Research Article

A Hierarchical Innovation-Related Crowdsourcing Decision in Fast Fashion Industry

Table 1

Main notations used in this paper.

TypeNotationDefinition

SetsISet of garment makers or tasks,
JSet of designers or design solutions,
Set of designer’s (j) completion tasks
Set of stable parings,
ParametersCost of completion of task i by designer j
Expected payoff for the next task if designer j completes the present design task i
Duration of task i completed by designer j
Unit time cost of task i completed by designer j
Cost of completion of task I within the time limits by designer j
Anticipated payoff for the case in which a normal-goodwill garment maker will offer a low reward in the near future
Anticipated payoff for the case in which a normal-goodwill garment maker will offer a high reward in the near future
Anticipated payoff for the case in which a better-goodwill garment maker will offer a low reward in the near future
Anticipated payoff for the case in which a better-goodwill garment maker will offer a high reward in the near future
Benefit of garment maker i from designers (j) solution
Payment to the crowdsourcing platform by garment maker i
Estimated parameters
Earliest start time of designer j
Latest submission time required by garment maker i
Minimum utility obtained when garment maker i chooses designer j
Minimum utility obtained when designer j accomplishes task i
Decision variables if garment maker i and designer j match as a pairing, , otherwise
Reward for design solution i is selected by garment maker j
Auxiliary variablesTotal utility of designer j taking on task i
Total utility of garment maker i selecting the designers (j) solution
Total surpluses of designer j if he matches with garment maker i
Total surpluses of garment maker i if he matches with designer j