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This New Articles Channel contents the latest articles published in Inderscience's distinguished academic, scientific and professional journals.



 



A study to identify the stock market participation and investment portfolio preferences of legislators
This study identified the determinants of legislator participation in the stock market and investment portfolio preference. All of the data used for this study were hand collected during 2010-2013 from the property declarations provided by legislators to the Sunshine Acts website of the Control Yuan, Republic of China (Taiwan). Statistical analysis shows that all of the legislators studied have a high education level and relatively uniform above-average assets. The study findings indicate that the stock market participation of legislators is strongly associated with political orientation, higher education level, and higher wealth than median citizens; the two most important factors influencing legislators to participate in the stock market are party and wealth. Furthermore, the wealth and education levels of Kuomintang party legislators are obviously higher than those of legislators of the other parties. The empirical results show that legislators prefer stocks in the electronic and others categories more than those in other categories. This information provides evidence that legislators use their political power in ruling legislative processes to impact the stock price of listed-stock firms, thereby benefitting their investments. In conclusion, this work is focussed on helping voters to understand the implied information behind the ruling effect of legislators.



Individual differences and knowledge acquisition capability in joint ICT project teams in Malaysia
This study investigates the underlying differences in individual knowledge acquisition capabilities. Drawing on the individual dimension of absorptive capacity, we clarify the antecedents of local team member's capability to acquire foreign partner's knowledge in joint ICT project team. Specifically, we proposed prior experience, learning goal orientation and need for cognition as antecedents to local employee's abilities to (1) recognise the value of and (2) assimilate foreign partner's knowledge. The hypothesised model was validated by the results of the structural equation modelling conducted using the data gathered from a cross-sectional survey of 205 local team members of joint ICT project teams in Malaysia. Most of the hypothesised relationships were supported, with further discussion focused on the non-supported relationships. Finally, the theoretical and practical implications of these findings were explained.



A new model for measuring the impact of patent value growth trajectory
Patents play a crucial role in determining the economy, industrial development, and R&D of a country. Extant patent literature has focussed on the decision model of the econometric method, which enables researchers to understand the short-term explanatory power of various factors for patent value. However, this method cannot be used to observe the degradation rate and growth trajectory of the patent value. In this study, we proposed a dynamic time-series design to further explore the growth trajectory of patent value by using the latent growth curve model. The results show that backward citation, non-patent reference, and number of claims positively affect the patent value growth rate. Patent disclosure information and characteristics are crucial for exploring the value of patents. Patent value is typically established on the basis of knowledge stock, patent breadth and international linkage. Therefore, this study applied an experimental map to validate the linkage relationship of the studied dimensions to provide governments, industries and patent assignees with some practical suggestions.



Efficiency differences of government investment projects: an application of a DEA and Tobit analysis
Previous studies have evaluated the investment efficiency of the government from a macro perspective, but few studies focus on specific projects with government investment. Therefore, this paper presents a method that combines data envelopment analysis and Tobit regression, which highlights the sources of funds, social benefits and influencing factors. It concludes that the overall efficiency of government investment projects (GIPs) is very high, but the excessive input and insufficient output are widespread and big improvement spaces exist; the public requirements rank first of all the influencing factors. This paper can provide references to guide the GIPs to gradually obtain better investment efficiencies.



Moving towards sustainable end-of-life tyre management from the cost and environmental perspectives: a case study of Thailand
This study aims to describe the current problems of the end-of-life tyre system, and propose possible end-of-life tyre management program for Thailand based on cost and environmental perspectives. This study can showcase the process for countries where end-of-life tyre management has not yet been implemented or countries that are facing problems with their end-of-life tyre management systems. Research findings indicate that, without an end-of-life tyre program through which customers would be charged a treatment fee, it is not feasible for tyre collectors to collect the used tyres that are discarded more than 150 km from a recycling plant. To increase the end-of-life tyre treatment percentage, a treatment fee must be collected, and the free market system should be used. Subsidy settings, estimated at approximately 20 baht/new tyre or $0.6/new tyre for the collection, processing and use of scrap tyres, should be configured to ameliorate the overall process.



Assessment of species diversity and impact of pollution on limnological conditions of River Ganga
The present study on dynamic flow of River Ganga was undertaken for a period of one year from October 2012 to September 2013 to assess the species diversity and impact of pollution on limnological conditions of River Ganga in Uttarakhand, India. In the present study water samples were collected from two important sampling sites Shivpuri and Pashulok barrage of River Ganga in Rishikesh. A total of three groups were identified, total diatoms, green algae and blue green algae, including six major species belonging to diatoms. Higher concentration of phytoplankton species at site 2 indicates polluted nature of river water and can be used as an indicator of organic pollution in the river for domestic use but having positive effect on the growth of these ecological indicators of aquatic ecosystem.



Sensitivity and uncertainty-based evaluation and simulation of MIKE SHE model in Guishui River Basin, Beijing, China
In the process of building a hydrological model, some basin feature parameters are expressed inaccurately. It is an important way to construct models and estimate the uncertainty parameters for evaluating the uncertainty of the overall output. In this paper, an uncertainty-based study was calibrated and evaluated the comprehensive distributed model MIKE SHE to hydrological data in the Guishui River Basin, Beijing of China. The generalised likelihood uncertainty estimation (GLUE) method was used to quantify uncertainties originating from the use of discharge observations and the presence of equifinal solutions. Monte Carlo sampling is randomly generated to 10,000 parameter sets during GLUE calibration. MIKE SHE parameter sets are identified and 5% and 95% uncertainty bounds for monthly streamflow are calculated. The behavioural values of nine individual parameters for MIKE SHE were explored against the likelihood measure values. The results show that more than 50% observations in calibration period fell within the corresponding uncertainty bounds, suggesting a similar level of model performance. The simulation results are corresponded better with the measured flow, but still need to be improved for higher accuracy. There are some relative sensitive and insensitive parameters in the result of uncertainty analysis.



Application of ensemble methods for classification of water quality
Groundwater pollution in Shoosh Aquifer located in Khuzestan Province, Iran, was considered, using an eight years time period data set collected from 30 sampling wells. Cluster analysis rendered a dendrogram where 30 sampling wells were grouped into three statistically significant clusters. The classification methods, k-nearest neighbour and classification tree, were utilised to classify sampling stations, with respect to the level of pollution. The optimum tree depth and number of neighbours were determined by 4-fold misclassification error which both had an error of 0.167. An ensemble was created using these base classifiers. In addition, considering the small sample size of our data in this study, random subspace as a feature selection method was amalgamated with k-nearest neighbour ensemble. The misclassification errors of classification tree and k-nearest neighbour ensembles were 0.13 and 0.10, respectively. The results of this study confirmed the high accuracy of ensemble methods for data classification.



Drought assessment using standardised precipitation evaporation index and its association with southern oscillation index in the Northwestern Bangladesh
The trend of drought in the northwestern region of Bangladesh was analysed in this study. To analyse the trend of the multiscalar drought index standardised precipitation evaporation index (SPEI), Mann-Kendall's test and Sen's slope estimator have been used. Assessment of variability of SPEI was conducted by means of the continuous wavelet power spectrum. Significant variability of 6 month scale SPEI was found at 16 to 32 months and 32 to 64 month period from almost 1987 to 2008. To grasp the influence of the southern oscillation index (SOI) on a 6 month scale SPEI, statistical tool wavelet coherence (WTC) has been used. Significant wavelet coherency was observed between SOI and 6 month SPEI at higher periodicity and short time span. The outcomes from this study could assist engineers of agriculture and the water resources sector to establish strategies in Northwestern Bangladesh.



Geo-hydroclimatological-based estimation of sediment yield by the artificial neural network
An artificial neural network (ANN) model is proposed for the estimation of sediment yield in Lake Urmia sub-basins. The number of model parameters were extended as far as possible to all geometric, geological and hydroclimatological parameters of the sub-basin. Also, various ANN structures, learning rules, and transfer functions were examined. The examinations show that extended delta and hyperbolic tangent were the best functions for the proposed ANN model. The best structure for the ANN model is a triangle with two hidden layers, containing five neurons in its first and three neurons in its second hidden layer. The comparison between the proposed and regional analysis models showed a notable increase in the accuracy by using the proposed model. Mean absolute error and the maximum absolute error of the estimation reduced to 2.5% and 3% of those regional analysis models, respectively, and therefore ANN model is recommended for sediment yield estimation.



Assessing the water quality in coastal aquifer of Chennai, India - a case study
To assess the groundwater quality and seawater intrusion in Chennai, the study has been carried out in June 2011. All the physico-chemical parameters were measured. Hard rock and sedimentary rock formation has been determined using the sodium/chloride ratio. Cross plots of bicarbonate%chloride versus TDS indicate that water samples in S1 zone were saline in nature. According to the hydrochemical analysis, except water samples in S2 zone, other groundwater samples are suitable for domestic purpose. Langelier saturation index has been used to identify the nature of water, especially the acidity or basicity of water. Seawater mixing index has been calculated using the concentrations of sodium, magnesium, chloride and sulphate. From this study, we concluded that high levels of sodium in S1 and S5 indicate that seawater intrusion takes place in this zone. Based on Gibbs calculation, rock water interaction was dominant in S3 and S4 zones, and evaporation is dominant in S1, S2 and S5 zones. Seawater mixing index was found to be a maximum of 8.72% in S1 and S2 zones.



Chinese temporal relation resolution based on Chinese-English parallel corpus
This paper studies the annotation of temporal objects such as EVENT-type and TIMEX3-type elements in Chinese text based on Chinese-English bilingual parallel corpus. We propose and implement a temporal relation resolution (TRR) engine for Chinese text. We use temporal recognition and normalisation tools to annotate the English text, and then map the annotations of English text to the Chinese text by word alignment. The constructed Chinese TimeBank could be used for TRR research based on TimeML in Chinese text.



A node localisation approach based on mobile beacon using particle swarm optimisation in wireless sensor networks
In most applications of wireless sensor network (WSN), the positions of nodes are important for environmental sensing, search and rescue, and geographical routing and tracking, and so on. An accurate and simple scheme of mobile-assisted localisation for the unknown wireless channel loss model is proposed in this paper. One localisation algorithm is implemented using the particle swarm optimisation (PSO). For improving the localisation performance, the path planning method based on a kind of grid scan is suggested. To evaluate the proposed localisation algorithm, the results of localisation algorithm based on multilateration and the iterative multilateration are also provided. Furthermore, the weight factor τ in the constructed fitness function is also discussed. Overall, it is obtained that the localisation effect of the proposed scheme is better than that of the localisation scheme based on the multilateration and the iterative multilateration for the unknown wireless channel loss model by the simulation experiments.



A comprehensive performance study of HTML5-enabled WebApps
Web applications (WebApps) built on top of HTML standards have the advantage of cross-platform portability. However, the user experience in terms of both functionality and performance provided by current generation WebApps is not comparable to native apps running on iOS or Android. Despite significant functional extensions in the new HTML5 standard, the poor performance of WebApps has not been addressed. To promote the adoption of WebApps, it is important to study their performance comprehensively. In this paper, we take Google Chrome as the target browsing engine, and evaluate its performance with a set of popular web pages and WebApps. We make in-depth analysis on the major performance-contributing aspects in a browser engine. Our study exposes a number of interesting observations, from which we make reasonings and provide suggestions for the optimisation of browser engines, as well as guidelines for developing efficient web-based applications.



Power of person-job fit: emotional labour for salespeople and its relation to job satisfaction
This study focused on the effect of person-job fit on the relationship between emotional labour and job satisfaction among salespeople in Turkey. Using survey data obtained from 204 salespeople working in different sectors, we analysed job satisfaction, person-job fit and three components of emotional labour, which are deep acting, surface acting and naturally felt emotions. We found that job satisfaction has a significant relationship positively with naturally felt emotions and negatively with surface acting. Although no significant moderation effect has been found for person-job fit, we found that person-job fit significantly mediates the relationship between job satisfaction and naturally felt emotions as well as the one between job satisfaction and surface acting.



Country of origin, familiarity, the perceived difference and MNC attractiveness
Is MNC's country of origin a factor affecting its attractiveness to potential applicants? Are MNCs from a country with a favourable image more attractive than MNCs from a country with a less favourable image? This study examined whether MNCs' country of origin influences its attractiveness as potential employers. The findings of this study suggest that potential applicants who have positive image towards a country are more likely attracted to apply for MNCs from that country.



What has emotional intelligence got to do with it: the moderating role of EI on the relationships between workplace incivility and mental health?
Workplace incivility (WI) has detrimental consequences on victims and has been linked positively to depression, anxiety and stress. However, emotional intelligence (EI) which involves the ability to manage one's and other's emotions has been positively associated with lower symptoms of depression, anxiety, and stress; suggesting that EI may act as a buffer against stressors. Therefore, the present study tested a model which proposed that EI would moderate the relationships between WI and depression, between WI and anxiety, as well as between WI and stress. Data was collected using an online survey from 184 Australian adult workers. Results indicated that EI moderated the relationships between WI and depression and between WI and stress. Although a main effect was found between WI and anxiety, EI did not significantly moderate the relationship between WI and anxiety. Implications and future directions were discussed.



How and why emotions matter in interprofessional healthcare
Institutional theory draws attention to organisational rules-of-thumb that guide individual action and legitimacy - this includes the use of emotion. Within medicine, emotion is largely underemphasised. The introduction of interprofessional practice (IPP) poses an under-explored potential challenge to these rules-of-thumb. Drawing on Foucault, this article examines: 1) the emotional discourse in tweets from member-based organisations for healthcare practitioners; 2) themes in interviews and a focus group with practitioners-in-training. While the tweets largely illustrated the illegitimacy of emotion within healthcare, the practitioners-in-training indicated the importance of emotions and emotion work to teamwork. These findings suggest a 'cultural clash' and demonstrate that emotions matter in IPP.



Modelling of business processes for software as a service
The traditional approach to business process modelling frequently results in large models that are difficult to change and maintain. In cloud-based environment, business dynamics are mandating that business processes normally be increasingly responsive to changes. This demands business process should be highly modular, scalable and flexible for cloud-based applications. Further, in cloud-based business environments, besides describing new capabilities, process models should also define how those capabilities can be integrated with the existing systems. In this paper, a hierarchical graph-based specification called business component graph for SaaS (BCGS) has been proposed to address those issues. The proposed BCGS, formally, realises the business components for software as a service (SaaS)-based applications. BCGS represents the complex business logic design as a set of business components and their inter-relationships. Here, business component is defined as methodical integration of business processes and business rules. This proposed integration approach facilitates high scalability and reusability of constituent elements of business components and ensures the consistency between processes and business rules. Moreover, this paper also includes the service orientation of the proposed concepts in SaaS framework. A detailed case study of BCGS also has been illustrated to show the expressiveness of the proposed concepts.



Methodological proposal for process mining projects
Process mining is a discipline that allows organisations to discover, analyse and improve their business processes. Although the techniques, algorithms and software packages intended for the application of this discipline have been evolving positively, challenges have appeared as it is applied to process improvement projects. This is because most of the methodological approaches developed for its application provide general guidelines, but they do not define the specific steps and tactics for the challenges that a practitioner must go through when facing a process redesign project through process mining. The current development contributes to improving the applicability of this discipline by designing a methodology that allows professionals and organizations to conduct process mining projects. The methodology is illustrated by applying to three case studies, after which it was subjected to evaluation by the personnel of the companies that participated in its application. The limitations of the designed methodology and future research perspectives are finally discussed.



Defending against malicious insiders: a conceptual framework for predicting, detecting, and deterring malicious insiders
Malicious insiders are posing unique security challenges to organisations owing to their knowledge, capabilities, and authorised access to information systems. Data theft and IT sabotage are two of the most recurring themes among crimes committed by malicious insiders. This paper has two aims: first, we investigate the scale and scope of malicious insider risks and explore the impact of such threats on business operations. Secondly, we present a conceptual design of the insider threat security framework (ITSF) that is able to provide self-protection capabilities. Our objective is to propose protection mechanisms that could minimise risk and battle unique threats posed by potential malicious insiders. Although as yet untested, the ITSF will treat every employee or user of a system as a prospective hacker. We believe this approach is feasible, affordable and assures compliance with systems security requirements as well as regulatory standards.



Enterprise ontologies for assessing information exchange and information quality in healthcare
Although the quality of information exchange is an important component in any organisation, this topic receives little attention in the literature. Expanding networks among organisations introduce increasing complexities when it comes to information exchange. However, information quality (IQ) assessment and improvement is poorly understood within the information exchange process. To address this gap in the literature, we apply design engineering methodology for organisations (DEMO) - a prominent enterprise ontology for organisational dynamics analysis - to examine causes of poor information exchange quality. An application of these techniques is carried out in a hospital emergency department. Evaluation is conducted through interviews and focus groups. Results suggest that this set of techniques elucidate IQ and information exchange problems and improvement potentials. Examination reveals the techniques are able to identify the causes of low information exchanges. The results provide insights for improving information exchange strategies.



Middleware platform for the synchronisation of mobile medical data
Several healthcare providers are adopting mobile technologies to facilitate remote transfer of the electronic health record (EHR). This paradigm is called mobile health (mHealth) and can enable caregivers to collect and transmit patient data in remote healthcare delivery scenarios. The challenge however is that mobile devices use wireless mediums such as Wi-Fi and 4G and these communication channels can experience network fluctuations and services unavailability. Also, the services unavailability can lead to difficult decision-making by the caregivers. Thus, this paper proposes a middleware platform that synchronises the EHR between the mobile devices of caregivers and the health information system (HIS) in soft-real-time. Specifically, the proposed system explores the impact on bandwidth consumption using two medical data transfer approaches: whole state medical data propagation, and the update only medical data propagation. The experimental results show that the latter approach facilitates faster medical data synchronisation and optimal utilisation of the wireless bandwidth.



A supervisory control method of upper limit constraints for workflow nets
This paper deals with supervisory control in workflow nets. Workflow nets are a particular class of Petri nets, but have analysis techniques for more properties, e.g., logical correctness called soundness. We tackled the following problem: given a (plant) workflow net (NP, M0P) and a constraint specification, construct a workflow net (NS, M0S) which consists of NP and a supervisory controller (Petri net) NC which satisfies the constraint specification. We propose a solution method for the problem. It consists of: 1) a sufficient condition for the existence of (NS, M0S) based on place-invariants; 2) a procedure to construct (NS, M0S). The advantage of our method is to enable us to take account of logical correctness which may be lost by supervisory control. We also illustrate the proposed method with an application example and show its usefulness.



RAILQUAL: a multiple item scale for evaluating railway passenger service quality and satisfaction
It was found that leading models and instruments in the area of service quality tend to be based on exploratory factor analysis and have not been informed by advances in measurement theory, particularly co-variance-based structural equation models. The diverse nature of requirements of stake holders in railways makes it extremely difficult to decide upon what constitutes quality in railway passenger services. Hence, identification of common minimum quality items suitable for all passengers will help design the system and there by improve passenger satisfaction. To address this issue, we applied the recent advances in measurement theory to the dataset and compared two different modelling methods namely exploratory factor analysis and confirmatory factor analysis. Based on the psychometric scale development approaches, this research conceptualised, constructed, refined, and tested a multi-item scale 'RAILQUAL' that examined key factors influencing railway passenger service quality. Through qualitative and quantitative studies in three phases a 18-item, six-dimensional 'RAILQUAL' model was developed. RAILQUAL is a measuring instrument for service quality and passenger satisfaction in Indian railways which can be applied across other railways also worldwide with some minor modifications locally.



A multi-criteria decision model for the selection of professional service innovative organisation
The purpose of this paper is to demonstrate an application of a multi-criteria decision model (MCDM) for the selection of best professional service organisation (PSO) from a number of available alternatives based on service innovation elements. For that purpose, a conceptual model for MCDM has been adopted. Different service innovation elements are classified into critical, objective and subjective factors in the evaluation process and the selection procedure is demonstrated with a hypothetical case. The decision to select a particular professional service organisation is very important when multiple professional service organisations are available. A quantitative basis for comparison and selection of the professional service organisation among a host of alternative professional service organisation could greatly impact on the eventual organisations brand image. Thus, an algorithm - performance value analysis (PVA), for the selection of PSO has been developed from literature. The study expands the scope for managers in selecting the best professional service organisation.



Emotional management and behavioural inhibition system in service failures
This study incorporates individual psychological differences - emotional management ability, behavioural inhibition system (BIS) and appraisal of service failure into the framework model of consumer coping. The model was tested on a sample of 301 respondents. Structural equation modelling was employed to assess data and the six hypothesised relationships. The findings reveal that customers' emotional management ability does affect their assessment and their behavioural inhibition system sensitivity. Severity perceived is positively linked to active and expressive coping while diminishing avoidance coping. Furthermore, BIS sensitivity leads to a greater intention to use both expressive and avoidance coping mechanisms in dealing with service failures. These results propose implications for how service providers should act in service recovery in order to obtain the most optimal outcome.



A survey on selected supplier issues in Indian manufacturing organisations
The objective of this paper is to identify and investigate the various supplier selection (SS) and supplier evaluation (SE) benefits, SS and SE criteria, supplier development (SD) benefits, SD criteria and SD activities, and rank them according to the level of importance. This paper reports the findings of a survey carried in 150 Indian manufacturing organisations over five sectors namely automobile, machine tool/equipment, electrical/electronics, process and fast-moving consumer goods (FMCG) through a well designed and validated instrument/questionnaire. The results of this survey give the top ten SS and SE benefits, SS and SE criteria, SD benefits, SD criteria and SD activities according to their level of importance. The practitioners and academicians working in this area can use the results of this survey to decide the importance level of these factors in their organisation. This study can be precise for a specific sector or type of industry by modifying the instrument/questionnaire, based on the opinion of experts from the specific sector or type of industry.



Product allocation of warehousing and cross docking: a genetic algorithm approach
In spite of the vast amount of researches on product allocation to distribution centres, allocating different products by considering different scenarios to plan the cross docking and warehouse operations is less investigated. To fill this gap, this research was conducted rationally to allocate different products to a distribution centre aligned with analysing different scenarios. The research case study was a distribution centre located in the South East of Asia supplying 19 different products (Li et al., 2008). A genetic algorithm was used to allocate different products to both cross dock and warehouse considering processing cost, demand, capacity and related constraints.



Application of multi-criteria decision making methods for balanced scorecard: a literature review investigation
Balanced scorecard has been selected as an organisation performance measurement tools in two last decades and implemented in both industrial and service companies. Using BSC and application with decision-making tools such as MCDM has received more attention by researches. In this paper, we have reviewed the literature on the balanced score card and MCDM methods. We have tried to identify different perspectives in terms of which to classify the existing papers. The result shows that about 30% of all researches about BSC have used MCDM tools to analysis and decision. Moreover, it is revealed that the number of publications since 1992 has a positive trend. More concentration has been taken in account for AHP, ANP and TOPSIS methods which is about totally 60% of the researches. Finally, this research represent that Iran and Taiwan are ranked as first and second with totally about 60% of the publication in this field of study. It also can be pertained that 65% of the questionnaires have been filled by experts from industrial or service companies.



A study on technique of inventory management system with respect to aviation spare parts
In the aviation industry, reliable spare parts supply is essential for continuous aircraft operations. This paper reviews one of the inventory techniques in the aviation industry. Spare parts that are of high value are repaired and returned to stock after removal from the aircraft. This study is to analyse the inventory level technique for helicopter spare parts used for manufacturing. Around 677 items are taken into considerations for analysing the inventory of one manufacturing unit. The paper represents inventory planning method that calculates optimum level of inventory management in aviation industry. This paper is based on exploratory research with secondary data collected from a company based in Thailand. The purpose of this classification is to ensure that purchasing staff use resources to maximum efficiency by concentrating on those items that have the greatest potential savings, selective control will be more effective than an approach that treats all items identically.



The effect of open innovation on technological entrepreneurship capabilities in high-tech firms: a fuzzy analysis
Technological entrepreneurship capabilities (TEC) offer a set of capabilities that help a firm to perform better in the exploration and exploitation of environmental opportunities. Open innovation (OI) concept is based on the knowledge in- and outflows across organisational boundaries. This study aims to discuss the link between OI and TEC. Literature review reveals a partial correlation between TEC and OI. The effort involve in identifying a set of relations between OI mechanisms and TEC dimensions in high-tech firms. A conceptual model and three scenarios have been investigated using fuzzy cognitive mapping. The scenarios deal with the effects of 'out-in', 'in-out', and coupled mechanisms of OI on TEC, respectively. Results revealed that implementing OI improves TEC, but the exploitation of 'in-out' mechanisms would leave a greater effect on technology paradigm and linkage dimensions, whereas the 'out-in' mechanism would rather affect the learning capabilities.



Stakeholder enrolment and business network formation: a process perspective on technology innovation
Entrepreneurial healthcare firms rarely possess all requisite resources to successfully develop and deploy knowledge-intensive technological innovations. It is critical for such firms to understand, manage, and cultivate networks of partners to gain access to essential strategic resources and to shape the viability of resultant networks in a mutually beneficial way. Firms accomplish this through an intentional process of stakeholder enrolment under conditions of risk and uncertainty. This paper examines a multi-year case study about the development and deployment of a personal health management system (PHMS) within the US healthcare industry in order to illustrate how organisational goals shape stakeholder enrolment processes and how outcomes affect the way in which networks form, adapt, and evolve. This study integrates and draws upon business network adaptation and stakeholder enrolment processes to present a theoretical framework for conceptualising and understanding entrepreneurial networks for technological innovations.



Do relationships facilitate growth in small technology firms?
Prior literature argues that business relationships provide firms with competitive advantage. However, there is a need for more empirical evidence on whether and how they influence the growth of small technology firms. Through a statistical analysis of 90 small technology firms in Finland, we explore whether the scope and scale of customer relationships and the level of networking with partners can be associated with the financial growth of a firm. The results show that the growth of operating income in small technology firms is linked with their scale of customer relationships; i.e., growth firms employ a broader scale of customer relationships compared to non-growth firms. Hence, we suggest that focusing on deeper relationships with few customers may hamper the firm's financial growth, and entrepreneurs and managers of small technology firms should aim at a broader customer base even in niche markets.



How academics' engagement in university-industry interactions influences their start-up intentions: a study on nanoscientists in Turkey
This paper investigates the start-up intentions of nanoscientists at Turkish universities. It specifically focuses on how (i) different forms of university-industry engagements such as informal interactions, research-based interactions, consultancy and academic interactions, (ii) the nature of research done by university scientists such as doing applied research or having an invention (or research outcome) ready for commercialisation and (iii) role models and motivations influence nanoscientists' start-up intentions. Data were collected from nanoscientists employed at Turkish universities through a questionnaire survey. Our results suggest that interactions with industry mostly are not related to start-up intentions of nanoscientists. However, doing applied research and the perceptions of academics regarding to the commercial value of their research outcomes are positively related to their entrepreneurial intentions. On the other hand, experience and the number of nanotechnology publications are negatively related to entrepreneurial intentions.



Filter-based recursive Bayesian algorithm with modified covariance resetting for non-uniformly sampled data systems
To identify a system with non-uniformly sampled data, a recursive Bayesian algorithm combined dynamic filter with covariance resetting is proposed. First, the input-output data is filtered by the estimated noise transfer function, and the system is decomposed into two fictitious sub-systems with a low dimension. Second, the estimated variance of the noise is employed in the proposed algorithm to improve the estimates. Furthermore, an efficient covariance resetting strategy is integrated into the algorithm to increase the convergence rate. Finally, the proposed algorithm is validated by a numeric example.



Multi-finger myoelectric signals for controlling a virtual robotic prosthetic hand
The paper investigates how multi-finger myoelectric signals could be used to control a virtual robotic prosthetic hand created by using robot operating system (ROS). Both off-line and online experiment phases are conducted by using ten electrodes and performing eight selected multi-finger motions on four healthy subjects. Classification accuracy and confusion matrix of eight time domain (TD)-features and two algorithms are compared during the off-line phase. Then the delay time and accuracy of online control of six selected TD-features and support vector machine (SVM) algorithm are presented with and without visual feedback from the virtual robotic prosthetic hand system. The experimental results show that different feature extraction principles have significant influence on online experiment performance when using SVM without visual feedback (SVMO), and the SVM with visual feedback (SVMW) has improved the online classification and recognition accuracy of eight multi-finger motions through all selected TD features.



Experimental implementation of MIMO model predictive controller-based second order divided difference filter for nonlinear systems
In this paper, we propose an experimental implementation of a nonlinear predictive controller based on the second order divided difference filter (DDF2) which is a derivate-free estimator. The used state estimator avoids the determination of Jacobian matrices required with the extended Kalman filter (EKF) for an easy implementation with nonlinear systems. In addition, the second order Stirling's interpolation of the estimator allows a more accurate a priori state prediction. A constrained nonlinear predictive controller-based DDF2 is designed to control a multivariable three-tank system. In order to generate the control signals, the controller solves a nonlinear objective function. To overcome the offset output error that appeared due to the inaccuracy of the system model, an internal state model correction scheme is adopted at each iteration. Practical results show the reliability of the proposed method in state estimation, setpoint tracking, and smooth control signal generation. The proposed controller outperforms the model predictive control based on linear state space model derived from the linearisation of the system model around the same setpoint trajectory.



Evolutionary game theory for multiple-mobile-robot flocking systems containing mutations
This paper studies some major issues encountered in the evolution of strategy choice for a multiple-mobile-robot flocking system that contains mutated individuals. The main objectives of the study are to analyse the effects of mutated strategies on the dynamic performance of the system (i.e., the convergence time and stabilisation time) and to explore the strategy evolution and distributions in flocking movement. Accordingly a payoff matrix directly related to these dynamic performance indicators is designed. The simulation results indicate that the system can achieve common consistency for any given initial conditions, and the final evolution reveals some degree of inherent regularity in the values of the payoff matrix elements. Furthermore, the simulation results confirm the validity of evolutionary game theory to enhance the dynamic performances of a system. The procedure developed from the work can facilitate group-based strategy selection as a creative solution.



Simplified algorithm of an adaptive fuzzy backstepping control for MIMO uncertain discrete-time nonlinear systems using a set of noisy measurements
This paper presents a simplified algorithm of an adaptive fuzzy backstepping control (AFBC) for multi-input multi-output uncertain discrete-time nonlinear systems with uncertainties viewed as the modelling errors and the unknown external disturbances, and the observation of the states is taken with measurement noises. The simplified algorithm of the proposed AFBC is designed as follows. The explosion of complexity problem due to repeated computation of nonlinear functions is removed to derive the simplified algorithm at the first stage, secondly the number of the adjustable parameters is reduced by using the fuzzy inference approach based on the proposed simplified extended single input rule modules, and finally the simplified weighted least squares estimator is constructed by reducing the computational burden of the estimation for the un-measurable states and the adjustable parameters. The effectiveness of the proposed approach is indicated through the simulation experiment of a simple numerical system.



Varying-sliding condition adaptive controller for a class of unknown discrete-time systems with data-driven model
In this paper, an adaptive controller is developed based on discrete-time sliding mode control with a varying-sliding condition. The controlled plant is considered as an unknown system dynamic. The dynamic model is estimated by a data-driven scheme with pseudo-partial derivative (PPD) of plant's input-output. The convergence analysis of estimated model is established under reasonable assumptions which exist in practical systems. Furthermore, the accuracy of the estimated PPD is verified by the computer simulation system. The control law is designed by the data-driven model and time varying-sliding gain which is proposed to guarantee the convergence of tracking error. A prototype DC-motor current control demonstrates the validation of the proposed control scheme as experimental results. The comparative results with the conventional data-driven controller represent the effectiveness and the applicability of the proposed controller.



Small morphing wing aerial vehicle dynamic modelling basing on simulation and flight test
Morphing wings can be more stable and more robust to gust in the flow of low Reynolds number compared with normal fixed wings. In contrast to big airplanes, small ones with morphing wings can rely on passive wing deformation to reduce disturbance rather than active control by multi-control surfaces. Engineering modelling for the prototype in the paper ignores aeroelastic effect because of the small deformation amount in terms of static aeroelasticity and high modal frequency in terms of dynamic aeroelasticity. Aerodynamic coefficients are determined through flight test and software calculation. An accurate trim condition is solved using a 6DOF flight model. The preciseness of the trim result is proved by comparing experiment results. The longitudinal and lateral state-space equations benchmarked against trim point is built. Dynamic response of the non-control perturbation motion are analysed.



Fault tolerant trajectory tracking control design for interval-type-2 Takagi-Sugeno fuzzy logic system
The interval type-2 Takagi-Sugeno fuzzy logic system (IT2 TS FLS) has been recently used in several control applications to handle nonlinear systems subjected to various uncertainties. This paper considers the problem of fault tolerant control (FTC) for discrete-time nonlinear system described by IT2 TS fuzzy model affected by actuator faults via state feedback control method. The IT2 fuzzy controller is designed to compensate the effect of the fault such that the stability of the closed loop system is ensured. Stability conditions for the IT2 faulty system are presented in terms of linear matrix inequalities (LMIs). Simulation results performed on the three tank system are presented to demonstrate the efficiency of the proposed controller over the traditional type-1 fuzzy fault tolerant controller.



Does correlation matrix influence prioritisation of the results of house of quality? The case of a manufacturing company
The aim of this article is to find whether correlation matrix influences prioritised results of house of quality (HOQ). For this purpose, prioritisation of EFQM enablers in the GasSouzan Company before and after computing correlation coefficients has been compared. First, the relationships among the criteria of the roof of HOQ which are the criteria of EFQM enablers have been determined and then, the correlation of each criterion has been calculated based on the priorities. Findings indicate that the correlation coefficients of criteria are close to each other and do not have considerable impact on the priorities.



Evaluating TQM adoption success factors to improve Indian MSMEs performance using fuzzy DEMATEL approach
With the advent of liberalisation, the manufacturing sector in India has grown tremendously but it still lags behind its other Asian neighbours by huge gap especially Indian micro, small and medium enterprises (MSMEs). India being a largest market in terms of production and consumption, the role of MSMEs cannot be under estimated. Contribution of MSMEs in manufacturing, exports and employment are significant. Quality management practices are very essential in order to improve financial, operational and strategic position of the organisation. Many organisations attained substantial benefits by employing quality practices and derived higher customer satisfaction. Quality dimension is the only available options with the organisations in today's competitive market where customers' demands better products and services at lower price. Since India want to become a manufacturing hub in the world through Make in India Plan 2015, hence, it is necessary to investigate total quality management (TQM) adoption success factors. This study identifies TQM adoption factors and evaluates them in order to improve the performances of Indian MSMEs. Fuzzy DEMATEL-based approach has been applied to find out the most important factors among them. By using fuzziness in decision-making impreciseness and vagueness of the decision makers can be considered easily.



Investigating the impact of quality management systems on business performance
In this paper, we study the problem of assessing the impact of quality management systems (QMS) on business performance of organisations. Several mediatory variables linking QMS and business performance namely information quality, design performance, operating and environmental performance, supplier relationships, customer relationships, product quality, service quality, and competitive priorities are investigated. Twelve hypotheses linking the impact of these factors on each other, QMS and business performance are proposed. Based on these hypotheses, a questionnaire instrument is developed. A survey study is conducted with industry professionals involved in quality management and engineering and the results analysed using factor analysis and regression analysis. The results of our study show that organisations often implement QMS as a catalyst for change and use them in daily practice. All the proposed hypotheses are found to be true indicating positive relationship between implementation of QMS and business performance and mediatory variables under study.



Exploring critical success factors for TQM implementation using interpretive structural modelling approach: extract from case studies
The purpose of this paper is to explore the critical success factors for TQM implementation from the real case analysis. Eisenhardt (1989) seminal article on 'Building theories from case study research' has motivated researchers from diverse areas to adopt case study methodology to build concepts and theories and case research on TQM implementation concepts is no exception. From extant literature review and many other sources of information, these critical success factors have been carried out. The successful TQM implementation set comprised seven companies. Interpretive structural modelling (ISM) approach has been applied in this study. From this case analysis, we found 18 success factors. This paper aims to identify and develop the structural relationship among different critical success factors for successful implementation of TQM. The findings of the study provide hierarchy level of all 14 factors from top to bottom level and critical input for TQM implementation with firms being more proactive and better prepared for TQM implementation.



EOQ model for deteriorating items with stock-dependent demand under inflation and trade credits
In this paper, an economic order quantity (EOQ) model is developed for deteriorating items with inflation under the condition of permissible delay in payment. In general, if the retailer orders a large quantity, the supplier usually willing to provide the retailer a permissible delay of payments. In this paper demand rate is considered as stock dependent. Mathematical model is then developed to determine the optimal cycle time and average cost. Next, we show that the average cost per unit time is a convex function of cycle time. Numerical examples are provided to illustrate the proposed model. Finally, sensitivity analysis of the optimal solution with respect to the parameters and some managerial relevance are discussed.



Prioritisation of quality dimensions of after-sales technical services
The purpose of this study is to structure quality dimensions and houses of quality for after-sales services of gas-fired combi boiler technical service companies. A survey methodology and site visits are structured to collect scores, dimensions and detailed activities on two houses of quality. Importance weights for customer expectations are calculated using the analytic hierarchy process. Importance rank orders of technical requirements and comparative scores of other brands are calculated within the ordinary procedure of quality function deployment. The results indicate that a clear understanding by employees of customer needs is the most demanded customer expectation, whereas professional abilities and ethical behaviour are the most important technical requirements. This study is unique not only because it presents detailed service quality activities in a second house of quality to achieve quality excellence but also because it is the first quality function deployment study on combi boiler technical services.



Deming's chain reaction revisited
Deming's chain reaction is a well-known proposal from Dr. W.E. Deming, in which he explains the positive effect of improving quality in different aspects of an organisation's activities and performance. Recognising and enhancing the value of Deming ideas, in this paper chain reaction is reevaluated and adapted to environments different to those considered by Deming, specifically to those where competition is not the motto for quality improvement. Three economic situations are considered: open competitive markets (as Deming considered); markets with no or very limited competition; and public services or organisations not oriented to profits but to cover social demands. Two additional versions of the chain reaction are proposed based in Deming's original, and finally a comprehensive chain reaction is presented, adequate to any type of economic environment. The paper enhances the strength and power of Deming's ideas, showing its ability to adapt to scenarios different to those originally considered.