Search results

The purpose of this study is to investigate the influence of IFRS convergence on annual report readability in an emerging market context, with an emphasis on the contents of management discussion and analysis (MD&A), notes to the accounts (Notes) and the whole annual report.

The study performs firm-fixed effect regression on a sample of 143 Indian listed companies over a period spanning from 2012 to 2021 to examine the influence of IFRS convergence on readability. This assessment primarily focuses on broader spectrums of readability dimensions, namely annual report length and complexity, wherein complexity is measured using the Gunning Fog, Flesch Reading ease and Flesch-Kincaid grade index.

As Indian firms shift to IFRS reporting, the findings suggest that annual reports have become significantly lengthier and more complex, causing deterioration in readability. The Notes section, in particular, exhibits the most significant increase in length and complexity, followed by the entire annual report and MD&A section. Furthermore, the findings also indicate that the complexity of the Notes section is instrumental in the observed complexity growth of the whole annual report in the post-IFRS period.

The current study employs readability indices rather than directly taking into consideration the opinions of actual users of annual reports to determine readability. As a result, the study does not provide direct evidence on how information in annual reports affects users' readability.

The findings provide insightful information to managers and policymakers about the difficulties stakeholders may encounter while reading IFRS-based annual reports, which ultimately impact their investment decisions. Thus, there is an important managerial implication from this, depending upon the severity of complexity corporations participate in while complying with IFRS in the post-IFRS period.

Analyzing the influence of exogenous information shock, such as IFRS convergence, on readability is critical, particularly for emerging markets like India, where a lack of financial literacy and weaker enforcement already have detrimental effects on the capital market. In light of this, the current study provides a comprehensive examination of the impact of IFRS convergence on annual report readability and contributes to the growing IFRS literature in the less explored emerging market context.

This study aims to empirically investigate the effect of International Financial Reporting Standards (IFRS) convergence on corporate risk disclosure, with a particular emphasis on the quantity and coverage of risk information. The research also conducts economic benefit and cost analysis to investigate the economic implications that may arise from the transition to IFRS reporting.

A content analysis approach is used to measure two broader dimensions of risk disclosure, namely, risk disclosure quantity and risk topic coverage. Furthermore, using firm-fixed effect regression on a sample of 143 Indian-listed companies, this study investigates the variations in these risk disclosure dimensions before (2012–2016) and subsequent to (2017–2021) the convergence with IFRS.

The empirical results of this research demonstrate that IFRS convergence has led to a significant improvement in firms’ risk disclosure across several dimensions. Particularly, during the post-IFRS period, firms’ usage of risk-related words and sentences has considerably surged in MD&A, Notes and whole annual reports. In addition, upon IFRS convergence, firms’ risk descriptions have become more extensive and evenly distributed across risk topic categories. Moreover, the in-depth benefit and cost analysis revealed that firms reporting under IFRS benefit from decreased cost of equity capital, but they also incur a higher cost of audit fees.

This study contributes to the literature in two ways. First, this is the only study, to the best of the authors’ knowledge, to conduct a broader examination of the impact of mandatory IFRS convergence on corporate risk disclosure, with a major focus on quantity and coverage of risk information. Second, by conducting economic benefit and cost analysis, this study provides novel insights into the critical role of IFRS risk disclosures toward multiple economic outcomes.

This study aims to investigate the effects of IFRS convergence on market liquidity and to analyze the firm-level heterogeneity in liquidity effects based on reporting incentive, firm size, ownership structure and firm leverage.

The empirical analysis is based on firm-fixed effect regression using several proxies of market liquidity as dependent variables. The sample consists of 337 firms listed on the National Stock Exchange (NSE) who shifted to IFRS from the financial year 2016–2017.

The empirical findings indicate that IFRS convergence has contributed to the significant increase in market liquidity in a weaker enforcement country, i.e. India. Additionally, when the study performs the heterogeneity test of IFRS impact, the results indicate the presence of significant cross-sectional differences in such liquidity effects across firms. Thus, altogether the findings suggest that both accounting convergence and firm-level factors are likely to be the mechanism underlying the observed improvement in market liquidity.

In the current literature, there is an ongoing debate about whether the observed post-IFRS effects are driven by the change in accounting standard per se or by other related factors. Therefore, by studying the liquidity effects of IFRS convergence in India, this study provides evidence regarding the sources of the documented IFRS effects. Moreover, the study indicates the significance of firm-level factors in determining the observed liquidity outcomes around IFRS adoption, which is unique to the literature.

This study aims to investigate redundant information in mandatory non-financial reports (NFRs) demanded by regulators, focusing primarily on overlapping disclosures in a new Indian sustainability reporting (SR) framework.

The study sample comprised NIFTY100 listed entities that published SR voluntarily during 2021–2022. The authors used content analysis and cosine similarity techniques to conceptually compare redundancy in SR disclosures with non-financial disclosures.

The findings reveal an information overlap in SR disclosure with other NFRs disclosures. The disclosures of Directors’ Report have higher cosine similarity scores at the firm level with SR, followed by the Management Discussion and Analysis report, Corporate Governance report and Corporate Social Responsibility report. The additional analysis reveals that qualitative disclosures and disclosures comprising governance factors overlap more in SR.

Policymakers should look to establish relevant disclosure guidelines in the SR system, and thereby, shed light on fundamental issues to enhance future SR framework reforms.

The study highlight the need for integration and amendment in the disclosure guidelines of NFRs to improve the overall transparency of the reports.

Previous studies have examined the redundancy in annual reports and SRs from the point of view of overlapping information. To the best author’s knowledge, this is possibly among the first studies to offer insights into the repetition of disclosures required by regulators in statutory NFRs based on environmental, social, and governance factors through the lenses of the institutional theory.

Generation scheduling (GS) is the most prominent and hard-hitting problem in the electrical power industry especially in an integrated power system. Countless techniques have been used so far to solve this GS problem for proper functioning of the units in the power system to dispatch the load economically to consumers at once. Therefore, this work aims to study for the best possible function of integrated power plants to obtain the most favourable solution to the GS problem.

An appropriate method works in a proper way and assures to give the best solution to the GS problem. The finest function of incorporated power plants should be mathematically devised as a problem and via that the aim of the GS problem to minimize the total fuel cost subject to different constraints will be achieved. In this research work, the latest meta-heuristic and swarm intelligence-based technique called grey wolf optimization (GWO) technique is used as an optimization tool that will work along with the formulated problem for correct scheduling of generating units and thus achieve the objective function.

The recommended GWO technique provides the best feasible solution which is optimal in its performance for different test cases in the GS problem of integrated power plant. It is further found that the obtained solutions using GWO method are better than the former reports of other traditional methods in terms of solution excellence. The GWO method is found to be unique in its performance and having superior computational efficiency.

Decision making is significant for effective operation of integrated power plants in an electrical power system. The recommended tactic implements a modern meta-heuristic procedure that is applied to diverse test systems. The method that is proposed is efficient in providing the best solutions of solving GS problems. The suggested method surpasses the early techniques by offering the most excellent feasible solutions. Thus, it is obvious that the proposed method may be the appropriate substitute to attain the optimal operation of GS problem.

Renewable energy sources are discontinuous and infrequent in nature, and it is tough to predict them in general. Further, integrating renewable energy source-based plants with the conventional plant is extremely difficult to operate and maintain. Operation of integrated power system is full of challenges and complications. To handle those complications and challenges, the GWO algorithm is suggested for solving the GS problem and thus obtain the optimal solution in integrated power systems by considering the reserve requirement, load balance, equality and inequality constraints.

The proposed system should be further tested on diverse test systems to evaluate its performance in solving a GS problem and the results should be compared. Computation results reveal that the proposed GWO method is efficient in attaining best solution in GS problem. Further, its performance is effectively established by comparing the result obtained by GWO with other traditional methods.

This paper aims to propose Hidden Converter (H-Converter) combined with dual port 3Ø inverter for energy storage application to produce wide range of voltage. Some of the application required wide range of voltages, but problem from E-chopper is either boost or buck mode of operations, both modes are not possible. To overcome this drawback, H-Converter is combined with dual port 3Ø inverter controlled by carrier-based pulse width modulation (CB-PWM) technique is added with zero sequence injection.

Hidden converter is a bidirectional DC-DC chopper used to convert fixed DC to variable DC and vice versa in both buck and boost modes of operations. Dual port inverter is combined with hidden DC-DC converter can produce wide range of voltages.

The bidirectional DC-AC converter requires less power for processing and consumes less power losses by using modest carrier built- pulse width modulation scheme through proposed zero structure addition.

By using this proposed strategy H-Converter can produce wide range of voltage in both the sides and mostly power is processed in the 3Ø inverter with a one stage conversion with less power loss. As a result, with one stage power conversion has more efficiency because of less power loss. This proposed converter has designed by analysis, and the real time result is tested in an experiment.

The purpose of this paper is to show that a popular conception among the practitioners is that Total Quality Service (TQS) has a long‐range perspective and the organizations that have adopted TQS could be able to see the results of their quality improvement initiatives only after a long duration. Hence firms that have been practicing TQS are interested to know the time duration before which they can get back the returns on investments in quality improvement programmes.

The present study attempts to empirically investigate the impact of TQS age on quality and operational performance. In order to examine the impact of TQS age on the different dimensions of TQS, out of the 12 critical dimensions of TQS, the two outcome constructs, namely Customer Focus and Satisfaction and Employee Satisfaction, have been considered for measuring quality performance while the other ten dimensions have been considered for measuring operational performance.

The results imply that the firms can get back their returns on investments in their quality management initiatives within three years of TQS implementation. The ways, commitment and the competence with which the TQS implementation is carried out are more important rather than the duration of TQS implementation. Further, among the successful firms, it has been observed that as TQS age increases, quality and operational performance also increases, since firms get more and more experienced in effective implementation of TQS in a continuously improving environment.

The impact of TQS age on quality and operational performance has been investigated in a developing economy with respect to the automobile service industry. Primarily this is a research paper and the results and findings will be of immense use to the business executives of service firms.

Among various metal oxide nano particles, MgO NPs and ZnO nanoparticles (NPs) in particular are gaining increasing attention due to their multifunctional characteristics, low cost and compatibility with textile materials. Each type of nanoparticle excels over others in certain properties. As such, it is often crucial to carry out comparative studies of NPs to identify the one showing higher efficiency/output for particular applications of textile products.

In the investigation reported in this paper, ZnO NPs and MgO NPs were synthesised via sol-gel technique and characterised. For comparative analysis, the synthesised NPs were evaluated for multiple properties using standard procedures before and after being applied on cotton fabrics by a dip-pad-dry-cure method.

XRD and FTIR analyses confirmed the successful synthesis of ZnO and MgO NPs. Homogeneous formation of desired NPs and their dense and uniform deposition on the cotton fibre surface were observed using SEM. ZnO NPs and MgO NPs coatings on cotton were observed to significantly enhance self-cleaning/stain removal properties achieving Grade 5 and Grade 4 categories, respectively. In terms of ultraviolet (UV) protection, ZnO or MgO NP coated fabrics showed UPF values of greater than 50, i.e. excellent in blocking UV rays. MgO NPs exhibited 20% cleaning efficiency in treating reactive dye wastewater against ZnO NPs which were 4% efficient in the same treatment, so MgO was more suitable for such type of treatments at low cost. Both NPs were able to impart multifunctionality to cotton fabrics as per requirement of the end products. However, ZnO NPs were better for stain removal from the fabrics while MgO NPs were appropriate for UV blocking.

It was therefore clear that multifunctional textile products could be developed by employing a single type of cost effective and efficient nano particles.

This study aims to examine the environmental effects of plastic waste on the atmosphere and its implications for disaster waste management. It focuses on using ammonia, pyrolyzed plastic oil and the effectiveness of alumina nanoparticles as a catalyst.

The research explores different combinations of conventional diesel and nano Al₂O₃ derived from pyrolyzed plastic oil (ranging from P10 to P40). Critical performance metrics evaluated include brake mean effective pressure (BMEP), brake specific fuel consumption, brake thermal efficiency and emissions of CO₂, CO and NOx. The study specifically investigates the impact of adding 50 ppm of Al₂O₃ nanoparticles to these blends.

The findings indicate that using blended fuels with nanoadditives significantly lowers pollution. Specifically, the P30 blend with 50 ppm of Al₂O₃ nanoparticles greatly reduced CO emissions. Additionally, the same blend reduced NOx emissions and CO₂ emissions. The P30 mix showed improved BMEP and brake thermal efficiency due to its density, calorific value and viscosity (6.3 bar). The P30 blend exhibited higher thermal efficiency due to decreased heat loss, whereas conventional diesel demonstrated the best mechanical efficiency due to its longer ignition delay.

This study highlights the potential of using Al₂O₃ nanoparticles and pyrolyzed plastic oil to reduce emissions and enhance the performance of internal combustion engines. It underscores the environmental benefits and implications for disaster waste management by converting plastic waste into useful resources and reducing air pollution.

In line with computational technological advances, obtaining optimal solutions for engineering problems has become attractive research topics in various disciplines and real engineering systems having multiple objectives. Therefore, it is aimed to ensure that the multiple objectives are simultaneously optimized by considering them among the trade-offs. Furthermore, the practical means of solving those problems are principally concentrated on handling various complicated constraints. The purpose of this paper is to suggest an algorithm based on symbiotic organisms search (SOS), which mimics the symbiotic reciprocal influence scheme adopted by organisms to live on and breed within the ecosystem, for constrained multi-objective engineering design problems.

Though the general performance of SOS algorithm was previously well demonstrated for ordinary single objective optimization problems, its efficacy on multi-objective real engineering problems will be decisive about the performance. The SOS algorithm is, hence, implemented to obtain the optimal solutions of challengingly constrained multi-objective engineering design problems using the Pareto optimality concept.

Four well-known mixed constrained multi-objective engineering design problems and a real-world complex constrained multilayer dielectric filter design problem are tackled to demonstrate the precision and stability of the multi-objective SOS (MOSOS) algorithm. Also, the comparison of the obtained results with some other well-known metaheuristics illustrates the validity and robustness of the proposed algorithm.

The algorithmic performance of the MOSOS on the challengingly constrained multi-objective multidisciplinary engineering design problems with constraint-handling approach is successfully demonstrated with respect to the obtained outperforming final optimal designs.

In recent years, the development of metaheuristic algorithms for solving optimization problems within a reasonable timeframe has garnered significant attention from the global scientific community. In this work, a new metaheuristic algorithm inspired by the inflection mechanism of the avian influenza virus H5N1 in poultry and humans, taking into account its mutation mechanism, called H5N1.

This algorithm aims to explore optimal solutions for optimization problems by simulating the adaptive behavior and evolutionary process of the H5N1 virus, thereby enhancing the algorithm’s performance for all types of optimization problems. Additionally, a balanced stochastic probability mechanism derived from the infection probability is presented. Using this mechanism, the H5N1 algorithm can change its phrase, including exploitation and exploration phases. Two versions of H5N1, SH5N1 and MH5N1, are presented to solve single-objective optimization problems (SOPs) and multi-objective optimization problems (MOPs).

The performance of the algorithm is evaluated using a set of benchmark functions, including seven unimodal, six multimodal, ten fixed-dimension multimodal to solve SOPs, ZDT functions and CEC2009 has been used to demonstrate its superiority over other recent algorithms. Finally, six optimization engineering problems have been tested. The results obtained indicate that the proposed algorithm outperformed ten algorithms in SOPs and seven algorithms in MOPs.

The experimental findings demonstrate the outstanding convergence of the H5N1 algorithm and its ability to generate solutions of superior quality.

Assembly sequence optimization is a difficult combinatorial optimization problem having to simultaneously satisfy various feasibility constraints and optimization criteria. Applications of evolutionary algorithms have shown a lot of promise in terms of lower computational cost and time. But there remain challenges like achieving global optimum in least number of iterations with fast convergence speed, robustness/consistency in finding global optimum, etc. With the above challenges in mind, this study aims to propose an improved flower pollination algorithm (FPA) and hybrid genetic algorithm (GA)-FPA.

In view of slower convergence rate and more computational time required by the previous discrete FPA, this paper presents an improved hybrid FPA with different representation scheme, initial population generation strategy and modifications in local and global pollination rules. Different optimization objectives are considered like direction changes, tool changes, assembly stability, base component location and feasibility. The parameter settings of hybrid GA-FPA are also discussed.

The results, when compared with previous discrete FPA and GA, memetic algorithm (MA), harmony search and improved FPA (IFPA), the proposed hybrid GA-FPA gives promising results with respect to higher global best fitness and higher average fitness, faster convergence (especially from the previously developed variant of FPA) and most importantly improved robustness/consistency in generating global optimum solutions.

It is anticipated that using the proposed approach, assembly sequence planning can be accomplished efficiently and consistently with reduced lead time for process planning, making it cost-effective for industrial applications.

Different representation schemes, initial population generation strategy and modifications in local and global pollination rules are introduced in the IFPA. Moreover, hybridization with GA is proposed to improve convergence speed and robustness/consistency in finding globally optimal solutions.

From the past few decades, parallel grippers are used successfully in the automation industries for performing various pick and place jobs due to their simple design, reliable nature and its economic feasibility. So, the purpose of this paperis to design a suitable gripper with appropriate design parameters for better performance in the robotic production systems.

In this paper, an enhanced multi-objective ant lion algorithm is introduced to find the optimal geometric and design variables of a parallel gripper. The considered robotic gripper systems are evaluated by considering three objective functions while satisfying eight constraint equations. The beta distribution function is introduced for generating the initial random number at the initialization phase of the proposed algorithm as a replacement of uniform distribution function. A local search algorithm, namely, achievement scalarizing function with multi-criteria decision-making technique and beta distribution are used to enhance the existing optimizer to evaluate the optimal gripper design problem. In this study, the newly proposed enhanced optimizer to obtain the optimum design condition of the design variables is called enhanced multi-objective ant lion optimizer.

This study aims to obtain optimal design parameters of the parallel gripper with the help of the developed algorithms. The acquired results are investigated with the past research paper conducted in that field for comparison. It is observed that the suggested method to get the best gripper arrangement and variables of the parallel gripper mechanism outperform its counterparts. The effects of the design variables are needed to be studied for a better design approach concerning the objective functions, which is achieved by sensitivity analysis.

The developed gripper is feasible to use in the assembly operation, as well as in other pick and place operations in different industries.

In this study, the problem to find the optimum design parameter (i.e. geometric parameters such as length of the link and parallel gripper joint angles) is addressed as a multi-objective optimization. The obtained results from the execution of the algorithm are evaluated using the performance indicator algorithm and a sensitivity analysis is introduced to validate the effects of the design variables. The obtained optimal parameters are used to develop a gripper prototype, which will be used for the assembly process.

The purpose of this paper is to establish a tolerance optimization method based on manufacturing difficulty computation using the genetic algorithm (GA) method. This proposal is among the authors’ perspectives of accomplished previous research work to cooperative optimal tolerance allocation approach for concurrent engineering area.

This study introduces the proposed GA modeling. The objective function of the proposed GA is to minimize total cost constrained by the equation of functional requirements tolerances considering difficulty coefficients. The manufacturing difficulty computation is based on tools for the study and analysis of reliability of the design or the process, as the failure mode, effects and criticality analysis (FMECA) and Ishikawa diagram.

The proposed approach, based on difficulty coefficient computation and GA optimization method [genetic algorithm optimization using difficulty coefficient computation (GADCC)], has been applied to mechanical assembly taken from the literature and compared to previous methods regarding tolerance values and computed total cost. The total cost is the summation of manufacturing cost and quality loss. The proposed approach is economic and efficient that leads to facilitate the manufacturing of difficult dimensions by increasing their tolerances and reducing the rate of defect parts of the assembly.

The originality of this new optimal tolerance allocation method is to make a marriage between GA and manufacturing difficulty. The computation of part dimensions difficulty is based on incorporating FMECA tool and Ishikawa diagram This comparative study highlights the benefits of the proposed GADCC optimization method. The results lead to obtain optimal tolerances that minimize the total cost and respect the functional, quality and manufacturing requirements.

Data mining is the process of detecting knowledge from a given huge data set. Among the data set, multimedia is the data which contains diverse data such as audio, video, image, text and motion. In this growing field of video data, mining the video data plays vital role in the field of video data mining. In video data mining, video data are grouped into frames. In this vast amount of video frames, the fast retrieval of needed information is important one. This paper aims to propose a Birch-based clustering method for content-based image retrieval.

In image retrieval system, image segmentation plays a very important role. A text file, normally, is divided into sections, that is, piece, sentences, word and character for this information which are organized and indexed effectively like in a video, the information is dynamic in nature and this information is converted to static for easy retrieval. For this, video files are divided into a number of frames or segments. After the segmentation process, images are trained for retrieval process, and from these, unwanted images are removed from the data set. The noise or unwanted image removal pseudo-code is shown below. In the code image, pixel value represents the value of the difference between the two adjacent image pixel values. By assuming a threshold for the image value, the duplicate images are found. After finding the duplicate image, it is removed from the data set. Clustering is used in many applications as a stand-alone tool to get insight into data distribution and as a pre-processing step for other algorithms (Ester et al., 1996). Specifically, it is used in pattern recognition, spatial data analysis, image processing, economic science document classification, etc. Hierarchical clustering algorithms are classified as agglomerative or divisive. BRICH uses clustering attribute (CA) and clustering feature hierarchy (CA_Hierarchy) for the formation of clusters. It perform multidimensional data objects. Every BRICH algorithm based on the memory-oriented information, that is, memory constrains, is involved in the processing of the data sets. This information is represented in Figures 6-10. For forming clusters, they use the amount of object in the cluster (A), the sum of all points in the data set (S) and need the square value of the all objects (P).

The proposed technique brings an effective result for cluster formation.

BRICH uses a novel approach to model the degree of inter-connectivity and closeness between each pair of clusters that takes into account the internal characteristics of the clusters themselves.

This study aimed to produce a functional gluten-free pasta, fortified with shrimp meat and shell powder, designed to be nutritionally rich and easily consumable and to meet the specific dietary needs of individuals with particular nutritional requirements.

The gluten-free pasta, developed using response surface methodology, incorporated 5.1% shrimp meat, 1.0% shrimp shell powder and 0.5% microbial transglutaminase, with psyllium husk powder utilized to enhance consistency. The pasta was dried using oven drying, fluidized bed drying and freeze-drying, and the resulting properties were characterized.

The nutritional content of the pasta remained consistent across the different drying methods. The cooking loss and weight gain values of the gluten-free pasta ranged from 6.95% to 7.29% and from 222.2% to 246.7%, respectively, with oven drying yielding the best cooking quality. The gluten-free pasta contained astaxanthin (1.361–1.691 ppm) and exhibited more than twice the antioxidant activity (0.158–0.187 µmol TE/g) compared to commercial pasta. While hardness, cohesion and chewiness values were highest in the freeze-dried pasta, the lowest springiness was observed. Texture profile analysis results were consistent with the scanning electron microscopy images. Mineral content was largely preserved by the freeze-drying method, with Na, P, K, Ca, Mg and Se being the most abundant, respectively. Gluten-free pasta offers a viable alternative for individuals with gluten intolerance, promotes increased consumption of aquatic products and contributes to waste recycling efforts.

The authors are aware that individuals with gluten intolerance have difficulty finding alternative foods.

Introducing a new formulation in gluten-free pasta production in order to overcome the difficulty of creating consistency in gluten-free dough. In addition to its nutritional value, a pasta that is rich in bioactive compounds has been produced, prominent in terms of astaxanthin, antioxidant activity and minerals.

Bring added value to pieces of shrimp meat with reduced economic value. Reuse of shrimp shells. Providing food security and a sustainable environment. Figure out the role of drying methods on gluten-free pasta comparatively with commercial pasta including gluten.

This study developed a novel functional gluten-free pasta formulation that promotes seafood consumption while offering ecological and economic benefits through the utilization of by-products.

When a large number of project proposals are evaluated to allocate available funds, grouping them based on their similarities is beneficial. Current approaches to group proposals are primarily based on manual matching of similar topics, discipline areas and keywords declared by project applicants. When the number of proposals increases, this task becomes complex and requires excessive time. This paper aims to demonstrate how to effectively use the rich information in the titles and abstracts of Turkish project proposals to group them automatically.

This study proposes a model that effectively groups Turkish project proposals by combining word embedding, clustering and classification techniques. The proposed model uses FastText, BERT and term frequency/inverse document frequency (TF/IDF) word-embedding techniques to extract terms from the titles and abstracts of project proposals in Turkish. The extracted terms were grouped using both the clustering and classification techniques. Natural groups contained within the corpus were discovered using k-means, k-means++, k-medoids and agglomerative clustering algorithms. Additionally, this study employs classification approaches to predict the target class for each document in the corpus. To classify project proposals, various classifiers, including k-nearest neighbors (KNN), support vector machines (SVM), artificial neural networks (ANN), classification and regression trees (CART) and random forest (RF), are used. Empirical experiments were conducted to validate the effectiveness of the proposed method by using real data from the Istanbul Development Agency.

The results show that the generated word embeddings can effectively represent proposal texts as vectors, and can be used as inputs for clustering or classification algorithms. Using clustering algorithms, the document corpus is divided into five groups. In addition, the results demonstrate that the proposals can easily be categorized into predefined categories using classification algorithms. SVM-Linear achieved the highest prediction accuracy (89.2%) with the FastText word embedding method. A comparison of manual grouping with automatic classification and clustering results revealed that both classification and clustering techniques have a high success rate.

The proposed model automatically benefits from the rich information in project proposals and significantly reduces numerous time-consuming tasks that managers must perform manually. Thus, it eliminates the drawbacks of the current manual methods and yields significantly more accurate results. In the future, additional experiments should be conducted to validate the proposed method using data from other funding organizations.

This study presents the application of word embedding methods to effectively use the rich information in the titles and abstracts of Turkish project proposals. Existing research studies focus on the automatic grouping of proposals; traditional frequency-based word embedding methods are used for feature extraction methods to represent project proposals. Unlike previous research, this study employs two outperforming neural network-based textual feature extraction techniques to obtain terms representing the proposals: BERT as a contextual word embedding method and FastText as a static word embedding method. Moreover, to the best of our knowledge, there has been no research conducted on the grouping of project proposals in Turkish.

The research presented in this study replicates and extends the QSport-10 scale proposed by Rial, Varela, Rial and Real in their 2010 study, by incorporating the Programme dimension into the original measurement of service quality in Physical Activity and Sports Centres (PSCs). The objective of this research is to examine the dimensionality of the QSport-10 scale and extend it to capture the additional Programme service quality dimension. Study results confirmed the dimensionality of the service quality measurement offered by the QSport-10 scale and presented strong empirical support for the existence of Programme, Installations and Staff dimensions. Programme dimension was considered the most important factor for the largest consumer segment in the study.

While rapid increase in demand for foods but limited availability of croplands has forced to adopt input-intensive farming practices to increase yield, there are serious long-term ecological implications including degradation of biodiversity. It is increasingly recognised that ensuring agricultural sustainability under the changing climatic conditions requires a change in the production system along with necessary policies and institutional arrangements. In this context, this chapter examines if climate-smart agriculture (CSA) can facilitate adaptation and mitigation practices by improving resource utilisation efficiency in India. Such an attempt has special significance as the existing studies have very limited discussions on three main aspects, viz., resource productivity, adaptation practices and mitigation strategies in a comprehensive manner. Based on insights from the existing studies, this chapter points out that CSA can potentially make significant contribution to enhancing resource productivity, adaptation practices, mitigation strategies and food security, especially among the land-constrained farmers who are highly prone to environmental shocks. In this connection, staggered trench irrigation structure has facilitated rainwater harvesting, local irrigation and livelihood generation in West Bengal. However, it is necessary to revisit the existing approaches to promotion of CSA and dissemination of information on the design of local adaptation strategies. This chapter also proposes a change in the food system from climate-sensitive to CSA through integration of technologies, institutions and policies.

The Fay and Riddell (F–R) formula is an empirical equation for estimating the stagnation-point heat flux on noncatalytic and fully catalytic surfaces, based on an assumption of equilibrium. Because of its simplicity, the F–R has been used extensively for reentry flight design as well as ground test facility applications. This study aims to investigate the uncertainties of the F-R formula by considering velocity gradient, chemical species at the boundary layer edge, and the thermochemical nonequilibrium (NEQ) behind the shock layer under various hypersonic NEQ flow environments.

The stagnation-point heat flux calculated with the F–R formula was evaluated by comparison with thermochemical NEQ calculations and existing flight experimental values.

The comparisons showed that the F–R underestimated the noncatalytic heat flux, because of the chemical composition at the surface. However, for fully catalytic heat flux, the F–R results were similar to values of surface heat flux from thermochemical NEQ calculations, because the F–R formula overestimates the diffusive heat flux. When compared with the surface heat flux results obtained from flight experimental data, the F–R overestimated the fully catalytic heat flux. The error was 50% at most.

The results provided guidelines for the F–R calculations under hypersonic flight conditions and for determining the approximate error range for noncatalytic and fully catalytic surfaces.

The purpose of this paper is to investigate the relationship between total quality management (TQM) practices and quality performance in Indian service companies.

The empirical data was collected using a self‐administered instrument that was distributed to 600 Indian service companies. Of the 600 instrument e‐mailed, 172 usable instrument were returned, yielding a response rate of 28.6 per cent. A stratified sampling procedure was utilized to obtain the minimum sample size of 600 from the four chosen service industries (i.e. Healthcare, Banking, Information and Communication Technology (ICT), and Hospitality). The data was analyzed using factor, Pearson's correlation, and multiple regression analyses.

The findings revealed that TQM practices were found to be partially correlated with quality performance of the Indian service companies. It was also found that quality culture was perceived as the dominant TQM practice in quality performance. The other practices such as quality systems, training and education, teamwork, and benchmarking showed a positive relationship with quality performance.

The research paper was limited by including only four industries in the selection of service companies in India, making this a possibly biased selection and it may not be adequate to generalize the results for the entire Indian service companies.

The study has contributed to the TQM literature with a better understanding of the 17 TQM practices and their association with a company's quality performance that will provide valuable knowledge to top‐management of service companies, to refine their current TQM practices and subsequently improve quality performance.

Most of the total quality management (TQM) programmes implemented in the printing industry fail to produce the intended benefit, because of the view that quality achievement is workers responsibility. The purpose of this paper is to examine the role management plays in the implementation of TQM programme in the Ghanaian printing firms.

The study employed mixed method in gathering relevant data. A cross-sectional survey questionnaire was given to 145 managers of registered members of Ghana Printers and Paper Converters Association, Southern Sector to assess the role management plays in TQM programme. Key informant interview was conducted among ten randomly selected production managers of printing firms to complement the survey data.

The study finds out that organizational performance (OP) is not significantly influenced by the level of commitment of top management in a printing organization. Rather OP is greatly influenced and determined by leadership styles of management and the quality policy which guides printing operations.

The Ghanaian printing industry can ensure better OP by considering the kind of leadership style exhibited in the firm and develop quality policy to guides printing operations and activities. No matter the level of commitment of organizational resources, if it is not back by a good leadership style and a quality policy, TQM initiative will not yield the intended result.

The study presents managerial issues and practices critical for successful TQM programme in the Ghanaian printing industry.

The purpose of this paper is to improve the positional accuracy, smoothness on motion and productivity of industrial robot through the proposed optimal joint trajectory planning method. Also a new improved algorithm, i.e. non-dominated sorting genetic algorithm-II (NSGA-II) with achievement scalarizing function (ASF) has been proposed to obtain better optimal results compared to previously used optimization methods.

The end effector positional errors can be reduced by limiting the uncertainties of dynamic parameter variations like torque rate of joints. The jerk induced in robot joints due to acceleration variations are need to be minimized which otherwise induces vibrations in the manipulator that causes deviation in the encoders. But these lead to a vast increase in total travel time which affects the cost function of trajectory planning. Therefore, these three objectives need to be minimized individually so that an optimal trajectory path can be achieved with minimum positional error.

The simulation results have been obtained by running the proposed hybrid NSGA-II with ASF in MATLAB R2017a software. The optimal time intervals have been used to calculate jerk, acceleration and torque values for consecutive points on the trajectory path. From the simulation and experimental results, it can be concluded that the optimization technique could be used effectively for the trajectory planning of six-axis industrial manipulator in the joint space on the basis of minimum time-jerk-torque rate criteria.

In this paper, a new approach based on hybrid multi-objective optimization technique by combining NSGA-II with ASF has been applied to find the minimal time-jerk- torque rate joint trajectory of a six-axis industrial robot for obtaining higher positional accuracy. The results obtained from the execution of algorithm have been validated through experimentation using Kawasaki RS06L industrial robot for a particular defined path.

This paper aims to find the optimal path using directionally driven self-regulating particle swarm optimization (DDSRPSO) with high accuracy and minimal response time.

This paper encompasses optimal path planning for automated wheelchair design using swarm intelligence algorithm DDSRPSO. Swarm intelligence is incorporated in optimization due to the cooperative behavior in it.

The proposed work has been evaluated in three different regions and the comparison has been made with particle swarm optimization and self-regulating particle swarm optimization and proved that the optimal path with robustness is from the proposed algorithm.

The performance metrics used for evaluation includes computational time, success rate and distance traveled.

Total quality management practices have been embraced by many quality-oriented firms around the world in order to improve performance in terms of quality, productivity, customer satisfaction and profitability. The purpose of this paper is to investigate the direct and indirect effects of TQM practices on various performance indicators specifically in the Indian manufacturing context. This paper focuses on developing an integrated model encompassing significant structural relations showing the linkage between TQM practices and multiple performance indicators – quality performance, customer satisfaction level, operating performance, employee performance, innovation performance, society results and financial performance. Apart from analyzing the direct relationship between constructs, the main purpose of this work is also to identify all the possible mediation effects of performance indicators on others using structural equation modeling (SEM).

An in-depth literature review was conducted to identify the key practices for the successful implementation of TQM in an organization as well as to explore TQM-performance effects. As a result, four TQM practices and seven performance indicators were identified. The data were collected from 260 Indian manufacturing organizations. After confirming the reliability and validity using exploratory and confirmatory factor analysis, the proposed hypotheses were tested using SEM.

Through testing the proposed hypothesized structural model, the direct and indirect effects of TQM practices have been examined. Moreover, this work developed an integrated model showing the interrelationships between TQM practices and performance indicators identified. The findings gave an insight that the effective implementation of TQM practices assists in reaping benefits in the every facet of an organization. By implementing these practices effectively, managers can expect to realize improvement in all these performance areas.

This study is subject to certain limitations. Even if all variables were found to be reliable, valid and satisfactory non-response bias test results, the remote possibility of bias in the data might not be fully ruled out. There is a probability of occurrence of common method variance and common method bias, since the data for both dependent and independent variables were collected from the same respondents in the organization. Additionally data on performance indicators were based on the respondent’s assessment and awareness only. The mediating relationship between individual TQM practice and performance indicators can be investigated in future studies. Since society results are a necessity in future, the direct and indirect practices focusing toward this can be explored. In addition, there is a research scope to identify the moderating effect of contextual factors such as degree of TQM implementation, scope of operation and type of organization.

The findings of the research offer some potentially valuable insights into the relevance of TQM practices and its strong linkage on various performance indicators, through which the overall organization performance can be enhanced. By implementing these practices effectively, managers can expect to realize improvement in all these performance areas. Hence, the managers can adopt this approach to assess their organization’s level in the quality path and as a guideline in implementing TQM practices. They can also measure the impacts of TQM practices on multiple performance measures in order to evaluate their TQM initiatives. Especially the deployment of quality culture is a requisite to excel in the every facet of performance. The positive relationship between TQM practices and various performance indicators can motivate the managers to allocate resources in time, effort and capital for TQM implementation in pursuing quality, leading to customer retention and competitiveness. The findings of the study strongly suggest the need for the holistic implementation of TQM practices for the survival of the organization.

While there is a considerable volume of researches carried out to investigate the linkage between TQM and organization’s performance across the globe, still little is evidenced regarding the mediating effect of performance indicators on others, especially in the Indian manufacturing context. The present paper attempts to extend and add knowledge to this line of research and to bridge the gap and provide sufficient empirical evidence specifically in the Indian scenario. Thereby helps the organization to follow a guideline to improve the overall performance.

The purpose of this paper is to examine the effect of total quality management (TQM) on service quality (SQ), market orientation (MO) and the subsequent effect on customer satisfaction (CS) and customer loyalty (CL). The research also analyses the direct effect of TQM on CS.

Data were collected from middle managers of retail banking sector in India using survey method. Structural equation modeling is used to analyze the data and to test the hypotheses.

The results show that TQM is positively associated with SQ, MO and CS. SQ and MO are significantly and positively associated with CS. CS subsequently leads to improved CL.

Enforcing TQM practices in their organizations as a change management tool, banks can achieve a greater degree of MO, improved SQ and higher CS to gain higher CL.

This paper empirically demonstrates that, by proper implementation of TQM in banks, the SQ and MO can be improved. Well implemented quality management practices, better customer service and market-focused attitude of banks will elevate the CS level and improve loyalty of customers toward the banks. With a little study has yet focused on India, the paper offers knowledge to banking professionals for increasing CL by effective implementation of TQM practices.

The paper aims to emphasise how switched systems can be analysed with elementary techniques which require only undergraduate-level linear algebra and differential equations. It is also emphasised how math software can become useful for simplifying analytic complications.

The time domain voltage balance methodology is used for stability analysis. As for deriving formulas for the asymptotic average of both capacitor voltage and inductor current, a new simple analytic method is introduced.

It was shown analytically that the time average of capacitor voltage converges to half of the source voltage. A formula for the time average of the current of the inductor is also computed. As a by-product, it was discovered that the period of the current is half of the switching period. Numerical simulations are obtained to illustrate the accuracy of the results.

Higher dimensional generalisations could become a bit complicated, as stability analysis of higher dimensional exponential matrices is not so easy to handle. On the other hand, the new discovery on the period of the current is more likely to give new insights into handling higher dimensional systems.

Analytical formulas are exact, and it helps in accurately modelling flying capacitor converts (FCCs) in practice.

FCC is well studied in engineering society. However, not much is done in obtaining closed form solutions using analysis. Also, math software is much used in computation of numerical results and obtaining simulations. In this paper, one more important aspect of math software is emphasised, namely, use symbolic and numeric computing environment Maple in analysis.

This chapter presents a case study on smallholder vulnerability and adaptation to long-term desiccation in the West African Sahel. Climatologists recognize Sahelian desiccation as a long-term multi-decadal dry period that persisted from roughly 1968 to 1995. This study draws on fine-scale ethnographic and daily rainfall data to elucidate local perspectives on this broad regional process. As such, this provides a window on the local lived experience of regional climate variability.

This study draws on multiple periods of ethnographic fieldwork in two different Mossi areas in north-central Burkina Faso (West Africa). Fieldwork consisted of key informant interviews, household surveys, and participant observation. The authors incorporate daily precipitation data from two meteorological stations provided by the General Directorate of Meteorology of Burkina Faso. Researchers assembled this data and graphed daily rainfall totals for individual rainfall seasons in the years preceding each period of fieldwork. The qualitative and quantitative data are analyzed by using a Sustainable Livelihoods (SL) framework.

The study finds that local perceptions of increased rainfall variability correspond to patterns evident in daily rainfall records for individual stations. Additionally, the authors document how rural producers are negatively affected by both intra-seasonal and multi-decadal rainfall variability. Mossi smallholders have adapted through new cropping patterns, livelihood diversification, and investments in agricultural intensification. These adaptations have been largely successful and could be adopted by other Sahelian groups in their efforts to adapt to climate change.

Fieldwork took place over several years in two different departments and five localities. The two anthropologists used a common livelihoods analytical framework but different research protocols over this time span. Thus, the data collection was not systematic across all locations and time periods. This limits the degree to which results are representative beyond surveyed localities at their respective points in time.

This study presents local views and perceptions of regional climate variability and ecological change. It is a rare bottom-up perspective supplemented with precipitation data.

Previous research showed that there are some barriers which hinder the implementation of total quality management (TQM) in organizations. But no study has been undertaken to understand the interaction among these barriers and to develop a hierarchy of TQM barriers model. There is an urgent need to analyze the behavior of these barriers so that TQM may be successfully implemented. This paper therefore, aims to understand the mutual interaction of these barriers and identify the “driving barriers” (i.e. which influence the other barriers) and the “dependent barriers” (i.e. which are influenced by others).

In this paper, an interpretive structural modeling (ISM) based approach has been utilized to understand the mutual influences among the barriers of TQM.

In the present research work, 12 TQM barriers are identified through the literature review and expert opinion. The research shows that there exist two groups of barriers, one having high driving power and low dependency requiring maximum attention and of strategic importance (such as lack of top‐management commitment, lack of coordination between departments) and the other having high dependence and low driving power and are resultant effects (such as high turnover at management level, lack of continuous improvement culture, employees' resistance to change).

The adoption of such an ISM‐based model on TQM barriers in service organizations would help managers, decision makers, and practitioners of TQM in better understanding of these barriers and to focus on major barriers while implementing TQM in their organizations.

Presentation of TQM barriers in the form of an ISM‐based model and the categorization into driver and dependent clusters is a new effort in the area of TQM.

This study aims to examine the correlation between the readability of financial statements and the likelihood of future stock price crashes in nonfinancial companies listed on the Egyptian Stock Exchange. It further explores the possible moderating effect of audit quality on this relationship.

The study uses ordinary least squares regression, generalized least squares estimation and two-stage least squares methodology to examine and validate the research hypotheses. The sample comprises 107 nonfinancial companies registered on the Egyptian Stock Exchange from 2016 to 2019.

The results reveal a significant negative association between the readability of financial statements and stock price crash risk. This suggests that companies with more complex financial statements tend to experience higher future crash risks. Additionally, the study identifies audit quality as a significant moderating factor. Higher audit quality, often indicated by engagements with Big-4 audit firms, strengthens the influence of financial statements readability on stock price crash risk. This implies that while high audit quality enhances investor confidence and market stability, it also accentuates the negative consequences of complex financial statements.

The findings of this paper have significant implications for regulators and standard-setting bodies in Egypt. They should consider refining and revising existing standards to emphasize the importance of enhancing the readability of financial reports. Additionally, auditing firms should actively engage in efforts to ensure clearer and more transparent financial reporting. These actions are vital for boosting investor confidence, strengthening Egypt’s capital market and mitigating potential risks associated with information opacity and complexity.

This study represents a pioneering endeavor within the Arab and Egyptian financial environments. To the best of the author’s knowledge, it is the first examination of the association between the readability of financial statements and stock price crash risk in these contexts. Furthermore, it explores factors such as audit quality that may influence this connection.

The purpose of the present study is to evaluate total quality service (TQS) from employees’ perspective, as they have direct contact with both customers and management. The study is descriptive and exploratory in nature.

The data were collected from 195 frontline employees of a leading Indian private sector bank. The study is confined to that bank's branches operating in a northern city of India.

The study reveals that though employees have made serious contributions towards the success of TQS, bank policies do not leave much scope for their autonomy and management lags in its efforts in implementing TQS properly. SEM analysis indicates that TQS has a significant impact on employees’ organizational commitment.

TQS is a systematic way of guaranteeing that all activities within an organization happen as per plan and meet the customers’ expectations. TQS aids the service marketers in the task of establishing and maintaining the customer base, which is the greatest challenge in today's competitive world. In this context, the present study seeks to evaluate the overall TQS prevalent in banking services.

The purpose of this paper is to investigate the influences of total quality management (TQM) and supply chain integration (SCI) practices on firm performance (FP) of container shipping industry in Singapore.

A survey was conducted with 159 container shipping companies in Singapore to examine the interrelationships between SCI and TQM practices and FP. A stepwise multiple regression analysis using SPSS version 14.0 was performed on the data.

Statistical results suggest that both TQM and SCI practices have positive effects on service quality and FP but at different extents, while TQM also contributes positively to SCI.

The small sample is the main limitation. The findings bear important implications for further research as understanding these dimensions can help to position key changes and industry improvement that will increase revenue and reduce cost to the container shipping companies in Singapore.

This research provides guidelines for shipping managers on how to implement the SCI and TQM practices appropriately to boost their FP to the fullest extent.

This study has unique implications for social sustainability especially the container shipping industry, which is hard pressed to combat the challenges within the logistics/transportation sector.

This is perhaps the first study that examines the influence of SCI and TQM practices on the performance of container shipping firms that helps them see beyond the silo mentality and focus on greater value addition in FP.

The purpose of this paper is to present a novel Kriging meta-model assisted method for multi-objective optimal tolerance design of the mechanical assemblies based on the operating conditions under both systematic and random uncertainties.

In the proposed method, the performance, the quality loss and the manufacturing cost issues are formulated as the main criteria in terms of systematic and random uncertainties. To investigate the mechanical assembly under the operating conditions, the behavior of the assembly can be simulated based on the finite element analysis (FEA). The objective functions in terms of uncertainties at the operating conditions can be modeled through the Kriging-based metamodeling based on the obtained results from the FEA simulations. Then, the optimal tolerance allocation procedure is formulated as a multi-objective optimization framework. For solving the multi conflicting objectives optimization problem, the multi-objective particle swarm optimization method is used. Then, a Shannon’s entropy-based TOPSIS is used for selection of the best tolerances from the optimal Pareto solutions.

The proposed method can be used for optimal tolerance design of mechanical assemblies in the operating conditions with including both random and systematic uncertainties. To reach an accurate model of the design function at the operating conditions, the Kriging meta-modeling is used. The efficiency of the proposed method by considering a case study is illustrated and the method is verified by comparison to a conventional tolerance allocation method. The obtained results show that using the proposed method can lead to the product with a more robust efficiency in the performance and a higher quality in comparing to the conventional results.

The proposed method is limited to the dimensional tolerances of components with the normal distribution.

The proposed method is practically easy to be automated for computer-aided tolerance design in industrial applications.

In conventional approaches, regardless of systematic and random uncertainties due to operating conditions, tolerances are allocated based on the assembly conditions. As uncertainties can significantly affect the system’s performance at operating conditions, tolerance allocation without including these effects may be inefficient. This paper aims to fill this gap in the literature by considering both systematic and random uncertainties for multi-objective optimal tolerance design of mechanical assemblies under operating conditions.

The purpose of this study is to augment the perceived service quality (PSQ) dimensions as well as evaluate the effects of pandemic susceptibility and severity by appending crucial enablers of customer satisfaction (CS) in the restaurant industry (RI).

The top 10 restaurants from Mumbai and Kolkata were selected based on the Conde Nast Traveller Magazine List, 2020. The study used a cross-sectional design to collect responses from 840 respondents across the two major metropolitans of India after the second wave of COVID-19 by employing a structured questionnaire. The proffered hypotheses in this study were validated using factor analysis and structural equation modelling (SEM) techniques.

This research espies pivotal facilitators of CS and customers' perceived value (CPV). The results divulge that food quality (FQ) and tangibility dimensions markedly enhance CS while the FQ and digital technologies (DT) dimensions augment CPV in Indian restaurants. The study asserts that CPV acts as a partial mediator between FQ and DT on the one hand and CS on the other. In addition, perceived pandemic susceptibility (PPSU) and perceived pandemic severity (PPSE) moderate the association between CPV and CS in restaurants.

This study exemplifies the critical enablers of CS and CPV that may invigorate restaurant owners, managers and policymakers to prioritize the identified dimensions to aggrandize CS and CPV quotients.

The study enriches the literature by assimilating DT and CPV dimensions in a comprehensive theoretical framework. The research is unique in attempting to unfurl the moderating effects of PPSU and PPSE in the RI.

Dynamic economic and emission dispatch (DEED) aims to optimally set the active power generation with constraints in a power system, which should target minimum operation cost and at the same time minimize the pollution in terms of emission when the load dynamically changes hour to hour. The purpose of this study is to achieve optimal economic and emission dispatch of an electrical system with a renewable generation mix, consisting of 3-unit thermal, 2-unit wind and 2-unit solar generators for dynamic load variation in a day. An improved version of a simple, easy to understand and popular optimization algorithm particle swarm optimization (PSO) referred to as a constriction factor-based particle swarm optimization (CFBPSO) algorithm is deployed to get optimal solution as compared to PSO, modified PSO and red deer algorithm (RDA).

Different model with and without wind and solar power generating systems; with valve point effect is analyzed. The thermal generating system (TGs) are the major green house gaseous emission producers on earth. To take up this ecological issue in addition to economic operation cost, the wind and solar energy sources are integrated with the thermal system in a phased manner for electrical power generation and optimized for dynamic load variation. This DEED being a multi-objective optimization (MO) has contradictory objectives of fuel cost and emission. To get the finest combination of the two objectives and to get a non-dominated solution the fuzzy decision-making (FDM) method is used herein, the MO problem is solved by a single objective function, including min-max price penalty factor on emission in the total cost to treat as cost. Further, the weight factor accumulation (WFA) technique normalizes the pair of objectives into a single objective by giving each objective a weightage. The weightage is decided by the FDM approach in a systematic manner from a set of non-dominated solutions. Here, the CFBPSO algorithm is applied to lessen the total generation cost and emission of the thermal power meeting the load dynamically.

The efficacy of the contribution of stochastic wind and solar power generation with the TGs in the dropping of net fuel cost and emission in a day for dynamic load vis-à-vis the case with TGs is established.

Cost and emission are conflicting objectives and can be handled carefully by weight factors and penalty factors to find out the best solution.

The proposed methodology and its strategy are very useful for thermal power plants incorporating diverse sources of generations. As the execution time is very less, practical implementation can be possible.

As the cheaper generation schedule is obtained with respect to time, cost and emission are minimized, a huge revenue can be saved over the passage of time, and therefore it has a societal impact.

In this work, the WFA with the FDM method is used to facilitate CFBPSO to decipher this DEED multi-objective problem. The results reveal the competence of the projected proposal to satisfy the dynamic load demand and to diminish the combined cost in contrast to the PSO algorithm, modified PSO algorithm and a newly developed meta-heuristic algorithm RDA in a similar system.

Enterprises realize that customers are their most important asset and recognize that a high level of customer satisfaction can only be achieved by enhancing service quality. Thus, how enterprises acquire customer knowledge by which to initiate and maintain customer relationships, as well as to enhance service quality has become an important issue. The paper aims to discuss these issues.

This study uses a questionnaire and statistical analytical techniques to explore the impact of customer knowledge and customer relationship management (CRM) on service quality.

The results indicated that customer knowledge has a positive influence on service quality and CRM is the partial intervening variable between customer knowledge and service quality. That is, customer knowledge enhances the CRM, while CRM, in turn, increases service quality and provides competitive advantages.

This research explored the impact of customer knowledge and CRM on service quality based on the company's perception and there was no validation on the customers' perception of the company. Therefore, it is suggested that future research should involve company staff, current customers, and latent customers to strengthen the triangulation.

The results found that customer knowledge is indeed an important source of competitive advantage. Hence, enterprises should acquire valuable customer knowledge in order to enhance the relationship with customers, as well as enhance their service quality.

There is still little related literature investigating the relationships amongst customer knowledge, CRM, and service quality. Hence, this study applies questionnaire methods as the main research tools in order to conduct an in-depth investigation into the influence of customer knowledge and CRM on service quality. Furthermore, this research is expected to provide enterprises with valuable suggestions for management practices.

Any node in a mobile ad hoc network (MANET) can act as a host or router at any time and so, the nodes in the MANET are vulnerable to many types of attacks. Sybil attack is one of the harmful attacks in the MANET, which produces fake identities similar to legitimate nodes in the network. It is a serious threat to the MANET when a malicious node uses the fake identities to enter the network illegally.

A MANET is an independent collection of mobile nodes that form a temporary or arbitrary network without any fixed infrastructure. The nodes in the MANET lack centralized administration to manage the network and change their links to other devices frequently.

So for securing a MANET, an approach based on biometric authentication can be used. The multimodal biometric technology has been providing some more potential solutions for the user to be able to devise an authentication in MANETs of high security.

The Sybil detection approach, which is based on the received signal strength indicator (RSSI) variations, permits the node to be able to verify the authenticity of communicating nodes in accordance with their localizations.

As the MANET node suffers from a low level of memory and power of computation, there is a novel technique of feature extraction that is proposed for the multimodal biometrics that makes use of palm prints that are based on a charge-coupled device and fingerprints, along with the features that are fused.

This paper proposes an RSSI-based multimodal biometric solution to detect Sybil attack in MANETs.

The results of the experiment have indicated that this method has achieved a performance which is better compared to that of the other methods.

This paper presents Quick Changeover Design (QCD), which is a structured methodological approach for Original Equipment Manufacturers to drive and support the design of machines in terms of rapid changeover capability.

To improve the performance in terms of set up time, QCD addresses machine design from a single-minute digit exchange of die (SMED). Although conceived to aid the design of completely new machines, QCD can be adapted to support for simple design upgrades on pre-existing machines. The QCD is structured in three consecutive steps, each supported by specific tools and analysis forms to facilitate and better structure the designers' activities.

QCD helps equipment manufacturers to understand the current and future needs of the manufacturers' customers to: (1) anticipate the requirements for new and different set-up process; (2) prioritize the possible technical solutions; (3) build machines and equipment that are easy and fast to set-up under variable contexts. When applied to a production system consisting of machines subject to frequent or time-consuming set-up processes, QCD enhances both responsiveness to external market demands and internal control of factory operations.

The QCD approach is a support system for the development of completely new machines and is also particularly effective in upgrading existing ones. QCD's practical application is demonstrated using a case study concerning a vertical spindle machine.

The purpose of this paper is to investigate the effects of internal marketing on service quality and the mediating role of OCB in their relationship.

A total of 162 random samples of the customers and employees of the Greater Tehran Gas Company were taken. The applied research methodology is based on survey design techniques, specifically structural equations modelling. To test the model questionnaire was designed, applied and then analyzed.

Findings clearly demonstrate that internal marketing actions can have a direct, meaningful and positive effect on organizational citizenship behaviours. Furthermore, the conceptual model shows that organizational citizenship behaviours act as a mediator between internal marketing and service quality.

The present study does have a number of methodological limitations that suggest areas for future research. First, the sample was from a public company, and this unique setting may limit the external validity of the findings. Second, the country in which the authors tested the hypothesis is an Islamic country with different cultural values from western countries and this fact might limit the generalization of the findings. But the authors believe that the proposed model and results of this research can aid service organization to offer better service quality to both their internal and external customers.

The paper may be of high value to researchers and managers in Marketing and Human Resource Management scopes. Results of this research have valuable guideline that can have tangible outcome for organization.

Diesel engine can produce power more efficiently with lower exhaust emissions when operated at optimum input parameter settings. To achieve this goal, the purpose of this paper is to optimize the input parameters of diesel engine which will lead to optimum performance and exhaust emissions.

To achieve the goal of improving diesel engine performance and exhaust emissions, four input parameters were considered in the study. Five different levels of each input parameter were taken. Four response variables under no load, half load and full load conditions were recorded. Experiments were performed in random manner according to selected Taguchi L25 orthogonal array. The data were analyzed using grey relational analysis coupled with principal component analysis. Analysis of S/N ratio was performed to obtain the optimum combination of input parameters. The grey relational grade at optimum setting of the input parameters was obtained by regression analysis.

Results of the current research work give the optimum input parameter settings for no load, half load and full load conditions of diesel engine. Engine produces power more efficiently with low exhaust emissions when operated at these optimum settings.

In view of the compliance to the stringent air pollution norms of the nations and fast depleting fossil fuels, it is of the utmost importance to design and operate the engine in the optimum range of its input parameters so that it produces more power with low exhaust emissions. This paper aims at optimizing input parameters of diesel engine to improve performance and exhaust emissions. Results of the study presented in this paper are significantly useful for diesel engine-related researchers and professionals.

From the literature review, it appears that only few researchers have conducted studies pertaining to the optimization of the input parameters of diesel engine to improve performance or exhaust emissions. Although few studies related to the optimization of compression ratio, fuel injection timing, fuel injection pressure and air pressure have been reported, no work related to optimization of temperature and pressure of turbocharged air has been reported. Therefore, the main focus of the current research work is on optimizing the charge air temperature and pressure with respect to performance and exhaust emissions.

The purpose of this paper is to identify and assess the perception of customers (students) about the services provided by Brazilian universities, through the identification of the attributes that impact on customer satisfaction and the dimensions or factors related to quality in services. This may generate a better management and seek more competitive edge in graduate courses.

The research method was developed in two phases: the first one is characterized by a qualitative and exploratory approach and the second one as a quantitative research of conclusive character. In the qualitative phase, in-depth interviews were implemented with a semi-structured approach. A survey was performed in the final phase and a multivariate statistical technique was used for the data analysis.

The results echoed in a set of 40 analyzed attributes (variables), distributed in six dimensions of quality in services, in the graduate courses (second cycle) of administration, which could serve as a basis for orienting other Brazilian universities.

The data analysis did not include crossed techniques that could have enriched the analysis process. Another limitation that can be pointed out is the fact of having only adopted a factor analysis method to identify the dimensions of service quality that influence customer satisfaction (students). In addition, data collection was cross-sectional, which does not allow any change verification of the respondents’ perception.

Taking into account the current scenario of increased competition between the Brazilian universities to attract and retain students, the knowledge of student’s preferences and the dimensions of quality service can effectively contribute in the development of strategies and actions for an effective graduate programs management (second cycle), and for their consolidation in the Brazilian market.

The development of more adequate courses, in terms of level of quality and relevancy.

The identification of the attributes that represent the quality dimensions, related to the services provided, can assist any Brazilian university to prioritize its strategies and actions and to contribute to excellence in education. In addition, it may encourage customer retention (students) and consolidate its market position. Moreover, the study can contribute as a source of empirical data for transferability and benchmark strategies in other contexts for Brazilian universities.

Implementing total quality management (TQM) is not without difficulties and achieving its promised benefits is not easy. The purpose of this paper is to identify the barriers to TQM successful implementation.

A literature review has been done to explore the major reasons for the failure of TQM programmes.

An examination of 54 TQM empirical studies identified 54 obstacles to successful TQM implementation. There are both theoretical and practical difficulties in applying TQM in organisations. An ineffective TQM package, inappropriate TQM implementation methods and an inappropriate environment for implementing TQM are the main reasons for TQM failure. The most frequently mentioned reasons for TQM implementation failures include insufficient education and training, lack of employees’ involvement, lack of top management support, inadequate resources, deficient leadership, lack of a quality-oriented culture, poor communication, lack of a plan for change and employee resistance to the change programme.

The review was limited to articles written in English language during the past 30 years (1980-2010).

TQM does deliver better performance when an appropriate model of TQM is appropriately implemented in a supportive environment. The findings of this paper provide managers with a practical understanding of the factors that are likely to obstruct TQM implementation. Managers should overcome these barriers to achieve the TQM benefits.

Understanding the factors that are likely to obstruct TQM implementation will help organisations in planning better TQM models.

The purpose of this paper is to provide a framework for designing a multiple performance measurement tool for evaluating, comparing and benchmarking the working of engineering educational institutes in a group based on total quality management (TQM) criteria and performance measurement criterion, respectively.

Proposed framework is based on fuzzy analytic hierarchy process (FAHP) which takes in to account the fuzziness of human opinion for realistic outcome and generalization of the results. Based on the proposed framework a case study was conducted on engineering institutes of central India for collecting data and analyzing the current practices followed in these institutes. A relationship among TQM implementation criterion was developed, their respective weights derived and then institutes were ranked.

It was found that the rank of institutions based on both the criterion is same, which indicates that the institutes having better TQM implementation have better performance.

The research in this paper is limited to Indian scenario; studies in other countries and sectors may be conducted to compare the results obtained.

The results will help policy makers in identifying institutions having poor performance in the region.

The paper is navel in its attempt to provide a model based on TQM criteria for evaluating the working of engineering educational institutes in a group in terms of their relative weightage and benchmark.

The purpose of this paper is to systematically review the functionalities, safety regulations and product applications of herb Stevia rebaudiana extract. This plant material is embedded with multiple functionalities such as antioxidant, antidiabetics, anti-inflammation and antimicrobial. The regulations released from global authorities are covered to ensure the safety premise of stevia. Besides, the product applications of the extract of aerial parts of the herb S. rebaudiana helps us to recognize its value from commercial side.

Relevant literatures are selected and obtained from main scientific databases such as Google Scholar, Web of Science, PubMed and trade magazines published between 2000 and 2023. The keywords and their possible combinations such as sweetening, antioxidant, antidiabetics, anti-inflammation, safety and product development were used to ensure the preciseness and completeness of literature searching. Major data such as sweetness, total phenolic content and dose together with latter critical conclusions from searched publications were appropriately used and discussed. In this review, approximately 150 scientific literatures were meticulously ordered and analyzed. In applications, it is the first time that sentiment analysis was used to obtain a market assessment of the stevia-containing products.

This review paper helps rearrange the scientific affairs of those stevia extract’s functions like sweetening, antioxidant, antidiabetics and inflammation. Sweetness indexes of steviol glycosides were summarized together for comparison while various in vitro and in vivo approaches were reviewed to quantify those functions’ capacities and to depict the related mechanism. The regulation of steviol glycoside compounds such as rebaudioside A was established by global authorities such as US Food and Drug Administration and Joint FAO/World Health Organization Expert Committee to ensure the safety endorsement before commercialization. Then, this study discussed about the market performance of stevia ingredients or products with the self-developed data analytics. This study also investigated the product development progress of stevia-containing food products in the categories of beverage, bakery, dairy and confectionery. Those stevia-containing food consumer goods can be acceptable by certain consumers.

This review paper precisely presents the evidential information about the stevia’s multiple functionalities with mechanisms and global regulation milestones. To the best of the authors’ knowledge, it is then the first time to probe the stevia-containing products’ market performance through data analytics.

This research aims to propose a framework for measuring customer loyalty for third party logistics (3PL) industry by exploring the attributes that are more attractive to customers and ascertain the mechanisms for increasing customer loyalty in 3PL industry.

Data were collected from one hundred and thirty-three (133) respondents who were employees of different industries that outsource 3PL services. The partial least square structural equation modeling (PLS–SEM) was deployed for analysis.

The results showed that service quality has a significant positive impact on customer orientation, customer satisfaction and relationship quality. On the other hand, customer orientation has been observed to positively impact customer satisfaction but an insignificant impact on customer loyalty and relationship quality. Customer satisfaction has a significant positive impact on relationship quality but an insignificant impact on customer loyalty. Also, relationship quality has a significant positive impact on customer loyalty.

The results recommend that 3PL companies' managers focus more on developing quality relationships with their customers, delivering exemplary service quality and offering customer orientation.

This study will help the stakeholders gain much more understanding and insights on how competitive advantage can be achieved and, consequently, help 3PL become the market leaders.

The purpose of this paper is to analyze if and how country- and sector-related contingency factors affect the implementation of TQM practices and various performance measures within a TQM-performance relationships model framework.

The authors used data from 156 firms in Turkey and 132 firms in North Cyprus (NC) to test the model relationships by utilizing multiple group structural equation modeling (SEM).

The study finds support for both the universal and the contingency argument within the context of country and sector analyses. Although our findings suggest no differences across the two countries, the authors find evidence for differences across sectors in terms of their TQM practices and performance outcomes. In the case of NC firms, the direct effects of TQM on human resource results and customer results constituted the missing linkages in the performance excellence framework.

This study suffers from the same limitations common to all survey research. However, it contributes strongly to the limited TQM contingency research by providing new findings and insights. This study must be replicated in different countries and other types of contextual factors must be used to determine if and how they moderate the model relationships. Other theories are also needed to better explain some of the relationships.

There needs to be a more holistic approach to quality management and increased institutional support for quality initiatives in developing countries. Through proper alignment and integration of their different components, organizations can realize maximum improvement in their business results. Understanding the sector level contingencies before implementing a performance excellence model is also recommended.

The study has several social, economic and policy implications, including the need to improve employees’ work environment to improve their lives and prevent brain drain; to pass legislation to improve lax consumer laws; to found quality institutes to promote the education, training, qualification and professional development of employees working in the various sectors of the economy; and for government and employers to realize the importance of valuing stakeholders and delivering value and results to them to ensure long-term success.

This is one of the few studies in TQM contingency research that tests various relationships among TQM and business results by using country and sector as contingency factors.

This paper aims to find the minimum possible number of phasor measurement units (PMUs) to achieve maximum and complete observability of the power system and improve the redundancy of measurements, in normal cases (with and without zero injection bus [ZIB]), and then in conditions of a single PMU failure and outage of a single line.

An efficient approach operates adequately and provides the optimal solutions for the PMUs placement problem. The finest function of optimal PMUs placement (OPP) should be mathematically devised as a problem, and via that, the aim of the OPP problem is to identify the buses of the power system to place the PMU devices to ensure full observability of the system. In this paper, the grey wolf optimizer (GWO) is used for training multi-layer perceptrons (MLPs), which is known as Grey Wolf Optimizer (GWO) based Neural Network (“GW-NN”) to place the PMUs in power grids optimally.

Following extensive simulation tests with MATLAB/Simulink, the results obtained for the placement of PMUs provide system measurements with less or at most the same number of PMUs, but with a greater degree of observability than other approaches.

The efficiency of the suggested method is tested on the IEEE 14-bus, 24-bus, New England 39-bus and Algerian 114-bus systems.

This paper proposes a new method for placing PMUs in the power grids as a multi-objective to reduce the cost and improve the observability of these grids in normal and faulty cases.

The purpose of this paper is to present a systematic literature review to identify new avenues of research in line with the ongoing changes in quality and management required to firms, especially regarding customers.

This study uses a systematic review of the literature contained in the three databases Ebsco, JSTOR, and Springerlink and on the search engine Google Scholar.

An analysis of the literature identifies three different clusters of papers: “identification” papers, which show that customer focus has gained importance in recent times; “implementation” papers, which highlight that a general or shared model or scale to successfully implement total quality management (TQM) does not yet exist; and “impact-on-performance” papers, which show that few studies have considered the relationship between TQM and the issues of both marketing and performance, underlining the most significant gap in the TQM literature.

This study is limited by the small number of databases and search engines used and by the restricted number of keywords used in searching these sources.

This work highlights a gap in the existing research and thus an incomplete consideration of the interplay between management, marketing, and quality issues, all centered on customers and other stakeholders. Researchers and firms are thus advised to adopt a wider view that considers the role of the quality process to support the firm’s engagement of customers in activities that enhance both the customer role and customer satisfaction.

This study uses a systematic literature review to review all critical factors of TQM and identifies new research avenues and different approaches to implementing TQM, focusing on the central role that customers play in achieving firm success.

The purpose of this study is to assess the impact of mobile phone usage on sales and profit as the indicator of business performance, to analyse the facilitating roles of mobile phones and factors affecting farmers' decision to use the mobile phone in agribusiness activities.

Intensive farming was selected in this study due to its higher profitability than other crops. Data were compiled from field surveys of 1,040 farmer households in vegetable production regions of Indonesia. This study employed structural equation modelling, identifying mediating variables and quantifying multiple endogenous variables' direct and indirect effects in simultaneous regression equations.

The results indicate that mobile phone usage enabled farmers to increase sales, obtain market information, acquire improved agronomic technology, access credit and contact customers. The device enhanced profit through mediations of high sales, reasonable prices and access to credit and market information. The personal attributes of farmers determined the adoption of mobile phones to support agribusiness activities.

This study paid attention to the use of mobile phones, which was considered an integral technology of information and communication. Other components, such as personal computers and other Internet-based devices, need further study.

As the rate of mobile phone use was still low, farmers should be encouraged to utilise the device. Socialisation and specially designed training workshops on agribusiness information systems using mobile phones are of the best ways.

Using structural equation modelling enables to analyse of multi-dependent variables in one model. Farm-level data provide a real situation, and policy implications should address the right target. The subject of this investigation is a semi-subsistence farm household that lacked access to information and communication technology.

The purpose of this paper is to explore the factors that lead to consulting success in the enterprise software environment and thereby develop a refined consulting services maturity (CSM) model which includes prioritised best practices grouped under eight key focus areas (KFAs).

The research is conducted among Tier‐1 enterprise resource planning (ERP) vendors using interviews, focus group sessions, and a web survey. Based on the findings of the survey, the CSM model is improved, refined, and ultimately ratified by a number of experienced ERP sector practitioners.

The fundamental basis of the CSM model is that an enterprise software company will be able to improve the maturity level of its consulting services operations by focusing on certain key areas and adopting prioritised best practices in each of the key areas. These key areas include leadership, values, consulting skills, consulting success factors, adaptability, project management practices, profitability, and customer focus. The level of maturity of the organisation increases as best practices are implemented and continuously refined.

The outcome is a blueprint for best practice consulting services for companies operating in the ERP software environment that can be adopted for very little cost. When implemented, the CSM model readily helps a company improve the performance of its consulting services business.

Business performance is enhanced by selecting KFAs, including their associated best practices, and then targeting these for improvement. As further best practices are implemented and refined, the maturity level of the consulting practice increases. This model can easily be adopted by any consulting services company and with the necessary focus, it should lead to a dramatic improvement of most dimensions of a consulting practice.