The purpose of this paper is to re‐introduce the APC model (developed by the American Productivity Center) through a spreadsheet application of the model in a real‐world setting…
Abstract
Purpose
The purpose of this paper is to re‐introduce the APC model (developed by the American Productivity Center) through a spreadsheet application of the model in a real‐world setting, with a case study of Harlingen Waterworks, Texas, USA.
Design/methodology/approach
This paper introduces a performance measurement system using a multi‐factor productivity measurement model in a real‐world setting. The model uses operational‐level accounting data such as quantities and prices of inputs and outputs of a revenue‐generating organization. Such operational data is rarely published or shared by for‐profit organizations. Thus, the study focused on a government‐run enterprise that cannot claim confidentiality. Since water utilities are experiencing financial pressures, this application is very timely. The spreadsheet‐based implementation, using multi‐period data, generates performance trend charts of productivity, price recovery and profitability contributions that give a better perspective to managers in identifying the problem areas.
Findings
As shown in this paper, the spreadsheet‐based application using the APC model has provided a better understanding of problem areas at Harlingen Waterworks.
Originality/value
The contribution of this paper is the actual application of the APC model using multi‐period data, and the outcomes of the application in a real‐world setting. This application is useful to any public or private organization generating revenues. The APC model, in this instance, is intended to provide readily interpretable performance feedback for financial managers.
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The profit‐linked total‐factor productivity measurement models,such as the American Productivity Center model, use base‐period data asthe standard against which the current‐period…
Abstract
The profit‐linked total‐factor productivity measurement models, such as the American Productivity Center model, use base‐period data as the standard against which the current‐period performance is measured. Hence, the design and development of accurate and appropriate base‐period data is critical in analysing performance. Presents a linear programming model to generate the optimal base‐period data as well as to provide valuable information through sensitivity analysis that is not possible by the measurement model. This information can lead to an investigation of the causes of problems such as resource inefficiencies, in addition to the validity and the flexibility of consumption and production figures.
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Mohan P. Rao and David M. Miller
The purpose of this paper is to describe the process of productivity management and potential expert systems applications at each stage of productivity analysis. Based on…
Abstract
The purpose of this paper is to describe the process of productivity management and potential expert systems applications at each stage of productivity analysis. Based on literature reviews it discusses the strengths and limitations of these technologies. Describes several tasks in the measurement, interpretation and evaluation phases and examines the appropriateness of an expert systems application. Finds that expert systems applications could be useful in interpretation and evaluation. Focuses on productivity analysis at the organizational‐level only. Opines that business managers with limited or no knowledge of productivity models may want to have expert systems applications developed to diagnose problems and take corrective actions in a timely manner. The paper could be useful to business practitioners as well as researchers. Contributions include a detailed description of productivity analysis and how and where expert systems applications could make a difference. Productivity management is critical for long‐term business survival.
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Mayoor Mohan, Kevin E. Voss, Fernando R. Jiménez and Bashar S. Gammoh
The purpose of this paper is to examine the role of the corporate brand in a brand alliance that includes one of the corporation’s product brands.
Abstract
Purpose
The purpose of this paper is to examine the role of the corporate brand in a brand alliance that includes one of the corporation’s product brands.
Design/methodology/approach
Using a scenario-based study, 899 participants were randomly assigned to one of 84 unique brand alliance scenarios involving a corporate brand, a product brand ally and a focal product brand; a total of 33 corporate brands were represented. Results were estimated using a three-stage least squares model.
Findings
Consumers’ evaluations of a focal brand were enhanced when a corporate brand name associated with a product brand ally was included in the brand alliance. The effect was mediated by attitude toward the product brand ally. The indirect effect of the corporate brand was stronger when consumers had low product category knowledge (PCK).
Research limitations/implications
Consistent with competitive cue theory, the findings suggest that a corporate brand can provide superior, consistent and unique information in a brand alliance.
Practical implications
Practitioners should note that the effectiveness of adding a corporate brand name into a product brand alliance is contingent on the extent of consumers’ PCK.
Originality/value
This paper examines when and why corporate brands are effective endorsers in product brand alliances. This paper adds empirical support to previous assertions that, if managed effectively, corporate brands can be valuable assets that convey unique valuable information to consumers.
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The cash flow from government agencies to contractors, called progress payment, is a critical step in public projects. The delays in progress payments significantly affect the…
Abstract
Purpose
The cash flow from government agencies to contractors, called progress payment, is a critical step in public projects. The delays in progress payments significantly affect the project performance of contractors and lead to conflicts between two parties in the Turkish construction industry. Although some previous studies focused on the issues in internal cash flows (e.g. inflows and outflows) of construction companies, the context of cash flows from public agencies to contractors in public projects is still unclear. Therefore, the primary objective of this study is to develop and test diverse machine learning-based predictive models on the progress payment performance of Turkish public agencies and improve the predictive performance of these models with two different optimization algorithms (e.g. first-order and second-order). In addition, this study explored the attributes that make the most significant contribution to predicting the payment performance of Turkish public agencies.
Design/methodology/approach
In total, project information of 2,319 building projects tendered by the Turkish public agencies was collected. Six different machine learning algorithms were developed and two different optimization methods were applied to achieve the best machine learning (ML) model for Turkish public agencies' cash flow performance in this study. The current research tested the effectiveness of each optimization algorithm for each ML model developed. In addition, the effect size achieved in the ML models was evaluated and ranked for each attribute, so that it is possible to observe which attributes make significant contributions to predicting the cash flow performance of Turkish public agencies.
Findings
The results show that the attributes “inflation rate” (F5; 11.2%), “consumer price index” (F6; 10.55%) and “total project duration” (T1; 10.9%) are the most significant factors affecting the progress payment performance of government agencies. While decision tree (DT) shows the best performance among ML models before optimization process, the prediction performance of models support vector machine (SVM) and genetic algorithm (GA) has been significantly improved by Broyden–Fletcher–Goldfarb–Shanno (BFGS)-based Quasi-Newton optimization algorithm by 14.3% and 18.65%, respectively, based on accuracy, AUROC (Area Under the Receiver Operating Characteristics) and F1 values.
Practical implications
The most effective ML model can be used and integrated into proactive systems in real Turkish public construction projects, which provides management of cash flow issues from public agencies to contractors and reduces conflicts between two parties.
Originality/value
The development and comparison of various predictive ML models on the progress payment performance of Turkish public owners in construction projects will be the first empirical attempt in the body of knowledge. This study has been carried out by using a high number of project information with diverse 27 attributes, which distinguishes this study in the body of knowledge. For the optimization process, a new hyper parameter tuning strategy, the Bayesian technique, was adopted for two different optimization methods. Thus, it is available to find the best predictive model to be integrated into real proactive systems in forecasting the cash flow performance of Turkish public agencies in public works projects. This study will also make novel contributions to the body of knowledge in understanding the key parameters that have a negative impact on the payment progress of public agencies.
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Sasanka Choudhury, Dhirendra Nath Thatoi, Jhalak Hota, Suman Sau and Mohan D. Rao
The purpose of this paper is to identify the crack in beam-like structures before the complete failure or damage occurs to the structure. The beam-like structure plays an…
Abstract
Purpose
The purpose of this paper is to identify the crack in beam-like structures before the complete failure or damage occurs to the structure. The beam-like structure plays an important role in modern architecture; hence, the safety of this structure is much dependent on the safety of the beam. Hence, predicting the cracks is much more important for the safety of the overall structure.
Design/methodology/approach
In the present work, the regression analysis has been carried out through LASSO and Ridge regression models. Both the statistical models have been well implemented in the detection of crack depth and crack location. A cantilever beam-like structure has been taken for the analysis in which the first three natural frequencies have been considered as the independent variable and crack location and depth is used as the dependent variable. The first three natural frequencies, f1, f2 and f3 are used as an independent variable. The crack location and crack depth are estimated though the regressor models and the accuracy are compared, to verify the correctness of the estimation.
Findings
As stated in the purpose of work, the main aim of the present work is to identify the crack parameters using an inverse technique, which will be more effective and will provide the results with less time. The data used for regression analysis are obtained from theoretical analysis and later the theoretical results are also verified through experimental analysis. The regression model developed is tested for its Bias Variance Trade-off (“Bias” – Overfitting, “variance” – generalization). The regression results have been compared with the theoretical results to check the robustness in the subsequent result section.
Originality/value
The idea is an amalgamation of existing and well-established technologies, that is aimed to achieve better performance for the given task. A regressor is trained from the data obtained through numerical simulation. The model is developed taking bias variance trade-off into consideration. This generalized model gives us very much acceptable performance.
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Gives a bibliographical review of the finite element methods (FEMs) applied for the linear and nonlinear, static and dynamic analyses of basic structural elements from the…
Abstract
Gives a bibliographical review of the finite element methods (FEMs) applied for the linear and nonlinear, static and dynamic analyses of basic structural elements from the theoretical as well as practical points of view. The range of applications of FEMs in this area is wide and cannot be presented in a single paper; therefore aims to give the reader an encyclopaedic view on the subject. The bibliography at the end of the paper contains 2,025 references to papers, conference proceedings and theses/dissertations dealing with the analysis of beams, columns, rods, bars, cables, discs, blades, shafts, membranes, plates and shells that were published in 1992‐1995.
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Sumanjeet Singh, Rohit Raj, Bishnu Mohan Dash, Vimal Kumar, Minakshi Paliwal and Sonam Chauhan
The present study aims to investigate the factors of loan access that affect entrepreneurial self-efficacy (ESE) and operating efficiency of Indian Micro, Small and Medium…
Abstract
Purpose
The present study aims to investigate the factors of loan access that affect entrepreneurial self-efficacy (ESE) and operating efficiency of Indian Micro, Small and Medium Enterprises (MSMEs). Furthermore, the study intended to investigate the influence of ESE on the operating efficiency of Indian MSMEs and its mediating role.
Design/methodology/approach
In this study, exploratory research design is used. The study heavily relies on the primary data which has been collected by using the survey research method from a cross-section of 617 women-owned MSMEs, located in urban, rural, suburban and exurban areas of Haryana, Uttarakhand, Himachal Pradesh and NCR-Delhi. The partial least square structural equation modeling method version 3.3.3 has been used to evaluate.
Findings
In terms of the selected factors affecting access to finance, it has been established that the Loan Formalities, Banking Process, Loan Process, Staff Responsiveness and Incentive Scheme have a positive and significant influence in enhancing accessibility to finance and improving the self-efficacy and operating performance of firms. The findings also show that ESE mediates the relationship between various factors of loan access and the operating efficiency of MSMEs.
Research limitations/implications
The study’s findings show that entrepreneurial capacity is significantly and favorably impacted by attitudes toward entrepreneurship, ESE, perceived access to findings and business operations. It has also been demonstrated that entrepreneurial intentions are strongly and favorably influenced by entrepreneurial ability to access commercial bank financing for small businesses and the impact of the same on the women-owned MSMEs in India. It also revealed unfavorable loan terms, limited collateral, fear of repaying of loan and intricate loan application were among the many reasons for loan denial.
Originality/value
The study offers a comprehensive approach that simultaneously considers financial accessibility and ESE. This all-encompassing method offers a thorough grasp of the variables affecting MSMEs' operational efficiency (OE). In contrast to earlier research that might have concentrated only on direct relationships, this study explores the mediating mechanisms involved. This study examines how ESE modulates the influence of financing availability on OE, providing a comprehensive understanding of the underlying mechanisms. By taking into account particular MSME sector characteristics like size, industry or regional variations, the study may provide a unique contextual lens. Understanding how these contextual factors interact with entrepreneurial attributes and access to finance adds depth to the analysis.
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The objective of this study is to investigate how country risk, different political actions from the government and bureaucratic behavior influence the activities in industry…
Abstract
The objective of this study is to investigate how country risk, different political actions from the government and bureaucratic behavior influence the activities in industry supply chains (SCs) in emerging markets. The main objective of this study is to investigate the influence of these external stakeholders’ elements to the demand-side and supply-side drivers and barriers for improving competitiveness of Ready-Made Garment (RMG) industry in the way of analyzing supply chain. Considering the phenomenon of recent change in the RMG business environment and the competitiveness issues this study uses the principles of stakeholder and resource dependence theory and aims to find out some factors which influence to make an efficient supply chain for improving competitiveness. The RMG industry of Bangladesh is the case application of this study. Following a positivist paradigm, this study adopts a two phase sequential mixed-method research design consisting of qualitative and quantitative approaches. A tentative research model is developed first based on extensive literature review. Qualitative field study is then carried out to fine tune the initial research model. Findings from the qualitative method are also used to develop measures and instruments for the next phase of quantitative method. A survey is carried out with sample of top and middle level executives of different garment companies of Dhaka city in Bangladesh and the collected quantitative data are analyzed by partial least square-based structural equation modeling. The findings support eight hypotheses. From the analysis the external stakeholders’ elements like bureaucratic behavior and country risk have significant influence to the barriers. From the internal stakeholders’ point of view the manufacturers’ and buyers’ drivers have significant influence on the competitiveness. Therefore, stakeholders need to take proper action to reduce the barriers and increase the drivers, as the drivers have positive influence to improve competitiveness.
This study has both theoretical and practical contributions. This study represents an important contribution to the theory by integrating two theoretical perceptions to identify factors of the RMG industry’s SC that affect the competitiveness of the RMG industry. This research study contributes to the understanding of both external and internal stakeholders of national and international perspectives in the RMG (textile and clothing) business. It combines the insights of stakeholder and resource dependence theories along with the concept of the SC in improving effectiveness. In a practical sense, this study certainly contributes to the Bangladeshi RMG industry. In accordance with the desire of the RMG manufacturers, the research has shown that some influential constructs of the RMG industry’s SC affect the competitiveness of the RMG industry. The outcome of the study is useful for various stakeholders of the Bangladeshi RMG industry sector ranging from the government to various private organizations. The applications of this study are extendable through further adaptation in other industries and various geographic contexts.