This paper develops a multicriteria analysis method for effectively making the selection decision on information systems (IS) projects for project management in organizations from a sustainability perspective. The triple bottom line principle of sustainability in organizations is carefully considered in formulating the IS project selection process as a multicriteria analysis problem. The subjectiveness of the decision-making process is modelled by linguistic variables approximated by fuzzy numbers. The positive and the negative ideal solution concepts are used to calculate the overall sustainability performance of individual IS projects in a comprehensive manner. A decision support system framework is then constructed with the use of the developed method for facilitating the IS project selection process. Such a system can provide organizations with an effective mechanism for comprehensively evaluating available IS projects from a sustainability perspective. An example is presented for demonstrating the flexibility and effectiveness of the proposed method in solving the IS project selection problem.

General Strain Theory delineates different types of strain and intervening processes from strain to deviance and crime. In addition to explaining individual strain-crime relationship, a contextualized version of general strain theory, which is called the Macro General Strain Theory, has been used to analyze how aggregate variables influence aggregate and individual deviance and crime. Using a sample of 1,852 students (Level 1) nested in 52 schools (Level 2), the current study tests the Macro General Strain Theory using Chinese data. The results revealed that aggregate life stress and strain have influences on aggregate and individual deviance, and reinforce the individual stress-deviance association. The current study contributes by providing the first Macro General Strain Theory test based on Chinese data and offering empirical evidence for the multilevel intervening processes from strain to deviance. Limitations and future research directions are discussed.

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This paper investigates a coordinated inventory and pricing problem with the e-retailer's price-protection service over multiple periods. By solving a stochastic dynamic programming in the two-dimensional state space, the optimal policy is fully characterized. Specifically, the inventory policy is a previous price-dependent base-stock policy. The pricing policy: as the previous price increases, the optimal current price stays unchanged first, then increases, and finally decreases. Numerical results indicate that with the impact of the price-protection service increasing, the base-stock level and current price rise under some conditions. Moreover, the price-protection service benefits the e-retailer when its impact is large enough.

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