THE EXPERIENCE OF FLOW IN COMPUTER-MEDIATED AND IN FACE-TO-FACE GROUPS

This paper proposes that optimal flow, based on a cognitive theory of human motivation provides a useful measure of individuals\u27 experiences as they participate in group work. Individuals\u27 experiences of flow, a state of being characterized by involvement in and enjoyment of a task, were determined to be significantly greater in computer-mediated groups than in face-to-face groups. Variables associated with flow included perceived control, task challenge, and required skill during a problem-solving activity performed by fifty-nine undergraduate business students in both settings. The level of skill was found to be positively linked with perceived control in both face-to-face and computer-mediated groups. Perceived control in turn, was positively linked with the flow experience in both groups. Results indicate that while skill is important in explaining flow in the face-to-face task, the perceived challenge is important in explaining flow in the computer-mediated task. Suggestions are offered for future research on flow and computer-supported collaborative work

The multi-stripe travelling salesman problem

In the classical Travelling Salesman Problem (TSP), the objective function sums the costs for travelling from one city to the next city along the tour. In the q-stripe TSP with q ≥ 1, the objective function sums the costs for travelling from one city to each of the next q cities along the tour. The resulting q-stripe TSP generalizes the TSP and forms a special case of the quadratic assignment problem. We analyze the computational complexity of the q-stripe TSP for various classes of specially structured distance matrices. We derive NP-hardness results as well as polyomially solvable cases. One of our main results generalizes a well-known theorem of Kalmanson from the classical TSP to the q-stripe TSP