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Considers that when efficiency and effectiveness of systems are measured by the quantity and quality of their output they may be inadequate for the purpose of comparing one system with another. Seeks new criteria and defines entropy, wastivity and quality concepts in relation to system performance. Establishes the interdependence of the three concepts. Proposes that system wastivity should be used as a measure of system performance.

The purpose of this paper is to propose a structured multilevel system that will distinguish the anomalies present in different online social networks (OSN).

Author first reviewed the related work, and then, the research model designed was explained. Furthermore, the details regarding Levels 1 and 2 were narrated.

By using the proposed technique, F_Score obtained for Twitter and Facebook data set was 96.22 and 94.63, respectively.

Four data sets were used for the experiment and the acquired outcomes demonstrate enhancement over the current existing frameworks.

This paper designed a multilevel framework that can be used to detect the anomalies present in the OSN.

This paper aims to study the impact of pyro-electricity, moisture and temperature diffusivity on the energy distribution of plane waves at the free surface of an orthotropic piezo-hygro-thermo-elastic medium.

This study presents the novel creation of governing equations for an anisotropic piezothermoelastic medium with moisture impact, which is a significant contribution of this paper.

In addition to providing numerical data for the amplitude ratios and energy ratios of reflected waves, this study identifies five different kinds of coupled reflected plane waves, namely, quasi-longitudinal P wave, quasi-thermal wave, quasi-transverse wave, quasi-moisture wave and electric potential wave.

The graphical analysis examines the impact of various factors, such as the angle of incidence, moisture and temperature diffusivity, pyro-electricity and frequency, on energy distribution.

This paper's results significantly impact the development of more efficient piezoelectric materials and their applications in geophysics.

The authors of the submitted document initiated and produced it collectively, with equal contributions from all members.

The purpose of this paper is to develop a methodology to analyze the total sintering energy (TSE) required for manufacturing a part in metal powder-based additive manufacturing (AM) processes and optimize AM processes for minimizing total energy and form errors of AM parts while maximizing part strength.

The paper uses a computational geometry approach to determine the TSE expended for manufacturing a metal AM part. The stereolithography (STL) file of a part is converted into a voxel data structure and the total sintering volume (TSV) is computed from the voxel representation. The TSE is then calculated from the TSV using the material property information of the metal powder.

The TSE of an AM part is calculated for different slice thickness and part orientations, and the correlation of the total energy to these parameters is calculated. Using these correlations, the AM process is optimized to calculate the optimal values of slice thickness and part orientation which would result in lower process energy, lower part form errors and higher part strength.

The methodology presented in this paper provides AM users a roadmap to predict the energy required for manufacturing a part. In addition, the optimization model will allow engineers to manufacture precision parts which satisfy their design specifications with minimal energy expenditure.

The purpose of this paper is to identify and quantify the key components of the overall cost of software development when warranty coverage is given by a developer. Also, the authors have studied the impact of imperfect debugging on the optimal release time, warranty policy and development cost which signifies that it is important for the developers to control the parameters that cause a sharp increase in cost.

An optimization problem is formulated to minimize software development cost by considering imperfect fault removal process, faults generation at a constant rate and an environmental factor to differentiate the operational phase from the testing phase. Another optimization problem under perfect debugging conditions, i.e. without error generation is constructed for comparison. These optimization models are solved in MATLAB, and their solutions provide insights to the degree of impact of imperfect debugging on the optimal policies with respect to software release time and warranty time.

A real-life fault data set of Radar System is used to study the impact of various cost factors via sensitivity analysis on release and warranty policy. If firms tend to provide warranty for a longer period of time, then they may have to bear losses due to increased debugging cost with more number of failures occurring during the warrantied time but if the warranty is not provided for sufficient time it may not act as sufficient hedge during field failures.

Every firm is fighting to remain in the competition and expand market share by offering the latest technology-based products, using innovative marketing strategies. Warranty is one such strategic tool to promote the product among masses and develop a sense of quality in the user’s mind. In this paper, the failures encountered during development and after software release are considered to model the failure process.

The software development team reviews the testing phase to assess if the reliability growth of software is as per plan and requirement and gives suggestions for improvement. The objective of this study is to determine the optimal review time such that there is enough time to make judgments about changes required before the scheduled release.

Testing utilizes majority of time and resources, assures reliability and plays a critical role in release and warranty decision-making reviews necessary. A very early review during testing may not give useful information for analyzing or improving project performance, and a very late review may delay product delivery and lead to opportunity loss for developers. Therefore, it is assumed that the optimal time for review is in the later stage of testing when the fault removal rate starts to decline. The expression for this time point is determined using the S-curve 2-D software reliability growth model (SRGM).

The methodology has been illustrated using the real-life fault datasets of Tandem computers and radar systems resulting in optimal review time of 14 weeks and 26 months, respectively, which is neither very early in testing nor very near to the scheduled release. The developer can make changes (more resources or postpone release) to expedite the process.

Most of the literature studies focus on determination of optimal testing or release time to achieve considerable reliability within the budget, but in this study, the authors determine the optimal review time during testing using SRGM to ensure the considerable reliability at release.

The ideology of this article is to study the performance concerns of SDN Controllers, with the help of developed SRGM and thereby obtain its optimal testing duration. The effect of undetected uncertainty in the parameter values have also been catered in the proposal.

These uncertainties in the parameter values are studied as the risk of not meeting desired set of requirements, whose removal causes additional cost. Considering these two constructs as attributes of MAUT, the controller's optimal testing duration is obtained.

The article focuses towards obtaining the optimal duration for which the SDN Controllers must be tested. It was observed that the inculcation of risk-attribute has provided the higher utility value as compared to any other existing scenarios.

Plenty of SRGM have been proposed in the literature which talks about the testing stop time determination problems. But, none of them have considered the impact of risk of not meeting the requirements (reliability) along with cost to obtain its testing stop time. Further, validation of the proposed model in presented with the help of two releases versions of SDN controller platform, ONOS, entitled as “Kingfisher” and “Loon” and has acquired promising results.

The purpose of this study is to explore the effect of economic complexity on services export diversification. This study has been built on two arguments. The first one draws from Eichengreen and Gupta (2013b) and states that countries that export complex products would have a high penetration in the international goods market and establish a network that could be exploited to expand their range of services export items. Second, by inducing higher inflows of foreign direct investment (FDI), greater economic complexity could contribute to fostering services export diversification.

The empirical analysis uses a panel data set of 109 countries (both developed and developing countries) over the period of 1985–2014, and in particular, non-overlapping sub-periods of five-year average data. Building on the two-step system Generalized Method of Moments, the empirical analysis has provided support for the above-mentioned two theoretical hypotheses.

The findings indicate that greater economic complexity has been associated with a higher level of services export diversification, and the magnitude of this positive effect is higher for high-income countries than for developing countries. Furthermore, the share of FDI inflows (in percentage of gross domestic product) matters for the effect of economic complexity on services export diversification. Specially, economic complexity exerts a higher positive effect on services export diversification, as the share of net FDI inflows in gross domestic product increases.

From a policy perspective, the analysis complements previous works on the effects of economic complexity (e.g. on economic growth, income inequality, poverty, etc.), by showing that economic complexity also matters for fostering the diversification of countries' services export items. Enhancing economic complexity should be at the heart of policymakers' agenda, both at the national and international levels, given its strong positive effect on macroeconomic aggregates, including on services export diversification, the latter being also an important engine for economic growth (Anand et al., 2012; Gnangnon, 2021a; Mishra et al., 2011; Stojkoski et al., 2016).

This study opens an avenue for future research on whether services export diversification influences economic complexity. One avenue for future research could also be to explore the effect of comparative advantage on goods and services (using the Balassa's revealed comparative advantage index) on services export diversification. Future works could also examine how economic complexity affects different categories of services sectors, including traditional services and modern services.

To the best of the author’s knowledge, this study is the first to address this topic in the literature.

This paper aims to develop an initial understanding of the Lean Six Sigma methodology since its inception and examine the few Lean Six Sigma dimensions as a research domain through a critical review of the literature.

The paper is structured in two-part. The first part of the paper attempts to dwell on the evolution of the Lean Philosophy and Six Sigma methodology individually and the emergence of Lean Six Sigma methodology, covered under the Lean Six Sigma: a historical outline section. The second part of the study examines the dimensions associated with Lean Six Sigma such as frameworks, critical success factors, critical failure factors, type of industry, performance metric, year, publisher and journal, based on a total of 223 articles published in 72 reputed journals from the year 2000 to 2019 as a literature review.

The adoption of Lean Six Sigma, as a continuous improvement methodology, has grown enormously in the manufacturing and few service sectors such as health care and higher education during the past decade. The study revealed that researchers came out with conceptual frameworks for the implementation of Lean Six Sigma, whereas the validation through case studies seems to be lacking. The integration of Lean Six Sigma and other approaches with a focus on sustainability and the environment has emerged as a research field. A few of the most common critical success and failure factors were identified from the articles studied during the study.

This paper may not have included some of the studies due to the inaccessibility and selection criteria followed for the study.

This paper will provide an initial introduction on Lean, Six Sigma and Lean Six Sigma and research insights Lean Six Sigma to beginners such as students, researchers and entry-level professionals.

The purpose of this paper is to develop a theoretical model to explain the impact of big data and predictive analytics (BDPA) on sustainable business development goal of the organization.

The authors have developed the theoretical model using resource-based view logic and contingency theory. The model was further tested using partial least squares-structural equation modeling (PLS-SEM) following Peng and Lai (2012) arguments. The authors gathered 205 responses using survey-based instrument for PLS-SEM.

The statistical results suggest that out of four research hypotheses, the authors found support for three hypotheses (H1-H3) and the authors did not find support for H4. Although the authors did not find support for H4 (moderating role of supply base complexity (SBC)), however, in future the relationship between BDPA, SBC and sustainable supply chain performance measures remain interesting research questions for further studies.

This study makes some original contribution to the operations and supply chain management literature. The authors provide theory-driven and empirically proven results which extend previous studies which have focused on single performance measures (i.e. economic or environmental). Hence, by studying the impact of BDPA on three performance measures the authors have attempted to answer some of the unresolved questions. The authors also offer numerous guidance to the practitioners and policy makers, based on empirical results.