Filters of weak signals hinder foresight: Monitoring weak signals efficiently in corporate decision-making

Already two decades ago strategy literature started a discussion on weak signals (H.I. Ansoff, Implanting Strategic Management, Prentice-Hall International, Englewood-Cliffs, NJ, 1984). Currently the weak signals approach is experiencing a renaissance in strategic planning but now either in the context of strategic flexibility or peripheral vision. In this paper we aim, firstly, to present theories describing filters that a weak signal has to pass in the strategy-creation process. Secondly, we present a construction for information filters in the strategy process and prove that the nature of objectives and the method used in environment scanning have a major impact on the outcome. Thirdly, we introduce an application that opens filters for weak signals in the strategy process and thus provides the organization with an opportunity for pro-active decision-making.     

Discovering bank risk factors from financial statements based on a new semi‐supervised text mining algorithm

This paper aims to comprehensively uncover bank risk factors from qualitative textual risk disclosures reported in financial statements, which contain a huge amount of information on bank risks. We propose a new semi‐supervised text mining approach named naive collision algorithm to analyse the textual risk disclosures, which can more accurately identify bank risk factors compared with the typical unsupervised text mining approach. We identified 21 bank risk factors in total, which is far more than identified in previous studies. We further analyse the importance of each bank risk factor and how the importance of each risk factor changes over time.     

Investment portfolio balancing: application of a generic self-organizing fuzzy neural network (GenSoFNN)

In contrast to short-term stock trading, portfolio managers are interested in the medium- to long-term peaks and troughs of the stock price cycles as signals to balance their stock portfolios – the predicted trough is the signal to buy the stock and the predicted peak is the signal to sell the stock. As statistical models are generally inadequate or incapable of providing such portfolio balancing signals, we propose using the generic self-organizing fuzzy neural network (GenSoFNN)—a fuzzy neural system – as a tool for portfolio balancing. The network adopts the supervised learning approach to detect inflection points in the stock price cycles, and a modified locally weighted regression algorithm is employed to smooth the stock cycles. The GenSoFNN-based portfolio balancing system was evaluated with experiments conducted using 23 stocks from the New York Stock Exchange and NASDAQ, and the results showed an average profit return of 65.66%. The contributions of the proposed GenSoFNN intelligent portfolio balancing system are twofold: it can be used as an efficient trading solution and it can provide decision support in trading via its generated rules. Copyright © 2009 John Wiley & Sons, Ltd.     

Insurance customer behavior: Lessons from behavioral economics

In economics it has traditionally been assumed that people make all their decisions like the so‐called homo oeconomicus – that is, maximizing (expected) utility of total wealth. In recent years, economics increasingly recognized that people often exhibit behavioral patterns which are incompatible with the idea of the homo oeconomicus. The field of behavioral economics incorporates insights from the field of psychology to explain discrepancies between predictions of traditional economic theory and actual observed behavior. In this paper, we summarize a selection of well‐established behavioral patterns observed in reality and discuss their relevance for the insurance industry when it comes to better understanding and predicting customer behavior. We also explain that people are not always risk‐averse and give a brief overview over Prospect Theory (probably the most popular behavioral economics alternative to Expected Utility Theory), its shortcomings for predicting behavior over a long time horizon, and its extensions. In total, we point out that, since dealing with risks and insurance products requires complex decision making processes, a deep understanding of the impacts of behavioral factors is essential to better assess and explain costumer behavior.     

A game-theoretic approach to decision making under uncertainty

We discuss the problem of decision making under uncertainty. Here an action choice must be made without knowing the value of all relevant variables. The importance of decision attitude, i.e. optimistic/pessimistic, is emphasized and a unified approach for evaluating alternatives under different attitudes is discussed. We show the connection between decision making under uncertainty and competitive decision making—game theory. We then draw upon a key concept used in game theory, the association of a selection probability with each alternative rather then a decisive selection of an alternative, and apply this idea to decision making under uncertainty. Copyright © 1999 John Wiley & Sons, Ltd.     

Integrating XBRL data with textual information in Chinese: A semantic web approach

Due to formatting differences, the difficulties of processing the textual disclosures and integrating them with quantitative financial data are well documented in the literature. Using a design science methodology, this paper describes a method that automatically extracts relevant textual data from annual reports published in Chinese. These extracted words are then mapped to a knowledge framework we proposed. This paper shows that it is technologically feasible to reorganize the MD&A contents into any given knowledge structure to improve the search capability, readability, and cohesiveness of the MD&A contents. Finally, we demonstrate a prototype system that uses semantic web technology to achieve information integration that presents XBRL formatted accounting data with relevant textual disclosures together to assist user decision making.     

Design junctions: Spaces and situations that frame weak signals – the example of hygiene and hospital planning

This article discusses the question: Are weak signals independent of framing and interactions with the environment? The response proposed here is that many of the developments identified by efforts to detect and interpret weak signals are the result of designed interventions that define the repertoire of actions and frames. Very often, as Ansoff argued, actors use a variety of models and filters for seeking and using weak signals. Thus weak signals are not only dependent on the interpretative equipment applied by actors, but from a constructivist perspective the identification of and meaning given to weak signals are strongly influenced by design choices made at the outset. In this sense design is a constitutive element of both the environment and signal detection/use. An example of how design is constitutive of both context and understanding can be found in the history of hospital hygiene. This case study illustrates how dominant regimes of practice, established through the conception of pathogen bacteria and antibacterial treatments and disinfection, are now creating signals that call into question fundamental design of hygiene practices. By examining the epistemic assumptions of scientific disciplines and the designed repertoire of practical responses it becomes clear how contexts and frames of interpretation are constituted and how such contexts and frames then define what is recognised as a weak signal.     

Does product market competition affect corporate governance? Evidence from corporate takeovers

We examine the extent to which shareholders strategically allow a weak governance structure in response to increasing competition pressures in the product market. We treat acquisitions by rival firms as shocks that increase threats in a competitive product market. We find that firms adopt greater entrenchment provisions when there are greater competition threats. Moreover, firms with high institutional ownership – especially by dedicated investors – and​ board independence within the compensation committee are particularly aggressive, which is consistent with our theory that aggressive behavior represents a strategic decision by shareholders. Finally, we find positive relationship between the adoption of entrenchment provisions and firm’s future performance, but only for the adoption under relatively severe competitive pressures.     

Learning to organise risk management in organisations: what future for enterprise risk management?

This paper identifies recurring issues in the regulation of new technologies through an historical review of the risk management of automobiles in the 1800s. Parallels are drawn between the regulation of early automobiles and that of the regulation of Unmanned Aircraft Systems (UASs) today. It is found that many of the regulatory challenges facing UASs are analogous to those which faced the automobile industry more than a century and half ago and that the need for informed and objective decision making in policy development is reinforced. A systems engineering approach, based on general systems theory and decision‐based design principles, is then proposed as a means for improving the objectivity, transparency and rationality in the risk management decision making process. An example risk management decision making scenario is given within the context of a small UAS operating over a populated area. The results obtained from this case study illustrate how even simple analysis can support the decision making process and highlights some of the potential challenges in the regulatory approach currently applied to UASs.     

Biogeography based optimization for mining rules to assess credit risk

Financial institutions, by and large, rely on the use of machine learning techniques to improve the classic credit risk assessment model for reduction of costs, delivery of faster decisions, guaranteed credit collections, and risk mitigations. As such, several data mining and machine learning approaches have been developed for computation of credit scores over the last few decades. Moreover, the existing rule-based classification algorithms tend to generate a number of rules with a large number of conditions in the antecedent part. However, these algorithms fail to demonstrate high predictive accuracy while balancing coverage and simplicity. Thus, it becomes quite a challenging task for the researchers to generate an optimal rule set with high predictive accuracy. In this paper, we present an effective rule based classification technique for the prediction of credit risk using a novel Biogeography Based Optimization (BBO) method. The novel BBO in the context of rule mining is named as locally and globally tuned biogeography based rule-miner (LGBBO-RuleMiner). This is applied for discovering optimal rule set with high predictive accuracy from the dataset containing both the categorical and continuous attributes. The performance of the proposed algorithm is compared against a variety of rule-miners such as OneR (1R), PART, JRip, Decision Table, Conjunctive Rule, J48, and Random Tree, along with some meta-heuristic based rule mining techniques by considering two credit risk datasets obtained from University of California, Irvine (UCI) repository. It is found from the comparative study that the proposed rule miner in ten independent runs of ten-fold cross validation outperforms all of the aforesaid algorithms in terms of predictive accuracy, coverage, and simplicity.     

Futures signals sense-making framework (FSSF): A start-up tool to analyse and categorise weak signals, wild cards, drivers, trends and other types of information

This article introduces future signals sense-making framework (FSSF), an alternative philosophy towards weak signals, emerging issues, drivers, and trends, that is in contrast to the traditional single signal or path extrapolation approach. The philosophy of FSSF is based on the principles of environmental scanning and pattern management, which state that if there is a grand transformation process on the way or if there is a new emerging pattern or phenomenon, such a process will certainly be reflected in many different ways. Therefore, in this philosophy, futures knowledge is believed to be fragmented between various simultaneous and overlapping sources. Here, a researcher's task is to carry out a sufficient environmental scanning process and to cluster and sense how to create the emerging future through a pattern management process where FSSF plays a role as the first start-up tool. Alternatively, FSSF can also be used as a general knowledge management and sense-making tool for any kind of analyses.     

我国企业环境管理会计实施现状及其对策——基于企业中高层管理人员的问卷调查

通过问卷调查,从企业环境管理决策的主体出发,对我国企业环境管理会计的关注度进行了描述性统计分析和因子分析,得出结论:(1)我国企业对于可持续发展和科学的环境管理方法等方面的认识还较薄弱;(2)大部分企业实施环境管理是一种策略性行为;(3)目前我国企业财会人员还未能真正参与到企业的环境管理决策工作当中来。     

Economic Value Added in performance measurement: A simulation approach and empirical evidence

With increasing criticism on measuring executive performance based primarily on Total Shareholder Return (TSR), some academics and practitioners have revived discussions on using Economic Value Added (EVA) as an alternative. But if EVA failed to gain traction over the past two decades, is there any new evidence for it or different approaches to better implement it in corporate settings? In this study, we start by confirming EVA-related metrics' significant positive relationships with long-term TSR in the Australian market. Our empirical findings also address EVA's major drawback – too much complexity arising from accounting adjustments. Our results suggest that accounting adjustments are generally not necessary, and efforts should be re-directed to designing direct and intuitive plan mechanisms. In addition, we develop a pseudo environment to illustrate EVA's managerial benefits and potential to cultivate sustainable growth. To study this influence, we leverage capital-based simulation techniques and mimic executive decision making under different performance measurement conditions, which was typically only discussed in a qualitative or theoretical sense. We find that EVA-related metrics naturally induce long-term, strategic and sustainable decision making without limiting executives to overly focus on short-term profitability. This simulation approach not only provides quantitative evidence, but also gives practitioners in different market environments an expandable and scalable pseudo framework to test the effect of different incentive plans and inform performance target setting, a useful but often overlooked feature in, for instance, the Australian market, where data is relatively scarce.     

Scenario planning interventions in organizations: An analysis of the causes of success and failure

This paper presents a case analysis of a successful scenario intervention in an organization. This intervention is compared and contrasted with an unsuccessful one reported in Hodgkinson and Wright [Confronting strategic inertia in a top management team: learning from failure, Organization Studies 23 (2002)949-977]. We demonstrate that analysis of the answers given by workshop participants in a pre-intervention interview can be helpful in determining the receptiveness of an organization to a subsequent scenario intervention. We theorize that strategic inertia-characterized by coping patterns of bolstering failing strategy, procrastination (over a strategic dilemma) and buck-passing (the responsibility for the dilemma's resolution), can be caused by the psychological attenuation of the perceived level of environmental threat to the organization, culminating in unconflicted adherence to the currently followed strategy. We contend that the expression of such coping behaviour is antithetical to a subsequent successful scenario exercise since, if the exercise fails to identify an unconflicted strategic alternative, the sharp focus of the scenarios on futures unfavourable to business-as-usual strategy will re-activate the cognitive stress-reduction mechanisms. Strategic inertia will thus be reinforced. We conclude with a review of the implications of our diagnosis for reflective practitioners.Our paper is divided into four sections. In Section 1, we overview writings on inertia in strategic decision making. We pay especial attention to identifying potential causes of inertia. Next, we present Janis and Mann's [Decision Making, Free Press, New York, 1979] views of the psychological processes invoked by conflicted decisions and analyse the relevance of this laboratory-based theory to provide a psychological explanation of strategic inertia. Finally, we briefly describe the scenario intervention process and argue that it contains the potential to overcome strategic inertia. In Section 2, we review an already-published study of an unsuccessful scenario planning intervention, which illustrates the operation of components of Janis and Mann's model. Next, in Section 3, we focus on our own case investigation of a successful scenario planning intervention. The early part of this section documents the “success”, whilst the latter part analyses the causes of the success—again using the components of Janis and Mann's model. We conclude in Section 4, where we compare and contrast the application of Janis and Mann's model to both cases and we demonstrate that application of the model to pre-intervention interview data can aid the practitioner determine, at the outset, whether or not the organizational context will be receptive to the intervention.     

Is Financial Reporting Still Useful? Australian Evidence

There has been recent and growing criticism of the usefulness of financial reporting for investors, particularly the annual financial statements. In response, the IASB is pursuing several projects aimed at improving the relevance of financial information. To inform the IASB’s work, we investigate, using a mixed-method approach, the extent and nature of the use of annual financial statements by equity investors. We examine the relevance of financial reporting for equity valuation in Australia across time. We find that financial reporting (specifically, reported net income, shareholders’ equity, and operating cash flows) remains relevant for investment decisions. We further support this finding with evidence from field interviews that provide insight into how and why financial statements are used by equity investors. The field evidence also demonstrates that no one financial statement dominates in investor decision making. Given the increasing availability of more timely, forward-looking information from alternative sources, we examine the relevance of non-GAAP financial information and other non-financial information for investor decision making. We find that non-GAAP financial information (as proxied by EBIT and EBITDA) is more value relevant than statutory measures. We further find a broad range of non-financial information is utilized by investors in making investment decisions both as a ‘screen’ and for valuation purposes. Our findings inform regulators and other stakeholders as we provide evidence of the continuing relevance of financial statements and the complementary role of non-GAAP financial and other information. Our evidence provides a rebuttal to the recent criticism.     

Integrating intelligent systems into marketing to support market segmentation decisions

For the last 50 years market segmentation has been considered to be a key concept in marketing strategy. As a means of tackling market heterogeneity, the underlying logic and managerial rationale for market segmentation is well established in the marketing literature. However, there is evidence to suggest that attempts by organizations to classify customers into distinct segments for whom product or services can be specifically tailored are proving to be difficult to implement in practice. As the business environment in which many organizations operate becomes increasingly uncertain and highly competitive, greater importance is now being attached to marketing knowledge. The purpose of this paper is to highlight market segmentation problems as a relevant area for a greater level of engagement of intelligent systems academic researchers and practitioners with their counterparts within the marketing discipline, in order to explore how data mining approaches can assist marketers in gaining valuable insights into patterns of consumer behaviour, which can then be used to inform market segmentation decision‐making. Since the application of data mining within the marketing domain is only in its infancy, a research agenda is proposed to encourage greater interdisciplinary collaboration between information systems and marketing so that data mining can more noticeably enter the repertoire of analytical techniques being employed for segmentation. Copyright © 2007 John Wiley & Sons, Ltd.     

DO STRATEGY AND MANAGEMENT MATTER IN MUNICIPAL ORGANISATIONS?

In Sweden, a large share of public services are organised, produced and delivered by municipalities, large and small, rich and poor. Contextual conditions (size and location) and economic conditions (efficiency and wealth) differ considerably among these service‐providing organisations. The question raised in this paper is whether a municipality's economic situation is a direct consequence of the contextual situation or the organisation's strategy and management – that is: Do strategy and management matter? Our analysis rests on a resource‐based view of organisation strategy. Both quantitative and qualitative observations have been made. First, cost savings data from 50 municipalities were examined for patterns and relationships between contextual and economic conditions. Second, about 100 representatives – municipal executive board members and leading officials – from 20 municipalities with different characteristics were interviewed. In this paper we outline an analytical framework and propose that sound and sustainable provision of municipal service depends on whether organisational decision‐making is in harmony with work methods and objectives. The results indicate that strategy and management do matter. Among the municipalities included in our study, we identify four prevalent basic strategies. Strategy tends to coincide with the economic situation rather than the contextual situation. A low‐performing municipality tends to have a predominantly outward orientation in its decision‐making, whereas a higher‐performing municipality makes decisions with both inward and outward orientation.     

Goodwill or “No-will”: Hubris in the tone at the top

In this study, we examine the effect of hubris in the “tone at the top” on goodwill accounting, specifically the proportion of the purchase price allocated to goodwill following a business combination, and subsequent decisions to write down goodwill. Using a sample of CEO letters to shareholders from firms listed on the Stockholm Stock Exchange, we carry out textual analysis of CEO letters to identify hubristic language markers. Regression analyses show that hubristic tone is positively and significantly associated with the purchase price allocation to goodwill. Furthermore, we predict that hubristic managers are more likely to overestimate future cash inflows related to goodwill and are less likely to perceive the need for a potential write-down. Consistent with this prediction, we find that hubristic tone in the CEO letters is associated with less timely goodwill write-downs. This study contributes to the literature on goodwill accounting, the role of CEO attributes on corporate decision making, and to research on CEO-speak, by providing evidence that a hubristic tone at the top can explain strategic choices by management and accounting outcomes.