Measuring productive performance using binary and ordinal output variables: the case of the Swedish fire and rescue services

Fire protection is an example of a complex production process. This study measures efficiency by constructing binary and ordinal output variables from information on residential fires in Sweden about how a fire spreads from when the fire and rescue brigade arrives to when a fire is suppressed. The motivations behind this study are that there are only a few studies trying to estimate production efficiency for fire and rescue services, that data on a more detailed level is interesting for some public services, and there is a need to be able to measure efficiency differences even if only a binary or ordinal output variable is available. Using a logit random parameter model, the random effects are interpreted as efficiency differences. The conclusions are that fire and rescue services with a more flexible fire organisation with first response persons, working in collaboration with other municipalities and with larger populations are more efficient.     

基于LOF算法的多维混合型数据控制图设计

为了解决含顺序型和名义型变量混合型数据的监测问题，提出了一种基于LOF算法的多维混合型数据控制图(mixed-type data local outlier factor control chart, MLOF)。在监测过程变量变化的过程中，该控制图充分考虑了顺序型变量的等级特性和名义型变量的信息熵，基于数据的密度来衡量观测点的异常程度。分别使用基于信用卡申请数据集的仿真案例和基于德国信用卡数据集的实例，对比MLOF控制图和现有混合型数据控制图在异常点检测上的表现。仿真案例共模拟了30种监测场景。结果表明，在57%的场景中，MLOF控制图的综合表现都是最好的。而实例也验证了MLOF控制图更适用于数据量大、聚类情况复杂的混合型数据监测过程中。     

Quantifying and using expert opinion for variable-selection problems in regression

This paper gives a general method for use in the chemical industry for eliciting and quantifying an expert's subjective opinion concerning a normal linear regression model. The intention is to ask the expert assessment questions that he or she can meaningfully answer and to use the elicited values to determine a probability distribution on the regression parameters that quantifies and expresses the expert's opinions. A regression model may represent a chemical production process, for example, and the corresponding elicited distribution would embody the expert's opinion concerning the effects on product output of independent variables for process control and environmental factors. It may be uncertain what independent variables should be featured in the regression, so the expert's opinion is represented by a mixture of multivariate distributions, where each distribution in the mixture corresponds to a different subset of independent variables. Among the uses to which an elicited distribution might be put is design of experiments, discussed here with regard to Bayesian design criteria. An example is given of the elicitation and use of a subjective distribution in which an industrial chemist quantified his opinion about a chemical process.     

企业过程再造：一个案例研究

企业过程再造是为了实现企业经营业绩的突破而对企业经营过程进行的根本性改造。实施过程再造常见的方法就是对企业现有经营过程进行分析和重新设计。但是这个出发点实际上极大地限制了对问题的解决,与过程再造的“根本性”的特点相矛盾。通过分析一个科技书店再造的案例,指出了实施过程再造时,既要从企业现有经营过程出发,又要超越这个范畴,从更广阔的视野寻找解决问题的方案。在案例分析的基础上,对企业过程再造理论进行了一     

Nonmetric Common Factor Analysis: An Alternating Least Squares Method with Optimal Scaling Features

Behaviormetrika - We describe a convergent procedure for fitting the common factor analysis model to multivariate data whose variables may be nominal, ordinal or interval. Any mixture of...     

Modelling and analysis of business process reengineering

Business process design and business process reengineering (BPR) depend crucially on linking production procedures and organizational services to business goals and objectives. There is currently very little formula support for this kind of reasoning as analytical tasks are usually carried out informally and individual design decisions are hard to relate to business objectives. If BPR is carried out without understanding the way it is done, then the most likely outcome would be continuing less-than-satisfactory current practice and automating outdated processes. This kind of practice misses opportunities for innovation and rationalization. The modelling and analysis of business processes along with business strategies and organizational structures are essential to study the implications of BPR. In this paper, an attempt has been made to study the modelling, analysis and tools/techniques used for modelling of BPR with the help of a survey on the recently (1993-2000) employed methods and tools used for BPR modelling and analysis. A framework for modelling and analysis, and guidelines for the selection of tools/techniques of business process reengineering are presented.     

Latent change‐point detection in ordinal categorical data

Statistical process control (SPC) techniques have been widely used for online surveillance and offline diagnosis in many applications. Because of cost constraint or technical difficulty, it is quite common that the quality of products or service is measured by ordinal factors with ordered attribute levels such as excellent, acceptable, and unacceptable. This article studies phase I analysis of such ordinal categorical processes to identify change points. By assuming that attribute levels are determined by a latent continuous variable, this work suggests a modified log‐linear model to characterize ordinal information among the attribute levels. Then a change‐point detection method is proposed on the basis of the generalized likelihood ratio test (GLRT). Simulation results prove the method's strong detection power, high diagnostic accuracy, and robustness under various distributions of the latent variable.     

Beyond business process redesign: redefining Baxter's business network

Business process redesign has focused almost exclusively on improving the firm's internal operations. Although internal efficiency and effectiveness are important objectives, the authors argue that business network redesign--reconceptualizing the role of the firm and its key business processes in the larger business network--is of greater strategic importance. To support their argument, they analyze the evolution of Baxter's ASAP system, one of the most publicized but inadequately understood strategic information systems of the 1980s. They conclude by examining whether ASAP's early successes have positioned the firm well for the changing hospital supplies marketplace of the 1990s.     

Optimization of a pipe end upsetting process

A method is proposed for the optimization, by finite element analysis, of design variables of sheet metal forming processes. The method is useful when the non-controllable process parameters (e.g. the coefficient of friction or the material properties) can be modelled as random variables, introducing a degree of uncertainty into any process solution. The method is suited for problems with large FEM computational times and small process window. The problem is formulated as the minimization of a cost function, subject to a reliability constraint. The cost function is indirectly optimized through a “metamodel”, built by “Kriging” interpolation. The reliability, i.e. the failure probability, is assessed by a binary logistic regression analysis of the simulation results. The method is applied to the u-channel forming and springback problem presented in Numisheet 1993, modified by handling the blankholder force as a time-dependent variable.     

Growth in Knowledge-Intensive Business Services: Evidence from Lombardy

This paper studies the growth patterns in knowledge-intensive business services (KIBS) in Lombardy on the basis of original firm-level survey data. The aim is to investigate in particular the role of and interplay between age and size of firms and the modes of innovation in the process of growth. Our findings indicate that younger firms tend to outperform incumbents for sales growth and that larger firms tend to grow more than smaller companies. However, the effects of firm size and age vary substantially according to the firm's specific pattern of innovation. In particular, highly innovative firms tend to outperform competitors regardless of their age or size, while for conservative KIBS, size is a prerequisite for growth. Investment in human capital and the service distribution network are important drivers of competition for growing KIBS.     

A Learning Experience: The Technology Innovation Program

The Technology Innovation Program (TIP) is a cooperative educational venture between the Department of Chemical Engineering and the School of Business at Queen's University at Kingston, Canada. First incorporated into the curriculum of senior year business and chemical engineering students in the 1994–1995 school year, TIP provides an invaluable opportunity for these students to work together in multi-disciplinary teams on real projects for industry clients. An academically rigorous exercise, TIP uses non-traditional instructional means such as problem-based learning, multi-disciplinary teams, and self-directed project work to create a learning environment paralleling that of the professional engineer or business person. Although it is still evolving, the Technology Innovation Program provides a model for other educational ventures seeking to bridge engineering and business, and to establish valuable links between the university and industry, while simultaneously easing the graduating student's transition into the workplace.     

The analysis of ordered categorical data: An overview and a survey of recent developments

This article review methodologies used for analyzing ordered categorical (ordinal) response variables. We begin by surveying models for data with a single ordinal response variable. We also survey recently proposed strategies for modeling ordinal response variables when the data have some type of clustering or when repeated measurement occurs at various occasions for each subject, such as in longitudinal studies. Primary models in that case includemarginal models andcluster-specific (conditional) models for which effects apply conditionally at the cluster level. Related discussion refers to multi-level and transitional models. The main emphasis is on maximum likelihood inference, although we indicate certain models (e.g., marginal models, multi-level models) for which this can be computationally difficult. The Bayesian approach has also received considerable attention for categorical data in the past decade, and we survey recent Bayesian approaches to modeling ordinal response variables. Alternative, non-model-based, approaches are also available for certain types of inference. This work was partially supported by a grant for A. Agresti from NSF and by a research study leave grant from Victoria University for I. Liu.     

Translating a typical business process modelling language to a web services ontology through lightweight mapping

Bridging the gap between enterprise modelling methods and Semantic Web services is an important yet challenging task. For organisations with business goals, the automation of business processes as Web services is increasingly important, especially with many business transactions taking place within the Web today. Taking one approach to address this problem, a lightweight mapping between Fundamental Business Process Modelling Language (FBPML) and the Web Services Ontology (OWL-S) is outlined. The framework entails a data model translation and a process model translation via the use of ontologies and mapping principles. Several working examples of the process model translations are presented together with the implementation of an automated translator. FBPML constructs and process models that could not be translated to OWL-S equivalents highlight the differences between the languages of the two domains. It also implies that evolving Semantic Web technologies, in particular OWL-S, are not adequate for all service modelling needs and could thus benefit from the more traditional and mature BPM methods. On a more interesting note, this is effectively the first step towards enabling a semantic-based business workflow system     

Correlating business process re-engineering with the information systems department

Despite the widespread use of re-engineering to enhance organizational competitiveness, the role of an information systems department in business process re-engineering is not clearly understood. The role of an information systems department in the success of business process re-engineering projects was empirically investigated. Structured interviews with 27 executives were initially conducted to identify critical information systems department roles in business process re-engineering. These roles were then empirically validated using survey research method to determine their extent of impact on business process re-engineering success. The results of hierarchical regression analysis show that support of top information system management, the existence of technology champion, the management of resistance to change, the quality of information system planning, the integration of an information system–business strategy, the sophistication of user's computer skill and the extent of integration of the information architecture are the most critical information systems department roles in business process re-engineering success. Other roles of an information systems department that facilitate business process re-engineering success include the management of transition, the provision of information technology training, the competency of information system staff and the extent of computer use by users. The implications of these findings for information system researchers and practitioners are discussed.     

Analysis of driver and passenger crash injury severity using partial proportional odds models

The question of whether crash injury severity should be modeled using an ordinal response model or a non-ordered (multinomial) response model is persistent in traffic safety engineering. This paper proposes the use of the partial proportional odds (PPO) model as a statistical modeling technique that both bridges the gap between ordered and non-ordered response modeling, and avoids violating the key assumptions in the behavior of crash severity inherent in these two alternatives. The partial proportional odds model is a type of logistic regression that allows certain individual predictor variables to ignore the proportional odds assumption which normally forces predictor variables to affect each level of the response variable with the same magnitude, while other predictor variables retain this proportional odds assumption. This research looks at the effectiveness of this PPO technique in predicting vehicular crash severities on Connecticut state roads using data from 1995 to 2009. The PPO model is compared to ordinal and multinomial response models on the basis of adequacy of model fit, significance of covariates, and out-of-sample prediction accuracy. The results of this study show that the PPO model has adequate fit and performs best overall in terms of covariate significance and holdout prediction accuracy. Combined with the ability to accurately represent the theoretical process of crash injury severity prediction, this makes the PPO technique a favorable approach for crash injury severity modeling by adequately modeling and predicting the ordinal nature of the crash severity process and addressing the non-proportional contributions of some covariates.     

Theory of constraint methodology where the constraint is the business model

This paper addresses the issue of business model (BM) management and its relationship to the theory of constraints (TOC). Coman and Ronen (Coman, A. and Ronen,B., 2007. Managing strategic and tactical constraints in the hi-tech industry. International Journal of Production Research, 38(7), 1631–1639) have extended TOC methodology to include the alignment of the organisation's competencies with the business arena's strategic constraints. The aim of this paper is to take TOC one step further and to combine it with the business models theory. Business models have become important value creators due to the proliferation of new and innovative business models (i.e. new ways of creating value). New firms with new business models are threatening and replacing established companies and conventional ways of doing business. Among these are the music, publishing, books, retail, airline and many other industries. This paper argues that in the wake of the World Wide Web, contract manufacturing and globalisation it not enough to manage the firms (internal, external or strategic) constraints. In addition, the management of the firm's BM as a potential constraint is a key factor in the modern management theory.     

Shapley values for assessing research production and impact of schools and scholars

Performance measures of individual scholars tend to ignore the context. I introduce contextualised metrics: cardinal and ordinal pseudo-Shapley values that measure a scholar’s contribution to (perhaps power over) her own school and her market value to other schools should she change job. I illustrate the proposed measures with business scholars and business schools in Ireland. Although conceptually superior, the power indicators imply a ranking of scholars within a school that is identical to the corresponding conventional performance measures. The market value indicators imply an identical ranking within schools and a very similar ranking between schools. The ordinal indices further contextualise performance measures and thus deviate further from the corresponding conventional indicators. As the ordinal measures are discontinuous by construction, a natural classification of scholars emerges. Averaged over schools, the market values offer little extra information over the corresponding production and impact measures. The ordinal power measure indicates the robustness or fragility of an institution’s place in the rank order. It is only weakly correlated with the concentration of publications and citations.     

Systematic approach for the gap analysis of business processes

Process benchmarking and business process re-engineering (BPR) have become two main methodologies used to implement business process improvement and have attracted much attention in a current fast-changing environment. Leveraging best practice has become the important factor of process benchmarking and BPR. Accurate knowledge of the gaps between best practice processes and a company's business processes is essential for the redesign of business processes. This paper proposes a systematic enterprise model comparison approach to assist a project team in business process gap analysis (BPGA). A three-phased framework including business process modelling, object semantic analysis phase and process gap analysis phase was developed. An approach of applying the concepts of semantic similarity analysis to find the semantic-related objects in different processes was also proposed. In addition, a set of process path patterns and an alternative process path analysis method was developed to facilitate the processed data and process logic gap analysis between two processes. With the proposed BPGA approach, project teams will understand and redesign their processes more effectively.     

Assessing intermediate infrastructural manufacturing decisions that affect a firm's market performance

The purpose of this study is to develop a strategic operations management model that links intermediate infrastructural operations decisions and market performance given process choice as a structural constraint for manufacturing firms. The results underscore the effects of manufacturing control and staff skill and knowledge development on a firm's market performance. Several conclusions are drawn. First, manufacturing control, and staff skill and knowledge development has played significant roles in determining market performance. Second, either alone or in tandem with other independent variables, technology application dose not appear to be the most critical factor to affect a firm's market performance in today's Chinese business environment. Third, process type may not have a direct impact on market performance.