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Short‐termism, especially in terms of marketing strategy, is supposed to be a problem afflicting various managements. We have found that one solution may be found in separating out longer‐term robust strategies from shorter‐term corporate strategy in a formal long‐range marketing plan. Using this approach, which starts with scenario forecasting and ends with the robust strategies coming out of this being compared with existing corporate strategy. The differences are usually easily reconciled, where the two typically converge on much the same issues. As a result, organisations are better able to ensure survival in the longer term. If they follow sound marketing practices, indeed, the price they might have to pay, in terms of the short‐term steering (changes), is usually small.

The purpose of this paper is to inform of the development and use of comprehensive system dynamics model for the formulation of robust strategies in project manufacturing business.

Experiences from action research involving field study with project manufacturing businesses are reported.

It is possible, using readily available resources, to develop comprehensive system dynamics model for project manufacturing business which can be used to facilitate the formulation of robust strategies.

Field study involved only five businesses serving three project manufacturing sectors.

The need for better approaches for dealing with dynamic complexity in project business is recognized in the literature. However, extant models deal with single projects or a few aspects of multiple projects. The research suggests that companies can develop system dynamics models that go beyond multiple projects to encompass broader business issues which cause effects within their projects. Further, such comprehensive models can be used to formulate robust strategies.

The originality of the research reported in this paper is that both immediate sources, and ultimate sources, of dynamic complexity are described. Extant system dynamics models are concerned with either, but not both. Hence, extant models are not comprehensive. That is, they do not encompass the full extent of sources of dynamic complexity in project business. The value of this paper is that it offers practical examples to inform the development of comprehensive system dynamics model for project manufacturing business. Moreover, the use of comprehensive model to facilitate the formulation of robust strategies is explained.

The purpose of this paper is to develop a mathematical model for the design of robust layout for unequal area-dynamic facility layout problem with flexible bay structure (UA-DFLP with FBS) and test the suitability of generated robust layout in a dynamic environment.

This research adopts formulation of a mathematical model for generating a single layout for unequal area facility layout problems with flexible bay structure under dynamic environment. The formulated model for the robust layout formation is solved by developing a simulated annealing algorithm. The proposed robust approach model for UA-DFLP with FBS is validated by conducting numerical experiments on standard UA-DFLPs reported in the literature. The suitability of the generated robust layout in a dynamic environment is tested with total penalty cost criteria.

The proposed model has given a better solution for some UA-DFLPs with FBS in comparison with the adaptive approach’s solution reported in the literature. The total penalty cost is within the specified limit given in the literature, for most of the layouts generated for UA-DFLPs with FBS. In the proposed model, there is no rearrangement of facilities in various periods of planning horizon and thus no disruptions in operations.

The present work has limitations that when the area and aspect ratio of the facilities are required to change from one period to another, then it is not possible to make application of the robust approach-based formulation to the dynamic environment facility layout problems.

Rearrangement of facilities in adaptive approach disrupts the operations whereas in the proposed approach no disruption of production. The FBS approach is more suitable for layout planning where proper aisle structure is required. The solution of the proposed approach helps to create a proper aisle structure in the detailed layout plan. Thus, easy interaction of the material handling equipment, men and materials is possible.

This paper proposes a mathematical formulation for the design of robust layout for UA-FLPs with FBS in a dynamic environment and an efficient simulated annealing algorithm as its solution procedure. The proposed robust approach generates a single layout for the entire planning horizon. This approach is more useful for facilities which are difficult/sensitive to relocate in various periods of the planning horizon.

Prepaid mobile Internet is one of the most profitable services that are composed of multiple attributes. The overall utility of Internet service can be broken down into the sum of the utility of individual attribute levels. Based on the multi-attribute theory, rational consumers choose the service that yields the highest utility from a number of possible alternatives. Determining the optimal attribute levels that satisfy consumers' preferences and maximize the total revenue of the firm is a challenging multi-attribute decision problem for any mobile operator. When designing mobile Internet services, adopting a robust composition of services against different realizations of competitors' strategies can bring advantages for network operators. The purpose of this study is to determine the optimal attribute levels of prepaid mobile Internet packages with the aim of maximizing the total revenue of the firm by considering the paradigms of multi-attribute utility theory about consumer choices and the issue of uncertainty in counterpart services offered by the competitors.

This paper formulates the problem of multi-attribute pricing and design of mobile Internet plans in a competitive environment by developing deterministic and robust scenario-based mathematical models and considering the paradigms of multi-attribute utility theory about consumer choices. The proposed robust scenario-based models are based on three different paradigms, including maximizing expected revenue, minimizing the negative deviation from expected revenue and minimizing the maximum regret. A comprehensive numerical analysis is conducted to evaluate and compare the efficiency of the proposed models.

The evaluations reveal that deploying recourse policy can result in higher revenue for the firm when facing uncertainty. By doing sensitivity analysis, this paper shows that consumer preferences for brand attribute and consumers' purchase frequency can influence the revenue of network operators.

This paper develops a novel deterministic multi-attribute product line design (PLD) model to address the problem of determining the price and composition of prepaid mobile Internet plans. Furthermore, the issue of uncertainty in counterpart services offered by the competitors is studied for the first time in the PLD literature.

The most important results of our recent work, the culmination of a decade of global research involving several thousand managers and professionals from large organisations, are explored in terms of how long‐range planning may be undertaken more effectively by a wider range of organisations. Thus, it has proved possible to use (simpler) scenario techniques to explore their likely futures and then develop suitable robust strategies to address these – usually with only a minimal impact on the existing optimal corporate strategies. The paper also includes summaries of the wider evidence which validates the fundamental concepts underpinning the concepts involved, but – especially – it illustrates the developments by their use with Surrey County Council.

The effects of supply chain risk management (SCRM) on the performance of a supply chain remain unexplored. It is assumed that SCRM helps supply chains to cope with vulnerabilities both proactively by supporting robustness and reactively by supporting agility. Both dimensions are assumed to have an influence on the supply chain's customer value and on business performance. The aim of this research is to provide clarity by empirically testing these hypotheses and scrutinizing the findings by the means of case studies.

The research is empirical. Survey data were collected from 270 manufacturing companies for hypotheses testing via structural equation modeling. Additionally, qualitative data were collected to explore the nature of non‐hypothesized findings.

It is found that SCRM is important for agility and robustness of a company. Both agility and robustness show to be important in improving performance. While agility has a strong positive effect only on the supply chain's customer value, but not directly on business performance, robustness has a strong positive effect on both performance dimensions. This important finding directs the strategic attention from agility‐centered supply chains to ones that are both robust and agile. The case studies provide insights to the fact that robustness can be considered a basic prerequisite to deal with supplier‐side risks, while agility is necessary to deal with customer‐side risks. The amount of agility and robustness needs to fit to the competitive strategy.

Since volatility has increasingly become a prevalent state of supply chains, companies need to consider robustness to be of primary importance to withstand everyday risks and exceptions.

This is the first study to view the relationship between SCRM, agility/robustness, and performance.

To survive and grow in an era of uncertainty, companies should strive not only for a single visionary view, which most likely corresponds with their expectations, but instead they should try to acquire multiple views that describe the whole ”window of opportunities”. The development of external market scenarios to assess current strategies is the usual way of coping with these uncertainties. Today this traditional scenario approach has to be extended in four directions: the use of market scenarios to systematically develop future‐robust strategies, the use of alternative strategy scenarios to address uncertainties within an organization, the use of scenarios as a basis for strategic early warning processes and the combination of performance measurement and strategic early warning in a scenario‐based future scorecard. In conclusion it is shown that scenarios could significantly help to bridge the gap between strategy implementation and early‐warning processes.

The outset of the COVID-19 pandemic caused disruptions of all forms in the supply chain globally for almost two and a half years. This study identifies various challenges in the effective functioning of the existing supply chain during COVID-19. The focus is to see the disruptions impacting the energy storage supply chains.

The procedure entails a thorough analysis of scholarly literature pertaining to various supply chain interruptions, confirmed and verified by experts working in an energy storage company in India. These experts also confirmed the occurrence of more disruptive factors during their interviews and questionnaire survey. Moreover, this process attempts to filter out the relevant causal disruption factors in an energy storage company by using the integrated approach of qualitative and quantitative methodologies.

The results provide practical insights for the company management in planning and devising new strategies to manage supply chain disruptions. Supply chains for companies in other industry sectors can also benefit from the proposed framework and results in making them more robust to counter future disastrous events.

The study provides an easily adaptable decision framework to different industries by closely examining supply chain disruptions and identifying associated causes for building a robust supply chain focused on the energy storage sector. It examines four disruption dimensions and investigates possible outcomes and impacts of disruptions.

The purpose of this paper is to summarize a simulation study that analyzed the performance of Bayesian audit strategies in a novel fashion – dynamically and with varying sample sizes depending on the extent of an auditor's prior information.

The prior information for the Bayesian strategies arises from a set of control tests that are evaluated making use of reliability theory. The entire audit strategy is simulated under systematically different control reliabilities and related amounts of total misstatements in an accounting population.

The major finding is that robust Bayesian audit strategies that have recently been developed in auditing research are more sensitive to non‐sampling errors than existing strategies of audit practice.

The authors find that there are differential effects of sampling error vs non‐sampling error on the Bayesian strategies and that controls testing does not need to be extensive to get full internal control reliance.

The paper adds to existing research by examining the performance of various Bayesian audit strategies under more realistic audit conditions of sampling and non‐sampling uncertainty.