Purpose “Relationship benefits” (RBs) is an approach in relationship marketing. The concept highlights that both customer and firm must receive benefits from the relationship to establish and maintain it. This study aims to identify the impacts of three types of RBs on creating four kinds of customer engagement value (CEVs). Design/methodology/approach This study synthesizes previous findings and proposes hypotheses with theoretical supports and reports results from a structural equation model that uses data gathered from 577 Iranian customers across a range of services- based on an extensive review of marketing literature related to RBs. Findings Confidence benefits are the strongest driver of customer lifetime value and customer influence value, while special treatment benefits are the strongest driver of customer knowledge value (CKV) and customer referral value. Social benefits only affect CKV. Research limitations/implications Future research should examine the role of other types of RBs in creating CEV, beyond the original three types of RBs. Originality/value There is no research addressing the impact of delivering RBs on CEV. This study combines RBs and CEV into a single model and demonstrates the roles of different types of RBs in creating CEV for service firms.

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PurposeGreen construction has begun implementing sustainable and environmentally friendly practices, but there has not yet been an assessment for green construction supply chain risks in the literature. Identification and assessment of potential risks will result in more appropriate risk mitigation strategies to overcome disruptions affecting higher performance. Thus, this study aims to identify green construction supply chain risks of residential mega-projects.Design/methodology/approachInterpretive structural modeling (ISM) provided a hierarchical model composed of seven layers that elucidated the driving influences between the elements. Matrice d’impacts croises-multiplication appliqúe an classement (MICMAC) analysis classified the elements into the driver, linkage and dependent variables based on their dependence and driving powers, providing a clearer understanding of risk factors and their influential characteristics. Using experts' knowledge and experience is compatible with the subjective nature of ‘supply chain risks’ and is more suitable while collecting pertinent quantitative data which is far more challenging.FindingsTenable output, using an international expert group, addressed key risk factors. Technical expertise and skilled labor, key customers, and corporate culture are found as elements with most driving power, and the final product and logistics coordination and supply chain configuration found as the most dependent risk factors. Managerial implications addressed the most fundamental risk sources and suggested practical proactive risk management approaches to maximize green supply chain performance.Originality/valueIdentified supply chain oriented key risk factors of the residential green mega projects add novelty to the context of green construction projects' supply chain management. And eliciting the influential relations of the key risk factors provide a bigger picture of key risks in green residential mega projects that can be extended by sub-risks related to process activities. Assessing supply chain risks' interactions in the context of green residential mega projects is a novel contribution to mega construction-project management's body of knowledge. Also, the key risk factors were categorized based on the characteristics known as driving power and dependence.

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