Double Entry For Sale Of Accounting System in PHP

In recent years, an increasing number of studies have attempted to extract information from journals that cannot be conveyed in financial statements. Journals are valuable assets that enhance corporate value and companies’ competitiveness because they contain abundant information about past transactions. However, only a few studies have quantitatively clarified the value of double-entry bookkeeping and journals. Therefore, finding useful business knowledge in journals is currently difficult for managers and administrators. This study focuses on cross-reference information, which is unique to double-entry bookkeeping and not included in financial statements and trial balances. We then created new features to enhance the explanatory power of future business performance from journals. To achieve this objective, we constructed a graph based on journals, in which cross-reference is represented as edges. We create features unique to journal entry using two methods: network metrics and feature generation by node embedding. Finally, we tested for Granger causality using a vector autoregressive model constructed from created feature and performance. Our experiment showed that we successfully identified Granger causality within the unique features of double-entry journals for all five performance indicators of seven companies. Practitioners can use the identified features to build an alert system for sudden performance declines and facilitate understanding of their business. Future research will be necessary to verify the significance of double-entry bookkeeping and journal entries.