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Sales forecasting and collaboration are two business phenomena that have independently been recognized as contributing to improved organizational performance. The present research employs case study methodology to explore the synergies to be gained from combining the two processes. Depth interviews were conducted with executives at three firms currently engaged in collaborative forecasting with supply chain partners. Results revealed unique approaches to collaborative forecasting that circumvent the inhibitors of collaborative planning, forecasting, and replenishment adoption, and yield substantial improvement in company and supply chain performance including increased responsiveness, product availability assurance, optimized inventory and associated costs, and increased revenues and earnings. Seven guidelines to implementing interfirm collaborative forecasting are presented.

This review aims to discuss concepts and theories from cognitive psychology, identifies tourism studies applying them and discusses key areas for future research. The paper aims to demonstrate the usefulness of cognitive psychology for understanding why tourists and particularly pleasure travellers demonstrate the behaviour they exhibit.

The paper reviews 165 papers from the cognitive psychology and literature regarding pleasure travel related to consciousness, mindfulness, flow, retrospection, prospection, attention, schema and memory, feelings and emotions. The papers are chosen to demonstrate the state of the art of the literature and provide guidance on how these concepts are vital for further research.

The paper demonstrates that research has favoured a behaviourist rather than cognitive approach to the study of hedonic travel. Cognitive psychology can help to understand the mental processes connecting perception of stimuli with behaviour. Numerous examples are provided: top-down and bottom-up attention processes help to understand advertising effectiveness, theories of consciousness and memory processes help to distinguish between lived and recalled experience, cognitive appraisal theory predicts the emotion elicited based on a small number of appraisal dimensions such as surprise and goals, knowledge of the mental organisation of autobiographical memory and schema support understanding of destination image formation and change and the effect of storytelling on decision-making, reconstructive bias in prospection or retrospection about a holiday inform the study of pleasurable experience. These findings indicate need for further cognitive psychology research in tourism generally and studies of holiday travel experiences.

This review is limited to cognitive psychology and excludes psychoanalytic studies.

Cognitive psychology provides insight into key areas of practical importance. In general, the use of a cognitive approach allows further understanding of leisure tourists’ behaviour. The concept of attention is vital to understand destination advertising effectiveness, biases in memory process help to understand visitor satisfaction and experience design and so on. Use of cognitive psychology theory will lead to better practical outcomes for tourists seeking pleasurable experiences and destination managers.

This is the first review that examines the application of concepts from cognitive psychology to the study of leisure tourism in particular. The concepts studied are also applicable to study of travellers generally.

The study aims to identify the gaps and the potentialities of citizen-generated data in four axes of warning system: (1) risk knowledge, (2) flood forecasting and monitoring, (3) risk communication and (4) flood risk governance.

Research inputs for this work were gathered during an international virtual dialogue that engaged 40 public servants, practitioners, academics and policymakers from Brazilian and British hazard and risk monitoring agencies during the Covid-19 pandemic.

The common challenges identified were lack of local data, data integration systems, data visualisation tools and lack of communication between flood agencies.

This work instigates an interdisciplinary cross-country collaboration and knowledge exchange, focused on tools, methods and policies used in the Brazil and the UK in an attempt to develop trans-disciplinary innovative ideas and initiatives for informing and enhancing flood risk governance.

In general, demand for functional products is dependent on a range of promotions offered in various retail outlets. To improve promotional sales many retailers collaborate with manufacturers for planning, forecasting and replenishment. The purpose of this paper is to hypothesize that collaborative forecasting will improve the forecast accuracy if all the partners can relate their demand forecast with underlying demand factors.

In this paper, the author uses a case study approach to study various demand factors of soft drink products of the UK based company which offers frequent promotions in retail outlets. The paper represents the case study findings in a conceptual framework called Reference Demand Model (RDM). Further, the case study findings are validated empirically by means of multiple linear regression analysis using actual sales data of the case company.

Surprisingly, some of the demand factors specified as very important by the case company are not found to be highly significant for actual sales. The paper uses the identified demand factors to suggest levels of collaboration.

Understanding the importance of product specific demand factors through regression models and incorporating the same in managerial decision making will aid managers to identify the necessary information to make accurate demand forecasts.

This approach unveils the presence of three levels of collaboration namely preparatory, progressive and futuristic levels among supply chain partners based on the information exchange. The proposed method will aid decision making on information sharing and collaborative planning among manufacturer and retailers for future promotional sales.

This research examines the use of a number of time series model structures of a moderate allocation mutual fund, PRWCX. PRWCX was rated as the top fund in its category during the past five years. The fund invests at least 50% of its total assets that the fund manager believes that have above average potential for capital growth. The remaining assets are generally invested in convertible securities, corporate and government debt bank loans, and foreign securities. Forecasting the total NAV of such a moderate allocation mutual fund, composed of an extremely large number of investments, requires a method that produces accurate results. These models are exponentially smoothing (single, double, and Winter’s Method), trend models (linear, quadratic, and exponential) are Box-Jenkins models.

FORECASTING is not just a specialized management technique, but something which we all understand and do quite naturally. Because of the existence of time, all of us run our lives by making forecasts. In the present (which is an infinitesimally short period of time) we have to make forecasts of what will happen in the future based upon our experience of the past. Without such forecasts, we could not run our lives because we have to keep making decisions about the future.

The purpose of this paper is to investigate the effects of personality dimensions (conscientiousness, neuroticism, extraversion, agreeableness, openness to experience, locus of control) on the efficacy of judgmental adjustments of statistical forecasts.

This paper uses a two-level hierarchical linear model to analyze a large data set obtained from an organizational setting (a quick service restaurant chain) that includes 3,812 judgmental adjustments of sales forecasts made by 112 store managers.

The results indicate that the average forecast accuracy improves as a result of judgmental adjustments, but performance of individual forecasters varies considerably based on their personality. Specifically, the trait of openness to experience tends to improve forecast accuracy while extraversion and external locus of control have negative effects.

Integration of human judgment with analytics algorithms is a major challenge for organizations. Documenting the impact of these traits on forecast accuracy opens the door for forecasting support system design, training, personnel selection and correction strategies that can be applied to judgmental adjustments.

Barton and Simko argue that the balance sheet information would serve as a constraint on accrual‐based earnings management. This paper aims to extend their argument by examining whether the balance sheet constraint increases managers' propensity to use either downward forecast guidance or real earnings management as a substitute mechanism to avoid earnings surprises.

Following Barton and Simko, the paper uses the beginning balance of net operating assets relative to sales as a proxy for the balance sheet constraint. The argument is that because of the articulation between the income statement and the balance sheet, previous accounting choices that increase earnings will also increase net assets and therefore the level of net assets reflects the extent of previous accrual management. Models from Matsumoto and Bartov et al. are used to measure forecast guidance. Following Rochowdhury and Cohen et al., a firm's abnormal level of production costs and discretionary expenditures are used as proxies of real earnings management. The empirical analysis is conducted based on the 1996‐2006 annual data for a sample of nonfinancial, nonregulated firms.

The paper finds that firms with higher level of beginning net operating assets relative to sales are more likely to guide analysts' earnings forecasts downward, and more likely to engage in real earnings management in terms of abnormal increases in production costs and abnormal reductions in discretionary expenditures.

Overall, the paper's evidence suggests that managers turn to real earnings management or downward forecast guidance as a substitute mechanism to avoid negative earnings surprises when their ability to manipulate accruals upward is constrained by the extent to which net assets are already overstated in the balance sheet.

This study adds to prior literature that examines how managers trade off different mechanisms used to meet or beat analysts' earnings expectations. It also contributes to the extant literature by providing further insights on the role of balance sheet information in the process of managing earnings and/or earnings surprises.

Examines the environment hostility‐planning‐performance relationship of Hong Kong retailers. A positive relationship is found between environment hostility and the threats encompassed by the existing labour shortage, rising rents, foreign‐based competition, the 1997 return to Chinese governance and Hong Kong′s relationship with mainland China. Retailers who perceive less hostility in their environment are more planning‐oriented. Short‐term planners significantly outperformed non‐planners. Formal long‐range planning was unrelated to retailer performance.