SSM and technology management: Developing multimethodology through practice

Growing competition and economic recession is driving the need for more rapid redesign of operations enabled by innovative technologies. The acquisition, development and implementation of systems to manage customer complaints and control the quality assurance process is a critical area for engineering and manufacturing companies. Multimethodologies, and especially those that can bridge ‘soft’ and ‘hard’ OR practices, have been seen as a possible means to facilitate rapid problem structuring, the analysis of alternative process design and then the specification through to implementation of systems solutions. Despite the many ‘hard’ and ‘soft’ OR problem structuring and management methods available, there are relatively few detailed empirical research studies of how they can be combined and conducted in practice. This study examines how a multimethodology was developed, and used successfully, in an engineering company to address customer complaints/concerns, both strategically and operationally. The action research study examined and utilised emerging ‘soft’ OR theory to iteratively develop a new framework that encompasses problem structuring through to technology selection and adoption. This was based on combining Soft Systems Methodology (SSM) for problem exploration and structuring, learning theories and methods for problem diagnosis, and technology management for selecting between alternatives and implementing the solution. The results show that, through the use of action research and the development of a contextualised multimethodology, stakeholders within organisations can participate in the design of new systems and more rapidly adopt technology to address the operational problems of customer complaints in more systemic, innovative and informed ways.     

‘Too Little’ or ‘Too Late’: The timing of supply chain demand collaboration

This study examines the supply chain demand collaboration between a manufacturer and a retailer. We study how the timing of collaboration facilitates production decision of the manufacturer when the information exchanged in the collaboration is asymmetric. We investigate two collaboration mechanisms: ‘Too Little’ and ‘Too Late’, depending on the timing of information sharing between the manufacturer and the retailer. Our research results indicate that early collaboration as in the ‘Too Little’ mechanism leads to a stable production schedule, which decreases the need of production adjustment when production cost information becomes available; whereas a late collaboration as in the ‘Too Late’ mechanism enhances the flexibility of production adjustment when demand information warrants it. In addition, the asymmetric demand information confounds production decisions all the time; the manufacturer has to provide proper incentives to ensure truthful information sharing in collaboration. Information asymmetry might also reduce the difference in production decision between the ‘Too Little’ and ‘Too Late’ collaboration mechanisms. Numerical analysis is further conducted to demonstrate the performance implications of the collaboration mechanisms on the supply chain.     

Supplier switching decisions

In order to maximize profit, a buying firm should continuously search for and access sources which offer more favorable prices. While the literature is replete with works on the formation and development of buyer–supplier relationships, there is surprisingly only scarce research on the termination of such relationships and supplier switching. Using the concept of switching costs in a principal-agent framework, we at first analyze whether a firm switches the entire or a partial quantity to an alternative supplier when there is either symmetric or asymmetric information about the alternative supplier’s cost structure. Information asymmetry results in inert supplier switching decisions. Subsequently, we extend our model and take competitive reactions of the incumbent supplier and economies of scale effects into consideration. We find conditions under which ‘no’, ‘partial’ and ‘complete’ switching occurs, which depend on the buying firm’s beliefs about the alternative supplier’s unit costs, switching costs, the price offered by the incumbent supplier, and refinements of the price offered by the incumbent supplier due to competitive reactions and economies of scale. Broader implications for supplier relationship management and sourcing strategy decisions are also provided.     

Variable annuities: A unifying valuation approach

Life annuities and pension products usually involve a number of guarantees, such as minimum accumulation rates, minimum annual payments or a minimum total payout. Packaging different types of guarantees is the feature of so-called variable annuities. Basically, these products are unit-linked investment policies providing a post-retirement income. The guarantees, commonly referred to as GMxBs (namely, Guaranteed Minimum Benefits of type ‘x’), include minimum benefits both in the case of death and survival. In this paper we propose a unifying framework for the valuation of variable annuities under quite general model assumptions. We compute and compare contract values and fair fee rates under ‘static’ and ‘mixed’ valuation approaches, via ordinary and least squares Monte Carlo methods, respectively.     

Analysis of the MAP/G/1/N queue with multiple vacations

This paper deals with a batch service queue and multiple vacations. The system consists of a single server and a waiting room of finite capacity. Arrival of customers follows a Markovian arrival process (MAP). The server is unavailable for occasional intervals of time called vacations, and when it is available, customers are served in batches of maximum size ‘b’ with a minimum threshold value ‘a’. We obtain the queue length distributions at various epochs along with some key performance measures. Finally, some numerical results have been presented.     

Problem structuring methods ‘in the Dock’: Arguing the case for Soft OR

Problem structuring methods (‘soft’ OR) have been around for approximately 40 years and yet these methods are still very much overlooked in the OR world. Whilst there is almost certainly a number of explanations for this, two key stumbling blocks are: (1) the subjective nature of the modelling yielding insights rather than testable results, and (2) the demand on users to both manage content (through modelling) and processes (work with rather than ‘on behalf’ of groups). However, as evidenced from practice there are also a number of significant benefits. This paper therefore aims to examine the case of Soft OR through examining the case for and against problem structuring methods.     

“I’m not very good at solving problems”: An exploration of students’ problem solving behaviours

This paper reports one aspect of a larger study which looked at the strategies used by a selection of grade 6 students to solve six non-routine mathematical problems. The data revealed that the students exhibited many of the behaviours identified in the literature as being associated with novice and expert problem solvers. However, the categories of ‘novice’ and ‘expert’ were not fully adequate to describe the range of behaviours observed and instead three categories that were characteristic of behaviours associated with ‘naïve’, ‘routine’ and ‘sophisticated’ approaches to solving problems were identified. Furthermore, examination of individual cases revealed that each student's problem solving performance was consistent across a range of problems, indicating a particular orientation towards naïve, routine or sophisticated problem solving behaviours. This paper describes common problem solving behaviours and details three individual cases involving naïve, routine and sophisticated problem solvers.     

A sensitivity analysis of typical life insurance contracts with respect to the technical basis

In [Christiansen, M.C., 2007. A sensitivity analysis concept for life insurance with respect to a valuation basis of infinite dimension. Insurance: Math. Econom. doi:10.1016/j.insmatheco.2007.07.005] a sensitivity analysis concept was introduced for the prospective reserve of individual life insurance contracts as functional of the technical basis parameters such as interest rate, mortality probability, disability probability, et cetera. On the basis of that concept, the present paper gives in addition the sensitivities of the premium level.Applying these approaches, an extensive sensitivity analysis is carried out: A study of the basic life insurance contract types ‘pure endowment insurance’, ‘temporary life insurance’, ‘annuity insurance’ and ‘disability insurance’ identifies their diverse characteristics, in particular their weakest points concerning fluctuations of the technical basis. An investigation of combinations of these insurance contract types shows what synergy effects can be expected by creating insurance packages.     

Auditors’ evidence evaluation and aggregation using beliefs and probabilities

This paper examines possible differences in auditors’ performance when they make belief-based versus probability-based risk assessments by focusing on two phases of the financial statement audit process: the assessment of two attributes of audit evidence (‘strength’ and ‘direction’) and the aggregation of evidence. Based on an experiment in which 48 experienced auditors participated, three important findings were observed. First, there was no significant difference in the mean assessment of strength of evidence measured using the likelihood ratio. However, the difference in the assessed direction of evidence, that is whether the evidence is interpreted as being confirming or disconfirming, is significant for one of the cases examined. This result shows that auditors making belief-based assessments are able to assess the direction of the evidence more accurately than auditors making probability-based assessments. Third, the auditors’ aggregation of evidence was not in accordance with ‘AND’ logic for either auditors making belief-based or probability-based assessments. These empirical results raise issues which need to be addressed in practice and in future research.     

On the parallel between normality and extremal disconnectedness

Several familiar results about normal and extremally disconnected (classical or pointfree) spaces shape the idea that the two notions are somehow dual to each other and can therefore be studied in parallel. This paper investigates the source of this ‘duality’ and shows that each pair of parallel results can be framed by the ‘same’ proof. The key tools for this purpose are relative notions of normality, extremal disconnectedness, semicontinuity and continuity (with respect to a fixed class of complemented sublocales of the given locale) that bring and extend to locale theory a variety of well-known classical variants of normality and upper and lower semicontinuities in an illuminating unified manner. This approach allows us to unify under a single localic proof all classical insertion, as well as their corresponding extension results.     

Diagnostic assessment of children’s proportional reasoning

A proportional reasoning item bank was created from the relevant literature and tested in various forms. Rasch analyses of 303 pupils’ test results were used to calibrate the bank, and data from 84 pupils’ interviews was used to confirm our diagnostic interpretations. A number of sub-tests were scaled, including parallel ‘without models’ and ‘with models’ forms. We provide details of the 13-item ‘without models’ test which was formed from the ‘richest’ diagnostic items and verified on a further test sample (N=212, ages 10-13). Two scales were constructed for this test, one that measures children’s ‘ratio attainment’ and one that measures their ‘tendency for additive strategy.’ Other significant errors — ‘incorrect build-up,’ ‘magical doubling/halving,’ ‘constant sum’ and ‘incomplete reasoning’ — were identified. Finally, an empirical hierarchy of pupils’ attainment of proportional reasoning was formed, incorporating the significant errors and the additive scale.     

A binary particle swarm optimization algorithm inspired by multi-level organizational learning behavior

Recently, nature-inspired algorithms have increasingly attracted the attention of researchers. Due to the fact that in BPSO the position vectors consisting of ‘0’ and ‘1’ can be seen as a decision behavior (support or oppose), in this paper, we propose a BPSO with hierarchical structure (BPSO_HS for short), on the basis of multi-level organizational learning behavior. At each iteration of BPSO_HS, particles are divided into two classes, named ‘leaders’ and ‘followers’, and different evolutionary strategies are used in each class. In addition, the mutation strategy is adopted to overcome the premature convergence and slow convergent speed during the later stages of optimization. The algorithm was tested on two discrete optimization problems (Traveling Salesman and Bin Packing) as well as seven real-parameter functions. The experimental results showed that the performance of BPSO_HS was significantly better than several existing algorithms.     

On the calculation of the Kauffman bracket polynomial

In this paper, we present a new algorithm to evaluate the Kauffman bracket polynomial. The algorithm uses cyclic permutations to count the number of states obtained by the application of ‘A’ and ‘B’ type smoothings to the each crossing of the knot. We show that our algorithm can be implemented easily by computer programming.     

A certain finiteness property of Pisot number systems

In the study of substitutative dynamical systems and Pisot number systems, an algebraic condition, which we call ‘weak finiteness’, plays a fundamental role. It is expected that all Pisot numbers would have this property. In this paper, we prove some basic facts about ‘weak finiteness’. We show that this property is valid for cubic Pisot units and for Pisot numbers of higher degree under a dominant condition.     

On nonatomicity for non-additive functions

The notion of nonatomicity for set functions plays a key role in classical measure theory and its applications. For classical measures taking values in finite dimensional Banach spaces, it guarantees the connectedness of range. Even just replacing σ-additivity with finite additivity for measures requires some stronger nonatomicity property for the same conclusion to hold. In the present paper, we deal with non-additive functions – called ‘s-outer’ and ‘quasi-triangular’ – defined on rings and taking values in Hausdorff topological spaces. No algebraic structure is required on their target spaces. In this context, we make use of a notion of strong nonatomicity involving just the behavior of functions on ultrafilters of their underlying Boolean domains. This notion is proved to be equivalent to that proposed in earlier contributions concerning Lyapunov-types theorems in additive and non-additive frameworks. Thus, in particular, our analysis allows to generalize, improve and unify several known results on this topic.     

Bayesian modeling of several covariance matrices and some results on propriety of the posterior for linear regression with correlated and/or heterogeneous errors

We explore simultaneous modeling of several covariance matrices across groups using the spectral (eigenvalue) decomposition and modified Cholesky decomposition. We introduce several models for covariance matrices under different assumptions about the mean structure. We consider ‘dependence’ matrices, which tend to have many parameters, as constant across groups and/or parsimoniously modeled via a regression formulation. For ‘variances’, we consider both unrestricted across groups and more parsimoniously modeled via log-linear models. In all these models, we explore the propriety of the posterior when improper priors are used on the mean and ‘variance’ parameters (and in some cases, on components of the ‘dependence’ matrices). The models examined include several common Bayesian regression models, whose propriety has not been previously explored, as special cases. We propose a simple approach to weaken the assumption of constant dependence matrices in an automated fashion and describe how to compute Bayes factors to test the hypothesis of constant ‘dependence’ across groups. The models are applied to data from two longitudinal clinical studies.     

Disseminating a warning message to evacuate: A simulation study of the behaviour of neighbours

Large-scale evacuations are a recurring theme on news channels, whether in response to major natural or manmade disasters. The role of warning dissemination is a key part in the success of such large-scale evacuations and its inadequacy in certain cases has been a ‘primary contribution to deaths and injuries’ (Hayden et al., 2007). Along with technology-driven ‘official warning channels’ (e.g. sirens, mass media), the role of unofficial channel (e.g. neighbours, personal contacts, volunteer wardens) has proven to be significant in warning the public of the need to evacuate. Although post-evacuation studies identify the behaviours of evacuees as disseminators of the warning message, there has not been a detailed study that quantifies the effects of such behaviour on the warning message dissemination. This paper develops an Agent-Based Simulation (ABS) model of multiple agents (evacuee households) in a hypothetical community to investigate the impact of behaviour as an unofficial channel on the overall warning dissemination. Parameters studied include the percentage of people who warn their neighbours, the efficiency of different official warning channels, and delay time to warn neighbours. Even with a low proportion of people willing to warn their neighbour, the results showed considerable impact on the overall warning dissemination.     

A multivariate version of the Benjamini-Hochberg method

We propose a multivariate method for combining results from independent studies about the same ‘large scale’ multiple testing problem. The method works asymptotically in the number of hypotheses and consists of applying the Benjamini-Hochberg procedure to the p-values of each study separately by determining the ‘individual false discovery rates’ which maximize power subject to a restriction on the (global) false discovery rate. We show how to obtain solutions to the associated optimization problem, provide both theoretical and numerical examples, and compare the method with univariate ones.