Bruce Cooil

Organizational noncompliance with legal rules can be consequential. The antecedents of such noncompliance as well as the remediation of it thus remain enduring subjects of research inquiry. However, prior studies have implicitly treated all rules alike. In contrast, we argue that rules are not all the same and that differences between rules might be systematically linked to variations in the likelihoods of noncompliance and remediation across the range of organizations under the purview of a rule system. We consider the role of two fundamental but distinct sources of rule complexity: components (i.e., sections that compose a rule) and connections (i.e., functional links to other rules in the same system). We analyzed data from 81,266 rule-level observations from 1,011 health inspections of 289 restaurants in Santa Monica, California, conducted from 2007 to 2010. As hypothesized, increases in either source of rule complexity were associated with higher probabilities of noncompliance. Unexpectedly, however, the two sources of rule complexity had divergent effects on remediation such that increases in the number of connections were associated with higher probabilities of repeated noncompliance, whereas increases in the number of components were not. Taken together, we suggest that our understanding of noncompliance and remediation can be enhanced by viewing them both as rule-level phenomena. A range of implications for theory and practice are discussed.

Purpose: – There is general agreement among researchers and practitioners that satisfaction is relative to competitive alternatives. Nonetheless, researchers and managers have not treated satisfaction as a relative construct. The result has been weak relationships between satisfaction and share of wallet in the literature, and challenges by managers as to whether satisfaction is a useful predictor of customer behavior and business outcomes. The purpose of this paper is to explore the best approach for linking satisfaction to share of wallet.Design/methodology/approach: – Using data from 79,543 consumers who provided 258,743 observations regarding the brands that they use (over 650 brands) covering 20 industries from 15 countries, various models such as the Wallet Allocation Rule (WAR), Zipf-AE, and Zipf-PM, truncated geometric model, generalization of the WAR and hierarchical regression models are compared to each other.Findings: – The results indicate that the relationship between satisfaction and share of wallet is primarily driven by the relative fulfillment customers perceive from the various brands that they use (as gauged by their relative ranked satisfaction level), and not the absolute level of satisfaction.Practical implications: – The findings provide practical insight into several easy-to-use approaches that researchers and managers can apply to improve the strength of the relationship between satisfaction and share of wallet.Originality/value: – This research provides support to the small number of studies that point to the superiority of using relative metrics, and encourages the adoption of relative satisfaction metrics by the academic community.

Context: Prior research has found that safety organizing behaviors of registered nurses (RNs) positively impact patient safety. However, little research exists on how engaging in safety organizing affects caregivers. Objectives: While we know that organizational processes can have divergent effects on organizational and employee outcomes, little research exists on the effects of pursuing highly reliable performance through safety organizing on caregivers. Specifically, we examined whether, and the conditions under which, safety organizing affects RN emotional exhaustion and nursing unit turnover rates. Subjects: Subjects included 1352 RNs in 50 intensive care, internal medicine, labor, and surgery nursing units in 3 Midwestern acute-care hospitals who completed questionnaires between August and December 2011 and 50 Nurse Managers from the units who completed questionnaires in December 2012. Research Design: Cross-sectional analyses of RN emotional exhaustion linked to survey data on safety organizing and hospital incident reporting system data on adverse event rates for the year before survey administration. Cross-sectional analysis of unit-level RN turnover rates for the year following the administration of the survey linked to survey data on safety organizing. Results: Multilevel regression analysis indicated that safety organizing was negatively associated with RN emotional exhaustion on units with higher rates of adverse events and positively associated with RN emotional exhaustion with lower rates of adverse events. Tobit regression analyses indicated that safety organizing was associated with lower unit level of turnover rates over time. Conclusions: Safety organizing is beneficial to caregivers in multiple ways, especially on nursing units with high levels of adverse events and over time.

Purpose: – This study aims to provide the first longitudinal examination of the relationship between affective, calculative, normative commitment and customer loyalty by using longitudinal panel survey data.Design/methodology/approach: – Repeated measures for 269 customers of a large financial services provider are employed. Two types of segmentation methods are compared: predefined classes and latent class models and predictive power of different models contrasted.Findings: – The results reveal that the impact that different dimensions of commitment have on share development varies across segments. A two-segment latent class model and a managerially relevant predefined two-segment customer model are identified. In addition, the results demonstrate the benefits of using panel survey data in models that are designed to study how loyalty develops over time.Practical implications: – This study illustrates the benefits of including both baseline level information and changes in the dimensions of commitment in models that try to understand how loyalty unfolds over time. It also demonstrates how managers can be misled by assuming that everyone will react to commitment improvement efforts similarly. This study also shows how different segmentation schemes can be employed and reveals that the most sophisticated ones are not necessarily the best.Originality/value: – This research provides the first examination of models for change in customer loyalty by employing survey panel data on the three-component model of customer commitment (affective, calculative, and normative) and considers alternative segmentation methods.

Electronic recommendation agents provide a way for online marketers to gather information about consumer preferences and assess the quality of consumer decisions. Much of the literature on recommendation agents, however, employs divergent measures to assess consumer decision quality. Moreover, decision quality measures are dictated by the type of agent employed. This article provides a review of the decision quality measures used in the recommendation agent research to date and proposes novel measures. We classify and examine the assumptions of–and relationships among–preference-dependent, preference-independent, and subjective measures of decision quality. The analysis of data from an experiment that simulates a broad spectrum of recommendation agents shows that the relative utility and the sum of attribute values of the chosen alternative capture the majority of variance in objective decision quality. Although subjective decision quality measures turn out to be poor proxies for objective measures, they provide important incremental information. Managerial implications for deploying electronic recommendation agents to gather information and measure consumer decision quality under different conditions are discussed.

Adoption of new services in the marketplace, and the impact that word of mouth (WOM) has on adoption, has long been of interest to marketers. Managers have therefore become increasingly interested in measuring WOM activity most commonly through the recommend intention metric. The circumstances under which the predictive ability of this metric can be established, however, are not clear. This research provides the first longitudinal examination of the relationship bet ween recommend intention and the adoption of a new-to-market service (NTMS) brand extension. Analysis is conducted using anonymized data provided by a large U.S. telecommunications provider for 791 customers and their corresponding telephone network (11,552 individuals). The findings indicate an interaction effect where recommend intention predicts new service adoption only when the recommending customers are more recent adopters of the service and are in more frequent contact with the potential customer. Therefore, when managers are using the recommend intention metric to predict adoption, there is a need to take into consideration the exposure of the individual to others in their network and the timing of their adoption.

Purpose – This research aims to investigate the moderating influence of both multichannel and multicompany usage on the impact that customer satisfaction has on share of wallet (SOW). Design/methodology/approach – The data used in the analyses were collected as part of both survey and transactional data of 802 households of a large financial services provider. Within class regression models were employed to test the moderating effects of different segments that were identified based on multichannel-multicompany customer differences. Findings – The findings confirm that using multiple channels has an overall positive moderating impact on the satisfaction-SOW link and that customer satisfaction matters more when the customer adopts multiple channels; online channel usage in addition to offline usage. Furthermore, this effect is even more pronounced for customers that transact with multiple providers. That is, the group of customers that use both the company's and competitors' offline and online channels reveal a higher satisfaction-SOW association than the group of customers that only adopted the offline channel with the company and competitor. Originality/value – This study broadens the understanding of multichannel behavior by comparing single (offline) and multiple channels (offline and online) for customers of multiple companies (two competitors).