and national heterogeneities with innovative performance. Market turbulence also plays a significant positive role on the relationship between national heterogeneity and innovative performance, while technological and market turbulence roles on the relationship between industry heterogeneity and innovative performance are not confirmed.

This paper refines the connotative dimensions of partner heterogeneity around the core concept of partner heterogeneity in open innovation in the context of emerging region, China. The study presents a systematic, in-depth analysis, and verifies the impact mechanisms of partner heterogeneity in open innovation on innovative performance by integrating the resource-based view, organizational learning theory, and transaction cost theory.

The purpose of this paper is to examine the effects of store managers’ employee climate perceptions on frontline employee (FLE), customer and store performance outcomes in the small-store setting.

This study derives the findings from a multi-source data set acquired in partnership with a North American-based retailer that includes survey responses from 1,133 store managers, 5,591 FLEs and 16,488 customers. This paper matches survey responses to corporate records and store sales and operations data.

This study finds that store managers’ employee climate perceptions affect FLEs both directly and indirectly, through store manager social support behaviors. This paper tests the boundary conditions for these findings by examining the moderating effects of store-level FLE tenure heterogeneity and competitive intensity. Study results provide partial support for the hypothesized relationships with regard to FLE tenure heterogeneity, but not competitive intensity.

This research is subject to many of the limitations common to a survey-based study. While the use of one retailer provided opportunities to examine store-level performance data, future research would benefit by using a more expansive data set spanning several companies and industries. Moreover, as the current study was set in the small-store setting, future research should explore how store managers’ influence fluctuates depending on store size and the mechanisms through which organizational priorities flow through other management levels (e.g. department managers) in large retailers.

Study results provide managerial guidance regarding the implementation of an employee climate for the delivery of an enhanced customer experience and superior financial performance.

Although researchers have paid considerable attention to employees’ psychological and organizational climate perceptions, this study makes a unique contribution by examining the effects of store managers’ employee climate perceptions on FLE, customer and store-level outcomes.

In many industrial contexts, firms are encountering increasingly uncertain demand. Numerous factors are driving this phenomenon; however, a major change that is spreading among different sectors is the ever‐growing attention to customers. Companies have identified that customers are critical not only because they directly influence the success of specific products or firms, but also because they play a fundamental role in many internal processes. Although the role of customers in business processes has been deeply analysed, the issue of demand forecasting and the role of customers has not been fully explored. The present study aims to examine the impact of heterogeneity of customer requests on demand forecasting approaches, based on three action research cases. Based on the analysis of customer behaviour, an appropriate methodology for each case is designed based on clustering customers according to their demand patterns.

Objectives are achieved by means of three action research case studies, developed in cooperation with three different companies. The paper structures a general methodology based on these three experiences to help managers in better dealing with uncertain demand.

By means of proper analysis of customers' heterogeneity and by using simple statistical techniques such as cluster analysis, forecasting performance can significantly improve. In these terms, this work claims that focusing on customers' heterogeneity is a relevant topic both for practitioners and researchers.

The paper proposes some specific guidelines to forecast demand where customers' differences impact significantly on demand variability. In these terms, results are relevant for practitioners. Moreover, the paper claims that this issue should be better analysed in future researches and proposes some guidelines for future works.

The study here responds to the view that the crucial problem in strategic management (research) is firm heterogeneity – why firms adopt different strategies and structures, why heterogeneity persists, and why competitors perform differently. The present study applies complexity theory tenets and a “neo-configurational perspective” of Misangyi et al. (2016) in proposing complex antecedent conditions affecting complex outcome conditions. Rather than examining variable directional relationships using null hypotheses statistical tests, the study examines case-based conditions using somewhat precise outcome tests (SPOT). The complex outcome conditions include firms with high financial performances in declining markets and firms with low financial performances in growing markets – the study focuses on seemingly paradoxical outcomes. The study here examines firm strategies and outcomes for separate samples of cross-sectional data of manufacturing firms with headquarters in one of two nations: Finland (n = 820) and Hungary (n = 300). The study includes examining the predictive validities of the models. The study contributes conceptual advances of complex firm orientation configurations and complex firm performance capabilities configurations as mediating conditions between firmographics, firm resources, and the two final complex outcome conditions (high performance in declining markets and low performance in growing markets). The study contributes by showing how fuzzy-logic computing with words (Zadeh, 1966) advances strategic management research toward achieving requisite variety to overcome the theory-analytic mismatch pervasive currently in the discipline (Fiss, 2007, 2011) – thus, this study is a useful step toward solving the crucial problem of how to explain firm heterogeneity.

With the rise of service economy, many companies are attempting to gain a competitive advantage through service innovation. However, the existing research has not drawn consistent conclusions about the relationship between service innovation and firm performance. Hence, the purpose of this paper is to provide a quantitative review on the service innovation-performance relationship based on research findings reported in the extant literature.

Studies from 46 peer-reviewed articles were sampled and analyzed. A meta-analytic approach was adopted to conduct a quantitative review on the relationship between service innovation and firm performance, and the effects of any potential moderators were further explored.

The results found that service innovation has a significant positive impact on firm performance. Additionally, the relationship between service innovation and firm performance is influenced by measurement moderators (economic region and performance measurement), and contextual moderators (firm type, innovation type, customer factors and attitudes toward risk).

The meta-analysis has been used to explore the relationship between service innovation and firm performance, and the findings have contributed to the literature on service innovation, as well as providing future research directions.