O presente estudo apresentou os objetivos de: desenvolver lista de indicadores para compor modelo de avaliação de desempenho para as CEs e após verificar sobre o uso e finalidade dos indicadores CEs, na sequência foi verificado sobre a existência de correlação (associação) dos indicadores com as finalidades de tomada de decisão estratégica, monitoramento e controle, educação e aprendizagem, legitimidade e comunicação externa, e por fim foi verificado sobre as finalidades mais relevantes no uso dos indicadores nas CEs. O desenvolvimento metodológico do estudo ocorreu em três etapas, sendo que na primeira e segunda etapa a pesquisa se caracterizou como do tipo exploratória, com dados coletados por meio das técnicas de pesquisa de grupo focal e Delphi e a terceira etapa da pesquisa foi do tipo descritiva e correlacional, com dados coletados por meio de pesquisa Survey. A primeira etapa do estudo iniciou a partir da relação teórica de trinta e quatro indicadores, que por meio da pesquisa de grupo focal junto a cooperativa Creluz foi possível acrescentar outros trinta e três indicadores de uso das CEs. Estes indicadores foram distribuídos nas seguintes dimensões: econômico-financeira, eficiência operacional, pessoas e inovação, qualidade técnica e comercial, satisfação do consumidor, relacionamento com associados e benefícios sociais e ambientais. Na segunda etapa do estudo, os 67 (sessenta e sete) indicadores foram submetidos a apreciação de quinze especialistas em eletrificação por meio da técnica de pesquisa Delphi, tendo em vista selecionar os indicadores mais importantes (privilegiados) para compor um modelo de avaliação de desempenho para as CEs - MADCE. Os especialistas indicaram quarenta e um indicadores para compor o modelo de avaliação de desempenho. Na sequência na terceira etapa do estudo os quarenta e um indicadores do modelo de avaliação, foram submetidos por meio de um instrumento de coleta de dados junto as CEs, tendo em vista: i) verificar sobre o uso e as finalidades de uso dos indicadores pelas diretorias das CEs, ii) verificar sobre o grau de associação/correlação do uso dos indicadores com as finalidades de tomada de decisão estratégica, monitoramento e controle, legitimidade, educação e aprendizagem e comunicação externa, e iii) verificar sobre as finalidades mais relevantes no uso dos indicadores. Os resultados demonstram que os indicadores que compõe o modelo de avaliação são quase sempre e sempre utilizados pelas CEs, com níveis de uso variando de 0,49 a 0,87 de uma escala de zero a um. Os indicadores mais utilizados pelas CEs fazem parte das dimensões que retratam sobre a eficiência operacional, o relacionamento com associados e econômico-financeiros. Quanto às finalidades das informações dos indicadores pelas diretorias, os resultados demonstram que os indicadores possuem os seguintes propósitos: i) para o monitoramento e controle (0,70), ii) para a tomada de decisão estratégica (0,67), iii) para a comunicação externa (0,66), iv) para a legitimidade (0,63) e v) para a educação e aprendizagem (0,62) de uma escala de zero a um. Após verificou-se sobre os graus de correlação (associação) dos indicadores com as finalidades descritas. Os resultados demonstram correlações fortes e positiva dos indicadores (variáveis) com a tomada de decisão estratégica e monitoramento e controle e correlação moderada e positiva com a educação e aprendizagem, legitimidade e comunicação externa. Por fim, foi possível verificar sobre as finalidades mais relevantes em função da frequência do número de correlações fortes. Os resultados demonstram que as finalidades mais relevantes no uso dos indicadores são as seguintes, pela ordem: tomada de decisão estratégica, monitoramento e controle, legitimidade e educação, aprendizagem e comunicação externa. / The present study has the following objectives: develop list of indicators to compose model performance evaluation for ECs and after checking on the use and purpose of the indicators ECs following was found on the correlation (association) with the indicators purposes of strategic decision making, monitoring and control, education and learning, legitimacy and external communication, and ultimately was found on the most important purposes in the use of indicators in ECs. The methodological development of the study occurred in three stages, with the first and second stage of the study was regarded as exploratory type, with data collected by the techniques of focus group research and Delphi and the third stage of the research was descriptive and correlational, with data collected through Survey Research. The first phase of the study started from the theoretical relationship of thirty-four indicators that through focus group research with the cooperative Creluz could add another thirty-three indicators of use of ECs. These indicators were distributed in the following dimensions: economic and financial, operational efficiency, people and innovation, technical and commercial quality, consumer satisfaction, and relationship with associated social and environmental benefits. In the second stage of the study, 67 (sixty seven) indicators underwent assessment of fifteen experts electrification through the Delphi survey technique, in order to select the most important indicators (privileged) to compose a model of performance evaluation for ECs - MADCE. Experts indicated forty-one indicators to compose the model performance evaluation. Following the third stage of the study the forty-one indicators of the evaluation model, submitted by an instrument to collect data from the ECs, in order to: i) check on the use and purpose of use of indicators by boards of ECs, ii) check on the degree of association / correlation of the use of indicators for the purposes of strategic decision making, monitoring and control, legitimacy, education and learning and external communication, and iii) check on the most important purposes in use of indicators. The results demonstrate that the indicators that make up the evaluation model are almost always used by CEs and always with use levels ranging from 0.49 to 0.87 on a scale of zero to one. The indicators used by more ECs are part of the dimensions that portray on operational efficiency, relationships with associates and economic-financial. As for information purposes by the boards of the indicators, the results show that the indicators have the following purposes: i) to monitor and control (0.70), ii) for strategic decision making (0.67), iii) for external communication (0.66), iv) to the legitimacy (0.63) ev) for education and learning (0.62) on a scale from zero to one. After it was found on the degrees of correlation (association) of the indicators for the purposes described. The results show strong correlations and positive indicators (variables) with strategic decision making and monitoring and control and moderate and positive correlation with education and learning, legitimacy and external communication. Finally, it was possible to check on the most relevant purposes depending on the frequency of the number of strong correlations. The results show that the most important purpose in the use of indicators are as follows, in order: strategic decision making, monitoring and control, legitimacy and education, learning and external communication.

Manufacturing enterprises are a key driver of economic growth (Eurostat, 2016). Implementing continuous improvement (CI) is commonly used to increase competitiveness (Hyland et al., 2007), but despite the well-known theory of CI, many manufacturing companies fail in implementing it (Bhasin, 2012; Nordin et al., 2012; Tiwari et al., 2007). An identified critical success factor in CI implementation is the evaluation of performance, including the performance evaluation system itself, the linkage between targets at different company levels, and continual evaluation of performance (Bakås et al., 2011; Scherrer-Rathje et al., 2009; Ukko et al., 2009). Another critical success factor in CI implementation is the communication of performance measures (Bakås et al., 2011; Ukko et al., 2009). This research explores the communication of performance measures. The aim is to support CI by improving the communication of performance measures, and to this end, this thesis concentrates on identifying the main challenges in the communication of performance measures supporting CI. The research scope is manufacturing companies in general, and manufacturing SMEs in particular. The relevant literature concerning the communication of performance measures in manufacturing companies is identified and summarized. Also, current practice is explored, focusing on how performance measures are communicated in manufacturing companies, and whether and how the communication supports CI. This has been done to identify divergences between current practice and theory. Finally, theory and empirical findings are synthesized to identify some of the main challenges to be addressed in order to succeed in CI. The main task is to support CI efforts in manufacturing SMEs, eliminating the identified divergences in the communication of performance measures by adapting these measures to these manufacturing SMEs. These challenges can be summarized as follows:  - using both financial performance measures as well as objective and subjective, non-financial performance measures  - aligning performance measures with strategy and targets  - integrating all performance measure communication, as related to both daily performance and CI, in the same communication loop.  - forming two-way communication channels between managers and operators  - aligning oral and written communication channels  - exploring how information systems can facilitate the communication of performance measures  - using and optimizing the visual communication of performance measures / <p>I avhandlingen ingår även följande publikationer:</p><p>Larsson, C., Strand, M., Persson, A., &amp; Syberfeldt, A., 2017. Communicating continuous improvement in manufacturing SMEs: Divergences between current practice and theory. Published at PMAA 2017 Conference “New Approaches, Changed Understandings”. Dunedin, New Zeeland, 2017.</p><p>Larsson, C., 2017. How to visualize performance measures in a manufacturing SME. Accepted for publication in Measuring Business Excellence.</p><p>Larsson, C., &amp; Syberfeldt, A., 2016. Communicating performance measures - current practice in manufacturing SMEs. Submitted to International Journal of Productivity and Performance Management.</p>

Abstract This dissertation aims to provide an extensive picture of management accounting systems and explore the relationships between management accounting systems, strategy, information technology, manufacturing technology and organizational performance. The dissertation consists of four essays. The first essay focuses on the adoption and benefits of management accounting practices, whereas the second essay studies the relations between customer-focused strategy, performance measurement techniques, information technology and their link to customer performance. The third essay studies the relations between manufacturing technology, information technology, strategy and organizational performance. The fourth essay, in turn, studies the management accounting systems and their relations to strategy and information technology. The first three essays employ the survey method while the last essay employs the case method. The framework used in this dissertation is the contingency theory. The results indicate that financial performance measures will be important in the future and that greater emphasis will be placed on contemporary management accounting practices such as customer satisfaction surveys and employee attitudes. Also, the relative benefits from the previous three years and the future emphasis in the next three years are generally greater when the size of the firm increases. The results show that there is a significant association between customer performance and the three-way interaction involving customer-focused strategy, contemporary performance measures and advanced information technology. The proposed three-way interaction between financial performance measures, customer-focused strategy and advanced information technology is not supported at conventional levels of statistical significance indicating that financial measures are not important in the model. The results also indicate that contemporary performance measures do not help highly customer-focused firms to achieve customer performance. For firms with a low customer-focus, emphasizing contemporary performance measures and advanced information technology assists in enhancing customer performance. The results also suggest that manufacturing technology and information technology together help firms to improve their organizational performance regardless of their emphasis on differentiation strategy.

Master of Science / Department of Agricultural Economics / Elizabeth Yeager / The main objective of this analysis was to examine the profitability and efficiency of Kansas farms in order to draw inferences among the profitability, efficiency, and growth of agricultural producers in Kansas. The time period analyzed was 2005 to 2015. Farms in the sample include a mix of 564 crop and/or livestock operations with 11 years of continuous data through the Kansas Farm Management Association data-bank. Efficiency scores were calculated to determine how close each farm was to the production possibilities frontier, or their cost efficiency. Profitability measures, (operating profit margin and return on assets), were obtained for each farm. The profitability dynamics in 2014 and 2015 for these farms changed compared to previous years. Crop farms generated less profits in 2014 and 2015 compared to previous years, and relative profits from average fluctuated more for sampled farms in 2014 and 2015. Farms were also categorized into risk classes. These classifications aim at distinguishing farms that are profitable or not, and their level of solvency, utilizing their net farm income from operations and their debt to asset ratio. Farms are migrating from the low risk classification, showing that Kansas farms are becoming less profitable, but are not transitioning to a higher risk solvency state. These farms will need to focus on utilizing their inputs more efficiently to keep their solvency levels in check. After analyzing persistence in profitability, the results suggest that farms with higher return on assets tend to be more solvent, but farms with higher operating profit margin tend to be less solvent. The analysis also suggests that there might have been persistence in profits in the years prior to 2015. The analysis of relative positioning of farms in terms of return on assets suggests that during 2007-2011 some farms were able to consistently differentiate themselves by generating either below or above normal profits. Some farms were able to become more profitable in 2012 and 2013, while others lagged behind supported by regression results that signaled divergence of profitability levels. The relative positioning analysis for operating profit margin indicates that farms had similar operating profit margins from 2010 through 2014, and divergence occurred in 2015 by farms that were able to differentiate themselves more through the average operating profit margin. Next the efficiencies of the farms were examined. Analysis of the efficiency scores suggests that the cost efficiencies of Kansas farms are not explained by risk classification significantly, but the crop-labor percentage ratio significantly explains the cost efficiency of the farms. The relationship between cost efficiency and profitability measures proved to be the strongest out of the three performance measures due to their correlation. The final step in the analysis was to examine farm characteristics of the top performing farms. Farms were ranked by profitability measurements and the efficiency measure. Variables of interest that were significantly different between the top 25 percent and the bottom 25 percent of farms include total farm assets, value of farm production, crop-labor percentage, crop acres, number of workers, and age of operators.

The need for a more authoritative approach to investment decision-making and cost control has been a requirement of office spending for many years now. The commercial offices find itself in an increasingly demanding position to allocate its budgets as wisely and prudently as possible. The significant percentage of total spending on buildings demands a more accurate and adaptable method of achieving quality of service within the constraints on the budgets. By adoption of life cycle costing techniques with risk management, practitioners have the ability to make accurate forecasts of likely future running costs. This thesis presents a novel framework (Artificial Neural Networks and probabilistic simulations) for modelling of operating and maintenance historical costs as well as economic performance measures of LCC. The methodology consisted of eight steps and presented a novel approach to modelling the LCC of operating and maintenance costs of two sustainable commercial office buildings. Finally, a set of performance measurement indicators were utilised to draw inference from these results. Therefore, the contribution that this research aimed to achieve was to develop a dynamic LCC framework for sustainable commercial office buildings, and by means of two existing buildings, demonstrate how assumption modelling can be utilised within a probabilistic environment. In this research, the key themes of risk assessment, probabilistic assumption modelling and stochastic assessment of LCC has been addressed. Significant improvements in existing LCC models have been achieved in this research in an attempt to make the LCC model more accurate and meaningful to estate managers and high-level capital investment decision makers A new approach to modelling historical costs and forecasting these costs in sustainable commercial office buildings is presented based upon a combination of ANN methods and stochastic modelling of the annual forecasted data. These models provide a far more accurate representation of long-term building costs as the inherent risk associated with the forecasts is easily quantifiable and the forecasts are based on a sounder approach to forecasting than what was previously used in the commercial sector. A novel framework for modelling the facilities management costs in two sustainable commercial office buildings is also presented. This is not only useful for modelling the LCC of existing commercial office buildings as presented here, but has wider implications for modelling LCC in competing option modelling in commercial office buildings. The processes of assumption modelling presented in this work can be modified easily to represent other types of commercial office buildings. Discussions with policy makers in the real estate industry revealed that concerns were held over how these building costs can be modelled given that available historical data represents wide spending and are not cost specific to commercial office buildings. Similarly, a pilot and main survey questionnaire was aimed at ascertaining current level of LCC application in sustainable construction; ranking drivers and barriers of sustainable commercial office buildings and determining the applications and limitations of LCC. The survey result showed that respondents strongly agreed that key performance indicators and economic performance measures need to be incorporated into LCC and that it is important to consider the initial, operating and maintenance costs of building when conducting LCC analysis, respondents disagreed that the current LCC techniques are suitable for calculating the whole costs of buildings but agreed that there is a low accuracy of historical cost data.

Continuously monitoring and automatically identifying existing problems in traffic signal operation is a challenging and time-consuming task. Although data are becoming available due to the adoption of emerging detection technologies, efforts on utilizing the data to diagnose signal control are limited. The current practices of retiming signals are still periodic and based on several days of aggregated turning movement counts. This dissertation developed a framework of automatic signal operation diagnosis with the aim to support decision-making processes by assessing the signal control and identifying the signal retiming needs. The developed framework used a combination of relatively low-cost data from Wi-Fi sensors and historical signal timing records from existing signal controllers. The development involved applying multiple data matching and filtering algorithms to allow the estimation of travel times of vehicular traversals. The Travel Time Index (TTI) was then used as a measure to assess the traffic conditions of various movements. Historical signal timing records were also analyzed, and an additional signal-timing measure, referred to as the Max-out Ratio (MR), was proposed to evaluate the frequency in which the green time demand of a phase exceeded its preset value. Thresholds for the TTI and MR variables were used as a basis for the diagnosis. This diagnosis first identified the needs for assigning additional green times for individual signal phases. Further assessments were then made to determine whether or not the cycle length for the entire intersection or capacity was sufficient. The developed framework was implemented in a real-world signalized intersection and proved to be capable of identifying retiming needs, as well as providing support for the retiming process. Compared to field observations, the diagnosis results were able to reflect the signal operations of most of the movements during various time periods. Moreover, the flexibility of the developed framework allows users to select different thresholds for various movements and times of day, and thus customize the analysis to agency needs.

Density-based clustering is one of the well-known algorithms focusing on grouping samples according to their densities. In the existing density-based clustering algorithms, samples are clustered according to the total number of points within the radius of the defined dense region. This method of determining density, however, provides little knowledge about the similarities among points. Additionally, they are not flexible enough to deal with dynamic data that changes over time. The current study addresses these challenges by proposing a new approach that incorporates new measures to evaluate the attributes similarities while clustering incoming samples rather than considering only the total number of points within a radius. The new approach is developed based on the notion of Gravity where incoming samples are clustered according to the force of their neighbouring samples. The Mass (density) of a cluster is measured using various approaches including the number of neighbouring samples and Silhouette measure. Then, the neighbouring sample with the highest force is the one that pulls in the new incoming sample to be part of that cluster. Taking into account the attribute similarities of points provides more information by accurately defining the dense regions around the incoming samples. Also, it determines the best neighbourhood to which the new sample belongs. In addition, the proposed algorithm introduces a new approach to utilize the memory efficiently. It forms clusters with different shapes over time when dealing with dynamic data. This approach, called Aging, enables the proposed algorithm to utilize the memory efficiently by removing points that are aged if they do not participate in clustering incoming samples, and consequently, changing the shapes of the clusters incrementally. Four experiments are conducted in this study to evaluate the performance of the proposed algorithm. The performance and effectiveness of the proposed algorithm are validated on a synthetic dataset (to visualize the changes of the clusters’ shapes over time), as well as real datasets. The experimental results confirm that the proposed algorithm is improved in terms of the performance measures including Dunn Index and SD Index. The experimental results also demonstrate that the proposed algorithm utilizes less memory, with the ability to form clusters with arbitrary shapes that are changeable over time.

La littérature en marketing souligne l’importance du personnel en contact avec la clientèle dans le secteur des services. Nous développons une recherche ancrée en contrôle de gestion qui intègre ce résultat en analysant le lien entre (1) le contrôle de la performance opérationnelle et (2) la performance organisationnelle dans l’hôtellerie. Nous considérons plus précisément les relations entre l’assignation des droits décisionnels, le système de mesure de la performance, et le système d’incitation dédiés au personnel en contact avec la clientèle ; et leur influence sur la performance de l’organisation. Ces relations sont étudiées à la lumière du critère stratégique d’orientation marché, traduit à partir d’une étude qualitative par le concept de proposition de valeur hôtelière. Afin de tester notre modèle fondé sur la théorie de l’agence et sur la base d’une étude menée auprès des hôteliers en PACA, nous utilisons une méthodologie quantitative, l’approche PLS. Les résultats conduisent, d’une part, à valider les liens de complémentarité entre les trois composantes du design organisationnel ; et d’autre part, à rejeter les hypothèses liées à l’existence de relations entre (1) le design organisationnel et la performance organisationnelle, et (2) la proposition de valeur et le design organisationnel. D’un point de vue global, ces résultats sont cohérents avec littérature, et montrent la nécessité de considérer l’assignation des droits de décision lors de l’étude des systèmes de contrôle de gestion. Ils offrent un éclairage sur le secteur des services en montrant l’importance de la mesure non financière dans les pratiques d’incitation aux niveaux inférieurs de la hiérarchie. / The marketing literature indicates that employees in contact with the customers in the service sector are prominent. This research in management accounting considers this result and investigates the relations between the control of operational performance and the organizational performance in the hotel industry. Specifically, we are interested in the relations between assignment of decision rights, performance measurement system and incentive system dedicated to employees in contact with customers, and we consider the effects of this organizational design on organizational performance. These relations are studied in light of the strategic concept of market orientation, this one being operationalized through a qualitative study of the concept of hotel value proposition. In order to test our agency model, we use a PLS approach on the basis of an empirical study of hotels in PACA. Our results indicate support to the hypothesized positive relations between assignment of decision rights and use of incentive systems, and between use of incentive systems and non-Financial measurement. We find no support to the hypotheses that organizational design is positively related to organizational performance, and that hotel value proposition influences organizational design. Overall, these results are consistent with prior literature indicating that assignment of decision rights and management control systems are complementary choices. Furthermore, they provide insights on the specificities of service activities, as they indicate the importance of non-Financial performance measurement in incentive systems at the worker level.

The vast majority of products and processes in industry and academia require human interaction. Thus, digital human models (DHMs) are becoming critical for improved designs, injury prevention, and a better understanding of human behavior. Although many capabilities in the DHM field continue to mature, there are still many opportunities for improvement, especially with respect to posture- and motion-prediction. Thus, this thesis investigates the use of artificial neural network (ANN) for improving predictive capabilities and for better understanding how and why human behave the way they do. With respect to motion prediction, one of the most challenging opportunities for improvement concerns computation speed. Especially, when considering dynamic motion prediction, the underlying optimization problems can be large and computationally complex. Even though the current optimization-based tools for predicting human posture are relatively fast and accurate and thus do not require as much improvement, posture prediction in general is a more tractable problem than motion prediction and can provide a test bead that can shed light on potential issues with motion prediction. Thus, we investigate the use of ANN with posture prediction in order to discover potential issues. In addition, directly using ANN with posture prediction provides a preliminary step towards using ANN to predict the most appropriate combination of performance measures (PMs) - what drives human behavior. The PMs, which are the cost functions that are minimized in the posture prediction problem, are typically selected manually depending on the task. This is perhaps the most significant impediment when using posture prediction. How does the user know which PMs should be used? Neural networks provide tools for solving this problem. This thesis hypothesizes that the ANN can be trained to predict human motion quickly and accurately, to predict human posture (while considering external forces), and to determine the most appropriate combination of PM(s) for posture prediction. Such capabilities will in turn provide a new tool for studying human behavior. Based on initial experimentation, the general regression neural network (GRNN) was found to be the most effective type of ANN for DHM applications. A semi-automated methodology was developed to ease network construction, training and testing processes, and network parameters. This in turn facilitates use with DHM applications. With regards to motion prediction, use of ANN was successful. The results showed that the calculation time was reduced from 1 to 40 minutes, to a fraction of a second without reducing accuracy. With regards to posture prediction, ANN was again found to be effective. However, potential issues with certain motion-prediction tasks were discovered and shed light on necessary future development with ANNs. Finally, a decision engine was developed using GRNN for automatically selecting four human PMs, and was shown to be very effective. In order to train this new approach, a novel optimization formulation was used to extract PM weights from pre-existing motion-capture data. Eventually, this work will lead to automatically and realistically driving predictive DHMs in a general virtual environment.

Purpose: The purpose of this study is to create a brief, but comprehensive process for developing KPIs independent of context. Bridging the current gap in the literature for a process that can be applied in any industry or situation and include instructions for each of the steps in the process. To fulfill the purpose, the following research question is answered: Independent of industry and application, how could a process for organizations that are interested in developing new KPIs be structured? Method: This is an abductive qualitative study that combine extant literature with empirical data from both in-depth analysis of a single case company as well as interviews with companies from different industries. The literature was analyzed through a content analysis. Thematical analysis was utilized for analyzing the interviews. A tentative process for new KPI development synthesized from the theory and empirical findings was applied in the case company to identify a process that is applicable in a practical setting. Findings: The findings consist of a process for developing new KPIs with (1) six activities that companies should undertake, (2) six critical success factors, one for each activity, they need to consider, and (3) actions and tools to utilize in each activity. Implications: This study contributes to the literature by combining the currently wide array of research into a brief but comprehensible and applicable process that can be used independent of context. For practitioners, this study contributes by creating an understanding of how to efficiently develop new KPIs that enables the whole organization to achieve the strategy and goals. Limitations and future research: There are two main limitations in this study; the process is only applied at one company and the timeframe inhibited the ability to study the effects of the developed KPIs. Hence, future research should investigate if the process is valid in other contexts as well as study the effects of the KPIs being developed through the process. / Syfte: Syftet med denna studie är att skapa en koncis och kontextoberoende process for utveckling av nya KPIer. Detta överbryggar det nuvarande gapet i litteraturen för en process som innehåller detaljerade instruktioner och kan appliceras i vilken industri och situation helst. Följande forskningsfråga besvaras för att uppfylla syftet: Oberoende av industri och användning, hur kan en process för organisationer som vill utveckla nya KPIer vara strukturerad? Metod: Detta är en abduktiv, kvalitativ studie som kombinerar nuvarande litteratur med empirisk data från både en djupgående analys av ett företag samt flertalet intervjuer med företag från olika industrier. Litteraturen analyserades med en innehållsanalys. En tematisk analys nyttjades för att analysera intervjuerna. En tentativ process för utveckling av nya KPIer syntetiserad från teoretiska och empiriska resultat applicerades i ett företag för att identifiera en process som var applicerbar i praktiken. Resultat: Resultatet består av en process för utveckling av nya KPIer med (1) sex aktiviteter företag bör utföra, (2) sex kritiska framgångsfaktorer, en för varje aktivitet, de behöver ta hänsyn till och (3) steg och verktyg att nyttja i varje aktivitet.  Bidrag: Denna studie bidrar till litteraturen genom att kombinera det nuvarande breda spektrumet av studier till en omfattande men koncis och applicerbar process som kan användas oberoende av kontext. Studiens praktiska bidrag är att processen skapar en förståelse för hur företag effektict kan utveckla nya KPIer som möjliggör att företagets strategi och mål uppnås.  Begränsningar och framtida forskning: Studien har två huvudsakliga begränsningar: processen är enbart applicerad i ett företag och tidsramen förhindrade undersökning av de utvecklade KPIernas effekt. Därför vore det värdefullt om framtida forskning studerade processens användning i fler industrier och situationer samt vilken effekt KPIer utvecklade med processen har.