A strategic performance measurement system for firms across supply and demand chains on the analogy of ecological succession

To answer the call for a new business that integrates economic, biological and human systems, this paper develops a strategic performance measurement system (SPMS) for firms across supply and demand chains (SDC) by analogy with ecological succession. Based on the explanation that SDC can be viewed as community, it develops SDC (monetary value) structure by analogy with community (trophic) structure. As energy flow in ecology follows the first and second laws of thermodynamics, monetary value flow in business follows two laws that are similar to the laws of thermodynamics. Based on these laws, as well as throughput accounting and traditional cost accounting, it puts forward a general monetary value flow model in SDC (i.e. in demand chain and in supply chain respectively). Based on the value flow model in SDC, it conceives an SDC evolution model with a case study on the maturity of Toyota Motor Corporation. Based on these two models, it develops an SPMS for firms across SDC with procedural and structural frameworks. The discussion about monetary value flows in business from nature to the final consumers or converse gives a chance to coordinate business with nature. The SPMS that rationally integrates effective evaluation of tiers in SDC and practical product development plans in firm will help firms create a sustainable commerce (e.g. product–service system).     

Evaluating the SDC Mergers and Acquisitions Database

We compare 20 years of data from Thompson Financial SDC Platinum (SDC)'s Mergers and Acquisitions database with a hand‐collected database, providing evidence on the completeness and accuracy of SDC data across time. We find that our hand‐collected data is generally more accurate than SDC, but SDC's accuracy and coverage improves over time. Our investigation of discrepancies between the databases finds that SDC is more prone to errors on smaller, high book‐to‐market acquirers with weak announcement period market responses. Preliminary analyses suggest that this potential bias is not significant, but could affect inferences when examining smaller, high book‐to‐market firms.