Strategic investment decision making practices: A contextual approach

This paper proposes a contextual approach to explaining differences in strategic investment decision (SID) making practices. First, a systematic contextual framework is developed from the existing research literature. Then this framework's potential for explaining differences in SID making practices is explored through 14 case studies of U.K., U.S. and Japanese companies from both stable and dynamic business sectors. Our findings suggest substantial SID differences across our four contextual categories of market creators, value creators, refocusers and restructurers. The differences relate to the emphasis on strategic versus financial considerations, the thoroughness and rigidity of financial analysis, the attitudes towards incorporating less easily quantifiable factors and the level of hurdle rates.     

A knowledge‐based framework for incorporating investor's preference into portfolio decision‐making

This paper describes a framework for the integration of a rule‐based system capable of identifying an investor's risk preference into a quantitative portfolio model based on risk and expected return. By inferring rules consisting of an investor's objective and subjective risk preferences, the integrated methodology provides the assets suitable for the preferences. Through investment in the portfolio composed of the assets, the investor is able to obtain the following bene?ts: reduction of costs and time spent to determine target assets, and alleviation of anxiety from ‘out‐of‐favor’ assets. The framework is applied to the development of a knowledge‐based portfolio system for constructing an investor's preference‐oriented portfolio. In the procedure of the system for ?nding an optimal portfolio, the system uses an arti?cial intelligence method of a case‐based reasoning to obtain preference thresholds for an investor when the investor's past investment records are available. Experimental results show that the framework contributes signi?cantly to the construction of a better portfolio from the perspective of an investor's bene?t/cost ratio than that produced by the existing portfolio models. Copyright © 2004 John Wiley & Sons, Ltd.     

Constructing a knowledge‐based system to aid scenario‐based strategic planning: an application to the European airline industry

This paper explores the use of scenario planning and the design of a knowledge‐based system in strategic decision making, in the context of the European airline industry. Several innovative strategies were derived, as well as other key recommendations based on sound strategic reasoning, and participants testified to the effectiveness of the approach in stretching their thinking. The requirement to draft strategies as expert system rules, with reasons, was useful in clarifying thinking and achieving group consensus. This methodology, therefore, aids effectiveness of the scenario planning process itself, while providing a dynamic, accessible means of storing the resulting strategic thinking. Copyright © 2005 John Wiley & Sons, Ltd.     

How information and communication technology affects decision‐making on innovation diffusion: An agent‐based modelling approach

We introduce a computational agent‐based model of innovation diffusion that allows us to analyse the influence of information and communication technology (ICT) development on decision‐making. Model dynamics are based on local emulation between pairs of individuals that generate an evolving social network on which an innovation is virally spread (by word of mouth). Results suggest that ICT development affects the data usefulness for decision‐making by changing the topology of the social network (the means whereby the innovation is propagated). Paradoxically, a higher level of ICT development (providing a larger volume of data) narrows the differences between better and worse launch strategies, thus reducing data‐driven decision‐making usefulness, which then shows diminishing returns on the ICT level.     

Decision‐making capabilities of a hybrid system applied to the auditor's going‐concern assessment

The purpose of this study is to evaluate a hybrid system as a decision support model to assist with the auditor's going‐concern assessment. The going‐concern assessment is often an unstructured decision that involves the use of both qualitative and quantitative information. An expert system that predicts the going‐concern decision has been developed in consultation with partners at three of the Big Five accounting firms. This system is combined with a statistical model that predicts bankruptcy, as a component of the auditor's decision, to form a hybrid system. The hybrid system, because it combines the use of quantitative and qualitative information, has the potential for better prediction accuracy than either the expert system or statistical model predicting separately. In addition, testing of the system provides some insight into the characteristics of firms that experience problems, but do not necessarily receive a going‐concern modification. Further investigation into those firms that have problems could reveal factors that may be incorporated into decision support systems for auditors, in order to improve accuracy and reliability of these decision tools. © 2001 John Wiley & Sons, Ltd.     

Risk management in the energy markets and Value-at-Risk modelling: a hybrid approach

This paper proposes a set of Value-at-Risk (VaR) models appropriate to capture the dynamics of energy prices and subsequently quantify energy price risk by calculating VaR and expected shortfall measures. Amongst the competing VaR methodologies evaluated in this paper, besides the commonly used benchmark models, a Monte Carlo (MC) simulation approach and a hybrid MC with historical simulation approach, both assuming various processes for the underlying spot prices, are also being employed. All VaR models are empirically tested on eight spot energy commodities that trade futures contracts on the New York Mercantile Exchange (NYMEX) and the constructed Spot Energy Index. A two-stage evaluation and selection process is applied, combining statistical and economic measures, to choose amongst the competing VaR models. Finally, both long and short trading positions are considered as it is of utmost importance for energy traders and risk managers to be able to capture efficiently the characteristics of both tails of the distributions.     

The decision game: a serious game approach to understanding environmental risk management decisions

Abstract

Here we describe the implementation of an experimental research tool called the Decision Game that we used to collect data on household flood risk management decisions. Participants using this tool play an interactive game that involves making household decisions about place of residence and a variety of household expenditures, including spending on flood insurance and private flood risk mitigation. Participants also answer survey questions before and after playing the game; the pre-game survey collected demographic information, and the post-game survey collected information about participant experiences with flooding and flood mitigation. Online and face-to-face participants showed similar engagement with the experiment, and most participants appeared to have made deliberate and considered decisions about risk mitigation. Online study participants had similar responses to those who participated in person, although face-to-face participants seemed slightly more likely to mitigate against risk. Overall, participants in this research were younger, more educated and more likely to rent a home than the average Canadian. Serious games may be useful for augmenting existing data gathering strategies used in understanding environmental decision making, particularly for rare catastrophic events for which stated preference surveys may be less informative. Serious games allow for sharing a mixture of information with study participants, including maps, video clips, text and even immersive 3D experiences, and can be administered online to increase participation levels. Future research will consider longer duration online experiments and more immersive interaction frameworks.     

Genetic testing: affected parties and decision making

The network of issues around information obtained from genetic testing is wide and complex. While risk assessment, awareness and discussion are often public driven, and in many instances, including that of nuclear power, are allied with democratic principles, the case of gene technology and genetic testing appears to be different. The opportunity for risk assessment by gene testing is rejected by many, and this rejection is supported by the claim of the right not to know. This article discusses the background to this development, and argues that decisions that consider issues related to genetic testing should be taken with the participation of affected parties.     

Accounting aggregation: User preferences and decision making

This experiment tests the effects of alternative aggregations of accounting data in a simulated portfolio task. Certain entropy-based aggregation criteria were used to prepare differentially aggregated financial statements for use in the task. Subjects made allocations of initial edowments between hypothetical firms, disclosed confidence in their allocation decisions and reported on specific characteristics of the financial statements. Differences in reported usefulness of statement sets furnished were found to be associated strongly with measured information content. The results also provide limited evidence that decisions and judgments of subjects were affected by the information content of the accounting aggregations provided.     

Strategic performance management: A balanced approach to performance management issues in local government

The drive for reform in the public sector worldwide has focussed attention on the measurement of performance in public sector organizations. This is particularly true in local government. Local government has traditionally been concerned with measuring the delivery of primary objectives, or results, at the expense of secondary objectives, or the determinants of organizational performance. Current strategic management literature suggests that there should be a strong linkage between strategic plans and performance measures.Kaplan and Norton’s (1992) balanced scorecard and Fitzgeraldet al. ’s (1991) results and determinants framework can provide this linkage. This paper reports on research into performance management systems in local government using the four dimensions of the balanced scorecard: financial, community, internal business processes and innovation and learning. It shows how the focus in this system of local government has been on the results of council work, ie. financial performance and to a lesser extent on how the community views performance. Local government performance measurement pays much less attention to the determinants, or means of achieving long-term, sustained organizational improvement in internal business processes, and innovation and learning. Whilst these issues are recognized as important, there are few measurement processes in place to manage performance in these areas. Strategic performance management demands an approach that recognizes the importance of a focus on both results and the means of achieving these results. This paper highlights a suggested framework for strategic and balanced local government performance measurement.     

Usage‐based insurance and its acceptance: An empirical approach

This study aims to explore the motor insurance market's attitude towards usage‐based insurance (UBI), and thus its readiness for a launch in the near future. Data on client perception was collected using a structured questionnaire. On the basis of this, an initial selection of factors, other than income, that could influence the declared attitude of drivers was demonstrated showing that it is primarily dependent on certain demographic characteristics like their age, sex, or place of residence. A strong relationship was also demonstrated with respect to the intensity of the vehicle's use, to the amount of the insurance premium they have paid, and to the self‐assessment of the respondents' driving skills. Clients are likely to accept the concept of UBI once implemented, but that they are not ready yet to give up the traditionally used methods of premium calculation. Their attachment to discounts granted can be very strong in particular to the no‐claims bonus.     

A neural‐network‐based decision‐making model in the peer‐to‐peer lending market

This study proposes an investment recommendation model for peer‐to‐peer (P2P) lending. P2P lenders usually are inexpert, so helping them to make the best decision for their investments is vital. In this study, while we aim to compare the performance of different artificial neural network (ANN) models, we evaluate loans from two perspectives: risk and return. The net present value (NPV) is considered as the return variable. To the best of our knowledge, NPV has been used in few studies in the P2P lending context. Considering the advantages of using NPV, we aim to improve decision‐making models in this market by the use of NPV and the integration of supervised learning and optimization algorithms that can be considered as one of our contributions. In order to predict NPV, three ANN models are compared concerning mean square error, mean absolute error, and root‐mean‐square error to find the optimal ANN model. Furthermore, for the risk evaluation, the probability of default of loans is computed using logistic regression. Investors in the P2P lending market can share their assets between different loans, so the procedure of P2P investment is similar to portfolio optimization. In this context, we minimize the risk of a portfolio for a minimum acceptable level of return. To analyse the effectiveness of our proposed model, we compare our decision‐making algorithm with the output of a traditional model. The experimental results on a real‐world data set show that our model leads to a better investment concerning both risk and return.     

Futures research and social decision making: Alternative futures as a case study

This article clarifies some basic features of futures research in order to make explicit the relation between futures research and social development in general as well as political planning and decision making in particular. Three paradigms for futures research are described and, as an example of an emancipatory futures research project, ‘Alternative futures’ will be introduced.     

Development of a case‐based decision support system for process modeling in BPR

This paper presents a knowledge‐based methodology for business process reengineering that uses a case‐based reasoning paradigm to provide decision support to its users in the modeling of a current problem and a redesign of critical business processes. As a process modeling tool for representing the business process, the event process chain (EPC) modeling method is used in this paper. We developed a CAPMOSS (CAse‐based Process MOdeling Supporting System) to support our proposed methodology. To reengineer a new business process problem, CAPMOSS retrieves from its case base the case that is most similar to the current problem. CAPMOSS uses a retrieved case to guide the structuring of AS‐IS models and TO‐BE models of a target business process. Using the transformational knowledge of a retrieved case, CAPMOSS helps the user to transform an AS‐IS model into a TO‐BE model for the target process with ease and the purchasing process in a government R&D institute is explained as an application of this approach. Copyright © 2000 John Wiley & Sons, Ltd.     

Merchants’ accounts,performance assessment and decision making in mercantilist Britain

The part played by double entry bookkeeping (DEB) in the rise of capitalism in Western Europe has been the subject of academic attention and debate for more than a century [Miller, P., & Napier, C. (1993). Genealogies of calculation. Accounting, Organizations and Society, 18(7/8), 631–647]. Our interest in this topic was aroused by sources of relevant comment concerning early uses of DEB identified in Chambers’ An Accounting Thesaurus (1995). In this paper these sources, augmented by a systematic search of surviving treatises on DEB published in Britain between 1547 and 1799, comprise extended evidence that enable us to make “justified statements” [Napier, C. J. (2002). The historian as auditor: Facts, judgments and evidence. Accounting Historians Journal, 29(2), 131–155] in support of the notion that writers encouraged a “capitalist mentality” [Bryer, R. A. (2000a). The history of accounting and the transition to capitalism in England. Part one: Theory. Accounting, Organizations and Society, 25(2), 131–162; Bryer, R. A. (2000b). The history of accounting and the transition to capitalism in England. Part two: Evidence. Accounting, Organizations and Society, 25(4/5), 327–381] among the rising merchant class. They did this by communicating to merchants the potential of DEB for presenting economic events in a financial form that enabled them to evaluate the amount and profitability of their business investments and provided data on which to base decisions designed to enhance the “Value and Condition of his Estate” (Stephens, 1735, p. 4). Further, based on the known occupations of these writers and drawing on knowledge of the operation of an international trading enterprise, the Hudson’s Bay Company, we speculate that DEB might have played a part in helping owners manage their affairs during the major economic and social developments that are known to have occurred in Britain and Western Society more generally between the 16th and 18th centuries.     

Barrier option pricing: a hybrid method approach

This paper adapts the hybrid method, a combination of the Laplace transformation and the finite-difference approach, to the pricing of barrier-style options. The hybrid method eliminates the time steps and provides a highly accurate and precise numerical solution that can be rapidly obtained. This method is superior to lattice methods when trying to solve barrier-style options. Previous studies have tried to solve barrier-style options; however, there have continually been several disadvantages. Very small time steps and stock node spaces are needed to avoid undesirable numerically induced oscillations in the solution of barrier option. In addition, all the intermediate option prices must be computed at each time step, even though one may be only interested in the terminal price of barrier-style complex options. The hybrid method may also solve more complex problems concerning barrier-style options with various boundary constraints such as options with a time-varying rebate. In order to demonstrate the accuracy and efficiency of the proposed scheme, we compare our algorithm with several well-known pricing formulas of barrier-type options. The numerical results show that the hybrid method is robust, and provides a highly accurate solution and fast convergence, regardless of whether or not the initial asset prices are close to the barrier.     

A multi‐agent‐based hybrid framework for international marketing planning under uncertainty

The increased complexity and competition in the global marketing environment present new challenges to decision‐makers. The characteristics of the international marketing planning problem are clarified in this paper. The advantages and disadvantages of relevant techniques and technologies that may be applied to deal with the planning problem are analysed. A multi‐agent‐based hybrid intelligent framework for international marketing planning and associated Internet strategy formulation is then established, with underlying techniques, technologies, software architecture and integration method outlined. In addition, a software prototype of the hybrid framework, called AgentsInternational, is created and presented, with initial evaluation results reported. Further work on this topic is also planned. Copyright © 2009 John Wiley & Sons, Ltd.     

Evaluating business credit risk by means of approach‐integrating decision rules and case‐based learning

This research utilizes a new approach which uses a hybrid learning system that combines two representations of knowledge: the first in a form of decision rules referring to general knowledge, and the other of single cases corresponding to exceptions or untypical situations. The Explore algorithm was chosen as a tool for inducing general rules. It generates all simple and sufficiently strong general rules from a given data set. Examples discovered by these rules are then used to identify exceptions and untypical cases. The paper discusses problems connected with tuning parameters of this approach and introduces a new procedure for this task. This methodology is applied to solve the problem of evaluating the risk of business credit applications in a Polish commercial bank. Using information about business credit applications, as described by 35 economic parameters and using five groups of banking risk, a knowledge base consisting of 70 decision rules and 15 specific cases was induced. Testing this model in the standard ‘leaving‐one‐out’ way we achieved the best classification accuracy of 81%. A comparative study showed that results obtained by other machine‐learning algorithms resulted in significantly worse classification accuracy. Copyright © 2001 John Wiley & Sons, Ltd.