Search results

This paper aims to introduce and demonstrate a method that supports design decisions in an easy and practicable way.

Complete paired comparison is a well‐established scaling method for ratio‐scaling sets of stimuli. This method is well‐proven for scaling variants of user interface designs. The paper demonstrates how the method can be applied to input forms, for example search masks of a library catalogue.

The investigation shows that paired comparison is well applicable for interfaces used in library systems and results are presented of the comparison that are relevant for the design of catalogue searches. Major aspects are influences of visual design, vertical alignment of (search‐) fields, and vertical spacing of form elements.

Since the method can be used without much (technical) effort, a theoretically quite complex approach can be used also by persons not familiar with psychometric scaling techniques.

Introduction: The insurance industry is one of the lucrative sectors of the economy. However, it is volatile because of the large chunk of data generated by the transactions taking place daily. However, every bit of it is responsible for creating market trends for stock investors to predict the returns. The specialised data mining techniques act as a solution for decision-making, reducing uncertainty in decision-making.

Purpose: There are limited studies that have examined the efficiency and effectiveness of data mining techniques across the companies in the insurance industry to date. To enable the companies to take exact benefit of data mining techniques in insurance, the present study will focus on investigating the efficiency of artificial neural network (ANN) and support vector machine SVM across insurance companies of CNX 500.

Method: For predictive models, various technical indicators were considered independent variables, and change in return, i.e. increase and decrease, was deemed a dependent variable. The indicators were transformed from daily raw data of insurance company’s stock values spanning four years. We formed 90 data sets of varied periods for building the model – specifically six months, one year, two years, and four years for selected six insurance companies.

Findings: The study’s findings revealed that ANN performed best for the ICICIPRULI data model in terms of hit ratio. Whereas the performance of SVM was observed to be the best for the ICICIGI data model. In the case of pairwise comparison among the six selected Indian insurance companies from CNX 500, the extracted data evaluated and concluded that there were eight significantly different pairs based on hit ratio in the case of ANN models and nine significantly different pairs based on hit ratio for SVM models.

This chapter introduces four research methods that are not covered in the previous chapters. They are (1) non-parametric statistics, (2) interpretive structural modeling, (3) analytic hierarchy process, and (4) data envelopment analysis. The methods are discussed with examples. The discussion, however, is introductory; so we urge the reader to go through the pertinent references for details.

Staff shortage in the UK National Health Service has a long history, but is widely predicted to become acute over the next decade. Falling enrolment rates in health professional training and restrictions to migrant labour recruitment have brought the, traditionally neglected, issue of staff retention into sharp relief. The purpose of this paper is to represent the first large scale systematic appraisal of the relative salience of recognised headline drivers of employee exodus from the NHS.

The data were collected from an opportunity sample of 1,594 health professionals, managers and administrators employed by the NHS. Participants completed a paired ranking task (Case V method of paired comparisons, Thurston, 1927) to determine the relative importance of eight widely cited reasons for exit. The item set was derived from focus groups conducted as a component of the wider study.

Findings revealed almost universal consensus regarding the primacy of shortage of resources, job demands and time pressure. Pay was ranked lower than predicted. Flexible working arrangements do not presented as a key solution, and there is no support for claims of generational differences.

Survivor population effects could constitute a source of sample bias, i.e. all participants were current NHS employees. It is possible that those who remain may be more resilient or hold different dispositions to leavers. Thus, comparisons by age and grade may not be comparing like with like. Tapping respondent beliefs about the actions of peers can embody some degree of inaccuracy and attribution bias. However, effects can be considered to operate as a source of common, rather than systematic, error across the demographics compared. The medical and dental sample was too small to give confidence in detected differences.

Findings challenge the claim that wider availability of flexible working hours will significantly reduce exit rates. Pay, being a source of dissatisfaction, does not constitute a key push variable in itself, rather its salience reflects the effort reward-imbalance produced by rises in job demands.

Staff shortages in the NHS represent a threat to: public well-being – waiting lists and demand for care; the well-being of who continue to work in the NHS – job demands and resources; the employment prospects of staff who leave involuntarily, e.g. on grounds of incapacity and threats to health and well-being – extending to impacts on their dependents.

Issues of staff retention within the NHS are topical and under researched. The findings provide an up to date picture of the relative influence of headline drivers of early exit from the NHS. The study draws upon a more diverse and comprehensive sample of NHS employees that any other known previous studies of early exit. Findings are of potential international relevance to other State health systems. The authors believe this to be the largest (sample) known application of the method of paired comparisons.

Income from investment properties can fluctuate depending on the state of the economy. The idea that there is always a potential exit (sale) value whenever the property stops performing at its optimum or deflation in the economy will always appeal to investors. To determine housing prices, investors would rely on a direct comparison approach (DCA) of recent substitute sales in the open market. Appraisers use this approach to develop an opinion of value when there is a plethora of recent sales to analyse.

The study was designed to establish the use of the analytical hierarchy process (AHP) approach as a support tool for deciding property appraisals. A case study of an industrial single-storey stand-alone building with grade-level parking in the south-east of Calgary, Canada, was investigated with the AHP approach. The result was cross-referenced with the DCA.

Using a consistency index of 0.077321 and a consistency ratio of 0.085912, the matrix multiplication was determined to be 0.456706. The average valuations derived from the adjusted price per square foot using the direct comparison method and the unadjusted price per square foot using the AHP were deemed the best value estimate in the light of available comparables. The implications of the findings suggest that AHP, as a quantitative technique, can support and validate the use of similar non-recent sale comparables when appraising investment properties with the DCA.

AHP is an alternative aid in quantitatively deciding the most significant value attribute for comparison before subjective adjustments. When intuitively applied in the DCA, these subjective adjustments almost always lead to an overvaluation of properties.

This study aims to describe the effectiveness of two arms of a personality disorder service: a modified mentalization based therapy (MBT) day programme and an open access service‐user network (SUN) support. Both arms utilised therapeutic community principles in service delivery.

Personality disorder subtypes for all patients entering the modified MBT programme were diagnosed at a clinical assessment interview and corroborated through use of a standardized semi‐structured interview (SCID II). All patients were also allowed open access to a service user network community support group (SUN Project). Outcome measures were applied at baseline, mid‐therapy and end of therapy and included self‐report measures of depression, anxiety, general symptom distress, interpersonal function, social adjustment and patient satisfaction. Clinician‐rated measures of general health and functioning were also used. Data analysis used paired sample T‐tests and Wilcoxon Rank Sum tests, depending upon the assessment of parametric or nonparametric tests of trend. The open access nature of the SUN Project demanded a different data collection method. All members received a Standardized Assessment of Personality – abbreviated scale (SAPAS). Two validated empowerment questionnaires were sent to all SUN members that had achieved six months of membership: the first relating to the six‐month period before joining the SUN and the second to the six‐month period after joining the SUN Project. Paired sample T‐tests were used to compare sets of empowerment scores.

Patients who completed 18 months of MBT‐tc treatment showed a statistically significant improvement on the clinician‐administered measures relating to psychological, social and occupational functioning, compared to baseline. Patients also reported statistically significant improvement in using the brief symptom inventory. All SUN members perceived significant increases in empowerment across the five score subscales. No completed suicidal acts were recorded within the period of analysis within either arm of the service.

An integrated therapeutic community day service appears to afford improvements in perceived empowerment and symptom severity for patients. Further data collection with a larger sample is needed to clarify whether these outcomes support the development of a wider integration of the relatively low cost SUN Project model and MBT within therapeutic communities.

The purpose of this paper was to test and explore alignment theory as a guiding principle for human resource development (HRD) by performing an empirical study. HRD scholars, professionals and others have adopted or assumed alignment theory to help explain HRD effectiveness.

Constructs to measure an organisation’s strategic priorities and its HRD practices. A measure of HRD effectiveness was developed. A survey gathered data from 270 employees, managers and HRD staff in a sample of 76 organisations.

The results show that HRD effectiveness does not vary with alignment as predicted. Forms of partial alignment, or the relations of an “odd couple”, are more strongly associated with HRD effectiveness than high alignment.

The use and integration of both normative measures (Likert scale) and ipsative measures (ranking) is necessary to capture alignment, but this limits the inferential statistics available to test validity and reliability. Qualitative data on case studies would be useful to explore alignment issues in context and depth.

Stakeholders in organisations can use the “odd couple” interpretation of alignment as a fresh way to review and explore the opportunities and challenges of managing HRD effectiveness in an era where a narrowing and retrenchment of provisions is occurring and increasing.

This study provides evidence which raises questions about alignment theory and policies intended to increase alignment. It suggests in the case of HRD, an alternative perspective that validates partial alignment can support effective HRD provisions.

The purpose of this research is to develop a distributed system with an innovative supplier selection approach within a mass customization (MC) environment. The aim is to help manufacturers to identify appropriate suppliers for the components, materials and services required within the procedure of product design and manufacture.

To identify the barriers for the supplier selection issues, current researches regarding the issues of supplier selection and MC have been reviewed. Based on the findings, the new supplier selection approach has been developed.

Within the global manufacturing environment, conventional way of appraising suppliers cannot enhance manufacturers' competitiveness advantage over their rivals. It is inevitable for manufacturers to identify appropriate competitive priorities for each of their potential market segments when designing products. Selecting appropriate suppliers is a fundamental issue to fulfill manufacturers' development strategy. The approach will enhance supplier selection efficiency and flexibility under the MC environment, enabling manufactures to avoid or minimize risks when external conditions change.

The case study is limited to selecting suppliers of two components for an ink cartridge, however, the general approach is applicable to other type of products.

The whole concept of this selection system is to provide a supplier selection approach for MC environment by utilizing the web‐based technologies to deliver a means which enables geographically dispersed functions making supplier selection more efficiently. Manufacturers can utilize this approach to evaluate and to find most appropriate suppliers based on various situations.

The supplier selection approach focuses on the general supplier selection issues incorporating with product market position and development directions issues for MC, which provides a more dynamic and robust method to select and evaluate potential suppliers according to a range of conditions.

The food industry is directly related to the health of humans and society and also that little attention has been paid to the assessment of sustainable supply chain risk management in this area, this will be qualified as an important research area. This study aims to develop a framework for assessing the sustainable supply chain risk management in the realm of the food industry (confectionery and chocolate) with a case study of three generic companies denotes as A1–A3. The proposed risk management was evaluated in three aforementioned manufacturing companies, and these three companies were ranked by the Fuzzy-Weighted Aggregated Sum Product Assessment (F-WASPAS) method in EXCEL.

The evaluation was carried out using integrated multi-criteria decision-making methods Best-Worst method (BWM)-WASPAS. Via an extensive literature review in the area of sustainable supply chain, sustainable food supply chain and risks in this, 9 risk criteria and 59 sub-criteria of risk were identified. Using expert opinion in the food industry, 8 risk criteria and 39 risk sub-criteria were identified for final evaluation. The final weight of the main and sub-criteria was obtained using the F-BWM method via LINGO software. Risk management in the sustainable supply chain has the role of identifying, analyzing and providing solutions to control risks.

The following criteria in each group gained more weight: loss of credibility and brand, dangerous and unhealthy working environment, unproductive use of energy, human error, supplier quality, quality risk, product perishability and security. Among the criteria, the economic risks have the highest weight and among the alternatives, A3 has obtained first ranking.

Modeling of risk for the food supply chain is the unique contribution of this work.

This study aims to identify and prioritize various growth-accelerating factors in the Indian automotive industry. It further develops a hierarchical model to examine the mutual interactions between the factors, their dependence and their driving power.

This study first identifies the growth-accelerating factors and then uses the modified total interpretive structural modeling (m-TISM) framework, which is an extended version of TISM. It further uses MICMAC analysis to analyze the mutual interrelation between the identified factors.

This study highlights the interrelation amongst the factors using m-TISM model. A hierarchical model shows the level of autonomous, dependence, linkage and independent factors considering the Indian automotive industry. This study also provides the understanding related to the interdependence of growth-accelerating factors.

The government and practitioners could evaluate the growth-accelerating factors which have higher driving power for implementing efficient policies and strategy formulation. By implementing m-TISM model in the Indian automotive industry, auto manufacturers can become more productive and profitable. Future studies could use other methods such as expert opinion to derive the factors, and further model could be verified using structural equation modeling technique.

This study uses a novel m-TISM framework for the analysis of growth-accelerating factors in the context of the Indian automotive industry. It further provides a detailed theoretical and conceptual understanding relating to the philosophy and establishes an interrelation amongst these under-researched growth-accelerating factors.