Lean e sua aplicabilidade na indústria da construção

Nos tempos que correm a gestão de topo das empresas tem como desafio adaptar-se às exigências do mercado, tendo em conta a crise atravessada nos diversos setores. O lean mais do que uma ferramenta, é uma filosofia de vida que visa a excelência. Esta filosofia contém dois pilares importantes, a melhoria contínua e o respeito pelas pessoas. A melhoria contínua pretendida visa a obtenção do valor esperado e definido perante um desafio. O lean é uma filosofia de gestão que nasce após a segunda guerra mundial caracterizado como sistema de produção enxuto que visa eliminação de desperdícios. Algumas empresas do setor da construção após verificar os resultados satisfatórios noutras áreas, impuseram a implementação da filosofia lean nas suas organizações. Esta implementação passa por adotar ferramentas que visam a eliminação de desperdícios, produção puxada e a flexibilidade de processos. A construção adotou ferramentas tais como: just in time, definição de valor, definição de desperdício, fluxo contínuo, task time, sistema puxado, poka-yoke, kanban, heijunka (nivelamento de produção), seis sigmas, last planner, kaizen, fluxo de valor, 5S`s. A presente tese pretende clarificar algumas destas ferramentas e conceitos, aproximando-os da área da construção. Inclui-se um questionário a um grupo de trabalhadores de uma empresa de construção que está na fase inicial de implementação do lean. O questionário visou entender em que fase se encontra a implementação e a importância dada ao tema pelos trabalhadores. Foram analisados alguns casos práticos onde a gestão da empresa decidiu implementar o lean.

Lean e sua aplicabilidade na indústria da construção

Nos tempos que correm a gestão de topo das empresas tem como desafio adaptar-se às exigências do mercado, tendo em conta a crise atravessada nos diversos setores. O lean mais do que uma ferramenta, é uma filosofia de vida que visa a excelência. Esta filosofia contém dois pilares importantes, a melhoria contínua e o respeito pelas pessoas. A melhoria contínua pretendida visa a obtenção do valor esperado e definido perante um desafio. O lean é uma filosofia de gestão que nasce após a segunda guerra mundial caracterizado como sistema de produção enxuto que visa eliminação de desperdícios. Algumas empresas do setor da construção após verificar os resultados satisfatórios noutras áreas, impuseram a implementação da filosofia lean nas suas organizações. Esta implementação passa por adotar ferramentas que visam a eliminação de desperdícios, produção puxada e a flexibilidade de processos. A construção adotou ferramentas tais como: just in time, definição de valor, definição de desperdício, fluxo contínuo, task time, sistema puxado, poka-yoke, kanban, heijunka (nivelamento de produção), seis sigmas, last planner, kaizen, fluxo de valor, 5S`s. A presente tese pretende clarificar algumas destas ferramentas e conceitos, aproximando-os da área da construção. Inclui-se um questionário a um grupo de trabalhadores de uma empresa de construção que está na fase inicial de implementação do lean. O questionário visou entender em que fase se encontra a implementação e a importância dada ao tema pelos trabalhadores. Foram analisados alguns casos práticos onde a gestão da empresa decidiu implementar o lean.

Bonnita

Bonnita es una empresa que nace en el año 2015 en el mes de marzo, su actividad económica se clasifica bajo el código CIIU 4751, comercio al por menor de productos textiles en establecimientos especializados, actualmente cuenta con un establecimiento de comercio ubicado en el barrio Kennedy de la ciudad de Bogotá, la inversión realizada para esta empresa se realizo en su totalidad con recursos propios, los resultados obtenidos hasta el momento han llenado la expectativas de los inversionistas y en el mes de agosto del presente año se abrirá una nueva tienda que mejorara las utilidades de la empresa. Las tiendas Bonnita enfocan todo su modelo de negocio a crear una experiencia de compra para su segmento objetivo que son las mujeres entre los 18 y 40 años de edad, de estrato 2 – 3 medio - bajo, por medio de estrategias de merchandising propias, que generan una actitud diferente y mas impulsiva dentro de la tienda, utilizando elementos sensoriales y psicológicos que el consumidor no percibe pero influye en su decisión y manera de comprar, haciendo de esta más rentable para las tiendas Bonnita. El segmento objetivo es grande en la ciudad de Bogotá, los competidores más representativos del mercado emplean modelos de negocio diferentes y no existe un líder en este segmento ya que muchas de estas empresas diversifican con respecto al género al que enfocan sus esfuerzos, Bonnita se dirige únicamente a la mujer, la rotación de sus productos es rápida debido al manejo de inventarios justo a tiempo, lo que permite ser competitivos frente al precio y innovación en los productos.

Estrategia del Grupo Volkswagen de México para la reducción del impacto ambiental generado por sus procesos productivos

El siguiente escrito pretende mostrar las estrategias que el Grupo Volkswagen de México implementó para reducir el impacto que generan sus dos fábricas en México al medio ambiente. La primera de ellas, y la más grande en cuanto a infraestructura, recurso humano, complejidad y productividad entre ambas, se ubica en el Estado de Puebla, en su capital Puebla. Se dedica a la fabricación de varios modelos de vehículos para el mercado interno y mundial. La segunda fábrica se ubica en la ciudad de Silao en el Estado de Guanajuato, esta fábrica se dedica principalmente a la fabricación de motores, los cuales posteriormente son distribuidos a distintos complejos productivos alrededor del mundo para allí ensamblarse en carrocerías. En primera instancia se describe la estrategia general con los debidos alcances establecidos desde la dirección de la empresa. Posteriormente se prosigue a desglosar cada una de las sub-estrategias, explicándolas y relacionándolas en contexto, tomando de esta manera, paso a paso, como se ha construido una campaña que ha logrado adquirir una identidad propia ampliamente reconocida tanto por la fuerza laboral de la compañía e inclusive por los agentes del mercado en el que se encuentran. Finalmente se reúnen datos numéricos relevantes en cuanto a la reducción del impacto ambiental que por último se ven reflejado en un ahorro económico para la empresa.

Gestión de la cadena de suministro de Bimbo

El presente trabajo es un informe final sobre los procesos de producción, logística y distribución de la empresa Bimbo. El informe está conformado por aspectos teóricos y prácticos, de esta manera, brinda información clara y concreta sobre los antecedentes más importantes de esta organización y su contribución a la productividad del país. La información presentada ha sido recolectada mediante una revisión teórica y una visita a sus instalaciones en Veracruz, México. De esta manera, se han estudiado sus procesos y logística de producción y cómo contribuyen en la eficiencia y calidad de la empresa; así mismo, son fundamentales para diagnosticar los aspectos a mejorar de la entidad. Por otro lado, gracias a la visita, se logró desarrollar habilidades administrativas que hasta el momento solo estaban en teoría. Llegar a un contexto real y con problemáticas evidentes permitió consolidar el aprendizaje que se obtuvo durante años en la carrera para plasmarlos en la labor. Así mismo, el detallar las instalaciones de Bimbo permitió alcanzar una mayor perspectiva con respecto a los aspectos importantes dentro del panorama organizacional; tales como la producción, la gestión y mejora de los procesos de la compañía. Esto se logró realizando labores correspondientes a la inspección, observación, revisión de logística y el análisis de los procesos productivos. El trabajo práctico indudablemente sirvió para acrecentar los conocimientos obtenidos en la universidad.

Nuevas tendencias en la Supply Management en Colombia y México

La Misión empresarial a México 2015, tiene como propósito brindar a los estudiantes espacios para el crecimiento profesional, mediante la aplicación de los conceptos y los modelos estudiados en las diferentes visitas empresariales que se realizaron. Se pretende conocer cuáles son las nuevas tendencias en el manejo y administración de la cadena de abastecimiento de las empresas, de manera que estos conceptos puedan ser aplicados en diferentes tipos de empresas. Se realizó una investigación de cada una de las empresas que fueron visitadas realizando un análisis de un punto clave en cada una, por ejemplo, se describe la política “Think Blue” empleada por el grupo Volkswagen para el éxito y reconocimiento empresarial en la logística verde, y se analizan los principales procesos de producción de la planta productora del grupo Modelo, entre otras. Por otra parte, se analiza el modelo de gestión logística para pequeñas y medianas empresas, desarrollado en la Universidad Popular Autónoma del Estado de Puebla, el cual puede ser usado como base para el progreso y fortalecimiento de las pymes en nuestro país.

La influencia de la cultura nacional en el desempeño logístico de los 123 primeros países en el logistics performance index (LPI)

En esta tesis se presenta la influencia que tiene la Cultura Nacional en el desempeño Logístico de una Nación, en especial de los 123 primeros países evaluados por el Índice de Desempeño Logístico (LPI) realizado por el Banco Mundial. Este estudio se realiza a partir de los seis ítems evaluados en el LPI y de las seis Dimensiones Culturales de Hofstede, para relacionar estas calificaciones se empleará el programa estadístico SPSS Statistical Package for the Social Sciences obteniendo como resultado posibles correlaciones para probar la hipótesis del efecto de la cultura en el desempeño logístico y establecer patrones de comportamiento en los mejores países de cada correlación. De acuerdo a los resultados obtenidos de estas correlaciones, se encontró que si existe una relación entre la cultura nacional y el desempeño logístico de un país, al igual que las dimensiones culturales más influyentes para obtener dichos resultados y se identificaron los países que cuentan con condiciones sobresalientes que facilitan tener altas posiciones en el LPI.

The role of time pressure and different psychological safety climate referents in the prediction of nurses’ hand hygiene compliance

In this study of 638 Australian nurses, compliance to hand hygiene (HH), as defined by the “five moments” recommended by the World Health Organisation (2009), was examined. Hypotheses focused on the extent to which time pressure reduces compliance and safety climate (operationalised in relation to HH using colleagues, manager, and hospital as referents) increases compliance. It also was proposed that HH climate would interact with time pressure, such that the negative effects of time pressure would be less marked when HH climate is high. The extent to which the three HH climate variables would interact among each other, either in the form of boosting or compensatory effects, was tested in an exploratory manner. A prospective research design was used in which time pressure and the HH climate variables were assessed at Time 1 and compliance was assessed by self-report two weeks later. Compliance was high but varied significantly across the 5 HH Moments, suggesting that nurses make distinctions between inherent and elective HH and also seemed to engage in some implicit rationing of HH. Time pressure dominated the utility of HH climate to have its positive impact on compliance. The most conducive workplace for compliance was one low in time pressure and high in HH climate. Colleagues were very influential in determining compliance, more so than the manager and hospital. Manager and hospital support for HH enhanced the positive effects of colleagues on compliance. Providing training and enhancing knowledge was important, not just for compliance, but for safety climate.

Heterogeneity assumptions in the specification of bargaining models: a study of household level trade-offs between commuting time and salary

With many real world decisions being made in conjunction with other decision makers, or single agent decisions having an influence on other members of the decision maker's immediate entourage, there is strong interest in studying the relative weight assigned to different agents in such contexts. In the present paper, we focus on the case of one member of a two person household being asked to make choices affecting the travel time and salary of both members. We highlight the presence of significant heterogeneity across individuals not just in their underlying sensitivities, but also in the relative weight they assign to their partner, and show how this weight varies across attributes. This is in contrast to existing work which uses weights assigned to individual agents at the level of the overall utility rather than for individual attributes. We also show clear evidence of a risk of confounding between heterogeneity in marginal sensitivities and heterogeneity in the weights assigned to each member. We show how this can lead to misleading model results, and argue that this may also explain past results showing bargaining or weight parameters outside the usual [0,1] range in more traditional joint decision making contexts. In terms of substantive results, we find that male respondents place more weight on their partner's travel time, while female respondents place more weight on their partner's salary.

TIME SERIES ANALYSIS AS INPUT FOR PREDICTIVE MODELING: PREDICTING CARDIAC ARREST IN A PEDIATRIC INTENSIVE CARE UNIT

The first manuscript, entitled "Time-Series Analysis as Input for Clinical Predictive Modeling: Modeling Cardiac Arrest in a Pediatric ICU" lays out the theoretical background for the project. There are several core concepts presented in this paper. First, traditional multivariate models (where each variable is represented by only one value) provide single point-in-time snapshots of patient status: they are incapable of characterizing deterioration. Since deterioration is consistently identified as a precursor to cardiac arrests, we maintain that the traditional multivariate paradigm is insufficient for predicting arrests. We identify time series analysis as a method capable of characterizing deterioration in an objective, mathematical fashion, and describe how to build a general foundation for predictive modeling using time series analysis results as latent variables. Building a solid foundation for any given modeling task involves addressing a number of issues during the design phase. These include selecting the proper candidate features on which to base the model, and selecting the most appropriate tool to measure them. We also identified several unique design issues that are introduced when time series data elements are added to the set of candidate features. One such issue is in defining the duration and resolution of time series elements required to sufficiently characterize the time series phenomena being considered as candidate features for the predictive model. Once the duration and resolution are established, there must also be explicit mathematical or statistical operations that produce the time series analysis result to be used as a latent candidate feature. In synthesizing the comprehensive framework for building a predictive model based on time series data elements, we identified at least four classes of data that can be used in the model design. The first two classes are shared with traditional multivariate models: multivariate data and clinical latent features. Multivariate data is represented by the standard one value per variable paradigm and is widely employed in a host of clinical models and tools. These are often represented by a number present in a given cell of a table. Clinical latent features derived, rather than directly measured, data elements that more accurately represent a particular clinical phenomenon than any of the directly measured data elements in isolation. The second two classes are unique to the time series data elements. The first of these is the raw data elements. These are represented by multiple values per variable, and constitute the measured observations that are typically available to end users when they review time series data. These are often represented as dots on a graph. The final class of data results from performing time series analysis. This class of data represents the fundamental concept on which our hypothesis is based. The specific statistical or mathematical operations are up to the modeler to determine, but we generally recommend that a variety of analyses be performed in order to maximize the likelihood that a representation of the time series data elements is produced that is able to distinguish between two or more classes of outcomes. The second manuscript, entitled "Building Clinical Prediction Models Using Time Series Data: Modeling Cardiac Arrest in a Pediatric ICU" provides a detailed description, start to finish, of the methods required to prepare the data, build, and validate a predictive model that uses the time series data elements determined in the first paper. One of the fundamental tenets of the second paper is that manual implementations of time series based models are unfeasible due to the relatively large number of data elements and the complexity of preprocessing that must occur before data can be presented to the model. Each of the seventeen steps is analyzed from the perspective of how it may be automated, when necessary. We identify the general objectives and available strategies of each of the steps, and we present our rationale for choosing a specific strategy for each step in the case of predicting cardiac arrest in a pediatric intensive care unit. Another issue brought to light by the second paper is that the individual steps required to use time series data for predictive modeling are more numerous and more complex than those used for modeling with traditional multivariate data. Even after complexities attributable to the design phase (addressed in our first paper) have been accounted for, the management and manipulation of the time series elements (the preprocessing steps in particular) are issues that are not present in a traditional multivariate modeling paradigm. In our methods, we present the issues that arise from the time series data elements: defining a reference time; imputing and reducing time series data in order to conform to a predefined structure that was specified during the design phase; and normalizing variable families rather than individual variable instances. The final manuscript, entitled: "Using Time-Series Analysis to Predict Cardiac Arrest in a Pediatric Intensive Care Unit" presents the results that were obtained by applying the theoretical construct and its associated methods (detailed in the first two papers) to the case of cardiac arrest prediction in a pediatric intensive care unit. Our results showed that utilizing the trend analysis from the time series data elements reduced the number of classification errors by 73%. The area under the Receiver Operating Characteristic curve increased from a baseline of 87% to 98% by including the trend analysis. In addition to the performance measures, we were also able to demonstrate that adding raw time series data elements without their associated trend analyses improved classification accuracy as compared to the baseline multivariate model, but diminished classification accuracy as compared to when just the trend analysis features were added (ie, without adding the raw time series data elements). We believe this phenomenon was largely attributable to overfitting, which is known to increase as the ratio of candidate features to class examples rises. Furthermore, although we employed several feature reduction strategies to counteract the overfitting problem, they failed to improve the performance beyond that which was achieved by exclusion of the raw time series elements. Finally, our data demonstrated that pulse oximetry and systolic blood pressure readings tend to start diminishing about 10-20 minutes before an arrest, whereas heart rates tend to diminish rapidly less than 5 minutes before an arrest.

Making decisions with the future in mind: Developmental and comparative identification of mental time travel

Mechanisms that produce behavior which increase future survival chances provide an adaptive advantage. The flexibility of human behavior is at least partly the result of one such mechanism, our ability to travel mentally in time and entertain potential future scenarios. We can study mental time travel in children using language. Current results suggest that key developments occur between the ages of three to five. However, linguistic performance can be misleading as language itself is developing. We therefore advocate the use of methodologies that focus on future-oriented action. Mental time travel required profound changes in humans' motivational system, so that current behavior could be directed to secure not just present, but individually anticipated future needs. Such behavior should be distinguishable from behavior based on current drives, or on other mechanisms. We propose an experimental paradigm that provides subjects with an opportunity to act now to satisfy a need not currently experienced. This approach may be used to assess mental time travel in nonhuman animals. We conclude by describing a preliminary study employing an adaptation of this paradigm for children. (c) 2005 Elsevier Inc. All rights reserved.

Consumer-based brand equity for Australia as a long haul tourism destination in an emerging market

Purpose: Although the branding literature emerged during the 1940s, research relating to tourism destination branding has only gained momentum since the late 1990s. There remains a lack of theory in particular that addresses the measurement of the effectiveness of destination branding over time. The purpose of the research was to test the effectiveness of a model of consumer-based brand equity (CBBE) for a country destination.---------- Design/methodology: A model of consumer-based brand equity was adapted from the marketing literature and applied to a nation context. The model was tested by using structural equation modelling with data from a large Chilean sample (n=845), comprising a mix of previous visitors and non-visitors. The model fits the data well. Findings: This paper reports the results of an investigation into brand equity for Australia as a long haul destination in an emerging market. The research took place just before the launch of the nation’s fourth new brand campaign in six years. The results indicate Australia is a well known but not compelling destination brand for tourists in Chile, which reflects the lower priority the South American market has been given by the national tourism office (NTO).---------- Practical implications: It is suggested that CBBE measures could be analysed at various points in time to track any strengthening or weakening of market perceptions in relation to brand objectives. A standard CBBE instrument could provide long-term effectiveness performance measures regardless of changes in destination marketing organisation (DMO) staff, advertising agency, other stakeholders, and budget.---------- Originality/value: This study contributes to the nation-branding literature by being one of the first to test the efficacy of a model of consumer-based brand equity for a tourism destination brand.

Metal Contaminants in Leachate from Sanitary Landfills

The uncontrolled disposal of solid wastes poses an immediate threat to public health and a long term threat to the environmental well being of future generations. Solid waste is waste resulting from human activities that is solid and unwanted (Peavy et al., 1985). If unmanaged, dumped solid wastes generate liquid and gaseous emissions that are detrimental to the environment. This can lead to a serious form of contamination known as metal contamination, which poses a risk to human health and ecosystems. For example, some heavy metals (cadmium, chromium compounds, and nickel tetracarbonyl) are known to be highly toxic, and are aggressive at elevated concentrations. Iron, copper, and manganese can cause staining, and aluminium causes depositions and discolorations. In addition, calcium and magnesium cause hardness in water causing scale deposition and scum formation. Though not a metal but a metalloid, arsenic is poisonous at relatively high concentrations and when diluted at low concentrations causes skin cancer. Normally, metal contaminants are found in a dissolved form in the liquid percolating through landfills. Because average metal concentrations from full-scale landfills, test cells, and laboratory studies have tended to be generally low, metal contamination originating from landfills is not generally considered a major concern (Kjeldsen et al., 2002; Christensen et al., 1999). However, a number of factors make it necessary to take a closer look at metal contaminants from landfills. One of these factors relates to variability. Landfill leachate can have different qualities depending on the weather and operating conditions. Therefore, at one moment in time, metal contaminant concentrations may be quite low, but at a later time these concentrations could be quite high. Also, these conditions relate to the amount of leachate that is being generated. Another factor is biodiversity. It cannot be assumed that a particular metal contaminant is harmless to flora and fauna (including micro organisms) just because it is harmless to human health. This has significant implications for ecosystems and the environment. Finally, there is the moral factor. Because uncertainty surrounds the potential effects of metal contamination, it is appropriate to take precautions to prevent it from taking place. Consequently, it is necessary to have good scientific knowledge (empirically supported) to adequately understand the extent of the problem and improve the way waste is being disposed of

Creating new narratives through shared time and space : the performer/audience connection in multi-site dance events

Site-specific performance provides choices in audience experience via degrees of scale, proximity, levels of immersion and viewing perspectives. Beyond these choices, multi-site promenade events also form a connected audience/performer relationship in which moving together in time and space can produce a shared narrative and aesthetic sensibility of collective, yet individuated and shifting meanings. This paper interrogates this notion through audience/performer experiences in two separate multi-site, dance-led events. here/there/then/now occurred in four intimate sites within the Brisbane Powerhouse, providing a theatricalised platform for audiences to create linked narratives through open-ended and fragmented intertextuality. Accented Body, based on the concept of “the body as site and in site” and notions of connectivity, provided a more expansive platform for a similar, but heightened, shared engagement. Audiences traversed 6 outdoor and 2 indoor Brisbane sites moving to varying levels of a large complex. Eleven, predominantly interactive, screens provided links to other sites as well as to distributed presences in Seoul and London. The differentiation in scale and travel time between sites deepened the immersive experiences of audiences who reported transformative engagements with both site and architecture, accompanied by a sense of extended and yet quickened time.

Validating the is-impact model in the Malaysian public sector

This research is one of several ongoing studies conducted within the IT Professional Services (ITPS) research programme at Queensland University of Technology (QUT). In 2003, ITPS introduced the IS-Impact model, a measurement model for measuring information systems success from the viewpoint of multiple stakeholders. The model, along with its instrument, is robust, simple, yet generalisable, and yields results that are comparable across time, stakeholders, different systems and system contexts. The IS-Impact model is defined as “a measure at a point in time, of the stream of net benefits from the Information System (IS), to date and anticipated, as perceived by all key-user-groups”. The model represents four dimensions, which are ‘Individual Impact’, ‘Organizational Impact’, ‘Information Quality’ and ‘System Quality’. The two Impact dimensions measure the up-to-date impact of the evaluated system, while the remaining two Quality dimensions act as proxies for probable future impacts (Gable, Sedera & Chan, 2008). To fulfil the goal of ITPS, “to develop the most widely employed model” this research re-validates and extends the IS-Impact model in a new context. This method/context-extension research aims to test the generalisability of the model by addressing known limitations of the model. One of the limitations of the model relates to the extent of external validity of the model. In order to gain wide acceptance, a model should be consistent and work well in different contexts. The IS-Impact model, however, was only validated in the Australian context, and packaged software was chosen as the IS understudy. Thus, this study is concerned with whether the model can be applied in another different context. Aiming for a robust and standardised measurement model that can be used across different contexts, this research re-validates and extends the IS-Impact model and its instrument to public sector organisations in Malaysia. The overarching research question (managerial question) of this research is “How can public sector organisations in Malaysia measure the impact of information systems systematically and effectively?” With two main objectives, the managerial question is broken down into two specific research questions. The first research question addresses the applicability (relevance) of the dimensions and measures of the IS-Impact model in the Malaysian context. Moreover, this research question addresses the completeness of the model in the new context. Initially, this research assumes that the dimensions and measures of the IS-Impact model are sufficient for the new context. However, some IS researchers suggest that the selection of measures needs to be done purposely for different contextual settings (DeLone & McLean, 1992, Rai, Lang & Welker, 2002). Thus, the first research question is as follows, “Is the IS-Impact model complete for measuring the impact of IS in Malaysian public sector organisations?” [RQ1]. The IS-Impact model is a multidimensional model that consists of four dimensions or constructs. Each dimension is represented by formative measures or indicators. Formative measures are known as composite variables because these measures make up or form the construct, or, in this case, the dimension in the IS-Impact model. These formative measures define different aspects of the dimension, thus, a measurement model of this kind needs to be tested not just on the structural relationship between the constructs but also the validity of each measure. In a previous study, the IS-Impact model was validated using formative validation techniques, as proposed in the literature (i.e., Diamantopoulos and Winklhofer, 2001, Diamantopoulos and Siguaw, 2006, Petter, Straub and Rai, 2007). However, there is potential for improving the validation testing of the model by adding more criterion or dependent variables. This includes identifying a consequence of the IS-Impact construct for the purpose of validation. Moreover, a different approach is employed in this research, whereby the validity of the model is tested using the Partial Least Squares (PLS) method, a component-based structural equation modelling (SEM) technique. Thus, the second research question addresses the construct validation of the IS-Impact model; “Is the IS-Impact model valid as a multidimensional formative construct?” [RQ2]. This study employs two rounds of surveys, each having a different and specific aim. The first is qualitative and exploratory, aiming to investigate the applicability and sufficiency of the IS-Impact dimensions and measures in the new context. This survey was conducted in a state government in Malaysia. A total of 77 valid responses were received, yielding 278 impact statements. The results from the qualitative analysis demonstrate the applicability of most of the IS-Impact measures. The analysis also shows a significant new measure having emerged from the context. This new measure was added as one of the System Quality measures. The second survey is a quantitative survey that aims to operationalise the measures identified from the qualitative analysis and rigorously validate the model. This survey was conducted in four state governments (including the state government that was involved in the first survey). A total of 254 valid responses were used in the data analysis. Data was analysed using structural equation modelling techniques, following the guidelines for formative construct validation, to test the validity and reliability of the constructs in the model. This study is the first research that extends the complete IS-Impact model in a new context that is different in terms of nationality, language and the type of information system (IS). The main contribution of this research is to present a comprehensive, up-to-date IS-Impact model, which has been validated in the new context. The study has accomplished its purpose of testing the generalisability of the IS-Impact model and continuing the IS evaluation research by extending it in the Malaysian context. A further contribution is a validated Malaysian language IS-Impact measurement instrument. It is hoped that the validated Malaysian IS-Impact instrument will encourage related IS research in Malaysia, and that the demonstrated model validity and generalisability will encourage a cumulative tradition of research previously not possible. The study entailed several methodological improvements on prior work, including: (1) new criterion measures for the overall IS-Impact construct employed in ‘identification through measurement relations’; (2) a stronger, multi-item ‘Satisfaction’ construct, employed in ‘identification through structural relations’; (3) an alternative version of the main survey instrument in which items are randomized (rather than blocked) for comparison with the main survey data, in attention to possible common method variance (no significant differences between these two survey instruments were observed); (4) demonstrates a validation process of formative indexes of a multidimensional, second-order construct (existing examples mostly involved unidimensional constructs); (5) testing the presence of suppressor effects that influence the significance of some measures and dimensions in the model; and (6) demonstrates the effect of an imbalanced number of measures within a construct to the contribution power of each dimension in a multidimensional model.