A doubly-inflated Poisson regression for correlated count data

Count data have emerged in many applied research areas. In recent years, there has been a considerable interest in models for count data. In modelling such data, it is common to face a large frequency of zeroes. The data are regarded as zero-inflated when the frequency of observed zeroes is larger than what is expected from a theoretical distribution such as Poisson distribution, as a standard model for analysing count data. Data analysis, using the simple Poisson model, may lead to over-dispersion. Several classes of different mixture models were proposed for handling zero-inflated data. But they do not apply to cases when inflated counts happen at some other points, in addition to zero. In these cases, a doubly-inflated Poisson model has been suggested which only be used for cross-sectional data and cannot consider correlations between observations. However, correlated count data have a large application, especially in the health and medical fields. The present study aims to introduce a Doubly-Inflated Poisson models with random effect for correlated doubly-inflated data. Then, the best performance of the proposed method is shown via different simulation scenarios. Finally, the proposed model is applied to a dental study.KEYWORDS: Count data, doubly-inflated, Poisson regression, zero-inflated, correlated data     

Divide and rule: The effects of diversity and network structure on a firm's sustainability performance

To tackle sustainability, firms often use partnerships with organizations from different industries or societal sectors such as government and civil society. While partnerships show potential for firms to improve their sustainability performance, they not only lead to a potential to learn from diversity but also to tensions due to a lack of unity between partners. In partnerships for sustainability, this unity-diversity tension particularly manifests itself in different views of sustainability. This paper examines how this tension affects the sustainability performance of firms taking part in partnerships for sustainability in developing countries. To address this question, this tension is conceptualized as being the result of differences in organizational frames and institutional logics between a focal firm and other organizations in the partnership. It is also taken into consideration that firms are embedded in an overarching, relational network structure that allows them to manage the diversity in frames and logics. To test the hypotheses, the study analyses 1353 greenhouse gas emission reduction projects of 322 firms from developing countries active in the carbon-offset market from 2007 to 2009. The findings show that if partners hold different frames and belong to different sectors, a firm's sustainability performance improves first due to learning from diversity but after a turning point decreases from a lack of unity. This inverse U-shape relationship is flipped if a firm occupies a brokerage position in its network.     

A change point method for Phase II monitoring of generalized linear profiles

In this article, we adopt the change point approach to monitor the generalized linear profiles in phase II Statistical process control (SPC). Generalized linear profiles include a large class of profiles defined in one framework. In contrast to the conventional change point approach, we adopt the Rao score test rather than the likelihood ratio test. Simulated results show that our approach has a good performance over any possible single step change in process parameters for two special cases of generalized linear profiles, namely Poisson and binomial profiles. Some diagnostic aids are also given and a real example is introduced to shed light on the merits of our approach in real applications.     

Hotelling’s T2 control chart with double warning lines

Recent studies have shown that the T ² control chart with variable sampling intervals (VSI) and/or variable sample sizes (VSS) detects process shifts faster than the traditional T ² chart. This article extends these studies for processes that are monitored with VSI and VSS using double warning lines (T ² —DWL). It is assumed that the length of time the process remains in control has exponential distribution. The properties of T ² —DWL chart are obtained using Markov chains. The results show that the T ² —DWL chart is quicker than VSI and/or VSS charts in detecting almost all shifts in the process mean.     

A unification and some corrections to Markov chain approaches to develop variable ratio sampling scheme control charts

We provide some unifying definitions, make some corrections to articles by Faraz and Parsian (J Stat Pap 47:569–593, 2006) and Costa (J Qual Technol 26:155–163, 1994; 29:197–204, 1997), and using these provide more accurate tables of results and comparisons of control charts. We also investigate the impact of an incorrectly specified process shift on signal frequency.     

Analysis of Local Decision Rules in a Dual-Kanban Flow Shop

A recent article reported the results of a study on the effects of two kanban policy variables—the length of withdrawal cycle and the type of priority rule—on average customer wait time and total inventory. This study extends that work by adding two kanban policy variables and two performance criteria. It reports the results of simulation experiments that were conducted to determine how four policy variables—withdrawal cycle, priority rule, status of waiting withdrawal kanbans, and number of kanbans influence four performance criteria—average customer wait-time, total inventory, and average number of full containers in the input and output stock points of stations. It was found that the information about waiting withdrawal kanbans in sequencing decisions results in the simultaneous improvement in two conflicting objectives—customer wait time and total inventory. Also, the effects of including the information regarding the status of waiting withdrawal kanbans on system performance are larger than the effects associated with the type of priority rule. The results provide insights into determining the level of each policy variable while fully considering the possible interactions among the variables and the levels of other policy variables to improve system performance. These insights allow for setting the levels of policy variables to make the improvement process smooth.     

Modeling the effectiveness of urban agriculture education courses

Urban Ecosystems - Urban agriculture can provide food security that is essential to sustainable development goals. Citizen education plays a vital role in urban agriculture formation. The present...