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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.

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.

As shown in this paper, the spreadsheet‐based application using the APC model has provided a better understanding of problem areas at Harlingen Waterworks.

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.

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.

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.

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.

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.

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).

Consistent with competitive cue theory, the findings suggest that a corporate brand can provide superior, consistent and unique information in a brand alliance.

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.

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.

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.

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.

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.

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.

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.

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.

Pull production systems have received much attention in the supply chain management environment. The number of Kanbans is a key decision variable in the pull production system as it affects the finished goods inventory (FGI) and backorders of the system. The purpose of this study is to compare the performance of the fixed and dynamic Kanban systems in terms of operational metrics (FGI and backorders) under the demand uncertainty.

In this paper, the system dynamics (SD) approach was used to model the performance of fixed and dynamic Kanban based production systems. SD approach has enabled the feedback mechanism and is an appropriate tool to incorporate the dynamic control during the simulation. Initially, a simple Kanban based production system was developed and then compared the performance of production systems with fixed and dynamic controlled Kanbans at the various demand scenarios.

From the present study, it is observed that the dynamic Kanban system has advantages over the fixed Kanban system and also observed that the variation in the backorders with respect to the demand uncertainty under the dynamic Kanban system is negligible.

In a just-in-time production system, the number of Kanbans is a key decision variable. The number of Kanbans is mainly depended on the demand, cycle time, safety stock factor (SSF) and container size. However, this study considered only demand uncertainty to compare the fixed and dynamic Kanban systems. This paper further recommends researchers to consider other control variables which may influence the number of Kanbans such as cycle time, SSF and container size.

This study will be useful to decision-makers and production managers in the selection of the Kanban systems in uncertain demand applications.