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.

Inferring the biggest and best: a measurement model for applying recognition to evoke consideration sets and judge between multiple alternatives

It has long been supposed that preference judgments between sets of to-be-considered possibilities are made by means of initially winnowing down the most promising-looking alternatives to form smaller “consideration sets” (Howard, 1963; Wright & Barbour, 1977). In preference choices with >2 options, it is standard to assume that a “consideration set”, based upon some simple criterion, is established to reduce the options available. Inferential judgments, in contrast, have more frequently been investigated in situations in which only two possibilities need to be considered (e.g., which of these two cities is the larger?) Proponents of the “fast and frugal” approach to decision-making suggest that such judgments are also made on the basis of limited, simple criteria. For example, if only one of two cities is recognized and the task is to judge which city has the larger population, the recognition heuristic states that the recognized city should be selected. A multinomial processing tree model is outlined which provides the basis for estimating the extent to which recognition is used as a criterion in establishing a consideration set for inferential judgments between three possible options.

A Measurement Model of Cortisol Reactivity of Healthy Older Adults

Research on the physiological adaptation process has found that stress is associated with the rate of cortisol secretion, the main hormone that reflects stress. However, considerable variation among subjects has been reported. Using a sample of older adults (N=46), we tested the hypothesis that cortisol reactivity is composed of (1) a situation-related component representing hypothalamic influence on cortisol secretion observed on three different occasions, and (2) a stable component representing a general trait responsible for cortisol responses observed from occasion to occasion. LISREL VIII was used to test this hypothesis. Results indicated that a homogeneous reliability model was not supported by the data. A congeneric measurement model represented a better fit to the data. Results suggest that subjects have consistent patterns of response during separate experimental occasions. However, results do not suggest a consistent pattern of response over time. The main implication of these results is that salivary cortisol measures are sensitive to experimental stress situations. As such, this noninvasive method may be useful in examining adaptive responses to stress.

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.