Knowledge accelerator by transversal competences and multivariate adaptive regression splines

Transversal competences constitute a set of the knowledge, skills, and attitudes required for various positions and in different professions. Such competences include: entrepreneurship, teamwork, creativity, and communicativeness; they are increasingly listed by employers in different countries as the key requirements in the labor market. The article presents the model of accelerating the process of acquiring transversal competences, developed based on the analysis of data collected in four countries of the European Union: Poland, Finland, Slovakia, and Slovenia. In the analysis, multivariate additive regression spline method was used, along with artificial neural networks, in order to create the best model describing the influence of different variables on the acceleration of acquiring transversal competences. Herewith, we demonstrated that by accelerating the acquisition of the transversal competence of entrepreneurship is influenced by the following factors: rank of the training method in the developed matrix, student numbers and the weighted average of the pace of acceleration regarding the acquisition of the remaining transversal competences, i.e., teamwork, communicativeness and creativity by the given student. The results validate our new method of the acceleration of acquiring transversal competences by students. Students may be from various higher education institutions in different countries. Developed results may be used in the course of education within the framework of the already planned vocational courses and for developing the skills required by employers for various positions and in different professions.

     

‘Good enough’ performance measurement: a trade-off between activity and action

Performance measurement systems along the lines of the EFQM and the balanced scorecard have developed rapidly in recent years, and now occupy much management time and effort. There is limited evidence that performance improvement has received proportionate attention. Six organisations selected for their success were studied using a grounded theory approach based on interviews with management accountants and operations managers in each of the organisations. It is clear that they are all making strenuous efforts to use their performance measurement systems but with a focus on the ‘good enough’ rather than the detail. This gave managers in these organisations the time and space to concentrate on the use of performance measures on forward looking relevance, understanding and action, rather than retrospective and detailed control. This approach was promoted by senior managers and was based on their ability to see the business in simple terms and their understanding of the key drivers of business performance.     

Customer satisfaction measurement in the private bank sector

Customer satisfaction represents a modern approach for quality in enterprises and organisations and serves the development of a truly customer-focused management and culture. Measuring customer satisfaction offers an immediate, meaningful and objective feedback about clients’ preferences and expectations. In this way, company’s performance may be evaluated in relation to a set of satisfaction dimensions that indicate the strong and the weak points of a business organisation. This paper presents an original customer satisfaction survey in the private bank sector. The implemented methodology is based on the principles of multicriteria analysis and preference disaggregation modelling. The most important results are focused on the determination of the critical service dimensions and the segmentation to customer clusters with distinctive preferences and expectations.     

On the nature of OR: taking stock

This paper argues that OR, having reached its maturity, must now play to its strengths. In strategic terms this means competing in those areas where OR's core competences can be brought to bear. Using a competence model it is suggested that OR's core products are (i) the development and implementation of the quantitative, algorithmic ‘smart bits’ and (ii) the ‘helpful ways’ of managing intervention processes. These core products are supported and sustained by three core competences labelled process, analytic, and context. Individuals and small groups of practitioners develop ‘strands of practice’ and larger groups ‘webs of practice’ on the basis of their core competences. It is argued that this is giving rise to the emergence of three archetypes of OR service, namely the OR technical consultancy, the OR process consultancy, and the full service OR consultancy. Both the technical and process consulting are built around ‘strands of practice’ of individuals and find their natural home in small service providers. The full service OR consulting practice, in the past located in internal OR groups, will in the future be located within the large management consultancies, which are capable of managing ‘webs of practice’. The implications for the worlds of OR practice and academia are examined.     

A model of professional competences in mathematics to update mathematical and didactic knowledge of teachers

This paper describes part of a research and development project carried out in public elementary schools. Its objective was to update the mathematical and didactic knowledge of teachers in two consecutive levels in urban and rural public schools of Region de Los Lagos and Region de Los Rios of southern Chile. To that effect, and by means of an advanced training project based on a professional competences model, didactic interventions based on types of problems and types of mathematical competences with analysis of contents and learning assessment were designed. The teachers’ competence regarding the didactic strategy used and its results, as well as the students’ learning achievements are specified. The project made possible to validate a strategy of lifelong improvement in mathematics, based on the professional competences of teachers and their didactic transposition in the classroom, as an alternative to consolidate learning in areas considered vulnerable in two regions of the country.     

Robust competence assessment for job assignment

Allocating the right person to a task or job is a key issue for improving quality and performance of achievements, usually addressed using the concept of “competences”. Nevertheless, providing an accurate assessment of the competences of an individual may be in practice a difficult task. We suggest in this paper to model the uncertainty on the competences possessed by a person using a possibility distribution, and the imprecision on the competences required for a task using a fuzzy constraint, taking into account the possible interactions between competences using a Choquet integral. As a difference with comparable approaches, we then suggest to perform the allocation of persons to jobs using a robust optimisation approach, allowing to minimise the risk taken by the decision maker. We first apply this framework to the problem of selecting a candidate within n for a job, then extend the method to the problem of selecting c candidates for j jobs (c ? j) using the leximin criterion.     

Real estate price estimation in French cities using geocoding and machine learning

This paper reviews real estate price estimation in France, a market that has received little attention. We compare seven popular machine learning techniques by proposing a different approach that quantifies the relevance of location features in real estate price estimation with high and fine levels of granularity. We take advantage of a newly available open dataset provided by the French government that contains 5 years of historical data of real estate transactions. At a high level of granularity, we obtain important differences regarding the models’ prediction powers between cities with medium and high standards of living (precision differences beyond 70% in some cases). At a low level of granularity, we use geocoding to add precise geographical location features to the machine learning algorithm inputs. We obtain important improvements regarding the models’ forecasting powers relative to models trained without these features (improvements beyond 50% for some forecasting error measures). Our results also reveal that neural networks and random forest techniques particularly outperform other methods when geocoding features are not accounted for, while random forest, adaboost and gradient boosting perform well when geocoding features are considered. For identifying opportunities in the real estate market through real estate price prediction, our results can be of particular interest. They can also serve as a basis for price assessment in revenue management for durable and non-replenishable products such as real estate.

     

The simplified updating rule in the formalization of digital educational games

Competence-based Knowledge Space Theory (CbKST) has been proven to be a very well-fitting basis for realizing personalization in technology-enhanced learning. Especially in the area of game-based learning, however, some extensions and improvements are needed.Personalization in a serious game cannot be regarded simply as the selection of game assets according to the individual learner's current competences but it must also pay heed to the up-keeping of a storyline, it must be ensured that no part of the story is omitted that may be necessary to understand a later part. Therefore, a CbKST-compatible Markovian model for storytelling is proposed.A second issue is the ongoing, non-invasive assessment of the learner's current competences during the game. Every action of the learner within the game should be taken into account for the competence assessment, and the assessment must be done in real-time, i.e. there must not be any delay caused by the assessment which would interrupt the flow of the game. A simplified update procedure for competence assessment within CbKST is suggested which can solve this issue, and simulation results are presented comparing the new procedure with the classical one.     

Quantum game approach for capacity allocation decisions under strategic reasoning

From a common point of view, quantum mechanics, psychology, and decision science disciplines try to predict how unruly systems (atomic particles, human behaviors, and decision makers’ choices) might behave in the future. Effective predicting outcome of a capacity allocation game under various allocation policies requires a profound understanding as how strategic reasoning of decision makers contributes to the financial gain of players. A quantum game framework is employed in the current study to investigate how performance of allocation policies is affected when buyers strategize over order quantities. The results show that the degree of being manipulative for allocation mechanisms is not identical and adopting adaptive quantum method is the most effective approach to secure the highest fill rate and profit when it is practiced under a reasonable range of entanglement levels.

     

A hybrid model based on dynamic programming,neural networks,and surrogate value for inventory optimisation applications

This paper proposes a new approach to minimise inventory levels and their associated costs within large geographically dispersed organisations. For such organisations, attaining a high degree of agility is becoming increasingly important. Linear regression-based tools have traditionally been employed to assist human experts in inventory optimisation; endeavours; recently, Neural Network (NN) techniques have been proposed for this domain. The objective of this paper is to create a hybrid framework that can be utilised for analysis, modelling and forecasting purposes. This framework combines two existing approaches and introduces a new associated cost parameter that serves as a surrogate for customer satisfaction. The use of this hybrid framework is described using a running example related to a large geographically dispersed organisation.     

Value-based DEA models: application-driven developments

Data envelopment analysis (DEA) is an approach based on linear programming to assess the relative efficiency of peer decision-making units (DMUs). Typically, each DMU is free to choose the weights of the factors used in its evaluation. However, the evaluator's preferences may not warrant so much freedom. Several approaches have been proposed to allow the incorporation of managerial preferences in DEA, but few address the additive DEA model specifically. This paper presents additive DEA models that use multi-criteria decision analysis concepts to incorporate managerial preferences, and presents the corresponding preference elicitation protocols. The models developed allow the incorporation of preferences at different levels: on valuing performance improvements, on introducing weight restrictions, and on finding adequate targets. These were application-driven developments, resulting from discussing modelling options and preliminary results with the top-level management of a retail chain in the context of an assessment of stores’ performance, also described in this paper.     

The group consensus based evidential reasoning approach for multiple attributive group decision analysis

Many multiple attribute decision analysis problems include both quantitative and qualitative attributes with various kinds of uncertainties such as ignorance, fuzziness, interval data, and interval belief degrees. An evidential reasoning (ER) approach developed in the 1990s and in recent years can be used to model these problems. In this paper, the ER approach is extended to group consensus (GC) situations for multiple attributive group decision analysis problems. In order to construct and check the GC, a compatibility measure between two belief structures is developed first. Considering two experts’ utilities, the compatibility between their assessments is naturally constructed using the compatibility measure. Based on the compatibility between two experts’ assessments, the GC at a specific level that may be the attribute level, the alternative level, or the global level, can be constructed and reached after the group analysis and discussion within specified times. Under the condition of GC, we conduct a study on the forming of group assessments for alternatives, the achievement of the aggregated utilities of assessment grades, and the properties and procedure of the extended ER approach. An engineering project management software selection problem is solved by the extended ER approach to demonstrate its detailed implementation process, and its validity and applicability.     

The assessment of user-perceived web quality: Application of a satisfaction benchmarking approach

The assessment of website quality is considered as a problem of measuring user satisfaction, in order to analyse user perceptions and preferences. The presented pilot user satisfaction survey concerns the major cellular phone service providers in Greece. The analysis is based on a multicriteria preference disaggregation approach for satisfaction benchmarking analysis and consists of the following parts: (1) the user satisfaction analysis, which concerns the identification of customer preferences and includes the estimation of the relative importance and the demanding level of the different user satisfaction dimensions, and (2) the satisfaction benchmarking analysis, which is mainly focused on the performance evaluation of the competitive organisations against the satisfaction criteria, as well as the identification of the competitive advantages of each company. The results presented in this paper demonstrate how business organisations may locate their position against competition, pinpoint their weak points and determine which website characteristics will improve their global performance.     

Measuring performance in Dumfries and Galloway Constabulary with the Balanced Scorecard

Measuring the performance of public sector organisations has always been a difficult and contentious area. However, with continuing pressures for transparency, accountability and value for money it is one that requires increasing management attention. This paper describes the Balanced Scorecard approach to performance measurement, assesses the applicability of the approach in the public sector and illustrates how the approach was used by Dumfries and Galloway Constabulary in Scotland as part of a strategic policing initiative.     

Enhancing language-responsive meaning-making processes as an epistemic catalyst for developing multiplicative reasoning in young children

Multiplicative reasoning involves the ability to coordinate bundled units on a more abstract level (“unitizing”; Lamon, 1994). As it is considered a “cutoff point” for students’ future mathematical learning, teachers must provide equitable access to mathematical conceptual understanding for all students on all mathematical achievement levels. The study presented in this paper investigates to what extent a preventive and a language-responsive instructional approach can have an effect on the outcome of students on different mathematical achievement levels. Three German second grade teachers introduced multiplication to students (n = 66, aged 7–8 years) in their classes using meaning-related phrases (e.g., “6 times 4 means 6 fours”), while teachers in the control group (n = 58) did not focus on using these phrases. Analyses of both a multiplication posttest and a follow-up test showed significant differences between the intervention and control groups on all achievement levels for both conceptual and procedural items.     

A longitudinal view of mathematics achievement of primary students: case studies from Japan, Singapore, and the United States

This paper shares results from a secondary analysis of data from the participation of Japanese, Singaporean, and U.S. students in the International Project on Mathematical Attainment (IPMA). IPMA was a longitudinal study to assess the mathematics achievement of primary students from their first year of schooling through the end of fifth grade. Tests were constructed to enable achievement on the same items to be assessed over multiple years, thus permitting the assessment of growth in achievement throughout primary school. Achievement is compared to the grade at which the content is introduced so that achievement can be related to students’ opportunity to learn.     

基于模糊证据推理及改进TOPSIS的多属性群决策方法

针对不同识别框架多属性群决策问题属性准则度量的不确定性、随机性,定义基于梯形模糊数表征的属性准则评价等级相似度量,求解专家决策权重的最优解。对公共识别框架备选方案属性准则采用模糊证据推理过程综合专家评价等级置信度信息;利用可严格区分属性准则评价等级的相似度量,改进TOPSIS方法中备选方案属性准则评价等级置信度距离因子,获取备选方案逼近正负理想解的贴近度。实例分析以某通信企业电信产品市场竞争力评估为例,说明基于模糊证据推理、改进TOPSIS的多属性群决策问题求解过程,从属性准则专家模糊评价等级置信度集中获取直观的待评估产品市场竞争力排序结果,验证该方法解决此类决策问题的可行性与有效性。     

BiLevel programming Data Envelopment Analysis with constrained resource

A new BiLevel programming Data Envelopment Analysis (DEA) approach is created to provide valuable managerial insights when assessing the performance of a system with Stackelberg-game relationships. This new approach allows us to evaluate the firm performance in decentralized decisions, which consist of the objective(s) of the leader at its first level and that is of the follower at the second level. This approach can help decentralized companies to optimize their performance using multiple inputs to produce multiples outputs in a cost-effective way, where both the system “black-box” and subsystem performance are exposed in details. We show the algorithms and solutions to our new models. We illustrate and validate the proposed new approach using two case studies: a banking chain and a manufacturing supply chain. The computation shows that subsystem being efficient at all levels results in an overall efficiency achievement in a decentralized BiLevel structure.     

合同能源管理中超额节能收益分配问题研究

在我国合同能源管理项目中,节能收益分享模式被广泛采用。通过构建“委托-代理”模型深入分析节能收益分享模式下的超额节能收益分配问题。研究发现:(1)无论是否出现超额节能收益,合同中用能方的节能收益分享比例不得超过50%;(2)在引入节能服务公司的努力成本系数且不考虑节能改造双方风险偏好的情况下(风险中性),当努力成本系数在特定的取值范围内,优化后的超额节能收益分配方式对节能服务公司更具激励作用;(3)考虑节能服务公司为风险规避时,其最优期望节能收益不但受其努力成本系数的影响,还受其风险规避程度以及节能收益期望方差的影响。     

Corporate Financial Planning in Insurance—A Case Study

ECGD's OR group has built a financial model to forecast accounts and performance indicators. This meets the need for soundly based financial planning, and its output is considered at the highest levels of the organization. The model enables senior management to evaluate the consequences of different courses of action against the background of varying world economic scenarios. Using a financial planning package has made for quick and efficient development of the model, which has been modified continually over the last 10 years. A flexible, adaptive approach has maintained the relevance of OR's contribution. The model forecasts the financial variables which underpin ECGD's quarterly financial review and annual business plan. The Department's Financial Policy and Planning Division uses the model extensively in its preparation of these documents and to explore feasible policies through ‘what-if’ analyses. Organizational changes, increasing delegation, and the introduction of strategic planning will require further adaptation of the model allowing access to a wider range of end-users.