Research on the Innovative Decisions of Supermarket Private Brands and Designated Manufacturers

One of the core competencies of a supermarket lies in its branding.With the continuous development of the market economy and the ongoing evolution of consumer demand,private brands have progressively emerged as significant contributors to supermarket growth.However,a pivotal developmental challenge for supermarkets is navigating the innovative decision-making process between private brands and designated manufacturers.This paper aims to investigate the innovative decisions between private brands and designated manufacturers,along with the relevant promotional strategies employed during entry into the United States market.

A Building Information Modeling-Life Cycle Cost Analysis Integrated Model to Enhance Decisions Related to the Selection of Construction Methods at the Conceptual Design Stage of Buildings

Life Cycle Cost Analysis (LCCA) provides a systematic approach to assess the total cost associated with owning, operating, and maintaining assets throughout their entire life. BIM empowers architects and designers to perform real-time evaluations to explore various design options. However, when integrated with LCCA, BIM provides a comprehensive economic perspective that helps stakeholders understand the long-term financial implications of design decisions. This study presents a methodology for developing a model that seamlessly integrates BIM and LCCA during the conceptual design stage of buildings. This integration allows for a comprehensive evaluation and analysis of the design process, ensuring that the development aligns with the principles of low carbon emissions by employing modular construction, 3D concrete printing methods, and different building design alternatives. The model considers the initial construction costs in addition to all the long-term operational, maintenance, and salvage values. It combines various tools and data through different modules, including energy analysis, Life Cycle Assessment (LCA), and Life Cycle Cost Analysis (LCCA) to execute a comprehensive assessment of the financial implications of a specific design option throughout the lifecycle of building projects. The development of the said model and its implementation involves the creation of a new plug-in for the BIM tool (i.e., Autodesk Revit) to enhance its functionalities and capabilities in forecasting the life-cycle costs of buildings in addition to generating associated cash flows, creating scenarios, and sensitivity analyses in an automatic manner. This model empowers designers to evaluate and justify their initial investments while designing and selecting potential construction methods for buildings, and enabling stakeholders to make informed decisions by assessing different design alternatives based on long-term financial considerations during the early stages of design.

超级决策软件(Super Decisions)在体育综合评价中的应用研究

通过教练员能力综合评价案例,运用网络分析法(ANP法)构建指标框架,使用Super Decision软件计算指标权重,为Super Deci-sions和(ANP法)更好地应用于体育综合评价提供参考。

石竹科技与CRYSTAL DECISIONS携手开拓中国市场

世界上领先的信息管理软件公司Crystal Decisions宣布与石竹科技正式签定合作协议，共同在中国市场推广其企业报表、分析和信息交付解决方案。

Sequential maneuvering decisions based on multi-stage influence diagram in air combat

A multi-stage influence diagram is used to model the pilot＇s sequential decision making in one on one air combat. The model based on the multi-stage influence diagram graphically describes the elements of decision process, and contains a point-mass model for the dynamics of an aircraft and takes into account the decision maker＇s preferences under uncertain conditions. Considering an active opponent, the opponent＇s maneuvers can be modeled stochastically. The solution of multistage influence diagram can be obtained by converting the multistage influence diagram into a two-level optimization problem. The simulation results show the model is effective.

Intelligent Decisions Modeling for Energy Saving in Lifts:An Application for Kleemann Hellas Elevators

The present work proposes a methodological approach for modeling decisions regarding energy reduction in an elevator. This is achieved with the integration of existing as well as acquired knowledge, in a decision module implemented in the electronics of an elevator. So far, elevators do not exploit information regarding their recent usage. In the developed system decisions are driven based on information arising from monitoring the use of the elevator. Monitoring provides various records of usage which consequently are used to predict elevator’s future usage and to adapt accordingly its functioning. Till now, there are only elevators that encompass in their electronics algorithms with if then rules in order to control elevator’s functioning. However, these if then rules are based only on good practice knowledge of similar elevators installed in similar buildings. Even this knowledge which unavoidably is associated with uncertainty is not encoded in a mathematically consisted way in the algorithms. The design, the implementation and a first pilot evaluation study of an elevator’s intelligent decision module are presented. The study concludes that the presented application sufficiently reduces energy consumption through properly controlled functioning.

Impact of cash crop cultivation on household income and migration decisions:Evidence from low-income regions in China

This study examines the impact of cash crop cultivation on household income and migration decisions,using survey data collected from low-income regions in China.Given farmers decide themselves whether to cultivate cash crops,an endogenous treatment regression model that accounts for potential selection bias issue is used to analyze the data.The empirical results show that cash crop cultivation exerts a positive and statistically significant impact on household income,but it does not affect household migration decisions significantly.The disaggregated analyses reveal that cash crop cultivation significantly increases farm income but decreases off-farm income.

Attributes reduct and decision rules optimization based on maximal tolerance classification in incomplete information systems with fuzzy decisions

A new approach to knowledge acquisition in incomplete information system with fuzzy decisions is proposed. In such incomplete information system, the universe of discourse is classified by the maximal tolerance classes, and fuzzy approximations are defined based on them. Three types of relative reducts of maximal tolerance classes are then proposed, and three types of fuzzy decision rules based on the proposed attribute description are defined. The judgment theorems and approximation discernibility functions with respect to them are presented to compute the relative reduct by using Boolean reasoning techniques, from which we can derive optimal fuzzy decision rules from the systems. At last, three types of relative reducts of the system and their computing methods are given.

What factors affect physicians’ decisions to use an e-health care system?

Prior studies have not explored physician’s attitudes toward, and behavior and willingness to accept an e-health care system. However, physicians can induce demand for their services. The development of the high-tech asthma care mobile service (ACMS) in Taiwan provided a means of exploring key factors in a physician’s choice of using an ACMS. The study was based on the technology acceptance model (TAM) and integrated “subjective norm,” “innovativeness,” and “managerial support” to understand and predict physicians’ attitudes and behavioral intentions toward adopting high-tech healthcare systems such as the ACMS. Of 700 questionnaires distributed to physicians with experience using ACMS, 504 completed returns were received (a 72% response rate). The data were analyzed using the structural equation modeling (SEM) method. The results of the study showed that the model selected to explain and predict utilization of the ACMS had high explanatory power and was a good-fit model. The most critical factor that affected behavioral intentions related to ACMS was user attitude, followed by perceived usefulness, managerial support, subjective norm, perceived ease of use, and innovativeness.

How time-inconsistent preferences influence venture capital exit decisions?A new perspective for grandstanding

Considering that the assumption of time consistency does not adequately reveal the mechanisms of exit decisions of venture capital(VC),this study proposes two kinds of time-inconsistent preferences(i.e.,time-flow inconsistency and time-point incon-sistency)to advance research in this field.Time-flow inconsistency is in line with the previous time inconsistency literature,while time-point inconsistency is rooted in the VC fund’s finite lifespan.Based on the assumption about the strategies guiding future behaviors,we consider four types of venture capitalists:time-consistent,time-point-inconsistent,naïve,and sophisticated venture capitalists,of which the latter three are time-inconsistent.We derive and compare the exit thresholds of these four types of venture capitalists.The main results include:(1)time-inconsistent preferences acceler-ate the exits of venture capitalists;(2)the closer the VC funds expiry dates are,t`he more likely time-inconsistent venture capitalists are to accelerate their exits;and(3)future selves caused by time-flow inconsistency weaken the effect of time-point inconsist-ency.Our study provides a behavioral explanation for the empirical fact of young VCs’grandstanding.

Autonomous Maneuver Decisions via Transfer Learning Pigeon-Inspired Optimization for UCAVs in Dogfight Engagements

This paper proposes an autonomous maneuver decision method using transfer learning pigeon-inspired optimization(TLPIO)for unmanned combat aerial vehicles(UCAVs)in dogfight engagements.Firstly,a nonlinear F-16 aircraft model and automatic control system are constructed by a MATLAB/Simulink platform.Secondly,a 3-degrees-of-freedom(3-DOF)aircraft model is used as a maneuvering command generator,and the expanded elemental maneuver library is designed,so that the aircraft state reachable set can be obtained.Then,the game matrix is composed with the air combat situation evaluation function calculated according to the angle and range threats.Finally,a key point is that the objective function to be optimized is designed using the game mixed strategy,and the optimal mixed strategy is obtained by TLPIO.Significantly,the proposed TLPIO does not initialize the population randomly,but adopts the transfer learning method based on Kullback-Leibler(KL)divergence to initialize the population,which improves the search accuracy of the optimization algorithm.Besides,the convergence and time complexity of TLPIO are discussed.Comparison analysis with other classical optimization algorithms highlights the advantage of TLPIO.In the simulation of air combat,three initial scenarios are set,namely,opposite,offensive and defensive conditions.The effectiveness performance of the proposed autonomous maneuver decision method is verified by simulation results.

Relationships between Features of EmergingAdulthood, Situated Decisions toward PhysicalActivity, and Physical Activity among CollegeStudents: The Moderating Role of ExerciseIntensity Tolerance

A significant portion of emerging adults do not achieve recommended levels of physical activity (PA). Previous studies observedassociations between features of emerging adulthood and PA levels, while the potential psychological mechanisms that mightexplain this phenomenon are not fully understood. In this context, there is some evidence that situated decisions towardphysical activity (SDPA) and exercise-intensity tolerance might influence PA level. To provide empirical support for thisassumption, the current study investigated whether (i) features of emerging adulthood are linked to SDPA, which, in turn,might affect PA engagement;(ii) exercise-intensity tolerance moderate the relationship between SDPA and PA level;and (iii)SDPA is a mediator of the relationship between features of emerging adulthood and PA levels under the prerequisite thatexercise-intensity tolerance moderates the link between SDPA and PA engagement. In this study a group of 1,706 Chinesecollege students was recruited and asked to complete a set of questionnaires assessing their SDPA, PA levels, exercise-intensitytolerance, and features associated with emerging adulthood, namely Self-exploration, Instability, and Possibility. Our resultsindicated that SDPA positively predicted PA levels and this relationship became stronger when exercise-intensity tolerance wasused as a moderator. Furthermore, it was observed that individuals with a higher level of Instability and a lower level ofPossibility during emerging adulthood exhibited a lower level of SDPA. Taken together, the results of our study providefurther insights on a potential psychological mechanism linking features of emerging adulthood and physical activity.

Application of TOPSIS Method in Support of Decisions Made in Staff Management Issues

Evaluation model was proposed which refers to fuzzy formalism of the personnel management issues taking account their specific characteristics. Application of TOPSIS （technique for order Performance by similarity to ideal solution） method for evaluation and regulation of alternatives based on hierarchically structured criteria of qualitative character by multiple experts to intellectually support decisions made in staff management issues is reviewed in the article. Candidate selection experiment based on criteria system formed using TOPSIS method for evaluation of candidates during solution of hiring problems reviewed and obtained results were compared with results obtained using Matlab program package.

Corporate governance and financing decisions by Saudi companies

This paper aims to contribute to the corporate governance literature in emerging economies by examining the effect of some corporate governance mechanisms on financing decisions in Saudi Arabian listed companies. A multiple regression model is used to examine the association between financing decisions and corporate governance mechanisms for a sample of 37 listed Saudi companies. In particular, we examine the effect of board size, ownership concentration and corporate governance reporting on the debt-to-equity ratio. Corporate governance reporting is measured by the content analysis approach. After controlling for companies＇ profitability and their growth opportunities, we found that both board size and ownership concentration are positively associated with debt-to-equity ratio. We limit our analysis to a small sample of firms that use the internet to communicate corporate governance information between October 2005 and January 2006. The findings suggest that managers are likely to choose higher financial leverage when they have stronger corporate governance （large number of directors on the board and higher ownership concentration）. However, we did not find any statistical association between corporate governance disclosure and debt-to-equity ratio. This suggests that firm＇s asymmetric information is not an important driver of the financing decision of Saudi Arabian companies. This might be due to the nature of the Saudi business environment. We strongly believe that this paper provides a novel contribution to the existing literature as we are the first to examine this issue in Saudi Arabia.

Managing Value-Based Activity Flexibility on Integrated ERP

On the background of integrated ERP development, activity-value-flexibility management (AVFM) is defined. By using economic-value-added (EVA) and corporate value creation as the objective of AVFM, custom value deviating rate, capital cost deviating rate, cash-flow-out per purchase deviating rate and cash-flow-in per sell deviating rate are developed to be the key responding variates for AVFM, and they also decide the rational quantity range for AVFM tactics. Method for rational AVFM tactics solution could be got by means of redesigning activity information process on integrated ERP.

Advanced decision support for complex clinical decisions

A Physician’s decision-making skills are directly related to the patient’s positive outcomes. Therefore, a wealth of medical knowledge and clinical experience are key assets for a physician to have. The goal here is to use historical clinical data and relationships processed by Artificial Intelligence (AI) techniques to aid physicians in their decision making process. Presenting this information in a Clinical Decision Support System (CDSS) is an effective means to consolidate decision results. The CDSS provides a large number of medical support functions to help clinicians make the most reasonable diagnosis and choose the best treatment measures. Initial results have shown great promise in accurately predicting Fibrosis Stage in Hepatitis patients. Utilizing this tool could mitigate the need for some liver biopsies in the more than 170 million Hepatitis patients worldwide. The prototype is extendable to accommodate additional techniques (for example genetic algorithms and logistics regression) and additional medical domain solutions (for example HIV/AIDS).

Value-Based Test Case Prioritization for Regression Testing Using Genetic Algorithms

Test Case Prioritization(TCP)techniques perform better than other regression test optimization techniques including Test Suite Reduction(TSR)and Test Case Selection(TCS).Many TCP techniques are available,and their performance is usually measured through a metric Average Percentage of Fault Detection(APFD).This metric is value-neutral because it only works well when all test cases have the same cost,and all faults have the same severity.Using APFD for performance evaluation of test case orders where test cases cost or faults severity varies is prone to produce false results.Therefore,using the right metric for performance evaluation of TCP techniques is very important to get reliable and correct results.In this paper,two value-based TCP techniques have been introduced using Genetic Algorithm(GA)including Value-Cognizant Fault Detection-Based TCP(VCFDB-TCP)and Value-Cognizant Requirements Coverage-Based TCP(VCRCB-TCP).Two novel value-based performance evaluation metrics are also introduced for value-based TCP including Average Percentage of Fault Detection per value(APFDv)and Average Percentage of Requirements Coverage per value(APRCv).Two case studies are performed to validate proposed techniques and performance evaluation metrics.The proposed GA-based techniques outperformed the existing state-of-the-art TCP techniques including Original Order(OO),Reverse Order(REV-O),Random Order(RO),and Greedy algorithm.

Re-Discussion on the Financial Boundaries for Corporate Merger and Acquisition Decisions

This paper discusses the acquiring methods of corporatemerger and acquisition,defines the financial boundariesof negotiation for both an acquirer and an acquiree,de-velops a new analyzing model to determine the financialboundary for the M&A decision.The paper also putsforward the negotiation range of transferring price andcondition for the acquirer and acquiree by quantitativeanalysis.In the end,the peper points out that it is prof-itable for both of the acquirer and acquiree to implementacquisition in the range of financial boundaries.

ERP Effects of Word Exposure and Orthographic Knowledge on Lexical Decisions in Spanish

Orthographic knowledge is affected by language processing, which is associated with word exposure. This study used event-related potentials (ERP) to explore this association in Spanish-speaking adults with different levels of orthographic competence (High Spelling Skills: HSS;Low Spelling Skills: LSS) while they performed a lexical decision task on previously exposed words (1 or 5 times). Both groups benefited from the exposure rate, but HSS reached significantly higher correct and faster responses, particularly with repeated words. Word recognition potential (RP) amplitude was higher bilaterally in HSS group, especially with repeated words, while P220 was found to be right-lateralized and sensitive to word exposure. Also, the amplitude of P600 varied as a function of word exposure and positively correlated with reading speed. Results suggest that LSS group is less sensitive to word exposure and fails to automatize strategies to word recognition that affect reading fluency.

Stress-assisted corrosion mechanism of 3Ni steel by using gradient boosting decision tree machining learning method

Traditional 3Ni weathering steel cannot completely meet the requirements for offshore engineering development,resulting in the design of novel 3Ni steel with the addition of microalloy elements such as Mn or Nb for strength enhancement becoming a trend.The stress-assisted corrosion behavior of a novel designed high-strength 3Ni steel was investigated in the current study using the corrosion big data method.The information on the corrosion process was recorded using the galvanic corrosion current monitoring method.The gradi-ent boosting decision tree(GBDT)machine learning method was used to mine the corrosion mechanism,and the importance of the struc-ture factor was investigated.Field exposure tests were conducted to verify the calculated results using the GBDT method.Results indic-ated that the GBDT method can be effectively used to study the influence of structural factors on the corrosion process of 3Ni steel.Dif-ferent mechanisms for the addition of Mn and Cu to the stress-assisted corrosion of 3Ni steel suggested that Mn and Cu have no obvious effect on the corrosion rate of non-stressed 3Ni steel during the early stage of corrosion.When the corrosion reached a stable state,the in-crease in Mn element content increased the corrosion rate of 3Ni steel,while Cu reduced this rate.In the presence of stress,the increase in Mn element content and Cu addition can inhibit the corrosion process.The corrosion law of outdoor-exposed 3Ni steel is consistent with the law based on corrosion big data technology,verifying the reliability of the big data evaluation method and data prediction model selection.