Search results for: a causal model

Authors: Tahmidul Islam

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Propensity Score Matching (PSM) technique has been widely used for estimating causal effect of treatment in observational studies. One major step of implementing PSM is estimating the propensity score (PS). Logistic regression model with additive linear terms of covariates is most used technique in many studies. Logistics regression model is also used with cubic splines for retaining flexibility in the model. However, choosing the functional form of the logistic regression model has been a question since the effectiveness of PSM depends on how accurately the PS been estimated. In many situations, the linearity assumption of linear logistic regression may not hold and non-linear relation between the logit and the covariates may be appropriate. One can estimate PS using machine learning techniques such as random forest, neural network etc for more accuracy in non-linear situation. In this study, an attempt has been made to compare the efficacy of Generalized Additive Model (GAM) in various linear and non-linear settings and compare its performance with usual logistic regression. GAM is a non-parametric technique where functional form of the covariates can be unspecified and a flexible regression model can be fitted. In this study various simple and complex models have been considered for treatment under several situations (small/large sample, low/high number of treatment units) and examined which method leads to more covariate balance in the matched dataset. It is found that logistic regression model is impressively robust against inclusion quadratic and interaction terms and reduces mean difference in treatment and control set equally efficiently as GAM does. GAM provided no significantly better covariate balance than logistic regression in both simple and complex models. The analysis also suggests that larger proportion of controls than treatment units leads to better balance for both of the methods.

Keywords: accuracy, covariate balances, generalized additive model, logistic regression, non-linearity, propensity score matching

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Authors: Lisandy Arinta Suryana, Santi Novani, Utomo Sarjono

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Paradox of business strategic is associated with the contradictory practice. It becomes one of the critical way to survive and win in the dynamic competitive landscape – high level of uncertainty and rapid change in the business environment. Those characteristics are similar with the environment of hijab fashion business, especially in Indonesia. This paper aims to describe the success of paradoxical strategic based on historical data of hijab fashion business which have been validated by qualitative approach. This paper discusses two main aspects of paradoxical strategic such as paradox in human resource management, and logistic center management. Then, the detail effects from each practice are described in term of causal loop diagram. Moreover, the practice of paradoxical strategic depends on leadership that can make a brave and dynamic decision by capturing the main problems and opportunities in their business, and also build commitment to achieve a specific goal.

Keywords: paradox of business strategic, paradoxical strategic, causal loop diagram, sustainable business, hijab fashion business, business strategic

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Authors: John McDowall, Lucy Lightfoot

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Stigma constitutes a significant barrier to the recovery and social integration of individuals affected by mental illness. Although there is some debate in the literature regarding the definition and utility of stigma as a concept, it is widely accepted that it comprises three components: stereotypical beliefs, prejudicial reactions, and discrimination. Stereotypical beliefs describe the cognitive knowledge-based component of stigma, referring to beliefs (often negative) about members of a group that is based on cultural and societal norms (e.g. ‘People with anxiety are just weak’). Prejudice refers to the affective/evaluative component of stigma and describes the endorsement of negative stereotypes and the resulting negative emotional reactions (e.g. ‘People with anxiety are just weak, and they frustrate me’). Discrimination refers to the behavioural component of stigma, which is arguably the most problematic, as it exerts a direct effect on the stigmatized person and may lead people to behave in a hostile or avoidant way towards them (i.e. refusal to hire them). Research exploring anti-stigma initiatives focus primarily on an educational approach, with the view that accurate information will replace misconceptions and decrease stigma. Many approaches take a biogenetic stance, emphasising brain and biochemical deficits - the idea being that ‘mental illness is an illness like any other.' While this approach tends to effectively reduce blame, it has also demonstrated negative effects such as increasing prognostic pessimism, the desire for social distance and perceptions of stereotypes. In the present study 144 participants were split into three groups and read one of three vignettes presenting causal explanations for Generalised Anxiety Disorder (GAD): One explanation emphasized biogenetic factors as being important in the etiology of GAD, another emphasised psychosocial factors (e.g. aversive life events, poverty, etc.), and a third stressed the adaptive features of the disorder from an evolutionary viewpoint. A variety of measures tapping the various components of stigma were administered following the vignettes. No difference in stigma measures as a function of causal explanation was found. People who had contact with mental illness in the past were significantly less stigmatising across a wide range of measures, but this did not interact with the type of causal explanation.

Keywords: generalised anxiety disorder, discrimination, prejudice, stigma

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Authors: Malte Brettel, David Bendig, Michael Keller, Marius Rosenberg

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What are the core competences necessary in order to sustain manufacturing in high-wage countries? Aspiring countries all over the world gain market share in manufacturing and rapidly close the productivity and quality gap that has until now protected some parts of the industry in Europe and the United States from dislocation. However, causal production planning and manufacturing, the basis for productivity and quality, is challenged by the ever-greater need for flexibility and customized products in an uncertain business environment. This article uses a case-study-based approach to assess how production managers in high-wage countries can apply decision-making principals from successful entrepreneurs. 'Effectuation' instead of causal decision making can be applied to handle uncertainty of mass customization, to seek the right partners in alliances and to advance towards virtual production. The findings help managers to use their resources more efficiently and contribute to bridge the gap between production research and entrepreneurship.

Keywords: case studies, decision-making behavior, effectuation, production planning

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Authors: Eftychia Kessopoulou, Styliani Xanthopoulou, Ypatia Theodorakioglou, George Tsiotras, Katerina Gotzamani

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Public sector managers frequently herald that implementing best practices as a set of standards, may lead to superior organizational performance. However, recent research questions the objectification of best practices, highlighting: a) the inability of public sector organizations to develop innovative administrative practices, as well as b) the adoption of stereotypical renowned practices inculcated in the public sector by international governance bodies. The process through which organizations construe what a best practice is, still remains a black box that is yet to be investigated, given the trend of continuous changes in public sector performance, as well as the burgeoning interest of sharing popular administrative practices put forward by international bodies. This study aims to describe and understand how organizational best practices are constructed by public sector performance management teams, like benchmarkers, during the benchmarking-mediated performance improvement process and what mechanisms enable this construction. A critical realist action research methodology is employed, starting from a description of various approaches on best practice nature when a benchmarking-mediated performance improvement initiative, such as the Common Assessment Framework, is applied. Firstly, we observed the benchmarker’s management process of best practices in a public organization, so as to map their theories-in-use. As a second step we contextualized best administrative practices by reflecting the different perspectives emerged from the previous stage on the design and implementation of an interview protocol. We used this protocol to conduct 30 semi-structured interviews with “best practice” process owners, in order to examine their experiences and performance needs. Previous research on best practices has shown that needs and intentions of benchmarkers cannot be detached from the causal mechanisms of the various contexts in which they work. Such causal mechanisms can be found in: a) process owner capabilities, b) the structural context of the organization, and c) state regulations. Therefore, we developed an interview protocol theoretically informed in the first part to spot causal mechanisms suggested by previous research studies and supplemented it with questions regarding the provision of best practice support from the government. Findings of this work include: a) a causal account of the nature of best administrative practices in the Greek public sector that shed light on explaining their management, b) a description of the various contexts affecting best practice conceptualization, and c) a description of how their interplay changed the organization’s best practice management.

Keywords: benchmarking, action research, critical realism, best practices, public sector

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Authors: Polvasut Mahaiamsiri, Piraphong Foosiri

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The purpose of this research is to explore the model of factors affecting decision making to select successor in family business of Thailand. A Structural Equation Model (SEM) was created from relevant theories and researches. Consequently, examine and analyse, the causal relation factors of Succession Plan, Recruitment Process and Strategic Planning, whether they have direct or indirect effects on Decision Making to Select Successor in family business. Units of analysis are selected from the family business, totalling 300 sampling. Population sampling is current owners or CEO from the percentage of six district areas in Thailand with multi-stage sampling. A set of questionnaires is used to collect data. An analysis of structural equation modelling (SEM) technique using AMOS 21 program is conducted to test the hypotheses and confirmatory factor analysis is performed and shows that these variables can be tested. The finding of this study revealed that these factors are separate constructs that combine to determine decision making to select successors.

Keywords: succession plan, family business, recruitment process, strategic planning, decision making to select successor

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Authors: Razak Rahmat, Azizah Ahmad, Rafidah Razak, Roshidi Din, Azizi Abas

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Telecenter is a place where communities can access computers, the Internet, and other digital technologies to enable them to gather information, create, learn, and communicate with others. However, previous studies found that sustainability issues related to economic, political and institutional, social and technology is one of the major problem faced by the telecenter. Based on that problem, this research is planning to design a possible solution on rural telecenters sustainability with the support of business intelligence (BI). The empirical study will be conducted through the qualitative and quantitative method including interviews and observations with a range of stakeholders including ministry officers, telecenters managers and operators. Result from the data collection will be analyze using the causal modeling approach of SEM SmartPLS for the validity. The expected finding from this research is the Business Intelligent Requirement Model as a guild for sustainability of the rural telecenters.

Keywords: Rural ICT Telecenter(RICTT), business intelligence, sustainability, requirement analysis modal

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Authors: Alireza Tavakoli Nia

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In order to understand the role of the injured party's fault in dividing liability, we studied its historical background. In common law, the traditional contributory negligence rule was a complete defense. Then the legislature and judicial procedure modified that rule to one of apportionment. In Islamic law, too, the Action rule was at first used when the injured party was the sole cause, but jurists expanded the scope of this rule, so this rule was used in cases where both the injured party's fault and that of the other party are involved. There are some popular approaches for apportionment of damages. Some common law countries like Britain had chosen ‘the causal potency approach’ and ‘fixed apportionment’. Islamic countries like Iran have chosen both ‘the relative blameworthiness’ and ‘equal apportionment’ approaches. The article concludes that both common law and Islamic law believe in the division of responsibility between a wrongdoer claimant and the defendant. In contrast, in the apportionment of responsibility, Islamic law mostly believes in equal apportionment that is way easier and saves time and money, but common law legal systems have chosen the causal potency approach, which is more complicated than the rival approach but is fairer.

Keywords: contributory negligence, tort law, damage apportionment, common law, Islamic law

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Authors: M. F. Wu, F. T. Cheng, C. S. Wu, M. C. Tan

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It is a critical time to upgrade technology and increase value added with manufacturing skills developing and management strategies that will highly satisfy the customers need in the precision machinery global market. In recent years, the supply side, each precision machinery manufacturers in each country are facing the pressures of price reducing from the demand side voices that pushes the high-end precision machinery manufacturers adopts low-cost and high-quality strategy to retrieve the market. Because of the trend of the global market, the manufacturers must take price reducing strategies and upgrade technology of low-end machinery for differentiations to consolidate the market. By using six key success factors (KSFs), customer perceived value, customer satisfaction, customer service, product design, product effectiveness and machine structure quality are causal conditions to explore the impact of competitive advantage of the enterprise, such as overall profitability and product pricing power. This research uses key success paths (KSPs) approach and f/s QCA software to explore various combinations of causal relationships, so as to fully understand the performance level of KSFs and business objectives in order to achieve competitive advantage. In this study, the combination of a causal relationships, are called Key Success Paths (KSPs). The key success paths guide the enterprise to achieve the specific outcomes of business. The findings of this study indicate that there are thirteen KSPs to achieve the overall profitability, sixteen KSPs to achieve the product pricing power and seventeen KSPs to achieve both overall profitability and pricing power of the enterprise. The KSPs provide the directions of resources integration and allocation, improve utilization efficiency of limited resources to realize the continuous vision of the enterprise.

Keywords: precision machinery industry, key success factors (KSFs), key success paths (KSPs), overall profitability, product pricing power, competitive advantages

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Authors: Yong Chen

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To understand the detailed molecular mechanisms of memory formation in engram cells is one of the most fundamental questions in neuroscience. Recent single-cell RNA-seq (scRNA-seq) and single-nucleus RNA-seq (snRNA-seq) techniques have allowed us to explore the sparsely activated engram ensembles, enabling access to the molecular mechanisms that underlie experience-dependent memory formation and consolidation. However, the absence of specific and powerful computational methods to detect memory-related genes (modules) and their regulatory relationships in the sc/snRNA-seq datasets has strictly limited the analysis of underlying mechanisms and memory coding principles in mammalian brains. Here, we present a deep-learning method named SCENTBOX, to detect memory-related gene modules and causal regulatory relationships among themfromsc/snRNA-seq datasets. SCENTBOX first constructs codifferential expression gene network (CEGN) from case versus control sc/snRNA-seq datasets. It then detects the highly correlated modules of differential expression genes (DEGs) in CEGN. The deep network embedding and attention-based convolutional neural network strategies are employed to precisely detect regulatory relationships among DEG genes in a module. We applied them on scRNA-seq datasets of TRAP; Ai14 mouse neurons with fear memory and detected not only known memory-related genes, but also the modules and potential causal regulations. Our results provided novel regulations within an interesting module, including Arc, Bdnf, Creb, Dusp1, Rgs4, and Btg2. Overall, our methods provide a general computational tool for processing sc/snRNA-seq data from case versus control studie and a systematic investigation of fear-memory-related gene modules.

Keywords: sc/snRNA-seq, memory formation, deep learning, gene module, causal inference

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Authors: Jingwen Shan

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In order to explore the key factors affecting the robot program learning intention of school students, this study takes the technology acceptance model as the theoretical basis and invites 167 students from Jiading District of Shanghai as the research subjects. In the robot course, the model of school students on their learning behavior is constructed. By verifying the causal path relationship between variables, it is concluded that teachers can enhance students’ perceptual usefulness to robotics courses by enhancing subjective norms, entertainment perception, and reducing technical anxiety, such as focusing on the gradual progress of programming and analyzing learner characteristics. Students can improve perceived ease of use by enhancing self-efficacy. At the same time, robot hardware designers can optimize in terms of entertainment and interactivity, which will directly or indirectly increase the learning intention of the robot course. By changing these factors, the learning behavior of primary and secondary school students can be more sustainable.

Keywords: TAM, learning behavior intentions, robot courses, primary and secondary school students

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Authors: Anne Davies

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Numerous students matriculating into university programs are surprised to find they are underprepared for the academic challenges of undergraduate studies. In many cases, they are unaware of their weaknesses as a scholar and unsure of how to develop their skills to succeed academically. Hypothesis: Early proactive intervention from faculty and staff members can mitigate academic issues and promote better student success outcomes. Method: After three weeks in their first semester, first-year students struggling-academically were recruited to attend individual weekly remediation sessions to develop effective learning practices. A causal-comparative methodology was used to evaluate their progress as compared to prior students with similar academic performances. Observations: Students welcomed the intervention from faculty and staff to remediate their individual needs. Those who received help in the third week had better outcomes than previous students with comparable performances who did not receive any interventional support. At the end of the semester, most students were back on track to complete their chosen degree programs. Conclusions: Early intervention by faculty and staff can improve the success of students in maintaining their status in their programs. In the future, this program will be incorporated into all first-year experience courses.

Keywords: Academic outcomes, program retention, remediation, undergraduate students

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Authors: Ricardo Schnug

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This paper puts the transnational crime of human trafficking in the context of Sub-Saharan Africa and its quickly growing youth bulge. By mapping recent and concurrent trends and emerging issues, it explores the implications that it has not only for the region itself but also for the greater global dynamics of the issue. Through the application of Causal Layered Analysis to various alternative future scenarios as well as the identification of the core narrative surrounding the international discourse, it is possible to understand more deeply the forces that underlie future trafficking and what change becomes possible. With the provision of a reconstructed narrative that avoids the current blind spots, this research points out the need for a new and organic leadership paradigm that allows for a more holistic and future-oriented inquiry about socio-economic and political change and what it entails for a transnational crime such as human trafficking. 'Ubuntu' as a social and leadership philosophy then, provides the principles needed for creating this path towards a truly preferred future. Furthermore, this paper inspires follow-up research and the continuous monitoring and transdisciplinary research of this region’s demographic emergence as well as its possible consequences that have been explored in this inquiry.

Keywords: causal layered analysis, emerging issues, human trafficking, scenarios, sub-Saharan Africa

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Authors: Hong Wu, Naiji Lu, Chenguang Wang, Xinming Tu

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This article analyzes the causal effects of informal care, mental health, and physical health on falls and other accidents (e.g. traffic accidents) among elderly people. To purge potential reversal causal effects, e.g., past accidents induce more future informal care, we use two-stage least squares to identify the impacts. By using longitudinal data from a representative national China Health and retirement longitudinal study of people aged 45 and older in China, our findings indicate that informal care decreases while poor health conditions increase the occurrence of accidents. We also find heterogeneous impacts on the occurrence of accidents, varying by gender, urban status, and past accident history. Our findings suggest the following three policy implications. First, policy makers who aim to decrease accidents should take informal care to elders into account. Second, ease of birth policy and postponed retirement policy are urgent to meet the demand of informal care. Third, medical policies should attach great importance to not only physical health but also mental health of elderly parents especially for older people with accident history.

Keywords: accident, China, fall, informal care, mental health, physical health

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Authors: S. Srinivasan, E. Cretu

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The information flow (e.g. block-diagram or signal flow graph) paradigm for the design and simulation of Microelectromechanical (MEMS)-based systems allows to model MEMS devices using causal transfer functions easily, and interface them with electronic subsystems for fast system-level explorations of design alternatives and optimization. Nevertheless, the physical bi-directional coupling between different energy domains is not easily captured in causal signal flow modeling. Moreover, models of fundamental components acting as building blocks (e.g. gap-varying MEMS capacitor structures) depend not only on the component, but also on the specific excitation mode (e.g. voltage or charge-actuation). In contrast, the energy flow modeling paradigm in terms of generalized across-through variables offers an acausal perspective, separating clearly the physical model from the boundary conditions. This promotes reusability and the use of primitive physical models for assembling MEMS devices from primitive structures, based on the interconnection topology in generalized circuits. The physical modeling capabilities of Simscape have been used in the present work in order to develop a MEMS library containing parameterized fundamental building blocks (area and gap-varying MEMS capacitors, nonlinear springs, displacement stoppers, etc.) for the design, simulation and optimization of MEMS inertial sensors. The models capture both the nonlinear electromechanical interactions and geometrical nonlinearities and can be used for both small and large signal analyses, including the numerical computation of pull-in voltages (stability loss). Simscape behavioral modeling language was used for the implementation of reduced-order macro models, that present the advantage of a seamless interface with Simulink blocks, for creating hybrid information/energy flow system models. Test bench simulations of the library models compare favorably with both analytical results and with more in-depth finite element simulations performed in ANSYS. Separate MEMS-electronic integration tests were done on closed-loop MEMS accelerometers, where Simscape was used for modeling the MEMS device and Simulink for the electronic subsystem.

Keywords: across-through variables, electromechanical coupling, energy flow, information flow, Matlab/Simulink, MEMS, nonlinear, pull-in instability, reduced order macro models, Simscape

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Authors: Murad Ali, Anderson Konan Seny Kan, Khalid A. Maimani

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Based on the theory of organizational design and the theory of knowledge, this study uses complexity theory to explain and better understand the causal impacts of various patterns of organizational structural factors stimulating absorptive capacity (ACAP). Organizational structure can be thought of as heterogeneous configurations where various components are often intertwined. This study argues that impact of the traditional variables which define a firm’s organizational structure (centralization, formalization, complexity and integration) on ACAP is better understood in terms of set-theoretic relations rather than correlations. This study uses a data sample of 347 from a multiple industrial sector in South Korea. The results from PLS-SEM support all the hypothetical relationships among the variables. However, fsQCA results suggest the possible configurations of centralization, formalization, complexity, integration, age, size, industry and revenue factors that contribute to high level of ACAP. The results from fsQCA demonstrate the usefulness of configurational approaches in helping understand equifinality in the field of knowledge management. A recent fsQCA procedure based on a modeling subsample and holdout subsample is use in this study to assess the predictive validity of the model under investigation. The same type predictive analysis is also made through PLS-SEM. These analyses reveal a good relevance of causal solutions leading to high level of ACAP. In overall, the results obtained from combining PLS-SEM and fsQCA are very insightful. In particular, they could help managers to link internal organizational structural with ACAP. In other words, managers may comprehend finely how different components of organizational structure can increase the level of ACAP. The configurational approach may trigger new insights that could help managers prioritize selection criteria and understand the interactions between organizational structure and ACAP. The paper also discusses theoretical and managerial implications arising from these findings.

Keywords: absorptive capacity, organizational structure, PLS-SEM, fsQCA, predictive analysis, modeling subsample, holdout subsample

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Authors: Abdullah Eqal Al Mazrooei

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In this work, a new nonlinear model will be introduced. The model is in the state-space form. The nonlinearity of this model is in the state equation where the state vector is multiplied by its self. This technique makes our model generalizes many famous models as Lotka-Volterra model and Lorenz model which have many applications in the real life. We will apply our new model to estimate the wind speed by using a new nonlinear estimator which suitable to work with our model.

Keywords: nonlinear systems, state-space model, Kronecker product, nonlinear estimator

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Authors: Alfred Quarcoo

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The main purpose of this paper is to examine the causal relationship between energy consumption and economic growth in Sub-Saharan Africa using panel data techniques. An annual data on energy consumption and Economic Growth (proxied by real gross domestic product per capita) spanning from 1990 to 2016 from the World bank index database was used. The results of the Augmented Dickey–Fuller unit root test shows that the series for all countries are not stationary at levels. However, the log of economic growth in Benin and Congo become stationary after taking the differences of the data, and log of energy consumption become stationary for all countries and Log of economic growth in Kenya and Zimbabwe were found to be stationary after taking the second differences of the panel series. The findings of the Johansen cointegration test demonstrate that the variables Log of Energy Consumption and Log of economic growth are not co-integrated for the cases of Kenya and Zimbabwe, so no long-run relationship between the variables were established in any country. The Granger causality test indicates that there is a unidirectional causality running from energy use to economic growth in Kenya and no causal linkage between Energy consumption and economic growth in Benin, Congo and Zimbabwe.

Keywords: Cointegration, Granger Causality, Sub-Sahara Africa, World Bank Development Indicators

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Authors: Abdelhamid Nechad, Ahmed Maghni, Khaoula Zahir

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Energy transition is one of Morocco's key sustainable development issues and is at the heart of the 2030 National Sustainable Development Strategy. On the one hand, it reflects the Moroccan government's determination to reduce the negative impact of energy consumption on the environment, and on the other, its determination to rely essentially on renewable energies to meet its energy needs. With this in mind, several tools are being implemented, including green bonds designed to finance projects with a high environmental or climate impact. Thus, since 2015, several green bonds have been issued for a cumulative total of $0.4 Billion . This article aims to examine the impact of green bonds on Morocco's energy transition. Through the Granger causality and cointegration test, this article examines the existence of a short- and long-term causal relationship between green bond issuance and investment in renewable energy projects on the one hand, and between green bond issuance and CO₂ emission reductions on the other. The results suggest that there is no short-term causal relationship between green bond issuance and renewable energy investments on one hand and CO₂ emissions reduction on the other hand. However, in the long run, there is a relationship between green bond issuance and CO₂ emissions reduction in Morocco.

Keywords: climate impact, CO₂ emissions, energy transition, green bonds, Morocco

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Authors: Liubov Evstigneeva

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In this paper an attempt is made to establish causal nexuses between innovation and international trade in Russia. The topicality of this issue is determined by the necessity of choosing policy instruments for economic modernization and transition to innovative development. The vector auto regression (VAR) model and Granger test are applied for the Russian monthly data from 2005 until the second quartile of 2015. Both lagged import and export at the national level cause innovation, the latter starts to stimulate foreign trade since it is a remote lag. In comparison to aggregate data, the results by patent’s categories are more diverse. Importing technologies from foreign countries stimulates patent activity, while innovations created in Russia are only Granger causality for import to Commonwealth of Independent States.

Keywords: export, import, innovation, patents

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Authors: Aliana Leong, T. C. Huan

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The purpose of Nostalgic themed tourism product is becoming popular in many countries. This study intends to investigate the role of nostalgia in destination image, experiential value and their effect on subsequent behavioral intention. The survey used stratified sampling method to include respondents from all the nearby Asian regions. The sampling is based on the data of inbound tourists provided by the Statistics and Census Service (DSEC) of government of Macau. The questionnaire consisted of five sections of 5 point Likert scale questions: (1) nostalgia, (2) destination image both before and after experience, (3) expected value, (4) experiential value, and (5) future visit intention. Data was analysed with structural equation modelling. The result indicates that nostalgia plays an important part in forming destination image and experiential value before individual had a chance to experience the destination. The destination image and experiential value share a bidirectional causal relationship that eventually contributes to future visit intention. The study also discovered that while experiential value is more effective in generating destination image, the later contribute more to future visit intention. The research design measures destination image and experiential value before and after respondents had experience the destination. The distinction between destination image and expected/experiential value can be examined because the longitudinal design of research method. It also allows this study to observe how nostalgia translates to future visit intention.

Keywords: nostalgia, destination image, experiential value, future visit intention

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Authors: Yuanxiaoyue Yang

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Emissions trading, or ‘cap-and-trade', has been long promoted by economists as a more cost-effective pollution control approach than traditional performance standard approaches. While there is a large body of empirical evidence for the overall effectiveness of emissions trading, relatively little attention has been paid to other unintended consequences brought by emissions trading. One important consequence is that cap-and-trade could introduce the risk of creating high-level emission concentrations in areas where emitting facilities purchase a large number of emission allowances, which may cause an unequal distribution of environmental benefits. This study will contribute to the current environmental policy literature by linking trading activity with environmental injustice concerns and empirically analyzing the causal relationship between trading activity and emissions reduction under a cap-and-trade program for the first time. To investigate the potential environmental injustice concern in cap-and-trade, this paper uses a differences-in-differences (DID) with instrumental variable method to identify the causal effect of allowance trading behaviors on emission reduction levels under the clean air interstate rule (CAIR), a cap-and-trade program targeting on the power sector in the eastern US. The major data source is the facility-year level emissions and allowance transaction data collected from US EPA air market databases. While polluting facilities from CAIR are the treatment group under our DID identification, we use non-CAIR facilities from the Acid Rain Program - another NOx control program without a trading scheme – as the control group. To isolate the causal effects of trading behaviors on emissions reduction, we also use eligibility for CAIR participation as the instrumental variable. The DID results indicate that the CAIR program was able to reduce NOx emissions from affected facilities by about 10% more than facilities who did not participate in the CAIR program. Therefore, CAIR achieves excellent overall performance in emissions reduction. The IV regression results also indicate that compared with non-CAIR facilities, purchasing emission permits still decreases a CAIR participating facility’s emissions level significantly. This result implies that even buyers under the cap-and-trade program have achieved a great amount of emissions reduction. Therefore, we conclude little evidence of environmental injustice from the CAIR program.

Keywords: air pollution, cap-and-trade, emissions trading, environmental justice

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Authors: Jihye Jeon

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This paper analyzes the conceptual framework of three statistical methods, multiple regression, path analysis, and structural equation models. When establishing research model of the statistical modeling of complex social phenomenon, it is important to know the strengths and limitations of three statistical models. This study explored the character, strength, and limitation of each modeling and suggested some strategies for accurate explaining or predicting the causal relationships among variables. Especially, on the studying of depression or mental health, the common mistakes of research modeling were discussed.

Keywords: multiple regression, path analysis, structural equation models, statistical modeling, social and psychological phenomenon

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Authors: Eka Yuliana, Siska Shabrina Julyan

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The competitive environment and high customer’s churn rate in telecommunication industries lead Indonesian telecommunication companies become strive to offer products with more value. Offering product with more value can encourage customers to keep using the companies product. One of way to retain customer is give a membership card to the customers as practiced by PT. Telkom by giving Telkom Membership Card to PT. Telkom loyal customer. This study aims to determine the influence of Telkom Membership Card customer perceived value on retaining PT. Telkom Indonesia’s customer in 2013-2014 by using quantitative method with causal study. Analythical technique used in this study is Structural Equation Modelling (SEM) to test the causal relationship with 216 owner of Telkom Membership Card in Indonesia. This study conclude that: (i) Customer perceived value on Telkom Membership Card is located in fair value zone, (ii) PT. Telkom efforts in order to retain the customers is classified as good, (iii) Customer perceived value is influencing the effort to retain the customer with the probability value less than 0.05 and level of influence 69%. Based on result of this study, PT. Telkom should (i) Improve Telkom Membership Card’s promotion because not all customer of PT. Telkom have the membership card. (iia) Adding Telkom Membership Card’s benefit such as discount at various merchant (iib) Making call center for member of Telkom Membership Card (iii) PT. Telkom should be ensure availability of their service. (iv) PT. Telkom should make a priority to customer who have telkom membership card and offers a better service.For future research should be use different variables.

Keywords: customer perceived value, customer retention, marketing, relationship marketing

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Authors: Le Linh, Truong Nguyen Luan Vu, Le Hieu Giang

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In this work, the IMC-PID controller cascaded filter based on Internal Model Control (IMC) scheme is systematically proposed for the simplified decoupling control system. The simplified decoupling is firstly introduced for multivariable processes by using coefficient matching to obtain a stable, proper, and causal simplified decoupler. Accordingly, transfer functions of decoupled apparent processes can be expressed as a set of n equivalent independent processes and then derived as a ratio of the original open-loop transfer function to the diagonal element of the dynamic relative gain array. The IMC-PID controller in series with filter is then directly employed to enhance the overall performance of the decoupling control system while avoiding difficulties arising from properties inherent to simplified decoupling. Some simulation studies are considered to demonstrate the simplicity and effectiveness of the proposed method. Simulations were conducted by tuning various controllers of the multivariate processes with multiple time delays. The results indicate that the proposed method consistently performs well with fast and well-balanced closed-loop time responses.

Keywords: coefficient matching method, internal model control (IMC) scheme, PID controller cascaded filter, simplified decoupler

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Authors: Ms Azam Najafkouchak, David Todem, Dorothy Pathak, Pramod Pathak, Joseph Gardiner

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Propensity score (PS) methods have recently become the standard analysis as a tool for the causal inference in the observational studies where exposure is not randomly assigned, thus, confounding can impact the estimation of treatment effect on the outcome. For the binary outcome, the effect of treatment on the outcome can be estimated by odds ratios, relative risks, and risk differences. However, using the different PS methods may give you a different estimation of the treatment effect on the outcome. Several methods of PS analyses have been used mainly, include matching, inverse probability of weighting, stratification, and covariate adjusted on PS. Due to the dangers of discretizing continuous variables (exposure, covariates), the focus of this paper will be on how the variation in cut-points or boundaries will affect the average treatment effect (ATE) utilizing the stratification of PS method. Therefore, we are trying to avoid choosing arbitrary cut-points, instead, we continuously discretize the PS and accumulate information across all cut-points for inferences. We will use Monte Carlo simulation to evaluate ATE, focusing on two PS methods, stratification and covariate adjusted on PS. We will then show how this can be observed based on the analyses of the data from a case-control study of breast cancer, the Polish Women’s Health Study.

Keywords: average treatment effect, propensity score, stratification, covariate adjusted, monte Calro estimation, breast cancer, case_control study

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Authors: Lynne Soon-Chean Park

Abstract:

Critical Realism (CR) has emerged as an alternative to both the positivist and constructivist perspectives that have long dominated social work research. By unpacking the epistemic weakness of two dogmatic perspectives, CR provides a useful philosophical approach that incorporates the ontological objectivist and subjectivist stance. The CR perspective suggests an alternative approach for social work researchers who have long been looking to engage in the complex interplay between perceived reality at the empirical level and the objective reality that lies behind the empirical event as a causal mechanism. However, despite the usefulness of CR in informing social work research, little practical guidance is available about how CR can inform methodological considerations in social work research studies. This presentation aims to provide a detailed description of CR-informed thematic analysis by drawing examples from a social work doctoral research of Korean migrants’ experiences and understanding of trust associated with their settlement experience in New Zealand. Because of its theoretical flexibility and accessibility as a qualitative analysis method, thematic analysis can be applied as a method that works both to search for the demi-regularities of the collected data and to identify the causal mechanisms that lay behind the empirical data. In so doing, this presentation seeks to provide a concrete and detailed exemplar for social work researchers wishing to employ CR in their qualitative thematic analysis process.

Keywords: critical Realism, data analysis, epistemology, research methodology, social work research, thematic analysis

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Authors: Arlett A. Rosado-Torres, Ismael Marino-Tapia

Abstract:

Changes in benthic cover of coral dominated systems to macroalgae dominance are widely studied worldwide. Watershed pollutants are potentially as important as overfishing causing phase shift. In certain regions of the world most of the continental inputs are through submarine groundwater discharges (SGD), which can play a significant ecological role because the concentration of its nutrients is usually greater that the one found in surface seawater. These stressors have adversely affected coral reefs, particularly in the Caribbean. Measurements of benthic cover (with video tracing, through a Go Pro camera), reef roughness (acoustic estimates with an Acoustic Doppler Current Velocity profiler and a differential GPS), thermohaline conditions (conductivity-temperature-depth (CTD) instrument) and nutrient measurements were taken in different sites in the reef lagoon of Puerto Morelos, Q. Roo, Mexico including those with influence of SGD and without it. The results suggest a link between SGD, macroalgae cover and structural complexity. Punctual water samples and data series from a CTD Diver confirm the presence of the SGD. On the site where the SGD is, the macroalgae cover is larger than in the other sites. To establish a causal link between this phase shift and SGD, the DELFT 3D hydrodynamic model (FLOW and WAVE modules) was performed under different environmental conditions and discharge magnitudes. The model was validated using measurements of oceanographic instruments anchored in the lagoon and forereef. The SGD is consistently favoring macroalgae populations and affecting structural complexity of the reef.

Keywords: hydrodynamic model, macroalgae, nutrients, phase shift

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Authors: Wanida Suwunniponth

Abstract:

This research paper aimed to developing a causal relationship model of success factors of customer relationship management of tourism in Thailand and to investigating relationships among the potential factors that facilitate the success of customer relationship management (CRM). The research was conducted in both quantitative and qualitative methods, by utilizing both questionnaire and in-depth interview. The questionnaire was used in collecting the data from 250 management staff in the hotels located within Bangkok area. Sampling techniques used in this research included cluster sampling according to the service quality and simple random sampling. The data input was analyzed by use of descriptive analysis and System Equation Model (SEM). The research findings demonstrated important factors accentuated by most respondents towards the success of CRM, which were organization, people, information technology and the process of CRM. Moreover, the customer relationship management of tourism business in Thailand was found to be successful at a very significant level. The hypothesis testing showed that the hypothesis was accepted, as the factors concerning with organization, people and information technology played an influence on the process and the success of customer relationship management, whereas the process of customer relationship management factor manipulated its success. The findings suggested that tourism business in Thailand with the implementation of customer relationship management should opt in improvement approach in terms of managerial structure, corporate culture building with customer- centralized approach accentuated, and investment of information technology and customer analysis, in order to capacitate higher efficiency of customer relationship management process that would result in customer satisfaction and retention of service.

Keywords: customer relationship management, casual relationship model, tourism, Thailand

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Authors: Entisar A. Elgmati

Abstract:

Recurrent infant diarrhea is studied using daily data collected in Salvador, Brazil over one year and three months. A logistic regression model is fitted instead of Aalen's additive model using the same covariates that were used in the analysis with the additive model. The model gives reasonably similar results to that using additive regression model. In addition, the problem with the estimated conditional probabilities not being constrained between zero and one in additive model is solved here. Also martingale residuals that have been used to judge the goodness of fit for the additive model are shown to be useful for judging the goodness of fit of the logistic model.

Keywords: additive model, cumulative probabilities, infant diarrhoea, recurrent event

Procedia PDF Downloads 635