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Firms face uncertain environments characterized by shifting demographics, disruptive technologies, new industries and competitors, and other challenges. To survive the tumultuous landscape, firm managers “make strategy” by assessing the organization's internal and external environments, questioning assumptions about how the world works and deciding how the firm should operate. We refer to this activity as “forecasting the future” and provide insights from our recent study of 394 senior managers.

We review the history of scenario planning, from military strategies to Royal Dutch/Shell's analysis of the oil crisis in 1974 and the scenario planning process. From our survey of managers, we identify the major perceived benefits and weaknesses of scenario planning, and how managers forecast the future. We identify two dimensions of forecasting – formality and breadth – and review three modes of forecasting – formal, focused and intuitive – and compare to complexity and costs of formal scenario planning. We conclude with key learning points from our survey.

When making strategy through scenario planning and forecasting methods, managers need to: examine the validity of current market assumptions used to guide forecasting efforts; involve key stakeholders in a debate about and assessment of these assumptions; update strategic plans with forecasting process outcomes; and regularly review key hypotheses about market events and their performance impacts.

Senior managers must understand the biases in managerial forecasting behavior and to work with these, to support a mix of forecasting behaviors in an organization, to deliberately allocate forecasting resources to cover environmental sectors, to selectively use managers external to the organization, to utilize a variety of sources, and to align forecasting activities with the organizational strategy process.

The paper presents a succinct summary of existing research, including findings from the authors' recent research, for both researchers and practising managers.

Using the hyperbolic discounting approach in qualitative manner, the purpose of this paper is to explore the linkage of the time preference bias towards the too early execution of strategic focused planning. The paper also investigates the role of psychological bias in explaining the early execution.

This research use qualitative methods to explore the role of hyperbolic discounting in driving the psychological bias towards too early strategic scenario planning, and its rationalization. The authors conducted a face‐to‐face survey going door‐to‐door of the small to medium‐sized enterprises (SMEs). The samples in this research are Indonesian SMEs from the northern part of Sumatra.

This research found most of the SMEs' managers are time preference biased due to hyperbolic discounting. This hyperbolic discounting awoke manager's psychological bias and resulted in too early decision making. This psychological bias might be due to prospect theory, or the representative effect, or framing bias, or the adaptive bias.

The sample is only taken from Northern part of Indonesia. To have a robust generalization, the research should be conducted in the whole of Indonesia.

This paper can be used by practitioners to understand their behaviour towards strategic decision making. Further, practitioners will know if their time preference bias will not generate better result.

Since the McKinsey Company first forecast, in 1994, that home shopping via the internet, would change our lives forever, there has been a continual concern that this demand would generate both more Business to Business (B2B) road transport trips, and a quantum leap in the Business to Consumer (B2C), householder delivery trips. This was also additional to the growth expected in most major capital cities over the next fifteen to twenty years.

Although there is much discussion as to when the internet began to generate, or most likely substitute existing business into either smaller B2B pulses to customers, or beginning the household e-Commerce deliveries, by 1998 the internet was generally accepted as having had an impact.

In spite of an intuitive appeal regarding association between personality and investment efficacy, there is a dearth of empirical support for the effects of theoretically meaningful personality difference on intuitive and analytical ability, which further explains investment efficacy. The current study aims to explore this link using multi-method analysis.

In Study 1, the experimental protocol captures intuitive responses of naïve investors in four different investment horizons and maps the findings with personality constituents of the Big Five (Costa and McCrae, 1992), while in Study 2, survey of active investors seeks their preference for intuition or deliberation (PID, Betsch, 2004) in decision-making, along with measuring their investment efficacy and analysing the results on the basis their personality Type A vs Type B.

Subjects with lower extraversion tend to have superior forecasting accuracy for gold and dollar, while those with lower neuroticism have tendency of superior forecasting for dollar and Nifty index in mid-term investment. Further, in Study 2, the results indicate superior intuitive ability, analytical ability and investment efficacy of Type B investors.

The study is unique in two ways. One, it explores the role of personality in ambidextrous decision-making framework, where rationality and intuition iteratively operate in a parallel, yet synchronous, fashion. Two, the study attempts to examine the role of personality in the unique socio-cultural context of an emerging economy such as India with Eastern religious traditions, having strong implications on the personal characteristics of the decision agents.

Mean absolute percentage error (MAPE) is the primary forecast evaluation metric in hospitality and tourism research; however its main shortcoming is that it is asymmetric. The asymmetry occurs due to over or under forecasts that introduce bias into forecast evaluation. This study aims to explore the nature of asymmetry and designs a new measure, one that reduces the asymmetric properties while maintaining MAPE’s scale-free and intuitive interpretation characteristics.

The study proposes and tests a new forecasting accuracy measure for hospitality revenue management (RM). A computer simulation is used to assess and demonstrate the problem of asymmetry when forecasting with MAPE, and the new measures’ (MSapeMER, that is, Mean of Selectively applied Absolute Percentage Error or Magnitude of Error Relative to the estimate) ability to reduce it. The MSapeMER’s effectiveness is empirically validated by using a large set of hotel forecasts.

The study demonstrates the ability of the MSapeMER to reduce the asymmetry bias generated by MAPE. Furthermore, this study demonstrates that MSapeMER is more effective than previous attempts to correct for asymmetry bias. The results show via simulation and empirical investigation that the error metric is more stable and less swayed by the presence of over and under forecasts.

It is recommended that hospitality RM researchers and professionals adopt MSapeMER when using MAPE to evaluate forecasting performance. The MSapeMER removes the potential bias that MAPE invites due to its calculation and presence of over and under forecasts. Therefore, forecasting evaluations may be less affected by the presence of over and under forecasts and their ability to bias forecasting results.

Hospitality RM should adopt this measure when MAPE is used, to reduce biased decisions driven by the “asymmetry of MAPE.”

The MAPE error metric exhibits an asymmetry problem, and this paper proposes a more effective solution to reduce biased results with two major methodological contributions. It is first to systematically study the characteristics of MAPE’s asymmetry, while proposing and testing a measure that considerably reduces the amount of asymmetry. This is a critical contribution because MAPE is the primary forecasting metric in hospitality and tourism studies. The second methodological contribution is a procedure developed to “quantify” the asymmetry. The approach is demonstrated and allows future research to compare asymmetric characteristics among various accuracy measures.

During recent years there has been a vast growth in the literature of and the study of the theory of the firm. Underlying the various different theories however is a generally acknowledged structure of a company having an objective(s) towards which it strives by laying down and implementing plans. Planning involves making decisions which will have their effects and outcomes in the future and so an estimate of this future is required. This assessment of the future is termed forecasting and it is a vital ingredient in any planning process.

Expectations play a crucial role in finance, macroeconomics, monetary economics, and fiscal policy. In the last decade a rapidly increasing number of laboratory experiments have been performed to study individual expectation formation, the interactions of individual forecasting rules, and the aggregate macro behavior they co-create. The aim of this article is to provide a comprehensive literature survey on laboratory experiments on expectations in macroeconomics and finance. In particular, we discuss the extent to which expectations are rational or may be described by simple forecasting heuristics, at the individual as well as the aggregate level.

The purpose of this paper is to propose a simple regression‐based method of forecasting daily electricity demand, which may serve as a more accurate benchmark for short‐term forecasts.

In order to make more efficient use of the calendar effects in electricity demand, including weekend, and seasonal effects, while maintaining the parsimony of the forecasting model, the authors match the demand on each day of an entire year with the average of the corresponding days in recent years. This matching‐day approach substantially simplifies the modeling procedure of complex periodicity in electricity demand without loss of information.

With daily data on electric power system load in New England, the authors' method provides quite accurate forecasts. The mean absolute percentage error (MAPE) (2.1 percent) is significantly lower than those of the seasonal ARIMA and exponential smoothing method, and also comparable to the performance of more sophisticated methods in the literature.

The authors' method needs to be modified or augmented by other techniques when the periodicity is not stable due to time trends, economic crises, and other factors.

The management of electric utility providers as well as professional forecasters may use this method as a handy benchmark.

While previous studies focus mainly on accuracy of forecasts, the method presented in the paper is developed with the balance between accuracy and ease of use in mind.

This paper aims to compare the accepted techniques of location analysis in the food sector with the realities of “real world” forecasting in convenience store (c‐store) retailing. To offer a conceptual framework for c‐store operators intending to become more strategic in their small store location planning but currently lacking established expertise or extensive research budgets.

Outlines potential best practice based on industry experience, and contact and discussion with location analysts and retail consultants, as well as a wide ranging examination of the academic literature in this area.

Finds that the traditional techniques of market analysis for large‐scale food stores will become largely redundant; that neighbourhood retailers are likely to manage their location decision‐making by incremental steps; that the requirements of convenience store forecasting inevitably read to a “back to basics” approach to market analysis; that the use of site visits in combination with more quantitative techniques will provide the most effective solutions; and that reconciling human institutions and their environment is key to effective site research decision‐making.

Academic conceptualisations of location planning in the convenience store sector are largely absent from the literature. This paper adopts a practical perspective.

Roles of leadership in coping with uncertainty are explored in this paper. Through an in‐depth, empirically (CEOs of top, ASEAN publicly listed corporations) grounded discussion, the authors argued for the presence of a deep cultural divide between Eastern and Western leaders on coping with uncertainty. In the process, the authors devise a two dimensional, organic versus forecastability model of strategy behavior for polarizing East‐West leadership styles. Aspects of the Sun Tzu’s Art of War and 5,000 years old, I Ching are discussed with respect to foreknowledge and foresight respectively.