Measuring CRM and SCM benefits : a preliminary measurement model

Organizations invest heavily in Customer Relationship Management (CRM) and Supply Chain Management (SCM) systems, and their related infrastructure, presumably expecting positive benefits to the organization. Assessing the benefits of such applications is an important aspect of managing such systems. Considering the salient differences between CRM and SCM applications with other intra-organizational applications, existing Information Systems benefits measurement models and frameworks are ill-suited to gauge benefits of inter-organizational systems. This paper reports the preliminary findings of a measurement model developed to assess benefits of CRM and SCM applications. The preliminary model, which reflects the characteristics of the Analytic Theory, is derived using a review of 55 academic studies and 44 papers from the practice. Six hundred and six identified benefits were then synthesized in to 74 non-overlapping benefits, arranged under six dimensions.

Towards a CRM and SCM Benefits Measurement Model

Organizations invest heavily in Customer Relationship Management (CRM) and Supply Chain Management (SCM) systems, and their related infrastructure, presumably expecting positive benefits to the organization. Assessing the benefits of such systems is an important aspect of managing such systems. Given the substantial differences between CRM and SCM systems with traditional intra-organizational applications, existing Information Systems benefits measurement models and frameworks are ill-suited to gauge CRM and SCM benefits. This paper reports the preliminary findings of a research that seeks to develop a measurement model to assess benefits of CRM and SCM applications. The a-priori benefits measurement model is developed reviewing the 55 academic studies and 40 practitioner papers. The review of related literature yielded 606 benefits, which were later synthesized into 74 mutually exclusive benefit measures of CRM and SCM applications arranged under five dimensions.

Triangular Linguistic Fuzzy based performance measurement model for supply chain to assess leanness attributes

Increasing global competitiveness worldwide has forced manufacturing organizations to produce high-quality products more quickly and at a competitive cost. In order to reach these goals, they need good quality components from suppliers at optimum price and lead time. This actually forced all the companies to adapt different improvement practices such as lean manufacturing, Just in Time (JIT) and effective supply chain management. Applying new improvement techniques and tools cause higher establishment costs and more Information Delay (ID). On the contrary, these new techniques may reduce the risk of stock outs and affect supply chain flexibility to give a better overall performance. But industry people are unable to measure the overall affects of those improvement techniques with a standard evaluation model .So an effective overall supply chain performance evaluation model is essential for suppliers as well as manufacturers to assess their companies under different supply chain strategies. However, literature on lean supply chain performance evaluation is comparatively limited. Moreover, most of the models assumed random values for performance variables. The purpose of this paper is to propose an effective supply chain performance evaluation model using triangular linguistic fuzzy numbers and to recommend optimum ranges for performance variables for lean implementation. The model initially considers all the supply chain performance criteria (input, output and flexibility), converts the values to triangular linguistic fuzzy numbers and evaluates overall supply chain performance under different situations. Results show that with the proposed performance measurement model, improvement area for each variable can be accurately identified.

Realizing benefits from enterprise architecture : a measurement model

Enterprise architecture (EA) management has become an intensively discussed approach to manage enterprise transformations. Despite the popularity and potential of EA, both researchers and practitioners lament a lack of knowledge about the realization of benefits from EA. To determine the benefits from EA, we explore the various dimensions of EA benefit realization and report on the development of a validated and robust measurement instrument. In this paper, we test the reliability and construct validity of the EA benefit realization model (EABRM), which we have designed based on the DeLone & McLean IS success model and findings from exploratory interviews. A confirmatory factor analysis confirms the existence of an impact of five distinct and individually important dimensions on the benefits derived from EA: EA artefact quality, EA infrastructure quality, EA service quality, EA culture, and EA use. The analysis presented in this paper shows that the EA benefit realization model is an instrument that demonstrates strong reliability and validity.

A formative measurement model of business process model quality

Business process management (BPM) is becoming the dominant management paradigm. Business process modelling is central to BPM, and the resultant business process model the core artefact guiding subsequent process change. Thus, model quality is at the centre, mediating between the modelling effort and related growing investment in ultimate process improvements. Nonetheless, though research interest in the properties that differentiate high quality process models is longstanding, there have been no past reports of a valid, operationalised, holistic measure of business process model quality. In attention to this gap, this paper reports validation of a Business Process Model Quality measurement model, conceptualised as a single-order, formative index. Such a measurement model has value as the dependent variable in rigorously researching the drivers of model quality; as antecedent of ultimate process improvements; and potentially as an economical comparator and diagnostic for practice.

Organisational culture in airworthiness management programs : developing a measurement model

All civil and private aircraft are required to comply with the airworthiness standards set by their national airworthiness authority and throughout their operational life must be in a condition of safe operation. Aviation accident data shows that over twenty percent of all fatal accidents in aviation are due to airworthiness issues, specifically aircraft mechanical failures. Ultimately it is the responsibility of each registered operator to ensure that their aircraft remain in a condition of safe operation, and this is done through both effective management of airworthiness activities and the effective program governance of safety outcomes. Typically, the projects within these airworthiness management programs are focused on acquiring, modifying and maintaining the aircraft as a capability supporting the business. Program governance provides the structure through which the goals and objectives of airworthiness programs are set along with the means of attaining them. Whilst the principal causes of failures in many programs can be traced to inadequate program governance, many of the failures in large scale projects can have their root causes in the organisational culture and more specifically in the organisational processes related to decision-making. This paper examines the primary theme of project and program based enterprises, and introduces a model for measuring organisational culture in airworthiness management programs using measures drawn from 211 respondents in Australian airline programs. The paper describes the theoretical perspectives applied to modifying an original model to specifically focus it on measuring the organisational culture of programs for managing airworthiness; identifying the most important factors needed to explain the relationship between the measures collected, and providing a description of the nature of these factors. The paper concludes by identifying a model that best describes the organisational culture data collected from seven airworthiness management programs.

Organizational culture in airworthiness management programmes : extending an existing measurement model

All civil and private aircraft are required to comply with the airworthiness standards set by their national airworthiness authority and throughout their operational life must be in a condition of safe operation. Aviation accident data shows that over 20% of all fatal accidents in aviation are due to airworthiness issues, specifically aircraft mechanical failures. Ultimately it is the responsibility of each registered operator to ensure that their aircraft remain in a condition of safe operation, and this is done through both effective management of airworthiness activities and the effective programme governance of safety outcomes. Typically, the projects within these airworthiness management programmes are focused on acquiring, modifying and maintaining the aircraft as a capability supporting the business. Programme governance provides the structure through which the goals and objectives of airworthiness programmes are set along with the means of attaining them. Whilst the principal causes of failures in many programmes can be traced to inadequate programme governance, many of the failures in large-scale projects can have their root causes in the organizational culture and more specifically in the organizational processes related to decision-making. This paper examines the primary theme of project and programme-based enterprises, and introduces a model for measuring organizational culture in airworthiness management programmes using measures drawn from 211 respondents in Australian airline programmes. The paper describes the theoretical perspectives applied to modifying an original model to specifically focus it on measuring the organizational culture of programmes for managing airworthiness; identifying the most important factors needed to explain the relationship between the measures collected, and providing a description of the nature of these factors. The paper concludes by identifying a model that best describes the organizational culture data collected from seven airworthiness management programmes.

A fuzzy TOPSIS based multi criteria performance measurement model for lean supply chain

Increasing global competition, rapid technological changes, advances in manufacturing and information technology and discerning customers are forcing supply chains to adopt improvement practices that enable them to deliver high quality products at a lower cost and in a shorter period of time. A lean initiative is one of the most effective approaches toward achieving this goal. In the lean improvement process, it is critical to measure current and desired performance level in order to clearly evaluate the lean implementation efforts. Many attempts have tried to measure supply chain performance incorporating both quantitative and qualitative measures but failed to provide an effective method of measuring improvements in performances for dynamic lean supply chain situations. Therefore, the necessity of appropriate measurement of lean supply chain performance has become imperative. There are many lean tools available for supply chains; however, effectiveness of a lean tool depends on the type of the product and supply chain. One tool may be highly effective for a supply chain involved in high volume products but may not be effective for low volume products. There is currently no systematic methodology available for selecting appropriate lean strategies based on the type of supply chain and market strategy This thesis develops an effective method to measure the performance of supply chain consisting of both quantitative and qualitative metrics and investigates the effects of product types and lean tool selection on the supply chain performance Supply chain performance matrices and the effects of various lean tools over performance metrics mentioned in the SCOR framework have been investigated. A lean supply chain model based on the SCOR metric framework is then developed where non- lean and lean as well as quantitative and qualitative metrics are incorporated in appropriate metrics. The values of appropriate metrics are converted into triangular fuzzy numbers using similarity rules and heuristic methods. Data have been collected from an apparel manufacturing company for multiple supply chain products and then a fuzzy based method is applied to measure the performance improvements in supply chains. Using the fuzzy TOPSIS method, which chooses an optimum alternative to maximise similarities with positive ideal solutions and to minimise similarities with negative ideal solutions, the performances of lean and non- lean supply chain situations for three different apparel products have been evaluated. To address the research questions related to effective performance evaluation method and the effects of lean tools over different types of supply chains; a conceptual framework and two hypotheses are investigated. Empirical results show that implementation of lean tools have significant effects over performance improvements in terms of time, quality and flexibility. Fuzzy TOPSIS based method developed is able to integrate multiple supply chain matrices onto a single performance measure while lean supply chain model incorporates qualitative and quantitative metrics. It can therefore effectively measure the improvements for supply chain after implementing lean tools. It is demonstrated that product types involved in the supply chain and ability to select right lean tools have significant effect on lean supply chain performance. Future study can conduct multiple case studies in different contexts.

University Students Depression Inventory : measurement model and psychometric properties

Depression is a serious condition that impacts the academic success and emotional well-being of the university students globally. Keeping in view the debilitating nature of this condition, the present study examined the stability of the factor structure and psychometric properties of the University Student Depression Inventory (USDI; Khawaja and Bryden, 2006). There is a need to translate and validate the scale for Persian speaking students, who live in Iran, its neighboring countries and in many other Western countries. The scale was translated into the Persian language and was used as part of a battery consisting of the scales measuring suicide, depression, stress, happiness and academic achievement. The battery was administered to 359 undergraduate students, and an additional 150 students who had been referred to the mental health center of the University of Tehran as clinical sample. Confirmatory factor analysis upheld the original three-factor structure. The results exhibited internal consistency, test-retest reliability, convergent, and divergent validity, and discriminant validity. There were gender differences and male had higher mean scores on Lethargy, Cognitive\emotion, and Academic motivation subscales than female students. Findings supported the Persian version of the USDI for cross-cultural use as a valid and reliable measure in the diagnosis of depression.

Revisiting the conceptualization and measurement of service quality

Since the 1980s, industries and researchers have sought to better understand the quality of services due to the rise in their importance (Brogowicz, Delene and Lyth 1990). More recent developments with online services, coupled with growing recognition of service quality (SQ) as a key contributor to national economies and as an increasingly important competitive differentiator, amplify the need to revisit our understanding of SQ and its measurement. Although ‘SQ’ can be broadly defined as “a global overarching judgment or attitude relating to the overall excellence or superiority of a service” (Parasuraman, Berry and Zeithaml 1988), the term has many interpretations. There has been considerable progress on how to measure SQ perceptions, but little consensus has been achieved on what should be measured. There is agreement that SQ is multi-dimensional, but little agreement as to the nature or content of these dimensions (Brady and Cronin 2001). For example, within the banking sector, there exist multiple SQ models, each consisting of varying dimensions. The existence of multiple conceptions and the lack of a unifying theory bring the credibility of existing conceptions into question, and beg the question of whether it is possible at some higher level to define SQ broadly such that it spans all service types and industries. This research aims to explore the viability of a universal conception of SQ, primarily through a careful re-visitation of the services and SQ literature. The study analyses the strengths and weaknesses of the highly regarded and widely used global SQ model (SERVQUAL) which reflects a single-level approach to SQ measurement. The SERVQUAL model states that customers evaluate SQ (of each service encounter) based on five dimensions namely reliability, assurance, tangibles, empathy and responsibility. SERVQUAL, however, failed to address what needs to be reliable, assured, tangible, empathetic and responsible. This research also addresses a more recent global SQ model from Brady and Cronin (2001); the B&C (2001) model, that has potential to be the successor of SERVQUAL in that it encompasses other global SQ models and addresses the ‘what’ questions that SERVQUAL didn’t. The B&C (2001) model conceives SQ as being multidimensional and multi-level; this hierarchical approach to SQ measurement better reflecting human perceptions. In-line with the initial intention of SERVQUAL, which was developed to be generalizable across industries and service types, this research aims to develop a conceptual understanding of SQ, via literature and reflection, that encompasses the content/nature of factors related to SQ; and addresses the benefits and weaknesses of various SQ measurement approaches (i.e. disconfirmation versus perceptions-only). Such understanding of SQ seeks to transcend industries and service types with the intention of extending our knowledge of SQ and assisting practitioners in understanding and evaluating SQ. The candidate’s research has been conducted within, and seeks to contribute to, the ‘IS-Impact’ research track of the IT Professional Services (ITPS) Research Program at QUT. The vision of the track is “to develop the most widely employed model for benchmarking Information Systems in organizations for the joint benefit of research and practice.” The ‘IS-Impact’ research track has developed an Information Systems (IS) success measurement model, the IS-Impact Model (Gable, Sedera and Chan 2008), which seeks to fulfill the track’s vision. Results of this study will help future researchers in the ‘IS-Impact’ research track address questions such as: • Is SQ an antecedent or consequence of the IS-Impact model or both? • Has SQ already been addressed by existing measures of the IS-Impact model? • Is SQ a separate, new dimension of the IS-Impact model? • Is SQ an alternative conception of the IS? Results from the candidate’s research suggest that SQ dimensions can be classified at a higher level which is encompassed by the B&C (2001) model’s 3 primary dimensions (interaction, physical environment and outcome). The candidate also notes that it might be viable to re-word the ‘physical environment quality’ primary dimension to ‘environment quality’ so as to better encompass both physical and virtual scenarios (E.g: web sites). The candidate does not rule out the global feasibility of the B&C (2001) model’s nine sub-dimensions, however, acknowledges that more work has to be done to better define the sub-dimensions. The candidate observes that the ‘expertise’, ‘design’ and ‘valence’ sub-dimensions are supportive representations of the ‘interaction’, physical environment’ and ‘outcome’ primary dimensions respectively. The latter statement suggests that customers evaluate each primary dimension (or each higher level of SQ classification) namely ‘interaction’, physical environment’ and ‘outcome’ based on the ‘expertise’, ‘design’ and ‘valence’ sub-dimensions respectively. The ability to classify SQ dimensions at a higher level coupled with support for the measures that make up this higher level, leads the candidate to propose the B&C (2001) model as a unifying theory that acts as a starting point to measuring SQ and the SQ of IS. The candidate also notes, in parallel with the continuing validation and generalization of the IS-Impact model, that there is value in alternatively conceptualizing the IS as a ‘service’ and ultimately triangulating measures of IS SQ with the IS-Impact model. These further efforts are beyond the scope of the candidate’s study. Results from the candidate’s research also suggest that both the disconfirmation and perceptions-only approaches have their merits and the choice of approach would depend on the objective(s) of the study. Should the objective(s) be an overall evaluation of SQ, the perceptions-only approached is more appropriate as this approach is more straightforward and reduces administrative overheads in the process. However, should the objective(s) be to identify SQ gaps (shortfalls), the (measured) disconfirmation approach is more appropriate as this approach has the ability to identify areas that need improvement.

Extending the IS-Impact Model into the higher education sector

The study addresses known limitations of what may be the most important dependent variable in Information Systems (IS) research; IS-Success or IS-Impact. The study is expected to force a deeper understanding of the broad notions of IS success and impact. The aims of the research are to: (1) enhance the robustness and minimize limitations of the IS-Impact model, and (2) introduce and operationalise a more rigorously validated IS Impact measurement model to Universities, as a reliable model for evaluating different Administrative Systems. In extending and further generalizing the IS-Impact model, the study will address contemporary validation issues.

Validating the IS-Impact Model At Queensland University Of Technology (QUT): Part A

The overall research aims to develop a standardised instrument to measure the impacts resulting from contemporary Information Systems (IS). The research adopts the IS-Impact measurement model, introduced by Gable et al, (2008), as its theoretical foundation, and applies the extension strategy described by Berthon et al. (2002); extending both theory and the context, where the new context is the Human Resource (HR) system. The research will be conducted in two phases, the exploratory phase and the specification phase. The purpose of this paper is to present the findings of the exploratory phase. 134 respondents from a major Australian University were involved in this phase. The findings have supported most of the existing IS-Impact model’s credibility. However, some textual data may suggest new measures for the IS-Impact model, while the low response rate or the averting of some may suggest the elimination of some measures from the model.

Validating the IS-Impact model in Australasian universities

This paper presents a novel study that aims to contribute to understanding the phenomenon of Enterprise Systems (ES) evaluation in Australasian universities. The proposed study addresses known limitations of arguably the most significant dependent variable in the Information System (IS) field - IS Success or IS-Impact. This study adopts the IS-Impact measurement model, reported by Gable et al. (2008), as the primary commencing theory-base and applies research extension strategy described by Berthon et al. (2002); extending both theory and the context. This study employs a longitudinal, multi-method research design, with two interrelated phases – exploratory and confirmatory. The exploratory phase aims to investigate the applicability and sufficiency of the IS-Impact dimensions and measures in the new context. The confirmatory phase will gather quantitative data to statistically validate IS-Impact model as a formative index.

Understanding the phenomenon of IS success in China through the lens of the IS-Impact model

This study is conducted within the IS-Impact Research Track at Queensland University of Technology (QUT). The goal of the IS-Impact Track is, “to develop the most widely employed model for benchmarking information systems in organizations for the joint benefit of both research and practice” (Gable et al, 2006). IS-Impact is defined as “a measure at a point in time, of the stream of net benefits from the IS, to date and anticipated, as perceived by all key-user-groups” (Gable Sedera and Chan, 2008). Track efforts have yielded the bicameral IS-Impact measurement model; the “impact” half includes Organizational-Impact and Individual-Impact dimensions; the “quality” half includes System-Quality and Information-Quality dimensions. The IS-Impact model, by design, is intended to be robust, simple and generalizable, to yield results that are comparable across time, stakeholders, different systems and system contexts. The model and measurement approach employ perceptual measures and an instrument that is relevant to key stakeholder groups, thereby enabling the combination or comparison of stakeholder perspectives. Such a validated and widely accepted IS-Impact measurement model has both academic and practical value. It facilitates systematic operationalization of a main dependent variable in research (IS-Impact), which can also serve as an important independent variable. For IS management practice it provides a means to benchmark and track the performance of information systems in use. The objective of this study is to develop a Mandarin version IS-Impact model, encompassing a list of China-specific IS-Impact measures, aiding in a better understanding of the IS-Impact phenomenon in a Chinese organizational context. The IS-Impact model provides a much needed theoretical guidance for this investigation of ES and ES impacts in a Chinese context. The appropriateness and soundness of employing the IS-Impact model as a theoretical foundation are evident: the model originated from a sound theory of IS Success (1992), developed through rigorous validation, and also derived in the context of Enterprise Systems. Based on the IS-Impact model, this study investigates a number of research questions (RQs). Firstly, the research investigated what essential impacts have been derived from ES by Chinese users and organizations [RQ1]. Secondly, we investigate which salient quality features of ES are perceived by Chinese users [RQ2]. Thirdly, we seek to answer whether the quality and impacts measures are sufficient to assess ES-success in general [RQ3]. Lastly, the study attempts to address whether the IS-Impact measurement model is appropriate for Chinese organizations in terms of evaluating their ES [RQ4]. An open-ended, qualitative identification survey was employed in the study. A large body of short text data was gathered from 144 Chinese users and 633 valid IS-Impact statements were generated from the data set. A generally inductive approach was applied in the qualitative data analysis. Rigorous qualitative data coding resulted in 50 first-order categories with 6 second-order categories that were grounded from the context of Chinese organization. The six second-order categories are: 1) System Quality; 2) Information Quality; 3) Individual Impacts;4) Organizational Impacts; 5) User Quality and 6) IS Support Quality. The final research finding of the study is the contextualized Mandarin version IS-Impact measurement model that includes 38 measures organized into 4 dimensions: System Quality, information Quality, Individual Impacts and Organizational Impacts. The study also proposed two conceptual models to harmonize the IS-Impact model and the two emergent constructs – User Quality and IS Support Quality by drawing on previous IS effectiveness literatures and the Work System theory proposed by Alter (1999) respectively. The study is significant as it is the first effort that empirically and comprehensively investigates IS-Impact in China. Specifically, the research contributions can be classified into theoretical contributions and practical contributions. From the theoretical perspective, through qualitative evidence, the study test and consolidate IS-Impact measurement model in terms of the quality of robustness, completeness and generalizability. The unconventional research design exhibits creativity of the study. The theoretical model does not work as a top-down a priori seeking for evidence demonstrating its credibility; rather, the study allows a competitive model to emerge from the bottom-up and open-coding analysis. Besides, the study is an example extending and localizing pre-existing theory developed in Western context when the theory is introduced to a different context. On the other hand, from the practical perspective, It is first time to introduce prominent research findings in field of IS Success to Chinese academia and practitioner. This study provides a guideline for Chinese organizations to assess their Enterprise System, and leveraging IT investment in the future. As a research effort in ITPS track, this study contributes the research team with an alternative operationalization of the dependent variable. The future research can take on the contextualized Mandarin version IS-Impact framework as a theoretical a priori model, further quantitative and empirical testing its validity.

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.