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This paper aims to theorize and examine how central cognition elaboration cue and peripheral cognition elaboration cue influence users’ health information sharing intention in Strong ties social media (STSM) in emerging markets.

This paper innovatively proposes two concepts of health information emotion and health information sharing value based on the in-depth observation of users’ social health behavior. We integrate Elaboration Likelihood Model, Media Richness Theory, Trust Theory and Regulatory Focus Theory to develop hypotheses and research models and lay emphasis on the study of health information emotion’s moderating effect. This paper conducts an empirical study by selecting 372 health information users of WeChat, a typical STSM, to verify the research model by structural equation model.

For the central route, individual motivation and health information richness positively influence health information sharing value. For peripheral route, health information source trust and health information recipient trust both positively influence the health information sharing attitude. Health information sharing value and sharing attitude can positively affect users’ health information sharing intention. In addition, health information positive emotion has significant moderating effect, while health information negative emotion does not have.

This study contributes to a comprehensive perspective for understanding users’ health information sharing intention in STSM in emerging markets, an important but understudied topic. The results can also give implications for researchers to explore users’ behavioral intention from the perspective of process-oriented persuasion and health information emotion’s moderating effect.

This study focuses on examining the impact of energy consumption, economic structure, population, and manufacturing output on the CO₂ emissions of selected emerging countries by utilizing the Structural Time Series Model (STSM). Based on the annual data ranging from 1970 to 2019, the model is built up using total primary energy consumption, GDP per capita, population and manufacturing value-added, and, finally, a stochastic Underlying Emission Trend as explanatory variables. STSM is extended by the introduction of the notion of Underlying Energy Demand Trend (UEDT) as a factor for exogenous effects, including development in technical progress, energy efficiency improvements, changes in human behaviors, economy, and environmental regulations. In this context, STSM and the notion of UEDT are implemented to form a forecasting model for CO₂ emissions of the selected emerging countries. The model discovers the significant influences of all selected variables of CO₂ emissions. The results suggest that the most forceful factor in CO₂ emissions is the total primary energy supply. Furthermore, while the long-term impact of economic growth on CO₂ emissions is negative for some emerging economies, it is positive for several others. The model also measures the long-term manufacturing value-added elasticity of CO₂ emissions in these emerging economies.

Online advertising such as Google AdWords gives small and medium-sized enterprises access to new markets at reduced costs. The purpose of this paper is to analyse the visibility and performance of a website and to test the effectiveness of online marketing using the data provided by Google Analytics.

The authors use a class of econometric time series models with unobservable components, Structural Time Series Models (STSM). The authors allow for time-varying trends to take into account the non-stationary behaviour displayed by time series. The authors illustrate the model using daily data from a local tourist website. Three specific questions are addressed: do paid keywords campaigns increase the volume and quality of search traffic? Do paid keywords affect the volume and quality of the unpaid traffic? How do paid and unpaid keywords perform?

The results for the case study show that: first, online campaigns affect traffic volume positively but their effectiveness on traffic quality is uncertain; second, paid keywords do not affect the volume and quality of unpaid traffic; third, the increase in traffic volume is not always due to the paid keywords and the lowest quality visits come from paid traffic.

This analysis may help webmasters to design successful online advertising strategies.

This study contributes to the development of user-friendly methodologies to monitor website performance. The analysis shows that STSM is a suitable methodology to test the effectiveness of online campaigns and to assess the changes over time in the performance of a website.

With the increasing spread of ontologies in various domains, units have gradually become an essential part of ontologies and units ontologies have been developed to offer a better expression ability for the practical usage. From the perspectives of architecture, comparison and reuse, the purpose of this paper is to provide a comprehensive survey on four mainstream units ontologies: quantity-unit-dimension-type, quantities, units, dimensions and values, ontology of units of measure and units ontology (UO) of the open biomedical ontologies, in order to address well the state of the art and the reuse strategies of the UO.

An architecture of units ontologies is presented, in which the relations between key factors (i.e. units of measure, quantity and dimension) are discussed. The criteria for comparing units ontologies are developed from the perspectives of organizational structure, pattern design and application scenario. Then, the authors compare four typical units ontologies based on the proposed comparison criteria. Furthermore, how to reuse these units ontologies is discussed in materials science domain by utilizing two reuse strategies of partial reference and complete reference.

Units ontologies have attracted high attention in the scientific domain. Based on the comparison of four popular units ontologies, this paper finds that different units ontologies have different design features from the perspectives of basis structure, units conversion and axioms design; a UO is better to be applied to the application areas that satisfy its design features; and many challenges remain to be done in the future research of the UO.

This paper makes an extensive review on units ontologies, by defining the comparison criteria and discussing the reuse strategies in the materials domain. Based on this investigation, guidelines are summarized for the selection and reuse of units ontologies.

To meet the need of reducing the cost of industrial systems, sensorless control applications on electrical machines are increasing day by day. This paper aims to improve the performance of the sensorless induction motor control system. To do this, the speed observer is designed based on the combination of the sliding mode and the fractional order integral.

Super-twisting sliding mode (STSM) and Grünwald–Letnikov approach are used on the proposed observer. The stability of the proposed observer is verified by using Lyapunov method. Then, the observer coefficients are optimized for minimizing the steady-state error and chattering amplitude. The optimum coefficients (c₁, c₂, k_i and λ) are obtained by using response surface method. To verify the effectiveness of proposed observer, a large number of experiments are performed for different operation conditions, such as different speeds (500, 1,000 and 1,500 rpm) and loads (100 and 50 per cent loads). Parameter uncertainties (rotor inertia J and friction factor F) are tested to prove the robustness of the proposed method. All these operation conditions are applied for both proportional integral (PI) and fractional order STSM (FOSTSM) observers and their performances are compared.

The observer model is tested with optimum coefficients to validate the proposed observer effectiveness. At the beginning, the motor is started without load. When it reaches reference speed, the motor is loaded. Estimated speed and actual speed trends are compared. The results are presented in tables and figures. As a result, the FOSTSM observer has less steady-state error than the PI observer for all operation conditions. However, chattering amplitudes are lower in some operation conditions. In addition, the proposed observer shows more robustness against the parameter changes than the PI observer.

The proposed FOSTSM observer can be applied easily for industrial variable speed drive systems which are using induction motor to improve the performance and stability.

The robustness of the STSM and the memory-intensive structure of the fractional order integral are combined to form a robust and flexible observer. This paper grants the lower steady-state error and chattering amplitude for sensorless speed control of the induction motor in different speed and load operation conditions. In addition, the proposed observer shows high robustness against the parameter uncertainties.

The aim of this paper is to establish the role of asymmetric price decompositions in UK road transportation fuel demand, make explicit the impact of the underlying energy demand trend, and disaggregate the estimation for gasoline and diesel demand as separate commodities.

Dynamic UK transport oil demand functions are estimated using the Seemingly Unrelated Structural Time Series Model with decomposed prices to allow for asymmetric price responses.

The importance of starting with a flexible modelling approach that incorporates both an underlying demand trend and asymmetric price response function is highlighted. Furthermore, these features can lead to different insights and policy implications than might arise from a model without them. As an example, a zero elasticity for a price‐cut is found (for both gasoline and diesel), implying that price reductions do not induce demand for road transportation fuel in the UK.

The paper illustrates the importance of joint modelling of gasoline and diesel demand incorporating both asymmetric price responses and stochastic underlying energy demand trends.

This chapter sheds new light on the linkages between stock market fluctuations and business cycles in Asia. It shows that at cyclical frequencies stock markets lead business cycles by six months on average. China, Korea, and Taiwan constitute exceptions, as their real and stock market cycles are contemporaneously synchronized. The low level of maturity of these markets offers a potential explanation of this outcome. Furthermore, we find that the linkage also holds during phases of cyclical upswing and downturn, with the exception of China, where the financial market lags behind industrial production during expansions. Finally, for most of the countries (except Thailand and Malaysia), the linkage is also robust to the presence of financial crises.

This paper aims to solve the problems of the synchronization between branches and the uncertainties such as joint friction, load variation and external interference of a hybrid mechanism. The controller is used to improve the synchronization and robustness of the hybrid mechanism system and achieve both finite time convergence and chattering-free sliding mode.

First, the dynamic model of hybrid mechanism containing lumped uncertainties is formulated by the Lagrange method, and a composite error based on coupling synchronization error and the end-effector tracking error is set up in the task space. Then, by combining the finite time super twisting sliding mode control algorithm, a composite error-based finite time super twisting sliding mode synchronous control law is designed to make the end-effector tracking error and coupling synchronization error achieve better tracking performance and convergence performance. Finally, the Lyapunov stability of the control law and the finite-time convergence of the composite error are proved theoretically.

To verify the effectiveness of the proposed control method, simulations and experiments for the prototype system of the hybrid mechanism are conducted. The results show that the proposed control method can achieve better tracking performance and convergence performance.

This is a new innovation for a hybrid mechanism containing lumped uncertainties to improve the robustness, convergence performance, tracking performance and synchronization of the system.

This study aims to find out the dynamic and causal long-run and the short-run relationship between energy consumption (electricity usage) and energy production (electricity creation) and also find out the relationship of these two variables based on past values for the SAARC nations (Pakistan, India, Bangladesh, Sri Lanka and Nepal).

Vector auto-regressive (VAR), auto-regressive distributive Lag (ARDL) and Granger causality test have been used in this study to estimate the dynamic and causal relationship between variables.

The unit-root tests were found insignificant at a magnitude but significant at the initial difference. VAR test results were found insignificant, which means co-integration among variables exists, which was tested by ARDL approach. Results suggested that energy consumption has a short-run relationship with energy production, but it was found insignificant in the other way round. The results of this study also suggest that both variables cause each other in the long run.

This study was conducted in a limited environment as we do not have access to energy policies of SAARC countries, and also data access was limited; only five countries’ data was available. This study can help government bodies and policymakers to exchange the electricity across borders to diminish the electricity shortage in the SAARC region, as countries with abandoned resources can produce electricity at a little cost.

Penal data for this study was collected from World Development Indicators from the year 1971 to 2015.

The purpose of this paper is to investigate the elements of lean concept and identify those principles which are applicable to service organizations, also, to compare the lean best practices with CMMI‐SVC v1.2 model goals and practices and find out the compatibility.

The capability maturity model integration (CMMI) for services (CMMI‐SVC v1.2) model, developed by Software Engineering Institute is a collection of best practices applicable to service operations. Lean concepts, on the other hand, originated from manufacturing but of late lean principles and best practices have been implemented in some services organizations. As lean concepts originated from manufacturing and CMMI‐SVC v1.2 from software industry, there could be some overlapping content and some differences and each may offer some distinct advantages. This paper is based on the review of the contemporary literature on lean concepts and CMMI‐SVC v1.2 model, including books, journal articles and handbooks. The authors involved a group of practitioners and experts with theoretical and practical expertise on the CMMI framework, software process improvements as well as lean principles and services to find out which lean principles are applicable to service organization and also the compatibility of lean and CMMI‐SVC v1.2 practices.

The authors have defined a set of lean best practices which can be applied to service organizations. It is concluded that integration and harmonization of both lean and CMMI‐SVC v1.2 practices is possible and in many ways the practices are complementary. In the future, a unified model based on both lean and CMMI‐SVC v1.2 can be developed by combining the best practices of both.

This paper has reviewed the lean literature and grouped the lean best practices which are applicable to service organizations. It has compared the lean best practices with CMMI‐SVC v1.2 best practices. Little research has been done on comparison of lean best practices with CMMI‐SVC v1.2 model.