Serving the IS Customer in Good Times and Bad: Pathways to Satisfaction and Value

Serving and satisfying customers are everlasting goals for organizations. This two-essay dissertation delves into two innovative ways in which a company and its information systems (IS) service providers can better serve internal and external customers. The first essay examines the concept of Data Monetization, whereby a company sells its customer data to upstream suppliers to ensure that the source company receives optimized inventory levels and unique consumer insights. In today’s era of big data, business analytics, and cloud computing, this case demonstrates that the elusive goal of data monetization has become achievable. In a second essay, we build on service marketing and social capital literature to understand factors that influence IS service recovery satisfaction following an IS service failure. This empirical study advances our theoretical understanding of internal customer satisfaction by theorizing that the success of IS service recovery depends on the way the IS Function (ISF) responds to an IS service failure and the ISF’s investment in building social capital with its internal customers. Essay 1 is a case study of a Fortune 500 drug store chain that has been successfully monetizing its data by selling it to its upstream suppliers. We present a four-stage model that illustrates the stages the retailer went through on its data monetization journey. We identify the characteristics of each stage that differ in the technical and analytical capabilities required, the type of trust built, the focus of the retailer’s information strategy, governance mechanisms, and the costs incurred and benefits achieved by various stakeholders. It was shown that a company could gain new revenue streams by selling its customer data while exploiting its suppliers’ technical and business analytical resources to ultimately serve the retailer’s customers. In Essay 2, we recognize that when IS service failures are encountered, IS service providers have to respond with an IS service recovery. Internal customers’ (employees) satisfaction with a recovery after a failure is important to restore an employee’s overall satisfaction with the ISF. We empirically examine the effect of the social capital shared between the ISF and employees as well as the dimensions of recovery procedures, interactions, and outcomes on IS service recovery satisfaction and overall satisfaction. Our results indicate that following a service failure, the recovery satisfaction has a direct effect on overall satisfaction with the ISF. We find that recovery procedures (effort and fairness) and the recovery outcomes (speed and level of recovery) influence recovery satisfaction. We do not find support that social capital dimensions affect recovery satisfaction; however social capital has a direct effect on overall satisfaction with the ISF. Moreover, we find that recovery interaction (apology and explanation) does not affect recovery satisfaction. These findings paint the picture whereby the ISF must continually build social capital to sustain overall satisfaction among employees but in the case of a IS service failure, employees are mainly concerned with being treated fairly and earnestly in getting their problem fixed fast and reliably, and they do not consider social capital or recovery interaction as factors that will make them more satisfied with the failure’s recovery

New Distance Measures for Arabic Handwritten Text Recognition

recent years, optical character recognition has attracted scientists and researchers. Latin, Chinese, Korean and Thai characters have been researched more thoroughly than Arabic characters. The research has concentrated firstly on printed and typeset characters until acceptable recognition accuracy has been achieved. Nowadays, most of the researches have gone towards handwritten character recognition. Arabic text is cursive as characters in a sub-word are connected to each other. This makes the recognition process more complex and a segmentation procedure is required to separate the connected characters from each other before they can be recognized. Features extracted have to be chosen carefully since it has a very important role in the segmentation and recognition process. The recognition accuracy mostly depends on the classifier applied and the segmentation procedure. In this research work, a framework for recognizing the Arabic handwriting is presented. Two approaches have been proposed. The first approach has been designed to recognize the word as a whole to fit applications such as sorting postal mails and bank checks where the number of words or digits that need to be recognized is limited. The words may include country and city names written on postal mails, or some reserved words or amounts used on bank checks. The second approach represents the general case where any type of documents or handwritten text can be recognized by this approach. In both approaches, a preprocessing stage including image enhancement and normalization. The most significant features are extracted by implementing the Principal Components Analysis. A new segmentation-based approach is designed and implemented for the second approach to segment the text into characters, while no or simple segmentation procedure is performed in the first approach. The recognition step is performed by applying the nearest neighbor algorithm. Four different distance measures are used with the nearest neighbor, the first norm, second norm (Euclidean), and two new norms proposed called ENorm, EEuclidean. The two new norms proposed (ENorm, EEuclidean) are derived from the first and second norm respectively. The recognition accuracy is enhanced by using the two new norms proposed. The approaches have been tested as well, and a number of experiments have been discussed more thoroughly. The first approach is experimented by four datasets, which are sub-words containing two characters, sub-words containing three characters, Latin letters and Hindi digits which are used with Arabic language nowadays. The recognition accuracy is the attribute used for measurement, and an 8-fold cross validation technique is used to test this attribute. The average recognition accuracy is 94.8% for the digits, 78% for the three-character sub-words, 77% for the two-character sub-words and 67% for Latin letters. The second approach has achieved recognition accuracy of 73% without detecting dots and 77% with dot detection

The Role of Social Support and Patient Empowerment Through Online Health Communities in Enhancing Patient–Physician Relationship

Purpose: The goal of this project is to investigate how online health communities can improve patient-physician relationships by providing social support and patient empowerment.   Theoretical framework: Nowadays, on online health forums, patients can connect with other patients and healthcare professionals and share knowledge and experiences. However, there is a dearth of research on how patient-physician relationships might be improved via online health communities.    Design/Methodology/Approach: In this analytical study, a sample of 61 individuals receiving treatment in Jordan's private hospitals were given a questionnaire via two of the most popular health communities' Facebook pages.   Findings: The findings showed that while patient empowerment had no impact on the patient-physician connection, computer-mediated social support had an impact on that relationship. These findings support the need to suggest Jordanian online health community models that might strengthen this kind of engagement.     Research, Practical and Social Implications: Online health community providers need to be aware of the tactics they should use in these communities to strengthen the patient-physician relationship and integrate these efforts into patient treatment. Additionally, these communities can help medical practitioners ensure that patients receive the appropriate information and type of support.   Originality/Value: As online health groups grew, so did the number of patients who relied on them for information and emotional support. Although the majority of studies focused on this type of support, little is known about how it affects the patient-physician interaction

Pengaruh Bahasa Jawa dalam pembauran kod golongan muda Melayu berketurunan Jawa.

Kajian ini dijalankan adalah untuk meninjau dan menilai sejauh mana pengaruh penggunaan bahasa Jawa menimbulkan fenomena pembauran kod dalam pertuturan dalam kalangan golongan muda. Kajian ini meninjau sejauh mana bahasa Jawa diamalkan oleh golongan muda yang berketurunan Jawa di kampung Sungai Leman, Sekinchan, Selangor. Penulis juga mengenal pasti tempat-tempat yang menjadi kebiasaan dan kekerapan bagi golongan muda menuturkan bahasa Jawa serta mengemukakan contoh-contoh percampuran bahasa Jawa dan bahasa Melayu dalam perbualan seharian. Penyelidikan ini telah dilakukan melalui temu bual dan soal selidik. Kaji selidik dijalankan ke atas 40 orang responden golongan muda yang berumur 6 hingga 25 tahun. Hasil kajian mendapati bahawa golongan muda pada peringkat rendah kurang menguasai penggunaan bahasa Jawa dan menyebabkan mereka mencampurkan bahasa Jawa dalam bahasa Melayu dalam komunikasi. Fenomena ini jika berlarutan dikhuatiri akan mengakibatkan kesalahan penggunaan bahasa, baik bahasa Melayu mahupun bahasa ibunda. Kajian ini penting bagi memberikan jaminan agar bahasa Melayu terus dimartabatkan seterusnya bahasa Jawa yang merupakan bahasa ibunda terus dipelihara dan tidak akan hilang penuturnya begitu sahaja. Kesimpulannya dapatlah dinyatakan bahawa penggunaan bahasa Jawa mempengaruhi fenomena pembauran kod dalam bahasa Melayu

Interfacial effects in fast reactors

"May 1979."Also written as a Ph. D. thesis by the first author and supervised by the second author, MIT Dept. of Nuclear Engineering, 1979Includes bibliographical references (pages 191-193)The problem of increased resonance capture rates near zone interfaces in fast reactor media has been examined both theoretically and experimentally. An interface traversing assembly was designed, constructed and employed to measure U-238 capture rates near the blanket-reflector interface in the MIT Blanket Test Facility. Prior MIT experiments on a thorium-uranium interface in a blanket assembly were also reanalyzed. Extremely localized fertile capture rate increases of on the order of 50% were measured immediately at the interfaces relative to extrapolation of asymptotic interior traverses, and relative to state-of-the-art (LIB-IV, SPHINX, ANISN/2DB) calculations which employ infinite-medium self-shileding throughout a given zone. A method was developed to compute a spatially varying background scattering cross section per absorber nucleus, a , which takes into account both homogeneous and heterogeneous effec~s on the interface flux transient. This permitted use of the standard self-shielding factor method (Bondarenko f-factors) to generate modified cross sections for thin layers near the interfaces. Calculations of the MIT experiments using this approach yielded good agreement with the measured data.U.S. Department of Energy contract EY-76-S-02-225

ASSESSMENT OF THE LEBANESE REAL ESTATE MARKET: A CONTENT ANALYSIS APPROACH

The purpose of this study is to assess the real estate market in Lebanon. The study was conducted by a group of MBA students at the Lebanese American University. A content analysis of the classified advertisements of the Lebanese Real Estate was conducted. Results identified four major elements that affect the Lebanese Real Estate market: Advertisements (R2=0.795559), Season of the advertisements (R2=0.741338), Location of the advertisement (R2= 0.594345), and Area of the advertisement (R2= 0.099588).The variable, advertisements, was most affected by the other variables. A recursive system test was conducted to show the relationship between advertisements, and the rest of the variables. (P43= 0.628947)real estate market, Lebanon, content analysis

A New Approach to Automatic Saliency Identification in Images Based on Irregularity of Regions

This research introduces an image retrieval system which is, in different ways, inspired by the human vision system. The main problems with existing machine vision systems and image understanding are studied and identified, in order to design a system that relies on human image understanding. The main improvement of the developed system is that it uses the human attention principles in the process of image contents identification. Human attention shall be represented by saliency extraction algorithms, which extract the salient regions or in other words, the regions of interest. This work presents a new approach for the saliency identification which relies on the irregularity of the region. Irregularity is clearly defined and measuring tools developed. These measures are derived from the formality and variation of the region with respect to the surrounding regions. Both local and global saliency have been studied and appropriate algorithms were developed based on the local and global irregularity defined in this work. The need for suitable automatic clustering techniques motivate us to study the available clustering techniques and to development of a technique that is suitable for salient points clustering. Based on the fact that humans usually look at the surrounding region of the gaze point, an agglomerative clustering technique is developed utilising the principles of blobs extraction and intersection. Automatic thresholding was needed in different stages of the system development. Therefore, a Fuzzy thresholding technique was developed. Evaluation methods of saliency region extraction have been studied and analysed; subsequently we have developed evaluation techniques based on the extracted regions (or points) and compared them with the ground truth data. The proposed algorithms were tested against standard datasets and compared with the existing state-of-the-art algorithms. Both quantitative and qualitative benchmarking are presented in this thesis and a detailed discussion for the results has been included. The benchmarking showed promising results in different algorithms. The developed algorithms have been utilised in designing an integrated saliency-based image retrieval system which uses the salient regions to give a description for the scene. The system auto-labels the objects in the image by identifying the salient objects and gives labels based on the knowledge database contents. In addition, the system identifies the unimportant part of the image (background) to give a full description for the scene

AN EXPERIMENTAL AND NUMERICAL PREDICTION OF MARINE PROPELLER NOISE UNDER CAVITATING AND NON-CAVITATING CONDITIONS

In this study, the hydrodynamics and noise prediction of a five blade marine propeller were analyzed through numerical and experimental methods under variety operational conditions. The hydrodynamics of the propeller was studied and the characteristic curves were presented in both numerical and experimental methods. Inception and development of sheet cavitation conditions are obtained in both numerical and experimental methods. The cavitation was started and developed by either increasing the propeller rotational speed in constant pressure or decreasing pressure, while the velocity was kept constant. Good agreements are observed between numerical and experimental results, qualitatively and quantitatively. The noise of the propeller was analyzed through Computational fluid dynamics (CFD) method, based on the formulation of Ffowcs Williams and Hawkings (FW-H). Similarly, the experimental results collected from hydrophones were compared with numerical simulations. Finally, the effects of reflection in cavitation tunnel were obtained by considering overall sound pressure levels in numerical and experimental results