Personality as a Predictor of Unit Nonresponse in Panel Data: An Analysis of an Internet-Based Survey

Unit nonresponse or attrition in panel data sets is often a source of nonrandom measurement error. Why certain individuals attrite from longitudinal studies and how to minimize this phenomenon have been examined by researchers. However, this research has typically focused on data sets collected via telephone, postal mail, or face-to-face interviews. Moreover, this research usually focuses on using demographic characteristics such as educational attainment or income to explain variation in the incidence of unit nonresponse. We make two contributions to the existing literature. First, we examine the incidence of unit nonresponse in an internet panel, a relatively new, and hence understudied, approach to gathering longitudinal data. Second, we hypothesize that personality traits, which typically remain unobserved and unmeasured in many data sets, affect the likelihood of unit nonresponse. Using data from an internet panel that includes self-reported measures of personality in its baseline survey, we find that conscientiousness and openness to experience predict the incidence of unit nonresponse in subsequent survey waves, even after controlling for cognitive ability and demographic characteristics that are usually available and used by researchers to correct for panel attrition. We also test the potential to use paradata as proxies for personality traits. Although we show that these proxies predict panel attrition in the same way as self-reported measures of personality traits, it is unclear to what extent they capture particular personality traits versus other individual circumstances related to future survey completion. Our results suggest that obtaining explicit measures of personality traits or finding better proxies for them are crucial to more fully address the potential bias that may arise as a result of panel attrition

Prediksi Kenaikan atau Penurunan Indeks Pasar Keuangan Indonesia dengan Menggunakan Bayesian Network

Investasi saham pada pasar keuangan dilakukan untuk meningkatkan aset pada masa depan. Dalam melakukan investasi harus mempertimbangkan hasil yang akan didapatkan atau biasa disebut return. Setiap investor akan berusaha mendapatkan return semaksimal mungkin dari investasi yang dilakukannya. Oleh karena itu, perlu dilakukan prediksi perubahan kenaikan atau penurunan pada pasar saham. Beberapa metode untuk membuat prediksi adalah Bayesian Network dan Algoritma Naive Bayes. Pada Tugas Akhir ini, dilakukan pemodelan jaringan sektor-sektor pasar keuangan Indonesia dengan menggunakan Bayesian Network, lalu melakukan prediksi berdasarkan kenaikan atau penurunan harga penutupan dari tiap sektor. Metode yang digunakan adalah menggunakan Algoritma Naive Bayes Diskrit dan Kontinu. Setelah itu, menentukan metode yang terbaik untuk perhitungan prediksi dengan melihat tingkat akurasi dari setiap metode dengan confusion matrix. Sektor pasar keuangan yang digunakan yaitu nilai tukar USD/IDR, IHSG, dan Obligasi. Perhitungan dilakukan berdasarkan ketergantungan antara nilai tukar USD/IDR terhadap IHSG, dan nilai tukar USD/IDR terhadap Obligasi. Metode Naive Bayes Diskrit menunjukan hasil yang lebih akurat dengan akurasi sebesar 84% untuk IHSG dan 76% untuk Obligasi. Sedangkan perhitungan dengan metode Naive Bayes Kontinu memiliki akurasi sebesar 52% untuk IHSG dan 48% untuk Obligasi. Sektor nilai tukar USD/IDR lebih mempengaruhi IHSG, karena tingkat akurasi yang diperoleh IHSG lebih tinggi dibandingkan dengan Obligasi

Specification of Payment Requirements for Business Collaborations, INFOLAB

Service-oriented computing (SOC) is the computing paradigm that utilizes services as fundamental elements for developing business collaborations. In order to realize this vision payment is a critical issue that must be addressed. Current work in this area is scarce, and usually focused on low level requirements. In this report we present a layered specification of payment properties for business collaboration. The approach supports specification of high level payment criteria, the mechanisms to achieve those, and the measures needed to implement these mechanisms. Moreover, dependencies among criteria, mechanisms and measures are made explicit as such creating a traceable path from criteria to measures

Rule-based business collaboration development and management

Business collaboration is about cooperation between organisations by linking their business processes and exchanging messages. Collaborative business process development requires loose coupling between individual business processes so that they can interact freely across the internet; and that the collaboration can be established in a highly dynamic fashion and on-demand basis. Unfortunately, the current web service development and management solutions including the de facto standard Business Process Execution Language for Web Service (WS-BPEL) are too narrowly focused and not capable of addressing the requirements of business collaboration that demand agility and dynamics. To remedy this situation, we advocate an approach in which rules are used to develop and maintain the business collaboration. We first introduce a Business Collaboration Context Framework (BCCF), which provides enterprises with the context required for business collaboration.We then show how enterprises can capture this context via a modelling process. Following these preliminaries, we demonstrate how the modelling endeavour is controlled by rules, and how consistency can be assessed by these rules. Lastly, we demonstrate the feasibility of the approach in the form of a prototype called Icarus.12 page(s

On the specification of payment requirements for collaborative services

Payment arrangement is one of the vital issues in a B2B setting. For example, failing to accurately specify and communicate payment details such as the method of the payment, whether payment is refundable and negotiable, and what settlement model is used, can lead to serious disputes between the provider and requester of a service. However current development and solutions in service description, e.g., WSDL, do not cater for the specification and negotiation of payment related requirements for services. In this paper we present a comprehensive modeling approach for capturing and specifying payment requirements in the context of business collaboration. It will lay a foundation for service providers and requesters to explicitly define and adjust their business and technical requirements for payment in an adaptive and verifiable way. Furthermore, it provides support for terms of payment to be negotiated effectively to reach service provisioning agreements.8 page(s