Mobile　edge　computing　(MEC)　offers　low-latency　and　flexible　computing　services　for　mobile　devices　(MDs)　in　Industrial　Internet　of　Things　(IIoT).　Edge　servers　(ESs)　in　general　belong　to　different　subjects　and　will　focus　on　their　own　interests.　They　may　be　reluctant　to　provide　computation　resources　to　MDs　without　appropriate　incentives.　Meanwhile,　there　is　a　trust　issue　in　trading　computation　resources　between　ESs　and　MDs.　Due　to　the　complex　interaction　between　ESs　and　MDs,　it　is　a　challenge　for　ESs　to　gain　satisfactory　revenue　through　reasonable　resource　pricing　strategies,　and　for　MDs　to　improve　their　Quality　of　Experience　(QoE)　through　efficient　computation　offloading　strategies.　This　article　proposes　a　Stackelberg　game-based　computation　offloading　and　resource　pricing　scheme　(SGCS)　in　blockchain-enable　MEC　for　IIoT.　First,　a　blockchain-based　resource　trading　framework　is　designed　to　enable　trusted　resource　transactions.　Second,　a　multileader　multifollower　Stackelberg　game　is　presented　to　analyze　the　complex　interactions　in　the　multi-ES　and　multi-MD　environments.　Finally,　the　iterative　proximal　algorithm　(IPA)　for　MDs＇　offloading　decision　and　the　subgradient-based　iterative　pricing　algorithm　(SIPA)　for　ESs＇　pricing　decision　are　proposed,　respectively,　which　guarantees　that　the　game　converges　to　a　Stackelberg　equilibrium　(SE).　Compared　with　multiagent　deep　deterministic　policy　gradient,　genetic　algorithm　and　PSO-GA　(i.e.,　benchmark　strategies),　the　average　disutility　of　MDs　with　our　proposed　scheme　is　reduced　by　6.95%-13.07%,　3.09%-20.41%,　and　2.36%-17.22%,　respectively.　Moreover,　with　the　increase　of　the　number　of　MDs,　our　proposed　scheme　has　better　robustness,　which　can　effectively　deal　with　large-scale　scenarios.　©　2014　IEEE.