A Partial Taxonomy of Substitutability and Interchangeability

Substitutability, interchangeability and related concepts in Constraint Programming were introduced approximately twenty years ago and have given rise to considerable subsequent research. We survey this work, classify, and relate the different concepts, and indicate directions for future work, in particular with respect to making connections with research into symmetry breaking. This paper is a condensed version of a larger work in progress.Comment: 18 pages, The 10th International Workshop on Symmetry in Constraint Satisfaction Problems (SymCon'10

The Effects Of Self-Directed Teams In An Automotive Manufacturing Environment

ABSTRACT THE EFFECTS OF SELF DIRECTED TEAMS IN AN AUTOMOTIVE MANUFACTURING ENVIRONMENT by DAVID W. SHALL December 2010 Advisor: James L. Moseley, EdD, LPC, CHES, CPT Major: Instructional Technology Degree: Doctor of Philosophy This study compares self-directed work structures to more traditional supervised work structures in order to determine if the expenditures and efforts required to implement self-directed work teams are warranted. Multiple internal performance metrics are examined in comparing plant work structures in various degrees of implementation between traditional work structures and self-directed work teams. The researcher collected data from multiple organizations within Ford Motor Company and four participating North American Ford production plants. Two Ford assembly plants and two Ford engine manufacturing plants were researched. Performance data from the 2004 production year were examined in each facility. Both assembly plants built the same Ford F-150 pick-up truck and both engine manufacturing plants produced the same V-6 engine in 2004. Data were collected to answer several questions including: 1) Does the presence of effectively rated self-directed work teams affect injury frequency; 2) Does the presence of effectively rated self-directed work teams affect injury severity; 3) Does the presence of effectively rated self-directed work teams affect unexcused absenteeism; 4) Does the presence of effectively rated self-directed work teams affect productivity; 5) Does the presence of effectively rated self-directed work teams affect cost performance; 6) Does the presence of effectively rated self-directed work teams affect external quality and customer satisfaction; 7) Does the presence of effectively rated self-directed work teams affect internal engine manufacturing quality; 8) Are Safety LTR, Safety SV, AWOL, Productivity, and Cost statistically significant predictors of customer satisfaction and, 9) Are Safety LTR, Safety SV, AWOL, Productivity, and Cost statistically significant predictors of work team effectiveness. By comparing the performance metrics and customer satisfaction data between like plants with separate and different work structures, the researcher isolated the impact that work structures have on safety, cost, productivity, quality and employee morale. The hypothesis in this research suggests that significant performance differences exist between effectively rated self-directed work teams and more traditionally supervised work groups in automotive assembly and engine manufacturing plants. Furthermore the hypothesis suggests that dependent performance variables predict customer satisfaction and work team efficiency. Several statistical procedures were used to answer the nine research questions which ranged from basic to theoretically experimental procedures. First, causal comparisons were drawn between plants with effectively rated self-directed work teams and plants with more traditionally supervised work structures to explore the relationship that the dependent performance metrics have with the independent work structures. Multivariate analysis of covariance was used to simultaneously test correlation between two independent predictor variables and several dependent variables. Second, a Hybrid Structural Equation Model (SEM) was utilized to further test and predict relationships between dependent and independent variables, but also within the dependent performance metrics. The technique allowed confirmatory and exploratory modeling to reveal the magnitude of performance variable interrelationships and predict their potential impact on customer satisfaction and work group efficiency. Statistical techniques increasingly dissected data with the goal of answering each research question with error-free statistical results. Many inferences can be made from the analysis of descriptive statistics in this research, most of which indicate favorable performance results in plants with effective self-directed work teams over plants with more traditional work forces. The basic assumptions are challenged statistically with multivariate test of covariance, univariate tests, pair-wise comparisons, test of moderation, Z-tests and a hybrid structural equation model. Pair-wise comparisons reveal five significant results in truck assembly plants. Effectively rated self-directed teams in Norfolk significantly outperformed their more traditionally supervised rivals in Kansas City in lost time case rate, severity rate and controllable employee absence. Furthermore, all of the effects are positive in nature and justify the effort required to implement self directed teams. Oppositely, in engine manufacturing plants, the more traditional workforce in Cleveland outperformed effectively rated self directed teams in Lima in terms of cost and customer satisfaction. Both findings were statistically significant and demonstrate adverse effects since improvements in work team effectiveness resulted in higher costs and lower customer satisfaction. Tests of moderation and subsequent Z tests for truck assembly plants support four significant findings. In Kansas City work team effectiveness had explanatory power for lost time case rate and severity rate although the predictive nature of work team effectiveness on lost time case rate and severity rate are adverse since both rates increased. Z tests reveal significant differences in the regression lines for employee absenteeism and customer satisfaction. Results for absenteeism show mixed predictions where the traditional workforce in Kansas City experience favorable reductions in absence while self-directed work teams in Norfolk experience increased absence as work team effectiveness improved. The Z test for customer satisfaction reveal promise for self-directed work teams in both truck assembly plants since quality defects decrease as work team effectiveness improves. Tests of moderation and subsequent Z tests for engine manufacturing plants support four significant findings. In Cleveland work team effectiveness demonstrates explanatory power for severity rate, cost and engine manufacturing quality. Work team effectiveness demonstrates positive predictive power over severity rate and engine manufacturing quality since injury severity and quality defects decrease as work team effectiveness improves. Conversely, cost predictably increases as work team effectiveness improves. Z tests revealed significant differences in the regression lines for employee absenteeism and engine manufacturing quality. Absenteeism results display mixed predictions where the traditional workforce in Cleveland anticipate an unfavorable increase in absence while self-directed work teams in Lima anticipate absence reductions as work team effectiveness improves. The Z test for engine manufacturing quality flaunted positive predictions for self-directed work teams in both engine manufacturing plants. As work team efficiency improves, engine quality defects are minimized. The two final research questions asked if the dependent performance variables in the study were statistically significant predictors of customer satisfaction and work team effectiveness. Beta Coefficients from the Hybrid Structural Equation Model estimated that three variables influenced performance including safety lost time case rate, safety severity rate and productivity. The multivariable interaction of these dependent variables resulted in a statistical prediction that positive internal performance affects customer satisfaction but not work team effectiveness ratings. This work adds relevant research findings to the body of literature in human performance improvement and instructional technology. Individuals contemplating an intervention involving teams or a work structure change are well served using this dissertation as a resource. To the extent possible the research follows Ford Motor Company\u27s path along the human performance technology (HPT) model (Van Tiem, Moseley, Dessinger, 2004) that is endorsed by the International Society for Performance Improvement

2022 Review of Data-Driven Plasma Science

Data-driven science and technology offer transformative tools and methods to science. This review article highlights the latest development and progress in the interdisciplinary field of data-driven plasma science (DDPS), i.e., plasma science whose progress is driven strongly by data and data analyses. Plasma is considered to be the most ubiquitous form of observable matter in the universe. Data associated with plasmas can, therefore, cover extremely large spatial and temporal scales, and often provide essential information for other scientific disciplines. Thanks to the latest technological developments, plasma experiments, observations, and computation now produce a large amount of data that can no longer be analyzed or interpreted manually. This trend now necessitates a highly sophisticated use of high-performance computers for data analyses, making artificial intelligence and machine learning vital components of DDPS. This article contains seven primary sections, in addition to the introduction and summary. Following an overview of fundamental data-driven science, five other sections cover widely studied topics of plasma science and technologies, i.e., basic plasma physics and laboratory experiments, magnetic confinement fusion, inertial confinement fusion and high-energy-density physics, space and astronomical plasmas, and plasma technologies for industrial and other applications. The final section before the summary discusses plasma-related databases that could significantly contribute to DDPS. Each primary section starts with a brief introduction to the topic, discusses the state-of-the-art developments in the use of data and/or data-scientific approaches, and presents the summary and outlook. Despite the recent impressive signs of progress, the DDPS is still in its infancy. This article attempts to offer a broad perspective on the development of this field and identify where further innovations are required

Differential effects of frontline employee feedback seeking behaviour towards customers in relational exchanges

The primary purpose of this research is to study the effects of frontline employee (FLE) feedback seeking behaviour (FSB) towards customers on customer relationship quality (with the FLE vs the firm) and performance measures as distal outcomes. While previous FSB studies have focused on peers and supervisors as targets, this study proposes a new conceptualisation of FSB similar to Gong et al.’s (2017) typology; along foci (self and firm) and valence (positive and negative) where customers are the target of the FLE’s FSB. Preliminary studies confirm the validity of the newly developed feedback seeking constructs. The main study uses hierarchical linear modelling to analyse survey data from 246 banking customers nested in 62 private banking reps across 47 branches of 13 of the largest commercial banks in Nigeria. The main study results show differential effects of the FSB types on customer relationship quality with the FLE vs the firm based on how FLEs frame FSB. In summary, the results show that the FLE’s positive (negative) feedback seeking behaviour is positively (negatively) related to the customer’s relationship quality with the FLE and the firm owing to mere measurement effects. The results also show moderating effects of customer and selling orientation on the relationship between firm FSB and customer relationship quality. Additionally, word of mouth was found to be a deterrent to the inherent risk of losing customers that stay loyal to their service reps should they defect to competing firms

The Prolific and other Priority Offender programme: in search of collaborative public management

The purpose of the research was to assess the implementation and management of the Prolific and Priority Offender (PPO) programme, examining the barriers to and enabling factors for managing in partnership, whilst evaluating the settlement between three management models. The research provides evidence for a newer model of management, better suited to deliver on the shared outcomes government requires from its public programmes. Research has shown that although crime is multi-causal, a range of agencies separately intervene into service users’ lives. Collaborative Public Management joins up these interventions to improve crime reduction

Redefining Strategic Corporate Social Responsibility (CSR) in the Sustainable Development Goals (SDGs) World

In a paradigm characterized by unprecedented levels of transparency and business risks, CSR reporting standards have gained substantial power in their ability to drive organizations towards more sustainable business practices. With the advent of the United Nations’ Sustainable Development Goals (SDGs), corporate sustainability discourse has progressed to a point where sustainability became critical to the success of firms. This dissertation explores the changes in the CSR domain post the introduction of the SDGs in 2015. The SDGs provide a robust framework for strategic CSR given their objective 17 goals along with 169 sub-goals and 232 indicators, which represent a comprehensive agenda for sustainable development. This dissertation explores the changes in the reporting practices by analyzing more than 14 thousand reports provided by 9,397 organizations to test a set of hypotheses that identify the factors that influence SDGs reporting within firms. Additionally, this dissertation highlights current gaps and challenges in the contemporary CSR domain and sheds light on the latest practices of CSR communication, such as the use of social media sites as platforms for CSR and SDGs reporting. We introduce a novel approach using social media analytics to analyze how corporations communicate about SDGs on social media, namely Twitter. The dissertation also highlights the current initiatives towards the standardization of reporting frameworks. Findings from this research contribute to strategic CSR literature by highlighting the nature of reporting per sector, and how organizations report on the SDGs that are related to their core operations. The results of the dissertation also contribute to legitimacy theory by identifying how and why corporations address the SDGs in their strategic CSR reporting. Finally, the dissertation provides a set of recommendations that can help improve strategic CSR reporting in the SDGs era

A novel computer aided engineering method for comparative evaluation of nonlinear structures in the conceptual design phase

Selection of the preferred design concept during design represents a major challenge to design engineers as the required level of information and rigour to achieve an objective evaluation at early stage of design is typically not available. This is particularly evident during evaluation of design concepts of complex load-bearing mechanical structures. The engineering design concepts during concept design phase typically lack detail and more specific performance indicators to enable accurate evaluation. Hence in such cases, a prevailing evaluation approach is based primarily on qualitative scores inferred through personal intuition and historical experience of the design team or individual experts. The principal motivation behind this research is to improve the ability and confidence to select a superior design concept early in the design process. The conventional approach is sensitive to individual expertise and availability of experienced designers. Therefore, in order to make more informed decisions especially in case of complex engineering designs, the concept evaluation methods require more detailed and accurate information. This research is concerned with the development of a novel method for comparative evaluation of engineering design concepts that exhibit nonlinear structural behaviour under load. The approach is based on two key concepts: i) an expansion of the conventional substructuring technique into the nonlinear domain to enable FEA to be more applicable, effective and computationally affordable in early stages of the conceptual design phase; and ii) a restructuring of the traditional process by incorporating the optimisation search to provide orderly rule-guided evolution of design concepts in order to produce objective development metrics which alleviates the dependence on personal intuition and historical experience of the engineering designers. A series of experiments and validation case studies conducted in this research provide conclusive evidence that demonstrates the applicability and the significance of the developed method in terms of reduced time for evaluation and amount of recurrent knowledge generated compared to the more traditional approaches based on the application of FEA in the conceptual design phase. Furthermore, a Confidence Index as a performance measure is developed in this research to describe the quality of the obtained solutions. The derived Confidence Index is a novel contribution to the fields of metaheuristic measurements and engineering concept validation methodology

Understandings, indicators, and implications of enhanced adaptive capacity within agricultural development interventions in Northern Ghana

Enhanced adaptive capacity is increasingly being pursued as an objective of agricultural development interventions due to the perceived vulnerability of smallholder farming communities to a range of shocks and stresses. This research used two case studies of agricultural development interventions in Northern Ghana to examine diverse understandings of adaptive capacity, potential indicators of enhanced adaptive capacity, and the implications of this for sustainable agricultural livelihoods. The thesis reviews relevant theoretical literature to situate the study among complex adaptive systems thinking and sustainability discourses. Associated policy documentation is reviewed to set the context in which, and identify why, development interventions seek to enhance adaptive capacity. The primary methods of data collection were interviews, focus groups, and ethnography, as well as secondary data in the form of documentation from the case studies. Multiple understandings of adaptive capacity were identified in both case studies, including ‘formal’ understandings of the projects’ funders and management, and ‘informal’ understandings of field staff and participating farmers. The findings contribute to theory, policy and practice through explicit recognition of the diversity of understandings of adaptive capacity, which has not been appreciated or analysed previously. Indicators of enhanced adaptive capacity emerged from the findings. Findings show how features of social capital were integral to enhanced adaptive capacity and played a dominant role in beneficial outcomes, even when not the priority of the interventions. This implies a set of indicators of enhanced adaptive capacity that can inform theoretical discourse, policy and programme planning, and monitoring and evaluation in practice. Finally, this research identified the role of social capital in contributing to enhanced adaptive capacity, which supports sustainable agricultural livelihoods. These findings contribute lessons for similar ongoing and future agricultural development interventions and recommend a focus on features of social capital rather than physical and technological capital