和顧客保持長期關係，對於企業經營是有利的，然而，由於資訊科技的進步與物流效率的提升，顧客越來越來越聰明，要尋找並取得替代產品與服務也越來越容易。在這樣的環境前提下，如何使顧客願意與企業維持長期關係而不轉向競爭者，是企業的一大挑戰。在文獻探討中本文發現，其關鍵是在於要能夠持續與顧客互動並了解顧客，並且將這些了解應用於產品設計、流程設計與組織設計。對於顧客的了解，本文定義其為顧客知識，就成為了顧客關係的基石。不過，由於與顧客的接觸點越多，了解顧客的管道就越多，其整合上有一定的難度，而資訊科技與傳統行銷方法都能夠產生對於顧客的了解，再加上產生並應用對於顧客的了解，以塑造顧客在消費與使用產品與服務時能得到高度的滿意，已經企業所有部門的責任，這樣跨部門的作業也不是一件簡單的事，這些議題都是企業在顧客知識管理上所需面對的。 在過往的文獻中所談的顧客知識管理，很多都混淆顧客資訊與知識，較無探討企業如何加工與顧客互動所得到的資訊，因此無法清楚了解企業在顧客知識管理上所作的貢獻為何。本文就以流程觀點，並以目前市場需求飽和且競爭激烈的人壽保險產業中的一家企業：保誠人壽為例，探討企業內的顧客知識流程，並且探討主要的影響因素，以了解企業在顧客知識管理上所作的努力。 而在本文個案的探訪後，本文還嘗試以服務業作業系統的角度，提出一種顧客知識的新分類：前台作業所需的顧客知識、後台作業所需的顧客知識，並且根據個案中保誠人壽的實際做法，修正文獻探討所提出的顧客知識管理架構，並且提出三種顧客知識管理的類型以及提出其管理重點，以作為實務界與後人研究的參考。 / It is beneficial for an enterprise to keep long-term relationship with its customers. However, owing to advances of information technology and the improvement of logistics efficiency, it is not difficult to search and acquire better products and services to substitute for what they are using now. Under these circumstances, it is a challenge for enterprises to retain their customers. How to do this? The answer in literatures is: to gain more customer insights (defined as customer knowledge in this study) through interactions with customers and apply them in product design, process design and organizational structure design. Therefore customer knowledge is the basics of long-term relationships with customers. But still, there are issues. First, an enterprise may have many contact points with its customers. Then, there are traditional ways versus information technology ways to generate customer knowledge. Finally, an enterprise has to think how to address appropriate customer knowledge to right departments and use them to enhance the total experience when interacting with customers. These are all issues an enterprise has to face with when trying to do “Customer Knowledge Management” (CKM). Most of past studies on CKM did not tell the difference between information and knowledge, thus can not clearly define what contributions an enterprise makes when implementing CKM. This study attempts to investigate practices of CKM in an enterprise in life insurance industry, in which the demand is saturated and the competition is fierce, from a process perspective to manifest how customer knowledge is generated and applied, and what main factors are to affect CKM in an enterprise. After investigation of the case, this study proposes a new framework, from the operation system in service industry, to classify customer knowledge into two categories: customer knowledge needed for front-office operations, and customer knowledge needed for back-office operations. In addition, according to practices in this case, this study will revise the CKM process framework proposed right after the literature review, and will raise keys to successful CKM in CKM processes, for the reference for following studies.

The main focus of thesis are two information systems in the company and their overall analysis. These key systems are Orsoft information system and Oracle system. An important objective is the economic information systems to assess, describe and compare their use in accounting, the advantages and disadvantages, to propose any improvement of the economic information systems. The prime objective is an assessment of these two information systems and their proposals for possible improvements. The company Fezko Thierry first used 13 years of information system Orsoft. Then it was decided to implement Oracle system. One of these information systems will be described more in depth, the different accounting modules, the use of, any improvement of this system and the work of this information system. The operational objective of work is the development of economic systems, accounting modules and a description of the implementation of the Oracle accounting system to the company. After experience with both systems, it was found that the system is reliable Orsoft. Workers are also of the opinion that it is better to work with reliable data in the system Orsoft than working with many and many dates in Oracle.

In the present hypercompetitive market environment of car producers established especially at the developed west european markets is very difficult to gain new customers and increase the market share. The car producing companies have to build and increase customer loyalty to ensure the sustainable growth of market share in the future. One possibility how to improve customer's loyality to brand is to provide the highest standard at both sales and service department and carefully monitor the customer satisfaction. From the satisfaction and performance indicators of the car producing company is possible to construct a mathematical model producing the market share in a given country as an output. Key indikators of customer satisfaction, sales and service and also the macroeconomical data has been used as the inputs for the model. As a target market for my analysis has been chosen Germany. This thesis presents a set of recommendations and proposals, whose implementation should ensure the improvement of the market share of the given brand on german market. The recommendation does not include only the tips for improvement of the key indicators but it also gives the overview of how to make the marketing strategy more efficient using Customer relationship management.

Abstracts in English, Zulu and Southern Sotho / The advent of Basel II Capital Accord has revolutionised credit risk measurement (CRM) to the extent that the once “perceived riskier bank assets” are now accommodated for lending. The Small and Medium Enterprise (SME) sector has been traditionally perceived as a riskier and unprofitable asset for lending activity by Commercial Banks, in particular. But empirical studies on the implementation of the Basel II internal-ratings-based (IRB) framework have demonstrated that SME credit risk is measurable. Banks are still finding it difficult to forecast SME loan default and to provide credit to the sector that meet Basel’s capital requirements. The thesis proposes to construct an empirical credit risk measurement (CRM) model, specifically for SMEs, to ameliorate the adverse effects of SME credit inaccessibility due to high information asymmetry between financial institutions (FI) and SMEs in Zimbabwe. A well-performing and accurate CRM helps FIs to control their risk exposure through selective granting of credit based on a thorough statistical analysis of historical customer data. This thesis develops a CRM model, built on a statistically random sample, known-good-bad (KGB) sample, which is a better representation of the through-the-door (TTD) population of SME loan applicants. The KGB sample incorporates both accepted and rejected applications, through reject inference (RI). A model-based bound and collapse (BC) reject inference methodology was empirically used to correct selectivity bias inherent in CRM domain. The results have shown great improvement in the classification power and aggregate supply of credit supply to the SME portfolio of the case-studied bank, as evidenced by substantial decrease of bad rates across models developed; from the preliminary model to final model designed for the case-studied bank. The final model was validated using both bad rate, confusion matrix metrics and Area under Receiver Operating Characteristic (AUROC) curve to assess the classification power of the model within-sample and out-of-sample. The AUROC for the final model (weak model) was found to be 0.9782 whilst bad rate was found to be 14.69%. There was 28.76% improvement in the bad rate in the final model in comparison with the current CRM model being used by the case-studied bank. / Isivumelwano seBasel II Capital Accord sesishintshe indlela yokulinganisa ubungozi bokunikezana ngesikweletu credit risk measurement (CRM) kwaze kwafika ezingeni lapho izimpahla ezazithathwa njengamagugu anobungozi “riskier bank assets” sezimukelwa njengesibambiso sokuboleka imali. Umkhakha wezamaBhizinisi Amancane naSafufusayo, phecelezi, Small and Medium Enterprise (SME) kudala uqondakala njengomkhakha onobungozi obukhulu futhi njengomkhakha ongangenisi inzuzo, ikakhulu njengesibambiso sokubolekwa imali ngamabhange ahwebayo. Kodwa izifundo zocwaningo ezimayelana nokusetshenziswa nokusetshenziswa kwesakhiwo iBasel II internal-ratings-based (IRB) sezikhombisile ukuthi ubungozi bokunikeza isikweletu kumabhizinisi amancane nasafufusayo (SME) sebuyalinganiseka. Yize kunjalo, amabhange asathola ukuthi kusenzima ukubona ngaphambili inkinga yokungabhadeleki kahle kwezikweletu kanye nokunikeza isikweletu imikhakha enemigomo edingekayo yezimali kaBasel. Lolu cwaningo beluphakamisa ukwakha uhlelo imodeli ephathekayo yokulinganisa izinga lobungozi bokubolekisa ngemali (CRM) kwihlelo lokuxhasa ngezimali ama-SME, okuyihlelo elilawulwa yiziko lezimali ezweni laseZimbabwe. Imodeli ye-CRM esebenza kahle futhi eshaya khona inceda amaziko ezimali ukugwema ubungozi bokunikezana ngezikweletu ngokusebenzisa uhlelo lokunikeza isikweletu ababoleki abakhethekile, lokhu kususelwa ohlelweni oluhlaziya amanani edatha engumlando wekhasimende. Imodeli ye-CRM ephakanyisiwe yaqala yakhiwa ngohlelo lwamanani, phecelezi istatistically random sample, okuluphawu olungcono olumele uhlelo lwe through-the-door (TTD) population lokukhetha abafakizicelo zokubolekwa imali bama SME, kanti lokhu kuxuba zona zombili izicelo eziphumelele kanye nezingaphumelelanga. Indlela yokukhetha abafakizicelo, phecelezi model-based bound-and-collapse (BC) reject-inference methodology isetshenzisiwe ukulungisa indlela yokukhetha ngokukhetha ngendlela yokucwasa kwisizinda seCRM. Imiphumela iye yakhombisa intuthuko enkulu mayelana namandla okwehlukanisa kanye nokunikezwa kwezikweletu kuma SME okungamamabhange enziwe ucwaningo lotho., njengoba lokhu kufakazelwa ukuncipha okukhulu kwe-bad rate kuwo wonke amamodeli athuthukisiwe. Imodeli yokuqala kanye neyokugcina zazidizayinelwe ibhange. Imodeli yokugcina yaqinisekiswa ngokusebenzisa zombili indlela isikweletu esingagculisi kanye negrafu ye-Area under Receiver Operating Characteristic (AUROC) ukulinganisa ukwehlukaniswa kwamandla emodeli engaphakathi kwesampuli nangaphandle kwesampuli. Uhlelo lwe-AUROC lwemodeli yokugcina (weak model) lwatholakala ukuthi luyi 0.9782, kanti ibad rate yatholakala ukuthi yenza i-14.69%. Kwaba khona ukuthuthuka nge-28.76% kwi-bad rate kwimodeli yokugcina uma iqhathaniswa nemodeli yamanje iCRM model ukuba isetshenziswe yibhange elithile. / Basel II Capital Accord e fetotse tekanyo ya kotsi ya mokitlane (credit risk measurement (CRM)) hoo “thepa e kotsi ya dibanka” ka moo e neng e bonwa ka teng, e seng e fuwa sebaka dikadimong. Lekala la Dikgwebo tse Nyane le tse Mahareng (SME) le bonwa ka tlwaelo jwalo ka lekala le kotsi e hodimo le senang ditswala bakeng sa ditshebetso tsa dikadimo haholo ke dibanka tsa kgwebo. Empa dipatlisiso tse thehilweng hodima se bonweng kapa se etsahetseng tsa tshebetso ya moralo wa Basel II internal-ratings-based (IRB) di supile hore kotsi ya mokitlane ya SME e kgona ho lekanngwa. Leha ho le jwalo, dibanka di ntse di thatafallwa ke ho bonelapele palo ya ditlholeho tsa ho lefa tsa diSME le ho fana ka mokitla lekaleng leo le kgotsofatsang ditlhoko tsa Basel tsa ditjhelete. Phuputso ena e ne sisinya ho etsa tekanyo ya se bonwang ho mmotlolo wa kotsi ya mokitlane (CRM) tshebetsong ya phano ya tjhelete ya diSME e etswang ke setsi sa ditjhelete (FI) ho la Zimbabwe. Mmotlolo o sebetsang hantle hape o fanang ka dipalo tse nepahetseng o dusa diFI hore di laole pepeso ya tsona ho kotsi ka phano e kgethang ya mokitlane, e thehilweng hodima manollo ya dipalopalo ya dintlha tsa histori ya bareki. Mmotlolo o sisingwang wa CRM o hlahisitswe ho tswa ho sampole e sa hlophiswang, e leng pontsho e betere ya setjhaba se ikenelang le monyako (TTD) ya batho bao e kang bakadimi ba tjhelete ho diSME, hobane e kenyelletsa bakopi ba amohetsweng le ba hannweng. Mokgwatshebetso wa bound-and-collapse (BC) reject-inference o kentswe tshebetsong ho nepahatsa tshekamelo ya kgetho e leng teng ho lekala la CRM. Diphetho tsena di bontshitse ntlafalo e kgolo ho matla a tlhophiso le palohare ya phano ya mokitlane ho diSME tsa banka eo ho ithutilweng ka yona, jwalo ka ha ho pakilwe ke ho phokotseho ya direite tse mpe ho pharalla le dimmotlolo tse hlahisitsweng. Mmotlolo wa ho qala le wa ho qetela e ile ya ralwa bakeng sa banka. Mmotlolo wa ho qetela o ile wa netefatswa ka tshebediso ya bobedi reite e mpe le mothinya wa Area under Receiver Operating Characteristic (AUROC) ho lekanya matla a kenyo mekgahlelong a mmotlolo kahare ho sampole le kantle ho yona. AUROC bakeng sa mmotlo wa ho qetela (mmotlolo o fokotseng) e fumanwe e le 0.9782, ha reite e mpe e fumanwe e le 14.69%. Ho bile le ntlafalo ya 28.76% ho reite e mpe bakeng sa mmotlolo wa ho qetela ha ho bapiswa le mmotlolo wa CRM ha o sebediswa bankeng yona eo. / Graduate School of Business Leadership / D.B.L.

<p>Course-based Undergraduate Research Experiences (CUREs) have been described in a range of educational contexts. Although various learning objectives, termed anticipated learning outcomes (ALOs) in this project, have been proposed, processes for identifying them may not be rigorous or well-documented, which can lead to inappropriate assessment and speculation about what students actually learn from CUREs. Additionally, evaluation of CUREs has primarily relied on student and instructor perception data rather than more reliable measures of learning.This dissertation investigated a novel biochemistry laboratory curriculum for a Course-based Undergraduate Research Experience (CURE) known as the Biochemistry Authentic Scientific Inquiry Lab (BASIL). Students participating in this CURE use a combination of computational and biochemical wet-lab techniques to elucidate the function of proteins of known structure but unknown function. The goal of the project was to evaluate the efficacy of the BASIL CURE curriculum for developing students’ research abilities across implementations. Towards achieving this goal, we addressed the following four research questions (RQs): <b>RQ1</b>) How can ALOs be rigorously identified for the BASIL CURE; <b>RQ2</b>) How can the identified ALOs be used to develop a matrix that characterizes the BASIL CURE; <b>RQ3</b>) What are students’ perceptions of their knowledge, confidence and competence regarding their abilities to perform the top-rated ALOs for this CURE; <b>RQ4</b>) What are appropriate assessments for student achievement of the identified ALOs and what is the nature of student learning, and related difficulties, developed by students during the BASIL CURE? To address these RQs, this project focused on the development and use of qualitative and quantitative methods guided by constructivism and situated cognition theoretical frameworks. Data was collected using a range of instruments including, content analysis, Qualtrics surveys, open-ended questions and interviews, in order to identify ALOs and to determine student learning for the BASIL CURE. Analysis of the qualitative data was through inductive coding guided by the concept-reasoning-mode (CRM) model and the assessment triangle, while analysis of quantitative data was done by using standard statistical techniques (e.g. conducting a parried t-test and effect size). The results led to the development of a novel method for identifying ALOs, namely a process for identifying course-based undergraduate research abilities (PICURA; RQ1; Irby, Pelaez, & Anderson 2018b). Application of PICURA to the BASIL CURE resulted in the identification and rating by instructors of a wide range of ALOs, termed course-based undergraduate research abilities (CURAs), which were formulated into a matrix (RQs 2; Irby, Pelaez, & Anderson, 2018a,). The matrix was, in turn, used to characterize the BASIL CURE and to inform the design of student assessments aimed at evaluating student development of the identified CURAs (RQs 4; Irby, Pelaez, & Anderson, 2018a). Preliminary findings from implementation of the open-ended assessments in a small case study of students, revealed a range of student competencies for selected top-rated CURAs as well as evidence for student difficulties (RQ4). In this way we were able to confirm that students are developing some of the ALOs as actual learning outcomes which we term VLOs or verified learning outcomes. In addition, a participant perception indicator (PPI) survey was used to gauge students’ perceptions of their gains in knowledge, experience, and confidence during the BASIL CURE and, therefore, to inform which CURAs should be specifically targeted for assessment in specific BASIL implementations (RQ3;). These results indicate that, across implementations of the CURE, students perceived significant gains with large effect sizes in their knowledge, experience, and confidence for items on the PPI survey (RQ3;). In our view, the results of this dissertation will make important contributions to the CURE literature, as well as to the biochemistry education and assessment literature in general. More specifically, it will significantly improve understanding of the nature of student learning from CUREs and how to identify ALOs and design assessments that reveal what students actually learn from such CUREs - an area where there has been a dearth of available knowledge in the past. The outcomes of this dissertation could also help instructors and administrators identify and align assessments with the actual features of a CURE (or courses in general), use the identified CURAs to ensure the material fits departmental or university needs, and evaluate the benefits of students participating in these innovative curricula. Future research will focus on expanding the development and validation of assessments so that practitioners can better evaluate the efficacy of their CUREs for developing the research competencies of their undergraduate students and continue to render improvements to their curricula.</p>