The design of computer based planning and modeling systems

Today there are nearly 2000 corporations in North America and Europe either using, developing, or experimenting with some form of corporate planning model. With the emergence of this new and rather substantial interest in the methodology of corporate planning modeling, there appears to be a definite need for a conceptual framework which can be used to design and implement computer based planning and modeling systems.In this paper the authors describe a collection of elements which they believe to be of critical importance in designing a corporate planning model. Their objective is to develop a set of criteria for not only designing a planning and modeling system, but a set of criteria which can also be used to facilitate the evaluation and comparison of alternative planning and modeling systems.There are over 50 planning and modeling software packages on the market today. These include systems such as BUDPLAN, COMOS and SIMPLAN. This paper attempts to provide the reader with a convenient checklist of possible features to consider in either designing one's own system or selecting an appropriate software package.     

An Integrated Approach to Oversight Assessment for Emerging Technologies

Analysis of oversight systems is often conducted from a single disciplinary perspective and by using a limited set of criteria for evaluation. In this article, we develop an approach that blends risk analysis, social science, public administration, legal, public policy, and ethical perspectives to develop a broad set of criteria for assessing oversight systems. Multiple methods, including historical analysis, expert elicitation, and behavioral consensus, were employed to develop multidisciplinary criteria for evaluating oversight of emerging technologies. Sixty‐six initial criteria were identified from extensive literature reviews and input from our Working Group. Criteria were placed in four categories reflecting the development, attributes, evolution, and outcomes of oversight systems. Expert elicitation, consensus methods, and multidisciplinary review of the literature were used to refine a condensed, operative set of criteria. Twenty‐eight criteria resulted spanning four categories: seven development criteria, 15 attribute criteria, five outcome criteria, and one evolution criterion. These criteria illuminate how oversight systems develop, operate, change, and affect society. We term our approach “integrated oversight assessment” and propose its use as a tool for analyzing relationships among features, outcomes, and tradeoffs of oversight systems. Comparisons among historical case studies of oversight using a consistent set of criteria should result in defensible and evidence‐supported lessons to guide the development of oversight systems for emerging technologies, such as nanotechnology.     

Multi-objective simulation optimization using data envelopment analysis and genetic algorithm: Specific application to determining optimal resource levels in surgical services

Simulation is a powerful tool for modeling complex systems with intricate relationships between various entities and resources. Simulation optimization refers to methods that search the design space (i.e., the set of all feasible system configurations) to find a system configuration (also called a design point) that gives the best performance. Since simulation is often time consuming, sampling as few design points from the design space as possible is desired. However, in the case of multiple objectives, traditional simulation optimization methods are ineffective to uncover the efficient frontier. We propose a framework for multi-objective simulation optimization that combines the power of genetic algorithm (GA), which can effectively search very large design spaces, with data envelopment analysis (DEA) used to evaluate the simulation results and guide the search process. In our framework, we use a design point's relative efficiency score from DEA as its fitness value in the selection operation of GA. We apply our algorithm to determine optimal resource levels in surgical services. Our numerical experiments show that our algorithm effectively furthers the frontier and identifies efficient design points.     

Management Control Systems: One View of Components and Their Interdependence1

Professor Robert Anthony's statement that ‘control is the process of assuring that the organization does what management wants done’ implies that systems for management control must be broadly conceived. This paper takes the view that a comprehensive view of control systems should include at least five components: performance measurement, strategy, organization structure, direction and motivation. Each of these components reflects management choices, but those choices have implications for the other components. A strategy of dynamic new product development for example, requires a flexible structure, and should have performance measures that relate to the structure and the desired achievements for that strategy. As what is measured signals what is important, the measures provide direction and the basis for incentives and rewards. The interdependence of the components is seen as a key factor in control system design. When the components support each other, the interdependence is a source of strength; conflict or even absence of support among the components can be a source of weakness. This paper describes the components and illustrates ways in which the design of control systems needs to recognize their interdependence. The process of system implementation is also reviewed, as process choices can be independent of design choices. The framework is related to prior research and writing, showing that the components are themselves complex and have been the focus of extensive study. Finally, several teaching cases are decribed in order to show how the design issues may appear in practice and how the framework can be used to help teach management control systems.     

Prokrastination als Coaching-Anliegen

Procrastination refers to non-deliberately delaying intended actions in the absence of external constraints that force one to do. It occurs frequently and can have negative consequences both for the procrastinating individual and the organizational unit in which he or she works. Procrastination tendencies of individuals themselves or of other people that they are working with can be topics that are addressed in coaching processes. The Temporal Motivation Theory provides a theoretical framework that is well suited as a guideline for structuring the coaching process in those instances and for selecting appropriate coaching tools.     

Systems‐Based Guiding Principles for Risk Modeling,Planning, Assessment,Management, and Communication

This article is grounded on the premise that the complex process of risk assessment, management, and communication, when applied to systems of systems, should be guided by universal systems‐based principles. It is written from the perspective of systems engineering with the hope and expectation that the principles introduced here will be supplemented and complemented by principles from the perspectives of other disciplines. Indeed, there is no claim that the following 10 guiding principles constitute a complete set; rather, the intent is to initiate a discussion on this important subject that will incrementally lead us to a more complete set of guiding principles. The 10 principles are as follows: First Principle: Holism is the common denominator that bridges risk analysis and systems engineering. Second Principle: The process of risk modeling, assessment, management, and communication must be systemic and integrated. Third Principle: Models and state variables are central to quantitative risk analysis. Fourth Principle: Multiple models are required to represent the essence of the multiple perspectives of complex systems of systems. Fifth Principle: Meta‐modeling and subsystems integration must be derived from the intrinsic states of the system of systems. Sixth Principle: Multiple conflicting and competing objectives are inherent in risk management. Seventh Principle: Risk analysis must account for epistemic and aleatory uncertainties. Eighth Principle: Risk analysis must account for risks of low probability with extreme consequences. Ninth Principle: The time frame is central to quantitative risk analysis. Tenth Principle: Risk analysis must be holistic, adaptive, incremental, and sustainable, and it must be supported with appropriate data collection, metrics with which to measure efficacious progress, and criteria on the basis of which to act. The relevance and efficacy of each guiding principle is demonstrated by applying it to the U.S. Federal Aviation Administration complex Next Generation (NextGen) system of systems.     

A proposed methodology for the prediction of mental workload, based on engineering system parameters

In the design of engineering systems, mental workload is one of the most important factors in the allocation of cognitive tasks. Current methods of task allocation have criteria that are defined in only general terms and are thus not very useful in aiding detailed decision-making in system design. Whilst there are many quantitative criteria available to determine the physical space in human-machine interaction, system designers really require an explicit model and specific criteria for the following identification of the mental workload imposed by the system; prediction of both human and system performance; evaluation of the alternatives of system design; and the design of system components. It is argued that the available methods of workload or performance are either too domain-dependent to apply to the design of other systems, or subject-dependent and thus do not reflect the objective workload imposed by the system. The presented research adopts a new approach to cognitive task analysis in dynamic decision-making systems. Based on the characteristics derived from task analysis, a general conceptual model of the prediction of mental workload in system design is proposed. In the new model, workload is represented by a set of system parameters—task arrival rate, task complexity, task uncertainty, and performance requirements—which are considered to be the main sources of workload. In this context, workload becomes an objective demand of engineering systems, independent of any subjective factors. Whether an individual or population is overloaded depends upon their workload threshold with respect to the specified task and environment. It is hoped that this new model, after both laboratory and industrial validation, could be used by system designers to predict the workload imposed on people by systems.     

Selecting R & D projects for development

This article describes a framework which attempts to identify R & D new product decision criteria in depth. Recommendations of attributes and measurement yardsticks, and examples of goal values, are difficult to provide since there is little support in this literature. For this reason, the major contribution of the framework is in the treatment of the attributes, yardsticks and goal values as a decision-making system. Attributes, yardsticks and goal values were chosen to complement each other and to describe a content picture.     

Relational Leadership Theory: Exploring the social processes of leadership and organizing

Relational leadership is a relatively new term in the leadership literature, and because of this, its meaning is open to interpretation. In the present article I describe two perspectives of relational leadership: an entity perspective that focuses on identifying attributes of individuals as they engage in interpersonal relationships, and a relational perspective that views leadership as a process of social construction through which certain understandings of leadership come about and are given privileged ontology. These approaches can be complementary, but their implications for study and practice are quite different. After reviewing leadership research relative to these two perspectives I offer Relational Leadership Theory (RLT) as an overarching framework for the study of leadership as a social influence process through which emergent coordination (e.g., evolving social order) and change (e.g., new approaches, values, attitudes, behaviors, ideologies) are constructed and produced. This framework addresses relationships both as an outcome of investigation (e.g., How are leadership relationships produced?) and a context for action (e.g., How do relational dynamics contribute to structuring?). RLT draws from both entity and relational ontologies and methodologies to more fully explore the relational dynamics of leadership and organizing.     

Performance evaluation based on multiple attributes with nonparametric frontiers

Performance rating and comparison of a group of entities is frequently based on the values of several attributes. Such evaluations are often complicated by the absence of a natural or obvious way to weight the importance of the individual dimensions of the performance. This paper proposes a framework based on nonparametric frontiers to rate and classify entities described by multiple performance attributes into ‘performers’ and ‘underperformers’. The method is equivalent to Data Envelopment Analysis (DEA) with entities defined only by outputs. In the spirit of DEA, the weights for each attribute are selected to maximize each entity’s performance score. This approach, however, results in a new linear program that is more direct and intuitive than traditional DEA formulations. The model can be easily understood and interpreted by practitioners since it conforms better to the practice of evaluating and comparing performance using standard specifications. We illustrate the model’s use with two examples. The first evaluates the performance of employees. The second is an application in manufacturing where multiple quality attributes are used to assess and compare performance of different manufacturing processes.     

DEA with streaming data

DEA can be interpreted as a tool for the identification of “frontier outliers” among data points. These are points that are potentially interesting because they exhibit extreme properties in that the values of their attributes, either alone or combined, are at the upper or lower limits of the data set to which they belong. A real challenge for this type of frontier analysis arises when data stream in at high rates and the DEA analysis needs to be performed quickly. This paper extends DEA into this dynamic data environment. The purpose is to propose a formal theoretical framework to handle streaming data and to answer the question of how fast data can be processed using this new framework. Potential applications involving large data sets include auditing, appraisals, fraud detection, and security. In such settings the situation is likely to be dynamic with the data domain constantly changing as new entities arrive in the course of time. New specialized tools to adapt DEA to deal with streaming data will be explored.     

Workforce/Population,Economy, Infrastructure,Geography, Hierarchy,and Time (WEIGHT): Reflections on the Plural Dimensions of Disaster Resilience

The concept of resilience and its relevance to disaster risk management has increasingly gained attention in recent years. It is common for risk and resilience studies to model system recovery by analyzing a single or aggregated measure of performance, such as economic output or system functionality. However, the history of past disasters and recent risk literature suggest that a single-dimension view of relevant systems is not only insufficient, but can compromise the ability to manage risk for these systems. In this article, we explore how multiple dimensions influence the ability for complex systems to function and effectively recover after a disaster. In particular, we compile evidence from the many competing resilience perspectives to identify the most critical resilience dimensions across several academic disciplines, applications, and disaster events. The findings demonstrate the need for a conceptual framework that decomposes resilience into six primary dimensions: workforce/population, economy, infrastructure, geography, hierarchy, and time (WEIGHT). These dimensions are not typically addressed holistically in the literature; often they are either modeled independently or in piecemeal combinations. The current research is the first to provide a comprehensive discussion of each resilience dimension and discuss how these dimensions can be integrated into a cohesive framework, suggesting that no single dimension is sufficient for a holistic analysis of a disaster risk management. Through this article, we also aim to spark discussions among researchers and policymakers to develop a multicriteria decision framework for evaluating the efficacy of resilience strategies. Furthermore, the WEIGHT dimensions may also be used to motivate the generation of new approaches for data analytics of resilience-related knowledge bases.     

ASSESSING INFORMATION SYSTEM VALUE: AN EXPERIMENTAL STUDY

Linear models of information system value that are a function of information attributes are empirically studied by having managers in two firms make assessments of the importance of attributes, the level of satisfaction produced by various levels of each attribute, and the overall value of total systems. The results verify that such models may be quite useful in information system design. It is also shown that ordinally ranked attributes work as well as the interval-scaled attributes in the linear model. Since ordinal measures are easier to obtain, this suggests that “linear ordinal” models may be the most practical method of quantifying information systems value.     

Commodification, construction and compression: a review of time metaphors in organizational analysis

This paper offers a historical review of forms of temporal structuring and experience in the evolution of work organization. Initially, we review some key images of time and temporality to emerge from philosophy and social theory. In particular, we discuss images of temporal structuring reflected in the two key time metaphors, the line and the cycle. Secondly, we examine some of the main images of time to emerge from the history of work organization. While initially the focus is upon those linear time images that stem from the progressive commodification of the labour process, subsequently this analysis is qualified by time images that reflect the social construction of organizational culture. An examination of the homogeneous time-reckoning systems of Taylorism is complemented by examples of heterogeneous time-reckoning from anthropological and ethnographic studies. Finally, we discuss the postmodernist debate in the sociology of time. Much of the foregoing analysis having been devoted to issues of clock-time, this section sees discussion of what has been referred to as "instantaneous-time", whereby organizational practices are based on time-frames that lie beyond conscious human experience. This concept is associated with the complex shifts from Fordism to the flexible accumulation of "post-Fordism". Central to this debate is the notion of the time–space compression of physical processes and human experiences.     

Modelling and controlling product manufacturing systems using bond-graphs and state equations: Continuous systems and discrete systems which can be represented by continuous models

This paper presents an approach to the modelling and control phases involved in a cooperative process of design and management of the manufacturing systems. Modelling the evolution of the production flow, in the different sections of the system, is based upon the use of the bondgraph methodology in order to reach the state formalism which constitutes one of the modern representations of automation. The class of the systems studied ranges from continuous systems to discrete systems, which can be represented by a continuous approach according to the level of approximation required. The first part of this paper is dedicated to the development of generic models associated with the various basic entities of the manufacturing systems. Then, the bondgraph model of any system is obtained by assembling generic models in relation to the implementation of the means of the studied system, thus guaranteeing a representation which is quite close to the engineering sketches. Finally, switching to the state equation is performed systematically with the easiness provided by this formalism while taking into account the causality principle. An application, involving most of the elementary models developed, concludes the paper.     

The Creation of Output and Quality in Services: A Framework to Analyze Information Technology‐Worker Systems

Information technology has profoundly impacted the operations of firms in the service industry and service environments within manufacturing. Two models are introduced that establish a conceptual framework linking firm profit to attributes of the IT‐worker system. The framework considers the impact of IT capabilities (such as functionality and ease‐of‐use) and worker skill as drivers of output volume and quality. The framework contrasts attributes of the IT‐worker systems when services are mass‐produced (flow shop) versus customized (job shop). Mathematical models are introduced to formalize the conceptual framework. Numerical examples are presented that illustrate the types of insights that can be obtained from the models.     

The stability of strategic alliances: Characteristics, factors and stages

This paper presents a theoretical framework for understanding the evolutionary dynamics of strategic alliances. Using an integrated process model, we analyze the conceptual characteristics and antecedents of the stability of strategic alliances. The primary purpose of this study is to (1) conceptualize and characterize alliance stability to fill the academic gap in the literature, and (2) identify a range of endogenous factors underlying alliance stability across four developmental stages — partner selection, structuring/negotiation, implementation and performance evaluation — so as to fill the managerial relevance gap. From the discussion, we develop a number of propositions to facilitate future empirical testing of our conceptual model. Finally, we indicate some key implications for theoretical research and managerial practice.     

Utility‐consistent Brand Demand Systems with Endogenous Category Consumption: Principles and Marketing Applications*

This paper introduces the design and implementation of utility‐consistent, brand, and category demand systems. It extends formal demand analysis to the area of brand and category demand, which directly concerns marketing researchers and managers. The proposed brand demand system is a set of interrelated demand functions that are derived explicitly from a utility function describing consumer preferences. The model generalizes by the integration of category expenditures, which are determined endogenously. The theoretical plausibility of the proposed demand model is demonstrated first and, subsequently, brand and category level systems are derived. Econometric methods for estimating the systems are also developed and illustrated in empirical data. The results yield empirically determined, quantitative insights into the structure of consumer demand for brands and product categories. The proposed approach has the attractive feature of structuring the interdependencies of consumer decisions and ensuring an explicit role for theory in applied research.     

Evidence-based versus tinkerable knowledge as strategic assets: A new perspective on the interplay between innovation and application

Organization success depends, at least in part, on a firm's ability to wisely manage what it knows in order to capitalize on technical achievements, develop new products and services, realize the benefits of innovation, achieve effective scale economies, and continuously advance and control its operations. This paper departs from familiar approaches to categorizing knowledge resources to distinguish between knowledge resources that are appropriate to replicate ‘as is’ (evidence-based knowledge resources) and those that are best suited to contribute to innovation and creative activity (tinkerable knowledge resources). A set of criteria for classifying different types of knowledge flow mechanisms is also introduced. We propose a framework for determining effective fit between knowledge resources and the mechanisms used to move and apply those resources. We discuss the benefits of achieving fit and the liabilities of misfit and illustrate these ideas with examples drawn from a variety of sources. The paper concludes with a discussion of implications for future research.