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Introduces and delineates the concept of strategic planning maturities. It thus represents a small addition to the total body of knowledge underlying the strategic planning process. Uses a conceptual model to explicate the dynamic interrelationship between planning horizons and strategic planning maturities. Theoretical applications and real‐world applications link the concept of strategic planning maturities to successful and unsuccessful strategic decisions actually made by top management in a cross‐section of large organizations.

Individuals tend to simplify a complex portfolio decision problem into several manageable dimensions, each of which can frame their perception of risk.We check this view by studying the effect of investment horizons on households’ portfolio decisions. Using the Survey of Consumer Finances (SCF) data, we find that households allocate more of their wealth in stocks if they report longer planning horizons. The existence of foreseeable expenditure significantly changes the dependence of risky stock investment on the planning horizon.We decompose the reported planning horizon into an objective part and a subjective mental accounting part, and find that the mental accounting part has a greater effect on household portfolio choice. This is consistent with the argument that individuals make investment decisions based on the horizon at which the risk is perceived rather than the horizon at which the investment reward or cash is needed.

This paper aims to explore the planning strategies of female entrepreneurs who have indicated a desire to grow their businesses, the time horizons of planning strategies and the relationship between planning horizons and number of employees and annual sales as measures of business performance.

In order to gather data for this exploratory study, a questionnaire was sent by e‐mail to members of networks of female entrepreneurs across England and Wales. Questionnaires were selected for analysis on the basis of an indication from the respondent that they wished to grow their business. Data were entered into SPSS to generate descriptive statistics, and conduct hypothesis testing.

The most preferred business growth strategies were: improving existing products or services and expanding advertising and promotion. Planning horizons are very short (often under three months), although the planning horizons associated with new products and entry into new markets were in some instances a little longer. Such short planning horizons could have serious consequences for business performance and growth. The planning horizons for cashflow, and investment in infrastructure showed a correlation with number of employees, whilst the planning horizons for cashflow, new product development, and expenditure showed a correlation with annual sales.

Female entrepreneurs need to be encouraged to extend their planning horizons, especially in terms of financial indicators such as expenditure, cash flow, and investment.

This research contributes to the growing literature on female entrepreneurs and their business, by providing further insight into their growth strategies and planning horizons.

The time horizons for setting out strategic plans have never been established in principle, and hence vary widely over one, two, three, five, ten, fifteen, twenty years and more. This paper presents a total system of planning horizons at one, three, seven, twelve and twenty‐five years. Each time horizon is linked to a specific organizational layer. The larger the organization, the longer is the top‐level planning horizon. The larger time horizons encompass the shorter, so that, for example, the CEO of a large corporation can set the corporate strategic plan in terms of a 25‐year plan, with corporate strategic milestones at twelve years, seven years, three years and one year. Every subordinate function can be planned in the same way.

Significant transitions in firms (e.g. outsourcing) may impact the relative importance of production and inventory assets, affecting the hierarchical separation of planning decisions. The purpose of this paper is to contribute to planning literature by investigating how the production system and the planning environment influence the performance difference between hierarchical and monolithic planning. Further, it seeks to reduce the prevailing theory-practice gap in tactical planning.

Through an action research study, a monolithic model integrating tactical production planning decisions, subject to upstream supply chain constraints, with strategic investments decisions was developed, tested and implemented in a global OEM. Using the developed model and a measure of the capital cost of production assets relative to the cost of holding inventory, it is numerically examined how the production system and planning environment influence the performance of hierarchical and monolithic planning.

The research demonstrates the potential of integrating decisions and reveals significant performance differences between hierarchical and monolithic planning for firms with low capital cost relative to inventory holding cost.

The findings suggest a fit between planning processes, the production system and planning environment. Future research should empirically validate the findings and propositions.

The paper combine capital investments and production planning decisions, which usually transpire at different hierarchical levels and on different time-horizons, and investigates the consequences of hierarchical separation through a real-life validated case and numerical analysis.

The production planning problem with fine-grained information has hardly been considered in practice. The purpose of this study is to investigate the data-driven production planning problem when a manufacturer can observe historical demand data with high-dimensional mixed-frequency features, which provides fine-grained information.

In this study, a two-step data-driven optimization model is proposed to examine production planning with the exploitation of mixed-frequency demand data is proposed. First, an Unrestricted MIxed DAta Sampling approach is proposed, which imposes Group LASSO Penalty (GP-U-MIDAS). The use of high frequency of massive demand information is analytically justified to significantly improve the predictive ability without sacrificing goodness-of-fit. Then, integrated with the GP-U-MIDAS approach, the authors develop a multiperiod production planning model with a rolling cycle. The performance is evaluated by forecasting outcomes, production planning decisions, service levels and total cost.

Numerical results show that the key variables influencing market demand can be completely recognized through the GP-U-MIDAS approach; in particular, the selected accuracy of crucial features exceeds 92%. Furthermore, the proposed approach performs well regarding both in-sample fitting and out-of-sample forecasting throughout most of the horizons. Taking the total cost and service level obtained under the actual demand as the benchmark, the mean values of both the service level and total cost differences are reduced. The mean deviations of the service level and total cost are reduced to less than 2.4%. This indicates that when faced with fluctuating demand, the manufacturer can adopt the proposed model to effectively manage total costs and experience an enhanced service level.

Compared with previous studies, the authors develop a two-step data-driven optimization model by directly incorporating a potentially large number of features; the model can help manufacturers effectively identify the key features of market demand, improve the accuracy of demand estimations and make informed production decisions. Moreover, demand forecasting and optimal production decisions behave robustly with shifting demand and different cost structures, which can provide manufacturers an excellent method for solving production planning problems under demand uncertainty.

Corporate commitment to environmental assessment with its kit of forecasting tools is expected to grow rapidly in the years ahead. This growth will be partly due to corporate willingness to confront turbulent environmental changes explicitly within a formal planning process.

When it comes to performance metrics, one size definitely does not fit ail—the right metric applied at the wrong time can stunt corporate growth.

The purpose of this paper is to understand how companies design sales and operations planning (S & OP) contingent on the planning environment (PE).

On the basis of the literature, the paper creates an analytical framework identifying the main constructs related to the PE and S & OP design, which is the basis for gathering and analysing qualitative data from eight cases in the food industry. The findings highlight the relations between S & OP and the PE, and are used for generating three propositions.

Responding to the complex and uncertain PE, the companies set up S & OP on a stock-keeping unit (SKU) level, with the possibility of re-planning and a flexible planning horizon, thus differing from what has generally been suggested in the literature. In addition, the companies are aligning the inputs, activities, and outcomes of the S & OP process to the PE. Particularly important environmental contingencies are uncertainty connected to demand and supply, frequent product launches, and production network complexity. Product-related variables have a lower impact on the S & OP design.

The present study is limited to one industry only and a comparison between industries with larger data sets would be valuable in future studies. The study selected cases based on their S & OP maturity; further studies need to explore the effect of the alignment of S & OP and the PE on the planning performance.

In the literature, S & OP is presented as a generic process with a strict formal design that is equal for all companies. The study provides insights into how companies adjust S & OP according to the PE.