The purpose of this dissertation is to propose a framework for sales and operations planning (S&OP), which is based on a modularized view of supply chains. The framework should support both process industries and discrete manufacturing industries in their quest for performance. S&OP has been highlighted in this framework due to its essential role in integrating different functions within a company and integrating a company with its supply chain partners (referred to as horizontal integration), and linking different planning levels in a company (referred to as vertical integration). As an integrator, S&ÖP influences companies’ performance. Originally, S&OP was developed as a generic process but still in line with the requirements of discrete manufacturing industries. The specific requirements of process industries have not been emphasized in this process to the same extent. In order to suggest a modularized S&OP framework for both process industries and  discrete manufacturing  industries, a systematic literature review is performed to understand the specific characteristics of S&OP in process industries. As a result, the importance of continuity/discontinuity of materials and its influence on the required production processes are highlighted. This indicates that the production process in process industries is actually a hybrid of continuous production and discrete production, whereas the discrete manufacturing industries often only deploy discrete production. Continuous production has specific characteristics that would be beneficial to include in the S&OP process; nonetheless, this is in contrast to the view in the literature that considers S&OP a generic process. Generic here means that S&OP is independent of the context in terms of, for example, the industry in which it is implemented. This issue is investigated in this dissertation by identifying the requirements, which can be considered in the S&OP of process industries as add-ons to the generic S&OP. In addition to this, two other concepts addressing the properties of the production process are identified as important in planning and control, including S&OP. One addresses the level of repetitivity of the production process in response to the market demand, and the other concerns the trigger of the production flow. The three concepts are related to three different types of decoupling points and are the basis for a typology developed herein that provides a modularized view of supply chains. The application of the typology to S&OP leads to a modularized S&OP framework applicable to both process industries and discrete manufacturing industries. The modularized view of supply chains has been long emphasized as an effective and efficient way to support companies’ performance and their competitive position. The typology and the S&OP framework are developed through conceptual research methods. To study how the modularized S&ÖP framework is related to companies’ performance measures, different performance measures (including sustainable performance measures) at the S&OP level are extracted from the literature. The performance measures are then classified according to the typology, and linked to strategic performance attributes. Aligning performance measures at S&OP levels and strategic performance attributes would help in enhancing companies’ performance. Sustainable performance measures are included in this classification to provide additional support for companies’ performance. Finally, this approach in classification of  performance measures is studied in four case companies, and the empirical performance measures are linked to the companies’ strategic performance attributes and competitive strategies. The results of this empirical study have, to some extent, verified the results from the classification of performance measures based on the literature. This dissertation contributes to the development of knowledge in S&OP. First, it identifies three key concepts in planning and control of manufacturing companies. Second, it investigates how S&OP should be tailored to the specific characteristics of companies and their supply chains. The modularized S&OP framework developed in this dissertation is based on the three identified concepts. This framework provides a foundation for fulfilling the supply chains needs by suggesting decision-making processes, planning techniques, and performance measures for different modules. More specifically, this work investigates how S&OP should be designed and implemented in process industries, which has not been extensively studied before. Third, this dissertation shows how S&OP level performance measures can be selected in line with the specific characteristics of supply chains. Finally, by integrating the sustainable performance measures in the S&OP process, this dissertation expands the scope of S&OP and its potential in supporting companies’ performance.

全權委託投資業務(俗稱代客操作),在證券市場中提供專業投資管理服務。我國證期會於民國81年，政策性地決定將開放此項業務。雖然整個規範體系已在民國87年建立，但它忽略掉經濟層面之考量，勢必造成全權委託投資契約無效率。 目前規範體系所允許之委託報酬的計算方法，稱之為「固定佣金制度」，由於此制度無法對業者提供經濟誘因，它會引發業者有嚴重之道德危險發生。因此，為解決誘因問題，應該使用「績效佣金制度」，不過在目前股市環境下，此一制度則引入過高之風險。因此，為解決兩種制度所帶來之問題，本文提出「改良式績效佣金制度」，在此制度下，委託報酬除基於傳統財務績效衡量值外，並基於非財務性績效衡量值，本文稱之為前瞻性績效衡量值（簡稱F-LPM）。 本文使用兩期之「主理人-代理人」模型，推導出最適委託報酬制度以及相關之比較靜態。在基本模式之下，本文進一步探討F-LPM之相關屬性及功能。所得結果與相關文獻一致，首先是，在最適委託報酬制度下，納入F-LPM可降低業者過度地重視短期，因而犧牲了委任人之報酬，這表示F-LPM具有增額資訊內涵。其次，無成本地提高F-LPM之精確度，可增加委任人之報酬。最後，改良式績效佣金制度優於固定佣金制度與績效佣金制度，因為它可降低風險，因而帶給委任人之報酬增加。 第壹章 緒論 第一節 / Discretion account business provides professional investment management service in the securities market. The Securities and Futures Commission decides in policy to approve the business in 1992. Althrough the regulation system of the discretion account business has been established, it will make the advisory contract inefficient with the negligence of economic consideration. The form of advisory fees permitted by the regulation system is 'constant fee system'. Under the system, advisory contract provides no incentive and serious moral harazd will occur. In order to solve the motivation problem, 'performance fee system' should be used. Under the circumstance of Taipei securities market, however, the performance fee system will bring in high risk. Hence, this paper suggests the 'improved performance fee system' to overcome the dilemma born by the performance fee system. In the improved system, advisory fees are based on the traditional performance measure and the fordward-looking performance measure (hereafter F-LPM). With a two-period principal-agent model, this paper develops the optimal reward system and related comparative static. Following the basic model, the paper examines the attributes and function of F-LPM. The findings are consistent with the related literature. First, the inclusion of a F-LPM in reward system can mitigate the potential for the advisor to focus excessively on the short-term at the expense of the investor. That is, F-LPM is incremental informative. Second, costless increases in precision of F-LPM will lead to increase in payoffs for the inveator. Finally, the improved performance fee system is superior to the constant fee system and the performance fee system in that it can reduce risk and results in higher payoffs to the investor.

The dairy industry is a complex system that involves many stakeholders and processes, from production to distribution. To measure and improve the performance of this system, a comprehensive and reliable Performance Measurement System (PMS) is needed. A PMS is a tool that helps to evaluate the efficiency and effectiveness of supply chain operations. One of the components of a PMS is the key performance indicators (KPIs), which reflect the performance of specific aspects of the supply chain. This thesis explores how KPIs can be used to enhance logistics performance in the dairy industry. The research is based on a single case study of a global company that operates in the dairy sector, which faces challenges such as high competition, customer demand variability, and food waste. The research uses a mix of literature review, interviews, and data analysis to identify and evaluate the relevant KPIs for logistics performance, as well as their interrelationships and impacts. The research applies the interpretive structural modeling (ISM) method to develop a hierarchical model of the KPIs and their causal relationships. The interpretive structural model of the indicators shows that the current indicators commonly used in the dairy industry today are not suitable for measuring performance, the indicators do not affect the current performance significantly but rather reflect the. This paper proposes a methodology for qualitatively evaluating performance measures, based on the integration of the ISM approach, the MICMAC analysis, and the seven criteria of a KPI. The ISM approach is a technique for identifying and analyzing the interrelationships among elements of a complex system. By applying this methodology, organizations and researchers can assess the suitability and importance of a set of KPIs. / Mejeriindustrin är ett komplext system som involverar många intressenter och processer, från produktion till distribution. För att mäta och förbättra systemets prestanda behövs ett heltäckande och tillförlitligt system för prestationsmätning (PMS). Ett PMS är ett verktyg som hjälper till att utvärdera effektiviteten i leveranskedjans verksamhet. En av komponenterna i ett PMS är nyckeltal (KPI:er), som är mått som återspeglar prestandan för specifika aspekter av leveranskedjan. Denna studie syftar till att undersöka hur KPI:er kan användas för att förbättra logistiken inom mejeriindustrin. Forskningen baseras på en fallstudie av ett globalt företag som är verksamt inom mejerisektorn, som står inför utmaningar som hög konkurrens, varierande kundefterfrågan och matsvinn. Forskningen använder en blandning av litteraturstudier, intervjuer och dataanalys för att identifiera och utvärdera relevanta KPI:er för logistikprestanda, samt deras inbördes relationer och påverkan. Forskningen tillämpar metoden ISM (Interpretive Structural Modeling) för att utveckla en hierarkisk modell av KPI:erna och deras orsakssamband. Den tolkande strukturella modellen av indikatorerna visar att de nuvarande indikatorerna som vanligtvis används i mejeriindustrin idag inte är lämpliga för att mäta prestanda, indikatorerna påverkar inte den nuvarande prestationen avsevärt utan återspeglar snarare resultaten. I denna rapport föreslås en metod för att utvärdera prestationsmått på ett kvalitativt sätt, baserat på integrationen av ISM-metoden, MICMAC-analysen och de sju kriterierna för en KPI. ISM-metoden är en teknik för att identifiera och analysera de inbördes relationerna mellan olika delar i ett komplext system. Genom att tillämpa denna metod kan organisationer och akademiker utvärdera lämpligheten och vikten av en uppsättning eller en KPI.

The quadratic class of time-frequency distributions (TFDs) forms a set of tools which allow to effectively extract important information from a nonstationary signal. To determine which TFD best represents the given signal, it is a common practice to visually compare different TFDs' time-frequency plots, and select as best the TFD with the most appealing plot. This visual comparison is not only subjective, but also difficult and unreliable especially when signal components are closely-spaced in the time-frequency plane. To objectively compare TFDs, a quantitative performance measure should be used. Several measures of concentration/complexity have been proposed in the literature. However, those measures by being derived with certain theoretical assumptions about TFDs are generally not suitable for the TFD selection problem encountered in practical applications. The non-existence of practically-valuable measures for TFDs' resolution comparison, and hence the non-existence of methodologies for the signal optimal TFD selection, has significantly limited the use of time-frequency tools in practice. In this thesis, by extending and complementing the concept of spectral resolution to the case of nonstationary signals, and by redefining the set of TFDs' properties desirable for practical applications, we define an objective measure to quantify the quality of TFDs. This local measure of TFDs' resolution performance combines all important signal time-varying parameters, along with TFDs' characteristics that influence their resolution. Methodologies for automatically selecting a TFD which best suits a given signal, including real-life signals, are also developed. The optimisation of the resolution performances of TFDs, by modifying their kernel filter parameters to enhance the TFDs' resolution capabilities, is an important prerequisite in satisfying any additional application-specific requirements by the TFDs. The resolution performance measure and the accompanying TFDs' comparison criteria allow to improve procedures for designing high-resolution quadratic TFDs for practical time-frequency analysis. The separable kernel TFDs, designed in this way, are shown to best resolve closely-spaced components for various classes of synthetic and real-life signals that we have analysed.