International Journal of Advanced Operations Management (7 papers in press)

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• Open Access

  Visual management in the era of industry 4.0: Perceived advantages and disadvantages of digital boards ( Free Full-text Access )

  by Robin Von Haartman, Linda Samen, Lisa Bengtsson, Stefan Eriksson 
  Abstract: The purpose of this paper is to investigate digitalised visual management, with a focus on the relative advantages and disadvantages of digital and analogue boards in manufacturing. The case study of this paper was conducted at two different business units within the same large multinational company, Sandvik. Data was collected through 15 unstructured and semi-structured interviews with managers and machine operators. More advantages than disadvantages with digital boards were found. Only two disadvantages are absolute, while the other disadvantages can be counteracted to some extent. Currently there is a shortage of studies exploring advantages and disadvantages of digital boards as visualisation tools. This paper is based on a single case study focusing on stoppage causes, and thus cannot be fully generalised to all manufacturing companies or all contexts. The actual performance effects of analogue and digital boards were not examined in this paper. The findings are applicable to for managers considering investing in digital boards in manufacturing, to be used for continuous improvement but also for other production-related applications.
  Keywords: continuous improvement; visual management; Kaizen; improvement boards; Industry 4.0; lean manufacturing; digital lean; display boards in production.
  
  
• SAME DAY DELIVERY IN B2C E-COMMERCE SYSTEMS IN THE UAE CONTEXT  
  by Mohammad Alsibaei, Salah Haridy, M. Affan Badar 
  Abstract: This work aimed to investigate the effect of various factors on cost, customer satisfaction and cycle time with respect to Same Day Delivery (SDD). Using survey and Pareto chart, four factors were identified as the most important: logistics resources ownership, operations management, IT infrastructure, and facility location. Analysis of Variance (ANOVA) revealed that all the four factors were significant for cost. For customer satisfaction and cycle time, all factors except logistics resources ownership were found to be significant. Correlation between cost, customer satisfaction and cycle time was studied and regression models were developed. A multi-objective optimization model was used to find the best levels of the significant factors to optimize SDD. Analytic Hierarchy Process (AHP) was used to determine the relative weights for the cost, customer satisfaction and cycle time. The findings would help E-retailers in decision-making. Since the survey was conducted in UAE, the result would be limited to UAE.
  Keywords: E-commerce; Same day delivery; Supply chain management; Logistics management; Multi-objective optimization; Multi-criterial decision making; United Arab Emirates.
  
  
• A comparative study of automobile sales forecasting with ARIMA, SARIMA and Deep Learning LSTM model  
  by Sharath Kariya Shetty, Rajesh Buktar 
  Abstract: In deciding production-plan, material-inventory, scheduling, etcetera of an automobile industry, the accuracy of forecasting techniques plays a very important role. In quantitative forecasting techniques in the automobile industry, conventional methods like auto-regressive, ARIMA, and seasonal-ARIMA are not accurate enough to extract all the information hidden in the time series data. With the recent developments in machine-learning and deep learning, RNN and LSTM can produce an impressive result out of time series data by dealing with the non-linearity and complexity of the data. In this study, we have compared the prediction accuracy among the ARIMA, SARIMA, and LSTM techniques for an Indian automobile company. The Deep Learning Model LSTM outperforms by 92% when compared with ARIMA and by 42.5% when compared with SARIMA techniques. Moreover, it is noticed that the accuracy of deep learning can be improved by tuning hyperparameters such as learning rate, neuron number in a layer, and choosing the correct weight initializer for the data.
  Keywords: Automobile Sales; Forecasting; ARIMA; SARIMA; Deep Learning; LSTM.
  
  
• Exploring the ethical decision-making practice among Malaysian consultant quantity surveyors: a qualitative study  
  by Nor Atikah Hashim, Ismi Arif Ismail, Khairuddin Idris, Seyedali Ahrari, Zoharah Omar, Zeinab Zaremohzzabieh 
  Abstract: The Malaysian Government has worked tirelessly to develop a comprehensive set of tactics aimed at fighting corruption. One of the sectors that have problems with corruption is the construction industry especially among consultant quantity surveyors (CQS) due to the nature of their work. Many unethical behaviours are being practiced in the construction industry. The goal of this research is to explore the ethical decision-making practice among CQS in Malaysia. Researchers described the results of a qualitative research study involving CQS. Purposive sampling was used to choose interviews. The eight selected respondents were from three main quantity surveyors institutions. This study employed semi-structured interviews for data gathering. Following the data analysis, seven key themes emerged: upbringing, skill and training, experience and intuitions, social interaction, adherence to the duty of care, company policy and compliance with the ethics code. Identifying these elements behind ethical decision-making will help the consultants quantity surveyors to perform their duty well.
  Keywords: ethical decision-making; EDM; consultant quantity surveyor; CQS; knowledge acquisition; learning.
  DOI: 10.1504/IJAOM.2022.10049843
   
  
• Examining the Impact of Recruitment Process Outsourcing (RPO) Motivators on Success of Relationship between Client and Service Provider in India  
  by Poonam Kaushik 
  Abstract: This study examines the impact of recruitment process outsourcing motivators on the success of relationship between client and service provider. This study uses a quantitative technique using data collected from 350 respondents. Structure equation modelling has been used to test the model. The findings indicate that as the motivators of outsourcing increases, it will lead to increase the benefits, which further improves the relationship between client and service provider. The findings also indicate that RPO motivators have a significant impact on relationship quality. This study provides evidence that the innovative factor embedded in the motivators of outsourcing are an important factor in determining RPO motivators and ultimately improve the relationship between client and service provider. RPO motivators have become an important point of contact for client and service provider.
  Keywords: India; outsourcing; recruitment process outsourcing; RPO; motivators; relationship quality; quantitative research.
  DOI: 10.1504/IJAOM.2022.10050207
   
  
• Consumer returns processing in a multi-period setting  
  by Kamil Ciftci, Yertai Tanai, George Wilson 
  Abstract: In this paper, we propose a framework for a responsive reverse supply chain where a retailer processes the returns. We characterize this responsiveness by imposing a diseconomies of scale for processing cost of returns. Utilizing price inversely influenced demand for a given period, we formulate a holistic profit maximization model for the entire planning horizon. We derive closed form solutions for the optimal sales price and quantity of processed returns for a particular period and derive the effects of some key parameters on the decision variables. The results indicate that the average selling price is always lower with processing. Furthermore, the value captured from the processing of returns increases as the product becomes more expensive to acquire. Lastly, the value gained from processing additional returns is always declining for each additional period of delay, indicating the importance of adopting a responsive returns management process.
  Keywords: reverse supply chain; closed-loop supply chain; consumer returns management; multi-period planning; pricing decisions.
  
  
• A sustainable production inventory model for growing items with trade credit policy under partial backlogging  
  by Shiv Raj Singh, Karuna Rana 
  Abstract: Most countries rely on the growth of commodity industries to sustain their economies. The growing commodity industries produce livestock such as sheep, pigs, chickens, and fish. The purpose of this paper is to develop a mathematical model for growing items with linear demand and deteriorating items. Most of the inventory models are considered with constant rate of deterioration. The paper explores deterioration rates changing with time and partially backlog shortages allowed. Furthermore, it is assumed that live newborn items are fed until their weight has grown to a customer-preferred level during breeding periods. Afterward, they are slaughtered and turned into deteriorating products susceptible to customer demand during consumption. This model is optimized by devising an analytical solution procedure to determine the appropriate purchasing quantity of the newborn animals and the breeding period. Numerical examples are provided, for a type of poultry, to illustrate the model. To study how model parameters affect the result of the objective function and decision variables, we do a sensitivity analysis.
  Keywords: Inventory Control; Growing items; Deteriorating items; Inflation; Trade Credit; Partially backlogged.