Since 2019 humanity has been subjected to the perturbations of pandemic, economic disruption, war, civil unrest and changes in whole-Earth dynamics associated with a human-induced Anthropocene. Each perturbation is like a wave-front breaking on the shore of our historical ways of thinking and acting, increasingly unfit for our human circumstances. This challenge to humanity is not new. In 1970 the French term ‘problematique’ was coined to refer to a set of 49 interrelated global problems; the classic description of wicked and tame problems was published soon after, yet little progress has been made towards answering the question: what purposeful action will aid human flourishing, create and sustain a viable space for humanity, in our ongoing co-evolution with the Anthropocene-Biosphere? A case for innovation in our ways of knowing and doing is made based on arguments that our social world is constrained by: (i) explanations we accept that are no longer relevant to our circumstances; (ii) outdated historical institutions (in the institutional economics sense) that contribute as social technologies to a broader human created and ungoverned technosphere; (iii) inadequate theory-informed practices, or praxis, and (iv) governance-systems no longer adequate for purpose. Practitioners of knowledge science and systems science are urged to act reflexively to critically evaluate the traditions-of-understanding out of which they think and act.

Perceived quality is consumers’ subjective perceptions of a product’s attributes, which directly influences the overall evaluation of the product. Existing research has suggested that the perceived quality of attributes has an asymmetric effect on the overall evaluation, but limited research has been conducted on this asymmetric effect in the automobile industry and the moderating effect of sentiment. This paper investigates the asymmetric effect of perceived quality on overall evaluation using social media data from the automobile industry. First, the asymmetric effect of perceived quality on overall evaluation was identified for different attributes using penalty-reward contrast analysis (PRCA), and attribute classification was realized by calculating the IA index, i.e., Appearance is an excitement attribute and the remaining attributes are basic attributes. Second, the differences in the asymmetric effects of each attribute category were analyzed, and the basic attributes were found to have a greater effect on the overall evaluation, with a positive moderating effect of sentiment on the effect. This study contributes to perceived quality research as well as consumer evaluation research and provides manufacturers with a prioritization method for attribute improvement.

We study a project management problem where the prime contractor needs to outsource tasks to subcontractors with the required resources. Successful execution of the project requires proper coordination among the subcontractors, as well as contract design by the prime contractor to incentivize the subcontractors. By modeling the subcontractors’ coordination problem as a cooperative game, we develop a profit sharing scheme to facilitate the subcontractors’ cooperation. We consider two contract designs for the prime contractor: a uniform contract across all subcontractors, and a nonuniform one that customizes incentives for each subcontractor. We propose efficient algorithms to solve the implicit optimization problems for optimal contract parameters. Computational experiments show that the pooling effect of subcontractors’ cooperation mitigates the negative impact of poor estimates about the crashing cost and resource availability. We observe three unexpected results through the randomized computation experiments: (i) the subcontractors’ profits may decrease if they provide false information; (ii) it is safer for the prime contractor to overestimate subcontractors’ crashing costs than underestimate them; and (iii) uniform contracts deliver more project profit for the subcontractors in the coalitions.

While coupons that can be redeemed only in online channels have been issued by e-commerce platforms for decades, a new type of platform’s coupons, i.e., omnichannel coupons, which can be redeemed in both online and store channels, is gaining popularity with the rise of the omnichannel retail mode. It is interesting to explore the conditions under which omnichannel coupons are more advantageous to platforms and multichannel suppliers that sell products through platforms and physical stores. Two game models are developed in two cases where an e-commerce platform offers single channel coupons or omnichannel coupons for a multichannel supplier. Two scenarios are considered: one in which a consumer’s valuation of a product that fits his or her need is homogeneous and another in which the valuation is heterogeneous. Equilibrium outcomes show that under the homogeneous scenario, the product price and coupon face value in both coupon modes increase with the product’s fit probability when the cross-selling revenue is high, while decrease with the product’s fit probability when the cross-selling revenue is low. However, under the heterogeneous scenario, the price in both modes increases with the product’s fit probability only when the supplier’s loss from returns is low and the cross-selling revenue is high, and the coupon face value always decreases with the product’s fit probability. Compared with single channel coupons, omnichannel coupons may lead to a higher product price under certain conditions. Furthermore, omnichannel coupons can lead to higher total demand and benefit both the platform and the supplier if and only if the product’s fit probability is low and the supplier’s loss from returns is high. An extension shows that the platform’s preference for omnichannel coupons is weakened when the supplier offers a partial refund policy.

Based on the value function of the prospect theory, this paper constructs a security function, which is used to describe the victims’ feelings about the distance in emergency evacuation. Since different paths between the demand points and the emergency shelters are generally of different importance degrees, they are divided into main paths and auxiliary paths. The security function values and the reliability levels of main paths and auxiliary paths are given different weights. The weighted sum of the security function values and the weighted sum of the reliability level function values of all demand points are maximized to determine the location and the number of the emergency shelters, the transfer paths, the reinforced edges and the incremental reliability level of the selected edge. In order to solve the model, a two-stage simulated annealing-particle swarm optimization algorithm is proposed. In this algorithm, the particle swarm optimization (PSO) algorithm is embedded into the simulated annealing (SA) algorithm. The cumulative probability operator and the cost probability operator are formed to determine the evolution of the particles. Considering the budget constraint, the algorithm eliminates the shelter combinations that do not meet the constraint, which greatly saves the calculation time and improves the efficiency. The proposed algorithm is applied to a case, which verifies its feasibility and stability. The model and the algorithm of this paper provide a basis for emergency management departments to make the earthquake emergency planning.