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Performance feedback can be constructed using firms’ own (historical) performance, or the performance of peers (social). Those two types of performance feedback can be consistent (both positive, both negative) or inconsistent (one positive, the other negative). The research on the impact of consistent versus inconsistent feedback has been inconclusive, suggesting that inconsistent feedback might lead to more intense or less intense responses, or no response. In this paper, we theorize and test how firms respond to (in)consistent performance feedback.

We test our hypotheses on a longitudinal sample of 2,819 private, high-growth firms in the US with 6,688 observations between the years 2007 and 2016. Our dataset comprises 25 different industries. We use topic modeling on textual data from firms’ web pages to capture portfolio expansion.

We find that consistent negative performance feedback strengthens portfolio expansion, but consistent positive feedback does not influence portfolio expansion. We also find that inconsistent performance feedback weakens portfolio expansion, but only with negative historical feedback and positive social feedback.

We contribute to the Behavioral Theory of the Firm by improving our understanding of mechanisms of feedback configurations. Specifically, we elaborate on the role of (in)consistent social feedback when firms respond to historical performance feedback. We also contribute to the theory by better understanding private firms’ responses to performance feedback.

The United Nations member countries adopted a set of 17 sustainable development goals (SDGs) to achieve a better and more sustainable future for all. It encourages the use of sustainable practices during new product development (NPD). Competitiveness has put pressure on organizations to maintain their market share and look for new approaches related to NPD. The current study aims to focus on creating a framework that can help to achieve the SDGs by adopting agile new product development (ANPD) practices and Industry 4.0 technologies.

From the literature, various ANPD practices, Industry 4.0 technologies, performance metrics, their interconnection and their contribution toward achieving SDGs are extracted. The weights of selected Industry 4.0–ANPD practices are computed by robust best worst method (RBWM), and the Fuzzy-VIKOR method is used to rank the selected performance metrics. To test the robustness of the developed framework, sensitivity analysis is also performed.

The results show that among the various Industry 4.0–ANPD practices “Multi-skilled employees” have the highest weight followed by “Customer requirement analysis and prioritization.” Whereas for performance metrics, “The number of innovative products launched per year” is ranked first, with the “Average time between two launches” at second place.

This research contributes to the adoption of ANPD practices and Industry 4.0 technologies for the achievement of the business SDGs. The shortlisted Industry 4.0–ANPD practices will help in resolving the social and environmental issues. The set of performance metrics will help practitioners and managers to evaluate the performance of ANPD in the context of business SDGs.

This study adds to the understanding related to Industry 4.0–ANPD practices adoption. And to the best of the authors’ knowledge, it is believed that no similar work has been done previously and by using industry insights into technology components, this work contributes to valuable insights into the subject.