PurposeThe current market conditions are driving firms to plan, design and implement corporate social responsibility (CSR) policies that are true to the firms' real sense, i.e. authentic. Authenticity is an important aspect of micro-foundations of CSR in shaping the way social responsibility initiatives would impact the stakeholders including the customers, partners, current members of the organization and shareholders. This calls for a need to synthesize past research on CSR authenticity in order to propose directions for future research.Design/methodology/approachThe current study synthesizes relevant literature on CSR authenticity using systematic literature review (SLR) approach. In total, 34 research works were identified and examined to seek insights on CSR authenticity.FindingsFindings of the study identified various miro-, meso- and macro-level determinants of CSR authenticity and different set of outcomes having implications on business and society. The study also proposes a comprehensive definition of CSR authenticity which was somewhat missing in existing literature.Practical implicationsThe study provides strong theoretical and managerial implications. Particularly, the study provides directions for future research on the topic.Originality/valueIn this paper, a review of literature on CSR authenticity is currently missing.

PurposeThis study investigates a production process that requires N kinds of components for the production of a finished product. The producer orders the various kinds of components from different suppliers and receives the orders in lots at the beginning of each production cycle. Similar to situations often encountered in real life, the lead times are random variables with known probability distributions so that a production cycle starts whenever all N kinds of components become available. Each of the lots received at the start of a production run contains both perfect and imperfect quality components. Once all N kinds of components become available, the producer initiates a screening process to detect the imperfect components. The production of the finished product uses only perfect quality components. The imperfect components are removed from inventory whenever the screening process is completed. The percentage of components of perfect quality present in each lot is a random variable with a known probability distribution.Design/methodology/approachThis production process is described and modeled mathematically and the optimal production/ordering policy is derived based on the mathematical model.FindingsThe formulated mathematical model resulted in the determination of the optimal policy consisting of the optimal number of finished items ordered to be produce during each production run, the number of components ordered from each supplier, and the reorder point. The derived closed form expression for the optimal lot size depends on the minimum of the number of perfect quality components in a lot, whereas the reorder point is determined based on the maximum lead time.Practical implicationsThe modeling approach and results of this study provide practical implications that may be beneficial to both production and supply chain managers as well as researchers.Originality/valueThis modeling approach that incorporates decision-making related to the logistics of acquiring the components and accounts for the probabilistic nature of the lead times and quality of components addresses a gap in the logistics/production literature.

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