Intuitive Implications Research Articles

When job resources function as a stress buffer: A resource allocation perspective of the job demands-resources model

The extant literature has found highly mixed findings regarding the stress buffering effect of job resources. Drawing upon the resource allocation perspective, we argue that the buffering effect of job resources would emerge only when employees allocate the resources to wellbeing goal; when job resources are allocated to performance goal, they would no longer buffer the demand-strain relationship. We consider conscientiousness as a dispositional factor affecting resource allocation such that employees low in conscientiousness are more likely to allocate resources to wellbeing goal than to performance goal. In a sample of Chinese employees from high-tech industry (the mean age was 31.46, with 34.80% female), we found that job resources buffered the demand-strain relationship for employees low in conscientiousness. For those high in conscientiousness who tend to allocate more resources to performance goal, job resources did not affect the demand-strain relationship but strengthened the demand-performance relationship. This research makes a meaningful extension to the JD-R model and offers intuitive implications for organizations to manage job stress more effectively.

Pinning of diffusional patterns by non-uniform curvature

Diffusion-driven patterns appear on curved surfaces in many settings, initiated by unstable modes of an underlying Laplacian operator. On a flat surface or perfect sphere, the patterns are degenerate, reflecting translational/rotational symmetry. Deformations, e.g., by a bulge or indentation, break symmetry and can pin a pattern. We adapt methods of conformal mapping and perturbation theory to examine how curvature inhomogeneities select and pin patterns, and confirm the results numerically. The theory provides an analogy to quantum mechanics in a geometry-dependent potential and yields intuitive implications for cell membranes, tissues, thin films, and noise-induced quasipatterns.

To infinity and some glimpses of beyond

When mathematical and computational dynamic models reach infinity in finite time, extending analysis and numerics beyond it becomes a notorious challenge. We suggest how, upon suitable transformations, it may become possible to go beyond infinity with the solution becoming again well behaved and the computations continuing normally. In our Ordinary Differential Equation examples the crossing of infinity occurs instantaneously. For Partial Differential Equations, the crossing of infinity may persist for finite time, necessitating the introduction of buffer zones, within which an appropriate transformation is adaptively identified. Along the path of our analysis, we present a regularization process via complexification and explore its impact on the dynamics; we also discuss a set of compactification transformations and their intuitive implications. This methodology could be useful toward a systematic approach to bypassing infinity and thus going beyond it in a broader range of evolution equation models.

Normative reasons as good bases

In this paper, I defend a new theory of normative reasons called reasons as good bases (RGB), according to which a normative reason to φ is something that is a good basis for φing. The idea is that the grounds on which we do things—bases—can be better or worse as things of their kind, and a normative reason—a good reason—is something that is just a good instance of such a ground. After introducing RGB, I clarify what it is to be a good basis, and argue that RGB has various attractive features: it has intuitive implications, makes good sense of the weights of reasons, and attractively explains the relationship between normative reasons and motivating reasons. I then briefly defend the view from objections and compare it to rivals. Finally, I sketch two possible implications of RGB: some kind of constitutivism, according to which the norms that govern us are explained by the nature of agency, and second, the claim that agents who do things for reasons generally do them for good reasons.

Balanced harvesting in fisheries: a preliminary analysis of management implications‡

AbstractBalanced harvest (BH) proposes to distribute a moderate mortality from fishing across the widest possible range of species, stocks, and sizes in an ecosystem, in proportion to their natural productivity so that the relative size and species composition are maintained, in line with the CBD requirement for sustainable use. This proposal has many and not always intuitive implications for fisheries management, e.g. in relation to selectivity, protection of juveniles and spawning sites, models of harvesting strategies, a focus on size and species, the impacts of discarding, aspects of emblematic species and ecosystem services, operational complexity, partial implementation, ecosystem rebuilding, and relations with broader management frameworks. The paper closes with a discussion of BH implementation, concluding that a logical step would be to integrate several separate initiatives to move fisheries into a more ecosystem-conscious context. Implementation challenges will be encountered, but there are lessons to be drawn from fishery ecosystems already close to BH, as in some tropical multispecies fisheries, and further, the implementation challenges are already being taken on in many well-managed fisheries and areas as management begins to address the realities of what ecosystem-based fishery management actually entails.

Reply to Comments

First, He suggests that the assumption of fully rational, autarkic agents can be misleading in view of growing experimental evidence on the role played by social norms and reciprocity in human behavior. In particular, it is likely that, as, e.g., in Cantono and Silverberg (2009), consumers' willingness to pay (WTP) for green products is affected by the WTPs of their neighbors. Including peer effects in consumption would certainly have relevant implications for our analysis giving an active role both to local (i.e. spatial) and aggregate income inequality. The spatial distribution of agents endowed with different income levels would affect the distribution of preferences for a given aggregate level of inequality. In spite of its relevance, this extension would deliver quite intuitive implications. Consider, for sake of simplicity, two populations charac- terized by the same level of aggregate inequality and different levels of segregation by incomes, which is here a sufficient statistics for broader socio-economic conditions. It is clear then that the first population would display a stronger pioneer consumer effect, while the second a larger mass of potential adopters, i.e. larger market size effect. From a purely theoretical perspective, all our results for technology diffusion apply to this more general case. Relevant implications would emerge, instead, by allowing the government to intervene in both the sorting process and in the determination of the income distribution. However, such analysis would lack realism: policies explicitly affecting sorting are not feasible in market economies where the house market determines the level of segregation. Finally, the empirical evidence in support of peer effects in consumption is still scant, see footnote 4 in the paper, so this assump-

Robustness to incomplete information in repeated games

This paper extends the framework of Kajii and Morris (1997) to study the question of robustness to incomplete information in repeated games. We show that dynamically robust equilibria can be characterized using a one-shot robustness principle that extends the one-shot deviation principle. Using this result, we compute explicitly the set of dynamically robust equilibrium values in the repeated prisoners’ dilemma. We show that robustness requirements have sharp intuitive implications regarding when cooperation can be sustained, what strategies are best suited to sustain cooperation, and how changes in payoffs affect the sustainability of cooperation. We also show that a folk theorem in dynamically robust equilibria holds, but requires stronger identifiability conditions than the pairwise full rank condition of Fudenberg et al. (1994).

Statistical Detection of Defect Patterns Using Hough Transform

Surface defects on semiconductor wafers often exhibit particular spatial patterns. These patterns contain valuable information of the fabrication processes and can help engineers identify the potential root causes. In this paper, we present a control chart technique to detect spatial patterns of surface defects by using the Hough transform. An approximate distribution model of the monitoring statistic is proposed, and a comprehensive control chart design method is developed. This method is characterized by its intuitive implication and a simple design procedure which relates the statistical performance of the control chart to the design parameters. A case study is presented to validate the effectiveness of this method.

Automated merging of conflicting knowledge bases, using a consistent, majority-rule approach with knowledge-form maintenance

This paper discusses an automated process of merging conflicting information from disparate sources into a combined knowledge base. The algorithm provided generates a mathematically consistent, majority-rule merging by assigning weights to the various sources. The sources may be either conflicting portions of a single knowledge base or multiple knowledge bases. Particular attention is paid to maintaining the original rule format of the knowledge, while ensuring logical equivalence. This preservation of rule format keeps the knowledge in a more intuitive implication form as opposed to a collection of clauses with many possible logical roots. It also facilitates tracking using the support for each deductive result so that final knowledge in rule form can be ascribed back to original experts. As the approach is fairly involved mathematically, an automated procedure is developed.

Standard State-Space Models Preclude Unawareness

We show that a very broad class of models, including possibility correspondences, necessarily fail to capture very simple and intuitive implications of unawareness. We explain why standard state–space formulations suffer from this problem, illustrating the point with an example of a nonstandard state–space model which avoids the difficulty.

Technical Note—On the Asymptotic Convergence Rate of Cost Differences for Markovian Decision Processes

The modified method of successive approximations for solving Markovian decision problems as formulated by White, Schweitzer, MacQueen, and Odoni, concentrates attention on cost differences either between successive stages in the same state, or relative to a base state in the same stage, rather than on the total cost function. The former bound the (discounted) gain of the optimal policy, while the latter relative-cost function determines the policy to be chosen at each stage. While these authors have demonstrated that these modified constructs converge to the gain and the optimal relative-cost function under rather general circumstances (undiscounted, single-chain, aperiodic processes), little is known about the rates of convergence. [Note that convergence of the relative-cost function guarantees optimality of a currently repeating policy, as noted by Howard.) A great deal of insight into this mathematically difficult question may be gained by working out the actual asymptotic convergence rates of these constructs for the special case of a single fixed policy. This is an easy exercise via Howward's methods, but very suggestive, since the policy will be asymptotically constant for a well-behaved problem. (In particular, if there is a unique optimal policy it will eventually repeat.) Convergence for both constructs for the fixed-policy case is very powerful even for discount rates greater than 1.0, depending principally on the dominant eigenvalue of the transition matrix. This note discusses the intuitive implications of this fact for the relative efficiencies of modified value iteration, policy iteration, policy iteration via successive approximations, or possible hybrids.