The rise of unstructured data (UD), propelled by novel technologies, is reshaping markets and the management of marketing activities. Yet these increased data remain mostly untapped by many firms, suggesting the potential for further research developments. The integrative framework proposed in this study addresses the nature of UD and pursues theoretical richness and computational advancements by integrating insights from other disciplines. This article makes three main contributions to the literature by (1) offering a unifying definition and conceptualization of UD in marketing; (2) bridging disjoint literature with an organizing framework that synthesizes various subsets of UD relevant for marketing management through an integrative review; and (3) identifying substantive, computational, and theoretical gaps in extant literature and ways to leverage interdisciplinary knowledge to advance marketing research by applying UD analyses to underdeveloped areas.

This study identifies a frontline mechanism comprising autonomy, cohesion, and feedback that helps explain when and why the simultaneous pursuit of quality and productivity orientations has positive or negative effects on unit revenue, efficiency, and customer satisfaction. An empirical test of the proposed framework using data from 423 employees in 30 strategic business units and longitudinal unit-level performance data indicates that frontline autonomy mediates the positive impact of productivity and quality orientations on unit revenue and customer satisfaction and their negative impact on unit efficiency. Feedback amplifies the influence of frontline autonomy by simultaneously enhancing its positive effect on satisfaction and its negative effect on efficiency. In contrast, unit cohesion strengthens the positive effect of frontline autonomy on revenue and customer satisfaction without augmenting its negative effect on unit efficiency. The results urge managers to shift their focus toward unit-level mechanisms to find clues for managing strategic dilemmas that stem from multiple goal pursuit in face-to-face service settings.

This study focuses on the dynamic process that governs the impact of market knowledge diffusion on innovation effort and its subsequent effect on firm performance. First, the author proposes that three aspects of market knowledge (knowledge level, knowledge change, and extent of shared knowledge about customers and competitors) influence innovation effort. In so doing, she explicitly models the dynamic process of competition, including heterogeneity in interdependence of innovation across competitors, firm-specific inertial tendency in innovation, and feedback effects reflected in satisfaction with past performance. Second, within a partial adjustment model of performance, the author studies the role of shared market knowledge and firm size in the translation of innovation effort into firm performance over time. She tests the conceptual framework with longitudinal quasi field experiments based on a Markstrat simulation exercise, including a main experiment and three validation studies. The results reveal a dynamic system in which some aspects of market knowledge diffusion propel innovation, whereas satisfaction with past performance hinders innovation effort. Furthermore, the results show that innovation effort, by itself, does not affect firm performance. In the context of the study, total shared market knowledge helps smaller firms actualize better returns from their innovation effort than larger firms.

Adopting a frontline employee (FLE) perspective, this study models a performance loss process during an organization's strategic change implementation. The process is activated by changes in unit management's emphases on cost containment and revenue-generating strategies and is governed by FLE detachment. The authors also examine an intervention mechanism for mitigating performance loss by including the influence of FLE participation in change decisions. The model is tested with data from five service organizations that employ 843 FLEs. The results indicate that (1) FLE detachment is effective in separating out the negative and positive effects of change, (2) FLE change perceptions are sensitive to the focus of strategic change (cost containment versus revenue enhancement strategies), and (3) FLE participation significantly enhances the positive effects of change and mitigates performance loss. Change is fundamental to a modern business organization as a means to keep up with evolving market demands and to stay competitive (Day 1994). However, implementing strategic change is a double-edged sword because it simultaneously generates expected performance gain and unexpected performance loss (Brown 2005;Kennedy, Goolsby, and Arnould 2003;Simester et al. 2000). When unexpected performance loss dominates or drains away expected performance gain, change becomes ineffective. Moreover, the coexistence of performance gain and loss is likely to yield confounded evidence for strategic change outcomes. Organizations may fail to maximize the performance benefits of strategic change because they either do not detect the presence of performance loss or fail to diagnose and mitigate the loss. It is not surprising that extant research provides evidence of equivocal effects of change that are either positive (e.g., Siguaw, Brown, and Widing 1994) or negative (e.g., Harris and Ogbonna 2000). To our knowledge, no study has offered a theoretical or empirical approach for identifying and isolating performance loss during strategic change implementation.To realize the performance benefits of strategic change, an organization must detect and diagnose performance loss in change implementation. This requires identifying a mediating process that is activated by change implementation and results only in performance decrements, which we refer to here as the "performance loss mechanism." This definition has two implications. First, this mediating mechanism acts as a pathway for performance loss and allows for the partialing out of performance gain as the direct pathway from change implementation to performance. Second, it emphasizes and captures a useful distinction between performance loss as an outcome (how much is the loss?) and performance loss as a mechanism (why did loss occur?). Making such a distinction allows for a diagnosis of the loss. To our knowledge, prior research has neither explicitly examined performance loss pathways nor conceptualized performance loss as an outcome-process duality.Diagnosing performance loss allows for con...