Kevin J. Dooley

Supply networks and complex adaptive systems: control versus emergence

In much of the current literature on supply chain management, supply networks are recognized as a system. In this paper, we take this observation to the next level by arguing the need to recognize supply networks as a complex adaptive system (CAS). We propose that many supply networks emerge rather than result from purposeful design by a singular entity. Most supply chain management literature emphasizes negative feedback for purposes of control; however, the emergent patterns in a supply network can much better be managed through positive feedback, which allows for autonomous action. Imposing too much control detracts from innovation and flexibility; conversely, allowing too much emergence can undermine managerial predictability and work routines. Therefore, when managing supply networks, managers must appropriately balance how much to control and how much to let emerge.

A complex adaptive systems model of organization change.

The study of complex adaptive systems has yielded great insight into how complex, organic-like structures can evolve order and purpose over time. Business organizations, typified by semi-autonomous organizational members interacting at many levels of cognition and action, can be portrayed by the generic constructs and driving mechanisms of complex adaptive systems theory. The purpose of this paper is to forge a unified description of complex adaptive systems from several sources, and then investigate the issue of change in a business organization via the framework of complex adaptive systems. The theory of complex adaptive systems uses components from three paradigms of management thought: systems theory, population ecology, and information processing. Specific propositions regarding the nature of dynamical change will be developed, driven by the complex adaptive systems model. Supporting evidence for these propositions is then sought within the existing management theory literature. In doing so, the complex adaptive systems approach to understanding organization change will be better grounded in domain-specific theory, and new insights and research areas will come to light.

Sustainable Product Indexing: Navigating the Challenge of Ecolabeling

There is growing scientific evidence that improving the sustainability of consumer products can lead to significant gains in global sustainability. Historically, environmental policy has been managed by bureaucracies and institutions in a mechanistic manner; this had led to many early successes. However, we believe that if policy concerning product sustainability is also managed in this way, negative unintended consequences are likely to occur. Thus, we propose a social-ecological systems approach to policy making concerning product sustainability that will lead to more rapid and meaningful progress toward improving the environmental and social impacts of consumer products.

Dynamic rules for due-date assignment

This paper presents two new dynamic due-date assignment rules which utilize shop congestion information. The new rules estimate job flowtime based on a sampling of recently completed jobs. These rules are compared with other established flowtime estimate models on the criterion of due-date performance via computer simulation. To evaluate the robustness of the rules, an experimental design with three different queue sequencing heuristics and two different shop balance levels was used. The results of this investigation clearly indicate that flowtimes from recently completed jobs provide very useful information for establishing effective due-dates in a job shop environment. In addition it is shown how the use of particular sequencing rules greatly increases the precision of flowtime estimates.

Strategies for software reuse: a principal component analysis of reuse practices

This research investigates the premise that the likelihood of success of software reuse efforts may vary with the reuse strategy employed and, hence, potential reuse adopters must be able to understand reuse strategy alternatives and their implications. We use survey data collected from 71 software development groups to empirically develop a set of six dimensions that describe the practices employed in reuse programs. The study investigates the patterns in which these practices co-occur in the real world, demonstrating that the dimensions cluster into five distinct reuse strategies, each with a different potential for reuse success. The findings provide a means to classify reuse settings and assess their potential for success.

Identification of change structure in statistical process control

In order to diagnose properly quality problems that occur in manufacturing the diagnostician, be it human or computer, must be privy to various sources of information about the process and its behaviour. This paper describes how neural networks and Bayesian discriminant function techniques can be used to provide knowledge of how a product characteristic changed, i.e. shift in mean or variability, when so noted by the control chart application. Such information is useful because there usually exists some underyling knowledge about the physical phenomena in question that relates the behaviour of the observed characteristic to its processing variables. When a change in the process is detected by the appropriate statistical method, a feature vector of process-related statistics is used to identify the change structure as a shift in mean or variance. This paper addresses various issues concerned with this problem, namely: process change detection, feature vector selection, training patterns, and error rates. S...

An investigation of dynamic group scheduling heuristics in a job shop manufacturing cell

SUMMARY The objective of this study is to develop dynamic scheduling heuristics for cellular manufacturing environments (group scheduling or family heuristics) and compare them with existing family heuristics under various shop floor conditions. The proposed family heuristics stress good due date performance while reducing overall set-up time. Computer simulation is used to test three queue selection rules in conjunction with three dispatching rules under eight experimental conditions in a job shop cell. The results indicate that several of the proposed heuristics substantially improve the performance of the cell over the best previously suggested family heuristic under all experimental conditions.

Productivity as a Performance Measure

Both the improvement of productivity and the effectiveness of performance measures have been topics of extreme interest to managers and researchers in recent years. Looks at the potential advantages and disadvantages of using the traditional productivity measure, output/input, as a measure of performance at the firm, work‐unit, individual, product, or product‐line level. Considers the ability of productivity measures to adjust for price changes and to detect factor substitutions. The distortion of productivity measures by fixed expenses and the inability of productivity measures to consider quality changes are among the disadvantage cited. Also, criticisms that have been levelled at traditional cost accounting measures are found to apply to productivity measures. Proposes three criteria that can aid in determining when productivity measures are appropriate as performance measures. Makes recommendations for ways of using productivity measures effectively also.

ADOPTION RATES AND PATTERNS OF BEST PRACTICES IN NEW PRODUCT DEVELOPMENT

Firms are experimenting with numerous different best practices in order to improve the timeliness and effectiveness of their new product development (NPD) process. This paper examines how widely adopted certain best practices are, and if the adoptions show any pattern in terms of being simultaneously adopted within organisations. We developed an inventory of best practices related to NPD, and an empirical survey was administered to 39 companies. Our results indicate that best practices associated with enhancing the human resources involved in NPD, and improving the fuzzy front end of NPD appear to be getting little attention to date, despite a strong call for such attention in the management literature. Best practices associated with the strategic implementation of NPD (project selection, goals, technological leadership, product strategy, and customer involvement) are on average all more widely adopted than best practices associated with controlling the execution of NPD (process control, metrics, documentation, change control).

Forces, trends, and decisions in pharmaceutical supply chain management

Purpose – The purpose of this paper is to identify and examine the major forces that are changing the way biopharmaceutical medications are purchased, distributed, and sold throughout the supply chain. This will become important as healthcare reform moves forward, and logistics will be transformed in this industry.Design/methodology/approach – Multiple interviews with key informants at each level of the value chain were combined with manifest text analysis from practitioner articles to derive key insights into the primary change drivers influencing the future of the biopharmaceutical supply chain.Findings – The research discovered radical shifts in the structure of the biopharmaceutical supply chain. Future research into biopharmaceutical supply chain practices will need to explore three primary issues: How will supply chain member compensation influence the power of parties within the network? How will the role of supply chain intermediaries change the landscape of medication delivery to the end customer...