Presence Of Environmental Uncertainty Research Articles

Disrupting optimal decision making in visual foraging: The impact of search experience.

This study introduces the diet-choice problem in foraging as a framework to investigate search and decision making in an uncertain environment. Using a mathematical model based on signal detection-based optimal foraging theory and conducting behavioral experiments, we examined whether the choice of uncertain options in a visual foraging task followed the optimal strategy. In addition, we explored whether search history affects behavior by changing the environment in a stepwise manner. We used a visual foraging task in which participants searched for visual stimuli and selected them using mouse clicks. To introduce uncertainty, the stimuli were designed in a way that they could not be completely discriminated by visual inspection. The study consisted of four sessions, during which the ratio of the number of gains to loss stimuli in Experiment 1 and the magnitude of loss in Experiment 2 were varied in a stepwise manner. Although search strategies can adapt to environmental changes, this adjustment is not always optimal. Specifically, although both the rising and falling groups experienced the same environment, their performance differed depending on the order in which participants experienced changing environments. Search strategy can be adjusted in the presence of environmental uncertainty, but it deviates from the optimal strategy due to the influence of the search history in the experienced environment. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Internal Control, Environmental Uncertainty and Total Factor Productivity of Firms—Evidence from Chinese Capital Market

Based on the data of China’s A-share listed companies from 2009 to 2019, this paper empirically examines the relationship between internal control and total factor productivity of enterprises in the presence of environmental uncertainty. The research shows that high quality internal control can effectively improve the total factor productivity of enterprises. Environmental uncertainty negatively moderates the relationship between internal control quality and total factor productivity. Further research in this paper shows that there are heterogeneous effects on the adjusting effects of different life cycles, property rights and regional distribution of enterprises, that is, when enterprises are in the growth stage, the quality of internal control has a significant effect on the improvement of total factor productivity of enterprises. For enterprises and non-state-owned enterprises located in the eastern region, the inhibition and adjustment effect of environmental uncertainty is more significant. At the same time, the supplementary research finds that internal control directly affects the total factor productivity of enterprises through the intermediary role of promoting enterprise development and innovation and easing financing constraints. The research conclusions enrich the literature on the mechanism of internal control affecting enterprises’ total factor productivity and provide a new reference and basis for enterprises to effectively manage the internal environment, strengthen the risk control management mechanism and improve the enterprise value.

The Impact of Environmental Uncertainty on Accounting Information Relevance and Performance: A Contingency Approach

This paper examines the association between environmental uncertainty, accounting information relevance, and organizational performance. From a contingency approach, this paper attempts to contribute to a stream of research that investigates the relationship between accounting information relevance and organizational performance. The presence of environmental uncertainty in this relationship has not been fully established. This paper contributes to this area by suggesting a framework to study and explain this connection. An online questionnaire-based survey was conducted, which produced 119 valid responses (a response rate of 23%) from large manufacturing companies operating in Portugal. The results suggest that in contexts of environmental uncertainty, the relevance of non-financial information increases. However, the relevance of financial information continues to outstrip that of non-financial information. The results also suggest that financial information and non-financial information are complementary, and not substitutes, and can be used simultaneously in different situations. These results have several implications for professionals involved in decision-making activities. It offers findings which are potentially useful for both theory and practice. The study addresses an identified gap in the literature and adds to the existing body of work analyzing the association between environmental uncertainty, accounting information relevance for decision-making purposes, and organizational performance.

Impact of the Strategic Role of IT on Explorative and Exploitative Innovation Activities: The Role of Environmental Uncertainty

ABSTRACTWhile numerous studies have examined the relationship between IT and innovation, comparatively few explore IT's contribution to explorative and exploitative innovation activities. A better understanding of the influence of IT's strategic role on exploration and exploitation innovation is critical for tracing the complex IT–innovation relationship. To address this gap, we develop a theoretical model that describes the contingent relationship between IT's strategic role and explorative and exploitative innovation activities. By testing the model using a multisource, matched sample of data from Chinese firms, we find that the IT roles of automation, information, and transformation differentially influence exploration and exploitation, underscoring IT's multifaceted role in organizational innovation activities. Specifically, IT‐enabled transformation positively affects exploration, and IT‐enabled information positively affects both exploration and exploitation. We also evidence the moderating effect of environmental uncertainty in these relationships by uncovering that IT‐enabled automation is negatively related to exploration, whereas IT‐enabled transformation positively affects both explorative and exploitative innovation activities with high environmental uncertainty. Our article contributes to the knowledge in the field by demonstrating the value of a firm's transformative IT investments to develop explorative and exploitative innovation activities in the presence of environmental uncertainty.

Robust Waveform Optimization for MIMO-OFDM-Based STAP in the Presence of Environmental Uncertainty

The issue of robust orthogonal frequency division multiplexing (OFDM) multi-input multi-output (MIMO) radar waveform optimization is considered here with clutter uncertainty to enhance the worst-case detection probability of the MIMO-OFDM radar-based space–time adaptive processing (STAP). Robust optimization is necessary on account of the fact that waveform design is generally sensitive to the initial parameter estimation errors. According to the max–min approach, the issue of robust waveform design is constructed with the criterion of maximizing the worst-case output SINR, namely signal-to-interference-noise ratio, under the constraints of the clutter covariance matrix (CCM) errors and constant modulus to ease this sensitivity systematically, and hence the robustness of STAP’s detection to the uncertainty in the CCM estimate can be enhanced. To handle the acquired nonlinear and sophisticated issue, an iterative approach based on diagonal loading (DL) is presented, in which the inner and outer optimization issues can be recast into semidefinite programming ones by employing DL method, and thus both of them can be tackled in an efficient way. As compared to uncorrelated waveforms and the non-robust algorithm, numerical simulations reveal that the developed approach can enhance the robustness of STAP’s detection to the uncertainty in the CCM considerably.

PENGARUH ORIENTASI CORPORATE SOCIAL RESPONSIBILITY (CSR) TERHADAP KINERJA SOSIAL PERUSAHAAN DENGAN KETIDAKPASTIAN LINGKUNGAN SEBAGAI VARIABEL PEMODERASI

The objective of this research is to investigates the relationship of company’s orientation toward social responsibility at small and medium enterprises to their social corporate performance. In addition, this research also examines the role of environmental uncertainty as the moderating variable in affecting the relationship of corporate social responsibility orientation and corporate social performance. Sample was taken from small and medium businesess in Jawa Tengah. Initial distribution of 300 set of questionnaires to SME respondents has resulted in final sample of 115 respondents that usable to the analysis stage. The results of this study show that company’s ethical orientation has positive relationship with corporate social performance, while company’s legal orientation has negative effect toward corporate social performance. Moreover, the presence of environmental uncertainty has resulted in two significant interactions with the two components of company’s orientation. The interaction of environmental uncertainty and company’s ethical orientation has negative relationship with corporate social performance. Similarly, the interaction of environmental uncertainty and company’s legal orientation has positive relationship with corporate social performance.

Sonar detection performance analysis with environmental uncertainty using vertical array data

Sonar detection performance is related to ocean environmental parameters, such as the source position, the ocean depth, the sound speed profile and geoacoustic parameters, etc. These parameters have strong spatial and temporal variability, which result to environmental uncertainty. The sonar detection system can be limited by the presence of environmental uncertainty. Based on a statistical model of the environmental uncertainty, the optimal Bayesian predictor by L. Sha has been applied in this paper to analyze the effects of environmental uncertainty on detection performance using vertical array data collected in two experiments. The first experiment took place in shallow water off the Italian west coast by the NATO SACLANT Center in 1993(SACLANT Sonar Data). The second experiment took place in shallow water in China in 2008(LOFAR'08 data). Quantitative effects of various uncertain parameters on detection performance have been illustrated to evaluate which one is the most sensitive and which one is insignificant. The present work is supported by the National Defense Fundamental Fund of China (No.613xxxxx).

Stochastic basis expansions applied to acoustic propagation in an uncertain, range, and depth-dependent, multi-layered waveguide.

We study the utility of stochastic basis expansions in acoustic propagation through a multi-layered ocean waveguide in the presence of environmental uncertainty. Environmental uncertainty means that the parameters that describe the waveguide are treated probabilistically. Specifically, in the differential equation governing propagation, the uncertainty appears in the sound speed profile as an explicit dependence on a set of random variables. This implies that the acoustic field itself is a random field. Stochastic basis expansions are attractive because of their often exponential convergence. We use a complete set of multivariate orthogonal polynomials to compute the acoustic field’s statistics. The field propagates by a wide-angle parabolic equation through a rectangular waveguide comprised of three layers separated by two horizontal interfaces. A pressure release surface and hard bottom bound the waveguide. The water’s sound speed is a constant perturbed by a small, random range, and depth-dependent term that models a frontal zone, the middle sedimentary layer is stratified and modeled to represent uncertainty in sound speed measurements, and the bottom layer is a deterministic attenuating layer. We compare the field’s statistics generated by the stochastic basis to those generated by Monte Carlo simulations.

ACOUSTIC PROPAGATION IN AN UNCERTAIN WAVEGUIDE ENVIRONMENT USING STOCHASTIC BASIS EXPANSIONS

A generalization of acoustic propagation in an uncertain ocean waveguide environment is described using a probabilistic formulation in terms of stochastic basis expansions. The problem is studied in the context of wave propagation in random media, where environmental uncertainty and its interaction with the acoustic field are described by stochastic, rather than deterministic parameters and fields. This representation, constructed explicitly in terms of Karhunen-Loève (KL) and polynomial chaos (PC) expansions, leads to coupled differential equations for the expansion coefficients from which the stochastic acoustic field can be obtained as a random process. The equations are solved in the narrow-angle parabolic approximation using a split-step method to compute moments of the random acoustic field at any point in the waveguide. Results are compared with Monte-Carlo computations of the acoustic field in the same environment to study the convergence of the truncated stochastic basis expansion representing the acoustic field. The rate of convergence of the truncated chaos expansion was found to be dependent on the particular moment computed. For the first and second moments corresponding to the mean field and the field intensity, convergence was achieved rapidly, only requiring low order expansions. Another second moment, the acoustic spatial coherence, converged more slowly due to the relative phase information that, in this formulation, is described by polynomial approximation. While stochastic basis expansions show promise for the development of compact representations of the acoustic field in the presence of environmental uncertainty, accelerated convergence schemes will be needed to allow for practical applications.

Acoustic propagation modeling in the presence of environmental uncertainty

Due to incomplete knowledge of ocean environments, this research incorporates environmental uncertainty into an acoustic model representing wave propagation in order to quantitatively represent the uncertainty of the acoustic field. The waveguide considered here has a spatially varying, uncertain sound speed distribution with a known correlation length. Karhunen‐Loeve and polynomial chaos expansions are used to represent the uncertainty in the environment and acoustic field, respectively, in a narrow‐ angle parabolic wave equation. In this two‐dimensional model, the water depth is 150 m and propagation is over a range of 20 km. The environmental uncertainty term in the wave equation is assumed to vary randomly in the range direction, and is characterized by an exponentially decaying correlation function. An implicit finite difference scheme is used to solve a set of coupled differential equations for the stochastic envelope function at different source frequencies in the range of a few hundred Hz. The simulated results will include probability density functions at selected spatial locations in the waveguide, first and second moments of the field, and these results will be compared with those obtained independently from Monte Carlo samplings from the same ocean environment. Work supported by ONR.

Use of polynomial chaos expansions in the design of uncertainty-robust matched field processing algorithms

The polynomial chaos (PC) expansion method has been recently applied to estimating the statistical properties of underwater acoustic propagation in the presence of environmental uncertainty. Here we use PC estimates of the field covariance structure to design uncertainty robust match field processing (MFP) weights using Krolik’s minimum variance beamformer with sound-speed perturbation constraints (MV-SPC) [J. Acoust. Soc. Am. 92 (3), 1408–1419 (1992)]. The idea behind the MV-SPC beamformer is to realize much of the high sidelobe rejection of MV processors in environments with environmental variability by opening up the signal model to include uncertainty effects. Here we compare the performance of MV-SPC designed with an adiabatic signal uncertainty model to the same beamformer designed with the PC signal model for realizations of the signal vector obtained with fully coupled propagation models, with results showing the superiority of the PC approach. [Work supported by ONR.]

Linking environmental uncertainty to non-financial performance measures and performance: a research note

Several previous research studies have reported mixed results concerning the direct association between non-financial performance measures and performance. The presence of environmental uncertainty on this relationship has not been established. This paper makes a contribution to this area by proposing that it is in conditions of environmental uncertainty that non-financial measures are most useful in improving organizational performance. It analyses empirical data from a sample of New Zealand manufacturing organizations to test the hypothesis that non-financial measures of performance would lead to improved organizational performance under conditions of increased environmental uncertainty. Multiple regression analysis of the data suggests that performance should be a declining function of the size of the ‘mismatch’ between an organization's environment and use of the different combinations of non-financial performance measures. Further, the paper concludes that prior mixed results may be attributed to the omission of environmental uncertainty.

Bayesian sonar detection performance prediction in the presence of interference in uncertain environments

The detection performance of sonar systems can be greatly limited by the presence of interference and environmental uncertainty. The classic sonar equation does not take into account these two limiting factors and is inaccurate in predicting sonar detection performance. Here we have developed closed-form receiver operating characteristic (ROC) performance expressions for the Bayesian detector in the presence of interference in uncertain environments. Various scenarios extended from a NRL benchmark shallow-water model were used to test the analytical ROC expressions and to analyze the effects of interference and environmental uncertainty on detection performance. The results show that (1) the degradation on detection performance due to interference is greatly magnified by the presence of environmental uncertainty; (2) Bayesian sonar detection performance depends on the following fundamental parameters: the signal-to-noise ratio, the rank of the signal matrix, and the signal-to-interference coefficient; (3) the proposed analytical ROC performance predictions can be computed much faster than performance evaluations with commonly used Monte Carlo techniques.

Performance of mode-based processing in the presence of environmental uncertainty

A critical limiting factor to the performance of many underwater sonar detection and localization techniques is the typically high degree of uncertainty regarding the ocean environment. Several researchers have proposed mode-based processing methods for Matched Field Processing, depth-dependent pre-filtering, and sub-array processing. Provided that an appropriate modal decomposition can be applied, these methods are believed to provide processing that is less sensitive to environmental mismatch, with the added potential advantage of computational efficiency. In this paper, we attempt to quantify the performance of mode-based processing in uncertain environments, and compare this performance to more classic processing approaches. Results are presented from Monte Carlo simulations of range-dependent environments in which the uncertainty is varied parametrically. An analytical framework for describing the uncertainty is presented and discussed.

On Temporal Controls and the Stochastic Behavior of Renewable Natural Resources

This paper provides a theoretical analysis of the effects of temporal controls on the stochastic behavior of renewable natural resources such as fisheries and rangelands. First, we show that temporal resource management is characterized by the existence of a threshold effect. Second, we point out that in the presence of environmental uncertainty, the ability of a manager to move a resource to a desirable state depends on the magnitude of the effect that the temporal control has on the state of the resource. Third, we show that if this magnitude is below a critical threshold then it will be impossible for the manger to reach any desirable state of the resource in a finite amount of time. Finally, we solve an optimization problem from the standpoint of a resource manager. Our analysis of this problem shows that the proper course of action involves choosing the temporal control in a way so that the resource is able to provide society with a flow of consumptive and non-consumptive services, and the persistence of the undesirable state is minimized.

On temporal controls and the stochastic behaviour of renewable natural resources

This paper provides a theoretical analysis of the effects of temporal controls on the stochastic behavior of renewable natural resources such as fisheries and rangelands. First, we show that temporal resource management is characterized by the existence of a threshold effect. Second, we point out that in the presence of environmental uncertainty, the ability of a manager to move a resource to a desirable state depends on the magnitude of the effect that the temporal control has on the state of the resource. Third, we show that if this magnitude is below a critical threshold then it will be impossible for the manger to reach any desirable state of the resource in a finite amount of time. Finally, we solve an optimization problem from the standpoint of a resource manager. Our analysis of this problem shows that the proper course of action involves choosing the temporal control in a way so that the resource is able to provide society with a flow of consumptive and non-consumptive services, and the persistence of the undesirable state is minimized.

DIVERSITY, KNOWLEDGE AND COMPLEXITY THEORY: SOME INTRODUCTORY ISSUES

This paper will discuss some introductory issues related to the role and importance of microdiversity of agents in the context of business networks. Traditional views emphasise the importance of connectivity in the making of industrial clusters, but neglect the crucial role of microdiversity. Microdiversity is important to achieve adaptive behaviour in the presence of environmental uncertainty. Diversity acts as a reservoir of potential strategies against unpredictable environments. Secondly, the formation of business networks is explained in terms of mechanisms generating diversity. Networks emerge as the organisational form in which the diversity of agents can self-organise. This paper suggests that the issue of diversity can be used to discriminate between the model of organisation based on rational allocation of resources — the firm — and the model of organisation based on emergence and self-organisation — the network. The paper concludes that the former is a diversity-reducing mechanism, whereas the latter is a diversity-enhancing mechanism

Diversity, Knowledge and Complexity Theory Some Introductory Issues

International Journal of Innovation ManagementVol. 05, No. 02, pp. 257-274 (2001) Special Issue: Distributed Systems of Knowledge and Complexity Theory; Guest Editors: Pierpaolo Andriani and Aldo RomanoNo AccessDIVERSITY, KNOWLEDGE AND COMPLEXITY THEORY: SOME INTRODUCTORY ISSUESPIERPAOLO ANDRIANIPIERPAOLO ANDRIANIUniversity of Durham Business School, Mill Hill Lane, Durham City DH1 3LB, United Kingdom Search for more papers by this author https://doi.org/10.1142/S1363919601000336Cited by:12 Previous AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsRecommend to Library ShareShare onFacebookTwitterLinked InRedditEmail AbstractThis paper will discuss some introductory issues related to the role and importance of microdiversity of agents in the context of business networks. Traditional views emphasise the importance of connectivity in the making of industrial clusters, but neglect the crucial role of microdiversity. Microdiversity is important to achieve adaptive behaviour in the presence of environmental uncertainty. Diversity acts as a reservoir of potential strategies against unpredictable environments. Secondly, the formation of business networks is explained in terms of mechanisms generating diversity. Networks emerge as the organisational form in which the diversity of agents can self-organise. This paper suggests that the issue of diversity can be used to discriminate between the model of organisation based on rational allocation of resources — the firm — and the model of organisation based on emergence and self-organisation — the network. The paper concludes that the former is a diversity-reducing mechanism, whereas the latter is a diversity-enhancing mechanismKeywords:complexityknowledgenetworksmicrodiversityclusters Remember to check out the Most Cited Articles! Be inspired by these New Titles in Business and Management FiguresReferencesRelatedDetailsCited By 12The impact of digital logistics start-ups on incumbent firms : a business model perspectiveJasmin Mikl, David M. Herold, Marek Ćwiklicki and Sebastian Kummer25 November 2020 | The International Journal of Logistics Management, Vol. 32, No. 4The effect of strategic knowledge management on the universities’ performance: an empirical approachSara Fernández-López, David Rodeiro-Pazos, Nuria Calvo and María Jesús Rodríguez-Gulías6 March 2018 | Journal of Knowledge Management, Vol. 22, No. 3The problem of student attrition in higher education: An alternative perspectiveColin Beer and Celeste Lawson13 June 2016 | Journal of Further and Higher Education, Vol. 41, No. 6Informed GovernanceCarlos Páscoa, Benjamin Fernandes and José Tribolet1 Jan 2016Competitive strategies and value creation: a twofold perspective analysisEmanuele Teti, Francesco Perrini and Linda Tirapelle7 Oct 2014 | Journal of Management Development, Vol. 33, No. 10The role of cross-national knowledge on organizational ambidexterity: A case of the global pharmaceutical industryDenise Dunlap, Tucker Marion and John Friar9 April 2013 | Management Learning, Vol. 45, No. 4Young People, Their Families and Social Supports: Understanding Resilience with Complexity TheoryJackie Sanders, Robyn Munford and Linda Liebenberg3 September 2011Evolving Specialization, Market and Productivity in an Agent-Based Cooperation ModelErbo Zhao, Guo Liu, Dan Luo, Xing’ang Xia and Zhangang Han1 Jan 2009Determinants of cross-national knowledge transfer and its effect on firm innovationMasaaki Kotabe, Denise Dunlap-Hinkler, Ronaldo Parente and Harsh A Mishra21 March 2007 | Journal of International Business Studies, Vol. 38, No. 2Emergence of Specialization from Global Optimizing Evolution in a Multi-agent SystemLei Chai, Jiawei Chen, Zhangang Han, Zengru Di and Ying Fan1 Jan 2007Knowledge for Free? Distributed Innovation as a Source of LearningAlistair Bowden17 August 2016 | Public Policy and Administration, Vol. 20, No. 3Reflective transformation: making the classroom work for organizations and their managersElizabeth Meuser and Cheryl Lapp11 October 2004 | Strategic Change, Vol. 13, No. 6 Recommended Vol. 05, No. 02 Metrics History Received 20 November 2000 Revised 20 February 2001 Accepted 27 February 2001 KeywordscomplexityknowledgenetworksmicrodiversityclustersPDF download

Robust matched-field localization in uncertain ocean environments

Matched-field source localization methods can be sensitive to environmental parameter mismatch. A statistically optimal approach to source localization in the presence of environmental uncertainty is the maximum a posteriori probability (MAP) estimator. Unfortunately, practical implementation of the MAP estimator results in a computationally intensive processor. In this paper, a localization technique is presented that is a computationally efficient approximation to the MAP estimator. A two-step search procedure is used to estimate source position. The first step utilizes an approximation to the MAP estimator which allows much of the computation to be computed efficiently off-line. This step also includes a computationally efficient range-depth smoothing which provides robustness to grid density. In step two, ambiguities arising from step one are resolved using a fine-grid search procedure over the source location parameters. Simulations using the NRL Workshop benchmark environment, which has seven uncertain environmental parameters, show the performance of the technique to be comparable to that of the MAP estimator while requiring only a fraction of the computations.

DESIGNING INSPECTION STRATEGIES FOR UNCERTAIN ENVIRONMENTS

ABSTRACTThis paper considers the problems of designing inspection strategies for production systems terms in the presence of environmental uncertainty. The framework for determining information priorities to support inspection system planning is presented in the contaxt of a generic production system that encompasses the characteristics of many real‐world serial production systems. The impact on the design decision of five key variables is considered: quality of producton processes, quality of inspection procedures, penalty cost for undetected defective units, relative cost of improving process vs. inspection, and shape of the cost functions for process and inspection enhancement. The framework for analysis involves varying factors over two or three orders of magnitude to determine optimal inspection strategies across a wide range of environments These results are used to compare design decisions made in the presence of environmental uncertainty using expected‐opportunity‐cost and minimization‐of‐maximum‐opportunity‐cost approaches. Design strategies are identified for situations ranging from complete lack of knowledge about the environment through increasing levels of information. Information‐gathering priorities are established, and the impact on the design decision of this additional information is assayed.