چارچوب حاکمیتی هوش تجاری در دانشگاه: مطالعه موردی دانشگاه دو لا کاستا
سال انتشار: 2020 - تعداد صفحات فایل pdf انگلیسی: 8 - تعداد صفحات فایل doc فارسی: 25
دانشگاه ها و شرکت ها دارای فرآیندهای تصمیم گیری هستند که به آنها اجازه می دهد تا به اهداف سازمانی دست پیدا کنند. در حال حاضر، تحلیل داده ها نقش مهمی در ایجاد دانش، بدست آوردن الگوهای مهم و پیش بینی استراتژی ها ایفا می کنند.این مقاله طراحی چارچوب نظارت هوش تجاری را برای دانشگاه دو لا کاستا ارائه کرده است که به آسانی برای سازمان های دیگر هم قابل استفاده است. برای این منظور، تشخیص انجام شده به منظور شناسایی میزان بلوغ تحلیلی انجام شده است. با استفاده از این چشم انداز، مدلی برای تقویت فرهنگ سازمانی ، زیر ساختارها، مدیریت داده، تحلیل داده و نظارت ارائه شده است.این مدل در بر گیرنده تعریف چارچوب نظارتی، اصول هدایت کننده، استراتژی ها، نهادهای تصمیم گیرنده و نقش ها می باشد. بنابراین، این چارچوب برای استفاده از کنترل های موثر جهت اطمینان از موفقیت پروژه های هوش تجاری و دست یابی به اهداف برنامه توسعه همراه با چسم انداز تحلیلی سازمان ارائه شده است.
کلمات کلیدی: هوش تجاری | نظارت | دانشگاه | تحلیل | تصمیم گیری
|مقاله ترجمه شده|
Breaking the barriers between intelligence, investigation and evaluation: A continuous approach to define the contribution and scope of forensic science
شکستن موانع بین هوشمندی ، تحقیق و ارزیابی: رویکردی مداوم برای تعریف سهم و دامنه علم پزشکی قانونی-2020
Forensic science has been evolving towards a separation of more and more specialised tasks, with forensic practitioners increasingly identifying themselves with only one sub-discipline or task of forensic science. Such divisions are viewed as a threat to the advancement of science because they tend to polarise researchers and tear apart scientific communities. The objective of this article is to highlight that a piece of information is not either intelligence or evidence, and that a forensic scientist is not either an investigator or an evaluator, but that these notions must all be applied in conjunction to successfully understand a criminal problem or solve a case. To capture the scope, strength and contribution of forensic science, this paper proposes a progressive but non-linear continuous model that could serve as a guide for forensic reasoning and processes. In this approach, hypothetico-deductive reasoning, iterative thinking and the notion of entropy are used to frame the continuum, situate forensic scientists’ operating contexts and decision points. Situations and examples drawn from experience and practice are used to illustrate the approach. The authors argue that forensic science, as a discipline, should not be defined according to the context it serves (i.e. an investigation, a court decision or an intelligence process), but as a general, scientific and holistic trace-focused practice that contributes to a broad range of goals in various contexts. Since forensic science does not work in isolation, the approach also provides a useful basis as to how forensic scientists should contribute to collective and collaborative problem-solving to improve justice and security.
Keywords: Crime | Decision points | Entropy | Hypothetico-deductive reasoning | Model
Customer-centric prioritization of process improvement projects
اولویت بندی مشتری محور پروژه های بهبود فرآیند-2020
Today, customers can conveniently compare products and decide how to interact with companies. With customer centricity becoming an important success factor, companies must drive customer satisfaction not only through excellent products but also through customer-centric processes. As many companies face an abundance of action possibilities, fast-changing customer needs, and scarce resources, guidance regarding the customercentric prioritization of process improvement projects is in high need. As existing approaches predominantly focus on process efficiency, we propose a decision model that accounts for the effects of process improvement on customer centricity in line with justificatory knowledge on value-based process decision-making, project portfolio selection, and the measurement of customer satisfaction. When building the decision model, we adopted the design science paradigm and used multi-criteria decision analysis as well as normative analytical modeling as research methods. We evaluated the model by discussing it with practitioners, by building a software prototype, and by applying it at a German insurance company. Overall, our research extends the prescriptive knowledge on process prioritization and customer process management.
Keywords: Business process management | Business process improvement | Process decision-making | Customer centricity | Project portfolio selection | Kano model
Juror appraisals of forensic evidence: Effects of blind proficiency and cross-examination
ارزیابی صلاحیت شواهد پزشکی قانونی: تأثیر مهارت کور و معاینه متقابل-2020
Forensic testimony plays a crucial role in many criminal cases, with requests to crime laboratories steadily increasing. As part of efforts to improve the reliability of forensic evidence, scientific and policy groups increasingly recommend routine and blind proficiency tests of practitioners. What is not known is how doing so affects how lay jurors assess testimony by forensic practitioners in court. In Study 1, we recruited 1398 lay participants, recruited online using Qualtrics to create a sample representative of the U.S. population with respect to age, gender, income, race/ethnicity, and geographic region. Each read a mock criminal trial transcript in which a forensic examiner presented the central evidence. The low- proficiency forensic examiner elicited a lower conviction rate and less favorable impressions than the control, an examiner for which no proficiency information was disclosed. However, the high-proficiency examiner did not correspondingly elicit a higher conviction rate or more favorable impressions than the control. In Study 2, 1420 participants, similarly recruited using Qualtrics, received the same testimony, but for some conditions the examiner was cross-examined by a defense attorney. We find crossexamination significantly reduced guilty votes and examiner ratings for low-proficiency examiners. These results suggest that disclosing results of blind proficiency testing can inform jury decision-making, and further, that defense lawyering can make proficiency information particularly salient at a criminal trial.
Keywords: Forensic science | Proficiency testing | Expert testimony | Cross-examination | Jury decision-making
Exploring the emergence of lock-in in large-scale projects: A process view
کاوش در ظهور قفل شدن در پروژه های مقیاس بزرگ: نمای فرآیند-2020
The purpose of this paper is to investigate the emergence of lock-in in large-scale projects. Although large-scale projects have been studied for decades, most studies have applied economic or psychological perspectives to emphasize decision-making processes at the project front-end. Of those studies, some have focused on poor decision-making due to lock-in and the escalating commitments of decision-makers to ineffective courses of action. However, little is known about the way that project decisions are affected by organizational and interorganizational contexts and the actors involved. Understanding decisions from a process viewpoint with a long-term (inter-) organizational perspective will lead to a better understanding of lock-in and the overall performance of large-scale projects. This qualitative research is based on a case study. The research setting is the multi-actor Madrid–Barcelona High-Speed rail Line (HSL) project in Spain. Through observations, interviews, several project documents, and report analysis, we explore the processual nature of the choices made during the course of the project. We consider the contextual conditions that give rise or support the emergence of lock-in in relation to pre- and post-project effects, institutional influences, and management practices that create action spaces at the project level. Our findings suggest that lock-in emergence requires the recognition of the long-term (inter-) organizational perspective regarding mechanisms and effects rather than confining decisions to the individual or single actor control in the front-end of projects. Based on organizational theory, the main contribution of this paper is to enrich our understanding of the emergence of lock-in using process theories.
Keywords: Lock-in | Path dependence and creation | The decision-making process | Large-scale projects | Temporary inter-organizational setting | Process theory
It is about time: Bias and its mitigation in time-saving decisions in software development projects
درباره زمان است: تعصب و کاهش آن در تصمیم گیری های صرفه جویی در زمان در پروژه های توسعه نرم افزار-2020
Estimates of completion times in software development projects are frequently inaccurate, potentially resulting in failure to meet project objectives. The present work aims at empirically investigating whether the time-saving bias, describing the human failure to correctly estimate the relationship between speed increase and time saving, can inform our understanding of the decades-long problem of time estimation in software development. In particular, this work examines whether a decision to save time in a software development project by increasing development speed is biased, whether this bias is observed when the decision is framed using plan-based and agile terminology, and whether the availability of relevant information mitigates this bias. These objectives are addressed in three experimental studies, in which senior information systems students (Study 1) and professional software project managers (Studies 2 and 3) are asked to make time-saving decisions about two similar scenarios, with and without relevant information. The findings confirm the existence of the bias and show that it is more likely to occur under an agile framing than under a plan-based framing, although students are highly biased in both cases. The findings also show that while the bias is mitigated, but not eliminated, when relevant information is included in the scenario, this effect dissipates once the information is no longer included in the following scenario. The accumulated evidence reported here contributes to research on the consequences of cognitive biases for project management decisions.
Keywords: Decision making | Time-saving bias | Software development projects | Experiments
Exponential operational laws and new aggregation operators for intuitionistic multiplicative set in multiple-attribute group decision making process
قوانین عملیاتی نمایی و اپراتورهای تجمیع جدید برای مجموعه چند برابر شهودی در فرایند تصمیم گیری گروهی چند صفت-2020
The intuitionistic multiplicative preference set is one of the replacements to the intuitionistic fuzzy preference set, where the preferences related to the object is asymmetrical distribution about 1. In it, Saaty’s 1–9 scale has been used to represent the uncertain and imprecise information. Meanwhile, an aggregation operator by using general operational laws for some fuzzy sets is an important task to aggregate the different numbers. Motivated by these primary characteristics, it is interesting to present the concept of exponential operational laws, which differs from the traditional laws by the way, in which bases are real numbers while exponents are the intuitionistic multiplicative numbers. In this paper, we develop a methodto solve the Multiple Attribute Group Decision Making (MAGDM) problem under the Intuitionistic Multiplicative Sets (IMS) environment. To do it, firstly, we define some new exponential operational laws and a score function for IMS and studied their properties. Secondly, based on this, we develop some averaging and geometric aggregation operators and characterize their various properties. Thirdly, a novel approach is promoted to solve MAGDM problems with IMS information. Finally, some numerical illustrations are given with a comparative study to verify the approach.
Keywords: Intuitionistic multiplicative sets | MAGDM | Exponential operational laws | Aggregation operators | Score function
Data mining of customer choice behavior in internet of things within relationship network
داده کاوی رفتار انتخاب مشتری در اینترنت اشیایی که در شبکه ارتباطی قرار دارند-2020
Internet of Things has changed the relationship between traditional customer networks, and traditional information dissemination has been affected. Smart environment accelerates the changes in customer behaviors. Apparently, the new customer relationship network, benefitted from the Internet of Things technology, will imperceptibly influence customer choice behaviors for the cyber intelligence. In this work, we selected 298 customers click browsing records as training data, and collected 50 customers who used the platform for the first time as research objects. and use the smart customer relationship network correspond to cyber intelligence to build the customer intelligence decision model in Internet of Things. The results showed that the MAE (Mean Absolute Deviation) of the customer trust evaluation model constructed in this study is 0.215, 45% improvement over the traditional equal assignment method. In addition, customers consumer experience can be enhanced with the support of data mining technology in cyber intelligence. Our work indicated the key to build eliminates confusion in customer choice behavior mechanism is to establish a consumer-centric, effective network of customers and service providers, and to be supported by the Internet of Things, big data analysis, and relational fusion technologies.
Keywords: Internet of things | Customer relationship network | Decision making | Recommendation | Fusion algorithm
A different sleep apnea classification system with neural network based on the acceleration signals
یک سیستم طبقه بندی sleep apnea متفاوت با شبکه عصبی مبتنی بر سیگنال های شتاب-2020
Background and objective: The apnea syndrome is characterized by an abnormal breath pause or reduction in the airflow during sleep. It is reported in the literature that it affects 2% of middle-aged women and 4% of middle-aged men, approximately. This study has vital importance, especially for the elderly, the disabled, and pediatric sleep apnea patients. Methods: In this study, a new diagnostic method is developed to detect the apnea event by using a microelectromechanical system (MEMS) based acceleration sensor. It records the value of acceleration by measuring the movements of the diaphragm in three axes during the respiratory. The measurements are carried out simultaneously, a medical spirometer (Fukuda Sangyo), to test the validity of measurement results. An artificial neural network model was designed to determine the apnea event. For the number of neurons in the hidden layer, 1-3-5-10-18-20-25 values were tried, and the network with three hidden neurons giving the most suitable result was selected. In the designed ANN, three layers were formed that three neurons in the hidden layer, the two neurons at the input, and two neurons at the output layer. Results: A study group was formed of 5 patients (having different characteristics (age, height, and body weight)). The patients in the study group have sleep apnea (SA) in different grades. Several 12.723 acceleration data (ACC) in the XYZ-axis from 5 different patients are recorded for apnea event training and detection. The measured accelerometer (ACC) data from one of the patients (called H1) are used to train an ANN. During the training phase, MSE is used to calculate the fitness value of the apnea event. Then Apnea event is detected successfully for the other patients by using ANN trained only with H1’s ACC data. Conclusions: The sleep apnea event detection system is presented by using ANN from directly acceleration values. Measurements are performed by the MEMS-based accelerometer and Industrial Spirometer simultaneously. A total of 12723 acceleration data is measured from 5 different patients. The best result in 7000 iterations was reached (the number of iterations was tried up to 10.000 with 1000 steps). 605 data of only H1 measurements are used to train ANN, and then all data used to check the performance of the ANN as well as H2, H3, H4, and H5 measurement results. MSE performance benchmark shows us that trained ANN successfully detects apnea events. One of the contributions of this study to literature is that only ACC data are used in the ANN training step. After training for one patient, the ANN system can monitor the apnea event situation on-line for others.
Keywords: Sleep apnea | Acceleration sensor | Acceleration data | Artificial neural network | Medical decision making
Intelligent decision-making of online shopping behavior based on internet of things
تصمیم گیری هوشمندانه از رفتار خرید آنلاین مبتنی بر اینترنت اشیا-2020
The development of big data and Internet of things (IoT) have brought big changes to e-commerce. Different kinds of information sources have improved the consumers’ online shopping performance and make it possible to realize the business intelligence. Grip force and eye-tracking sensors are applied to consumers online reviews search behavior by relating them to the research approaches in IoT. To begin with, public cognition of human contact degrees of recycled water reuses with grip force test was measured. According to the human contact degrees, 9 recycled water reuses presented by the experiment are classified into 4 categories. Based on the conclusion drawn from grip force test, purified recycled water and fresh vegetable irrigated with recycled water are regarded as the drinking for high-level human contact degree and the irrigation of food crops for low-level human contact degree respectively. Several pictures are designed for eye-tracking test by simulating an on-line shopping web page on Taobao (the most popular online shopping platform in China). By comparing the fixation time participants spent on the areas of interest (AOIs), we justify that consumers online reviews search behavior is substantially affected by human contact degrees of recycled products. It was found that consumers rely on safety perception reviews when buying high contact goods.
Keywords: Online reviews search behavior | Recycled products | Grip force sensor | Eye-tracking sensor | Internet of Things (IoT)