Peter Öhman, professor i företagsekonomi, utvecklar en modell som stöttar fortbildning. Foto Torbjörn Bergkvist. Peter Öhman, professor i företagsekonomi och centrumledare vid Centrum för forskning och ekonomiska relationer, CER och är en av dem som initierat projektet.
– Vi startade detta som ett pilotprojekt med stöd av Vinnova. Vi vände oss först till företag inom bank och försäkring, eftersom vi hade ett uppbyggt nätverk där, men meningen är att modellen ska kunna användas av alla branscher, berättar
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