An activity decomposition methodology with theoretical foundation in the principles of activity control and stated focus of interest in the enterprise value-chain is presented. Characteristics of inputs and outputs are discussed, where a set of non-transformable inputs are defined and motivated. An integrated partial efficiency measure is formulated, compensating for some weaknesses of the Debreu-Farrell technical efficiency concept. Providing a coherent basis for productivity analysis, the IPE approach poses an alternative to e.g. DEA especially in the case of multi-level systems and sparse data. The method is easily communicable in terms of measurement and analysis, and may be extended to complement economic performance assessments and benchmarks.

A multi-criteria formulation for continuous and discrete-time dynamic systems is presented. The fundamental problem in the design of dynamic systems is the trade-off between response speed (e.g., the time to reach final value and the raise time) and response smoothness (e.g., the overshoot, the undershoot, and the transient dampening). Separate optimisation of criteria is impossible, thus the problem is inherently multiobjective. In a general dynamic system, this is accomplished by adjusting a number of technical parameters in accordance with some ad hoc practice. Previous multi-criteria approaches have been modelled as weighted sums of criteria, with shortcomings in terms of sensitivity analysis and preference articulation. The proposed framework enables the decision maker to design a most preferred system, with full knowledge of local trade-off ratios in terms of chosen criteria. Combining analytical techniques with simulation, the formulation makes the optimisation process transparent to the decision maker, working entirely in decision space. The framework is demonstrated on a dynamic production-inventory model.

This study of scheduling work in practice addresses how the production scheduling processes in four companies are influenced by human, technological, and organizational aspects. A conclusion is that the outcome of the scheduling process is influenced by the scheduler adding human capabilities that cannot be automated, by technical constraints in the scheduled production system and by the available scheduling software tools. Furthermore, the outcome is influenced not only by how the scheduling process is formally organized, but also by the scheduler’s informal authority and the role taken to interconnect activities between different organizational groups. The findings from the study support a number of previous studies done on scheduling in practice whilst giving new insights into their interpretation.

This study explains the constructs of a purchasing portfolio model (PPM) that defence authorities can use in practice in defence procurement and designs a segmentation model. We identify open PPM design and application questions in the literature and conduct a Delphi study with twenty experts from Swedish defence authorities to design a segmentation model that is fit-for-purpose. The paper addresses the open design and application questions discussed in the literature and satisfies the operational requirements of the Swedish Armed Forces (SwAF). The proposed segmentation model builds on three dimensions: the operational requirements of the SwAF, the market's ability to deliver supplies on time, and limitations in the SwAF operational capability if the market does not deliver supplies on time. To reduce complexity, we propose a two-stage model in which we use one dimension as a precursor to a two-dimensional model. In the latter, we merge sixteen elements into one square along with three other segments which users should treat differently. The paper contributes to extant academic knowledge on PPMs by eliciting practitioners' views on open design and application questions. We develop the proposed segmentation model in cooperation with practitioners and believe that it will be of value in defence procurement practice.

The paper aims at presenting the thoughts behind concurrent cost estimation as a tool for engineering companies to obtain enhanced producibility for their products by the possibility of performing producibility studies. The two main parts of the paper are: the presentation of a method for system development, focusing on a number of general criteria of system development; and how such a system can act as a support in the product development process by providing the possibility of performing different types of producibility studies.

In this article we model standard inventory ordering rules in terms of control systems theory. A differential equation is designed describing the development of a system in which an input signal reaching a predefined level triggers an output. The reorder point of inventory control systems may be interpreted as such a level triggering a replenishment. Systems using this kind of control are frequent in a variety of applications. Apart from inventory, domestic heat and pressure control are but two examples.

Dynamic capabilities such as flexibility are considered influential in achieving superior performance, especially under uncertain circumstances. Among others, postponement is a well-established concept in operations and supply chain management (OSCM) and has been regarded as a key concept in managing supply and demand while increasing flexibility. This study investigates the effect of postponement on logistics flexibility, and that of the latter on retail firm performance. In addition, the moderating roles of logistics integration and demand uncertainty on these relationships are investigated. The study utilizes a quantitative survey and draws on a sample of 261 retailers in Sweden. Logistics flexibility proves to have a mediating role in the postponement–performance relationship. Furthermore, we provide support for the direct effect that postponement can have on logistics flexibility, and the subsequent effect of logistics flexibility on retail firm performance. We contribute by simultaneously studying postponement and logistics flexibility in the retailing context. We find conditional support for the moderating roles of logistics integration and demand uncertainty. The results show that for medium levels of uncertainty, the positive relationship between postponement and logistics flexibility, as well as logistics flexibility and firm performance, are intensified. From a practical standpoint, the findings underline that in the presence of high or low demand uncertainty, applying postponement may not always be beneficial in achieving logistics flexibility, and subsequently better performance. Moreover, if retailers prioritize logistics integration, they should not always expect superior performance gains from the flexibility benefits of postponement.

The pharmaceutical landscape has changed, and new business models, based on alliances, are increasingly being adopted in this industry. Biotechnology advances have pushed this development, and pooling complementary resources coming from incumbents and newcomers is a key skill to succeed: these are the premises for a quick spread of the open innovation (OI) paradigm in this industry. R&D portfolio selection needs R&D project evaluation, and Real Options Analysis (ROA) is acknowledged as a powerful tool to evaluate uncertain projects that have an intrinsic flexibility. The present research aims to foster the use of ROA in the OI field in order to encourage firms to undertake this innovation model; to achieve this goal the authors propose a closed-form model that is easy to implement, to evaluate the OI initiative for selecting an optimal R&D portfolio. The study wants to support managers in optimal R&D portfolio construction in terms of choosing the most promising products, the means by which the related project has to be undertaken (in an open or closed manner; i.e. licensing-in or not) and the self-financing policy. The proposed model can be easily implemented into a spreadsheet, and the inputs needed to run it are usually requested to evaluate projects using the most used net-present-value-based methods. Moreover, some parameters of the model allow strategic aspects to be considered: for example the nature of the project (core/non-core), the impending project phase, and the risk-sharing opportunity. The results of the developed numerical example show that the selected portfolio is well balanced in terms of development stages, core/non-core therapeutic areas and, licensing-in (an inbound open innovation solution), is preferred in the case of products at their early stages of development.

This paper is an empirical analysis of knowledge capital and performance heterogeneity at the firm level. We apply new econometric methods to extensive data on innovation and innovative activities in Swedish manufacturing. A number of interesting results emerge. First, the results show that knowledge capital, defined as the ratio of innovation sales to total sales, is found to be a significant factor contributing to performance heterogeneity among firms. This relationship holds even when we control for human capital, type of output, firm size, and the entry, merger, partial closure or exit of firms. Second, knowledge capital rises with innovation input, the firm’s internal knowledge for innovation, and co-operation on innovation with domestic universities. Third, when controlling for differences in innovation investments and human capital, knowledge-intensive firms are not more innovative than labor-intensive or capital-intensive firms. Fourth, organizational rigidities in innovation projects and a lack of appropriate investment sources for innovative activities are found to have a negative impact on productivity. Finally, we find a positive association between an outspoken aggressive innovation strategy, customers and a firm’s internal resources for innovation and the size of innovation investment. ©2002 Elsevier Science B.V. All rights reserved.

Business sustainability integration is a complex task and strongly linked to operations management. In fact, sustainability based approaches demand operations management boundaries' expansion, creation and integration of new performance goals into traditional company's performance management system, and new criteria and policies for operations' decision areas development. The challenge is to conduct more sustainable operations through companies' value chain and their operations network. Maturity models have been used in different areas as a process improvement and change management model for complex contexts. In sustainable operations management area, maturity models have been developed for specific purposes, e.g., sustainable production, sustainable supply chain management, corporate social responsibility, and life cycle management. However, there is a lack of models that considers sustainability integration through the evolution of sustainable operations' capabilities in an integrated way. Based on literature review and results from two panel studies conducted with academics and practitioners, this paper proposes a maturity framework for sustainability integration guided by sustainable operations capabilities evolution. The findings pointed out that its is possible to identify an evolutionary path, which goes from an initial approach focused in compliance aspects and firm's value protection to an innovative approach, based on corporate social responsibility supporting operations' integration in a sustainable system, and long-term values development. The experts' studies identified key processes that need to be prioritized in each level, and also evaluate the adaptation of some elements from Capability Maturity Model Integration (CMMI) to sustainable maturity framework design. The framework represents company's vision regarding its value chain and operations network, and it is indicated for manufacturing companies.

Scania has performed well above average in the heavy truck industry during a considerable time span. Scania's sources of competitive advantage are presented and their interrelations and significance for the business strategy analysed in order to explain the success of Scania. Strategic issues are traditionally analysed in a top-down procedure starting with the corporate strategy and proceeding by disaggregation of the strategy down in the organisation. This is known as the grand strategy perspective and views strategy as a “chain of causality”. We introduce the grounded strategy perspective which views strategy as a “pattern in a stream of decisions and actions”, and takes its starting point in the stream of activities within the company. Grounded strategy synthesises the strategy according to a bottom-up procedure. The case of Scania and the heavy truck industry is analysed according to these two different perspectives on strategy. The methodological approach may be different depending on the perspective. The results of the case study from each perspective reveal interesting implications to strategists: scholars as well as practitioners. The grand strategy approach appears to be advantageous for analysis at the higher levels of strategy, while the grounded approach appear to be advantageous at the lower levels of strategy.

Efficient long-term capacity management is vital to any manufacturing firm. It has implications on competitive performance in terms of cost, delivery speed, dependability and flexibility. In a manufacturing strategy, capacity is a structural decision category, dealing with dynamic capacity expansion and reduction relative to the long-term changes in demand levels. Sales and operations planning (S&OP) is the long-term planning of production levels relative to sales within the framework of a manufacturing planning and control system. Within the S&OP, resource planning is used for determining the appropriate capacity levels in order to support the production plan. Manufacturing strategy and sales and operations planning provide two perspectives on long-term capacity management, raising and treating different issues. In this paper, we compare and link them in a framework for long-term capacity management.

If automation is to support the competitiveness for a manufacturing company, strategic as well as operational issues need consideration. To best support competitiveness, decisions concerning automation should be treated as one of several decisions in a manufacturing strategy. Furthermore, to fully utilise the advantages from automation, the manufacturing strategy content and process needs refinement. In this paper improvement of the manufacturing strategy theory is suggested, mainly based on employment of human factors engineering.

A three-echelon Forrester production distribution system is used as a supply chain reference model for comparing various methods of improving total dynamic performance. Many authors have exploited the original simulation results for the nominal system, especially when describing problems associated with supply chain behaviour. However, few of these authors have attempted to produce a dynamically superior supply chain as distinct from offering detailed organisational and attitudinal changes needed to achieve any improvement. As the starting point of this paper, the production-distribution system has been transformed into a block diagram representation capable of considerable simplification. A combination of analysis and simulation can then be used to gain a far deeper understanding of the system dynamics than has so far been published. Thus, although the Forrester model is far from optimal, it does provide a well established benchmark against which proposals may be evaluated. For the purpose of illustration, five different approaches are then used to improve the supply chain dynamics. These are

-“fine tuning” the existing ordering policy parameters;

-reducing system delays;

-removal of the distribution echelon;

-changing the individual echelon decision rules;

-better use of information flow throughout the supply chain.

It is shown that by better utilisation of the information flow, significant reductions in the demand amplification can be achieved without substantial expenditure. This is because it is only necessary to separate out the flow of “real” orders from “system” orders as they are passed up the chain. Such collaboration does, however, correspond to the establishment of an integrated supply chain in which the concept of “total system stocks” is accepted.