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Purpose The purpose of this paper is to study how repeat customers utilize their established overall restaurant brand image (ORBI), overall restaurant loyalty, satisfaction and behavioral intentions (revisit, recommend) to reengage with a casual-dining restaurant brand. Design/methodology/approach The study design consists of a mixed-methods, two-phase research approach that includes both qualitative and quantitative data. First, focus groups and in-depth interviews with adult customers reveal preliminary insights on restaurant dining patterns and familiarity with franchised casual dining restaurants. Second, an online self-administered survey tests the influence of ORBI on repeat customers’ overall restaurant loyalty, satisfaction and behavioral intentions. Findings For repeat customers, ORBI positively predicts loyalty and satisfaction. Loyalty and satisfaction mediate the relationship between ORBI and intentions to recommend, while loyalty alone mediates the relationship between ORBI and intentions to revisit a casual dining restaurant. Practical implications Managers looking to stimulate recommendation intentions can increase ORBI, loyalty or satisfaction among repeat customers; or choose some combination of these three predictors. To improve revisit intentions, managers should first increase loyalty, followed by ORBI. Importantly, management needs to tailor information given to repeat customers differently than other customers. Originality/value This paper provides a first conceptualization of how both loyalty and satisfaction jointly mediate the relationships between ORBI and two behavioral intentions (revisit, recommend). The results show that loyalty plays a significant role in these predictive relationships and is more important than satisfaction for enhancing intentions to revisit a restaurant.

Purpose The purpose of this paper is to explore the processing of product returns at five case companies using a complex adaptive systems (CAS) logic to identify agent interactions, organization, schema, learning and the emergence of adaptations in the reverse supply chain. Design/methodology/approach Using a multiple-case study design, this research applies abductive reasoning to examine data from in-depth, semi-structured interviews and direct researcher observations collected during site visits at case companies. Findings Costly or high-risk returns may require agents to specialize the depth of their mental schema. Processing agents need freedom to interact, self-organize and learn from other agents to generate emergent ideas and adapt. Practical implications Limiting the depth of individual agent schema allows managers to better allocate labor to processing product returns during peak volume. To boost adaptability, managers need to craft a dynamic environment that encourages agents with diverse schema to interact, anticipate, and self-organize to brainstorm new ideas. Managers need to resist the urge to “control” the dynamic environment that ensues. Originality/value This paper builds on existing research that studies the key decision points in the analysis of product returns by exploring how processing-agent behaviors can create adaptability in the reverse supply chain. Additionally, this research follows in the tradition of Choi et al. (2001) and Surana et al. (2005) and proposes the application of CAS to a specific part of the supply chain – the processing of product returns.

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