This paper presents a mathematical model to choose appropriate technology for production and capacity planning. The proposed study considers manufacturing planning in textile industry as a make-to-order (MTO) system by managing employees and water consumption and the possibility of outsourcing. The resulted model has been formulated as a mixed integer programming problem, which can be solved using a commercial software package. The implementation of the proposed study has been considered for a real-world case study and the results are discussed.

Lean Six Sigma is systematic and excellent operation management approach aimed to en-hance overall production through the elimination of waste and improve customer satisfaction. In the present case study, automobile part manufacturing unit has been selected and found 22% wastage in manufacturing steps resulting reduction in production. The primary objective of this research is to find the main reasons of production wastage and recommend corresponding remedies to counter the wastage reasons. For this purpose, Lean Six Sigma approach with the help of DMAIC methodology is implemented to observe and examine different root causes of the frame lugs production losses and rejection problems. The result reveals that the movement of material and employee are critical issues for wastage of resources, ultimately affecting production of industry. Lastly, the possible solutions are to be advised to tackling these issues. The successful execution of the proposed solutions show 7% growth in the production of the component which saves annually INR 15, 64, 056.

This paper deals with developing an inventory model for two warehouses. In today’s business era, there are various types of conditions such as discounts, bulk storage and seasonal products forcing the buyer to purchase the order more than owned warehouse capacity. To store the excess unit of purchase order, buyer arrange additional storage space called as rented warehouse. It is known that the demand of the seasonal products (as woolen garments) increases at the beginning of the season up to a certain time and then stabilizes to a constant rate for the remaining time of the season. The ramp type demand rate forces the buyer to store a higher quantity of the product at the beginning of the season. Most of the physical goods undergo decay or deterioration over time so we study deteriorating seasonal products in this paper. This two warehouse inventory model is developed with inflation and shortages. The model starts with rent warehouse, in first rent warehouse’s inventory level is depleted due to demand and deterioration. At this time own warehouse is depleted due to deterioration only. But after that the inventory level of owned warehouse is depleted due to both demand and deterioration. The shortages are considered in owned warehouse, which is partially backlogged. Numerical solution of the model is obtained to verify the optimal solution. Comprehensive sensitivity analysis has been carried out for showing the effect of variations in the parameters. The model is solved analytically by minimizing the total cost.

This study deals with an economic order quantity model to find out the optimal selling price and optimal ordering quantity for the products which deteriorates over time. The demand for the products depends on available stock level and selling price of the products. The shortages are allowed, and it is assumed that the occurring shortages are partially backlogged. Depending on the rate of backlogging two models are presented in this study. The first model assumes a constant rate of backlogging, while in second model the backlogging rate is assumed to be dependent on waiting time. Numerical example and sensitivity analysis are presented to illustrate the results of the proposed model.

A two warehouse production inventory model is developed for deteriorating items under reliability consideration. The effect of trade credit is considered under inflation. Since, formulating a suitable inventory model is one of the major concerns for an industry, the main objective of this paper is to optimize the total related cost for reliable production process. The model is illustrated through numerical example. The sensitivity analyses of the cost function are performed due to different measures and some managerial inferences are presented.

This paper formulates a multi-level supply chain network with a single producer, multi distributors and multi retailers during a finite planning horizon. The demand rate is assumed to be exponential function of time; shortages are allowed and completely backlogged. The stock is assumed to undergo deterioration as soon as it is produced. The production rate is dependent on demand rate and greater than the demand rate. Optimal solution for the proposed model is derived and using a numerical example, the behavior of the model is analyzed.

The objective of this study was to analyze and determine the impact of digital transformation on the individual job performance of insurance companies in Peru. The deductive inferential scientific method of explanatory level was used, with a non-experimental design, to four insurance companies that operate in the regions of Arequipa, Cusco, Iquitos, Lima, Tacna and Trujillo. The results generated by structural equations show that customer service experience (CSE), based on digital transformation, had a positive impact on task performance (p ≤ 0.05) and contextual performance (p ≤ 0.05); in contrast, the customer service experience (CSE), based on digital transformation, was found to have no impact on counterproductive behavior (p≥ 0.05). In relation to the collaborator's capabilities (CC) based on digital transformation, the results reveal that it had a significant influence on task performance (p ≤0.05) and contextual performance (p ≤ 0.05), while it did not have any impact on counterproductive behavior (p ≥ 0.05). Likewise, processes based on digital transformation (P) significantly influence task performance (p ≤ 0.05) and contextual performance (p ≤ 0.05), unlike counter-productive behavior that did not present a causal link with the processes (p> 0.05). Finally, the business model based on digital transformation (BM) had no implications for task performance (p> 0.05), contextual performance (p> 0.05) and counterproductive behaviors (p> 0.05). The conclusion of the study indicates that the customer service experience, the collaborator's capabilities and processes based on digital transformation contribute to the performance and contextual performance of the workers of the insurance companies in Peru.

The purpose of these comments is to serve as a revision to the article by Khan et al. (2016) [Khan, M., Jaber, M.Y., Zanoni, S., & Zavanella, L. (2016). Vendor managed inventory with consignment stock agreement for a supply chain with defective items. Applied Mathematical Modelling, 40(15–16), 7102–7114.]. This commenting paper suggests that the expected total cost function derived in Khan et al. (2016) was incorrect, and then offers revisions to complement the shortcomings.

To conduct business in the global market in the era of digitalization, hotels need to pay more attention to the complaint behavior of guests with different cultures to adjust their methods of handling these complaints. The purpose of this study is to analyze the influence of Hofstede's five cultural dimensions on the complaint behavior of guests. This study also offers strategic solutions for hoteliers in facing various kinds of complaint behavior from guests with different cultures. This research was conducted on tourists who have stayed in five-star hotels in Badung Regency – Bali, with a total sample of 110 respondents. The data were col-lected through questionnaires. The data analysis was performed using the structural equation model (SEM) with the partial least square (PLS) approach. The results of this study indicate that the power distance cultural dimension has a significant influence on public action and private action. Uncertainty avoidance, individualism versus collectivism, and long term versus short term orientation dimension have a significant influence on public action and private action. The culture of masculinity versus femininity has a significant influence on private action and no action.

Structural Equation Modeling (SEM) includes measurement and structural model for hypothesis testing. The results yielded from structural model is unlikely to be valid if a poor loading of an indicator is selected. The impact of these erroneous result on standardized loading is disregard. Thus, knowing how poor loading can affect the validity of measurement model is a crucial issue. This paper attempts to compare the standardized loadings result between two prominent SEM methods (CBSEM and PLS-SEM) using three varied of simulation models (TRA, Loyalty and UTAUT model) to investigate their effects on reliability and validity of measurement model. The data for each model were generated using R software by setting the value of standardized loading and the construct correlations (N=50, 100, 200 and 500). The value of standardized loadings was set to 0.60 for each construct in the model while the construct correlations were set in the range between 0.45 to 0.65. Then, the AMOS 21.0 and ADANCO 2.0 were used to perform the statistical analysis. It shows that good standardized loading can increase the reliability and validity of construct representation. CBSEM is particularly yielded valid and unbiased estimation under confirmatory condition (established theory) compared with PLS-SEM. The results are illustrated with empirical examples. This paper provides updated evidence about CBSEM and PLS-SEM when assessing the measurement model.