The importance of knowing the affective meaning of job demands revisited

This paper starts with the assumption that when people are asked to describe the level of demands they face at work, it cannot be assumed that those demands are necessarily stressful, even if they are rated as strong or high demands. Thirty demand questions were designed for use with a sample of 2,253 public sector employees in Western Australia. As well as rating frequency of demand the respondents were asked to rate their level of dissatisfaction with the demand. For only 16 of the demands was there a correlation high enough to assume that the demand might be a stressor. Having demonstrated this, the rest of the paper compares different ways of combining the two scores to predict the level of psychological distress as measured by the General Health Questionnaire (GHQ12). The results support the claim in the title, that it is important to know the affective meaning of job demands.     

Multi-item inventory model with quantity-dependent inventory costs and demand-dependent unit cost under imprecise objective and restrictions: A geometric programming approach

A multi-item inventory model with constant demand and infinite replenishment is developed under the restrictions on storage area, total average shortage cost and total average inventory investment cost. These restrictions may be precise or imprecise. Here, it is assumed that inventory costs are directly proportional to the respective quantities, and unit purchase/production cost is inversely related to the demand. Restricted shortages are allowed but fully backlogged. First, the problem is formulated in crisp environment taking the deterministic and precise inventory parameters. It is solved by both geometric programming (GP) and gradient-based non-linear programming (NLP) methods. Later, the problem is formulated with fuzzy goals on constraints and objectives where impreciseness is introduced through linear membership functions. It is solved using the fuzzy geometric programming (FGP) method. The inventory models are illustrated with numerical values and compared with the crisp results. A sensitivity analysis on the optimum order quantity and average cost is also presented due to the variation in the tolerance of total average inventory investment cost and total average shortage cost following Dutta et al., 1993, Fuzzy Sets and Systems, 55, 133-142.     

Nonparametric Bayesian Methods for Benchmark Dose Estimation

The article proposes and investigates the performance of two Bayesian nonparametric estimation procedures in the context of benchmark dose estimation in toxicological animal experiments. The methodology is illustrated using several existing animal dose‐response data sets and is compared with traditional parametric methods available in standard benchmark dose estimation software (BMDS), as well as with a published model‐averaging approach and a frequentist nonparametric approach. These comparisons together with simulation studies suggest that the nonparametric methods provide a lot of flexibility in terms of model fit and can be a very useful tool in benchmark dose estimation studies, especially when standard parametric models fail to fit to the data adequately.     

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.     

Evaluating Scholarship Productivity in COAMFTE‐Accredited Doctoral Programs: An Update

Scholarly productivity continues to be used as a significant factor when universities make decisions about granting tenure to faculty, allocating resources, and supporting program goals. In 2009, DuPree, White, Meredith, Ruddick, and Anderson reviewed research productivity in faculty from COAMFTE‐accredited PhD programs. As an update, the purpose of this article is to re‐examine scholarly productivity trends among COAMFTE‐accredited doctoral programs through the use of several evaluation methods. Specifically, productivity was examined in the following areas: (a) family therapy journal publications; (b) publications in any type of peer‐reviewed journal; (c) h‐factor index scores; and (d) historic and recent journal publication trends.     

A mixed-method exploration of functioning in Safe Schools/Healthy Students partnerships

This paper presents a mixed-method approach to measuring the functioning of Safe Schools/Healthy Students (SS/HS) Initiative partnerships. The SS/HS national evaluation team developed a survey to collect partners’ perceptions of functioning within SS/HS partnerships. Average partnership functioning scores were used to rank each site from lowest to highest. Sites with the most favorable perceptions of partnership functioning were defined as having average scores in the top 10% (n = 10) and sites with the least favorable perceptions of partnership functioning were defined as having average scores in the bottom 10% (n = 10). Qualitative data for these 20 sites were inductively open coded for emergent themes and analyzed for patterns using grounded theory approach. Six themes emerged that distinguished sites reporting the most favorable and least favorable perceptions of partnership functioning: partner engagement, facilitators, barriers, shared decision making, partnership structure, and sustainability. Sites reporting the most favorable perceptions of partnership functioning effectively utilized collaboration processes that facilitate coalition building, such as shared decision making, effective communication, and developing a clearly defined structure. Qualitative themes from this analysis provide evidence of validity for the partnership functioning scale used and illustrate distinguishing features between sites with the most favorable and least favorable perceptions of partnership functioning.     

Hierarchy of players in swap robust voting games

Ordinarily, the process of decision making by a committee through voting is modeled by a monotonic game the range of whose characteristic function is restricted to {0, 1}. The decision rule that governs the collective action of a voting body induces a hierarchy in the set of players in terms of the a-priori influence that the players have over the decision making process. In order to determine this hierarchy in a swap robust game, one has to either evaluate a power index (e.g., the Shapley–Shubik index, the Banzhaf–Coleman index) for each player or conduct a pairwise comparison between players, whereby a player i is ranked higher than another player j if there exists a coalition in which i is more desirable as a coalition partner than j. In this paper, we outline an alternative mechanism to determine the ranking of players in terms of their a-priori power. This simple and elegant method uses only minimal winning coalitions, rather than the entire set of winning coalitions.     

One-mode projection analysis and design of covert affiliation networks

Within the field of national security and counterterrorism a great need exists to understand covert organizations. To better understand these cellular structures we model and analyze these cells as a collection of subsets of all participants in the covert organization, i.e., as hypergraphs or affiliation networks. Such a covert affiliation network structure is analyzed by evaluating the one-mode projection of the corresponding hypergraph. First we provide a characterization of the total distance in the one-mode projection using its corresponding cell-shrunken version. Secondly we evaluate the one-mode projection with respect to the secrecy versus information tradeoff dilemma every covert organization has to solve. We present and analyze affiliation networks representing common covert organizational forms: star, path and semi-complete hypergraphs. In addition we evaluate an example of a covert organization wishing to conduct an attack and compare its performance to that of the common covert organizational forms. Finally we investigate affiliation networks that are optimal in the sense of balancing secrecy and information. We show how any affiliation tree can be improved by altering its structure. Finally we prove that among covert organizational forms in the class of hypertrees with the same number of cells uniform star affiliation networks are optimal.