Modelling Resource Allocation in a Decentralized Organization with an AI-Based,Goal-Directive Model*

Modelling the resource allocation decision process in a decentralized organization using mathematical programming decomposition approaches has proven intractable for all but the smallest of problems. In this paper three artificial intelligence (AI) techniques are integrated to model the resource allocation decision process, and the solution for a three-level decentralized organization is illustrated. The techniques are (1) the filtered beam search, which selects a list of potential projects at the subordinate level, (2) the world model, which describes the ordinate and superordinate's worlds and their decision-making processes, and (3) the blackboard model, which allows for global, but selective, storage of information. Benefits of the new approach include: several different mechanisms of managerial control may be modelled, the true information flow in an organization is more closely mirrored, and problems of a more realistic size are now viable. There are three primary ways in which the new model could be useful to management: The desirability and effects of different organizational structures can be modeled, the efficacy of various coordination mechanisms along the organizational structure can be examined, and a subset of projects from a wider list of possibilities can be selected. Also, an example is given showing how the model may be extended to scenarios with asymetric information and divergence of preferences, whereby subordinates have different objectives than their managers and where there is no way for managers to verify the truthfulness of their subordinates' responses.     

Family Therapy: Inner,Outer and the Issue of Pathology

This paper sets out to examine the relationship between ‘the inner’, ‘the outer’, and ‘the issue of pathology’ in the family therapy field. It begins with the observations that ‘pathology’ has become a rarely mentioned issue in family therapy, and ‘what is wrong’ is increasingly located in ‘the outer’: the family ‘game’, ‘linguistic activity’ or ‘the cultural discourse’. At the same time, family therapy often hosts forums in which presenters are ‘attacked’ for not seeming to hold the ‘correct view’. The paper considers these phenomena in tandem, looks at the matter of ‘method’, and applies James Hillman's critique of psychoanalysis to family therapy. The suggestion is that family therapy has been blinded by its own metaphor of ‘seeing’, symbolised and literalised in the one way screen. Alternative metaphors privileging intuition, feeling and aesthetics are put forward, before discussion points are raised, and before this paper on therapy concludes poetically, or this paper concludes that therapy may be poetry.     

Queer theory, late capitalism, and internalized homophobia

The emergence of queer theory represents a transformation in the approach to lesbian, gay, bisexual and transgendered peoples. It has claimed new ground for treating sexuality and gender as worthy subjects in their own rights, rather than offshoots of gay and lesbian studies or of general cultural theory. The author contends, however, that it is doubtful that this approach can lead to social change. Queer theory has dismissed the usefulness of the disciplines that were the foundation of the social movements that initiated gay and lesbian studies, such as political economy, and in doing so, it has surreptitiously mirrored the social relations of reproduction that constitute late capitalism. This mirroring has had unseen consequences for the individual in society, and with queer theory's insistence on the relativity of experience and the dismissal of identity, has set the stage for a benign reinforcement of internalized homophobia. The author argues that this approach can be mediated by recognizing that identity is fluid, and that by focusing on identifying with social movements rather than centering analyses on the problems associated with identifying as a particular category of status and being, we can refocus our energies on the building and maintenance of mutual support and collective recognition that can lead to resolving the stagnation now dominating attempts to develop coalitions around issues that matter.     

County child poverty rates in the US: a spatial regression approach

We apply methods of exploratory spatial data analysis (ESDA) and spatial regression analysis to examine intercounty variation in child poverty rates in the US. Such spatial analyses are important because regression models that exclude explicit specification of spatial effects, when they exist, can lead to inaccurate inferences about predictor variables. Using county-level data for 1990, we re-examine earlier published results [Friedman and Lichter (Popul Res Policy Rev 17:91–109, 1998)]. We find that formal tests for spatial autocorrelation among county child poverty rates confirm and quantify what is obvious from simple maps of such rates: the risk of a child living in poverty is not (spatially) a randomly distributed risk at the county level. Explicit acknowledgment of spatial effects in an explanatory regression model improves considerably the earlier published regression results, which did not take account of spatial autocorrelation. These improvements include: (1) the shifting of “wrong sign” parameters in the direction originally hypothesized by the authors, (2) a reduction of residual squared error, and (3) the elimination of any substantive residual spatial autocorrelation. While not without its own problems and some remaining ambiguities, this reanalysis is a convincing demonstration of the need for demographers and other social scientists to examine spatial autocorrelation in their data and to explicitly correct for spatial externalities, if indicated, when performing multiple regression analyses on variables that are spatially referenced. Substantively, the analysis improves the estimates of the joint effects of place-influences and family-influences on child poverty.

Time Insensitivity for Protective Investments

Investments in protective measures involve an initial immediate cost in exchange for a stream of potential benefits accruing over time in the form of reduced expected losses. This paper describes two studies in which individuals were asked both to make choices and indicate the maximum amount they were willing to pay (WTP) for such protective measures. By varying the number of years that the measures provided protection, we observed four different decision strategies that individuals use to determine their maximum WTP. The findings from these experiments strongly suggest that most individuals do not take into account the added benefits of having a protective measure in place over a longer period of time when determining the likelihood of purchasing protection or the maximum price they are willing to pay. The behavior of a relatively small proportion of the subjects was consistent with a discounted utility model. Most subjects were either myopic in their behavior or did not change their maximum WTP as the time horizon changed. Despite the fact that most subjects were insensitive to time changes, they were generally willing to purchase the protective measures. Implications of these results for investment in risk mitigation measures are briefly explored.     

A Bayesian-loss function-based method in assessing loss caused by ship-source oil spills in the arctic area

It is difficult to assess the risk of ship-source oil spills in Arctic waters for insurance purposes due to many unknowns and the lack of reliable data. However, maritime activities in the Arctic area continue to grow, indicating the urgent needs for the development of innovative methods to estimate loss from potential ship-source oil spills in the Arctic area. To fill this gap, we develop a hybrid Bayesian-loss function-based method to assess ship-source oil spill-related loss and implement an illustrative test on Baffin Island, Nunavut in Canada. The results confirm that our method can accurately assess loss and, subsequently, develop reliable insurance premiums for shipping activities in the Arctic area. This enables governmental and nongovernmental organizations alike to use the method as a reliable loss estimation mechanism for ship-source oil spills. Also, it is a valuable tool in designing measures for safer and more resilient Arctic shipping.     

Implementing the right project structure to achieve coopetitive innovation projects

This research focuses on the project structure used by coopetitors to achieve common innovation projects. Scholars have recently identified an original but complex project structure that they call the Coopetitive Project Team (CPT). However, other project structures can also be implemented by coopetitors to achieve innovation. Therefore, we address the following question: for which types of innovation projects is CPT appropriate? We argue that coopetitors need to use CPT for high-risk and high-cost projects when the aim is to develop radical innovation. CPT allows coopetitors not only to develop innovation capabilities through close resource and knowledge sharing but also to manage the risk of opportunism. Conversely, coopetitors should use another project structure, Separated Project Teams (SPTs), for low-cost and low-risk projects when the aim is to develop incremental innovation. The SPT design allows coopetitors both to achieve the goal of the project and to minimize the risk of opportunism. To confirm our assumptions, we studied the project portfolios of Airbus and Thales, two firms in the space satellite industry. Our findings confirm that coopetitors should implement CPTs to handle innovation projects that are costly, risky and highly innovative. CPTs permit the sharing of knowledge and the management of high opportunism risk, both of which are necessary to achieve radical innovation. Conversely, coopetitors rely on SPTs for low-cost projects that require a low degree of knowledge sharing, thus avoiding the risk of opportunism in achieving their incremental innovation objectives.     

Job-related diversity: the comprehensiveness and speed of board decision-making processes—an upper echelons approach

Strategic decision-making processes influence firm-level outcomes. Using the theory of upper echelons, this study investigates how diversity in directors’ skills, knowledge, and industry experience influence board decision-making processes that may impact overall strategic decision-making processes. Such diversity has been commonly accepted to be a ‘double-edged sword’—enhancing comprehensiveness but hindering the speed of decision-making. On the contrary, we used an existing large survey database to show that directors’ diverse educational background, functional background, and industry experience (job-related diversity) have a positive effect on comprehensiveness as well as the speed of board decision-making. In addition, our results indicate that board processes (directors’ use of their knowledge and skills) play an important role by transmitting the positive effects of diversity. The study is in a tradition of exploring how boards may influence firms’ strategic decision-making processes. Our findings provide additional arguments for adding job-related diversity to boards of directors.