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The purpose of this paper is to present and test a new model for competitive capabilities. Traditionally, a cumulative model has been viewed as having one sequence of building competitive capabilities in a firm in support of market needs, including quality, delivery, cost efficiency and flexibility. Although appealing as a conceptual model, empirical testing has not been able to fully support the cumulative model. This paper acknowledges the need for a hybrid approach to managing capability progression. It brings together the literature on trade‐offs, cumulative capabilities, and order winners and qualifiers.

A new hybrid approach for modelling competitive capabilities is tested empirically using data from the high performance manufacturing (HPM) study, round 3, including three industries and seven countries – a total of 211 plants.

The hybrid model shows significantly better fit with the data from the sample than the cumulative models suggested by previous literature. Empirical support is found for the traditional perception that a high level of quality is a prerequisite for a high level of delivery performance. However, cost efficiency and flexibility do not exhibit a cumulative pattern. Instead, the results show that they are developed in parallel. The findings suggest that a balance between cost efficiency and flexibility is built upon high levels of quality and delivery performance.

Since we limit the empirical investigation to three industries and seven countries, it would be interesting to extend the testing of this model to more industries and countries. This research shows that combining perspectives and insights from different research streams – in this case, trade‐off theory and the concepts of cumulative capabilities, and order winners and qualifiers – can be fruitful.

The results of this paper provides managers with guidelines concerning the configuration of competitive capabilities. First, a qualifying level of quality needs to be attained, followed by a qualifying level of delivery. Then, a balance between potential order winners, i.e. cost efficiency and flexibility, needs to be attained.

This paper presents a new approach to modelling competitive capabilities that synthesises previous research streams and perspectives from cumulative capabilities, contesting capabilities (trade‐offs), and order winners and qualifiers.

The continuous need for change in corporate real estate spaces warrants consideration of flexibility in new space design. To help decision makers invest more effectively in physical infrastructure and its ability to evolve, a formal method of identifying and valuing flexibility is developed. A model, based on real options techniques for valuing managerial flexibility, is constructed to answer the following question: how much is it worth to invest in a space that could be renovated to office space for a specified renovation cost in the future? Decision makers can use the option valuation results to determine whether the initial design and construction costs to achieve flexibility are justifiable. The transparent model is intended to be accessible to design teams in practice. It is an improvement on net present value and first‐cost based decision‐making techniques in that it explicitly accounts for uncertainty and for the ability of managers to make a rational future decision (between renting and renovating). The model considers three sources of uncertainty: the market price of rent for office space (as measured by volatility); date of space need; and amount of space need. Input values and/or probability distributions are needed for these variables. The model is constructed using a binomial lattice technique and Monte Carlo simulation. Results are given in a format that allows for comparison with cost estimates of physical architectural designs. For example, in a case study where current five‐year office‐space leases are estimated at US$98 per square foot and 0.39 annual volatility and the mean amount of space needed in the future is 50 per cent of the total, the real options valuation suggests that it is worth up to US$40 per square foot in initial investment expenses to achieve a space that could be renovated to office space for US$25 per square foot within the next eight years. The concept of addressing risk through ‘flexible design’ and analysing the value of flexibility is pertinent to judicious management of any new building project that is subject to uncertain future conditions.

The purpose of this paper is to examine the relationships between strategic manufacturing capabilities, particularly whether they are cumulative or trade‐off in nature.

Uses statistical analyses, particularly structural equation modelling based on data from the third round of the International Manufacturing Strategy Survey.

Finds mostly cumulative effects between the strategic capabilities. Shows that “quality” is a basis for “delivery”, which is a basis for “flexibility” and “cost”; between “flexibility” and “cost” an unclear relationship is found. Whether “flexibility” and “cost” are pursued exclusively or simultaneously seems to be connected with the implementation of certain improvement programmes.

Results cannot be interpreted in a prescriptive way, but only as descriptive findings stemming from a large empirical database. Future research in this area needs to be extended by longitudinal analyses and simulation studies because cross‐sectional analyses can only provide indirect empirical measures of dynamic changes of capabilities.

Describes a common pattern of capability accumulation in the industries investigated. This information can be used to estimate potential competitor behaviour or as a way to perform in an innovative manner.

Offers a clear conceptualisation of strategic capabilities with the help of an empirical study.

Cumulative capability models are dominating frameworks explaining how manufacturing organizations gain their performance capabilities, such as quality, delivery, flexibility and cost. When innovation capabilities are excluded from the framework, the models are incapable of explaining how companies sustain substantive capabilities in a changing environment. Responding to this gap, the purpose of this paper is to propose and test a “sand cone” cumulative capability model that includes the innovation competitive performance alongside the competitive performance of quality, delivery flexibility and cost.

Two competing cumulative models were proposed. The extended cumulative capability model hypothesizes the development of innovation in sequence with other competitive performance dimensions. The affected with innovation cumulative model hypothesizes innovation performance as a predecessor of other performance dimensions. The models were tested using a multimethod approach on a representative sample of 500 manufacturing companies. An analysis of correlations among competitive performance, frequencies of plants following prescribed sequences, fit statistics of covariance-based structural equation modeling and analysis of strength and statistical significance of path coefficients enabled us to select a model that best represents the collected data.

The findings reveal that innovation competitive performance operates as a predecessor of quality, delivery, flexibility and cost and is developed in relation to these performance dimensions. The modified model also provides a theoretical explanation of how innovation performance helps to sustain reliable production systems that can perform consistently over time within a tolerable range of quality, delivery, flexibility and cost performance.

The results are significant for practitioners, especially for companies that are operating in volatile environments because the results provide insight on how to develop innovation competitive performance in relation to quality, delivery, flexibility and cost performance.

This study extends the cumulative capability models with innovation competitive performance. It advances the contingency approach on cumulative capability models.

The purpose of this study is to identify a typology of procurement contracts in the context of software development projects that allows firms to align design flexibility with design uncertainty at the project level. The theoretical lenses of contract theory and software engineering are used to explain why the five archetypes in the proposed typology provide gradually increasing levels of design flexibility and to develop hypotheses about the associations between design flexibility and a set of project cost dimensions.

The hypotheses are tested with objective contractual data from 270 software development contracts entered into by a leading international bank over a period of three years.

Data analysis confirms the existence of the proposed typology and shows that design flexibility is negatively associated with control and positively associated with coordination, trust, duration and price.

Although the findings are based on the contracting practices of a single, albeit sophisticated, organization, they shed light on the ability of firms to align flexibility with uncertainty at the onset of new projects by taking advantage of nuanced contractual mechanisms to produce a broader set of contractual archetypes.

This paper is the first in the outsourcing literature to analyze a nuanced contractual typology in software development projects through the perspectives of both contract theory and software engineering.

Companies must use their resources effectively and productively if they are to compete in an increasingly competitive globalized economy. Effective performance measurement can support this competitiveness. To be able to do this, companies must know the factors that influence their performance and manage these factors in an effective manner. This study seeks to investigate the effect of manufacturing strategies of manufacturing companies on their financial performance and also the effect of firm size on the impact of manufacturing strategies.

A total of 200 manufacturing companies that are registered under the Chamber of Commerce in Gebze, Turkey were selected and their managers interviewed. A total of 102 questionnaires were returned out of 200. Regression analyses were performed using the results of the survey.

It was found, that an increase in the quality and cost/flexibility increased financial performance. However, the rate of delivery did not have any statistical influence on the financial performance. On the basis of the analysis done on the firm size, the last finding is that the effect of the quality and cost flexibility on financial performance is higher for large companies compared with SMEs.

The paper identifies the manufacturing strategies that significantly influence the financial performance of manufacturing companies and the effect of firm size on the effect of these strategies.

This study analyzes strategic flexibility with a two-dimensional approach (structural and decisional flexibility). It also investigates the relationships among competitive strategy, structural flexibility, decisional flexibility, and financial and nonfinancial performance.

The authors collected data from members of 16 chambers of commerce in the United States and used PLS-SEM (partial least squares structural equation modeling) to test the hypotheses.

The findings suggest that strategic flexibility impacts financial and nonfinancial performance in different ways. While financial performance is influenced by both the structural and decisional dimensions of strategic flexibility, nonfinancial performance is impacted only by structural flexibility. In addition, the research indicates a negative relationship between cost leadership and structural flexibility and positions structural flexibility as a mediator between cost-leadership and nonfinancial performance.

The authors contribute to strategic flexibility research in the following ways: (1) analyzed the impact on nonfinancial performance; (2) examined structural and decisional elements and (3) identified cost leadership as a potential barrier.

The purpose of this paper is to examine whether modular product design is an appropriate practice to improve manufacturers’ flexibility performance and cost performance as well as to evaluate whether combined effects of modular product design and delivery performance on flexibility performance and cost performance exist.

Structural equation modeling with moderating effects is used. Moderating effects allow an evaluation whether combined effects of modular product design and delivery performance exist. For the analysis, data from the international high-performance manufacturing survey are used.

Analysis results show a positive relationship between modular product design and cost performance, but do not show a significant moderating effect. Thus, no combined effect of modular product design and delivery performance exists in the data at hand.

A potential limitation of this study is the cross-sectional nature of the analysis. In order to test for causal relationships or chronological sequences, longitudinal data are deemed more suitable.

The findings make improvement processes more predictable and help managers to overcome traditional trade-off situations, especially in terms of flexibility performance and cost performance. Manufacturers are still neglecting the implementation of complementary methods for achieving an increase in flexibility while maintaining efficiency.

This paper complements prior research on the effect of improvement practices on operational performance dimensions. It also takes an alternative approach to examine whether a beneficial implementation sequence of improvement practices can be assumed.

The purpose of this paper is to examine how active consumers, i.e. consumers that can inter-temporally shift their load, can influence electricity prices. As demonstrated in this paper, inter-temporal load shifting can induce negative electricity prices, a recurring phenomenon on power exchanges.

The paper presents a novel electricity-market model assuming a nodal-pricing, energy-only spot market with active consumers. This study formulates an economic equilibrium problem as a linear program and uses an established six-node case study to compare equilibrium prices of a model with inflexible demand to a model with flexible demand of active consumers.

This study illustrates that temporal coupling of hourly market clearing through load shifting of active consumers can cause negative electricity prices that are not observed in a model with ceteris paribus inflexible demand. In such situations, where compared to the case of inflexible demand more flexibility is available in the system, negative electricity prices signal lower total system costs. These negative prices result from the use of demand flexibility, which, however, cannot be fully exploited due to limited transmission capacities, respectively, loop-flow restrictions.

Literature indicates that negative electricity prices result from lacking flexibility. The results illustrate that active consumers and their additional flexibility can lead to negative electricity prices in temporally coupled markets, which in general contributes to increased system efficiency as well as increased use of renewable energy sources. These findings extend existing research in both the area of energy flexibility and causes for negative electricity prices. Therefore, policymakers should be aware of such (temporal coupling) effects and, e.g. continue to allow negative electricity prices in the future that can serve as investment signals for active consumers.

In this paper we introduce a simulative model, designed and developed to optimally manage an integrated finished goods inventory system, and suitable for adoption in a wide range of make to stock manufacturing firms. The goal of the model is to manage optimally finished goods inventory levels, in order to minimize costs deriving from holding inventory and from adjustment to the master production schedule (MPS) to prevent stock‐outs. A trade off is sought between these costs components. The input variables of the model are: safety stock levels, assessed through coefficients k1, k2 and k3, and the stochastic distribution functions of products demand. The model performances are assessed considering the annual total cost for the inventory management. The model is then tested by a numerical application. The case considered refers to a major firm operating in the zootechnical feeds production industry.