Basic coset geometries

In earlier work we gave a characterisation of pregeometries which are ‘basic’ (that is, admit no ‘non-degenerate’ quotients) relative to two different kinds of quotient operation, namely taking imprimitive quotients and normal quotients. Each basic geometry was shown to involve a faithful group action, which is primitive or quasiprimitive, respectively, on the set of elements of each type. For each O’Nan-Scott type of primitive group, we construct a new infinite family of geometries, which are thick and of unbounded rank, and which admit a flag-transitive automorphism group acting faithfully on the set of elements of each type as a primitive group of the given O’Nan-Scott type.     

Metrics for bullwhip effect analysis

A bullwhip measurement system based on a two-criterion assessment—‘internal process efficiency’ and ‘customer service level’—is developed in this paper. The framework is designed to assess both individual (single member) and systemic (whole supply chain) performances. Data collection and calculation methods, update and monitoring mechanisms, as well as related procedures for each metric used, are detailed. A comparative analysis with a recent work by Barlas and Gunduz is performed, showing that the adoption of the proposed performance measurement system can help academics and practitioners to better understand, study and avoid the bullwhip effect. Such analysis also provides evidence on the relevance of considering when analysing the bullwhip effect in supply chains, the ‘customer importance’ aspect that is often forgotten in the published literature.     

Operational complexity and supplier–customer integration: case study insights and complexity rebound

The main contribution of this paper is the demonstration that, contrary to conventional thinking, a measurable increase in the operational complexity of the production scheduling function between two companies can occur following closer supply chain integration. The paper presents the practical application of previous work carried out and validated by the authors in terms of (a) methodology for measuring operational complexity, (b) predicted implications of Supplier–Customer integration and (c) derivation of an operational complexity measure applied to before and after Supplier–Customer integration. This application is illustrated via a longitudinal case study. The analysis is based on information theory, whereby operational complexity of a Supplier–Customer system is defined as the amount of information required to describe the state of this system. The results show that operational complexity can increase when companies decide to integrate more closely, which is a fact likely to be overlooked when making decisions to pursue closer Supply-Chain integration. In this study, operational complexity increases due to reduced buffering arising from reduction in the Supplier's inventory capacity. The Customer did not change their operational practices to improve their schedule adherence post-integration, and, consequently, suffered an increase in complexity due to complexity rebound. Both the Supplier's and Customer's decision-making processes after the case study reported in this paper were enhanced by being able to quantify the complex areas to prioritise and direct managerial efforts towards them, through the use of the operational complexity measure. Future work could extend this study (in the ‘low product customisation’ and ‘low product value impact’ quadrant) to investigate Supplier–Customer integration in other quadrants resulting from further combinations between ‘product customisation’ and ‘product value impact’ levels.     

Observing mathematical fluency through students’ oral responses

‘Procedural’ fluency in mathematics is often judged solely on numerical representations. ‘Mathematical’ fluency incorporates explaining and justifying as well as producing correct numerical solutions. To observe mathematical fluency, representations additional to a student’s numerical work should be considered. This paper presents analysis of students’ oral responses. Findings suggested oral responses are important vantage points from which to view fluency – particularly characteristics harder to notice through numerical work such as reasoning. Students’ oral responses were particularly important when students’ written (language) responses were absent/inconsistent. Findings also revealed the importance of everyday language alongside technical terms for observing reasoning as a fluency characteristic. Students used high modality verbs and language features, such as connectives, to explain concepts and justify their thinking. The results of this study purport that to gain a fuller picture of students’ fluency, specifically their explanations or reasoning, students’ oral responses should be analyzed, not simply numerical work.     

The impact of instructor pedagogy on college calculus students’ attitude toward mathematics

College calculus teaches students important mathematical concepts and skills. The course also has a substantial impact on students’ attitude toward mathematics, affecting their career aspirations and desires to take more mathematics. This national US study of 3103 students at 123 colleges and universities tracks changes in students’ attitudes toward mathematics during a ‘mainstream’ calculus course while controlling for student backgrounds. The attitude measure combines students’ self-ratings of their mathematics confidence, interest in, and enjoyment of mathematics. Three major kinds of instructor pedagogy, identified through the factor analysis of 61 student-reported variables, are investigated for impact on student attitude as follows: (1) instructors who employ generally accepted ‘good teaching’ practices (e.g. clarity in presentation and answering questions, useful homework, fair exams, help outside of class) are found to have the most positive impact, particularly with students who began with a weaker initial attitude. (2) Use of educational ‘technology’ (e.g. graphing calculators, for demonstrations, in homework), on average, is found to have no impact on attitudes, except when used by graduate student instructors, which negatively affects students’ attitudes towards mathematics. (3) ‘Ambitious teaching’ (e.g. group work, word problems, ‘flipped’ reading, student explanations of thinking) has a small negative impact on student attitudes, while being a relatively more constructive influence only on students who already enjoyed a positive attitude toward mathematics and in classrooms with a large number of students. This study provides support for efforts to improve calculus teaching through the training of faculty and graduate students to use traditional ‘good teaching’ practices through professional development workshops and courses. As currently implemented, technology and ambitious pedagogical practices, while no doubt effective in certain classrooms, do not appear to have a reliable, positive impact on student attitudes toward mathematics.     

Towards improving the utilization of university teaching space

There is a perception that teaching space in universities is a rather scarce resource. However, some studies have revealed that in many institutions it is actually chronically under-used. Often, rooms are occupied only half the time, and even when in use they are often only half full. This is usually measured by the ‘utilization’ which is defined as the percentage of available ‘seat-hours’ that are employed. Within real institutions, studies have shown that this utilization can often take values as low as 20–40%. One consequence of such a low level of utilization is that space managers are under pressure to make more efficient use of the available teaching space. However, better management is hampered because there does not appear to be a good understanding within space management (near-term planning) of why this happens. This is accompanied, within space planning (long-term planning) by a lack of experise on how best to accommodate the expected low utilizations. This motivates our two main goals: (i) To understand the factors that drive down utilizations, (ii) To set up methods to provide better space planning. Here, we provide quantitative evidence that constraints arising from timetabling and location requirements easily have the potential to explain the low utilizations seen in reality. Furthermore, on considering the decision question ‘Can this given set of courses all be allocated in the available teaching space?’ we find that the answer depends on the associated utilization in a way that exhibits threshold behaviour: There is a sharp division between regions in which the answer is ‘almost always yes’ and those of ‘almost always no’. Through analysis and understanding of the space of potential solutions, our work suggests that better use of space within universities will come about through an understanding of the effects of timetabling constraints and when it is statistically likely that it will be possible for a set of courses to be allocated to a particular space. The results presented here provide a firm foundation for university managers to take decisions on how space should be managed and planned for more effectively. Our multi-criteria approach and new methodology together provide new insight into the interaction between the course timetabling problem and the crucial issue of space planning.     

Budget and long-range planning in public transportation — An applicative linear programming model

Economic and financial planning is an actual problem for Italian Transport Authorities, since in Italy there are scarce financial resources, to cover either the difference between costs and fares proceeds or investment needs. The proposed model is ‘just tailored’ on public transport, subjected to the Italian laws; it takes into account the particular activities (‘functions’) connected with public transport operating (e.g.: fare collection, service production, maintenance, purchases, inventories, administration). Each function is considered as a ‘module’ with its own constraints, and it is connected with the other ‘modules’, so that we can get a ‘representative’ model. Also the most significant parameters of the ‘public transport operating problem’ (e.g.: vehicle miles, passenger journeys, number of vehicles, number of employees, and so on) are connected one another. Since all relations and constraints, connecting the ‘problem variables’ can be represented as linear, the model structure is based on linear programming; this fact allows to pursue an optimum for one or more objective functions, each of them identifing an operational policy. So it is possible to connect simulation with optimization. A multi-period model can be used for long-range planning, pursuing a multi-year optimum; this is the most significant use. The Administrative Module contains Balance-Sheet, Cash-Flow, Profit and Loss Account, which are ‘constraints’ in the model and are expressed as Italian financial laws require; this structure is one of the main characteristics. Modules' dimensions and additional constraints (e.g. economic or financial ratios, fare level, turnover of inventories, and so on) can be ‘tailored’ on each particular case, driving the model towards more realistic solutions.     

Relative deprivation as a cause of risky behaviors

ABSTRACT

Combining a standard measure of concern about low relative wealth and a standard measure of relative risk aversion leads to a novel explanation of variation in risk-taking behavior identified and documented by social psychologists and economists. We obtain two results: (1) Holding individual i’s wealth and his rank in the wealth distribution constant, the individual’s relative risk aversion decreases when he becomes more relatively deprived as a result of an increase in the average wealth of the individuals who are wealthier than he is. (2) If relative deprivation enters the individual’s utility function approximately linearly then, holding constant individual i’s wealth and the average wealth of the individuals who are wealthier than he is, the individual’s relative risk aversion decreases when he becomes more relatively deprived as a result of a decline in his rank. Our findings provide a theoretical support for evidence about the propensity of relatively deprived individuals to gamble and resort to other risky behaviors.     

Dynamic programming in cricket: optimizing batting order for a sticky wicket

In cricket, a rain-affected pitch can make batting more difficult than normal. Several other conditions such as poor light or an initially lively pitch, may also result in difficulties for the batsmen. In this note, we refer to all of them as ‘sticky wickets’. On sticky wickets, lower order batsmen are often sent into ‘hold the fort’ until conditions improve. In this paper, a stochastic dynamic programming model is used to examine the appropriateness of this policy. The model suggests that the tactic is often optimal when the sticky wicket persists until the end of the day's play, but not often when the sticky wicket is transitory. In some circumstances, it is worthwhile, on a normal wicket near the end of the day, to send in a lower order batsman to hold the fort (a night watchman): when the wicket is sticky, this tactic is even more worthwhile.     

Leibniz’s Logic and the “Cube of Opposition”

After giving a short summary of the traditional theory of the syllogism, it is shown how the square of opposition reappears in the much more powerful concept logic of Leibniz (1646–1716). Within Leibniz’s algebra of concepts (which may be regarded as an “intensional” counterpart of the extensional Boolean algebra of sets), the categorical forms are formalized straightforwardly by means of the relation of concept-containment plus the operator of concept-negation as ‘S contains P’ and ‘S contains Not-P’, ‘S doesn’t contain P’ and ‘S doesn’t contain Not-P’, respectively. Next we consider Leibniz’s version of the so-called Quantification of the Predicate which consists in the introduction of four additional forms ‘Every S is every P’, ‘Some S is every P’, ‘Every S isn’t some P’, and ‘Some S isn’t some P’. Given the logical interpretation suggested by Leibniz, these unorthodox propositions also form a Square of Opposition which, when added to the traditional Square, yields a “Cube of Opposition”. Finally it is shown that besides the categorical forms, also the non-categorical forms can be formalized within an extension of Leibniz’s logic where “indefinite concepts” X, Y, Z\({\ldots}\) function as quantifiers and where individual concepts are introduced as maximally consistent concepts.     

Regularizing Portfolio Risk Analysis: A Bayesian Approach

It is important for a portfolio manager to estimate and analyze portfolio volatility, to keep the portfolio’s risk within limit. Though the number of financial instruments in the portfolio can be very large, sometimes more than thousands, daily returns considered for analysis are only for a month or even less. In this case rank of portfolio covariance matrix is less than full, hence solution is not unique. It is typically known as the “ill-posed” problem. In this paper we discuss a Bayesian approach to regularize the problem. One of the additional advantages of this approach is to analyze the source of risk by estimating the probability of positive ‘conditional contribution to total risk’ (CCTR). Each source’s CCTR would sum up to the portfolio’s total volatility risk. Existing methods only estimate CCTR of a source, and does not estimate the probability of CCTR to be significantly greater (or less) than zero. This paper presents Bayesian methodology to do so. We propose a simple Monte Carlo (MC) approach to achieve our objective, which can be paralleled. Estimation of various risk measures, such as Value at Risk and Expected Shortfall, becomes a by-product of this Monte-Carlo approach.     

Multivariate analysis using ‘and’ and ‘or’

The connectives ‘and’ and ‘or’ are potentially useful in multivariate analysis and theory construction. They are simple, logical ways to connect two or more variables together. However, until recently there has been no framework for operationalizing these connectives for continuous variables, and this lack has severely limited their use. Using fuzzy set theory as a basis for such a framework, this paper lays out the necessary tools and models to permit the use of ‘and’ and ‘or’ in multivariate analysis.Section 1 introduces conventional operators for ‘and’ and ‘or’, and Section 2 provides suitable extensions and generalizations of them. Section 3 sets out the required least-squares techniques for fitting these generalized operators to data, first in the context of ANOVA problems and then in regression contexts, for single-connective (three-variable) models. The theoretical developments and examples from real data-sets demonstrate the utility of ‘and’ and ‘or’ as a means to cell-specific interpretations of interaction effects which can also readily be translated into English. Section 4 extends these developments to multivariate, multiple-connective models and discusses issues of generalizability. The paper concludes (Section 5) with a brief discussion of remaining unsolved problems, future prospects for more sophisticated models, and computer programs.     

Inequity aversion in a joint economic lot sizing environment with asymmetric holding cost information

Screening contracts (or ‘menu of contracts’) are frequently used for aligning the incentives in supply chains with private information. In this context, it is assumed that all supply chain parties are strictly (expected) profit-maximizing. However, previous empirical work shows that this is a critical assumption. In fact, it seems that inequity adverse subjects are willing to invest money for achieving higher relative payoffs. Interestingly, the classical approach to design incentive compatible mechanisms gives the agent cheap leeway to increase relative pecuniary payoffs and thereby achieving more equitable profit allocations, because the agent is left (almost) indifferent between two contract alternatives. In other words, we argue (and actually observe in laboratory experiments) that this classical approach of contract design allows the agent to achieve more equitable outcomes at low cost. Since the agent’s better relative performance solely stems from reducing the principal’s payoffs, we observe a substantial negative impact on the overall supply chain performance. The present work relaxes the assumption of the profit-maximizing buyer (agent) in a serial supply chain for a lot sizing framework with asymmetrically distributed holding cost information and deterministic end-customer demand. The study provides researchers and managers an approach on how to account for disadvantageous inequity aversion (ie, the agent suffers from profits being lower than the principals profits) by designing a contract that anticipates such behaviour while providing a solution method for the resulting non-linear mathematical program. We denote the resulting contract as ‘behavioural robust’, since it limits the inefficiency losses that result if agents exhibit disadvantageous inequity aversion instead of being strictly profit-maximizing. A numerical study compares the advantages of the ‘behavioural robust’ contract against the classical screening contract. The results highlight that supply chain performance losses can be substantially reduced under the behavioural robust contract.     

Large deviations and estimation in infinite-dimensional models

Consider a random sample from a statistical model with an unknown, and possibly infinite-dimensional, parameter - e.g., a nonparametric or semiparametric model - and a real-valued functional T of this parameter which is to be estimated. The objective is to develop bounds on the (negative) exponential rate at which consistent estimates converge in probability to T, or, equivalently, lower bounds for the asymptotic effective standard deviation of such estimates - that is, to extend work of R.R. Bahadur from parametric models to more general (semiparametric and nonparametric) models. The approach is to define a finite-dimensional submodel, determine Bahadur's bounds for a finite-dimensional model, and then ‘sup’ or ‘inf’ the bounds with respect to ways of defining the submodels; this can be construed as a ‘directional approach’, the submodels being in a specified ‘direction’ from a specific model. Extension is made to the estimation of vector-valued and infinite-dimensional functionals T, by expressing consistency in terms of a distance, or, alternatively, by treating classes of real functionals of T. Several examples are presented.     

Recent Developments in Critical Management Science

For much of its history management science had a quantitative and technical emphasis. More recently, there has been a move towards more subjective approaches such as ‘soft OR’ and ‘soft systems’. Currently, there is interest in ‘critical management science’ drawing on critical theory, particularly the work of Habermas. This paper reviews developments in critical management science, in particular critiques of traditional and ‘soft’ management science; Jackson and Keys' system of systems methodology; critical management science methodologies and the problem of power in bringing about change; and the postmodernist critique.     

Re-sourcing teachers’ work and interactions: a collective perspective on resources, their use and transformation

This paper reviews the literature on the theme of mathematics teachers’ work and interactions with resources, taking a particular perspective, the so-called ‘collective perspective’ on resources, their use and transformation. The review is presented under three headings: (1) theoretical frameworks commonly used in this area of research; (2) teachers’ interactions with resources in terms of their design and use; and (3) teachers’ interactions with resources in terms of teacher learning and professional development. From the literature, and the collection of papers in this issue, we argue that the collective dimensions play an important role in mathematics teachers’ work with resources and in their professional learning/development. Further empirical investigations are likely to be needed on: how teachers may work in collectives and with resources, and in which ways ‘productive’ collectives may form and work together; which roles particular resources can play in these delicate constellations and how particular resources may support teachers in their work and learning; and which kinds of resources offer opportunities for community building.     

Minimal rank of abelian group matrices

The minimal rank of abelian group matrices with positive integral entries is determined.The corresponding problem for circulant matrices have been investigated by Ingleton and more recently by Shiu-Ma-Fang. Our work can be viewed as a generalization of their results, since a group matrix becomes circulant when the group is cyclic.     

Symmetry in de Branges almost Pontryagin spaces

In many examples of de Branges spaces symmetry appears naturally. Presence of symmetry gives rise to a decomposition of the space into two parts, the ‘even’ and the ‘odd’ part, which themselves can be regarded as de Branges spaces. The converse question is to decide whether a given space is the ‘even’ part or the ‘odd’ part of some symmetric space, and, if yes, to describe the totality of all such symmetric spaces. We consider this question in an indefinite (almost Pontryagin space) setting, and give a complete answer. Interestingly, it turns out that the answers for the ‘even’ and ‘odd’ cases read quite differently; the latter is significantly more complex.     

On Picard's iteration method to solve differential equations and a pedagogical space for otherness

Recently, Robin claimed to introduce clever innovations (‘wrinkles’) into the mathematics education literature concerning the solutions, and methods of solution, to differential equations. In particular, Robin formulated an iterative scheme in the form of a single integral representation. These ideas were applied to a range of examples involving differential equations. In this article, we respond to Robin's work by subjecting these claims, methods and applications to closer scrutiny. By outlining the historical development of Picard's iterative method for differential equations and drawing on relevant literature, we show that the iterative scheme of Robin has been known for some time. We introduce the need for a ‘space for otherness’ in mathematics education, by drawing on Foucault and posit alternative pedagogical approaches as heterotopias. We open a space for otherness and make it concrete by considering alternative perspectives to Robin's work. On a practical note, we see the importance of history and theory to be part of the pedagogical conversation when teaching and learning iterative methods; and provide a set of Maple code with which students and teachers can experiment, explore and learn. We also advocate more broadly for educators to open a space for otherness in their own pedagogical practice.