With　the　rapid　development　of　new　technology,　robots　are　increasingly　being　introduced　into　decision-making　such　that　people　can　receive　advice　from　them.　Decision-making　involves　many　variables,　which　should　be　investigated　together.　In　the　current　study,　we　explored　human-robot　interaction　in　decision-making　from　the　perspectives　of　confidence,　trust,　decision　change,　and　reciprocity.　We　also　investigated　the　effects　of　robot　ability,　task　complexity,　and　risk　on　human-robot　interaction　in　decision-making.　We　conducted　an　experiment　where　participants　received　advice　from　robots　in　a　length　judgment　task,　for　which　the　participants　had　to　select　the　longest　line　among　eight　lines.　The　results　showed　that　participants　had　higher　trust　and　confidence　when　receiving　advice　from　high-ability　robots.　However,　the　participants　had　less　confidence,　reduced　trust　in　the　robots,　a　lower　tendency　to　change　their　decision,　and　shared　more　losses　with　robots　during　complex　tasks.　They　placed　less　trust　in　the　robots　and　shared　fewer　benefits　with　them　in　a　high-risk　condition.　Additionally,　the　participants’　self-construal　was　significantly　correlated　with　trust　and　gender　was　significantly　correlated　with　confidence,　benefits　shared　with　the　robot,　and　decision　change.　These　findings　can　aid　researchers　and　designers　in　the　development　of　service　robots.　©　2021　Informa　UK　Limited,　trading　as　Taylor　&　Francis　Group　and　The　Robotics　Society　of　Japan.